Index: /issm/trunk-jpl/src/m/archive/arch.py =================================================================== --- /issm/trunk-jpl/src/m/archive/arch.py (revision 24212) +++ /issm/trunk-jpl/src/m/archive/arch.py (revision 24213) @@ -4,262 +4,277 @@ from collections import OrderedDict -def archwrite(filename,*args): # {{{ - """ - ARCHWRITE - Write data to a field, given the file name, field name, and data. - - Usage: - archwrite('archive101.arch','variable_name',data); - """ - nargs=len(args); - if nargs % 2 != 0 : - raise ValueError('Incorrect number of arguments.') - # open file - try: - if not path.isfile(filename): - fid=open(filename,'wb') - else: - fid=open(filename,'ab') - except IOError as e: - raise IOError("archwrite error: could not open '%s' to write to." % filename) - - nfields=len(args)/2 - # generate data to write - for i in range(nfields): - # write field name - name=args[2*i] - write_field_name(fid,name) - - # write data associated with field name - data=args[2*i+1] - code=format_archive_code(data) - if code==1: - raise ValueError("archwrite : error writing data, string should not be written as field data") - elif code==2: - write_scalar(fid,data) - elif code==3: - write_vector(fid,data) - else: - raise ValueError("archwrite : error writing data, invalid code entered '%d'" % code) - - fid.close() - -# }}} -def archread(filename,fieldname): # {{{ - """ - ARCHREAD - Given an arch file name, and a field name, find and return the data - associated with that field name. - Usage: - archread('archive101.arch','field_var_1') - """ - try: - if path.isfile(filename): - fid=open(filename,'rb') - else: - raise IOError("archread error : file '%s' does not exist" % filename) - except IOError as e: - raise IOError("archread error : could not open file '%s' to read from" % filename) - - archive_results=[] - - # read first result - result=read_field(fid) - - while result: - if fieldname == result['field_name']: - # found the data we wanted - archive_results=result['data']; # we only want the data - break - - # read next result - result=read_field(fid) - - # close file - fid.close() - - return archive_results -# }}} -def archdisp(filename): # {{{ - """ - ARCHDISP - Given an arch filename, display the contents of that file - - Usage: - archdisp('archive101.arch') - """ - try: - if path.isfile(filename): - fid=open(filename,'rb') - else: - raise IOError("archread error : file '%s' does not exist" % filename) - except IOError as e: - raise IOError("archread error : could not open file '%s' to read from" % filename) - - print('Source file: ') - print(('\t{0}'.format(filename))) - print('Variables: ') - - result=read_field(fid) - while result: - print(('\t{0}'.format(result['field_name']))) - print(('\t\tSize:\t\t{0}'.format(result['size']))) - print(('\t\tDatatype:\t{0}'.format(result['data_type']))) - # go to next result - result=read_field(fid) - - # close file - fid.close() - -# }}} - -# Helper functions -def write_field_name(fid,data): # {{{ - """ - Routine to write field name (variable name) to an archive file. - """ - # write the length of the record - # length to write + string size (len) + format code - reclen=len(data)+4+4 - fid.write(struct.pack('>i',reclen)) - - # write format code - code=format_archive_code(data); - if code != 1: - raise TypeError("archwrite : error writing field name, expected string, but got %s" % type(data)) - fid.write(struct.pack('>i',1)) - - # write string length, and then the string - fid.write(struct.pack('>i',len(data))) - fid.write(struct.pack('>{}s'.format(len(data)),data.encode('utf8'))) -# }}} -def write_scalar(fid,data): # {{{ - """ - Procedure to write a double to an arch file pointed to by fid - """ - # write length of record - # double (8 bytes) + format code (4 bytes) - reclen=8+4 - fid.write(struct.pack('>i',reclen)) - - # write the format code (2 for scalar) - fid.write(struct.pack('>i',2)) - - # write the double - fid.write(struct.pack('>d',data)) - -# }}} -def write_vector(fid,data): # {{{ - """ - Procedure to write a np.array to an arch file - """ - # Make sure our vector is the correct shape. - # Reshape it into a row vector if it is not correct. - if isinstance(data,(bool,int,float)): - data=np.array([data]) - elif isinstance(data,(list,tuple)): - data=np.array(data).reshape(-1,) - - if np.ndim(data) == 1: - if np.size(data): - data=data.reshape(np.size(data),) - else: - data=data.reshape(0,0) - - # get size of data - sz=data.shape - - # write length of record - # format code + row size + col size + (double size * row amt * col amt) - reclen=4+4+4+8*sz[0]*sz[1] - # make sure we can fit data into file - if reclen>2**31: - raise ValueError("archwrite error : can not write vector to binary file because it is too large") - fid.write(struct.pack('>i',reclen)) - - # write format code - fid.write(struct.pack('>i',3)) - - # write vector - fid.write(struct.pack('>i',sz[0])) - fid.write(struct.pack('>i',sz[1])) - for i in range(sz[0]): - for j in range(sz[1]): - fid.write(struct.pack('>d',float(data[i][j]))) - -# }}} - -def read_field(fid): # {{{ - """ - Procedure to read a field and return a results list with the following attributes: - result['field_name'] -> the name of the variable that was just read - result['size'] -> size (dimensions) of the variable just read - result['data_type'] -> the type of data that was just read - result['data'] -> the actual data - """ - - try: - # first, read the string - reclen=struct.unpack('>i',fid.read(struct.calcsize('>i')))[0] - check_name=struct.unpack('>i',fid.read(struct.calcsize('>i')))[0] - if check_name != 1: - raise ValueError('archread error : a string was not present at the start of the arch file') - namelen=struct.unpack('>i',fid.read(struct.calcsize('>i')))[0] - fieldname=struct.unpack('>{}s'.format(namelen),fid.read(namelen))[0] - - # then, read the data - datalen=struct.unpack('>i',fid.read(struct.calcsize('>i')))[0] - data_type=struct.unpack('>i',fid.read(struct.calcsize('>i')))[0] - - if data_type==2: - # struct.upack scalar - data=struct.unpack('>d',fid.read(struct.calcsize('>d')))[0] - elif data_type==3: - rows=struct.unpack('>i',fid.read(struct.calcsize('>i')))[0] - cols=struct.unpack('>i',fid.read(struct.calcsize('>i')))[0] - raw_data=np.zeros(shape=(rows,cols),dtype=float) - for i in range(rows): - raw_data[i,:]=struct.unpack('>{}d'.format(cols),fid.read(cols*struct.calcsize('>d'))) - # The matrix will be struct.upacked in order and will be filled left -> right by column - # We need to reshape and transpose the matrix so it can be read correctly - data=raw_data.reshape(raw_data.shape[::-1]).T - else: - raise TypeError("Cannot read data type %d" % data_type) - - # give additional data to user - if data_type==2: - data_size='1x1' - data_type_str='double' - elif data_type==3: - data_size='{0}x{1}'.format(rows,cols) - data_type_str='vector/matrix' - - result=OrderedDict() - result['field_name']=fieldname.decode('utf8') - result['size']=data_size - result['data_type']=data_type_str - result['data']=data - - except struct.error as e: - result=None - - return result -# }}} - -def format_archive_code(format): # {{{ - """ - Given a variable, determine it's type and return - an integer value: - - 1 : string - 2 : double (scalar) - 3 : vector or matrix (of type double) - - """ - if isinstance(format,str): - code=1 - elif format.shape[0] == 1 and format.shape[1] == 1: - code=2 - elif isinstance(format,(list,tuple,np.ndarray)): - code=3 - else: - raise TypeError("archwrite error: data type '%s' is not valid." % type(format)) - return code -# }}} + +def archwrite(filename, *args): # {{{ + """ + ARCHWRITE - Write data to a field, given the file name, field name, and data. + + Usage: + archwrite('archive101.arch', 'variable_name', data) + """ + nargs = len(args) + if nargs % 2 != 0: + raise ValueError('Incorrect number of arguments.') + # open file + try: + if not path.isfile(filename): + fid = open(filename, 'wb') + else: + fid = open(filename, 'ab') + except IOError as e: + raise IOError("archwrite error: could not open '{}' to write to due to:".format(filename), e) + + nfields = len(args) / 2 + # generate data to write + for i in range(nfields): + # write field name + name = args[2 * i] + write_field_name(fid, name) + + # write data associated with field name + data = args[2 * i + 1] + code = format_archive_code(data) + if code == 1: + raise ValueError("archwrite : error writing data, string should not be written as field data") + elif code == 2: + write_scalar(fid, data) + elif code == 3: + write_vector(fid, data) + else: + raise ValueError("archwrite : error writing data, invalid code entered '{}'".format(code)) + + fid.close() + + # }}} + + +def archread(filename, fieldname): # {{{ + """ + ARCHREAD - Given an arch file name, and a field name, find and return the data + associated with that field name. + Usage: + archread('archive101.arch', 'field_var_1') + """ + try: + if path.isfile(filename): + fid = open(filename, 'rb') + else: + raise IOError("archread error : file '{}' does not exist".format(filename)) + except IOError as e: + raise IOError("archread error : could not open file '{}' to read from due to :".format(filename), e) + + archive_results = [] + + # read first result + result = read_field(fid) + + while result: + if fieldname == result['field_name']: + # found the data we wanted + archive_results = result['data'] # we only want the data + break + + # read next result + result = read_field(fid) + + # close file + fid.close() + + return archive_results + # }}} + + +def archdisp(filename): # {{{ + """ + ARCHDISP - Given an arch filename, display the contents of that file + + Usage: + archdisp('archive101.arch') + """ + try: + if path.isfile(filename): + fid = open(filename, 'rb') + else: + raise IOError("archread error : file '{}' does not exist".format(filename)) + except IOError as e: + raise IOError("archread error : could not open file '{}' to read from due to ".format(filename), e) + + print('Source file: ') + print(('\t{0}'.format(filename))) + print('Variables: ') + + result = read_field(fid) + while result: + print(('\t{0}'.format(result['field_name']))) + print(('\t\tSize:\t\t{0}'.format(result['size']))) + print(('\t\tDatatype:\t{0}'.format(result['data_type']))) + # go to next result + result = read_field(fid) + + # close file + fid.close() + + # }}} + + # Helper functions + + +def write_field_name(fid, data): # {{{ + """ + Routine to write field name (variable name) to an archive file. + """ + # write the length of the record + # length to write + string size (len) + format code + reclen = len(data) + 4 + 4 + fid.write(struct.pack('>i', reclen)) + + # write format code + code = format_archive_code(data) + if code != 1: + raise TypeError("archwrite : error writing field name, expected string, but got %s" % type(data)) + fid.write(struct.pack('>i', 1)) + + # write string length, and then the string + fid.write(struct.pack('>i', len(data))) + fid.write(struct.pack('>{}s'.format(len(data)), data.encode('utf8'))) + # }}} + + +def write_scalar(fid, data): # {{{ + """ + Procedure to write a double to an arch file pointed to by fid + """ + # write length of record + # double (8 bytes) + format code (4 bytes) + reclen = 8 + 4 + fid.write(struct.pack('>i', reclen)) + + # write the format code (2 for scalar) + fid.write(struct.pack('>i', 2)) + + # write the double + fid.write(struct.pack('>d', data)) + + # }}} + + +def write_vector(fid, data): # {{{ + """ + Procedure to write a np.array to an arch file + """ + # Make sure our vector is the correct shape. + # Reshape it into a row vector if it is not correct. + if isinstance(data, (bool, int, float)): + data = np.array([data]) + elif isinstance(data, (list, tuple)): + data = np.array(data).reshape(- 1, ) + + if np.ndim(data) == 1: + if np.size(data): + data = data.reshape(np.size(data), ) + else: + data = data.reshape(0, 0) + + # get size of data + sz = data.shape + + # write length of record + # format code + row size + col size + (double size * row amt * col amt) + reclen = 4 + 4 + 4 + 8 * sz[0] * sz[1] + # make sure we can fit data into file + if reclen > 2**31: + raise ValueError("archwrite error : can not write vector to binary file because it is too large") + fid.write(struct.pack('>i', reclen)) + + # write format code + fid.write(struct.pack('>i', 3)) + + # write vector + fid.write(struct.pack('>i', sz[0])) + fid.write(struct.pack('>i', sz[1])) + for i in range(sz[0]): + for j in range(sz[1]): + fid.write(struct.pack('>d', float(data[i][j]))) + + # }}} + + +def read_field(fid): # {{{ + """ + Procedure to read a field and return a results list with the following attributes: + result['field_name'] - > the name of the variable that was just read + result['size'] - > size (dimensions) of the variable just read + result['data_type'] - > the type of data that was just read + result['data'] - > the actual data + """ + + try: + # first, read the string + #first read the size and continue reading + struct.unpack('>i', fid.read(struct.calcsize('>i')))[0] #name length + check_name = struct.unpack('>i', fid.read(struct.calcsize('>i')))[0] + if check_name != 1: + raise ValueError('archread error : a string was not present at the start of the arch file') + namelen = struct.unpack('>i', fid.read(struct.calcsize('>i')))[0] + fieldname = struct.unpack('>{}s'.format(namelen), fid.read(namelen))[0] + # then, read the data + #first read the size and continue reading + struct.unpack('>i', fid.read(struct.calcsize('>i')))[0] #data length + data_type = struct.unpack('>i', fid.read(struct.calcsize('>i')))[0] + + if data_type == 2: + # struct.upack scalar + data = struct.unpack('>d', fid.read(struct.calcsize('>d')))[0] + elif data_type == 3: + rows = struct.unpack('>i', fid.read(struct.calcsize('>i')))[0] + cols = struct.unpack('>i', fid.read(struct.calcsize('>i')))[0] + raw_data = np.zeros(shape=(rows, cols), dtype=float) + for i in range(rows): + raw_data[i, :] = struct.unpack('>{}d'.format(cols), fid.read(cols * struct.calcsize('>d'))) + # The matrix will be struct.upacked in order and will be filled left - > right by column + # We need to reshape and transpose the matrix so it can be read correctly + data = raw_data.reshape(raw_data.shape[::-1]).T + else: + raise TypeError("Cannot read data type {}".format(data_type)) + + # give additional data to user + if data_type == 2: + data_size = '1x1' + data_type_str = 'double' + elif data_type == 3: + data_size = '{0}x{1}'.format(rows, cols) + data_type_str = 'vector/matrix' + + result = OrderedDict() + result['field_name'] = fieldname.decode('utf8') + result['size'] = data_size + result['data_type'] = data_type_str + result['data'] = data + + except struct.error as e: + result = None + print("result is empty due to", e) + + return result + # }}} + + +def format_archive_code(format): # {{{ + """ + Given a variable, determine it's type and return + an integer value: + + 1 : string + 2 : double (scalar) + 3 : vector or matrix (of type double) + + """ + if isinstance(format, str): + code = 1 + elif format.shape[0] == 1 and format.shape[1] == 1: + code = 2 + elif isinstance(format, (list, tuple, np.ndarray)): + code = 3 + else: + raise TypeError("archwrite error: data type '%s' is not valid." % type(format)) + return code + # }}} Index: /issm/trunk-jpl/src/m/array/MatlabArray.py =================================================================== --- /issm/trunk-jpl/src/m/array/MatlabArray.py (revision 24212) +++ /issm/trunk-jpl/src/m/array/MatlabArray.py (revision 24213) @@ -2,276 +2,283 @@ import numpy as np from MatlabFuncs import * - #move this later from helpers import * from functools import reduce + def allempty(cin): - ''' - function to return an empty cell array if all array elements are empty - cout=allempty(cin) -''' - for i in cin: - if not isempty(i): - cout = cin - return cout - return [] - -def allequal(ain,aval): - ''' - function to return an empty array if all array elements are - equal to the given value, which may also be empty but not nan. - - (note that by definition, nan is not equal to nan; this could - be changed by using isequalwithequalnans.) - - aout=allequal(ain,aval) -''' - if type(ain) != type(aval): - print((allequal.__doc__)) - raise RuntimeError("ain and aval must be of the same type") - - if type(ain) == list: - ain = np.array(ain) - if type(ain) == np.ndarray: - ain = ain.flatten() - - for i in ain: - if i != aval: - if type(ain) == str: - return '' - else: - return [] - return ain + ''' + function to return an empty cell array if all array elements are empty + cout = allempty(cin) + ''' + for i in cin: + if not isempty(i): + cout = cin + return cout + return [] + + +def allequal(ain, aval): + ''' + function to return an empty array if all array elements are + equal to the given value, which may also be empty but not nan. + + (note that by definition, nan is not equal to nan; this could + be changed by using isequalwithequalnans.) + + aout = allequal(ain, aval) + ''' + if type(ain) != type(aval): + print((allequal.__doc__)) + raise RuntimeError("ain and aval must be of the same type") + + if type(ain) == list: + ain = np.array(ain) + if type(ain) == np.ndarray: + ain = ain.flatten() + + for i in ain: + if i != aval: + if type(ain) == str: + return '' + else: + return [] + return ain + def array_numel(*args): - ''' - function to find a number of elements from a list of arrays. - - asize=array_numel(varargin) - - see array_size to check the number and shape of elements, if - multiple indices will be used. -''' - anum = 0 - inum = 0 - for arg in args: - if type(arg) == str: - inum = len(arg) - else: - inum = np.size(arg) - - if inum != 0: - if anum == 0: - anum = inum - else: - if inum != anum: - raise RuntimeError('Inputs had inconsistent number of elements') - return anum + ''' + function to find a number of elements from a list of arrays. + + asize = array_numel(varargin) + + see array_size to check the number and shape of elements, if + multiple indices will be used. + ''' + anum = 0 + inum = 0 + for arg in args: + if type(arg) == str: + inum = len(arg) + else: + inum = np.size(arg) + + if inum != 0: + if anum == 0: + anum = inum + else: + if inum != anum: + raise RuntimeError('Inputs had inconsistent number of elements') + return anum + def array_size(*args): - ''' - function to find an array size from a list of arrays. - - asize=array_size(varargin) - - see array_numel to check only the number of elements, if - single indices will be used. - all arguments are assumed to be 1 or 2 dimensional - - Note: to call on all elements of an array use: array_size(*x) - in Matlab this would be array_size(x{1:end}) - - Note: to get all elements in a linear array use: array_size(np.array(x).flatten()[0:]) - in Matlab this would be array_size(x{1:end}) - because Matlab allows direct 1D access of nD arrays -''' - asize = (0,0) - isize = (0,0) - for arg in args: - if type(arg) == str: - isize = (1,1) #cellstr in matlab makes this happen - else: - isize = np.shape(arg) - if isize == (): #arg is a single value, ex. 0.3, 5, False, etc - isize = (1,1) - - if isize != (0,0): - if asize == (0,0): - asize = isize - else: - if isize != asize: - raise RuntimeError('Inputs had inconsistent shapes') - - #numpy gives (y,) if x = 1, must be reversed to match matlab syntax in this case - if len(asize) == 1: - asize = (1,asize[0]) - - return asize - -def str2int(astr,cfl='first',asint=True): - ''' - function to find and read the first or last positive integer - in a character string. cfl={'first','f','last','l'}; default: 'first' - returns 0 if astr has no positive integers - - Setting asint=False returns a list of strings - eg. ['1','2','3'] from '123' - - aint=str2int(astr,cfl) -''' - aint = [] - - num = '1234567890' - - if type(cfl) != str or type(astr) != str or len(cfl) == 0 or len(astr) == 0: - raise TypeError('str2int(astr,cfl): both arguments must be strings with length > 0') - - # find last positive int - if cfl[0] in ['l','L']: - for i in reversed(astr): - if i in num: - aint.append(i) - else: - if len(aint) > 0: - # aint is backwards since we were iterating backwards - aint = list(reversed(aint)) - if asint: - # convert list(str) to int - aint = int(reduce(lambda x,y: x+y,aint)) - break - - elif cfl[0] in ['f','F']: - for i in astr: - if i in num: - aint.append(i) - else: - if len(aint) > 0: - if asint: - # convert list(str) to int - aint = int(reduce(lambda x,y: x+y,aint)) - break - - # return 0 if aint is still [] (no integers found) - return aint or 0 - -def string_dim(a,idim,*args): - ''' - function to return the string dimension of an array element - - function sdim=string_dim(a,idim,varargin) - - such that: given the array/matrix a, - idim is the linear index of an element in a, - return the x/y/z/w/... coordinates of idim in n dimensions - - ex. a = [1 2 3 - 4 5 6] - - idim = 4 - (a[4] == 5; counted as [1,4,2,5,3,6] linearly in matlab) - - x = string_dim(a,4) -> '[1,1]' - - a[x] == a[4] == a[1,1] == 5 - - example use: exec('print a'+string_dim(a,4)) -> print a[1,1] -''' - sdmin = '' - if type(a) == list: - a = np.array(a) - if type(a) != np.ndarray: - raise TypeError('string_dim(a,idim,*args): a must be a numpy array . Try passing np.array(a) instead') - - if np.size(a) == 0 and idim == 0: - return sdim - - if idim >= np.size(a): - raise RuntimeError('string_dim(a,idim,*args): index idim exceeds number of elements in a') - - #check for column or row vector - for iarg in args: - if strcmpi(iarg,'vector'): - if a.ndim == 2 and (np.shape(a,1) == 1 or np.shape(a,2) == 1): - return '('+str(idim)+')' - - #transpose to compensate for differences in linear indexing in - # matlab vs in python (y/x + linear vs x/y) - a = a.T - - #general case - asize = np.shape(a) - i = np.zeros((np.shape(asize))) - aprod = np.prod(asize) - idim = idim - 1 - index = np.zeros((len(asize))) - - #calculate indices base 0 - for i in range(len(asize)): - aprod=aprod/asize[i] - index[i]=np.floor(idim/aprod) - idim=idim-index[i]*aprod - - #assemble string for output - sdim ='[' - for i in range(len(asize)-1): - sdim += str(int(index[i])) + ',' - - sdim += str(int(index[-1])) + ']' - - # happens due to how python does indexing, this response in matlab is just '' - if sdim == '[-1]': - return '' - - return sdim + ''' + function to find an array size from a list of arrays. + + asize = array_size(varargin) + + see array_numel to check only the number of elements, if + single indices will be used. + all arguments are assumed to be 1 or 2 dimensional + + Note: to call on all elements of an array use: array_size(* x) + in Matlab this would be array_size(x{1:end}) + + Note: to get all elements in a linear array use: array_size(np.array(x).flatten()[0:]) + in Matlab this would be array_size(x{1:end}) + because Matlab allows direct 1D access of nD arrays + ''' + asize = (0, 0) + isize = (0, 0) + for arg in args: + if type(arg) == str: + isize = (1, 1) #cellstr in matlab makes this happen + else: + isize = np.shape(arg) + if isize == (): #arg is a single value, ex. 0.3, 5, False, etc + isize = (1, 1) + + if isize != (0, 0): + if asize == (0, 0): + asize = isize + else: + if isize != asize: + raise RuntimeError('Inputs had inconsistent shapes') + + #numpy gives (y, ) if x = 1, must be reversed to match matlab syntax in this case + if len(asize) == 1: + asize = (1, asize[0]) + + return asize + + +def str2int(astr, cfl='first', asint=True): + ''' + function to find and read the first or last positive integer + in a character string. cfl={'first', 'f', 'last', 'l'}; default: 'first' + returns 0 if astr has no positive integers + + Setting asint = False returns a list of strings + eg. ['1', '2', '3'] from '123' + + aint = str2int(astr, cfl) + ''' + aint = [] + + num = '1234567890' + + if type(cfl) != str or type(astr) != str or len(cfl) == 0 or len(astr) == 0: + raise TypeError('str2int(astr, cfl): both arguments must be strings with length > 0') + + # find last positive int + if cfl[0] in ['l', 'L']: + for i in reversed(astr): + if i in num: + aint.append(i) + else: + if len(aint) > 0: + # aint is backwards since we were iterating backwards + aint = list(reversed(aint)) + if asint: + # convert list(str) to int + aint = int(reduce(lambda x, y: x + y, aint)) + break + + elif cfl[0] in ['f', 'F']: + for i in astr: + if i in num: + aint.append(i) + else: + if len(aint) > 0: + if asint: + # convert list(str) to int + aint = int(reduce(lambda x, y: x + y, aint)) + break + + # return 0 if aint is still [] (no integers found) + return aint or 0 + + +def string_dim(a, idim, *args): + ''' + function to return the string dimension of an array element + + function sdim = string_dim(a, idim, varargin) + + such that: given the array / matrix a, + idim is the linear index of an element in a, + return the x / y / z / w / ... coordinates of idim in n dimensions + + ex. a = [1 2 3 + 4 5 6] + + idim = 4 + (a[4] == 5; counted as [1, 4, 2, 5, 3, 6] linearly in matlab) + + x = string_dim(a, 4) - > '[1, 1]' + + a[x] == a[4] == a[1, 1] == 5 + + example use: exec('print a' + string_dim(a, 4)) - > print a[1, 1] + ''' + + if type(a) == list: + a = np.array(a) + if type(a) != np.ndarray: + raise TypeError('string_dim(a, idim, *args): a must be a numpy array < numpy.ndarray > . Try passing np.array(a) instead') + + if np.size(a) == 0 and idim == 0: + return sdim + + if idim >= np.size(a): + raise RuntimeError('string_dim(a, idim, *args): index idim exceeds number of elements in a') + + #check for column or row vector + for iarg in args: + if strcmpi(iarg, 'vector'): + if a.ndim == 2 and (np.shape(a, 1) == 1 or np.shape(a, 2) == 1): + return '(' + str(idim) + ')' + + #transpose to compensate for differences in linear indexing in + # matlab vs in python (y / x + linear vs x / y) + a = a.T + + #general case + asize = np.shape(a) + i = np.zeros((np.shape(asize))) + aprod = np.prod(asize) + idim = idim - 1 + index = np.zeros((len(asize))) + + #calculate indices base 0 + for i in range(len(asize)): + aprod = aprod / asize[i] + index[i] = np.floor(idim / aprod) + idim = idim - index[i] * aprod + + #assemble string for output + sdim = '[' + for i in range(len(asize) - 1): + sdim += str(int(index[i])) + ', ' + + sdim += str(int(index[-1])) + ']' + + # happens due to how python does indexing, this response in matlab is just '' + if sdim == '[-1]': + return '' + + return sdim + def string_vec(a): - ''' - function to return the string of a vector - - function svec=string_vec(a) -''' - return str(a) - -def struc_class(sclass,cstr,name): - ''' - function to find the structural fields of a specified class - - sclasso=struc_class(sclass,cstr,variable_name) - - such that: - sclasso.variable_name == sclass (hard copy) - - if variable_name == '' - sclasso.cstr == sclass (hard copy) -''' - try: - # I tried other methods, but this is, unfortunately, the best behaving by far - exec('from '+cstr+' import *') - except: - raise RuntimeError('MatlabArray.struc_class Class Error: class "'+cstr+'" does not exist') - - sclasso = struct() - - if isinstance(sclass,eval(cstr)): - # if we were given no name, call it by its class name - if name != '': - setattr(sclasso, name, deepcopy(sclass)) - else: - setattr(sclasso, cstr, deepcopy(sclass)) - else: - raise RuntimeError('MatlabArray.struc_class Match Error: provided object of type "'+str(type(sclass))+'" does not match provided string; object should be of type '+cstr) - - #may need this later depending on how src/m/classes/qmu works out - - #if len(vars(sclass)) == 0: - #return Lstruct() - - #else: - #fnames = fieldnames(sclass) - #for f in fnames: - #if isinstance(vars(sclass)[f],eval(cstr)): - #exec('sclasso.%s = vars(sclass)[f]')%(f) - #vars(sclasso)[f] = vars(sclass)[f] - - return sclasso + ''' + function to return the string of a vector + + function svec = string_vec(a) + ''' + return str(a) + + +def struc_class(sclass, cstr, name): + ''' + function to find the structural fields of a specified class + + sclasso = struc_class(sclass, cstr, variable_name) + + such that: + sclasso.variable_name == sclass (hard copy) + + if variable_name == '' + sclasso.cstr == sclass (hard copy) + ''' + try: + # I tried other methods, but this is, unfortunately, the best behaving by far + exec('from ' + cstr + ' import * ') + except: + raise RuntimeError('MatlabArray.struc_class Class Error: class "' + cstr + '" does not exist') + + sclasso = struct() + + if isinstance(sclass, eval(cstr)): + # if we were given no name, call it by its class name + if name != '': + setattr(sclasso, name, deepcopy(sclass)) + else: + setattr(sclasso, cstr, deepcopy(sclass)) + else: + raise RuntimeError('MatlabArray.struc_class Match Error: provided object of type "' + str(type(sclass)) + '" does not match provided string; object should be of type ' + cstr) + + #may need this later depending on how src / m / classes / qmu works out + + #if len(vars(sclass)) == 0: + #return Lstruct() + + #else: + #fnames = fieldnames(sclass) + #for f in fnames: + #if isinstance(vars(sclass)[f], eval(cstr)): + #exec('sclasso.%s = vars(sclass)[f]')%(f) + #vars(sclasso)[f] = vars(sclass)[f] + + return sclasso Index: /issm/trunk-jpl/src/m/boundaryconditions/PattynSMB.py =================================================================== --- /issm/trunk-jpl/src/m/boundaryconditions/PattynSMB.py (revision 24212) +++ /issm/trunk-jpl/src/m/boundaryconditions/PattynSMB.py (revision 24213) @@ -1,11 +1,12 @@ -import os -import numpy as np -def PattynSMB(md,Tf): - """ - PATTYNSMB- Compute SMB over Antarctica (from Pattyn 2006, pg. 18, "GRANTISM: An ExcelTM model for Greenland - and Antarctic ice-sheet response to climate changes") +import numpy as np + + +def PattynSMB(md, Tf): + """ + PATTYNSMB - Compute SMB over Antarctica (from Pattyn 2006, pg. 18, "GRANTISM: An ExcelTM model for Greenland + and Antarctic ice-sheet response to climate changes") Usage: - md=PattynSMB(md,Tf) + md = PattynSMB(md, Tf) where Tf is a background forcing temperature ("an anomalous temperature relative to the present conditions) @@ -13,38 +14,37 @@ See also: SETICESHELFBC, SETMARINEICESHEETBC - """ - - # Tma : Mean annual surface temperature in [deg C] - # Tms : Mean summer temperature in [deg C] - # h : Surface/bedrock elevation (I assume in meters but paper does not specify) - # phi : Latitude in degrees SOUTH - # lambda : Longitude in degrees WEST - # Tf : Background forcing temperature ("an anomalous temperature relative to the present conditions) - # ACCdot : Accumulation rate in units of [m/a] ice equivalent - # ABLdot : Surface ablation rate in [m/a] ice equivalent + """ - #Double check lat and long exist: - if np.any(np.isnan(md.mesh.lat)): - raise IOError('PattynSMB error message: md.mesh.lat field required') + # Tma : Mean annual surface temperature in [deg C] + # Tms : Mean summer temperature in [deg C] + # h : Surface / bedrock elevation (I assume in meters but paper does not specify) + # phi : Latitude in degrees SOUTH + # lambda : Longitude in degrees WEST + # Tf : Background forcing temperature ("an anomalous temperature relative to the present conditions) + # ACCdot : Accumulation rate in units of [m / a] ice equivalent + # ABLdot : Surface ablation rate in [m / a] ice equivalent - # Calculate mean annual surface temperature, Eqn (11) - # Here, -0.012 is the atmospheric Lapse rate from sea level in deg/m. - # It is multiplied by surface elevation from sea level - Tma = -15.15 - 0.012*md.geometry.surface - + #Double check lat and long exist: + if np.any(np.isnan(md.mesh.lat)): + raise IOError('PattynSMB error message: md.mesh.lat field required') - # Calculate summer temperature, Eqn (12) - # No melting at PIG in mean conditions - need about 6 degress Tf to start having a negative yearly SMB - Tms = 16.81 - 0.00692*md.geometry.surface - 0.27937*np.abs(md.mesh.lat) + Tf - Tms= Tms[0] + # Calculate mean annual surface temperature, Eqn (11) + # Here, - 0.012 is the atmospheric Lapse rate from sea level in deg / m. + # It is multiplied by surface elevation from sea level + Tma = - 15.15 - 0.012 * md.geometry.surface - # Calculate Accumulation perturbation with Tf forcing, Eqn (9) - ACCdot = 2.5*2**((Tma+Tf)/10.) - 2.5*2**(Tma/10.) + # Calculate summer temperature, Eqn (12) + # No melting at PIG in mean conditions - need about 6 degress Tf to start having a negative yearly SMB + Tms = 16.81 - 0.00692 * md.geometry.surface - 0.27937 * np.abs(md.mesh.lat) + Tf + Tms = Tms[0] - # Calculate Ablation, Eqn (10) (use for both Antarctica & Greenland), max melt is 10m/a - ABLdot=0.*np.ones(md.mesh.numberofvertices) - pos=np.nonzero(Tms>=0) - ABLdot[pos]=np.minimum(1.4*Tms[pos],10) + # Calculate Accumulation perturbation with Tf forcing, Eqn (9) + ACCdot = 2.5 * 2**((Tma + Tf) / 10.) - 2.5 * 2**(Tma / 10.) - smb=ACCdot-ABLdot - return smb[0] + # Calculate Ablation, Eqn (10) (use for both Antarctica & Greenland), max melt is 10m / a + ABLdot = 0. * np.ones(md.mesh.numberofvertices) + pos = np.nonzero(Tms >= 0) + ABLdot[pos] = np.minimum(1.4 * Tms[pos], 10) + + smb = ACCdot - ABLdot + return smb[0] Index: /issm/trunk-jpl/src/m/boundaryconditions/SetIceSheetBC.py =================================================================== --- /issm/trunk-jpl/src/m/boundaryconditions/SetIceSheetBC.py (revision 24212) +++ /issm/trunk-jpl/src/m/boundaryconditions/SetIceSheetBC.py (revision 24213) @@ -1,59 +1,57 @@ -import os import numpy as np -from ContourToMesh import ContourToMesh + def SetIceSheetBC(md): - """ - SETICESHEETBC - Create the boundary conditions for stressbalance and thermal models for an IceSheet with no Ice Front + """ + SETICESHEETBC - Create the boundary conditions for stressbalance and thermal models for an IceSheet with no Ice Front - Usage: - md=SetIceSheetBC(md) + Usage: + md = SetIceSheetBC(md) - See also: SETICESHELFBC, SETMARINEICESHEETBC - """ + See also: SETICESHELFBC, SETMARINEICESHEETBC + """ - #node on Dirichlet - pos=np.nonzero(md.mesh.vertexonboundary) - md.stressbalance.spcvx=float('nan')*np.ones((md.mesh.numberofvertices)) - md.stressbalance.spcvy=float('nan')*np.ones((md.mesh.numberofvertices)) - md.stressbalance.spcvz=float('nan')*np.ones((md.mesh.numberofvertices)) - md.stressbalance.spcvx[pos]=0 - md.stressbalance.spcvy[pos]=0 - md.stressbalance.spcvz[pos]=0 - md.stressbalance.referential=float('nan')*np.ones((md.mesh.numberofvertices,6)) - md.stressbalance.loadingforce=0*np.ones((md.mesh.numberofvertices,3)) + #node on Dirichlet + pos = np.nonzero(md.mesh.vertexonboundary) + md.stressbalance.spcvx = float('nan') * np.ones((md.mesh.numberofvertices)) + md.stressbalance.spcvy = float('nan') * np.ones((md.mesh.numberofvertices)) + md.stressbalance.spcvz = float('nan') * np.ones((md.mesh.numberofvertices)) + md.stressbalance.spcvx[pos] = 0 + md.stressbalance.spcvy[pos] = 0 + md.stressbalance.spcvz[pos] = 0 + md.stressbalance.referential = float('nan') * np.ones((md.mesh.numberofvertices, 6)) + md.stressbalance.loadingforce = 0 * np.ones((md.mesh.numberofvertices, 3)) - #Dirichlet Values - if isinstance(md.inversion.vx_obs,np.ndarray) and np.size(md.inversion.vx_obs,axis=0)==md.mesh.numberofvertices and isinstance(md.inversion.vy_obs,np.ndarray) and np.size(md.inversion.vy_obs,axis=0)==md.mesh.numberofvertices: - print(" boundary conditions for stressbalance model: spc set as observed velocities") - md.stressbalance.spcvx[pos]=md.inversion.vx_obs[pos] - md.stressbalance.spcvy[pos]=md.inversion.vy_obs[pos] - else: - print(" boundary conditions for stressbalance model: spc set as zero") + #Dirichlet Values + if isinstance(md.inversion.vx_obs, np.ndarray) and np.size(md.inversion.vx_obs, axis=0) == md.mesh.numberofvertices and isinstance(md.inversion.vy_obs, np.ndarray) and np.size(md.inversion.vy_obs, axis=0) == md.mesh.numberofvertices: + print(" boundary conditions for stressbalance model: spc set as observed velocities") + md.stressbalance.spcvx[pos] = md.inversion.vx_obs[pos] + md.stressbalance.spcvy[pos] = md.inversion.vy_obs[pos] + else: + print(" boundary conditions for stressbalance model: spc set as zero") - #No ice front -> do nothing + #No ice front - > do nothing - #Create zeros basalforcings and smb - md.smb.initialize(md) - md.basalforcings.initialize(md) + #Create zeros basalforcings and smb + md.smb.initialize(md) + md.basalforcings.initialize(md) - #Deal with other boundary conditions - if np.all(np.isnan(md.balancethickness.thickening_rate)): - md.balancethickness.thickening_rate=np.zeros((md.mesh.numberofvertices)) - print(" no balancethickness.thickening_rate specified: values set as zero") - md.masstransport.spcthickness=float('nan')*np.ones((md.mesh.numberofvertices)) - md.balancethickness.spcthickness=float('nan')*np.ones((md.mesh.numberofvertices)) - md.damage.spcdamage=float('nan')*np.ones((md.mesh.numberofvertices)) + #Deal with other boundary conditions + if np.all(np.isnan(md.balancethickness.thickening_rate)): + md.balancethickness.thickening_rate = np.zeros((md.mesh.numberofvertices)) + print(" no balancethickness.thickening_rate specified: values set as zero") + md.masstransport.spcthickness = float('nan') * np.ones((md.mesh.numberofvertices)) + md.balancethickness.spcthickness = float('nan') * np.ones((md.mesh.numberofvertices)) + md.damage.spcdamage = float('nan') * np.ones((md.mesh.numberofvertices)) - if isinstance(md.initialization.temperature,np.ndarray) and np.size(md.initialization.temperature,axis=0)==md.mesh.numberofvertices: - md.thermal.spctemperature=float('nan')*np.ones((md.mesh.numberofvertices)) - if hasattr(md.mesh,'vertexonsurface'): - pos=np.nonzero(md.mesh.vertexonsurface)[0] - md.thermal.spctemperature[pos]=md.initialization.temperature[pos] #impose observed temperature on surface - if not isinstance(md.basalforcings.geothermalflux,np.ndarray) or not np.size(md.basalforcings.geothermalflux)==md.mesh.numberofvertices: - md.basalforcings.geothermalflux=50.*10**-3*np.ones((md.mesh.numberofvertices)) #50 mW/m^2 - else: - print(" no thermal boundary conditions created: no observed temperature found") + if isinstance(md.initialization.temperature, np.ndarray) and np.size(md.initialization.temperature, axis=0) == md.mesh.numberofvertices: + md.thermal.spctemperature = float('nan') * np.ones((md.mesh.numberofvertices)) + if hasattr(md.mesh, 'vertexonsurface'): + pos = np.nonzero(md.mesh.vertexonsurface)[0] + md.thermal.spctemperature[pos] = md.initialization.temperature[pos] #impose observed temperature on surface + if not isinstance(md.basalforcings.geothermalflux, np.ndarray) or not np.size(md.basalforcings.geothermalflux) == md.mesh.numberofvertices: + md.basalforcings.geothermalflux = 50. * 10**- 3 * np.ones((md.mesh.numberofvertices)) #50 mW / m^2 + else: + print(" no thermal boundary conditions created: no observed temperature found") - return md - + return md Index: /issm/trunk-jpl/src/m/boundaryconditions/SetIceShelfBC.py =================================================================== --- /issm/trunk-jpl/src/m/boundaryconditions/SetIceShelfBC.py (revision 24212) +++ /issm/trunk-jpl/src/m/boundaryconditions/SetIceShelfBC.py (revision 24213) @@ -4,98 +4,98 @@ import MatlabFuncs as m -def SetIceShelfBC(md,icefrontfile=''): - """ - SETICESHELFBC - Create the boundary conditions for stressbalance and thermal models for a Ice Shelf with Ice Front - Neumann BC are used on the ice front (an ARGUS contour around the ice front - must be given in input) - Dirichlet BC are used elsewhere for stressbalance +def SetIceShelfBC(md, icefrontfile=''): + """ + SETICESHELFBC - Create the boundary conditions for stressbalance and thermal models for a Ice Shelf with Ice Front - Usage: - md=SetIceShelfBC(md,varargin) + Neumann BC are used on the ice front (an ARGUS contour around the ice front + must be given in input) + Dirichlet BC are used elsewhere for stressbalance - Example: - md=SetIceShelfBC(md); - md=SetIceShelfBC(md,'Front.exp'); + Usage: + md = SetIceShelfBC(md, varargin) - See also: SETICESHEETBC, SETMARINEICESHEETBC - """ + Example: + md = SetIceShelfBC(md) + md = SetIceShelfBC(md, 'Front.exp') - #node on Dirichlet (boundary and ~icefront) - if icefrontfile: - if not os.path.exists(icefrontfile): - raise IOError("SetIceShelfBC error message: ice front file '%s' not found." % icefrontfile) - nodeinsideicefront=ContourToMesh(md.mesh.elements,md.mesh.x,md.mesh.y,icefrontfile,'node',2) - nodeonicefront=np.logical_and(md.mesh.vertexonboundary,nodeinsideicefront.reshape(-1)) - else: - nodeonicefront=np.zeros((md.mesh.numberofvertices),bool) + See also: SETICESHEETBC, SETMARINEICESHEETBC + """ -# pos=find(md.mesh.vertexonboundary & ~nodeonicefront); - pos=np.nonzero(np.logical_and(md.mesh.vertexonboundary,np.logical_not(nodeonicefront)))[0] - md.stressbalance.spcvx=float('nan')*np.ones(md.mesh.numberofvertices) - md.stressbalance.spcvy=float('nan')*np.ones(md.mesh.numberofvertices) - md.stressbalance.spcvz=float('nan')*np.ones(md.mesh.numberofvertices) - md.stressbalance.referential=float('nan')*np.ones((md.mesh.numberofvertices,6)) - md.stressbalance.loadingforce=0*np.ones((md.mesh.numberofvertices,3)) + #node on Dirichlet (boundary and ~icefront) + if icefrontfile: + if not os.path.exists(icefrontfile): + raise IOError("SetIceShelfBC error message: ice front file '%s' not found." % icefrontfile) + nodeinsideicefront = ContourToMesh(md.mesh.elements, md.mesh.x, md.mesh.y, icefrontfile, 'node', 2) + nodeonicefront = np.logical_and(md.mesh.vertexonboundary, nodeinsideicefront.reshape(- 1)) + else: + nodeonicefront = np.zeros((md.mesh.numberofvertices), bool) - #Icefront position - pos=np.nonzero(nodeonicefront)[0] - md.mask.ice_levelset[pos]=0 + # pos = find(md.mesh.vertexonboundary & ~nodeonicefront) + pos = np.nonzero(np.logical_and(md.mesh.vertexonboundary, np.logical_not(nodeonicefront)))[0] + md.stressbalance.spcvx = float('nan') * np.ones(md.mesh.numberofvertices) + md.stressbalance.spcvy = float('nan') * np.ones(md.mesh.numberofvertices) + md.stressbalance.spcvz = float('nan') * np.ones(md.mesh.numberofvertices) + md.stressbalance.referential = float('nan') * np.ones((md.mesh.numberofvertices, 6)) + md.stressbalance.loadingforce = 0 * np.ones((md.mesh.numberofvertices, 3)) - #First find segments that are not completely on the front - if m.strcmp(md.mesh.elementtype(),'Penta'): - numbernodesfront=4; - elif m.strcmp(md.mesh.elementtype(),'Tria'): - numbernodesfront=2; - else: - raise error('mesh type not supported yet') - if any(md.mask.ice_levelset<=0): - values=md.mask.ice_levelset[md.mesh.segments[:,0:-1]-1] - segmentsfront=1-values - np.sum(segmentsfront,axis=1)!=numbernodesfront - segments=np.nonzero(np.sum(segmentsfront,axis=1)!=numbernodesfront)[0] - #Find all nodes for these segments and spc them - pos=md.mesh.segments[segments,0:-1]-1 - else: - pos=np.nonzero(md.mesh.vertexonboundary)[0] - md.stressbalance.spcvx[pos]=0 - md.stressbalance.spcvy[pos]=0 - md.stressbalance.spcvz[pos]=0 - - #Dirichlet Values - if isinstance(md.inversion.vx_obs,np.ndarray) and np.size(md.inversion.vx_obs,axis=0)==md.mesh.numberofvertices and isinstance(md.inversion.vy_obs,np.ndarray) and np.size(md.inversion.vy_obs,axis=0)==md.mesh.numberofvertices: - #reshape to rank-2 if necessary to match spc arrays - if np.ndim(md.inversion.vx_obs)==1: - md.inversion.vx_obs=md.inversion.vx_obs.reshape(-1,) - if np.ndim(md.inversion.vy_obs)==1: - md.inversion.vy_obs=md.inversion.vy_obs.reshape(-1,) - print(" boundary conditions for stressbalance model: spc set as observed velocities") - md.stressbalance.spcvx[pos]=md.inversion.vx_obs[pos] - md.stressbalance.spcvy[pos]=md.inversion.vy_obs[pos] - else: - print(" boundary conditions for stressbalance model: spc set as zero") + #Icefront position + pos = np.nonzero(nodeonicefront)[0] + md.mask.ice_levelset[pos] = 0 - #Create zeros basalforcings and smb - md.smb.initialize(md) - md.basalforcings.initialize(md) + #First find segments that are not completely on the front + if m.strcmp(md.mesh.elementtype(), 'Penta'): + numbernodesfront = 4 + elif m.strcmp(md.mesh.elementtype(), 'Tria'): + numbernodesfront = 2 + else: + raise NameError('mesh type not supported yet') + if any(md.mask.ice_levelset <= 0): + values = md.mask.ice_levelset[md.mesh.segments[:, 0: - 1] - 1] + segmentsfront = 1 - values + np.sum(segmentsfront, axis=1) != numbernodesfront + segments = np.nonzero(np.sum(segmentsfront, axis=1) != numbernodesfront)[0] + #Find all nodes for these segments and spc them + pos = md.mesh.segments[segments, 0: - 1] - 1 + else: + pos = np.nonzero(md.mesh.vertexonboundary)[0] + md.stressbalance.spcvx[pos] = 0 + md.stressbalance.spcvy[pos] = 0 + md.stressbalance.spcvz[pos] = 0 - #Deal with other boundary conditions - if np.all(np.isnan(md.balancethickness.thickening_rate)): - md.balancethickness.thickening_rate=np.zeros((md.mesh.numberofvertices)) - print(" no balancethickness.thickening_rate specified: values set as zero") - md.masstransport.spcthickness=float('nan')*np.ones((md.mesh.numberofvertices)) - md.balancethickness.spcthickness=float('nan')*np.ones((md.mesh.numberofvertices)) - md.damage.spcdamage=float('nan')*np.ones((md.mesh.numberofvertices)) + #Dirichlet Values + if isinstance(md.inversion.vx_obs, np.ndarray) and np.size(md.inversion.vx_obs, axis=0) == md.mesh.numberofvertices and isinstance(md.inversion.vy_obs, np.ndarray) and np.size(md.inversion.vy_obs, axis=0) == md.mesh.numberofvertices: + #reshape to rank - 2 if necessary to match spc arrays + if np.ndim(md.inversion.vx_obs) == 1: + md.inversion.vx_obs = md.inversion.vx_obs.reshape(- 1, ) + if np.ndim(md.inversion.vy_obs) == 1: + md.inversion.vy_obs = md.inversion.vy_obs.reshape(- 1, ) + print(" boundary conditions for stressbalance model: spc set as observed velocities") + md.stressbalance.spcvx[pos] = md.inversion.vx_obs[pos] + md.stressbalance.spcvy[pos] = md.inversion.vy_obs[pos] + else: + print(" boundary conditions for stressbalance model: spc set as zero") - if isinstance(md.initialization.temperature,np.ndarray) and np.size(md.initialization.temperature,axis=0)==md.mesh.numberofvertices: - md.thermal.spctemperature=float('nan')*np.ones((md.mesh.numberofvertices)) - if hasattr(md.mesh,'vertexonsurface'): - pos=np.nonzero(md.mesh.vertexonsurface)[0] - md.thermal.spctemperature[pos]=md.initialization.temperature[pos] #impose observed temperature on surface - if not isinstance(md.basalforcings.geothermalflux,np.ndarray) or not np.size(md.basalforcings.geothermalflux,axis=0)==md.mesh.numberofvertices: - md.basalforcings.geothermalflux=np.zeros((md.mesh.numberofvertices)) - else: - print(" no thermal boundary conditions created: no observed temperature found") + #Create zeros basalforcings and smb + md.smb.initialize(md) + md.basalforcings.initialize(md) - return md + #Deal with other boundary conditions + if np.all(np.isnan(md.balancethickness.thickening_rate)): + md.balancethickness.thickening_rate = np.zeros((md.mesh.numberofvertices)) + print(" no balancethickness.thickening_rate specified: values set as zero") + md.masstransport.spcthickness = float('nan') * np.ones((md.mesh.numberofvertices)) + md.balancethickness.spcthickness = float('nan') * np.ones((md.mesh.numberofvertices)) + md.damage.spcdamage = float('nan') * np.ones((md.mesh.numberofvertices)) + if isinstance(md.initialization.temperature, np.ndarray) and np.size(md.initialization.temperature, axis=0) == md.mesh.numberofvertices: + md.thermal.spctemperature = float('nan') * np.ones((md.mesh.numberofvertices)) + if hasattr(md.mesh, 'vertexonsurface'): + pos = np.nonzero(md.mesh.vertexonsurface)[0] + md.thermal.spctemperature[pos] = md.initialization.temperature[pos] #impose observed temperature on surface + if not isinstance(md.basalforcings.geothermalflux, np.ndarray) or not np.size(md.basalforcings.geothermalflux, axis=0) == md.mesh.numberofvertices: + md.basalforcings.geothermalflux = np.zeros((md.mesh.numberofvertices)) + else: + print(" no thermal boundary conditions created: no observed temperature found") + + return md Index: /issm/trunk-jpl/src/m/boundaryconditions/SetMarineIceSheetBC.py =================================================================== --- /issm/trunk-jpl/src/m/boundaryconditions/SetMarineIceSheetBC.py (revision 24212) +++ /issm/trunk-jpl/src/m/boundaryconditions/SetMarineIceSheetBC.py (revision 24213) @@ -2,110 +2,108 @@ import numpy as np from ContourToMesh import ContourToMesh -import MatlabFuncs as m -def SetMarineIceSheetBC(md,icefrontfile=''): - """ - SETICEMARINESHEETBC - Create the boundary conditions for stressbalance and thermal models for a Marine Ice Sheet with Ice Front - Neumann BC are used on the ice front (an ARGUS contour around the ice front - can be given in input, or it will be deduced as onfloatingice & onboundary) - Dirichlet BC are used elsewhere for stressbalance +def SetMarineIceSheetBC(md, icefrontfile=''): + """ + SETICEMARINESHEETBC - Create the boundary conditions for stressbalance and thermal models for a Marine Ice Sheet with Ice Front - Usage: - md=SetMarineIceSheetBC(md,icefrontfile) - md=SetMarineIceSheetBC(md) + Neumann BC are used on the ice front (an ARGUS contour around the ice front + can be given in input, or it will be deduced as onfloatingice & onboundary) + Dirichlet BC are used elsewhere for stressbalance - Example: - md=SetMarineIceSheetBC(md,'Front.exp') - md=SetMarineIceSheetBC(md) + Usage: + md = SetMarineIceSheetBC(md, icefrontfile) + md = SetMarineIceSheetBC(md) - See also: SETICESHELFBC, SETMARINEICESHEETBC - """ + Example: + md = SetMarineIceSheetBC(md, 'Front.exp') + md = SetMarineIceSheetBC(md) - #node on Dirichlet (boundary and ~icefront) - if icefrontfile: - #User provided Front.exp, use it - if not os.path.exists(icefrontfile): - raise IOError("SetMarineIceSheetBC error message: ice front file '%s' not found." % icefrontfile) - incontour=ContourToMesh(md.mesh.elements,md.mesh.x,md.mesh.y,icefrontfile,'node',2) - vertexonicefront=np.logical_and(md.mesh.vertexonboundary,incontour.reshape(-1)) - else: - #Guess where the ice front is - vertexonfloatingice=np.zeros((md.mesh.numberofvertices)) - pos=np.nonzero(np.sum(md.mask.groundedice_levelset[md.mesh.elements-1]<0.,axis=1) >0.)[0] - vertexonfloatingice[md.mesh.elements[pos].astype(int)-1]=1. - vertexonicefront=np.logical_and(np.reshape(md.mesh.vertexonboundary,(-1,)),vertexonfloatingice>0.) + See also: SETICESHELFBC, SETMARINEICESHEETBC + """ + #node on Dirichlet (boundary and ~icefront) + if icefrontfile: + #User provided Front.exp, use it + if not os.path.exists(icefrontfile): + raise IOError("SetMarineIceSheetBC error message: ice front file '%s' not found." % icefrontfile) + incontour = ContourToMesh(md.mesh.elements, md.mesh.x, md.mesh.y, icefrontfile, 'node', 2) + vertexonicefront = np.logical_and(md.mesh.vertexonboundary, incontour.reshape(- 1)) + else: + #Guess where the ice front is + vertexonfloatingice = np.zeros((md.mesh.numberofvertices)) + pos = np.nonzero(np.sum(md.mask.groundedice_levelset[md.mesh.elements - 1] < 0., axis=1) > 0.)[0] + vertexonfloatingice[md.mesh.elements[pos].astype(int) - 1] = 1. + vertexonicefront = np.logical_and(np.reshape(md.mesh.vertexonboundary, (- 1, )), vertexonfloatingice > 0.) -# pos=find(md.mesh.vertexonboundary & ~vertexonicefront); - pos=np.nonzero(np.logical_and(md.mesh.vertexonboundary,np.logical_not(vertexonicefront)))[0] - if not np.size(pos): - print("SetMarineIceSheetBC warning: ice front all around the glacier, no dirichlet found. Dirichlet must be added manually.") + #pos = find(md.mesh.vertexonboundary & ~vertexonicefront) + pos = np.nonzero(np.logical_and(md.mesh.vertexonboundary, np.logical_not(vertexonicefront)))[0] + if not np.size(pos): + print("SetMarineIceSheetBC warning: ice front all around the glacier, no dirichlet found. Dirichlet must be added manually.") - md.stressbalance.spcvx=float('nan')*np.ones(md.mesh.numberofvertices) - md.stressbalance.spcvy=float('nan')*np.ones(md.mesh.numberofvertices) - md.stressbalance.spcvz=float('nan')*np.ones(md.mesh.numberofvertices) - md.stressbalance.referential=float('nan')*np.ones((md.mesh.numberofvertices,6)) - md.stressbalance.loadingforce=0*np.ones((md.mesh.numberofvertices,3)) + md.stressbalance.spcvx = float('nan') * np.ones(md.mesh.numberofvertices) + md.stressbalance.spcvy = float('nan') * np.ones(md.mesh.numberofvertices) + md.stressbalance.spcvz = float('nan') * np.ones(md.mesh.numberofvertices) + md.stressbalance.referential = float('nan') * np.ones((md.mesh.numberofvertices, 6)) + md.stressbalance.loadingforce = 0 * np.ones((md.mesh.numberofvertices, 3)) - #Position of ice front - pos=np.nonzero(vertexonicefront)[0] - md.mask.ice_levelset[pos]=0 + #Position of ice front + pos = np.nonzero(vertexonicefront)[0] + md.mask.ice_levelset[pos] = 0 - #First find segments that are not completely on the front - if m.strcmp(md.mesh.elementtype(),'Penta'): - numbernodesfront=4 - elif m.strcmp(md.mesh.elementtype(),'Tria'): - numbernodesfront=2 - else: - raise Exception("Mesh type not supported") - if any(md.mask.ice_levelset<=0): - values=md.mask.ice_levelset[md.mesh.segments[:,0:-1]-1] - segmentsfront=1-values - np.sum(segmentsfront,axis=1)!=numbernodesfront - segments=np.nonzero(np.sum(segmentsfront,axis=1)!=numbernodesfront)[0] - #Find all nodes for these segments and spc them - pos=md.mesh.segments[segments,0:-1]-1 - else: - pos=np.nonzero(md.mesh.vertexonboundary)[0] - md.stressbalance.spcvx[pos]=0 - md.stressbalance.spcvy[pos]=0 - md.stressbalance.spcvz[pos]=0 + #First find segments that are not completely on the front + if md.mesh.elementtype() == 'Penta': + numbernodesfront = 4 + elif md.mesh.elementtype() == 'Tria': + numbernodesfront = 2 + else: + raise Exception("Mesh type not supported") + if any(md.mask.ice_levelset <= 0): + values = md.mask.ice_levelset[md.mesh.segments[:, 0:-1] - 1] + segmentsfront = 1 - values + np.sum(segmentsfront, axis=1) != numbernodesfront + segments = np.nonzero(np.sum(segmentsfront, axis=1) != numbernodesfront)[0] + #Find all nodes for these segments and spc them + pos = md.mesh.segments[segments, 0: - 1] - 1 + else: + pos = np.nonzero(md.mesh.vertexonboundary)[0] + md.stressbalance.spcvx[pos] = 0 + md.stressbalance.spcvy[pos] = 0 + md.stressbalance.spcvz[pos] = 0 - #Dirichlet Values - if isinstance(md.inversion.vx_obs,np.ndarray) and np.size(md.inversion.vx_obs,axis=0)==md.mesh.numberofvertices and isinstance(md.inversion.vy_obs,np.ndarray) and np.size(md.inversion.vy_obs,axis=0)==md.mesh.numberofvertices: - print(" boundary conditions for stressbalance model: spc set as observed velocities") - md.stressbalance.spcvx[pos]=md.inversion.vx_obs[pos] - md.stressbalance.spcvy[pos]=md.inversion.vy_obs[pos] - else: - print(" boundary conditions for stressbalance model: spc set as zero") + #Dirichlet Values + if isinstance(md.inversion.vx_obs, np.ndarray) and np.size(md.inversion.vx_obs, axis=0) == md.mesh.numberofvertices and isinstance(md.inversion.vy_obs, np.ndarray) and np.size(md.inversion.vy_obs, axis=0) == md.mesh.numberofvertices: + print(" boundary conditions for stressbalance model: spc set as observed velocities") + md.stressbalance.spcvx[pos] = md.inversion.vx_obs[pos] + md.stressbalance.spcvy[pos] = md.inversion.vy_obs[pos] + else: + print(" boundary conditions for stressbalance model: spc set as zero") - md.hydrology.spcwatercolumn=np.zeros((md.mesh.numberofvertices,2)) - pos=np.nonzero(md.mesh.vertexonboundary)[0] - md.hydrology.spcwatercolumn[pos,0]=1 + md.hydrology.spcwatercolumn = np.zeros((md.mesh.numberofvertices, 2)) + pos = np.nonzero(md.mesh.vertexonboundary)[0] + md.hydrology.spcwatercolumn[pos, 0] = 1 - #Create zeros basalforcings and smb - md.smb.initialize(md) - md.basalforcings.initialize(md) + #Create zeros basalforcings and smb + md.smb.initialize(md) + md.basalforcings.initialize(md) - #Deal with other boundary conditions - if np.all(np.isnan(md.balancethickness.thickening_rate)): - md.balancethickness.thickening_rate=np.zeros((md.mesh.numberofvertices)) - print(" no balancethickness.thickening_rate specified: values set as zero") + #Deal with other boundary conditions + if np.all(np.isnan(md.balancethickness.thickening_rate)): + md.balancethickness.thickening_rate = np.zeros((md.mesh.numberofvertices)) + print(" no balancethickness.thickening_rate specified: values set as zero") - md.masstransport.spcthickness=float('nan')*np.ones((md.mesh.numberofvertices)) - md.balancethickness.spcthickness=float('nan')*np.ones((md.mesh.numberofvertices)) - md.damage.spcdamage=float('nan')*np.ones((md.mesh.numberofvertices)) + md.masstransport.spcthickness = float('nan') * np.ones((md.mesh.numberofvertices)) + md.balancethickness.spcthickness = float('nan') * np.ones((md.mesh.numberofvertices)) + md.damage.spcdamage = float('nan') * np.ones((md.mesh.numberofvertices)) - if isinstance(md.initialization.temperature,np.ndarray) and np.size(md.initialization.temperature,axis=0)==md.mesh.numberofvertices: - md.thermal.spctemperature=float('nan')*np.ones((md.mesh.numberofvertices)) - if hasattr(md.mesh,'vertexonsurface'): - pos=np.nonzero(md.mesh.vertexonsurface)[0] - md.thermal.spctemperature[pos]=md.initialization.temperature[pos] #impose observed temperature on surface - if not isinstance(md.basalforcings.geothermalflux,np.ndarray) or not np.size(md.basalforcings.geothermalflux,axis=0)==md.mesh.numberofvertices: - md.basalforcings.geothermalflux=np.zeros((md.mesh.numberofvertices)) - md.basalforcings.geothermalflux[np.nonzero(md.mask.groundedice_levelset>0.)]=50.*10.**-3 #50mW/m2 - else: - print(" no thermal boundary conditions created: no observed temperature found") + if isinstance(md.initialization.temperature, np.ndarray) and np.size(md.initialization.temperature, axis=0) == md.mesh.numberofvertices: + md.thermal.spctemperature = float('nan') * np.ones((md.mesh.numberofvertices)) + if hasattr(md.mesh, 'vertexonsurface'): + pos = np.nonzero(md.mesh.vertexonsurface)[0] + md.thermal.spctemperature[pos] = md.initialization.temperature[pos] #impose observed temperature on surface + if not isinstance(md.basalforcings.geothermalflux, np.ndarray) or not np.size(md.basalforcings.geothermalflux, axis=0) == md.mesh.numberofvertices: + md.basalforcings.geothermalflux = np.zeros((md.mesh.numberofvertices)) + md.basalforcings.geothermalflux[np.nonzero(md.mask.groundedice_levelset > 0.)] = 50. * 10.**- 3 #50mW / m2 + else: + print(" no thermal boundary conditions created: no observed temperature found") - return md - + return md Index: /issm/trunk-jpl/src/m/boundaryconditions/love_numbers.py =================================================================== --- /issm/trunk-jpl/src/m/boundaryconditions/love_numbers.py (revision 24212) +++ /issm/trunk-jpl/src/m/boundaryconditions/love_numbers.py (revision 24213) @@ -1,10063 +1,10062 @@ -from MatlabFuncs import * -from model import * import numpy as np -def love_numbers(value,*varargin): -#LOVE_NUMBERS: provide love numbers (value 'h','k','l','gamma' and 'lambda' -# retrieved from: http://www.srosat.com/iag-jsg/loveNb.php -# Usage: series=love_numbers(value) -# series=love_numbers(value,reference_frame) -# -# where value is one of 'h','k','l','gamma' and 'lambda'. -# reference_frame = one of 'CM' (default) and 'CF'. -# -# Example: -# love_k=love_numbers('k'); -# love_k=love_numbers('k','CF'); -# + +def love_numbers(value, * varargin): + '''LOVE_NUMBERS: provide love numbers (value 'h', 'k', 'l', 'gamma' and 'lambda' + retrieved from: http: / / www.srosat.com / iag - jsg / loveNb.php + Usage: series = love_numbers(value) + series = love_numbers(value, reference_frame) + + where value is one of 'h', 'k', 'l', 'gamma' and 'lambda'. + reference_frame = one of 'CM' (default) and 'CF'. + + Example: + love_k = love_numbers('k') + love_k = love_numbers('k', 'CF') + + ''' # some checks: - if len(varargin)==0: - frame='CM'; + if len(varargin) == 0: + frame = 'CM' print('Info: computation is done in Center of Mass (CM) reference frame by default') - elif len(varargin)==1: + elif len(varargin) == 1: reference_frame = varargin[0] - if (reference_frame in ['CF','CM']): - frame=reference_frame; + if (reference_frame in ['CF', 'CM']): + frame = reference_frame else: raise RuntimeError('reference_frame should be one of ''CM'' or ''CF''') else: - raise RuntimeError('love_numbers error message: bad usage') - - if value not in ['h','k','l','gamma','lambda']: - raise RuntimeError('value should be one of ''h'',''k'',''l'',''gamma'' and ''lambda''') - - if len(varargin)>1: - raise RuntimeError('love_numbers error message: wrong usage') - - love_numbers=np.array([[ 0 , 0 ,0 ,0 ,0 ,0 ,0 ], - [ -1.28740059,-1.00000000,-0.89858519,1.28740059, 0.42519882 ,0.89858519 ,0.00000000 ], - [ -1.00025365, -0.30922675, 0.02060926, 1.69102690, 0.46358648, 0.67016399, 0.61829668], - [ -1.06243501, -0.19927948, 0.06801636, 1.86315553, 0.55741597, 0.73270416, 0.56270589], - [ -1.06779588, -0.13649834, 0.05667027, 1.93129754, 0.63672498, 0.80683140, 0.51132745], - [ -1.10365923, -0.10736896, 0.04401221, 1.99629027, 0.68737906, 0.84861883, 0.48642259], - [ -1.16440348, -0.09295485, 0.03638747, 2.07144863, 0.72031283, 0.87065768, 0.47898268], - [ -1.23634156, -0.08469861, 0.03202759, 2.15164295, 0.74355796, 0.88327380, 0.47955214], - [ -1.31140380, -0.07921412, 0.02937593, 2.23218968, 0.76126493, 0.89140995, 0.48323250], - [ -1.38582399, -0.07513541, 0.02762338, 2.31068858, 0.77552290, 0.89724121, 0.48795424], - [ -1.45807465, -0.07187005, 0.02638627, 2.38620460, 0.78744212, 0.90174369, 0.49291061], - [ -1.52763314, -0.06913154, 0.02547640, 2.45850160, 0.79766475, 0.90539206, 0.49779422], - [ -1.59437866, -0.06676258, 0.02479080, 2.52761607, 0.80659635, 0.90844662, 0.50248477], - [ -1.65833071, -0.06466619, 0.02426511, 2.59366452, 0.81451271, 0.91106870, 0.50693175], - [ -1.71954820, -0.06277732, 0.02385464, 2.65677088, 0.82161167, 0.91336804, 0.51111243], - [ -1.77809640, -0.06105001, 0.02352654, 2.71704639, 0.82804049, 0.91542346, 0.51501712], - [ -1.83403970, -0.05945081, 0.02325609, 2.77458889, 0.83391153, 0.91729309, 0.51864363], - [ -1.88744242, -0.05795502, 0.02302469, 2.82948740, 0.83931209, 0.91902029, 0.52199490], - [ -1.93837115, -0.05654418, 0.02281843, 2.88182697, 0.84431095, 0.92063739, 0.52507761], - [ -1.98689666, -0.05520447, 0.02262706, 2.93169219, 0.84896295, 0.92216847, 0.52790108], - [ -2.03309477, -0.05392545, 0.02244322, 2.97916932, 0.85331225, 0.92363132, 0.53047654], - [ -2.07704643, -0.05269926, 0.02226173, 3.02434717, 0.85739480, 0.92503902, 0.53281639], - 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[ -6.27341946, -0.00031292, 0.00019168, 7.27310654, 0.99904419, 0.99949539, 0.49327063], - [ -6.27341954, -0.00031289, 0.00019166, 7.27310665, 0.99904428, 0.99949545, 0.49327050], - [ -6.27341962, -0.00031286, 0.00019164, 7.27310676, 0.99904438, 0.99949550, 0.49327069], - [ -6.27341969, -0.00031283, 0.00019162, 7.27310686, 0.99904448, 0.99949555, 0.49327081], - [ -6.27341977, -0.00031280, 0.00019161, 7.27310697, 0.99904457, 0.99949560, 0.49327077], - [ -6.27341984, -0.00031276, 0.00019159, 7.27310708, 0.99904467, 0.99949565, 0.49327081], - [ -6.27341992, -0.00031273, 0.00019157, 7.27310719, 0.99904477, 0.99949570, 0.49327088], - [ -6.27341999, -0.00031270, 0.00019155, 7.27310729, 0.99904486, 0.99949575, 0.49327082], - [ -6.27342007, -0.00031267, 0.00019153, 7.27310740, 0.99904496, 0.99949580, 0.49327067], - [ -6.27342015, -0.00031264, 0.00019151, 7.27310751, 0.99904506, 0.99949585, 0.49327061], - [ -6.27342022, -0.00031261, 0.00019149, 7.27310761, 0.99904515, 0.99949590, 0.49327079], - [ -6.27342030, -0.00031258, 0.00019147, 7.27310772, 0.99904525, 0.99949595, 0.49327103], - [ -6.27342037, -0.00031254, 0.00019145, 7.27310783, 0.99904535, 0.99949601, 0.49327107], - [ -6.27342045, -0.00031251, 0.00019143, 7.27310794, 0.99904544, 0.99949606, 0.49327084], - [ -6.27342052, -0.00031248, 0.00019141, 7.27310804, 0.99904554, 0.99949611, 0.49327096], - [ -6.27342060, -0.00031245, 0.00019139, 7.27310815, 0.99904563, 0.99949616, 0.49327062], - [ -6.27342067, -0.00031242, 0.00019137, 7.27310826, 0.99904573, 0.99949621, 0.49327088], - [ -6.27342075, -0.00031239, 0.00019135, 7.27310836, 0.99904583, 0.99949626, 0.49327094], - [ -6.27342083, -0.00031235, 0.00019133, 7.27310847, 0.99904592, 0.99949631, 0.49327095], - [ -6.27342090, -0.00031232, 0.00019132, 7.27310858, 0.99904602, 0.99949636, 0.49327111], - [ -6.27342098, -0.00031229, 0.00019130, 7.27310869, 0.99904612, 0.99949641, 0.49327066], - [ -6.27342105, -0.00031226, 0.00019128, 7.27310879, 0.99904621, 0.99949646, 0.49327112], - [ -6.27342113, -0.00031223, 0.00019126, 7.27310890, 0.99904631, 0.99949651, 0.49327094], - [ -6.27342120, -0.00031220, 0.00019124, 7.27310901, 0.99904641, 0.99949656, 0.49327097], - [ -6.27342128, -0.00031217, 0.00019122, 7.27310911, 0.99904650, 0.99949662, 0.49327094], - [ -6.27342135, -0.00031213, 0.00019120, 7.27310922, 0.99904660, 0.99949667, 0.49327120], - [ -6.27342143, -0.00031210, 0.00019118, 7.27310933, 0.99904669, 0.99949672, 0.49327123], - [ -6.27342150, -0.00031207, 0.00019116, 7.27310943, 0.99904679, 0.99949677, 0.49327124], - [ -6.27342158, -0.00031204, 0.00019114, 7.27310954, 0.99904689, 0.99949682, 0.49327089], - [ -6.27342166, -0.00031201, 0.00019112, 7.27310965, 0.99904698, 0.99949687, 0.49327096], - [ -6.27342173, -0.00031198, 0.00019110, 7.27310975, 0.99904708, 0.99949692, 0.49327093], - [ -6.27342181, -0.00031195, 0.00019108, 7.27310986, 0.99904717, 0.99949697, 0.49327128], - [ -6.27342188, -0.00031191, 0.00019106, 7.27310997, 0.99904727, 0.99949702, 0.49327122], - [ -6.27342196, -0.00031188, 0.00019105, 7.27311007, 0.99904737, 0.99949707, 0.49327128], - [ -6.27342203, -0.00031185, 0.00019103, 7.27311018, 0.99904746, 0.99949712, 0.49327113], - [ -6.27342211, -0.00031182, 0.00019101, 7.27311029, 0.99904756, 0.99949717, 0.49327121], - [ -6.27342218, -0.00031179, 0.00019099, 7.27311039, 0.99904765, 0.99949722, 0.49327115], - [ -6.27342226, -0.00031176, 0.00019097, 7.27311050, 0.99904775, 0.99949727, 0.49327114], - [ -6.27342233, -0.00031173, 0.00019095, 7.27311061, 0.99904785, 0.99949733, 0.49327102], - [ -6.27342241, -0.00031169, 0.00019093, 7.27311071, 0.99904794, 0.99949738, 0.49327120], - [ -6.27342248, -0.00031166, 0.00019091, 7.27311082, 0.99904804, 0.99949743, 0.49327130], - [ -6.27342256, -0.00031163, 0.00019089, 7.27311093, 0.99904813, 0.99949748, 0.49327109], - [ -6.27342263, -0.00031160, 0.00019087, 7.27311103, 0.99904823, 0.99949753, 0.49327132], - [ -6.27342271, -0.00031157, 0.00019085, 7.27311114, 0.99904833, 0.99949758, 0.49327146], - [ -6.27342278, -0.00031154, 0.00019083, 7.27311125, 0.99904842, 0.99949763, 0.49327090], - [ -6.27342286, -0.00031151, 0.00019081, 7.27311135, 0.99904852, 0.99949768, 0.49327123], - [ -6.27342293, -0.00031147, 0.00019080, 7.27311146, 0.99904861, 0.99949773, 0.49327134], - [ -6.27342301, -0.00031144, 0.00019078, 7.27311156, 0.99904871, 0.99949778, 0.49327133], - [ -6.27342308, -0.00031141, 0.00019076, 7.27311167, 0.99904880, 0.99949783, 0.49327117], - [ -6.27342316, -0.00031138, 0.00019074, 7.27311178, 0.99904890, 0.99949788, 0.49327124], - [ -6.27342323, -0.00031135, 0.00019072, 7.27311188, 0.99904900, 0.99949793, 0.49327116], - [ -6.27342331, -0.00031132, 0.00019070, 7.27311199, 0.99904909, 0.99949798, 0.49327125], - [ -6.27342338, -0.00031129, 0.00019068, 7.27311210, 0.99904919, 0.99949803, 0.49327132], - [ -6.27342346, -0.00031126, 0.00019066, 7.27311220, 0.99904928, 0.99949808, 0.49327161], - [ -6.27342353, -0.00031122, 0.00019064, 7.27311231, 0.99904938, 0.99949813, 0.49327137], - [ -6.27342361, -0.00031119, 0.00019062, 7.27311242, 0.99904947, 0.99949818, 0.49327141], - [ -6.27342368, -0.00031116, 0.00019060, 7.27311252, 0.99904957, 0.99949824, 0.49327151], - [ -6.27342376, -0.00031113, 0.00019058, 7.27311263, 0.99904966, 0.99949829, 0.49327147], - [ -6.27342383, -0.00031110, 0.00019057, 7.27311273, 0.99904976, 0.99949834, 0.49327157], - [ -6.27342391, -0.00031107, 0.00019055, 7.27311284, 0.99904986, 0.99949839, 0.49327158], - [ -6.27342398, -0.00031104, 0.00019053, 7.27311295, 0.99904995, 0.99949844, 0.49327140], - [ -6.27342406, -0.00031101, 0.00019051, 7.27311305, 0.99905005, 0.99949849, 0.49327149], - [ -6.27342413, -0.00031097, 0.00019049, 7.27311316, 0.99905014, 0.99949854, 0.49327130], - [ -6.27342421, -0.00031094, 0.00019047, 7.27311326, 0.99905024, 0.99949859, 0.49327138], - [ -6.27342428, -0.00031091, 0.00019045, 7.27311337, 0.99905033, 0.99949864, 0.49327154], - [ -6.27342436, -0.00031088, 0.00019043, 7.27311348, 0.99905043, 0.99949869, 0.49327144], - [ -6.27342443, -0.00031085, 0.00019041, 7.27311358, 0.99905052, 0.99949874, 0.49327149], - [ -6.27342451, -0.00031082, 0.00019039, 7.27311369, 0.99905062, 0.99949879, 0.49327160], - [ -6.27342458, -0.00031079, 0.00019037, 7.27311379, 0.99905071, 0.99949884, 0.49327162], - [ -6.27342466, -0.00031076, 0.00019035, 7.27311390, 0.99905081, 0.99949889, 0.49327146], - [ -6.27342473, -0.00031072, 0.00019034, 7.27311401, 0.99905091, 0.99949894, 0.49327178], - [ -6.27342480, -0.00031069, 0.00019032, 7.27311411, 0.99905100, 0.99949899, 0.49327156], - [ -6.27342488, -0.00031066, 0.00019030, 7.27311422, 0.99905110, 0.99949904, 0.49327151], - [ -6.27342495, -0.00031063, 0.00019028, 7.27311432, 0.99905119, 0.99949909, 0.49327157], - [ -6.27342503, -0.00031060, 0.00019026, 7.27311443, 0.99905129, 0.99949914, 0.49327162], - [ -6.27342510, -0.00031057, 0.00019024, 7.27311453, 0.99905138, 0.99949919, 0.49327180], - [ -6.27342518, -0.00031054, 0.00019022, 7.27311464, 0.99905148, 0.99949924, 0.49327153], - [ -6.27342525, -0.00031051, 0.00019020, 7.27311475, 0.99905157, 0.99949929, 0.49327170], - [ -6.27342533, -0.00031047, 0.00019018, 7.27311485, 0.99905167, 0.99949934, 0.49327164], - [ -6.27342540, -0.00031044, 0.00019016, 7.27311496, 0.99905176, 0.99949939, 0.49327177], - [ -6.27342548, -0.00031041, 0.00019014, 7.27311506, 0.99905186, 0.99949944, 0.49327171], - [ -6.27342555, -0.00031038, 0.00019013, 7.27311517, 0.99905195, 0.99949949, 0.49327163], - [ -6.27342563, -0.00031035, 0.00019011, 7.27311527, 0.99905205, 0.99949954, 0.49327148], - [ -6.27342570, -0.00031032, 0.00019009, 7.27311538, 0.99905214, 0.99949959, 0.49327177], - [ -6.27342577, -0.00031029, 0.00019007, 7.27311549, 0.99905224, 0.99949964, 0.49327190], - [ -6.27342585, -0.00031026, 0.00019005, 7.27311559, 0.99905233, 0.99949969, 0.49327174], - [ -6.27342592, -0.00031023, 0.00019003, 7.27311570, 0.99905243, 0.99949974, 0.49327179], - [ -6.27342600, -0.00031019, 0.00019001, 7.27311580, 0.99905252, 0.99949979, 0.49327165], - [ -6.27342607, -0.00031016, 0.00018999, 7.27311591, 0.99905262, 0.99949984, 0.49327180], - [ -6.27342615, -0.00031013, 0.00018997, 7.27311601, 0.99905271, 0.99949989, 0.49327176], - [ -6.27342622, -0.00031010, 0.00018995, 7.27311612, 0.99905281, 0.99949994, 0.49327155], - [ -6.27342630, -0.00031007, 0.00018993, 7.27311622, 0.99905290, 0.99949999, 0.49327169], - [ -6.27342637, -0.00031004, 0.00018992, 7.27311633, 0.99905300, 0.99950004, 0.49327184], - [ -6.27342644, -0.00031001, 0.00018990, 7.27311644, 0.99905309, 0.99950009, 0.49327184], - [ -6.27342652, -0.00030998, 0.00018988, 7.27311654, 0.99905319, 0.99950014, 0.49327176], - [ -6.27342659, -0.00030995, 0.00018986, 7.27311665, 0.99905328, 0.99950019, 0.49327184], - [ -6.27342667, -0.00030992, 0.00018984, 7.27311675, 0.99905338, 0.99950024, 0.49327166], - [ -6.27342674, -0.00030988, 0.00018982, 7.27311686, 0.99905347, 0.99950029, 0.49327222], - [ -6.27342682, -0.00030985, 0.00018980, 7.27311696, 0.99905357, 0.99950034, 0.49327211], - [ -6.27342689, -0.00030982, 0.00018978, 7.27311707, 0.99905366, 0.99950039, 0.49327202], - [ -6.27342696, -0.00030979, 0.00018976, 7.27311717, 0.99905376, 0.99950044, 0.49327179], - [ -6.27342704, -0.00030976, 0.00018974, 7.27311728, 0.99905385, 0.99950049, 0.49327176], - [ -6.27342711, -0.00030973, 0.00018973, 7.27311738, 0.99905394, 0.99950054, 0.49327202], - [ -6.27342719, -0.00030970, 0.00018971, 7.27311749, 0.99905404, 0.99950059, 0.49327184], - [ -6.27342726, -0.00030967, 0.00018969, 7.27311759, 0.99905413, 0.99950064, 0.49327198], - [ -6.27342733, -0.00030964, 0.00018967, 7.27311770, 0.99905423, 0.99950069, 0.49327205], - [ -6.27342741, -0.00030961, 0.00018965, 7.27311780, 0.99905432, 0.99950074, 0.49327200], - [ -6.27342748, -0.00030957, 0.00018963, 7.27311791, 0.99905442, 0.99950079, 0.49327197], - [ -6.27342756, -0.00030954, 0.00018961, 7.27311801, 0.99905451, 0.99950084, 0.49327183], - [ -6.27342763, -0.00030951, 0.00018959, 7.27311812, 0.99905461, 0.99950089, 0.49327208], - [ -6.27342771, -0.00030948, 0.00018957, 7.27311822, 0.99905470, 0.99950094, 0.49327205], - [ -6.27342778, -0.00030945, 0.00018956, 7.27311833, 0.99905480, 0.99950099, 0.49327194]]); - - if value=='h': - series=love_numbers[:,0]; - elif value=='k': - series=love_numbers[:,1]; - elif value=='l': - series=love_numbers[:,2]; - elif value=='gamma': - series=love_numbers[:,3]; - elif value=='lambda': - series=love_numbers[:,4]; + raise RuntimeError('love_numbers error message: bad usage') + + if value not in ['h', 'k', 'l', 'gamma', 'lambda']: + raise RuntimeError('value should be one of ''h'', ''k'', ''l'', ''gamma'' and ''lambda''') + + if len(varargin) > 1: + raise RuntimeError('love_numbers error message: wrong usage') + + love_numbers = np.array([[0, 0, 0, 0, 0, 0, 0], + [- 1.28740059, - 1.00000000, - 0.89858519, 1.28740059, 0.42519882, 0.89858519, 0.00000000], + [- 1.00025365, - 0.30922675, 0.02060926, 1.69102690, 0.46358648, 0.67016399, 0.61829668], + [- 1.06243501, - 0.19927948, 0.06801636, 1.86315553, 0.55741597, 0.73270416, 0.56270589], + [- 1.06779588, - 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0.00031176, 0.00019097, 7.27311050, 0.99904775, 0.99949727, 0.49327114], + [- 6.27342233, - 0.00031173, 0.00019095, 7.27311061, 0.99904785, 0.99949733, 0.49327102], + [- 6.27342241, - 0.00031169, 0.00019093, 7.27311071, 0.99904794, 0.99949738, 0.49327120], + [- 6.27342248, - 0.00031166, 0.00019091, 7.27311082, 0.99904804, 0.99949743, 0.49327130], + [- 6.27342256, - 0.00031163, 0.00019089, 7.27311093, 0.99904813, 0.99949748, 0.49327109], + [- 6.27342263, - 0.00031160, 0.00019087, 7.27311103, 0.99904823, 0.99949753, 0.49327132], + [- 6.27342271, - 0.00031157, 0.00019085, 7.27311114, 0.99904833, 0.99949758, 0.49327146], + [- 6.27342278, - 0.00031154, 0.00019083, 7.27311125, 0.99904842, 0.99949763, 0.49327090], + [- 6.27342286, - 0.00031151, 0.00019081, 7.27311135, 0.99904852, 0.99949768, 0.49327123], + [- 6.27342293, - 0.00031147, 0.00019080, 7.27311146, 0.99904861, 0.99949773, 0.49327134], + [- 6.27342301, - 0.00031144, 0.00019078, 7.27311156, 0.99904871, 0.99949778, 0.49327133], + [- 6.27342308, - 0.00031141, 0.00019076, 7.27311167, 0.99904880, 0.99949783, 0.49327117], + [- 6.27342316, - 0.00031138, 0.00019074, 7.27311178, 0.99904890, 0.99949788, 0.49327124], + [- 6.27342323, - 0.00031135, 0.00019072, 7.27311188, 0.99904900, 0.99949793, 0.49327116], + [- 6.27342331, - 0.00031132, 0.00019070, 7.27311199, 0.99904909, 0.99949798, 0.49327125], + [- 6.27342338, - 0.00031129, 0.00019068, 7.27311210, 0.99904919, 0.99949803, 0.49327132], + [- 6.27342346, - 0.00031126, 0.00019066, 7.27311220, 0.99904928, 0.99949808, 0.49327161], + [- 6.27342353, - 0.00031122, 0.00019064, 7.27311231, 0.99904938, 0.99949813, 0.49327137], + [- 6.27342361, - 0.00031119, 0.00019062, 7.27311242, 0.99904947, 0.99949818, 0.49327141], + [- 6.27342368, - 0.00031116, 0.00019060, 7.27311252, 0.99904957, 0.99949824, 0.49327151], + [- 6.27342376, - 0.00031113, 0.00019058, 7.27311263, 0.99904966, 0.99949829, 0.49327147], + [- 6.27342383, - 0.00031110, 0.00019057, 7.27311273, 0.99904976, 0.99949834, 0.49327157], + [- 6.27342391, - 0.00031107, 0.00019055, 7.27311284, 0.99904986, 0.99949839, 0.49327158], + [- 6.27342398, - 0.00031104, 0.00019053, 7.27311295, 0.99904995, 0.99949844, 0.49327140], + [- 6.27342406, - 0.00031101, 0.00019051, 7.27311305, 0.99905005, 0.99949849, 0.49327149], + [- 6.27342413, - 0.00031097, 0.00019049, 7.27311316, 0.99905014, 0.99949854, 0.49327130], + [- 6.27342421, - 0.00031094, 0.00019047, 7.27311326, 0.99905024, 0.99949859, 0.49327138], + [- 6.27342428, - 0.00031091, 0.00019045, 7.27311337, 0.99905033, 0.99949864, 0.49327154], + [- 6.27342436, - 0.00031088, 0.00019043, 7.27311348, 0.99905043, 0.99949869, 0.49327144], + [- 6.27342443, - 0.00031085, 0.00019041, 7.27311358, 0.99905052, 0.99949874, 0.49327149], + [- 6.27342451, - 0.00031082, 0.00019039, 7.27311369, 0.99905062, 0.99949879, 0.49327160], + [- 6.27342458, - 0.00031079, 0.00019037, 7.27311379, 0.99905071, 0.99949884, 0.49327162], + [- 6.27342466, - 0.00031076, 0.00019035, 7.27311390, 0.99905081, 0.99949889, 0.49327146], + [- 6.27342473, - 0.00031072, 0.00019034, 7.27311401, 0.99905091, 0.99949894, 0.49327178], + [- 6.27342480, - 0.00031069, 0.00019032, 7.27311411, 0.99905100, 0.99949899, 0.49327156], + [- 6.27342488, - 0.00031066, 0.00019030, 7.27311422, 0.99905110, 0.99949904, 0.49327151], + [- 6.27342495, - 0.00031063, 0.00019028, 7.27311432, 0.99905119, 0.99949909, 0.49327157], + [- 6.27342503, - 0.00031060, 0.00019026, 7.27311443, 0.99905129, 0.99949914, 0.49327162], + [- 6.27342510, - 0.00031057, 0.00019024, 7.27311453, 0.99905138, 0.99949919, 0.49327180], + [- 6.27342518, - 0.00031054, 0.00019022, 7.27311464, 0.99905148, 0.99949924, 0.49327153], + [- 6.27342525, - 0.00031051, 0.00019020, 7.27311475, 0.99905157, 0.99949929, 0.49327170], + [- 6.27342533, - 0.00031047, 0.00019018, 7.27311485, 0.99905167, 0.99949934, 0.49327164], + [- 6.27342540, - 0.00031044, 0.00019016, 7.27311496, 0.99905176, 0.99949939, 0.49327177], + [- 6.27342548, - 0.00031041, 0.00019014, 7.27311506, 0.99905186, 0.99949944, 0.49327171], + [- 6.27342555, - 0.00031038, 0.00019013, 7.27311517, 0.99905195, 0.99949949, 0.49327163], + [- 6.27342563, - 0.00031035, 0.00019011, 7.27311527, 0.99905205, 0.99949954, 0.49327148], + [- 6.27342570, - 0.00031032, 0.00019009, 7.27311538, 0.99905214, 0.99949959, 0.49327177], + [- 6.27342577, - 0.00031029, 0.00019007, 7.27311549, 0.99905224, 0.99949964, 0.49327190], + [- 6.27342585, - 0.00031026, 0.00019005, 7.27311559, 0.99905233, 0.99949969, 0.49327174], + [- 6.27342592, - 0.00031023, 0.00019003, 7.27311570, 0.99905243, 0.99949974, 0.49327179], + [- 6.27342600, - 0.00031019, 0.00019001, 7.27311580, 0.99905252, 0.99949979, 0.49327165], + [- 6.27342607, - 0.00031016, 0.00018999, 7.27311591, 0.99905262, 0.99949984, 0.49327180], + [- 6.27342615, - 0.00031013, 0.00018997, 7.27311601, 0.99905271, 0.99949989, 0.49327176], + [- 6.27342622, - 0.00031010, 0.00018995, 7.27311612, 0.99905281, 0.99949994, 0.49327155], + [- 6.27342630, - 0.00031007, 0.00018993, 7.27311622, 0.99905290, 0.99949999, 0.49327169], + [- 6.27342637, - 0.00031004, 0.00018992, 7.27311633, 0.99905300, 0.99950004, 0.49327184], + [- 6.27342644, - 0.00031001, 0.00018990, 7.27311644, 0.99905309, 0.99950009, 0.49327184], + [- 6.27342652, - 0.00030998, 0.00018988, 7.27311654, 0.99905319, 0.99950014, 0.49327176], + [- 6.27342659, - 0.00030995, 0.00018986, 7.27311665, 0.99905328, 0.99950019, 0.49327184], + [- 6.27342667, - 0.00030992, 0.00018984, 7.27311675, 0.99905338, 0.99950024, 0.49327166], + [- 6.27342674, - 0.00030988, 0.00018982, 7.27311686, 0.99905347, 0.99950029, 0.49327222], + [- 6.27342682, - 0.00030985, 0.00018980, 7.27311696, 0.99905357, 0.99950034, 0.49327211], + [- 6.27342689, - 0.00030982, 0.00018978, 7.27311707, 0.99905366, 0.99950039, 0.49327202], + [- 6.27342696, - 0.00030979, 0.00018976, 7.27311717, 0.99905376, 0.99950044, 0.49327179], + [- 6.27342704, - 0.00030976, 0.00018974, 7.27311728, 0.99905385, 0.99950049, 0.49327176], + [- 6.27342711, - 0.00030973, 0.00018973, 7.27311738, 0.99905394, 0.99950054, 0.49327202], + [- 6.27342719, - 0.00030970, 0.00018971, 7.27311749, 0.99905404, 0.99950059, 0.49327184], + [- 6.27342726, - 0.00030967, 0.00018969, 7.27311759, 0.99905413, 0.99950064, 0.49327198], + [- 6.27342733, - 0.00030964, 0.00018967, 7.27311770, 0.99905423, 0.99950069, 0.49327205], + [- 6.27342741, - 0.00030961, 0.00018965, 7.27311780, 0.99905432, 0.99950074, 0.49327200], + [- 6.27342748, - 0.00030957, 0.00018963, 7.27311791, 0.99905442, 0.99950079, 0.49327197], + [- 6.27342756, - 0.00030954, 0.00018961, 7.27311801, 0.99905451, 0.99950084, 0.49327183], + [- 6.27342763, - 0.00030951, 0.00018959, 7.27311812, 0.99905461, 0.99950089, 0.49327208], + [- 6.27342771, - 0.00030948, 0.00018957, 7.27311822, 0.99905470, 0.99950094, 0.49327205], + [- 6.27342778, - 0.00030945, 0.00018956, 7.27311833, 0.99905480, 0.99950099, 0.49327194]]) + + if value == 'h': + series = love_numbers[:, 0] + elif value == 'k': + series = love_numbers[:, 1] + elif value == 'l': + series = love_numbers[:, 2] + elif value == 'gamma': + series = love_numbers[:, 3] + elif value == 'lambda': + series = love_numbers[:, 4] else: raise RuntimeError(['love_numbers error message: unknow value:', value]) - - # choose degree 1 term for CF reference system - if frame=='CF': # from Blewitt, 2003, JGR - if value=='h': - series[1] = -0.269; - elif value=='k': - series[1] = 0.021; - elif value=='l': - series[1] = 0.134; + + # choose degree 1 term for CF reference system + if frame == 'CF': # from Blewitt, 2003, JGR + if value == 'h': + series[1] = - 0.269 + elif value == 'k': + series[1] = 0.021 + elif value == 'l': + series[1] = 0.134 return series - Index: /issm/trunk-jpl/src/m/classes/SMBcomponents.py =================================================================== --- /issm/trunk-jpl/src/m/classes/SMBcomponents.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/SMBcomponents.py (revision 24213) @@ -3,4 +3,5 @@ from project3d import * from WriteData import * + class SMBcomponents(object): @@ -9,95 +10,97 @@ Usage: - SMBcomponents=SMBcomponents(); + SMBcomponents = SMBcomponents() """ - def __init__(self): # {{{ + def __init__(self): # {{{ self.accumulation = float('NaN') self.runoff = float('NaN') self.evaporation = float('NaN') self.isclimatology = 0 - self.requested_outputs = [] - #}}} - def __repr__(self): # {{{ - string=" surface forcings parameters (SMB=accumulation-runoff-evaporation) :" - string="%s\n%s"%(string,fielddisplay(self,'accumulation','accumulated snow [m/yr ice eq]')) - string="%s\n%s"%(string,fielddisplay(self,'runoff','amount of ice melt lost from the ice column [m/yr ice eq]')) - string="%s\n%s"%(string,fielddisplay(self,'evaporation','mount of ice lost to evaporative processes [m/yr ice eq]')) - string="%s\n%s"%(string,fielddisplay(self,'isclimatology','repeat all forcings when past last forcing time (default false)')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) + self.requested_outputs = [] + #}}} + + def __repr__(self): # {{{ + string = " surface forcings parameters (SMB = accumulation - runoff - evaporation) :" + string = "%s\n%s" % (string, fielddisplay(self, 'accumulation', 'accumulated snow [m / yr ice eq]')) + string = "%s\n%s" % (string, fielddisplay(self, 'runoff', 'amount of ice melt lost from the ice column [m / yr ice eq]')) + string = "%s\n%s" % (string, fielddisplay(self, 'evaporation', 'mount of ice lost to evaporative processes [m / yr ice eq]')) + string = "%s\n%s" % (string, fielddisplay(self, 'isclimatology', 'repeat all forcings when past last forcing time (default false)')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) return string - #}}} - def extrude(self,md): # {{{ + #}}} - self.mass_balance=project3d(md,'vector',self.accumulation,'type','node'); - self.mass_balance=project3d(md,'vector',self.runoff,'type','node'); - self.mass_balance=project3d(md,'vector',self.evaporation,'type','node'); + def extrude(self, md): # {{{ + self.mass_balance = project3d(md, 'vector', self.accumulation, 'type', 'node') + self.mass_balance = project3d(md, 'vector', self.runoff, 'type', 'node') + self.mass_balance = project3d(md, 'vector', self.evaporation, 'type', 'node') return self #}}} - def defaultoutputs(self,md): # {{{ + + def defaultoutputs(self, md): # {{{ return [] #}}} - def initialize(self,md): # {{{ + def initialize(self, md): # {{{ if np.all(np.isnan(self.accumulation)): - self.accumulation=np.zeros((md.mesh.numberofvertices)) + self.accumulation = np.zeros((md.mesh.numberofvertices)) print(" no SMB.accumulation specified: values set as zero") if np.all(np.isnan(self.runoff)): - self.runoff=np.zeros((md.mesh.numberofvertices)) + self.runoff = np.zeros((md.mesh.numberofvertices)) print(" no SMB.runoff specified: values set as zero") if np.all(np.isnan(self.evaporation)): - self.evaporation=np.zeros((md.mesh.numberofvertices)) + self.evaporation = np.zeros((md.mesh.numberofvertices)) print(" no SMB.evaporation specified: values set as zero") return self #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + + def checkconsistency(self, md, solution, analyses): # {{{ + if 'MasstransportAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'smb.accumulation', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + + if 'BalancethicknessAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'smb.accumulation', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.accumulation','timeseries',1,'NaN',1,'Inf',1) + md = checkfield(md, 'fieldname', 'smb.runoff', 'timeseries', 1, 'NaN', 1, 'Inf', 1) if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.accumulation','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) + md = checkfield(md, 'fieldname', 'smb.runoff', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.runoff','timeseries',1,'NaN',1,'Inf',1) + md = checkfield(md, 'fieldname', 'smb.evaporation', 'timeseries', 1, 'NaN', 1, 'Inf', 1) if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.runoff','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) + md = checkfield(md, 'fieldname', 'smb.evaporation', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) - if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.evaporation','timeseries',1,'NaN',1,'Inf',1) - - if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.evaporation','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - - md = checkfield(md,'fieldname','masstransport.requested_outputs','stringrow',1) - md = checkfield(md,'fieldname','smb.isclimatology','values',[0,1]) + md = checkfield(md, 'fieldname', 'masstransport.requested_outputs', 'stringrow', 1) + md = checkfield(md, 'fieldname', 'smb.isclimatology', 'values', [0, 1]) return md # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts - WriteData(fid,prefix,'name','md.smb.model','data',2,'format','Integer'); - WriteData(fid,prefix,'object',self,'class','smb','fieldname','accumulation','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','runoff','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','evaporation','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - - #process requested outputs + WriteData(fid, prefix, 'name', 'md.smb.model', 'data', 2, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'accumulation', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'runoff', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'evaporation', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + + #process requested outputs outputs = self.requested_outputs indices = [i for i, x in enumerate(outputs) if x == 'default'] if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.smb.requested_outputs','format','StringArray') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','isclimatology','format','Boolean') - if (self.isclimatology>0): - md = checkfield(md,'fieldname', 'smb.accumulation', 'size',[md.mesh.numberofvertices+1],'message','accumulation must have md.mesh.numberofvertices+1 rows in order to force a climatology') - md = checkfield(md,'fieldname', 'smb.runoff', 'size',[md.mesh.numberofvertices+1],'message','runoff must have md.mesh.numberofvertices+1 rows in order to force a climatology') - md = checkfield(md,'fieldname', 'smb.evaporation', 'size',[md.mesh.numberofvertices+1],'message','evaporation must have md.mesh.numberofvertices+1 rows in order to force a climatology') + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.smb.requested_outputs', 'format', 'StringArray') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isclimatology', 'format', 'Boolean') + if (self.isclimatology > 0): + md = checkfield(md, 'fieldname', 'smb.accumulation', 'size', [md.mesh.numberofvertices + 1], 'message', 'accumulation must have md.mesh.numberofvertices + 1 rows in order to force a climatology') + md = checkfield(md, 'fieldname', 'smb.runoff', 'size', [md.mesh.numberofvertices + 1], 'message', 'runoff must have md.mesh.numberofvertices + 1 rows in order to force a climatology') + md = checkfield(md, 'fieldname', 'smb.evaporation', 'size', [md.mesh.numberofvertices + 1], 'message', 'evaporation must have md.mesh.numberofvertices + 1 rows in order to force a climatology') # }}} Index: /issm/trunk-jpl/src/m/classes/SMBd18opdd.py =================================================================== --- /issm/trunk-jpl/src/m/classes/SMBd18opdd.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/SMBd18opdd.py (revision 24213) @@ -5,199 +5,209 @@ from project3d import project3d + class SMBd18opdd(object): - """ - SMBd18opdd Class definition - - Usage: - SMBd18opdd=SMBd18opdd(); - """ - - def __init__(self): # {{{ - self.desfac = 0. - self.s0p = float('NaN') - self.s0t = float('NaN') - self.rlaps = 0. - self.rlapslgm = 0. - self.dpermil = 0. - self.f = 0. - self.Tdiff = float('NaN') - self.sealev = float('NaN') - self.ismungsm = 0 - self.isd18opd = 0 - self.issetpddfac = 0 - self.istemperaturescaled = 0 - self.isprecipscaled = 0 - self.delta18o = float('NaN') - self.delta18o_surface = float('NaN') - self.temperatures_presentday = float('NaN') - self.precipitations_presentday = float('NaN') - self.temperatures_reconstructed = float('NaN') - self.precipitations_reconstructed = float('NaN') - self.pddfac_snow = float('NaN') - self.pddfac_ice = float('NaN') - - #set defaults - self.setdefaultparameters() - self.requested_outputs = [] - #}}} - def __repr__(self): # {{{ - string=" surface forcings parameters:" - - string="%s\n%s"%(string,fielddisplay(self,'isd18opd','is delta18o parametrisation from present day temperature and precipitation activated (0 or 1, default is 0)')) - string="%s\n%s"%(string,fielddisplay(self,'issetpddfac','is user passing in defined pdd factors at each vertex (0 or 1, default is 0)')) - string="%s\n%s"%(string,fielddisplay(self,'desfac','desertification elevation factor (between 0 and 1, default is 0.5) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'s0p','should be set to elevation from precip source (between 0 and a few 1000s m, default is 0) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'s0t','should be set to elevation from temperature source (between 0 and a few 1000s m, default is 0) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'rlaps','present day lapse rate [degree/km]')) - if self.isd18opd: - string="%s\n%s"%(string,fielddisplay(self,'temperatures_presentday','monthly present day surface temperatures [K], required if delta18o/mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'precipitations_presentday','monthly surface precipitation [m/yr water eq], required if delta18o or mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'istemperaturescaled','if delta18o parametrisation from present day temperature and precipitation is activated, is temperature scaled to delta18o value? (0 or 1, default is 1)')) - string="%s\n%s"%(string,fielddisplay(self,'isprecipscaled','if delta18o parametrisation from present day temperature and precipitation is activated, is precipitation scaled to delta18o value? (0 or 1, default is 1)')) - - if self.istemperaturescaled==0: - string="%s\n%s"%(string,fielddisplay(self,'temperatures_reconstructed','monthly historical surface temperatures [K], required if delta18o/mungsm/d18opd is activated and istemperaturescaled is not activated')) - - if self.isprecipscaled==0: - string="%s\n%s"%(string,fielddisplay(self,'precipitations_reconstructed','monthly historical precipitation [m/yr water eq], required if delta18o/mungsm/d18opd is activated and isprecipscaled is not activated')) - - string="%s\n%s"%(string,fielddisplay(self,'delta18o','delta18o [per mil], required if pdd is activated and delta18o activated')) - string="%s\n%s"%(string,fielddisplay(self,'dpermil','degree per mil, required if d18opd is activated')) - string="%s\n%s"%(string,fielddisplay(self,'f','precip/temperature scaling factor, required if d18opd is activated')) - - if self.issetpddfac==1: - string="%s\n%s"%(string,fielddisplay(self,'pddfac_snow','Pdd factor for snow, at each vertex [mm ice equiv/day/degree C]')) - string="%s\n%s"%(string,fielddisplay(self,'pddfac_ice','Pdd factor for ice, at each vertex [mm ice equiv/day/degree C]')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) - - return string - #}}} - def extrude(self,md): # {{{ - - if self.isd18opd: self.temperatures_presentday=project3d(md,'vector',self.temperatures_presentday,'type','node') - if self.isd18opd: self.precipitations_presentday=project3d(md,'vector',self.precipitations_presentday,'type','node') - if self.istemperaturescaled==0: self.temperatures_reconstructed=project3d(md,'vector',self.temperatures_reconstructed,'type','node') - if self.isprecipscaled==0: self.temperatures_reconstructed=project3d(md,'vector',self.precipitations_reconstructed,'type','node') - if self.isd18opd: self.precipitations_presentday=project3d(md,'vector',self.precipitations_presentday,'type','node') - if self.issetpddfac: self.pddfac_snow=project3d(md,'vector',self.pddfac_snow,'type','node') - if self.issetpddfac: self.pddfac_ice=project3d(md,'vector',self.pddfac_ice,'type','node') - self.s0p=project3d(md,'vector',self.s0p,'type','node') - self.s0t=project3d(md,'vector',self.s0t,'type','node') - - return self - #}}} - def defaultoutputs(self,md): # {{{ - return [] - #}}} - def initialize(self,md): # {{{ - - if np.all(np.isnan(self.s0p)): - self.s0p=np.zeros((md.mesh.numberofvertices)) - print(" no SMBd18opdd.s0p specified: values set as zero") - - if np.all(np.isnan(self.s0t)): - self.s0t=np.zeros((md.mesh.numberofvertices)) - print(" no SMBd18opdd.s0t specified: values set as zero") - - return self - # }}} - def setdefaultparameters(self): # {{{ - - #pdd method not used in default mode - self.ismungsm = 0 - self.isd18opd = 1 - self.istemperaturescaled = 1 - self.isprecipscaled = 1 - self.desfac = 0.5 - self.rlaps = 6.5 - self.rlapslgm = 6.5 - self.dpermil = 2.4 - self.f = 0.169 - self.issetpddfac = 0 - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - - if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.desfac','<=',1,'numel',[1]) - md = checkfield(md,'fieldname','smb.s0p','>=',0,'NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','smb.s0t','>=',0,'NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','smb.rlaps','>=',0,'numel',[1]) - md = checkfield(md,'fieldname','smb.rlapslgm','>=',0,'numel',[1]) - - if self.isd18opd: - lent=float(np.size(self.temperatures_presentday,1)) - lenp=float(np.size(self.precipitations_presentday,1)) - multt=np.ceil(lent/12.)*12. - multp=np.ceil(lenp/12.)*12. - md = checkfield(md,'fieldname','smb.temperatures_presentday','size',[md.mesh.numberofvertices+1,12],'NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','smb.precipitations_presentday','size',[md.mesh.numberofvertices+1,12],'NaN',1,'Inf',1,'timeseries',1) - - if self.istemperaturescaled==0: - lent=float(np.size(self.temperatures_reconstructed,1)) - multt=np.ceil(lent/12.)*12. - md = checkfield(md,'fieldname','smb.temperatures_reconstructed','size',[md.mesh.numberofvertices+1,multt],'NaN',1,'Inf',1,'timeseries',1) - - if self.isprecipscaled==0: - lenp=float(np.size(self.precipitations_reconstructed,1)) - multp=np.ceil(lent/12.)*12. - md = checkfield(md,'fieldname','smb.precipitations_reconstructed','size',[md.mesh.numberofvertices+1,multt],'NaN',1,'Inf',1,'timeseries',1) - - md = checkfield(md,'fieldname','smb.delta18o','NaN',1,'Inf',1,'size',[2,np.nan],'singletimeseries',1) - md = checkfield(md,'fieldname','smb.dpermil','>=',0,'numel',[1]) - md = checkfield(md,'fieldname','smb.f','>=',0,'numel',[1]) - - if self.issetpddfac: - md = checkfield(md,'fieldname','smb.pddfac_snow','>=',0,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.pddfac_ice','>=',0,'NaN',1,'Inf',1) - - md = checkfield(md,'fieldname','masstransport.requested_outputs','stringrow',1) - - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - - yts=md.constants.yts - - WriteData(fid,prefix,'name','md.smb.model','data',5,'format','Integer') - - WriteData(fid,prefix,'object',self,'class','smb','fieldname','ismungsm','format','Boolean') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','isd18opd','format','Boolean') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','issetpddfac','format','Boolean'); - WriteData(fid,prefix,'object',self,'class','smb','fieldname','desfac','format','Double') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','s0p','format','DoubleMat','mattype',1); - WriteData(fid,prefix,'object',self,'class','smb','fieldname','s0t','format','DoubleMat','mattype',1); - WriteData(fid,prefix,'object',self,'class','smb','fieldname','rlaps','format','Double') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','rlapslgm','format','Double') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','Tdiff','format','DoubleMat','mattype',1,'timeserieslength',2,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','sealev','format','DoubleMat','mattype',1,'timeserieslength',2,'yts',md.constants.yts) - - if self.isd18opd: - WriteData(fid,prefix,'object',self,'class','smb','fieldname','temperatures_presentday','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','precipitations_presentday','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','istemperaturescaled','format','Boolean') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','isprecipscaled','format','Boolean') - - if self.istemperaturescaled==0: - WriteData(fid,prefix,'object',self,'class','smb','fieldname','temperatures_reconstructed','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - - if self.isprecipscaled==0: - WriteData(fid,prefix,'object',self,'class','smb','fieldname','precipitations_reconstructed','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - - WriteData(fid,prefix,'object',self,'class','smb','fieldname','delta18o','format','DoubleMat','mattype',1,'timeserieslength',2,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','dpermil','format','Double') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','f','format','Double') - - if self.issetpddfac: - WriteData(fid,prefix,'object',self,'class','smb','fieldname','pddfac_snow','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','pddfac_ice','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.smb.requested_outputs','format','StringArray') - - # }}} + """ + SMBd18opdd Class definition + + Usage: + SMBd18opdd = SMBd18opdd() + """ + + def __init__(self): # {{{ + self.desfac = 0. + self.s0p = float('NaN') + self.s0t = float('NaN') + self.rlaps = 0. + self.rlapslgm = 0. + self.dpermil = 0. + self.f = 0. + self.Tdiff = float('NaN') + self.sealev = float('NaN') + self.ismungsm = 0 + self.isd18opd = 0 + self.issetpddfac = 0 + self.istemperaturescaled = 0 + self.isprecipscaled = 0 + self.delta18o = float('NaN') + self.delta18o_surface = float('NaN') + self.temperatures_presentday = float('NaN') + self.precipitations_presentday = float('NaN') + self.temperatures_reconstructed = float('NaN') + self.precipitations_reconstructed = float('NaN') + self.pddfac_snow = float('NaN') + self.pddfac_ice = float('NaN') + + #set defaults + self.setdefaultparameters() + self.requested_outputs = [] + #}}} + + def __repr__(self): # {{{ + string = " surface forcings parameters:" + + string = "%s\n%s" % (string, fielddisplay(self, 'isd18opd', 'is delta18o parametrisation from present day temperature and precipitation activated (0 or 1, default is 0)')) + string = "%s\n%s" % (string, fielddisplay(self, 'issetpddfac', 'is user passing in defined pdd factors at each vertex (0 or 1, default is 0)')) + string = "%s\n%s" % (string, fielddisplay(self, 'desfac', 'desertification elevation factor (between 0 and 1, default is 0.5) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 's0p', 'should be set to elevation from precip source (between 0 and a few 1000s m, default is 0) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 's0t', 'should be set to elevation from temperature source (between 0 and a few 1000s m, default is 0) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'rlaps', 'present day lapse rate [degree / km]')) + if self.isd18opd: + string = "%s\n%s" % (string, fielddisplay(self, 'temperatures_presentday', 'monthly present day surface temperatures [K], required if delta18o / mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'precipitations_presentday', 'monthly surface precipitation [m / yr water eq], required if delta18o or mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'istemperaturescaled', 'if delta18o parametrisation from present day temperature and precipitation is activated, is temperature scaled to delta18o value? (0 or 1, default is 1)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isprecipscaled', 'if delta18o parametrisation from present day temperature and precipitation is activated, is precipitation scaled to delta18o value? (0 or 1, default is 1)')) + + if self.istemperaturescaled == 0: + string = "%s\n%s" % (string, fielddisplay(self, 'temperatures_reconstructed', 'monthly historical surface temperatures [K], required if delta18o / mungsm / d18opd is activated and istemperaturescaled is not activated')) + + if self.isprecipscaled == 0: + string = "%s\n%s" % (string, fielddisplay(self, 'precipitations_reconstructed', 'monthly historical precipitation [m / yr water eq], required if delta18o / mungsm / d18opd is activated and isprecipscaled is not activated')) + + string = "%s\n%s" % (string, fielddisplay(self, 'delta18o', 'delta18o [per mil], required if pdd is activated and delta18o activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'dpermil', 'degree per mil, required if d18opd is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'f', 'precip/temperature scaling factor, required if d18opd is activated')) + + if self.issetpddfac == 1: + string = "%s\n%s" % (string, fielddisplay(self, 'pddfac_snow', 'Pdd factor for snow, at each vertex [mm ice equiv / day / degree C]')) + string = "%s\n%s" % (string, fielddisplay(self, 'pddfac_ice', 'Pdd factor for ice, at each vertex [mm ice equiv / day / degree C]')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) + + return string + #}}} + + def extrude(self, md): # {{{ + if self.isd18opd: + self.temperatures_presentday = project3d(md, 'vector', self.temperatures_presentday, 'type', 'node') + if self.isd18opd: + self.precipitations_presentday = project3d(md, 'vector', self.precipitations_presentday, 'type', 'node') + if self.istemperaturescaled == 0: + self.temperatures_reconstructed = project3d(md, 'vector', self.temperatures_reconstructed, 'type', 'node') + if self.isprecipscaled == 0: + self.temperatures_reconstructed = project3d(md, 'vector', self.precipitations_reconstructed, 'type', 'node') + if self.isd18opd: + self.precipitations_presentday = project3d(md, 'vector', self.precipitations_presentday, 'type', 'node') + if self.issetpddfac: + self.pddfac_snow = project3d(md, 'vector', self.pddfac_snow, 'type', 'node') + if self.issetpddfac: + self.pddfac_ice = project3d(md, 'vector', self.pddfac_ice, 'type', 'node') + self.s0p = project3d(md, 'vector', self.s0p, 'type', 'node') + self.s0t = project3d(md, 'vector', self.s0t, 'type', 'node') + + return self + #}}} + + def defaultoutputs(self, md): # {{{ + return [] + #}}} + + def initialize(self, md): # {{{ + if np.all(np.isnan(self.s0p)): + self.s0p = np.zeros((md.mesh.numberofvertices)) + print(" no SMBd18opdd.s0p specified: values set as zero") + + if np.all(np.isnan(self.s0t)): + self.s0t = np.zeros((md.mesh.numberofvertices)) + print(" no SMBd18opdd.s0t specified: values set as zero") + + return self + # }}} + + def setdefaultparameters(self): # {{{ + #pdd method not used in default mode + self.ismungsm = 0 + self.isd18opd = 1 + self.istemperaturescaled = 1 + self.isprecipscaled = 1 + self.desfac = 0.5 + self.rlaps = 6.5 + self.rlapslgm = 6.5 + self.dpermil = 2.4 + self.f = 0.169 + self.issetpddfac = 0 + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + if 'MasstransportAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'smb.desfac', '<=', 1, 'numel', [1]) + md = checkfield(md, 'fieldname', 'smb.s0p', '>=', 0, 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'smb.s0t', '>=', 0, 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'smb.rlaps', '>=', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'smb.rlapslgm', '>=', 0, 'numel', [1]) + + if self.isd18opd: + lent = float(np.size(self.temperatures_presentday, 1)) + lenp = float(np.size(self.precipitations_presentday, 1)) + multt = np.ceil(lent / 12.) * 12. + multp = np.ceil(lenp / 12.) * 12. + md = checkfield(md, 'fieldname', 'smb.temperatures_presentday', 'size', [md.mesh.numberofvertices + 1, 12], 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'smb.precipitations_presentday', 'size', [md.mesh.numberofvertices + 1, 12], 'NaN', 1, 'Inf', 1, 'timeseries', 1) + + if self.istemperaturescaled == 0: + lent = float(np.size(self.temperatures_reconstructed, 1)) + multt = np.ceil(lent / 12.) * 12. + md = checkfield(md, 'fieldname', 'smb.temperatures_reconstructed', 'size', [md.mesh.numberofvertices + 1, multt], 'NaN', 1, 'Inf', 1, 'timeseries', 1) + + if self.isprecipscaled == 0: + lenp = float(np.size(self.precipitations_reconstructed, 1)) + multp = np.ceil(lent / 12.) * 12. + md = checkfield(md, 'fieldname', 'smb.precipitations_reconstructed', 'size', [md.mesh.numberofvertices + 1, multp], 'NaN', 1, 'Inf', 1, 'timeseries', 1) + + md = checkfield(md, 'fieldname', 'smb.delta18o', 'NaN', 1, 'Inf', 1, 'size', [2, np.nan], 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'smb.dpermil', '>=', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'smb.f', '>=', 0, 'numel', [1]) + + if self.issetpddfac: + md = checkfield(md, 'fieldname', 'smb.pddfac_snow', '>=', 0, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.pddfac_ice', '>=', 0, 'NaN', 1, 'Inf', 1) + + md = checkfield(md, 'fieldname', 'masstransport.requested_outputs', 'stringrow', 1) + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + + WriteData(fid, prefix, 'name', 'md.smb.model', 'data', 5, 'format', 'Integer') + + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'ismungsm', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isd18opd', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'issetpddfac', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'desfac', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 's0p', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 's0t', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'rlaps', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'rlapslgm', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Tdiff', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', 2, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'sealev', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', 2, 'yts', md.constants.yts) + + if self.isd18opd: + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'temperatures_presentday', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'precipitations_presentday', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'istemperaturescaled', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isprecipscaled', 'format', 'Boolean') + + if self.istemperaturescaled == 0: + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'temperatures_reconstructed', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + + if self.isprecipscaled == 0: + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'precipitations_reconstructed', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'delta18o', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', 2, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'dpermil', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'f', 'format', 'Double') + + if self.issetpddfac: + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'pddfac_snow', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'pddfac_ice', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.smb.requested_outputs', 'format', 'StringArray') + + # }}} Index: /issm/trunk-jpl/src/m/classes/SMBforcing.py =================================================================== --- /issm/trunk-jpl/src/m/classes/SMBforcing.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/SMBforcing.py (revision 24213) @@ -5,4 +5,5 @@ from project3d import project3d + class SMBforcing(object): """ @@ -10,66 +11,68 @@ Usage: - SMB=SMBforcing(); + SMB = SMBforcing() """ - def __init__(self): # {{{ + def __init__(self): # {{{ self.mass_balance = float('NaN') - self.requested_outputs = [] + self.requested_outputs = [] self.isclimatology = 0 - #}}} - def __repr__(self): # {{{ - string=" surface forcings parameters:" - string="%s\n%s"%(string,fielddisplay(self,'mass_balance','surface mass balance [m/yr ice eq]')) - string="%s\n%s"%(string,fielddisplay(self,'isclimatology','repeat all forcings when past last forcing time (default false)')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) + #}}} + + def __repr__(self): # {{{ + string = " surface forcings parameters:" + string = "%s\n%s" % (string, fielddisplay(self, 'mass_balance', 'surface mass balance [m / yr ice eq]')) + string = "%s\n%s" % (string, fielddisplay(self, 'isclimatology', 'repeat all forcings when past last forcing time (default false)')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) return string - #}}} - def extrude(self,md): # {{{ + #}}} - self.mass_balance=project3d(md,'vector',self.mass_balance,'type','node'); + def extrude(self, md): # {{{ + + self.mass_balance = project3d(md, 'vector', self.mass_balance, 'type', 'node') return self #}}} - def defaultoutputs(self,md): # {{{ + + def defaultoutputs(self, md): # {{{ return [] #}}} - def initialize(self,md): # {{{ + def initialize(self, md): # {{{ if np.all(np.isnan(self.mass_balance)): - self.mass_balance=np.zeros((md.mesh.numberofvertices)) + self.mass_balance = np.zeros((md.mesh.numberofvertices)) print(" no SMBforcing.mass_balance specified: values set as zero") return self #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.mass_balance','timeseries',1,'NaN',1,'Inf',1) + md = checkfield(md, 'fieldname', 'smb.mass_balance', 'timeseries', 1, 'NaN', 1, 'Inf', 1) if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.mass_balance','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) + md = checkfield(md, 'fieldname', 'smb.mass_balance', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) - md = checkfield(md,'fieldname','masstransport.requested_outputs','stringrow',1) - md = checkfield(md,'fieldname','smb.isclimatology','values',[0,1]) - if (self.isclimatology>0): - md = checkfield(md,'fieldname', 'smb.mass_balance', 'size',[md.mesh.numberofvertices+1],'message','mass_balance must have md.mesh.numberofvertices+1 rows in order to force a climatology') + md = checkfield(md, 'fieldname', 'masstransport.requested_outputs', 'stringrow', 1) + md = checkfield(md, 'fieldname', 'smb.isclimatology', 'values', [0, 1]) + if (self.isclimatology > 0): + md = checkfield(md, 'fieldname', 'smb.mass_balance', 'size', [md.mesh.numberofvertices + 1], 'message', 'mass_balance must have md.mesh.numberofvertices + 1 rows in order to force a climatology') return md # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts - WriteData(fid,prefix,'name','md.smb.model','data',1,'format','Integer'); - WriteData(fid,prefix,'object',self,'class','smb','fieldname','mass_balance','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - #WriteData(fid,prefix,'object',self,'class','smb','fieldname','mass_balance','format','CompressedMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts); - + WriteData(fid, prefix, 'name', 'md.smb.model', 'data', 1, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'mass_balance', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + #process requested outputs outputs = self.requested_outputs indices = [i for i, x in enumerate(outputs) if x == 'default'] if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.smb.requested_outputs','format','StringArray') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','isclimatology','format','Boolean') + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.smb.requested_outputs', 'format', 'StringArray') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isclimatology', 'format', 'Boolean') # }}} Index: /issm/trunk-jpl/src/m/classes/SMBgemb.py =================================================================== --- /issm/trunk-jpl/src/m/classes/SMBgemb.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/SMBgemb.py (revision 24213) @@ -5,438 +5,437 @@ from project3d import project3d + class SMBgemb(object): - """ - SMBgemb Class definition - - Usage: - SMB = SMBgemb() - """ - - def __init__(self): # {{{ - #each one of these properties is a transient forcing to the GEMB model, loaded from meteorological data derived - #from an automatic weather stations (AWS). Each property is therefore a matrix, of size (numberofvertices x number - #of time steps. ) - - #solution choices - #check these: - #isgraingrowth - #isalbedo - #isshortwave - #isthermal - #isaccumulation - #ismelt - #isdensification - #isturbulentflux - - #inputs: - Ta = float('NaN') #2 m air temperature, in Kelvin - V = float('NaN') #wind speed (m/s-1) - dswrf = float('NaN') #downward shortwave radiation flux [W/m^2] - dlwrf = float('NaN') #downward longwave radiation flux [W/m^2] - P = float('NaN') #precipitation [mm w.e. / m^2] - eAir = float('NaN') #screen level vapor pressure [Pa] - pAir = float('NaN') #surface pressure [Pa] - Tmean = float('NaN') #mean annual temperature [K] - Vmean = float('NaN') #mean annual wind velocity [m s-1] - C = float('NaN') #mean annual snow accumulation [kg m-2 yr-1] - Tz = float('NaN') #height above ground at which temperature (T) was sampled [m] - Vz = float('NaN') #height above ground at which wind (V) was sampled [m] - - #optional inputs: - aValue = float('NaN') #Albedo forcing at every element. Used only if aIdx == 0. - teValue = float('NaN') #Outward longwave radiation thermal emissivity forcing at every element (default in code is 1) - - # Initialization of snow properties - Dzini = float('NaN') #cell depth (m) - Dini = float('NaN') #snow density (kg m-3) - Reini = float('NaN') #effective grain size (mm) - Gdnini = float('NaN') #grain dricity (0-1) - Gspini = float('NaN') #grain sphericity (0-1) - ECini = float('NaN') #evaporation/condensation (kg m-2) - Wini = float('NaN') #Water content (kg m-2) - Aini = float('NaN') #albedo (0-1) - Tini = float('NaN') #snow temperature (K) - Sizeini = float('NaN') #Number of layers - - #settings: - aIdx = float('NaN') #method for calculating albedo and subsurface absorption (default is 1) - # 0: direct input from aValue parameter - # 1: effective grain radius [Gardner & Sharp, 2009] - # 2: effective grain radius [Brun et al., 2009] - # 3: density and cloud amount [Greuell & Konzelmann, 1994] - # 4: exponential time decay & wetness [Bougamont & Bamber, 2005] - # 5: ingest MODIS mode, direct input from aValue parameter applied to surface ice only - swIdx = float('NaN') # apply all SW to top grid cell (0) or allow SW to penetrate surface (1) (default 1) - denIdx = float('NaN') #densification model to use (default is 2): - # 1 = emperical model of Herron and Langway (1980) - # 2 = semi-emperical model of Anthern et al. (2010) - # 3 = DO NOT USE: physical model from Appix B of Anthern et al. (2010) - # 4 = DO NOT USE: emperical model of Li and Zwally (2004) - # 5 = DO NOT USE: modified emperical model (4) by Helsen et al. (2008) - # 6 = Antarctica semi-emperical model of Ligtenberg et al. (2011) - # 7 = Greenland semi-emperical model of Kuipers Munneke et al. (2015) - dsnowIdx = float('NaN') #model for fresh snow accumulation density (default is 1): - # 0 = Original GEMB value, 150 kg/m^3 - # 1 = Antarctica value of fresh snow density, 350 kg/m^3 - # 2 = Greenland value of fresh snow density, 315 kg/m^3, Fausto et al. (2008) - # 3 = Antarctica model of Kaspers et al. (2004) - # 4 = Greenland model of Kuipers Munneke et al. (2015) - - zTop = float('NaN') # depth over which grid length is constant at the top of the snopack (default 10) [m] - dzTop = float('NaN') # initial top vertical grid spacing (default .05) [m] - dzMin = float('NaN') # initial min vertical allowable grid spacing (default dzTop/2) [m] - zY = float('NaN') # strech grid cells bellow top_z by a [top_dz * y ^ (cells bellow top_z)] - zMax = float('NaN') #initial max model depth (default is min(thickness,250)) [m] - zMin = float('NaN') #initial min model depth (default is min(thickness,130)) [m] - outputFreq = float('NaN') #output frequency in days (default is monthly, 30) - - #specific albedo parameters: - #Method 1 and 2: - aSnow = float('NaN') # new snow albedo (0.64 - 0.89) - aIce = float('NaN') # range 0.27-0.58 for old snow - #Method 3: Radiation Correction Factors -> only used for met station data and Greuell & Konzelmann, 1994 albedo - cldFrac = float('NaN') # average cloud amount - #Method 4: additonal tuning parameters albedo as a funtion of age and water content (Bougamont et al., 2005) - t0wet = float('NaN') # time scale for wet snow (15-21.9) - t0dry = float('NaN') # warm snow timescale (30) - K = float('NaN') # time scale temperature coef. (7) - adThresh = float('NaN') # Apply aIdx method to all areas with densities below this value, - # or else apply direct input value from aValue, allowing albedo to be altered. - # Default value is rho water (1023 kg m-3). - - #densities: - InitDensityScaling = float('NaN') #initial scaling factor multiplying the density of ice, which describes the density of the snowpack. - - #thermo: - ThermoDeltaTScaling = float('NaN') #scaling factor to multiply the thermal diffusion timestep (delta t) - - requested_outputs = [] - - #Several fields are missing from the standard GEMB model, which are capture intrinsically by ISSM. - #dateN: that's the last row of the above fields. - #dt: included in dateN. Not an input. - #elev: this is taken from the ISSM surface itself. - - #}}} - def __repr__(self): # {{{ - #string = " surface forcings parameters:" - #string = "#s\n#s"%(string,fielddisplay(self,'mass_balance','surface mass balance [m/yr ice eq]')) - #string = "#s\n#s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) - string = ' surface forcings for SMB GEMB model :' - string = "%s\n%s"%(string,fielddisplay(self,'issmbgradients','is smb gradients method activated (0 or 1, default is 0)')) - string = "%s\n%s"%(string,fielddisplay(self,'isgraingrowth','run grain growth module (default true)')) - string = "%s\n%s"%(string,fielddisplay(self,'isalbedo','run albedo module (default true)')) - string = "%s\n%s"%(string,fielddisplay(self,'isshortwave','run short wave module (default true)')) - string = "%s\n%s"%(string,fielddisplay(self,'isthermal','run thermal module (default true)')) - string = "%s\n%s"%(string,fielddisplay(self,'isaccumulation','run accumulation module (default true)')) - string = "%s\n%s"%(string,fielddisplay(self,'ismelt','run melting module (default true)')) - string = "%s\n%s"%(string,fielddisplay(self,'isdensification','run densification module (default true)')) - string = "%s\n%s"%(string,fielddisplay(self,'isturbulentflux','run turbulant heat fluxes module (default true)')) - string = "%s\n%s"%(string,fielddisplay(self,'isclimatology','repeat all forcings when past last forcing time (default false)')) - string = "%s\n%s"%(string,fielddisplay(self,'Ta','2 m air temperature, in Kelvin')) - string = "%s\n%s"%(string,fielddisplay(self,'V','wind speed (m s-1)')) - string = "%s\n%s"%(string,fielddisplay(self,'dlwrf','downward shortwave radiation flux [W/m^2]')) - string = "%s\n%s"%(string,fielddisplay(self,'dswrf','downward longwave radiation flux [W/m^2]')) - string = "%s\n%s"%(string,fielddisplay(self,'P','precipitation [mm w.e. / m^2]')) - string = "%s\n%s"%(string,fielddisplay(self,'eAir','screen level vapor pressure [Pa]')) - string = "%s\n%s"%(string,fielddisplay(self,'pAir','surface pressure [Pa]')) - string = "%s\n%s"%(string,fielddisplay(self,'Tmean','mean annual temperature [K]')) - string = "%s\n%s"%(string,fielddisplay(self,'C','mean annual snow accumulation [kg m-2 yr-1]')) - string = "%s\n%s"%(string,fielddisplay(self,'Vmean','mean annual wind velocity [m s-1] (default 10 m/s)')) - string = "%s\n%s"%(string,fielddisplay(self,'Tz','height above ground at which temperature (T) was sampled [m]')) - string = "%s\n%s"%(string,fielddisplay(self,'Vz','height above ground at which wind (V) was sampled [m]')) - string = "%s\n%s"%(string,fielddisplay(self,'zTop','depth over which grid length is constant at the top of the snopack (default 10) [m]')) - string = "%s\n%s"%(string,fielddisplay(self,'dzTop','initial top vertical grid spacing (default .05) [m] ')) - string = "%s\n%s"%(string,fielddisplay(self,'dzMin','initial min vertical allowable grid spacing (default dzMin/2) [m] ')) - string = "%s\n%s"%(string,fielddisplay(self,'zMax','initial max model depth (default is min(thickness,500)) [m]')) - string = "%s\n%s"%(string,fielddisplay(self,'zMin','initial min model depth (default is min(thickness,30)) [m]')) - string = "%s\n%s"%(string,fielddisplay(self,'zY','strech grid cells bellow top_z by a [top_dz * y ^ (cells bellow top_z)]')) - string = "%s\n%s"%(string,fielddisplay(self,'InitDensityScaling',['initial scaling factor multiplying the density of ice','which describes the density of the snowpack.'])) - string = "%s\n%s"%(string,fielddisplay(self,'ThermoDeltaTScaling','scaling factor to multiply the thermal diffusion timestep (delta t)')) - string = "%s\n%s"%(string,fielddisplay(self,'outputFreq','output frequency in days (default is monthly, 30)')) - string = "%s\n%s"%(string,fielddisplay(self,'adThresh','Apply aIdx method to all areas with densities below this value,','or else apply direct input value from aValue, allowing albedo to be altered.')) - string = "%s\n%s"%(string,fielddisplay(self,'aIdx',['method for calculating albedo and subsurface absorption (default is 1)', - '0: direct input from aValue parameter', - '1: effective grain radius [Gardner & Sharp, 2009]', - '2: effective grain radius [Brun et al., 2009]', - '3: density and cloud amount [Greuell & Konzelmann, 1994]', - '4: exponential time decay & wetness [Bougamont & Bamber, 2005]'])) - string = "%s\n%s"%(string,fielddisplay(self,'teValue','Outward longwave radiation thermal emissivity forcing at every element (default in code is 1)')) - #snow properties init - string = "%s\n%s"%(string,fielddisplay(self,'Dzini','Initial cell depth when restart [m]')) - string = "%s\n%s"%(string,fielddisplay(self,'Dini','Initial snow density when restart [kg m-3]')) - string = "%s\n%s"%(string,fielddisplay(self,'Reini','Initial grain size when restart [mm]')) - string = "%s\n%s"%(string,fielddisplay(self,'Gdnini','Initial grain dricity when restart [-]')) - string = "%s\n%s"%(string,fielddisplay(self,'Gspini','Initial grain sphericity when restart [-]')) - string = "%s\n%s"%(string,fielddisplay(self,'ECini','Initial evaporation/condensation when restart [kg m-2]')) - string = "%s\n%s"%(string,fielddisplay(self,'Wini','Initial snow water content when restart [kg m-2]')) - string = "%s\n%s"%(string,fielddisplay(self,'Aini','Initial albedo when restart [-]')) - string = "%s\n%s"%(string,fielddisplay(self,'Tini','Initial snow temperature when restart [K]')) - string = "%s\n%s"%(string,fielddisplay(self,'Sizeini','Initial number of layers when restart [K]')) - - #additional albedo parameters: - if type(self.aIdx) == list or type(self.aIdx) == type(np.array([1,2])) and (self.aIdx == [1,2] or (1 in self.aIdx and 2 in self.aIdx)): - string = "%s\n%s"%(string,fielddisplay(self,'aSnow','new snow albedo (0.64 - 0.89)')) - string = "%s\n%s"%(string,fielddisplay(self,'aIce','albedo of ice (0.27-0.58)')) - elif elf.aIdx == 0: - string = "%s\n%s"%(string,fielddisplay(self,'aValue','Albedo forcing at every element. Used only if aIdx == {0,5}')) - elif elf.aIdx == 5: - string = "%s\n%s"%(string,fielddisplay(self,'aValue','Albedo forcing at every element. Used only if aIdx == {0,5}')) - elif self.aIdx == 3: - string = "%s\n%s"%(string,fielddisplay(self,'cldFrac','average cloud amount')) - elif self.aIdx == 4: - string = "%s\n%s"%(string,fielddisplay(self,'t0wet','time scale for wet snow (15-21.9) [d]')) - string = "%s\n%s"%(string,fielddisplay(self,'t0dry','warm snow timescale (30) [d]')) - string = "%s\n%s"%(string,fielddisplay(self,'K','time scale temperature coef. (7) [d]')) - - string = "%s\n%s"%(string,fielddisplay(self,'swIdx','apply all SW to top grid cell (0) or allow SW to penetrate surface (1) [default 1]')) - string = "%s\n%s"%(string,fielddisplay(self,'denIdx',['densification model to use (default is 2):', - '1 = emperical model of Herron and Langway (1980)', - '2 = semi-emperical model of Anthern et al. (2010)', - '3 = DO NOT USE: physical model from Appix B of Anthern et al. (2010)', - '4 = DO NOT USE: emperical model of Li and Zwally (2004)', - '5 = DO NOT USE: modified emperical model (4) by Helsen et al. (2008)', - '6 = Antarctica semi-emperical model of Ligtenberg et al. (2011)', - '7 = Greenland semi-emperical model of Kuipers Munneke et al. (2015)'])) - string = "%s\n%s"%(string,fielddisplay(self,'dsnowIdx',['model for fresh snow accumulation density (default is 1):', - '0 = Original GEMB value, 150 kg/m^3', - '1 = Antarctica value of fresh snow density, 350 kg/m^3', - '2 = Greenland value of fresh snow density, 315 kg/m^3, Fausto et al. (2008)', - '3 = Antarctica model of Kaspers et al. (2004), Make sure to set Vmean accurately', - '4 = Greenland model of Kuipers Munneke et al. (2015)'])); - string = "%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) - return string - #}}} - - def extrude(self,md): # {{{ - - self.Ta = project3d(md,'vector',self.Ta,'type','node') - self.V = project3d(md,'vector',self.V,'type','node') - self.dswrf = project3d(md,'vector',self.dswrf,'type','node') - self.dswrf = project3d(md,'vector',self.dswrf,'type','node') - self.P = project3d(md,'vector',self.P,'type','node') - self.eAir = project3d(md,'vector',self.eAir,'type','node') - self.pAir = project3d(md,'vector',self.pAir,'type','node') - - if (aIdx == 0) and np.isnan(self.aValue): - self.aValue=project3d(md,'vector',self.aValue,'type','node'); - if np.isnan(self.teValue): - self.teValue=project3d(md,'vector',self.teValue,'type','node'); - - return self - #}}} - def defaultoutputs(self,md): # {{{ - return ['SmbMassBalance'] - #}}} - - def setdefaultparameters(self,mesh,geometry): # {{{ - self.isgraingrowth = 1 - self.isalbedo = 1 - self.isshortwave = 1 - self.isthermal = 1 - self.isaccumulation = 1 - self.ismelt = 1 - self.isdensification = 1 - self.isturbulentflux = 1 - self.isclimatology = 0 - - self.aIdx = 1 - self.swIdx = 1 - self.denIdx = 2 - self.dsnowIdx = 1 - self.zTop = 10*np.ones((mesh.numberofelements,)) - self.dzTop = .05* np.ones((mesh.numberofelements,)) - self.dzMin = self.dzTop/2 - self.InitDensityScaling = 1.0 - self.ThermoDeltaTScaling = 1/11.0 - - self.Vmean = 10*np.ones((mesh.numberofelements,)) - - self.zMax = 250*np.ones((mesh.numberofelements,)) - self.zMin = 130*np.ones((mesh.numberofelements,)) - self.zY = 1.10*np.ones((mesh.numberofelements,)) - self.outputFreq = 30 - - #additional albedo parameters - self.aSnow = 0.85 - self.aIce = 0.48 - self.cldFrac = 0.1 - self.t0wet = 15 - self.t0dry = 30 - self.K = 7 - self.adThresh = 1023 - - self.teValue = np.ones((mesh.numberofelements,)); - self.aValue = self.aSnow*np.ones(mesh.numberofelements,); - - self.Dzini = 0.05*np.ones((mesh.numberofelements,2)) - self.Dini = 910.0*np.ones((mesh.numberofelements,2)) - self.Reini = 2.5*np.ones((mesh.numberofelements,2)) - self.Gdnini = 0.0*np.ones((mesh.numberofelements,2)) - self.Gspini = 0.0*np.ones((mesh.numberofelements,2)) - self.ECini = 0.0*np.ones((mesh.numberofelements,)) - self.Wini = 0.0*np.ones((mesh.numberofelements,2)) - self.Aini = self.aSnow*np.ones((mesh.numberofelements,2)) - self.Tini = 273.15*np.ones((mesh.numberofelements,2)) -# /!\ Default value of Tini must be equal to Tmean but don't know Tmean yet (computed when atmospheric forcings are interpolated on mesh). -# If initialization without restart, this value will be overwritten when snow parameters are retrieved in Element.cpp - self.Sizeini = 2*np.ones((mesh.numberofelements,)) - #}}} - - def checkconsistency(self,md,solution,analyses): # {{{ - - md = checkfield(md,'fieldname','smb.isgraingrowth','values',[0,1]) - md = checkfield(md,'fieldname','smb.isalbedo','values',[0,1]) - md = checkfield(md,'fieldname','smb.isshortwave','values',[0,1]) - md = checkfield(md,'fieldname','smb.isthermal','values',[0,1]) - md = checkfield(md,'fieldname','smb.isaccumulation','values',[0,1]) - md = checkfield(md,'fieldname','smb.ismelt','values',[0,1]) - md = checkfield(md,'fieldname','smb.isdensification','values',[0,1]) - md = checkfield(md,'fieldname','smb.isturbulentflux','values',[0,1]) - md = checkfield(md,'fieldname','smb.isclimatology','values',[0,1]) - - md = checkfield(md,'fieldname','smb.Ta','timeseries',1,'NaN',1,'Inf',1,'>',273-100,'<',273+100) #-100/100 celsius min/max value - md = checkfield(md,'fieldname','smb.V','timeseries',1,'NaN',1,'Inf',1,'> = ',0,'<',45,'size',np.shape(self.Ta)) #max 500 km/h - md = checkfield(md,'fieldname','smb.dswrf','timeseries',1,'NaN',1,'Inf',1,'> = ',0,'< = ',1400,'size',np.shape(self.Ta)) - md = checkfield(md,'fieldname','smb.dlwrf','timeseries',1,'NaN',1,'Inf',1,'> = ',0,'size',np.shape(self.Ta)) - md = checkfield(md,'fieldname','smb.P','timeseries',1,'NaN',1,'Inf',1,'> = ',0,'< = ',100,'size',np.shape(self.Ta)) - md = checkfield(md,'fieldname','smb.eAir','timeseries',1,'NaN',1,'Inf',1,'size',np.shape(self.Ta)) - - if (self.isclimatology>0): - md = checkfield(md,'fieldname', 'smb.Ta', 'size',[md.mesh.numberofelements+1],'message','Ta must have md.mesh.numberofelements+1 rows in order to force a climatology') - md = checkfield(md,'fieldname', 'smb.V', 'size',[md.mesh.numberofelements+1],'message','V must have md.mesh.numberofelements+1 rows in order to force a climatology') - md = checkfield(md,'fieldname', 'smb.dswrf', 'size',[md.mesh.numberofelements+1],'message','dswrf must have md.mesh.numberofelements+1 rows in order to force a climatology') - md = checkfield(md,'fieldname', 'smb.dlwrf', 'size',[md.mesh.numberofelements+1],'message','dlwrf must have md.mesh.numberofelements+1 rows in order to force a climatology') - md = checkfield(md,'fieldname', 'smb.P', 'size',[md.mesh.numberofelements+1],'message','P must have md.mesh.numberofelements+1 rows in order to force a climatology') - md = checkfield(md,'fieldname', 'smb.eAir', 'size',[md.mesh.numberofelements+1],'message','eAir must have md.mesh.numberofelements+1 rows in order to force a climatology') - - md = checkfield(md,'fieldname','smb.Tmean','size',[md.mesh.numberofelements],'NaN',1,'Inf',1,'>',273-100,'<',273+100) #-100/100 celsius min/max value - md = checkfield(md,'fieldname','smb.C','size',[md.mesh.numberofelements],'NaN',1,'Inf',1,'> = ',0) - md = checkfield(md,'fieldname','smb.Vmean','size',[md.mesh.numberofelements],'NaN',1,'Inf',1,'> = ',0) - md = checkfield(md,'fieldname','smb.Tz','size',[md.mesh.numberofelements],'NaN',1,'Inf',1,'> = ',0,'< = ',5000) - md = checkfield(md,'fieldname','smb.Vz','size',[md.mesh.numberofelements],'NaN',1,'Inf',1,'> = ',0,'< = ',5000) - - md = checkfield(md,'fieldname','smb.teValue','timeseries',1,'NaN',1,'Inf',1,'>=',0,'<=',1); - - md = checkfield(md,'fieldname','smb.aIdx','NaN',1,'Inf',1,'values',[0,1,2,3,4]) - md = checkfield(md,'fieldname','smb.swIdx','NaN',1,'Inf',1,'values',[0,1]) - md = checkfield(md,'fieldname','smb.denIdx','NaN',1,'Inf',1,'values',[1,2,3,4,5,6,7]) - md = checkfield(md,'fieldname','smb.dsnowIdx','NaN',1,'Inf',1,'values',[0,1,2,3,4]) - - md = checkfield(md,'fieldname','smb.zTop','NaN',1,'Inf',1,'> = ',0) - md = checkfield(md,'fieldname','smb.dzTop','NaN',1,'Inf',1,'>',0) - md = checkfield(md,'fieldname','smb.dzMin','NaN',1,'Inf',1,'>',0) - md = checkfield(md,'fieldname','smb.zY','NaN',1,'Inf',1,'> = ',1) - md = checkfield(md,'fieldname','smb.outputFreq','NaN',1,'Inf',1,'>',0,'<',10*365) #10 years max - md = checkfield(md,'fieldname','smb.InitDensityScaling','NaN',1,'Inf',1,'> = ',0,'< = ',1) - md = checkfield(md,'fieldname','smb.ThermoDeltaTScaling','NaN',1,'Inf',1,'> = ',0,'< = ',1) - md = checkfield(md,'fieldname','smb.adThresh','NaN',1,'Inf',1,'>=',0) - - if type(self.aIdx) == list or type(self.aIdx) == type(np.array([1,2])) and (self.aIdx == [1,2] or (1 in self.aIdx and 2 in self.aIdx)): - md = checkfield(md,'fieldname','smb.aSnow','NaN',1,'Inf',1,'> = ',.64,'< = ',.89) - md = checkfield(md,'fieldname','smb.aIce','NaN',1,'Inf',1,'> = ',.27,'< = ',.58) - elif self.aIdx == 0: - md = checkfield(md,'fieldname','smb.aValue','timeseries',1,'NaN',1,'Inf',1,'>=',0,'<=',1); - elif self.aIdx == 3: - md = checkfield(md,'fieldname','smb.cldFrac','NaN',1,'Inf',1,'> = ',0,'< = ',1) - elif self.aIdx == 4: - md = checkfield(md,'fieldname','smb.t0wet','NaN',1,'Inf',1,'> = ',15,'< = ',21.9) - md = checkfield(md,'fieldname','smb.t0dry','NaN',1,'Inf',1,'> = ',30,'< = ',30) - md = checkfield(md,'fieldname','smb.K','NaN',1,'Inf',1,'> = ',7,'< = ',7) - - - #check zTop is < local thickness: - he = np.sum(md.geometry.thickness[md.mesh.elements-1],axis=1)/np.size(md.mesh.elements,1) - if np.any(he= 1e-10): - error('smb_dt/dt = #f. The number of SMB time steps in one transient core time step has to be an an integer',md.timestepping.time_step/dt) - - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - - WriteData(fid,prefix,'data',outputs,'name','md.smb.requested_outputs','format','StringArray') - # }}} + """ + SMBgemb Class definition + + Usage: + SMB = SMBgemb() + """ + + def __init__(self): # {{{ + #each one of these properties is a transient forcing to the GEMB model, loaded from meteorological data derived + #from an automatic weather stations (AWS). Each property is therefore a matrix, of size (numberofvertices x number + #of time steps. ) + + #solution choices + #check these: + #isgraingrowth + #isalbedo + #isshortwave + #isthermal + #isaccumulation + #ismelt + #isdensification + #isturbulentflux + + #inputs: + self.Ta = float('NaN') #2 m air temperature, in Kelvin + self.V = float('NaN') #wind speed (m / s - 1) + self.dswrf = float('NaN') #downward shortwave radiation flux [W / m^2] + self.dlwrf = float('NaN') #downward longwave radiation flux [W / m^2] + self.P = float('NaN') #precipitation [mm w.e. / m^2] + self.eAir = float('NaN') #screen level vapor pressure [Pa] + self.pAir = float('NaN') #surface pressure [Pa] + self.Tmean = float('NaN') #mean annual temperature [K] + self.Vmean = float('NaN') #mean annual wind velocity [m s - 1] + self.C = float('NaN') #mean annual snow accumulation [kg m - 2 yr - 1] + self.Tz = float('NaN') #height above ground at which temperature (T) was sampled [m] + self.Vz = float('NaN') #height above ground at which wind (V) was sampled [m] + + #optional inputs: + self.aValue = float('NaN') #Albedo forcing at every element. Used only if aIdx == 0. + self.teValue = float('NaN') #Outward longwave radiation thermal emissivity forcing at every element (default in code is 1) + + # Initialization of snow properties + self.Dzini = float('NaN') #cell depth (m) + self.Dini = float('NaN') #snow density (kg m - 3) + self.Reini = float('NaN') #effective grain size (mm) + self.Gdnini = float('NaN') #grain dricity (0 - 1) + self.Gspini = float('NaN') #grain sphericity (0 - 1) + self.ECini = float('NaN') #evaporation/condensation (kg m - 2) + self.Wini = float('NaN') #Water content (kg m - 2) + self.Aini = float('NaN') #albedo (0 - 1) + self.Tini = float('NaN') #snow temperature (K) + self.Sizeini = float('NaN') #Number of layers + + #settings: + self.aIdx = float('NaN') #method for calculating albedo and subsurface absorption (default is 1) + # 0: direct input from aValue parameter + # 1: effective grain radius [Gardner & Sharp, 2009] + # 2: effective grain radius [Brun et al., 2009] + # 3: density and cloud amount [Greuell & Konzelmann, 1994] + # 4: exponential time decay & wetness [Bougamont & Bamber, 2005] + # 5: ingest MODIS mode, direct input from aValue parameter applied to surface ice only + self.swIdx = float('NaN') # apply all SW to top grid cell (0) or allow SW to penetrate surface (1) (default 1) + self.denIdx = float('NaN') #densification model to use (default is 2): + # 1 = emperical model of Herron and Langway (1980) + # 2 = semi - emperical model of Anthern et al. (2010) + # 3 = DO NOT USE: physical model from Appix B of Anthern et al. (2010) + # 4 = DO NOT USE: emperical model of Li and Zwally (2004) + # 5 = DO NOT USE: modified emperical model (4) by Helsen et al. (2008) + # 6 = Antarctica semi - emperical model of Ligtenberg et al. (2011) + # 7 = Greenland semi - emperical model of Kuipers Munneke et al. (2015) + self.dsnowIdx = float('NaN') #model for fresh snow accumulation density (default is 1): + # 0 = Original GEMB value, 150 kg / m^3 + # 1 = Antarctica value of fresh snow density, 350 kg / m^3 + # 2 = Greenland value of fresh snow density, 315 kg / m^3, Fausto et al. (2008) + # 3 = Antarctica model of Kaspers et al. (2004) + # 4 = Greenland model of Kuipers Munneke et al. (2015) + + self.zTop = float('NaN') # depth over which grid length is constant at the top of the snopack (default 10) [m] + self.dzTop = float('NaN') # initial top vertical grid spacing (default .05) [m] + self.dzMin = float('NaN') # initial min vertical allowable grid spacing (default dzTop / 2) [m] + self.zY = float('NaN') # strech grid cells bellow top_z by a [top_dz * y ^ (cells bellow top_z)] + self.zMax = float('NaN') #initial max model depth (default is min(thickness, 250)) [m] + self.zMin = float('NaN') #initial min model depth (default is min(thickness, 130)) [m] + self.outputFreq = float('NaN') #output frequency in days (default is monthly, 30) + + #specific albedo parameters: + #Method 1 and 2: + self.aSnow = float('NaN') # new snow albedo (0.64 - 0.89) + self.aIce = float('NaN') # range 0.27 - 0.58 for old snow + #Method 3: Radiation Correction Factors - > only used for met station data and Greuell & Konzelmann, 1994 albedo + self.cldFrac = float('NaN') # average cloud amount + #Method 4: additonal tuning parameters albedo as a funtion of age and water content (Bougamont et al., 2005) + self.t0wet = float('NaN') # time scale for wet snow (15 - 21.9) + self.t0dry = float('NaN') # warm snow timescale (30) + self.K = float('NaN') # time scale temperature coef. (7) + self.adThresh = float('NaN') # Apply aIdx method to all areas with densities below this value, + # or else apply direct input value from aValue, allowing albedo to be altered. + # Default value is rho water (1023 kg m - 3). + + #densities: + self.InitDensityScaling = float('NaN') #initial scaling factor multiplying the density of ice, which describes the density of the snowpack. + + #thermo: + self.ThermoDeltaTScaling = float('NaN') #scaling factor to multiply the thermal diffusion timestep (delta t) + + self.requested_outputs = [] + + #Several fields are missing from the standard GEMB model, which are capture intrinsically by ISSM. + #dateN: that's the last row of the above fields. + #dt: included in dateN. Not an input. + #elev: this is taken from the ISSM surface itself. + + #}}} + + def __repr__(self): # {{{ + #string = " surface forcings parameters:" + #string = " #s\n #s" % (string, fielddisplay(self, 'mass_balance', 'surface mass balance [m / yr ice eq]')) + #string = " #s\n #s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) + string = ' surface forcings for SMB GEMB model :' + string = "%s\n%s" % (string, fielddisplay(self, 'issmbgradients', 'is smb gradients method activated (0 or 1, default is 0)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isgraingrowth', 'run grain growth module (default true)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isalbedo', 'run albedo module (default true)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isshortwave', 'run short wave module (default true)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isthermal', 'run thermal module (default true)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isaccumulation', 'run accumulation module (default true)')) + string = "%s\n%s" % (string, fielddisplay(self, 'ismelt', 'run melting module (default true)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isdensification', 'run densification module (default true)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isturbulentflux', 'run turbulant heat fluxes module (default true)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isclimatology', 'repeat all forcings when past last forcing time (default false)')) + string = "%s\n%s" % (string, fielddisplay(self, 'Ta', '2 m air temperature, in Kelvin')) + string = "%s\n%s" % (string, fielddisplay(self, 'V', 'wind speed (m s - 1)')) + string = "%s\n%s" % (string, fielddisplay(self, 'dlwrf', 'downward shortwave radiation flux [W / m^2]')) + string = "%s\n%s" % (string, fielddisplay(self, 'dswrf', 'downward longwave radiation flux [W / m^2]')) + string = "%s\n%s" % (string, fielddisplay(self, 'P', 'precipitation [mm w.e. / m^2]')) + string = "%s\n%s" % (string, fielddisplay(self, 'eAir', 'screen level vapor pressure [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'pAir', 'surface pressure [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'Tmean', 'mean annual temperature [K]')) + string = "%s\n%s" % (string, fielddisplay(self, 'C', 'mean annual snow accumulation [kg m - 2 yr - 1]')) + string = "%s\n%s" % (string, fielddisplay(self, 'Vmean', 'mean annual wind velocity [m s - 1] (default 10 m / s)')) + string = "%s\n%s" % (string, fielddisplay(self, 'Tz', 'height above ground at which temperature (T) was sampled [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'Vz', 'height above ground at which wind (V) was sampled [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'zTop', 'depth over which grid length is constant at the top of the snopack (default 10) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'dzTop', 'initial top vertical grid spacing (default .05) [m] ')) + string = "%s\n%s" % (string, fielddisplay(self, 'dzMin', 'initial min vertical allowable grid spacing (default dzMin / 2) [m] ')) + string = "%s\n%s" % (string, fielddisplay(self, 'zMax', 'initial max model depth (default is min(thickness, 500)) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'zMin', 'initial min model depth (default is min(thickness, 30)) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'zY', 'strech grid cells bellow top_z by a [top_dz * y ^ (cells bellow top_z)]')) + string = "%s\n%s" % (string, fielddisplay(self, 'InitDensityScaling', ['initial scaling factor multiplying the density of ice', 'which describes the density of the snowpack.'])) + string = "%s\n%s" % (string, fielddisplay(self, 'ThermoDeltaTScaling', 'scaling factor to multiply the thermal diffusion timestep (delta t)')) + string = "%s\n%s" % (string, fielddisplay(self, 'outputFreq', 'output frequency in days (default is monthly, 30)')) + string = "%s\n%s" % (string, fielddisplay(self, 'adThresh', 'Apply aIdx method to all areas with densities below this value, ', 'or else apply direct input value from aValue, allowing albedo to be altered.')) + string = "%s\n%s" % (string, fielddisplay(self, 'aIdx', ['method for calculating albedo and subsurface absorption (default is 1)', + '0: direct input from aValue parameter', + '1: effective grain radius [Gardner & Sharp, 2009]', + '2: effective grain radius [Brun et al., 2009]', + '3: density and cloud amount [Greuell & Konzelmann, 1994]', + '4: exponential time decay & wetness [Bougamont & Bamber, 2005]'])) + string = "%s\n%s" % (string, fielddisplay(self, 'teValue', 'Outward longwave radiation thermal emissivity forcing at every element (default in code is 1)')) + #snow properties init + string = "%s\n%s" % (string, fielddisplay(self, 'Dzini', 'Initial cell depth when restart [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'Dini', 'Initial snow density when restart [kg m - 3]')) + string = "%s\n%s" % (string, fielddisplay(self, 'Reini', 'Initial grain size when restart [mm]')) + string = "%s\n%s" % (string, fielddisplay(self, 'Gdnini', 'Initial grain dricity when restart [ - ]')) + string = "%s\n%s" % (string, fielddisplay(self, 'Gspini', 'Initial grain sphericity when restart [ - ]')) + string = "%s\n%s" % (string, fielddisplay(self, 'ECini', 'Initial evaporation / condensation when restart [kg m - 2]')) + string = "%s\n%s" % (string, fielddisplay(self, 'Wini', 'Initial snow water content when restart [kg m - 2]')) + string = "%s\n%s" % (string, fielddisplay(self, 'Aini', 'Initial albedo when restart [ - ]')) + string = "%s\n%s" % (string, fielddisplay(self, 'Tini', 'Initial snow temperature when restart [K]')) + string = "%s\n%s" % (string, fielddisplay(self, 'Sizeini', 'Initial number of layers when restart [K]')) + + #additional albedo parameters: + if isinstance(self.aIdx, list) or isinstance(self.aIdx, np.ndarray) and (self.aIdx == [1, 2] or (1 in self.aIdx and 2 in self.aIdx)): + string = "%s\n%s" % (string, fielddisplay(self, 'aSnow', 'new snow albedo (0.64 - 0.89)')) + string = "%s\n%s" % (string, fielddisplay(self, 'aIce', 'albedo of ice (0.27 - 0.58)')) + elif elf.aIdx == 0: + string = "%s\n%s" % (string, fielddisplay(self, 'aValue', 'Albedo forcing at every element. Used only if aIdx == {0, 5}')) + elif elf.aIdx == 5: + string = "%s\n%s" % (string, fielddisplay(self, 'aValue', 'Albedo forcing at every element. Used only if aIdx == {0, 5}')) + elif self.aIdx == 3: + string = "%s\n%s" % (string, fielddisplay(self, 'cldFrac', 'average cloud amount')) + elif self.aIdx == 4: + string = "%s\n%s" % (string, fielddisplay(self, 't0wet', 'time scale for wet snow (15 - 21.9) [d]')) + string = "%s\n%s" % (string, fielddisplay(self, 't0dry', 'warm snow timescale (30) [d]')) + string = "%s\n%s" % (string, fielddisplay(self, 'K', 'time scale temperature coef. (7) [d]')) + + string = "%s\n%s" % (string, fielddisplay(self, 'swIdx', 'apply all SW to top grid cell (0) or allow SW to penetrate surface (1) [default 1]')) + string = "%s\n%s" % (string, fielddisplay(self, 'denIdx', ['densification model to use (default is 2):', + '1 = emperical model of Herron and Langway (1980)', + '2 = semi - emperical model of Anthern et al. (2010)', + '3 = DO NOT USE: physical model from Appix B of Anthern et al. (2010)', + '4 = DO NOT USE: emperical model of Li and Zwally (2004)', + '5 = DO NOT USE: modified emperical model (4) by Helsen et al. (2008)', + '6 = Antarctica semi - emperical model of Ligtenberg et al. (2011)', + '7 = Greenland semi - emperical model of Kuipers Munneke et al. (2015)'])) + string = "%s\n%s" % (string, fielddisplay(self, 'dsnowIdx', ['model for fresh snow accumulation density (default is 1):', + '0 = Original GEMB value, 150 kg / m^3', + '1 = Antarctica value of fresh snow density, 350 kg / m^3', + '2 = Greenland value of fresh snow density, 315 kg / m^3, Fausto et al. (2008)', + '3 = Antarctica model of Kaspers et al. (2004), Make sure to set Vmean accurately', + '4 = Greenland model of Kuipers Munneke et al. (2015)'])) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) + return string + #}}} + + def extrude(self, md): # {{{ + self.Ta = project3d(md, 'vector', self.Ta, 'type', 'node') + self.V = project3d(md, 'vector', self.V, 'type', 'node') + self.dswrf = project3d(md, 'vector', self.dswrf, 'type', 'node') + self.dswrf = project3d(md, 'vector', self.dswrf, 'type', 'node') + self.P = project3d(md, 'vector', self.P, 'type', 'node') + self.eAir = project3d(md, 'vector', self.eAir, 'type', 'node') + self.pAir = project3d(md, 'vector', self.pAir, 'type', 'node') + + if (self.aIdx == 0) and np.isnan(self.aValue): + self.aValue = project3d(md, 'vector', self.aValue, 'type', 'node') + if np.isnan(self.teValue): + self.teValue = project3d(md, 'vector', self.teValue, 'type', 'node') + + return self + #}}} + + def defaultoutputs(self, md): # {{{ + return ['SmbMassBalance'] + #}}} + + def setdefaultparameters(self, mesh, geometry): # {{{ + self.isgraingrowth = 1 + self.isalbedo = 1 + self.isshortwave = 1 + self.isthermal = 1 + self.isaccumulation = 1 + self.ismelt = 1 + self.isdensification = 1 + self.isturbulentflux = 1 + self.isclimatology = 0 + + self.aIdx = 1 + self.swIdx = 1 + self.denIdx = 2 + self.dsnowIdx = 1 + self.zTop = 10 * np.ones((mesh.numberofelements, )) + self.dzTop = .05 * np.ones((mesh.numberofelements, )) + self.dzMin = self.dzTop / 2 + self.InitDensityScaling = 1.0 + self.ThermoDeltaTScaling = 1 / 11.0 + + self.Vmean = 10 * np.ones((mesh.numberofelements, )) + + self.zMax = 250 * np.ones((mesh.numberofelements, )) + self.zMin = 130 * np.ones((mesh.numberofelements, )) + self.zY = 1.10 * np.ones((mesh.numberofelements, )) + self.outputFreq = 30 + + #additional albedo parameters + self.aSnow = 0.85 + self.aIce = 0.48 + self.cldFrac = 0.1 + self.t0wet = 15 + self.t0dry = 30 + self.K = 7 + self.adThresh = 1023 + + self.teValue = np.ones((mesh.numberofelements, )) + self.aValue = self.aSnow * np.ones(mesh.numberofelements, ) + + self.Dzini = 0.05 * np.ones((mesh.numberofelements, 2)) + self.Dini = 910.0 * np.ones((mesh.numberofelements, 2)) + self.Reini = 2.5 * np.ones((mesh.numberofelements, 2)) + self.Gdnini = 0.0 * np.ones((mesh.numberofelements, 2)) + self.Gspini = 0.0 * np.ones((mesh.numberofelements, 2)) + self.ECini = 0.0 * np.ones((mesh.numberofelements, )) + self.Wini = 0.0 * np.ones((mesh.numberofelements, 2)) + self.Aini = self.aSnow * np.ones((mesh.numberofelements, 2)) + self.Tini = 273.15 * np.ones((mesh.numberofelements, 2)) + # / !\ Default value of Tini must be equal to Tmean but don't know Tmean yet (computed when atmospheric forcings are interpolated on mesh). + # If initialization without restart, this value will be overwritten when snow parameters are retrieved in Element.cpp + self.Sizeini = 2 * np.ones((mesh.numberofelements, )) + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'smb.isgraingrowth', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'smb.isalbedo', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'smb.isshortwave', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'smb.isthermal', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'smb.isaccumulation', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'smb.ismelt', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'smb.isdensification', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'smb.isturbulentflux', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'smb.isclimatology', 'values', [0, 1]) + + md = checkfield(md, 'fieldname', 'smb.Ta', 'timeseries', 1, 'NaN', 1, 'Inf', 1, '>', 273 - 100, '<', 273 + 100) # - 100 / 100 celsius min / max value + md = checkfield(md, 'fieldname', 'smb.V', 'timeseries', 1, 'NaN', 1, 'Inf', 1, '>=', 0, '<', 45, 'size', np.shape(self.Ta)) #max 500 km / h + md = checkfield(md, 'fieldname', 'smb.dswrf', 'timeseries', 1, 'NaN', 1, 'Inf', 1, '>=', 0, '<=', 1400, 'size', np.shape(self.Ta)) + md = checkfield(md, 'fieldname', 'smb.dlwrf', 'timeseries', 1, 'NaN', 1, 'Inf', 1, '>=', 0, 'size', np.shape(self.Ta)) + md = checkfield(md, 'fieldname', 'smb.P', 'timeseries', 1, 'NaN', 1, 'Inf', 1, '>=', 0, '<=', 100, 'size', np.shape(self.Ta)) + md = checkfield(md, 'fieldname', 'smb.eAir', 'timeseries', 1, 'NaN', 1, 'Inf', 1, 'size', np.shape(self.Ta)) + + if (self.isclimatology > 0): + md = checkfield(md, 'fieldname', 'smb.Ta', 'size', [md.mesh.numberofelements + 1], 'message', 'Ta must have md.mesh.numberofelements + 1 rows in order to force a climatology') + md = checkfield(md, 'fieldname', 'smb.V', 'size', [md.mesh.numberofelements + 1], 'message', 'V must have md.mesh.numberofelements + 1 rows in order to force a climatology') + md = checkfield(md, 'fieldname', 'smb.dswrf', 'size', [md.mesh.numberofelements + 1], 'message', 'dswrf must have md.mesh.numberofelements + 1 rows in order to force a climatology') + md = checkfield(md, 'fieldname', 'smb.dlwrf', 'size', [md.mesh.numberofelements + 1], 'message', 'dlwrf must have md.mesh.numberofelements + 1 rows in order to force a climatology') + md = checkfield(md, 'fieldname', 'smb.P', 'size', [md.mesh.numberofelements + 1], 'message', 'P must have md.mesh.numberofelements + 1 rows in order to force a climatology') + md = checkfield(md, 'fieldname', 'smb.eAir', 'size', [md.mesh.numberofelements + 1], 'message', 'eAir must have md.mesh.numberofelements + 1 rows in order to force a climatology') + + md = checkfield(md, 'fieldname', 'smb.Tmean', 'size', [md.mesh.numberofelements], 'NaN', 1, 'Inf', 1, '>', 273 - 100, '<', 273 + 100) # - 100 / 100 celsius min / max value + md = checkfield(md, 'fieldname', 'smb.C', 'size', [md.mesh.numberofelements], 'NaN', 1, 'Inf', 1, '>=', 0) + md = checkfield(md, 'fieldname', 'smb.Vmean', 'size', [md.mesh.numberofelements], 'NaN', 1, 'Inf', 1, '>=', 0) + md = checkfield(md, 'fieldname', 'smb.Tz', 'size', [md.mesh.numberofelements], 'NaN', 1, 'Inf', 1, '>=', 0, '<=', 5000) + md = checkfield(md, 'fieldname', 'smb.Vz', 'size', [md.mesh.numberofelements], 'NaN', 1, 'Inf', 1, '>=', 0, '<=', 5000) + + md = checkfield(md, 'fieldname', 'smb.teValue', 'timeseries', 1, 'NaN', 1, 'Inf', 1, '>=', 0, '<=', 1) + + md = checkfield(md, 'fieldname', 'smb.aIdx', 'NaN', 1, 'Inf', 1, 'values', [0, 1, 2, 3, 4]) + md = checkfield(md, 'fieldname', 'smb.swIdx', 'NaN', 1, 'Inf', 1, 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'smb.denIdx', 'NaN', 1, 'Inf', 1, 'values', [1, 2, 3, 4, 5, 6, 7]) + md = checkfield(md, 'fieldname', 'smb.dsnowIdx', 'NaN', 1, 'Inf', 1, 'values', [0, 1, 2, 3, 4]) + + md = checkfield(md, 'fieldname', 'smb.zTop', 'NaN', 1, 'Inf', 1, '>=', 0) + md = checkfield(md, 'fieldname', 'smb.dzTop', 'NaN', 1, 'Inf', 1, '>', 0) + md = checkfield(md, 'fieldname', 'smb.dzMin', 'NaN', 1, 'Inf', 1, '>', 0) + md = checkfield(md, 'fieldname', 'smb.zY', 'NaN', 1, 'Inf', 1, '>=', 1) + md = checkfield(md, 'fieldname', 'smb.outputFreq', 'NaN', 1, 'Inf', 1, '>', 0, '<', 10 * 365) #10 years max + md = checkfield(md, 'fieldname', 'smb.InitDensityScaling', 'NaN', 1, 'Inf', 1, '>=', 0, '<=', 1) + md = checkfield(md, 'fieldname', 'smb.ThermoDeltaTScaling', 'NaN', 1, 'Inf', 1, '>=', 0, '<=', 1) + md = checkfield(md, 'fieldname', 'smb.adThresh', 'NaN', 1, 'Inf', 1, '>=', 0) + + if isinstance(self.aIdx, list) or isinstance(self.aIdx, np.ndarray) and (self.aIdx == [1, 2] or (1 in self.aIdx and 2 in self.aIdx)): + md = checkfield(md, 'fieldname', 'smb.aSnow', 'NaN', 1, 'Inf', 1, '>=', .64, '<=', .89) + md = checkfield(md, 'fieldname', 'smb.aIce', 'NaN', 1, 'Inf', 1, '>=', .27, '<=', .58) + elif self.aIdx == 0: + md = checkfield(md, 'fieldname', 'smb.aValue', 'timeseries', 1, 'NaN', 1, 'Inf', 1, '>=', 0, '<=', 1) + elif self.aIdx == 3: + md = checkfield(md, 'fieldname', 'smb.cldFrac', 'NaN', 1, 'Inf', 1, '>=', 0, '<=', 1) + elif self.aIdx == 4: + md = checkfield(md, 'fieldname', 'smb.t0wet', 'NaN', 1, 'Inf', 1, '>=', 15, '<=', 21.9) + md = checkfield(md, 'fieldname', 'smb.t0dry', 'NaN', 1, 'Inf', 1, '>=', 30, '<=', 30) + md = checkfield(md, 'fieldname', 'smb.K', 'NaN', 1, 'Inf', 1, '>=', 7, '<=', 7) + + #check zTop is < local thickness: + he = np.sum(md.geometry.thickness[md.mesh.elements - 1], axis=1) / np.size(md.mesh.elements, 1) + if np.any(he < self.zTop): + error('SMBgemb consistency check error: zTop should be smaller than local ice thickness') + + md = checkfield(md, 'fieldname', 'smb.requested_outputs', 'stringrow', 1) + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + + WriteData(fid, prefix, 'name', 'md.smb.model', 'data', 8, 'format', 'Integer') + + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isgraingrowth', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isalbedo', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isshortwave', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isthermal', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isaccumulation', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'ismelt', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isdensification', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isturbulentflux', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isclimatology', 'format', 'Boolean') + + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Ta', 'format', 'DoubleMat', 'mattype', 2, 'timeserieslength', md.mesh.numberofelements + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'V', 'format', 'DoubleMat', 'mattype', 2, 'timeserieslength', md.mesh.numberofelements + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'dswrf', 'format', 'DoubleMat', 'mattype', 2, 'timeserieslength', md.mesh.numberofelements + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'dlwrf', 'format', 'DoubleMat', 'mattype', 2, 'timeserieslength', md.mesh.numberofelements + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'P', 'format', 'DoubleMat', 'mattype', 2, 'timeserieslength', md.mesh.numberofelements + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'eAir', 'format', 'DoubleMat', 'mattype', 2, 'timeserieslength', md.mesh.numberofelements + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'pAir', 'format', 'DoubleMat', 'mattype', 2, 'timeserieslength', md.mesh.numberofelements + 1, 'yts', yts) + + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Tmean', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'C', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Vmean', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Tz', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Vz', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'zTop', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'dzTop', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'dzMin', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'zY', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'zMax', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'zMin', 'format', 'DoubleMat', 'mattype', 2) + + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'aIdx', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'swIdx', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'denIdx', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'dsnowIdx', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'InitDensityScaling', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'ThermoDeltaTScaling', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'outputFreq', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'aSnow', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'aIce', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'cldFrac', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 't0wet', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 't0dry', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'K', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'adThresh', 'format', 'Double') + + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'aValue', 'format', 'DoubleMat', 'mattype', 2, 'timeserieslength', md.mesh.numberofelements + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'teValue', 'format', 'DoubleMat', 'mattype', 2, 'timeserieslength', md.mesh.numberofelements + 1, 'yts', yts) + + #snow properties init + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Dzini', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Dini', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Reini', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Gdnini', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Gspini', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'ECini', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Wini', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Aini', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Tini', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Sizeini', 'format', 'IntMat', 'mattype', 2) + + #figure out dt from forcings: + time = self.Ta[-1] #assume all forcings are on the same time step + dtime = np.diff(time, n=1, axis=0) + dt = min(dtime) / yts + + WriteData(fid, prefix, 'data', dt, 'name', 'md.smb.dt', 'format', 'Double', 'scale', yts) + + # Check if smb_dt goes evenly into transient core time step + if (md.timestepping.time_step % dt >= 1e-10): + error('smb_dt/dt = #f. The number of SMB time steps in one transient core time step has to be an an integer', md.timestepping.time_step / dt) + + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + + WriteData(fid, prefix, 'data', outputs, 'name', 'md.smb.requested_outputs', 'format', 'StringArray') + # }}} Index: /issm/trunk-jpl/src/m/classes/SMBgradients.py =================================================================== --- /issm/trunk-jpl/src/m/classes/SMBgradients.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/SMBgradients.py (revision 24213) @@ -2,75 +2,76 @@ from checkfield import checkfield from WriteData import WriteData -from project3d import project3d + class SMBgradients(object): - """ - SMBgradients Class definition + """ + SMBgradients Class definition - Usage: - SMBgradients=SMBgradients(); - """ + Usage: + SMBgradients = SMBgradients() + """ - def __init__(self): # {{{ - self.href = float('NaN') - self.smbref = float('NaN') - self.b_pos = float('NaN') - self.b_neg = float('NaN') - self.requested_outputs = [] - #}}} - def __repr__(self): # {{{ - string=" surface forcings parameters:" + def __init__(self): # {{{ + self.href = float('NaN') + self.smbref = float('NaN') + self.b_pos = float('NaN') + self.b_neg = float('NaN') + self.requested_outputs = [] + #}}} - string="%s\n%s"%(string,fielddisplay(self,'issmbgradients','is smb gradients method activated (0 or 1, default is 0)')) - string="%s\n%s"%(string,fielddisplay(self,'href',' reference elevation from which deviation is used to calculate SMB adjustment in smb gradients method')) - string="%s\n%s"%(string,fielddisplay(self,'smbref',' reference smb from which deviation is calculated in smb gradients method')) - string="%s\n%s"%(string,fielddisplay(self,'b_pos',' slope of hs - smb regression line for accumulation regime required if smb gradients is activated')) - string="%s\n%s"%(string,fielddisplay(self,'b_neg',' slope of hs - smb regression line for ablation regime required if smb gradients is activated')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) + def __repr__(self): # {{{ + string = " surface forcings parameters:" - return string - #}}} - def extrude(self,md): # {{{ + string = "%s\n%s" % (string, fielddisplay(self, 'issmbgradients', 'is smb gradients method activated (0 or 1, default is 0)')) + string = "%s\n%s" % (string, fielddisplay(self, 'href', ' reference elevation from which deviation is used to calculate SMB adjustment in smb gradients method')) + string = "%s\n%s" % (string, fielddisplay(self, 'smbref', ' reference smb from which deviation is calculated in smb gradients method')) + string = "%s\n%s" % (string, fielddisplay(self, 'b_pos', ' slope of hs - smb regression line for accumulation regime required if smb gradients is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'b_neg', ' slope of hs - smb regression line for ablation regime required if smb gradients is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) - #Nothing for now - return self - #}}} - def defaultoutputs(self,md): # {{{ - return [] - #}}} - def initialize(self,md): # {{{ + return string + #}}} - #Nothing for now + def extrude(self, md): # {{{ + #Nothing for now + return self + #}}} - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def defaultoutputs(self, md): # {{{ + return [] + #}}} - if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.href','timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.smbref','timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.b_pos','timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.b_neg','timeseries',1,'NaN',1,'Inf',1) + def initialize(self, md): # {{{ + #Nothing for now + return self + #}}} - md = checkfield(md,'fieldname','masstransport.requested_outputs','stringrow',1) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ + if 'MasstransportAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'smb.href', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.smbref', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.b_pos', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.b_neg', 'timeseries', 1, 'NaN', 1, 'Inf', 1) - yts=md.constants.yts + md = checkfield(md, 'fieldname', 'masstransport.requested_outputs', 'stringrow', 1) + return md + # }}} - WriteData(fid,prefix,'name','md.smb.model','data',6,'format','Integer'); - WriteData(fid,prefix,'object',self,'class','smb','fieldname','href','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','smbref','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','b_pos','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','b_neg','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.smb.requested_outputs','format','StringArray') + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts - # }}} + WriteData(fid, prefix, 'name', 'md.smb.model', 'data', 6, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'href', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'smbref', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'b_pos', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'b_neg', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.smb.requested_outputs', 'format', 'StringArray') + + # }}} Index: /issm/trunk-jpl/src/m/classes/SMBgradientscomponents.py =================================================================== --- /issm/trunk-jpl/src/m/classes/SMBgradientscomponents.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/SMBgradientscomponents.py (revision 24213) @@ -2,77 +2,81 @@ from checkfield import checkfield from WriteData import WriteData -from project3d import project3d + class SMBgradientscomponents(object): - """ - SMBgradients Class definition + """ + SMBgradients Class definition - Usage: - SMBgradients=SMBgradientscomponents(); - For now it has accumulation, runoff ans retention which could be aither refreezing and/or evaporation - """ + Usage: + SMBgradients = SMBgradientscomponents() + For now it has accumulation, runoff ans retention which could be aither refreezing and / or evaporation + """ - def __init__(self): # {{{ - self.accuref = float('NaN') - self.accualti = float('NaN') - self.accugrad = float('NaN') - self.runoffref = float('NaN') - self.runoffalti = float('NaN') - self.runoffgrad = float('NaN') - self.requested_outputs = ['default'] - #}}} - def __repr__(self): # {{{ - string=" surface forcings parameters:" - string="%s\n%s"%(string,fielddisplay(self,'accuref',' reference value of the accumulation')) - string="%s\n%s"%(string,fielddisplay(self,'accualti',' Altitude at which the accumulation is equal to the reference value')) - string="%s\n%s"%(string,fielddisplay(self,'accugrad',' Gradient of the variation of the accumulation (0 for uniform accumulation)')) - string="%s\n%s"%(string,fielddisplay(self,'runoffref',' reference value of the runoff m w.e. y-1 (temperature times ddf)')) - string="%s\n%s"%(string,fielddisplay(self,'runoffalti',' Altitude at which the runoff is equal to the reference value')) - string="%s\n%s"%(string,fielddisplay(self,'runoffgrad',' Gradient of the variation of the runoff (0 for uniform runoff) m w.e. m-1 y-1 (lpase rate times ddf)')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) + def __init__(self): # {{{ + self.accuref = float('NaN') + self.accualti = float('NaN') + self.accugrad = float('NaN') + self.runoffref = float('NaN') + self.runoffalti = float('NaN') + self.runoffgrad = float('NaN') + self.requested_outputs = ['default'] + #}}} - return string - #}}} - def extrude(self,md): # {{{ - #Nothing for now - return self - #}}} - def defaultoutputs(self,md): # {{{ - return ['SmbMassBalance','SmbRunoff'] - #}}} - def initialize(self,md): # {{{ - #Nothing for now - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.accuref','singletimeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.accualti','numel',[1],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.accugrad','numel',[1],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.runoffref','singletimeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.runoffalti','numel',[1],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.runoffgrad','numel',[1],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','masstransport.requested_outputs','stringrow',1) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + def __repr__(self): # {{{ + string = " surface forcings parameters:" + string = "%s\n%s" % (string, fielddisplay(self, 'accuref', ' reference value of the accumulation')) + string = "%s\n%s" % (string, fielddisplay(self, 'accualti', ' Altitude at which the accumulation is equal to the reference value')) + string = "%s\n%s" % (string, fielddisplay(self, 'accugrad', ' Gradient of the variation of the accumulation (0 for uniform accumulation)')) + string = "%s\n%s" % (string, fielddisplay(self, 'runoffref', ' reference value of the runoff m w.e. y - 1 (temperature times ddf)')) + string = "%s\n%s" % (string, fielddisplay(self, 'runoffalti', ' Altitude at which the runoff is equal to the reference value')) + string = "%s\n%s" % (string, fielddisplay(self, 'runoffgrad', ' Gradient of the variation of the runoff (0 for uniform runoff) m w.e. m - 1 y - 1 (lpase rate times ddf)')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) - yts=md.constants.yts + return string + #}}} - WriteData(fid,prefix,'name','md.smb.model','data',11,'format','Integer') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','accuref','format','DoubleMat','mattype',1,'timeserieslength',2,'yts',md.constants.yts,'scale',1./md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','accualti','format','Double') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','accugrad','format','Double','scale',1./md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','runoffref','format','DoubleMat','mattype',1,'timeserieslength',2,'yts',md.constants.yts,'scale',1./md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','runoffalti','format','Double') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','runoffgrad','format','Double','scale',1./md.constants.yts) + def extrude(self, md): # {{{ + #Nothing for now + return self + #}}} - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.smb.requested_outputs','format','StringArray') + def defaultoutputs(self, md): # {{{ + return ['SmbMassBalance', 'SmbRunoff'] + #}}} - # }}} + def initialize(self, md): # {{{ + #Nothing for now + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + if 'MasstransportAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'smb.accuref', 'singletimeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.accualti', 'numel', [1], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.accugrad', 'numel', [1], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.runoffref', 'singletimeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.runoffalti', 'numel', [1], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.runoffgrad', 'numel', [1], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'masstransport.requested_outputs', 'stringrow', 1) + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + WriteData(fid, prefix, 'name', 'md.smb.model', 'data', 11, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'accuref', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', 2, 'yts', yts, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'accualti', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'accugrad', 'format', 'Double', 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'runoffref', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', 2, 'yts', yts, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'runoffalti', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'runoffgrad', 'format', 'Double', 'scale', 1. / yts) + + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.smb.requested_outputs', 'format', 'StringArray') + + # }}} Index: /issm/trunk-jpl/src/m/classes/SMBgradientsela.py =================================================================== --- /issm/trunk-jpl/src/m/classes/SMBgradientsela.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/SMBgradientsela.py (revision 24213) @@ -2,85 +2,87 @@ from checkfield import checkfield from WriteData import WriteData -from project3d import project3d + class SMBgradientsela(object): - """ - SMBgradientsela Class definition + """ + SMBgradientsela Class definition - Usage: - SMBgradientsela=SMBgradientsela() - """ + Usage: + SMBgradientsela = SMBgradientsela() + """ - def __init__(self): # {{{ - self.ela = float('NaN') - self.b_pos = float('NaN') - self.b_neg = float('NaN') - self.b_max = float('NaN') - self.b_min = float('NaN') - self.requested_outputs = [] - self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string = " surface forcings parameters:" - string+= '\n SMB gradients ela parameters:' + def __init__(self): # {{{ + self.ela = float('NaN') + self.b_pos = float('NaN') + self.b_neg = float('NaN') + self.b_max = float('NaN') + self.b_min = float('NaN') + self.requested_outputs = [] + self.setdefaultparameters() + #}}} - string="%s\n%s"%(string,fielddisplay(self,'ela',' equilibrium line altitude from which deviation is used to calculate smb using the smb gradients ela method [m a.s.l.]')) - string="%s\n%s"%(string,fielddisplay(self,'b_pos',' vertical smb gradient (dB/dz) above ela')) - string="%s\n%s"%(string,fielddisplay(self,'b_neg',' vertical smb gradient (dB/dz) below ela')) - string="%s\n%s"%(string,fielddisplay(self,'b_max',' upper cap on smb rate, default: 9999 (no cap) [m ice eq./yr]')) - string="%s\n%s"%(string,fielddisplay(self,'b_min',' lower cap on smb rate, default: -9999 (no cap) [m ice eq./yr]')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) + def __repr__(self): # {{{ + string = " surface forcings parameters:" + string += '\n SMB gradients ela parameters:' - return string - #}}} - def extrude(self,md): # {{{ + string = "%s\n%s" % (string, fielddisplay(self, 'ela', ' equilibrium line altitude from which deviation is used to calculate smb using the smb gradients ela method [m a.s.l.]')) + string = "%s\n%s" % (string, fielddisplay(self, 'b_pos', ' vertical smb gradient (dB / dz) above ela')) + string = "%s\n%s" % (string, fielddisplay(self, 'b_neg', ' vertical smb gradient (dB / dz) below ela')) + string = "%s\n%s" % (string, fielddisplay(self, 'b_max', ' upper cap on smb rate, default: 9999 (no cap) [m ice eq. / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'b_min', ' lower cap on smb rate, default: - 9999 (no cap) [m ice eq. / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) - #Nothing for now - return self - #}}} - def defaultoutputs(self,md): # {{{ - return [] - #}}} - def initialize(self,md): # {{{ + return string + #}}} - #Nothing for now + def extrude(self, md): # {{{ + #Nothing for now + return self + #}}} - return self - #}}} - def setdefaultparameters(self): # {{{ - self.b_max=9999. - self.b_min=-9999. - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def defaultoutputs(self, md): # {{{ + return [] + #}}} - if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.ela','timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.b_pos','timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.b_neg','timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.b_max','timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','smb.b_min','timeseries',1,'NaN',1,'Inf',1) + def initialize(self, md): # {{{ + #Nothing for now + return self + #}}} - md = checkfield(md,'fieldname','smb.requested_outputs','stringrow',1) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + def setdefaultparameters(self): # {{{ + self.b_max = 9999. + self.b_min = -9999. + return self + #}}} - yts=md.constants.yts + def checkconsistency(self, md, solution, analyses): # {{{ + if 'MasstransportAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'smb.ela', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.b_pos', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.b_neg', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.b_max', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'smb.b_min', 'timeseries', 1, 'NaN', 1, 'Inf', 1) - WriteData(fid,prefix,'name','md.smb.model','data',9,'format','Integer'); - WriteData(fid,prefix,'object',self,'class','smb','fieldname','ela','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','b_pos','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','b_neg','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','b_max','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','b_min','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.smb.requested_outputs','format','StringArray') + md = checkfield(md, 'fieldname', 'smb.requested_outputs', 'stringrow', 1) + return md + # }}} - # }}} + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + + WriteData(fid, prefix, 'name', 'md.smb.model', 'data', 9, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'ela', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'b_pos', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'b_neg', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'b_max', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'b_min', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.smb.requested_outputs', 'format', 'StringArray') + + # }}} Index: /issm/trunk-jpl/src/m/classes/SMBmeltcomponents.py =================================================================== --- /issm/trunk-jpl/src/m/classes/SMBmeltcomponents.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/SMBmeltcomponents.py (revision 24213) @@ -3,4 +3,5 @@ from project3d import * from WriteData import * + class SMBmeltcomponents(object): @@ -9,108 +10,110 @@ Usage: - SMBmeltcomponents=SMBmeltcomponents(); + SMBmeltcomponents = SMBmeltcomponents() """ - def __init__(self): # {{{ + def __init__(self): # {{{ self.accumulation = float('NaN') self.runoff = float('NaN') self.evaporation = float('NaN') self.isclimatology = 0 - self.requested_outputs = [] - #}}} - def __repr__(self): # {{{ - string=" surface forcings parameters with melt (SMB=accumulation-evaporation-melt+refreeze) :" - string="%s\n%s"%(string,fielddisplay(self,'accumulation','accumulated snow [m/yr ice eq]')) - string="%s\n%s"%(string,fielddisplay(self,'evaporation','mount of ice lost to evaporative processes [m/yr ice eq]')) - string="%s\n%s"%(string,fielddisplay(self,'melt','amount of ice melt in the ice column [m/yr ice eq]')) - string="%s\n%s"%(string,fielddisplay(self,'refreeze','amount of ice melt refrozen in the ice column [m/yr ice eq]')) - string="%s\n%s"%(string,fielddisplay(self,'isclimatology','repeat all forcings when past last forcing time (default false)')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) + self.requested_outputs = [] + #}}} + + def __repr__(self): # {{{ + string = " surface forcings parameters with melt (SMB = accumulation - evaporation - melt + refreeze) :" + string = "%s\n%s" % (string, fielddisplay(self, 'accumulation', 'accumulated snow [m / yr ice eq]')) + string = "%s\n%s" % (string, fielddisplay(self, 'evaporation', 'mount of ice lost to evaporative processes [m / yr ice eq]')) + string = "%s\n%s" % (string, fielddisplay(self, 'melt', 'amount of ice melt in the ice column [m / yr ice eq]')) + string = "%s\n%s" % (string, fielddisplay(self, 'refreeze', 'amount of ice melt refrozen in the ice column [m / yr ice eq]')) + string = "%s\n%s" % (string, fielddisplay(self, 'isclimatology', 'repeat all forcings when past last forcing time (default false)')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) return string - #}}} - def extrude(self,md): # {{{ + #}}} - self.accumulation=project3d(md,'vector',self.accumulation,'type','node'); - self.evaporation=project3d(md,'vector',self.evaporation,'type','node'); - self.melt=project3d(md,'vector',self.melt,'type','node'); - self.refreeze=project3d(md,'vector',self.refreeze,'type','node'); + def extrude(self, md): # {{{ + self.accumulation = project3d(md, 'vector', self.accumulation, 'type', 'node') + self.evaporation = project3d(md, 'vector', self.evaporation, 'type', 'node') + self.melt = project3d(md, 'vector', self.melt, 'type', 'node') + self.refreeze = project3d(md, 'vector', self.refreeze, 'type', 'node') return self #}}} - def defaultoutputs(self,md): # {{{ + + def defaultoutputs(self, md): # {{{ return [] #}}} - def initialize(self,md): # {{{ + def initialize(self, md): # {{{ if np.all(np.isnan(self.accumulation)): - self.accumulation=np.zeros((md.mesh.numberofvertices)) + self.accumulation = np.zeros((md.mesh.numberofvertices)) print(" no SMB.accumulation specified: values set as zero") if np.all(np.isnan(self.evaporation)): - self.evaporation=np.zeros((md.mesh.numberofvertices)) + self.evaporation = np.zeros((md.mesh.numberofvertices)) print(" no SMB.evaporation specified: values set as zero") if np.all(np.isnan(self.melt)): - self.melt=np.zeros((md.mesh.numberofvertices)) + self.melt = np.zeros((md.mesh.numberofvertices)) print(" no SMB.melt specified: values set as zero") if np.all(np.isnan(self.refreeze)): - self.refreeze=np.zeros((md.mesh.numberofvertices)) + self.refreeze = np.zeros((md.mesh.numberofvertices)) print(" no SMB.refreeze specified: values set as zero") return self #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + + def checkconsistency(self, md, solution, analyses): # {{{ + if 'MasstransportAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'smb.accumulation', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + + if 'BalancethicknessAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'smb.accumulation', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.accumulation','timeseries',1,'NaN',1,'Inf',1) + md = checkfield(md, 'fieldname', 'smb.melt', 'timeseries', 1, 'NaN', 1, 'Inf', 1) if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.accumulation','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) + md = checkfield(md, 'fieldname', 'smb.melt', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.melt','timeseries',1,'NaN',1,'Inf',1) + md = checkfield(md, 'fieldname', 'smb.refreeze', 'timeseries', 1, 'NaN', 1, 'Inf', 1) if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.melt','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) + md = checkfield(md, 'fieldname', 'smb.refreeze', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.refreeze','timeseries',1,'NaN',1,'Inf',1) + md = checkfield(md, 'fieldname', 'smb.evaporation', 'timeseries', 1, 'NaN', 1, 'Inf', 1) if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.refreeze','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) + md = checkfield(md, 'fieldname', 'smb.evaporation', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) - if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.evaporation','timeseries',1,'NaN',1,'Inf',1) - - if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.evaporation','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - - md = checkfield(md,'fieldname','masstransport.requested_outputs','stringrow',1) - md = checkfield(md,'fieldname','smb.isclimatology','values',[0,1]) + md = checkfield(md, 'fieldname', 'masstransport.requested_outputs', 'stringrow', 1) + md = checkfield(md, 'fieldname', 'smb.isclimatology', 'values', [0, 1]) return md # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts - WriteData(fid,prefix,'name','md.smb.model','data',3,'format','Integer'); - WriteData(fid,prefix,'object',self,'class','smb','fieldname','accumulation','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','evaporation','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','melt','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','refreeze','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) + WriteData(fid, prefix, 'name', 'md.smb.model', 'data', 3, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'accumulation', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'evaporation', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'melt', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'refreeze', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) - #process requested outputs + #process requested outputs outputs = self.requested_outputs indices = [i for i, x in enumerate(outputs) if x == 'default'] if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.smb.requested_outputs','format','StringArray') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','isclimatology','format','Boolean') - if (self.isclimatology>0): - md = checkfield(md,'fieldname', 'smb.accumulation', 'size',[md.mesh.numberofvertices+1],'message','accumulation must have md.mesh.numberofvertices+1 rows in order to force a climatology') - md = checkfield(md,'fieldname', 'smb.melt', 'size',[md.mesh.numberofvertices+1],'message','melt must have md.mesh.numberofvertices+1 rows in order to force a climatology') - md = checkfield(md,'fieldname', 'smb.refreeze', 'size',[md.mesh.numberofvertices+1],'message','refreeze must have md.mesh.numberofvertices+1 rows in order to force a climatology') - md = checkfield(md,'fieldname', 'smb.evaporation', 'size',[md.mesh.numberofvertices+1],'message','evaporation must have md.mesh.numberofvertices+1 rows in order to force a climatology') + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.smb.requested_outputs', 'format', 'StringArray') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isclimatology', 'format', 'Boolean') + if (self.isclimatology > 0): + md = checkfield(md, 'fieldname', 'smb.accumulation', 'size', [md.mesh.numberofvertices + 1], 'message', 'accumulation must have md.mesh.numberofvertices + 1 rows in order to force a climatology') + md = checkfield(md, 'fieldname', 'smb.melt', 'size', [md.mesh.numberofvertices + 1], 'message', 'melt must have md.mesh.numberofvertices + 1 rows in order to force a climatology') + md = checkfield(md, 'fieldname', 'smb.refreeze', 'size', [md.mesh.numberofvertices + 1], 'message', 'refreeze must have md.mesh.numberofvertices + 1 rows in order to force a climatology') + md = checkfield(md, 'fieldname', 'smb.evaporation', 'size', [md.mesh.numberofvertices + 1], 'message', 'evaporation must have md.mesh.numberofvertices + 1 rows in order to force a climatology') # }}} Index: /issm/trunk-jpl/src/m/classes/SMBpdd.py =================================================================== --- /issm/trunk-jpl/src/m/classes/SMBpdd.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/SMBpdd.py (revision 24213) @@ -5,191 +5,201 @@ from project3d import project3d + class SMBpdd(object): - """ - SMBpdd Class definition - - Usage: - SMBpdd=SMBpdd(); - """ - - def __init__(self): # {{{ - self.precipitation = float('NaN') - self.monthlytemperatures = float('NaN') - self.desfac = 0. - self.s0p = float('NaN') - self.s0t = float('NaN') - self.rlaps = 0. - self.rlapslgm = 0. - self.Pfac = float('NaN') - self.Tdiff = float('NaN') - self.sealev = float('NaN') - self.isdelta18o = 0 - self.ismungsm = 0 - self.issetpddfac = 0 - self.delta18o = float('NaN') - self.delta18o_surface = float('NaN') - self.temperatures_presentday = float('NaN') - self.temperatures_lgm = float('NaN') - self.precipitations_presentday = float('NaN') - self.precipitations_lgm = float('NaN') - - #set defaults - self.setdefaultparameters() - self.requested_outputs = [] - #}}} - def __repr__(self): # {{{ - string=" surface forcings parameters:" - - string="%s\n%s"%(string,fielddisplay(self,'isdelta18o','is temperature and precipitation delta18o parametrisation activated (0 or 1, default is 0)')) - string="%s\n%s"%(string,fielddisplay(self,'ismungsm','is temperature and precipitation mungsm parametrisation activated (0 or 1, default is 0)')) - string="%s\n%s"%(string,fielddisplay(self,'desfac','desertification elevation factor (between 0 and 1, default is 0.5) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'s0p','should be set to elevation from precip source (between 0 and a few 1000s m, default is 0) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'s0t','should be set to elevation from temperature source (between 0 and a few 1000s m, default is 0) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'rlaps','present day lapse rate [degree/km]')) - string="%s\n%s"%(string,fielddisplay(self,'rlapslgm','LGM lapse rate [degree/km]')) - if not (self.isdelta18o and self.ismungsm): - string="%s\n%s"%(string,fielddisplay(self,'monthlytemperatures',['monthly surface temperatures [K], required if pdd is activated and delta18o not activated'])) - string="%s\n%s"%(string,fielddisplay(self,'precipitation',['monthly surface precipitation [m/yr water eq], required if pdd is activated and delta18o or mungsm not activated'])) - if self.isdelta18o: - string="%s\n%s"%(string,fielddisplay(self,'delta18o','delta18o [per mil], required if pdd is activated and delta18o activated')) - string="%s\n%s"%(string,fielddisplay(self,'delta18o_surface','surface elevation of the delta18o site, required if pdd is activated and delta18o activated')) - string="%s\n%s"%(string,fielddisplay(self,'temperatures_presentday','monthly present day surface temperatures [K], required if delta18o/mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'temperatures_lgm','monthly LGM surface temperatures [K], required if delta18o or mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'precipitations_presentday','monthly surface precipitation [m/yr water eq], required if delta18o or mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'precipitations_lgm','monthly surface precipitation [m/yr water eq], required if delta18o or mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'Tdiff','time interpolation parameter for temperature, 1D(year), required if mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'sealev','sea level [m], 1D(year), required if mungsm is activated')) - if self.ismungsm: - string="%s\n%s"%(string,fielddisplay(self,'temperatures_presentday','monthly present day surface temperatures [K], required if delta18o/mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'temperatures_lgm','monthly LGM surface temperatures [K], required if delta18o or mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'precipitations_presentday','monthly surface precipitation [m/yr water eq], required if delta18o or mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'precipitations_lgm','monthly surface precipitation [m/yr water eq], required if delta18o or mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'Pfac','time interpolation parameter for precipitation, 1D(year), required if mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'Tdiff','time interpolation parameter for temperature, 1D(year), required if mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'sealev','sea level [m], 1D(year), required if mungsm is activated')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) - - return string - # }}} - def extrude(self,md): # {{{ - - if not (self.isdelta18o and self.ismungsm): - self.precipitation=project3d(md,'vector',self.precipitation,'type','node') - self.monthlytemperatures=project3d(md,'vector',self.monthlytemperatures,'type','node') - if self.isdelta18o: self.temperatures_lgm=project3d(md,'vector',self.temperatures_lgm,'type','node') - if self.isdelta18o: self.temperatures_presentday=project3d(md,'vector',self.temperatures_presentday,'type','node') - if self.isdelta18o: self.precipitations_presentday=project3d(md,'vector',self.precipitations_presentday,'type','node') - if self.isdelta18o: self.precipitations_lgm=project3d(md,'vector',self.precipitations_lgm,'type','node') - if self.ismungsm: self.temperatures_lgm=project3d(md,'vector',self.temperatures_lgm,'type','node') - if self.ismungsm: self.temperatures_presentday=project3d(md,'vector',self.temperatures_presentday,'type','node') - if self.ismungsm: self.precipitations_presentday=project3d(md,'vector',self.precipitations_presentday,'type','node') - if self.ismungsm: self.precipitations_lgm=project3d(md,'vector',self.precipitations_lgm,'type','node') - self.s0p=project3d(md,'vector',self.s0p,'type','node') - self.s0t=project3d(md,'vector',self.s0t,'type','node') - - return self - #}}} - def defaultoutputs(self,md): # {{{ - return [] - #}}} - def initialize(self,md): # {{{ - - if np.all(np.isnan(self.s0p)): - self.s0p=np.zeros((md.mesh.numberofvertices)) - print(" no SMBpdd.s0p specified: values set as zero") - - if np.all(np.isnan(self.s0t)): - self.s0t=np.zeros((md.mesh.numberofvertices)) - print(" no SMBpdd.s0t specified: values set as zero") - - return self - #}}} - def setdefaultparameters(self): # {{{ - - #pdd method not used in default mode - self.isdelta18o = 0 - self.ismungsm = 0 - self.desfac = 0.5 - self.rlaps = 6.5 - self.rlapslgm = 6.5 - - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - - if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.desfac','<=',1,'numel',[1]) - md = checkfield(md,'fieldname','smb.s0p','>=',0,'NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','smb.s0t','>=',0,'NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','smb.rlaps','>=',0,'numel',[1]) - md = checkfield(md,'fieldname','smb.rlapslgm','>=',0,'numel',[1]) - - if (self.isdelta18o==0 and self.ismungsm==0): - md = checkfield(md,'fieldname','smb.monthlytemperatures','NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','smb.precipitation','NaN',1,'Inf',1,'timeseries',1) - elif self.isdelta18o: - md = checkfield(md,'fieldname','smb.delta18o','NaN',1,'Inf',1,'size',[2,np.nan],'singletimeseries',1) - md = checkfield(md,'fieldname','smb.delta18o_surface','NaN',1,'Inf',1,'size',[2,np.nan],'singletimeseries',1) - md = checkfield(md,'fieldname','smb.temperatures_presentday','size',[md.mesh.numberofvertices+1,12],'NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','smb.temperatures_lgm','size',[md.mesh.numberofvertices+1,12],'NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','smb.precipitations_presentday','size',[md.mesh.numberofvertices+1,12],'NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','smb.precipitations_lgm','size',[md.mesh.numberofvertices+1,12],'NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','smb.Tdiff','NaN',1,'Inf',1,'size',[2,np.nan],'singletimeseries',1) - md = checkfield(md,'fieldname','smb.sealev','NaN',1,'Inf',1,'size',[2,np.nan],'singletimeseries',1) - elif self.ismungsm: - md = checkfield(md,'fieldname','smb.temperatures_presentday','size',[md.mesh.numberofvertices+1,12],'NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','smb.temperatures_lgm','size',[md.mesh.numberofvertices+1,12],'NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','smb.precipitations_presentday','size',[md.mesh.numberofvertices+1,12],'NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','smb.precipitations_lgm','size',[md.mesh.numberofvertices+1,12],'NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','smb.Pfac','NaN',1,'Inf',1,'size',[2,np.nan],'singletimeseries',1) - md = checkfield(md,'fieldname','smb.Tdiff','NaN',1,'Inf',1,'size',[2,np.nan],'singletimeseries',1) - md = checkfield(md,'fieldname','smb.sealev','NaN',1,'Inf',1,'size',[2,np.nan],'singletimeseries',1) - - md = checkfield(md,'fieldname','masstransport.requested_outputs','stringrow',1) - return md - #}}} - def marshall(self,prefix,md,fid): # {{{ - - yts=md.constants.yts - - WriteData(fid,prefix,'name','md.smb.model','data',4,'format','Integer') - - WriteData(fid,prefix,'object',self,'class','smb','fieldname','isdelta18o','format','Boolean') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','ismungsm','format','Boolean') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','issetpddfac','format','Boolean'); - WriteData(fid,prefix,'object',self,'class','smb','fieldname','desfac','format','Double') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','s0p','format','DoubleMat','mattype',1); - WriteData(fid,prefix,'object',self,'class','smb','fieldname','s0t','format','DoubleMat','mattype',1); - WriteData(fid,prefix,'object',self,'class','smb','fieldname','rlaps','format','Double') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','rlapslgm','format','Double') - - if (self.isdelta18o==0 and self.ismungsm==0): - WriteData(fid,prefix,'object',self,'class','smb','fieldname','monthlytemperatures','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','precipitation','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - elif self.isdelta18o: - WriteData(fid,prefix,'object',self,'class','smb','fieldname','temperatures_presentday','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','temperatures_lgm','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','precipitations_presentday','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','precipitations_lgm','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','delta18o_surface','format','DoubleMat','mattype',1,'timeserieslength',2,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','delta18o','format','DoubleMat','mattype',1,'timeserieslength',2,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','Tdiff','format','DoubleMat','mattype',1,'timeserieslength',2,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','sealev','format','DoubleMat','mattype',1,'timeserieslength',2,'yts',md.constants.yts) - elif self.ismungsm: - WriteData(fid,prefix,'object',self,'class','smb','fieldname','temperatures_presentday','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','temperatures_lgm','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','precipitations_presentday','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','precipitations_lgm','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','Pfac','format','DoubleMat','mattype',1,'timeserieslength',2,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','Tdiff','format','DoubleMat','mattype',1,'timeserieslength',2,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','sealev','format','DoubleMat','mattype',1,'timeserieslength',2,'yts',md.constants.yts) - - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.smb.requested_outputs','format','StringArray') - - # }}} + """ + SMBpdd Class definition + + Usage: + SMBpdd = SMBpdd() + """ + + def __init__(self): # {{{ + self.precipitation = float('NaN') + self.monthlytemperatures = float('NaN') + self.desfac = 0. + self.s0p = float('NaN') + self.s0t = float('NaN') + self.rlaps = 0. + self.rlapslgm = 0. + self.Pfac = float('NaN') + self.Tdiff = float('NaN') + self.sealev = float('NaN') + self.isdelta18o = 0 + self.ismungsm = 0 + self.issetpddfac = 0 + self.delta18o = float('NaN') + self.delta18o_surface = float('NaN') + self.temperatures_presentday = float('NaN') + self.temperatures_lgm = float('NaN') + self.precipitations_presentday = float('NaN') + self.precipitations_lgm = float('NaN') + + #set defaults + self.setdefaultparameters() + self.requested_outputs = [] + #}}} + + def __repr__(self): # {{{ + string = " surface forcings parameters:" + + string = "%s\n%s" % (string, fielddisplay(self, 'isdelta18o', 'is temperature and precipitation delta18o parametrisation activated (0 or 1, default is 0)')) + string = "%s\n%s" % (string, fielddisplay(self, 'ismungsm', 'is temperature and precipitation mungsm parametrisation activated (0 or 1, default is 0)')) + string = "%s\n%s" % (string, fielddisplay(self, 'desfac', 'desertification elevation factor (between 0 and 1, default is 0.5) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 's0p', 'should be set to elevation from precip source (between 0 and a few 1000s m, default is 0) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 's0t', 'should be set to elevation from temperature source (between 0 and a few 1000s m, default is 0) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'rlaps', 'present day lapse rate [degree / km]')) + string = "%s\n%s" % (string, fielddisplay(self, 'rlapslgm', 'LGM lapse rate [degree / km]')) + if not (self.isdelta18o and self.ismungsm): + string = "%s\n%s" % (string, fielddisplay(self, 'monthlytemperatures', ['monthly surface temperatures [K], required if pdd is activated and delta18o not activated'])) + string = "%s\n%s" % (string, fielddisplay(self, 'precipitation', ['monthly surface precipitation [m / yr water eq], required if pdd is activated and delta18o or mungsm not activated'])) + if self.isdelta18o: + string = "%s\n%s" % (string, fielddisplay(self, 'delta18o', 'delta18o [per mil], required if pdd is activated and delta18o activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'delta18o_surface', 'surface elevation of the delta18o site, required if pdd is activated and delta18o activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'temperatures_presentday', 'monthly present day surface temperatures [K], required if delta18o / mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'temperatures_lgm', 'monthly LGM surface temperatures [K], required if delta18o or mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'precipitations_presentday', 'monthly surface precipitation [m / yr water eq], required if delta18o or mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'precipitations_lgm', 'monthly surface precipitation [m / yr water eq], required if delta18o or mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'Tdiff', 'time interpolation parameter for temperature, 1D(year), required if mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'sealev', 'sea level [m], 1D(year), required if mungsm is activated')) + if self.ismungsm: + string = "%s\n%s" % (string, fielddisplay(self, 'temperatures_presentday', 'monthly present day surface temperatures [K], required if delta18o / mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'temperatures_lgm', 'monthly LGM surface temperatures [K], required if delta18o or mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'precipitations_presentday', 'monthly surface precipitation [m / yr water eq], required if delta18o or mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'precipitations_lgm', 'monthly surface precipitation [m / yr water eq], required if delta18o or mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'Pfac', 'time interpolation parameter for precipitation, 1D(year), required if mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'Tdiff', 'time interpolation parameter for temperature, 1D(year), required if mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'sealev', 'sea level [m], 1D(year), required if mungsm is activated')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) + + return string + # }}} + + def extrude(self, md): # {{{ + if not (self.isdelta18o and self.ismungsm): + self.precipitation = project3d(md, 'vector', self.precipitation, 'type', 'node') + self.monthlytemperatures = project3d(md, 'vector', self.monthlytemperatures, 'type', 'node') + if self.isdelta18o: + self.temperatures_lgm = project3d(md, 'vector', self.temperatures_lgm, 'type', 'node') + if self.isdelta18o: + self.temperatures_presentday = project3d(md, 'vector', self.temperatures_presentday, 'type', 'node') + if self.isdelta18o: + self.precipitations_presentday = project3d(md, 'vector', self.precipitations_presentday, 'type', 'node') + if self.isdelta18o: + self.precipitations_lgm = project3d(md, 'vector', self.precipitations_lgm, 'type', 'node') + if self.ismungsm: + self.temperatures_lgm = project3d(md, 'vector', self.temperatures_lgm, 'type', 'node') + if self.ismungsm: + self.temperatures_presentday = project3d(md, 'vector', self.temperatures_presentday, 'type', 'node') + if self.ismungsm: + self.precipitations_presentday = project3d(md, 'vector', self.precipitations_presentday, 'type', 'node') + if self.ismungsm: + self.precipitations_lgm = project3d(md, 'vector', self.precipitations_lgm, 'type', 'node') + self.s0p = project3d(md, 'vector', self.s0p, 'type', 'node') + self.s0t = project3d(md, 'vector', self.s0t, 'type', 'node') + + return self + #}}} + + def defaultoutputs(self, md): # {{{ + return [] + #}}} + + def initialize(self, md): # {{{ + if np.all(np.isnan(self.s0p)): + self.s0p = np.zeros((md.mesh.numberofvertices)) + print(" no SMBpdd.s0p specified: values set as zero") + + if np.all(np.isnan(self.s0t)): + self.s0t = np.zeros((md.mesh.numberofvertices)) + print(" no SMBpdd.s0t specified: values set as zero") + + return self + #}}} + + def setdefaultparameters(self): # {{{ + #pdd method not used in default mode + self.isdelta18o = 0 + self.ismungsm = 0 + self.desfac = 0.5 + self.rlaps = 6.5 + self.rlapslgm = 6.5 + + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + if 'MasstransportAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'smb.desfac', '<=', 1, 'numel', [1]) + md = checkfield(md, 'fieldname', 'smb.s0p', '>=', 0, 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'smb.s0t', '>=', 0, 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'smb.rlaps', '>=', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'smb.rlapslgm', '>=', 0, 'numel', [1]) + + if (self.isdelta18o == 0 and self.ismungsm == 0): + md = checkfield(md, 'fieldname', 'smb.monthlytemperatures', 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'smb.precipitation', 'NaN', 1, 'Inf', 1, 'timeseries', 1) + elif self.isdelta18o: + md = checkfield(md, 'fieldname', 'smb.delta18o', 'NaN', 1, 'Inf', 1, 'size', [2, np.nan], 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'smb.delta18o_surface', 'NaN', 1, 'Inf', 1, 'size', [2, np.nan], 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'smb.temperatures_presentday', 'size', [md.mesh.numberofvertices + 1, 12], 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'smb.temperatures_lgm', 'size', [md.mesh.numberofvertices + 1, 12], 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'smb.precipitations_presentday', 'size', [md.mesh.numberofvertices + 1, 12], 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'smb.precipitations_lgm', 'size', [md.mesh.numberofvertices + 1, 12], 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'smb.Tdiff', 'NaN', 1, 'Inf', 1, 'size', [2, np.nan], 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'smb.sealev', 'NaN', 1, 'Inf', 1, 'size', [2, np.nan], 'singletimeseries', 1) + elif self.ismungsm: + md = checkfield(md, 'fieldname', 'smb.temperatures_presentday', 'size', [md.mesh.numberofvertices + 1, 12], 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'smb.temperatures_lgm', 'size', [md.mesh.numberofvertices + 1, 12], 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'smb.precipitations_presentday', 'size', [md.mesh.numberofvertices + 1, 12], 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'smb.precipitations_lgm', 'size', [md.mesh.numberofvertices + 1, 12], 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'smb.Pfac', 'NaN', 1, 'Inf', 1, 'size', [2, np.nan], 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'smb.Tdiff', 'NaN', 1, 'Inf', 1, 'size', [2, np.nan], 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'smb.sealev', 'NaN', 1, 'Inf', 1, 'size', [2, np.nan], 'singletimeseries', 1) + + md = checkfield(md, 'fieldname', 'masstransport.requested_outputs', 'stringrow', 1) + return md + #}}} + + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + + WriteData(fid, prefix, 'name', 'md.smb.model', 'data', 4, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isdelta18o', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'ismungsm', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'issetpddfac', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'desfac', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 's0p', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 's0t', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'rlaps', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'rlapslgm', 'format', 'Double') + + if (self.isdelta18o == 0 and self.ismungsm == 0): + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'monthlytemperatures', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'precipitation', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + elif self.isdelta18o: + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'temperatures_presentday', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'temperatures_lgm', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'precipitations_presentday', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'precipitations_lgm', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'delta18o_surface', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', 2, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'delta18o', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', 2, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Tdiff', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', 2, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'sealev', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', 2, 'yts', yts) + elif self.ismungsm: + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'temperatures_presentday', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'temperatures_lgm', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'precipitations_presentday', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'precipitations_lgm', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Pfac', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', 2, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'Tdiff', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', 2, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'sealev', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', 2, 'yts', yts) + + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.smb.requested_outputs', 'format', 'StringArray') + + # }}} Index: /issm/trunk-jpl/src/m/classes/SMBpddSicopolis.py =================================================================== --- /issm/trunk-jpl/src/m/classes/SMBpddSicopolis.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/SMBpddSicopolis.py (revision 24213) @@ -7,147 +7,143 @@ from helpers import * + class SMBpddSicopolis(object): - """ - SMBpddSicopolis Class definition + """ + SMBpddSicopolis Class definition - Usage: - SMBpddSicopolis=SMBpddSicopolis() + Usage: + SMBpddSicopolis = SMBpddSicopolis() """ - def __init__(self): # {{{ - self.precipitation = float('NaN') - self.monthlytemperatures = float('NaN') - self.temperature_anomaly = float('NaN') - self.precipitation_anomaly = float('NaN') - self.smb_corr = float('NaN') - self.desfac = 0 - self.s0p = float('NaN') - self.s0t = float('NaN') - self.rlaps = 0 - self.isfirnwarming = 0 - self.requested_outputs = [] - - self.setdefaultparameters() - # }}} - - @staticmethod - def SMBpddSicopolis(*args): # {{{ - nargin = len(args) + def __init__(self): # {{{ + self.precipitation = float('NaN') + self.monthlytemperatures = float('NaN') + self.temperature_anomaly = float('NaN') + self.precipitation_anomaly = float('NaN') + self.smb_corr = float('NaN') + self.desfac = 0 + self.s0p = float('NaN') + self.s0t = float('NaN') + self.rlaps = 0 + self.isfirnwarming = 0 + self.requested_outputs = [] - if nargin == 0: - return SMBpddSicopolis() - else: - raise RuntimeError('SMBpddSicopolis: constructor not supported') - # }}} + self.setdefaultparameters() + # }}} - def extrude(self,md): # {{{ - self.precipitation = project3d(md,'vector',self.precipitation,'type','node') - self.monthlytemperatures = project3d(md,'vector',self.monthlytemperatures,'type','node') - self.temperature_anomaly = project3d(md,'vector',self.temperature_anomaly,'type','node') - self.precipitation_anomaly = project3d(md,'vector',self.precipitation_anomaly,'type','node') - self.smb_corr = project3d(md,'vector',self.smb_corr,'type','node') - self.s0p = project3d(md,'vector',self.s0p,'type','node') - self.s0t = project3d(md,'vector',self.s0t,'type','node') - # }}} + @staticmethod + def SMBpddSicopolis(*args): # {{{ + nargin = len(args) - def defaultoutputs(self,md): # {{{ - l = [''] - return l - # }}} + if nargin == 0: + return SMBpddSicopolis() + else: + raise RuntimeError('SMBpddSicopolis: constructor not supported') + # }}} - def initialize(self,md): # {{{ - - if np.isnan(self.s0p): - self.s0p = np.zeros((md.mesh.numberofvertices,)) - print(' no SMBpddSicopolis.s0p specified: values set as zero') - - if np.isnan(self.s0t): - self.s0t = np.zeros((md.mesh.numberofvertices,)) - print(' no SMBpddSicopolis.s0t specified: values set as zero') - - if np.isnan(self.temperature_anomaly): - self.temperature_anomaly = np.zeros((md.mesh.numberofvertices,)) - print(' no SMBpddSicopolis.temperature_anomaly specified: values set as zero') - - if np.isnan(self.precipitation_anomaly): - self.precipitation_anomaly = np.ones((md.mesh.numberofvertices,)) - print(' no SMBpddSicopolis.precipitation_anomaly specified: values set as ones') - - if np.isnan(self.smb_corr): - self.smb_corr = np.zeros((md.mesh.numberofvertices,)) - print(' no SMBpddSicopolis.smb_corr specified: values set as zero') - # }}} + def extrude(self, md): # {{{ + self.precipitation = project3d(md, 'vector', self.precipitation, 'type', 'node') + self.monthlytemperatures = project3d(md, 'vector', self.monthlytemperatures, 'type', 'node') + self.temperature_anomaly = project3d(md, 'vector', self.temperature_anomaly, 'type', 'node') + self.precipitation_anomaly = project3d(md, 'vector', self.precipitation_anomaly, 'type', 'node') + self.smb_corr = project3d(md, 'vector', self.smb_corr, 'type', 'node') + self.s0p = project3d(md, 'vector', self.s0p, 'type', 'node') + self.s0t = project3d(md, 'vector', self.s0t, 'type', 'node') + # }}} - def setdefaultparameters(self): # {{{ + def defaultoutputs(self, md): # {{{ + listing = [''] + return listing + # }}} - self.isfirnwarming = 1 - self.desfac = -np.log(2.0)/1000 - self.rlaps = 7.4 - - # }}} + def initialize(self, md): # {{{ - def checkconsistency(self,md,solution,analyses): # {{{ + if np.isnan(self.s0p): + self.s0p = np.zeros((md.mesh.numberofvertices, )) + print(' no SMBpddSicopolis.s0p specified: values set as zero') - if (strcmp(solution,'TransientSolution') and md.transient.issmb == 0): - return + if np.isnan(self.s0t): + self.s0t = np.zeros((md.mesh.numberofvertices, )) + print(' no SMBpddSicopolis.s0t specified: values set as zero') - if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','smb.desfac','<=',1,'numel',1) - md = checkfield(md,'fieldname','smb.s0p','>=',0,'NaN',1,'Inf',1,'size',[md.mesh.numberofvertices,1]) - md = checkfield(md,'fieldname','smb.s0t','>=',0,'NaN',1,'Inf',1,'size',[md.mesh.numberofvertices,1]) - md = checkfield(md,'fieldname','smb.rlaps','>=',0,'numel',1) - md = checkfield(md,'fieldname','smb.monthlytemperatures','timeseries',1,'NaN',1,'Inf',1,'size',[md.mesh.numberofvertices+1,12]) - md = checkfield(md,'fieldname','smb.precipitation','timeseries',1,'NaN',1,'Inf',1,'size',[md.mesh.numberofvertices+1,12]) - - md = checkfield(md,'fieldname','smb.requested_outputs','stringrow',1) - - return md - # }}} + if np.isnan(self.temperature_anomaly): + self.temperature_anomaly = np.zeros((md.mesh.numberofvertices, )) + print(' no SMBpddSicopolis.temperature_anomaly specified: values set as zero') - def __repr__(self): # {{{ - string = ' surface forcings parameters:' - string += '\n SICOPOLIS PDD scheme (Calov & Greve, 2005) :' + if np.isnan(self.precipitation_anomaly): + self.precipitation_anomaly = np.ones((md.mesh.numberofvertices, )) + print(' no SMBpddSicopolis.precipitation_anomaly specified: values set as ones') - string = "%s\n%s"%(string,fielddisplay(self,'monthlytemperatures','monthly surface temperatures [K]')) - string = "%s\n%s"%(string,fielddisplay(self,'precipitation','monthly surface precipitation [m/yr water eq]')) - string = "%s\n%s"%(string,fielddisplay(self,'temperature_anomaly','anomaly to monthly reference temperature (additive [K])')) - string = "%s\n%s"%(string,fielddisplay(self,'precipitation_anomaly','anomaly to monthly precipitation (multiplicative, e.g. q=q0*exp(0.070458*DeltaT) after Huybrechts (2002)) [no unit])')) - string = "%s\n%s"%(string,fielddisplay(self,'smb_corr','correction of smb after PDD call [m/a]')) - string = "%s\n%s"%(string,fielddisplay(self,'s0p','should be set to elevation from precip source (between 0 and a few 1000s m, default is 0) [m]')) - string = "%s\n%s"%(string,fielddisplay(self,'s0t','should be set to elevation from temperature source (between 0 and a few 1000s m, default is 0) [m]')) - string = "%s\n%s"%(string,fielddisplay(self,'rlaps','present day lapse rate (default is 7.4 degree/km)')) - string = "%s\n%s"%(string,fielddisplay(self,'desfac','desertification elevation factor (default is -log(2.0)/1000)')) - string = "%s\n%s"%(string,fielddisplay(self,'isfirnwarming','is firnwarming (Reeh 1991) activated (0 or 1, default is 1)')) - string = "%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested (TemperaturePDD, SmbAccumulation, SmbMelt)')) - # }}} + if np.isnan(self.smb_corr): + self.smb_corr = np.zeros((md.mesh.numberofvertices, )) + print(' no SMBpddSicopolis.smb_corr specified: values set as zero') + # }}} - def marshall(self,prefix,md,fid): # {{{ + def setdefaultparameters(self): # {{{ + self.isfirnwarming = 1 + self.desfac = - np.log(2.0) / 1000 + self.rlaps = 7.4 - yts=md.constants.yts + # }}} - WriteData(fid,prefix,'name','md.smb.model','data',10,'format','Integer') + def checkconsistency(self, md, solution, analyses): # {{{ + if (strcmp(solution, 'TransientSolution') and md.transient.issmb == 0): + return - WriteData(fid,prefix,'object',self,'class','smb','fieldname','isfirnwarming','format','Boolean') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','desfac','format','Double') - WriteData(fid,prefix,'object',self,'class','smb','fieldname','s0p','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','s0t','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','rlaps','format','Double') + if 'MasstransportAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'smb.desfac', '<=', 1, 'numel', 1) + md = checkfield(md, 'fieldname', 'smb.s0p', '>=', 0, 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices, 1]) + md = checkfield(md, 'fieldname', 'smb.s0t', '>=', 0, 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices, 1]) + md = checkfield(md, 'fieldname', 'smb.rlaps', '>=', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'smb.monthlytemperatures', 'timeseries', 1, 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices + 1, 12]) + md = checkfield(md, 'fieldname', 'smb.precipitation', 'timeseries', 1, 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices + 1, 12]) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','monthlytemperatures','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','precipitation','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','temperature_anomaly','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','precipitation_anomaly','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','smb','fieldname','smb_corr','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) + md = checkfield(md, 'fieldname', 'smb.requested_outputs', 'stringrow', 1) - #process requested outputs - outputs = self.requested_outputs - pos = np.where('default' in outputs) - if not isempty(pos): - outputs[pos] = [] #remove 'default' from outputs - outputs = [outputs,defaultoutputs(self,md)] #add defaults - - WriteData(fid,prefix,'data',outputs,'name','md.smb.requested_outputs','format','StringArray') + return md + # }}} - # }}} - + def __repr__(self): # {{{ + string = ' surface forcings parameters:' + string += '\n SICOPOLIS PDD scheme (Calov & Greve, 2005) :' + string = "%s\n%s" % (string, fielddisplay(self, 'monthlytemperatures', 'monthly surface temperatures [K]')) + string = "%s\n%s" % (string, fielddisplay(self, 'precipitation', 'monthly surface precipitation [m / yr water eq]')) + string = "%s\n%s" % (string, fielddisplay(self, 'temperature_anomaly', 'anomaly to monthly reference temperature (additive [K])')) + string = "%s\n%s" % (string, fielddisplay(self, 'precipitation_anomaly', 'anomaly to monthly precipitation (multiplicative, e.g. q = q0 * exp(0.070458 * DeltaT) after Huybrechts (2002)) [no unit])')) + string = "%s\n%s" % (string, fielddisplay(self, 'smb_corr', 'correction of smb after PDD call [m / a]')) + string = "%s\n%s" % (string, fielddisplay(self, 's0p', 'should be set to elevation from precip source (between 0 and a few 1000s m, default is 0) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 's0t', 'should be set to elevation from temperature source (between 0 and a few 1000s m, default is 0) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'rlaps', 'present day lapse rate (default is 7.4 degree / km)')) + string = "%s\n%s" % (string, fielddisplay(self, 'desfac', 'desertification elevation factor (default is - log(2.0) / 1000)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isfirnwarming', 'is firnwarming (Reeh 1991) activated (0 or 1, default is 1)')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested (TemperaturePDD, SmbAccumulation, SmbMelt)')) + # }}} + + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + + WriteData(fid, prefix, 'name', 'md.smb.model', 'data', 10, 'format', 'Integer') + + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'isfirnwarming', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'desfac', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 's0p', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 's0t', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'rlaps', 'format', 'Double') + + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'monthlytemperatures', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'precipitation', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'temperature_anomaly', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'precipitation_anomaly', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'smb', 'fieldname', 'smb_corr', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + + #process requested outputs + outputs = self.requested_outputs + pos = np.where('default' in outputs) + if not isempty(pos): + outputs[pos] = [] #remove 'default' from outputs + outputs = [outputs, defaultoutputs(self, md)] #add defaults + + WriteData(fid, prefix, 'data', outputs, 'name', 'md.smb.requested_outputs', 'format', 'StringArray') + + # }}} Index: /issm/trunk-jpl/src/m/classes/amr.py =================================================================== --- /issm/trunk-jpl/src/m/classes/amr.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/amr.py (revision 24213) @@ -2,4 +2,5 @@ from checkfield import checkfield from WriteData import WriteData + class amr(object): @@ -8,114 +9,118 @@ Usage: - amr=amr(); + amr = amr() """ - def __init__(self): # {{{ - self.hmin = 0. - self.hmax = 0. - self.fieldname ='' - self.err = 0. - self.keepmetric = 0. - self.gradation = 0. - self.groundingline_resolution = 0. - self.groundingline_distance = 0. - self.icefront_resolution = 0. - self.icefront_distance = 0. - self.thicknesserror_resolution = 0. - self.thicknesserror_threshold = 0. - self.thicknesserror_groupthreshold = 0. - self.thicknesserror_maximum = 0. - self.deviatoricerror_resolution = 0. - self.deviatoricerror_threshold = 0. - self.deviatoricerror_groupthreshold = 0. - self.deviatoricerror_maximum = 0. - self.restart = 0. - #set defaults + def __init__(self): # {{{ + self.hmin = 0. + self.hmax = 0. + self.fieldname = '' + self.err = 0. + self.keepmetric = 0. + self.gradation = 0. + self.groundingline_resolution = 0. + self.groundingline_distance = 0. + self.icefront_resolution = 0. + self.icefront_distance = 0. + self.thicknesserror_resolution = 0. + self.thicknesserror_threshold = 0. + self.thicknesserror_groupthreshold = 0. + self.thicknesserror_maximum = 0. + self.deviatoricerror_resolution = 0. + self.deviatoricerror_threshold = 0. + self.deviatoricerror_groupthreshold = 0. + self.deviatoricerror_maximum = 0. + self.restart = 0. + #set defaults self.setdefaultparameters() #}}} - def __repr__(self): # {{{ - string=" amr parameters:" - string="%s\n%s"%(string,fielddisplay(self,"hmin","minimum element length")) - string="%s\n%s"%(string,fielddisplay(self,"hmax","maximum element length")) - string="%s\n%s"%(string,fielddisplay(self,"fieldname","name of input that will be used to compute the metric (should be an input of FemModel)")) - string="%s\n%s"%(string,fielddisplay(self,"keepmetric","indicates whether the metric should be kept every remeshing time")) - string="%s\n%s"%(string,fielddisplay(self,"gradation","maximum ratio between two adjacent edges")) - string="%s\n%s"%(string,fielddisplay(self,"groundingline_resolution","element length near the grounding line")) - string="%s\n%s"%(string,fielddisplay(self,"groundingline_distance","distance around the grounding line which elements will be refined")) - string="%s\n%s"%(string,fielddisplay(self,"icefront_resolution","element length near the ice front")) - string="%s\n%s"%(string,fielddisplay(self,"icefront_distance","distance around the ice front which elements will be refined")) - string="%s\n%s"%(string,fielddisplay(self,"thicknesserror_resolution","element length when thickness error estimator is used")) - string="%s\n%s"%(string,fielddisplay(self,"thicknesserror_threshold","maximum threshold thickness error permitted")) - string="%s\n%s"%(string,fielddisplay(self,"thicknesserror_groupthreshold","maximum group threshold thickness error permitted")) - string="%s\n%s"%(string,fielddisplay(self,"thicknesserror_maximum","maximum thickness error permitted")) - string="%s\n%s"%(string,fielddisplay(self,"deviatoricerror_resolution","element length when deviatoric stress error estimator is used")) - string="%s\n%s"%(string,fielddisplay(self,"deviatoricerror_threshold","maximum threshold deviatoricstress error permitted")) - string="%s\n%s"%(string,fielddisplay(self,"deviatoricerror_groupthreshold","maximum group threshold deviatoric stress error permitted")) - string="%s\n%s"%(string,fielddisplay(self,"deviatoricerror_maximum","maximum deviatoricstress error permitted")) - string="%s\n%s"%(string,fielddisplay(self,"restart","indicates if ReMesh() will call before first time step")) + + def __repr__(self): # {{{ + string = " amr parameters:" + string = "%s\n%s" % (string, fielddisplay(self, "hmin", "minimum element length")) + string = "%s\n%s" % (string, fielddisplay(self, "hmax", "maximum element length")) + string = "%s\n%s" % (string, fielddisplay(self, "fieldname", "name of input that will be used to compute the metric (should be an input of FemModel)")) + string = "%s\n%s" % (string, fielddisplay(self, "keepmetric", "indicates whether the metric should be kept every remeshing time")) + string = "%s\n%s" % (string, fielddisplay(self, "gradation", "maximum ratio between two adjacent edges")) + string = "%s\n%s" % (string, fielddisplay(self, "groundingline_resolution", "element length near the grounding line")) + string = "%s\n%s" % (string, fielddisplay(self, "groundingline_distance", "distance around the grounding line which elements will be refined")) + string = "%s\n%s" % (string, fielddisplay(self, "icefront_resolution", "element length near the ice front")) + string = "%s\n%s" % (string, fielddisplay(self, "icefront_distance", "distance around the ice front which elements will be refined")) + string = "%s\n%s" % (string, fielddisplay(self, "thicknesserror_resolution", "element length when thickness error estimator is used")) + string = "%s\n%s" % (string, fielddisplay(self, "thicknesserror_threshold", "maximum threshold thickness error permitted")) + string = "%s\n%s" % (string, fielddisplay(self, "thicknesserror_groupthreshold", "maximum group threshold thickness error permitted")) + string = "%s\n%s" % (string, fielddisplay(self, "thicknesserror_maximum", "maximum thickness error permitted")) + string = "%s\n%s" % (string, fielddisplay(self, "deviatoricerror_resolution", "element length when deviatoric stress error estimator is used")) + string = "%s\n%s" % (string, fielddisplay(self, "deviatoricerror_threshold", "maximum threshold deviatoricstress error permitted")) + string = "%s\n%s" % (string, fielddisplay(self, "deviatoricerror_groupthreshold", "maximum group threshold deviatoric stress error permitted")) + string = "%s\n%s" % (string, fielddisplay(self, "deviatoricerror_maximum", "maximum deviatoricstress error permitted")) + string = "%s\n%s" % (string, fielddisplay(self, "restart", "indicates if ReMesh() will call before first time step")) return string #}}} - def setdefaultparameters(self): # {{{ - self.hmin = 100. - self.hmax = 100.e3 - self.fieldname = 'Vel' - self.err = 3. - self.keepmetric = 1 - self.gradation = 1.5 - self.groundingline_resolution = 500. - self.groundingline_distance = 0 - self.icefront_resolution = 500. - self.icefront_distance = 0 - self.thicknesserror_resolution = 500. - self.thicknesserror_threshold = 0 - self.thicknesserror_groupthreshold = 0 - self.thicknesserror_maximum = 0 - self.deviatoricerror_resolution = 500. - self.deviatoricerror_threshold = 0 - self.deviatoricerror_groupthreshold = 0 - self.deviatoricerror_maximum = 0 - self.restart = 0. + + def setdefaultparameters(self): # {{{ + self.hmin = 100. + self.hmax = 100.e3 + self.fieldname = 'Vel' + self.err = 3. + self.keepmetric = 1 + self.gradation = 1.5 + self.groundingline_resolution = 500. + self.groundingline_distance = 0 + self.icefront_resolution = 500. + self.icefront_distance = 0 + self.thicknesserror_resolution = 500. + self.thicknesserror_threshold = 0 + self.thicknesserror_groupthreshold = 0 + self.thicknesserror_maximum = 0 + self.deviatoricerror_resolution = 500. + self.deviatoricerror_threshold = 0 + self.deviatoricerror_groupthreshold = 0 + self.deviatoricerror_maximum = 0 + self.restart = 0. return self #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - md = checkfield(md,'fieldname','amr.hmax','numel',[1],'>',0,'NaN',1) - md = checkfield(md,'fieldname','amr.hmin','numel',[1],'>',0,'<',self.hmax,'NaN',1) - md = checkfield(md,'fieldname','amr.keepmetric','numel',[1],'>=',0,'<=',1,'NaN',1); - md = checkfield(md,'fieldname','amr.gradation','numel',[1],'>=',1.1,'<=',5,'NaN',1); - md = checkfield(md,'fieldname','amr.groundingline_resolution','numel',[1],'>',0,'<',self.hmax,'NaN',1); - md = checkfield(md,'fieldname','amr.groundingline_distance','numel',[1],'>=',0,'NaN',1,'Inf',1); - md = checkfield(md,'fieldname','amr.icefront_resolution','numel',[1],'>',0,'<',self.hmax,'NaN',1); - md = checkfield(md,'fieldname','amr.icefront_distance','numel',[1],'>=',0,'NaN',1,'Inf',1); - md = checkfield(md,'fieldname','amr.thicknesserror_resolution','numel',[1],'>',0,'<',self.hmax,'NaN',1); - md = checkfield(md,'fieldname','amr.thicknesserror_threshold','numel',[1],'>=',0,'<=',1,'NaN',1); - md = checkfield(md,'fieldname','amr.thicknesserror_groupthreshold','numel',[1],'>=',0,'<=',1,'NaN',1); - md = checkfield(md,'fieldname','amr.thicknesserror_maximum','numel',[1],'>=',0,'NaN',1,'Inf',1); - md = checkfield(md,'fieldname','amr.deviatoricerror_resolution','numel',[1],'>',0,'<',self.hmax,'NaN',1); - md = checkfield(md,'fieldname','amr.deviatoricerror_threshold','numel',[1],'>=',0,'<=',1,'NaN',1); - md = checkfield(md,'fieldname','amr.deviatoricerror_groupthreshold','numel',[1],'>=',0,'<=',1,'NaN',1); - md = checkfield(md,'fieldname','amr.deviatoricerror_maximum','numel',[1],'>=',0,'NaN',1,'Inf',1); - md = checkfield(md,'fieldname','amr.restart','numel',[1],'>=',0,'<=',1,'NaN',1) + + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'amr.hmax', 'numel', [1], '>', 0, 'NaN', 1) + md = checkfield(md, 'fieldname', 'amr.hmin', 'numel', [1], '>', 0, '<', self.hmax, 'NaN', 1) + md = checkfield(md, 'fieldname', 'amr.keepmetric', 'numel', [1], '>=', 0, '<=', 1, 'NaN', 1) + md = checkfield(md, 'fieldname', 'amr.gradation', 'numel', [1], '>=', 1.1, '<=', 5, 'NaN', 1) + md = checkfield(md, 'fieldname', 'amr.groundingline_resolution', 'numel', [1], '>', 0, '<', self.hmax, 'NaN', 1) + md = checkfield(md, 'fieldname', 'amr.groundingline_distance', 'numel', [1], '>=', 0, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'amr.icefront_resolution', 'numel', [1], '>', 0, '<', self.hmax, 'NaN', 1) + md = checkfield(md, 'fieldname', 'amr.icefront_distance', 'numel', [1], '>=', 0, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'amr.thicknesserror_resolution', 'numel', [1], '>', 0, '<', self.hmax, 'NaN', 1) + md = checkfield(md, 'fieldname', 'amr.thicknesserror_threshold', 'numel', [1], '>=', 0, '<=', 1, 'NaN', 1) + md = checkfield(md, 'fieldname', 'amr.thicknesserror_groupthreshold', 'numel', [1], '>=', 0, '<=', 1, 'NaN', 1) + md = checkfield(md, 'fieldname', 'amr.thicknesserror_maximum', 'numel', [1], '>=', 0, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'amr.deviatoricerror_resolution', 'numel', [1], '>', 0, '<', self.hmax, 'NaN', 1) + md = checkfield(md, 'fieldname', 'amr.deviatoricerror_threshold', 'numel', [1], '>=', 0, '<=', 1, 'NaN', 1) + md = checkfield(md, 'fieldname', 'amr.deviatoricerror_groupthreshold', 'numel', [1], '>=', 0, '<=', 1, 'NaN', 1) + md = checkfield(md, 'fieldname', 'amr.deviatoricerror_maximum', 'numel', [1], '>=', 0, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'amr.restart', 'numel', [1], '>=', 0, '<=', 1, 'NaN', 1) return md # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.amr.type','data',1,'format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','hmin','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','hmax','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','fieldname','format','String'); - WriteData(fid,prefix,'object',self,'fieldname','err','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','keepmetric','format','Integer'); - WriteData(fid,prefix,'object',self,'fieldname','gradation','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','groundingline_resolution','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','groundingline_distance','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','icefront_resolution','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','icefront_distance','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','thicknesserror_resolution','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','thicknesserror_threshold','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','thicknesserror_groupthreshold','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','thicknesserror_maximum','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','deviatoricerror_resolution','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','deviatoricerror_threshold','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','deviatoricerror_groupthreshold','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','deviatoricerror_maximum','format','Double'); - WriteData(fid,prefix,'object',self,'class','amr','fieldname','restart','format','Integer') + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.amr.type', 'data', 1, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'hmin', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'hmax', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'fieldname', 'format', 'String') + WriteData(fid, prefix, 'object', self, 'fieldname', 'err', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'keepmetric', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'gradation', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'groundingline_resolution', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'groundingline_distance', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'icefront_resolution', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'icefront_distance', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'thicknesserror_resolution', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'thicknesserror_threshold', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'thicknesserror_groupthreshold', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'thicknesserror_maximum', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'deviatoricerror_resolution', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'deviatoricerror_threshold', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'deviatoricerror_groupthreshold', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'deviatoricerror_maximum', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'amr', 'fieldname', 'restart', 'format', 'Integer') # }}} Index: /issm/trunk-jpl/src/m/classes/autodiff.py =================================================================== --- /issm/trunk-jpl/src/m/classes/autodiff.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/autodiff.py (revision 24213) @@ -7,215 +7,215 @@ from MatlabArray import * + class autodiff(object): - """ - AUTODIFF class definition - - Usage: - autodiff=autodiff(); - """ - def __init__(self,*args): # {{{ - self.isautodiff = False - self.dependents = [] - self.independents = [] - self.driver = 'fos_forward' - self.obufsize = float('NaN') - self.lbufsize = float('NaN') - self.cbufsize = float('NaN') - self.tbufsize = float('NaN') - self.gcTriggerMaxSize = float('NaN') - self.gcTriggerRatio = float('NaN') - self.tapeAlloc = float('NaN') - if not len(args): - self.setdefaultparameters() - else: - raise RuntimeError("constructor not supported") - # }}} - - def __repr__(self): # {{{ - s =" automatic differentiation parameters:\n" - s+="%s\n" % fielddisplay(self,'isautodiff',"indicates if the automatic differentiation is activated") - s+="%s\n" % fielddisplay(self,'dependents',"list of dependent variables") - s+="%s\n" % fielddisplay(self,'independents',"list of independent variables") - s+="%s\n" % fielddisplay(self,'driver',"ADOLC driver ('fos_forward' or 'fov_forward')") - s+="%s\n" % fielddisplay(self,'obufsize',"Number of operations per buffer (==OBUFSIZE in usrparms.h)") - s+="%s\n" % fielddisplay(self,'lbufsize',"Number of locations per buffer (==LBUFSIZE in usrparms.h)") - s+="%s\n" % fielddisplay(self,'cbufsize',"Number of values per buffer (==CBUFSIZE in usrparms.h)") - s+="%s\n" % fielddisplay(self,'tbufsize',"Number of taylors per buffer (<=TBUFSIZE in usrparms.h)") - s+="%s\n" % fielddisplay(self,'gcTriggerRatio',"free location block sorting/consolidation triggered if the ratio between allocated and used locations exceeds gcTriggerRatio") - s+="%s\n" % fielddisplay(self,'gcTriggerMaxSize',"free location block sorting/consolidation triggered if the allocated locations exceed gcTriggerMaxSize)") - s+="%s\n" % fielddisplay(self,'tapeAlloc','Iteration count of a priori memory allocation of the AD tape'); - - return s - # }}} - - def setdefaultparameters(self): # {{{ - self.obufsize = 524288 - self.lbufsize = 524288 - self.cbufsize = 524288 - self.tbufsize = 524288 - self.gcTriggerRatio = 2.0 - self.gcTriggerMaxSize = 65536 - self.tapeAlloc = 15000000; - return self - # }}} - - def checkconsistency(self,md,solution,analyses): # {{{ - #Early return - if not self.isautodiff: - return md - - md = checkfield(md,'fieldname','autodiff.obufsize','>=',524288) - md = checkfield(md,'fieldname','autodiff.lbufsize','>=',524288) - md = checkfield(md,'fieldname','autodiff.cbufsize','>=',524288) - md = checkfield(md,'fieldname','autodiff.tbufsize','>=',524288) - md = checkfield(md,'fieldname','autodiff.gcTriggerRatio','>=',2.0) - md = checkfield(md,'fieldname','autodiff.gcTriggerMaxSize','>=',65536) - md = checkfield(md,'fieldname','autodiff.tapeAlloc','>=',0); - - #Driver value: - md = checkfield(md,'fieldname','autodiff.driver','values',['fos_forward','fov_forward','fov_forward_all','fos_reverse','fov_reverse','fov_reverse_all']) - - #go through our dependents and independents and check consistency: - for dep in self.dependents: - dep.checkconsistency(md,solution,analyses) - for i,indep in enumerate(self.independents): - indep.checkconsistency(md,i,solution,analyses,self.driver) - - return md - # }}} - - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','isautodiff','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','driver','format','String') - - #early return - if not self.isautodiff: - WriteData(fid,prefix,'data',False,'name','md.autodiff.mass_flux_segments_present','format','Boolean') - WriteData(fid,prefix,'data',False,'name','md.autodiff.keep','format','Boolean') - return - - #buffer sizes {{{ - WriteData(fid,prefix,'object',self,'fieldname','obufsize','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','lbufsize','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','cbufsize','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','tbufsize','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','gcTriggerRatio','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','gcTriggerMaxSize','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','tapeAlloc','format','Integer'); - #}}} - #process dependent variables {{{ - num_dependent_objects=len(self.dependents) - WriteData(fid,prefix,'data',num_dependent_objects,'name','md.autodiff.num_dependent_objects','format','Integer') - - if num_dependent_objects: - names=[] - types=np.zeros(num_dependent_objects) - indices=np.zeros(num_dependent_objects) - - for i,dep in enumerate(self.dependents): - names.append(dep.name) - types[i]=dep.typetoscalar() - indices[i]=dep.index - - WriteData(fid,prefix,'data',names,'name','md.autodiff.dependent_object_names','format','StringArray') - WriteData(fid,prefix,'data',types,'name','md.autodiff.dependent_object_types','format','IntMat','mattype',3) - WriteData(fid,prefix,'data',indices,'name','md.autodiff.dependent_object_indices','format','IntMat','mattype',3) - #}}} - #process independent variables {{{ - num_independent_objects=len(self.independents) - WriteData(fid,prefix,'data',num_independent_objects,'name','md.autodiff.num_independent_objects','format','Integer') - - if num_independent_objects: - names=[None] * num_independent_objects - types=np.zeros(num_independent_objects) - - for i,indep in enumerate(self.independents): - names[i]=indep.name - types[i]=indep.typetoscalar() - - WriteData(fid,prefix,'data',names,'name','md.autodiff.independent_object_names','format','StringArray') - WriteData(fid,prefix,'data',types,'name','md.autodiff.independent_object_types','format','IntMat','mattype',3) - #}}} - #if driver is fos_forward, build index: {{{ - if strcmpi(self.driver,'fos_forward'): - index=0 - - for indep in self.independents: - if not np.isnan(indep.fos_forward_index): - index+=indep.fos_forward_index - break - else: - if strcmpi(indep.type,'scalar'): - index+=1 - else: - index+=indep.nods - - index-=1 #get c-index numbering going - WriteData(fid,prefix,'data',index,'name','md.autodiff.fos_forward_index','format','Integer') - #}}} - #if driver is fos_reverse, build index: {{{ - if strcmpi(self.driver,'fos_reverse'): - index=0 - - for dep in self.dependents: - if not np.isnan(dep.fos_reverse_index): - index+=dep.fos_reverse_index - break - else: - if strcmpi(dep.type,'scalar'): - index+=1 - else: - index+=dep.nods - - index-=1 #get c-index numbering going - WriteData(fid,prefix,'data',index,'name','md.autodiff.fos_reverse_index','format','Integer') - #}}} - #if driver is fov_forward, build indices: {{{ - if strcmpi(self.driver,'fov_forward'): - indices=0 - - for indep in self.independents: - if indep.fos_forward_index: - indices+=indep.fov_forward_indices - break - else: - if strcmpi(indep.type,'scalar'): - indices+=1 - else: - indices+=indep.nods - - indices-=1 #get c-indices numbering going - WriteData(fid,prefix,'data',indices,'name','md.autodiff.fov_forward_indices','format','IntMat','mattype',3) - #}}} - #deal with mass fluxes: {{{ - mass_flux_segments=[dep.segments for dep in self.dependents if strcmpi(dep.name,'MassFlux')] - - if mass_flux_segments: - WriteData(fid,prefix,'data',mass_flux_segments,'name','md.autodiff.mass_flux_segments','format','MatArray') - flag=True - else: - flag=False - WriteData(fid,prefix,'data',flag,'name','md.autodiff.mass_flux_segments_present','format','Boolean') - #}}} - #deal with trace keep on: {{{ - keep=False - - #From ADOLC userdoc: - # The optional integer argument keep of trace on determines whether the numerical values of all active variables are - # recorded in a buffered temporary array or file called the taylor stack. This option takes effect if keep = 1 and - # prepares the scene for an immediately following gradient evaluation by a call to a routine implementing the reverse - # mode as described in the Section 4 and Section 5. - # - - if len(self.driver)<=3: - keep=False #there is no "_reverse" string within the driver string: - else: - if strncmpi(self.driver[3:],'_reverse',8): - keep=True - else: - keep=False - WriteData(fid,prefix,'data',keep,'name','md.autodiff.keep','format','Boolean') - #}}} - - return - # }}} + """ + AUTODIFF class definition + + Usage: + autodiff = autodiff() + """ + def __init__(self, *args): # {{{ + self.isautodiff = False + self.dependents = [] + self.independents = [] + self.driver = 'fos_forward' + self.obufsize = float('NaN') + self.lbufsize = float('NaN') + self.cbufsize = float('NaN') + self.tbufsize = float('NaN') + self.gcTriggerMaxSize = float('NaN') + self.gcTriggerRatio = float('NaN') + self.tapeAlloc = float('NaN') + if not len(args): + self.setdefaultparameters() + else: + raise RuntimeError("constructor not supported") + # }}} + + def __repr__(self): # {{{ + s = " automatic differentiation parameters:\n" + s += "%s\n" % fielddisplay(self, 'isautodiff', "indicates if the automatic differentiation is activated") + s += "%s\n" % fielddisplay(self, 'dependents', "list of dependent variables") + s += "%s\n" % fielddisplay(self, 'independents', "list of independent variables") + s += "%s\n" % fielddisplay(self, 'driver', "ADOLC driver ('fos_forward' or 'fov_forward')") + s += "%s\n" % fielddisplay(self, 'obufsize', "Number of operations per buffer (== OBUFSIZE in usrparms.h)") + s += "%s\n" % fielddisplay(self, 'lbufsize', "Number of locations per buffer (== LBUFSIZE in usrparms.h)") + s += "%s\n" % fielddisplay(self, 'cbufsize', "Number of values per buffer (== CBUFSIZE in usrparms.h)") + s += "%s\n" % fielddisplay(self, 'tbufsize', "Number of taylors per buffer (<=TBUFSIZE in usrparms.h)") + s += "%s\n" % fielddisplay(self, 'gcTriggerRatio', "free location block sorting / consolidation triggered if the ratio between allocated and used locations exceeds gcTriggerRatio") + s += "%s\n" % fielddisplay(self, 'gcTriggerMaxSize', "free location block sorting / consolidation triggered if the allocated locations exceed gcTriggerMaxSize)") + s += "%s\n" % fielddisplay(self, 'tapeAlloc', 'Iteration count of a priori memory allocation of the AD tape') + + return s + # }}} + + def setdefaultparameters(self): # {{{ + self.obufsize = 524288 + self.lbufsize = 524288 + self.cbufsize = 524288 + self.tbufsize = 524288 + self.gcTriggerRatio = 2.0 + self.gcTriggerMaxSize = 65536 + self.tapeAlloc = 15000000 + return self + # }}} + + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if not self.isautodiff: + return md + + md = checkfield(md, 'fieldname', 'autodiff.obufsize', '>=', 524288) + md = checkfield(md, 'fieldname', 'autodiff.lbufsize', '>=', 524288) + md = checkfield(md, 'fieldname', 'autodiff.cbufsize', '>=', 524288) + md = checkfield(md, 'fieldname', 'autodiff.tbufsize', '>=', 524288) + md = checkfield(md, 'fieldname', 'autodiff.gcTriggerRatio', '>=', 2.0) + md = checkfield(md, 'fieldname', 'autodiff.gcTriggerMaxSize', '>=', 65536) + md = checkfield(md, 'fieldname', 'autodiff.tapeAlloc', '>=', 0) + + #Driver value: + md = checkfield(md, 'fieldname', 'autodiff.driver', 'values', ['fos_forward', 'fov_forward', 'fov_forward_all', 'fos_reverse', 'fov_reverse', 'fov_reverse_all']) + + #go through our dependents and independents and check consistency: + for dep in self.dependents: + dep.checkconsistency(md, solution, analyses) + for i, indep in enumerate(self.independents): + indep.checkconsistency(md, i, solution, analyses, self.driver) + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'isautodiff', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'driver', 'format', 'String') + + #early return + if not self.isautodiff: + WriteData(fid, prefix, 'data', False, 'name', 'md.autodiff.mass_flux_segments_present', 'format', 'Boolean') + WriteData(fid, prefix, 'data', False, 'name', 'md.autodiff.keep', 'format', 'Boolean') + return + + #buffer sizes {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'obufsize', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'lbufsize', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'cbufsize', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'tbufsize', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'gcTriggerRatio', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'gcTriggerMaxSize', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'tapeAlloc', 'format', 'Integer') + #}}} + #process dependent variables {{{ + num_dependent_objects = len(self.dependents) + WriteData(fid, prefix, 'data', num_dependent_objects, 'name', 'md.autodiff.num_dependent_objects', 'format', 'Integer') + + if num_dependent_objects: + names = [] + types = np.zeros(num_dependent_objects) + indices = np.zeros(num_dependent_objects) + + for i, dep in enumerate(self.dependents): + names.append(dep.name) + types[i] = dep.typetoscalar() + indices[i] = dep.index + + WriteData(fid, prefix, 'data', names, 'name', 'md.autodiff.dependent_object_names', 'format', 'StringArray') + WriteData(fid, prefix, 'data', types, 'name', 'md.autodiff.dependent_object_types', 'format', 'IntMat', 'mattype', 3) + WriteData(fid, prefix, 'data', indices, 'name', 'md.autodiff.dependent_object_indices', 'format', 'IntMat', 'mattype', 3) + #}}} + #process independent variables {{{ + num_independent_objects = len(self.independents) + WriteData(fid, prefix, 'data', num_independent_objects, 'name', 'md.autodiff.num_independent_objects', 'format', 'Integer') + + if num_independent_objects: + names = [None] * num_independent_objects + types = np.zeros(num_independent_objects) + + for i, indep in enumerate(self.independents): + names[i] = indep.name + types[i] = indep.typetoscalar() + + WriteData(fid, prefix, 'data', names, 'name', 'md.autodiff.independent_object_names', 'format', 'StringArray') + WriteData(fid, prefix, 'data', types, 'name', 'md.autodiff.independent_object_types', 'format', 'IntMat', 'mattype', 3) + #}}} + #if driver is fos_forward, build index: {{{ + if strcmpi(self.driver, 'fos_forward'): + index = 0 + + for indep in self.independents: + if not np.isnan(indep.fos_forward_index): + index += indep.fos_forward_index + break + else: + if strcmpi(indep.type, 'scalar'): + index += 1 + else: + index += indep.nods + + index -= 1 #get c - index numbering going + WriteData(fid, prefix, 'data', index, 'name', 'md.autodiff.fos_forward_index', 'format', 'Integer') + #}}} + #if driver is fos_reverse, build index: {{{ + if strcmpi(self.driver, 'fos_reverse'): + index = 0 + + for dep in self.dependents: + if not np.isnan(dep.fos_reverse_index): + index += dep.fos_reverse_index + break + else: + if strcmpi(dep.type, 'scalar'): + index += 1 + else: + index += dep.nods + + index -= 1 #get c - index numbering going + WriteData(fid, prefix, 'data', index, 'name', 'md.autodiff.fos_reverse_index', 'format', 'Integer') + #}}} + #if driver is fov_forward, build indices: {{{ + if strcmpi(self.driver, 'fov_forward'): + indices = 0 + + for indep in self.independents: + if indep.fos_forward_index: + indices += indep.fov_forward_indices + break + else: + if strcmpi(indep.type, 'scalar'): + indices += 1 + else: + indices += indep.nods + + indices -= 1 #get c - indices numbering going + WriteData(fid, prefix, 'data', indices, 'name', 'md.autodiff.fov_forward_indices', 'format', 'IntMat', 'mattype', 3) + #}}} + #deal with mass fluxes: {{{ + mass_flux_segments = [dep.segments for dep in self.dependents if strcmpi(dep.name, 'MassFlux')] + + if mass_flux_segments: + WriteData(fid, prefix, 'data', mass_flux_segments, 'name', 'md.autodiff.mass_flux_segments', 'format', 'MatArray') + flag = True + else: + flag = False + WriteData(fid, prefix, 'data', flag, 'name', 'md.autodiff.mass_flux_segments_present', 'format', 'Boolean') + #}}} + #deal with trace keep on: {{{ + keep = False + + #From ADOLC userdoc: + # The optional integer argument keep of trace on determines whether the numerical values of all active variables are + # recorded in a buffered temporary array or file called the taylor stack. This option takes effect if keep = 1 and + # prepares the scene for an immediately following gradient evaluation by a call to a routine implementing the reverse + # mode as described in the Section 4 and Section 5. + # + if len(self.driver) <= 3: + keep = False #there is no "_reverse" string within the driver string: + else: + if strncmpi(self.driver[3:], '_reverse', 8): + keep = True + else: + keep = False + WriteData(fid, prefix, 'data', keep, 'name', 'md.autodiff.keep', 'format', 'Boolean') + #}}} + + return + # }}} Index: /issm/trunk-jpl/src/m/classes/balancethickness.py =================================================================== --- /issm/trunk-jpl/src/m/classes/balancethickness.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/balancethickness.py (revision 24213) @@ -3,61 +3,60 @@ from WriteData import WriteData + class balancethickness(object): - """ - BALANCETHICKNESS class definition + """ + BALANCETHICKNESS class definition - Usage: - balancethickness=balancethickness(); - """ + Usage: + balancethickness = balancethickness() + """ - def __init__(self): # {{{ - self.spcthickness = float('NaN') - self.thickening_rate = float('NaN') - self.stabilization = 0 - - self.omega = float('NaN') - self.slopex = float('NaN') - self.slopey = float('NaN') + def __init__(self): # {{{ + self.spcthickness = float('NaN') + self.thickening_rate = float('NaN') + self.stabilization = 0 + self.omega = float('NaN') + self.slopex = float('NaN') + self.slopey = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - - string=' balance thickness solution parameters:' - - string="%s\n%s"%(string,fielddisplay(self,'spcthickness','thickness constraints (NaN means no constraint) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'thickening_rate','ice thickening rate used in the mass conservation (dh/dt) [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'stabilization',"0: None, 1: SU, 2: SSA's artificial diffusivity, 3:DG")) - return string - #}}} - def setdefaultparameters(self): # {{{ - - #Type of stabilization used - self.stabilization=1 + #}}} - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - #Early return - if not solution=='BalancethicknessSolution': - return md + def __repr__(self): # {{{ + string = ' balance thickness solution parameters:' - md = checkfield(md,'fieldname','balancethickness.spcthickness') - md = checkfield(md,'fieldname','balancethickness.thickening_rate','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','balancethickness.stabilization','size',[1],'values',[0,1,2,3]) - #md = checkfield(md,'fieldname','balancethickness.omega','size', [md.mesh.numberofvertices],'NaN',1,'Inf',1,'>=',0); - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + string = "%s\n%s" % (string, fielddisplay(self, 'spcthickness', 'thickness constraints (NaN means no constraint) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'thickening_rate', 'ice thickening rate used in the mass conservation (dh / dt) [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'stabilization', "0: None, 1: SU, 2: SSA's artificial diffusivity, 3:DG")) + return string + #}}} - yts=md.constants.yts + def setdefaultparameters(self): # {{{ + #Type of stabilization used + self.stabilization = 1 + return self + #}}} - WriteData(fid,prefix,'object',self,'fieldname','spcthickness','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','thickening_rate','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'fieldname','stabilization','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','slopex','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','slopey','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','omega','format','DoubleMat','mattype',1) - # }}} + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if not solution == 'BalancethicknessSolution': + return md + + md = checkfield(md, 'fieldname', 'balancethickness.spcthickness') + md = checkfield(md, 'fieldname', 'balancethickness.thickening_rate', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'balancethickness.stabilization', 'size', [1], 'values', [0, 1, 2, 3]) + #md = checkfield(md, 'fieldname', 'balancethickness.omega', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1, '>=', 0) + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + WriteData(fid, prefix, 'object', self, 'fieldname', 'spcthickness', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'thickening_rate', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'stabilization', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'slopex', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'slopey', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'omega', 'format', 'DoubleMat', 'mattype', 1) + # }}} Index: /issm/trunk-jpl/src/m/classes/bamggeom.py =================================================================== --- /issm/trunk-jpl/src/m/classes/bamggeom.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/bamggeom.py (revision 24213) @@ -1,45 +1,47 @@ import numpy as np + class bamggeom(object): - """ - BAMGGEOM class definition + """ + BAMGGEOM class definition - Usage: - bamggeom(varargin) - """ + Usage: + bamggeom(varargin) + """ - def __init__(self,*args): # {{{ - self.Vertices=np.empty((0,3)) - self.Edges=np.empty((0,3)) - self.TangentAtEdges=np.empty((0,4)) - self.Corners=np.empty((0,1)) - self.RequiredVertices=np.empty((0,1)) - self.RequiredEdges=np.empty((0,1)) - self.CrackedEdges=np.empty((0,0)) - self.SubDomains=np.empty((0,4)) + def __init__(self, *args): # {{{ + self.Vertices = np.empty((0, 3)) + self.Edges = np.empty((0, 3)) + self.TangentAtEdges = np.empty((0, 4)) + self.Corners = np.empty((0, 1)) + self.RequiredVertices = np.empty((0, 1)) + self.RequiredEdges = np.empty((0, 1)) + self.CrackedEdges = np.empty((0, 0)) + self.SubDomains = np.empty((0, 4)) - if not len(args): - # if no input arguments, create a default object - pass + if not len(args): + # if no input arguments, create a default object + pass - elif len(args) == 1: - object=args[0] - for field in list(object.keys()): - if field in vars(self): - setattr(self,field,object[field]) + elif len(args) == 1: + object = args[0] + for field in list(object.keys()): + if field in vars(self): + setattr(self, field, object[field]) - else: - raise TypeError("bamggeom constructor error message: unknown type of constructor call") - # }}} - def __repr__(self): # {{{ - s ="class '%s' object '%s' = \n" % (type(self),'self') - s+=" Vertices: %s\n" % str(self.Vertices) - s+=" Edges: %s\n" % str(self.Edges) - s+=" TangentAtEdges: %s\n" % str(self.TangentAtEdges) - s+=" Corners: %s\n" % str(self.Corners) - s+=" RequiredVertices: %s\n" % str(self.RequiredVertices) - s+=" RequiredEdges: %s\n" % str(self.RequiredEdges) - s+=" CrackedEdges: %s\n" % str(self.CrackedEdges) - s+=" SubDomains: %s\n" % str(self.SubDomains) - return s - # }}} + else: + raise TypeError("bamggeom constructor error message: unknown type of constructor call") + # }}} + + def __repr__(self): # {{{ + s = "class '%s' object '%s'=\n" % (type(self), 'self') + s += " Vertices: %s\n" % str(self.Vertices) + s += " Edges: %s\n" % str(self.Edges) + s += " TangentAtEdges: %s\n" % str(self.TangentAtEdges) + s += " Corners: %s\n" % str(self.Corners) + s += " RequiredVertices: %s\n" % str(self.RequiredVertices) + s += " RequiredEdges: %s\n" % str(self.RequiredEdges) + s += " CrackedEdges: %s\n" % str(self.CrackedEdges) + s += " SubDomains: %s\n" % str(self.SubDomains) + return s + # }}} Index: /issm/trunk-jpl/src/m/classes/bamgmesh.py =================================================================== --- /issm/trunk-jpl/src/m/classes/bamgmesh.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/bamgmesh.py (revision 24213) @@ -1,59 +1,61 @@ import numpy as np + class bamgmesh(object): - """ - BAMGMESH class definition + """ + BAMGMESH class definition - Usage: - bamgmesh(varargin) - """ + Usage: + bamgmesh(varargin) + """ - def __init__(self,*args): # {{{ - self.Vertices=np.empty((0,3)) - self.Edges=np.empty((0,3)) - self.Triangles=np.empty((0,0)) - self.IssmEdges=np.empty((0,0)) - self.IssmSegments=np.empty((0,0)) - self.VerticesOnGeomVertex=np.empty((0,0)) - self.VerticesOnGeomEdge=np.empty((0,0)) - self.EdgesOnGeomEdge=np.empty((0,0)) - self.SubDomains=np.empty((0,4)) - self.SubDomainsFromGeom=np.empty((0,0)) - self.ElementConnectivity=np.empty((0,0)) - self.NodalConnectivity=np.empty((0,0)) - self.NodalElementConnectivity=np.empty((0,0)) - self.CrackedVertices=np.empty((0,0)) - self.CrackedEdges=np.empty((0,0)) + def __init__(self, *args): # {{{ + self.Vertices = np.empty((0, 3)) + self.Edges = np.empty((0, 3)) + self.Triangles = np.empty((0, 0)) + self.IssmEdges = np.empty((0, 0)) + self.IssmSegments = np.empty((0, 0)) + self.VerticesOnGeomVertex = np.empty((0, 0)) + self.VerticesOnGeomEdge = np.empty((0, 0)) + self.EdgesOnGeomEdge = np.empty((0, 0)) + self.SubDomains = np.empty((0, 4)) + self.SubDomainsFromGeom = np.empty((0, 0)) + self.ElementConnectivity = np.empty((0, 0)) + self.NodalConnectivity = np.empty((0, 0)) + self.NodalElementConnectivity = np.empty((0, 0)) + self.CrackedVertices = np.empty((0, 0)) + self.CrackedEdges = np.empty((0, 0)) - if not len(args): - # if no input arguments, create a default object - pass + if not len(args): + # if no input arguments, create a default object + pass - elif len(args) == 1: - object=args[0] - for field in list(object.keys()): - if field in vars(self): - setattr(self,field,object[field]) + elif len(args) == 1: + object = args[0] + for field in list(object.keys()): + if field in vars(self): + setattr(self, field, object[field]) - else: - raise TypeError("bamgmesh constructor error message: unknown type of constructor call") - # }}} - def __repr__(self): # {{{ - s ="class '%s' object '%s' = \n" % (type(self),'self') - s+=" Vertices: %s\n" % str(self.Vertices) - s+=" Edges: %s\n" % str(self.Edges) - s+=" Triangles: %s\n" % str(self.Triangles) - s+=" IssmEdges: %s\n" % str(self.IssmEdges) - s+=" IssmSegments: %s\n" % str(self.IssmSegments) - s+=" VerticesOnGeomVertex: %s\n" % str(self.VerticesOnGeomVertex) - s+=" VerticesOnGeomEdge: %s\n" % str(self.VerticesOnGeomEdge) - s+=" EdgesOnGeomEdge: %s\n" % str(self.EdgesOnGeomEdge) - s+=" SubDomains: %s\n" % str(self.SubDomains) - s+=" SubDomainsFromGeom: %s\n" % str(self.SubDomainsFromGeom) - s+=" ElementConnectivity: %s\n" % str(self.ElementConnectivity) - s+=" NodalConnectivity: %s\n" % str(self.NodalConnectivity) - s+=" NodalElementConnectivity: %s\n" % str(self.NodalElementConnectivity) - s+=" CrackedVertices: %s\n" % str(self.CrackedVertices) - s+=" CrackedEdges: %s\n" % str(self.CrackedEdges) - return s - # }}} + else: + raise TypeError("bamgmesh constructor error message: unknown type of constructor call") + # }}} + + def __repr__(self): # {{{ + s = "class '%s' object '%s' = \n" % (type(self), 'self') + s += " Vertices: %s\n" % str(self.Vertices) + s += " Edges: %s\n" % str(self.Edges) + s += " Triangles: %s\n" % str(self.Triangles) + s += " IssmEdges: %s\n" % str(self.IssmEdges) + s += " IssmSegments: %s\n" % str(self.IssmSegments) + s += " VerticesOnGeomVertex: %s\n" % str(self.VerticesOnGeomVertex) + s += " VerticesOnGeomEdge: %s\n" % str(self.VerticesOnGeomEdge) + s += " EdgesOnGeomEdge: %s\n" % str(self.EdgesOnGeomEdge) + s += " SubDomains: %s\n" % str(self.SubDomains) + s += " SubDomainsFromGeom: %s\n" % str(self.SubDomainsFromGeom) + s += " ElementConnectivity: %s\n" % str(self.ElementConnectivity) + s += " NodalConnectivity: %s\n" % str(self.NodalConnectivity) + s += " NodalElementConnectivity: %s\n" % str(self.NodalElementConnectivity) + s += " CrackedVertices: %s\n" % str(self.CrackedVertices) + s += " CrackedEdges: %s\n" % str(self.CrackedEdges) + return s + # }}} Index: /issm/trunk-jpl/src/m/classes/basalforcings.py =================================================================== --- /issm/trunk-jpl/src/m/classes/basalforcings.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/basalforcings.py (revision 24213) @@ -5,77 +5,83 @@ import numpy as np + class basalforcings(object): - """ - BASAL FORCINGS class definition + """ + BASAL FORCINGS class definition - Usage: - basalforcings=basalforcings(); - """ + Usage: + basalforcings = basalforcings() + """ - def __init__(self): # {{{ - self.groundedice_melting_rate = float('NaN') - self.floatingice_melting_rate = float('NaN') - self.geothermalflux = float('NaN') + def __init__(self): # {{{ + self.groundedice_melting_rate = float('NaN') + self.floatingice_melting_rate = float('NaN') + self.geothermalflux = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=" basal forcings parameters:" + #}}} - string="%s\n%s"%(string,fielddisplay(self,"groundedice_melting_rate","basal melting rate (positive if melting) [m/yr]")) - string="%s\n%s"%(string,fielddisplay(self,"floatingice_melting_rate","basal melting rate (positive if melting) [m/yr]")) - string="%s\n%s"%(string,fielddisplay(self,"geothermalflux","geothermal heat flux [W/m^2]")) - return string - #}}} - def extrude(self,md): # {{{ - self.groundedice_melting_rate=project3d(md,'vector',self.groundedice_melting_rate,'type','node','layer',1) - self.floatingice_melting_rate=project3d(md,'vector',self.floatingice_melting_rate,'type','node','layer',1) - self.geothermalflux=project3d(md,'vector',self.geothermalflux,'type','node','layer',1) #bedrock only gets geothermal flux - return self - #}}} - def initialize(self,md): # {{{ + def __repr__(self): # {{{ + string = " basal forcings parameters:" - if np.all(np.isnan(self.groundedice_melting_rate)): - self.groundedice_melting_rate=np.zeros((md.mesh.numberofvertices)) - print(" no basalforcings.groundedice_melting_rate specified: values set as zero") + string = "%s\n%s" % (string, fielddisplay(self, "groundedice_melting_rate", "basal melting rate (positive if melting) [m / yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "floatingice_melting_rate", "basal melting rate (positive if melting) [m / yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "geothermalflux", "geothermal heat flux [W / m^2]")) + return string + #}}} - if np.all(np.isnan(self.floatingice_melting_rate)): - self.floatingice_melting_rate=np.zeros((md.mesh.numberofvertices)) - print(" no basalforcings.floatingice_melting_rate specified: values set as zero") - #if np.all(np.isnan(self.geothermalflux)): - #self.geothermalflux=np.zeros((md.mesh.numberofvertices)) - #print " no basalforcings.geothermalflux specified: values set as zero" + def extrude(self, md): # {{{ + self.groundedice_melting_rate = project3d(md, 'vector', self.groundedice_melting_rate, 'type', 'node', 'layer', 1) + self.floatingice_melting_rate = project3d(md, 'vector', self.floatingice_melting_rate, 'type', 'node', 'layer', 1) + self.geothermalflux = project3d(md, 'vector', self.geothermalflux, 'type', 'node', 'layer', 1) #bedrock only gets geothermal flux + return self + #}}} - return self - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def initialize(self, md): # {{{ + if np.all(np.isnan(self.groundedice_melting_rate)): + self.groundedice_melting_rate = np.zeros((md.mesh.numberofvertices)) + print(" no basalforcings.groundedice_melting_rate specified: values set as zero") - if 'MasstransportAnalysis' in analyses and not (solution=='TransientSolution' and not md.transient.ismasstransport): - md = checkfield(md,'fieldname','basalforcings.groundedice_melting_rate','NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','basalforcings.floatingice_melting_rate','NaN',1,'Inf',1,'timeseries',1) + if np.all(np.isnan(self.floatingice_melting_rate)): + self.floatingice_melting_rate = np.zeros((md.mesh.numberofvertices)) + print(" no basalforcings.floatingice_melting_rate specified: values set as zero") + #if np.all(np.isnan(self.geothermalflux)): + #self.geothermalflux = np.zeros((md.mesh.numberofvertices)) + #print " no basalforcings.geothermalflux specified: values set as zero" - if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','basalforcings.groundedice_melting_rate','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','basalforcings.floatingice_melting_rate','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) + return self + #}}} - if 'ThermalAnalysis' in analyses and not (solution=='TransientSolution' and not md.transient.isthermal): - md = checkfield(md,'fieldname','basalforcings.groundedice_melting_rate','NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','basalforcings.floatingice_melting_rate','NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','basalforcings.geothermalflux','NaN',1,'Inf',1,'timeseries',1,'>=',0) + def setdefaultparameters(self): # {{{ + return self + #}}} - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ - yts=md.constants.yts + if 'MasstransportAnalysis' in analyses and not (solution == 'TransientSolution' and not md.transient.ismasstransport): + md = checkfield(md, 'fieldname', 'basalforcings.groundedice_melting_rate', 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.floatingice_melting_rate', 'NaN', 1, 'Inf', 1, 'timeseries', 1) - WriteData(fid,prefix,'name','md.basalforcings.model','data',1,'format','Integer'); - WriteData(fid,prefix,'object',self,'fieldname','groundedice_melting_rate','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','floatingice_melting_rate','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','geothermalflux','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - # }}} + if 'BalancethicknessAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'basalforcings.groundedice_melting_rate', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'basalforcings.floatingice_melting_rate', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + + if 'ThermalAnalysis' in analyses and not (solution == 'TransientSolution' and not md.transient.isthermal): + md = checkfield(md, 'fieldname', 'basalforcings.groundedice_melting_rate', 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.floatingice_melting_rate', 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.geothermalflux', 'NaN', 1, 'Inf', 1, 'timeseries', 1, '>=', 0) + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + + yts = md.constants.yts + + WriteData(fid, prefix, 'name', 'md.basalforcings.model', 'data', 1, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'groundedice_melting_rate', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'floatingice_melting_rate', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'geothermalflux', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + # }}} Index: /issm/trunk-jpl/src/m/classes/calving.py =================================================================== --- /issm/trunk-jpl/src/m/classes/calving.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/calving.py (revision 24213) @@ -4,50 +4,53 @@ from WriteData import WriteData + class calving(object): - """ - CALVING class definition + """ + CALVING class definition - Usage: - calving=calving(); - """ + Usage: + calving = calving() + """ - def __init__(self): # {{{ + def __init__(self): # {{{ - self.calvingrate = float('NaN') - self.meltingrate = float('NaN') + self.calvingrate = float('NaN') + self.meltingrate = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' Calving parameters:' - string="%s\n%s"%(string,fielddisplay(self,'calvingrate','calving rate at given location [m/a]')) + #}}} - return string - #}}} - def extrude(self,md): # {{{ - self.calvingrate=project3d(md,'vector',self.calvingrate,'type','node') - return self - #}}} - def setdefaultparameters(self): # {{{ + def __repr__(self): # {{{ + string = ' Calving parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'calvingrate', 'calving rate at given location [m / a]')) - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + return string + #}}} - #Early return - if (solution!='TransientSolution') or (not md.transient.ismovingfront): - return md + def extrude(self, md): # {{{ + self.calvingrate = project3d(md, 'vector', self.calvingrate, 'type', 'node') + return self + #}}} - md = checkfield(md,'fieldname','calving.calvingrate','>=',0,'timeseries',1,'NaN',1,'Inf',1); + def setdefaultparameters(self): # {{{ + return self + #}}} - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if (solution != 'TransientSolution') or (not md.transient.ismovingfront): + return md - yts=md.constants.yts + md = checkfield(md, 'fieldname', 'calving.calvingrate', '>=', 0, 'timeseries', 1, 'NaN', 1, 'Inf', 1) - WriteData(fid,prefix,'name','md.calving.law','data',1,'format','Integer'); - WriteData(fid,prefix,'object',self,'fieldname','calvingrate','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts,'scale',1./yts) - # }}} + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + + WriteData(fid, prefix, 'name', 'md.calving.law', 'data', 1, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'calvingrate', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts, 'scale', 1. / yts) + # }}} Index: /issm/trunk-jpl/src/m/classes/calvingdev.py =================================================================== --- /issm/trunk-jpl/src/m/classes/calvingdev.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/calvingdev.py (revision 24213) @@ -4,57 +4,63 @@ from WriteData import WriteData + class calvingdev(object): - """ - CALVINGDEV class definition + """ + CALVINGDEV class definition - Usage: - calvingdev=calvingdev(); - """ + Usage: + calvingdev = calvingdev() + """ - def __init__(self): # {{{ + def __init__(self): # {{{ - self.stress_threshold_groundedice = 0. - self.stress_threshold_floatingice = 0. - self.meltingrate = float('NaN') + self.stress_threshold_groundedice = 0. + self.stress_threshold_floatingice = 0. + self.meltingrate = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' Calving Pi parameters:' - string="%s\n%s"%(string,fielddisplay(self,'stress_threshold_groundedice','sigma_max applied to grounded ice only [Pa]')) - string="%s\n%s"%(string,fielddisplay(self,'stress_threshold_floatingice','sigma_max applied to floating ice only [Pa]')) + #}}} - string="%s\n%s"%(string,fielddisplay(self,'meltingrate','melting rate at given location [m/a]')) - return string - #}}} - def extrude(self,md): # {{{ - self.meltingrate=project3d(md,'vector',self.meltingrate,'type','node') - return self - #}}} - def setdefaultparameters(self): # {{{ - #Default sigma max - self.stress_threshold_groundedice = 1e6 - self.stress_threshold_floatingice = 150e3 - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - #Early return - if solution == 'TransientSolution' or md.transient.ismovingfront == 0: - return + def __repr__(self): # {{{ + string = ' Calving Pi parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'stress_threshold_groundedice', 'sigma_max applied to grounded ice only [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'stress_threshold_floatingice', 'sigma_max applied to floating ice only [Pa]')) - md = checkfield(md,'fieldname','calving.stress_threshold_groundedice','>',0,'nan',1,'Inf',1) - md = checkfield(md,'fieldname','calving.stress_threshold_floatingice','>',0,'nan',1,'Inf',1) - md = checkfield(md,'fieldname','calving.meltingrate','NaN',1,'Inf',1,'timeseries',1,'>=',0) + string = "%s\n%s" % (string, fielddisplay(self, 'meltingrate', 'melting rate at given location [m / a]')) + return string + #}}} - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts + def extrude(self, md): # {{{ + self.meltingrate = project3d(md, 'vector', self.meltingrate, 'type', 'node') + return self + #}}} - WriteData(fid,prefix,'name','md.calving.law','data',2,'format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','stress_threshold_groundedice','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','stress_threshold_floatingice','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','meltingrate','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts,'scale',1./yts) - # }}} + def setdefaultparameters(self): # {{{ + #Default sigma max + self.stress_threshold_groundedice = 1e6 + self.stress_threshold_floatingice = 150e3 + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if solution == 'TransientSolution' or md.transient.ismovingfront == 0: + return + + md = checkfield(md, 'fieldname', 'calving.stress_threshold_groundedice', '>', 0, 'nan', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'calving.stress_threshold_floatingice', '>', 0, 'nan', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'calving.meltingrate', 'NaN', 1, 'Inf', 1, 'timeseries', 1, '>=', 0) + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + + WriteData(fid, prefix, 'name', 'md.calving.law', 'data', 2, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'stress_threshold_groundedice', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'stress_threshold_floatingice', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'meltingrate', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts, 'scale', 1. / yts) + # }}} Index: /issm/trunk-jpl/src/m/classes/calvinglevermann.py =================================================================== --- /issm/trunk-jpl/src/m/classes/calvinglevermann.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/calvinglevermann.py (revision 24213) @@ -2,49 +2,53 @@ from checkfield import checkfield from WriteData import WriteData +from project3d import project3d + class calvinglevermann(object): - """ - CALVINGLEVERMANN class definition + """ + CALVINGLEVERMANN class definition - Usage: - calvinglevermann=calvinglevermann(); - """ + Usage: + calvinglevermann = calvinglevermann() + """ - def __init__(self): # {{{ + def __init__(self): # {{{ - self.coeff = float('NaN') - self.meltingrate = float('NaN') + self.coeff = float('NaN') + self.meltingrate = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' Calving Levermann parameters:' - string="%s\n%s"%(string,fielddisplay(self,'coeff','proportionality coefficient in Levermann model')) + #}}} - return string - #}}} - def extrude(self,md): # {{{ - self.coeff=project3d(md,'vector',self.coeff,'type','node') - return self - #}}} - def setdefaultparameters(self): # {{{ + def __repr__(self): # {{{ + string = ' Calving Levermann parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'coeff', 'proportionality coefficient in Levermann model')) - #Proportionality coefficient in Levermann model - self.coeff=2e13; - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + return string + #}}} - #Early return - if (solution!='TransientSolution') or (not md.transient.ismovingfront): - return md + def extrude(self, md): # {{{ + self.coeff = project3d(md, 'vector', self.coeff, 'type', 'node') + return self + #}}} - md = checkfield(md,'fieldname','calving.coeff','size',[md.mesh.numberofvertices],'>',0) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts - WriteData(fid,prefix,'name','md.calving.law','data',3,'format','Integer'); - WriteData(fid,prefix,'object',self,'fieldname','coeff','format','DoubleMat','mattype',1) - # }}} + def setdefaultparameters(self): # {{{ + #Proportionality coefficient in Levermann model + self.coeff = 2e13 + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if (solution != 'TransientSolution') or (not md.transient.ismovingfront): + return md + + md = checkfield(md, 'fieldname', 'calving.coeff', 'size', [md.mesh.numberofvertices], '>', 0) + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.calving.law', 'data', 3, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'coeff', 'format', 'DoubleMat', 'mattype', 1) + # }}} Index: /issm/trunk-jpl/src/m/classes/calvingminthickness.py =================================================================== --- /issm/trunk-jpl/src/m/classes/calvingminthickness.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/calvingminthickness.py (revision 24213) @@ -3,46 +3,49 @@ from WriteData import WriteData + class calvingminthickness(object): - """ - CALVINGMINTHICKNESS class definition + """ + CALVINGMINTHICKNESS class definition - Usage: - calvingminthickness=calvingminthickness() - """ + Usage: + calvingminthickness = calvingminthickness() + """ - def __init__(self): # {{{ + def __init__(self): # {{{ - self.min_thickness = 0. - self.meltingrate = float('NaN') + self.min_thickness = 0. + self.meltingrate = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' Calving Minimum thickness:' - string="%s\n%s"%(string,fielddisplay(self,'min_thickness','minimum thickness below which no ice is allowed')) - return string - #}}} - def extrude(self,md): # {{{ - return self - #}}} - def setdefaultparameters(self): # {{{ + #}}} - #minimum thickness is 100 m by default - self.min_thickness = 100. - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def __repr__(self): # {{{ + string = ' Calving Minimum thickness:' + string = "%s\n%s" % (string, fielddisplay(self, 'min_thickness', 'minimum thickness below which no ice is allowed')) + return string + #}}} - #Early return - if solution == 'TransientSolution' or md.transient.ismovingfront == 0: - return + def extrude(self, md): # {{{ + return self + #}}} - md = checkfield(md,'fieldname','calving.min_thickness','>',0,'NaN',1,'Inf',1) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts - WriteData(fid,prefix,'name','md.calving.law','data',4,'format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','min_thickness','format','Double') - # }}} + def setdefaultparameters(self): # {{{ + #minimum thickness is 100 m by default + self.min_thickness = 100. + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if solution == 'TransientSolution' or md.transient.ismovingfront == 0: + return + + md = checkfield(md, 'fieldname', 'calving.min_thickness', '>', 0, 'NaN', 1, 'Inf', 1) + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.calving.law', 'data', 4, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'min_thickness', 'format', 'Double') + # }}} Index: /issm/trunk-jpl/src/m/classes/calvingvonmises.py =================================================================== --- /issm/trunk-jpl/src/m/classes/calvingvonmises.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/calvingvonmises.py (revision 24213) @@ -1,6 +1,6 @@ from fielddisplay import fielddisplay -from project3d import project3d from checkfield import checkfield from WriteData import WriteData + class calvingvonmises(object): @@ -9,30 +9,33 @@ Usage: - calvingvonmises=calvingvonmises() + calvingvonmises = calvingvonmises() """ - def __init__(self): # {{{ + def __init__(self): # {{{ self.stress_threshold_groundedice = 0. self.stress_threshold_floatingice = 0. - self.meltingrate = float('NaN') + self.meltingrate = float('NaN') self.min_thickness = 0. - #set defaults + #set defaults self.setdefaultparameters() #}}} - def __repr__(self): # {{{ - string=' Calving VonMises parameters:' - string="%s\n%s"%(string,fielddisplay(self,'stress_threshold_groundedice','sigma_max applied to grounded ice only [Pa]')) - string="%s\n%s"%(string,fielddisplay(self,'stress_threshold_floatingice','sigma_max applied to floating ice only [Pa]')) - string="%s\n%s"%(string,fielddisplay(self,'min_thickness','minimum thickness below which no ice is allowed [m]')) + + def __repr__(self): # {{{ + string = ' Calving VonMises parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'stress_threshold_groundedice', 'sigma_max applied to grounded ice only [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'stress_threshold_floatingice', 'sigma_max applied to floating ice only [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'min_thickness', 'minimum thickness below which no ice is allowed [m]')) return string #}}} - def extrude(self,md): # {{{ + + def extrude(self, md): # {{{ return self #}}} - def setdefaultparameters(self): # {{{ + + def setdefaultparameters(self): # {{{ #Default sigma max self.stress_threshold_groundedice = 1e6 @@ -40,24 +43,24 @@ #turn off min_thickness by default. - self.min_thickness=0. + self.min_thickness = 0. return self #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + + def checkconsistency(self, md, solution, analyses): # {{{ #Early return if solution == 'TransientSolution' or md.transient.ismovingfront == 0: return - md = checkfield(md,'fieldname','calving.stress_threshold_groundedice','>',0,'nan',1,'Inf',1) - md = checkfield(md,'fieldname','calving.stress_threshold_floatingice','>',0,'nan',1,'Inf',1) - md = checkfield(md,'fieldname','calving.min_thickness','>=',0,'NaN',1,'Inf',1,'numel',[1]); + md = checkfield(md, 'fieldname', 'calving.stress_threshold_groundedice', '>', 0, 'nan', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'calving.stress_threshold_floatingice', '>', 0, 'nan', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'calving.min_thickness', '>=', 0, 'NaN', 1, 'Inf', 1, 'numel', [1]) return md # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts - WriteData(fid,prefix,'name','md.calving.law','data',2,'format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','stress_threshold_groundedice','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','stress_threshold_floatingice','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','min_thickness','format','Double'); + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.calving.law', 'data', 2, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'stress_threshold_groundedice', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'stress_threshold_floatingice', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'min_thickness', 'format', 'Double') # }}} Index: /issm/trunk-jpl/src/m/classes/clusters/cyclone.py =================================================================== --- /issm/trunk-jpl/src/m/classes/clusters/cyclone.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/clusters/cyclone.py (revision 24213) @@ -5,120 +5,107 @@ from issmscpin import issmscpin from issmscpout import issmscpout -from QueueRequirements import QueueRequirements -import datetime try: - from cyclone_settings import cyclone_settings + from cyclone_settings import cyclone_settings except ImportError: - print('You need cyclone_settings.py to proceed, check presence and sys.path') - + print('You need cyclone_settings.py to proceed, check presence and sys.path') + + class cyclone(object): - """ - Be aware that this is not a cluster as we usually know them. There is no scheduling and ressources are pretty low. - The Computer have 20 cpus and 512Gb of memory used by a number of person so be respectful with your usage. - I putted some restrictive upper limits to avoid over-use. (Basile) - - Usage: - cluster=cyclone(); - """ + """ + Be aware that this is not a cluster as we usually know them. There is no scheduling and ressources are pretty low. + The Computer have 20 cpus and 512Gb of memory used by a number of person so be respectful with your usage. + I putted some restrictive upper limits to avoid over - use. (Basile) - def __init__(self,*args): - # {{{ - self.name = 'cyclone' - self.login = '' - self.np = 2 - self.time = 100 - self.codepath = '' - self.executionpath = '' - self.port = '' - self.interactive = 0 + Usage: + cluster = cyclone() + """ - #use provided options to change fields - options=pairoptions(*args) + def __init__(self, *args): # {{{ + self.name = 'cyclone' + self.login = '' + self.np = 2 + self.time = 100 + self.codepath = '' + self.executionpath = '' + self.port = '' + self.interactive = 0 - #initialize cluster using user settings if provided - self=cyclone_settings(self) - #OK get other fields - self=options.AssignObjectFields(self) - - # }}} + #use provided options to change fields + options = pairoptions(*args) - def __repr__(self): - # {{{ - # display the object - s = "class cyclone object:" - s = "%s\n%s"%(s,fielddisplay(self,'name','name of the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'login','login')) - s = "%s\n%s"%(s,fielddisplay(self,'np','number of processes')) - s = "%s\n%s"%(s,fielddisplay(self,'time','walltime requested in minutes')) - s = "%s\n%s"%(s,fielddisplay(self,'codepath','code path on the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'executionpath','execution path on the cluster')) - return s - # }}} + #initialize cluster using user settings if provided + self = cyclone_settings(self) + #OK get other fields + self = options.AssignObjectFields(self) - def checkconsistency(self,md,solution,analyses): - # {{{ - #Miscelaneous - if not self.login: - md = md.checkmessage('login empty') - if not self.codepath: - md = md.checkmessage('codepath empty') - if not self.executionpath: - md = md.checkmessage('executionpath empty') - if self.time>72: - md = md.checkmessage('walltime exceeds 72h for niceness this is not allowed, if you need more time consider shifting to one of the Notur systems') - if self.np >10: - md = md.checkmessage('number of process excess 10, if you need more processing power consider shifting to one of the Notur systems') + # }}} - return self - # }}} - def BuildQueueScript(self,dirname,modelname,solution,io_gather,isvalgrind,isgprof,isdakota,isoceancoupling): - # {{{ + def __repr__(self): # {{{ + # display the object + s = "class cyclone object:" + s = "%s\n%s" % (s, fielddisplay(self, 'name', 'name of the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'login', 'login')) + s = "%s\n%s" % (s, fielddisplay(self, 'np', 'number of processes')) + s = "%s\n%s" % (s, fielddisplay(self, 'time', 'walltime requested in minutes')) + s = "%s\n%s" % (s, fielddisplay(self, 'codepath', 'code path on the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'executionpath', 'execution path on the cluster')) + return s + # }}} - executable='issm.exe' - - #write queuing script - shortname=modelname[0:min(12,len(modelname))] - fid=open(modelname+'.queue','w') - fid.write('export ISSM_DIR="%s/../"\n' % self.codepath) - fid.write('source $ISSM_DIR/etc/environment.sh\n') - fid.write('INTELLIBS="/opt/intel/intelcompiler-12.04/composerxe-2011.4.191/compiler/lib/intel64"\n') - fid.write('export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib/:$INTELLIBS\n') - fid.write('export CPLUS_INCLUDE_PATH=$CPLUS_INCLUDE_PATH:/usr/include/x86_64-linux-gnu/c++/4.8\n') - fid.write('cd %s/%s/\n\n' % (self.executionpath,dirname)) - rundir=self.executionpath+'/'+dirname - runfile=self.executionpath+'/'+dirname+'/'+modelname - fid.write('mpiexec -np %i %s/%s %s %s %s >%s.outlog 2>%s.errlog\n' % (self.np,self.codepath,executable,str(solution),rundir,modelname,runfile,runfile)) - fid.close() + def checkconsistency(self, md, solution, analyses): # {{{ + #Miscelaneous + if not self.login: + md = md.checkmessage('login empty') + if not self.codepath: + md = md.checkmessage('codepath empty') + if not self.executionpath: + md = md.checkmessage('executionpath empty') + if self.time > 72: + md = md.checkmessage('walltime exceeds 72h for niceness this is not allowed, if you need more time consider shifting to one of the Notur systems') + if self.np > 10: + md = md.checkmessage('number of process excess 10, if you need more processing power consider shifting to one of the Notur systems') - # }}} - def UploadQueueJob(self,modelname,dirname,filelist): - # {{{ + return self + # }}} - #compress the files into one zip. - compressstring='tar -zcf %s.tar.gz ' % dirname - for file in filelist: - compressstring += ' %s' % file - subprocess.call(compressstring,shell=True) + def BuildQueueScript(self, dirname, modelname, solution, io_gather, isvalgrind, isgprof, isdakota, isoceancoupling): # {{{ + executable = 'issm.exe' + #write queuing script + fid = open(modelname + '.queue', 'w') + fid.write('export ISSM_DIR = "%s/../ "\n' % self.codepath) + fid.write('source $ISSM_DIR/etc/environment.sh\n') + fid.write('INTELLIBS = "/opt/intel/intelcompiler-12.04/composerxe-2011.4.191/compiler/lib/intel64"\n') + fid.write('export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib/:$INTELLIBS\n') + fid.write('export CPLUS_INCLUDE_PATH=$CPLUS_INCLUDE_PATH:/usr/include/x86_64-linux-gnu/c++/4.8\n') + fid.write('cd %s/%s/ \n\n' % (self.executionpath, dirname)) + rundir = self.executionpath + '/' + dirname + runfile = self.executionpath + '/' + dirname + '/' + modelname + fid.write('mpiexec -np %i %s/%s %s %s %s>%s.outlog 2>%s.errlog\n' % (self.np, self.codepath, executable, str(solution), rundir, modelname, runfile, runfile)) + fid.close() - print('uploading input file and queueing script') - issmscpout(self.name,self.executionpath,self.login,self.port,[dirname+'.tar.gz']) + # }}} + def UploadQueueJob(self, modelname, dirname, filelist): # {{{ + #compress the files into one zip. + compressstring = 'tar -zcf %s.tar.gz ' % dirname + for file in filelist: + compressstring += ' %s' % file + subprocess.call(compressstring, shell=True) - # }}} - def LaunchQueueJob(self,modelname,dirname,filelist,restart,batch): - # {{{ + print('uploading input file and queueing script') + issmscpout(self.name, self.executionpath, self.login, self.port, [dirname + '.tar.gz']) - print('launching solution sequence on remote cluster') - if restart: - launchcommand='cd %s && cd %s && qsub %s.queue' % (self.executionpath,dirname,modelname) - else: - launchcommand='cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && chmod +x ./%s.queue && ./%s.queue' % (self.executionpath,dirname,dirname,dirname,dirname,dirname,modelname,modelname) - issmssh(self.name,self.login,self.port,launchcommand) + # }}} + def LaunchQueueJob(self, modelname, dirname, filelist, restart, batch): # {{{ + print('launching solution sequence on remote cluster') + if restart: + launchcommand = 'cd %s && cd %s && qsub %s.queue' % (self.executionpath, dirname, modelname) + else: + launchcommand = 'cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && chmod +x ./%s.queue && ./%s.queue' % (self.executionpath, dirname, dirname, dirname, dirname, dirname, modelname, modelname) + issmssh(self.name, self.login, self.port, launchcommand) - # }}} - def Download(self,dirname,filelist): - # {{{ - - #copy files from cluster to current directory - directory='%s/%s/' % (self.executionpath,dirname) - issmscpin(self.name,self.login,self.port,directory,filelist) - # }}} + # }}} + def Download(self, dirname, filelist): # {{{ + #copy files from cluster to current directory + directory = '%s/%s/' % (self.executionpath, dirname) + issmscpin(self.name, self.login, self.port, directory, filelist) + # }}} Index: /issm/trunk-jpl/src/m/classes/clusters/fram.py =================================================================== --- /issm/trunk-jpl/src/m/classes/clusters/fram.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/clusters/fram.py (revision 24213) @@ -7,160 +7,154 @@ from issmscpout import issmscpout from QueueRequirements import QueueRequirements -import datetime +from IssmConfig import IssmConfig try: - from fram_settings import fram_settings + from fram_settings import fram_settings except ImportError: - print('You need fram_settings.py to proceed, check presence and sys.path') - + print('You need fram_settings.py to proceed, check presence and sys.path') + + class fram(object): - """ - Fram cluster class definition - This is a SLURM queue - The priorities are based on a point system, reservation when reaching 20000 and earning 1 point per min. - -Devel queue starts at 19990 - -Normal starts at 19940 - -Normal unpri atarts at 19400 + """ + Fram cluster class definition + This is a SLURM queue + The priorities are based on a point system, reservation when reaching 20000 and earning 1 point per min. + - Devel queue starts at 19990 + - Normal starts at 19940 + - Normal unpri atarts at 19400 - Jobs can be: - -normal (4 to 30 nodes, more if asked, 48h max walltime, 60Gb per nodes) - -bigmem for big memory nodes (8 512Gb nodes and 2 6Tb nodes, shared nodes, 14days max walltime + Jobs can be: + - normal (4 to 30 nodes, more if asked, 48h max walltime, 60Gb per nodes) + - bigmem for big memory nodes (8 512Gb nodes and 2 6Tb nodes, shared nodes, 14days max walltime - Usage: - cluster=stallo(); - """ + Usage: + cluster = stallo() + """ - def __init__(self,*args): - # {{{ - self.name = 'fram' - self.login = '' - self.numnodes = 2 - self.cpuspernode = 20 - self.mem = 1.6 - self.queue = 'normal' - self.time = 2*60 - self.codepath = '' - self.executionpath = '' - self.interactive = 0 - self.port = [] - self.accountname = '' - self.profiling = 0 - #use provided options to change fields - options=pairoptions(*args) + def __init__(self, *args): # {{{ + self.name = 'fram' + self.login = '' + self.numnodes = 2 + self.cpuspernode = 20 + self.mem = 1.6 + self.queue = 'normal' + self.time = 2 * 60 + self.codepath = '' + self.executionpath = '' + self.interactive = 0 + self.port = [] + self.accountname = '' + self.profiling = 0 + #use provided options to change fields + options = pairoptions(*args) - #initialize cluster using user settings if provided - self=stallo_settings(self) - #OK get other fields - self=options.AssignObjectFields(self) - self.np=self.numnodes*self.cpuspernode - # }}} - - def __repr__(self): - # {{{ - # display the object - s = "class vilje object:" - s = "%s\n%s"%(s,fielddisplay(self,'name','name of the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'login','login')) - s = "%s\n%s"%(s,fielddisplay(self,'numnodes','number of nodes')) - s = "%s\n%s"%(s,fielddisplay(self,'cpuspernode','number of nodes per CPUs')) - s = "%s\n%s"%(s,fielddisplay(self,'mem','memory per CPU')) - s = "%s\n%s"%(s,fielddisplay(self,'queue','name of the queue (normal (D), short,singlenode,multinode,devel)')) - s = "%s\n%s"%(s,fielddisplay(self,'time','walltime requested in minutes')) - s = "%s\n%s"%(s,fielddisplay(self,'codepath','code path on the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'executionpath','execution path on the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'interactive','')) - s = "%s\n%s"%(s,fielddisplay(self,'accountname','your cluster account')) - s = "%s\n%s"%(s,fielddisplay(self,'profiling','enable profiling if 1 default is 0')) - return s - # }}} - def checkconsistency(self,md,solution,analyses): - # {{{ - #Queue dictionarry gives queue name as key and max walltime and cpus as var - queuedict = {'normal':[2*24*60,2048], - 'devel':[4*60,2048]} - QueueRequirements(queuedict,self.queue,self.np,self.time) + #initialize cluster using user settings if provided + self = fram_settings(self) + #OK get other fields + self = options.AssignObjectFields(self) + self.np = self.numnodes * self.cpuspernode + # }}} - #Miscelaneous - if not self.login: - md = md.checkmessage('login empty') - if not self.codepath: - md = md.checkmessage('codepath empty') - if not self.executionpath: - md = md.checkmessage('executionpath empty') - if self.interactive==1: - md = md.checkmessage('interactive mode not implemented') - return self - # }}} - def BuildQueueScript(self,dirname,modelname,solution,io_gather,isvalgrind,isgprof,isdakota,isoceancoupling): - # {{{ + def __repr__(self): # {{{ + # display the object + s = "class vilje object:" + s = "%s\n%s" % (s, fielddisplay(self, 'name', 'name of the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'login', 'login')) + s = "%s\n%s" % (s, fielddisplay(self, 'numnodes', 'number of nodes')) + s = "%s\n%s" % (s, fielddisplay(self, 'cpuspernode', 'number of nodes per CPUs')) + s = "%s\n%s" % (s, fielddisplay(self, 'mem', 'memory per CPU')) + s = "%s\n%s" % (s, fielddisplay(self, 'queue', 'name of the queue (normal (D), short, singlenode, multinode, devel)')) + s = "%s\n%s" % (s, fielddisplay(self, 'time', 'walltime requested in minutes')) + s = "%s\n%s" % (s, fielddisplay(self, 'codepath', 'code path on the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'executionpath', 'execution path on the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'interactive', '')) + s = "%s\n%s" % (s, fielddisplay(self, 'accountname', 'your cluster account')) + s = "%s\n%s" % (s, fielddisplay(self, 'profiling', 'enable profiling if 1 default is 0')) + return s + # }}} - executable='issm.exe' - if isdakota: - version=IssmConfig('_DAKOTA_VERSION_')[0:2] - version=float(version) - if version>=6: - executable='issm_dakota.exe' - if isoceancoupling: - executable='issm_ocean.exe' - #write queuing script - shortname=modelname[0:min(12,len(modelname))] - fid=open(modelname+'.queue','w') - - fid.write('#!/bin/bash -l\n') - fid.write('#SBATCH --job-name=%s \n' % shortname) - fid.write('#SBATCH --partition %s \n' % self.queue) - fid.write('#SBATCH --nodes=%i' % self.numnodes) - fid.write('#SBATCH --ntasks-per-nodes==%i \n' % self.cpuspernode) - fid.write('#SBATCH --time=%s\n' % self.time) #walltime is minutes - fid.write('#SBATCH --mem-per-cpu=%iGB\n' % self.mem)# mem is in GB - if (np.mod(self.np,16)+np.mod(self.np,20))==0: - fid.write('#SBATCH --ntask=%i\n' % self.np) - fid.write('#SBATCH --account=%s\n' % self.accountname) - fid.write('#SBATCH --output %s/%s/%s.outlog \n' % (self.executionpath,dirname,modelname)) - fid.write('#SBATCH --error %s/%s/%s.errlog \n\n' % (self.executionpath,dirname,modelname)) + def checkconsistency(self, md, solution, analyses): # {{{ + #Queue dictionarry gives queue name as key and max walltime and cpus as var + queuedict = {'normal': [2 * 24 * 60, 2048], + 'devel': [4 * 60, 2048]} + QueueRequirements(queuedict, self.queue, self.np, self.time) - fid.write('export ISSM_DIR="%s/../"\n' % self.codepath) - fid.write('module restore system\n') - fid.write('module load load Automake/1.15.1-GCCcore-6.3.0\n') - fid.write('module load libtool/2.4.6-GCCcore-6.3.0\n') - fid.write('module load CMake/3.9.1\n') - fid.write('module load PETSc/3.8.0-intel-2017a-Python-2.7.13\n') - fid.write('module load ParMETIS/4.0.3-intel-2017a\n') - fid.write('cd %s/%s/\n\n' % (self.executionpath,dirname)) - if self.profiling==1: - fid.write('module load perf-report\n') - fid.write('perf-report mpirun -np %i %s/%s %s %s/%s %s\n' % (self.np,self.codepath,executable,str(solution),self.executionpath,dirname,modelname)) - else: - fid.write('mpirun -np %i %s/%s %s %s/%s %s\n' % (self.np,self.codepath,executable,str(solution),self.executionpath,dirname,modelname)) - fid.close() + #Miscelaneous + if not self.login: + md = md.checkmessage('login empty') + if not self.codepath: + md = md.checkmessage('codepath empty') + if not self.executionpath: + md = md.checkmessage('executionpath empty') + if self.interactive == 1: + md = md.checkmessage('interactive mode not implemented') + return self + # }}} - # }}} - def UploadQueueJob(self,modelname,dirname,filelist): - # {{{ - #compress the files into one zip. - compressstring='tar -zcf %s.tar.gz ' % dirname - for file in filelist: - compressstring += ' %s' % file - subprocess.call(compressstring,shell=True) + def BuildQueueScript(self, dirname, modelname, solution, io_gather, isvalgrind, isgprof, isdakota, isoceancoupling): # {{{ + executable = 'issm.exe' + if isdakota: + version = IssmConfig('_DAKOTA_VERSION_')[0:2] + version = float(version) + if version >= 6: + executable = 'issm_dakota.exe' + if isoceancoupling: + executable = 'issm_ocean.exe' + #write queuing script + shortname = modelname[0:min(12, len(modelname))] + fid = open(modelname + '.queue', 'w') - print('uploading input file and queueing script') - issmscpout(self.name,self.executionpath,self.login,self.port,[dirname+'.tar.gz']) + fid.write('#!/bin/bash -l\n') + fid.write('#SBATCH --job-name=%s \n' % shortname) + fid.write('#SBATCH --partition %s \n' % self.queue) + fid.write('#SBATCH --nodes=%i' % self.numnodes) + fid.write('#SBATCH --ntasks-per-nodes==%i \n' % self.cpuspernode) + fid.write('#SBATCH --time=%s\n' % self.time) #walltime is minutes + fid.write('#SBATCH --mem-per-cpu=%iGB\n' % self.mem) # mem is in GB + if (np.mod(self.np, 16) + np.mod(self.np, 20)) == 0: + fid.write('#SBATCH --ntask=%i\n' % self.np) + fid.write('#SBATCH --account=%s\n' % self.accountname) + fid.write('#SBATCH --output %s/%s /%s.outlog \n' % (self.executionpath, dirname, modelname)) + fid.write('#SBATCH --error %s/%s /%s.errlog \n\n' % (self.executionpath, dirname, modelname)) - # }}} - def LaunchQueueJob(self,modelname,dirname,filelist,restart,batch): - # {{{ + fid.write('export ISSM_DIR="%s/../ "\n' % self.codepath) + fid.write('module restore system\n') + fid.write('module load load Automake/1.15.1-GCCcore-6.3.0\n') + fid.write('module load libtool/2.4.6-GCCcore-6.3.0\n') + fid.write('module load CMake/3.9.1\n') + fid.write('module load PETSc/3.8.0-intel-2017a-Python-2.7.13\n') + fid.write('module load ParMETIS/4.0.3-intel-2017a\n') + fid.write('cd %s/%s/ \n\n' % (self.executionpath, dirname)) + if self.profiling == 1: + fid.write('module load perf-report\n') + fid.write('perf-report mpirun -np %i %s/%s %s %s/%s %s\n' % (self.np, self.codepath, executable, str(solution), self.executionpath, dirname, modelname)) + else: + fid.write('mpirun -np %i %s/%s %s %s/%s %s\n' % (self.np, self.codepath, executable, str(solution), self.executionpath, dirname, modelname)) + fid.close() - print('launching solution sequence on remote cluster') - if restart: - launchcommand='cd %s && cd %s && sbatch %s.queue' % (self.executionpath,dirname,modelname) - else: - launchcommand='cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && sbatch %s.queue' % (self.executionpath,dirname,dirname,dirname,dirname,dirname,modelname) - issmssh(self.name,self.login,self.port,launchcommand) + # }}} - # }}} - def Download(self,dirname,filelist): - # {{{ + def UploadQueueJob(self, modelname, dirname, filelist): # {{{ + #compress the files into one zip. + compressstring = 'tar -zcf %s.tar.gz ' % dirname + for file in filelist: + compressstring += ' %s' % file + subprocess.call(compressstring, shell=True) - #copy files from cluster to current directory - directory='%s/%s/' % (self.executionpath,dirname) - issmscpin(self.name,self.login,self.port,directory,filelist) - # }}} + print('uploading input file and queueing script') + issmscpout(self.name, self.executionpath, self.login, self.port, [dirname + '.tar.gz']) + + # }}} + def LaunchQueueJob(self, modelname, dirname, filelist, restart, batch): # {{{ + print('launching solution sequence on remote cluster') + if restart: + launchcommand = 'cd %s && cd %s && sbatch %s.queue' % (self.executionpath, dirname, modelname) + else: + launchcommand = 'cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && sbatch %s.queue' % (self.executionpath, dirname, dirname, dirname, dirname, dirname, modelname) + issmssh(self.name, self.login, self.port, launchcommand) + + # }}} + def Download(self, dirname, filelist): # {{{ + #copy files from cluster to current directory + directory = '%s/%s/' % (self.executionpath, dirname) + issmscpin(self.name, self.login, self.port, directory, filelist) + # }}} Index: /issm/trunk-jpl/src/m/classes/clusters/generic.py =================================================================== --- /issm/trunk-jpl/src/m/classes/clusters/generic.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/clusters/generic.py (revision 24213) @@ -11,4 +11,5 @@ import MatlabFuncs as m + class generic(object): """ @@ -16,194 +17,193 @@ Usage: - cluster=generic('name','astrid','np',3); - cluster=generic('name',gethostname(),'np',3,'login','username'); + cluster = generic('name', 'astrid', 'np', 3) + cluster = generic('name', gethostname(), 'np', 3, 'login', 'username') """ - def __init__(self,*args): # {{{ - - self.name='' - self.login='' - self.np=1 - self.port=0 - self.interactive=1 - self.codepath=IssmConfig('ISSM_PREFIX')[0]+'/bin' - self.executionpath=issmdir()+'/execution' - self.valgrind=issmdir()+'/externalpackages/valgrind/install/bin/valgrind' - self.valgrindlib=issmdir()+'/externalpackages/valgrind/install/lib/libmpidebug.so' - self.valgrindsup=issmdir()+'/externalpackages/valgrind/issm.supp' - - #use provided options to change fields - options=pairoptions(*args) - - #get name - self.name=socket.gethostname() - - #initialize cluster using user settings if provided - if os.path.exists(self.name+'_settings.py'): - exec(compile(open(self.name+'_settings.py').read(), self.name+'_settings.py', 'exec'),globals()) - - #OK get other fields - self=options.AssignObjectFields(self) - # }}} - def __repr__(self): # {{{ - # display the object - s ="class '%s' object '%s' = \n" % (type(self),'self') - s+=" name: %s\n" % self.name - s+=" login: %s\n" % self.login - s+=" np: %i\n" % self.np - s+=" port: %i\n" % self.port - s+=" codepath: %s\n" % self.codepath - s+=" executionpath: %s\n" % self.executionpath - s+=" valgrind: %s\n" % self.valgrind - s+=" valgrindlib: %s\n" % self.valgrindlib - s+=" valgrindsup: %s\n" % self.valgrindsup - return s - # }}} - def checkconsistency(self,md,solution,analyses): # {{{ - if self.np<1: - md = checkmessage(md,'number of processors should be at least 1') - if math.isnan(self.np): - md = checkmessage(md,'number of processors should not be NaN!') - - return md - # }}} - def BuildQueueScript(self,dirname,modelname,solution,io_gather,isvalgrind,isgprof,isdakota,isoceancoupling): # {{{ - - executable='issm.exe'; - if isdakota: - version=IssmConfig('_DAKOTA_VERSION_') - version=float(version[0]) - if version>=6: - executable='issm_dakota.exe' - if isoceancoupling: - executable='issm_ocean.exe' - - #write queuing script - if not m.ispc(): - - fid=open(modelname+'.queue','w') - fid.write('#!/bin/sh\n') - if not isvalgrind: - if self.interactive: - if IssmConfig('_HAVE_MPI_')[0]: - fid.write('mpiexec -np %i %s/%s %s %s/%s %s ' % (self.np,self.codepath,executable,solution,self.executionpath,dirname,modelname)) - else: - fid.write('%s/%s %s %s/%s %s ' % (self.codepath,executable,solution,self.executionpath,dirname,modelname)) - else: - if IssmConfig('_HAVE_MPI_')[0]: - fid.write('mpiexec -np %i %s/%s %s %s/%s %s 2> %s.errlog >%s.outlog ' % (self.np,self.codepath,executable,solution,self.executionpath,dirname,modelname,modelname,modelname)) - else: - fid.write('%s/%s %s %s/%s %s 2> %s.errlog >%s.outlog ' % (self.codepath,executable,solution,self.executionpath,dirname,modelname,modelname,modelname)) - elif isgprof: - fid.write('\n gprof %s/%s gmon.out > %s.performance' % (self.codepath,executable,modelname)) + def __init__(self, *args): # {{{ + + self.name = '' + self.login = '' + self.np = 1 + self.port = 0 + self.interactive = 1 + self.codepath = IssmConfig('ISSM_PREFIX')[0] + '/bin' + self.executionpath = issmdir() + '/execution' + self.valgrind = issmdir() + '/externalpackages/valgrind/install/bin/valgrind' + self.valgrindlib = issmdir() + '/externalpackages/valgrind/install/lib/libmpidebug.so' + self.valgrindsup = issmdir() + '/externalpackages/valgrind/issm.supp' + + #use provided options to change fields + options = pairoptions(*args) + + #get name + self.name = socket.gethostname() + + #initialize cluster using user settings if provided + if os.path.exists(self.name + '_settings.py'): + exec(compile(open(self.name + '_settings.py').read(), self.name + '_settings.py', 'exec'), globals()) + + #OK get other fields + self = options.AssignObjectFields(self) + # }}} + + def __repr__(self): # {{{ + # display the object + s = "class '%s' object '%s' = \n" % (type(self), 'self') + s += " name: %s\n" % self.name + s += " login: %s\n" % self.login + s += " np: %i\n" % self.np + s += " port: %i\n" % self.port + s += " codepath: %s\n" % self.codepath + s += " executionpath: %s\n" % self.executionpath + s += " valgrind: %s\n" % self.valgrind + s += " valgrindlib: %s\n" % self.valgrindlib + s += " valgrindsup: %s\n" % self.valgrindsup + return s + # }}} + + def checkconsistency(self, md, solution, analyses): # {{{ + if self.np < 1: + md = checkmessage(md, 'number of processors should be at least 1') + if math.isnan(self.np): + md = checkmessage(md, 'number of processors should not be NaN!') + + return md + # }}} + def BuildQueueScript(self, dirname, modelname, solution, io_gather, isvalgrind, isgprof, isdakota, isoceancoupling): # {{{ + + executable = 'issm.exe' + if isdakota: + version = IssmConfig('_DAKOTA_VERSION_') + version = float(version[0]) + if version >= 6: + executable = 'issm_dakota.exe' + if isoceancoupling: + executable = 'issm_ocean.exe' + + #write queuing script + if not m.ispc(): + fid = open(modelname + '.queue', 'w') + fid.write('#!/bin/sh\n') + if not isvalgrind: + if self.interactive: + if IssmConfig('_HAVE_MPI_')[0]: + fid.write('mpiexec -np {} {}/{} {} {}/{} {}'.format(self.np, self.codepath, executable, solution, self.executionpath, dirname, modelname)) else: - #Add --gen-suppressions=all to get suppression lines - fid.write('LD_PRELOAD=%s \\\n' % self.valgrindlib) - if IssmConfig('_HAVE_MPI_')[0]: - fid.write('mpiexec -np %i %s --leak-check=full --suppressions=%s %s/%s %s %s/%s %s 2> %s.errlog >%s.outlog ' % \ - (self.np,self.valgrind,self.valgrindsup,self.codepath,executable,solution,self.executionpath,dirname,modelname,modelname,modelname)) - else: - fid.write('%s --leak-check=full --suppressions=%s %s/%s %s %s/%s %s 2> %s.errlog >%s.outlog ' % \ - (self.valgrind,self.valgrindsup,self.codepath,executable,solution,self.executionpath,dirname,modelname,modelname,modelname)) - - if not io_gather: #concatenate the output files: - fid.write('\ncat %s.outbin.* > %s.outbin' % (modelname,modelname)) - fid.close() - - else: # Windows - - fid=open(modelname+'.bat','w') - fid.write('@echo off\n') - if self.interactive: - fid.write('"%s/%s" %s "%s/%s" %s ' % (self.codepath,executable,solution,self.executionpath,dirname,modelname)) + fid.write('{}/{} {} {}/{} {} '.format(self.codepath, executable, solution, self.executionpath, dirname, modelname)) + else: + if IssmConfig('_HAVE_MPI_')[0]: + fid.write('mpiexec -np {} {}/{} {} {}/{} {} 2>{}.errlog>{}.outlog'. + format(self.np, self.codepath, executable, solution, self.executionpath, dirname, modelname, modelname, modelname)) else: - fid.write('"%s/%s" %s "%s/%s" %s 2> %s.errlog >%s.outlog' % \ - (self.codepath,executable,solution,self.executionpath,dirname,modelname,modelname,modelname)) - fid.close() + fid.write('{}/{} {} {}/{} {} 2>{}.errlog>{}.outlog '. + format(self.codepath, executable, solution, self.executionpath, dirname, modelname, modelname, modelname)) + elif isgprof: + fid.write('\n gprof {}/{} gmon.out > {}.performance'.format(self.codepath, executable, modelname)) + else: + #Add --gen -suppressions = all to get suppression lines + fid.write('LD_PRELOAD={} \\\n'.format(self.valgrindlib)) + if IssmConfig('_HAVE_MPI_')[0]: + fid.write('mpiexec -np {} {} --leak-check=full --suppressions={} {}/{} {} {}/{} {} 2>{}.errlog>{}.outlog '. + format(self.np, self.valgrind, self.valgrindsup, self.codepath, executable, solution, self.executionpath, dirname, modelname, modelname, modelname)) + else: + fid.write('{} --leak-check=full --suppressions={} {}/{} {} {}/{} {} 2>{}.errlog>{}.outlog '. + format(self.valgrind, self.valgrindsup, self.codepath, executable, solution, self.executionpath, dirname, modelname, modelname, modelname)) + + if not io_gather: #concatenate the output files: + fid.write('\ncat {}.outbin .*>{}.outbin'.format(modelname, modelname)) + fid.close() + + else: # Windows + + fid = open(modelname + '.bat', 'w') + fid.write('@echo off\n') + if self.interactive: + fid.write('"{}/{}" {} "{}/{}" {} '.format(self.codepath, executable, solution, self.executionpath, dirname, modelname)) + else: + fid.write('"{}/{}" {} "{}/{}" {} 2>{}.errlog>{}.outlog'. + format(self.codepath, executable, solution, self.executionpath, dirname, modelname, modelname, modelname)) + fid.close() #in interactive mode, create a run file, and errlog and outlog file + if self.interactive: + fid = open(modelname + '.errlog', 'w') + fid.close() + fid = open(modelname + '.outlog', 'w') + fid.close() + # }}} + + def BuildKrigingQueueScript(self, modelname, solution, io_gather, isvalgrind, isgprof): # {{{ + #write queuing script + if not m.ispc(): + fid = open(modelname + '.queue', 'w') + fid.write('#!/bin/sh\n') + if not isvalgrind: + if self.interactive: + fid.write('mpiexec -np {} {}/kriging.exe {}/{} {} '.format(self.np, self.codepath, self.executionpath, modelname, modelname)) + else: + fid.write('mpiexec -np {} {}/kriging.exe {}/{} {} 2>{}.errlog>{}.outlog '.format(self.np, self.codepath, self.executionpath, modelname, modelname, modelname, modelname)) + elif isgprof: + fid.write('\n gprof {}/kriging.exe gmon.out>{}.performance'.format(self.codepath, modelname)) + else: + #Add - - gen - suppressions = all to get suppression lines + #fid.write('LD_PRELOAD={} \\\n'.format(self.valgrindlib)) + fid.write('mpiexec - np {} {} --leak -check=full --suppressions={} {}/kriging.exe {}/{} {} 2 > {}.errlog > {}.outlog ' .format + (self.np, self.valgrind, self.valgrindsup, self.codepath, self.executionpath, modelname, modelname, modelname, modelname)) + if not io_gather: #concatenate the output files: + fid.write('\ncat {}.outbin. *>{}.outbin'.format(modelname, modelname)) + fid.close() + + else: # Windows + + fid = open(modelname + '.bat', 'w') + fid.write('@echo off\n') if self.interactive: - fid=open(modelname+'.errlog','w') - fid.close() - fid=open(modelname+'.outlog','w') - fid.close() - # }}} - def BuildKrigingQueueScript(self,modelname,solution,io_gather,isvalgrind,isgprof): # {{{ - - #write queuing script - if not m.ispc(): - - fid=open(modelname+'.queue','w') - fid.write('#!/bin/sh\n') - if not isvalgrind: - if self.interactive: - fid.write('mpiexec -np %i %s/kriging.exe %s/%s %s ' % (self.np,self.codepath,self.executionpath,modelname,modelname)) - else: - fid.write('mpiexec -np %i %s/kriging.exe %s/%s %s 2> %s.errlog >%s.outlog ' % (self.np,self.codepath,self.executionpath,modelname,modelname,modelname,modelname)) - elif isgprof: - fid.write('\n gprof %s/kriging.exe gmon.out > %s.performance' & (self.codepath,modelname)) - else: - #Add --gen-suppressions=all to get suppression lines - fid.write('LD_PRELOAD=%s \\\n' % self.valgrindlib) - fid.write('mpiexec -np %i %s --leak-check=full --suppressions=%s %s/kriging.exe %s/%s %s 2> %s.errlog >%s.outlog ' % \ - (self.np,self.valgrind,self.valgrindsup,self.codepath,self.executionpath,modelname,modelname,modelname,modelname)) - if not io_gather: #concatenate the output files: - fid.write('\ncat %s.outbin.* > %s.outbin' % (modelname,modelname)) - fid.close() - - else: # Windows - - fid=open(modelname+'.bat','w') - fid.write('@echo off\n') - if self.interactive: - fid.write('"%s/issm.exe" %s "%s/%s" %s ' % (self.codepath,solution,self.executionpath,modelname,modelname)) - else: - fid.write('"%s/issm.exe" %s "%s/%s" %s 2> %s.errlog >%s.outlog' % \ - (self.codepath,solution,self.executionpath,modelname,modelname,modelname,modelname)) - fid.close() - - #in interactive mode, create a run file, and errlog and outlog file - if self.interactive: - fid=open(modelname+'.errlog','w') - fid.close() - fid=open(modelname+'.outlog','w') - fid.close() - # }}} - def UploadQueueJob(self,modelname,dirname,filelist): # {{{ - + fid.write('"{}/issm.exe" {} "{}/{}" {} '.format(self.codepath, solution, self.executionpath, modelname, modelname)) + else: + fid.write('"{}/issm.exe" {} "{}/{}" {} 2>{}.errlog>{}.outlog'.format + (self.codepath, solution, self.executionpath, modelname, modelname, modelname, modelname)) + fid.close() + + #in interactive mode, create a run file, and errlog and outlog file + if self.interactive: + fid = open(modelname + '.errlog', 'w') + fid.close() + fid = open(modelname + '.outlog', 'w') + fid.close() + # }}} + + def UploadQueueJob(self, modelname, dirname, filelist): # {{{ #compress the files into one zip. - compressstring='tar -zcf %s.tar.gz ' % dirname + compressstring = 'tar -zcf {}.tar.gz '.format(dirname) for file in filelist: - compressstring += ' %s' % file + compressstring += ' {}'.format(file) if self.interactive: - compressstring += ' %s.errlog %s.outlog ' % (modelname,modelname) - subprocess.call(compressstring,shell=True) + compressstring += ' {}.errlog {}.outlog '.format(modelname, modelname) + subprocess.call(compressstring, shell=True) print('uploading input file and queueing script') - issmscpout(self.name,self.executionpath,self.login,self.port,[dirname+'.tar.gz']) - - # }}} - def LaunchQueueJob(self,modelname,dirname,filelist,restart,batch): # {{{ - + issmscpout(self.name, self.executionpath, self.login, self.port, [dirname + '.tar.gz']) + + # }}} + + def LaunchQueueJob(self, modelname, dirname, filelist, restart, batch): # {{{ print('launching solution sequence on remote cluster') if restart: - launchcommand='cd %s && cd %s chmod 777 %s.queue && ./%s.queue' % (self.executionpath,dirname,modelname,modelname) + launchcommand = 'cd {} && cd {} chmod 777 {}.queue && ./{}.queue'.format(self.executionpath, dirname, modelname, modelname) else: if batch: - launchcommand='cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz' % \ - (self.executionpath,dirname,dirname,dirname,dirname,dirname) - else: - launchcommand='cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && chmod 777 %s.queue && ./%s.queue' % \ - (self.executionpath,dirname,dirname,dirname,dirname,dirname,modelname,modelname) - issmssh(self.name,self.login,self.port,launchcommand) - # }}} - def Download(self,dirname,filelist): # {{{ - + launchcommand = 'cd {} && rm -rf ./{} && mkdir {} && cd {} && mv ../{}.tar.gz ./&& tar -zxf {}.tar.gz'.format(self.executionpath, dirname, dirname, dirname, dirname, dirname) + else: + launchcommand = 'cd {} && rm -rf ./{} && mkdir {} && cd {} && mv ../{}.tar.gz ./&& tar -zxf {}.tar.gz && chmod 777 {}.queue && ./{}.queue'.format(self.executionpath, dirname, dirname, dirname, dirname, dirname, modelname, modelname) + issmssh(self.name, self.login, self.port, launchcommand) + # }}} + + def Download(self, dirname, filelist): # {{{ if m.ispc(): #do nothing return - #copy files from cluster to current directory - directory='%s/%s/' % (self.executionpath,dirname) - issmscpin(self.name,self.login,self.port,directory,filelist) - # }}} + directory = '{}/{}/'.format(self.executionpath, dirname) + issmscpin(self.name, self.login, self.port, directory, filelist) + # }}} Index: /issm/trunk-jpl/src/m/classes/clusters/hexagon.py =================================================================== --- /issm/trunk-jpl/src/m/classes/clusters/hexagon.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/clusters/hexagon.py (revision 24213) @@ -5,147 +5,141 @@ from issmscpin import issmscpin from issmscpout import issmscpout -from QueueRequirements import QueueRequirements +from IssmConfig import IssmConfig import datetime try: - from hexagon_settings import hexagon_settings + from hexagon_settings import hexagon_settings except ImportError: - print('You need hexagon_settings.py to proceed, check presence and sys.path') + print('You need hexagon_settings.py to proceed, check presence and sys.path') + class hexagon(object): - """ - Hexagon cluster class definition - Hexagon have nodes built of 2*16 CPUs. Nodes are dedicated to one job so the best usage is to use 32 procs per nodes (16 per cores) as it is what is billed anyway. - You can reduce this number if you run out of memory as the total node memory is divided by the number of procs - Usage: - cluster=hexagon(); - """ + """ + Hexagon cluster class definition + Hexagon have nodes built of 2 * 16 CPUs. Nodes are dedicated to one job so the best usage is to use 32 procs per nodes (16 per cores) as it is what is billed anyway. + You can reduce this number if you run out of memory as the total node memory is divided by the number of procs + Usage: + cluster = hexagon() + """ - def __init__(self,*args): - # {{{ - self.name = 'hexagon' - self.login = '' - self.numnodes = 2 - self.procspernodes = 32 - self.mem = 32000 - self.queue = 'batch' - self.time = 2*60 - self.codepath = '' - self.executionpath = '' - self.interactive = 0 - self.port = [] - self.accountname = '' + def __init__(self, *args): # {{{ + self.name = 'hexagon' + self.login = '' + self.numnodes = 2 + self.procspernodes = 32 + self.mem = 32000 + self.queue = 'batch' + self.time = 2 * 60 + self.codepath = '' + self.executionpath = '' + self.interactive = 0 + self.port = [] + self.accountname = '' - #use provided options to change fields - options=pairoptions(*args) + #use provided options to change fields + options = pairoptions(*args) - #initialize cluster using user settings if provided - self=hexagon_settings(self) + #initialize cluster using user settings if provided + self = hexagon_settings(self) - #OK get other fields - self=options.AssignObjectFields(self) - self.np=self.numnodes*self.procspernodes - # }}} + #OK get other fields + self = options.AssignObjectFields(self) + self.np = self.numnodes * self.procspernodes + # }}} - def __repr__(self): - # {{{ - # display the object - s = "class hexagon object:" - s = "%s\n%s"%(s,fielddisplay(self,'name','name of the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'login','login')) - s = "%s\n%s"%(s,fielddisplay(self,'numnodes','number of nodes')) - s = "%s\n%s"%(s,fielddisplay(self,'procspernodes','number of mpi procs per nodes default and optimal is 32')) - s = "%s\n%s"%(s,fielddisplay(self,'mem','Total node memory')) - s = "%s\n%s"%(s,fielddisplay(self,'queue','name of the queue')) - s = "%s\n%s"%(s,fielddisplay(self,'time','walltime requested in minutes')) - s = "%s\n%s"%(s,fielddisplay(self,'codepath','code path on the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'executionpath','execution path on the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'interactive','')) - s = "%s\n%s"%(s,fielddisplay(self,'accountname','your cluster account')) - return s - # }}} + def __repr__(self): # {{{ + # display the object + s = "class hexagon object:" + s = "%s\n%s" % (s, fielddisplay(self, 'name', 'name of the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'login', 'login')) + s = "%s\n%s" % (s, fielddisplay(self, 'numnodes', 'number of nodes')) + s = "%s\n%s" % (s, fielddisplay(self, 'procspernodes', 'number of mpi procs per nodes default and optimal is 32')) + s = "%s\n%s" % (s, fielddisplay(self, 'mem', 'Total node memory')) + s = "%s\n%s" % (s, fielddisplay(self, 'queue', 'name of the queue')) + s = "%s\n%s" % (s, fielddisplay(self, 'time', 'walltime requested in minutes')) + s = "%s\n%s" % (s, fielddisplay(self, 'codepath', 'code path on the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'executionpath', 'execution path on the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'interactive', '')) + s = "%s\n%s" % (s, fielddisplay(self, 'accountname', 'your cluster account')) + return s + # }}} - def checkconsistency(self,md,solution,analyses): - # {{{ - #mem should not be over 32000mb - #numprocs should not be over 4096 - #we have cpupernodes*numberofcpus=mppwidth and mppnppn=cpupernodes, - #Miscelaneous - if not self.login: - md = md.checkmessage('login empty') - if not self.codepath: - md = md.checkmessage('codepath empty') - if not self.executionpath: - md = md.checkmessage('executionpath empty') - if self.interactive==1: - md = md.checkmessage('interactive mode not implemented') - if self.mem>32000: - md = md.checkmessage('asking too much memory max is 32000 per node') - return self - # }}} + def checkconsistency(self, md, solution, analyses): # {{{ + #mem should not be over 32000mb + #numprocs should not be over 4096 + #we have cpupernodes * numberofcpus = mppwidth and mppnppn = cpupernodes, + #Miscelaneous + if not self.login: + md = md.checkmessage('login empty') + if not self.codepath: + md = md.checkmessage('codepath empty') + if not self.executionpath: + md = md.checkmessage('executionpath empty') + if self.interactive == 1: + md = md.checkmessage('interactive mode not implemented') + if self.mem > 32000: + md = md.checkmessage('asking too much memory max is 32000 per node') + return self + # }}} - def BuildQueueScript(self,dirname,modelname,solution,io_gather,isvalgrind,isgprof,isdakota,isoceancoupling): - # {{{ - executable='issm.exe' - if isdakota: - version=IssmConfig('_DAKOTA_VERSION_')[0:2] - version=float(version) - if version>=6: - executable='issm_dakota.exe' - if isoceancoupling: - executable='issm_ocean.exe' + def BuildQueueScript(self, dirname, modelname, solution, io_gather, isvalgrind, isgprof, isdakota, isoceancoupling): # {{{ + executable = 'issm.exe' + if isdakota: + version = IssmConfig('_DAKOTA_VERSION_')[0:2] + version = float(version) + if version >= 6: + executable = 'issm_dakota.exe' + if isoceancoupling: + executable = 'issm_ocean.exe' - #write queuing script - shortname=modelname[0:min(12,len(modelname))] - fid=open(modelname+'.queue','w') - fid.write('#!/bin/bash\n') - fid.write('#PBS -N %s \n' % shortname) - fid.write('#PBS -l mppwidth=%i,mppnppn=%i\n' % (self.np,self.procspernodes)) - timeobj=datetime.timedelta(minutes=self.time) - m,s=divmod(timeobj.total_seconds(), 60) - h,m=divmod(m, 60) - timestring="%02d:%02d:%02d" % (h, m, s) - fid.write('#PBS -l walltime=%s\n' % timestring) #walltime is hh:mm:ss - fid.write('#PBS -l mppmem=%imb\n' % int(self.mem/self.procspernodes)) - fid.write('#PBS -A %s\n' % self.accountname) - fid.write('#PBS -o %s/%s/%s.outlog \n' % (self.executionpath,dirname,modelname)) - fid.write('#PBS -e %s/%s/%s.errlog \n\n' % (self.executionpath,dirname,modelname)) - fid.write('export ISSM_DIR="%s/../"\n' % self.codepath) - fid.write('export CRAY_ROOTFS=DSL\n') - fid.write('module swap PrgEnv-cray/5.2.40 PrgEnv-gnu\n') - fid.write('module load cray-petsc\n') - fid.write('module load cray-tpsl\n') - fid.write('module load cray-mpich\n') - fid.write('module load gsl\n') - fid.write('cd %s/%s/\n\n' % (self.executionpath,dirname)) - fid.write('aprun -B %s/%s %s %s/%s %s\n' % (self.codepath,executable,str(solution),self.executionpath,dirname,modelname)) - fid.close() - # }}} + #write queuing script + shortname = modelname[0:min(12, len(modelname))] + fid = open(modelname + '.queue', 'w') + fid.write(' #!/bin/bash\n') + fid.write(' #PBS - N %s \n' % shortname) + fid.write(' #PBS - l mppwidth=%i, mppnppn=%i\n' % (self.np, self.procspernodes)) + timeobj = datetime.timedelta(minutes=self.time) + m, s = divmod(timeobj.total_seconds(), 60) + h, m = divmod(m, 60) + timestring = "%02d:%02d:%02d" % (h, m, s) + fid.write('#PBS -l walltime=%s\n' % timestring) #walltime is hh:mm:ss + fid.write('#PBS -l mppmem=%imb\n' % int(self.mem / self.procspernodes)) + fid.write('#PBS -A %s\n' % self.accountname) + fid.write('#PBS -o %s/%s/%s.outlog \n' % (self.executionpath, dirname, modelname)) + fid.write('#PBS -e %s/%s/%s.errlog \n\n' % (self.executionpath, dirname, modelname)) + fid.write('export ISSM_DIR = "%s/../"\n' % self.codepath) + fid.write('export CRAY_ROOTFS = DSL\n') + fid.write('module swap PrgEnv-cray / 5.2.40 PrgEnv - gnu\n') + fid.write('module load cray-petsc\n') + fid.write('module load cray-tpsl\n') + fid.write('module load cray-mpich\n') + fid.write('module load gsl\n') + fid.write('cd %s/%s/\n\n' % (self.executionpath, dirname)) + fid.write('aprun -B %s/%s %s %s/%s %s\n' % (self.codepath, executable, str(solution), self.executionpath, dirname, modelname)) + fid.close() + # }}} - def UploadQueueJob(self,modelname,dirname,filelist): - # {{{ - #compress the files into one zip. - compressstring='tar -zcf %s.tar.gz ' % dirname - for file in filelist: - compressstring += ' %s' % file - subprocess.call(compressstring,shell=True) + def UploadQueueJob(self, modelname, dirname, filelist): # {{{ + #compress the files into one zip. + compressstring = 'tar -zcf %s.tar.gz ' % dirname + for file in filelist: + compressstring += ' %s' % file + subprocess.call(compressstring, shell=True) - print('uploading input file and queueing script') - issmscpout(self.name,self.executionpath,self.login,self.port,[dirname+'.tar.gz']) - # }}} + print('uploading input file and queueing script') + issmscpout(self.name, self.executionpath, self.login, self.port, [dirname + '.tar.gz']) + # }}} - def LaunchQueueJob(self,modelname,dirname,filelist,restart,batch): - # {{{ - print('launching solution sequence on remote cluster') - if restart: - launchcommand='cd %s && cd %s && qsub %s.queue' % (self.executionpath,dirname,modelname) - else: - launchcommand='cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && qsub %s.queue' % (self.executionpath,dirname,dirname,dirname,dirname,dirname,modelname) - issmssh(self.name,self.login,self.port,launchcommand) - # }}} + def LaunchQueueJob(self, modelname, dirname, filelist, restart, batch): # {{{ + print('launching solution sequence on remote cluster') + if restart: + launchcommand = 'cd %s && cd %s && qsub %s.queue' % (self.executionpath, dirname, modelname) + else: + launchcommand = 'cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && qsub %s.queue' % (self.executionpath, dirname, dirname, dirname, dirname, dirname, modelname) + issmssh(self.name, self.login, self.port, launchcommand) + # }}} - def Download(self,dirname,filelist): - # {{{ - #copy files from cluster to current directory - directory='%s/%s/' % (self.executionpath,dirname) - issmscpin(self.name,self.login,self.port,directory,filelist) - # }}} + def Download(self, dirname, filelist): # {{{ + #copy files from cluster to current directory + directory = '%s/%s/' % (self.executionpath, dirname) + issmscpin(self.name, self.login, self.port, directory, filelist) + # }}} Index: /issm/trunk-jpl/src/m/classes/clusters/pfe.py =================================================================== --- /issm/trunk-jpl/src/m/classes/clusters/pfe.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/clusters/pfe.py (revision 24213) @@ -1,5 +1,2 @@ -# import socket -# import os -# import math import subprocess from fielddisplay import fielddisplay @@ -9,192 +6,182 @@ from issmscpout import issmscpout from QueueRequirements import QueueRequirements +from IssmConfig import IssmConfig try: - from pfe_settings import pfe_settings + from pfe_settings import pfe_settings except ImportError: - print('You need pfe_settings.py to proceed, check presence and sys.path') - -class pfe(object): - """ - PFE cluster class definition - - Usage: - cluster=pfe(); - cluster=pfe('np',3); - cluster=pfe('np',3,'login','username'); - """ - - def __init__(self,*args): - # {{{ - - self.name = 'pfe' - self.login = '' - self.numnodes = 20 - self.cpuspernode = 8 - self.port = 1025 - self.queue = 'long' - self.time = 12*60 - self.processor = 'wes' - self.codepath = '' - self.executionpath = '' - self.grouplist = 's1010' - self.interactive = 0 - self.bbftp = 0 - self.numstreams = 8 - self.hyperthreading = 0 - - #use provided options to change fields - options=pairoptions(*args) - - #initialize cluster using user settings if provided - self=pfe_settings(self) - self.np=self.nprocs() - #OK get other fields - self=options.AssignObjectFields(self) - - # }}} - - def __repr__(self): - # {{{ - # display the object - s = "class pfe object:" - s = "%s\n%s"%(s,fielddisplay(self,'name','name of the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'login','login')) - s = "%s\n%s"%(s,fielddisplay(self,'numnodes','number of nodes')) - s = "%s\n%s"%(s,fielddisplay(self,'cpuspernode','number of nodes per CPUs')) - s = "%s\n%s"%(s,fielddisplay(self,'np','number of CPUs')) - s = "%s\n%s"%(s,fielddisplay(self,'port','machine access port')) - s = "%s\n%s"%(s,fielddisplay(self,'codepath','code path on the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'executionpath','execution path on the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'queue','name of the queue')) - s = "%s\n%s"%(s,fielddisplay(self,'time','walltime requested')) - s = "%s\n%s"%(s,fielddisplay(self,'processor','type of processor')) - s = "%s\n%s"%(s,fielddisplay(self,'grouplist','name of the group')) - s = "%s\n%s"%(s,fielddisplay(self,'interactive','')) - s = "%s\n%s"%(s,fielddisplay(self,'bbftp','')) - s = "%s\n%s"%(s,fielddisplay(self,'numstreams','')) - s = "%s\n%s"%(s,fielddisplay(self,'hyperthreading','')) - return s - # }}} - - def nprocs(self): - # {{{ - self.np=self.numnodes*self.cpuspernode - return self.np - # }}} - def checkconsistency(self,md,solution,analyses): - # {{{ + print('You need pfe_settings.py to proceed, check presence and sys.path') - queuedict = {'long': [5*24*60, 2048], - 'normal': [8*60, 2048], - 'debug':[2*60,150], - 'devel':[2*60,150]} - QueueRequirements(queuedict,self.queue,self.nprocs(),self.time) +class pfe(object): + """ + PFE cluster class definition - #now, check cluster.cpuspernode according to processor type - if self.processor=='har' or self.processor=='neh': - if self.hyperthreading: - if not 0=6: - executable='issm_dakota.exe' - if isoceancoupling: - executable='issm_ocean.exe' + #initialize cluster using user settings if provided + self = pfe_settings(self) + self.np = self.nprocs() + #OK get other fields + self = options.AssignObjectFields(self) - #write queuing script - fid=open(modelname+'.queue','w') - fid.write('#PBS -S /bin/bash\n') - fid.write('#PBS -l select=%i:ncpus=%i:model=%s\n' % (self.numnodes,self.cpuspernode,self.processor)) - fid.write('#PBS -l walltime=%i\n' % (self.time*60)) - fid.write('#PBS -q %s \n' % self.queue) - fid.write('#PBS -W group_list=%s\n' % self.grouplist) - fid.write('#PBS -m e\n') - fid.write('#PBS -o %s/%s/%s.outlog \n' % (self.executionpath,dirname,modelname)) - fid.write('#PBS -e %s/%s/%s.errlog \n\n' % (self.executionpath,dirname,modelname)) - fid.write('. /usr/share/modules/init/bash\n\n') - fid.write('module load comp-intel/2015.0.090\n') - fid.write('module load mpi-sgi/mpt.2.11r13\n') - fid.write('export PATH="$PATH:."\n\n') - fid.write('export MPI_GROUP_MAX=64\n\n') - fid.write('export ISSM_DIR="%s/../"\n' % self.codepath) - fid.write('source $ISSM_DIR/etc/environment.sh\n') - fid.write('cd %s/%s/\n\n' % (self.executionpath,dirname)) - fid.write('mpiexec -np %i %s/%s %s %s/%s %s\n' % (self.nprocs(),self.codepath,executable,str(solution),self.executionpath,dirname,modelname)) - - fid.close() + # }}} - # }}} - def UploadQueueJob(self,modelname,dirname,filelist): - # {{{ + def __repr__(self): # {{{ + # display the object + s = "class pfe object:" + s = "%s\n%s" % (s, fielddisplay(self, 'name', 'name of the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'login', 'login')) + s = "%s\n%s" % (s, fielddisplay(self, 'numnodes', 'number of nodes')) + s = "%s\n%s" % (s, fielddisplay(self, 'cpuspernode', 'number of nodes per CPUs')) + s = "%s\n%s" % (s, fielddisplay(self, 'np', 'number of CPUs')) + s = "%s\n%s" % (s, fielddisplay(self, 'port', 'machine access port')) + s = "%s\n%s" % (s, fielddisplay(self, 'codepath', 'code path on the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'executionpath', 'execution path on the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'queue', 'name of the queue')) + s = "%s\n%s" % (s, fielddisplay(self, 'time', 'walltime requested')) + s = "%s\n%s" % (s, fielddisplay(self, 'processor', 'type of processor')) + s = "%s\n%s" % (s, fielddisplay(self, 'grouplist', 'name of the group')) + s = "%s\n%s" % (s, fielddisplay(self, 'interactive', '')) + s = "%s\n%s" % (s, fielddisplay(self, 'bbftp', '')) + s = "%s\n%s" % (s, fielddisplay(self, 'numstreams', '')) + s = "%s\n%s" % (s, fielddisplay(self, 'hyperthreading', '')) + return s + # }}} - #compress the files into one zip. - compressstring='tar -zcf %s.tar.gz ' % dirname - for file in filelist: - compressstring += ' %s' % file - subprocess.call(compressstring,shell=True) + def nprocs(self): # {{{ + self.np = self.numnodes * self.cpuspernode + return self.np + # }}} - print('uploading input file and queueing script') - issmscpout(self.name,self.executionpath,self.login,self.port,[dirname+'.tar.gz']) + def checkconsistency(self, md, solution, analyses): # {{{ + queuedict = {'long': [5 * 24 * 60, 2048], + 'normal': [8 * 60, 2048], + 'debug': [2 * 60, 150], + 'devel': [2 * 60, 150]} + QueueRequirements(queuedict, self.queue, self.nprocs(), self.time) - # }}} - def LaunchQueueJob(self,modelname,dirname,filelist,restart,batch): - # {{{ + #now, check cluster.cpuspernode according to processor type + if self.processor == 'har' or self.processor == 'neh': + if self.hyperthreading: + if not 0 < self.cpuspernode < 17: + md = md.checkmessage('cpuspernode should be between 1 and 16 for ''neh'' and ''har'' processors in hyperthreading mode') + else: + if not 0 < self.cpuspernode < 9: + md = md.checkmessage('cpuspernode should be between 1 and 8 for ''neh'' and ''har'' processors') - print('launching solution sequence on remote cluster') - if restart: - launchcommand='cd %s && cd %s && qsub %s.queue' % (self.executionpath,dirname,modelname) - else: - launchcommand='cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && qsub %s.queue' % (self.executionpath,dirname,dirname,dirname,dirname,dirname,modelname) - issmssh(self.name,self.login,self.port,launchcommand) + elif self.processor == 'wes': + if self.hyperthreading: + if not 0 < self.cpuspernode < 25: + md = md.checkmessage('cpuspernode should be between 1 and 24 for ''wes'' processors in hyperthreading mode') + else: + if not 0 < self.cpuspernode < 13: + md = md.checkmessage('cpuspernode should be between 1 and 12 for ''wes'' processors') - # }}} - def Download(self,dirname,filelist): - # {{{ + elif self.processor == 'ivy': + if self.hyperthreading: + if not 0 < self.cpuspernode < 41: + md = md.checkmessage('cpuspernode should be between 1 and 40 for ''ivy'' processors in hyperthreading mode') + else: + if not 0 < self.cpuspernode < 21: + md = md.checkmessage('cpuspernode should be between 1 and 20 for ''ivy'' processors') + else: + md = md.checkmessage('unknown processor type, should be ''neh'', ''wes'' or ''har'' or ''ivy''') - #copy files from cluster to current directory - directory='%s/%s/' % (self.executionpath,dirname) - issmscpin(self.name,self.login,self.port,directory,filelist) - # }}} + #Miscelaneous + if not self.login: + md = md.checkmessage('login empty') + if not self.codepath: + md = md.checkmessage('codepath empty') + if not self.executionpath: + md = md.checkmessage('executionpath empty') + if not self.grouplist: + md = md.checkmessage('grouplist empty') + if self.interactive == 1: + md = md.checkmessage('interactive mode not implemented') + + return self + # }}} + + def BuildQueueScript(self, dirname, modelname, solution, io_gather, isvalgrind, isgprof, isdakota, isoceancoupling): # {{{ + executable = 'issm.exe' + if isdakota: + version = IssmConfig('_DAKOTA_VERSION_')[0:2] + version = float(version) + if version >= 6: + executable = 'issm_dakota.exe' + if isoceancoupling: + executable = 'issm_ocean.exe' + + #write queuing script + fid = open(modelname + '.queue', 'w') + fid.write('#PBS -S / bin / bash\n') + fid.write('#PBS -l select=%i:ncpus=%i:model=%s\n' % (self.numnodes, self.cpuspernode, self.processor)) + fid.write('#PBS -l walltime=%i\n' % (self.time * 60)) + fid.write('#PBS -q %s \n' % self.queue) + fid.write('#PBS -W group_list=%s\n' % self.grouplist) + fid.write('#PBS -m e\n') + fid.write('#PBS -o %s/%s/%s.outlog \n' % (self.executionpath, dirname, modelname)) + fid.write('#PBS -e %s/%s/%s.errlog \n\n' % (self.executionpath, dirname, modelname)) + fid.write('./usr/share/modules/init/bash\n\n') + fid.write('module load comp-intel/2015.0.090\n') + fid.write('module load mpi-sgi/mpt.2.11r13\n') + fid.write('export PATH = "$PATH:."\n\n') + fid.write('export MPI_GROUP_MAX = 64\n\n') + fid.write('export ISSM_DIR = "%s/../ "\n' % self.codepath) + fid.write('source $ISSM_DIR/etc/environment.sh\n') + fid.write('cd %s/%s/ \n\n' % (self.executionpath, dirname)) + fid.write('mpiexec - np %i %s/%s %s %s/%s %s\n' % (self.nprocs(), self.codepath, executable, str(solution), self.executionpath, dirname, modelname)) + + fid.close() + + # }}} + + def UploadQueueJob(self, modelname, dirname, filelist): # {{{ + #compress the files into one zip. + compressstring = 'tar -zcf %s.tar.gz ' % dirname + for file in filelist: + compressstring += ' %s' % file + subprocess.call(compressstring, shell=True) + + print('uploading input file and queueing script') + issmscpout(self.name, self.executionpath, self.login, self.port, [dirname + '.tar.gz']) + + # }}} + def LaunchQueueJob(self, modelname, dirname, filelist, restart, batch): # {{{ + print('launching solution sequence on remote cluster') + if restart: + launchcommand = 'cd %s && cd %s && qsub %s.queue' % (self.executionpath, dirname, modelname) + else: + launchcommand = 'cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && qsub %s.queue' % (self.executionpath, dirname, dirname, dirname, dirname, dirname, modelname) + issmssh(self.name, self.login, self.port, launchcommand) + + # }}} + def Download(self, dirname, filelist): # {{{ + #copy files from cluster to current directory + directory = '%s/%s/' % (self.executionpath, dirname) + issmscpin(self.name, self.login, self.port, directory, filelist) + # }}} Index: /issm/trunk-jpl/src/m/classes/clusters/stallo.py =================================================================== --- /issm/trunk-jpl/src/m/classes/clusters/stallo.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/clusters/stallo.py (revision 24213) @@ -7,168 +7,166 @@ from issmscpout import issmscpout from QueueRequirements import QueueRequirements +from IssmConfig import IssmConfig import datetime try: - from stallo_settings import stallo_settings + from stallo_settings import stallo_settings except ImportError: - print('You need stallo_settings.py to proceed, check presence and sys.path') + print('You need stallo_settings.py to proceed, check presence and sys.path') + class stallo(object): - """ - Stallo cluster class definition - This is a SLURM queue - The priorities are given to: - - Large jobs - - Short jobs - - small number of job per user + """ + Stallo cluster class definition + This is a SLURM queue + The priorities are given to: + - Large jobs + - Short jobs + - small number of job per user - There are some 20cpu nodes and 16cpu nodes, with 32GB (a few with 128GB) mem per node, you can ask for part of a node if you need more memory.(1 node, 2 CPUS and 10GB per cpu for example) + There are some 20cpu nodes and 16cpu nodes, with 32GB (a few with 128GB) mem per node, you can ask for part of a node if you need more memory.(1 node, 2 CPUS and 10GB per cpu for example) - Usage: - cluster=stallo(); - """ + Usage: + cluster = stallo() + """ - def __init__(self,*args): - # {{{ - self.name = 'stallo' - self.login = '' - self.numnodes = 2 - self.cpuspernode = 20 - self.mem = 1.6 - self.queue = 'normal' - self.time = 2*60 - self.codepath = '' - self.executionpath = '' - self.interactive = 0 - self.port = [] - self.accountname = '' - self.profiling = 0 - #use provided options to change fields - options=pairoptions(*args) + def __init__(self, *args): # {{{ + self.name = 'stallo' + self.login = '' + self.numnodes = 2 + self.cpuspernode = 20 + self.mem = 1.6 + self.queue = 'normal' + self.time = 2 * 60 + self.codepath = '' + self.executionpath = '' + self.interactive = 0 + self.port = [] + self.accountname = '' + self.profiling = 0 + #use provided options to change fields + options = pairoptions(*args) - #initialize cluster using user settings if provided - self=stallo_settings(self) - #OK get other fields - self=options.AssignObjectFields(self) - self.np=self.numnodes*self.cpuspernode - # }}} + #initialize cluster using user settings if provided + self = stallo_settings(self) + #OK get other fields + self = options.AssignObjectFields(self) + self.np = self.numnodes * self.cpuspernode + # }}} - def __repr__(self): - # {{{ - # display the object - s = "class vilje object:" - s = "%s\n%s"%(s,fielddisplay(self,'name','name of the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'login','login')) - s = "%s\n%s"%(s,fielddisplay(self,'numnodes','number of nodes')) - s = "%s\n%s"%(s,fielddisplay(self,'cpuspernode','number of CPUs per nodes')) - s = "%s\n%s"%(s,fielddisplay(self,'mem','memory per CPU')) - s = "%s\n%s"%(s,fielddisplay(self,'queue','name of the queue (normal (D), short,singlenode,multinode,devel)')) - s = "%s\n%s"%(s,fielddisplay(self,'time','walltime requested in minutes')) - s = "%s\n%s"%(s,fielddisplay(self,'codepath','code path on the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'executionpath','execution path on the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'interactive','')) - s = "%s\n%s"%(s,fielddisplay(self,'accountname','your cluster account')) - s = "%s\n%s"%(s,fielddisplay(self,'profiling','enable profiling if 1 default is 0')) - return s - # }}} - def checkconsistency(self,md,solution,analyses): - # {{{ - #Queue dictionarry gives queue name as key and max walltime and cpus as var - queuedict = {'short':[60, 2048], - 'normal':[2*24*60,2048], - 'singlenode':[28*24*60,20], - 'multinode':[28*24*60,2048], - 'devel':[4*60,2048]} - QueueRequirements(queuedict,self.queue,self.np,self.time) + def __repr__(self): # {{{ + # display the object + s = "class vilje object:" + s = "%s\n%s" % (s, fielddisplay(self, 'name', 'name of the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'login', 'login')) + s = "%s\n%s" % (s, fielddisplay(self, 'numnodes', 'number of nodes')) + s = "%s\n%s" % (s, fielddisplay(self, 'cpuspernode', 'number of CPUs per nodes')) + s = "%s\n%s" % (s, fielddisplay(self, 'mem', 'memory per CPU')) + s = "%s\n%s" % (s, fielddisplay(self, 'queue', 'name of the queue (normal (D), short, singlenode, multinode, devel)')) + s = "%s\n%s" % (s, fielddisplay(self, 'time', 'walltime requested in minutes')) + s = "%s\n%s" % (s, fielddisplay(self, 'codepath', 'code path on the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'executionpath', 'execution path on the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'interactive', '')) + s = "%s\n%s" % (s, fielddisplay(self, 'accountname', 'your cluster account')) + s = "%s\n%s" % (s, fielddisplay(self, 'profiling', 'enable profiling if 1 default is 0')) + return s + # }}} - #Miscelaneous - if not self.login: - md = md.checkmessage('login empty') - if not self.codepath: - md = md.checkmessage('codepath empty') - if not self.executionpath: - md = md.checkmessage('executionpath empty') - if self.interactive==1: - md = md.checkmessage('interactive mode not implemented') - return self - # }}} - def BuildQueueScript(self,dirname,modelname,solution,io_gather,isvalgrind,isgprof,isdakota,isoceancoupling): - # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ + #Queue dictionarry gives queue name as key and max walltime and cpus as var + queuedict = {'short': [60, 2048], + 'normal': [2 * 24 * 60, 2048], + 'singlenode': [28 * 24 * 60, 20], + 'multinode': [28 * 24 * 60, 2048], + 'devel': [4 * 60, 2048]} + QueueRequirements(queuedict, self.queue, self.np, self.time) - executable='issm.exe' - if isdakota: - version=IssmConfig('_DAKOTA_VERSION_')[0:2] - version=float(version) - if version>=6: - executable='issm_dakota.exe' - if isoceancoupling: - executable='issm_ocean.exe' - #write queuing script - shortname=modelname[0:min(12,len(modelname))] - timeobj=datetime.timedelta(minutes=self.time) - m,s=divmod(timeobj.total_seconds(), 60) - h,m=divmod(m, 60) - d,h=divmod(h, 60) - timestring="%02d-%02d:%02d:%02d" % (d, h, m, s) + #Miscelaneous + if not self.login: + md = md.checkmessage('login empty') + if not self.codepath: + md = md.checkmessage('codepath empty') + if not self.executionpath: + md = md.checkmessage('executionpath empty') + if self.interactive == 1: + md = md.checkmessage('interactive mode not implemented') + return self + # }}} - fid=open(modelname+'.queue','w') - fid.write('#!/bin/bash -l\n') - fid.write('#SBATCH --job-name=%s \n' % shortname) - fid.write('#SBATCH --qos=%s \n' % self.queue) - fid.write('#SBATCH --nodes=%i \n' % self.numnodes) - fid.write('#SBATCH --ntasks-per-node=%i \n' % self.cpuspernode) - fid.write('#SBATCH --time={}\n'.format(timestring)) #walltime is minutes - fid.write('#SBATCH --mem-per-cpu={}MB\n'.format(int(1000*self.mem)))# mem is in MB - if (np.mod(self.np,16)+np.mod(self.np,20))==0: - fid.write('#SBATCH --ntask=%i\n' % self.np) - fid.write('#SBATCH --account=%s\n' % self.accountname) - fid.write('#SBATCH --output %s/%s/%s.outlog \n' % (self.executionpath,dirname,modelname)) - fid.write('#SBATCH --error %s/%s/%s.errlog \n\n' % (self.executionpath,dirname,modelname)) + def BuildQueueScript(self, dirname, modelname, solution, io_gather, isvalgrind, isgprof, isdakota, isoceancoupling): # {{{ - fid.write('export ISSM_DIR="%s/../"\n' % self.codepath) - fid.write('module purge\n') - fid.write('module load CMake/3.8.0-GCCcore-6.3.0\n') - fid.write('module load Automake/1.15.1-GCCcore-6.3.0\n') - fid.write('module load libtool/2.4.6\n') - fid.write('module load OpenSSL/1.1.0e-intel-2017a\n') - fid.write('module load PETSc/3.7.5-intel-2017a-downloaded-deps\n') + executable = 'issm.exe' + if isdakota: + version = IssmConfig('_DAKOTA_VERSION_')[0:2] + version = float(version) + if version >= 6: + executable = 'issm_dakota.exe' + if isoceancoupling: + executable = 'issm_ocean.exe' + #write queuing script + shortname = modelname[0:min(12, len(modelname))] + timeobj = datetime.timedelta(minutes=self.time) + m, s = divmod(timeobj.total_seconds(), 60) + h, m = divmod(m, 60) + d, h = divmod(h, 60) + timestring = "%02d-%02d:%02d:%02d" % (d, h, m, s) - fid.write('cd %s/%s/\n\n' % (self.executionpath,dirname)) - if self.profiling==1: - fid.write('module load perf-report\n') - fid.write('perf-report mpirun -np %i %s/%s %s %s/%s %s\n' % (self.np,self.codepath,executable,str(solution),self.executionpath,dirname,modelname)) - else: - fid.write('mpirun -np %i %s/%s %s %s/%s %s\n' % (self.np,self.codepath,executable,str(solution),self.executionpath,dirname,modelname)) - fid.close() + fid = open(modelname + '.queue', 'w') + fid.write('#!/bin/bash -l\n') + fid.write('#SBATCH --job - name=%s \n' % shortname) + fid.write('#SBATCH --qos=%s \n' % self.queue) + fid.write('#SBATCH --nodes=%i \n' % self.numnodes) + fid.write('#SBATCH --ntasks - per - node=%i \n' % self.cpuspernode) + fid.write('#SBATCH --time={}\n'.format(timestring)) #walltime is minutes + fid.write('#SBATCH --mem-per-cpu={}MB\n'.format(int(1000 * self.mem))) # mem is in MB + if (np.mod(self.np, 16) + np.mod(self.np, 20)) == 0: + fid.write(' #SBATCH --ntask=%i\n' % self.np) + fid.write('#SBATCH --account=%s\n' % self.accountname) + fid.write('#SBATCH --output %s/%s/%s.outlog \n' % (self.executionpath, dirname, modelname)) + fid.write('#SBATCH --error %s/%s/%s.errlog \n\n' % (self.executionpath, dirname, modelname)) - # }}} - def UploadQueueJob(self,modelname,dirname,filelist): - # {{{ - #compress the files into one zip. - compressstring='tar -zcf %s.tar.gz ' % dirname - for file in filelist: - compressstring += ' %s' % file - subprocess.call(compressstring,shell=True) + fid.write('export ISSM_DIR = "%s/../"\n' % self.codepath) + fid.write('module purge\n') + fid.write('module load CMake/3.8.0-GCCcore-6.3.0\n') + fid.write('module load Automake/1.15.1-GCCcore-6.3.0\n') + fid.write('module load libtool/2.4.6\n') + fid.write('module load OpenSSL/1.1.0e-intel-2017a\n') + fid.write('module load PETSc/3.7.5-intel-2017a-downloaded-deps\n') - print('uploading input file and queueing script') - issmscpout(self.name,self.executionpath,self.login,self.port,[dirname+'.tar.gz']) + fid.write('cd %s/%s/ \n\n' % (self.executionpath, dirname)) + if self.profiling == 1: + fid.write('module load perf-report\n') + fid.write('perf-report mpirun -np %i %s/%s %s %s/%s %s\n' % (self.np, self.codepath, executable, str(solution), self.executionpath, dirname, modelname)) + else: + fid.write('mpirun -np %i %s/%s %s %s/%s %s\n' % (self.np, self.codepath, executable, str(solution), self.executionpath, dirname, modelname)) + fid.close() - # }}} - def LaunchQueueJob(self,modelname,dirname,filelist,restart,batch): - # {{{ + # }}} + def UploadQueueJob(self, modelname, dirname, filelist): # {{{ + #compress the files into one zip. + compressstring = 'tar -zcf %s.tar.gz ' % dirname + for file in filelist: + compressstring += ' %s' % file + subprocess.call(compressstring, shell=True) - print('launching solution sequence on remote cluster') - if restart: - launchcommand='cd %s && cd %s && sbatch %s.queue' % (self.executionpath,dirname,modelname) - else: - launchcommand='cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && sbatch %s.queue' % (self.executionpath,dirname,dirname,dirname,dirname,dirname,modelname) - issmssh(self.name,self.login,self.port,launchcommand) + print('uploading input file and queueing script') + issmscpout(self.name, self.executionpath, self.login, self.port, [dirname + '.tar.gz']) - # }}} - def Download(self,dirname,filelist): - # {{{ + # }}} - #copy files from cluster to current directory - directory='%s/%s/' % (self.executionpath,dirname) - issmscpin(self.name,self.login,self.port,directory,filelist) - # }}} + def LaunchQueueJob(self, modelname, dirname, filelist, restart, batch): # {{{ + + print('launching solution sequence on remote cluster') + if restart: + launchcommand = 'cd %s && cd %s && sbatch %s.queue' % (self.executionpath, dirname, modelname) + else: + launchcommand = 'cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && sbatch %s.queue' % (self.executionpath, dirname, dirname, dirname, dirname, dirname, modelname) + issmssh(self.name, self.login, self.port, launchcommand) + + # }}} + + def Download(self, dirname, filelist): # {{{ + #copy files from cluster to current directory + directory = '%s/%s/' % (self.executionpath, dirname) + issmscpin(self.name, self.login, self.port, directory, filelist) + # }}} Index: /issm/trunk-jpl/src/m/classes/clusters/vilje.py =================================================================== --- /issm/trunk-jpl/src/m/classes/clusters/vilje.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/clusters/vilje.py (revision 24213) @@ -6,146 +6,140 @@ from issmscpout import issmscpout from QueueRequirements import QueueRequirements +from IssmConfig import IssmConfig import datetime try: - from vilje_settings import vilje_settings + from vilje_settings import vilje_settings except ImportError: - print('You need vilje_settings.py to proceed, check presence and sys.path') + print('You need vilje_settings.py to proceed, check presence and sys.path') + class vilje(object): - """ - Vilje cluster class definition + """ + Vilje cluster class definition - Usage: - cluster=vilje(); - """ + Usage: + cluster = vilje() + """ - def __init__(self,*args): - # {{{ - self.name = 'vilje' - self.login = '' - self.numnodes = 2 - self.cpuspernode = 32 - self.procspernodes = 16 - self.mem = 28 - self.queue = 'workq' - self.time = 2*60 - self.codepath = '' - self.executionpath = '' - self.interactive = 0 - self.port = [] - self.accountname = '' + def __init__(self, *args): # {{{ + self.name = 'vilje' + self.login = '' + self.numnodes = 2 + self.cpuspernode = 32 + self.procspernodes = 16 + self.mem = 28 + self.queue = 'workq' + self.time = 2 * 60 + self.codepath = '' + self.executionpath = '' + self.interactive = 0 + self.port = [] + self.accountname = '' - #use provided options to change fields - options=pairoptions(*args) + #use provided options to change fields + options = pairoptions(*args) - #initialize cluster using user settings if provided - self=vilje_settings(self) - #OK get other fields - self=options.AssignObjectFields(self) - self.np=self.numnodes*self.procspernodes - # }}} + #initialize cluster using user settings if provided + self = vilje_settings(self) + #OK get other fields + self = options.AssignObjectFields(self) + self.np = self.numnodes * self.procspernodes + # }}} - def __repr__(self): - # {{{ - # display the object - s = "class vilje object:" - s = "%s\n%s"%(s,fielddisplay(self,'name','name of the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'login','login')) - s = "%s\n%s"%(s,fielddisplay(self,'numnodes','number of nodes')) - s = "%s\n%s"%(s,fielddisplay(self,'cpuspernode','number of nodes per CPUs (32)')) - s = "%s\n%s"%(s,fielddisplay(self,'procspernodes','number of mpi procs per nodes')) - s = "%s\n%s"%(s,fielddisplay(self,'mem','node memory')) - s = "%s\n%s"%(s,fielddisplay(self,'queue','name of the queue (test is an option, workq the default)')) - s = "%s\n%s"%(s,fielddisplay(self,'time','walltime requested in minutes')) - s = "%s\n%s"%(s,fielddisplay(self,'codepath','code path on the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'executionpath','execution path on the cluster')) - s = "%s\n%s"%(s,fielddisplay(self,'interactive','')) - s = "%s\n%s"%(s,fielddisplay(self,'accountname','your cluster account')) - return s - # }}} + def __repr__(self): # {{{ + # display the object + s = "class vilje object:" + s = "%s\n%s" % (s, fielddisplay(self, 'name', 'name of the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'login', 'login')) + s = "%s\n%s" % (s, fielddisplay(self, 'numnodes', 'number of nodes')) + s = "%s\n%s" % (s, fielddisplay(self, 'cpuspernode', 'number of nodes per CPUs (32)')) + s = "%s\n%s" % (s, fielddisplay(self, 'procspernodes', 'number of mpi procs per nodes')) + s = "%s\n%s" % (s, fielddisplay(self, 'mem', 'node memory')) + s = "%s\n%s" % (s, fielddisplay(self, 'queue', 'name of the queue (test is an option, workq the default)')) + s = "%s\n%s" % (s, fielddisplay(self, 'time', 'walltime requested in minutes')) + s = "%s\n%s" % (s, fielddisplay(self, 'codepath', 'code path on the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'executionpath', 'execution path on the cluster')) + s = "%s\n%s" % (s, fielddisplay(self, 'interactive', '')) + s = "%s\n%s" % (s, fielddisplay(self, 'accountname', 'your cluster account')) + return s + # }}} - def checkconsistency(self,md,solution,analyses): - # {{{ - #Queue dictionarry gives queu name as key and max walltime and cpus as var - queuedict = {'workq':[5*24*60, 30], - 'test':[30,4]} - QueueRequirements(queuedict,self.queue,self.np,self.time) + def checkconsistency(self, md, solution, analyses): # {{{ + #Queue dictionarry gives queu name as key and max walltime and cpus as var + queuedict = {'workq': [5 * 24 * 60, 30], + 'test': [30, 4]} + QueueRequirements(queuedict, self.queue, self.np, self.time) - #Miscelaneous - if not self.login: - md = md.checkmessage('login empty') - if not self.codepath: - md = md.checkmessage('codepath empty') - if not self.executionpath: - md = md.checkmessage('executionpath empty') - if self.interactive==1: - md = md.checkmessage('interactive mode not implemented') - return self - # }}} + #Miscelaneous + if not self.login: + md = md.checkmessage('login empty') + if not self.codepath: + md = md.checkmessage('codepath empty') + if not self.executionpath: + md = md.checkmessage('executionpath empty') + if self.interactive == 1: + md = md.checkmessage('interactive mode not implemented') + return self + # }}} - def BuildQueueScript(self,dirname,modelname,solution,io_gather,isvalgrind,isgprof,isdakota,isoceancoupling): - # {{{ - executable='issm.exe' - if isdakota: - version=IssmConfig('_DAKOTA_VERSION_')[0:2] - version=float(version) - if version>=6: - executable='issm_dakota.exe' - if isoceancoupling: - executable='issm_ocean.exe' + def BuildQueueScript(self, dirname, modelname, solution, io_gather, isvalgrind, isgprof, isdakota, isoceancoupling): # {{{ + executable = 'issm.exe' + if isdakota: + version = IssmConfig('_DAKOTA_VERSION_')[0:2] + version = float(version) + if version >= 6: + executable = 'issm_dakota.exe' + if isoceancoupling: + executable = 'issm_ocean.exe' - #write queuing script - shortname=modelname[0:min(12,len(modelname))] - fid=open(modelname+'.queue','w') - fid.write('#PBS -S /bin/bash\n') - fid.write('#PBS -N %s \n' % shortname) - fid.write('#PBS -q %s \n' % self.queue) - fid.write('#PBS -l select=%i:ncpus=%i:mpiprocs=%s\n' % (self.numnodes,self.cpuspernode,self.procspernodes)) - timeobj=datetime.timedelta(minutes=self.time) - m,s=divmod(timeobj.total_seconds(), 60) - h,m=divmod(m, 60) - timestring="%02d:%02d:%02d" % (h, m, s) - fid.write('#PBS -l walltime=%s\n' % timestring) #walltime is hh:mm:ss - #fid.write('#PBS -l mem=%igb\n' % self.mem) - fid.write('#PBS -A %s\n' % self.accountname) - fid.write('#PBS -o %s/%s/%s.outlog \n' % (self.executionpath,dirname,modelname)) - fid.write('#PBS -e %s/%s/%s.errlog \n\n' % (self.executionpath,dirname,modelname)) - fid.write('export ISSM_DIR="%s/../"\n' % self.codepath) - fid.write('module load intelcomp/17.0.0\n') - fid.write('module load mpt/2.14\n') - fid.write('module load petsc/3.7.4d\n') - fid.write('module load parmetis/4.0.3\n') - fid.write('module load mumps/5.0.2\n') - fid.write('cd %s/%s/\n\n' % (self.executionpath,dirname)) - fid.write('mpiexec_mpt -np %i %s/%s %s %s/%s %s\n' % (self.np,self.codepath,executable,str(solution),self.executionpath,dirname,modelname)) - fid.close() - # }}} + #write queuing script + shortname = modelname[0:min(12, len(modelname))] + fid = open(modelname + '.queue', 'w') + fid.write('#PBS -S / bin / bash\n') + fid.write('#PBS -N %s \n' % shortname) + fid.write('#PBS -q %s \n' % self.queue) + fid.write('#PBS -l select=%i:ncpus=%i:mpiprocs=%s\n' % (self.numnodes, self.cpuspernode, self.procspernodes)) + timeobj = datetime.timedelta(minutes=self.time) + m, s = divmod(timeobj.total_seconds(), 60) + h, m = divmod(m, 60) + timestring = "%02d:%02d:%02d" % (h, m, s) + fid.write('#PBS -l walltime=%s\n' % timestring) #walltime is hh:mm:ss + fid.write('#PBS -A %s\n' % self.accountname) + fid.write('#PBS -o %s/%s/%s.outlog \n' % (self.executionpath, dirname, modelname)) + fid.write('#PBS -e %s/%s/%s.errlog \n\n' % (self.executionpath, dirname, modelname)) + fid.write('export ISSM_DIR = "%s/../ "\n' % self.codepath) + fid.write('module load intelcomp/17.0.0\n') + fid.write('module load mpt/2.14\n') + fid.write('module load petsc/3.7.4d\n') + fid.write('module load parmetis/4.0.3\n') + fid.write('module load mumps/5.0.2\n') + fid.write('cd %s/%s/\n\n' % (self.executionpath, dirname)) + fid.write('mpiexec_mpt -np %i %s/%s %s %s/%s %s\n' % (self.np, self.codepath, executable, str(solution), self.executionpath, dirname, modelname)) + fid.close() + # }}} - def UploadQueueJob(self,modelname,dirname,filelist): - # {{{ - #compress the files into one zip. - compressstring='tar -zcf %s.tar.gz ' % dirname - for file in filelist: - compressstring += ' %s' % file - subprocess.call(compressstring,shell=True) + def UploadQueueJob(self, modelname, dirname, filelist): # {{{ + #compress the files into one zip. + compressstring = 'tar -zcf %s.tar.gz ' % dirname + for file in filelist: + compressstring += ' %s' % file + subprocess.call(compressstring, shell=True) - print('uploading input file and queueing script') - issmscpout(self.name,self.executionpath,self.login,self.port,[dirname+'.tar.gz']) - # }}} + print('uploading input file and queueing script') + issmscpout(self.name, self.executionpath, self.login, self.port, [dirname + '.tar.gz']) + # }}} - def LaunchQueueJob(self,modelname,dirname,filelist,restart,batch): - # {{{ - print('launching solution sequence on remote cluster') - if restart: - launchcommand='cd %s && cd %s && qsub %s.queue' % (self.executionpath,dirname,modelname) - else: - launchcommand='cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && qsub %s.queue' % (self.executionpath,dirname,dirname,dirname,dirname,dirname,modelname) - issmssh(self.name,self.login,self.port,launchcommand) - # }}} + def LaunchQueueJob(self, modelname, dirname, filelist, restart, batch): # {{{ + print('launching solution sequence on remote cluster') + if restart: + launchcommand = 'cd %s && cd %s && qsub %s.queue' % (self.executionpath, dirname, modelname) + else: + launchcommand = 'cd %s && rm -rf ./%s && mkdir %s && cd %s && mv ../%s.tar.gz ./ && tar -zxf %s.tar.gz && qsub %s.queue' % (self.executionpath, dirname, dirname, dirname, dirname, dirname, modelname) + issmssh(self.name, self.login, self.port, launchcommand) + # }}} - def Download(self,dirname,filelist): - # {{{ - #copy files from cluster to current directory - directory='%s/%s/' % (self.executionpath,dirname) - issmscpin(self.name,self.login,self.port,directory,filelist) - # }}} + def Download(self, dirname, filelist): # {{{ + #copy files from cluster to current directory + directory = '%s/%s/' % (self.executionpath, dirname) + issmscpin(self.name, self.login, self.port, directory, filelist) + # }}} Index: /issm/trunk-jpl/src/m/classes/constants.py =================================================================== --- /issm/trunk-jpl/src/m/classes/constants.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/constants.py (revision 24213) @@ -3,60 +3,62 @@ from WriteData import WriteData + class constants(object): - """ - CONSTANTS class definition + """ + CONSTANTS class definition - Usage: - constants=constants(); - """ + Usage: + constants = constants() + """ - def __init__(self): # {{{ - self.g = 0. - self.omega = 0. - self.yts = 0. - self.referencetemperature = 0. - - #set defaults - self.setdefaultparameters() + def __init__(self): # {{{ + self.g = 0. + self.omega = 0. + self.yts = 0. + self.referencetemperature = 0. - #}}} - def __repr__(self): # {{{ - string=" constants parameters:" + #set defaults + self.setdefaultparameters() - string="%s\n%s"%(string,fielddisplay(self,"g","gravitational acceleration [m/s^2]")) - string="%s\n%s"%(string,fielddisplay(self,"omega","angular velocity of Earth [rad/s]")) - string="%s\n%s"%(string,fielddisplay(self,"yts","number of seconds in a year [s/yr]")) - string="%s\n%s"%(string,fielddisplay(self,"referencetemperature","reference temperature used in the enthalpy model [K]")) + #}}} + def __repr__(self): # {{{ + string = " constants parameters:" - return string - #}}} - def setdefaultparameters(self): # {{{ - - #acceleration due to gravity (m/s^2) - self.g=9.81 + string = "%s\n%s" % (string, fielddisplay(self, "g", "gravitational acceleration [m / s^2]")) + string = "%s\n%s" % (string, fielddisplay(self, "omega", "angular velocity of Earth [rad / s]")) + string = "%s\n%s" % (string, fielddisplay(self, "yts", "number of seconds in a year [s / yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "referencetemperature", "reference temperature used in the enthalpy model [K]")) - #Earth's rotation speed - self.omega = 7.292*1e-5; + return string + #}}} - #converstion from year to seconds - self.yts=365.*24.*3600. + def setdefaultparameters(self): # {{{ + #acceleration due to gravity (m / s^2) + self.g = 9.81 - #the reference temperature for enthalpy model (cf Aschwanden) - self.referencetemperature=223.15 + #Earth's rotation speed + self.omega = 7.292 * 1e-5 - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + #converstion from year to seconds + self.yts = 365. * 24. * 3600. - md = checkfield(md,'fieldname','constants.g','>=',0,'size',[1]) - md = checkfield(md,'fieldname','constants.omega','>=',0,'size',[1]) - md = checkfield(md,'fieldname','constants.yts','>',0,'size',[1]) - md = checkfield(md,'fieldname','constants.referencetemperature','size',[1]) + #the reference temperature for enthalpy model (cf Aschwanden) + self.referencetemperature = 223.15 - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','g','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','yts','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','referencetemperature','format','Double') - # }}} + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'constants.g', '>=', 0, 'size', [1]) + md = checkfield(md, 'fieldname', 'constants.omega', '>=', 0, 'size', [1]) + md = checkfield(md, 'fieldname', 'constants.yts', '>', 0, 'size', [1]) + md = checkfield(md, 'fieldname', 'constants.referencetemperature', 'size', [1]) + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'g', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'yts', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'referencetemperature', 'format', 'Double') + # }}} Index: /issm/trunk-jpl/src/m/classes/damage.py =================================================================== --- /issm/trunk-jpl/src/m/classes/damage.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/damage.py (revision 24213) @@ -4,169 +4,165 @@ from WriteData import WriteData + class damage(object): - """ - DAMAGE class definition + """ + DAMAGE class definition - Usage: - damage=damage() - """ + Usage: + damage = damage() + """ - def __init__(self,*args): # {{{ - #damage: - self.isdamage = 0. - self.D = float('NaN') - self.law = float('NaN') - self.spcdamage = float('NaN') - self.max_damage = float('NaN') + def __init__(self, *args): # {{{ + #damage: + self.isdamage = 0. + self.D = float('NaN') + self.law = float('NaN') + self.spcdamage = float('NaN') + self.max_damage = float('NaN') - #numerical - self.stabilization = float('NaN') - self.maxiter = float('NaN') - self.elementinterp = '' + #numerical + self.stabilization = float('NaN') + self.maxiter = float('NaN') + self.elementinterp = '' - #general parameters for evolution law: - self.stress_threshold = float('NaN') - self.stress_ubound = float('NaN') - self.kappa = float('NaN') - self.c1 = float('NaN') - self.c2 = float('NaN') - self.c3 = float('NaN') - self.c4 = float('NaN') - self.healing = float('NaN') - self.equiv_stress = float('NaN') - self.requested_outputs = [] + #general parameters for evolution law: + self.stress_threshold = float('NaN') + self.stress_ubound = float('NaN') + self.kappa = float('NaN') + self.c1 = float('NaN') + self.c2 = float('NaN') + self.c3 = float('NaN') + self.c4 = float('NaN') + self.healing = float('NaN') + self.equiv_stress = float('NaN') + self.requested_outputs = [] - if not len(args): - self.setdefaultparameters() - else: - raise RuntimeError("constructor not supported") - # }}} + if not len(args): + self.setdefaultparameters() + else: + raise RuntimeError("constructor not supported") + # }}} - def __repr__(self): # {{{ - s =' Damage:\n' - s+="%s\n" % fielddisplay(self,"isdamage","is damage mechanics being used? [0 (default) or 1]") - if self.isdamage: - s+="%s\n" % fielddisplay(self,"D","damage tensor (scalar for now)") - s+="%s\n" % fielddisplay(self,"law","damage law ['0: analytical','1: pralong']") - s+="%s\n" % fielddisplay(self,"spcdamage","damage constraints (NaN means no constraint)") - s+="%s\n" % fielddisplay(self,"max_damage","maximum possible damage (0<=max_damage<1)") - s+="%s\n" % fielddisplay(self,"stabilization","0: no, 1: artificial_diffusivity, 2: SUPG (not working), 4: Flux corrected transport") - s+="%s\n" % fielddisplay(self,"maxiter","maximum number of non linear iterations") - s+="%s\n" % fielddisplay(self,"elementinterp","interpolation scheme for finite elements [''P1'',''P2'']") - s+="%s\n" % fielddisplay(self,"stress_threshold","stress threshold for damage initiation (Pa)") - s+="%s\n" % fielddisplay(self,"stress_ubound","stress upper bound for damage healing (Pa)") - s+="%s\n" % fielddisplay(self,"kappa","ductility parameter for stress softening and damage [>1]") - s+="%s\n" % fielddisplay(self,"c1","damage parameter 1 ") - s+="%s\n" % fielddisplay(self,"c2","damage parameter 2 ") - s+="%s\n" % fielddisplay(self,"c3","damage parameter 3 ") - s+="%s\n" % fielddisplay(self,"c4","damage parameter 4 ") - s+="%s\n" % fielddisplay(self,"healing","damage healing parameter") - s+="%s\n" % fielddisplay(self,"equiv_stress","0: von Mises, 1: max principal") - s+="%s\n" % fielddisplay(self,'requested_outputs','additional outputs requested') + def __repr__(self): # {{{ + s = ' Damage:\n' + s += "%s\n" % fielddisplay(self, "isdamage", "is damage mechanics being used? [0 (default) or 1]") + if self.isdamage: + s += "%s\n" % fielddisplay(self, "D", "damage tensor (scalar for now)") + s += "%s\n" % fielddisplay(self, "law", "damage law ['0: analytical', '1: pralong']") + s += "%s\n" % fielddisplay(self, "spcdamage", "damage constraints (NaN means no constraint)") + s += "%s\n" % fielddisplay(self, "max_damage", "maximum possible damage (0 <=max_damage < 1)") + s += "%s\n" % fielddisplay(self, "stabilization", "0: no, 1: artificial_diffusivity, 2: SUPG (not working), 4: Flux corrected transport") + s += "%s\n" % fielddisplay(self, "maxiter", "maximum number of non linear iterations") + s += "%s\n" % fielddisplay(self, "elementinterp", "interpolation scheme for finite elements [''P1'', ''P2'']") + s += "%s\n" % fielddisplay(self, "stress_threshold", "stress threshold for damage initiation (Pa)") + s += "%s\n" % fielddisplay(self, "stress_ubound", "stress upper bound for damage healing (Pa)") + s += "%s\n" % fielddisplay(self, "kappa", "ductility parameter for stress softening and damage [ > 1]") + s += "%s\n" % fielddisplay(self, "c1", "damage parameter 1 ") + s += "%s\n" % fielddisplay(self, "c2", "damage parameter 2 ") + s += "%s\n" % fielddisplay(self, "c3", "damage parameter 3 ") + s += "%s\n" % fielddisplay(self, "c4", "damage parameter 4 ") + s += "%s\n" % fielddisplay(self, "healing", "damage healing parameter") + s += "%s\n" % fielddisplay(self, "equiv_stress", "0: von Mises, 1: max principal") + s += "%s\n" % fielddisplay(self, 'requested_outputs', 'additional outputs requested') - return s - # }}} + return s + # }}} - def extrude(self,md): # {{{ - self.D=project3d(md,'vector',self.D,'type','node') - self.spcdamage=project3d(md,'vector',self.spcdamage,'type','node') - return self - #}}} + def extrude(self, md): # {{{ + self.D = project3d(md, 'vector', self.D, 'type', 'node') + self.spcdamage = project3d(md, 'vector', self.spcdamage, 'type', 'node') + return self + #}}} - def setdefaultparameters(self): # {{{ - #damage parameters: - self.isdamage = 0 - self.D = 0 - self.law = 0 - self.max_damage = 1-1e-5 #if damage reaches 1, solve becomes singular, as viscosity becomes nil + def setdefaultparameters(self): # {{{ + #damage parameters: + self.isdamage = 0 + self.D = 0 + self.law = 0 + self.max_damage = 1 - 1e-5 #if damage reaches 1, solve becomes singular, as viscosity becomes nil + #Type of stabilization used + self.stabilization = 4 + #Maximum number of iterations + self.maxiter = 100 + #finite element interpolation + self.elementinterp = 'P1' + #damage evolution parameters + self.stress_threshold = 1.3e5 + self.kappa = 2.8 + self.c1 = 0 + self.c2 = 0 + self.c3 = 0 + self.c4 = 0 + self.healing = 0 + self.equiv_stress = 0 + #output default: + self.requested_outputs = ['default'] - #Type of stabilization used - self.stabilization=4 + return self + # }}} - #Maximum number of iterations - self.maxiter=100 + def defaultoutputs(self, md): # {{{ + if md.mesh.domaintype().lower() == '2dhorizontal': + list = ['DamageDbar'] + else: + list = ['DamageD'] + return list + #}}} - #finite element interpolation - self.elementinterp='P1' + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'damage.isdamage', 'numel', [1], 'values', [0, 1]) + if self.isdamage: + md = checkfield(md, 'fieldname', 'damage.D', '>=', 0, '<=', self.max_damage, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'damage.max_damage', '<', 1, '>=', 0) + md = checkfield(md, 'fieldname', 'damage.law', 'numel', [1], 'values', [0, 1, 2, 3]) + md = checkfield(md, 'fieldname', 'damage.spcdamage', 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'damage.stabilization', 'numel', [1], 'values', [0, 1, 2, 4]) + md = checkfield(md, 'fieldname', 'damage.maxiter', ' >= 0', 0) + md = checkfield(md, 'fieldname', 'damage.elementinterp', 'values', ['P1', 'P2']) + md = checkfield(md, 'fieldname', 'damage.stress_threshold', '>=', 0) + md = checkfield(md, 'fieldname', 'damage.stress_ubound', '>=', 0) + md = checkfield(md, 'fieldname', 'damage.kappa', '>', 1) + md = checkfield(md, 'fieldname', 'damage.healing', '>=', 0) + md = checkfield(md, 'fieldname', 'damage.c1', '>=', 0) + md = checkfield(md, 'fieldname', 'damage.c2', '>=', 0) + md = checkfield(md, 'fieldname', 'damage.c3', '>=', 0) + md = checkfield(md, 'fieldname', 'damage.c4', '>=', 0) + md = checkfield(md, 'fieldname', 'damage.healing', '>=', 0) + md = checkfield(md, 'fieldname', 'damage.equiv_stress', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'damage.requested_outputs', 'stringrow', 1) + elif self.law != 0: + if (solution == 'DamageEvolutionSolution'): + raise RuntimeError('Invalid evolution law (md.damage.law) for a damage solution') - #damage evolution parameters - self.stress_threshold=1.3e5 - self.kappa=2.8 - self.c1=0 - self.c2=0 - self.c3=0 - self.c4=0 - self.healing=0 - self.equiv_stress=0 + return md + # }}} - #output default: - self.requested_outputs=['default'] + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'isdamage', 'format', 'Boolean') + if self.isdamage: + WriteData(fid, prefix, 'object', self, 'fieldname', 'D', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'law', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'spcdamage', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'max_damage', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'stabilization', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'maxiter', 'format', 'Integer') + WriteData(fid, prefix, 'name', 'md.damage.elementinterp', 'data', self.elementinterp, 'format', 'String') + WriteData(fid, prefix, 'object', self, 'fieldname', 'stress_threshold', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'stress_ubound', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'kappa', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'c1', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'c2', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'c3', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'c4', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'healing', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'equiv_stress', 'format', 'Integer') - return self - # }}} - - def defaultoutputs(self,md): # {{{ - if md.mesh.domaintype().lower()=='2dhorizontal': - list = ['DamageDbar'] - else: - list = ['DamageD'] - return list - #}}} - - def checkconsistency(self,md,solution,analyses): # {{{ - md = checkfield(md,'fieldname','damage.isdamage','numel',[1],'values',[0,1]) - if self.isdamage: - md = checkfield(md,'fieldname','damage.D','>=',0,'<=',self.max_damage,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','damage.max_damage','<',1,'>=',0) - md = checkfield(md,'fieldname','damage.law','numel',[1],'values',[0,1,2,3]) - md = checkfield(md,'fieldname','damage.spcdamage','Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','damage.stabilization','numel',[1],'values',[0,1,2,4]) - md = checkfield(md,'fieldname','damage.maxiter','>=0',0) - md = checkfield(md,'fieldname','damage.elementinterp','values',['P1','P2']) - md = checkfield(md,'fieldname','damage.stress_threshold','>=',0) - md = checkfield(md,'fieldname','damage.stress_ubound','>=',0) - md = checkfield(md,'fieldname','damage.kappa','>',1) - md = checkfield(md,'fieldname','damage.healing','>=',0) - md = checkfield(md,'fieldname','damage.c1','>=',0) - md = checkfield(md,'fieldname','damage.c2','>=',0) - md = checkfield(md,'fieldname','damage.c3','>=',0) - md = checkfield(md,'fieldname','damage.c4','>=',0) - md = checkfield(md,'fieldname','damage.healing','>=',0) - md = checkfield(md,'fieldname','damage.equiv_stress','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','damage.requested_outputs','stringrow',1) - elif self.law != 0: - if (solution=='DamageEvolutionSolution'): - raise RuntimeError('Invalid evolution law (md.damage.law) for a damage solution') - - return md - # }}} - - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','isdamage','format','Boolean') - if self.isdamage: - WriteData(fid,prefix,'object',self,'fieldname','D','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','law','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','spcdamage','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','max_damage','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','stabilization','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','maxiter','format','Integer') - WriteData(fid,prefix,'name','md.damage.elementinterp','data',self.elementinterp,'format','String') - WriteData(fid,prefix,'object',self,'fieldname','stress_threshold','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','stress_ubound','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','kappa','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','c1','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','c2','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','c3','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','c4','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','healing','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','equiv_stress','format','Integer') - - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - if self.isdamage: - WriteData(fid,prefix,'data',outputs,'name','md.damage.requested_outputs','format','StringArray') - # }}} + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + if self.isdamage: + WriteData(fid, prefix, 'data', outputs, 'name', 'md.damage.requested_outputs', 'format', 'StringArray') + # }}} Index: /issm/trunk-jpl/src/m/classes/debug.py =================================================================== --- /issm/trunk-jpl/src/m/classes/debug.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/debug.py (revision 24213) @@ -2,33 +2,36 @@ from WriteData import * + class debug(object): - """ - DEBUG class definition + """ + DEBUG class definition - Usage: - debug=debug(); - """ + Usage: + debug = debug() + """ - def __init__(self): # {{{ - self.valgrind = False - self.gprof = False - self.profiling = False - - #set defaults - self.setdefaultparameters() + def __init__(self): # {{{ + self.valgrind = False + self.gprof = False + self.profiling = False - #}}} - def __repr__(self): # {{{ - string=" debug parameters:" + #set defaults + self.setdefaultparameters() - string="%s\n%s"%(string,fielddisplay(self,"valgrind","use Valgrind to debug (0 or 1)")) - string="%s\n%s"%(string,fielddisplay(self,"gprof","use gnu-profiler to find out where the time is spent")) - string="%s\n%s"%(string,fielddisplay(self,'profiling','enables profiling (memory, flops, time)')) - return string - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','profiling','format','Boolean') - # }}} + #}}} + def __repr__(self): # {{{ + string = " debug parameters:" + + string = "%s\n%s" % (string, fielddisplay(self, "valgrind", "use Valgrind to debug (0 or 1)")) + string = "%s\n%s" % (string, fielddisplay(self, "gprof", "use gnu - profiler to find out where the time is spent")) + string = "%s\n%s" % (string, fielddisplay(self, 'profiling', 'enables profiling (memory, flops, time)')) + return string + #}}} + + def setdefaultparameters(self): # {{{ + return self + #}}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'profiling', 'format', 'Boolean') + # }}} Index: /issm/trunk-jpl/src/m/classes/dependent.py =================================================================== --- /issm/trunk-jpl/src/m/classes/dependent.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/dependent.py (revision 24213) @@ -6,82 +6,87 @@ from MeshProfileIntersection import MeshProfileIntersection + class dependent(object): - """ - DEPENDENT class definition + """ + DEPENDENT class definition - Usage: - dependent=dependent(); - """ + Usage: + dependent = dependent() + """ - def __init__(self,*args): # {{{ - self.name = '' - self.type = '' - self.fos_reverse_index = float('NaN') - self.exp = '' - self.segments = [] - self.index = -1 - self.nods = 0 + def __init__(self, *args): # {{{ + self.name = '' + self.type = '' + self.fos_reverse_index = float('NaN') + self.exp = '' + self.segments = [] + self.index = - 1 + self.nods = 0 - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #use provided options to change fields - options=pairoptions(*args) + #use provided options to change fields + options = pairoptions(*args) - self.name=options.getfieldvalue('name','') - self.type=options.getfieldvalue('type','') - self.exp=options.getfieldvalue('exp','') - self.segments=options.getfieldvalue('segments',[]) - self.index=options.getfieldvalue('index',-1) - self.nods=options.getfieldvalue('nods',0) + self.name = options.getfieldvalue('name', '') + self.type = options.getfieldvalue('type', '') + self.exp = options.getfieldvalue('exp', '') + self.segments = options.getfieldvalue('segments', []) + self.index = options.getfieldvalue('index', - 1) + self.nods = options.getfieldvalue('nods', 0) - #if name is mass flux: - if strcmpi(self.name,'MassFlux'): - #make sure that we supplied a file and that it exists! - if not os.path.exists(self.exp): - raise IOError("dependent checkconsistency: specified 'exp' file does not exist!") - #process the file and retrieve segments - mesh=options.getfieldvalue('mesh') - self.segments=MeshProfileIntersection(mesh.elements,mesh.x,mesh.y,self.exp)[0] - # }}} - def __repr__(self): # {{{ - s =" dependent variable:\n" + #if name is mass flux: + if strcmpi(self.name, 'MassFlux'): + #make sure that we supplied a file and that it exists! + if not os.path.exists(self.exp): + raise IOError("dependent checkconsistency: specified 'exp' file does not exist!") + #process the file and retrieve segments + mesh = options.getfieldvalue('mesh') + self.segments = MeshProfileIntersection(mesh.elements, mesh.x, mesh.y, self.exp)[0] + # }}} - s+="%s\n" % fielddisplay(self,'name',"variable name (must match corresponding String)") - s+="%s\n" % fielddisplay(self,'type',"type of variable ('vertex' or 'scalar')") + def __repr__(self): # {{{ + s = " dependent variable:\n" - if not np.isnan(self.fos_reverse_index): - s+="%s\n" % fielddisplay(self,'fos_reverse_index',"index for fos_reverse driver of ADOLC") - if self.exp: - s+="%s\n" % fielddisplay(self,'exp',"file needed to compute dependent variable") - s+="%s\n" % fielddisplay(self,'segments',"mass flux segments") + s += "%s\n" % fielddisplay(self, 'name', "variable name (must match corresponding String)") + s += "%s\n" % fielddisplay(self, 'type', "type of variable ('vertex' or 'scalar')") - return s - # }}} - def setdefaultparameters(self): # {{{ - #do nothing - return self - # }}} - def checkconsistency(self,md,solution,analyses): # {{{ - if strcmpi(self.name,'MassFlux'): - if not self.segments: - raise RuntimeError("dependent checkconsistency error: need segments to compute this dependent response") - if self.index<0: - raise RuntimeError("dependent checkconsistency error: index for segments should be >=0") + if not np.isnan(self.fos_reverse_index): + s += "%s\n" % fielddisplay(self, 'fos_reverse_index', "index for fos_reverse driver of ADOLC") + if self.exp: + s += "%s\n" % fielddisplay(self, 'exp', "file needed to compute dependent variable") + s += "%s\n" % fielddisplay(self, 'segments', "mass flux segments") - if not np.isnan(self.fos_reverse_index): - if not strcmpi(driver,'fos_reverse'): - raise TypeError("cannot declare a dependent with a fos_reverse_index when the driver is not fos_reverse!") - if self.nods==0: - raise TypeError("dependent checkconsistency error: nods should be set to the size of the independent variable") + return s + # }}} - return md - # }}} - def typetoscalar(self): # {{{ - if strcmpi(self.type,'scalar'): - scalar=0 - elif strcmpi(self.type,'vertex'): - scalar=1 + def setdefaultparameters(self): # {{{ + #do nothing + return self + # }}} - return scalar - # }}} + def checkconsistency(self, md, solution, analyses): # {{{ + if strcmpi(self.name, 'MassFlux'): + if not self.segments: + raise RuntimeError("dependent checkconsistency error: need segments to compute this dependent response") + if self.index < 0: + raise RuntimeError("dependent checkconsistency error: index for segments should be >= 0") + + if not np.isnan(self.fos_reverse_index): + if not strcmpi(driver, 'fos_reverse'): + raise TypeError("cannot declare a dependent with a fos_reverse_index when the driver is not fos_reverse!") + if self.nods == 0: + raise TypeError("dependent checkconsistency error: nods should be set to the size of the independent variable") + + return md + # }}} + + def typetoscalar(self): # {{{ + if strcmpi(self.type, 'scalar'): + scalar = 0 + elif strcmpi(self.type, 'vertex'): + scalar = 1 + + return scalar + # }}} Index: /issm/trunk-jpl/src/m/classes/esa.py =================================================================== --- /issm/trunk-jpl/src/m/classes/esa.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/esa.py (revision 24213) @@ -2,96 +2,92 @@ from MatlabFuncs import * from model import * -import numpy as np from checkfield import checkfield from WriteData import WriteData + class esa(object): - """ - ESA class definition + """ + ESA class definition - Usage: - esa=esa(); - """ + Usage: + esa = esa(); + """ - def __init__(self): # {{{ - self.deltathickness = float('NaN') - self.love_h = 0 #provided by PREM model() - self.love_l = 0 #ideam - self.hemisphere = 0 - self.degacc = 0 - self.requested_outputs = [] - self.transitions = [] + def __init__(self): # {{{ + self.deltathickness = float('NaN') + self.love_h = 0 #provided by PREM model() + self.love_l = 0 #ideam + self.hemisphere = 0 + self.degacc = 0 + self.requested_outputs = [] + self.transitions = [] - #set defaults - self.setdefaultparameters() - #}}} + #set defaults + self.setdefaultparameters() + #}}} - def __repr__(self): # {{{ - string=' esa parameters:' - string="%s\n%s"%(string,fielddisplay(self,'deltathickness','thickness change: ice height equivalent [m]')) - string="%s\n%s"%(string,fielddisplay(self,'love_h','load Love number for radial displacement')) - string="%s\n%s"%(string,fielddisplay(self,'love_l','load Love number for horizontal displaements')) - string="%s\n%s"%(string,fielddisplay(self,'hemisphere','North-south, East-west components of 2-D horiz displacement vector: -1 south, 1 north')) - string="%s\n%s"%(string,fielddisplay(self,'degacc','accuracy (default .01 deg) for numerical discretization of the Green''s functions')) - string="%s\n%s"%(string,fielddisplay(self,'transitions','indices into parts of the mesh that will be icecaps')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested (default: EsaUmotion)')) + def __repr__(self): # {{{ + string = ' esa parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'deltathickness', 'thickness change: ice height equivalent [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'love_h', 'load Love number for radial displacement')) + string = "%s\n%s" % (string, fielddisplay(self, 'love_l', 'load Love number for horizontal displaements')) + string = "%s\n%s" % (string, fielddisplay(self, 'hemisphere', 'North - south, East - west components of 2 - D horiz displacement vector: - 1 south, 1 north')) + string = "%s\n%s" % (string, fielddisplay(self, 'degacc', 'accuracy (default .01 deg) for numerical discretization of the Green''s functions')) + string = "%s\n%s" % (string, fielddisplay(self, 'transitions', 'indices into parts of the mesh that will be icecaps')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested (default: EsaUmotion)')) - return string - # }}} + return string + # }}} - def setdefaultparameters(self): # {{{ - #numerical discretization accuracy - self.degacc=.01 + def setdefaultparameters(self): # {{{ + #numerical discretization accuracy + self.degacc = 0.01 + #computational flags: + self.hemisphere = 0 + #output default: + self.requested_outputs = ['default'] + #transitions should be a cell array of vectors: + self.transitions = [] + #default output + self.requested_outputs = ['default'] + return self + #}}} - #computational flags: - self.hemisphere=0; + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if (solution != 'EsaAnalysis'): + return md - #output default: - self.requested_outputs=['default'] + md = checkfield(md, 'fieldname', 'esa.deltathickness', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofelements, 1]) + md = checkfield(md, 'fieldname', 'esa.love_h', 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'esa.love_l', 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'esa.hemisphere', 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'esa.degacc', 'size', [1, 1], '>=', 1e-10) + md = checkfield(md, 'fieldname', 'esa.requested_outputs', 'stringrow', 1) - #transitions should be a cell array of vectors: - self.transitions=[] + #check that love numbers are provided at the same level of accuracy: + if (size(self.love_h, 0) != size(self.love_l, 0)): + error('esa error message: love numbers should be provided at the same level of accuracy') + return md + # }}} - #default output - self.requested_outputs=['default'] - return self - #}}} + def defaultoutputs(self, md): # {{{ + return ['EsaUmotion'] + # }}} - def checkconsistency(self,md,solution,analyses): # {{{ - #Early return - if (solution!='EsaAnalysis'): - return md + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'deltathickness', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'fieldname', 'love_h', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'love_l', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'hemisphere', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'degacc', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'transitions', 'format', 'MatArray') - md = checkfield(md,'fieldname','esa.deltathickness','NaN',1,'Inf',1,'size',[md.mesh.numberofelements,1]) - md = checkfield(md,'fieldname','esa.love_h','NaN',1,'Inf',1) - md = checkfield(md,'fieldname','esa.love_l','NaN',1,'Inf',1) - md = checkfield(md,'fieldname','esa.hemisphere','NaN',1,'Inf',1) - md = checkfield(md,'fieldname','esa.degacc','size',[1,1],'>=',1e-10) - md = checkfield(md,'fieldname','esa.requested_outputs','stringrow',1) - - #check that love numbers are provided at the same level of accuracy: - if (size(self.love_h,0) != size(self.love_l,0)): - error('esa error message: love numbers should be provided at the same level of accuracy') - return md - # }}} - - def defaultoutputs(self,md): # {{{ - return ['EsaUmotion'] - # }}} - - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','deltathickness','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'fieldname','love_h','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','love_l','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','hemisphere','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','degacc','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','transitions','format','MatArray') - - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.esa.requested_outputs','format','StringArray') - # }}} + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.esa.requested_outputs', 'format', 'StringArray') + # }}} Index: /issm/trunk-jpl/src/m/classes/flowequation.py =================================================================== --- /issm/trunk-jpl/src/m/classes/flowequation.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/flowequation.py (revision 24213) @@ -1,4 +1,3 @@ import numpy as np -import copy from project3d import project3d from fielddisplay import fielddisplay @@ -7,139 +6,144 @@ import MatlabFuncs as m + class flowequation(object): - """ - FLOWEQUATION class definition + """ + FLOWEQUATION class definition - Usage: - flowequation=flowequation(); - """ + Usage: + flowequation = flowequation() + """ - def __init__(self): # {{{ + def __init__(self): # {{{ - self.isSIA = 0 - self.isSSA = 0 - self.isL1L2 = 0 - self.isHO = 0 - self.isFS = 0 - self.fe_SSA = '' - self.fe_HO = '' - self.fe_FS = '' - self.augmented_lagrangian_r = 1. - self.augmented_lagrangian_rhop = 1. - self.augmented_lagrangian_rlambda = 1. - self.augmented_lagrangian_rholambda = 1. - self.XTH_theta = 0. - self.vertex_equation = float('NaN') - self.element_equation = float('NaN') - self.borderSSA = float('NaN') - self.borderHO = float('NaN') - self.borderFS = float('NaN') + self.isSIA = 0 + self.isSSA = 0 + self.isL1L2 = 0 + self.isHO = 0 + self.isFS = 0 + self.fe_SSA = '' + self.fe_HO = '' + self.fe_FS = '' + self.augmented_lagrangian_r = 1. + self.augmented_lagrangian_rhop = 1. + self.augmented_lagrangian_rlambda = 1. + self.augmented_lagrangian_rholambda = 1. + self.XTH_theta = 0. + self.vertex_equation = float('NaN') + self.element_equation = float('NaN') + self.borderSSA = float('NaN') + self.borderHO = float('NaN') + self.borderFS = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' flow equation parameters:' + #}}} - string="%s\n%s"%(string,fielddisplay(self,'isSIA',"is the Shallow Ice Approximation (SIA) used ?")) - string="%s\n%s"%(string,fielddisplay(self,'isSSA',"is the Shelfy-Stream Approximation (SSA) used ?")) - string="%s\n%s"%(string,fielddisplay(self,'isL1L2',"are L1L2 equations used ?")) - string="%s\n%s"%(string,fielddisplay(self,'isHO',"is the Higher-Order (HO) approximation used ?")) - string="%s\n%s"%(string,fielddisplay(self,'isFS',"are the Full-FS (FS) equations used ?")) - string="%s\n%s"%(string,fielddisplay(self,'fe_SSA',"Finite Element for SSA: 'P1', 'P1bubble' 'P1bubblecondensed' 'P2'")) - string="%s\n%s"%(string,fielddisplay(self,'fe_HO' ,"Finite Element for HO: 'P1','P1bubble','P1bubblecondensed','P1xP2','P2xP1','P2','P2bubble','P1xP3','P2xP4'")) - string="%s\n%s"%(string,fielddisplay(self,'fe_FS' ,"Finite Element for FS: 'P1P1' (debugging only) 'P1P1GLS' 'MINIcondensed' 'MINI' 'TaylorHood' 'LATaylorHood' 'XTaylorHood'")) - string="%s\n%s"%(string,fielddisplay(self,'vertex_equation',"flow equation for each vertex")) - string="%s\n%s"%(string,fielddisplay(self,'element_equation',"flow equation for each element")) - string="%s\n%s"%(string,fielddisplay(self,'borderSSA',"vertices on SSA's border (for tiling)")) - string="%s\n%s"%(string,fielddisplay(self,'borderHO',"vertices on HO's border (for tiling)")) - string="%s\n%s"%(string,fielddisplay(self,'borderFS',"vertices on FS' border (for tiling)")) - return string - #}}} - def extrude(self,md): # {{{ - self.element_equation=project3d(md,'vector',self.element_equation,'type','element') - self.vertex_equation=project3d(md,'vector',self.vertex_equation,'type','node') - self.borderSSA=project3d(md,'vector',self.borderSSA,'type','node') - self.borderHO=project3d(md,'vector',self.borderHO,'type','node') - self.borderFS=project3d(md,'vector',self.borderFS,'type','node') - return self - #}}} - def setdefaultparameters(self): # {{{ + def __repr__(self): # {{{ + string = ' flow equation parameters:' - #P1 for SSA - self.fe_SSA= 'P1'; + string = "%s\n%s" % (string, fielddisplay(self, 'isSIA', "is the Shallow Ice Approximation (SIA) used ?")) + string = "%s\n%s" % (string, fielddisplay(self, 'isSSA', "is the Shelfy - Stream Approximation (SSA) used ?")) + string = "%s\n%s" % (string, fielddisplay(self, 'isL1L2', "are L1L2 equations used ?")) + string = "%s\n%s" % (string, fielddisplay(self, 'isHO', "is the Higher - Order (HO) approximation used ?")) + string = "%s\n%s" % (string, fielddisplay(self, 'isFS', "are the Full - FS (FS) equations used ?")) + string = "%s\n%s" % (string, fielddisplay(self, 'fe_SSA', "Finite Element for SSA: 'P1', 'P1bubble' 'P1bubblecondensed' 'P2'")) + string = "%s\n%s" % (string, fielddisplay(self, 'fe_HO', "Finite Element for HO: 'P1', 'P1bubble', 'P1bubblecondensed', 'P1xP2', 'P2xP1', 'P2', 'P2bubble', 'P1xP3', 'P2xP4'")) + string = "%s\n%s" % (string, fielddisplay(self, 'fe_FS', "Finite Element for FS: 'P1P1' (debugging only) 'P1P1GLS' 'MINIcondensed' 'MINI' 'TaylorHood' 'LATaylorHood' 'XTaylorHood'")) + string = "%s\n%s" % (string, fielddisplay(self, 'vertex_equation', "flow equation for each vertex")) + string = "%s\n%s" % (string, fielddisplay(self, 'element_equation', "flow equation for each element")) + string = "%s\n%s" % (string, fielddisplay(self, 'borderSSA', "vertices on SSA's border (for tiling)")) + string = "%s\n%s" % (string, fielddisplay(self, 'borderHO', "vertices on HO's border (for tiling)")) + string = "%s\n%s" % (string, fielddisplay(self, 'borderFS', "vertices on FS' border (for tiling)")) + return string + #}}} - #P1 for HO - self.fe_HO= 'P1'; + def extrude(self, md): # {{{ + self.element_equation = project3d(md, 'vector', self.element_equation, 'type', 'element') + self.vertex_equation = project3d(md, 'vector', self.vertex_equation, 'type', 'node') + self.borderSSA = project3d(md, 'vector', self.borderSSA, 'type', 'node') + self.borderHO = project3d(md, 'vector', self.borderHO, 'type', 'node') + self.borderFS = project3d(md, 'vector', self.borderFS, 'type', 'node') + return self + #}}} - #MINI condensed element for FS by default - self.fe_FS = 'MINIcondensed'; + def setdefaultparameters(self): # {{{ + #P1 for SSA + self.fe_SSA = 'P1' - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + #P1 for HO + self.fe_HO = 'P1' - #Early return - if ('StressbalanceAnalysis' not in analyses and 'StressbalanceSIAAnalysis' not in analyses) or (solution=='TransientSolution' and not md.transient.isstressbalance): - return md + #MINI condensed element for FS by default + self.fe_FS = 'MINIcondensed' - md = checkfield(md,'fieldname','flowequation.isSIA','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','flowequation.isSSA','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','flowequation.isL1L2','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','flowequation.isHO','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','flowequation.isFS','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','flowequation.fe_SSA','values',['P1','P1bubble','P1bubblecondensed','P2','P2bubble']) - md = checkfield(md,'fieldname','flowequation.fe_HO' ,'values',['P1','P1bubble','P1bubblecondensed','P1xP2','P2xP1','P2','P2bubble','P1xP3','P2xP4']) - md = checkfield(md,'fieldname','flowequation.fe_FS' ,'values',['P1P1','P1P1GLS','MINIcondensed','MINI','TaylorHood','LATaylorHood','XTaylorHood','OneLayerP4z','CrouzeixRaviart','LACrouzeixRaviart']) - md = checkfield(md,'fieldname','flowequation.borderSSA','size',[md.mesh.numberofvertices],'values',[0,1]) - md = checkfield(md,'fieldname','flowequation.borderHO','size',[md.mesh.numberofvertices],'values',[0,1]) - md = checkfield(md,'fieldname','flowequation.borderFS','size',[md.mesh.numberofvertices],'values',[0,1]) - md = checkfield(md,'fieldname','flowequation.augmented_lagrangian_r','numel',[1],'>',0.) - md = checkfield(md,'fieldname','flowequation.augmented_lagrangian_rhop','numel',[1],'>',0.) - md = checkfield(md,'fieldname','flowequation.augmented_lagrangian_rlambda','numel',[1],'>',0.) - md = checkfield(md,'fieldname','flowequation.augmented_lagrangian_rholambda','numel',[1],'>',0.) - md = checkfield(md,'fieldname','flowequation.XTH_theta','numel',[1],'>=',0.,'<',.5) - if m.strcmp(md.mesh.domaintype(),'2Dhorizontal'): - md = checkfield(md,'fieldname','flowequation.vertex_equation','size',[md.mesh.numberofvertices],'values',[1,2]) - md = checkfield(md,'fieldname','flowequation.element_equation','size',[md.mesh.numberofelements],'values',[1,2]) - elif m.strcmp(md.mesh.domaintype(),'2Dvertical'): - md = checkfield(md,'fieldname','flowequation.vertex_equation','size',[md.mesh.numberofvertices],'values',[2,4,5]) - md = checkfield(md,'fieldname','flowequation.element_equation','size',[md.mesh.numberofelements],'values',[2,4,5]) - elif m.strcmp(md.mesh.domaintype(),'3D'): - md = checkfield(md,'fieldname','flowequation.vertex_equation','size',[md.mesh.numberofvertices],'values',np.arange(0,8+1)) - md = checkfield(md,'fieldname','flowequation.element_equation','size',[md.mesh.numberofelements],'values',np.arange(0,8+1)) - else: - raise RuntimeError('mesh type not supported yet') - if not (self.isSIA or self.isSSA or self.isL1L2 or self.isHO or self.isFS): - md.checkmessage("no element types set for this model") + return self + #}}} - if 'StressbalanceSIAAnalysis' in analyses: - if any(self.element_equation==1): - if np.any(np.logical_and(self.vertex_equation,md.mask.groundedice_levelset)): - print("\n !!! Warning: SIA's model is not consistent on ice shelves !!!\n") + def checkconsistency(self, md, solution, analyses): # {{{ - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','isSIA','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isSSA','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isL1L2','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isHO','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isFS','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','fe_SSA','data',self.fe_SSA,'format','String') - WriteData(fid,prefix,'object',self,'fieldname','fe_HO','data',self.fe_HO,'format','String') - WriteData(fid,prefix,'object',self,'fieldname','fe_FS','data',self.fe_FS ,'format','String') - WriteData(fid,prefix,'object',self,'fieldname','augmented_lagrangian_r','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','augmented_lagrangian_rhop','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','augmented_lagrangian_rlambda','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','augmented_lagrangian_rholambda','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','XTH_theta','data',self.XTH_theta ,'format','Double') - WriteData(fid,prefix,'object',self,'fieldname','borderSSA','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','borderHO','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','borderFS','format','DoubleMat','mattype',1) - #convert approximations to enums - WriteData(fid,prefix,'data',self.vertex_equation,'name','md.flowequation.vertex_equation','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'data',self.element_equation,'name','md.flowequation.element_equation','format','DoubleMat','mattype',2) + #Early return + if ('StressbalanceAnalysis' not in analyses and 'StressbalanceSIAAnalysis' not in analyses) or (solution == 'TransientSolution' and not md.transient.isstressbalance): + return md - # }}} + md = checkfield(md, 'fieldname', 'flowequation.isSIA', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'flowequation.isSSA', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'flowequation.isL1L2', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'flowequation.isHO', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'flowequation.isFS', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'flowequation.fe_SSA', 'values', ['P1', 'P1bubble', 'P1bubblecondensed', 'P2', 'P2bubble']) + md = checkfield(md, 'fieldname', 'flowequation.fe_HO', 'values', ['P1', 'P1bubble', 'P1bubblecondensed', 'P1xP2', 'P2xP1', 'P2', 'P2bubble', 'P1xP3', 'P2xP4']) + md = checkfield(md, 'fieldname', 'flowequation.fe_FS', 'values', ['P1P1', 'P1P1GLS', 'MINIcondensed', 'MINI', 'TaylorHood', 'LATaylorHood', 'XTaylorHood', 'OneLayerP4z', 'CrouzeixRaviart', 'LACrouzeixRaviart']) + md = checkfield(md, 'fieldname', 'flowequation.borderSSA', 'size', [md.mesh.numberofvertices], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'flowequation.borderHO', 'size', [md.mesh.numberofvertices], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'flowequation.borderFS', 'size', [md.mesh.numberofvertices], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'flowequation.augmented_lagrangian_r', 'numel', [1], '>', 0.) + md = checkfield(md, 'fieldname', 'flowequation.augmented_lagrangian_rhop', 'numel', [1], '>', 0.) + md = checkfield(md, 'fieldname', 'flowequation.augmented_lagrangian_rlambda', 'numel', [1], '>', 0.) + md = checkfield(md, 'fieldname', 'flowequation.augmented_lagrangian_rholambda', 'numel', [1], '>', 0.) + md = checkfield(md, 'fieldname', 'flowequation.XTH_theta', 'numel', [1], '>=', 0., '<', .5) + if m.strcmp(md.mesh.domaintype(), '2Dhorizontal'): + md = checkfield(md, 'fieldname', 'flowequation.vertex_equation', 'size', [md.mesh.numberofvertices], 'values', [1, 2]) + md = checkfield(md, 'fieldname', 'flowequation.element_equation', 'size', [md.mesh.numberofelements], 'values', [1, 2]) + elif m.strcmp(md.mesh.domaintype(), '2Dvertical'): + md = checkfield(md, 'fieldname', 'flowequation.vertex_equation', 'size', [md.mesh.numberofvertices], 'values', [2, 4, 5]) + md = checkfield(md, 'fieldname', 'flowequation.element_equation', 'size', [md.mesh.numberofelements], 'values', [2, 4, 5]) + elif m.strcmp(md.mesh.domaintype(), '3D'): + md = checkfield(md, 'fieldname', 'flowequation.vertex_equation', 'size', [md.mesh.numberofvertices], 'values', np.arange(0, 8 + 1)) + md = checkfield(md, 'fieldname', 'flowequation.element_equation', 'size', [md.mesh.numberofelements], 'values', np.arange(0, 8 + 1)) + else: + raise RuntimeError('mesh type not supported yet') + if not (self.isSIA or self.isSSA or self.isL1L2 or self.isHO or self.isFS): + md.checkmessage("no element types set for this model") + + if 'StressbalanceSIAAnalysis' in analyses: + if any(self.element_equation == 1): + if np.any(np.logical_and(self.vertex_equation, md.mask.groundedice_levelset)): + print("\n !!! Warning: SIA's model is not consistent on ice shelves !!!\n") + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'isSIA', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isSSA', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isL1L2', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isHO', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isFS', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'fe_SSA', 'data', self.fe_SSA, 'format', 'String') + WriteData(fid, prefix, 'object', self, 'fieldname', 'fe_HO', 'data', self.fe_HO, 'format', 'String') + WriteData(fid, prefix, 'object', self, 'fieldname', 'fe_FS', 'data', self.fe_FS, 'format', 'String') + WriteData(fid, prefix, 'object', self, 'fieldname', 'augmented_lagrangian_r', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'augmented_lagrangian_rhop', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'augmented_lagrangian_rlambda', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'augmented_lagrangian_rholambda', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'XTH_theta', 'data', self.XTH_theta, 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'borderSSA', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'borderHO', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'borderFS', 'format', 'DoubleMat', 'mattype', 1) + #convert approximations to enums + WriteData(fid, prefix, 'data', self.vertex_equation, 'name', 'md.flowequation.vertex_equation', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'data', self.element_equation, 'name', 'md.flowequation.element_equation', 'format', 'DoubleMat', 'mattype', 2) + + # }}} Index: /issm/trunk-jpl/src/m/classes/fourierlove.py =================================================================== --- /issm/trunk-jpl/src/m/classes/fourierlove.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/fourierlove.py (revision 24213) @@ -3,102 +3,103 @@ from WriteData import WriteData + class fourierlove(object): - """ - Fourier Love Number class definition + """ + Fourier Love Number class definition - Usage: - fourierlove=fourierlove(); - """ - def __init__(self): # {{{ - self.nfreq = 0; - self.frequencies = 0; - self.sh_nmax = 0; - self.sh_nmin = 0; - self.g0 = 0; - self.r0 = 0; - self.mu0 = 0; - self.allow_layer_deletion = 0; - self.love_kernels = 0; - self.forcing_type = 0; + Usage: + fourierlove = fourierlove() + """ + def __init__(self): # {{{ + self.nfreq = 0 + self.frequencies = 0 + self.sh_nmax = 0 + self.sh_nmin = 0 + self.g0 = 0 + self.r0 = 0 + self.mu0 = 0 + self.allow_layer_deletion = 0 + self.love_kernels = 0 + self.forcing_type = 0 - #set defaults - self.setdefaultparameters() - #}}} + #set defaults + self.setdefaultparameters() + #}}} - def __repr__(self): # {{{ - string=' Fourier Love class:' - string="%s\n%s"%(string,fielddisplay(self,'nfreq','number of frequencies sampled (default 1, elastic) [Hz]')) - string="%s\n%s"%(string,fielddisplay(self,'frequencies','frequencies sampled (convention defaults to 0 for the elastic case) [Hz]')) - string="%s\n%s"%(string,fielddisplay(self,'sh_nmax','maximum spherical harmonic degree (default 256, .35 deg, or 40 km at equator)')) - string="%s\n%s"%(string,fielddisplay(self,'sh_nmin','minimum spherical harmonic degree (default 1)')) - string="%s\n%s"%(string,fielddisplay(self,'g0','adimensioning constant for gravity (default 10) [m/s^2]')) - string="%s\n%s"%(string,fielddisplay(self,'r0','adimensioning constant for radius (default 6378*10^3) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'mu0','adimensioning constant for stress (default 10^11) [Pa]')) - string="%s\n%s"%(string,fielddisplay(self,'allow_layer_deletion','allow for migration of the integration boundary with increasing spherical harmonics degree (default 1)')) - string="%s\n%s"%(string,fielddisplay(self,'love_kernels','compute love numbers at depth? (default 0)')) - string="%s\n%s"%(string,fielddisplay(self,'forcing_type','integer indicating the nature and depth of the forcing for the Love number calculation (default 11) :')) - string="%s\n%s"%(string,' 1: Inner core boundary -- Volumic Potential') - string="%s\n%s"%(string,' 2: Inner core boundary -- Pressure') - string="%s\n%s"%(string,' 3: Inner core boundary -- Loading') - string="%s\n%s"%(string,' 4: Inner core boundary -- Tangential traction') - string="%s\n%s"%(string,' 5: Core mantle boundary -- Volumic Potential') - string="%s\n%s"%(string,' 6: Core mantle boundary -- Pressure') - string="%s\n%s"%(string,' 7: Core mantle boundary -- Loading') - string="%s\n%s"%(string,' 8: Core mantle boundary -- Tangential traction') - string="%s\n%s"%(string,' 9: Surface -- Volumic Potential') - string="%s\n%s"%(string,' 10: Surface -- Pressure') - string="%s\n%s"%(string,' 11: Surface -- Loading') - string="%s\n%s"%(string,' 12: Surface -- Tangential traction ') + def __repr__(self): # {{{ + string = ' Fourier Love class:' + string = "%s\n%s" % (string, fielddisplay(self, 'nfreq', 'number of frequencies sampled (default 1, elastic) [Hz]')) + string = "%s\n%s" % (string, fielddisplay(self, 'frequencies', 'frequencies sampled (convention defaults to 0 for the elastic case) [Hz]')) + string = "%s\n%s" % (string, fielddisplay(self, 'sh_nmax', 'maximum spherical harmonic degree (default 256, .35 deg, or 40 km at equator)')) + string = "%s\n%s" % (string, fielddisplay(self, 'sh_nmin', 'minimum spherical harmonic degree (default 1)')) + string = "%s\n%s" % (string, fielddisplay(self, 'g0', 'adimensioning constant for gravity (default 10) [m / s^2]')) + string = "%s\n%s" % (string, fielddisplay(self, 'r0', 'adimensioning constant for radius (default 6378 * 10^3) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'mu0', 'adimensioning constant for stress (default 10^11) [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'allow_layer_deletion', 'allow for migration of the integration boundary with increasing spherical harmonics degree (default 1)')) + string = "%s\n%s" % (string, fielddisplay(self, 'love_kernels', 'compute love numbers at depth? (default 0)')) + string = "%s\n%s" % (string, fielddisplay(self, 'forcing_type', 'integer indicating the nature and depth of the forcing for the Love number calculation (default 11) :')) + string = "%s\n%s" % (string, ' 1: Inner core boundary -- Volumic Potential') + string = "%s\n%s" % (string, ' 2: Inner core boundary -- Pressure') + string = "%s\n%s" % (string, ' 3: Inner core boundary -- Loading') + string = "%s\n%s" % (string, ' 4: Inner core boundary -- Tangential traction') + string = "%s\n%s" % (string, ' 5: Core mantle boundary -- Volumic Potential') + string = "%s\n%s" % (string, ' 6: Core mantle boundary -- Pressure') + string = "%s\n%s" % (string, ' 7: Core mantle boundary -- Loading') + string = "%s\n%s" % (string, ' 8: Core mantle boundary -- Tangential traction') + string = "%s\n%s" % (string, ' 9: Surface-- Volumic Potential') + string = "%s\n%s" % (string, ' 10: Surface-- Pressure') + string = "%s\n%s" % (string, ' 11: Surface-- Loading') + string = "%s\n%s" % (string, ' 12: Surface-- Tangential traction ') - return string; - #}}} + return string + #}}} - def extrude(self,md): # {{{ - return self - #}}} + def extrude(self, md): # {{{ + return self + #}}} - def setdefaultparameters(self): # {{{ - #we setup an elastic love number computation by default. - self.nfreq=1 - self.frequencies=[0]; #Hz - self.sh_nmax=256 # .35 degree, 40 km at the equator. - self.sh_nmin=1 - self.g0=10 # m/s^2 - self.r0=6378*1e3 #m - self.mu0=1e11 # Pa - self.allow_layer_deletion=1 - self.love_kernels=0 - self.forcing_type = 11 + def setdefaultparameters(self): # {{{ + #we setup an elastic love number computation by default. + self.nfreq = 1 + self.frequencies = [0] #Hz + self.sh_nmax = 256 # .35 degree, 40 km at the equator. + self.sh_nmin = 1 + self.g0 = 10 # m / s^2 + self.r0 = 6378 * 1e3 #m + self.mu0 = 1e11 # Pa + self.allow_layer_deletion = 1 + self.love_kernels = 0 + self.forcing_type = 11 - return self - #}}} + return self + #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - md = checkfield(md,'fieldname','love.nfreq','NaN',1,'Inf',1,'numel',[1],'>',0); - md = checkfield(md,'fieldname','love.frequencies','NaN',1,'Inf',1,'numel',[md.love.nfreq]); - md = checkfield(md,'fieldname','love.sh_nmax','NaN',1,'Inf',1,'numel',[1],'>',0); - md = checkfield(md,'fieldname','love.sh_nmin','NaN',1,'Inf',1,'numel',[1],'>',0); - md = checkfield(md,'fieldname','love.g0','NaN',1,'Inf',1,'numel',[1],'>',0); - md = checkfield(md,'fieldname','love.r0','NaN',1,'Inf',1,'numel',[1],'>',0); - md = checkfield(md,'fieldname','love.mu0','NaN',1,'Inf',1,'numel',[1],'>',0); - md = checkfield(md,'fieldname','love.allow_layer_deletion','values',[0,1]); - md = checkfield(md,'fieldname','love.love_kernels','values',[0,1]); - md = checkfield(md,'fieldname','love.forcing_type','NaN',1,'Inf',1,'numel',[1],'>',0, '<=', 12); - if md.love.sh_nmin<=1 and md.love.forcing_type==9: - raise RuntimeError("Degree 1 not supported for Volumetric Potential forcing. Use sh_min>=2 for this kind of calculation.") + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'love.nfreq', 'NaN', 1, 'Inf', 1, 'numel', [1], '>', 0) + md = checkfield(md, 'fieldname', 'love.frequencies', 'NaN', 1, 'Inf', 1, 'numel', [md.love.nfreq]) + md = checkfield(md, 'fieldname', 'love.sh_nmax', 'NaN', 1, 'Inf', 1, 'numel', [1], '>', 0) + md = checkfield(md, 'fieldname', 'love.sh_nmin', 'NaN', 1, 'Inf', 1, 'numel', [1], '>', 0) + md = checkfield(md, 'fieldname', 'love.g0', 'NaN', 1, 'Inf', 1, 'numel', [1], '>', 0) + md = checkfield(md, 'fieldname', 'love.r0', 'NaN', 1, 'Inf', 1, 'numel', [1], '>', 0) + md = checkfield(md, 'fieldname', 'love.mu0', 'NaN', 1, 'Inf', 1, 'numel', [1], '>', 0) + md = checkfield(md, 'fieldname', 'love.allow_layer_deletion', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'love.love_kernels', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'love.forcing_type', 'NaN', 1, 'Inf', 1, 'numel', [1], '>', 0, '<=', 12) + if md.love.sh_nmin <= 1 and md.love.forcing_type == 9: + raise RuntimeError("Degree 1 not supported for Volumetric Potential forcing. Use sh_min >= 2 for this kind of calculation.") - return md - # }}} + return md + # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','nfreq','format','Integer'); - WriteData(fid,prefix,'object',self,'fieldname','frequencies','format','DoubleMat','mattype',3); - WriteData(fid,prefix,'object',self,'fieldname','sh_nmax','format','Integer'); - WriteData(fid,prefix,'object',self,'fieldname','sh_nmin','format','Integer'); - WriteData(fid,prefix,'object',self,'fieldname','g0','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','r0','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','mu0','format','Double'); - WriteData(fid,prefix,'object',self,'fieldname','allow_layer_deletion','format','Boolean'); - WriteData(fid,prefix,'object',self,'fieldname','love_kernels','format','Boolean'); - WriteData(fid,prefix,'object',self,'fieldname','forcing_type','format','Integer'); - # }}} + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'nfreq', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'frequencies', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'fieldname', 'sh_nmax', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'sh_nmin', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'g0', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'r0', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'mu0', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'allow_layer_deletion', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'love_kernels', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'forcing_type', 'format', 'Integer') + # }}} Index: /issm/trunk-jpl/src/m/classes/friction.py =================================================================== --- /issm/trunk-jpl/src/m/classes/friction.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/friction.py (revision 24213) @@ -10,5 +10,5 @@ Usage: - friction=friction() + friction = friction() """ @@ -19,10 +19,11 @@ self.coupling = 0 self.effective_pressure = float('NaN') - #set defaults + #set defaults self.setdefaultparameters() + self.requested_outputs = [] #}}} def __repr__(self): # {{{ - string = "Basal shear stress parameters: Sigma_b = coefficient^2 * Neff ^r * |u_b|^(s-1) * u_b,\n(effective stress Neff=rho_ice*g*thickness+rho_water*g*base, r=q/p and s=1/p)" + string = "Basal shear stress parameters: Sigma_b = coefficient^2 * Neff ^r * |u_b|^(s - 1) * u_b, \n(effective stress Neff = rho_ice * g * thickness + rho_water * g * base, r = q / p and s = 1 / p)" string = "%s\n%s" % (string, fielddisplay(self, "coefficient", "friction coefficient [SI]")) @@ -31,4 +32,5 @@ string = "%s\n%s" % (string, fielddisplay(self, 'coupling', 'Coupling flag 0: uniform sheet (negative pressure ok, default), 1: ice pressure only, 2: water pressure assuming uniform sheet (no negative pressure), 3: use provided effective_pressure, 4: used coupled model (not implemented yet)')) string = "%s\n%s" % (string, fielddisplay(self, 'effective_pressure', 'Effective Pressure for the forcing if not coupled [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) return string #}}} @@ -38,5 +40,5 @@ self.p = project3d(md, 'vector', self.p, 'type', 'element') self.q = project3d(md, 'vector', self.q, 'type', 'element') - #if self.coupling==0: #doesnt work with empty loop, so just skip it? + #if self.coupling == 0: #doesnt work with empty loop, so just skip it? if self.coupling in[3, 4]: self.effective_pressure = project3d(md, 'vector', self.effective_pressure, 'type', 'node', 'layer', 1) @@ -47,5 +49,11 @@ def setdefaultparameters(self): # {{{ + self.requested_outputs = ['default'] return self + #}}} + + def defaultoutputs(self, md): # {{{ + list = [] + return list #}}} @@ -63,5 +71,6 @@ md = checkfield(md, 'fieldname', 'friction.effective_pressure', 'NaN', 1, 'Inf', 1, 'timeseries', 1) elif self.coupling > 4: - raise ValueError('md.friction.coupling larger than 4, not supported yet') + raise ValueError('md.friction.coupling larger than 4, not supported yet') + md = checkfield(md, 'fieldname', 'friction.requested_outputs', 'stringrow', 1) return md # }}} @@ -73,7 +82,17 @@ WriteData(fid, prefix, 'object', self, 'fieldname', 'q', 'format', 'DoubleMat', 'mattype', 2) WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'coupling', 'format', 'Integer') - if self.coupling in[3, 4]: + if self.coupling == 3: WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'effective_pressure', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + if self.coupling == 4: + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'effective_pressure', 'format', 'DoubleMat', 'mattype', 1) elif self.coupling > 4: - raise ValueError('md.friction.coupling larger than 4, not supported yet') + raise ValueError('md.friction.coupling larger than 4, not supported yet') + + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.friction.requested_outputs', 'format', 'StringArray') # }}} Index: /issm/trunk-jpl/src/m/classes/frictioncoulomb.py =================================================================== --- /issm/trunk-jpl/src/m/classes/frictioncoulomb.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/frictioncoulomb.py (revision 24213) @@ -4,81 +4,83 @@ from WriteData import WriteData + class frictioncoulomb(object): - """ - FRICTIONCOULOMB class definition + """ + FRICTIONCOULOMB class definition - Usage: - frictioncoulomb=frictioncoulomb() - """ + Usage: + frictioncoulomb = frictioncoulomb() + """ - def __init__(self): # {{{ - self.coefficient = float('NaN') - self.coefficientcoulomb = float('NaN') - self.p = float('NaN') - self.q = float('NaN') - self.coupling = 0 - self.effective_pressure = float('NaN') - #set defaults - self.setdefaultparameters() + def __init__(self): # {{{ + self.coefficient = float('NaN') + self.coefficientcoulomb = float('NaN') + self.p = float('NaN') + self.q = float('NaN') + self.coupling = 0 + self.effective_pressure = float('NaN') + #set defaults + self.setdefaultparameters() #}}} - def __repr__(self): # {{{ - string="Basal shear stress parameters: Sigma_b = min(coefficient^2 * Neff ^r * |u_b|^(s-1) * u_b,\n coefficientcoulomb^2 * rho_i * g * (h-h_f)), (effective stress Neff=rho_ice*g*thickness+rho_water*g*bed, r=q/p and s=1/p)." - string="%s\n%s"%(string,fielddisplay(self,"coefficient","power law (Weertman) friction coefficient [SI]")) - string="%s\n%s"%(string,fielddisplay(self,"coefficientcoulomb","Coulomb friction coefficient [SI]")) - string="%s\n%s"%(string,fielddisplay(self,"p","p exponent")) - string="%s\n%s"%(string,fielddisplay(self,"q","q exponent")) - string="%s\n%s"%(string,fielddisplay(self,'coupling','Coupling flag: 0 for default, 1 for forcing(provide md.friction.effective_pressure) and 2 for coupled(not implemented yet)')) - string="%s\n%s"%(string,fielddisplay(self,'effective_pressure','Effective Pressure for the forcing if not coupled [Pa]')) - return string - #}}} - def extrude(self,md): # {{{ - self.coefficient=project3d(md,'vector',self.coefficient,'type','node','layer',1) - self.coefficientcoulomb=project3d(md,'vector',self.coefficientcoulomb,'type','node','layer',1) - self.p=project3d(md,'vector',self.p,'type','element') - self.q=project3d(md,'vector',self.q,'type','element') - if self.coupling==1: - self.effective_pressure=project3d(md,'vector',self.effective_pressure,'type','node','layer',1) - elif self.coupling==2: - raise ValueError('coupling not supported yet') - elif self.coupling > 2: - raise ValueError('md.friction.coupling larger than 2, not supported yet') - return self - #}}} + def __repr__(self): # {{{ + string = "Basal shear stress parameters: Sigma_b = min(coefficient^2 * Neff ^r * |u_b|^(s - 1) * u_b, \n coefficientcoulomb^2 * rho_i * g * (h - h_f)), (effective stress Neff = rho_ice * g * thickness + rho_water * g * bed, r = q / p and s = 1 / p)." + string = "%s\n%s" % (string, fielddisplay(self, "coefficient", "power law (Weertman) friction coefficient [SI]")) + string = "%s\n%s" % (string, fielddisplay(self, "coefficientcoulomb", "Coulomb friction coefficient [SI]")) + string = "%s\n%s" % (string, fielddisplay(self, "p", "p exponent")) + string = "%s\n%s" % (string, fielddisplay(self, "q", "q exponent")) + string = "%s\n%s" % (string, fielddisplay(self, 'coupling', 'Coupling flag: 0 for default, 1 for forcing(provide md.friction.effective_pressure) and 2 for coupled(not implemented yet)')) + string = "%s\n%s" % (string, fielddisplay(self, 'effective_pressure', 'Effective Pressure for the forcing if not coupled [Pa]')) + return string + #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} + def extrude(self, md): # {{{ + self.coefficient = project3d(md, 'vector', self.coefficient, 'type', 'node', 'layer', 1) + self.coefficientcoulomb = project3d(md, 'vector', self.coefficientcoulomb, 'type', 'node', 'layer', 1) + self.p = project3d(md, 'vector', self.p, 'type', 'element') + self.q = project3d(md, 'vector', self.q, 'type', 'element') + if self.coupling == 1: + self.effective_pressure = project3d(md, 'vector', self.effective_pressure, 'type', 'node', 'layer', 1) + elif self.coupling == 2: + raise ValueError('coupling not supported yet') + elif self.coupling > 2: + raise ValueError('md.friction.coupling larger than 2, not supported yet') + return self + #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - #Early return - if 'StressbalanceAnalysis' not in analyses and 'ThermalAnalysis' not in analyses: - return md + def setdefaultparameters(self): # {{{ + return self + #}}} - md = checkfield(md,'fieldname','friction.coefficient','timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','friction.coefficientcoulomb','timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','friction.q','NaN',1,'Inf',1,'size',[md.mesh.numberofelements]) - md = checkfield(md,'fieldname','friction.p','NaN',1,'Inf',1,'size',[md.mesh.numberofelements]) - if self.coupling==1: - md = checkfield(md,'fieldname','friction.effective_pressure','NaN',1,'Inf',1,'timeseries',1) - elif self.coupling==2: - raise ValueError('coupling not supported yet') - elif self.coupling > 2: - raise ValueError('md.friction.coupling larger than 2, not supported yet') - return md + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if 'StressbalanceAnalysis' not in analyses and 'ThermalAnalysis' not in analyses: + return md + + md = checkfield(md, 'fieldname', 'friction.coefficient', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'friction.coefficientcoulomb', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'friction.q', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofelements]) + md = checkfield(md, 'fieldname', 'friction.p', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofelements]) + if self.coupling == 1: + md = checkfield(md, 'fieldname', 'friction.effective_pressure', 'NaN', 1, 'Inf', 1, 'timeseries', 1) + elif self.coupling == 2: + raise ValueError('coupling not supported yet') + elif self.coupling > 2: + raise ValueError('md.friction.coupling larger than 2, not supported yet') + return md # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.friction.law','data',7,'format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','coefficient','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','coefficientcoulomb','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','p','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'fieldname','q','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'class','friction','object',self,'fieldname','coupling','format','Integer') - if self.coupling==1: - WriteData(fid,prefix,'class','friction','object',self,'fieldname','effective_pressure','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - elif self.coupling==2: - raise ValueError('coupling not supported yet') - elif self.coupling > 2: - raise ValueError('md.friction.coupling larger than 2, not supported yet') + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.friction.law', 'data', 7, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'coefficient', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'coefficientcoulomb', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'p', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'fieldname', 'q', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'coupling', 'format', 'Integer') + if self.coupling == 1: + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'effective_pressure', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + elif self.coupling == 2: + raise ValueError('coupling not supported yet') + elif self.coupling > 2: + raise ValueError('md.friction.coupling larger than 2, not supported yet') # }}} Index: /issm/trunk-jpl/src/m/classes/frictionhydro.py =================================================================== --- /issm/trunk-jpl/src/m/classes/frictionhydro.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/frictionhydro.py (revision 24213) @@ -7,76 +7,74 @@ class frictionhydro(object): - """ - friction hydro is the friction law from Schoof 2005 or Gagliardini2007 + """ + friction hydro is the friction law from Schoof 2005 or Gagliardini2007 - Usage: - friction=frictionhydro(); - """ - def __init__(self): # {{{ - self.coupling = 0 - self.q = np.nan - self.C = np.nan - self.As = np.nan - self.effective_pressure = np.nan - #set defaults + Usage: + friction = frictionhydro() + """ + def __init__(self): # {{{ + self.coupling = 0 + self.q = np.nan + self.C = np.nan + self.As = np.nan + self.effective_pressure = np.nan + #set defaults - self.setdefaultparameters() - # }}} + self.setdefaultparameters() + # }}} - def __repr__(self): # {{{ - string='Effective Pressure based friction law described in Gagliardini 2007' - string="%s\n%s"%(string,fielddisplay(self,'coupling','Coupling flag 0: uniform sheet (negative pressure ok, default), 1: ice pressure only, 2: water pressure assuming uniform sheet (no negative pressure), 3: use provided effective_pressure, 4: used coupled model (not implemented yet)')) - string="%s\n%s"%(string,fielddisplay(self,'q','friction law exponent q>=1')) - string="%s\n%s"%(string,fielddisplay(self,'C','friction law max value (Iken bound)')) - string="%s\n%s"%(string,fielddisplay(self,'As','Sliding Parameter without cavitation [m Pa^-n s^-1]')) - string="%s\n%s"%(string,fielddisplay(self,'effective_pressure','Effective Pressure for the forcing if not coupled [Pa]')) + def __repr__(self): # {{{ + string = 'Effective Pressure based friction law described in Gagliardini 2007' + string = "%s\n%s" % (string, fielddisplay(self, 'coupling', 'Coupling flag 0: uniform sheet (negative pressure ok, default), 1: ice pressure only, 2: water pressure assuming uniform sheet (no negative pressure), 3: use provided effective_pressure, 4: used coupled model (not implemented yet)')) + string = "%s\n%s" % (string, fielddisplay(self, 'q', 'friction law exponent q >= 1')) + string = "%s\n%s" % (string, fielddisplay(self, 'C', 'friction law max value (Iken bound)')) + string = "%s\n%s" % (string, fielddisplay(self, 'As', 'Sliding Parameter without cavitation [m Pa^ - n s^ - 1]')) + string = "%s\n%s" % (string, fielddisplay(self, 'effective_pressure', 'Effective Pressure for the forcing if not coupled [Pa]')) - return string - # }}} + return string + # }}} - def extrude(self,md): # {{{ - self.q=project3d(md,'vector',self.q,'type','element') - self.C=project3d(md,'vector',self.C,'type','element') - self.As=project3d(md,'vector',self.As,'type','element') - if self.coupling in[3,4]: - self.effective_pressure=project3d(md,'vector',self.effective_pressure,'type','node','layer',1) - elif self.coupling > 4: - raise ValueError('md.friction.coupling larger than 4, not supported yet') - return self - # }}} + def extrude(self, md): # {{{ + self.q = project3d(md, 'vector', self.q, 'type', 'element') + self.C = project3d(md, 'vector', self.C, 'type', 'element') + self.As = project3d(md, 'vector', self.As, 'type', 'element') + if self.coupling in[3, 4]: + self.effective_pressure = project3d(md, 'vector', self.effective_pressure, 'type', 'node', 'layer', 1) + elif self.coupling > 4: + raise ValueError('md.friction.coupling larger than 4, not supported yet') + return self + # }}} - def setdefaultparameters(self): # {{{ + def setdefaultparameters(self): # {{{ + self.coupling = 0 + self.effective_pressure = np.nan - self.coupling = 0 - self.effective_pressure = np.nan + return self + # }}} - return self - # }}} + def checkconsistency(self, md, solution, analyses): #{{{ + #Early return + if 'StressbalanceAnalysis' in analyses and 'ThermalAnalysis' in analyses: + return md - def checkconsistency(self,md,solution,analyses): #{{{ + md = checkfield(md, 'fieldname', 'friction.coupling', 'numel', [1], 'values', [0, 1, 2, 3, 4]) + md = checkfield(md, 'fieldname', 'friction.q', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofelements]) + md = checkfield(md, 'fieldname', 'friction.C', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofelements]) + md = checkfield(md, 'fieldname', 'friction.As', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofelements]) + if self.coupling == 3: + md = checkfield(md, 'fieldname', 'friction.effective_pressure', 'NaN', 1, 'Inf', 1, 'timeseries', 1) + elif self.coupling > 4: + raise ValueError('md.friction.coupling larger than 4, not supported yet') + # }}} - #Early return - if 'StressbalanceAnalysis' in analyses and 'ThermalAnalysis' in analyses: - return md - - md = checkfield(md,'fieldname','friction.coupling','numel',[1],'values',[0,1,2,3,4]) - md = checkfield(md,'fieldname','friction.q','NaN',1,'Inf',1,'size',[md.mesh.numberofelements]) - md = checkfield(md,'fieldname','friction.C','NaN',1,'Inf',1,'size',[md.mesh.numberofelements]) - md = checkfield(md,'fieldname','friction.As','NaN',1,'Inf',1,'size',[md.mesh.numberofelements]) - if self.coupling==3: - md = checkfield(md,'fieldname','friction.effective_pressure','NaN',1,'Inf',1,'timeseries',1) - elif self.coupling > 4: - raise ValueError('md.friction.coupling larger than 4, not supported yet') - # }}} - - def marshall(self,prefix,md,fid): #{{{ - WriteData(fid,prefix,'name','md.friction.law','data',3,'format','Integer') - WriteData(fid,prefix,'class','friction','object',self,'fieldname','coupling','format','Integer') - WriteData(fid,prefix,'class','friction','object',self,'fieldname','q','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'class','friction','object',self,'fieldname','C','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'class','friction','object',self,'fieldname','As','format','DoubleMat','mattype',2) - if self.coupling in[3,4]: - WriteData(fid,prefix,'class','friction','object',self,'fieldname','effective_pressure','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - elif self.coupling > 4: - raise ValueError('md.friction.coupling larger than 4, not supported yet') - #}}} + def marshall(self, prefix, md, fid): #{{{ + WriteData(fid, prefix, 'name', 'md.friction.law', 'data', 3, 'format', 'Integer') + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'coupling', 'format', 'Integer') + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'q', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'C', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'As', 'format', 'DoubleMat', 'mattype', 2) + if self.coupling in[3, 4]: + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'effective_pressure', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + elif self.coupling > 4: + raise ValueError('md.friction.coupling larger than 4, not supported yet') + #}}} Index: /issm/trunk-jpl/src/m/classes/frictionshakti.py =================================================================== --- /issm/trunk-jpl/src/m/classes/frictionshakti.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/frictionshakti.py (revision 24213) @@ -4,45 +4,45 @@ from WriteData import WriteData + class frictionshakti(object): - """ - FRICTIONSHAKTI class definition + """ + FRICTIONSHAKTI class definition - Usage: - friction=frictionshakti() - """ + Usage: + friction = frictionshakti() + """ - def __init__(self,md): # {{{ - self.coefficient = md.friction.coefficient - #set defaults - self.setdefaultparameters() - #}}} + def __init__(self, md): # {{{ + self.coefficient = md.friction.coefficient + #set defaults + self.setdefaultparameters() + #}}} - def __repr__(self): # {{{ - string="Basal shear stress parameters: Sigma_b = coefficient^2 * Neff * u_b\n(effective stress Neff=rho_ice*g*thickness+rho_water*g*(head-b))" - string="%s\n%s"%(string,fielddisplay(self,"coefficient","friction coefficient [SI]")) - return string - #}}} + def __repr__(self): # {{{ + string = "Basal shear stress parameters: Sigma_b = coefficient^2 * Neff * u_b\n(effective stress Neff = rho_ice * g * thickness + rho_water * g * (head - b))" + string = "%s\n%s" % (string, fielddisplay(self, "coefficient", "friction coefficient [SI]")) + return string + #}}} - def extrude(self,md): # {{{ - self.coefficient=project3d(md,'vector',self.coefficient,'type','node','layer',1) - return self - #}}} + def extrude(self, md): # {{{ + self.coefficient = project3d(md, 'vector', self.coefficient, 'type', 'node', 'layer', 1) + return self + #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} + def setdefaultparameters(self): # {{{ + return self + #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - #Early return - if 'StressbalanceAnalysis' not in analyses and 'ThermalAnalysis' not in analyses: - return md + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if 'StressbalanceAnalysis' not in analyses and 'ThermalAnalysis' not in analyses: + return md - md = checkfield(md,'fieldname','friction.coefficient','timeseries',1,'NaN',1,'Inf',1) - return md - # }}} + md = checkfield(md, 'fieldname', 'friction.coefficient', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + return md + # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts - WriteData(fid,prefix,'name','md.friction.law','data',8,'format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','coefficient','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.friction.law', 'data', 8, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'coefficient', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) # }}} Index: /issm/trunk-jpl/src/m/classes/frictionwaterlayer.py =================================================================== --- /issm/trunk-jpl/src/m/classes/frictionwaterlayer.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/frictionwaterlayer.py (revision 24213) @@ -1,3 +1,2 @@ -import numpy as np from project3d import project3d from fielddisplay import fielddisplay @@ -7,61 +6,56 @@ class frictionwaterlayer(object): - """ - frictionwaterlayer class definition + """ + frictionwaterlayer class definition - Usage: - friction=frictionwaterlayer(md); - """ - def __init__(self,md): # {{{ - self.coefficient = md.friction.coefficient - self.f = float('NaN') - self.p = md.friction.p - self.q = md.friction.q - self.water_layer = float('NaN') - #}}} - - def checkconsistency(self,md,solution,analyses): #{{{ - #Early return - if ('StressbalanceAnalysis' not in analyses) and ('ThermalAnalysis' not in analyses): - return + Usage: + friction = frictionwaterlayer(md) + """ + def __init__(self, md): # {{{ + self.coefficient = md.friction.coefficient + self.f = float('NaN') + self.p = md.friction.p + self.q = md.friction.q + self.water_layer = float('NaN') + #}}} - md = checkfield(md,'fieldname','friction.coefficient','timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','friction.f','size',[1],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','friction.q','NaN',1,'Inf',1,'size',[md.mesh.numberofelements]) - md = checkfield(md,'fieldname','friction.p','NaN',1,'Inf',1,'size',[md.mesh.numberofelements]) - md = checkfield(md,'fieldname','thermal.spctemperature','Inf',1,'timeseries',1,'>=',0.) - # }}} + def checkconsistency(self, md, solution, analyses): #{{{ + #Early return + if ('StressbalanceAnalysis' not in analyses) and ('ThermalAnalysis' not in analyses): + return - def extrude(self,md): # {{{ - self.coefficient=project3d(md,'vector',self.coefficient,'type','node','layer',1) - self.p=project3d(md,'vector',self.p,'type','element') - self.q=project3d(md,'vector',self.q,'type','element') - self.water_layer=project3d(md,'vector',self.water_layer,'type','node','layer',1) - return self - # }}} + md = checkfield(md, 'fieldname', 'friction.coefficient', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'friction.f', 'size', [1], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'friction.q', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofelements]) + md = checkfield(md, 'fieldname', 'friction.p', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofelements]) + md = checkfield(md, 'fieldname', 'thermal.spctemperature', 'Inf', 1, 'timeseries', 1, '>=', 0.) + # }}} + def extrude(self, md): # {{{ + self.coefficient = project3d(md, 'vector', self.coefficient, 'type', 'node', 'layer', 1) + self.p = project3d(md, 'vector', self.p, 'type', 'element') + self.q = project3d(md, 'vector', self.q, 'type', 'element') + self.water_layer = project3d(md, 'vector', self.water_layer, 'type', 'node', 'layer', 1) + return self + # }}} - def __repr__(self): # {{{ - string='Basal shear stress parameters: tau_b = coefficient^2 * Neff ^r * |u_b|^(s-1) * u_b * 1/f(T)\n(effective stress Neff=rho_ice*g*thickness+rho_water*g*(bed+water_layer), r=q/p and s=1/p)' - string="%s\n%s"%(string,fielddisplay(self,'coefficient','frictiontemp coefficient [SI]')) - string="%s\n%s"%(string,fielddisplay(self,'f','f variable for effective pressure')) - string="%s\n%s"%(string,fielddisplay(self,'p','p exponent')) - string="%s\n%s"%(string,fielddisplay(self,'q','q exponent')) - string="%s\n%s"%(string,fielddisplay(self,'water_layer','water thickness at the base of the ice (m)')) + def __repr__(self): # {{{ + string = 'Basal shear stress parameters: tau_b = coefficient^2 * Neff ^r * |u_b|^(s - 1) * u_b * 1 / f(T)\n(effective stress Neff = rho_ice * g * thickness + rho_water * g * (bed + water_layer), r = q / p and s = 1 / p)' + string = "%s\n%s" % (string, fielddisplay(self, 'coefficient', 'frictiontemp coefficient [SI]')) + string = "%s\n%s" % (string, fielddisplay(self, 'f', 'f variable for effective pressure')) + string = "%s\n%s" % (string, fielddisplay(self, 'p', 'p exponent')) + string = "%s\n%s" % (string, fielddisplay(self, 'q', 'q exponent')) + string = "%s\n%s" % (string, fielddisplay(self, 'water_layer', 'water thickness at the base of the ice (m)')) - return string - #}}} + return string + #}}} - - def marshall(self,prefix,md,fid): #{{{ - yts=md.constants.yts - - WriteData(fid,prefix,'name','md.friction.law','data',5,'format','Integer') - WriteData(fid,prefix,'class','friction','object',self,'fieldname','coefficient','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'class','friction','object',self,'fieldname','f','format','Double') - WriteData(fid,prefix,'class','friction','object',self,'fieldname','p','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'class','friction','object',self,'fieldname','q','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'class','friction','object',self,'fieldname','water_layer','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - #}}} - - + def marshall(self, prefix, md, fid): #{{{ + yts = md.constants.yts + WriteData(fid, prefix, 'name', 'md.friction.law', 'data', 5, 'format', 'Integer') + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'coefficient', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'f', 'format', 'Double') + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'p', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'q', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'water_layer', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + #}}} Index: /issm/trunk-jpl/src/m/classes/frictionweertman.py =================================================================== --- /issm/trunk-jpl/src/m/classes/frictionweertman.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/frictionweertman.py (revision 24213) @@ -1,47 +1,51 @@ from fielddisplay import fielddisplay -from project3d import project3d from checkfield import checkfield from WriteData import WriteData + class frictionweertman(object): - """ - FRICTIONWEERTMAN class definition + """ + FRICTIONWEERTMAN class definition - Usage: - frictionweertman=frictionweertman(); - """ + Usage: + frictionweertman = frictionweertman() + """ - def __init__(self): # {{{ - self.C = float('NaN') - self.m = float('NaN') + def __init__(self): # {{{ + self.C = float('NaN') + self.m = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string="Weertman sliding law parameters: Sigma_b = C^(-1/m) * |u_b|^(1/m-1) * u_b" + #}}} - string="%s\n%s"%(string,fielddisplay(self,"C","friction coefficient [SI]")) - string="%s\n%s"%(string,fielddisplay(self,"m","m exponent")) - return string - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def __repr__(self): # {{{ + string = "Weertman sliding law parameters: Sigma_b = C^(- 1 / m) * |u_b|^(1 / m - 1) * u_b" - #Early return - if 'StressbalanceAnalysis' not in analyses and 'ThermalAnalysis' not in analyses: - return md + string = "%s\n%s" % (string, fielddisplay(self, "C", "friction coefficient [SI]")) + string = "%s\n%s" % (string, fielddisplay(self, "m", "m exponent")) + return string + #}}} - md = checkfield(md,'fieldname','friction.C','timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','friction.m','NaN',1,'Inf',1,'size',[md.mesh.numberofelements]) + def setdefaultparameters(self): # {{{ + return self + #}}} - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.friction.law','data',2,'format','Integer') - WriteData(fid,prefix,'class','friction','object',self,'fieldname','C','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'class','friction','object',self,'fieldname','m','format','DoubleMat','mattype',2) - # }}} + def checkconsistency(self, md, solution, analyses): # {{{ + + #Early return + if 'StressbalanceAnalysis' not in analyses and 'ThermalAnalysis' not in analyses: + return md + + md = checkfield(md, 'fieldname', 'friction.C', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'friction.m', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofelements]) + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.friction.law', 'data', 2, 'format', 'Integer') + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'C', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'class', 'friction', 'object', self, 'fieldname', 'm', 'format', 'DoubleMat', 'mattype', 2) + # }}} Index: /issm/trunk-jpl/src/m/classes/frontalforcings.py =================================================================== --- /issm/trunk-jpl/src/m/classes/frontalforcings.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/frontalforcings.py (revision 24213) @@ -4,47 +4,48 @@ from WriteData import WriteData + class frontalforcings(object): - """ - FRONTAL FORCINGS class definition + """ + FRONTAL FORCINGS class definition - Usage: - frontalforcings=frontalforcings(); - """ + Usage: + frontalforcings = frontalforcings() + """ - def __init__(self): # {{{ - self.meltingrate = float('NaN') + def __init__(self): # {{{ + self.meltingrate = float('NaN') - #set defaults - self.setdefaultparameters() - #}}} + #set defaults + self.setdefaultparameters() + #}}} - def __repr__(self): # {{{ - string=' Frontalforcings parameters:' - string="%s\n%s"%(string,fielddisplay(self,'meltingrate','melting rate at given location [m/a]')) + def __repr__(self): # {{{ + string = ' Frontalforcings parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'meltingrate', 'melting rate at given location [m / a]')) - return string - #}}} + return string + #}}} - def extrude(self,md): # {{{ - self.meltingrate=project3d(md,'vector',self.meltingrate,'type','node') - return self - #}}} + def extrude(self, md): # {{{ + self.meltingrate = project3d(md, 'vector', self.meltingrate, 'type', 'node') + return self + #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} + def setdefaultparameters(self): # {{{ + return self + #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - #Early return - if (solution!='TransientSolution') or (not md.transient.ismovingfront): - return md + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if (solution != 'TransientSolution') or (not md.transient.ismovingfront): + return md - md = checkfield(md,'fieldname','frontalforcings.meltingrate','NaN',1,'Inf',1,'timeseries',1,'>=',0); - return md - # }}} + md = checkfield(md, 'fieldname', 'frontalforcings.meltingrate', 'NaN', 1, 'Inf', 1, 'timeseries', 1, '>=', 0) + return md + # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts - WriteData(fid,prefix,'name','md.frontalforcings.parameterization','data',1,'format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','meltingrate','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts,'scale',1./yts); - # }}} + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + WriteData(fid, prefix, 'name', 'md.frontalforcings.parameterization', 'data', 1, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'meltingrate', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts, 'scale', 1. / yts) + # }}} Index: /issm/trunk-jpl/src/m/classes/frontalforcingsrignot.py =================================================================== --- /issm/trunk-jpl/src/m/classes/frontalforcingsrignot.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/frontalforcingsrignot.py (revision 24213) @@ -1,64 +1,63 @@ -from fielddisplay import fielddisplay -from project3d import project3d from checkfield import checkfield from WriteData import WriteData +from fielddisplay import fielddisplay + class frontalforcingsrignot(object): - """ - FRONTAL FORCINGS Rignot class definition + """ + FRONTAL FORCINGS Rignot class definition - Usage: - frontalforcingsrignot=frontalforcingsrignot(); - """ + Usage: + frontalforcingsrignot = frontalforcingsrignot() + """ - def __init__(self): # {{{ + def __init__(self): # {{{ + self.basin = float('NaN') + self.numberofbasins = 0. + self.subglacial_discharge = float('NaN') + self.thermalforcing = float('NaN') - self.basin= float('NaN'); - self.numberofbasins = 0.; - self.subglacial_discharge = float('NaN'); - self.thermalforcing = float('NaN'); + #set defaults + self.setdefaultparameters() - #set defaults - self.setdefaultparameters() + #}}} - #}}} - def __repr__(self): # {{{ - string=' Frontalforcings parameters:' - string="%s\n%s"%(string,fielddisplay(self,'basin','basin ID for vertices')) - string="%s\n%s"%(string,fielddisplay(self,'numberofbasins','number of basins')) - string="%s\n%s"%(string,fielddisplay(self,'subglacial_discharge','sum of subglacial discharge for each basin [m/d]')) - string="%s\n%s"%(string,fielddisplay(self,'thermalforcing','thermal forcing [C]')) + def __repr__(self): # {{{ + string = ' Frontalforcings parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'basin', 'basin ID for vertices')) + string = "%s\n%s" % (string, fielddisplay(self, 'numberofbasins', 'number of basins')) + string = "%s\n%s" % (string, fielddisplay(self, 'subglacial_discharge', 'sum of subglacial discharge for each basin [m / d]')) + string = "%s\n%s" % (string, fielddisplay(self, 'thermalforcing', 'thermal forcing [C]')) - return string - #}}} - def extrude(self,md): # {{{ - return self - #}}} - def setdefaultparameters(self): # {{{ + return string + #}}} - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def extrude(self, md): # {{{ + return self + #}}} - #Early return - if (solution!='TransientSolution') or (not md.transient.ismovingfront): - return md + def setdefaultparameters(self): # {{{ - md = checkfield(md,'fieldname','frontalforcings.basin','>',0,'nan',1,'Inf',1); - md = checkfield(md,'fieldname','frontalforcings.numberofbasins','numel',[1]); - md = checkfield(md,'fieldname','frontalforcings.subglacial_discharge','>=',0,'nan',1,'Inf',1,'timeseries',1); - md = checkfield(md,'fieldname','frontalforcings.thermalforcing','nan',1,'Inf',1,'timeseries',1); + return self + #}}} - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if (solution != 'TransientSolution') or (not md.transient.ismovingfront): + return md - yts=md.constants.yts + md = checkfield(md, 'fieldname', 'frontalforcings.basin', '>', 0, 'nan', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'frontalforcings.numberofbasins', 'numel', [1]) + md = checkfield(md, 'fieldname', 'frontalforcings.subglacial_discharge', '>=', 0, 'nan', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'frontalforcings.thermalforcing', 'nan', 1, 'Inf', 1, 'timeseries', 1) + return md + # }}} - WriteData(fid,prefix,'name','md.frontalforcings.parameterization','data',2,'format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','basin','format','DoubleMat','mattype',1); - WriteData(fid,prefix,'object',self,'fieldname','numberofbasins','format','Integer'); - WriteData(fid,prefix,'object',self,'fieldname','subglacial_discharge','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1); - WriteData(fid,prefix,'object',self,'fieldname','thermalforcing','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1); + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.frontalforcings.parameterization', 'data', 2, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'basin', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'numberofbasins', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'subglacial_discharge', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'thermalforcing', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1) - # }}} + # }}} Index: /issm/trunk-jpl/src/m/classes/geometry.py =================================================================== --- /issm/trunk-jpl/src/m/classes/geometry.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/geometry.py (revision 24213) @@ -5,71 +5,76 @@ from WriteData import WriteData + class geometry(object): - """ - GEOMETRY class definition + """ + GEOMETRY class definition - Usage: - geometry=geometry(); - """ + Usage: + geometry = geometry() + """ - def __init__(self): # {{{ - self.surface = float('NaN') - self.thickness = float('NaN') - self.base = float('NaN') - self.bed = float('NaN') - self.hydrostatic_ratio = float('NaN') + def __init__(self): # {{{ + self.surface = float('NaN') + self.thickness = float('NaN') + self.base = float('NaN') + self.bed = float('NaN') + self.hydrostatic_ratio = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ + #}}} - string=" geometry parameters:" - string="%s\n%s"%(string,fielddisplay(self,'surface','ice upper surface elevation [m]')) - string="%s\n%s"%(string,fielddisplay(self,'thickness','ice thickness [m]')) - string="%s\n%s"%(string,fielddisplay(self,'base','ice base elevation [m]')) - string="%s\n%s"%(string,fielddisplay(self,'bed','bed elevation [m]')) - return string - #}}} - def extrude(self,md): # {{{ - self.surface=project3d(md,'vector',self.surface,'type','node') - self.thickness=project3d(md,'vector',self.thickness,'type','node') - self.hydrostatic_ratio=project3d(md,'vector',self.hydrostatic_ratio,'type','node') - self.base=project3d(md,'vector',self.base,'type','node') - self.bed=project3d(md,'vector',self.bed,'type','node') - return self - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def __repr__(self): # {{{ - if (solution=='TransientSolution' and md.transient.isgia) or (solution=='GiaSolution'): - md = checkfield(md,'fieldname','geometry.thickness','NaN',1,'Inf',1,'timeseries',1) - elif solution=='LoveSolution': - return - else: - md = checkfield(md,'fieldname','geometry.surface' ,'NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','geometry.base' ,'NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','geometry.thickness','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices],'>',0,'timeseries',1) - if any(abs(self.thickness-self.surface+self.base)>10**-9): - md.checkmessage("equality thickness=surface-base violated") - if solution=='TransientSolution' and md.transient.isgroundingline: - md = checkfield(md,'fieldname','geometry.bed','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - if np.any(self.bed - self.base > 10**-12): - md.checkmessage('base 0) - if np.any(np.abs(self.bed[pos]-self.base[pos])>10**-9): - md.checkmessage('equality base=bed on grounded ice violated') - md = checkfield(md,'fieldname','geometry.bed','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) + string = " geometry parameters:" + string = "%s\n%s" % (string, fielddisplay(self, 'surface', 'ice upper surface elevation [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'thickness', 'ice thickness [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'base', 'ice base elevation [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'bed', 'bed elevation [m]')) + return string + #}}} - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','surface','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','thickness','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','base','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','bed','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','hydrostatic_ratio','format','DoubleMat','mattype',1) - # }}} + def extrude(self, md): # {{{ + self.surface = project3d(md, 'vector', self.surface, 'type', 'node') + self.thickness = project3d(md, 'vector', self.thickness, 'type', 'node') + self.hydrostatic_ratio = project3d(md, 'vector', self.hydrostatic_ratio, 'type', 'node') + self.base = project3d(md, 'vector', self.base, 'type', 'node') + self.bed = project3d(md, 'vector', self.bed, 'type', 'node') + return self + #}}} + + def setdefaultparameters(self): # {{{ + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + if (solution == 'TransientSolution' and md.transient.isgia) or (solution == 'GiaSolution'): + md = checkfield(md, 'fieldname', 'geometry.thickness', 'NaN', 1, 'Inf', 1, 'timeseries', 1) + elif solution == 'LoveSolution': + return + else: + md = checkfield(md, 'fieldname', 'geometry.surface', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'geometry.base', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'geometry.thickness', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices], '>', 0, 'timeseries', 1) + if any(abs(self.thickness - self.surface + self.base) > 10**- 9): + md.checkmessage("equality thickness = surface-base violated") + if solution == 'TransientSolution' and md.transient.isgroundingline: + md = checkfield(md, 'fieldname', 'geometry.bed', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + if np.any(self.bed - self.base > 10**- 12): + md.checkmessage('base < bed on one or more vertex') + pos = np.where(md.mask.groundedice_levelset > 0) + if np.any(np.abs(self.bed[pos] - self.base[pos]) > 10**- 9): + md.checkmessage('equality base = bed on grounded ice violated') + md = checkfield(md, 'fieldname', 'geometry.bed', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'surface', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'thickness', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'base', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'bed', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'hydrostatic_ratio', 'format', 'DoubleMat', 'mattype', 1) + # }}} Index: /issm/trunk-jpl/src/m/classes/giaivins.py =================================================================== --- /issm/trunk-jpl/src/m/classes/giaivins.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/giaivins.py (revision 24213) @@ -4,60 +4,62 @@ from WriteData import WriteData + class giaivins(object): - """ - GIA class definition + """ + GIA class definition - Usage: - giaivins=giaivins(); - """ + Usage: + giaivins = giaivins() + """ - def __init__(self): # {{{ - self.mantle_viscosity = float('NaN'); - self.lithosphere_thickness = float('NaN'); - self.cross_section_shape = 0; - - #set defaults - self.setdefaultparameters() + def __init__(self): # {{{ + self.mantle_viscosity = float('NaN') + self.lithosphere_thickness = float('NaN') + self.cross_section_shape = 0 - #}}} - def __repr__(self): # {{{ - - string=' giaivins solution parameters:' - - string="%s\n%s"%(string,fielddisplay(self,'mantle_viscosity','mantle viscosity constraints (NaN means no constraint) (Pa s)')) - string="%s\n%s"%(string,fielddisplay(self,'lithosphere_thickness','lithosphere thickness constraints (NaN means no constraint) (m)')) - string="%s\n%s"%(string,fielddisplay(self,'cross_section_shape',"1: square-edged, 2: elliptical-edged surface")) - return string - #}}} - def extrude(self,md): # {{{ - self.mantle_viscosity=project3d(md,'vector',self.mantle_viscosity,'type','node') - self.lithosphere_thickness=project3d(md,'vector',self.lithosphere_thickness,'type','node') - return self - #}}} - def setdefaultparameters(self): # {{{ + #set defaults + self.setdefaultparameters() - self.cross_section_shape=1; + #}}} - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def __repr__(self): # {{{ + string = ' giaivins solution parameters:' - # Early return - if ('GiaAnalysis' not in analyses): - return md - - md = checkfield(md,'fieldname','gia.mantle_viscosity','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices],'>',0) - md = checkfield(md,'fieldname','gia.lithosphere_thickness','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices],'>',0) - md = checkfield(md,'fieldname','gia.cross_section_shape','numel',[1],'values',[1,2]) + string = "%s\n%s" % (string, fielddisplay(self, 'mantle_viscosity', 'mantle viscosity constraints (NaN means no constraint) (Pa s)')) + string = "%s\n%s" % (string, fielddisplay(self, 'lithosphere_thickness', 'lithosphere thickness constraints (NaN means no constraint) (m)')) + string = "%s\n%s" % (string, fielddisplay(self, 'cross_section_shape', "1: square-edged, 2: elliptical - edged surface")) + return string + #}}} - #be sure that if we are running a masstransport ice flow model coupled with giaivins, that thickness forcings - #are not provided into the future. + def extrude(self, md): # {{{ + self.mantle_viscosity = project3d(md, 'vector', self.mantle_viscosity, 'type', 'node') + self.lithosphere_thickness = project3d(md, 'vector', self.lithosphere_thickness, 'type', 'node') + return self + #}}} - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + def setdefaultparameters(self): # {{{ + self.cross_section_shape = 1 + return self + #}}} - WriteData(fid,prefix,'object',self,'fieldname','mantle_viscosity','format','DoubleMat','mattype',1); - WriteData(fid,prefix,'object',self,'fieldname','lithosphere_thickness','format','DoubleMat','mattype',1,'scale',10.**3.); - WriteData(fid,prefix,'object',self,'fieldname','cross_section_shape','format','Integer'); - # }}} + def checkconsistency(self, md, solution, analyses): # {{{ + # Early return + if ('GiaAnalysis' not in analyses): + return md + + md = checkfield(md, 'fieldname', 'gia.mantle_viscosity', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices], '>', 0) + md = checkfield(md, 'fieldname', 'gia.lithosphere_thickness', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices], '>', 0) + md = checkfield(md, 'fieldname', 'gia.cross_section_shape', 'numel', [1], 'values', [1, 2]) + + #be sure that if we are running a masstransport ice flow model coupled with giaivins, that thickness forcings + #are not provided into the future. + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + + WriteData(fid, prefix, 'object', self, 'fieldname', 'mantle_viscosity', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'lithosphere_thickness', 'format', 'DoubleMat', 'mattype', 1, 'scale', 10.**3.) + WriteData(fid, prefix, 'object', self, 'fieldname', 'cross_section_shape', 'format', 'Integer') + # }}} Index: /issm/trunk-jpl/src/m/classes/groundingline.py =================================================================== --- /issm/trunk-jpl/src/m/classes/groundingline.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/groundingline.py (revision 24213) @@ -5,58 +5,63 @@ import MatlabFuncs as m + class groundingline(object): - """ - GROUNDINGLINE class definition + """ + GROUNDINGLINE class definition - Usage: - groundingline=groundingline(); - """ + Usage: + groundingline = groundingline() + """ - def __init__(self): # {{{ - self.migration='' - self.friction_interpolation='' - self.melt_interpolation='' + def __init__(self): # {{{ + self.migration = '' + self.friction_interpolation = '' + self.melt_interpolation = '' - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' grounding line migration parameters:' + #}}} - string="%s\n%s"%(string,fielddisplay(self,'migration','type of grounding line migration: ''SoftMigration'',''SubelementMigration'',''AggressiveMigration'',''Contact'',''None''')) - string="%s\n%s"%(string,fielddisplay(self,'migration','type of friction interpolation on partially floating elements: ''SubelementFriction1'',''SubelementFriction2'',''NoFrictionOnPartiallyFloating''')) - string="%s\n%s"%(string,fielddisplay(self,'migration','type of melt interpolation on partially floating elements: ''SubelementMelt1'',''SubelementMelt2'',''NoMeltOnPartiallyFloating'',''FullMeltOnPartiallyFloating''')) - return string - #}}} - def setdefaultparameters(self): # {{{ + def __repr__(self): # {{{ + string = ' grounding line migration parameters:' - #Type of migration - self.migration='SubelementMigration' - self.friction_interpolation='SubelementFriction1' - self.melt_interpolation='NoMeltOnPartiallyFloating' + string = "%s\n%s" % (string, fielddisplay(self, 'migration', 'type of grounding line migration: ''SoftMigration'', ''SubelementMigration'', ''AggressiveMigration'', ''Contact'', ''None''')) + string = "%s\n%s" % (string, fielddisplay(self, 'migration', 'type of friction interpolation on partially floating elements: ''SubelementFriction1'', ''SubelementFriction2'', ''NoFrictionOnPartiallyFloating''')) + string = "%s\n%s" % (string, fielddisplay(self, 'migration', 'type of melt interpolation on partially floating elements: ''SubelementMelt1'', ''SubelementMelt2'', ''NoMeltOnPartiallyFloating'', ''FullMeltOnPartiallyFloating''')) + return string + #}}} - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def setdefaultparameters(self): # {{{ - md = checkfield(md,'fieldname','groundingline.migration','values',['None','SubelementMigration','AggressiveMigration','SoftMigration','Contact','GroundingOnly']) - md = checkfield(md,'fieldname','groundingline.friction_interpolation','values',['SubelementFriction1','SubelementFriction2','NoFrictionOnPartiallyFloating']) - md = checkfield(md,'fieldname','groundingline.melt_interpolation','values',['SubelementMelt1','SubelementMelt2','NoMeltOnPartiallyFloating','FullMeltOnPartiallyFloating']) + #Type of migration + self.migration = 'SubelementMigration' + self.friction_interpolation = 'SubelementFriction1' + self.melt_interpolation = 'NoMeltOnPartiallyFloating' - if(not m.strcmp(self.migration,'None') and md.transient.isgroundingline and solution=='TransientSolution'): - if np.any(np.isnan(md.geometry.bed)): - md.checkmessage("requesting grounding line migration, but bathymetry is absent!") - pos=np.nonzero(md.mask.groundedice_levelset>0.)[0] - if any(np.abs(md.geometry.base[pos]-md.geometry.bed[pos])>10**-10): - md.checkmessage("base not equal to bed on grounded ice!") - if any(md.geometry.bed - md.geometry.base > 10**-9): - md.checkmessage("bed superior to base on floating ice!") + return self + #}}} - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'data',self.migration,'name','md.groundingline.migration','format','String') - WriteData(fid,prefix,'data',self.friction_interpolation,'name','md.groundingline.friction_interpolation','format','String') - WriteData(fid,prefix,'data',self.melt_interpolation,'name','md.groundingline.melt_interpolation','format','String') - # }}} + def checkconsistency(self, md, solution, analyses): # {{{ + + md = checkfield(md, 'fieldname', 'groundingline.migration', 'values', ['None', 'SubelementMigration', 'AggressiveMigration', 'SoftMigration', 'Contact', 'GroundingOnly']) + md = checkfield(md, 'fieldname', 'groundingline.friction_interpolation', 'values', ['SubelementFriction1', 'SubelementFriction2', 'NoFrictionOnPartiallyFloating']) + md = checkfield(md, 'fieldname', 'groundingline.melt_interpolation', 'values', ['SubelementMelt1', 'SubelementMelt2', 'NoMeltOnPartiallyFloating', 'FullMeltOnPartiallyFloating']) + + if(not m.strcmp(self.migration, 'None') and md.transient.isgroundingline and solution == 'TransientSolution'): + if np.any(np.isnan(md.geometry.bed)): + md.checkmessage("requesting grounding line migration, but bathymetry is absent!") + pos = np.nonzero(md.mask.groundedice_levelset > 0.)[0] + if any(np.abs(md.geometry.base[pos] - md.geometry.bed[pos]) > 10**- 10): + md.checkmessage("base not equal to bed on grounded ice!") + if any(md.geometry.bed - md.geometry.base > 10**- 9): + md.checkmessage("bed superior to base on floating ice!") + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'data', self.migration, 'name', 'md.groundingline.migration', 'format', 'String') + WriteData(fid, prefix, 'data', self.friction_interpolation, 'name', 'md.groundingline.friction_interpolation', 'format', 'String') + WriteData(fid, prefix, 'data', self.melt_interpolation, 'name', 'md.groundingline.melt_interpolation', 'format', 'String') + # }}} Index: /issm/trunk-jpl/src/m/classes/hydrologydc.py =================================================================== --- /issm/trunk-jpl/src/m/classes/hydrologydc.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/hydrologydc.py (revision 24213) @@ -11,5 +11,5 @@ Usage: - hydrologydc=hydrologydc(); + hydrologydc = hydrologydc() """ @@ -48,5 +48,5 @@ self.eplflip_lock = 0 - #set defaults + #set defaults self.setdefaultparameters() #}}} @@ -54,13 +54,13 @@ def __repr__(self): # {{{ string = ' hydrology Dual Porous Continuum Equivalent parameters:' - string = ' - general parameters' - string = "%s\n%s" % (string, fielddisplay(self, 'water_compressibility', 'compressibility of water [Pa^-1]')) + string = ' - general parameters' + string = "%s\n%s" % (string, fielddisplay(self, 'water_compressibility', 'compressibility of water [Pa^ - 1]')) string = "%s\n%s" % (string, fielddisplay(self, 'isefficientlayer', 'do we use an efficient drainage system [1: true 0: false]')) string = "%s\n%s" % (string, fielddisplay(self, 'penalty_factor', 'exponent of the value used in the penalisation method [dimensionless]')) - string = "%s\n%s" % (string, fielddisplay(self, 'penalty_lock', 'stabilize unstable constraints that keep zigzagging after n iteration (default is 0, no stabilization)')) + string = "%s\n%s" % (string, fielddisplay(self, 'penalty_lock', 'stabilize unstable constraints that keep zigzagging after n iteration (default is 0, no stabilization)')) string = "%s\n%s" % (string, fielddisplay(self, 'rel_tol', 'tolerance of the nonlinear iteration for the transfer between layers [dimensionless]')) string = "%s\n%s" % (string, fielddisplay(self, 'max_iter', 'maximum number of nonlinear iteration')) string = "%s\n%s" % (string, fielddisplay(self, 'steps_per_step', 'number of hydrology steps per time step')) - string = "%s\n%s" % (string, fielddisplay(self, 'basal_moulin_input', 'water flux at a given point [m3 s-1]')) + string = "%s\n%s" % (string, fielddisplay(self, 'basal_moulin_input', 'water flux at a given point [m3 s - 1]')) string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) string = "%s\n%s" % (string, fielddisplay(self, 'sedimentlimit_flag', 'what kind of upper limit is applied for the inefficient layer')) @@ -82,19 +82,19 @@ string = "%s\n%s" % (string, fielddisplay(self, 'unconfined_flag', 'using an unconfined scheme or not (transitory)')) string = "%s\n\t\t%s" % (string, '0: Confined only') - string = "%s\n\t\t%s" % (string, '1: Confined-Unconfined') - - string = "%s\n%s" % (string, ' - for the sediment layer') + string = "%s\n\t\t%s" % (string, '1: Confined - Unconfined') + + string = "%s\n%s" % (string, ' - for the sediment layer') string = "%s\n%s" % (string, fielddisplay(self, 'spcsediment_head', 'sediment water head constraints (NaN means no constraint) [m above MSL]')) - string = "%s\n%s" % (string, fielddisplay(self, 'sediment_compressibility', 'sediment compressibility [Pa^-1]')) + string = "%s\n%s" % (string, fielddisplay(self, 'sediment_compressibility', 'sediment compressibility [Pa^ - 1]')) string = "%s\n%s" % (string, fielddisplay(self, 'sediment_porosity', 'sediment [dimensionless]')) string = "%s\n%s" % (string, fielddisplay(self, 'sediment_thickness', 'sediment thickness [m]')) - string = "%s\n%s" % (string, fielddisplay(self, 'sediment_transmitivity', 'sediment transmitivity [m^2/s]')) + string = "%s\n%s" % (string, fielddisplay(self, 'sediment_transmitivity', 'sediment transmitivity [m^2 / s]')) string = "%s\n%s" % (string, fielddisplay(self, 'mask_thawed_node', 'IDS is deactivaed (0) on frozen nodes')) if self.isefficientlayer == 1: - string = "%s\n%s" % (string, ' - for the epl layer') + string = "%s\n%s" % (string, ' - for the epl layer') string = "%s\n%s" % (string, fielddisplay(self, 'spcepl_head', 'epl water head constraints (NaN means no constraint) [m above MSL]')) string = "%s\n%s" % (string, fielddisplay(self, 'mask_eplactive_node', 'active (1) or not (0) EPL')) - string = "%s\n%s" % (string, fielddisplay(self, 'epl_compressibility', 'epl compressibility [Pa^-1]')) + string = "%s\n%s" % (string, fielddisplay(self, 'epl_compressibility', 'epl compressibility [Pa^ - 1]')) string = "%s\n%s" % (string, fielddisplay(self, 'epl_porosity', 'epl [dimensionless]')) string = "%s\n%s" % (string, fielddisplay(self, 'epl_max_thickness', 'epl maximal thickness [m]')) @@ -102,6 +102,6 @@ string = "%s\n%s" % (string, fielddisplay(self, 'epl_colapse_thickness', 'epl colapsing thickness [m]')) string = "%s\n%s" % (string, fielddisplay(self, 'epl_thick_comp', 'epl thickness computation flag')) - string = "%s\n%s" % (string, fielddisplay(self, 'epl_conductivity', 'epl conductivity [m^2/s]')) - string = "%s\n%s" % (string, fielddisplay(self, 'eplflip_lock', 'lock epl activity to avoid flip-floping (default is 0, no stabilization)')) + string = "%s\n%s" % (string, fielddisplay(self, 'epl_conductivity', 'epl conductivity [m^2 / s]')) + string = "%s\n%s" % (string, fielddisplay(self, 'eplflip_lock', 'lock epl activity to avoid flip - floping (default is 0, no stabilization)')) return string @@ -132,5 +132,4 @@ self.leakage_factor = 10.0 self.requested_outputs = ['default'] - self.sediment_compressibility = 1.0e-08 self.sediment_porosity = 0.4 @@ -171,5 +170,4 @@ def checkconsistency(self, md, solution, analyses): #{{{ - #Early return if 'HydrologyDCInefficientAnalysis' not in analyses and 'HydrologyDCEfficientAnalysis' not in analyses: @@ -254,5 +252,5 @@ WriteData(fid, prefix, 'object', self, 'fieldname', 'eplflip_lock', 'format', 'Integer') - #process requested outputs + #process requested outputs outputs = self.requested_outputs indices = [i for i, x in enumerate(outputs) if x == 'default'] Index: /issm/trunk-jpl/src/m/classes/hydrologyshakti.py =================================================================== --- /issm/trunk-jpl/src/m/classes/hydrologyshakti.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/hydrologyshakti.py (revision 24213) @@ -3,105 +3,106 @@ from WriteData import WriteData + class hydrologyshakti(object): - """ - HYDROLOGYSHAKTI class definition + """ + HYDROLOGYSHAKTI class definition - Usage: - hydrologyshakti=hydrologyshakti() - """ + Usage: + hydrologyshakti = hydrologyshakti() + """ - def __init__(self): # {{{ - self.head = float('NaN') - self.gap_height = float('NaN') - self.bump_spacing = float('NaN') - self.bump_height = float('NaN') - self.englacial_input = float('NaN') - self.moulin_input = float('NaN') - self.reynolds = float('NaN') - self.spchead = float('NaN') - self.neumannflux = float('NaN') - self.relaxation = 0 - self.storage = 0 - self.requested_outputs = [] + def __init__(self): # {{{ + self.head = float('NaN') + self.gap_height = float('NaN') + self.bump_spacing = float('NaN') + self.bump_height = float('NaN') + self.englacial_input = float('NaN') + self.moulin_input = float('NaN') + self.reynolds = float('NaN') + self.spchead = float('NaN') + self.neumannflux = float('NaN') + self.relaxation = 0 + self.storage = 0 + self.requested_outputs = [] - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' hydrologyshakti solution parameters:' - string="%s\n%s"%(string,fielddisplay(self,'head','subglacial hydrology water head (m)')) - string="%s\n%s"%(string,fielddisplay(self,'gap_height','height of gap separating ice to bed (m)')) - string="%s\n%s"%(string,fielddisplay(self,'bump_spacing','characteristic bedrock bump spacing (m)')) - string="%s\n%s"%(string,fielddisplay(self,'bump_height','characteristic bedrock bump height (m)')) - string="%s\n%s"%(string,fielddisplay(self,'englacial_input','liquid water input from englacial to subglacial system (m/yr)')) - string="%s\n%s"%(string,fielddisplay(self,'moulin_input','liquid water input from moulins (at the vertices) to subglacial system (m^3/s)')) - string="%s\n%s"%(string,fielddisplay(self,'reynolds','Reynolds'' number')) - string="%s\n%s"%(string,fielddisplay(self,'neumannflux','water flux applied along the model boundary (m^2/s)')) - string="%s\n%s"%(string,fielddisplay(self,'spchead','water head constraints (NaN means no constraint) (m)')) - string="%s\n%s"%(string,fielddisplay(self,'relaxation','under-relaxation coefficient for nonlinear iteration')) - string="%s\n%s"%(string,fielddisplay(self,'storage','englacial storage coefficient (void ratio)')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) - return string - #}}} + #}}} + def __repr__(self): # {{{ + string = ' hydrologyshakti solution parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'head', 'subglacial hydrology water head (m)')) + string = "%s\n%s" % (string, fielddisplay(self, 'gap_height', 'height of gap separating ice to bed (m)')) + string = "%s\n%s" % (string, fielddisplay(self, 'bump_spacing', 'characteristic bedrock bump spacing (m)')) + string = "%s\n%s" % (string, fielddisplay(self, 'bump_height', 'characteristic bedrock bump height (m)')) + string = "%s\n%s" % (string, fielddisplay(self, 'englacial_input', 'liquid water input from englacial to subglacial system (m / yr)')) + string = "%s\n%s" % (string, fielddisplay(self, 'moulin_input', 'liquid water input from moulins (at the vertices) to subglacial system (m^3 / s)')) + string = "%s\n%s" % (string, fielddisplay(self, 'reynolds', 'Reynolds'' number')) + string = "%s\n%s" % (string, fielddisplay(self, 'neumannflux', 'water flux applied along the model boundary (m^2 / s)')) + string = "%s\n%s" % (string, fielddisplay(self, 'spchead', 'water head constraints (NaN means no constraint) (m)')) + string = "%s\n%s" % (string, fielddisplay(self, 'relaxation', 'under - relaxation coefficient for nonlinear iteration')) + string = "%s\n%s" % (string, fielddisplay(self, 'storage', 'englacial storage coefficient (void ratio)')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) + return string + #}}} - def extrude(self,md): # {{{ - return self - #}}} + def extrude(self, md): # {{{ + return self + #}}} - def setdefaultparameters(self): # {{{ - # Set under-relaxation parameter to be 1 (no under-relaxation of nonlinear iteration) - self.relaxation=1 - self.storage=0 - self.requested_outputs=['default'] - return self - #}}} + def setdefaultparameters(self): # {{{ + # Set under - relaxation parameter to be 1 (no under - relaxation of nonlinear iteration) + self.relaxation = 1 + self.storage = 0 + self.requested_outputs = ['default'] + return self + #}}} - def defaultoutputs(self,md): # {{{ - list = ['HydrologyHead','HydrologyGapHeight','EffectivePressure','HydrologyBasalFlux','DegreeOfChannelization'] - return list - #}}} + def defaultoutputs(self, md): # {{{ + list = ['HydrologyHead', 'HydrologyGapHeight', 'EffectivePressure', 'HydrologyBasalFlux', 'DegreeOfChannelization'] + return list + #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - #Early return - if 'HydrologyShaktiAnalysis' not in analyses: - return md + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if 'HydrologyShaktiAnalysis' not in analyses: + return md - md = checkfield(md,'fieldname','hydrology.head','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','hydrology.gap_height','>=',0,'size',[md.mesh.numberofelements],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','hydrology.bump_spacing','>',0,'size',[md.mesh.numberofelements],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','hydrology.bump_height','>=',0,'size',[md.mesh.numberofelements],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','hydrology.englacial_input','>=',0,'NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','hydrology.moulin_input','>=',0,'NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','hydrology.reynolds','>',0,'size',[md.mesh.numberofelements],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','hydrology.neumannflux','timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','hydrology.spchead','size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','hydrology.relaxation','>=',0) - md = checkfield(md,'fieldname','hydrology.storage','>=',0) - md = checkfield(md,'fieldname','hydrology.requested_outputs','stringrow',1) - return md - # }}} + md = checkfield(md, 'fieldname', 'hydrology.head', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'hydrology.gap_height', '>=', 0, 'size', [md.mesh.numberofelements], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'hydrology.bump_spacing', '>', 0, 'size', [md.mesh.numberofelements], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'hydrology.bump_height', '>=', 0, 'size', [md.mesh.numberofelements], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'hydrology.englacial_input', '>=', 0, 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'hydrology.moulin_input', '>=', 0, 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'hydrology.reynolds', '>', 0, 'size', [md.mesh.numberofelements], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'hydrology.neumannflux', 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'hydrology.spchead', 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'hydrology.relaxation', '>=', 0) + md = checkfield(md, 'fieldname', 'hydrology.storage', '>=', 0) + md = checkfield(md, 'fieldname', 'hydrology.requested_outputs', 'stringrow', 1) + return md + # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts - WriteData(fid,prefix,'name','md.hydrology.model','data',3,'format','Integer') - WriteData(fid,prefix,'object',self,'class','hydrology','fieldname','head','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','hydrology','fieldname','gap_height','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'class','hydrology','fieldname','bump_spacing','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'class','hydrology','fieldname','bump_height','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'class','hydrology','fieldname','englacial_input','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','hydrology','fieldname','moulin_input','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','hydrology','fieldname','reynolds','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'class','hydrology','fieldname','neumannflux','format','DoubleMat','mattype',2,'timeserieslength',md.mesh.numberofelements+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','hydrology','fieldname','spchead','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','hydrology','fieldname','relaxation','format','Double') - WriteData(fid,prefix,'object',self,'class','hydrology','fieldname','storage','format','Double') - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.hydrology.requested_outputs','format','StringArray') - # }}} + WriteData(fid, prefix, 'name', 'md.hydrology.model', 'data', 3, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'hydrology', 'fieldname', 'head', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'hydrology', 'fieldname', 'gap_height', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'hydrology', 'fieldname', 'bump_spacing', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'hydrology', 'fieldname', 'bump_height', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'hydrology', 'fieldname', 'englacial_input', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'hydrology', 'fieldname', 'moulin_input', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'hydrology', 'fieldname', 'reynolds', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'hydrology', 'fieldname', 'neumannflux', 'format', 'DoubleMat', 'mattype', 2, 'timeserieslength', md.mesh.numberofelements + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'hydrology', 'fieldname', 'spchead', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'hydrology', 'fieldname', 'relaxation', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'hydrology', 'fieldname', 'storage', 'format', 'Double') + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.hydrology.requested_outputs', 'format', 'StringArray') + # }}} Index: /issm/trunk-jpl/src/m/classes/hydrologyshreve.py =================================================================== --- /issm/trunk-jpl/src/m/classes/hydrologyshreve.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/hydrologyshreve.py (revision 24213) @@ -3,65 +3,69 @@ from WriteData import WriteData + class hydrologyshreve(object): - """ - HYDROLOGYSHREVE class definition + """ + HYDROLOGYSHREVE class definition - Usage: - hydrologyshreve=hydrologyshreve(); - """ + Usage: + hydrologyshreve = hydrologyshreve() + """ - def __init__(self): # {{{ - self.spcwatercolumn = float('NaN') - self.stabilization = 0 - self.requested_outputs = [] - #set defaults - self.setdefaultparameters() + def __init__(self): # {{{ + self.spcwatercolumn = float('NaN') + self.stabilization = 0 + self.requested_outputs = [] + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - - string=' hydrologyshreve solution parameters:' - string="%s\n%s"%(string,fielddisplay(self,'spcwatercolumn','water thickness constraints (NaN means no constraint) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'stabilization','artificial diffusivity (default is 1). can be more than 1 to increase diffusivity.')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) - return string - #}}} - def extrude(self,md): # {{{ - return self - #}}} - def setdefaultparameters(self): # {{{ - - #Type of stabilization to use 0:nothing 1:artificial_diffusivity - self.stabilization=1 - self.requested_outputs= ['default'] - return self - #}}} - def defaultoutputs(self,md): # {{{ - list = ['Watercolumn','HydrologyWaterVx','HydrologyWaterVy'] - return list - #}}} + #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - - #Early return - if 'HydrologyShreveAnalysis' not in analyses: - return md + def __repr__(self): # {{{ - md = checkfield(md,'fieldname','hydrology.spcwatercolumn','Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','hydrology.stabilization','>=',0) - md = checkfield(md,'fieldname','hydrology.requested_outputs','stringrow',1) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.hydrology.model','data',2,'format','Integer'); - WriteData(fid,prefix,'object',self,'fieldname','spcwatercolumn','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','stabilization','format','Double') - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.hydrology.requested_outputs','format','StringArray') + string = ' hydrologyshreve solution parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'spcwatercolumn', 'water thickness constraints (NaN means no constraint) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'stabilization', 'artificial diffusivity (default is 1). can be more than 1 to increase diffusivity.')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) + return string + #}}} - # }}} + def extrude(self, md): # {{{ + return self + #}}} + + def setdefaultparameters(self): # {{{ + #Type of stabilization to use 0:nothing 1:artificial_diffusivity + self.stabilization = 1 + self.requested_outputs = ['default'] + return self + #}}} + + def defaultoutputs(self, md): # {{{ + list = ['Watercolumn', 'HydrologyWaterVx', 'HydrologyWaterVy'] + return list + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if 'HydrologyShreveAnalysis' not in analyses: + return md + + md = checkfield(md, 'fieldname', 'hydrology.spcwatercolumn', 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'hydrology.stabilization', '>=', 0) + md = checkfield(md, 'fieldname', 'hydrology.requested_outputs', 'stringrow', 1) + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.hydrology.model', 'data', 2, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'spcwatercolumn', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'stabilization', 'format', 'Double') + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.hydrology.requested_outputs', 'format', 'StringArray') + + # }}} Index: /issm/trunk-jpl/src/m/classes/independent.py =================================================================== --- /issm/trunk-jpl/src/m/classes/independent.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/independent.py (revision 24213) @@ -5,66 +5,71 @@ from MatlabFuncs import * + class independent(object): - """ - INDEPENDENT class definition + """ + INDEPENDENT class definition - Usage: - independent=independent(); - """ + Usage: + independent = independent() + """ - def __init__(self,*args): # {{{ - self.name = '' - self.type = '' - self.fos_forward_index = float('NaN') - self.fov_forward_indices = np.array([]) - self.nods = 0 + def __init__(self, *args): # {{{ + self.name = '' + self.type = '' + self.fos_forward_index = float('NaN') + self.fov_forward_indices = np.array([]) + self.nods = 0 - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #use provided options to change fields - options=pairoptions(*args) + #use provided options to change fields + options = pairoptions(*args) - #OK get other fields - self=options.AssignObjectFields(self) - # }}} - def __repr__(self): # {{{ - s =" independent variable:\n" + #OK get other fields + self = options.AssignObjectFields(self) + # }}} - s+="%s\n" % fielddisplay(self,'name',"variable name (must match corresponding String)") - s+="%s\n" % fielddisplay(self,'type',"type of variable ('vertex' or 'scalar')") - if not np.isnan(self.fos_forward_index): - s+="%s\n" % fielddisplay(self,'fos_forward_index',"index for fos_foward driver of ADOLC") - if np.any(np.logical_not(np.isnan(self.fov_forward_indices))): - s+="%s\n" % fielddisplay(self,'fov_forward_indices',"indices for fov_foward driver of ADOLC") + def __repr__(self): # {{{ + s = " independent variable:\n" - return s - # }}} - def setdefaultparameters(self): # {{{ - #do nothing - return self - # }}} - def checkconsistency(self,md,i,solution,analyses,driver): # {{{ - if not np.isnan(self.fos_forward_index): - if not strcmpi(driver,'fos_forward'): - raise TypeError("cannot declare an independent with a fos_forward_index when the driver is not fos_forward!") - if self.nods==0: - raise TypeError("independent checkconsistency error: nods should be set to the size of the independent variable") + s += "%s\n" % fielddisplay(self, 'name', "variable name (must match corresponding String)") + s += "%s\n" % fielddisplay(self, 'type', "type of variable ('vertex' or 'scalar')") + if not np.isnan(self.fos_forward_index): + s += "%s\n" % fielddisplay(self, 'fos_forward_index', "index for fos_foward driver of ADOLC") + if np.any(np.logical_not(np.isnan(self.fov_forward_indices))): + s += "%s\n" % fielddisplay(self, 'fov_forward_indices', "indices for fov_foward driver of ADOLC") - if len(self.fov_forward_indices) > 0: - if not strcmpi(driver,'fov_forward'): - raise TypeError("cannot declare an independent with fov_forward_indices when the driver is not fov_forward!") - if self.nods==0: - raise TypeError("independent checkconsistency error: nods should be set to the size of the independent variable") - md = checkfield(md,'fieldname',"autodiff.independents[%d].fov_forward_indices" % i,'>=',1,'<=',self.nods) + return s + # }}} - return md - # }}} - def typetoscalar(self): # {{{ - if strcmpi(self.type,'scalar'): - scalar=0 - elif strcmpi(self.type,'vertex'): - scalar=1 + def setdefaultparameters(self): # {{{ + #do nothing + return self + # }}} - return scalar - # }}} + def checkconsistency(self, md, i, solution, analyses, driver): # {{{ + if not np.isnan(self.fos_forward_index): + if not strcmpi(driver, 'fos_forward'): + raise TypeError("cannot declare an independent with a fos_forward_index when the driver is not fos_forward!") + if self.nods == 0: + raise TypeError("independent checkconsistency error: nods should be set to the size of the independent variable") + + if len(self.fov_forward_indices) > 0: + if not strcmpi(driver, 'fov_forward'): + raise TypeError("cannot declare an independent with fov_forward_indices when the driver is not fov_forward!") + if self.nods == 0: + raise TypeError("independent checkconsistency error: nods should be set to the size of the independent variable") + md = checkfield(md, 'fieldname', "autodiff.independents[%d].fov_forward_indices" % i, '>=', 1, '<=', self.nods) + + return md + # }}} + + def typetoscalar(self): # {{{ + if strcmpi(self.type, 'scalar'): + scalar = 0 + elif strcmpi(self.type, 'vertex'): + scalar = 1 + + return scalar + # }}} Index: /issm/trunk-jpl/src/m/classes/initialization.py =================================================================== --- /issm/trunk-jpl/src/m/classes/initialization.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/initialization.py (revision 24213) @@ -4,143 +4,147 @@ from checkfield import checkfield from WriteData import WriteData -import MatlabFuncs as m + class initialization(object): """ INITIALIZATION class definition - + Usage: - initialization=initialization(); + initialization = initialization() """ - def __init__(self): # {{{ - - self.vx = float('NaN') - self.vy = float('NaN') - self.vz = float('NaN') - self.vel = float('NaN') - self.enthalpy = float('NaN') - self.pressure = float('NaN') - self.temperature = float('NaN') + def __init__(self): # {{{ + + self.vx = float('NaN') + self.vy = float('NaN') + self.vz = float('NaN') + self.vel = float('NaN') + self.enthalpy = float('NaN') + self.pressure = float('NaN') + self.temperature = float('NaN') self.waterfraction = float('NaN') - self.watercolumn = float('NaN') + self.watercolumn = float('NaN') self.sediment_head = float('NaN') - self.epl_head = float('NaN') + self.epl_head = float('NaN') self.epl_thickness = float('NaN') - #set defaults + #set defaults self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' initial field values:' - string="%s\n%s"%(string,fielddisplay(self,'vx','x component of velocity [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'vy','y component of velocity [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'vz','z component of velocity [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'vel','velocity norm [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'pressure','pressure [Pa]')) - string="%s\n%s"%(string,fielddisplay(self,'temperature','temperature [K]')) - string="%s\n%s"%(string,fielddisplay(self,'enthalpy','enthalpy [J]')) - string="%s\n%s"%(string,fielddisplay(self,'waterfraction','fraction of water in the ice')) - string="%s\n%s"%(string,fielddisplay(self,'watercolumn','thickness of subglacial water [m]')) - string="%s\n%s"%(string,fielddisplay(self,'sediment_head','sediment water head of subglacial system [m]')) - string="%s\n%s"%(string,fielddisplay(self,'epl_head','epl water head of subglacial system [m]')) - string="%s\n%s"%(string,fielddisplay(self,'epl_thickness','thickness of the epl [m]')) + #}}} + + def __repr__(self): # {{{ + string = ' initial field values:' + string = "%s\n%s" % (string, fielddisplay(self, 'vx', 'x component of velocity [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'vy', 'y component of velocity [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'vz', 'z component of velocity [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'vel', 'velocity norm [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'pressure', 'pressure [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'temperature', 'temperature [K]')) + string = "%s\n%s" % (string, fielddisplay(self, 'enthalpy', 'enthalpy [J]')) + string = "%s\n%s" % (string, fielddisplay(self, 'waterfraction', 'fraction of water in the ice')) + string = "%s\n%s" % (string, fielddisplay(self, 'watercolumn', 'thickness of subglacial water [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'sediment_head', 'sediment water head of subglacial system [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'epl_head', 'epl water head of subglacial system [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'epl_thickness', 'thickness of the epl [m]')) return string - #}}} - def extrude(self,md): # {{{ - self.vx=project3d(md,'vector',self.vx,'type','node') - self.vy=project3d(md,'vector',self.vy,'type','node') - self.vz=project3d(md,'vector',self.vz,'type','node') - self.vel=project3d(md,'vector',self.vel,'type','node') - self.temperature=project3d(md,'vector',self.temperature,'type','node') - self.enthalpy=project3d(md,'vector',self.enthalpy,'type','node') - self.waterfraction=project3d(md,'vector',self.waterfraction,'type','node') - self.watercolumn=project3d(md,'vector',self.watercolumn,'type','node') - self.sediment_head=project3d(md,'vector',self.sediment_head,'type','node','layer',1) - self.epl_head=project3d(md,'vector',self.epl_head,'type','node','layer',1) - self.epl_thickness=project3d(md,'vector',self.epl_thickness,'type','node','layer',1) + #}}} + + def extrude(self, md): # {{{ + self.vx = project3d(md, 'vector', self.vx, 'type', 'node') + self.vy = project3d(md, 'vector', self.vy, 'type', 'node') + self.vz = project3d(md, 'vector', self.vz, 'type', 'node') + self.vel = project3d(md, 'vector', self.vel, 'type', 'node') + self.temperature = project3d(md, 'vector', self.temperature, 'type', 'node') + self.enthalpy = project3d(md, 'vector', self.enthalpy, 'type', 'node') + self.waterfraction = project3d(md, 'vector', self.waterfraction, 'type', 'node') + self.watercolumn = project3d(md, 'vector', self.watercolumn, 'type', 'node') + self.sediment_head = project3d(md, 'vector', self.sediment_head, 'type', 'node', 'layer', 1) + self.epl_head = project3d(md, 'vector', self.epl_head, 'type', 'node', 'layer', 1) + self.epl_thickness = project3d(md, 'vector', self.epl_thickness, 'type', 'node', 'layer', 1) #Lithostatic pressure by default - # self.pressure=md.constants.g*md.materials.rho_ice*(md.geometry.surface[:,0]-md.mesh.z) - #self.pressure=md.constants.g*md.materials.rho_ice*(md.geometry.surface-md.mesh.z.reshape(-1,)) + # self.pressure = md.constants.g * md.materials.rho_ice * (md.geometry.surface[:, 0] - md.mesh.z) + #self.pressure = md.constants.g * md.materials.rho_ice * (md.geometry.surface-md.mesh.z.reshape(- 1, )) - if np.ndim(md.geometry.surface)==2: + if np.ndim(md.geometry.surface) == 2: print('Reshaping md.geometry.surface for you convenience but you should fix it in you files') - self.pressure=md.constants.g*md.materials.rho_ice*(md.geometry.surface.reshape(-1,)-md.mesh.z) + self.pressure = md.constants.g * md.materials.rho_ice * (md.geometry.surface.reshape(- 1, ) - md.mesh.z) else: - self.pressure=md.constants.g*md.materials.rho_ice*(md.geometry.surface-md.mesh.z) + self.pressure = md.constants.g * md.materials.rho_ice * (md.geometry.surface - md.mesh.z) return self #}}} - def setdefaultparameters(self): # {{{ + + def setdefaultparameters(self): # {{{ return self #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + + def checkconsistency(self, md, solution, analyses): # {{{ if 'StressbalanceAnalysis' in analyses: - if not np.any(np.logical_or(np.isnan(md.initialization.vx),np.isnan(md.initialization.vy))): - md = checkfield(md,'fieldname','initialization.vx','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','initialization.vy','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) + if not np.any(np.logical_or(np.isnan(md.initialization.vx), np.isnan(md.initialization.vy))): + md = checkfield(md, 'fieldname', 'initialization.vx', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'initialization.vy', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) if 'MasstransportAnalysis' in analyses: - md = checkfield(md,'fieldname','initialization.vx','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','initialization.vy','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'initialization.vx', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'initialization.vy', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','initialization.vx','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','initialization.vy','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'initialization.vx', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'initialization.vy', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) #Triangle with zero velocity - if np.any(np.logical_and(np.sum(np.abs(md.initialization.vx[md.mesh.elements-1]),axis=1)==0,\ - np.sum(np.abs(md.initialization.vy[md.mesh.elements-1]),axis=1)==0)): + if np.any(np.logical_and(np.sum(np.abs(md.initialization.vx[md.mesh.elements - 1]), axis=1) == 0, + np.sum(np.abs(md.initialization.vy[md.mesh.elements - 1]), axis=1) == 0)): md.checkmessage("at least one triangle has all its vertices with a zero velocity") if 'ThermalAnalysis' in analyses: - md = checkfield(md,'fieldname','initialization.vx','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','initialization.vy','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','initialization.temperature','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - if md.mesh.dimension()==3: - md = checkfield(md,'fieldname','initialization.vz','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','initialization.pressure','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'initialization.vx', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'initialization.vy', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'initialization.temperature', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + if md.mesh.dimension() == 3: + md = checkfield(md, 'fieldname', 'initialization.vz', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'initialization.pressure', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) if ('EnthalpyAnalysis' in analyses and md.thermal.isenthalpy): - md = checkfield(md,'fieldname','initialization.waterfraction','>=',0,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','initialization.watercolumn' ,'>=',0,'size',[md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'initialization.waterfraction', '>=', 0, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'initialization.watercolumn', '>=', 0, 'size', [md.mesh.numberofvertices]) pos = np.nonzero(md.initialization.waterfraction > 0.)[0] if(pos.size): - md = checkfield(md,'fieldname', 'delta Tpmp', 'field', np.absolute(md.initialization.temperature[pos]-(md.materials.meltingpoint-md.materials.beta*md.initialization.pressure[pos])),'<',1e-11, 'message','set temperature to pressure melting point at locations with waterfraction>0'); + md = checkfield(md, 'fieldname', 'delta Tpmp', 'field', np.absolute(md.initialization.temperature[pos] - (md.materials.meltingpoint - md.materials.beta * md.initialization.pressure[pos])), '<', 1e-11, 'message', 'set temperature to pressure melting point at locations with waterfraction > 0') if 'HydrologyShreveAnalysis' in analyses: - if hasattr(md.hydrology,'hydrologyshreve'): - md = checkfield(md,'fieldname','initialization.watercolumn','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) + if hasattr(md.hydrology, 'hydrologyshreve'): + md = checkfield(md, 'fieldname', 'initialization.watercolumn', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) if 'HydrologyDCInefficientAnalysis' in analyses: - if hasattr(md.hydrology,'hydrologydc'): - md = checkfield(md,'fieldname','initialization.sediment_head','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) + if hasattr(md.hydrology, 'hydrologydc'): + md = checkfield(md, 'fieldname', 'initialization.sediment_head', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) if 'HydrologyDCEfficientAnalysis' in analyses: - if hasattr(md.hydrology,'hydrologydc'): - if md.hydrology.isefficientlayer==1: - md = checkfield(md,'fieldname','initialization.epl_head','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','initialization.epl_thickness','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) + if hasattr(md.hydrology, 'hydrologydc'): + if md.hydrology.isefficientlayer == 1: + md = checkfield(md, 'fieldname', 'initialization.epl_head', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'initialization.epl_thickness', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) return md # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts + def marshall(self, prefix, md, fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','vx','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'fieldname','vy','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'fieldname','vz','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'fieldname','pressure','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','temperature','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','waterfraction','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','sediment_head','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','epl_head','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','epl_thickness','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','watercolumn','format','DoubleMat','mattype',1) - + yts = md.constants.yts + + WriteData(fid, prefix, 'object', self, 'fieldname', 'vx', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'vy', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'vz', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'pressure', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'temperature', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'waterfraction', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'sediment_head', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'epl_head', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'epl_thickness', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'watercolumn', 'format', 'DoubleMat', 'mattype', 1) + if md.thermal.isenthalpy: - if (np.size(self.enthalpy)<=1): - tpmp = md.materials.meltingpoint - md.materials.beta*md.initialization.pressure; - pos = np.nonzero(md.initialization.waterfraction > 0.)[0] - self.enthalpy = md.materials.heatcapacity*(md.initialization.temperature-md.constants.referencetemperature); - self.enthalpy[pos] = md.materials.heatcapacity*(tpmp[pos].reshape(-1,) - md.constants.referencetemperature) + md.materials.latentheat*md.initialization.waterfraction[pos].reshape(-1,) + if (np.size(self.enthalpy) <= 1): + tpmp = md.materials.meltingpoint - md.materials.beta * md.initialization.pressure + pos = np.nonzero(md.initialization.waterfraction > 0.)[0] + self.enthalpy = md.materials.heatcapacity * (md.initialization.temperature - md.constants.referencetemperature) + self.enthalpy[pos] = md.materials.heatcapacity * (tpmp[pos].reshape(- 1, ) - md.constants.referencetemperature) + md.materials.latentheat * md.initialization.waterfraction[pos].reshape(- 1, ) - WriteData(fid,prefix,'data',self.enthalpy,'format','DoubleMat','mattype',1,'name','md.initialization.enthalpy'); - + WriteData(fid, prefix, 'data', self.enthalpy, 'format', 'DoubleMat', 'mattype', 1, 'name', 'md.initialization.enthalpy') # }}} Index: /issm/trunk-jpl/src/m/classes/inversion.py =================================================================== --- /issm/trunk-jpl/src/m/classes/inversion.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/inversion.py (revision 24213) @@ -8,185 +8,182 @@ from marshallcostfunctions import marshallcostfunctions + class inversion(object): - """ - INVERSION class definition + """ + INVERSION class definition - Usage: - inversion=inversion() - """ + Usage: + inversion = inversion() + """ - def __init__(self): # {{{ - self.iscontrol = 0 - self.incomplete_adjoint = 0 - self.control_parameters = float('NaN') - self.nsteps = 0 - self.maxiter_per_step = float('NaN') - self.cost_functions = '' - self.cost_functions_coefficients = float('NaN') - self.gradient_scaling = float('NaN') - self.cost_function_threshold = 0 - self.min_parameters = float('NaN') - self.max_parameters = float('NaN') - self.step_threshold = float('NaN') - self.vx_obs = float('NaN') - self.vy_obs = float('NaN') - self.vz_obs = float('NaN') - self.vel_obs = float('NaN') - self.thickness_obs = float('NaN') - self.surface_obs = float('NaN') + def __init__(self): # {{{ + self.iscontrol = 0 + self.incomplete_adjoint = 0 + self.control_parameters = float('NaN') + self.nsteps = 0 + self.maxiter_per_step = float('NaN') + self.cost_functions = '' + self.cost_functions_coefficients = float('NaN') + self.gradient_scaling = float('NaN') + self.cost_function_threshold = 0 + self.min_parameters = float('NaN') + self.max_parameters = float('NaN') + self.step_threshold = float('NaN') + self.vx_obs = float('NaN') + self.vy_obs = float('NaN') + self.vz_obs = float('NaN') + self.vel_obs = float('NaN') + self.thickness_obs = float('NaN') + self.surface_obs = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' inversion parameters:' - string="%s\n%s"%(string,fielddisplay(self,'iscontrol','is inversion activated?')) - string="%s\n%s"%(string,fielddisplay(self,'incomplete_adjoint','1: linear viscosity, 0: non-linear viscosity')) - string="%s\n%s"%(string,fielddisplay(self,'control_parameters','ex: {''FrictionCoefficient''}, or {''MaterialsRheologyBbar''}')) - string="%s\n%s"%(string,fielddisplay(self,'nsteps','number of optimization searches')) - string="%s\n%s"%(string,fielddisplay(self,'cost_functions','indicate the type of response for each optimization step')) - string="%s\n%s"%(string,fielddisplay(self,'cost_functions_coefficients','cost_functions_coefficients applied to the misfit of each vertex and for each control_parameter')) - string="%s\n%s"%(string,fielddisplay(self,'cost_function_threshold','misfit convergence criterion. Default is 1%, NaN if not applied')) - string="%s\n%s"%(string,fielddisplay(self,'maxiter_per_step','maximum iterations during each optimization step')) - string="%s\n%s"%(string,fielddisplay(self,'gradient_scaling','scaling factor on gradient direction during optimization, for each optimization step')) - string="%s\n%s"%(string,fielddisplay(self,'step_threshold','decrease threshold for misfit, default is 30%')) - string="%s\n%s"%(string,fielddisplay(self,'min_parameters','absolute minimum acceptable value of the inversed parameter on each vertex')) - string="%s\n%s"%(string,fielddisplay(self,'max_parameters','absolute maximum acceptable value of the inversed parameter on each vertex')) - string="%s\n%s"%(string,fielddisplay(self,'vx_obs','observed velocity x component [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'vy_obs','observed velocity y component [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'vel_obs','observed velocity magnitude [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'thickness_obs','observed thickness [m]')) - string="%s\n%s"%(string,fielddisplay(self,'surface_obs','observed surface elevation [m]')) - string="%s\n%s"%(string,'Available cost functions:') - string="%s\n%s"%(string,' 101: SurfaceAbsVelMisfit') - string="%s\n%s"%(string,' 102: SurfaceRelVelMisfit') - string="%s\n%s"%(string,' 103: SurfaceLogVelMisfit') - string="%s\n%s"%(string,' 104: SurfaceLogVxVyMisfit') - string="%s\n%s"%(string,' 105: SurfaceAverageVelMisfit') - string="%s\n%s"%(string,' 201: ThicknessAbsMisfit') - string="%s\n%s"%(string,' 501: DragCoefficientAbsGradient') - string="%s\n%s"%(string,' 502: RheologyBbarAbsGradient') - string="%s\n%s"%(string,' 503: ThicknessAbsGradient') - return string - #}}} - def extrude(self,md): # {{{ - self.vx_obs=project3d(md,'vector',self.vx_obs,'type','node') - self.vy_obs=project3d(md,'vector',self.vy_obs,'type','node') - self.vel_obs=project3d(md,'vector',self.vel_obs,'type','node') - self.thickness_obs=project3d(md,'vector',self.thickness_obs,'type','node') - if not np.any(np.isnan(self.cost_functions_coefficients)): - self.cost_functions_coefficients=project3d(md,'vector',self.cost_functions_coefficients,'type','node') - if not np.any(np.isnan(self.min_parameters)): - self.min_parameters=project3d(md,'vector',self.min_parameters,'type','node') - if not np.any(np.isnan(self.max_parameters)): - self.max_parameters=project3d(md,'vector',self.max_parameters,'type','node') - return self - #}}} - def setdefaultparameters(self): # {{{ - - #default is incomplete adjoint for now - self.incomplete_adjoint=1 + #}}} - #parameter to be inferred by control methods (only - #drag and B are supported yet) - self.control_parameters='FrictionCoefficient' + def __repr__(self): # {{{ + string = ' inversion parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'iscontrol', 'is inversion activated?')) + string = "%s\n%s" % (string, fielddisplay(self, 'incomplete_adjoint', '1: linear viscosity, 0: non - linear viscosity')) + string = "%s\n%s" % (string, fielddisplay(self, 'control_parameters', 'ex: {''FrictionCoefficient''}, or {''MaterialsRheologyBbar''}')) + string = "%s\n%s" % (string, fielddisplay(self, 'nsteps', 'number of optimization searches')) + string = "%s\n%s" % (string, fielddisplay(self, 'cost_functions', 'indicate the type of response for each optimization step')) + string = "%s\n%s" % (string, fielddisplay(self, 'cost_functions_coefficients', 'cost_functions_coefficients applied to the misfit of each vertex and for each control_parameter')) + string = "%s\n%s" % (string, fielddisplay(self, 'cost_function_threshold', 'misfit convergence criterion. Default is 1%, NaN if not applied')) + string = "%s\n%s" % (string, fielddisplay(self, 'maxiter_per_step', 'maximum iterations during each optimization step')) + string = "%s\n%s" % (string, fielddisplay(self, 'gradient_scaling', 'scaling factor on gradient direction during optimization, for each optimization step')) + string = "%s\n%s" % (string, fielddisplay(self, 'step_threshold', 'decrease threshold for misfit, default is 30%')) + string = "%s\n%s" % (string, fielddisplay(self, 'min_parameters', 'absolute minimum acceptable value of the inversed parameter on each vertex')) + string = "%s\n%s" % (string, fielddisplay(self, 'max_parameters', 'absolute maximum acceptable value of the inversed parameter on each vertex')) + string = "%s\n%s" % (string, fielddisplay(self, 'vx_obs', 'observed velocity x component [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'vy_obs', 'observed velocity y component [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'vel_obs', 'observed velocity magnitude [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'thickness_obs', 'observed thickness [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'surface_obs', 'observed surface elevation [m]')) + string = "%s\n%s" % (string, 'Available cost functions:') + string = "%s\n%s" % (string, ' 101: SurfaceAbsVelMisfit') + string = "%s\n%s" % (string, ' 102: SurfaceRelVelMisfit') + string = "%s\n%s" % (string, ' 103: SurfaceLogVelMisfit') + string = "%s\n%s" % (string, ' 104: SurfaceLogVxVyMisfit') + string = "%s\n%s" % (string, ' 105: SurfaceAverageVelMisfit') + string = "%s\n%s" % (string, ' 201: ThicknessAbsMisfit') + string = "%s\n%s" % (string, ' 501: DragCoefficientAbsGradient') + string = "%s\n%s" % (string, ' 502: RheologyBbarAbsGradient') + string = "%s\n%s" % (string, ' 503: ThicknessAbsGradient') + return string + #}}} - #number of steps in the control methods - self.nsteps=20 + def extrude(self, md): # {{{ + self.vx_obs = project3d(md, 'vector', self.vx_obs, 'type', 'node') + self.vy_obs = project3d(md, 'vector', self.vy_obs, 'type', 'node') + self.vel_obs = project3d(md, 'vector', self.vel_obs, 'type', 'node') + self.thickness_obs = project3d(md, 'vector', self.thickness_obs, 'type', 'node') + if not np.any(np.isnan(self.cost_functions_coefficients)): + self.cost_functions_coefficients = project3d(md, 'vector', self.cost_functions_coefficients, 'type', 'node') + if not np.any(np.isnan(self.min_parameters)): + self.min_parameters = project3d(md, 'vector', self.min_parameters, 'type', 'node') + if not np.any(np.isnan(self.max_parameters)): + self.max_parameters = project3d(md, 'vector', self.max_parameters, 'type', 'node') + return self + #}}} - #maximum number of iteration in the optimization algorithm for - #each step - self.maxiter_per_step=20*np.ones(self.nsteps) + def setdefaultparameters(self): # {{{ - #the inversed parameter is updated as follows: - #new_par=old_par + gradient_scaling(n)*C*gradient with C in [0 1]; - #usually the gradient_scaling must be of the order of magnitude of the - #inversed parameter (10^8 for B, 50 for drag) and can be decreased - #after the first iterations - self.gradient_scaling=50*np.ones((self.nsteps,1)) + #default is incomplete adjoint for now + self.incomplete_adjoint = 1 + #parameter to be inferred by control methods (only + #drag and B are supported yet) + self.control_parameters = 'FrictionCoefficient' + #number of steps in the control methods + self.nsteps = 20 + #maximum number of iteration in the optimization algorithm for + #each step + self.maxiter_per_step = 20 * np.ones(self.nsteps) + #the inversed parameter is updated as follows: + #new_par = old_par + gradient_scaling(n) * C * gradient with C in [0 1] + #usually the gradient_scaling must be of the order of magnitude of the + #inversed parameter (10^8 for B, 50 for drag) and can be decreased + #after the first iterations + self.gradient_scaling = 50 * np.ones((self.nsteps, 1)) + #several responses can be used: + self.cost_functions = [101, ] + #step_threshold is used to speed up control method. When + #misfit(1) / misfit(0) < self.step_threshold, we go directly to + #the next step + self.step_threshold = 0.7 * np.ones(self.nsteps) #30 per cent decrement + #cost_function_threshold is a criteria to stop the control methods. + #if J[n] - J[n - 1] / J[n] < criteria, the control run stops + #NaN if not applied + self.cost_function_threshold = float('NaN') #not activated - #several responses can be used: - self.cost_functions=[101,] + return self + #}}} - #step_threshold is used to speed up control method. When - #misfit(1)/misfit(0) < self.step_threshold, we go directly to - #the next step - self.step_threshold=.7*np.ones(self.nsteps) #30 per cent decrement + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if not self.iscontrol: + return md - #cost_function_threshold is a criteria to stop the control methods. - #if J[n]-J[n-1]/J[n] < criteria, the control run stops - #NaN if not applied - self.cost_function_threshold=float('NaN') #not activated + num_controls = np.size(md.inversion.control_parameters) + num_costfunc = np.size(md.inversion.cost_functions) - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + md = checkfield(md, 'fieldname', 'inversion.iscontrol', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'inversion.incomplete_adjoint', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'inversion.control_parameters', 'cell', 1, 'values', supportedcontrols()) + md = checkfield(md, 'fieldname', 'inversion.nsteps', 'numel', [1], '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.maxiter_per_step', 'size', [md.inversion.nsteps], '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.step_threshold', 'size', [md.inversion.nsteps]) + md = checkfield(md, 'fieldname', 'inversion.cost_functions', 'size', [num_costfunc], 'values', supportedcostfunctions()) + md = checkfield(md, 'fieldname', 'inversion.cost_functions_coefficients', 'size', [md.mesh.numberofvertices, num_costfunc], '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.gradient_scaling', 'size', [md.inversion.nsteps, num_controls]) + md = checkfield(md, 'fieldname', 'inversion.min_parameters', 'size', [md.mesh.numberofvertices, num_controls]) + md = checkfield(md, 'fieldname', 'inversion.max_parameters', 'size', [md.mesh.numberofvertices, num_controls]) - #Early return - if not self.iscontrol: - return md + #Only SSA, HO and FS are supported right now + if solution == 'StressbalanceSolution': + if not (md.flowequation.isSSA or md.flowequation.isHO or md.flowequation.isFS or md.flowequation.isL1L2): + md.checkmessage("'inversion can only be performed for SSA, HO or FS ice flow models") - num_controls=np.size(md.inversion.control_parameters) - num_costfunc=np.size(md.inversion.cost_functions) + if solution == 'BalancethicknessSolution': + md = checkfield(md, 'fieldname', 'inversion.thickness_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + else: + md = checkfield(md, 'fieldname', 'inversion.vx_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'inversion.vy_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) - md = checkfield(md,'fieldname','inversion.iscontrol','values',[0,1]) - md = checkfield(md,'fieldname','inversion.incomplete_adjoint','values',[0,1]) - md = checkfield(md,'fieldname','inversion.control_parameters','cell',1,'values',supportedcontrols()) - md = checkfield(md,'fieldname','inversion.nsteps','numel',[1],'>=',0) - md = checkfield(md,'fieldname','inversion.maxiter_per_step','size',[md.inversion.nsteps],'>=',0) - md = checkfield(md,'fieldname','inversion.step_threshold','size',[md.inversion.nsteps]) - md = checkfield(md,'fieldname','inversion.cost_functions','size',[num_costfunc],'values',supportedcostfunctions()) - md = checkfield(md,'fieldname','inversion.cost_functions_coefficients','size',[md.mesh.numberofvertices,num_costfunc],'>=',0) - md = checkfield(md,'fieldname','inversion.gradient_scaling','size',[md.inversion.nsteps,num_controls]) - md = checkfield(md,'fieldname','inversion.min_parameters','size',[md.mesh.numberofvertices,num_controls]) - md = checkfield(md,'fieldname','inversion.max_parameters','size',[md.mesh.numberofvertices,num_controls]) + return md + # }}} - #Only SSA, HO and FS are supported right now - if solution=='StressbalanceSolution': - if not (md.flowequation.isSSA or md.flowequation.isHO or md.flowequation.isFS or md.flowequation.isL1L2): - md.checkmessage("'inversion can only be performed for SSA, HO or FS ice flow models"); + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts - if solution=='BalancethicknessSolution': - md = checkfield(md,'fieldname','inversion.thickness_obs','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - else: - md = checkfield(md,'fieldname','inversion.vx_obs','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','inversion.vy_obs','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) + WriteData(fid, prefix, 'name', 'md.inversion.type', 'data', 0, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'iscontrol', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'incomplete_adjoint', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'vel_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + if not self.iscontrol: + return + WriteData(fid, prefix, 'object', self, 'fieldname', 'nsteps', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'maxiter_per_step', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'fieldname', 'cost_functions_coefficients', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'gradient_scaling', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'fieldname', 'cost_function_threshold', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'min_parameters', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'fieldname', 'max_parameters', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'fieldname', 'step_threshold', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'fieldname', 'vx_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'vy_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'vz_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'thickness_obs', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'surface_obs', 'format', 'DoubleMat', 'mattype', 1) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + #process control parameters + num_control_parameters = len(self.control_parameters) + WriteData(fid, prefix, 'object', self, 'fieldname', 'control_parameters', 'format', 'StringArray') + WriteData(fid, prefix, 'data', num_control_parameters, 'name', 'md.inversion.num_control_parameters', 'format', 'Integer') - yts=md.constants.yts - - WriteData(fid,prefix,'name','md.inversion.type','data',0,'format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','iscontrol','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','incomplete_adjoint','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','vel_obs','format','DoubleMat','mattype',1,'scale',1./yts) - if not self.iscontrol: - return - WriteData(fid,prefix,'object',self,'fieldname','nsteps','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','maxiter_per_step','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'fieldname','cost_functions_coefficients','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','gradient_scaling','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'fieldname','cost_function_threshold','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','min_parameters','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'fieldname','max_parameters','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'fieldname','step_threshold','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'fieldname','vx_obs','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'fieldname','vy_obs','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'fieldname','vz_obs','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'fieldname','thickness_obs','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','surface_obs','format','DoubleMat','mattype',1) - - #process control parameters - num_control_parameters=len(self.control_parameters) - WriteData(fid,prefix,'object',self,'fieldname','control_parameters','format','StringArray') - WriteData(fid,prefix,'data',num_control_parameters,'name','md.inversion.num_control_parameters','format','Integer') - - #process cost functions - num_cost_functions=np.size(self.cost_functions) - data=marshallcostfunctions(self.cost_functions) - WriteData(fid,prefix,'data',data,'name','md.inversion.cost_functions','format','StringArray') - WriteData(fid,prefix,'data',num_cost_functions,'name','md.inversion.num_cost_functions','format','Integer') - # }}} + #process cost functions + num_cost_functions = np.size(self.cost_functions) + data = marshallcostfunctions(self.cost_functions) + WriteData(fid, prefix, 'data', data, 'name', 'md.inversion.cost_functions', 'format', 'StringArray') + WriteData(fid, prefix, 'data', num_cost_functions, 'name', 'md.inversion.num_cost_functions', 'format', 'Integer') + # }}} Index: /issm/trunk-jpl/src/m/classes/issmsettings.py =================================================================== --- /issm/trunk-jpl/src/m/classes/issmsettings.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/issmsettings.py (revision 24213) @@ -9,5 +9,5 @@ Usage: - issmsettings=issmsettings(); + issmsettings = issmsettings() """ @@ -22,13 +22,14 @@ self.solver_residue_threshold = 0 - #set defaults + #set defaults self.setdefaultparameters() - #}}} + #}}} + def __repr__(self): # {{{ string = " general issmsettings parameters:" string = "%s\n%s" % (string, fielddisplay(self, "results_on_nodes", "list of output for which results will be output for all the nodes of each element, Use 'all' for all output on nodes.")) - string = "%s\n%s" % (string, fielddisplay(self, "io_gather", "I/O gathering strategy for result outputs (default 1)")) + string = "%s\n%s" % (string, fielddisplay(self, "io_gather", "I / O gathering strategy for result outputs (default 1)")) string = "%s\n%s" % (string, fielddisplay(self, "lowmem", "is the memory limited ? (0 or 1)")) string = "%s\n%s" % (string, fielddisplay(self, "output_frequency", "frequency at which results are saved in all solutions with multiple time_steps")) @@ -41,26 +42,19 @@ def setdefaultparameters(self): # {{{ - #are we short in memory ? (0 faster but requires more memory) self.lowmem = 0 - - #i/o: + #i / o: self.io_gather = 1 - #results frequency by default every step self.output_frequency = 1 - #coupling frequency of the stress balance solver by default every step self.sb_coupling_frequency = 1 - #checkpoints frequency, by default never: self.recording_frequency = 0 - #this option can be activated to load automatically the results #onto the model after a parallel run by waiting for the lock file #N minutes that is generated once the solution has converged #0 to deactivate - self.waitonlock = 2 ** 31 - 1 - + self.waitonlock = 2**31 - 1 #throw an error if solver residue exceeds this value self.solver_residue_threshold = 1e-6 @@ -69,5 +63,5 @@ #}}} - def checkconsistency(self, md, solution, analyses): # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ md = checkfield(md, 'fieldname', 'settings.results_on_nodes', 'stringrow', 1) md = checkfield(md, 'fieldname', 'settings.io_gather', 'numel', [1], 'values', [0, 1]) @@ -82,5 +76,5 @@ # }}} - def marshall(self, prefix, md, fid): # {{{ + def marshall(self, prefix, md, fid): # {{{ WriteData(fid, prefix, 'data', self.results_on_nodes, 'name', 'md.settings.results_on_nodes', 'format', 'StringArray') WriteData(fid, prefix, 'object', self, 'class', 'settings', 'fieldname', 'io_gather', 'format', 'Boolean') Index: /issm/trunk-jpl/src/m/classes/levelset.py =================================================================== --- /issm/trunk-jpl/src/m/classes/levelset.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/levelset.py (revision 24213) @@ -10,5 +10,5 @@ Usage: - levelset=levelset(); + levelset = levelset() """ @@ -22,15 +22,15 @@ self.fe = 'P1' - #set defaults + #set defaults self.setdefaultparameters() #}}} def __repr__(self): # {{{ - string = ' Level-set parameters:' + string = ' Level - set parameters:' string = "%s\n%s" % (string, fielddisplay(self, 'stabilization', '0: no, 1: artificial_diffusivity, 2: streamline upwinding')) string = "%s\n%s" % (string, fielddisplay(self, 'spclevelset', 'levelset constraints (NaN means no constraint)')) string = "%s\n%s" % (string, fielddisplay(self, 'reinit_frequency', 'Amount of time steps after which the levelset function in re-initialized')) string = "%s\n%s" % (string, fielddisplay(self, 'kill_icebergs', 'remove floating icebergs to prevent rigid body motions (1: true, 0: false)')) - string = "%s\n%s" % (string, fielddisplay(self, 'calving_max', 'maximum allowed calving rate (m/a)')) + string = "%s\n%s" % (string, fielddisplay(self, 'calving_max', 'maximum allowed calving rate (m / a)')) string = "%s\n%s" % (string, fielddisplay(self, 'fe', 'Finite Element type: ''P1'' (default), or ''P2''')) @@ -44,5 +44,4 @@ def setdefaultparameters(self): # {{{ - #stabilization = 1 by default self.stabilization = 1 @@ -51,11 +50,11 @@ self.calving_max = 3000. - #Linear elements by default + #Linear elements by default self.fe = 'P1' return self #}}} - def checkconsistency(self, md, solution, analyses): # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ #Early return if (solution != 'TransientSolution') or (not md.transient.ismovingfront): @@ -71,6 +70,5 @@ # }}} - def marshall(self, prefix, md, fid): # {{{ - + def marshall(self, prefix, md, fid): # {{{ yts = md.constants.yts Index: /issm/trunk-jpl/src/m/classes/linearbasalforcings.py =================================================================== --- /issm/trunk-jpl/src/m/classes/linearbasalforcings.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/linearbasalforcings.py (revision 24213) @@ -4,105 +4,106 @@ import numpy as np + class linearbasalforcings(object): - """ - LINEAR BASAL FORCINGS class definition + """ + LINEAR BASAL FORCINGS class definition - Usage: - basalforcings=linearbasalforcings(); - """ + Usage: + basalforcings = linearbasalforcings() + """ - def __init__(self,*args): # {{{ + def __init__(self, *args): # {{{ - if not len(args): - print('empty init') - self.groundedice_melting_rate = float('NaN') - self.deepwater_melting_rate = 0. - self.deepwater_elevation = 0. - self.upperwater_melting_rate = 0. - self.upperwater_elevation = 0. - self.geothermalflux = float('NaN') + if not len(args): + print('empty init') + self.groundedice_melting_rate = float('NaN') + self.deepwater_melting_rate = 0. + self.deepwater_elevation = 0. + self.upperwater_melting_rate = 0. + self.upperwater_elevation = 0. + self.geothermalflux = float('NaN') - #set defaults - self.setdefaultparameters() - elif len(args)==1 and args[0].__module__=='basalforcings': - print('converting basalforings to linearbasalforcings') - inv=args[0] - self.groundedice_melting_rate = inv.groundedice_melting_rate - self.geothermalflux = inv.geothermalflux - self.deepwater_melting_rate = 0. - self.deepwater_elevation = 0. - self.upperwater_melting_rate = 0. - self.upperwater_elevation = 0. + #set defaults + self.setdefaultparameters() + elif len(args) == 1 and args[0].__module__ == 'basalforcings': + print('converting basalforings to linearbasalforcings') + inv = args[0] + self.groundedice_melting_rate = inv.groundedice_melting_rate + self.geothermalflux = inv.geothermalflux + self.deepwater_melting_rate = 0. + self.deepwater_elevation = 0. + self.upperwater_melting_rate = 0. + self.upperwater_elevation = 0. - #set defaults - self.setdefaultparameters() - else: - raise Exception('constructor not supported') + #set defaults + self.setdefaultparameters() + else: + raise Exception('constructor not supported') - #}}} - def __repr__(self): # {{{ - string=" linear basal forcings parameters:" + #}}} + def __repr__(self): # {{{ + string = " linear basal forcings parameters:" - string="%s\n%s"%(string,fielddisplay(self,"deepwater_melting_rate","basal melting rate (positive if melting applied for floating ice whith base < deepwater_elevation) [m/yr]")) - string="%s\n%s"%(string,fielddisplay(self,"deepwater_elevation","elevation of ocean deepwater [m]")) - string="%s\n%s"%(string,fielddisplay(self,"upperwater_melting_rate","upper melting rate (positive if melting applied for floating ice whith base >= upperwater_elevation) [m/yr]")) - string="%s\n%s"%(string,fielddisplay(self,"upperwater_elevation","elevation of ocean upper water [m]")) - string="%s\n%s"%(string,fielddisplay(self,"groundedice_melting_rate","basal melting rate (positive if melting) [m/yr]")) - string="%s\n%s"%(string,fielddisplay(self,"geothermalflux","geothermal heat flux [W/m^2]")) - return string - #}}} - def initialize(self,md): # {{{ + string = "%s\n%s" % (string, fielddisplay(self, "deepwater_melting_rate", "basal melting rate (positive if melting applied for floating ice whith base < deepwater_elevation) [m/yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "deepwater_elevation", "elevation of ocean deepwater [m]")) + string = "%s\n%s" % (string, fielddisplay(self, "upperwater_melting_rate", "upper melting rate (positive if melting applied for floating ice whith base >= upperwater_elevation) [m/yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "upperwater_elevation", "elevation of ocean upper water [m]")) + string = "%s\n%s" % (string, fielddisplay(self, "groundedice_melting_rate", "basal melting rate (positive if melting) [m/yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "geothermalflux", "geothermal heat flux [W/m^2]")) + return string + #}}} + def initialize(self, md): # {{{ - if np.all(np.isnan(self.groundedice_melting_rate)): - self.groundedice_melting_rate=np.zeros((md.mesh.numberofvertices)) - print(" no basalforcings.groundedice_melting_rate specified: values set as zero") + if np.all(np.isnan(self.groundedice_melting_rate)): + self.groundedice_melting_rate = np.zeros((md.mesh.numberofvertices)) + print(" no basalforcings.groundedice_melting_rate specified: values set as zero") - return self - #}}} - def setdefaultparameters(self): # {{{ + return self + #}}} + def setdefaultparameters(self): # {{{ - self.deepwater_melting_rate = 50.0 - self.deepwater_elevation = -800.0 - self.upperwater_melting_rate = 0.0 - self.upperwater_elevation = -400.0 + self.deepwater_melting_rate = 50.0 + self.deepwater_elevation = - 800.0 + self.upperwater_melting_rate = 0.0 + self.upperwater_elevation = - 400.0 - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + return self + #}}} + def checkconsistency(self, md, solution, analyses): # {{{ - if 'MasstransportAnalysis' in analyses and not (solution=='TransientSolution' and not md.transient.ismasstransport): - md = checkfield(md,'fieldname','basalforcings.groundedice_melting_rate','NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','basalforcings.deepwater_melting_rate','>=',0,'singletimeseries',1) - md = checkfield(md,'fieldname','basalforcings.upperwater_melting_rate','>=',0,'singletimeseries',1) - md = checkfield(md,'fieldname','basalforcings.deepwater_elevation','<','basalforcings.upperwater_elevation','singletimeseries',1) - md = checkfield(md,'fieldname','basalforcings.upperwater_elevation','<=',0,'singletimeseries',1) + if 'MasstransportAnalysis' in analyses and not (solution == 'TransientSolution' and not md.transient.ismasstransport): + md = checkfield(md, 'fieldname', 'basalforcings.groundedice_melting_rate', 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.deepwater_melting_rate', '>=', 0, 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.upperwater_melting_rate', '>=', 0, 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.deepwater_elevation', '<', 'basalforcings.upperwater_elevation', 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.upperwater_elevation', '<=', 0, 'singletimeseries', 1) - if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','basalforcings.groundedice_melting_rate','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','basalforcings.deepwater_melting_rate','>=',0,'singletimeseries',1) - md = checkfield(md,'fieldname','basalforcings.upperwater_melting_rate','>=',0,'singletimeseries',1) - md = checkfield(md,'fieldname','basalforcings.deepwater_elevation','<','basalforcings.upperwater_elevation','singletimeseries',1) - md = checkfield(md,'fieldname','basalforcings.upperwater_elevation','<=',0,'singletimeseries',1) + if 'BalancethicknessAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'basalforcings.groundedice_melting_rate', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'basalforcings.deepwater_melting_rate', '>=', 0, 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.upperwater_melting_rate', '>=', 0, 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.deepwater_elevation', '<', 'basalforcings.upperwater_elevation', 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.upperwater_elevation', '<=', 0, 'singletimeseries', 1) - if 'ThermalAnalysis' in analyses and not (solution=='TransientSolution' and not md.transient.isthermal): - md = checkfield(md,'fieldname','basalforcings.groundedice_melting_rate','NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','basalforcings.deepwater_melting_rate','>=',0,'singletimeseries',1) - md = checkfield(md,'fieldname','basalforcings.upperwater_melting_rate','>=',0,'singletimeseries',1) - md = checkfield(md,'fieldname','basalforcings.deepwater_elevation','<','basalforcings.upperwater_elevation','singletimeseries',1) - md = checkfield(md,'fieldname','basalforcings.upperwater_elevation','<=',0,'singletimeseries',1) - md = checkfield(md,'fieldname','basalforcings.geothermalflux','NaN',1,'Inf',1,'timeseries',1,'>=',0) + if 'ThermalAnalysis' in analyses and not (solution == 'TransientSolution' and not md.transient.isthermal): + md = checkfield(md, 'fieldname', 'basalforcings.groundedice_melting_rate', 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.deepwater_melting_rate', '>=', 0, 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.upperwater_melting_rate', '>=', 0, 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.deepwater_elevation', '<', 'basalforcings.upperwater_elevation', 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.upperwater_elevation', '<=', 0, 'singletimeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.geothermalflux', 'NaN', 1, 'Inf', 1, 'timeseries', 1, '>=', 0) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + return md + # }}} + def marshall(self, prefix, md, fid): # {{{ - yts=md.constants.yts + yts = md.constants.yts - WriteData(fid,prefix,'name','md.basalforcings.model','data',2,'format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','groundedice_melting_rate','name','md.basalforcings.groundedice_melting_rate','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','geothermalflux','name','md.basalforcings.geothermalflux','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','deepwater_melting_rate','format','DoubleMat','mattype',3,'timeserieslength',2,'name','md.basalforcings.deepwater_melting_rate','scale',1./yts,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','deepwater_elevation','format','DoubleMat','mattype',3,'name','md.basalforcings.deepwater_elevation','yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','upperwater_melting_rate','format','DoubleMat','mattype',3,'timeserieslength',2,'name','md.basalforcings.upperwater_melting_rate','scale',1./yts,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','upperwater_elevation','format','DoubleMat','mattype',3,'name','md.basalforcings.upperwater_elevation','yts',md.constants.yts) - # }}} + WriteData(fid, prefix, 'name', 'md.basalforcings.model', 'data', 2, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'groundedice_melting_rate', 'name', 'md.basalforcings.groundedice_melting_rate', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'geothermalflux', 'name', 'md.basalforcings.geothermalflux', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'deepwater_melting_rate', 'format', 'DoubleMat', 'mattype', 3, 'timeserieslength', 2, 'name', 'md.basalforcings.deepwater_melting_rate', 'scale', 1. / yts, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'deepwater_elevation', 'format', 'DoubleMat', 'mattype', 3, 'name', 'md.basalforcings.deepwater_elevation', 'yts', yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'upperwater_melting_rate', 'format', 'DoubleMat', 'mattype', 3, 'timeserieslength', 2, 'name', 'md.basalforcings.upperwater_melting_rate', 'scale', 1. / yts, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'upperwater_elevation', 'format', 'DoubleMat', 'mattype', 3, 'name', 'md.basalforcings.upperwater_elevation', 'yts', yts) + # }}} Index: /issm/trunk-jpl/src/m/classes/m1qn3inversion.py =================================================================== --- /issm/trunk-jpl/src/m/classes/m1qn3inversion.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/m1qn3inversion.py (revision 24213) @@ -8,188 +8,185 @@ from marshallcostfunctions import marshallcostfunctions + class m1qn3inversion(object): - ''' - M1QN3 class definition + ''' + M1QN3 class definition Usage: - m1qn3inversion=m1qn3inversion() - ''' + m1qn3inversion = m1qn3inversion() + ''' - def __init__(self,*args): # {{{ + def __init__(self, *args): # {{{ - if not len(args): - print('empty init') - self.iscontrol = 0 - self.incomplete_adjoint = 0 - self.control_parameters = float('NaN') - self.control_scaling_factors = float('NaN') - self.maxsteps = 0 - self.maxiter = 0 - self.dxmin = 0. - self.gttol = 0. - self.cost_functions = float('NaN') - self.cost_functions_coefficients = float('NaN') - self.min_parameters = float('NaN') - self.max_parameters = float('NaN') - self.vx_obs = float('NaN') - self.vy_obs = float('NaN') - self.vz_obs = float('NaN') - self.vel_obs = float('NaN') - self.thickness_obs = float('NaN') + if not len(args): + print('empty init') + self.iscontrol = 0 + self.incomplete_adjoint = 0 + self.control_parameters = float('NaN') + self.control_scaling_factors = float('NaN') + self.maxsteps = 0 + self.maxiter = 0 + self.dxmin = 0. + self.gttol = 0. + self.cost_functions = float('NaN') + self.cost_functions_coefficients = float('NaN') + self.min_parameters = float('NaN') + self.max_parameters = float('NaN') + self.vx_obs = float('NaN') + self.vy_obs = float('NaN') + self.vz_obs = float('NaN') + self.vel_obs = float('NaN') + self.thickness_obs = float('NaN') - #set defaults - self.setdefaultparameters() - elif len(args)==1 and args[0].__module__=='inversion': - print('converting inversion to m1qn3inversion') - inv=args[0] - #first call setdefaultparameters: - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() + elif len(args) == 1 and args[0].__module__ == 'inversion': + print('converting inversion to m1qn3inversion') + inv = args[0] + #first call setdefaultparameters: + self.setdefaultparameters() - #then go fish whatever is available in the inversion object provided to the constructor - self.iscontrol = inv.iscontrol - self.incomplete_adjoint = inv.incomplete_adjoint - self.control_parameters = inv.control_parameters - self.maxsteps = inv.nsteps - self.cost_functions = inv.cost_functions - self.cost_functions_coefficients = inv.cost_functions_coefficients - self.min_parameters = inv.min_parameters - self.max_parameters = inv.max_parameters - self.vx_obs = inv.vx_obs - self.vy_obs = inv.vy_obs - self.vz_obs = inv.vz_obs - self.vel_obs = inv.vel_obs - self.thickness_obs = inv.thickness_obs - else: - raise Exception('constructor not supported') - #}}} - def __repr__(self): # {{{ - string=' m1qn3inversion parameters:' - string="%s\n%s"%(string,fielddisplay(self,'iscontrol','is inversion activated?')) - string="%s\n%s"%(string,fielddisplay(self,'incomplete_adjoint','1: linear viscosity, 0: non-linear viscosity')) - string="%s\n%s"%(string,fielddisplay(self,'control_parameters','ex: [''FrictionCoefficient''], or [''MaterialsRheologyBbar'']')) - string="%s\n%s"%(string,fielddisplay(self,'control_scaling_factors','order of magnitude of each control (useful for multi-parameter optimization)')) - string="%s\n%s"%(string,fielddisplay(self,'maxsteps','maximum number of iterations (gradient computation)')) - string="%s\n%s"%(string,fielddisplay(self,'maxiter','maximum number of Function evaluation (forward run)')) - string="%s\n%s"%(string,fielddisplay(self,'dxmin','convergence criterion: two points less than dxmin from eachother (sup-norm) are considered identical')) - string="%s\n%s"%(string,fielddisplay(self,'gttol','||g(X)||/||g(X0)|| (g(X0): gradient at initial guess X0)')) - string="%s\n%s"%(string,fielddisplay(self,'cost_functions','indicate the type of response for each optimization step')) - string="%s\n%s"%(string,fielddisplay(self,'cost_functions_coefficients','cost_functions_coefficients applied to the misfit of each vertex and for each control_parameter')) - string="%s\n%s"%(string,fielddisplay(self,'min_parameters','absolute minimum acceptable value of the inversed parameter on each vertex')) - string="%s\n%s"%(string,fielddisplay(self,'max_parameters','absolute maximum acceptable value of the inversed parameter on each vertex')) - string="%s\n%s"%(string,fielddisplay(self,'vx_obs','observed velocity x component [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'vy_obs','observed velocity y component [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'vel_obs','observed velocity magnitude [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'thickness_obs','observed thickness [m]')) - string="%s\n%s"%(string,'Available cost functions:') - string="%s\n%s"%(string,' 101: SurfaceAbsVelMisfit') - string="%s\n%s"%(string,' 102: SurfaceRelVelMisfit') - string="%s\n%s"%(string,' 103: SurfaceLogVelMisfit') - string="%s\n%s"%(string,' 104: SurfaceLogVxVyMisfit') - string="%s\n%s"%(string,' 105: SurfaceAverageVelMisfit') - string="%s\n%s"%(string,' 201: ThicknessAbsMisfit') - string="%s\n%s"%(string,' 501: DragCoefficientAbsGradient') - string="%s\n%s"%(string,' 502: RheologyBbarAbsGradient') - string="%s\n%s"%(string,' 503: ThicknessAbsGradient') - return string - #}}} - def extrude(self,md): # {{{ - self.vx_obs=project3d(md,'vector',self.vx_obs,'type','node') - self.vy_obs=project3d(md,'vector',self.vy_obs,'type','node') - self.vel_obs=project3d(md,'vector',self.vel_obs,'type','node') - self.thickness_obs=project3d(md,'vector',self.thickness_obs,'type','node') - if not np.any(np.isnan(self.cost_functions_coefficients)): - self.cost_functions_coefficients=project3d(md,'vector',self.cost_functions_coefficients,'type','node') - if not np.any(np.isnan(self.min_parameters)): - self.min_parameters=project3d(md,'vector',self.min_parameters,'type','node') - if not np.any(np.isnan(self.max_parameters)): - self.max_parameters=project3d(md,'vector',self.max_parameters,'type','node') - return self - #}}} - def setdefaultparameters(self): # {{{ - - #default is incomplete adjoint for now - self.incomplete_adjoint=1 + #then go fish whatever is available in the inversion object provided to the constructor + self.iscontrol = inv.iscontrol + self.incomplete_adjoint = inv.incomplete_adjoint + self.control_parameters = inv.control_parameters + self.maxsteps = inv.nsteps + self.cost_functions = inv.cost_functions + self.cost_functions_coefficients = inv.cost_functions_coefficients + self.min_parameters = inv.min_parameters + self.max_parameters = inv.max_parameters + self.vx_obs = inv.vx_obs + self.vy_obs = inv.vy_obs + self.vz_obs = inv.vz_obs + self.vel_obs = inv.vel_obs + self.thickness_obs = inv.thickness_obs + else: + raise Exception('constructor not supported') + #}}} - #parameter to be inferred by control methods (only - #drag and B are supported yet) - self.control_parameters='FrictionCoefficient' - - #Scaling factor for each control - self.control_scaling_factors=1 + def __repr__(self): # {{{ + string = ' m1qn3inversion parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'iscontrol', 'is inversion activated?')) + string = "%s\n%s" % (string, fielddisplay(self, 'incomplete_adjoint', '1: linear viscosity, 0: non - linear viscosity')) + string = "%s\n%s" % (string, fielddisplay(self, 'control_parameters', 'ex: [''FrictionCoefficient''], or [''MaterialsRheologyBbar'']')) + string = "%s\n%s" % (string, fielddisplay(self, 'control_scaling_factors', 'order of magnitude of each control (useful for multi - parameter optimization)')) + string = "%s\n%s" % (string, fielddisplay(self, 'maxsteps', 'maximum number of iterations (gradient computation)')) + string = "%s\n%s" % (string, fielddisplay(self, 'maxiter', 'maximum number of Function evaluation (forward run)')) + string = "%s\n%s" % (string, fielddisplay(self, 'dxmin', 'convergence criterion: two points less than dxmin from eachother (sup - norm) are considered identical')) + string = "%s\n%s" % (string, fielddisplay(self, 'gttol', '||g(X)||/||g(X0)|| (g(X0): gradient at initial guess X0)')) + string = "%s\n%s" % (string, fielddisplay(self, 'cost_functions', 'indicate the type of response for each optimization step')) + string = "%s\n%s" % (string, fielddisplay(self, 'cost_functions_coefficients', 'cost_functions_coefficients applied to the misfit of each vertex and for each control_parameter')) + string = "%s\n%s" % (string, fielddisplay(self, 'min_parameters', 'absolute minimum acceptable value of the inversed parameter on each vertex')) + string = "%s\n%s" % (string, fielddisplay(self, 'max_parameters', 'absolute maximum acceptable value of the inversed parameter on each vertex')) + string = "%s\n%s" % (string, fielddisplay(self, 'vx_obs', 'observed velocity x component [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'vy_obs', 'observed velocity y component [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'vel_obs', 'observed velocity magnitude [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'thickness_obs', 'observed thickness [m]')) + string = "%s\n%s" % (string, 'Available cost functions:') + string = "%s\n%s" % (string, ' 101: SurfaceAbsVelMisfit') + string = "%s\n%s" % (string, ' 102: SurfaceRelVelMisfit') + string = "%s\n%s" % (string, ' 103: SurfaceLogVelMisfit') + string = "%s\n%s" % (string, ' 104: SurfaceLogVxVyMisfit') + string = "%s\n%s" % (string, ' 105: SurfaceAverageVelMisfit') + string = "%s\n%s" % (string, ' 201: ThicknessAbsMisfit') + string = "%s\n%s" % (string, ' 501: DragCoefficientAbsGradient') + string = "%s\n%s" % (string, ' 502: RheologyBbarAbsGradient') + string = "%s\n%s" % (string, ' 503: ThicknessAbsGradient') + return string + #}}} - #number of iterations - self.maxsteps=20 - self.maxiter=40 + def extrude(self, md): # {{{ + self.vx_obs = project3d(md, 'vector', self.vx_obs, 'type', 'node') + self.vy_obs = project3d(md, 'vector', self.vy_obs, 'type', 'node') + self.vel_obs = project3d(md, 'vector', self.vel_obs, 'type', 'node') + self.thickness_obs = project3d(md, 'vector', self.thickness_obs, 'type', 'node') + if not np.any(np.isnan(self.cost_functions_coefficients)): + self.cost_functions_coefficients = project3d(md, 'vector', self.cost_functions_coefficients, 'type', 'node') + if not np.any(np.isnan(self.min_parameters)): + self.min_parameters = project3d(md, 'vector', self.min_parameters, 'type', 'node') + if not np.any(np.isnan(self.max_parameters)): + self.max_parameters = project3d(md, 'vector', self.max_parameters, 'type', 'node') + return self + #}}} - #several responses can be used: - self.cost_functions=101 + def setdefaultparameters(self): # {{{ + #default is incomplete adjoint for now + self.incomplete_adjoint = 1 + #parameter to be inferred by control methods (only + #drag and B are supported yet) + self.control_parameters = 'FrictionCoefficient' + #Scaling factor for each control + self.control_scaling_factors = 1 + #number of iterations + self.maxsteps = 20 + self.maxiter = 40 + #several responses can be used: + self.cost_functions = 101 + #m1qn3 parameters + self.dxmin = 0.1 + self.gttol = 1e-4 - #m1qn3 parameters - self.dxmin = 0.1 - self.gttol = 1e-4 + return self + #}}} - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if not self.iscontrol: + return md - #Early return - if not self.iscontrol: - return md + num_controls = np.size(md.inversion.control_parameters) + num_costfunc = np.size(md.inversion.cost_functions) - num_controls=np.size(md.inversion.control_parameters) - num_costfunc=np.size(md.inversion.cost_functions) + md = checkfield(md, 'fieldname', 'inversion.iscontrol', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'inversion.incomplete_adjoint', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'inversion.control_parameters', 'cell', 1, 'values', supportedcontrols()) + md = checkfield(md, 'fieldname', 'inversion.control_scaling_factors', 'size', [num_controls], '>', 0, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'inversion.maxsteps', 'numel', [1], '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.maxiter', 'numel', [1], '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.dxmin', 'numel', [1], '>', 0.) + md = checkfield(md, 'fieldname', 'inversion.gttol', 'numel', [1], '>', 0.) + md = checkfield(md, 'fieldname', 'inversion.cost_functions', 'size', [num_costfunc], 'values', supportedcostfunctions()) + md = checkfield(md, 'fieldname', 'inversion.cost_functions_coefficients', 'size', [md.mesh.numberofvertices, num_costfunc], '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.min_parameters', 'size', [md.mesh.numberofvertices, num_controls]) + md = checkfield(md, 'fieldname', 'inversion.max_parameters', 'size', [md.mesh.numberofvertices, num_controls]) - md = checkfield(md,'fieldname','inversion.iscontrol','values',[0,1]) - md = checkfield(md,'fieldname','inversion.incomplete_adjoint','values',[0,1]) - md = checkfield(md,'fieldname','inversion.control_parameters','cell',1,'values',supportedcontrols()) - md = checkfield(md,'fieldname','inversion.control_scaling_factors','size',[num_controls],'>',0,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','inversion.maxsteps','numel',[1],'>=',0) - md = checkfield(md,'fieldname','inversion.maxiter','numel',[1],'>=',0) - md = checkfield(md,'fieldname','inversion.dxmin','numel',[1],'>',0.) - md = checkfield(md,'fieldname','inversion.gttol','numel',[1],'>',0.) - md = checkfield(md,'fieldname','inversion.cost_functions','size',[num_costfunc],'values',supportedcostfunctions()) - md = checkfield(md,'fieldname','inversion.cost_functions_coefficients','size',[md.mesh.numberofvertices,num_costfunc],'>=',0) - md = checkfield(md,'fieldname','inversion.min_parameters','size',[md.mesh.numberofvertices,num_controls]) - md = checkfield(md,'fieldname','inversion.max_parameters','size',[md.mesh.numberofvertices,num_controls]) + if solution == 'BalancethicknessSolution': + md = checkfield(md, 'fieldname', 'inversion.thickness_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + else: + md = checkfield(md, 'fieldname', 'inversion.vx_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'inversion.vy_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) - if solution=='BalancethicknessSolution': - md = checkfield(md,'fieldname','inversion.thickness_obs','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - else: - md = checkfield(md,'fieldname','inversion.vx_obs','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','inversion.vy_obs','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) + return md + # }}} - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'iscontrol', 'format', 'Boolean') + WriteData(fid, prefix, 'name', 'md.inversion.type', 'data', 2, 'format', 'Integer') + if not self.iscontrol: + return + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'incomplete_adjoint', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'control_scaling_factors', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'maxsteps', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'maxiter', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'dxmin', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'gttol', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'cost_functions_coefficients', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'min_parameters', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'max_parameters', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'vx_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'vy_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'vz_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'thickness_obs', 'format', 'DoubleMat', 'mattype', 1) - yts=md.constants.yts + #process control parameters + num_control_parameters = len(self.control_parameters) + WriteData(fid, prefix, 'object', self, 'fieldname', 'control_parameters', 'format', 'StringArray') + WriteData(fid, prefix, 'data', num_control_parameters, 'name', 'md.inversion.num_control_parameters', 'format', 'Integer') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','iscontrol','format','Boolean') - WriteData(fid,prefix,'name','md.inversion.type','data',2,'format','Integer') - if not self.iscontrol: - return - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','incomplete_adjoint','format','Boolean') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','control_scaling_factors','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','maxsteps','format','Integer') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','maxiter','format','Integer') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','dxmin','format','Double') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','gttol','format','Double') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','cost_functions_coefficients','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','min_parameters','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','max_parameters','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','vx_obs','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','vy_obs','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','vz_obs','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','thickness_obs','format','DoubleMat','mattype',1) - - #process control parameters - num_control_parameters=len(self.control_parameters) - WriteData(fid,prefix,'object',self,'fieldname','control_parameters','format','StringArray') - WriteData(fid,prefix,'data',num_control_parameters,'name','md.inversion.num_control_parameters','format','Integer') - - #process cost functions - num_cost_functions=np.size(self.cost_functions) - data=marshallcostfunctions(self.cost_functions) - WriteData(fid,prefix,'data',data,'name','md.inversion.cost_functions','format','StringArray') - WriteData(fid,prefix,'data',num_cost_functions,'name','md.inversion.num_cost_functions','format','Integer') - # }}} + #process cost functions + num_cost_functions = np.size(self.cost_functions) + data = marshallcostfunctions(self.cost_functions) + WriteData(fid, prefix, 'data', data, 'name', 'md.inversion.cost_functions', 'format', 'StringArray') + WriteData(fid, prefix, 'data', num_cost_functions, 'name', 'md.inversion.num_cost_functions', 'format', 'Integer') + # }}} Index: /issm/trunk-jpl/src/m/classes/mask.py =================================================================== --- /issm/trunk-jpl/src/m/classes/mask.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/mask.py (revision 24213) @@ -4,50 +4,55 @@ from checkfield import checkfield from WriteData import WriteData -import MatlabFuncs as m + class mask(object): - """ - MASK class definition + """ + MASK class definition - Usage: - mask=mask(); - """ + Usage: + mask = mask() + """ - def __init__(self): # {{{ - self.ice_levelset = float('NaN') - self.groundedice_levelset = float('NaN') + def __init__(self): # {{{ + self.ice_levelset = float('NaN') + self.groundedice_levelset = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=" masks:" + #}}} - string="%s\n%s"%(string,fielddisplay(self,"groundedice_levelset","is ice grounded ? grounded ice if > 0, grounding line position if = 0, floating ice if < 0")) - string="%s\n%s"%(string,fielddisplay(self,"ice_levelset","presence of ice if < 0, icefront position if = 0, no ice if > 0")) - return string - #}}} - def extrude(self,md): # {{{ - self.ice_levelset=project3d(md,'vector',self.ice_levelset,'type','node') - self.groundedice_levelset=project3d(md,'vector',self.groundedice_levelset,'type','node') - return self - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - if(solution=='LoveSolution'): - return + def __repr__(self): # {{{ + string = " masks:" - md = checkfield(md,'fieldname','mask.ice_levelset' ,'size',[md.mesh.numberofvertices]) - isice=np.array(md.mask.ice_levelset<=0,int) - if np.sum(isice)==0: - raise TypeError("no ice present in the domain") + string = "%s\n%s" % (string, fielddisplay(self, "groundedice_levelset", "is ice grounded ? grounded ice if > 0, grounding line position if = 0, floating ice if < 0")) + string = "%s\n%s" % (string, fielddisplay(self, "ice_levelset", "presence of ice if < 0, icefront position if = 0, no ice if > 0")) + return string + #}}} - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','groundedice_levelset','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','ice_levelset','format','DoubleMat','mattype',1) - # }}} + def extrude(self, md): # {{{ + self.ice_levelset = project3d(md, 'vector', self.ice_levelset, 'type', 'node') + self.groundedice_levelset = project3d(md, 'vector', self.groundedice_levelset, 'type', 'node') + return self + #}}} + + def setdefaultparameters(self): # {{{ + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + if(solution == 'LoveSolution'): + return + + md = checkfield(md, 'fieldname', 'mask.ice_levelset', 'size', [md.mesh.numberofvertices]) + isice = np.array(md.mask.ice_levelset <= 0, int) + if np.sum(isice) == 0: + raise TypeError("no ice present in the domain") + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'groundedice_levelset', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'ice_levelset', 'format', 'DoubleMat', 'mattype', 1) + # }}} Index: /issm/trunk-jpl/src/m/classes/maskpsl.py =================================================================== --- /issm/trunk-jpl/src/m/classes/maskpsl.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/maskpsl.py (revision 24213) @@ -6,94 +6,98 @@ from WriteData import WriteData + class maskpsl(object): -#MASKPSL class definition -# -# Usage: -# maskpsl=maskpsl(); + #MASKPSL class definition + # + # Usage: + # maskpsl = maskpsl() - def __init__(self,*args): # {{{ - self.groundedice_levelset = float('NaN') - self.ice_levelset = float('NaN') - self.ocean_levelset = float('NaN') - self.land_levelset = float('NaN') + def __init__(self, *args): # {{{ + self.groundedice_levelset = float('NaN') + self.ice_levelset = float('NaN') + self.ocean_levelset = float('NaN') + self.land_levelset = float('NaN') - if not len(args): - self.setdefaultparameters() - else: - raise RuntimeError('constructor not supported') - # }}} - def __repr__(self): # {{{ - string=' masks:' - string="%s\n%s"%(string,fielddisplay(self,'groundedice_levelset','is ice grounded ? grounded ice if > 0, grounding line position if = 0, floating ice if < 0')) - string="%s\n%s"%(string,fielddisplay(self,'ice_levelset','presence of ice if < 0, icefront position if = 0, no ice if > 0')) - string="%s\n%s"%(string,fielddisplay(self,'ocean_levelset','is the vertex on the ocean ? yes if = 1, no if = 0')) - string="%s\n%s"%(string,fielddisplay(self,'land_levelset','is the vertex on the land ? yes if = 1, no if = 0')) - return string + if not len(args): + self.setdefaultparameters() + else: + raise RuntimeError('constructor not supported') + # }}} - # }}} - def loadobj(self): # {{{ - # This def is directly called by matlab when a model object is - # loaded. Update old properties here - #2014 February 5th - if numel(self.ice_levelset)>1 and all(self.ice_levelset>=0): - print('WARNING: md.mask.ice_levelset>=0, you probably need to change the sign of this levelset') - return self - # }}} + def __repr__(self): # {{{ + string = ' masks:' + string = "%s\n%s" % (string, fielddisplay(self, 'groundedice_levelset', 'is ice grounded ? grounded ice if > 0, grounding line position if = 0, floating ice if < 0')) + string = "%s\n%s" % (string, fielddisplay(self, 'ice_levelset', 'presence of ice if < 0, icefront position if = 0, no ice if > 0')) + string = "%s\n%s" % (string, fielddisplay(self, 'ocean_levelset', 'is the vertex on the ocean ? yes if = 1, no if = 0')) + string = "%s\n%s" % (string, fielddisplay(self, 'land_levelset', 'is the vertex on the land ? yes if = 1, no if = 0')) + return string - def setdefaultparameters(self): # {{{ - return self + # }}} - # }}} + def loadobj(self): # {{{ + # This def is directly called by matlab when a model object is + # loaded. Update old properties here + #2014 February 5th + if numel(self.ice_levelset) > 1 and all(self.ice_levelset >= 0): + print('WARNING: md.mask.ice_levelset >= 0, you probably need to change the sign of this levelset') + return self + # }}} - def checkconsistency(self,md,solution,analyses): # {{{ - md = checkfield(md,'fieldname','mask.groundedice_levelset','size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mask.ice_levelset' ,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mask.ocean_levelset','size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mask.land_levelset','size',[md.mesh.numberofvertices]) - isice=(md.mask.ice_levelset<=0) - if sum(isice)==0: - print('no ice present in the domain') + def setdefaultparameters(self): # {{{ + return self - if max(md.mask.ice_levelset)<0: - print('no ice front provided') + # }}} - elements=md.mesh.elements-1; elements=elements.astype(np.int32, copy=False); - icefront=np.sum(md.mask.ice_levelset[elements]==0,axis=1) - if (max(icefront)==3 & m.strcmp(md.mesh.elementtype(),'Tria')) or (max(icefront==6) & m.strcmp(md.mesh.elementtype(),'Penta')): - raise RuntimeError('At least one element has all nodes on ice front, change md.mask.ice_levelset to fix it') + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'mask.groundedice_levelset', 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mask.ice_levelset', 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mask.ocean_levelset', 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mask.land_levelset', 'size', [md.mesh.numberofvertices]) + isice = (md.mask.ice_levelset <= 0) + if sum(isice) == 0: + print('no ice present in the domain') - return md + if max(md.mask.ice_levelset) < 0: + print('no ice front provided') - # }}} + elements = md.mesh.elements - 1 + elements = elements.astype(np.int32, copy=False) + icefront = np.sum(md.mask.ice_levelset[elements] == 0, axis=1) + if (max(icefront) == 3 & m.strcmp(md.mesh.elementtype(), 'Tria')) or (max(icefront == 6) & m.strcmp(md.mesh.elementtype(), 'Penta')): + raise RuntimeError('At least one element has all nodes on ice front, change md.mask.ice_levelset to fix it') - def extrude(self,md): # {{{ - self.groundedice_levelset=project3d(md,'vector',self.groundedice_levelset,'type','node') - self.ice_levelset=project3d(md,'vector',self.ice_levelset,'type','node') - self.ocean_levelset=project3d(md,'vector',self.ocean_levelset,'type','node') - self.land_levelset=project3d(md,'vector',self.land_levelset,'type','node') - return self - # }}} + return md - def mask(*args): # {{{ - if not len(args): - self.setdefaultparameters() - else: - raise RuntimeError('constructor not supported') - return self + # }}} - # }}} + def extrude(self, md): # {{{ + self.groundedice_levelset = project3d(md, 'vector', self.groundedice_levelset, 'type', 'node') + self.ice_levelset = project3d(md, 'vector', self.ice_levelset, 'type', 'node') + self.ocean_levelset = project3d(md, 'vector', self.ocean_levelset, 'type', 'node') + self.land_levelset = project3d(md, 'vector', self.land_levelset, 'type', 'node') + return self + # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.mask.type','data',type(md.mask).__name__,'format','String') - WriteData(fid,prefix,'object',self,'class','mask','fieldname','groundedice_levelset','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mask','fieldname','ice_levelset','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mask','fieldname','ocean_levelset','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mask','fieldname','land_levelset','format','DoubleMat','mattype',1) - # }}} - def savemodeljs(self,fid,modelname): # {{{ - writejs1Darray(fid,[modelname, '.mask.groundedice_levelset'],self.groundedice_levelset) - writejs1Darray(fid,[modelname, '.mask.ice_levelset'],self.ice_levelset) - writejs1Darray(fid,[modelname, '.mask.ocean_levelset'],self.ocean_levelset) - writejs1Darray(fid,[modelname, '.mask.land_levelset'],self.land_levelset) - # }}} + def mask(*args): # {{{ + if not len(args): + self.setdefaultparameters() + else: + raise RuntimeError('constructor not supported') + return self + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.mask.type', 'data', type(md.mask).__name__, 'format', 'String') + WriteData(fid, prefix, 'object', self, 'class', 'mask', 'fieldname', 'groundedice_levelset', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mask', 'fieldname', 'ice_levelset', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mask', 'fieldname', 'ocean_levelset', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mask', 'fieldname', 'land_levelset', 'format', 'DoubleMat', 'mattype', 1) + # }}} + + def savemodeljs(self, fid, modelname): # {{{ + writejs1Darray(fid, [modelname, '.mask.groundedice_levelset'], self.groundedice_levelset) + writejs1Darray(fid, [modelname, '.mask.ice_levelset'], self.ice_levelset) + writejs1Darray(fid, [modelname, '.mask.ocean_levelset'], self.ocean_levelset) + writejs1Darray(fid, [modelname, '.mask.land_levelset'], self.land_levelset) + # }}} Index: /issm/trunk-jpl/src/m/classes/massfluxatgate.py =================================================================== --- /issm/trunk-jpl/src/m/classes/massfluxatgate.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/massfluxatgate.py (revision 24213) @@ -6,73 +6,77 @@ import os + class massfluxatgate(object): - """ - MASSFLUXATEGATE class definition + """ + MASSFLUXATEGATE class definition - Usage: - massfluxatgate=massfluxatgate('GateName','PathToExpFile') - """ + Usage: + massfluxatgate = massfluxatgate('GateName', 'PathToExpFile') + """ - def __init__(self,*args): # {{{ + def __init__(self, *args): # {{{ - self.name = '' - self.definitionstring = '' - self.profilename = '' - self.segments = float('NaN') + self.name = '' + self.definitionstring = '' + self.profilename = '' + self.segments = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #use provided options to change fields - options=pairoptions(*args) + #use provided options to change fields + options = pairoptions(*args) - #OK get other fields - self=options.AssignObjectFields(self) + #OK get other fields + self = options.AssignObjectFields(self) - #}}} - def __repr__(self): # {{{ + #}}} - string=" Massfluxatgate:" - string="%s\n%s"%(string,fielddisplay(self,'name','identifier for this massfluxatgate response')) - string="%s\n%s"%(string,fielddisplay(self,'definitionstring','string that identifies this output definition uniquely, from Outputdefinition[1-100]')) - string="%s\n%s"%(string,fielddisplay(self,'profilename','name of file (shapefile or argus file) defining a profile (or gate)')) - return string - #}}} - def extrude(self,md): # {{{ - return self - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def __repr__(self): # {{{ - if not isinstance(self.name, str): - raise RuntimeError("massfluxatgate error message: 'name' field should be a string!") + string = " Massfluxatgate:" + string = "%s\n%s" % (string, fielddisplay(self, 'name', 'identifier for this massfluxatgate response')) + string = "%s\n%s" % (string, fielddisplay(self, 'definitionstring', 'string that identifies this output definition uniquely, from Outputdefinition[1 - 100]')) + string = "%s\n%s" % (string, fielddisplay(self, 'profilename', 'name of file (shapefile or argus file) defining a profile (or gate)')) + return string + #}}} - if not isinstance(self.profilename, str): - raise RuntimeError("massfluxatgate error message: 'profilename' field should be a string!") + def extrude(self, md): # {{{ + return self + #}}} - OutputdefinitionStringArray=[] - for i in range(1,100): - x='Outputdefinition'+str(i) - OutputdefinitionStringArray.append(x) + def setdefaultparameters(self): # {{{ + return self + #}}} - md = checkfield(md,'field',self.definitionstring,'values',OutputdefinitionStringArray) + def checkconsistency(self, md, solution, analyses): # {{{ + if not isinstance(self.name, str): + raise RuntimeError("massfluxatgate error message: 'name' field should be a string!") - #check the profilename points to a file!: - if not os.path.isfile(self.profilename): - raise RuntimeError("massfluxatgate error message: file name for profile corresponding to gate does not point to a legitimate file on disk!") + if not isinstance(self.profilename, str): + raise RuntimeError("massfluxatgate error message: 'profilename' field should be a string!") - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + OutputdefinitionStringArray = [] + for i in range(1, 100): + x = 'Outputdefinition' + str(i) + OutputdefinitionStringArray.append(x) - #before marshalling, we need to create the segments out of the profilename: - self.segments=MeshProfileIntersection(md.mesh.elements,md.mesh.x,md.mesh.y,self.profilename)[0] + md = checkfield(md, 'field', self.definitionstring, 'values', OutputdefinitionStringArray) - #ok, marshall name and segments: - WriteData(fid,prefix,'data',self.name,'name','md.massfluxatgate.name','format','String'); - WriteData(fid,prefix,'data',self.definitionstring,'name','md.massfluxatgate.definitionstring','format','String'); - WriteData(fid,prefix,'data',self.segments,'name','md.massfluxatgate.segments','format','DoubleMat','mattype',1); + #check the profilename points to a file!: + if not os.path.isfile(self.profilename): + raise RuntimeError("massfluxatgate error message: file name for profile corresponding to gate does not point to a legitimate file on disk!") - # }}} + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + #before marshalling, we need to create the segments out of the profilename: + self.segments = MeshProfileIntersection(md.mesh.elements, md.mesh.x, md.mesh.y, self.profilename)[0] + + #ok, marshall name and segments: + WriteData(fid, prefix, 'data', self.name, 'name', 'md.massfluxatgate.name', 'format', 'String') + WriteData(fid, prefix, 'data', self.definitionstring, 'name', 'md.massfluxatgate.definitionstring', 'format', 'String') + WriteData(fid, prefix, 'data', self.segments, 'name', 'md.massfluxatgate.segments', 'format', 'DoubleMat', 'mattype', 1) + + # }}} Index: /issm/trunk-jpl/src/m/classes/masstransport.py =================================================================== --- /issm/trunk-jpl/src/m/classes/masstransport.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/masstransport.py (revision 24213) @@ -4,97 +4,93 @@ from WriteData import WriteData + class masstransport(object): - """ - MASSTRANSPORT class definition + """ + MASSTRANSPORT class definition - Usage: - masstransport=masstransport(); - """ + Usage: + masstransport = masstransport() + """ - def __init__(self): # {{{ - self.spcthickness = float('NaN') - self.isfreesurface = 0 - self.min_thickness = 0. - self.hydrostatic_adjustment = 0 - self.stabilization = 0 - self.vertex_pairing = float('NaN') - self.penalty_factor = 0 - self.requested_outputs = [] + def __init__(self): # {{{ + self.spcthickness = float('NaN') + self.isfreesurface = 0 + self.min_thickness = 0. + self.hydrostatic_adjustment = 0 + self.stabilization = 0 + self.vertex_pairing = float('NaN') + self.penalty_factor = 0 + self.requested_outputs = [] - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' Masstransport solution parameters:' - string="%s\n%s"%(string,fielddisplay(self,'spcthickness','thickness constraints (NaN means no constraint) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'isfreesurface','do we use free surfaces (FS only) or mass conservation')) - string="%s\n%s"%(string,fielddisplay(self,'min_thickness','minimum ice thickness allowed [m]')) - string="%s\n%s"%(string,fielddisplay(self,'hydrostatic_adjustment','adjustment of ice shelves surface and bed elevations: ''Incremental'' or ''Absolute'' ')) - string="%s\n%s"%(string,fielddisplay(self,'stabilization','0: no, 1: artificial_diffusivity, 2: streamline upwinding, 3: discontinuous Galerkin, 4: Flux Correction Transport')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) + #}}} - return string - #}}} - def extrude(self,md): # {{{ - self.spcthickness=project3d(md,'vector',self.spcthickness,'type','node') - return self - #}}} - def defaultoutputs(self,md): # {{{ + def __repr__(self): # {{{ + string = ' Masstransport solution parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'spcthickness', 'thickness constraints (NaN means no constraint) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'isfreesurface', 'do we use free surfaces (FS only) or mass conservation')) + string = "%s\n%s" % (string, fielddisplay(self, 'min_thickness', 'minimum ice thickness allowed [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'hydrostatic_adjustment', 'adjustment of ice shelves surface and bed elevations: ''Incremental'' or ''Absolute'' ')) + string = "%s\n%s" % (string, fielddisplay(self, 'stabilization', '0: no, 1: artificial_diffusivity, 2: streamline upwinding, 3: discontinuous Galerkin, 4: Flux Correction Transport')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) - return ['Thickness','Surface','Base'] + return string + #}}} - #}}} - def setdefaultparameters(self): # {{{ + def extrude(self, md): # {{{ + self.spcthickness = project3d(md, 'vector', self.spcthickness, 'type', 'node') + return self + #}}} - #Type of stabilization to use 0:nothing 1:artificial_diffusivity 3:Discontinuous Galerkin - self.stabilization=1 + def defaultoutputs(self, md): # {{{ + return ['Thickness', 'Surface', 'Base'] - #Factor applied to compute the penalties kappa=max(stiffness matrix)*10^penalty_factor - self.penalty_factor=3 + #}}} + def setdefaultparameters(self): # {{{ + #Type of stabilization to use 0:nothing 1:artificial_diffusivity 3:Discontinuous Galerkin + self.stabilization = 1 + #Factor applied to compute the penalties kappa = max(stiffness matrix) * 10^penalty_factor + self.penalty_factor = 3 + #Minimum ice thickness that can be used + self.min_thickness = 1 + #Hydrostatic adjustment + self.hydrostatic_adjustment = 'Absolute' + #default output + self.requested_outputs = ['default'] + return self + #}}} - #Minimum ice thickness that can be used - self.min_thickness=1 + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if ('MasstransportAnalysis' not in analyses) or (solution == 'TransientSolution' and not md.transient.ismasstransport): + return md - #Hydrostatic adjustment - self.hydrostatic_adjustment='Absolute' + md = checkfield(md, 'fieldname', 'masstransport.spcthickness', 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'masstransport.isfreesurface', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'masstransport.hydrostatic_adjustment', 'values', ['Absolute', 'Incremental']) + md = checkfield(md, 'fieldname', 'masstransport.stabilization', 'values', [0, 1, 2, 3, 4]) + md = checkfield(md, 'fieldname', 'masstransport.min_thickness', '>', 0) + md = checkfield(md, 'fieldname', 'masstransport.requested_outputs', 'stringrow', 1) - #default output - self.requested_outputs=['default'] - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + return md + # }}} - #Early return - if ('MasstransportAnalysis' not in analyses) or (solution=='TransientSolution' and not md.transient.ismasstransport): - return md + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'spcthickness', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'isfreesurface', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'min_thickness', 'format', 'Double') + WriteData(fid, prefix, 'data', self.hydrostatic_adjustment, 'format', 'String', 'name', 'md.masstransport.hydrostatic_adjustment') + WriteData(fid, prefix, 'object', self, 'fieldname', 'stabilization', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'vertex_pairing', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'fieldname', 'penalty_factor', 'format', 'Double') - md = checkfield(md,'fieldname','masstransport.spcthickness','Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','masstransport.isfreesurface','values',[0,1]) - md = checkfield(md,'fieldname','masstransport.hydrostatic_adjustment','values',['Absolute','Incremental']) - md = checkfield(md,'fieldname','masstransport.stabilization','values',[0,1,2,3,4]) - md = checkfield(md,'fieldname','masstransport.min_thickness','>',0) - md = checkfield(md,'fieldname','masstransport.requested_outputs','stringrow',1) - - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - - yts=md.constants.yts - - WriteData(fid,prefix,'object',self,'fieldname','spcthickness','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','isfreesurface','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','min_thickness','format','Double') - WriteData(fid,prefix,'data',self.hydrostatic_adjustment,'format','String','name','md.masstransport.hydrostatic_adjustment') - WriteData(fid,prefix,'object',self,'fieldname','stabilization','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','vertex_pairing','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'fieldname','penalty_factor','format','Double') - - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.masstransport.requested_outputs','format','StringArray') - # }}} + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.masstransport.requested_outputs', 'format', 'StringArray') + # }}} Index: /issm/trunk-jpl/src/m/classes/matdamageice.py =================================================================== --- /issm/trunk-jpl/src/m/classes/matdamageice.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/matdamageice.py (revision 24213) @@ -4,156 +4,156 @@ from WriteData import WriteData + class matdamageice(object): - """ - MATICE class definition + """ + MATICE class definition - Usage: - matdamagice=matdamageice(); - """ + Usage: + matdamagice = matdamageice() + """ - def __init__(self): # {{{ - self.rho_ice = 0. - self.rho_water = 0. - self.rho_freshwater = 0. - self.mu_water = 0. - self.heatcapacity = 0. - self.latentheat = 0. - self.thermalconductivity = 0. - self.temperateiceconductivity = 0. - self.effectiveconductivity_averaging = 0 - self.meltingpoint = 0. - self.beta = 0. - self.mixed_layer_capacity = 0. - self.thermal_exchange_velocity = 0. - self.rheology_B = float('NaN') - self.rheology_n = float('NaN') - self.rheology_law = '' + def __init__(self): # {{{ + self.rho_ice = 0. + self.rho_water = 0. + self.rho_freshwater = 0. + self.mu_water = 0. + self.heatcapacity = 0. + self.latentheat = 0. + self.thermalconductivity = 0. + self.temperateiceconductivity = 0. + self.effectiveconductivity_averaging = 0 + self.meltingpoint = 0. + self.beta = 0. + self.mixed_layer_capacity = 0. + self.thermal_exchange_velocity = 0. + self.rheology_B = float('NaN') + self.rheology_n = float('NaN') + self.rheology_law = '' - #giaivins: - self.lithosphere_shear_modulus = 0. - self.lithosphere_density = 0. - self.mantle_shear_modulus = 0. - self.mantle_density = 0. + #giaivins: + self.lithosphere_shear_modulus = 0. + self.lithosphere_density = 0. + self.mantle_shear_modulus = 0. + self.mantle_density = 0. - #SLR - self.earth_density= 5512; # average density of the Earth, (kg/m^3) + #SLR + self.earth_density = 5512 # average density of the Earth, (kg / m^3) + self.setdefaultparameters() + #}}} - self.setdefaultparameters() - #}}} + def __repr__(self): # {{{ + string = " Materials:" + string = "%s\n%s" % (string, fielddisplay(self, "rho_ice", "ice density [kg / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "rho_water", "water density [kg / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "rho_freshwater", "fresh water density [kg / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "mu_water", "water viscosity [N s / m^2]")) + string = "%s\n%s" % (string, fielddisplay(self, "heatcapacity", "heat capacity [J / kg / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "thermalconductivity", "ice thermal conductivity [W / m / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "temperateiceconductivity", "temperate ice thermal conductivity [W / m / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "effectiveconductivity_averaging", "computation of effectiveconductivity: (0) arithmetic mean, (1) harmonic mean, (2) geometric mean (default)")) + string = "%s\n%s" % (string, fielddisplay(self, "meltingpoint", "melting point of ice at 1atm in K")) + string = "%s\n%s" % (string, fielddisplay(self, "latentheat", "latent heat of fusion [J / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "beta", "rate of change of melting point with pressure [K / Pa]")) + string = "%s\n%s" % (string, fielddisplay(self, "mixed_layer_capacity", "mixed layer capacity [W / kg / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "thermal_exchange_velocity", "thermal exchange velocity [m / s]")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_B", "flow law parameter [Pa s^(1 / n)]")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_n", "Glen's flow law exponent")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_law", "law for the temperature dependance of the rheology: 'None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius' or 'LliboutryDuval'")) + string = "%s\n%s" % (string, fielddisplay(self, "lithosphere_shear_modulus", "Lithosphere shear modulus [Pa]")) + string = "%s\n%s" % (string, fielddisplay(self, "lithosphere_density", "Lithosphere density [g / cm^ - 3]")) + string = "%s\n%s" % (string, fielddisplay(self, "mantle_shear_modulus", "Mantle shear modulus [Pa]")) + string = "%s\n%s" % (string, fielddisplay(self, "mantle_density", "Mantle density [g / cm^ - 3]")) + string = "%s\n%s" % (string, fielddisplay(self, "earth_density", "Mantle density [kg / m^ - 3]")) + return string + #}}} - def __repr__(self): # {{{ - string=" Materials:" - string="%s\n%s"%(string,fielddisplay(self,"rho_ice","ice density [kg/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"rho_water","water density [kg/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"rho_freshwater","fresh water density [kg/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"mu_water","water viscosity [N s/m^2]")) - string="%s\n%s"%(string,fielddisplay(self,"heatcapacity","heat capacity [J/kg/K]")) - string="%s\n%s"%(string,fielddisplay(self,"thermalconductivity","ice thermal conductivity [W/m/K]")) - string="%s\n%s"%(string,fielddisplay(self,"temperateiceconductivity","temperate ice thermal conductivity [W/m/K]")) - string="%s\n%s"%(string,fielddisplay(self,"effectiveconductivity_averaging","computation of effectiveconductivity: (0) arithmetic mean, (1) harmonic mean, (2) geometric mean (default)")) - string="%s\n%s"%(string,fielddisplay(self,"meltingpoint","melting point of ice at 1atm in K")) - string="%s\n%s"%(string,fielddisplay(self,"latentheat","latent heat of fusion [J/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"beta","rate of change of melting point with pressure [K/Pa]")) - string="%s\n%s"%(string,fielddisplay(self,"mixed_layer_capacity","mixed layer capacity [W/kg/K]")) - string="%s\n%s"%(string,fielddisplay(self,"thermal_exchange_velocity","thermal exchange velocity [m/s]")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_B","flow law parameter [Pa s^(1/n)]")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_n","Glen's flow law exponent")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_law","law for the temperature dependance of the rheology: 'None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius' or 'LliboutryDuval'")) - string="%s\n%s"%(string,fielddisplay(self,"lithosphere_shear_modulus","Lithosphere shear modulus [Pa]")) - string="%s\n%s"%(string,fielddisplay(self,"lithosphere_density","Lithosphere density [g/cm^-3]")) - string="%s\n%s"%(string,fielddisplay(self,"mantle_shear_modulus","Mantle shear modulus [Pa]")) - string="%s\n%s"%(string,fielddisplay(self,"mantle_density","Mantle density [g/cm^-3]")) - string="%s\n%s"%(string,fielddisplay(self,"earth_density","Mantle density [kg/m^-3]")) - return string - #}}} + def extrude(self, md): # {{{ + self.rheology_B = project3d(md, 'vector', self.rheology_B, 'type', 'node') + self.rheology_n = project3d(md, 'vector', self.rheology_n, 'type', 'element') + return self + #}}} - def extrude(self,md): # {{{ - self.rheology_B=project3d(md,'vector',self.rheology_B,'type','node') - self.rheology_n=project3d(md,'vector',self.rheology_n,'type','element') - return self - #}}} + def setdefaultparameters(self): # {{{ + #ice density (kg / m^3) + self.rho_ice = 917. + #ocean water density (kg / m^3) + self.rho_water = 1023. + #fresh water density (kg / m^3) + self.rho_freshwater = 1000. + #water viscosity (N.s / m^2) + self.mu_water = 0.001787 + #ice heat capacity cp (J / kg / K) + self.heatcapacity = 2093. + #ice latent heat of fusion L (J / kg) + self.latentheat = 3.34 * 1.0e5 + #ice thermal conductivity (W / m / K) + self.thermalconductivity = 2.4 + #temperate ice thermal conductivity (W / m / K) + self.temperateiceconductivity = 0.24 + #computation of effective conductivity + self.effectiveconductivity_averaging = 1 + #the melting point of ice at 1 atmosphere of pressure in K + self.meltingpoint = 273.15 + #rate of change of melting point with pressure (K / Pa) + self.beta = 9.8 * 1.0e-8 + #mixed layer (ice-water interface) heat capacity (J / kg / K) + self.mixed_layer_capacity = 3974. + #thermal exchange velocity (ice-water interface) (m / s) + self.thermal_exchange_velocity = 1.00 * 1.0e-4 + #Rheology law: what is the temperature dependence of B with T + #available: none, paterson and arrhenius + self.rheology_law = 'Paterson' - def setdefaultparameters(self): # {{{ - #ice density (kg/m^3) - self.rho_ice=917. - #ocean water density (kg/m^3) - self.rho_water=1023. - #fresh water density (kg/m^3) - self.rho_freshwater=1000. - #water viscosity (N.s/m^2) - self.mu_water=0.001787 - #ice heat capacity cp (J/kg/K) - self.heatcapacity=2093. - #ice latent heat of fusion L (J/kg) - self.latentheat=3.34*10**5 - #ice thermal conductivity (W/m/K) - self.thermalconductivity=2.4 - #temperate ice thermal conductivity (W/m/K) - self.temperateiceconductivity=0.24 - #computation of effective conductivity - self.effectiveconductivity_averaging=1 - #the melting point of ice at 1 atmosphere of pressure in K - self.meltingpoint=273.15 - #rate of change of melting point with pressure (K/Pa) - self.beta=9.8*10**-8 - #mixed layer (ice-water interface) heat capacity (J/kg/K) - self.mixed_layer_capacity=3974. - #thermal exchange velocity (ice-water interface) (m/s) - self.thermal_exchange_velocity=1.00*10**-4 - #Rheology law: what is the temperature dependence of B with T - #available: none, paterson and arrhenius - self.rheology_law='Paterson' + # GIA: + self.lithosphere_shear_modulus = 6.7 * 1.0e10 # (Pa) + self.lithosphere_density = 3.32 # (g / cm^ - 3) + self.mantle_shear_modulus = 1.45 * 1.0e11 # (Pa) + self.mantle_density = 3.34 # (g / cm^ - 3) - # GIA: - self.lithosphere_shear_modulus = 6.7*10**10 # (Pa) - self.lithosphere_density = 3.32 # (g/cm^-3) - self.mantle_shear_modulus = 1.45*10**11 # (Pa) - self.mantle_density = 3.34 # (g/cm^-3) + #SLR + self.earth_density = 5512 #average density of the Earth, (kg / m^3) + return self + #}}} - #SLR - self.earth_density= 5512; #average density of the Earth, (kg/m^3) - return self - #}}} + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'materials.rho_ice', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rho_water', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rho_freshwater', '>', 0) + md = checkfield(md, 'fieldname', 'materials.mu_water', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rheology_B', '>', 0, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'materials.rheology_n', '>', 0, 'size', [md.mesh.numberofelements]) + md = checkfield(md, 'fieldname', 'materials.rheology_law', 'values', ['None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius', 'LliboutryDuval']) + md = checkfield(md, 'fieldname', 'materials.effectiveconductivity_averaging', 'numel', [1], 'values', [0, 1, 2]) + md = checkfield(md, 'fieldname', 'materials.lithosphere_shear_modulus', '>', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'materials.lithosphere_density', '>', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'materials.mantle_shear_modulus', '>', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'materials.mantle_density', '>', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'materials.earth_density', '>', 0, 'numel', [1]) + return md + # }}} - def checkconsistency(self,md,solution,analyses): # {{{ - md = checkfield(md,'fieldname','materials.rho_ice','>',0) - md = checkfield(md,'fieldname','materials.rho_water','>',0) - md = checkfield(md,'fieldname','materials.rho_freshwater','>',0) - md = checkfield(md,'fieldname','materials.mu_water','>',0) - md = checkfield(md,'fieldname','materials.rheology_B','>',0,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','materials.rheology_n','>',0,'size',[md.mesh.numberofelements]) - md = checkfield(md,'fieldname','materials.rheology_law','values',['None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson','Arrhenius','LliboutryDuval']) - md = checkfield(md,'fieldname','materials.effectiveconductivity_averaging','numel',[1],'values',[0,1,2]) - md = checkfield(md,'fieldname','materials.lithosphere_shear_modulus','>',0,'numel',[1]); - md = checkfield(md,'fieldname','materials.lithosphere_density','>',0,'numel',[1]); - md = checkfield(md,'fieldname','materials.mantle_shear_modulus','>',0,'numel',[1]); - md = checkfield(md,'fieldname','materials.mantle_density','>',0,'numel',[1]); - md = checkfield(md,'fieldname','materials.earth_density','>',0,'numel',[1]); - return md - # }}} + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.materials.type', 'data', 1, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_ice', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_water', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_freshwater', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mu_water', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'heatcapacity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'latentheat', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'thermalconductivity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'temperateiceconductivity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'effectiveconductivity_averaging', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'meltingpoint', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'beta', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mixed_layer_capacity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'thermal_exchange_velocity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rheology_B', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rheology_n', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'data', self.rheology_law, 'name', 'md.materials.rheology_law', 'format', 'String') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'lithosphere_shear_modulus', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'lithosphere_density', 'format', 'Double', 'scale', 10.**3.) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mantle_shear_modulus', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mantle_density', 'format', 'Double', 'scale', 10.**3.) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'earth_density', 'format', 'Double') - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.materials.type','data',1,'format','Integer'); - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_ice','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_water','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_freshwater','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mu_water','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','heatcapacity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','latentheat','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','thermalconductivity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','temperateiceconductivity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','effectiveconductivity_averaging','format','Integer') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','meltingpoint','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','beta','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mixed_layer_capacity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','thermal_exchange_velocity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rheology_B','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rheology_n','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'data',self.rheology_law,'name','md.materials.rheology_law','format','String') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','lithosphere_shear_modulus','format','Double'); - WriteData(fid,prefix,'object',self,'class','materials','fieldname','lithosphere_density','format','Double','scale',10.**3.); - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mantle_shear_modulus','format','Double'); - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mantle_density','format','Double','scale',10.**3.); - WriteData(fid,prefix,'object',self,'class','materials','fieldname','earth_density','format','Double'); - - # }}} + # }}} Index: /issm/trunk-jpl/src/m/classes/matenhancedice.py =================================================================== --- /issm/trunk-jpl/src/m/classes/matenhancedice.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/matenhancedice.py (revision 24213) @@ -4,164 +4,164 @@ from WriteData import WriteData + class matenhancedice(object): - """ - MATICE class definition + """ + MATICE class definition - Usage: - matenhancedice=matenhancedice(); - """ + Usage: + matenhancedice = matenhancedice() + """ - def __init__(self): # {{{ - self.rho_ice = 0. - self.rho_water = 0. - self.rho_freshwater = 0. - self.mu_water = 0. - self.heatcapacity = 0. - self.latentheat = 0. - self.thermalconductivity = 0. - self.temperateiceconductivity = 0. - self.effectiveconductivity_averaging = 0 - self.meltingpoint = 0. - self.beta = 0. - self.mixed_layer_capacity = 0. - self.thermal_exchange_velocity = 0. - self.rheology_E = float('NaN') - self.rheology_B = float('NaN') - self.rheology_n = float('NaN') - self.rheology_law = '' + def __init__(self): # {{{ + self.rho_ice = 0. + self.rho_water = 0. + self.rho_freshwater = 0. + self.mu_water = 0. + self.heatcapacity = 0. + self.latentheat = 0. + self.thermalconductivity = 0. + self.temperateiceconductivity = 0. + self.effectiveconductivity_averaging = 0 + self.meltingpoint = 0. + self.beta = 0. + self.mixed_layer_capacity = 0. + self.thermal_exchange_velocity = 0. + self.rheology_E = float('NaN') + self.rheology_B = float('NaN') + self.rheology_n = float('NaN') + self.rheology_law = '' - #giaivins: - self.lithosphere_shear_modulus = 0. - self.lithosphere_density = 0. - self.mantle_shear_modulus = 0. - self.mantle_density = 0. + #giaivins: + self.lithosphere_shear_modulus = 0. + self.lithosphere_density = 0. + self.mantle_shear_modulus = 0. + self.mantle_density = 0. - #SLR - self.earth_density= 0 # average density of the Earth, (kg/m^3) + #SLR + self.earth_density = 0 # average density of the Earth, (kg / m^3) + self.setdefaultparameters() + #}}} - self.setdefaultparameters() - #}}} + def __repr__(self): # {{{ + string = " Materials:" + string = "%s\n%s" % (string, fielddisplay(self, "rho_ice", "ice density [kg / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "rho_water", "water density [kg / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "rho_freshwater", "fresh water density [kg / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "mu_water", "water viscosity [N s / m^2]")) + string = "%s\n%s" % (string, fielddisplay(self, "heatcapacity", "heat capacity [J / kg / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "thermalconductivity", "ice thermal conductivity [W / m / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "temperateiceconductivity", "temperate ice thermal conductivity [W / m / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "effectiveconductivity_averaging", "computation of effectiveconductivity: (0) arithmetic mean, (1) harmonic mean, (2) geometric mean (default)")) + string = "%s\n%s" % (string, fielddisplay(self, "meltingpoint", "melting point of ice at 1atm in K")) + string = "%s\n%s" % (string, fielddisplay(self, "latentheat", "latent heat of fusion [J / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "beta", "rate of change of melting point with pressure [K / Pa]")) + string = "%s\n%s" % (string, fielddisplay(self, "mixed_layer_capacity", "mixed layer capacity [W / kg / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "thermal_exchange_velocity", "thermal exchange velocity [m / s]")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_E", "enhancement factor")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_B", "flow law parameter [Pa s^(1 / n)]")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_n", "Glen's flow law exponent")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_law", "law for the temperature dependance of the rheology: 'None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius' or 'LliboutryDuval'")) + string = "%s\n%s" % (string, fielddisplay(self, "lithosphere_shear_modulus", "Lithosphere shear modulus [Pa]")) + string = "%s\n%s" % (string, fielddisplay(self, "lithosphere_density", "Lithosphere density [g / cm^ - 3]")) + string = "%s\n%s" % (string, fielddisplay(self, "mantle_shear_modulus", "Mantle shear modulus [Pa]")) + string = "%s\n%s" % (string, fielddisplay(self, "mantle_density", "Mantle density [g / cm^ - 3]")) + string = "%s\n%s" % (string, fielddisplay(self, "earth_density", "Mantle density [kg / m^ - 3]")) + return string + #}}} - def __repr__(self): # {{{ - string=" Materials:" - string="%s\n%s"%(string,fielddisplay(self,"rho_ice","ice density [kg/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"rho_water","water density [kg/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"rho_freshwater","fresh water density [kg/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"mu_water","water viscosity [N s/m^2]")) - string="%s\n%s"%(string,fielddisplay(self,"heatcapacity","heat capacity [J/kg/K]")) - string="%s\n%s"%(string,fielddisplay(self,"thermalconductivity","ice thermal conductivity [W/m/K]")) - string="%s\n%s"%(string,fielddisplay(self,"temperateiceconductivity","temperate ice thermal conductivity [W/m/K]")) - string="%s\n%s"%(string,fielddisplay(self,"effectiveconductivity_averaging","computation of effectiveconductivity: (0) arithmetic mean, (1) harmonic mean, (2) geometric mean (default)")) - string="%s\n%s"%(string,fielddisplay(self,"meltingpoint","melting point of ice at 1atm in K")) - string="%s\n%s"%(string,fielddisplay(self,"latentheat","latent heat of fusion [J/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"beta","rate of change of melting point with pressure [K/Pa]")) - string="%s\n%s"%(string,fielddisplay(self,"mixed_layer_capacity","mixed layer capacity [W/kg/K]")) - string="%s\n%s"%(string,fielddisplay(self,"thermal_exchange_velocity","thermal exchange velocity [m/s]")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_E","enhancement factor")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_B","flow law parameter [Pa s^(1/n)]")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_n","Glen's flow law exponent")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_law","law for the temperature dependance of the rheology: 'None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius' or 'LliboutryDuval'")) - string="%s\n%s"%(string,fielddisplay(self,"lithosphere_shear_modulus","Lithosphere shear modulus [Pa]")) - string="%s\n%s"%(string,fielddisplay(self,"lithosphere_density","Lithosphere density [g/cm^-3]")) - string="%s\n%s"%(string,fielddisplay(self,"mantle_shear_modulus","Mantle shear modulus [Pa]")) - string="%s\n%s"%(string,fielddisplay(self,"mantle_density","Mantle density [g/cm^-3]")) - string="%s\n%s"%(string,fielddisplay(self,"earth_density","Mantle density [kg/m^-3]")) - return string - #}}} + def extrude(self, md): # {{{ + self.rheology_E = project3d(md, 'vector', self.rheology_E, 'type', 'node') + self.rheology_B = project3d(md, 'vector', self.rheology_B, 'type', 'node') + self.rheology_n = project3d(md, 'vector', self.rheology_n, 'type', 'element') + return self + #}}} - def extrude(self,md): # {{{ - self.rheology_E=project3d(md,'vector',self.rheology_E,'type','node') - self.rheology_B=project3d(md,'vector',self.rheology_B,'type','node') - self.rheology_n=project3d(md,'vector',self.rheology_n,'type','element') - return self - #}}} + def setdefaultparameters(self): # {{{ + #ice density (kg / m^3) + self.rho_ice = 917. + #ocean water density (kg / m^3) + self.rho_water = 1023. + #fresh water density (kg / m^3) + self.rho_freshwater = 1000. + #water viscosity (N.s / m^2) + self.mu_water = 0.001787 + #ice heat capacity cp (J / kg / K) + self.heatcapacity = 2093. + #ice latent heat of fusion L (J / kg) + self.latentheat = 3.34 * 10**5 + #ice thermal conductivity (W / m / K) + self.thermalconductivity = 2.4 + #temperate ice thermal conductivity (W / m / K) + self.temperateiceconductivity = 0.24 + #computation of effective conductivity + self.effectiveconductivity_averaging = 1 + #the melting point of ice at 1 atmosphere of pressure in K + self.meltingpoint = 273.15 + #rate of change of melting point with pressure (K / Pa) + self.beta = 9.8 * 10**- 8 + #mixed layer (ice-water interface) heat capacity (J / kg / K) + self.mixed_layer_capacity = 3974. + #thermal exchange velocity (ice-water interface) (m / s) + self.thermal_exchange_velocity = 1.00 * 10**- 4 + #Rheology law: what is the temperature dependence of B with T + #available: none, paterson and arrhenius + self.rheology_law = 'Paterson' - def setdefaultparameters(self): # {{{ - #ice density (kg/m^3) - self.rho_ice=917. - #ocean water density (kg/m^3) - self.rho_water=1023. - #fresh water density (kg/m^3) - self.rho_freshwater=1000. - #water viscosity (N.s/m^2) - self.mu_water=0.001787 - #ice heat capacity cp (J/kg/K) - self.heatcapacity=2093. - #ice latent heat of fusion L (J/kg) - self.latentheat=3.34*10**5 - #ice thermal conductivity (W/m/K) - self.thermalconductivity=2.4 - #temperate ice thermal conductivity (W/m/K) - self.temperateiceconductivity=0.24 - #computation of effective conductivity - self.effectiveconductivity_averaging=1 - #the melting point of ice at 1 atmosphere of pressure in K - self.meltingpoint=273.15 - #rate of change of melting point with pressure (K/Pa) - self.beta=9.8*10**-8 - #mixed layer (ice-water interface) heat capacity (J/kg/K) - self.mixed_layer_capacity=3974. - #thermal exchange velocity (ice-water interface) (m/s) - self.thermal_exchange_velocity=1.00*10**-4 - #Rheology law: what is the temperature dependence of B with T - #available: none, paterson and arrhenius - self.rheology_law='Paterson' + # GIA: + self.lithosphere_shear_modulus = 6.7 * 10**10 # (Pa) + self.lithosphere_density = 3.32 # (g / cm^ - 3) + self.mantle_shear_modulus = 1.45 * 10**11 # (Pa) + self.mantle_density = 3.34 # (g / cm^ - 3) - # GIA: - self.lithosphere_shear_modulus = 6.7*10**10 # (Pa) - self.lithosphere_density = 3.32 # (g/cm^-3) - self.mantle_shear_modulus = 1.45*10**11 # (Pa) - self.mantle_density = 3.34 # (g/cm^-3) + #SLR + self.earth_density = 5512 #average density of the Earth, (kg / m^3) - #SLR - self.earth_density= 5512 #average density of the Earth, (kg/m^3) + return self + #}}} - return self - #}}} + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'materials.rho_ice', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rho_water', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rho_freshwater', '>', 0) + md = checkfield(md, 'fieldname', 'materials.mu_water', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rheology_E', '>', 0, 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'materials.rheology_B', '>', 0, 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'materials.rheology_n', '>', 0, 'size', [md.mesh.numberofelements]) + md = checkfield(md, 'fieldname', 'materials.rheology_law', 'values', ['None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius', 'LliboutryDuval']) + md = checkfield(md, 'fieldname', 'materials.effectiveconductivity_averaging', 'numel', [1], 'values', [0, 1, 2]) - def checkconsistency(self,md,solution,analyses): # {{{ - md = checkfield(md,'fieldname','materials.rho_ice','>',0) - md = checkfield(md,'fieldname','materials.rho_water','>',0) - md = checkfield(md,'fieldname','materials.rho_freshwater','>',0) - md = checkfield(md,'fieldname','materials.mu_water','>',0) - md = checkfield(md,'fieldname','materials.rheology_E','>',0,'timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','materials.rheology_B','>',0,'timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','materials.rheology_n','>',0,'size',[md.mesh.numberofelements]) - md = checkfield(md,'fieldname','materials.rheology_law','values',['None','BuddJacka','Cuffey','CuffeyTemperate','Paterson','Arrhenius','LliboutryDuval']) - md = checkfield(md,'fieldname','materials.effectiveconductivity_averaging','numel',[1],'values',[0,1,2]) + if 'GiaAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'materials.lithosphere_shear_modulus', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'materials.lithosphere_density', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'materials.mantle_shear_modulus', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'materials.mantle_density', '>', 0, 'numel', 1) + if 'SealevelriseAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'materials.earth_density', '>', 0, 'numel', 1) + return md + # }}} - if 'GiaAnalysis' in analyses: - md = checkfield(md,'fieldname','materials.lithosphere_shear_modulus','>',0,'numel',1) - md = checkfield(md,'fieldname','materials.lithosphere_density','>',0,'numel',1) - md = checkfield(md,'fieldname','materials.mantle_shear_modulus','>',0,'numel',1) - md = checkfield(md,'fieldname','materials.mantle_density','>',0,'numel',1) - if 'SealevelriseAnalysis' in analyses: - md = checkfield(md,'fieldname','materials.earth_density','>',0,'numel',1) - return md - # }}} - - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.materials.type','data',4,'format','Integer') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_ice','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_water','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_freshwater','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mu_water','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','heatcapacity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','latentheat','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','thermalconductivity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','temperateiceconductivity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','effectiveconductivity_averaging','format','Integer') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','meltingpoint','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','beta','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mixed_layer_capacity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','thermal_exchange_velocity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rheology_E','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rheology_B','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rheology_n','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'data',self.rheology_law,'name','md.materials.rheology_law','format','String') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','lithosphere_shear_modulus','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','lithosphere_density','format','Double','scale',10^3) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mantle_shear_modulus','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mantle_density','format','Double','scale',10^3) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','earth_density','format','Double') - # }}} + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.materials.type', 'data', 4, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_ice', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_water', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_freshwater', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mu_water', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'heatcapacity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'latentheat', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'thermalconductivity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'temperateiceconductivity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'effectiveconductivity_averaging', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'meltingpoint', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'beta', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mixed_layer_capacity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'thermal_exchange_velocity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rheology_E', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rheology_B', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rheology_n', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'data', self.rheology_law, 'name', 'md.materials.rheology_law', 'format', 'String') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'lithosphere_shear_modulus', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'lithosphere_density', 'format', 'Double', 'scale', 10**3) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mantle_shear_modulus', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mantle_density', 'format', 'Double', 'scale', 10**3) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'earth_density', 'format', 'Double') + # }}} Index: /issm/trunk-jpl/src/m/classes/materials.py =================================================================== --- /issm/trunk-jpl/src/m/classes/materials.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/materials.py (revision 24213) @@ -5,263 +5,266 @@ from WriteData import WriteData -def naturetointeger(strnat): #{{{ - - intnat=np.zeros(len(strnat)) - for i in range(len(intnat)): - if strnat[i]=='damageice': - intnat[i]=1 - elif strnat[i]=='estar': - intnat[i]=2 - elif strnat[i]=='ice': - intnat[i]=3 - elif strnat[i]=='enhancedice': - intnat[i]=4 - elif strnat[i]=='litho': - intnat[i]=5 - else: - raise RuntimeError("materials constructor error message: nature of the material not supported yet! (''ice'' or ''litho'')"); - - return intnat -# }}} + +def naturetointeger(strnat): #{{{ + + intnat = np.zeros(len(strnat)) + for i in range(len(intnat)): + if strnat[i] == 'damageice': + intnat[i] = 1 + elif strnat[i] == 'estar': + intnat[i] = 2 + elif strnat[i] == 'ice': + intnat[i] = 3 + elif strnat[i] == 'enhancedice': + intnat[i] = 4 + elif strnat[i] == 'litho': + intnat[i] = 5 + else: + raise RuntimeError("materials constructor error message: nature of the material not supported yet! (''ice'' or ''litho'')") + + return intnat + # }}} + class materials(object): - """ - MATERIALS class definition - - Usage: - materials=materials(); - """ - - def __init__(self,*args): # {{{ - self.nature = [] - if not len(args): - self.nature=['ice'] - else: - self.nature=args - - for i in range(len(self.nature)): - if not(self.nature[i] == 'litho' or self.nature[i]=='ice'): - raise RuntimeError("materials constructor error message: nature of the material not supported yet! ('ice' or 'litho')") - - #start filling in the dynamic fields: - for i in range(len(self.nature)): - nat=self.nature[i]; - if nat=='ice': - setattr(self,'rho_ice',0) - setattr(self,'rho_ice',0); - setattr(self,'rho_water',0); - setattr(self,'rho_freshwater',0); - setattr(self,'mu_water',0); - setattr(self,'heatcapacity',0); - setattr(self,'latentheat',0); - setattr(self,'thermalconductivity',0); - setattr(self,'temperateiceconductivity',0); - setattr(self,'meltingpoint',0); - setattr(self,'beta',0); - setattr(self,'mixed_layer_capacity',0); - setattr(self,'thermal_exchange_velocity',0); - setattr(self,'rheology_B',0); - setattr(self,'rheology_n',0); - setattr(self,'rheology_law',0); - elif nat=='litho': - setattr(self,'numlayers',0); - setattr(self,'radius',0); - setattr(self,'viscosity',0); - setattr(self,'lame_lambda',0); - setattr(self,'lame_mu',0); - setattr(self,'burgers_viscosity',0); - setattr(self,'burgers_mu',0); - setattr(self,'isburgers',0); - setattr(self,'density',0); - setattr(self,'issolid',0); - else: - raise RuntimeError("materials constructor error message: nature of the material not supported yet! ('ice' or 'litho')"); - #set default parameters: - self.setdefaultparameters() - #}}} - - def __repr__(self): # {{{ - string=" Materials:" - for i in range(len(self.nature)): - nat=self.nature[i]; - if nat=='ice': - string="%s\n%s"%(string,'Ice:'); - string="%s\n%s"%(string,fielddisplay(self,"rho_ice","ice density [kg/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"rho_water","water density [kg/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"rho_freshwater","fresh water density [kg/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"mu_water","water viscosity [N s/m^2]")) - string="%s\n%s"%(string,fielddisplay(self,"heatcapacity","heat capacity [J/kg/K]")) - string="%s\n%s"%(string,fielddisplay(self,"thermalconductivity","ice thermal conductivity [W/m/K]")) - string="%s\n%s"%(string,fielddisplay(self,"temperateiceconductivity","temperate ice thermal conductivity [W/m/K]")) - string="%s\n%s"%(string,fielddisplay(self,"meltingpoint","melting point of ice at 1atm in K")) - string="%s\n%s"%(string,fielddisplay(self,"latentheat","latent heat of fusion [J/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"beta","rate of change of melting point with pressure [K/Pa]")) - string="%s\n%s"%(string,fielddisplay(self,"mixed_layer_capacity","mixed layer capacity [W/kg/K]")) - string="%s\n%s"%(string,fielddisplay(self,"thermal_exchange_velocity","thermal exchange velocity [m/s]")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_B","flow law parameter [Pa s^(1/n)]")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_n","Glen's flow law exponent")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_law","law for the temperature dependance of the rheology: 'None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius', 'LliboutryDuval', 'NyeCO2', or 'NyeH2O'")) - elif nat=='litho': - string="%s\n%s"%(string,'Litho:'); - string="%s\n%s"%(string,fielddisplay(self,'numlayers','number of layers (default 2)')) - string="%s\n%s"%(string,fielddisplay(self,'radius','array describing the radius for each interface (numlayers+1) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'viscosity','array describing each layer''s viscosity (numlayers) [Pa.s]')) - string="%s\n%s"%(string,fielddisplay(self,'lame_lambda','array describing the lame lambda parameter (numlayers) [Pa]')) - string="%s\n%s"%(string,fielddisplay(self,'lame_mu','array describing the shear modulus for each layers (numlayers) [Pa]')) - string="%s\n%s"%(string,fielddisplay(self,'burgers_viscosity','array describing each layer''s transient viscosity, only for Burgers rheologies (numlayers) [Pa.s]')) - string="%s\n%s"%(string,fielddisplay(self,'burgers_mu','array describing each layer''s transient shear modulus, only for Burgers rheologies (numlayers) [Pa]')) - string="%s\n%s"%(string,fielddisplay(self,'isburgers','array describing whether we adopt a MaxWell (0) or Burgers (1) rheology (default 0)')) - string="%s\n%s"%(string,fielddisplay(self,'density','array describing each layer''s density (numlayers) [kg/m^3]')) - string="%s\n%s"%(string,fielddisplay(self,'issolid','array describing whether the layer is solid or liquid (default 1) (numlayers)')) - - else: - raise RuntimeError("materials constructor error message: nature of the material not supported yet! ('ice' or 'litho')"); - - return string - #}}} - - def extrude(self,md): # {{{ - for i in range(len(self.nature)): - nat=self.nature[i]; - if nat=='ice': - self.rheology_B=project3d(md,'vector',self.rheology_B,'type','node') - self.rheology_n=project3d(md,'vector',self.rheology_n,'type','element') - return self - #}}} - - def setdefaultparameters(self): # {{{ - for i in range(len(self.nature)): - nat=self.nature[i]; - if nat=='ice': - #ice density (kg/m^3) - self.rho_ice=917. - #ocean water density (kg/m^3) - self.rho_water=1023. - #fresh water density (kg/m^3) - self.rho_freshwater=1000. - #water viscosity (N.s/m^2) - self.mu_water=0.001787 - #ice heat capacity cp (J/kg/K) - self.heatcapacity=2093. - #ice latent heat of fusion L (J/kg) - self.latentheat=3.34*10^5 - #ice thermal conductivity (W/m/K) - self.thermalconductivity=2.4 - #wet ice thermal conductivity (W/m/K) - self.temperateiceconductivity=.24 - #the melting point of ice at 1 atmosphere of pressure in K - self.meltingpoint=273.15 - #rate of change of melting point with pressure (K/Pa) - self.beta=9.8*10^-8 - #mixed layer (ice-water interface) heat capacity (J/kg/K) - self.mixed_layer_capacity=3974. - #thermal exchange velocity (ice-water interface) (m/s) - self.thermal_exchange_velocity=1.00*10^-4 - #Rheology law: what is the temperature dependence of B with T - #available: none, paterson and arrhenius - self.rheology_law='Paterson' - - elif nat=='litho': - #we default to a configuration that enables running GIA solutions using giacaron and/or giaivins. - self.numlayers=2 - #center of the earth (approximation, must not be 0), then the lab (lithosphere/asthenosphere boundary) then the surface - #(with 1d3 to avoid numerical singularities) - self.radius=[1e3,6278*1e3,6378*1e3] - self.viscosity=[1e21,1e40] #mantle and lithosphere viscosity (respectively) [Pa.s] - self.lame_mu=[1.45*1e11,6.7*1e10] # (Pa) #lithosphere and mantle shear modulus (respectively) [Pa] - self.lame_lambda=self.lame_mu # (Pa) #mantle and lithosphere lamba parameter (respectively) [Pa] - self.burgers_viscosity=[np.nan,np.nan] - self.burgers_mu=[np.nan,np.nan] - self.isburgers=[0,0] - self.density=[5.51*1e3,5.50*1e3] # (Pa) #mantle and lithosphere density [kg/m^3] - self.issolid=[1,1] # is layer solid or liquid. - - else: - raise RuntimeError("materials setdefaultparameters error message: nature of the material not supported yet! ('ice' or 'litho')"); - - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - for i in range(len(self.nature)): - nat=self.nature[i]; - if nat=='ice': - md = checkfield(md,'fieldname','materials.rho_ice','>',0) - md = checkfield(md,'fieldname','materials.rho_water','>',0) - md = checkfield(md,'fieldname','materials.rho_freshwater','>',0) - md = checkfield(md,'fieldname','materials.mu_water','>',0) - md = checkfield(md,'fieldname','materials.rheology_B','>',0,'timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','materials.rheology_n','>',0,'size',[md.mesh.numberofelements]) - md = checkfield(md,'fieldname','materials.rheology_law','values',['None','BuddJacka','Cuffey','CuffeyTemperate','Paterson','Arrhenius','LliboutryDuval','NyeCO2','NyeH2O']) - - elif nat=='litho': - if 'LoveAnalysis' not in analyses: - return md - - md = checkfield(md,'fieldname','materials.numlayers','NaN',1,'Inf',1,'>',0,'numel',[1]) - md = checkfield(md,'fieldname','materials.radius','NaN',1,'Inf',1,'size',[md.materials.numlayers+1,1],'>',0) - md = checkfield(md,'fieldname','materials.lame_mu','NaN',1,'Inf',1,'size',[md.materials.numlayers,1],'>=',0) - md = checkfield(md,'fieldname','materials.lame_lambda','NaN',1,'Inf',1,'size',[md.materials.numlayers,1],'>=',0) - md = checkfield(md,'fieldname','materials.issolid','NaN',1,'Inf',1,'size',[md.materials.numlayers,1],'>=',0,'<',2) - md = checkfield(md,'fieldname','materials.density','NaN',1,'Inf',1,'size',[md.materials.numlayers,1],'>',0) - md = checkfield(md,'fieldname','materials.viscosity','NaN',1,'Inf',1,'size',[md.materials.numlayers,1],'>=',0) - md = checkfield(md,'fieldname','materials.isburgers','NaN',1,'Inf',1,'size',[md.materials.numlayers,1],'>=',0,'<=',1) - md = checkfield(md,'fieldname','materials.burgers_viscosity','Inf',1,'size',[md.materials.numlayers,1],'>=',0) - md = checkfield(md,'fieldname','materials.burgers_mu','Inf',1,'size',[md.materials.numlayers,1],'>=',0) - - for i in range(md.materials.numlayers): - if md.materials.isburgers[i] and (np.isnan(md.materials.burgers_viscosity[i] or np.isnan(md.materials.burgers_mu[i]))): - raise RuntimeError("materials checkconsistency error message: Litho burgers_viscosity or burgers_mu has NaN values, inconsistent with isburgers choice") - - if md.materials.issolid[0]==0 or md.materials.lame_mu[0]==0: - raise RuntimeError('First layer must be solid (issolid(1) > 0 AND lame_mu(1) > 0). Add a weak inner core if necessary.') - - for i in range(md.materials.numlayers-1): - if (not md.materials.issolid[i]) and (not md.materials.issolid[i+1]): #if there are at least two consecutive indices that contain issolid = 0 - raise RuntimeError("%s%i%s"%('2 or more adjacent fluid layers detected starting at layer ',i,'. This is not supported yet. Consider merging them.')) - - else: - raise RuntimeError("materials checkconsistency error message: nature of the material not supported yet! ('ice' or 'litho')"); - - return md - # }}} - - def marshall(self,prefix,md,fid): # {{{ - #1: MatdamageiceEnum 2: MatestarEnum 3: MaticeEnum 4: MatenhancediceEnum 5: MaterialsEnum - WriteData(fid,prefix,'name','md.materials.type','data',6,'format','Integer') - WriteData(fid,prefix,'name','md.materials.nature','data',naturetointeger(self.nature),'format','IntMat','mattype',3) - - for i in range(len(self.nature)): - nat=self.nature[i]; - if nat=='ice': - WriteData(fid,prefix,'name','md.materials.type','data',3,'format','Integer') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_ice','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_water','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_freshwater','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mu_water','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','heatcapacity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','latentheat','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','thermalconductivity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','temperateiceconductivity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','meltingpoint','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','beta','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mixed_layer_capacity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','thermal_exchange_velocity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rheology_B','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rheology_n','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'data',self.rheology_law,'name','md.materials.rheology_law','format','String') - - elif nat=='litho': - WriteData(fid,prefix,'object',self,'class','materials','fieldname','numlayers','format','Integer') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','radius','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','lame_mu','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','lame_lambda','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','issolid','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','density','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','viscosity','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','isburgers','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','burgers_viscosity','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','burgers_mu','format','DoubleMat','mattype',3) - - else: - raise RuntimeError("materials constructor error message: nature of the material not supported yet! (''ice'' or ''litho'')") - # }}} + """ + MATERIALS class definition + + Usage: + materials = materials() + """ + + def __init__(self, *args): # {{{ + self.nature = [] + if not len(args): + self.nature = ['ice'] + else: + self.nature = args + + for i in range(len(self.nature)): + if not(self.nature[i] == 'litho' or self.nature[i] == 'ice'): + raise RuntimeError("materials constructor error message: nature of the material not supported yet! ('ice' or 'litho')") + + #start filling in the dynamic fields: + for i in range(len(self.nature)): + nat = self.nature[i] + if nat == 'ice': + setattr(self, 'rho_ice', 0) + setattr(self, 'rho_ice', 0) + setattr(self, 'rho_water', 0) + setattr(self, 'rho_freshwater', 0) + setattr(self, 'mu_water', 0) + setattr(self, 'heatcapacity', 0) + setattr(self, 'latentheat', 0) + setattr(self, 'thermalconductivity', 0) + setattr(self, 'temperateiceconductivity', 0) + setattr(self, 'meltingpoint', 0) + setattr(self, 'beta', 0) + setattr(self, 'mixed_layer_capacity', 0) + setattr(self, 'thermal_exchange_velocity', 0) + setattr(self, 'rheology_B', 0) + setattr(self, 'rheology_n', 0) + setattr(self, 'rheology_law', 0) + elif nat == 'litho': + setattr(self, 'numlayers', 0) + setattr(self, 'radius', 0) + setattr(self, 'viscosity', 0) + setattr(self, 'lame_lambda', 0) + setattr(self, 'lame_mu', 0) + setattr(self, 'burgers_viscosity', 0) + setattr(self, 'burgers_mu', 0) + setattr(self, 'isburgers', 0) + setattr(self, 'density', 0) + setattr(self, 'issolid', 0) + else: + raise RuntimeError("materials constructor error message: nature of the material not supported yet! ('ice' or 'litho')") + #set default parameters: + self.setdefaultparameters() + #}}} + + def __repr__(self): # {{{ + string = " Materials:" + for i in range(len(self.nature)): + nat = self.nature[i] + if nat == 'ice': + string = "%s\n%s" % (string, 'Ice:') + string = "%s\n%s" % (string, fielddisplay(self, "rho_ice", "ice density [kg / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "rho_water", "water density [kg / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "rho_freshwater", "fresh water density [kg / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "mu_water", "water viscosity [N s / m^2]")) + string = "%s\n%s" % (string, fielddisplay(self, "heatcapacity", "heat capacity [J / kg / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "thermalconductivity", "ice thermal conductivity [W / m / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "temperateiceconductivity", "temperate ice thermal conductivity [W / m / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "meltingpoint", "melting point of ice at 1atm in K")) + string = "%s\n%s" % (string, fielddisplay(self, "latentheat", "latent heat of fusion [J / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "beta", "rate of change of melting point with pressure [K / Pa]")) + string = "%s\n%s" % (string, fielddisplay(self, "mixed_layer_capacity", "mixed layer capacity [W / kg / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "thermal_exchange_velocity", "thermal exchange velocity [m / s]")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_B", "flow law parameter [Pa s^(1 / n)]")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_n", "Glen's flow law exponent")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_law", "law for the temperature dependance of the rheology: 'None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius', 'LliboutryDuval', 'NyeCO2', or 'NyeH2O'")) + elif nat == 'litho': + string = "%s\n%s" % (string, 'Litho:') + string = "%s\n%s" % (string, fielddisplay(self, 'numlayers', 'number of layers (default 2)')) + string = "%s\n%s" % (string, fielddisplay(self, 'radius', 'array describing the radius for each interface (numlayers + 1) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'viscosity', 'array describing each layer''s viscosity (numlayers) [Pa.s]')) + string = "%s\n%s" % (string, fielddisplay(self, 'lame_lambda', 'array describing the lame lambda parameter (numlayers) [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'lame_mu', 'array describing the shear modulus for each layers (numlayers) [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'burgers_viscosity', 'array describing each layer''s transient viscosity, only for Burgers rheologies (numlayers) [Pa.s]')) + string = "%s\n%s" % (string, fielddisplay(self, 'burgers_mu', 'array describing each layer''s transient shear modulus, only for Burgers rheologies (numlayers) [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'isburgers', 'array describing whether we adopt a MaxWell (0) or Burgers (1) rheology (default 0)')) + string = "%s\n%s" % (string, fielddisplay(self, 'density', 'array describing each layer''s density (numlayers) [kg / m^3]')) + string = "%s\n%s" % (string, fielddisplay(self, 'issolid', 'array describing whether the layer is solid or liquid (default 1) (numlayers)')) + + else: + raise RuntimeError("materials constructor error message: nature of the material not supported yet! ('ice' or 'litho')") + + return string + #}}} + + def extrude(self, md): # {{{ + for i in range(len(self.nature)): + nat = self.nature[i] + if nat == 'ice': + self.rheology_B = project3d(md, 'vector', self.rheology_B, 'type', 'node') + self.rheology_n = project3d(md, 'vector', self.rheology_n, 'type', 'element') + return self + #}}} + + def setdefaultparameters(self): # {{{ + for i in range(len(self.nature)): + nat = self.nature[i] + if nat == 'ice': + #ice density (kg / m^3) + self.rho_ice = 917. + #ocean water density (kg / m^3) + self.rho_water = 1023. + #fresh water density (kg / m^3) + self.rho_freshwater = 1000. + #water viscosity (N.s / m^2) + self.mu_water = 0.001787 + #ice heat capacity cp (J / kg / K) + self.heatcapacity = 2093. + #ice latent heat of fusion L (J / kg) + self.latentheat = 3.34 * 1.0e5 + #ice thermal conductivity (W / m / K) + self.thermalconductivity = 2.4 + #wet ice thermal conductivity (W / m / K) + self.temperateiceconductivity = 0.24 + #the melting point of ice at 1 atmosphere of pressure in K + self.meltingpoint = 273.15 + #rate of change of melting point with pressure (K / Pa) + self.beta = 9.8 * 1.0e-8 + #mixed layer (ice-water interface) heat capacity (J / kg / K) + self.mixed_layer_capacity = 3974. + #thermal exchange velocity (ice-water interface) (m / s) + self.thermal_exchange_velocity = 1.00 * 1.0e-4 + #Rheology law: what is the temperature dependence of B with T + #available: none, paterson and arrhenius + self.rheology_law = 'Paterson' + + elif nat == 'litho': + #we default to a configuration that enables running GIA solutions using giacaron and / or giaivins. + self.numlayers = 2 + #center of the earth (approximation, must not be 0), then the lab (lithosphere / asthenosphere boundary) then the surface + #(with 1d3 to avoid numerical singularities) + self.radius = [1e3, 6278 * 1e3, 6378 * 1e3] + self.viscosity = [1e21, 1e40] #mantle and lithosphere viscosity (respectively) [Pa.s] + self.lame_mu = [1.45 * 1e11, 6.7 * 1e10] # (Pa) #lithosphere and mantle shear modulus (respectively) [Pa] + self.lame_lambda = self.lame_mu # (Pa) #mantle and lithosphere lamba parameter (respectively) [Pa] + self.burgers_viscosity = [np.nan, np.nan] + self.burgers_mu = [np.nan, np.nan] + self.isburgers = [0, 0] + self.density = [5.51 * 1e3, 5.50 * 1e3] # (Pa) #mantle and lithosphere density [kg / m^3] + self.issolid = [1, 1] # is layer solid or liquid. + + else: + raise RuntimeError("materials setdefaultparameters error message: nature of the material not supported yet! ('ice' or 'litho')") + + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + for i in range(len(self.nature)): + nat = self.nature[i] + if nat == 'ice': + md = checkfield(md, 'fieldname', 'materials.rho_ice', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rho_water', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rho_freshwater', '>', 0) + md = checkfield(md, 'fieldname', 'materials.mu_water', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rheology_B', '>', 0, 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'materials.rheology_n', '>', 0, 'size', [md.mesh.numberofelements]) + md = checkfield(md, 'fieldname', 'materials.rheology_law', 'values', ['None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius', 'LliboutryDuval', 'NyeCO2', 'NyeH2O']) + + elif nat == 'litho': + if 'LoveAnalysis' not in analyses: + return md + + md = checkfield(md, 'fieldname', 'materials.numlayers', 'NaN', 1, 'Inf', 1, '>', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'materials.radius', 'NaN', 1, 'Inf', 1, 'size', [md.materials.numlayers + 1, 1], '>', 0) + md = checkfield(md, 'fieldname', 'materials.lame_mu', 'NaN', 1, 'Inf', 1, 'size', [md.materials.numlayers, 1], '>=', 0) + md = checkfield(md, 'fieldname', 'materials.lame_lambda', 'NaN', 1, 'Inf', 1, 'size', [md.materials.numlayers, 1], '>=', 0) + md = checkfield(md, 'fieldname', 'materials.issolid', 'NaN', 1, 'Inf', 1, 'size', [md.materials.numlayers, 1], '>=', 0, '<', 2) + md = checkfield(md, 'fieldname', 'materials.density', 'NaN', 1, 'Inf', 1, 'size', [md.materials.numlayers, 1], '>', 0) + md = checkfield(md, 'fieldname', 'materials.viscosity', 'NaN', 1, 'Inf', 1, 'size', [md.materials.numlayers, 1], '>=', 0) + md = checkfield(md, 'fieldname', 'materials.isburgers', 'NaN', 1, 'Inf', 1, 'size', [md.materials.numlayers, 1], '>=', 0, '<=', 1) + md = checkfield(md, 'fieldname', 'materials.burgers_viscosity', 'Inf', 1, 'size', [md.materials.numlayers, 1], '>=', 0) + md = checkfield(md, 'fieldname', 'materials.burgers_mu', 'Inf', 1, 'size', [md.materials.numlayers, 1], '>=', 0) + + for i in range(md.materials.numlayers): + if md.materials.isburgers[i] and (np.isnan(md.materials.burgers_viscosity[i] or np.isnan(md.materials.burgers_mu[i]))): + raise RuntimeError("materials checkconsistency error message: Litho burgers_viscosity or burgers_mu has NaN values, inconsistent with isburgers choice") + + if md.materials.issolid[0] == 0 or md.materials.lame_mu[0] == 0: + raise RuntimeError('First layer must be solid (issolid(1) > 0 AND lame_mu(1) > 0). Add a weak inner core if necessary.') + + for i in range(md.materials.numlayers - 1): + if (not md.materials.issolid[i]) and (not md.materials.issolid[i + 1]): #if there are at least two consecutive indices that contain issolid = 0 + raise RuntimeError("%s%i%s" % ('2 or more adjacent fluid layers detected starting at layer ', i, '. This is not supported yet. Consider merging them.')) + + else: + raise RuntimeError("materials checkconsistency error message: nature of the material not supported yet! ('ice' or 'litho')") + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + #1: MatdamageiceEnum 2: MatestarEnum 3: MaticeEnum 4: MatenhancediceEnum 5: MaterialsEnum + WriteData(fid, prefix, 'name', 'md.materials.type', 'data', 6, 'format', 'Integer') + WriteData(fid, prefix, 'name', 'md.materials.nature', 'data', naturetointeger(self.nature), 'format', 'IntMat', 'mattype', 3) + + for i in range(len(self.nature)): + nat = self.nature[i] + if nat == 'ice': + WriteData(fid, prefix, 'name', 'md.materials.type', 'data', 3, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_ice', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_water', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_freshwater', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mu_water', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'heatcapacity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'latentheat', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'thermalconductivity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'temperateiceconductivity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'meltingpoint', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'beta', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mixed_layer_capacity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'thermal_exchange_velocity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rheology_B', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rheology_n', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'data', self.rheology_law, 'name', 'md.materials.rheology_law', 'format', 'String') + + elif nat == 'litho': + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'numlayers', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'radius', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'lame_mu', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'lame_lambda', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'issolid', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'density', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'viscosity', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'isburgers', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'burgers_viscosity', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'burgers_mu', 'format', 'DoubleMat', 'mattype', 3) + + else: + raise RuntimeError("materials constructor error message: nature of the material not supported yet! (''ice'' or ''litho'')") + # }}} Index: /issm/trunk-jpl/src/m/classes/matestar.py =================================================================== --- /issm/trunk-jpl/src/m/classes/matestar.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/matestar.py (revision 24213) @@ -1,3 +1,2 @@ -import numpy as np from fielddisplay import fielddisplay from project3d import project3d @@ -5,165 +4,166 @@ from WriteData import WriteData + class matestar(object): - """ - matestar class definition + """ + matestar class definition - Usage: - matestar=matestar() - """ + Usage: + matestar = matestar() + """ - def __init__(self): # {{{ - rho_ice = 0. - rho_water = 0. - rho_freshwater = 0. - mu_water = 0. - heatcapacity = 0. - latentheat = 0. - thermalconductivity = 0. - temperateiceconductivity = 0. - self.effectiveconductivity_averaging = 0 - meltingpoint = 0. - beta = 0. - mixed_layer_capacity = 0. - thermal_exchange_velocity = 0. - rheology_B = float('NaN') - rheology_Ec = float('NaN') - rheology_Es = float('NaN') - rheology_law = '' + def __init__(self): # {{{ + self.rho_ice = 0. + self.rho_water = 0. + self.rho_freshwater = 0. + self.mu_water = 0. + self.heatcapacity = 0. + self.latentheat = 0. + self.thermalconductivity = 0. + self.temperateiceconductivity = 0. + self.effectiveconductivity_averaging = 0 + self.meltingpoint = 0. + self.beta = 0. + self.mixed_layer_capacity = 0. + self.thermal_exchange_velocity = 0. + self.rheology_B = float('NaN') + self.rheology_Ec = float('NaN') + self.rheology_Es = float('NaN') + self.rheology_law = '' - #giaivins: - lithosphere_shear_modulus = 0. - lithosphere_density = 0. - mantle_shear_modulus = 0. - mantle_density = 0. + #giaivins: + self.lithosphere_shear_modulus = 0. + self.lithosphere_density = 0. + self.mantle_shear_modulus = 0. + self.mantle_density = 0. - #slr - earth_density = 0 + #slr + self.earth_density = 0 - #set default parameters: - self.setdefaultparameters() - #}}} + #set default parameters: + self.setdefaultparameters() + #}}} - def __repr__(self): # {{{ - string=" Materials:" - string="%s\n%s"%(string,fielddisplay(self,'rho_ice','ice density [kg/m^3]')) - string="%s\n%s"%(string,fielddisplay(self,'rho_water','ocean water density [kg/m^3]')) - string="%s\n%s"%(string,fielddisplay(self,'rho_freshwater','fresh water density [kg/m^3]')) - string="%s\n%s"%(string,fielddisplay(self,'mu_water','water viscosity [N s/m^2]')) - string="%s\n%s"%(string,fielddisplay(self,'heatcapacity','heat capacity [J/kg/K]')) - string="%s\n%s"%(string,fielddisplay(self,'thermalconductivity',['ice thermal conductivity [W/m/K]'])) - string="%s\n%s"%(string,fielddisplay(self,'temperateiceconductivity','temperate ice thermal conductivity [W/m/K]')) - string="%s\n%s"%(string,fielddisplay(self,"effectiveconductivity_averaging","computation of effectiveconductivity: (0) arithmetic mean, (1) harmonic mean, (2) geometric mean (default)")) - string="%s\n%s"%(string,fielddisplay(self,'meltingpoint','melting point of ice at 1atm in K')) - string="%s\n%s"%(string,fielddisplay(self,'latentheat','latent heat of fusion [J/kg]')) - string="%s\n%s"%(string,fielddisplay(self,'beta','rate of change of melting point with pressure [K/Pa]')) - string="%s\n%s"%(string,fielddisplay(self,'mixed_layer_capacity','mixed layer capacity [W/kg/K]')) - string="%s\n%s"%(string,fielddisplay(self,'thermal_exchange_velocity','thermal exchange velocity [m/s]')) - string="%s\n%s"%(string,fielddisplay(self,'rheology_B','flow law parameter [Pa s^(1/3)]')) - string="%s\n%s"%(string,fielddisplay(self,'rheology_Ec','compressive enhancement factor')) - string="%s\n%s"%(string,fielddisplay(self,'rheology_Es','shear enhancement factor')) - string="%s\n%s"%(string,fielddisplay(self,'rheology_law',['law for the temperature dependance of the rheology: ''None'', ''BuddJacka'', ''Cuffey'', ''CuffeyTemperate'', ''Paterson'', ''Arrhenius'' or ''LliboutryDuval'''])) - string="%s\n%s"%(string,fielddisplay(self,'lithosphere_shear_modulus','Lithosphere shear modulus [Pa]')) - string="%s\n%s"%(string,fielddisplay(self,'lithosphere_density','Lithosphere density [g/cm^-3]')) - string="%s\n%s"%(string,fielddisplay(self,'mantle_shear_modulus','Mantle shear modulus [Pa]')) - string="%s\n%s"%(string,fielddisplay(self,'mantle_density','Mantle density [g/cm^-3]')) - string="%s\n%s"%(string,fielddisplay(self,'earth_density','Mantle density [kg/m^-3]')) - return string - #}}} + def __repr__(self): # {{{ + string = " Materials:" + string = "%s\n%s" % (string, fielddisplay(self, 'rho_ice', 'ice density [kg / m^3]')) + string = "%s\n%s" % (string, fielddisplay(self, 'rho_water', 'ocean water density [kg / m^3]')) + string = "%s\n%s" % (string, fielddisplay(self, 'rho_freshwater', 'fresh water density [kg / m^3]')) + string = "%s\n%s" % (string, fielddisplay(self, 'mu_water', 'water viscosity [N s / m^2]')) + string = "%s\n%s" % (string, fielddisplay(self, 'heatcapacity', 'heat capacity [J / kg / K]')) + string = "%s\n%s" % (string, fielddisplay(self, 'thermalconductivity', ['ice thermal conductivity [W / m / K]'])) + string = "%s\n%s" % (string, fielddisplay(self, 'temperateiceconductivity', 'temperate ice thermal conductivity [W / m / K]')) + string = "%s\n%s" % (string, fielddisplay(self, "effectiveconductivity_averaging", "computation of effectiveconductivity: (0) arithmetic mean, (1) harmonic mean, (2) geometric mean (default)")) + string = "%s\n%s" % (string, fielddisplay(self, 'meltingpoint', 'melting point of ice at 1atm in K')) + string = "%s\n%s" % (string, fielddisplay(self, 'latentheat', 'latent heat of fusion [J / kg]')) + string = "%s\n%s" % (string, fielddisplay(self, 'beta', 'rate of change of melting point with pressure [K / Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'mixed_layer_capacity', 'mixed layer capacity [W / kg / K]')) + string = "%s\n%s" % (string, fielddisplay(self, 'thermal_exchange_velocity', 'thermal exchange velocity [m / s]')) + string = "%s\n%s" % (string, fielddisplay(self, 'rheology_B', 'flow law parameter [Pa s^(1 / 3)]')) + string = "%s\n%s" % (string, fielddisplay(self, 'rheology_Ec', 'compressive enhancement factor')) + string = "%s\n%s" % (string, fielddisplay(self, 'rheology_Es', 'shear enhancement factor')) + string = "%s\n%s" % (string, fielddisplay(self, 'rheology_law', ['law for the temperature dependance of the rheology: ''None'', ''BuddJacka'', ''Cuffey'', ''CuffeyTemperate'', ''Paterson'', ''Arrhenius'' or ''LliboutryDuval'''])) + string = "%s\n%s" % (string, fielddisplay(self, 'lithosphere_shear_modulus', 'Lithosphere shear modulus [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'lithosphere_density', 'Lithosphere density [g / cm^ - 3]')) + string = "%s\n%s" % (string, fielddisplay(self, 'mantle_shear_modulus', 'Mantle shear modulus [Pa]')) + string = "%s\n%s" % (string, fielddisplay(self, 'mantle_density', 'Mantle density [g / cm^ - 3]')) + string = "%s\n%s" % (string, fielddisplay(self, 'earth_density', 'Mantle density [kg / m^ - 3]')) + return string + #}}} - def extrude(self,md): # {{{ - self.rheology_B=project3d(md,'vector',self.rheology_B,'type','node') - self.rheology_Ec=project3d(md,'vector',self.rheology_Ec,'type','node') - self.rheology_Es=project3d(md,'vector',self.rheology_Es,'type','node') - return self - #}}} + def extrude(self, md): # {{{ + self.rheology_B = project3d(md, 'vector', self.rheology_B, 'type', 'node') + self.rheology_Ec = project3d(md, 'vector', self.rheology_Ec, 'type', 'node') + self.rheology_Es = project3d(md, 'vector', self.rheology_Es, 'type', 'node') + return self + #}}} - def setdefaultparameters(self): # {{{ - #ice density (kg/m^3) - self.rho_ice=917. - #ocean water density (kg/m^3) - self.rho_water=1023. - #fresh water density (kg/m^3) - self.rho_freshwater=1000. - #water viscosity (N.s/m^2) - self.mu_water=0.001787 - #ice heat capacity cp (J/kg/K) - self.heatcapacity=2093. - #ice latent heat of fusion L (J/kg) - self.latentheat=3.34*10**5 - #ice thermal conductivity (W/m/K) - self.thermalconductivity=2.4 - #wet ice thermal conductivity (W/m/K) - self.temperateiceconductivity=.24 - #computation of effective conductivity - self.effectiveconductivity_averaging=1 - #the melting point of ice at 1 atmosphere of pressure in K - self.meltingpoint=273.15 - #rate of change of melting point with pressure (K/Pa) - self.beta=9.8*10**-8 - #mixed layer (ice-water interface) heat capacity (J/kg/K) - self.mixed_layer_capacity=3974. - #thermal exchange velocity (ice-water interface) (m/s) - self.thermal_exchange_velocity=1.00*10**-4 - #Rheology law: what is the temperature dependence of B with T - #available: none, paterson and arrhenius - self.rheology_law='Paterson' - # GIA: - self.lithosphere_shear_modulus = 6.7*10**10 # (Pa) - self.lithosphere_density = 3.32 # (g/cm^-3) - self.mantle_shear_modulus = 1.45*10**11 # (Pa) - self.mantle_density = 3.34 # (g/cm^-3) - #SLR - self.earth_density= 5512 # average density of the Earth, (kg/m^3) + def setdefaultparameters(self): # {{{ + #ice density (kg / m^3) + self.rho_ice = 917. + #ocean water density (kg / m^3) + self.rho_water = 1023. + #fresh water density (kg / m^3) + self.rho_freshwater = 1000. + #water viscosity (N.s / m^2) + self.mu_water = 0.001787 + #ice heat capacity cp (J / kg / K) + self.heatcapacity = 2093. + #ice latent heat of fusion L (J / kg) + self.latentheat = 3.34 * 1.0e5 + #ice thermal conductivity (W / m / K) + self.thermalconductivity = 2.4 + #wet ice thermal conductivity (W / m / K) + self.temperateiceconductivity = 0.24 + #computation of effective conductivity + self.effectiveconductivity_averaging = 1 + #the melting point of ice at 1 atmosphere of pressure in K + self.meltingpoint = 273.15 + #rate of change of melting point with pressure (K / Pa) + self.beta = 9.8 * 1.0e-8 + #mixed layer (ice-water interface) heat capacity (J / kg / K) + self.mixed_layer_capacity = 3974. + #thermal exchange velocity (ice-water interface) (m / s) + self.thermal_exchange_velocity = 1.00 * 1.0e-4 + #Rheology law: what is the temperature dependence of B with T + #available: none, paterson and arrhenius + self.rheology_law = 'Paterson' + # GIA: + self.lithosphere_shear_modulus = 6.7 * 1.0e10 # (Pa) + self.lithosphere_density = 3.32 # (g / cm^ - 3) + self.mantle_shear_modulus = 1.45 * 1.0e11 # (Pa) + self.mantle_density = 3.34 # (g / cm^ - 3) + #SLR + self.earth_density = 5512 # average density of the Earth, (kg / m^3) - return self - #}}} + return self + #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - md = checkfield(md,'fieldname','materials.rho_ice','>',0) - md = checkfield(md,'fieldname','materials.rho_water','>',0) - md = checkfield(md,'fieldname','materials.rho_freshwater','>',0) - md = checkfield(md,'fieldname','materials.mu_water','>',0) - md = checkfield(md,'fieldname','materials.rheology_B','>',0,'size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','materials.rheology_Ec','>',0,'size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','materials.rheology_Es','>',0,'size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','materials.rheology_law','values',['None','BuddJacka', 'Cuffey','CuffeyTemperate','Paterson','Arrhenius','LliboutryDuval']) - md = checkfield(md,'fieldname','materials.effectiveconductivity_averaging','numel',[1],'values',[0,1,2]) + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'materials.rho_ice', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rho_water', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rho_freshwater', '>', 0) + md = checkfield(md, 'fieldname', 'materials.mu_water', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rheology_B', '>', 0, 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'materials.rheology_Ec', '>', 0, 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'materials.rheology_Es', '>', 0, 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'materials.rheology_law', 'values', ['None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius', 'LliboutryDuval']) + md = checkfield(md, 'fieldname', 'materials.effectiveconductivity_averaging', 'numel', [1], 'values', [0, 1, 2]) - if 'GiaAnalysis' in analyses: - md = checkfield(md,'fieldname','materials.lithosphere_shear_modulus','>',0,'numel',1) - md = checkfield(md,'fieldname','materials.lithosphere_density','>',0,'numel',1) - md = checkfield(md,'fieldname','materials.mantle_shear_modulus','>',0,'numel',1) - md = checkfield(md,'fieldname','materials.mantle_density','>',0,'numel',1) + if 'GiaAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'materials.lithosphere_shear_modulus', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'materials.lithosphere_density', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'materials.mantle_shear_modulus', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'materials.mantle_density', '>', 0, 'numel', 1) - if 'SealevelriseAnalysis' in analyses: - md = checkfield(md,'fieldname','materials.earth_density','>',0,'numel',1) + if 'SealevelriseAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'materials.earth_density', '>', 0, 'numel', 1) - return md - # }}} + return md + # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.materials.type','data',2,'format','Integer') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_ice','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_water','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_freshwater','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mu_water','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','heatcapacity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','latentheat','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','thermalconductivity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','temperateiceconductivity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','effectiveconductivity_averaging','format','Integer') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','meltingpoint','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','beta','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mixed_layer_capacity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','thermal_exchange_velocity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rheology_B','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rheology_Ec','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rheology_Es','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'data',self.rheology_law,'name','md.materials.rheology_law','format','String') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','lithosphere_shear_modulus','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','lithosphere_density','format','Double','scale',10^3) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mantle_shear_modulus','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mantle_density','format','Double','scale',10**3) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','earth_density','format','Double') - # }}} + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.materials.type', 'data', 2, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_ice', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_water', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_freshwater', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mu_water', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'heatcapacity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'latentheat', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'thermalconductivity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'temperateiceconductivity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'effectiveconductivity_averaging', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'meltingpoint', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'beta', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mixed_layer_capacity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'thermal_exchange_velocity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rheology_B', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rheology_Ec', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rheology_Es', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'data', self.rheology_law, 'name', 'md.materials.rheology_law', 'format', 'String') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'lithosphere_shear_modulus', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'lithosphere_density', 'format', 'Double', 'scale', 1.0e3) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mantle_shear_modulus', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mantle_density', 'format', 'Double', 'scale', 1.0e3) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'earth_density', 'format', 'Double') + # }}} Index: /issm/trunk-jpl/src/m/classes/matice.py =================================================================== --- /issm/trunk-jpl/src/m/classes/matice.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/matice.py (revision 24213) @@ -4,158 +4,158 @@ from WriteData import WriteData + class matice(object): - """ - MATICE class definition + """ + MATICE class definition - Usage: - matice=matice(); - """ + Usage: + matice = matice() + """ - def __init__(self): # {{{ - self.rho_ice = 0. - self.rho_water = 0. - self.rho_freshwater = 0. - self.mu_water = 0. - self.heatcapacity = 0. - self.latentheat = 0. - self.thermalconductivity = 0. - self.temperateiceconductivity = 0. - self.effectiveconductivity_averaging = 0 - self.meltingpoint = 0. - self.beta = 0. - self.mixed_layer_capacity = 0. - self.thermal_exchange_velocity = 0. - self.rheology_B = float('NaN') - self.rheology_n = float('NaN') - self.rheology_law = '' + def __init__(self): # {{{ + self.rho_ice = 0. + self.rho_water = 0. + self.rho_freshwater = 0. + self.mu_water = 0. + self.heatcapacity = 0. + self.latentheat = 0. + self.thermalconductivity = 0. + self.temperateiceconductivity = 0. + self.effectiveconductivity_averaging = 0 + self.meltingpoint = 0. + self.beta = 0. + self.mixed_layer_capacity = 0. + self.thermal_exchange_velocity = 0. + self.rheology_B = float('NaN') + self.rheology_n = float('NaN') + self.rheology_law = '' - #giaivins: - self.lithosphere_shear_modulus = 0. - self.lithosphere_density = 0. - self.mantle_shear_modulus = 0. - self.mantle_density = 0. + #giaivins: + self.lithosphere_shear_modulus = 0. + self.lithosphere_density = 0. + self.mantle_shear_modulus = 0. + self.mantle_density = 0. - #SLR - self.earth_density= 5512; + #SLR + self.earth_density = 5512 + self.setdefaultparameters() + #}}} - self.setdefaultparameters() - #}}} + def __repr__(self): # {{{ + string = " Materials:" - def __repr__(self): # {{{ - string=" Materials:" + string = "%s\n%s" % (string, fielddisplay(self, "rho_ice", "ice density [kg / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "rho_water", "water density [kg / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "rho_freshwater", "fresh water density [kg / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "mu_water", "water viscosity [N s / m^2]")) + string = "%s\n%s" % (string, fielddisplay(self, "heatcapacity", "heat capacity [J / kg / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "thermalconductivity", "ice thermal conductivity [W / m / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "temperateiceconductivity", "temperate ice thermal conductivity [W / m / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "effectiveconductivity_averaging", "computation of effectiveconductivity: (0) arithmetic mean, (1) harmonic mean, (2) geometric mean (default)")) + string = "%s\n%s" % (string, fielddisplay(self, "meltingpoint", "melting point of ice at 1atm in K")) + string = "%s\n%s" % (string, fielddisplay(self, "latentheat", "latent heat of fusion [J / m^3]")) + string = "%s\n%s" % (string, fielddisplay(self, "beta", "rate of change of melting point with pressure [K / Pa]")) + string = "%s\n%s" % (string, fielddisplay(self, "mixed_layer_capacity", "mixed layer capacity [W / kg / K]")) + string = "%s\n%s" % (string, fielddisplay(self, "thermal_exchange_velocity", "thermal exchange velocity [m / s]")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_B", "flow law parameter [Pa s^(1 / n)]")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_n", "Glen's flow law exponent")) + string = "%s\n%s" % (string, fielddisplay(self, "rheology_law", "law for the temperature dependance of the rheology: 'None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius', 'LliboutryDuval', 'NyeCO2', or 'NyeH2O'")) + string = "%s\n%s" % (string, fielddisplay(self, "lithosphere_shear_modulus", "Lithosphere shear modulus [Pa]")) + string = "%s\n%s" % (string, fielddisplay(self, "lithosphere_density", "Lithosphere density [g / cm^ - 3]")) + string = "%s\n%s" % (string, fielddisplay(self, "mantle_shear_modulus", "Mantle shear modulus [Pa]")) + string = "%s\n%s" % (string, fielddisplay(self, "mantle_density", "Mantle density [g / cm^ - 3]")) + string = "%s\n%s" % (string, fielddisplay(self, "earth_density", "Mantle density [kg / m^ - 3]")) + return string + #}}} - string="%s\n%s"%(string,fielddisplay(self,"rho_ice","ice density [kg/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"rho_water","water density [kg/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"rho_freshwater","fresh water density [kg/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"mu_water","water viscosity [N s/m^2]")) - string="%s\n%s"%(string,fielddisplay(self,"heatcapacity","heat capacity [J/kg/K]")) - string="%s\n%s"%(string,fielddisplay(self,"thermalconductivity","ice thermal conductivity [W/m/K]")) - string="%s\n%s"%(string,fielddisplay(self,"temperateiceconductivity","temperate ice thermal conductivity [W/m/K]")) - string="%s\n%s"%(string,fielddisplay(self,"effectiveconductivity_averaging","computation of effectiveconductivity: (0) arithmetic mean, (1) harmonic mean, (2) geometric mean (default)")) - string="%s\n%s"%(string,fielddisplay(self,"meltingpoint","melting point of ice at 1atm in K")) - string="%s\n%s"%(string,fielddisplay(self,"latentheat","latent heat of fusion [J/m^3]")) - string="%s\n%s"%(string,fielddisplay(self,"beta","rate of change of melting point with pressure [K/Pa]")) - string="%s\n%s"%(string,fielddisplay(self,"mixed_layer_capacity","mixed layer capacity [W/kg/K]")) - string="%s\n%s"%(string,fielddisplay(self,"thermal_exchange_velocity","thermal exchange velocity [m/s]")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_B","flow law parameter [Pa s^(1/n)]")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_n","Glen's flow law exponent")) - string="%s\n%s"%(string,fielddisplay(self,"rheology_law","law for the temperature dependance of the rheology: 'None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius', 'LliboutryDuval', 'NyeCO2', or 'NyeH2O'")) - string="%s\n%s"%(string,fielddisplay(self,"lithosphere_shear_modulus","Lithosphere shear modulus [Pa]")) - string="%s\n%s"%(string,fielddisplay(self,"lithosphere_density","Lithosphere density [g/cm^-3]")) - string="%s\n%s"%(string,fielddisplay(self,"mantle_shear_modulus","Mantle shear modulus [Pa]")) - string="%s\n%s"%(string,fielddisplay(self,"mantle_density","Mantle density [g/cm^-3]")) - string="%s\n%s"%(string,fielddisplay(self,"earth_density","Mantle density [kg/m^-3]")) - return string - #}}} + def extrude(self, md): # {{{ + self.rheology_B = project3d(md, 'vector', self.rheology_B, 'type', 'node') + self.rheology_n = project3d(md, 'vector', self.rheology_n, 'type', 'element') + return self + #}}} - def extrude(self,md): # {{{ - self.rheology_B=project3d(md,'vector',self.rheology_B,'type','node') - self.rheology_n=project3d(md,'vector',self.rheology_n,'type','element') - return self - #}}} + def setdefaultparameters(self): # {{{ + #ice density (kg / m^3) + self.rho_ice = 917. + #ocean water density (kg / m^3) + self.rho_water = 1023. + #fresh water density (kg / m^3) + self.rho_freshwater = 1000. + #water viscosity (N.s / m^2) + self.mu_water = 0.001787 + #ice heat capacity cp (J / kg / K) + self.heatcapacity = 2093. + #ice latent heat of fusion L (J / kg) + self.latentheat = 3.34 * 1.0e5 + #ice thermal conductivity (W / m / K) + self.thermalconductivity = 2.4 + #computation of effective conductivity + self.effectiveconductivity_averaging = 1 + #temperate ice thermal conductivity (W / m / K) + self.temperateiceconductivity = 0.24 + #the melting point of ice at 1 atmosphere of pressure in K + self.meltingpoint = 273.15 + #rate of change of melting point with pressure (K / Pa) + self.beta = 9.8 * 1.0e-8 + #mixed layer (ice-water interface) heat capacity (J / kg / K) + self.mixed_layer_capacity = 3974. + #thermal exchange velocity (ice-water interface) (m / s) + self.thermal_exchange_velocity = 1.00 * 1.0e-4 + #Rheology law: what is the temperature dependence of B with T + #available: none, paterson and arrhenius + self.rheology_law = 'Paterson' - def setdefaultparameters(self): # {{{ - #ice density (kg/m^3) - self.rho_ice=917. - #ocean water density (kg/m^3) - self.rho_water=1023. - #fresh water density (kg/m^3) - self.rho_freshwater=1000. - #water viscosity (N.s/m^2) - self.mu_water=0.001787 - #ice heat capacity cp (J/kg/K) - self.heatcapacity=2093. - #ice latent heat of fusion L (J/kg) - self.latentheat=3.34*10**5 - #ice thermal conductivity (W/m/K) - self.thermalconductivity=2.4 - #computation of effective conductivity - self.effectiveconductivity_averaging=1 - #temperate ice thermal conductivity (W/m/K) - self.temperateiceconductivity=0.24 - #the melting point of ice at 1 atmosphere of pressure in K - self.meltingpoint=273.15 - #rate of change of melting point with pressure (K/Pa) - self.beta=9.8*10**-8 - #mixed layer (ice-water interface) heat capacity (J/kg/K) - self.mixed_layer_capacity=3974. - #thermal exchange velocity (ice-water interface) (m/s) - self.thermal_exchange_velocity=1.00*10**-4 - #Rheology law: what is the temperature dependence of B with T - #available: none, paterson and arrhenius - self.rheology_law='Paterson' + # GIA: + self.lithosphere_shear_modulus = 6.7 * 1.0e10 # (Pa) + self.lithosphere_density = 3.32 # (g / cm^ - 3) + self.mantle_shear_modulus = 1.45 * 1.0e11 # (Pa) + self.mantle_density = 3.34 # (g / cm^ - 3) - # GIA: - self.lithosphere_shear_modulus = 6.7*10**10 # (Pa) - self.lithosphere_density = 3.32 # (g/cm^-3) - self.mantle_shear_modulus = 1.45*10**11 # (Pa) - self.mantle_density = 3.34 # (g/cm^-3) + #SLR + self.earth_density = 5512 # average density of the Earth, (kg / m^3) + return self + #}}} - #SLR - self.earth_density= 5512; # average density of the Earth, (kg/m^3) - return self - #}}} + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'materials.rho_ice', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rho_water', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rho_freshwater', '>', 0) + md = checkfield(md, 'fieldname', 'materials.mu_water', '>', 0) + md = checkfield(md, 'fieldname', 'materials.rheology_B', '>', 0, 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'materials.rheology_n', '>', 0, 'size', [md.mesh.numberofelements]) + md = checkfield(md, 'fieldname', 'materials.rheology_law', 'values', ['None', 'BuddJacka', 'Cuffey', 'CuffeyTemperate', 'Paterson', 'Arrhenius', 'LliboutryDuval', 'NyeCO2', 'NyeH2O']) + md = checkfield(md, 'fieldname', 'materials.effectiveconductivity_averaging', 'numel', [1], 'values', [0, 1, 2]) + md = checkfield(md, 'fieldname', 'materials.lithosphere_shear_modulus', '>', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'materials.lithosphere_density', '>', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'materials.mantle_shear_modulus', '>', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'materials.mantle_density', '>', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'materials.earth_density', '>', 0, 'numel', [1]) + return md + # }}} - def checkconsistency(self,md,solution,analyses): # {{{ - md = checkfield(md,'fieldname','materials.rho_ice','>',0) - md = checkfield(md,'fieldname','materials.rho_water','>',0) - md = checkfield(md,'fieldname','materials.rho_freshwater','>',0) - md = checkfield(md,'fieldname','materials.mu_water','>',0) - md = checkfield(md,'fieldname','materials.rheology_B','>',0,'timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','materials.rheology_n','>',0,'size',[md.mesh.numberofelements]) - md = checkfield(md,'fieldname','materials.rheology_law','values',['None','BuddJacka','Cuffey','CuffeyTemperate','Paterson','Arrhenius','LliboutryDuval','NyeCO2','NyeH2O']) - md = checkfield(md,'fieldname','materials.effectiveconductivity_averaging','numel',[1],'values',[0,1,2]) - md = checkfield(md,'fieldname','materials.lithosphere_shear_modulus','>',0,'numel',[1]); - md = checkfield(md,'fieldname','materials.lithosphere_density','>',0,'numel',[1]); - md = checkfield(md,'fieldname','materials.mantle_shear_modulus','>',0,'numel',[1]); - md = checkfield(md,'fieldname','materials.mantle_density','>',0,'numel',[1]); - md = checkfield(md,'fieldname','materials.earth_density','>',0,'numel',[1]); - return md - # }}} + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.materials.type', 'data', 3, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_ice', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_water', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rho_freshwater', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mu_water', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'heatcapacity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'latentheat', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'thermalconductivity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'temperateiceconductivity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'effectiveconductivity_averaging', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'meltingpoint', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'beta', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mixed_layer_capacity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'thermal_exchange_velocity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rheology_B', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'rheology_n', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'data', self.rheology_law, 'name', 'md.materials.rheology_law', 'format', 'String') - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.materials.type','data',3,'format','Integer'); - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_ice','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_water','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rho_freshwater','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mu_water','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','heatcapacity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','latentheat','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','thermalconductivity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','temperateiceconductivity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','effectiveconductivity_averaging','format','Integer') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','meltingpoint','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','beta','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mixed_layer_capacity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','thermal_exchange_velocity','format','Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rheology_B','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','materials','fieldname','rheology_n','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'data',self.rheology_law,'name','md.materials.rheology_law','format','String') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'lithosphere_shear_modulus', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'lithosphere_density', 'format', 'Double', 'scale', 10.**3.) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mantle_shear_modulus', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'mantle_density', 'format', 'Double', 'scale', 10.**3.) + WriteData(fid, prefix, 'object', self, 'class', 'materials', 'fieldname', 'earth_density', 'format', 'Double') - WriteData(fid,prefix,'object',self,'class','materials','fieldname','lithosphere_shear_modulus','format','Double'); - WriteData(fid,prefix,'object',self,'class','materials','fieldname','lithosphere_density','format','Double','scale',10.**3.); - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mantle_shear_modulus','format','Double'); - WriteData(fid,prefix,'object',self,'class','materials','fieldname','mantle_density','format','Double','scale',10.**3.); - WriteData(fid,prefix,'object',self,'class','materials','fieldname','earth_density','format','Double'); - - # }}} + # }}} Index: /issm/trunk-jpl/src/m/classes/mesh2d.py =================================================================== --- /issm/trunk-jpl/src/m/classes/mesh2d.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/mesh2d.py (revision 24213) @@ -5,129 +5,136 @@ from WriteData import WriteData + class mesh2d(object): - """ - MESH2D class definition + """ + MESH2D class definition - Usage: - mesh2d=mesh2d(); - """ + Usage: + mesh2d = mesh2d() + """ - def __init__(self): # {{{ - self.x = float('NaN'); - self.y = float('NaN'); - self.elements = float('NaN'); - self.numberofelements = 0; - self.numberofvertices = 0; - self.numberofedges = 0; - - self.lat = float('NaN'); - self.long = float('NaN'); - self.epsg = 0; - self.scale_factor = float('NaN'); + def __init__(self): # {{{ + self.x = float('NaN') + self.y = float('NaN') + self.elements = float('NaN') + self.numberofelements = 0 + self.numberofvertices = 0 + self.numberofedges = 0 - self.vertexonboundary = float('NaN'); - self.edges = float('NaN'); - self.segments = float('NaN'); - self.segmentmarkers = float('NaN'); - self.vertexconnectivity = float('NaN'); - self.elementconnectivity = float('NaN'); - self.average_vertex_connectivity = 0; + self.lat = float('NaN') + self.long = float('NaN') + self.epsg = 0 + self.scale_factor = float('NaN') - self.extractedvertices = float('NaN'); - self.extractedelements = float('NaN'); + self.vertexonboundary = float('NaN') + self.edges = float('NaN') + self.segments = float('NaN') + self.segmentmarkers = float('NaN') + self.vertexconnectivity = float('NaN') + self.elementconnectivity = float('NaN') + self.average_vertex_connectivity = 0 - #set defaults - self.setdefaultparameters() + self.extractedvertices = float('NaN') + self.extractedelements = float('NaN') - #}}} - def __repr__(self): # {{{ - string=" 2D tria Mesh (horizontal):" + #set defaults + self.setdefaultparameters() - string="%s\n%s"%(string,"\n Elements and vertices:") - string="%s\n%s"%(string,fielddisplay(self,"numberofelements","number of elements")) - string="%s\n%s"%(string,fielddisplay(self,"numberofvertices","number of vertices")) - string="%s\n%s"%(string,fielddisplay(self,"elements","vertex indices of the mesh elements")) - string="%s\n%s"%(string,fielddisplay(self,"x","vertices x coordinate [m]")) - string="%s\n%s"%(string,fielddisplay(self,"y","vertices y coordinate [m]")) - string="%s\n%s"%(string,fielddisplay(self,"edges","edges of the 2d mesh (vertex1 vertex2 element1 element2)")) - string="%s\n%s"%(string,fielddisplay(self,"numberofedges","number of edges of the 2d mesh")) + #}}} - string="%s%s"%(string,"\n\n Properties:") - string="%s\n%s"%(string,fielddisplay(self,"vertexonboundary","vertices on the boundary of the domain flag list")) - string="%s\n%s"%(string,fielddisplay(self,"segments","edges on domain boundary (vertex1 vertex2 element)")) - string="%s\n%s"%(string,fielddisplay(self,"segmentmarkers","number associated to each segment")) - string="%s\n%s"%(string,fielddisplay(self,"vertexconnectivity","list of elements connected to vertex_i")) - string="%s\n%s"%(string,fielddisplay(self,"elementconnectivity","list of elements adjacent to element_i")) - string="%s\n%s"%(string,fielddisplay(self,"average_vertex_connectivity","average number of vertices connected to one vertex")) + def __repr__(self): # {{{ + string = " 2D tria Mesh (horizontal):" - string="%s%s"%(string,"\n\n Extracted model:") - string="%s\n%s"%(string,fielddisplay(self,"extractedvertices","vertices extracted from the model")) - string="%s\n%s"%(string,fielddisplay(self,"extractedelements","elements extracted from the model")) + string = "%s\n%s" % (string, "\n Elements and vertices:") + string = "%s\n%s" % (string, fielddisplay(self, "numberofelements", "number of elements")) + string = "%s\n%s" % (string, fielddisplay(self, "numberofvertices", "number of vertices")) + string = "%s\n%s" % (string, fielddisplay(self, "elements", "vertex indices of the mesh elements")) + string = "%s\n%s" % (string, fielddisplay(self, "x", "vertices x coordinate [m]")) + string = "%s\n%s" % (string, fielddisplay(self, "y", "vertices y coordinate [m]")) + string = "%s\n%s" % (string, fielddisplay(self, "edges", "edges of the 2d mesh (vertex1 vertex2 element1 element2)")) + string = "%s\n%s" % (string, fielddisplay(self, "numberofedges", "number of edges of the 2d mesh")) - string="%s%s"%(string,"\n\n Projection:") - string="%s\n%s"%(string,fielddisplay(self,"lat","vertices latitude [degrees]")) - string="%s\n%s"%(string,fielddisplay(self,"long","vertices longitude [degrees]")) - string="%s\n%s"%(string,fielddisplay(self,"epsg","EPSG code (ex: 3413 for UPS Greenland, 3031 for UPS Antarctica)")) - string="%s\n%s"%(string,fielddisplay(self,"scale_factor","Projection correction for volume, area, etc. computation")) - return string - #}}} - def setdefaultparameters(self): # {{{ - - #the connectivity is the averaged number of nodes linked to a - #given node through an edge. This connectivity is used to initially - #allocate memory to the stiffness matrix. A value of 16 seems to - #give a good memory/time ration. This value can be checked in - #trunk/test/Miscellaneous/runme.m - self.average_vertex_connectivity=25 + string = "%s%s" % (string, "\n\n Properties:") + string = "%s\n%s" % (string, fielddisplay(self, "vertexonboundary", "vertices on the boundary of the domain flag list")) + string = "%s\n%s" % (string, fielddisplay(self, "segments", "edges on domain boundary (vertex1 vertex2 element)")) + string = "%s\n%s" % (string, fielddisplay(self, "segmentmarkers", "number associated to each segment")) + string = "%s\n%s" % (string, fielddisplay(self, "vertexconnectivity", "list of elements connected to vertex_i")) + string = "%s\n%s" % (string, fielddisplay(self, "elementconnectivity", "list of elements adjacent to element_i")) + string = "%s\n%s" % (string, fielddisplay(self, "average_vertex_connectivity", "average number of vertices connected to one vertex")) - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - if(solution=='LoveSolution'): - return + string = "%s%s" % (string, "\n\n Extracted model:") + string = "%s\n%s" % (string, fielddisplay(self, "extractedvertices", "vertices extracted from the model")) + string = "%s\n%s" % (string, fielddisplay(self, "extractedelements", "elements extracted from the model")) - md = checkfield(md,'fieldname','mesh.x','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.y','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.elements','NaN',1,'Inf',1,'>',0,'values',np.arange(1,md.mesh.numberofvertices+1)) - md = checkfield(md,'fieldname','mesh.elements','size',[md.mesh.numberofelements,3]) - if np.any(np.logical_not(m.ismember(np.arange(1,md.mesh.numberofvertices+1),md.mesh.elements))): - md.checkmessage("orphan nodes have been found. Check the mesh outline") - md = checkfield(md,'fieldname','mesh.numberofelements','>',0) - md = checkfield(md,'fieldname','mesh.numberofvertices','>',0) - md = checkfield(md,'fieldname','mesh.average_vertex_connectivity','>=',9,'message',"'mesh.average_vertex_connectivity' should be at least 9 in 2d") - md = checkfield(md,'fieldname','mesh.segments','NaN',1,'Inf',1,'>',0,'size',[np.nan,3]); - if(np.size(self.scale_factor)>1): - md = checkfield(md,'fieldname','mesh.scale_factor','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - - if solution=='ThermalSolution': - md.checkmessage("thermal not supported for 2d mesh") + string = "%s%s" % (string, "\n\n Projection:") + string = "%s\n%s" % (string, fielddisplay(self, "lat", "vertices latitude [degrees]")) + string = "%s\n%s" % (string, fielddisplay(self, "long", "vertices longitude [degrees]")) + string = "%s\n%s" % (string, fielddisplay(self, "epsg", "EPSG code (ex: 3413 for UPS Greenland, 3031 for UPS Antarctica)")) + string = "%s\n%s" % (string, fielddisplay(self, "scale_factor", "Projection correction for volume, area, etc. computation")) + return string + #}}} - return md - # }}} - def domaintype(self): # {{{ - return "2Dhorizontal" - #}}} - def dimension(self): # {{{ - return 2 - #}}} - def elementtype(self): # {{{ - return "Tria" - #}}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.mesh.domain_type','data',"Domain"+self.domaintype(),'format','String'); - WriteData(fid,prefix,'name','md.mesh.domain_dimension','data',self.dimension(),'format','Integer'); - WriteData(fid,prefix,'name','md.mesh.elementtype','data',self.elementtype(),'format','String'); - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','x','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','y','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'name','md.mesh.z','data',np.zeros(self.numberofvertices),'format','DoubleMat','mattype',1); - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','elements','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','numberofelements','format','Integer') - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','numberofvertices','format','Integer') - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','average_vertex_connectivity','format','Integer') - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','vertexonboundary','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','segments','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','scale_factor','format','DoubleMat','mattype',1) - if md.transient.isoceancoupling: - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','lat','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','long','format','DoubleMat','mattype',1) - # }}} + def setdefaultparameters(self): # {{{ + #the connectivity is the averaged number of nodes linked to a + #given node through an edge. This connectivity is used to initially + #allocate memory to the stiffness matrix. A value of 16 seems to + #give a good memory / time ration. This value can be checked in + #trunk / test / Miscellaneous / runme.m + self.average_vertex_connectivity = 25 + + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + if(solution == 'LoveSolution'): + return + + md = checkfield(md, 'fieldname', 'mesh.x', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.y', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.elements', 'NaN', 1, 'Inf', 1, '>', 0, 'values', np.arange(1, md.mesh.numberofvertices + 1)) + md = checkfield(md, 'fieldname', 'mesh.elements', 'size', [md.mesh.numberofelements, 3]) + if np.any(np.logical_not(m.ismember(np.arange(1, md.mesh.numberofvertices + 1), md.mesh.elements))): + md.checkmessage("orphan nodes have been found. Check the mesh outline") + md = checkfield(md, 'fieldname', 'mesh.numberofelements', '>', 0) + md = checkfield(md, 'fieldname', 'mesh.numberofvertices', '>', 0) + md = checkfield(md, 'fieldname', 'mesh.average_vertex_connectivity', '>=', 9, 'message', "'mesh.average_vertex_connectivity' should be at least 9 in 2d") + md = checkfield(md, 'fieldname', 'mesh.segments', 'NaN', 1, 'Inf', 1, '>', 0, 'size', [np.nan, 3]) + if(np.size(self.scale_factor) > 1): + md = checkfield(md, 'fieldname', 'mesh.scale_factor', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + + if solution == 'ThermalSolution': + md.checkmessage("thermal not supported for 2d mesh") + + return md + # }}} + + def domaintype(self): # {{{ + return "2Dhorizontal" + #}}} + + def dimension(self): # {{{ + return 2 + #}}} + + def elementtype(self): # {{{ + return "Tria" + #}}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.mesh.domain_type', 'data', "Domain" + self.domaintype(), 'format', 'String') + WriteData(fid, prefix, 'name', 'md.mesh.domain_dimension', 'data', self.dimension(), 'format', 'Integer') + WriteData(fid, prefix, 'name', 'md.mesh.elementtype', 'data', self.elementtype(), 'format', 'String') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'x', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'y', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'name', 'md.mesh.z', 'data', np.zeros(self.numberofvertices), 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'elements', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'numberofelements', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'numberofvertices', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'average_vertex_connectivity', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'vertexonboundary', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'segments', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'scale_factor', 'format', 'DoubleMat', 'mattype', 1) + if md.transient.isoceancoupling: + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'lat', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'long', 'format', 'DoubleMat', 'mattype', 1) + # }}} Index: /issm/trunk-jpl/src/m/classes/mesh2dvertical.py =================================================================== --- /issm/trunk-jpl/src/m/classes/mesh2dvertical.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/mesh2dvertical.py (revision 24213) @@ -5,131 +5,138 @@ from WriteData import WriteData + class mesh2dvertical(object): - """ - MESH2DVERTICAL class definition + """ + MESH2DVERTICAL class definition - Usage: - mesh2dvertical=mesh2dvertical(); - """ + Usage: + mesh2dvertical = mesh2dvertical() + """ - def __init__(self): # {{{ - self.x = float('NaN') - self.y = float('NaN') - self.elements = float('NaN') - self.numberofelements = 0 - self.numberofvertices = 0 - self.numberofedges = 0 - - self.lat = float('NaN') - self.long = float('NaN') - self.epsg = float('NaN') - self.scale_factor = float('NaN'); + def __init__(self): # {{{ + self.x = float('NaN') + self.y = float('NaN') + self.elements = float('NaN') + self.numberofelements = 0 + self.numberofvertices = 0 + self.numberofedges = 0 - self.vertexonboundary = float('NaN') - self.vertexonbase = float('NaN') - self.vertexonsurface = float('NaN') + self.lat = float('NaN') + self.long = float('NaN') + self.epsg = float('NaN') + self.scale_factor = float('NaN') - self.edges = float('NaN') - self.segments = float('NaN') - self.segmentmarkers = float('NaN') - self.vertexconnectivity = float('NaN') - self.elementconnectivity = float('NaN') - self.average_vertex_connectivity = 0 + self.vertexonboundary = float('NaN') + self.vertexonbase = float('NaN') + self.vertexonsurface = float('NaN') - #set defaults - self.setdefaultparameters() + self.edges = float('NaN') + self.segments = float('NaN') + self.segmentmarkers = float('NaN') + self.vertexconnectivity = float('NaN') + self.elementconnectivity = float('NaN') + self.average_vertex_connectivity = 0 - #}}} - def __repr__(self): # {{{ - string=" 2D tria Mesh (vertical):" + #set defaults + self.setdefaultparameters() - string="%s\n%s"%(string,"\n Elements and vertices:") - string="%s\n%s"%(string,fielddisplay(self,"numberofelements","number of elements")) - string="%s\n%s"%(string,fielddisplay(self,"numberofvertices","number of vertices")) - string="%s\n%s"%(string,fielddisplay(self,"elements","vertex indices of the mesh elements")) - string="%s\n%s"%(string,fielddisplay(self,"x","vertices x coordinate [m]")) - string="%s\n%s"%(string,fielddisplay(self,"y","vertices y coordinate [m]")) - string="%s\n%s"%(string,fielddisplay(self,"edges","edges of the 2d mesh (vertex1 vertex2 element1 element2)")) - string="%s\n%s"%(string,fielddisplay(self,"numberofedges","number of edges of the 2d mesh")) + #}}} + def __repr__(self): # {{{ + string = " 2D tria Mesh (vertical):" - string="%s%s"%(string,"\n\n Properties:") - string="%s\n%s"%(string,fielddisplay(self,"vertexonboundary","vertices on the boundary of the domain flag list")) - string="%s\n%s"%(string,fielddisplay(self,'vertexonbase','vertices on the bed of the domain flag list')) - string="%s\n%s"%(string,fielddisplay(self,'vertexonsurface','vertices on the surface of the domain flag list')) - string="%s\n%s"%(string,fielddisplay(self,"segments","edges on domain boundary (vertex1 vertex2 element)")) - string="%s\n%s"%(string,fielddisplay(self,"segmentmarkers","number associated to each segment")) - string="%s\n%s"%(string,fielddisplay(self,"vertexconnectivity","list of elements connected to vertex_i")) - string="%s\n%s"%(string,fielddisplay(self,"elementconnectivity","list of elements adjacent to element_i")) - string="%s\n%s"%(string,fielddisplay(self,"average_vertex_connectivity","average number of vertices connected to one vertex")) + string = "%s\n%s" % (string, "\n Elements and vertices:") + string = "%s\n%s" % (string, fielddisplay(self, "numberofelements", "number of elements")) + string = "%s\n%s" % (string, fielddisplay(self, "numberofvertices", "number of vertices")) + string = "%s\n%s" % (string, fielddisplay(self, "elements", "vertex indices of the mesh elements")) + string = "%s\n%s" % (string, fielddisplay(self, "x", "vertices x coordinate [m]")) + string = "%s\n%s" % (string, fielddisplay(self, "y", "vertices y coordinate [m]")) + string = "%s\n%s" % (string, fielddisplay(self, "edges", "edges of the 2d mesh (vertex1 vertex2 element1 element2)")) + string = "%s\n%s" % (string, fielddisplay(self, "numberofedges", "number of edges of the 2d mesh")) - string="%s%s"%(string,"\n\n Projection:") - string="%s\n%s"%(string,fielddisplay(self,"lat","vertices latitude [degrees]")) - string="%s\n%s"%(string,fielddisplay(self,"long","vertices longitude [degrees]")) - string="%s\n%s"%(string,fielddisplay(self,"epsg","EPSG code (ex: 3413 for UPS Greenland, 3031 for UPS Antarctica)")) - string="%s\n%s"%(string,fielddisplay(self,"scale_factor","Projection correction for volume, area, etc. computation")) - return string - #}}} - def setdefaultparameters(self): # {{{ - - #the connectivity is the averaged number of nodes linked to a - #given node through an edge. This connectivity is used to initially - #allocate memory to the stiffness matrix. A value of 16 seems to - #give a good memory/time ration. This value can be checked in - #trunk/test/Miscellaneous/runme.m - self.average_vertex_connectivity=25. + string = "%s%s" % (string, "\n\n Properties:") + string = "%s\n%s" % (string, fielddisplay(self, "vertexonboundary", "vertices on the boundary of the domain flag list")) + string = "%s\n%s" % (string, fielddisplay(self, 'vertexonbase', 'vertices on the bed of the domain flag list')) + string = "%s\n%s" % (string, fielddisplay(self, 'vertexonsurface', 'vertices on the surface of the domain flag list')) + string = "%s\n%s" % (string, fielddisplay(self, "segments", "edges on domain boundary (vertex1 vertex2 element)")) + string = "%s\n%s" % (string, fielddisplay(self, "segmentmarkers", "number associated to each segment")) + string = "%s\n%s" % (string, fielddisplay(self, "vertexconnectivity", "list of elements connected to vertex_i")) + string = "%s\n%s" % (string, fielddisplay(self, "elementconnectivity", "list of elements adjacent to element_i")) + string = "%s\n%s" % (string, fielddisplay(self, "average_vertex_connectivity", "average number of vertices connected to one vertex")) - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - if(solution=='LoveSolution'): - return + string = "%s%s" % (string, "\n\n Projection:") + string = "%s\n%s" % (string, fielddisplay(self, "lat", "vertices latitude [degrees]")) + string = "%s\n%s" % (string, fielddisplay(self, "long", "vertices longitude [degrees]")) + string = "%s\n%s" % (string, fielddisplay(self, "epsg", "EPSG code (ex: 3413 for UPS Greenland, 3031 for UPS Antarctica)")) + string = "%s\n%s" % (string, fielddisplay(self, "scale_factor", "Projection correction for volume, area, etc. computation")) + return string + #}}} - md = checkfield(md,'fieldname','mesh.x','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.y','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.elements','NaN',1,'Inf',1,'>',0,'values',np.arange(1,md.mesh.numberofvertices+1)) - md = checkfield(md,'fieldname','mesh.elements','size',[md.mesh.numberofelements,3]) - if np.any(np.logical_not(m.ismember(np.arange(1,md.mesh.numberofvertices+1),md.mesh.elements))): - md.checkmessage("orphan nodes have been found. Check the mesh outline") - md = checkfield(md,'fieldname','mesh.numberofelements','>',0) - md = checkfield(md,'fieldname','mesh.numberofvertices','>',0) - md = checkfield(md,'fieldname','mesh.vertexonbase','size',[md.mesh.numberofvertices],'values',[0,1]) - md = checkfield(md,'fieldname','mesh.vertexonsurface','size',[md.mesh.numberofvertices],'values',[0,1]) - md = checkfield(md,'fieldname','mesh.average_vertex_connectivity','>=',9,'message',"'mesh.average_vertex_connectivity' should be at least 9 in 2d") - if(np.size(self.scale_factor)>1): - md = checkfield(md,'fieldname','mesh.scale_factor','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) + def setdefaultparameters(self): # {{{ + #the connectivity is the averaged number of nodes linked to a + #given node through an edge. This connectivity is used to initially + #allocate memory to the stiffness matrix. A value of 16 seems to + #give a good memory / time ration. This value can be checked in + #trunk / test / Miscellaneous / runme.m + self.average_vertex_connectivity = 25. - if solution=='ThermalSolution': - md.checkmessage("thermal not supported for 2d mesh") + return self + #}}} - return md - # }}} - def domaintype(self): # {{{ - return "2Dvertical" - #}}} - def dimension(self): # {{{ - return 2 - #}}} - def elementtype(self): # {{{ - return "Tria" - #}}} - def vertexflags(self,value): # {{{ - flags = np.zeros((self.numberofvertices,)) - pos = self.segments[np.where(self.segmentmarkers==value),0:2]-1 - flags[pos] = 1 - return flags - #}}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.mesh.domain_type','data',"Domain"+self.domaintype(),'format','String'); - WriteData(fid,prefix,'name','md.mesh.domain_dimension','data',self.dimension(),'format','Integer'); - WriteData(fid,prefix,'name','md.mesh.elementtype','data',self.elementtype(),'format','String'); - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','x','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','y','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'name','md.mesh.z','data',np.zeros(self.numberofvertices),'format','DoubleMat','mattype',1); - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','elements','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','numberofelements','format','Integer') - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','numberofvertices','format','Integer') - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','vertexonbase','format','BooleanMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','vertexonsurface','format','BooleanMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','average_vertex_connectivity','format','Integer') - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','scale_factor','format','DoubleMat','mattype',1) - # }}} + def checkconsistency(self, md, solution, analyses): # {{{ + if(solution == 'LoveSolution'): + return + + md = checkfield(md, 'fieldname', 'mesh.x', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.y', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.elements', 'NaN', 1, 'Inf', 1, '>', 0, 'values', np.arange(1, md.mesh.numberofvertices + 1)) + md = checkfield(md, 'fieldname', 'mesh.elements', 'size', [md.mesh.numberofelements, 3]) + if np.any(np.logical_not(m.ismember(np.arange(1, md.mesh.numberofvertices + 1), md.mesh.elements))): + md.checkmessage("orphan nodes have been found. Check the mesh outline") + md = checkfield(md, 'fieldname', 'mesh.numberofelements', '>', 0) + md = checkfield(md, 'fieldname', 'mesh.numberofvertices', '>', 0) + md = checkfield(md, 'fieldname', 'mesh.vertexonbase', 'size', [md.mesh.numberofvertices], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'mesh.vertexonsurface', 'size', [md.mesh.numberofvertices], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'mesh.average_vertex_connectivity', '>=', 9, 'message', "'mesh.average_vertex_connectivity' should be at least 9 in 2d") + if(np.size(self.scale_factor) > 1): + md = checkfield(md, 'fieldname', 'mesh.scale_factor', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + + if solution == 'ThermalSolution': + md.checkmessage("thermal not supported for 2d mesh") + + return md + # }}} + + def domaintype(self): # {{{ + return "2Dvertical" + #}}} + + def dimension(self): # {{{ + return 2 + #}}} + + def elementtype(self): # {{{ + return "Tria" + #}}} + + def vertexflags(self, value): # {{{ + flags = np.zeros((self.numberofvertices, )) + pos = self.segments[np.where(self.segmentmarkers == value), 0:2] - 1 + flags[pos] = 1 + return flags + #}}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.mesh.domain_type', 'data', "Domain" + self.domaintype(), 'format', 'String') + WriteData(fid, prefix, 'name', 'md.mesh.domain_dimension', 'data', self.dimension(), 'format', 'Integer') + WriteData(fid, prefix, 'name', 'md.mesh.elementtype', 'data', self.elementtype(), 'format', 'String') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'x', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'y', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'name', 'md.mesh.z', 'data', np.zeros(self.numberofvertices), 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'elements', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'numberofelements', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'numberofvertices', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'vertexonbase', 'format', 'BooleanMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'vertexonsurface', 'format', 'BooleanMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'average_vertex_connectivity', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'scale_factor', 'format', 'DoubleMat', 'mattype', 1) + # }}} Index: /issm/trunk-jpl/src/m/classes/mesh3dprisms.py =================================================================== --- /issm/trunk-jpl/src/m/classes/mesh3dprisms.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/mesh3dprisms.py (revision 24213) @@ -5,155 +5,161 @@ from WriteData import WriteData + class mesh3dprisms(object): - """ - MESH3DPRISMS class definition + """ + MESH3DPRISMS class definition - Usage: - mesh3d=mesh3dprisms(); - """ + Usage: + mesh3d = mesh3dprisms() + """ - def __init__(self): # {{{ - self.x = float('NaN'); - self.y = float('NaN'); - self.z = float('NaN'); - self.elements = float('NaN'); - self.numberoflayers = 0; - self.numberofelements = 0; - self.numberofvertices = 0; - - self.lat = float('NaN'); - self.long = float('NaN'); - self.epsg = 0; - self.scale_factor = float('NaN'); + def __init__(self): # {{{ + self.x = float('NaN') + self.y = float('NaN') + self.z = float('NaN') + self.elements = float('NaN') + self.numberoflayers = 0 + self.numberofelements = 0 + self.numberofvertices = 0 - self.vertexonbase = float('NaN'); - self.vertexonsurface = float('NaN'); - self.lowerelements = float('NaN'); - self.lowervertex = float('NaN'); - self.upperelements = float('NaN'); - self.uppervertex = float('NaN'); - self.vertexonboundary = float('NaN'); + self.lat = float('NaN') + self.long = float('NaN') + self.epsg = 0 + self.scale_factor = float('NaN') - self.vertexconnectivity = float('NaN'); - self.elementconnectivity = float('NaN'); - self.average_vertex_connectivity = 0; + self.vertexonbase = float('NaN') + self.vertexonsurface = float('NaN') + self.lowerelements = float('NaN') + self.lowervertex = float('NaN') + self.upperelements = float('NaN') + self.uppervertex = float('NaN') + self.vertexonboundary = float('NaN') - self.x2d = float('NaN'); - self.y2d = float('NaN'); - self.elements2d = float('NaN'); - self.numberofvertices2d = 0; - self.numberofelements2d = 0; + self.vertexconnectivity = float('NaN') + self.elementconnectivity = float('NaN') + self.average_vertex_connectivity = 0 - self.extractedvertices = float('NaN'); - self.extractedelements = float('NaN'); + self.x2d = float('NaN') + self.y2d = float('NaN') + self.elements2d = float('NaN') + self.numberofvertices2d = 0 + self.numberofelements2d = 0 - #set defaults - self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=" 3D prism Mesh:" + self.extractedvertices = float('NaN') + self.extractedelements = float('NaN') - string="%s\n%s"%(string,"\n Elements and vertices of the original 2d mesh3dprisms:") - - string="%s\n%s"%(string,fielddisplay(self,"numberofelements2d","number of elements")) - string="%s\n%s"%(string,fielddisplay(self,"numberofvertices2d","number of vertices")) - string="%s\n%s"%(string,fielddisplay(self,"elements2d","vertex indices of the mesh3dprisms elements")) - string="%s\n%s"%(string,fielddisplay(self,"x2d","vertices x coordinate [m]")) - string="%s\n%s"%(string,fielddisplay(self,"y2d","vertices y coordinate [m]")) + #set defaults + self.setdefaultparameters() + #}}} - string="%s\n%s"%(string,"\n\n Elements and vertices of the extruded 3d mesh3dprisms:") - string="%s\n%s"%(string,fielddisplay(self,"numberofelements","number of elements")) - string="%s\n%s"%(string,fielddisplay(self,"numberofvertices","number of vertices")) - string="%s\n%s"%(string,fielddisplay(self,"elements","vertex indices of the mesh3dprisms elements")) - string="%s\n%s"%(string,fielddisplay(self,"x","vertices x coordinate [m]")) - string="%s\n%s"%(string,fielddisplay(self,"y","vertices y coordinate [m]")) - string="%s\n%s"%(string,fielddisplay(self,"z","vertices z coordinate [m]")) + def __repr__(self): # {{{ + string = " 3D prism Mesh:" - string="%s%s"%(string,"\n\n Properties:") - string="%s\n%s"%(string,fielddisplay(self,"numberoflayers","number of extrusion layers")) - string="%s\n%s"%(string,fielddisplay(self,"vertexonbase","lower vertices flags list")) - string="%s\n%s"%(string,fielddisplay(self,"vertexonsurface","upper vertices flags list")) - string="%s\n%s"%(string,fielddisplay(self,"uppervertex","upper vertex list (NaN for vertex on the upper surface)")) - string="%s\n%s"%(string,fielddisplay(self,"upperelements","upper element list (NaN for element on the upper layer)")) - string="%s\n%s"%(string,fielddisplay(self,"lowervertex","lower vertex list (NaN for vertex on the lower surface)")) - string="%s\n%s"%(string,fielddisplay(self,"lowerelements","lower element list (NaN for element on the lower layer)")) - string="%s\n%s"%(string,fielddisplay(self,"vertexonboundary","vertices on the boundary of the domain flag list")) - string="%s\n%s"%(string,fielddisplay(self,"vertexconnectivity","list of elements connected to vertex_i")) - string="%s\n%s"%(string,fielddisplay(self,"elementconnectivity","list of elements adjacent to element_i")) - string="%s\n%s"%(string,fielddisplay(self,"average_vertex_connectivity","average number of vertices connected to one vertex")) + string = "%s\n%s" % (string, "\n Elements and vertices of the original 2d mesh3dprisms:") - string="%s%s"%(string,"\n\n Extracted model:") - string="%s\n%s"%(string,fielddisplay(self,"extractedvertices","vertices extracted from the model")) - string="%s\n%s"%(string,fielddisplay(self,"extractedelements","elements extracted from the model")) + string = "%s\n%s" % (string, fielddisplay(self, "numberofelements2d", "number of elements")) + string = "%s\n%s" % (string, fielddisplay(self, "numberofvertices2d", "number of vertices")) + string = "%s\n%s" % (string, fielddisplay(self, "elements2d", "vertex indices of the mesh3dprisms elements")) + string = "%s\n%s" % (string, fielddisplay(self, "x2d", "vertices x coordinate [m]")) + string = "%s\n%s" % (string, fielddisplay(self, "y2d", "vertices y coordinate [m]")) - string="%s%s"%(string,"\n\n Projection:") - string="%s\n%s"%(string,fielddisplay(self,"lat","vertices latitude [degrees]")) - string="%s\n%s"%(string,fielddisplay(self,"long","vertices longitude [degrees]")) - string="%s\n%s"%(string,fielddisplay(self,"epsg","EPSG code (ex: 3413 for UPS Greenland, 3031 for UPS Antarctica)")) - string="%s\n%s"%(string,fielddisplay(self,"scale_factor","Projection correction for volume, area, etc. computation")) - return string - #}}} - def setdefaultparameters(self): # {{{ - - #the connectivity is the averaged number of nodes linked to a - #given node through an edge. This connectivity is used to initially - #allocate memory to the stiffness matrix. A value of 16 seems to - #give a good memory/time ration. This value can be checked in - #trunk/test/Miscellaneous/runme.m - self.average_vertex_connectivity=25 + string = "%s\n%s" % (string, "\n\n Elements and vertices of the extruded 3d mesh3dprisms:") + string = "%s\n%s" % (string, fielddisplay(self, "numberofelements", "number of elements")) + string = "%s\n%s" % (string, fielddisplay(self, "numberofvertices", "number of vertices")) + string = "%s\n%s" % (string, fielddisplay(self, "elements", "vertex indices of the mesh3dprisms elements")) + string = "%s\n%s" % (string, fielddisplay(self, "x", "vertices x coordinate [m]")) + string = "%s\n%s" % (string, fielddisplay(self, "y", "vertices y coordinate [m]")) + string = "%s\n%s" % (string, fielddisplay(self, "z", "vertices z coordinate [m]")) - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + string = "%s%s" % (string, "\n\n Properties:") + string = "%s\n%s" % (string, fielddisplay(self, "numberoflayers", "number of extrusion layers")) + string = "%s\n%s" % (string, fielddisplay(self, "vertexonbase", "lower vertices flags list")) + string = "%s\n%s" % (string, fielddisplay(self, "vertexonsurface", "upper vertices flags list")) + string = "%s\n%s" % (string, fielddisplay(self, "uppervertex", "upper vertex list (NaN for vertex on the upper surface)")) + string = "%s\n%s" % (string, fielddisplay(self, "upperelements", "upper element list (NaN for element on the upper layer)")) + string = "%s\n%s" % (string, fielddisplay(self, "lowervertex", "lower vertex list (NaN for vertex on the lower surface)")) + string = "%s\n%s" % (string, fielddisplay(self, "lowerelements", "lower element list (NaN for element on the lower layer)")) + string = "%s\n%s" % (string, fielddisplay(self, "vertexonboundary", "vertices on the boundary of the domain flag list")) + string = "%s\n%s" % (string, fielddisplay(self, "vertexconnectivity", "list of elements connected to vertex_i")) + string = "%s\n%s" % (string, fielddisplay(self, "elementconnectivity", "list of elements adjacent to element_i")) + string = "%s\n%s" % (string, fielddisplay(self, "average_vertex_connectivity", "average number of vertices connected to one vertex")) - md = checkfield(md,'fieldname','mesh.x','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.y','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.z','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.elements','NaN',1,'Inf',1,'>',0,'values',np.arange(1,md.mesh.numberofvertices+1)) - md = checkfield(md,'fieldname','mesh.elements','size',[md.mesh.numberofelements,6]) - if np.any(np.logical_not(m.ismember(np.arange(1,md.mesh.numberofvertices+1),md.mesh.elements))): - md.checkmessage("orphan nodes have been found. Check the mesh3dprisms outline") - md = checkfield(md,'fieldname','mesh.numberoflayers','>=',0) - md = checkfield(md,'fieldname','mesh.numberofelements','>',0) - md = checkfield(md,'fieldname','mesh.numberofvertices','>',0) - md = checkfield(md,'fieldname','mesh.vertexonbase','size',[md.mesh.numberofvertices],'values',[0,1]) - md = checkfield(md,'fieldname','mesh.vertexonsurface','size',[md.mesh.numberofvertices],'values',[0,1]) - md = checkfield(md,'fieldname','mesh.average_vertex_connectivity','>=',24,'message',"'mesh.average_vertex_connectivity' should be at least 24 in 3d") - if(np.size(self.scale_factor)>1): - md = checkfield(md,'fieldname','mesh.scale_factor','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) + string = "%s%s" % (string, "\n\n Extracted model:") + string = "%s\n%s" % (string, fielddisplay(self, "extractedvertices", "vertices extracted from the model")) + string = "%s\n%s" % (string, fielddisplay(self, "extractedelements", "elements extracted from the model")) - return md - # }}} - def domaintype(self): # {{{ - return "3D" - #}}} - def dimension(self): # {{{ - return 3 - #}}} - def elementtype(self): # {{{ - return "Penta" - #}}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.mesh.domain_type','data',"Domain"+self.domaintype(),'format','String'); - WriteData(fid,prefix,'name','md.mesh.domain_dimension','data',self.dimension(),'format','Integer'); - WriteData(fid,prefix,'name','md.mesh.elementtype','data',self.elementtype(),'format','String'); - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','x','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','y','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','z','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','elements','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','numberoflayers','format','Integer') - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','numberofelements','format','Integer') - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','numberofvertices','format','Integer') - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','vertexonbase','format','BooleanMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','vertexonsurface','format','BooleanMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','lowerelements','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','upperelements','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','average_vertex_connectivity','format','Integer') - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','elements2d','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','numberofvertices2d','format','Integer') - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','numberofelements2d','format','Integer') - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','scale_factor','format','DoubleMat','mattype',1) - if md.transient.isoceancoupling: - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','lat','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','mesh','fieldname','long','format','DoubleMat','mattype',1) - # }}} + string = "%s%s" % (string, "\n\n Projection:") + string = "%s\n%s" % (string, fielddisplay(self, "lat", "vertices latitude [degrees]")) + string = "%s\n%s" % (string, fielddisplay(self, "long", "vertices longitude [degrees]")) + string = "%s\n%s" % (string, fielddisplay(self, "epsg", "EPSG code (ex: 3413 for UPS Greenland, 3031 for UPS Antarctica)")) + string = "%s\n%s" % (string, fielddisplay(self, "scale_factor", "Projection correction for volume, area, etc. computation")) + return string + #}}} + + def setdefaultparameters(self): # {{{ + #the connectivity is the averaged number of nodes linked to a + #given node through an edge. This connectivity is used to initially + #allocate memory to the stiffness matrix. A value of 16 seems to + #give a good memory / time ration. This value can be checked in + #trunk / test / Miscellaneous / runme.m + self.average_vertex_connectivity = 25 + + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'mesh.x', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.y', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.z', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.elements', 'NaN', 1, 'Inf', 1, '>', 0, 'values', np.arange(1, md.mesh.numberofvertices + 1)) + md = checkfield(md, 'fieldname', 'mesh.elements', 'size', [md.mesh.numberofelements, 6]) + if np.any(np.logical_not(m.ismember(np.arange(1, md.mesh.numberofvertices + 1), md.mesh.elements))): + md.checkmessage("orphan nodes have been found. Check the mesh3dprisms outline") + md = checkfield(md, 'fieldname', 'mesh.numberoflayers', '>=', 0) + md = checkfield(md, 'fieldname', 'mesh.numberofelements', '>', 0) + md = checkfield(md, 'fieldname', 'mesh.numberofvertices', '>', 0) + md = checkfield(md, 'fieldname', 'mesh.vertexonbase', 'size', [md.mesh.numberofvertices], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'mesh.vertexonsurface', 'size', [md.mesh.numberofvertices], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'mesh.average_vertex_connectivity', '>=', 24, 'message', "'mesh.average_vertex_connectivity' should be at least 24 in 3d") + if(np.size(self.scale_factor) > 1): + md = checkfield(md, 'fieldname', 'mesh.scale_factor', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + + return md + # }}} + + def domaintype(self): # {{{ + return "3D" + #}}} + + def dimension(self): # {{{ + return 3 + #}}} + + def elementtype(self): # {{{ + return "Penta" + #}}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.mesh.domain_type', 'data', "Domain" + self.domaintype(), 'format', 'String') + WriteData(fid, prefix, 'name', 'md.mesh.domain_dimension', 'data', self.dimension(), 'format', 'Integer') + WriteData(fid, prefix, 'name', 'md.mesh.elementtype', 'data', self.elementtype(), 'format', 'String') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'x', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'y', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'z', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'elements', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'numberoflayers', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'numberofelements', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'numberofvertices', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'vertexonbase', 'format', 'BooleanMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'vertexonsurface', 'format', 'BooleanMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'lowerelements', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'upperelements', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'average_vertex_connectivity', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'elements2d', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'numberofvertices2d', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'numberofelements2d', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'scale_factor', 'format', 'DoubleMat', 'mattype', 1) + if md.transient.isoceancoupling: + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'lat', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'mesh', 'fieldname', 'long', 'format', 'DoubleMat', 'mattype', 1) + # }}} Index: /issm/trunk-jpl/src/m/classes/mesh3dsurface.py =================================================================== --- /issm/trunk-jpl/src/m/classes/mesh3dsurface.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/mesh3dsurface.py (revision 24213) @@ -6,187 +6,193 @@ from WriteData import WriteData + class mesh3dsurface(object): -#MESH3DSURFACE class definition -# -# Usage: -# mesh3dsurface=mesh3dsurface(); - def __init__(self,*args): # {{{ - self.x = np.nan - self.y = np.nan - self.z = np.nan - self.elements = np.nan - self.numberofelements = 0 - self.numberofvertices = 0 - self.numberofedges = 0 + #MESH3DSURFACE class definition + # + # Usage: + # mesh3dsurface = mesh3dsurface(); + def __init__(self, *args): # {{{ + self.x = np.nan + self.y = np.nan + self.z = np.nan + self.elements = np.nan + self.numberofelements = 0 + self.numberofvertices = 0 + self.numberofedges = 0 - self.lat = np.nan - self.long = np.nan - self.r = np.nan + self.lat = np.nan + self.long = np.nan + self.r = np.nan - self.vertexonboundary = np.nan - self.edges = np.nan - self.segments = np.nan - self.segmentmarkers = np.nan - self.vertexconnectivity = np.nan - self.elementconnectivity = np.nan - self.average_vertex_connectivity = 0 + self.vertexonboundary = np.nan + self.edges = np.nan + self.segments = np.nan + self.segmentmarkers = np.nan + self.vertexconnectivity = np.nan + self.elementconnectivity = np.nan + self.average_vertex_connectivity = 0 - self.extractedvertices = np.nan - self.extractedelements = np.nan - - if not len(args): - self.setdefaultparameters() - elif len(args)==1: - self=mesh3dsurface() - arg=args[1] - fields=fieldnames(arg) - for i in range(len(fields)): - field=fields[i] - if ismember(field,properties('mesh3dsurface')): - self.field=arg.field - else: - raise RuntimeError('constructor not supported') + self.extractedvertices = np.nan + self.extractedelements = np.nan - # }}} - def __repr__(self): # {{{ - string=' 2D tria Mesh (horizontal):' - - string+='\n Elements and vertices:' - string="%s\n%s"%(string,fielddisplay(self,'numberofelements','number of elements')) - string="%s\n%s"%(string,fielddisplay(self,'numberofvertices','number of vertices')) - string="%s\n%s"%(string,fielddisplay(self,'elements','vertex indices of the mesh elements')) - string="%s\n%s"%(string,fielddisplay(self,'x','vertices x coordinate [m]')) - string="%s\n%s"%(string,fielddisplay(self,'y','vertices y coordinate [m]')) - string="%s\n%s"%(string,fielddisplay(self,'z','vertices z coordinate [m]')) - string="%s\n%s"%(string,fielddisplay(self,'lat','vertices latitude [degrees]')) - string="%s\n%s"%(string,fielddisplay(self,'long','vertices longitude [degrees]')) - string="%s\n%s"%(string,fielddisplay(self,'r','vertices radius [m]')) - - string="%s\n%s"%(string,fielddisplay(self,'edges','edges of the 2d mesh (vertex1 vertex2 element1 element2)')) - string="%s\n%s"%(string,fielddisplay(self,'numberofedges','number of edges of the 2d mesh')) + if not len(args): + self.setdefaultparameters() + elif len(args) == 1: + self = mesh3dsurface() + arg = args[1] + fields = fieldnames(arg) + for i in range(len(fields)): + field = fields[i] + if ismember(field, properties('mesh3dsurface')): + self.field = arg.field + else: + raise RuntimeError('constructor not supported') - string+='\n Properties:' - string="%s\n%s"%(string,fielddisplay(self,'vertexonboundary','vertices on the boundary of the domain flag list')) - string="%s\n%s"%(string,fielddisplay(self,'segments','edges on domain boundary (vertex1 vertex2 element)')) - string="%s\n%s"%(string,fielddisplay(self,'segmentmarkers','number associated to each segment')) - string="%s\n%s"%(string,fielddisplay(self,'vertexconnectivity','list of elements connected to vertex_i')) - string="%s\n%s"%(string,fielddisplay(self,'elementconnectivity','list of elements adjacent to element_i')) - string="%s\n%s"%(string,fielddisplay(self,'average_vertex_connectivity','average number of vertices connected to one vertex')) + # }}} - string+='\n Extracted model():' - string="%s\n%s"%(string,fielddisplay(self,'extractedvertices','vertices extracted from the model()')) - string="%s\n%s"%(string,fielddisplay(self,'extractedelements','elements extracted from the model()')) - - return string - # }}} - def loadobj(self): # {{{ - # This def is directly called by matlab when a model() selfect is - # loaded. Update old properties here + def __repr__(self): # {{{ + string = ' 2D tria Mesh (horizontal):' - #2014 Oct. 1st - if isstruct(self): - oldself=self - #Assign property values from struct - self=structtoobj(mesh3dsurface(),oldself) - if isfield(oldself,'hemisphere'): - print ('md.mesh.hemisphere has been automatically converted to EPSG code') - if strcmpi(oldself.hemisphere,'n'): - self.epsg=3413 - else: - self.epsg=3031 - return self - # }}} - def setdefaultparameters(self): # {{{ + string += '\n Elements and vertices:' + string = "%s\n%s" % (string, fielddisplay(self, 'numberofelements', 'number of elements')) + string = "%s\n%s" % (string, fielddisplay(self, 'numberofvertices', 'number of vertices')) + string = "%s\n%s" % (string, fielddisplay(self, 'elements', 'vertex indices of the mesh elements')) + string = "%s\n%s" % (string, fielddisplay(self, 'x', 'vertices x coordinate [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'y', 'vertices y coordinate [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'z', 'vertices z coordinate [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'lat', 'vertices latitude [degrees]')) + string = "%s\n%s" % (string, fielddisplay(self, 'long', 'vertices longitude [degrees]')) + string = "%s\n%s" % (string, fielddisplay(self, 'r', 'vertices radius [m]')) - #the connectivity is the averaged number of nodes linked to a - #given node through an edge. This connectivity is used to initially - #allocate memory to the stiffness matrix. A value of 16 seems to - #give a good memory/time ration. This value can be checked in - #trunk/test/Miscellaneous/runme.m - self.average_vertex_connectivity=25 - return self - # }}} - def checkconsistency(self,md,solution,analyses): # {{{ + string = "%s\n%s" % (string, fielddisplay(self, 'edges', 'edges of the 2d mesh (vertex1 vertex2 element1 element2)')) + string = "%s\n%s" % (string, fielddisplay(self, 'numberofedges', 'number of edges of the 2d mesh')) - md = checkfield(md,'fieldname','mesh.x','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.y','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.z','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.lat','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.long','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.r','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','mesh.elements','NaN',1,'Inf',1,'>',0,'values',np.arange(1,md.mesh.numberofvertices+1)) - md = checkfield(md,'fieldname','mesh.elements','size',[md.mesh.numberofelements,3]) - if np.any(np.logical_not(np.in1d(np.arange(1,md.mesh.numberofvertices+1),md.mesh.elements.flat))): - md = checkmessage(md,'orphan nodes have been found. Check the mesh outline') - - md = checkfield(md,'fieldname','mesh.numberofelements','>',0) - md = checkfield(md,'fieldname','mesh.numberofvertices','>',0) - md = checkfield(md,'fieldname','mesh.average_vertex_connectivity','>=',9,'message','"mesh.average_vertex_connectivity" should be at least 9 in 2d') + string += '\n Properties:' + string = "%s\n%s" % (string, fielddisplay(self, 'vertexonboundary', 'vertices on the boundary of the domain flag list')) + string = "%s\n%s" % (string, fielddisplay(self, 'segments', 'edges on domain boundary (vertex1 vertex2 element)')) + string = "%s\n%s" % (string, fielddisplay(self, 'segmentmarkers', 'number associated to each segment')) + string = "%s\n%s" % (string, fielddisplay(self, 'vertexconnectivity', 'list of elements connected to vertex_i')) + string = "%s\n%s" % (string, fielddisplay(self, 'elementconnectivity', 'list of elements adjacent to element_i')) + string = "%s\n%s" % (string, fielddisplay(self, 'average_vertex_connectivity', 'average number of vertices connected to one vertex')) - if (solution=='ThermalSolution'): - md = checkmessage(md,'thermal not supported for 2d mesh'); - - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'name','md.mesh.domain_type','data','Domain' + self.domaintype(),'format','String') - WriteData(fid,prefix,'name','md.mesh.domain_dimension','data',self.dimension(),'format','Integer') - WriteData(fid,prefix,'name','md.mesh.elementtype','data',self.elementtype(),'format','String') - WriteData(fid,prefix,'object',self,'fieldname','x','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','y','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','z','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','lat','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','long','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','r','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'name','md.mesh.z','data',np.zeros(md.mesh.numberofvertices),'format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','elements','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'fieldname','numberofelements','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','numberofvertices','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','average_vertex_connectivity','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','vertexonboundary','format','DoubleMat','mattype',1) - # }}} - def domaintype(self): # {{{ - return '3Dsurface' - # }}} - def dimension(self): # {{{ - return 2 - # }}} - def elementtype(self): # {{{ - return 'Tria' - # }}} - def processmesh(self,options): # {{{ - - isplanet = 1 - is2d = 0 + string += '\n Extracted model():' + string = "%s\n%s" % (string, fielddisplay(self, 'extractedvertices', 'vertices extracted from the model()')) + string = "%s\n%s" % (string, fielddisplay(self, 'extractedelements', 'elements extracted from the model()')) - elements = self.elements - x = self.x - y = self.y - z = self.z - return [x, y, z, elements, is2d, isplanet] - # }}} - def savemodeljs(self,fid,modelname): # {{{ - - fid.write('#s.mesh=new mesh3dsurface()\n'%modelname) - writejs1Darray(fid,[modelname, '.mesh.x'],self.x) - writejs1Darray(fid,[modelname, '.mesh.y'],self.y) - writejs1Darray(fid,[modelname, '.mesh.z'],self.z) - writejs2Darray(fid,[modelname, '.mesh.elements'],self.elements) - writejsdouble(fid,[modelname, '.mesh.numberofelements'],self.numberofelements) - writejsdouble(fid,[modelname, '.mesh.numberofvertices'],self.numberofvertices) - writejsdouble(fid,[modelname, '.mesh.numberofedges'],self.numberofedges) - writejs1Darray(fid,[modelname, '.mesh.lat'],self.lat) - writejs1Darray(fid,[modelname, '.mesh.long'],self.long) - writejs1Darray(fid,[modelname, '.mesh.r'],self.r) - writejs1Darray(fid,[modelname, '.mesh.vertexonboundary'],self.vertexonboundary) - writejs2Darray(fid,[modelname, '.mesh.edges'],self.edges) - writejs2Darray(fid,[modelname, '.mesh.segments'],self.segments) - writejs2Darray(fid,[modelname, '.mesh.segmentmarkers'],self.segmentmarkers) - writejs2Darray(fid,[modelname, '.mesh.vertexconnectivity'],self.vertexconnectivity) - writejs2Darray(fid,[modelname, '.mesh.elementconnectivity'],self.elementconnectivity) - writejsdouble(fid,[modelname, '.mesh.average_vertex_connectivity'],self.average_vertex_connectivity) - writejs1Darray(fid,[modelname, '.mesh.extractedvertices'],self.extractedvertices) - writejs1Darray(fid,[modelname, '.mesh.extractedelements'],self.extractedelements) + return string + # }}} - # }}} - + def loadobj(self): # {{{ + # This def is directly called by matlab when a model() selfect is + # loaded. Update old properties here + + #2014 Oct. 1st + if isstruct(self): + oldself = self + #Assign property values from struct + self = structtoobj(mesh3dsurface(), oldself) + if isfield(oldself, 'hemisphere'): + print('md.mesh.hemisphere has been automatically converted to EPSG code') + if strcmpi(oldself.hemisphere, 'n'): + self.epsg = 3413 + else: + self.epsg = 3031 + return self + # }}} + + def setdefaultparameters(self): # {{{ + #the connectivity is the averaged number of nodes linked to a + #given node through an edge. This connectivity is used to initially + #allocate memory to the stiffness matrix. A value of 16 seems to + #give a good memory / time ration. This value can be checked in + #trunk / test / Miscellaneous / runme.m + self.average_vertex_connectivity = 25 + return self + # }}} + + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'mesh.x', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.y', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.z', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.lat', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.long', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.r', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'mesh.elements', 'NaN', 1, 'Inf', 1, '>', 0, 'values', np.arange(1, md.mesh.numberofvertices + 1)) + md = checkfield(md, 'fieldname', 'mesh.elements', 'size', [md.mesh.numberofelements, 3]) + if np.any(np.logical_not(np.in1d(np.arange(1, md.mesh.numberofvertices + 1), md.mesh.elements.flat))): + md = checkmessage(md, 'orphan nodes have been found. Check the mesh outline') + + md = checkfield(md, 'fieldname', 'mesh.numberofelements', '>', 0) + md = checkfield(md, 'fieldname', 'mesh.numberofvertices', '>', 0) + md = checkfield(md, 'fieldname', 'mesh.average_vertex_connectivity', '>=', 9, 'message', '"mesh.average_vertex_connectivity" should be at least 9 in 2d') + + if (solution == 'ThermalSolution'): + md = checkmessage(md, 'thermal not supported for 2d mesh') + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'name', 'md.mesh.domain_type', 'data', 'Domain' + self.domaintype(), 'format', 'String') + WriteData(fid, prefix, 'name', 'md.mesh.domain_dimension', 'data', self.dimension(), 'format', 'Integer') + WriteData(fid, prefix, 'name', 'md.mesh.elementtype', 'data', self.elementtype(), 'format', 'String') + WriteData(fid, prefix, 'object', self, 'fieldname', 'x', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'y', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'z', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'lat', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'long', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'r', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'name', 'md.mesh.z', 'data', np.zeros(md.mesh.numberofvertices), 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'elements', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'fieldname', 'numberofelements', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'numberofvertices', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'average_vertex_connectivity', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'vertexonboundary', 'format', 'DoubleMat', 'mattype', 1) + # }}} + + def domaintype(self): # {{{ + return '3Dsurface' + # }}} + + def dimension(self): # {{{ + return 2 + # }}} + + def elementtype(self): # {{{ + return 'Tria' + # }}} + + def processmesh(self, options): # {{{ + isplanet = 1 + is2d = 0 + + elements = self.elements + x = self.x + y = self.y + z = self.z + return [x, y, z, elements, is2d, isplanet] + # }}} + + def savemodeljs(self, fid, modelname): # {{{ + fid.write(' #s.mesh = new mesh3dsurface()\n' % modelname) + writejs1Darray(fid, [modelname, '.mesh.x'], self.x) + writejs1Darray(fid, [modelname, '.mesh.y'], self.y) + writejs1Darray(fid, [modelname, '.mesh.z'], self.z) + writejs2Darray(fid, [modelname, '.mesh.elements'], self.elements) + writejsdouble(fid, [modelname, '.mesh.numberofelements'], self.numberofelements) + writejsdouble(fid, [modelname, '.mesh.numberofvertices'], self.numberofvertices) + writejsdouble(fid, [modelname, '.mesh.numberofedges'], self.numberofedges) + writejs1Darray(fid, [modelname, '.mesh.lat'], self.lat) + writejs1Darray(fid, [modelname, '.mesh.long'], self.long) + writejs1Darray(fid, [modelname, '.mesh.r'], self.r) + writejs1Darray(fid, [modelname, '.mesh.vertexonboundary'], self.vertexonboundary) + writejs2Darray(fid, [modelname, '.mesh.edges'], self.edges) + writejs2Darray(fid, [modelname, '.mesh.segments'], self.segments) + writejs2Darray(fid, [modelname, '.mesh.segmentmarkers'], self.segmentmarkers) + writejs2Darray(fid, [modelname, '.mesh.vertexconnectivity'], self.vertexconnectivity) + writejs2Darray(fid, [modelname, '.mesh.elementconnectivity'], self.elementconnectivity) + writejsdouble(fid, [modelname, '.mesh.average_vertex_connectivity'], self.average_vertex_connectivity) + writejs1Darray(fid, [modelname, '.mesh.extractedvertices'], self.extractedvertices) + writejs1Darray(fid, [modelname, '.mesh.extractedelements'], self.extractedelements) + + # }}} Index: /issm/trunk-jpl/src/m/classes/miscellaneous.py =================================================================== --- /issm/trunk-jpl/src/m/classes/miscellaneous.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/miscellaneous.py (revision 24213) @@ -4,37 +4,41 @@ from WriteData import WriteData + class miscellaneous(object): - """ - MISCELLANEOUS class definition + """ + MISCELLANEOUS class definition - Usage: - miscellaneous=miscellaneous(); - """ + Usage: + miscellaneous = miscellaneous() + """ - def __init__(self): # {{{ - self.notes = '' - self.name = '' - self.dummy = OrderedDict() + def __init__(self): # {{{ + self.notes = '' + self.name = '' + self.dummy = OrderedDict() - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' miscellaneous parameters:' + #}}} + def __repr__(self): # {{{ + string = ' miscellaneous parameters:' - string="%s\n%s"%(string,fielddisplay(self,'notes','notes in a cell of strings')) - string="%s\n%s"%(string,fielddisplay(self,'name','model name')) - string="%s\n%s"%(string,fielddisplay(self,'dummy','empty field to store some data')) - return string - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - md = checkfield(md,'fieldname','miscellaneous.name','empty',1) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','name','format','String'); - # }}} + string = "%s\n%s" % (string, fielddisplay(self, 'notes', 'notes in a cell of strings')) + string = "%s\n%s" % (string, fielddisplay(self, 'name', 'model name')) + string = "%s\n%s" % (string, fielddisplay(self, 'dummy', 'empty field to store some data')) + return string + #}}} + + def setdefaultparameters(self): # {{{ + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'miscellaneous.name', 'empty', 1) + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'name', 'format', 'String') + # }}} Index: /issm/trunk-jpl/src/m/classes/misfit.py =================================================================== --- /issm/trunk-jpl/src/m/classes/misfit.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/misfit.py (revision 24213) @@ -1,6 +1,4 @@ import numpy as np from project3d import project3d -from pairoptions import * -from collections import OrderedDict from fielddisplay import fielddisplay from checkfield import checkfield @@ -9,101 +7,91 @@ class misfit(object): - """ - MISFIT class definition + """ + MISFIT class definition - Usage: - misfit=misfit() - misfit=misfit(name='SurfaceAltimetry', - definitionstring='Outputdefinition1', - model_string='Surface', - observation_string='SurfaceObservations', - observation=md.geometry.surface, - timeinterpolation='nearestneighbor', - local=1, - weights=np.ones((md.mesh.numberofvertices,1)), - weights_string='WeightsSurfaceObservations') - """ + Usage: + misfit = misfit() + misfit = misfit(name = 'SurfaceAltimetry', + definitionstring = 'Outputdefinition1', + model_string = 'Surface', + observation_string = 'SurfaceObservations', + observation = md.geometry.surface, + timeinterpolation = 'nearestneighbor', + local = 1, + weights = np.ones((md.mesh.numberofvertices, 1)), + weights_string = 'WeightsSurfaceObservations') + """ - def __init__(self, name = None, definitionstring = None, model_string = None, observation = None, observation_string = None, timeinterpolation = None, local = None, weights = None, weights_string = None, cumulated = None): - # {{{ - self.name = name if name is not None else '' + def __init__(self, name=None, definitionstring=None, model_string=None, observation=None, observation_string=None, timeinterpolation=None, local=None, weights=None, weights_string=None, cumulated=None): # {{{ + self.name = name if name is not None else '' + #string that identifies this output definition uniquely, from 'Outputdefinition[1 - 100]' + self.definitionstring = definitionstring if definitionstring is not None else '' + #string for field that is modeled + self.model_string = model_string if model_string is not None else '' + #observed field that we compare the model against + self.observation = observation if observation is not None else float('NaN') + #string for observed field. + self.observation_string = observation_string if observation_string is not None else '' + self.timeinterpolation = timeinterpolation if timeinterpolation is not None else 'nearestneighbor' + self.local = local if local is not None else 1 + #weight coefficients for every vertex + self.weights = weights if weights is not None else float('NaN') + #string to identify this particular set of weights + self.weights_string = weights_string if weights_string is not None else '' + #do we cumulate misfit through time? + self.cumulated = cumulated if cumulated is not None else float('NaN') + #}}} - #string that identifies this output definition uniquely, from 'Outputdefinition[1-100]' - self.definitionstring = definitionstring if definitionstring is not None else '' + def __repr__(self): # {{{ + string = ' Misfit:' - #string for field that is modeled - self.model_string = model_string if model_string is not None else '' + string = "%s\n%s" % (string, fielddisplay(self, 'name', 'identifier for this misfit response')) + string = "%s\n%s" % (string, fielddisplay(self, 'definitionstring', 'string that identifies this output definition uniquely, from "Outputdefinition[1 - 10]"')) + string = "%s\n%s" % (string, fielddisplay(self, 'model_string', 'string for field that is modeled')) + string = "%s\n%s" % (string, fielddisplay(self, 'observation', 'observed field that we compare the model against')) + string = "%s\n%s" % (string, fielddisplay(self, 'observation_string', 'observation string')) + string = "%s\n%s" % (string, fielddisplay(self, 'local', 'is the response local to the elements, or global? (default is 1)')) + string = "%s\n%s" % (string, fielddisplay(self, 'timeinterpolation', 'interpolation routine used to interpolate misfit between two time steps (default is "nearestneighbor"')) + string = "%s\n%s" % (string, fielddisplay(self, 'weights', 'weights (at vertices) to apply to the misfit')) + string = "%s\n%s" % (string, fielddisplay(self, 'weights_string', 'string for weights for identification purposes')) + return string + #}}} - #observed field that we compare the model against - self.observation = observation if observation is not None else float('NaN') + def extrude(self, md): # {{{ + if not np.any(np.isnan(self.weights)): + self.weights = project3d(md, 'vector', self.weights, 'type', 'node') + if not np.any(np.isnan(self.observation)): + self.observation = project3d(md, 'vector', self.observation, 'type', 'node') + return self + #}}} - #string for observed field. - self.observation_string = observation_string if observation_string is not None else '' + def checkconsistency(self, md, solution, analyses): # {{{ + if type(self.name) != str: + raise TypeError('misfit error message: "name" field should be a string!') - self.timeinterpolation = timeinterpolation if timeinterpolation is not None else 'nearestneighbor' + OutputdefinitionStringArray = [] + for i in range(100): + OutputdefinitionStringArray.append('Outputdefinition' + str(i)) - self.local = local if local is not None else 1 + md = checkfield(md, 'fieldname', 'self.definitionstring', 'field', self.definitionstring, 'values', OutputdefinitionStringArray) + if type(self.timeinterpolation) != str: + raise TypeError('misfit error message: "timeinterpolation" field should be a string!') - #weight coefficients for every vertex - self.weights = weights if weights is not None else float('NaN') + md = checkfield(md, 'fieldname', 'self.observation', 'field', self.observation, 'timeseries', 1, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'self.timeinterpolation', 'field', self.timeinterpolation, 'values', ['nearestneighbor']) + md = checkfield(md, 'fieldname', 'self.weights', 'field', self.weights, 'timeseries', 1, 'NaN', 1, 'Inf', 1) - #string to identify this particular set of weights - self.weights_string = weights_string if weights_string is not None else '' + return md + # }}} - #do we cumulate misfit through time? - self.cumulated = cumulated if cumulated is not None else float('NaN') - #}}} - - def __repr__(self): # {{{ - string=' Misfit:' - - string="%s\n%s"%(string,fielddisplay(self,'name','identifier for this misfit response')) - string="%s\n%s"%(string,fielddisplay(self,'definitionstring','string that identifies this output definition uniquely, from "Outputdefinition[1-10]"')) - string="%s\n%s"%(string,fielddisplay(self,'model_string','string for field that is modeled')) - string="%s\n%s"%(string,fielddisplay(self,'observation','observed field that we compare the model against')) - string="%s\n%s"%(string,fielddisplay(self,'observation_string','observation string')) - string="%s\n%s"%(string,fielddisplay(self,'local','is the response local to the elements, or global? (default is 1)')) - string="%s\n%s"%(string,fielddisplay(self,'timeinterpolation','interpolation routine used to interpolate misfit between two time steps (default is "nearestneighbor"')) - string="%s\n%s"%(string,fielddisplay(self,'weights','weights (at vertices) to apply to the misfit')) - string="%s\n%s"%(string,fielddisplay(self,'weights_string','string for weights for identification purposes')) - return string - #}}} - - def extrude(self,md): # {{{ - if not np.any(np.isnan(self.weights)): - self.weights = project3d(md,'vector',self.weights,'type','node') - if not np.any(np.isnan(self.observation)): - self.observation = project3d(md,'vector',self.observation,'type','node') - return self - #}}} - - def checkconsistency(self,md,solution,analyses): # {{{ - if type(self.name) != str: - raise TypeError('misfit error message: "name" field should be a string!') - - OutputdefinitionStringArray = [] - for i in range(100): - OutputdefinitionStringArray.append('Outputdefinition' + str(i)) - - md = checkfield(md,'fieldname','self.definitionstring','field',self.definitionstring,'values',OutputdefinitionStringArray) - if type(self.timeinterpolation) != str: - raise TypeError('misfit error message: "timeinterpolation" field should be a string!') - - md = checkfield(md,'fieldname','self.observation','field',self.observation,'timeseries',1,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','self.timeinterpolation','field',self.timeinterpolation,'values',['nearestneighbor']) - md = checkfield(md,'fieldname','self.weights','field',self.weights,'timeseries',1,'NaN',1,'Inf',1) - - return md - # }}} - - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'data',self.name,'name','md.misfit.name','format','String') - WriteData(fid,prefix,'data',self.definitionstring,'name','md.misfit.definitionstring','format','String') - WriteData(fid,prefix,'data',self.model_string,'name','md.misfit.model_string','format','String') - WriteData(fid,prefix,'data',self.observation,'name','md.misfit.observation','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'data',self.observation_string,'name','md.misfit.observation_string','format','String') - WriteData(fid,prefix,'data',self.local,'name','md.misfit.local','format','Integer') - WriteData(fid,prefix,'data',self.timeinterpolation,'name','md.misfit.timeinterpolation','format','String') - WriteData(fid,prefix,'data',self.weights,'name','md.misfit.weights','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'data',self.weights_string,'name','md.misfit.weights_string','format','String') - # }}} + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'data', self.name, 'name', 'md.misfit.name', 'format', 'String') + WriteData(fid, prefix, 'data', self.definitionstring, 'name', 'md.misfit.definitionstring', 'format', 'String') + WriteData(fid, prefix, 'data', self.model_string, 'name', 'md.misfit.model_string', 'format', 'String') + WriteData(fid, prefix, 'data', self.observation, 'name', 'md.misfit.observation', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'data', self.observation_string, 'name', 'md.misfit.observation_string', 'format', 'String') + WriteData(fid, prefix, 'data', self.local, 'name', 'md.misfit.local', 'format', 'Integer') + WriteData(fid, prefix, 'data', self.timeinterpolation, 'name', 'md.misfit.timeinterpolation', 'format', 'String') + WriteData(fid, prefix, 'data', self.weights, 'name', 'md.misfit.weights', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'data', self.weights_string, 'name', 'md.misfit.weights_string', 'format', 'String') + # }}} Index: /issm/trunk-jpl/src/m/classes/mismipbasalforcings.py =================================================================== --- /issm/trunk-jpl/src/m/classes/mismipbasalforcings.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/mismipbasalforcings.py (revision 24213) @@ -5,83 +5,90 @@ import numpy as np + class mismipbasalforcings(object): - """ - MISMIP Basal Forcings class definition + """ + MISMIP Basal Forcings class definition - Usage: - mismipbasalforcings=mismipbasalforcings() - """ + Usage: + mismipbasalforcings = mismipbasalforcings() + """ - def __init__(self): # {{{ - self.groundedice_melting_rate = float('NaN') - self.meltrate_factor = float('NaN') - self.threshold_thickness = float('NaN') - self.upperdepth_melt = float('NaN') - self.geothermalflux = float('NaN') - self.setdefaultparameters() + def __init__(self): # {{{ + self.groundedice_melting_rate = float('NaN') + self.meltrate_factor = float('NaN') + self.threshold_thickness = float('NaN') + self.upperdepth_melt = float('NaN') + self.geothermalflux = float('NaN') + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=" MISMIP+ basal melt parameterization\n" - string="%s\n%s"%(string,fielddisplay(self,"groundedice_melting_rate","basal melting rate (positive if melting) [m/yr]")) - string="%s\n%s"%(string,fielddisplay(self,"meltrate_factor","Melt-rate rate factor [1/yr] (sign is opposite to MISMIP+ benchmark to remain consistent with ISSM convention of positive values for melting)")) - string="%s\n%s"%(string,fielddisplay(self,"threshold_thickness","Threshold thickness for saturation of basal melting [m]")) - string="%s\n%s"%(string,fielddisplay(self,"upperdepth_melt","Depth above which melt rate is zero [m]")) - string="%s\n%s"%(string,fielddisplay(self,"geothermalflux","Geothermal heat flux [W/m^2]")) - return string - #}}} - def extrude(self,md): # {{{ - self.groundedice_melting_rate=project3d(md,'vector',self.groundedice_melting_rate,'type','node','layer',1) - self.geothermalflux=project3d(md,'vector',self.geothermalflux,'type','node','layer',1) #bedrock only gets geothermal flux - return self - #}}} - def initialize(self,md): # {{{ - if np.all(np.isnan(self.groundedice_melting_rate)): - self.groundedice_melting_rate=np.zeros((md.mesh.numberofvertices)) - print(' no basalforcings.groundedice_melting_rate specified: values set as zero') - if np.all(np.isnan(self.geothermalflux)): - self.geothermalflux=np.zeros((md.mesh.numberofvertices)) - print(" no basalforcings.geothermalflux specified: values set as zero") - return self - #}}} - def setdefaultparameters(self): # {{{ - # default values for melting parameterization - self.meltrate_factor = 0.2 - self.threshold_thickness = 75. - self.upperdepth_melt = -100. - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - #Early return - if 'MasstransportAnalysis' in analyses and not (solution=='TransientSolution' and md.transient.ismasstransport==0): - md = checkfield(md,'fieldname','basalforcings.groundedice_melting_rate','NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','basalforcings.meltrate_factor','>=',0,'numel',[1]) - md = checkfield(md,'fieldname','basalforcings.threshold_thickness','>=',0,'numel',[1]) - md = checkfield(md,'fieldname','basalforcings.upperdepth_melt','<=',0,'numel',[1]) + #}}} - if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','basalforcings.groundedice_melting_rate','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','basalforcings.meltrate_factor','>=',0,'numel',[1]) - md = checkfield(md,'fieldname','basalforcings.threshold_thickness','>=',0,'numel',[1]) - md = checkfield(md,'fieldname','basalforcings.upperdepth_melt','<=',0,'numel',[1]) + def __repr__(self): # {{{ + string = " MISMIP + basal melt parameterization\n" + string = "%s\n%s" % (string, fielddisplay(self, "groundedice_melting_rate", "basal melting rate (positive if melting) [m / yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "meltrate_factor", "Melt - rate rate factor [1 / yr] (sign is opposite to MISMIP + benchmark to remain consistent with ISSM convention of positive values for melting)")) + string = "%s\n%s" % (string, fielddisplay(self, "threshold_thickness", "Threshold thickness for saturation of basal melting [m]")) + string = "%s\n%s" % (string, fielddisplay(self, "upperdepth_melt", "Depth above which melt rate is zero [m]")) + string = "%s\n%s" % (string, fielddisplay(self, "geothermalflux", "Geothermal heat flux [W / m^2]")) + return string + #}}} - if 'ThermalAnalysis' in analyses and not (solution=='TransientSolution' and md.transient.isthermal==0): - md = checkfield(md,'fieldname','basalforcings.groundedice_melting_rate','NaN',1,'Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','basalforcings.meltrate_factor','>=',0,'numel',[1]) - md = checkfield(md,'fieldname','basalforcings.threshold_thickness','>=',0,'numel',[1]) - md = checkfield(md,'fieldname','basalforcings.upperdepth_melt','<=',0,'numel',[1]) - md = checkfield(md,'fieldname','basalforcings.geothermalflux','NaN',1,'Inf',1,'timeseries',1,'>=',0) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts - if yts!=365.2422*24.*3600.: - print('WARNING: value of yts for MISMIP+ runs different from ISSM default!') + def extrude(self, md): # {{{ + self.groundedice_melting_rate = project3d(md, 'vector', self.groundedice_melting_rate, 'type', 'node', 'layer', 1) + self.geothermalflux = project3d(md, 'vector', self.geothermalflux, 'type', 'node', 'layer', 1) #bedrock only gets geothermal flux + return self + #}}} - WriteData(fid,prefix,'name','md.basalforcings.model','data',3,'format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','groundedice_melting_rate','format','DoubleMat','name','md.basalforcings.groundedice_melting_rate','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','geothermalflux','name','md.basalforcings.geothermalflux','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','meltrate_factor','format','Double','scale',1./yts) - WriteData(fid,prefix,'object',self,'fieldname','threshold_thickness','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','upperdepth_melt','format','Double') + def initialize(self, md): # {{{ + if np.all(np.isnan(self.groundedice_melting_rate)): + self.groundedice_melting_rate = np.zeros((md.mesh.numberofvertices)) + print(' no basalforcings.groundedice_melting_rate specified: values set as zero') + if np.all(np.isnan(self.geothermalflux)): + self.geothermalflux = np.zeros((md.mesh.numberofvertices)) + print(" no basalforcings.geothermalflux specified: values set as zero") + return self + #}}} + + def setdefaultparameters(self): # {{{ + # default values for melting parameterization + self.meltrate_factor = 0.2 + self.threshold_thickness = 75. + self.upperdepth_melt = - 100. + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if 'MasstransportAnalysis' in analyses and not (solution == 'TransientSolution' and md.transient.ismasstransport == 0): + md = checkfield(md, 'fieldname', 'basalforcings.groundedice_melting_rate', 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.meltrate_factor', '>=', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'basalforcings.threshold_thickness', '>=', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'basalforcings.upperdepth_melt', '<=', 0, 'numel', [1]) + + if 'BalancethicknessAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'basalforcings.groundedice_melting_rate', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'basalforcings.meltrate_factor', '>=', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'basalforcings.threshold_thickness', '>=', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'basalforcings.upperdepth_melt', '<=', 0, 'numel', [1]) + + if 'ThermalAnalysis' in analyses and not (solution == 'TransientSolution' and md.transient.isthermal == 0): + md = checkfield(md, 'fieldname', 'basalforcings.groundedice_melting_rate', 'NaN', 1, 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.meltrate_factor', '>=', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'basalforcings.threshold_thickness', '>=', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'basalforcings.upperdepth_melt', '<=', 0, 'numel', [1]) + md = checkfield(md, 'fieldname', 'basalforcings.geothermalflux', 'NaN', 1, 'Inf', 1, 'timeseries', 1, '>=', 0) + return md # }}} + + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + if yts != 365.2422 * 24. * 3600.: + print('WARNING: value of yts for MISMIP + runs different from ISSM default!') + + WriteData(fid, prefix, 'name', 'md.basalforcings.model', 'data', 3, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'groundedice_melting_rate', 'format', 'DoubleMat', 'name', 'md.basalforcings.groundedice_melting_rate', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'geothermalflux', 'name', 'md.basalforcings.geothermalflux', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'meltrate_factor', 'format', 'Double', 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'threshold_thickness', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'upperdepth_melt', 'format', 'Double') + # }}} Index: /issm/trunk-jpl/src/m/classes/model.py =================================================================== --- /issm/trunk-jpl/src/m/classes/model.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/model.py (revision 24213) @@ -75,11 +75,9 @@ #properties def __init__(self): #{{{ - - # classtype = model.properties - - # for classe in dict.keys(classtype): - # print classe - # self.__dict__[classe] = classtype[str(classe)] - + ''' classtype = model.properties + for classe in dict.keys(classtype): + print classe + self.__dict__[classe] = classtype[str(classe)] + ''' self.mesh = mesh2d() self.mask = mask() @@ -176,50 +174,50 @@ def __repr__(obj): #{{{ - #print "Here %s the number: %d" % ("is", 37) - string = "%19s: %-22s -- %s" % ("mesh", "[%s, %s]" % ("1x1", obj.mesh.__class__.__name__), "mesh properties") - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("mask", "[%s, %s]" % ("1x1", obj.mask.__class__.__name__), "defines grounded and floating elements")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("geometry", "[%s, %s]" % ("1x1", obj.geometry.__class__.__name__), "surface elevation, bedrock topography, ice thickness, ...")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("constants", "[%s, %s]" % ("1x1", obj.constants.__class__.__name__), "physical constants")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("smb", "[%s, %s]" % ("1x1", obj.smb.__class__.__name__), "surface mass balance")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("basalforcings", "[%s, %s]" % ("1x1", obj.basalforcings.__class__.__name__), "bed forcings")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("materials", "[%s, %s]" % ("1x1", obj.materials.__class__.__name__), "material properties")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("damage", "[%s, %s]" % ("1x1", obj.damage.__class__.__name__), "damage propagation laws")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("friction", "[%s, %s]" % ("1x1", obj.friction.__class__.__name__), "basal friction/drag properties")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("flowequation", "[%s, %s]" % ("1x1", obj.flowequation.__class__.__name__), "flow equations")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("timestepping", "[%s, %s]" % ("1x1", obj.timestepping.__class__.__name__), "time stepping for transient models")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("initialization", "[%s, %s]" % ("1x1", obj.initialization.__class__.__name__), "initial guess/state")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("rifts", "[%s, %s]" % ("1x1", obj.rifts.__class__.__name__), "rifts properties")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("slr", "[%s, %s]" % ("1x1", obj.slr.__class__.__name__), "slr forcings")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("debug", "[%s, %s]" % ("1x1", obj.debug.__class__.__name__), "debugging tools (valgrind, gprof)")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("verbose", "[%s, %s]" % ("1x1", obj.verbose.__class__.__name__), "verbosity level in solve")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("settings", "[%s, %s]" % ("1x1", obj.settings.__class__.__name__), "settings properties")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("toolkits", "[%s, %s]" % ("1x1", obj.toolkits.__class__.__name__), "PETSc options for each solution")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("cluster", "[%s, %s]" % ("1x1", obj.cluster.__class__.__name__), "cluster parameters (number of cpus...)")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("balancethickness", "[%s, %s]" % ("1x1", obj.balancethickness.__class__.__name__), "parameters for balancethickness solution")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("stressbalance", "[%s, %s]" % ("1x1", obj.stressbalance.__class__.__name__), "parameters for stressbalance solution")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("groundingline", "[%s, %s]" % ("1x1", obj.groundingline.__class__.__name__), "parameters for groundingline solution")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("hydrology", "[%s, %s]" % ("1x1", obj.hydrology.__class__.__name__), "parameters for hydrology solution")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("masstransport", "[%s, %s]" % ("1x1", obj.masstransport.__class__.__name__), "parameters for masstransport solution")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("thermal", "[%s, %s]" % ("1x1", obj.thermal.__class__.__name__), "parameters for thermal solution")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("steadystate", "[%s, %s]" % ("1x1", obj.steadystate.__class__.__name__), "parameters for steadystate solution")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("transient", "[%s, %s]" % ("1x1", obj.transient.__class__.__name__), "parameters for transient solution")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("levelset", "[%s, %s]" % ("1x1", obj.levelset.__class__.__name__), "parameters for moving boundaries (level-set method)")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("calving", "[%s, %s]" % ("1x1", obj.calving.__class__.__name__), "parameters for calving")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("frontalforcings", "[%s, %s]" % ("1x1", obj.frontalforcings.__class__.__name__), "parameters for frontalforcings")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("gia", "[%s, %s]" % ("1x1", obj.gia.__class__.__name__), "parameters for gia solution")) - string = "%s\n%s" % (string, '%19s: %-22s -- %s' % ("love", "[%s, %s]" % ("1x1", obj.love.__class__.__name__), "parameters for love solution")) - string = "%s\n%s" % (string, '%19s: %-22s -- %s' % ("esa", "[%s, %s]" % ("1x1", obj.esa.__class__.__name__), "parameters for elastic adjustment solution")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("autodiff", "[%s, %s]" % ("1x1", obj.autodiff.__class__.__name__), "automatic differentiation parameters")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("inversion", "[%s, %s]" % ("1x1", obj.inversion.__class__.__name__), "parameters for inverse methods")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("qmu", "[%s, %s]" % ("1x1", obj.qmu.__class__.__name__), "dakota properties")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("amr", "[%s, %s]" % ("1x1", obj.amr.__class__.__name__), "adaptive mesh refinement properties")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("outputdefinition", "[%s, %s]" % ("1x1", obj.outputdefinition.__class__.__name__), "output definition")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("results", "[%s, %s]" % ("1x1", obj.results.__class__.__name__), "model results")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("radaroverlay", "[%s, %s]" % ("1x1", obj.radaroverlay.__class__.__name__), "radar image for plot overlay")) - string = "%s\n%s" % (string, "%19s: %-22s -- %s" % ("miscellaneous", "[%s, %s]" % ("1x1", obj.miscellaneous.__class__.__name__), "miscellaneous fields")) + #print "Here %s the number: %d" % ("is", 37) + string = "%19s: % - 22s - - %s" % ("mesh", "[%s, %s]" % ("1x1", obj.mesh.__class__.__name__), "mesh properties") + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("mask", "[%s, %s]" % ("1x1", obj.mask.__class__.__name__), "defines grounded and floating elements")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("geometry", "[%s, %s]" % ("1x1", obj.geometry.__class__.__name__), "surface elevation, bedrock topography, ice thickness, ...")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("constants", "[%s, %s]" % ("1x1", obj.constants.__class__.__name__), "physical constants")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("smb", "[%s, %s]" % ("1x1", obj.smb.__class__.__name__), "surface mass balance")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("basalforcings", "[%s, %s]" % ("1x1", obj.basalforcings.__class__.__name__), "bed forcings")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("materials", "[%s, %s]" % ("1x1", obj.materials.__class__.__name__), "material properties")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("damage", "[%s, %s]" % ("1x1", obj.damage.__class__.__name__), "damage propagation laws")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("friction", "[%s, %s]" % ("1x1", obj.friction.__class__.__name__), "basal friction / drag properties")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("flowequation", "[%s, %s]" % ("1x1", obj.flowequation.__class__.__name__), "flow equations")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("timestepping", "[%s, %s]" % ("1x1", obj.timestepping.__class__.__name__), "time stepping for transient models")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("initialization", "[%s, %s]" % ("1x1", obj.initialization.__class__.__name__), "initial guess / state")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("rifts", "[%s, %s]" % ("1x1", obj.rifts.__class__.__name__), "rifts properties")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("slr", "[%s, %s]" % ("1x1", obj.slr.__class__.__name__), "slr forcings")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("debug", "[%s, %s]" % ("1x1", obj.debug.__class__.__name__), "debugging tools (valgrind, gprof)")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("verbose", "[%s, %s]" % ("1x1", obj.verbose.__class__.__name__), "verbosity level in solve")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("settings", "[%s, %s]" % ("1x1", obj.settings.__class__.__name__), "settings properties")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("toolkits", "[%s, %s]" % ("1x1", obj.toolkits.__class__.__name__), "PETSc options for each solution")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("cluster", "[%s, %s]" % ("1x1", obj.cluster.__class__.__name__), "cluster parameters (number of cpus...)")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("balancethickness", "[%s, %s]" % ("1x1", obj.balancethickness.__class__.__name__), "parameters for balancethickness solution")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("stressbalance", "[%s, %s]" % ("1x1", obj.stressbalance.__class__.__name__), "parameters for stressbalance solution")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("groundingline", "[%s, %s]" % ("1x1", obj.groundingline.__class__.__name__), "parameters for groundingline solution")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("hydrology", "[%s, %s]" % ("1x1", obj.hydrology.__class__.__name__), "parameters for hydrology solution")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("masstransport", "[%s, %s]" % ("1x1", obj.masstransport.__class__.__name__), "parameters for masstransport solution")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("thermal", "[%s, %s]" % ("1x1", obj.thermal.__class__.__name__), "parameters for thermal solution")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("steadystate", "[%s, %s]" % ("1x1", obj.steadystate.__class__.__name__), "parameters for steadystate solution")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("transient", "[%s, %s]" % ("1x1", obj.transient.__class__.__name__), "parameters for transient solution")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("levelset", "[%s, %s]" % ("1x1", obj.levelset.__class__.__name__), "parameters for moving boundaries (level - set method)")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("calving", "[%s, %s]" % ("1x1", obj.calving.__class__.__name__), "parameters for calving")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("frontalforcings", "[%s, %s]" % ("1x1", obj.frontalforcings.__class__.__name__), "parameters for frontalforcings")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("gia", "[%s, %s]" % ("1x1", obj.gia.__class__.__name__), "parameters for gia solution")) + string = "%s\n%s" % (string, '%19s: % - 22s - - %s' % ("love", "[%s, %s]" % ("1x1", obj.love.__class__.__name__), "parameters for love solution")) + string = "%s\n%s" % (string, '%19s: % - 22s - - %s' % ("esa", "[%s, %s]" % ("1x1", obj.esa.__class__.__name__), "parameters for elastic adjustment solution")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("autodiff", "[%s, %s]" % ("1x1", obj.autodiff.__class__.__name__), "automatic differentiation parameters")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("inversion", "[%s, %s]" % ("1x1", obj.inversion.__class__.__name__), "parameters for inverse methods")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("qmu", "[%s, %s]" % ("1x1", obj.qmu.__class__.__name__), "dakota properties")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("amr", "[%s, %s]" % ("1x1", obj.amr.__class__.__name__), "adaptive mesh refinement properties")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("outputdefinition", "[%s, %s]" % ("1x1", obj.outputdefinition.__class__.__name__), "output definition")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("results", "[%s, %s]" % ("1x1", obj.results.__class__.__name__), "model results")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("radaroverlay", "[%s, %s]" % ("1x1", obj.radaroverlay.__class__.__name__), "radar image for plot overlay")) + string = "%s\n%s" % (string, "%19s: % - 22s - - %s" % ("miscellaneous", "[%s, %s]" % ("1x1", obj.miscellaneous.__class__.__name__), "miscellaneous fields")) return string # }}} - def checkmessage(self, string): # {{{ + def checkmessage(self, string): # {{{ print("model not consistent: {}".format(string)) self.private.isconsistent = False @@ -228,5 +226,5 @@ #@staticmethod - def extract(self, area): # {{{ + def extract(self, area): # {{{ """ extract - extract a model according to an Argus contour or flag list @@ -234,7 +232,7 @@ This routine extracts a submodel from a bigger model with respect to a given contour md must be followed by the corresponding exp file or flags list - It can either be a domain file (argus type, .exp extension), or an array of element flags. + It can either be a domain file (argus type, .exp extension), or an array of element flags. If user wants every element outside the domain to be - extract2d, add '~' to the name of the domain file (ex: '~HO.exp') + extract2d, add '~' to the name of the domain file (ex: '~HO.exp') an empty string '' will be considered as an empty domain a string 'all' will be considered as the entire domain @@ -246,16 +244,16 @@ md2 = extract(md, 'Domain.exp') - See also: EXTRUDE, COLLAPSE + See also: EXTRUDE, COLLAPSE """ - #copy model + #copy model md1 = copy.deepcopy(self) - #get elements that are inside area + #get elements that are inside area flag_elem = FlagElements(md1, area) if not np.any(flag_elem): raise RuntimeError("extracted model is empty") - #kick out all elements with 3 dirichlets + #kick out all elements with 3 dirichlets spc_elem = np.nonzero(np.logical_not(flag_elem))[0] spc_node = np.unique(md1.mesh.elements[spc_elem, :]) - 1 @@ -265,9 +263,9 @@ flag_elem[pos] = 0 - #extracted elements and nodes lists + #extracted elements and nodes lists pos_elem = np.nonzero(flag_elem)[0] pos_node = np.unique(md1.mesh.elements[pos_elem, :]) - 1 - #keep track of some fields + #keep track of some fields numberofvertices1 = md1.mesh.numberofvertices numberofelements1 = md1.mesh.numberofelements @@ -277,5 +275,5 @@ flag_node[pos_node] = 1 - #Create Pelem and Pnode (transform old nodes in new nodes and same thing for the elements) + #Create Pelem and Pnode (transform old nodes in new nodes and same thing for the elements) Pelem = np.zeros(numberofelements1, int) Pelem[pos_elem] = np.arange(1, numberofelements2 + 1) @@ -283,5 +281,5 @@ Pnode[pos_node] = np.arange(1, numberofvertices2 + 1) - #renumber the elements (some node won't exist anymore) + #renumber the elements (some node won't exist anymore) elements_1 = copy.deepcopy(md1.mesh.elements) elements_2 = elements_1[pos_elem, :] @@ -294,12 +292,12 @@ elements_2[:, 5] = Pnode[elements_2[:, 5] - 1] - #OK, now create the new model! - - #take every field from model + #OK, now create the new model! + + #take every field from model md2 = copy.deepcopy(md1) - #automatically modify fields - - #loop over model fields + #automatically modify fields + + #loop over model fields model_fields = vars(md1) for fieldi in model_fields: @@ -334,5 +332,4 @@ #modify some specific fields - #Mesh md2.mesh.numberofelements = numberofelements2 @@ -377,7 +374,7 @@ #Edges if md1.mesh.domaintype() == '2Dhorizontal': - if np.ndim(md2.mesh.edges) > 1 and np.size(md2.mesh.edges, axis=1) > 1: #do not use ~isnan because there are some np.nans... + if np.ndim(md2.mesh.edges) > 1 and np.size(md2.mesh.edges, axis=1) > 1: #do not use ~isnan because there are some np.nans... #renumber first two columns - pos = np.nonzero(md2.mesh.edges[:, 3] != -1)[0] + pos = np.nonzero(md2.mesh.edges[:, 3] != - 1)[0] md2.mesh.edges[:, 0] = Pnode[md2.mesh.edges[:, 0] - 1] md2.mesh.edges[:, 1] = Pnode[md2.mesh.edges[:, 1] - 1] @@ -386,11 +383,11 @@ #remove edges when the 2 vertices are not in the domain. md2.mesh.edges = md2.mesh.edges[np.nonzero(np.logical_and(md2.mesh.edges[:, 0], md2.mesh.edges[:, 1]))[0], :] - #Replace all zeros by -1 in the last two columns + #Replace all zeros by - 1 in the last two columns pos = np.nonzero(md2.mesh.edges[:, 2] == 0)[0] - md2.mesh.edges[pos, 2] = -1 + md2.mesh.edges[pos, 2] = - 1 pos = np.nonzero(md2.mesh.edges[:, 3] == 0)[0] - md2.mesh.edges[pos, 3] = -1 - #Invert -1 on the third column with last column (Also invert first two columns!!) - pos = np.nonzero(md2.mesh.edges[:, 2] == -1)[0] + md2.mesh.edges[pos, 3] = - 1 + #Invert - 1 on the third column with last column (Also invert first two columns!!) + pos = np.nonzero(md2.mesh.edges[:, 2] == - 1)[0] md2.mesh.edges[pos, 2] = md2.mesh.edges[pos, 3] md2.mesh.edges[pos, 3] = - 1 @@ -502,5 +499,5 @@ setattr(fieldr, solutionsubfield, subfield) - #Keep track of pos_node and pos_elem + #Keep track of pos_node and pos_elem md2.mesh.extractedvertices = pos_node + 1 md2.mesh.extractedelements = pos_elem + 1 @@ -509,5 +506,5 @@ # }}} - def extrude(md, *args): # {{{ + def extrude(md, *args): # {{{ """ EXTRUDE - vertically extrude a 2d mesh @@ -515,7 +512,7 @@ vertically extrude a 2d mesh and create corresponding 3d mesh. The vertical distribution can: - - follow a polynomial law - - follow two polynomial laws, one for the lower part and one for the upper part of the mesh - - be discribed by a list of coefficients (between 0 and 1) + - follow a polynomial law + - follow two polynomial laws, one for the lower part and one for the upper part of the mesh + - be discribed by a list of coefficients (between 0 and 1) @@ -526,9 +523,9 @@ Example: - md = extrude(md, 15, 1.3); - md = extrude(md, 15, 1.3, 1.2); + md = extrude(md, 15, 1.3) + md = extrude(md, 15, 1.3, 1.2) md = extrude(md, [0 0.2 0.5 0.7 0.9 0.95 1]) - See also: MODELEXTRACT, COLLAPSE + See also: MODELEXTRACT, COLLAPSE """ #some checks on list of arguments @@ -537,5 +534,5 @@ #Extrude the mesh - if len(args) == 1: #list of coefficients + if len(args) == 1: #list of coefficients clist = args[0] if any(clist < 0) or any(clist > 1): @@ -546,11 +543,11 @@ numlayers = len(extrusionlist) - elif len(args) == 2: #one polynomial law + elif len(args) == 2: #one polynomial law if args[1] <= 0: - raise TypeError("extrusionexponent must be >=0") + raise TypeError("extrusionexponent must be >= 0") numlayers = args[0] extrusionlist = (np.arange(0., float(numlayers - 1) + 1., 1.) / float(numlayers - 1))**args[1] - elif len(args) == 3: #two polynomial laws + elif len(args) == 3: #two polynomial laws numlayers = args[0] lowerexp = args[1] @@ -558,5 +555,5 @@ if args[1] <= 0 or args[2] <= 0: - raise TypeError("lower and upper extrusionexponents must be >=0") + raise TypeError("lower and upper extrusionexponents must be >= 0") lowerextrusionlist = (np.arange(0., 1. + 2. / float(numlayers - 1), 2. / float(numlayers - 1)))**lowerexp / 2. @@ -593,6 +590,6 @@ x3d = np.empty((0)) y3d = np.empty((0)) - z3d = np.empty((0)) #the lower node is on the bed - thickness3d = md.geometry.thickness #thickness and bed for these nodes + z3d = np.empty((0)) #the lower node is on the bed + thickness3d = md.geometry.thickness #thickness and bed for these nodes bed3d = md.geometry.base @@ -602,6 +599,6 @@ y3d = np.concatenate((y3d, md.mesh.y)) #nodes are distributed between bed and surface accordingly to the given exponent - z3d = np.concatenate((z3d, (bed3d + thickness3d * extrusionlist[i]).reshape(-1))) - number_nodes3d = np.size(x3d) #number of 3d nodes for the non extruded part of the mesh + z3d = np.concatenate((z3d, (bed3d + thickness3d * extrusionlist[i]).reshape(- 1))) + number_nodes3d = np.size(x3d) #number of 3d nodes for the non extruded part of the mesh #Extrude elements @@ -609,6 +606,6 @@ for i in range(numlayers - 1): elements3d = np.vstack((elements3d, np.hstack((md.mesh.elements + i * md.mesh.numberofvertices, - md.mesh.elements + (i + 1) * md.mesh.numberofvertices)))) #Create the elements of the 3d mesh for the non extruded part - number_el3d = np.size(elements3d, axis=0) #number of 3d nodes for the non extruded part of the mesh + md.mesh.elements + (i + 1) * md.mesh.numberofvertices)))) #Create the elements of the 3d mesh for the non extruded part + number_el3d = np.size(elements3d, axis=0) #number of 3d nodes for the non extruded part of the mesh #Keep a trace of lower and upper nodes @@ -644,6 +641,5 @@ md.mesh.numberoflayers = numlayers - #Ok, now deal with the other fields from the 2d mesh: - + #Ok, now deal with the other fields from the 2d mesh: #bedinfo and surface info md.mesh.vertexonbase = project3d(md, 'vector', np.ones(md.mesh.numberofvertices2d, bool), 'type', 'node', 'layer', 1) @@ -697,5 +693,5 @@ return md - # }}} + # }}} def collapse(md): #{{{ @@ -704,5 +700,5 @@ This routine collapses a 3d model into a 2d model and collapses all - the fileds of the 3d model by taking their depth-averaged values + the fileds of the 3d model by taking their depth - averaged values Usage: @@ -719,5 +715,5 @@ md.friction.coefficient = project2d(md, md.friction.coefficient, 1) - #p and q (same deal, except for element that are on the bedrock: ) + #p and q (same deal, except for element that are on the bedrock: ) if hasattr(md.friction, 'p'): md.friction.p = project2d(md, md.friction.p, 1) @@ -802,5 +798,4 @@ if isvector: md.hydrology.__dict__[field] = project2d(md, md.hydrology.__dict__[field], 1) - #boundary conditions @@ -883,3 +878,3 @@ return md -#}}} + #}}} Index: /issm/trunk-jpl/src/m/classes/organizer.py =================================================================== --- /issm/trunk-jpl/src/m/classes/organizer.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/organizer.py (revision 24213) @@ -8,179 +8,180 @@ #hack to keep python 2 compatipility try: - #py3 import - from dbm.ndbm import whichdb + #py3 import + from dbm.ndbm import whichdb except ImportError: - #py2 import - from whichdb import whichdb + #py2 import + from whichdb import whichdb import MatlabFuncs as m + class organizer(object): - """ - ORGANIZER class definition + """ + ORGANIZER class definition - Supported options: - repository: directory where all models will be saved - prefix: prefix for saved model names - steps: requested steps - trunkprefix:prefix of previous run with a different prefix. Used to branch. + Supported options: + repository: directory where all models will be saved + prefix: prefix for saved model names + steps: requested steps + trunkprefix:prefix of previous run with a different prefix. Used to branch. - Usage: - org = organizer(varargin) + Usage: + org = organizer(varargin) - Examples: - org = organizer('repository','Models/','prefix','AGU2015','steps',0); %build an empty organizer object with a given repository - """ + Examples: + org = organizer('repository', 'Models/', 'prefix', 'AGU2015', 'steps', 0); %build an empty organizer object with a given repository + """ - def __init__(self,*args): # {{{ - self._currentstep =0 - self.repository ='./' - self.prefix ='model.' - self.trunkprefix ='' - self.steps =[] - self.requestedsteps=[0] + def __init__(self, *args): # {{{ + self._currentstep = 0 + self.repository = './' + self.prefix = 'model.' + self.trunkprefix = '' + self.steps = [] + self.requestedsteps = [0] - #process options - options=pairoptions.pairoptions(*args) + #process options + options = pairoptions.pairoptions(*args) - #Get prefix - prefix=options.getfieldvalue('prefix','model.') - if not isinstance(prefix,str): - raise TypeError("prefix is not a string") - if not m.strcmp(prefix,prefix.strip()) or len(prefix.split()) > 1: - raise TypeError("prefix should not have any white space") - self.prefix=prefix + #Get prefix + prefix = options.getfieldvalue('prefix', 'model.') + if not isinstance(prefix, str): + raise TypeError("prefix is not a string") + if not m.strcmp(prefix, prefix.strip()) or len(prefix.split()) > 1: + raise TypeError("prefix should not have any white space") + self.prefix = prefix - #Get repository - repository=options.getfieldvalue('repository','./') - if not isinstance(repository,str): - raise TypeError("repository is not a string") - if not os.path.isdir(repository): - raise IOError("Directory '%s' not found" % repository) - self.repository=repository + #Get repository + repository = options.getfieldvalue('repository', './') + if not isinstance(repository, str): + raise TypeError("repository is not a string") + if not os.path.isdir(repository): + raise IOError("Directory '%s' not found" % repository) + self.repository = repository - #Get steps - self.requestedsteps=options.getfieldvalue('steps',[0]) + #Get steps + self.requestedsteps = options.getfieldvalue('steps', [0]) - #Get trunk prefix (only if provided by user) - if options.exist('trunkprefix'): - trunkprefix=options.getfieldvalue('trunkprefix','') - if not isinstance(trunkprefix,str): - raise TypeError("trunkprefix is not a string") - if not m.strcmp(trunkprefix,trunkprefix.strip()) or len(trunkprefix.split()) > 1: - raise TypeError("trunkprefix should not have any white space") - self.trunkprefix=trunkprefix - #}}} - def __repr__(self): # {{{ - s ="" + #Get trunk prefix (only if provided by user) + if options.exist('trunkprefix'): + trunkprefix = options.getfieldvalue('trunkprefix', '') + if not isinstance(trunkprefix, str): + raise TypeError("trunkprefix is not a string") + if not m.strcmp(trunkprefix, trunkprefix.strip()) or len(trunkprefix.split()) > 1: + raise TypeError("trunkprefix should not have any white space") + self.trunkprefix = trunkprefix + #}}} - s+="%s\n" % " Repository: '%s'" % self.repository - s+="%s\n" % " Prefix: '%s'" % self.prefix - if not self.steps: - s+="%s\n" % " no step" - else: - for step in self.steps: - s+="%s\n" % " step #%2i: '%s'",step['id'],step['string'] - #}}} - def load(self,string): # {{{ + def __repr__(self): # {{{ + s = "" + s += "%s\n" % " Repository: '%s'" % self.repository + s += "%s\n" % " Prefix: '%s'" % self.prefix + if not self.steps: + s += "%s\n" % " no step" + else: + for step in self.steps: + s += "%s\n" % " step #%2i: '%s'", step['id'], step['string'] + #}}} - #Get model path - if not isinstance(string,str): - raise TypeError("argument provided is not a string") - path=os.path.join(self.repository,self.prefix+string) + def load(self, string): # {{{ + #Get model path + if not isinstance(string, str): + raise TypeError("argument provided is not a string") + path = os.path.join(self.repository, self.prefix + string) - #figure out if the model is there - if os.path.exists(path): - struc=loadvars(path) - name=name=[key for key in list(struc.keys())] - md=struc.name[0] - else: - raise IOError("Could not find '%s'" % path) + #figure out if the model is there + if os.path.exists(path): + struc = loadvars(path) + name = name = [key for key in list(struc.keys())] + md = struc.name[0] + else: + raise IOError("Could not find '%s'" % path) - return md - #}}} - def loadmodel(self,string): # {{{ + return md + #}}} - #Get model path - if not isinstance(string,str): - raise TypeError("argument provided is not a string") - path1=os.path.join(self.repository,self.prefix+string+'.python') - path2=os.path.join(self.repository,string) + def loadmodel(self, string): # {{{ + #Get model path + if not isinstance(string, str): + raise TypeError("argument provided is not a string") + path1 = os.path.join(self.repository, self.prefix + string + '.python') + path2 = os.path.join(self.repository, string) - #figure out if the model is there, otherwise, we have to use the default path supplied by user. - if whichdb(path1): - md=loadmodel(path1) - return md - elif whichdb(path2): - md=loadmodel(path2) - return md + #figure out if the model is there, otherwise, we have to use the default path supplied by user. + if whichdb(path1): + md = loadmodel(path1) + return md + elif whichdb(path2): + md = loadmodel(path2) + return md - #If we are here, the model has not been found. Try trunk prefix if provided - if self.trunkprefix: - path2=os.path.join(self.repository,self.trunkprefix+string) - if not os.path.exists(path2): - raise IOError("Could find neither '%s' nor '%s'" % (path,path2)) - else: - print(("--> Branching '%s' from trunk '%s'" % (self.prefix,self.trunkprefix))) - md=loadmodel(path2) - return md - else: - raise IOError("Could not find '%s'" % path1) - #}}} - def perform(self,string): # {{{ + #If we are here, the model has not been found. Try trunk prefix if provided + if self.trunkprefix: + path2 = os.path.join(self.repository, self.trunkprefix + string) + if not os.path.exists(path2): + raise IOError("Could find neither '%s' nor '%s'" % (path1, path2)) + else: + print((" - - > Branching '%s' from trunk '%s'" % (self.prefix, self.trunkprefix))) + md = loadmodel(path2) + return md + else: + raise IOError("Could not find '%s'" % path1) + #}}} - bool=False + def perform(self, string): # {{{ + bool = False - #Some checks - if not isinstance(string,str): - raise TypeError("Step provided should be a string") - if not m.strcmp(string,string.strip()) or len(string.split()) > 1: - raise TypeError("Step provided should not have any white space") - if self._currentstep>0 and string in [step['string'] for step in self.steps]: - raise RuntimeError("Step '%s' already present. Change name" % string) + #Some checks + if not isinstance(string, str): + raise TypeError("Step provided should be a string") + if not m.strcmp(string, string.strip()) or len(string.split()) > 1: + raise TypeError("Step provided should not have any white space") + if self._currentstep > 0 and string in [step['string'] for step in self.steps]: + raise RuntimeError("Step '%s' already present. Change name" % string) - #Add step - self.steps.append(OrderedDict()) - self.steps[-1]['id']=len(self.steps) - self.steps[-1]['string']=string - self._currentstep+=1 + #Add step + self.steps.append(OrderedDict()) + self.steps[-1]['id'] = len(self.steps) + self.steps[-1]['string'] = string + self._currentstep += 1 - #if requestedsteps = 0, print all steps in self - if 0 in self.requestedsteps: - if self._currentstep==1: - print((" prefix: %s" % self.prefix)) - print((" step #%i : %s" % (self.steps[self._currentstep-1]['id'],self.steps[self._currentstep-1]['string']))) + #if requestedsteps = 0, print all steps in self + if 0 in self.requestedsteps: + if self._currentstep == 1: + print((" prefix: %s" % self.prefix)) + print((" step #%i : %s" % (self.steps[self._currentstep - 1]['id'], self.steps[self._currentstep - 1]['string']))) - #Ok, now if _currentstep is a member of steps, return true - if self._currentstep in self.requestedsteps: - print(("\n step #%i : %s\n" % (self.steps[self._currentstep-1]['id'],self.steps[self._currentstep-1]['string']))) - bool=True + #Ok, now if _currentstep is a member of steps, return true + if self._currentstep in self.requestedsteps: + print(("\n step #%i : %s\n" % (self.steps[self._currentstep - 1]['id'], self.steps[self._currentstep - 1]['string']))) + bool = True - #assign self back to calling workspace - # (no need, since Python modifies class instance directly) + #assign self back to calling workspace + # (no need, since Python modifies class instance directly) - return bool - #}}} - def savemodel(self,md, name='default'): # {{{ + return bool + #}}} - #check - if self._currentstep==0: - raise RuntimeError("Cannot save model because organizer (org) is empty! Make sure you did not skip any perform call") - if self._currentstep>len(self.steps): - raise RuntimeError("Cannot save model because organizer (org) is not up to date!") + def savemodel(self, md, name='default'): # {{{ + #check + if self._currentstep == 0: + raise RuntimeError("Cannot save model because organizer (org) is empty! Make sure you did not skip any perform call") + if self._currentstep > len(self.steps): + raise RuntimeError("Cannot save model because organizer (org) is not up to date!") - if (name=='default'): - name=os.path.join(self.repository,self.prefix+self.steps[self._currentstep-1]['string']+'.python') - else: - name=os.path.join(self.repository,name) - print(("saving model as: '%s'" % name)) + if (name == 'default'): + name = os.path.join(self.repository, self.prefix + self.steps[self._currentstep - 1]['string'] + '.python') + else: + name = os.path.join(self.repository, name) + print(("saving model as: '%s'" % name)) - #check that md is a model - if not isinstance(md,model): - print("second argument is not a model") - if self._currentstep>len(self.steps): - raise RuntimeError("organizer error message: element with id %d not found" % self._currentstep) + #check that md is a model + if not isinstance(md, model): + print("second argument is not a model") + if self._currentstep > len(self.steps): + raise RuntimeError("organizer error message: element with id %d not found" % self._currentstep) - #save model - savevars(name,'md',md) - #}}} + #save model + savevars(name, 'md', md) + #}}} Index: /issm/trunk-jpl/src/m/classes/outputdefinition.py =================================================================== --- /issm/trunk-jpl/src/m/classes/outputdefinition.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/outputdefinition.py (revision 24213) @@ -2,49 +2,55 @@ from checkfield import checkfield from WriteData import WriteData -import numpy as np +import numpy as np + class outputdefinition(object): - """ - OUTPUTDEFINITION class definition + """ + OUTPUTDEFINITION class definition - Usage: - outputdefinition=outputdefinition(); - """ + Usage: + outputdefinition = outputdefinition() + """ - def __init__(self): # {{{ - self.definitions = [] - #}}} - def __repr__(self): # {{{ - string=" Outputdefinitions:" + def __init__(self): # {{{ + self.definitions = [] + #}}} - string="%s\n%s"%(string,fielddisplay(self,"definitions","list of potential outputs that can be requested, but which need additional data to be defined")) + def __repr__(self): # {{{ + string = " Outputdefinitions:" - return string - #}}} - def extrude(self,md): # {{{ - for definition in self.definitions: - definition.extrude(md); + string = "%s\n%s" % (string, fielddisplay(self, "definitions", "list of potential outputs that can be requested, but which need additional data to be defined")) - return self - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - - md = checkfield(md,'fieldname','outputdefinition.definitions','cell',1) - for definition in self.definitions: - definition.checkconsistency(md,solution,analyses); + return string + #}}} - # }}} - def marshall(self,prefix,md,fid): # {{{ - data=[]; - for i in range(len(self.definitions)): - self.definitions[i].marshall(prefix,md,fid); - classdefinition=self.definitions[i].__class__.__name__; - classdefinition=classdefinition[0].upper()+classdefinition[1:] - data.append(classdefinition) + def extrude(self, md): # {{{ + for definition in self.definitions: + definition.extrude(md) - data=np.unique(data); - WriteData(fid,prefix,'data',data,'name','md.outputdefinition.list','format','StringArray'); - # }}} + return self + #}}} + + def setdefaultparameters(self): # {{{ + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + + md = checkfield(md, 'fieldname', 'outputdefinition.definitions', 'cell', 1) + for definition in self.definitions: + definition.checkconsistency(md, solution, analyses) + + # }}} + + def marshall(self, prefix, md, fid): # {{{ + data = [] + for i in range(len(self.definitions)): + self.definitions[i].marshall(prefix, md, fid) + classdefinition = self.definitions[i].__class__.__name__ + classdefinition = classdefinition[0].upper() + classdefinition[1:] + data.append(classdefinition) + + data = np.unique(data) + WriteData(fid, prefix, 'data', data, 'name', 'md.outputdefinition.list', 'format', 'StringArray') + # }}} Index: /issm/trunk-jpl/src/m/classes/pairoptions.py =================================================================== --- /issm/trunk-jpl/src/m/classes/pairoptions.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/pairoptions.py (revision 24213) @@ -1,172 +1,177 @@ from collections import OrderedDict -from WriteData import WriteData + class pairoptions(object): - """ - PAIROPTIONS class definition + """ + PAIROPTIONS class definition - Usage: - pairoptions=pairoptions(); - pairoptions=pairoptions('module',true,'solver',false); - """ + Usage: + pairoptions = pairoptions() + pairoptions = pairoptions('module', true, 'solver', false) + """ - def __init__(self,*arg): # {{{ - self.functionname = '' - self.list = OrderedDict() + def __init__(self, * arg): # {{{ + self.functionname = '' + self.list = OrderedDict() - #get calling function name - import inspect - if len(inspect.stack()) > 1: - self.functionname=inspect.stack()[1][3] + #get calling function name + import inspect + if len(inspect.stack()) > 1: + self.functionname = inspect.stack()[1][3] - #initialize list - if not len(arg): - pass #Do nothing, - else: - self.buildlist(*arg) - # }}} - def __repr__(self): # {{{ - s=" functionname: '{}'\n".format(self.functionname) - if self.list: - s+=" list: ({}x{}) \n\n".format(len(self.list),2) - for item in list(self.list.items()): - #if isinstance(item[1],str): - s+=" field: {} value: '{}'\n".format((item[0],item[1])) - # elif isinstance(item[1],(bool,int,float)): - # s+=" field: %-10s value: %g\n" % (item[0],item[1]) - # else: - # s+=" field: %-10s value: %s\n" % (item[0],type(item[1])) - else: - s+=" list: empty\n" - return s - # }}} - def buildlist(self,*arg): # {{{ - """BUILDLIST - build list of objects from input""" + #initialize list + if not len(arg): + pass #Do nothing, + else: + self.buildlist(* arg) + # }}} - #check length of input - if len(arg) % 2: - raise TypeError('Invalid parameter/value pair arguments') - numoptions = int(len(arg)/2) + def __repr__(self): # {{{ + s = " functionname: '{}'\n".format(self.functionname) + if self.list: + s += " list: ({}x{}) \n\n".format(len(self.list), 2) + for item in list(self.list.items()): + s += " field: {} value: '{}'\n".format((item[0], item[1])) + else: + s += " list: empty\n" + return s + # }}} - #go through arg and build list of objects - for i in range(numoptions): - if isinstance(arg[2*i],str): - self.list[arg[2*i]] = arg[2*i+1]; - else: - #option is not a string, ignore it - print(("WARNING: option number {} is not a string and will be ignored.".format(i+1))) - # }}} - def addfield(self,field,value): # {{{ - """ADDFIELD - add a field to an options list""" - if isinstance(field,str): - if field in self.list: - print(("WARNING: field '{}' with value={} exists and will be overwritten with value={}.".format(field,str(self.list[field]),str(value)))) - self.list[field] = value - # }}} - def addfielddefault(self,field,value): # {{{ - """ADDFIELDDEFAULT - add a field to an options list if it does not already exist""" - if isinstance(field,str): - if field not in self.list: - self.list[field] = value - # }}} - def AssignObjectFields(self,obj2): # {{{ - """ASSIGNOBJECTFIELDS - assign object fields from options""" - for item in list(self.list.items()): - if item[0] in dir(obj2): - setattr(obj2,item[0],item[1]) - else: - print(("WARNING: field '%s' is not a property of '%s'." % (item[0],type(obj2)))) - return obj2 - # }}} - def changefieldvalue(self,field,newvalue): # {{{ - """CHANGEOPTIONVALUE - change the value of an option in an option list""" + def buildlist(self, * arg): # {{{ + """BUILDLIST - build list of objects from input""" - self.list[field]=newvalue; - # }}} - def exist(self,field): # {{{ - """EXIST - check if the option exist""" + #check length of input + if len(arg) % 2: + raise TypeError('Invalid parameter / value pair arguments') + numoptions = int(len(arg) / 2) - #some argument checking: - if field == None or field == '': - raise ValueError('exist error message: bad usage'); - if not isinstance(field,str): - raise TypeError("exist error message: field '%s' should be a string." % str(field)); + #go through arg and build list of objects + for i in range(numoptions): + if isinstance(arg[2 * i], str): + self.list[arg[2 * i]] = arg[2 * i + 1] + else: + #option is not a string, ignore it + print(("WARNING: option number {} is not a string and will be ignored.".format(i + 1))) + # }}} - #Recover option - if field in self.list: - return True - else: - return False - # }}} - def getfieldvalue(self,field,default=None): # {{{ - """ - GETOPTION - get the value of an option + def addfield(self, field, value): # {{{ + """ADDFIELD - add a field to an options list""" + if isinstance(field, str): + if field in self.list: + print(("WARNING: field '{}' with value={} exists and will be overwritten with value={}.".format(field, str(self.list[field]), str(value)))) + self.list[field] = value + # }}} - Usage: - value=options.getfieldvalue(field,default) + def addfielddefault(self, field, value): # {{{ + """ADDFIELDDEFAULT - add a field to an options list if it does not already exist""" + if isinstance(field, str): + if field not in self.list: + self.list[field] = value + # }}} - Find an option value from a field. A default option - can be given in input if the field does not exist + def AssignObjectFields(self, obj2): # {{{ + """ASSIGNOBJECTFIELDS - assign object fields from options""" + for item in list(self.list.items()): + if item[0] in dir(obj2): + setattr(obj2, item[0], item[1]) + else: + print(("WARNING: field '%s' is not a property of '%s'." % (item[0], type(obj2)))) + return obj2 + # }}} - Examples: - value=options.getfieldvalue(options,'caxis') - value=options.getfieldvalue(options,'caxis',[0 2]) - """ + def changefieldvalue(self, field, newvalue): # {{{ + """CHANGEOPTIONVALUE - change the value of an option in an option list""" - #some argument checking: - if field == None or field == '': - raise ValueError('getfieldvalue error message: bad usage'); - if not isinstance(field,str): - raise TypeError("getfieldvalue error message: field '%s' should be a string." % str(field)); + self.list[field] = newvalue + # }}} - #Recover option - if field in self.list: - value=self.list[field] - else: - if not default == None: - value=default - else: - raise KeyError("error message: field '%s' has not been provided by user (and no default value has been specified)." % field) + def exist(self, field): # {{{ + """EXIST - check if the option exist""" - return value - # }}} - def removefield(self,field,warn): # {{{ - """ - REMOVEFIELD - delete a field in an option list + #some argument checking: + if field is None or field == '': + raise ValueError('exist error message: bad usage') + if not isinstance(field, str): + raise TypeError("exist error message: field '%s' should be a string." % str(field)) - Usage: - obj=removefield(self,field,warn) + #Recover option + if field in self.list: + return True + else: + return False + # }}} - if warn==1 display an info message to warn user that - some of his options have been removed. - """ + def getfieldvalue(self, field, default=None): # {{{ + """ + GETOPTION - get the value of an option - #check if field exist - if field in self.list: + Usage: + value = options.getfieldvalue(field, default) - #remove duplicates from the options list - del self.list[field] + Find an option value from a field. A default option + can be given in input if the field does not exist - #warn user if requested - if warn: - print(("removefield info: option '%s' has been removed from the list of options." % field)) - # }}} - def marshall(self,md,fid,firstindex): # {{{ + Examples: + value = options.getfieldvalue(options, 'caxis') + value = options.getfieldvalue(options, 'caxis', [0 2]) + """ - for i,item in enumerate(self.list.items()): - name = item[0] - value = item[1] + #some argument checking: + if field is None or field == '': + raise ValueError('getfieldvalue error message: bad usage') + if not isinstance(field, str): + raise TypeError("getfieldvalue error message: field '%s' should be a string." % str(field)) - raise NameError('need to sync with MATLAB') + #Recover option + if field in self.list: + value = self.list[field] + else: + if default is not None: + value = default + else: + raise KeyError("error message: field '%s' has not been provided by user (and no default value has been specified)." % field) - ##Write option name - #WriteData(fid,prefix,'enum',(firstindex-1)+2*i+1,'data',name,'format','String') + return value + # }}} - ##Write option value - #if isinstance(value,(str,unicode)): - # WriteData(fid,prefix,'enum',(firstindex-1)+2*i+2,'data',value,'format','String') - #elif isinstance(value,(bool,int,long,float)): - # WriteData(fid,prefix,'enum',(firstindex-1)+2*i+2,'data',value,'format','Double') - #else: - #raise TypeError("Cannot marshall option '%s': format not supported yet." % name) - # }}} + def removefield(self, field, warn): # {{{ + """ + REMOVEFIELD - delete a field in an option list + + Usage: + obj = removefield(self, field, warn) + + if warn == 1 display an info message to warn user that + some of his options have been removed. + """ + + #check if field exist + if field in self.list: + + #remove duplicates from the options list + del self.list[field] + + #warn user if requested + if warn: + print(("removefield info: option '%s' has been removed from the list of options." % field)) + # }}} + + def marshall(self, md, fid, firstindex): # {{{ + + for i, item in enumerate(self.list.items()): + name = item[0] + value = item[1] + + raise NameError('need to sync with MATLAB') + + #Write option name + #WriteData(fid, prefix, 'enum', (firstindex - 1) + 2 * i + 1, 'data', name, 'format', 'String') + + #Write option value + #if isinstance(value, (str, unicode)): + # WriteData(fid, prefix, 'enum', (firstindex - 1) + 2 * i + 2, 'data', value, 'format', 'String') + #elif isinstance(value, (bool, int, long, float)): + # WriteData(fid, prefix, 'enum', (firstindex - 1) + 2 * i + 2, 'data', value, 'format', 'Double') + #else: + #raise TypeError("Cannot marshall option '%s': format not supported yet." % name) + # }}} Index: /issm/trunk-jpl/src/m/classes/plotoptions.py =================================================================== --- /issm/trunk-jpl/src/m/classes/plotoptions.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/plotoptions.py (revision 24213) @@ -1,128 +1,131 @@ -from collections import OrderedDict, Counter, defaultdict +from collections import OrderedDict import pairoptions + class plotoptions(object): - ''' - PLOTOPTIONS class definition + ''' + PLOTOPTIONS class definition - Usage: - plotoptions=plotoptions(*arg) - ''' + Usage: + plotoptions = plotoptions(* arg) + ''' - def __init__(self,*arg):# {{{ - self.numberofplots = 0 - self.figurenumber = 1 - self.list = OrderedDict() + def __init__(self, * arg): # {{{ + self.numberofplots = 0 + self.figurenumber = 1 + self.list = OrderedDict() - self.buildlist(*arg) - #}}} - def __repr__(self): #{{{ - s="\n" - s+=" numberofplots: %i\n" % self.numberofplots - s+=" figurenumber: %i\n" % self.figurenumber - if self.list: - s+=" list: (%ix%i)\n" % (len(self.list),2) - for item in list(self.list.items()): - #s+=" options of plot number %i\n" % item - if isinstance(item[1],str): - s+=" field: %-10s value: '%s'\n" % (item[0],item[1]) - elif isinstance(item[1],(bool,int,float)): - s+=" field: %-10s value: '%g'\n" % (item[0],item[1]) - else: - s+=" field: %-10s value: '%s'\n" % (item[0],item[1]) - else: - s+=" list: empty\n" - return s - #}}} - def buildlist(self,*arg): #{{{ - #check length of input - if len(arg) % 2: - raise TypeError('Invalid parameter/value pair arguments') + self.buildlist(* arg) + #}}} - #go through args and build list (like pairoptions) - rawoptions=pairoptions.pairoptions(*arg) - numoptions=int(len(arg)/2) - rawlist=[] # cannot be a dict since they do not support duplicate keys + def __repr__(self): #{{{ + s = "\n" + s += " numberofplots: %i\n" % self.numberofplots + s += " figurenumber: %i\n" % self.figurenumber + if self.list: + s += " list: (%ix%i)\n" % (len(self.list), 2) + for item in list(self.list.items()): + #s += " options of plot number %i\n" % item + if isinstance(item[1], str): + s += " field: % - 10s value: '%s'\n" % (item[0], item[1]) + elif isinstance(item[1], (bool, int, float)): + s += " field: % - 10s value: '%g'\n" % (item[0], item[1]) + else: + s += " field: % - 10s value: '%s'\n" % (item[0], item[1]) + else: + s += " list: empty\n" + return s + #}}} - for i in range(numoptions): - if isinstance(arg[2*i],str): - rawlist.append([arg[2*i],arg[2*i+1]]) - else: - #option is not a string, ignore it - print(("WARNING: option number %d is not a string and will be ignored." % (i+1))) + def buildlist(self, * arg): #{{{ + #check length of input + if len(arg) % 2: + raise TypeError('Invalid parameter / value pair arguments') - #get figure number - self.figurenumber=rawoptions.getfieldvalue('figure',1) - rawoptions.removefield('figure',0) + #go through args and build list (like pairoptions) + rawoptions = pairoptions.pairoptions(* arg) + numoptions = int(len(arg) / 2) + rawlist = [] # cannot be a dict since they do not support duplicate keys - #get number of subplots - numberofplots=len([1 for sublist in rawlist for x in sublist if str(x)=='data']) - self.numberofplots=numberofplots + for i in range(numoptions): + if isinstance(arg[2 * i], str): + rawlist.append([arg[2 * i], arg[2 * i + 1]]) + else: + #option is not a string, ignore it + print(("WARNING: option number %d is not a string and will be ignored." % (i + 1))) - #figure out whether alloptions flag is on - if rawoptions.getfieldvalue('alloptions','off') is 'on': - allflag=1 - else: - allflag=0 + #get figure number + self.figurenumber = rawoptions.getfieldvalue('figure', 1) + rawoptions.removefield('figure', 0) - #initialize self.list (will need a list of dict's (or nested dict) for numberofplots>1) - #self.list=defaultdict(dict) - for i in range(numberofplots): - self.list[i]=pairoptions.pairoptions() + #get number of subplots + numberofplots = len([1 for sublist in rawlist for x in sublist if str(x) == 'data']) + self.numberofplots = numberofplots - #process plot options - for i in range(len(rawlist)): + #figure out whether alloptions flag is on + if rawoptions.getfieldvalue('alloptions', 'off') == 'on': + allflag = 1 + else: + allflag = 0 - #if alloptions flag is on, apply to all plots - if (allflag and 'data' not in rawlist[i][0] and '#' not in rawlist[i][0]): + #initialize self.list (will need a list of dict's (or nested dict) for numberofplots > 1) + #self.list = defaultdict(dict) + for i in range(numberofplots): + self.list[i] = pairoptions.pairoptions() - for j in range(numberofplots): - self.list[j].addfield(rawlist[i][0],rawlist[i][1]) + #process plot options + for i in range(len(rawlist)): - elif '#' in rawlist[i][0]: + #if alloptions flag is on, apply to all plots + if (allflag and 'data' not in rawlist[i][0] and ' #' not in rawlist[i][0]): - #get subplots associated - string=rawlist[i][0].split('#') - plotnums=string[-1].split(',') - field=string[0] + for j in range(numberofplots): + self.list[j].addfield(rawlist[i][0], rawlist[i][1]) - #loop over plotnums - for k in range(len(plotnums)): - plotnum=plotnums[k] + elif ' #' in rawlist[i][0]: + #get subplots associated + string = rawlist[i][0].split(' #') + plotnums = string[-1].split(', ') + field = string[0] - #Empty - if not plotnum: continue + #loop over plotnums + for k in range(len(plotnums)): + plotnum = plotnums[k] - # '#all' - elif 'all' in plotnum: - for j in range(numberofplots): - self.list[j].addfield(field,rawlist[i][1]) + #Empty + if not plotnum: + continue - # '#i-j' - elif '-' in plotnum: - nums=plotnum.split('-') - if len(nums)!=2: continue - if False in [x.isdigit() for x in nums]: - raise ValueError('error: in option i-j both i and j must be integers') - for j in range(int(nums[0])-1,int(nums[1])): - self.list[j].addfield(field,rawlist[i][1]) + # ' #all' + elif 'all' in plotnum: + for j in range(numberofplots): + self.list[j].addfield(field, rawlist[i][1]) - # Deal with #i - else: - #assign to subplot - if int(plotnum)>numberofplots: - raise ValueError('error: %s cannot be assigned %d which exceeds the number of subplots' % (field,plotnum)) - self.list[int(plotnum)-1].addfield(field,rawlist[i][1]) - else: + # ' #i - j' + elif '-' in plotnum: + nums = plotnum.split(' - ') + if len(nums) != 2: + continue + if False in [x.isdigit() for x in nums]: + raise ValueError('error: in option i - j both i and j must be integers') + for j in range(int(nums[0]) - 1, int(nums[1])): + self.list[j].addfield(field, rawlist[i][1]) - #go through all subplots and assign key-value pairs - j=0 - while j <= numberofplots-1: - if not self.list[j].exist(rawlist[i][0]): - self.list[j].addfield(rawlist[i][0],rawlist[i][1]) - break - else: - j=j+1 - if j+1>numberofplots: - print(("WARNING: too many instances of '%s' in options" % rawlist[i][0])) - #}}} + # Deal with #i + else: + #assign to subplot + if int(plotnum) > numberofplots: + raise ValueError('error: %s cannot be assigned %d which exceeds the number of subplots' % (field, plotnum)) + self.list[int(plotnum) - 1].addfield(field, rawlist[i][1]) + else: + #go through all subplots and assign key - value pairs + j = 0 + while j <= numberofplots - 1: + if not self.list[j].exist(rawlist[i][0]): + self.list[j].addfield(rawlist[i][0], rawlist[i][1]) + break + else: + j = j + 1 + if j + 1 > numberofplots: + print(("WARNING: too many instances of '%s' in options" % rawlist[i][0])) + #}}} Index: /issm/trunk-jpl/src/m/classes/plumebasalforcings.py =================================================================== --- /issm/trunk-jpl/src/m/classes/plumebasalforcings.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/plumebasalforcings.py (revision 24213) @@ -1,2 +1,3 @@ +import numpy as np from fielddisplay import fielddisplay from checkfield import checkfield @@ -4,123 +5,125 @@ from project3d import project3d + class plumebasalforcings(object): - ''' - PLUME BASAL FORCINGS class definition + ''' + PLUME BASAL FORCINGS class definition - Usage: - plumebasalforcings=plumebasalforcings() - ''' + Usage: + plumebasalforcings = plumebasalforcings() + ''' - def __init__(self): # {{{ - floatingice_melting_rate = float('NaN') - groundedice_melting_rate = float('NaN') - mantleconductivity = float('NaN') - nusselt = float('NaN') - dtbg = float('NaN') - plumeradius = float('NaN') - topplumedepth = float('NaN') - bottomplumedepth = float('NaN') - plumex = float('NaN') - plumey = float('NaN') - crustthickness = float('NaN') - uppercrustthickness = float('NaN') - uppercrustheat = float('NaN') - lowercrustheat = float('NaN') + def __init__(self): # {{{ + self.floatingice_melting_rate = float('NaN') + self.groundedice_melting_rate = float('NaN') + self.mantleconductivity = float('NaN') + self.nusselt = float('NaN') + self.dtbg = float('NaN') + self.plumeradius = float('NaN') + self.topplumedepth = float('NaN') + self.bottomplumedepth = float('NaN') + self.plumex = float('NaN') + self.plumey = float('NaN') + self.crustthickness = float('NaN') + self.uppercrustthickness = float('NaN') + self.uppercrustheat = float('NaN') + self.lowercrustheat = float('NaN') - self.setdefaultparameters() - #}}} + self.setdefaultparameters() + #}}} - def __repr__(self): # {{{ - print(' mantle plume basal melt parameterization:') + def __repr__(self): # {{{ + string = ' mantle plume basal melt parameterization:' - string="%s\n%s"%(string,fielddisplay(self,'groundedice_melting_rate','basal melting rate (positive if melting) [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'floatingice_melting_rate','basal melting rate (positive if melting) [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'mantleconductivity','mantle heat conductivity [W/m^3]')) - string="%s\n%s"%(string,fielddisplay(self,'nusselt','nusselt number, ratio of mantle to plume [1]')) - string="%s\n%s"%(string,fielddisplay(self,'dtbg','background temperature gradient [degree/m]')) - string="%s\n%s"%(string,fielddisplay(self,'plumeradius','radius of the mantle plume [m]')) - string="%s\n%s"%(string,fielddisplay(self,'topplumedepth','depth of the mantle plume top below the crust [m]')) - string="%s\n%s"%(string,fielddisplay(self,'bottomplumedepth','depth of the mantle plume base below the crust [m]')) - string="%s\n%s"%(string,fielddisplay(self,'plumex','x coordinate of the center of the plume [m]')) - string="%s\n%s"%(string,fielddisplay(self,'plumey','y coordinate of the center of the plume [m]')) - string="%s\n%s"%(string,fielddisplay(self,'crustthickness','thickness of the crust [m]')) - string="%s\n%s"%(string,fielddisplay(self,'uppercrustthickness','thickness of the upper crust [m]')) - string="%s\n%s"%(string,fielddisplay(self,'uppercrustheat','volumic heat of the upper crust [w/m^3]')) - string="%s\n%s"%(string,fielddisplay(self,'lowercrustheat','volumic heat of the lowercrust [w/m^3]')) + string = "%s\n%s" % (string, fielddisplay(self, 'groundedice_melting_rate', 'basal melting rate (positive if melting) [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'floatingice_melting_rate', 'basal melting rate (positive if melting) [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'mantleconductivity', 'mantle heat conductivity [W / m^3]')) + string = "%s\n%s" % (string, fielddisplay(self, 'nusselt', 'nusselt number, ratio of mantle to plume [1]')) + string = "%s\n%s" % (string, fielddisplay(self, 'dtbg', 'background temperature gradient [degree / m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'plumeradius', 'radius of the mantle plume [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'topplumedepth', 'depth of the mantle plume top below the crust [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'bottomplumedepth', 'depth of the mantle plume base below the crust [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'plumex', 'x coordinate of the center of the plume [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'plumey', 'y coordinate of the center of the plume [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'crustthickness', 'thickness of the crust [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'uppercrustthickness', 'thickness of the upper crust [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'uppercrustheat', 'volumic heat of the upper crust [w / m^3]')) + string = "%s\n%s" % (string, fielddisplay(self, 'lowercrustheat', 'volumic heat of the lowercrust [w / m^3]')) - return string - #}}} + return string + #}}} - def initialize(self,md): #{{{ - if np.all(np.isnan(self.groundedice_melting_rate)): - self.groundedice_melting_rate=np.zeros((md.mesh.numberofvertices,)) - print(' no basalforcings.groundedice_melting_rate specified: values set as zero') - if np.all(np.isnan(self.floatingice_melting_rate)): - self.floatingice_melting_rate=np.zeros((md.mesh.numberofvertices,)) - print(' no basalforcings.floatingice_melting_rate specified: values set as zero') - return - #}}} + def initialize(self, md): #{{{ + if np.all(np.isnan(self.groundedice_melting_rate)): + self.groundedice_melting_rate = np.zeros((md.mesh.numberofvertices, )) + print(' no basalforcings.groundedice_melting_rate specified: values set as zero') + if np.all(np.isnan(self.floatingice_melting_rate)): + self.floatingice_melting_rate = np.zeros((md.mesh.numberofvertices, )) + print(' no basalforcings.floatingice_melting_rate specified: values set as zero') + return + #}}} - def extrude(self,md): # {{{ - self.groundedice_melting_rate=project3d(md,'vector',self.groundedice_melting_rate,'type','node','layer',1); - self.floatingice_melting_rate=project3d(md,'vector',self.floatingice_melting_rate,'type','node','layer',1); - return self - #}}} + def extrude(self, md): # {{{ + self.groundedice_melting_rate = project3d(md, 'vector', self.groundedice_melting_rate, 'type', 'node', 'layer', 1) + self.floatingice_melting_rate = project3d(md, 'vector', self.floatingice_melting_rate, 'type', 'node', 'layer', 1) + return self + #}}} - def setdefaultparameters(self): # {{{ - #default values for melting parameterization - self.mantleconductivity = 2.2 - self.nusselt = 300 - self.dtbg = 11/1000. - self.plumeradius = 100000 - self.topplumedepth = 10000 - self.bottomplumedepth = 1050000 - self.crustthickness = 30000 - self.uppercrustthickness = 14000 - self.uppercrustheat = 1.7*10**-6 - self.lowercrustheat = 0.4*10**-6 - return self - #}}} + def setdefaultparameters(self): # {{{ + #default values for melting parameterization + self.mantleconductivity = 2.2 + self.nusselt = 300 + self.dtbg = 11 / 1000. + self.plumeradius = 100000 + self.topplumedepth = 10000 + self.bottomplumedepth = 1050000 + self.crustthickness = 30000 + self.uppercrustthickness = 14000 + self.uppercrustheat = 1.7 * 10**- 6 + self.lowercrustheat = 0.4 * 10**- 6 + return self + #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - if 'MasstransportAnalysis' in analyses and not (solution == 'TransientSolution' and md.transient.ismasstransport==0): - md = checkfield(md,'fieldname','basalforcings.groundedice_melting_rate','NaN',1,'timeseries',1) - md = checkfield(md,'fieldname','basalforcings.floatingice_melting_rate','NaN',1,'timeseries',1) - if 'BalancethicknessAnalysis' in analyses: - md = checkfield(md,'fieldname','basalforcings.groundedice_melting_rate','NaN',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','basalforcings.floatingice_melting_rate','NaN',1,'size',[md.mesh.numberofvertices]) - if 'ThermalAnalysis' in analyses and not (solution == 'TransientSolution' and md.transient.isthermal==0): - md = checkfield(md,'fieldname','basalforcings.groundedice_melting_rate','NaN',1,'timeseries',1) - md = checkfield(md,'fieldname','basalforcings.floatingice_melting_rate','NaN',1,'timeseries',1) - md = checkfield(md,'fieldname','basalforcings.mantleconductivity','>=',0,'numel',1) - md = checkfield(md,'fieldname','basalforcings.nusselt','>',0,'numel',1) - md = checkfield(md,'fieldname','basalforcings.dtbg','>',0,'numel',1) - md = checkfield(md,'fieldname','basalforcings.topplumedepth','>',0,'numel',1) - md = checkfield(md,'fieldname','basalforcings.bottomplumedepth','>',0,'numel',1) - md = checkfield(md,'fieldname','basalforcings.plumex','numel',1) - md = checkfield(md,'fieldname','basalforcings.plumey','numel',1) - md = checkfield(md,'fieldname','basalforcings.crustthickness','>',0,'numel',1) - md = checkfield(md,'fieldname','basalforcings.uppercrustthickness','>',0,'numel',1) - md = checkfield(md,'fieldname','basalforcings.uppercrustheat','>',0,'numel',1) - md = checkfield(md,'fieldname','basalforcings.lowercrustheat','>',0,'numel',1) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts + def checkconsistency(self, md, solution, analyses): # {{{ + if 'MasstransportAnalysis' in analyses and not (solution == 'TransientSolution' and md.transient.ismasstransport == 0): + md = checkfield(md, 'fieldname', 'basalforcings.groundedice_melting_rate', 'NaN', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.floatingice_melting_rate', 'NaN', 1, 'timeseries', 1) + if 'BalancethicknessAnalysis' in analyses: + md = checkfield(md, 'fieldname', 'basalforcings.groundedice_melting_rate', 'NaN', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'basalforcings.floatingice_melting_rate', 'NaN', 1, 'size', [md.mesh.numberofvertices]) + if 'ThermalAnalysis' in analyses and not (solution == 'TransientSolution' and md.transient.isthermal == 0): + md = checkfield(md, 'fieldname', 'basalforcings.groundedice_melting_rate', 'NaN', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.floatingice_melting_rate', 'NaN', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'basalforcings.mantleconductivity', '>=', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'basalforcings.nusselt', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'basalforcings.dtbg', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'basalforcings.topplumedepth', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'basalforcings.bottomplumedepth', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'basalforcings.plumex', 'numel', 1) + md = checkfield(md, 'fieldname', 'basalforcings.plumey', 'numel', 1) + md = checkfield(md, 'fieldname', 'basalforcings.crustthickness', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'basalforcings.uppercrustthickness', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'basalforcings.uppercrustheat', '>', 0, 'numel', 1) + md = checkfield(md, 'fieldname', 'basalforcings.lowercrustheat', '>', 0, 'numel', 1) + return md + # }}} - WriteData(fid,prefix,'name','md.basalforcings.model','data',4,'format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','floatingice_melting_rate','format','DoubleMat','name','md.basalforcings.floatingice_melting_rate','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','groundedice_melting_rate','format','DoubleMat','name','md.basalforcings.groundedice_melting_rate','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','mantleconductivity','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','nusselt','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','dtbg','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','plumeradius','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','topplumedepth','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','bottomplumedepth','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','plumex','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','plumey','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','crustthickness','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','uppercrustthickness','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','uppercrustheat','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','lowercrustheat','format','Double') - # }}} + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + + WriteData(fid, prefix, 'name', 'md.basalforcings.model', 'data', 4, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'floatingice_melting_rate', 'format', 'DoubleMat', 'name', 'md.basalforcings.floatingice_melting_rate', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'groundedice_melting_rate', 'format', 'DoubleMat', 'name', 'md.basalforcings.groundedice_melting_rate', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'mantleconductivity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'nusselt', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'dtbg', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'plumeradius', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'topplumedepth', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'bottomplumedepth', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'plumex', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'plumey', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'crustthickness', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'uppercrustthickness', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'uppercrustheat', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'lowercrustheat', 'format', 'Double') + # }}} Index: /issm/trunk-jpl/src/m/classes/private.py =================================================================== --- /issm/trunk-jpl/src/m/classes/private.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/private.py (revision 24213) @@ -1,37 +1,40 @@ from collections import OrderedDict from fielddisplay import fielddisplay -from checkfield import checkfield + class private(object): - """ - PRIVATE class definition + """ + PRIVATE class definition - Usage: - private=private(); - """ + Usage: + private = private() + """ - def __init__(self): # {{{ - self.isconsistent = True - self.runtimename = '' - self.bamg = OrderedDict() - self.solution = '' + def __init__(self): # {{{ + self.isconsistent = True + self.runtimename = '' + self.bamg = OrderedDict() + self.solution = '' - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' private parameters: do not change' + #}}} - string="%s\n%s"%(string,fielddisplay(self,'isconsistent','is model self consistent')) - string="%s\n%s"%(string,fielddisplay(self,'runtimename','name of the run launched')) - string="%s\n%s"%(string,fielddisplay(self,'bamg','structure with mesh properties constructed if bamg is used to mesh the domain')) - string="%s\n%s"%(string,fielddisplay(self,'solution','type of solution launched')) - return string - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - return md - # }}} + def __repr__(self): # {{{ + string = ' private parameters: do not change' + + string = "%s\n%s" % (string, fielddisplay(self, 'isconsistent', 'is model self consistent')) + string = "%s\n%s" % (string, fielddisplay(self, 'runtimename', 'name of the run launched')) + string = "%s\n%s" % (string, fielddisplay(self, 'bamg', 'structure with mesh properties constructed if bamg is used to mesh the domain')) + string = "%s\n%s" % (string, fielddisplay(self, 'solution', 'type of solution launched')) + return string + #}}} + + def setdefaultparameters(self): # {{{ + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + return md + # }}} Index: /issm/trunk-jpl/src/m/classes/qmu.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu.py (revision 24213) @@ -10,186 +10,190 @@ from dakota_method import * + class qmu(object): - """ - QMU class definition + """ + QMU class definition - Usage: - qmu=qmu(); - """ + Usage: + qmu = qmu() + """ - def __init__(self): # {{{ - self.isdakota = 0 - self.variables = OrderedStruct() - self.responses = OrderedStruct() - self.method = OrderedDict() - self.params = OrderedStruct() - self.results = OrderedDict() - self.vpartition = float('NaN') - self.epartition = float('NaN') - self.numberofpartitions = 0 - self.numberofresponses = 0 - self.variabledescriptors = [] - self.responsedescriptors = [] - self.mass_flux_profile_directory = float('NaN') - self.mass_flux_profiles = float('NaN') - self.mass_flux_segments = [] - self.adjacency = float('NaN') - self.vertex_weight = float('NaN') + def __init__(self): # {{{ + self.isdakota = 0 + self.variables = OrderedStruct() + self.responses = OrderedStruct() + self.method = OrderedDict() + self.params = OrderedStruct() + self.results = OrderedDict() + self.vpartition = float('NaN') + self.epartition = float('NaN') + self.numberofpartitions = 0 + self.numberofresponses = 0 + self.variabledescriptors = [] + self.responsedescriptors = [] + self.mass_flux_profile_directory = float('NaN') + self.mass_flux_profiles = float('NaN') + self.mass_flux_segments = [] + self.adjacency = float('NaN') + self.vertex_weight = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - s =' qmu parameters:\n' + #}}} + def __repr__(self): # {{{ + s = ' qmu parameters:\n' - s+="%s\n" % fielddisplay(self,'isdakota','is qmu analysis activated?') - maxlen = 0 - s+=" variables: (arrays of each variable class)\n" + s += "%s\n" % fielddisplay(self, 'isdakota', 'is qmu analysis activated?') + maxlen = 0 + s += " variables: (arrays of each variable class)\n" - # OrderedStruct's iterator returns individual name/array-of-functions pairs - for variable in self.variables: - fname=variable[0] - maxlen=max(maxlen,len(fname)) - size = np.shape(variable[1]) - a = size[0] - b = 1 if len(size) < 2 else size[1] - s+=" %-*s: [%ix%i] '%s'\n" % (maxlen+1,fname,a,b,type(variable[1][0])) + # OrderedStruct's iterator returns individual name / array - of - functions pairs + for variable in self.variables: + fname = variable[0] + maxlen = max(maxlen, len(fname)) + size = np.shape(variable[1]) + a = size[0] + b = 1 if len(size) < 2 else size[1] + s += " %-*s: [%ix%i] '%s'\n" % (maxlen + 1, fname, a, b, type(variable[1][0])) - s+=" responses: (arrays of each response class)\n" - for response in self.responses: - fname=response[0] - maxlen=max(maxlen,len(fname)) - size = np.shape(response[1]) - a = size[0] - b = 1 if len(size) < 2 else size[1] - s+=" %-*s: [%ix%i] '%s'\n" % (maxlen+1,fname,a,b,type(response[1][0])) + s += " responses: (arrays of each response class)\n" + for response in self.responses: + fname = response[0] + maxlen = max(maxlen, len(fname)) + size = np.shape(response[1]) + a = size[0] + b = 1 if len(size) < 2 else size[1] + s += " %-*s: [%ix%i] '%s'\n" % (maxlen + 1, fname, a, b, type(response[1][0])) - s+="%s\n" % fielddisplay(self,'numberofresponses','number of responses') + s += "%s\n" % fielddisplay(self, 'numberofresponses', 'number of responses') - if type(self.method) != OrderedDict: - self.method = [self.method] - # self.method must be iterable - for method in self.method: - if isinstance(method,dakota_method): - s+=" method : '%s'\n" % (method.method) + if type(self.method) != OrderedDict: + self.method = [self.method] + # self.method must be iterable + for method in self.method: + if isinstance(method, dakota_method): + s += " method : '%s'\n" % (method.method) - # params could be have a number of forms (mainly 1 struct or many) - if type(self.params) == OrderedStruct: - params = [self.params] - else: - params = np.hstack(np.atleast_1d(np.array(self.params))) - for param in params: - print(type(param)) - print(param) - s+=" params: (array of method-independent parameters)\n" - fnames=vars(param) - maxlen=0 - for fname in fnames: - maxlen=max(maxlen,len(fname)) + # params could be have a number of forms (mainly 1 struct or many) + if type(self.params) == OrderedStruct: + params = [self.params] + else: + params = np.hstack(np.atleast_1d(np.array(self.params))) + for param in params: + print(type(param)) + print(param) + s += " params: (array of method - independent parameters)\n" + fnames = vars(param) + maxlen = 0 + for fname in fnames: + maxlen = max(maxlen, len(fname)) - for fname in fnames: - s+=" %-*s: %s\n" % (maxlen+1,fname,str(getattr(param,fname))) + for fname in fnames: + s += " %-*s: %s\n" % (maxlen + 1, fname, str(getattr(param, fname))) - # results could be have a number of forms (mainly 1 struct or many) - results = np.hstack(np.atleast_1d(np.array(self.results))) - for result in results: - s+=" results: (information from dakota files)\n" - fnames=vars(result) - maxlen=0 - for fname in fnames: - maxlen=max(maxlen,len(fname)) + # results could be have a number of forms (mainly 1 struct or many) + results = np.hstack(np.atleast_1d(np.array(self.results))) + for result in results: + s += " results: (information from dakota files)\n" + fnames = vars(result) + maxlen = 0 + for fname in fnames: + maxlen = max(maxlen, len(fname)) - for fname in fnames: - size = np.shape(response[1]) - a = size[0] - b = 0 if len(size) < 2 else size[1] - size = np.shape(getattr(result,fname)) - s+=" %-*s: [%ix%i] '%s'\n" % (maxlen+1,fname,a,b,type(getattr(result,fname))) + for fname in fnames: + size = np.shape(response[1]) + a = size[0] + b = 0 if len(size) < 2 else size[1] + size = np.shape(getattr(result, fname)) + s += " %-*s: [%ix%i] '%s'\n" % (maxlen + 1, fname, a, b, type(getattr(result, fname))) - s+="%s\n" % fielddisplay(self,'vpartition','user provided mesh partitioning (vertex based)') - s+="%s\n" % fielddisplay(self,'epartition','user provided mesh partitioning (element based)') - s+="%s\n" % fielddisplay(self,'numberofpartitions','number of partitions for semi-discrete qmu') - s+="%s\n" % fielddisplay(self,'variabledescriptors','') - s+="%s\n" % fielddisplay(self,'responsedescriptors','') - s+="%s\n" % fielddisplay(self,'method','array of dakota_method class') - s+="%s\n" % fielddisplay(self,'mass_flux_profile_directory','directory for mass flux profiles') - s+="%s\n" % fielddisplay(self,'mass_flux_profiles','list of mass_flux profiles') - s+="%s\n" % fielddisplay(self,'mass_flux_segments','') - s+="%s\n" % fielddisplay(self,'adjacency','') - s+="%s\n" % fielddisplay(self,'vertex_weight','weight applied to each mesh vertex') + s += "%s\n" % fielddisplay(self, 'vpartition', 'user provided mesh partitioning (vertex based)') + s += "%s\n" % fielddisplay(self, 'epartition', 'user provided mesh partitioning (element based)') + s += "%s\n" % fielddisplay(self, 'numberofpartitions', 'number of partitions for semi - discrete qmu') + s += "%s\n" % fielddisplay(self, 'variabledescriptors', '') + s += "%s\n" % fielddisplay(self, 'responsedescriptors', '') + s += "%s\n" % fielddisplay(self, 'method', 'array of dakota_method class') + s += "%s\n" % fielddisplay(self, 'mass_flux_profile_directory', 'directory for mass flux profiles') + s += "%s\n" % fielddisplay(self, 'mass_flux_profiles', 'list of mass_flux profiles') + s += "%s\n" % fielddisplay(self, 'mass_flux_segments', '') + s += "%s\n" % fielddisplay(self, 'adjacency', '') + s += "%s\n" % fielddisplay(self, 'vertex_weight', 'weight applied to each mesh vertex') - return s - # }}} - def extrude(self,md): # {{{ - self.vpartition=project3d(md,'vector',np.transpose(self.vpartition),'type','node') - self.epartition=project3d(md,'vector',np.transpose(self.epartition),'type','element') - return self - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + return s + # }}} - #Early return - if not md.qmu.isdakota: - return + def extrude(self, md): # {{{ + self.vpartition = project3d(md, 'vector', np.transpose(self.vpartition), 'type', 'node') + self.epartition = project3d(md, 'vector', np.transpose(self.epartition), 'type', 'element') + return self + #}}} - version=IssmConfig('_DAKOTA_VERSION_') - version=float(version[0]) + def setdefaultparameters(self): # {{{ + return self + #}}} - if version < 6: - if not md.qmu.params.evaluation_concurrency==1: - md.checkmessage("concurrency should be set to 1 when running dakota in library mode") - else: - if not strcmpi(self.params.evaluation_scheduling,'master'): - md.checkmessage('evaluation_scheduling in qmu.params should be set to "master"') + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if not md.qmu.isdakota: + return - if md.cluster.np <= 1: - md.checkmessage('in parallel library mode, Dakota needs to run on at least 2 cpus, 1 cpu for the master, 1 cpu for the slave. Modify md.cluser.np accordingly.') - - if self.params.processors_per_evaluation < 1: - md.checkmessage('in parallel library mode, Dakota needs to run at least one slave on one cpu (md.qmu.params.processors_per_evaluation >=1)!') - - if np.mod(md.cluster.np-1,self.params.processors_per_evaluation): - md.checkmessage('in parallel library mode, the requirement is for md.cluster.np = md.qmu.params.processors_per_evaluation * number_of_slaves, where number_of_slaves will automatically be determined by Dakota. Modify md.cluster.np accordingly') - - if np.size(md.qmu.vpartition) > 0: - if np.size(md.qmu.vpartition,0)!=md.mesh.numberofvertices: - md.checkmessage("user supplied vertex partition for qmu analysis should have size (md.mesh.numberofvertices x 1)") - if not min(md.qmu.vpartition.flatten())==0: - md.checkmessage("vertex partition vector not indexed from 0 on") - if max(md.qmu.vpartition.flatten())>=md.qmu.numberofpartitions: - md.checkmessage("for qmu analysis, vertex partitioning vector cannot go over npart, number of partition areas") + version = IssmConfig('_DAKOTA_VERSION_') + version = float(version[0]) + + if version < 6: + if not md.qmu.params.evaluation_concurrency == 1: + md.checkmessage("concurrency should be set to 1 when running dakota in library mode") + else: + if not strcmpi(self.params.evaluation_scheduling, 'master'): + md.checkmessage('evaluation_scheduling in qmu.params should be set to "master"') + + if md.cluster.np <= 1: + md.checkmessage('in parallel library mode, Dakota needs to run on at least 2 cpus, 1 cpu for the master, 1 cpu for the slave. Modify md.cluser.np accordingly.') + + if self.params.processors_per_evaluation < 1: + md.checkmessage('in parallel library mode, Dakota needs to run at least one slave on one cpu (md.qmu.params.processors_per_evaluation >= 1)!') + + if np.mod(md.cluster.np - 1, self.params.processors_per_evaluation): + md.checkmessage('in parallel library mode, the requirement is for md.cluster.np = md.qmu.params.processors_per_evaluation * number_of_slaves, where number_of_slaves will automatically be determined by Dakota. Modify md.cluster.np accordingly') + + if np.size(md.qmu.vpartition) > 0: + if np.size(md.qmu.vpartition, 0) != md.mesh.numberofvertices: + md.checkmessage("user supplied vertex partition for qmu analysis should have size (md.mesh.numberofvertices x 1)") + if not min(md.qmu.vpartition.flatten()) == 0: + md.checkmessage("vertex partition vector not indexed from 0 on") + if max(md.qmu.vpartition.flatten()) >= md.qmu.numberofpartitions: + md.checkmessage("for qmu analysis, vertex partitioning vector cannot go over npart, number of partition areas") if np.size(md.qmu.epartition) > 0: - if np.size(md.qmu.epartition,0) != md.mesh.numberofelements: - md.checkmessage("user supplied element partition for qmu analysis should have size (md.mesh.numberofelements x 1)") - if not min(md.qmu.epartition.flatten())==0: - md.checkmessage("elememtn partition vector not indexed from 0 on") - if max(md.qmu.epartition.flatten())>=md.qmu.numberofpartitions: - md.checkmessage("for qmu analysis, element partitioning vector cannot go over npart, number of partition areas") + if np.size(md.qmu.epartition, 0) != md.mesh.numberofelements: + md.checkmessage("user supplied element partition for qmu analysis should have size (md.mesh.numberofelements x 1)") + if not min(md.qmu.epartition.flatten()) == 0: + md.checkmessage("elememtn partition vector not indexed from 0 on") + if max(md.qmu.epartition.flatten()) >= md.qmu.numberofpartitions: + md.checkmessage("for qmu analysis, element partitioning vector cannot go over npart, number of partition areas") if np.size(md.qmu.vpartition) == 0 or np.any(np.isnan(md.qmu.vpartition)) or np.size(md.qmu.epartition) == 0 or np.any(np.isnan(md.qmu.epartition)): - md.checkmessage("for qmu analysis, both an element and partitioning vectors need to be supplied with no nan values! One can be defaulted to all zeros.") + md.checkmessage("for qmu analysis, both an element and partitioning vectors need to be supplied with no nan values! One can be defaulted to all zeros.") - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','isdakota','format','Boolean') - if not self.isdakota: - WriteData(fid,prefix,'data',False,'name','md.qmu.mass_flux_segments_present','format','Boolean'); - return - WriteData(fid,prefix,'object',self,'fieldname','vpartition','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'fieldname','epartition','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'fieldname','numberofpartitions','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','numberofresponses','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','variabledescriptors','format','StringArray') - WriteData(fid,prefix,'object',self,'fieldname','responsedescriptors','format','StringArray') - if not isempty(self.mass_flux_segments): - WriteData(fid,prefix,'data',self.mass_flux_segments,'name','md.qmu.mass_flux_segments','format','MatArray'); - flag=True; - else: - flag=False; - WriteData(fid,prefix,'data',flag,'name','md.qmu.mass_flux_segments_present','format','Boolean'); - # }}} + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'isdakota', 'format', 'Boolean') + if not self.isdakota: + WriteData(fid, prefix, 'data', False, 'name', 'md.qmu.mass_flux_segments_present', 'format', 'Boolean') + return + WriteData(fid, prefix, 'object', self, 'fieldname', 'vpartition', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'fieldname', 'epartition', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'fieldname', 'numberofpartitions', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'numberofresponses', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'variabledescriptors', 'format', 'StringArray') + WriteData(fid, prefix, 'object', self, 'fieldname', 'responsedescriptors', 'format', 'StringArray') + if not isempty(self.mass_flux_segments): + WriteData(fid, prefix, 'data', self.mass_flux_segments, 'name', 'md.qmu.mass_flux_segments', 'format', 'MatArray') + flag = True + else: + flag = False + WriteData(fid, prefix, 'data', flag, 'name', 'md.qmu.mass_flux_segments_present', 'format', 'Boolean') + # }}} Index: /issm/trunk-jpl/src/m/classes/qmu/@dakota_method/dakota_method.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/@dakota_method/dakota_method.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/@dakota_method/dakota_method.py (revision 24213) @@ -5,9 +5,10 @@ import numpy as np + class dakota_method(object): - ''' + ''' definition for the dakota_method class. - [dm]=dakota_method(method) + [dm] = dakota_method(method) where the required input is: @@ -21,5 +22,5 @@ responses (cell array, applicable response types, []) ghspec (cell array, gradient and hessian specs, []) - params (structure, method-depent parameters, []) + params (structure, method - depent parameters, []) this class is used to guide the writing of a dakota input @@ -43,863 +44,863 @@ authority as may be required before exporting such np.information to foreign countries or providing access to foreign persons." - ''' - - def __init__(self,*args): - self.method ='' - self.type ='' - self.variables=[] - self.lcspec =[] - self.responses=[] - self.ghspec =[] - #properites - self.params =struct() - - @staticmethod - def dakota_method(*args): - dm = dakota_method() - # return a default object - if len(args) == 0: - return dm - - # copy the object or create the object from the input - elif len(args) == 1: - method = args[0] - - #given argument was a method, copy it - if isinstance(method,dakota_method): - #dm=method - object=method - for field in object.keys(): - if field in vars(dm): - setattr(dm,field,object[field]) - return dm - - #given argument was a way of constructing a method - else: - mlist=['dot_bfgs', - 'dot_frcg', - 'dot_mmfd', - 'dot_slp', - 'dot_sqp', - 'npsol_sqp', - 'conmin_frcg', - 'conmin_mfd', - 'optpp_cg', - 'optpp_q_newton', - 'optpp_fd_newton', - 'optpp_newton', - 'optpp_pds', - 'asynch_pattern_search', - 'coliny_cobyla', - 'coliny_direct', - 'coliny_ea', - 'coliny_pattern_search', - 'coliny_solis_wets', - 'ncsu_direct', - 'surrogate_based_local', - 'surrogate_based_global', - 'moga', - 'soga', - 'nl2sol', - 'nlssol_sqp', - 'optpp_g_newton', - 'nond_sampling', - 'nond_local_reliability', - 'nond_global_reliability', - 'nond_polynomial_chaos', - 'nond_stoch_collocation', - 'nond_evidence', - 'dace', - 'fsu_quasi_mc', - 'fsu_cvt', - 'vector_parameter_study', - 'list_parameter_study', - 'centered_parameter_study', - 'multidim_parameter_study', - 'bayes_calibration'] - - mlist2=[] - for i in range(len(mlist)): - if strncmpi(method,mlist[i],len(method)): - mlist2.append(mlist[i]) - # check for a unique match in the list of methods - l = len(mlist2) - if l == 0: - raise RuntimeError('Unrecognized method: '+str(method)+'.') - elif l == 1: - dm.method=mlist2[0] - else: - raise RuntimeError('Non-unique method: '+str(method)+' matches '+string_cell(mlist2)) - - # assign the default values for the method - # switch dm.method - if dm.method in ['dot_bfgs','dot_frcg']: - dm.type ='dot' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.constraint_tolerance=False - dm.params.output=False - dm.params.speculative=False - dm.params.scaling=False - dm.params.optimization_type='minimize' - - elif dm.method in ['dot_mmfd','dot_slp','dot_sqp']: - dm.type ='dot' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =['linear_inequality_constraint', - 'linear_equality_constraint'] - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.constraint_tolerance=False - dm.params.output=False - dm.params.speculative=False - dm.params.scaling=False - dm.params.optimization_type='minimize' - - elif dm.method == 'npsol_sqp': - dm.type ='npsol' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =['linear_inequality_constraint', - 'linear_equality_constraint'] - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.constraint_tolerance=False - dm.params.output=False - dm.params.speculative=False - dm.params.scaling=False - dm.params.verify_level=-1 - dm.params.function_precision=1.0e-10 - dm.params.linesearch_tolerance=0.9 - - elif dm.method == 'conmin_frcg': - dm.type ='conmin' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.constraint_tolerance=False - dm.params.output=False - dm.params.speculative=False - dm.params.scaling=False - - elif dm.method == 'conmin_mfd': - dm.type ='conmin' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =['linear_inequality_constraint', - 'linear_equality_constraint'] - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.constraint_tolerance=False - dm.params.output=False - dm.params.speculative=False - dm.params.scaling=False - - elif dm.method == 'optpp_cg': - dm.type ='optpp' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.output=False - dm.params.speculative=False - dm.params.scaling=False - dm.params.max_step=1000. - dm.params.gradient_tolerance=1.0e-4 - - elif dm.method in ['optpp_q_newton', - 'optpp_fd_newton', - 'optpp_newton']: - dm.type ='optpp' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =['linear_inequality_constraint', - 'linear_equality_constraint'] - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.output=False - dm.params.speculative=False - dm.params.scaling=False - dm.params.value_based_line_search=False - dm.params.gradient_based_line_search=False - dm.params.trust_region=False - dm.params.tr_pds=False - dm.params.max_step=1000. - dm.params.gradient_tolerance=1.0e-4 - dm.params.merit_function='argaez_tapia' - dm.params.central_path=dm.params.merit_function - dm.params.steplength_to_boundary=0.99995 - dm.params.centering_parameter=0.2 - - elif dm.method == 'optpp_pds': - dm.type ='optpp' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.output=False - dm.params.speculative=False - dm.params.scaling=False - dm.params.search_scheme_size=32 - - elif dm.method == 'asynch_pattern_search': - dm.type ='apps' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =['linear_inequality_constraint', - 'linear_equality_constraint'] - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_function_evaluations=False - dm.params.constraint_tolerance=False - dm.params.output=False - dm.params.scaling=False - dm.params.initial_delta=1.0 - dm.params.threshold_delta=0.01 - dm.params.contraction_factor=0.5 - dm.params.solution_target=False - dm.params.synchronization='nonblocking' - dm.params.merit_function='merit2_smooth' - dm.params.constraint_penalty=1.0 - dm.params.smoothing_factor=1.0 - - elif dm.method == 'coliny_cobyla': - dm.type ='coliny' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.output=False - dm.params.scaling=False - dm.params.show_misc_options=False - dm.params.misc_options=[] - dm.params.solution_accuracy=-np.inf - dm.params.initial_delta=[] - dm.params.threshold_delta=[] - - elif dm.method == 'coliny_direct': - dm.type ='coliny' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.output=False - dm.params.scaling=False - dm.params.show_misc_options=False - dm.params.misc_options=[] - dm.params.solution_accuracy=-np.inf - dm.params.division='major_dimension' - dm.params.global_balance_parameter=0.0 - dm.params.local_balance_parameter=1.0e-8 - dm.params.max_boxsize_limit=0.0 - dm.params.min_boxsize_limit=0.0001 - dm.params.constraint_penalty=1000.0 - - elif dm.method == 'coliny_ea': - dm.type ='coliny' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.output=False - dm.params.scaling=False - dm.params.show_misc_options=False - dm.params.misc_options=[] - dm.params.solution_accuracy=-np.inf - dm.params.seed=False - dm.params.population_size=50 - dm.params.initialization_type='unique_random' - dm.params.fitness_type='linear_rank' - dm.params.replacement_type='elitist' - dm.params.random=[] - dm.params.chc=[] - dm.params.elitist=[] - dm.params.new_solutions_generated='population_size - replacement_size' - dm.params.crossover_type='two_point' - dm.params.crossover_rate=0.8 - dm.params.mutation_type='offset_normal' - dm.params.mutation_scale=0.1 - dm.params.mutation_range=1 - dm.params.dimension_ratio=1.0 - dm.params.mutation_rate=1.0 - dm.params.non_adaptive=False - - elif dm.method == 'coliny_pattern_search': - dm.type ='coliny' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.output=False - dm.params.scaling=False - dm.params.show_misc_options=False - dm.params.misc_options=[] - dm.params.solution_accuracy=-np.inf - dm.params.stochastic=False - dm.params.seed=False - dm.params.initial_delta=[] - dm.params.threshold_delta=[] - dm.params.constraint_penalty=1.0 - dm.params.constant_penalty=False - dm.params.pattern_basis='coordinate' - dm.params.total_pattern_size=False - dm.params.no_expansion=False - dm.params.expand_after_success=1 - dm.params.contraction_factor=0.5 - dm.params.synchronization='nonblocking' - dm.params.exploratory_moves='basic_pattern' - - elif dm.method == 'coliny_solis_wets': - dm.type ='coliny' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.output=False - dm.params.scaling=False - dm.params.show_misc_options=False - dm.params.misc_options=[] - dm.params.solution_accuracy=-np.inf - dm.params.seed=False - dm.params.initial_delta=[] - dm.params.threshold_delta=[] - dm.params.no_expansion=False - dm.params.expand_after_success=5 - dm.params.contract_after_failure=3 - dm.params.contraction_factor=0.5 - dm.params.constraint_penalty=1.0 - dm.params.constant_penalty=False - - elif dm.method == 'ncsu_direct': - dm.type ='ncsu' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =['linear_inequality_constraint', - 'linear_equality_constraint'] # ? - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] # ? - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.scaling=False - dm.params.solution_accuracy=0. - dm.params.min_boxsize_limit=1.0e-8 - dm.params.vol_boxsize_limit=1.0e-8 - - #if dm.method in ['surrogate_based_local', - #'surrogate_based_global']: - - elif dm.method == 'moga': - dm.type ='jega' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =['linear_inequality_constraint', - 'linear_equality_constraint'] - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.output=False - dm.params.scaling=False - dm.params.seed=False - dm.params.log_file='JEGAGlobal.log' - dm.params.population_size=50 - dm.params.print_each_pop=False - #according to documentation, uses method-indepent control - #dm.params.output='normal' - dm.params.initialization_type='unique_random' - dm.params.mutation_type='replace_uniform' - dm.params.mutation_scale=0.15 - dm.params.mutation_rate=0.08 - dm.params.replacement_type='' - dm.params.below_limit=6 - dm.params.shrinkage_percentage=0.9 - dm.params.crossover_type='shuffle_random' - dm.params.multi_point_binary=[] - dm.params.multi_point_parameterized_binary=[] - dm.params.multi_point_real=[] - dm.params.shuffle_random=[] - dm.params.num_parents=2 - dm.params.num_offspring=2 - dm.params.crossover_rate=0.8 - dm.params.fitness_type='' - dm.params.niching_type=False - dm.params.radial=[0.01] - dm.params.distance=[0.01] - dm.params.metric_tracker=False - dm.params.percent_change=0.1 - dm.params.num_generations=10 - dm.params.postprocessor_type=False - dm.params.orthogonal_distance=[0.01] - - elif dm.method == 'soga': - dm.type ='jega' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =['linear_inequality_constraint', - 'linear_equality_constraint'] - dm.responses=['objective_function', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.output=False - dm.params.scaling=False - dm.params.seed=False - dm.params.log_file='JEGAGlobal.log' - dm.params.population_size=50 - dm.params.print_each_pop=False - dm.params.output='normal' - dm.params.initialization_type='unique_random' - dm.params.mutation_type='replace_uniform' - dm.params.mutation_scale=0.15 - dm.params.mutation_rate=0.08 - dm.params.replacement_type='' - dm.params.below_limit=6 - dm.params.shrinkage_percentage=0.9 - dm.params.crossover_type='shuffle_random' - dm.params.multi_point_binary=[] - dm.params.multi_point_parameterized_binary=[] - dm.params.multi_point_real=[] - dm.params.shuffle_random=[] - dm.params.num_parents=2 - dm.params.num_offspring=2 - dm.params.crossover_rate=0.8 - dm.params.fitness_type='merit_function' - dm.params.constraint_penalty=1.0 - dm.params.replacement_type='' - dm.params.convergence_type=False - dm.params.num_generations=10 - dm.params.percent_change=0.1 - - elif dm.method == 'nl2sol': - dm.type ='lsq' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['least_squares_term'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.output=False - dm.params.scaling=False - dm.params.function_precision=1.0e-10 - dm.params.absolute_conv_tol=-1. - dm.params.x_conv_tol=-1. - dm.params.singular_conv_tol=-1. - dm.params.singular_radius=-1. - dm.params.False_conv_tol=-1. - dm.params.initial_trust_radius=-1. - dm.params.covariance=0 - dm.params.regression_stressbalances=False - - elif dm.method == 'nlssol_sqp': - dm.type ='lsq' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =['linear_inequality_constraint', - 'linear_equality_constraint'] - dm.responses=['least_squares_term', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.constraint_tolerance=False - dm.params.output=False - dm.params.speculative=False - dm.params.scaling=False - dm.params.verify_level=-1 - dm.params.function_precision=1.0e-10 - dm.params.linesearch_tolerance=0.9 - - elif dm.method == 'optpp_g_newton': - dm.type ='lsq' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =['linear_inequality_constraint', - 'linear_equality_constraint'] - dm.responses=['least_squares_term', - 'nonlinear_inequality_constraint', - 'nonlinear_equality_constraint'] - dm.ghspec =['grad'] - dm.params.max_iterations=False - dm.params.max_function_evaluations=False - dm.params.convergence_tolerance=False - dm.params.output=False - dm.params.speculative=False - dm.params.scaling=False - dm.params.value_based_line_search=False - dm.params.gradient_based_line_search=False - dm.params.trust_region=False - dm.params.tr_pds=False - dm.params.max_step=1000. - dm.params.gradient_tolerance=1.0e-4 - dm.params.merit_function='argaez_tapia' - dm.params.central_path=dm.params.merit_function - dm.params.steplength_to_boundary=0.99995 - dm.params.centering_parameter=0.2 - - elif dm.method == 'nond_sampling': - dm.type ='nond' - dm.variables=['normal_uncertain', - 'uniform_uncertain', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['response_function'] - dm.ghspec =[] - # not documented, but apparently works - dm.params.output=False - dm.params.seed=False - dm.params.fixed_seed=False - dm.params.rng=False - dm.params.samples=False - dm.params.sample_type='lhs' - dm.params.all_variables=False - dm.params.variance_based_decomp=False - dm.params.previous_samples=0 - - elif dm.method == 'nond_local_reliability': - dm.type ='nond' - dm.variables=['normal_uncertain', - 'uniform_uncertain', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['response_function'] - dm.ghspec =['grad'] - # not documented, but may work - dm.params.output=False - dm.params.max_iterations=False - dm.params.convergence_tolerance=False - dm.params.mpp_search=False - dm.params.sqp=False - dm.params.nip=False - dm.params.integration='first_order' - dm.params.refinement=False - dm.params.samples=0 - dm.params.seed=False - - elif dm.method == 'nond_global_reliability': - dm.type ='nond' - dm.variables=['normal_uncertain', - 'uniform_uncertain', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['response_function'] - dm.ghspec =['grad'] - # not documented, but may work - dm.params.output=False - dm.params.x_gaussian_process=False - dm.params.u_gaussian_process=False - dm.params.all_variables=False - dm.params.seed=False - - elif dm.method == 'nond_polynomial_chaos': - dm.type ='nond' - dm.variables=['normal_uncertain', - 'uniform_uncertain', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['response_function'] - dm.ghspec =['grad'] - # not documented, but may work - dm.params.output=False - dm.params.expansion_order=[] - dm.params.expansion_terms=[] - dm.params.quadrature_order=[] - dm.params.sparse_grid_level=[] - dm.params.expansion_samples=[] - dm.params.incremental_lhs=False - dm.params.collocation_points=[] - dm.params.collocation_ratio=[] - dm.params.reuse_samples=False - dm.params.expansion_import_file='' - dm.params.seed=False - dm.params.fixed_seed=False - dm.params.samples=0 - dm.params.sample_type='lhs' - dm.params.all_variables=False - - elif dm.method == 'nond_stoch_collocation': - dm.type ='nond' - dm.variables=['normal_uncertain', - 'uniform_uncertain', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['response_function'] - dm.ghspec =['grad'] - # not documented, but may work - dm.params.output=False - dm.params.quadrature_order=[] - dm.params.sparse_grid_level=[] - dm.params.seed=False - dm.params.fixed_seed=False - dm.params.samples=0 - dm.params.sample_type='lhs' - dm.params.all_variables=False - - elif dm.method == 'nond_evidence': - dm.type ='nond' - dm.variables=['normal_uncertain', - 'uniform_uncertain', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['response_function'] - dm.ghspec =['grad'] - # not documented, but may work - dm.params.output=False - dm.params.seed=False - dm.params.samples=10000 - - elif dm.method == 'dace': - dm.type ='dace' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'response_function'] - dm.ghspec =[] - dm.params.grid=False - dm.params.random=False - dm.params.oas=False - dm.params.lhs=False - dm.params.oa_lhs=False - dm.params.box_behnken=False - dm.params.central_composite=False - dm.params.seed=False - dm.params.fixed_seed=False - dm.params.samples=False - dm.params.symbols=False - dm.params.quality_metrics=False - dm.params.variance_based_decomp=False - - elif dm.method == 'fsu_quasi_mc': - dm.type ='dace' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'response_function'] - dm.ghspec =[] - dm.params.halton=False - dm.params.hammersley=False - dm.params.samples=0 - dm.params.sequence_start=[0] - dm.params.sequence_leap=[1] - dm.params.prime_base=False - dm.params.fixed_sequence=False - dm.params.latinize=False - dm.params.variance_based_decomp=False - dm.params.quality_metrics=False - - elif dm.method == 'fsu_cvt': - dm.type ='dace' - dm.variables=['continuous_design', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'response_function'] - dm.ghspec =[] - dm.params.seed=False - dm.params.fixed_seed=False - dm.params.samples=0 - dm.params.num_trials=10000 - dm.params.trial_type='random' - dm.params.latinize=False - dm.params.variance_based_decomp=False - dm.params.quality_metrics=False - - elif dm.method == 'vector_parameter_study': - dm.type ='param' - dm.variables=['continuous_design', - 'normal_uncertain', - 'uniform_uncertain', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'response_function'] - dm.ghspec =[] - dm.params.output=False - dm.params.final_point=[] - dm.params.step_length=[] - dm.params.num_steps=[] - dm.params.step_vector=[] - dm.params.num_steps=[] - - elif dm.method == 'list_parameter_study': - dm.type ='param' - dm.variables=['continuous_design', - 'normal_uncertain', - 'uniform_uncertain', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'response_function'] - dm.ghspec =[] - dm.params.output=False - dm.params.list_of_points=[] - - elif dm.method == 'centered_parameter_study': - dm.type ='param' - dm.variables=['continuous_design', - 'normal_uncertain', - 'uniform_uncertain', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'response_function'] - dm.ghspec =[] - dm.params.output=False - dm.params.percent_delta=[] - dm.params.deltas_per_variable=[] - - elif dm.method == 'multidim_parameter_study': - dm.type ='param' - dm.variables=['continuous_design', - 'normal_uncertain', - 'uniform_uncertain', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'response_function'] - dm.ghspec =[] - dm.params.output=False - dm.params.partitions=[] - - elif dm.method == 'bayes_calibration': - dm.type ='bayes' - dm.variables=['continuous_design', - 'normal_uncertain', - 'uniform_uncertain', - 'continuous_state'] - dm.lcspec =[] - dm.responses=['objective_function', - 'response_function', - 'calibration_function'] - dm.ghspec =[] - dm.params.queso=False - dm.params.dream=False - dm.params.gpmsa=False - dm.params.samples=0 - dm.params.seed=False - dm.params.output=False - dm.params.metropolis_hastings=False - dm.params.proposal_covariance=False - dm.params.diagonal=False - dm.params.values=[] - - else: - raise RuntimeError('Unimplemented method: {}.'.format(dm.method)) - - # if more than one argument, issue warning - else: - print('Warning: dakota_method:extra_arg: Extra arguments for object of class '+str(type(dm))+'.') - return dm - - def __repr__(dm): - - # display the object - string = '\nclass dakota_method object = \n' - string += ' method: '+str(dm.method) + '\n' - string += ' type: '+str(dm.type) + '\n' - string += ' variables: '+str(dm.variables) + '\n' - string += ' lcspec: '+str(dm.lcspec) + '\n' - string += ' responses: '+str(dm.responses) + '\n' - string += ' ghspec: '+str(dm.ghspec) + '\n' - - # display the parameters within the object - - fnames=fieldnames(dm.params) - #get rid of stuff we aren't using - try: - fnames.remove('__module__') - except ValueError: - pass - - maxlen=0 - for i in range(len(fnames)): - maxlen=max(maxlen,len(fnames[i])) - - for i in fnames: - string += ' params.{:{space}s}: {}\n'.format(str(i),str(dm.params.__dict__[i]),space=maxlen+1) - #params.x : y - #with maxlen+1 spaces between x and : - return string + ''' + + def __init__(self, *args): + self.method = '' + self.type = '' + self.variables = [] + self.lcspec = [] + self.responses = [] + self.ghspec = [] + #properites + self.params = struct() + + @staticmethod + def dakota_method(*args): + dm = dakota_method() + # return a default object + if len(args) == 0: + return dm + + # copy the object or create the object from the input + elif len(args) == 1: + method = args[0] + + #given argument was a method, copy it + if isinstance(method, dakota_method): + #dm = method + object = method + for field in object.keys(): + if field in vars(dm): + setattr(dm, field, object[field]) + return dm + + #given argument was a way of constructing a method + else: + mlist = ['dot_bfgs', + 'dot_frcg', + 'dot_mmfd', + 'dot_slp', + 'dot_sqp', + 'npsol_sqp', + 'conmin_frcg', + 'conmin_mfd', + 'optpp_cg', + 'optpp_q_newton', + 'optpp_fd_newton', + 'optpp_newton', + 'optpp_pds', + 'asynch_pattern_search', + 'coliny_cobyla', + 'coliny_direct', + 'coliny_ea', + 'coliny_pattern_search', + 'coliny_solis_wets', + 'ncsu_direct', + 'surrogate_based_local', + 'surrogate_based_global', + 'moga', + 'soga', + 'nl2sol', + 'nlssol_sqp', + 'optpp_g_newton', + 'nond_sampling', + 'nond_local_reliability', + 'nond_global_reliability', + 'nond_polynomial_chaos', + 'nond_stoch_collocation', + 'nond_evidence', + 'dace', + 'fsu_quasi_mc', + 'fsu_cvt', + 'vector_parameter_study', + 'list_parameter_study', + 'centered_parameter_study', + 'multidim_parameter_study', + 'bayes_calibration'] + + mlist2 = [] + for i in range(len(mlist)): + if strncmpi(method, mlist[i], len(method)): + mlist2.append(mlist[i]) + # check for a unique match in the list of methods + length = len(mlist2) + if length == 0: + raise RuntimeError('Unrecognized method: ' + str(method) + '.') + elif length == 1: + dm.method = mlist2[0] + else: + raise RuntimeError('Non - unique method: ' + str(method) + ' matches ' + string_cell(mlist2)) + + # assign the default values for the method + # switch dm.method + if dm.method in ['dot_bfgs', 'dot_frcg']: + dm.type = 'dot' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.constraint_tolerance = False + dm.params.output = False + dm.params.speculative = False + dm.params.scaling = False + dm.params.optimization_type = 'minimize' + + elif dm.method in ['dot_mmfd', 'dot_slp', 'dot_sqp']: + dm.type = 'dot' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = ['linear_inequality_constraint', + 'linear_equality_constraint'] + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.constraint_tolerance = False + dm.params.output = False + dm.params.speculative = False + dm.params.scaling = False + dm.params.optimization_type = 'minimize' + + elif dm.method == 'npsol_sqp': + dm.type = 'npsol' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = ['linear_inequality_constraint', + 'linear_equality_constraint'] + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.constraint_tolerance = False + dm.params.output = False + dm.params.speculative = False + dm.params.scaling = False + dm.params.verify_level = -1 + dm.params.function_precision = 1.0e-10 + dm.params.linesearch_tolerance = 0.9 + + elif dm.method == 'conmin_frcg': + dm.type = 'conmin' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.constraint_tolerance = False + dm.params.output = False + dm.params.speculative = False + dm.params.scaling = False + + elif dm.method == 'conmin_mfd': + dm.type = 'conmin' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = ['linear_inequality_constraint', + 'linear_equality_constraint'] + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.constraint_tolerance = False + dm.params.output = False + dm.params.speculative = False + dm.params.scaling = False + + elif dm.method == 'optpp_cg': + dm.type = 'optpp' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.output = False + dm.params.speculative = False + dm.params.scaling = False + dm.params.max_step = 1000. + dm.params.gradient_tolerance = 1.0e-4 + + elif dm.method in ['optpp_q_newton', + 'optpp_fd_newton', + 'optpp_newton']: + dm.type = 'optpp' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = ['linear_inequality_constraint', + 'linear_equality_constraint'] + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.output = False + dm.params.speculative = False + dm.params.scaling = False + dm.params.value_based_line_search = False + dm.params.gradient_based_line_search = False + dm.params.trust_region = False + dm.params.tr_pds = False + dm.params.max_step = 1000. + dm.params.gradient_tolerance = 1.0e-4 + dm.params.merit_function = 'argaez_tapia' + dm.params.central_path = dm.params.merit_function + dm.params.steplength_to_boundary = 0.99995 + dm.params.centering_parameter = 0.2 + + elif dm.method == 'optpp_pds': + dm.type = 'optpp' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.output = False + dm.params.speculative = False + dm.params.scaling = False + dm.params.search_scheme_size = 32 + + elif dm.method == 'asynch_pattern_search': + dm.type = 'apps' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = ['linear_inequality_constraint', + 'linear_equality_constraint'] + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_function_evaluations = False + dm.params.constraint_tolerance = False + dm.params.output = False + dm.params.scaling = False + dm.params.initial_delta = 1.0 + dm.params.threshold_delta = 0.01 + dm.params.contraction_factor = 0.5 + dm.params.solution_target = False + dm.params.synchronization = 'nonblocking' + dm.params.merit_function = 'merit2_smooth' + dm.params.constraint_penalty = 1.0 + dm.params.smoothing_factor = 1.0 + + elif dm.method == 'coliny_cobyla': + dm.type = 'coliny' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.output = False + dm.params.scaling = False + dm.params.show_misc_options = False + dm.params.misc_options = [] + dm.params.solution_accuracy = -np.inf + dm.params.initial_delta = [] + dm.params.threshold_delta = [] + + elif dm.method == 'coliny_direct': + dm.type = 'coliny' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.output = False + dm.params.scaling = False + dm.params.show_misc_options = False + dm.params.misc_options = [] + dm.params.solution_accuracy = -np.inf + dm.params.division = 'major_dimension' + dm.params.global_balance_parameter = 0.0 + dm.params.local_balance_parameter = 1.0e-8 + dm.params.max_boxsize_limit = 0.0 + dm.params.min_boxsize_limit = 0.0001 + dm.params.constraint_penalty = 1000.0 + + elif dm.method == 'coliny_ea': + dm.type = 'coliny' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.output = False + dm.params.scaling = False + dm.params.show_misc_options = False + dm.params.misc_options = [] + dm.params.solution_accuracy = -np.inf + dm.params.seed = False + dm.params.population_size = 50 + dm.params.initialization_type = 'unique_random' + dm.params.fitness_type = 'linear_rank' + dm.params.replacement_type = 'elitist' + dm.params.random = [] + dm.params.chc = [] + dm.params.elitist = [] + dm.params.new_solutions_generated = 'population_size-replacement_size' + dm.params.crossover_type = 'two_point' + dm.params.crossover_rate = 0.8 + dm.params.mutation_type = 'offset_normal' + dm.params.mutation_scale = 0.1 + dm.params.mutation_range = 1 + dm.params.dimension_ratio = 1.0 + dm.params.mutation_rate = 1.0 + dm.params.non_adaptive = False + + elif dm.method == 'coliny_pattern_search': + dm.type = 'coliny' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.output = False + dm.params.scaling = False + dm.params.show_misc_options = False + dm.params.misc_options = [] + dm.params.solution_accuracy = - np.inf + dm.params.stochastic = False + dm.params.seed = False + dm.params.initial_delta = [] + dm.params.threshold_delta = [] + dm.params.constraint_penalty = 1.0 + dm.params.constant_penalty = False + dm.params.pattern_basis = 'coordinate' + dm.params.total_pattern_size = False + dm.params.no_expansion = False + dm.params.expand_after_success = 1 + dm.params.contraction_factor = 0.5 + dm.params.synchronization = 'nonblocking' + dm.params.exploratory_moves = 'basic_pattern' + + elif dm.method == 'coliny_solis_wets': + dm.type = 'coliny' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.output = False + dm.params.scaling = False + dm.params.show_misc_options = False + dm.params.misc_options = [] + dm.params.solution_accuracy = -np.inf + dm.params.seed = False + dm.params.initial_delta = [] + dm.params.threshold_delta = [] + dm.params.no_expansion = False + dm.params.expand_after_success = 5 + dm.params.contract_after_failure = 3 + dm.params.contraction_factor = 0.5 + dm.params.constraint_penalty = 1.0 + dm.params.constant_penalty = False + + elif dm.method == 'ncsu_direct': + dm.type = 'ncsu' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = ['linear_inequality_constraint', + 'linear_equality_constraint'] # ? + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] # ? + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.scaling = False + dm.params.solution_accuracy = 0. + dm.params.min_boxsize_limit = 1.0e-8 + dm.params.vol_boxsize_limit = 1.0e-8 + + #if dm.method in ['surrogate_based_local', + #'surrogate_based_global']: + + elif dm.method == 'moga': + dm.type = 'jega' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = ['linear_inequality_constraint', + 'linear_equality_constraint'] + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.output = False + dm.params.scaling = False + dm.params.seed = False + dm.params.log_file = 'JEGAGlobal.log' + dm.params.population_size = 50 + dm.params.print_each_pop = False + #according to documentation, uses method - indepent control + #dm.params.output = 'normal' + dm.params.initialization_type = 'unique_random' + dm.params.mutation_type = 'replace_uniform' + dm.params.mutation_scale = 0.15 + dm.params.mutation_rate = 0.08 + dm.params.replacement_type = '' + dm.params.below_limit = 6 + dm.params.shrinkage_percentage = 0.9 + dm.params.crossover_type = 'shuffle_random' + dm.params.multi_point_binary = [] + dm.params.multi_point_parameterized_binary = [] + dm.params.multi_point_real = [] + dm.params.shuffle_random = [] + dm.params.num_parents = 2 + dm.params.num_offspring = 2 + dm.params.crossover_rate = 0.8 + dm.params.fitness_type = '' + dm.params.niching_type = False + dm.params.radial = [0.01] + dm.params.distance = [0.01] + dm.params.metric_tracker = False + dm.params.percent_change = 0.1 + dm.params.num_generations = 10 + dm.params.postprocessor_type = False + dm.params.orthogonal_distance = [0.01] + + elif dm.method == 'soga': + dm.type = 'jega' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = ['linear_inequality_constraint', + 'linear_equality_constraint'] + dm.responses = ['objective_function', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.output = False + dm.params.scaling = False + dm.params.seed = False + dm.params.log_file = 'JEGAGlobal.log' + dm.params.population_size = 50 + dm.params.print_each_pop = False + dm.params.output = 'normal' + dm.params.initialization_type = 'unique_random' + dm.params.mutation_type = 'replace_uniform' + dm.params.mutation_scale = 0.15 + dm.params.mutation_rate = 0.08 + dm.params.replacement_type = '' + dm.params.below_limit = 6 + dm.params.shrinkage_percentage = 0.9 + dm.params.crossover_type = 'shuffle_random' + dm.params.multi_point_binary = [] + dm.params.multi_point_parameterized_binary = [] + dm.params.multi_point_real = [] + dm.params.shuffle_random = [] + dm.params.num_parents = 2 + dm.params.num_offspring = 2 + dm.params.crossover_rate = 0.8 + dm.params.fitness_type = 'merit_function' + dm.params.constraint_penalty = 1.0 + dm.params.replacement_type = '' + dm.params.convergence_type = False + dm.params.num_generations = 10 + dm.params.percent_change = 0.1 + + elif dm.method == 'nl2sol': + dm.type = 'lsq' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['least_squares_term'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.output = False + dm.params.scaling = False + dm.params.function_precision = 1.0e-10 + dm.params.absolute_conv_tol = -1. + dm.params.x_conv_tol = -1. + dm.params.singular_conv_tol = -1. + dm.params.singular_radius = -1. + dm.params.False_conv_tol = -1. + dm.params.initial_trust_radius = -1. + dm.params.covariance = 0 + dm.params.regression_stressbalances = False + + elif dm.method == 'nlssol_sqp': + dm.type = 'lsq' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = ['linear_inequality_constraint', + 'linear_equality_constraint'] + dm.responses = ['least_squares_term', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.constraint_tolerance = False + dm.params.output = False + dm.params.speculative = False + dm.params.scaling = False + dm.params.verify_level = -1 + dm.params.function_precision = 1.0e-10 + dm.params.linesearch_tolerance = 0.9 + + elif dm.method == 'optpp_g_newton': + dm.type = 'lsq' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = ['linear_inequality_constraint', + 'linear_equality_constraint'] + dm.responses = ['least_squares_term', + 'nonlinear_inequality_constraint', + 'nonlinear_equality_constraint'] + dm.ghspec = ['grad'] + dm.params.max_iterations = False + dm.params.max_function_evaluations = False + dm.params.convergence_tolerance = False + dm.params.output = False + dm.params.speculative = False + dm.params.scaling = False + dm.params.value_based_line_search = False + dm.params.gradient_based_line_search = False + dm.params.trust_region = False + dm.params.tr_pds = False + dm.params.max_step = 1000. + dm.params.gradient_tolerance = 1.0e-4 + dm.params.merit_function = 'argaez_tapia' + dm.params.central_path = dm.params.merit_function + dm.params.steplength_to_boundary = 0.99995 + dm.params.centering_parameter = 0.2 + + elif dm.method == 'nond_sampling': + dm.type = 'nond' + dm.variables = ['normal_uncertain', + 'uniform_uncertain', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['response_function'] + dm.ghspec = [] + # not documented, but apparently works + dm.params.output = False + dm.params.seed = False + dm.params.fixed_seed = False + dm.params.rng = False + dm.params.samples = False + dm.params.sample_type = 'lhs' + dm.params.all_variables = False + dm.params.variance_based_decomp = False + dm.params.previous_samples = 0 + + elif dm.method == 'nond_local_reliability': + dm.type = 'nond' + dm.variables = ['normal_uncertain', + 'uniform_uncertain', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['response_function'] + dm.ghspec = ['grad'] + # not documented, but may work + dm.params.output = False + dm.params.max_iterations = False + dm.params.convergence_tolerance = False + dm.params.mpp_search = False + dm.params.sqp = False + dm.params.nip = False + dm.params.integration = 'first_order' + dm.params.refinement = False + dm.params.samples = 0 + dm.params.seed = False + + elif dm.method == 'nond_global_reliability': + dm.type = 'nond' + dm.variables = ['normal_uncertain', + 'uniform_uncertain', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['response_function'] + dm.ghspec = ['grad'] + # not documented, but may work + dm.params.output = False + dm.params.x_gaussian_process = False + dm.params.u_gaussian_process = False + dm.params.all_variables = False + dm.params.seed = False + + elif dm.method == 'nond_polynomial_chaos': + dm.type = 'nond' + dm.variables = ['normal_uncertain', + 'uniform_uncertain', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['response_function'] + dm.ghspec = ['grad'] + # not documented, but may work + dm.params.output = False + dm.params.expansion_order = [] + dm.params.expansion_terms = [] + dm.params.quadrature_order = [] + dm.params.sparse_grid_level = [] + dm.params.expansion_samples = [] + dm.params.incremental_lhs = False + dm.params.collocation_points = [] + dm.params.collocation_ratio = [] + dm.params.reuse_samples = False + dm.params.expansion_import_file = '' + dm.params.seed = False + dm.params.fixed_seed = False + dm.params.samples = 0 + dm.params.sample_type = 'lhs' + dm.params.all_variables = False + + elif dm.method == 'nond_stoch_collocation': + dm.type = 'nond' + dm.variables = ['normal_uncertain', + 'uniform_uncertain', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['response_function'] + dm.ghspec = ['grad'] + # not documented, but may work + dm.params.output = False + dm.params.quadrature_order = [] + dm.params.sparse_grid_level = [] + dm.params.seed = False + dm.params.fixed_seed = False + dm.params.samples = 0 + dm.params.sample_type = 'lhs' + dm.params.all_variables = False + + elif dm.method == 'nond_evidence': + dm.type = 'nond' + dm.variables = ['normal_uncertain', + 'uniform_uncertain', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['response_function'] + dm.ghspec = ['grad'] + # not documented, but may work + dm.params.output = False + dm.params.seed = False + dm.params.samples = 10000 + + elif dm.method == 'dace': + dm.type = 'dace' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'response_function'] + dm.ghspec = [] + dm.params.grid = False + dm.params.random = False + dm.params.oas = False + dm.params.lhs = False + dm.params.oa_lhs = False + dm.params.box_behnken = False + dm.params.central_composite = False + dm.params.seed = False + dm.params.fixed_seed = False + dm.params.samples = False + dm.params.symbols = False + dm.params.quality_metrics = False + dm.params.variance_based_decomp = False + + elif dm.method == 'fsu_quasi_mc': + dm.type = 'dace' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'response_function'] + dm.ghspec = [] + dm.params.halton = False + dm.params.hammersley = False + dm.params.samples = 0 + dm.params.sequence_start = [0] + dm.params.sequence_leap = [1] + dm.params.prime_base = False + dm.params.fixed_sequence = False + dm.params.latinize = False + dm.params.variance_based_decomp = False + dm.params.quality_metrics = False + + elif dm.method == 'fsu_cvt': + dm.type = 'dace' + dm.variables = ['continuous_design', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'response_function'] + dm.ghspec = [] + dm.params.seed = False + dm.params.fixed_seed = False + dm.params.samples = 0 + dm.params.num_trials = 10000 + dm.params.trial_type = 'random' + dm.params.latinize = False + dm.params.variance_based_decomp = False + dm.params.quality_metrics = False + + elif dm.method == 'vector_parameter_study': + dm.type = 'param' + dm.variables = ['continuous_design', + 'normal_uncertain', + 'uniform_uncertain', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'response_function'] + dm.ghspec = [] + dm.params.output = False + dm.params.final_point = [] + dm.params.step_length = [] + dm.params.num_steps = [] + dm.params.step_vector = [] + dm.params.num_steps = [] + + elif dm.method == 'list_parameter_study': + dm.type = 'param' + dm.variables = ['continuous_design', + 'normal_uncertain', + 'uniform_uncertain', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'response_function'] + dm.ghspec = [] + dm.params.output = False + dm.params.list_of_points = [] + + elif dm.method == 'centered_parameter_study': + dm.type = 'param' + dm.variables = ['continuous_design', + 'normal_uncertain', + 'uniform_uncertain', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'response_function'] + dm.ghspec = [] + dm.params.output = False + dm.params.percent_delta = [] + dm.params.deltas_per_variable = [] + + elif dm.method == 'multidim_parameter_study': + dm.type = 'param' + dm.variables = ['continuous_design', + 'normal_uncertain', + 'uniform_uncertain', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'response_function'] + dm.ghspec = [] + dm.params.output = False + dm.params.partitions = [] + + elif dm.method == 'bayes_calibration': + dm.type = 'bayes' + dm.variables = ['continuous_design', + 'normal_uncertain', + 'uniform_uncertain', + 'continuous_state'] + dm.lcspec = [] + dm.responses = ['objective_function', + 'response_function', + 'calibration_function'] + dm.ghspec = [] + dm.params.queso = False + dm.params.dream = False + dm.params.gpmsa = False + dm.params.samples = 0 + dm.params.seed = False + dm.params.output = False + dm.params.metropolis_hastings = False + dm.params.proposal_covariance = False + dm.params.diagonal = False + dm.params.values = [] + + else: + raise RuntimeError('Unimplemented method: {}.'.format(dm.method)) + + # if more than one argument, issue warning + else: + print('Warning: dakota_method:extra_arg: Extra arguments for object of class ' + str(type(dm)) + '.') + return dm + + def __repr__(dm): + + # display the object + string = '\nclass dakota_method object = \n' + string += ' method: ' + str(dm.method) + '\n' + string += ' type: ' + str(dm.type) + '\n' + string += ' variables: ' + str(dm.variables) + '\n' + string += ' lcspec: ' + str(dm.lcspec) + '\n' + string += ' responses: ' + str(dm.responses) + '\n' + string += ' ghspec: ' + str(dm.ghspec) + '\n' + + # display the parameters within the object + + fnames = fieldnames(dm.params) + #get rid of stuff we aren't using + try: + fnames.remove('__module__') + except ValueError: + pass + + maxlen = 0 + for i in range(len(fnames)): + maxlen = max(maxlen, len(fnames[i])) + + for i in fnames: + string += ' params.{:{space}s}: {}\n'.format(str(i), str(dm.params.__dict__[i]), space=maxlen + 1) + #params.x : y + #with maxlen + 1 spaces between x and : + return string Index: /issm/trunk-jpl/src/m/classes/qmu/@dakota_method/dmeth_params_set.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/@dakota_method/dmeth_params_set.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/@dakota_method/dmeth_params_set.py (revision 24213) @@ -2,22 +2,23 @@ from dakota_method import * -def dmeth_params_set(dm,*args): -# -# set parameters of a dakota_method object. -# -# dm=dmeth_params_set(dm,*args) -# - if not isinstance(dm,dakota_method): - raise RuntimeError('Provided object is a \''+str(type(dm))+'\' class object, not \'dakota_method\'') +def dmeth_params_set(dm, *args): + # + # set parameters of a dakota_method object. + # + # dm = dmeth_params_set(dm, *args) + # - # loop through each parameter field in the input list - for i in range(0,len(args),2): - if isfield(dm.params,args[i]): - #vars(dresp)[fnames[i]] - exec(('dm.params.%s = args[i+1]')%(args[i])) - #vars(dm.params)[args[i]]=args[i+1] - else: - print('WARNING: dmeth_params_set:unknown_param No parameter \''+str(args[i])+'\' for dakota_method \''+str(dm.method)+'\'.') + if not isinstance(dm, dakota_method): + raise RuntimeError('Provided object is a \'' + str(type(dm)) + '\' class object, not \'dakota_method\'') - return dm + # loop through each parameter field in the input list + for i in range(0, len(args), 2): + if isfield(dm.params, args[i]): + #vars(dresp)[fnames[i]] + exec(('dm.params.%s = args[i + 1]') % (args[i])) + #vars(dm.params)[args[i]] = args[i + 1] + else: + print('WARNING: dmeth_params_set:unknown_param No parameter \'' + str(args[i]) + '\' for dakota_method \'' + str(dm.method) + '\'.') + + return dm Index: /issm/trunk-jpl/src/m/classes/qmu/@dakota_method/dmeth_params_write.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/@dakota_method/dmeth_params_write.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/@dakota_method/dmeth_params_write.py (revision 24213) @@ -2,552 +2,537 @@ from MatlabFuncs import * from IssmConfig import * - #move this later: from helpers import * -# -# write the parameters from a dakota_method object. -# -# []=dmeth_params_write(dm,fid,sbeg) -# -def dmeth_params_write(dm,fid,sbeg='\t '): - - if not isinstance(dm,dakota_method): - raise RuntimeError('Object '+str(dm)+' is a '+type(dm)+' class object, not .') - - if sbeg == None or sbeg =='': - sbeg='\t ' - - # perform some error checking, but leave the rest to dakota. - # unfortunately this prevents merely looping through the fields - # of the parameters structure. - - # write method-indepent controls - - # param_write(fid,sbeg,'id_method',' = ','\n',dm.params) - # param_write(fid,sbeg,'model_pointer',' = ','\n',dm.params) - - # write method-depent controls - - #switch dm.type - if dm.type == 'dot': - param_write(fid,sbeg,'max_iterations',' = ','\n',dm.params) - param_write(fid,sbeg,'max_function_evaluations',' = ','\n',dm.params) - param_write(fid,sbeg,'convergence_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'constraint_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' ','\n',dm.params) - param_write(fid,sbeg,'speculative','','\n',dm.params) - param_write(fid,sbeg,'scaling','','\n',dm.params) - #switch dm.method - if dm.method in ['dot_bfgs', - 'dot_frcg', - 'dot_mmfd', - 'dot_slp', - 'dot_sqp']: - param_write(fid,sbeg,'optimization_type',' = ','\n',dm.params) - - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - - elif dm.type == 'npsol': - param_write(fid,sbeg,'max_iterations',' = ','\n',dm.params) - param_write(fid,sbeg,'max_function_evaluations',' = ','\n',dm.params) - param_write(fid,sbeg,'convergence_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'constraint_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' ','\n',dm.params) - param_write(fid,sbeg,'speculative','','\n',dm.params) - param_write(fid,sbeg,'scaling','','\n',dm.params) - #switch dm.method - if dm.method == 'npsol_sqp': - param_write(fid,sbeg,'verify_level',' = ','\n',dm.params) - param_write(fid,sbeg,'function_precision',' = ','\n',dm.params) - param_write(fid,sbeg,'linesearch_tolerance',' = ','\n',dm.params) - - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - - elif dm.type == 'conmin': - param_write(fid,sbeg,'max_iterations',' = ','\n',dm.params) - param_write(fid,sbeg,'max_function_evaluations',' = ','\n',dm.params) - param_write(fid,sbeg,'convergence_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'constraint_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' ','\n',dm.params) - param_write(fid,sbeg,'speculative','','\n',dm.params) - param_write(fid,sbeg,'scaling','','\n',dm.params) - #switch dm.method - if dm.method in ['conmin_frcg','conmin_mfd']: - pass - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - - elif dm.type == 'optpp': - param_write(fid,sbeg,'max_iterations',' = ','\n',dm.params) - param_write(fid,sbeg,'max_function_evaluations',' = ','\n',dm.params) - param_write(fid,sbeg,'convergence_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' ','\n',dm.params) - param_write(fid,sbeg,'speculative','','\n',dm.params) - param_write(fid,sbeg,'scaling','','\n',dm.params) - #switch dm.method - if dm.method == 'optpp_cg': - param_write(fid,sbeg,'max_step',' = ','\n',dm.params) - param_write(fid,sbeg,'gradient_tolerance',' = ','\n',dm.params) - - elif dm.method in ['optpp_q_newton','optpp_fd_newton','optpp_newton']: - if (dm.params.value_based_line_search + - dm.params.gradient_based_line_search + - dm.params.trust_region + - dm.params.tr_pds > 1): - raise RuntimeError('#s'' method must have only one algorithm.', - dm.method) - param_write(fid,sbeg,'value_based_line_search','','\n',dm.params) - param_write(fid,sbeg,'gradient_based_line_search','','\n',dm.params) - param_write(fid,sbeg,'trust_region','','\n',dm.params) - param_write(fid,sbeg,'tr_pds','','\n',dm.params) - param_write(fid,sbeg,'max_step',' = ','\n',dm.params) - param_write(fid,sbeg,'gradient_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'merit_function',' = ','\n',dm.params) - param_write(fid,sbeg,'central_path',' = ','\n',dm.params) - param_write(fid,sbeg,'steplength_to_boundary',' = ','\n',dm.params) - param_write(fid,sbeg,'centering_parameter',' = ','\n',dm.params) - - elif dm.method == 'optpp_pds': - param_write(fid,sbeg,'search_scheme_size',' = ','\n',dm.params) - - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - - elif dm.type == 'apps': - param_write(fid,sbeg,'max_function_evaluations',' = ','\n',dm.params) - param_write(fid,sbeg,'constraint_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' ','\n',dm.params) - param_write(fid,sbeg,'scaling','','\n',dm.params) - #switch dm.method - if dm.method == 'asynch_pattern_search': - param_write(fid,sbeg,'initial_delta',' = ','\n',dm.params) - param_write(fid,sbeg,'threshold_delta',' = ','\n',dm.params) - param_write(fid,sbeg,'contraction_factor',' = ','\n',dm.params) - param_write(fid,sbeg,'solution_target',' = ','\n',dm.params) - param_write(fid,sbeg,'synchronization',' = ','\n',dm.params) - param_write(fid,sbeg,'merit_function',' = ','\n',dm.params) - param_write(fid,sbeg,'constraint_penalty',' = ','\n',dm.params) - param_write(fid,sbeg,'smoothing_factor',' = ','\n',dm.params) - - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - - elif dm.type == 'coliny': - param_write(fid,sbeg,'max_iterations',' = ','\n',dm.params) - param_write(fid,sbeg,'max_function_evaluations',' = ','\n',dm.params) - param_write(fid,sbeg,'convergence_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' ','\n',dm.params) - param_write(fid,sbeg,'scaling','','\n',dm.params) - param_write(fid,sbeg,'show_misc_options','','\n',dm.params) - param_write(fid,sbeg,'misc_options',' = ','\n',dm.params) - param_write(fid,sbeg,'solution_accuracy',' = ','\n',dm.params) - #switch dm.method - if dm.method == 'coliny_cobyla': - param_write(fid,sbeg,'initial_delta',' = ','\n',dm.params) - param_write(fid,sbeg,'threshold_delta',' = ','\n',dm.params) - - elif dm.method == 'coliny_direct': - param_write(fid,sbeg,'division',' = ','\n',dm.params) - param_write(fid,sbeg,'global_balance_parameter',' = ','\n',dm.params) - param_write(fid,sbeg,'local_balance_parameter',' = ','\n',dm.params) - param_write(fid,sbeg,'max_boxsize_limit',' = ','\n',dm.params) - param_write(fid,sbeg,'min_boxsize_limit',' = ','\n',dm.params) - param_write(fid,sbeg,'constraint_penalty',' = ','\n',dm.params) - - elif dm.method == 'coliny_ea': - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - param_write(fid,sbeg,'population_size',' = ','\n',dm.params) - param_write(fid,sbeg,'initialization_type',' = ','\n',dm.params) - param_write(fid,sbeg,'fitness_type',' = ','\n',dm.params) - param_write(fid,sbeg,'replacement_type',' = ','\n',dm.params) - param_write(fid,sbeg,'random',' = ','\n',dm.params) - param_write(fid,sbeg,'chc',' = ','\n',dm.params) - param_write(fid,sbeg,'elitist',' = ','\n',dm.params) - param_write(fid,sbeg,'new_solutions_generated',' = ','\n',dm.params) - param_write(fid,sbeg,'crossover_type',' = ','\n',dm.params) - param_write(fid,sbeg,'crossover_rate',' = ','\n',dm.params) - param_write(fid,sbeg,'mutation_type',' = ','\n',dm.params) - param_write(fid,sbeg,'mutation_scale',' = ','\n',dm.params) - param_write(fid,sbeg,'mutation_range',' = ','\n',dm.params) - param_write(fid,sbeg,'dimension_ratio',' = ','\n',dm.params) - param_write(fid,sbeg,'mutation_rate',' = ','\n',dm.params) - param_write(fid,sbeg,'non_adaptive','','\n',dm.params) - - elif dm.method == 'coliny_pattern_search': - param_write(fid,sbeg,'stochastic','','\n',dm.params) - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - param_write(fid,sbeg,'initial_delta',' = ','\n',dm.params) - param_write(fid,sbeg,'threshold_delta',' = ','\n',dm.params) - param_write(fid,sbeg,'constraint_penalty',' = ','\n',dm.params) - param_write(fid,sbeg,'constant_penalty','','\n',dm.params) - param_write(fid,sbeg,'pattern_basis',' = ','\n',dm.params) - param_write(fid,sbeg,'total_pattern_size',' = ','\n',dm.params) - param_write(fid,sbeg,'no_expansion','','\n',dm.params) - param_write(fid,sbeg,'expand_after_success',' = ','\n',dm.params) - param_write(fid,sbeg,'contraction_factor',' = ','\n',dm.params) - param_write(fid,sbeg,'synchronization',' = ','\n',dm.params) - param_write(fid,sbeg,'exploratory_moves',' = ','\n',dm.params) - - elif dm.method == 'coliny_solis_wets': - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - param_write(fid,sbeg,'initial_delta',' = ','\n',dm.params) - param_write(fid,sbeg,'threshold_delta',' = ','\n',dm.params) - param_write(fid,sbeg,'no_expansion','','\n',dm.params) - param_write(fid,sbeg,'expand_after_success',' = ','\n',dm.params) - param_write(fid,sbeg,'contract_after_failure',' = ','\n',dm.params) - param_write(fid,sbeg,'contraction_factor',' = ','\n',dm.params) - param_write(fid,sbeg,'constraint_penalty',' = ','\n',dm.params) - param_write(fid,sbeg,'constant_penalty','','\n',dm.params) - - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - - elif dm.type == 'ncsu': - param_write(fid,sbeg,'max_iterations',' = ','\n',dm.params) - param_write(fid,sbeg,'max_function_evaluations',' = ','\n',dm.params) - param_write(fid,sbeg,'scaling','','\n',dm.params) - #switch dm.method - if dm.method == 'ncsu_direct': - param_write(fid,sbeg,'solution_accuracy',' = ','\n',dm.params) - param_write(fid,sbeg,'min_boxsize_limit',' = ','\n',dm.params) - param_write(fid,sbeg,'vol_boxsize_limit',' = ','\n',dm.params) - - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - - elif dm.type == 'jega': - param_write(fid,sbeg,'max_iterations',' = ','\n',dm.params) - param_write(fid,sbeg,'max_function_evaluations',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' ','\n',dm.params) - param_write(fid,sbeg,'scaling','','\n',dm.params) - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - param_write(fid,sbeg,'log_file',' = ','\n',dm.params) - param_write(fid,sbeg,'population_size',' = ','\n',dm.params) - param_write(fid,sbeg,'print_each_pop','','\n',dm.params) - param_write(fid,sbeg,'output',' = ','\n',dm.params) - param_write(fid,sbeg,'initialization_type',' = ','\n',dm.params) - param_write(fid,sbeg,'mutation_type',' = ','\n',dm.params) - param_write(fid,sbeg,'mutation_scale',' = ','\n',dm.params) - param_write(fid,sbeg,'mutation_rate',' = ','\n',dm.params) - param_write(fid,sbeg,'replacement_type',' = ','\n',dm.params) - param_write(fid,sbeg,'below_limit',' = ','\n',dm.params) - param_write(fid,sbeg,'shrinkage_percentage',' = ','\n',dm.params) - param_write(fid,sbeg,'crossover_type',' = ','\n',dm.params) - param_write(fid,sbeg,'multi_point_binary',' = ','\n',dm.params) - param_write(fid,sbeg,'multi_point_parameterized_binary',' = ','\n',dm.params) - param_write(fid,sbeg,'multi_point_real',' = ','\n',dm.params) - param_write(fid,sbeg,'shuffle_random',' = ','\n',dm.params) - param_write(fid,sbeg,'num_parents',' = ','\n',dm.params) - param_write(fid,sbeg,'num_offspring',' = ','\n',dm.params) - param_write(fid,sbeg,'crossover_rate',' = ','\n',dm.params) - - #switch dm.method - if dm.method == 'moga': - param_write(fid,sbeg,'fitness_type',' = ','\n',dm.params) - param_write(fid,sbeg,'niching_type',' = ','\n',dm.params) - if not isempty(dm.params.radial) and not isempty(dm.params.distance): - raise RuntimeError('#s'' method must have only one niching distance.', - dm.method) - param_write(fid,sbeg,'radial',' = ','\n',dm.params) - param_write(fid,sbeg,'distance',' = ','\n',dm.params) - param_write(fid,sbeg,'metric_tracker','','\n',dm.params) - param_write(fid,sbeg,'percent_change',' = ','\n',dm.params) - param_write(fid,sbeg,'num_generations',' = ','\n',dm.params) - param_write(fid,sbeg,'postprocessor_type',' = ','\n',dm.params) - param_write(fid,sbeg,'orthogonal_distance',' = ','\n',dm.params) - - elif dm.method == 'soga': - param_write(fid,sbeg,'fitness_type',' = ','\n',dm.params) - param_write(fid,sbeg,'constraint_penalty',' = ','\n',dm.params) - param_write(fid,sbeg,'replacement_type',' = ','\n',dm.params) - param_write(fid,sbeg,'convergence_type',' = ','\n',dm.params) - param_write(fid,sbeg,'num_generations',' = ','\n',dm.params) - param_write(fid,sbeg,'percent_change',' = ','\n',dm.params) - - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - - elif dm.type == 'lsq': - #switch dm.method - if dm.method == 'nl2sol': - param_write(fid,sbeg,'max_iterations',' = ','\n',dm.params) - param_write(fid,sbeg,'max_function_evaluations',' = ','\n',dm.params) - param_write(fid,sbeg,'convergence_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' ','\n',dm.params) - param_write(fid,sbeg,'scaling','','\n',dm.params) - param_write(fid,sbeg,'function_precision',' = ','\n',dm.params) - param_write(fid,sbeg,'absolute_conv_tol',' = ','\n',dm.params) - param_write(fid,sbeg,'x_conv_tol',' = ','\n',dm.params) - param_write(fid,sbeg,'singular_conv_tol',' = ','\n',dm.params) - param_write(fid,sbeg,'singular_radius',' = ','\n',dm.params) - param_write(fid,sbeg,'false_conv_tol',' = ','\n',dm.params) - param_write(fid,sbeg,'initial_trust_radius',' = ','\n',dm.params) - param_write(fid,sbeg,'covariance',' = ','\n',dm.params) - param_write(fid,sbeg,'regression_stressbalances','','\n',dm.params) - - elif dm.method == 'nlssol_sqp': - param_write(fid,sbeg,'max_iterations',' = ','\n',dm.params) - param_write(fid,sbeg,'max_function_evaluations',' = ','\n',dm.params) - param_write(fid,sbeg,'convergence_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'constraint_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' ','\n',dm.params) - param_write(fid,sbeg,'speculative','','\n',dm.params) - param_write(fid,sbeg,'scaling','','\n',dm.params) - param_write(fid,sbeg,'verify_level',' = ','\n',dm.params) - param_write(fid,sbeg,'function_precision',' = ','\n',dm.params) - param_write(fid,sbeg,'linesearch_tolerance',' = ','\n',dm.params) - - elif dm.method == 'optpp_g_newton': - param_write(fid,sbeg,'max_iterations',' = ','\n',dm.params) - param_write(fid,sbeg,'max_function_evaluations',' = ','\n',dm.params) - param_write(fid,sbeg,'convergence_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' ','\n',dm.params) - param_write(fid,sbeg,'speculative','','\n',dm.params) - param_write(fid,sbeg,'scaling','','\n',dm.params) - - if (dm.params.value_based_line_search + - dm.params.gradient_based_line_search + - dm.params.trust_region + - dm.params.tr_pds > 1): - raise RuntimeError('#s'' method must have only one algorithm.', - dm.method) - - param_write(fid,sbeg,'value_based_line_search','','\n',dm.params) - param_write(fid,sbeg,'gradient_based_line_search','','\n',dm.params) - param_write(fid,sbeg,'trust_region','','\n',dm.params) - param_write(fid,sbeg,'tr_pds','','\n',dm.params) - param_write(fid,sbeg,'max_step',' = ','\n',dm.params) - param_write(fid,sbeg,'gradient_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'merit_function',' = ','\n',dm.params) - param_write(fid,sbeg,'central_path',' = ','\n',dm.params) - param_write(fid,sbeg,'steplength_to_boundary',' = ','\n',dm.params) - param_write(fid,sbeg,'centering_parameter',' = ','\n',dm.params) - - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - - elif dm.type == 'nond': - #switch dm.method - if dm.method == 'nond_sampling': - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - param_write(fid,sbeg,'fixed_seed','','\n',dm.params) - dver = str(IssmConfig('_DAKOTA_VERSION_')[0]) - if ((int(dver[0])==4 and int(dver[2])>2) or int(dver[0])>4): - param_write(fid,sbeg,'rng',' ','\n',dm.params) - param_write(fid,sbeg,'samples',' = ','\n',dm.params) - param_write(fid,sbeg,'sample_type',' ','\n',dm.params) - param_write(fid,sbeg,'all_variables','','\n',dm.params) - param_write(fid,sbeg,'variance_based_decomp','','\n',dm.params) - if strcmp(dm.params.sample_type,'incremental_random') or strcmp(dm.params.sample_type,'incremental_lhs'): - param_write(fid,sbeg,'previous_samples',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' ','\n',dm.params) - - elif dm.method == 'nond_local_reliability': - param_write(fid,sbeg,'max_iterations',' = ','\n',dm.params) - param_write(fid,sbeg,'convergence_tolerance',' = ','\n',dm.params) - param_write(fid,sbeg,'mpp_search',' = ','\n',dm.params) - if type(dm.params.mpp_search) == str: - if (dm.params.sqp +dm.params.nip > 1): - raise RuntimeError('#s'' method must have only one algorithm.', - dm.method) - - param_write(fid,sbeg,'sqp','','\n',dm.params) - param_write(fid,sbeg,'nip','','\n',dm.params) - param_write(fid,sbeg,'integration',' ','\n',dm.params) - param_write(fid,sbeg,'refinement',' = ','\n',dm.params) - if type(dm.params.refinement) == str: - param_write(fid,sbeg,'samples',' = ','\n',dm.params) - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' ','\n',dm.params) - - elif dm.method == 'nond_global_reliability': - if (dm.params.x_gaussian_process + dm.params.u_gaussian_process != 1): - raise RuntimeError('#s'' method must have one and only one algorithm.', - dm.method) - - param_write(fid,sbeg,'x_gaussian_process','','\n',dm.params) - param_write(fid,sbeg,'u_gaussian_process','','\n',dm.params) - param_write(fid,sbeg,'all_variables','','\n',dm.params) - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - - elif dm.method == 'nond_polynomial_chaos': - param_write(fid,sbeg,'expansion_order',' = ','\n',dm.params) - param_write(fid,sbeg,'expansion_terms',' = ','\n',dm.params) - param_write(fid,sbeg,'quadrature_order',' = ','\n',dm.params) - param_write(fid,sbeg,'sparse_grid_level',' = ','\n',dm.params) - param_write(fid,sbeg,'expansion_samples',' = ','\n',dm.params) - param_write(fid,sbeg,'incremental_lhs','','\n',dm.params) - param_write(fid,sbeg,'collocation_points',' = ','\n',dm.params) - param_write(fid,sbeg,'collocation_ratio',' = ','\n',dm.params) - param_write(fid,sbeg,'reuse_samples','','\n',dm.params) - param_write(fid,sbeg,'expansion_import_file',' = ','\n',dm.params) - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - param_write(fid,sbeg,'fixed_seed','','\n',dm.params) - param_write(fid,sbeg,'samples',' = ','\n',dm.params) - param_write(fid,sbeg,'sample_type',' = ','\n',dm.params) - param_write(fid,sbeg,'all_variables','','\n',dm.params) - - elif dm.method == 'nond_stoch_collocation': - param_write(fid,sbeg,'quadrature_order',' = ','\n',dm.params) - param_write(fid,sbeg,'sparse_grid_level',' = ','\n',dm.params) - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - param_write(fid,sbeg,'fixed_seed','','\n',dm.params) - param_write(fid,sbeg,'samples',' = ','\n',dm.params) - param_write(fid,sbeg,'sample_type',' = ','\n',dm.params) - param_write(fid,sbeg,'all_variables','','\n',dm.params) - - elif dm.method == 'nond_evidence': - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - param_write(fid,sbeg,'samples',' = ','\n',dm.params) - - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - - - elif dm.type == 'dace': - #switch dm.method - if dm.method == 'dace': - if (dm.params.grid + dm.params.random + dm.params.oas + dm.params.lhs + dm.params.oa_lhs + dm.params.box_behnken + dm.params.central_composite != 1): - raise RuntimeError('#s'' method must have one and only one algorithm.', - dm.method) - - param_write(fid,sbeg,'grid','','\n',dm.params) - param_write(fid,sbeg,'random','','\n',dm.params) - param_write(fid,sbeg,'oas','','\n',dm.params) - param_write(fid,sbeg,'lhs','','\n',dm.params) - param_write(fid,sbeg,'oa_lhs','','\n',dm.params) - param_write(fid,sbeg,'box_behnken','','\n',dm.params) - param_write(fid,sbeg,'central_composite','','\n',dm.params) - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - param_write(fid,sbeg,'fixed_seed','','\n',dm.params) - param_write(fid,sbeg,'samples',' = ','\n',dm.params) - param_write(fid,sbeg,'symbols',' = ','\n',dm.params) - param_write(fid,sbeg,'quality_metrics','','\n',dm.params) - param_write(fid,sbeg,'variance_based_decomp','','\n',dm.params) - - elif dm.method == 'fsu_quasi_mc': - if (dm.params.halton + dm.params.hammersley != 1): - raise RuntimeError('#s'' method must have one and only one sequence type.',dm.method) - - param_write(fid,sbeg,'halton','','\n',dm.params) - param_write(fid,sbeg,'hammersley','','\n',dm.params) - param_write(fid,sbeg,'samples',' = ','\n',dm.params) - param_write(fid,sbeg,'sequence_start',' = ','\n',dm.params) - param_write(fid,sbeg,'sequence_leap',' = ','\n',dm.params) - param_write(fid,sbeg,'prime_base',' = ','\n',dm.params) - param_write(fid,sbeg,'fixed_sequence','','\n',dm.params) - param_write(fid,sbeg,'latinize','','\n',dm.params) - param_write(fid,sbeg,'variance_based_decomp','','\n',dm.params) - param_write(fid,sbeg,'quality_metrics','','\n',dm.params) - - elif dm.method == 'fsu_cvt': - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - param_write(fid,sbeg,'fixed_seed','','\n',dm.params) - param_write(fid,sbeg,'samples',' = ','\n',dm.params) - param_write(fid,sbeg,'num_trials',' = ','\n',dm.params) - param_write(fid,sbeg,'trial_type',' = ','\n',dm.params) - param_write(fid,sbeg,'latinize','','\n',dm.params) - param_write(fid,sbeg,'variance_based_decomp','','\n',dm.params) - param_write(fid,sbeg,'quality_metrics','','\n',dm.params) - - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - - elif dm.type == 'param': - param_write(fid,sbeg,'output',' ','\n',dm.params) - #switch dm.method - if dm.method == 'vector_parameter_study': - if not np.logical_xor(isempty(dm.params.final_point),isempty(dm.params.step_vector)): - raise RuntimeError(str(dm.method)+' method must have one and only one specification.') - - if not isempty(dm.params.final_point): - param_write(fid,sbeg,'final_point',' = ','\n',dm.params) - param_write(fid,sbeg,'step_length',' = ','\n',dm.params) - param_write(fid,sbeg,'num_steps',' = ','\n',dm.params) - - elif not isempty(dm.params.step_vector): - param_write(fid,sbeg,'step_vector',' = ','\n',dm.params) - param_write(fid,sbeg,'num_steps',' = ','\n',dm.params) - - elif dm.method == 'list_parameter_study': - param_write(fid,sbeg,'list_of_points',' = ','\n',dm.params) - - elif dm.method == 'centered_parameter_study': - param_write(fid,sbeg,'percent_delta',' = ','\n',dm.params) - param_write(fid,sbeg,'deltas_per_variable',' = ','\n',dm.params) - - elif dm.method == 'multidim_parameter_study': - param_write(fid,sbeg,'partitions',' = ','\n',dm.params) - - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - - - elif dm.type == 'bayes': - #switch dm.method - if dm.method == 'bayes_calibration': - # if (dm.params.queso + - # dm.params.dream + - # dm.params.gpmsa ~= 1) - # raise RuntimeError('''#s'' method must have one and only one bayes type. YOU SUCK', - # dm.method) - # - param_write(fid,sbeg,'queso','','\n',dm.params) - param_write(fid,sbeg,'dream','','\n',dm.params) - param_write(fid,sbeg,'gpmsa','','\n',dm.params) - param_write(fid,sbeg,'samples',' = ','\n',dm.params) - param_write(fid,sbeg,'seed',' = ','\n',dm.params) - param_write(fid,sbeg,'output',' =','\n',dm.params) - param_write(fid,sbeg,'metropolis_hastings','','\n',dm.params) - param_write(fid,sbeg,'proposal_covariance','','\n',dm.params) - param_write(fid,sbeg,'diagonal','','\n',dm.params) - param_write(fid,sbeg,'values',' = ','\n',dm.params) - - else: - raise RuntimeError('Unrecognized '+dm.type+' method: '+dm.method+'.') - -## function to write a structure of parameters -def param_struc_write(fidi,sbeg,smid,s,params): - # loop through each parameter field in the structure - fnames=fieldnames(params) - for i in range(np.size(fnames)): - param_write(fidi,sbeg,fnames[i],smid,s,params) - - return - -## function to write a parameter -def param_write(fidi,sbeg,pname,smid,s,params): - # check for errors - if not isfield(params,pname): - warning('param_write:param_not_found', - 'Parameter '+str(pname)+' not found in '+params+'.') - return - elif type(vars(params)[pname]) == bool and not vars(params)[pname]: - return - elif isempty(vars(params)[pname]): - print('Warning: param_write:param_empty: Parameter {} requires input of type {}.'.format(pname,type(vars(params)[pname]))) - return - - # construct the parameter string based on type - if type(vars(params)[pname]) == bool: - fidi.write(sbeg+str(pname)+s) - - elif type(vars(params)[pname]) in [int,float]: - fidi.write(sbeg+str(pname)+smid+str(vars(params)[pname])+s) - - elif type(vars(params)[pname]) == list: - fidi.write(sbeg+str(pname)+smid+str(vars(params)[pname][0])) - for i in range(1,np.size(vars(params)[pname])): - fidi.write(' '+str(vars(params)[pname][i])) - - fidi.write(s) - - elif type(vars(params)[pname]) == str: - fidi.write(sbeg+str(pname)+smid+str(vars(params)[pname])+s) - - else: - print('Warning: param_write:param_unrecog: Parameter {} is of unrecognized type {}.'.format(pname,type(vars(params)[pname]))) - return + +def dmeth_params_write(dm, fid, sbeg='\t '): + ''' write the parameters from a dakota_method object. + [] = dmeth_params_write(dm, fid, sbeg) + ''' + + if not isinstance(dm, dakota_method): + raise RuntimeError('Object ' + str(dm) + ' is a ' + type(dm) + ' class object, not < dakota_method > .') + + if sbeg is None or sbeg == '': + sbeg = '\t ' + + # perform some error checking, but leave the rest to dakota. + # unfortunately this prevents merely looping through the fields + # of the parameters structure. + + # write method - indepent controls + + # param_write(fid, sbeg, 'id_method', ' = ', '\n', dm.params) + # param_write(fid, sbeg, 'model_pointer', ' = ', '\n', dm.params) + + # write method - depent controls + + #switch dm.type + if dm.type == 'dot': + param_write(fid, sbeg, 'max_iterations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'max_function_evaluations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'convergence_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'constraint_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + param_write(fid, sbeg, 'speculative', '', '\n', dm.params) + param_write(fid, sbeg, 'scaling', '', '\n', dm.params) + #switch dm.method + if dm.method in ['dot_bfgs', + 'dot_frcg', + 'dot_mmfd', + 'dot_slp', + 'dot_sqp']: + param_write(fid, sbeg, 'optimization_type', ' = ', '\n', dm.params) + + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + elif dm.type == 'npsol': + param_write(fid, sbeg, 'max_iterations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'max_function_evaluations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'convergence_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'constraint_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + param_write(fid, sbeg, 'speculative', '', '\n', dm.params) + param_write(fid, sbeg, 'scaling', '', '\n', dm.params) + #switch dm.method + if dm.method == 'npsol_sqp': + param_write(fid, sbeg, 'verify_level', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'function_precision', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'linesearch_tolerance', ' = ', '\n', dm.params) + + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + elif dm.type == 'conmin': + param_write(fid, sbeg, 'max_iterations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'max_function_evaluations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'convergence_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'constraint_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + param_write(fid, sbeg, 'speculative', '', '\n', dm.params) + param_write(fid, sbeg, 'scaling', '', '\n', dm.params) + #switch dm.method + if dm.method in ['conmin_frcg', 'conmin_mfd']: + pass + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + elif dm.type == 'optpp': + param_write(fid, sbeg, 'max_iterations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'max_function_evaluations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'convergence_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + param_write(fid, sbeg, 'speculative', '', '\n', dm.params) + param_write(fid, sbeg, 'scaling', '', '\n', dm.params) + #switch dm.method + if dm.method == 'optpp_cg': + param_write(fid, sbeg, 'max_step', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'gradient_tolerance', ' = ', '\n', dm.params) + + elif dm.method in ['optpp_q_newton', 'optpp_fd_newton', 'optpp_newton']: + if (dm.params.value_based_line_search + dm.params.gradient_based_line_search + dm.params.trust_region + dm.params.tr_pds > 1): + raise RuntimeError(' #s'' method must have only one algorithm.', dm.method) + param_write(fid, sbeg, 'value_based_line_search', '', '\n', dm.params) + param_write(fid, sbeg, 'gradient_based_line_search', '', '\n', dm.params) + param_write(fid, sbeg, 'trust_region', '', '\n', dm.params) + param_write(fid, sbeg, 'tr_pds', '', '\n', dm.params) + param_write(fid, sbeg, 'max_step', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'gradient_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'merit_function', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'central_path', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'steplength_to_boundary', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'centering_parameter', ' = ', '\n', dm.params) + + elif dm.method == 'optpp_pds': + param_write(fid, sbeg, 'search_scheme_size', ' = ', '\n', dm.params) + + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + elif dm.type == 'apps': + param_write(fid, sbeg, 'max_function_evaluations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'constraint_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + param_write(fid, sbeg, 'scaling', '', '\n', dm.params) + #switch dm.method + if dm.method == 'asynch_pattern_search': + param_write(fid, sbeg, 'initial_delta', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'threshold_delta', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'contraction_factor', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'solution_target', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'synchronization', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'merit_function', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'constraint_penalty', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'smoothing_factor', ' = ', '\n', dm.params) + + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + elif dm.type == 'coliny': + param_write(fid, sbeg, 'max_iterations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'max_function_evaluations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'convergence_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + param_write(fid, sbeg, 'scaling', '', '\n', dm.params) + param_write(fid, sbeg, 'show_misc_options', '', '\n', dm.params) + param_write(fid, sbeg, 'misc_options', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'solution_accuracy', ' = ', '\n', dm.params) + #switch dm.method + if dm.method == 'coliny_cobyla': + param_write(fid, sbeg, 'initial_delta', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'threshold_delta', ' = ', '\n', dm.params) + + elif dm.method == 'coliny_direct': + param_write(fid, sbeg, 'division', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'global_balance_parameter', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'local_balance_parameter', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'max_boxsize_limit', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'min_boxsize_limit', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'constraint_penalty', ' = ', '\n', dm.params) + + elif dm.method == 'coliny_ea': + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'population_size', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'initialization_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'fitness_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'replacement_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'random', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'chc', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'elitist', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'new_solutions_generated', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'crossover_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'crossover_rate', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'mutation_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'mutation_scale', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'mutation_range', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'dimension_ratio', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'mutation_rate', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'non_adaptive', '', '\n', dm.params) + + elif dm.method == 'coliny_pattern_search': + param_write(fid, sbeg, 'stochastic', '', '\n', dm.params) + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'initial_delta', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'threshold_delta', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'constraint_penalty', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'constant_penalty', '', '\n', dm.params) + param_write(fid, sbeg, 'pattern_basis', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'total_pattern_size', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'no_expansion', '', '\n', dm.params) + param_write(fid, sbeg, 'expand_after_success', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'contraction_factor', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'synchronization', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'exploratory_moves', ' = ', '\n', dm.params) + + elif dm.method == 'coliny_solis_wets': + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'initial_delta', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'threshold_delta', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'no_expansion', '', '\n', dm.params) + param_write(fid, sbeg, 'expand_after_success', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'contract_after_failure', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'contraction_factor', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'constraint_penalty', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'constant_penalty', '', '\n', dm.params) + + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + elif dm.type == 'ncsu': + param_write(fid, sbeg, 'max_iterations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'max_function_evaluations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'scaling', '', '\n', dm.params) + #switch dm.method + if dm.method == 'ncsu_direct': + param_write(fid, sbeg, 'solution_accuracy', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'min_boxsize_limit', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'vol_boxsize_limit', ' = ', '\n', dm.params) + + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + elif dm.type == 'jega': + param_write(fid, sbeg, 'max_iterations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'max_function_evaluations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + param_write(fid, sbeg, 'scaling', '', '\n', dm.params) + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'log_file', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'population_size', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'print_each_pop', '', '\n', dm.params) + param_write(fid, sbeg, 'output', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'initialization_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'mutation_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'mutation_scale', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'mutation_rate', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'replacement_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'below_limit', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'shrinkage_percentage', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'crossover_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'multi_point_binary', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'multi_point_parameterized_binary', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'multi_point_real', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'shuffle_random', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'num_parents', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'num_offspring', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'crossover_rate', ' = ', '\n', dm.params) + + #switch dm.method + if dm.method == 'moga': + param_write(fid, sbeg, 'fitness_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'niching_type', ' = ', '\n', dm.params) + if not isempty(dm.params.radial) and not isempty(dm.params.distance): + raise RuntimeError(' #s'' method must have only one niching distance.', dm.method) + param_write(fid, sbeg, 'radial', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'distance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'metric_tracker', '', '\n', dm.params) + param_write(fid, sbeg, 'percent_change', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'num_generations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'postprocessor_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'orthogonal_distance', ' = ', '\n', dm.params) + + elif dm.method == 'soga': + param_write(fid, sbeg, 'fitness_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'constraint_penalty', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'replacement_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'convergence_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'num_generations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'percent_change', ' = ', '\n', dm.params) + + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + elif dm.type == 'lsq': + #switch dm.method + if dm.method == 'nl2sol': + param_write(fid, sbeg, 'max_iterations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'max_function_evaluations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'convergence_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + param_write(fid, sbeg, 'scaling', '', '\n', dm.params) + param_write(fid, sbeg, 'function_precision', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'absolute_conv_tol', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'x_conv_tol', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'singular_conv_tol', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'singular_radius', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'false_conv_tol', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'initial_trust_radius', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'covariance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'regression_stressbalances', '', '\n', dm.params) + + elif dm.method == 'nlssol_sqp': + param_write(fid, sbeg, 'max_iterations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'max_function_evaluations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'convergence_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'constraint_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + param_write(fid, sbeg, 'speculative', '', '\n', dm.params) + param_write(fid, sbeg, 'scaling', '', '\n', dm.params) + param_write(fid, sbeg, 'verify_level', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'function_precision', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'linesearch_tolerance', ' = ', '\n', dm.params) + + elif dm.method == 'optpp_g_newton': + param_write(fid, sbeg, 'max_iterations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'max_function_evaluations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'convergence_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + param_write(fid, sbeg, 'speculative', '', '\n', dm.params) + param_write(fid, sbeg, 'scaling', '', '\n', dm.params) + + if (dm.params.value_based_line_search + dm.params.gradient_based_line_search + dm.params.trust_region + dm.params.tr_pds > 1): + raise RuntimeError(' #s'' method must have only one algorithm.', dm.method) + + param_write(fid, sbeg, 'value_based_line_search', '', '\n', dm.params) + param_write(fid, sbeg, 'gradient_based_line_search', '', '\n', dm.params) + param_write(fid, sbeg, 'trust_region', '', '\n', dm.params) + param_write(fid, sbeg, 'tr_pds', '', '\n', dm.params) + param_write(fid, sbeg, 'max_step', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'gradient_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'merit_function', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'central_path', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'steplength_to_boundary', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'centering_parameter', ' = ', '\n', dm.params) + + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + elif dm.type == 'nond': + #switch dm.method + if dm.method == 'nond_sampling': + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'fixed_seed', '', '\n', dm.params) + dver = str(IssmConfig('_DAKOTA_VERSION_')[0]) + if ((int(dver[0]) == 4 and int(dver[2]) > 2) or int(dver[0]) > 4): + param_write(fid, sbeg, 'rng', ' ', '\n', dm.params) + param_write(fid, sbeg, 'samples', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'sample_type', ' ', '\n', dm.params) + param_write(fid, sbeg, 'all_variables', '', '\n', dm.params) + param_write(fid, sbeg, 'variance_based_decomp', '', '\n', dm.params) + if strcmp(dm.params.sample_type, 'incremental_random') or strcmp(dm.params.sample_type, 'incremental_lhs'): + param_write(fid, sbeg, 'previous_samples', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + + elif dm.method == 'nond_local_reliability': + param_write(fid, sbeg, 'max_iterations', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'convergence_tolerance', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'mpp_search', ' = ', '\n', dm.params) + if type(dm.params.mpp_search) == str: + if (dm.params.sqp + dm.params.nip > 1): + raise RuntimeError(' #s'' method must have only one algorithm.', dm.method) + + param_write(fid, sbeg, 'sqp', '', '\n', dm.params) + param_write(fid, sbeg, 'nip', '', '\n', dm.params) + param_write(fid, sbeg, 'integration', ' ', '\n', dm.params) + param_write(fid, sbeg, 'refinement', ' = ', '\n', dm.params) + if type(dm.params.refinement) == str: + param_write(fid, sbeg, 'samples', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + + elif dm.method == 'nond_global_reliability': + if (dm.params.x_gaussian_process + dm.params.u_gaussian_process != 1): + raise RuntimeError(' #s'' method must have one and only one algorithm.', dm.method) + + param_write(fid, sbeg, 'x_gaussian_process', '', '\n', dm.params) + param_write(fid, sbeg, 'u_gaussian_process', '', '\n', dm.params) + param_write(fid, sbeg, 'all_variables', '', '\n', dm.params) + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + + elif dm.method == 'nond_polynomial_chaos': + param_write(fid, sbeg, 'expansion_order', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'expansion_terms', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'quadrature_order', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'sparse_grid_level', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'expansion_samples', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'incremental_lhs', '', '\n', dm.params) + param_write(fid, sbeg, 'collocation_points', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'collocation_ratio', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'reuse_samples', '', '\n', dm.params) + param_write(fid, sbeg, 'expansion_import_file', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'fixed_seed', '', '\n', dm.params) + param_write(fid, sbeg, 'samples', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'sample_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'all_variables', '', '\n', dm.params) + + elif dm.method == 'nond_stoch_collocation': + param_write(fid, sbeg, 'quadrature_order', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'sparse_grid_level', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'fixed_seed', '', '\n', dm.params) + param_write(fid, sbeg, 'samples', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'sample_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'all_variables', '', '\n', dm.params) + + elif dm.method == 'nond_evidence': + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'samples', ' = ', '\n', dm.params) + + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + elif dm.type == 'dace': + #switch dm.method + if dm.method == 'dace': + if (dm.params.grid + dm.params.random + dm.params.oas + dm.params.lhs + dm.params.oa_lhs + dm.params.box_behnken + dm.params.central_composite != 1): + raise RuntimeError(' #s'' method must have one and only one algorithm.', dm.method) + + param_write(fid, sbeg, 'grid', '', '\n', dm.params) + param_write(fid, sbeg, 'random', '', '\n', dm.params) + param_write(fid, sbeg, 'oas', '', '\n', dm.params) + param_write(fid, sbeg, 'lhs', '', '\n', dm.params) + param_write(fid, sbeg, 'oa_lhs', '', '\n', dm.params) + param_write(fid, sbeg, 'box_behnken', '', '\n', dm.params) + param_write(fid, sbeg, 'central_composite', '', '\n', dm.params) + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'fixed_seed', '', '\n', dm.params) + param_write(fid, sbeg, 'samples', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'symbols', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'quality_metrics', '', '\n', dm.params) + param_write(fid, sbeg, 'variance_based_decomp', '', '\n', dm.params) + + elif dm.method == 'fsu_quasi_mc': + if (dm.params.halton + dm.params.hammersley != 1): + raise RuntimeError(' #s'' method must have one and only one sequence type.', dm.method) + + param_write(fid, sbeg, 'halton', '', '\n', dm.params) + param_write(fid, sbeg, 'hammersley', '', '\n', dm.params) + param_write(fid, sbeg, 'samples', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'sequence_start', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'sequence_leap', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'prime_base', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'fixed_sequence', '', '\n', dm.params) + param_write(fid, sbeg, 'latinize', '', '\n', dm.params) + param_write(fid, sbeg, 'variance_based_decomp', '', '\n', dm.params) + param_write(fid, sbeg, 'quality_metrics', '', '\n', dm.params) + + elif dm.method == 'fsu_cvt': + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'fixed_seed', '', '\n', dm.params) + param_write(fid, sbeg, 'samples', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'num_trials', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'trial_type', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'latinize', '', '\n', dm.params) + param_write(fid, sbeg, 'variance_based_decomp', '', '\n', dm.params) + param_write(fid, sbeg, 'quality_metrics', '', '\n', dm.params) + + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + elif dm.type == 'param': + param_write(fid, sbeg, 'output', ' ', '\n', dm.params) + #switch dm.method + if dm.method == 'vector_parameter_study': + if not np.logical_xor(isempty(dm.params.final_point), isempty(dm.params.step_vector)): + raise RuntimeError(str(dm.method) + ' method must have one and only one specification.') + + if not isempty(dm.params.final_point): + param_write(fid, sbeg, 'final_point', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'step_length', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'num_steps', ' = ', '\n', dm.params) + + elif not isempty(dm.params.step_vector): + param_write(fid, sbeg, 'step_vector', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'num_steps', ' = ', '\n', dm.params) + + elif dm.method == 'list_parameter_study': + param_write(fid, sbeg, 'list_of_points', ' = ', '\n', dm.params) + + elif dm.method == 'centered_parameter_study': + param_write(fid, sbeg, 'percent_delta', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'deltas_per_variable', ' = ', '\n', dm.params) + + elif dm.method == 'multidim_parameter_study': + param_write(fid, sbeg, 'partitions', ' = ', '\n', dm.params) + + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + elif dm.type == 'bayes': + #switch dm.method + if dm.method == 'bayes_calibration': + # if (dm.params.queso + + # dm.params.dream + + # dm.params.gpmsa ~= 1) + # raise RuntimeError(''' #s'' method must have one and only one bayes type. YOU SUCK', + # dm.method) + # + param_write(fid, sbeg, 'queso', '', '\n', dm.params) + param_write(fid, sbeg, 'dream', '', '\n', dm.params) + param_write(fid, sbeg, 'gpmsa', '', '\n', dm.params) + param_write(fid, sbeg, 'samples', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'seed', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'output', ' = ', '\n', dm.params) + param_write(fid, sbeg, 'metropolis_hastings', '', '\n', dm.params) + param_write(fid, sbeg, 'proposal_covariance', '', '\n', dm.params) + param_write(fid, sbeg, 'diagonal', '', '\n', dm.params) + param_write(fid, sbeg, 'values', ' = ', '\n', dm.params) + + else: + raise RuntimeError('Unrecognized ' + dm.type + ' method: ' + dm.method + '.') + + +# function to write a structure of parameters +def param_struc_write(fidi, sbeg, smid, s, params): + # loop through each parameter field in the structure + fnames = fieldnames(params) + for i in range(np.size(fnames)): + param_write(fidi, sbeg, fnames[i], smid, s, params) + + return + + +# function to write a parameter +def param_write(fidi, sbeg, pname, smid, s, params): + # check for errors + if not isfield(params, pname): + warning('param_write:param_not_found', 'Parameter ' + str(pname) + ' not found in ' + params + '.') + return + elif type(vars(params)[pname]) == bool and not vars(params)[pname]: + return + elif isempty(vars(params)[pname]): + print('Warning: param_write:param_empty: Parameter {} requires input of type {}.'.format(pname, type(vars(params)[pname]))) + return + + # construct the parameter string based on type + if type(vars(params)[pname]) == bool: + fidi.write(sbeg + str(pname) + s) + + elif type(vars(params)[pname]) in [int, float]: + fidi.write(sbeg + str(pname) + smid + str(vars(params)[pname]) + s) + + elif type(vars(params)[pname]) == list: + fidi.write(sbeg + str(pname) + smid + str(vars(params)[pname][0])) + for i in range(1, np.size(vars(params)[pname])): + fidi.write(' ' + str(vars(params)[pname][i])) + + fidi.write(s) + + elif type(vars(params)[pname]) == str: + fidi.write(sbeg + str(pname) + smid + str(vars(params)[pname]) + s) + + else: + print('Warning: param_write:param_unrecog: Parameter {} is of unrecognized type {}.'.format(pname, type(vars(params)[pname]))) + return Index: /issm/trunk-jpl/src/m/classes/qmu/calibration_function.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/calibration_function.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/calibration_function.py (revision 24213) @@ -3,10 +3,11 @@ from MatlabArray import * + class calibration_function(object): - ''' + ''' definition for the calibration_function class. [cf] = calibration_function.calibration_function(args) - cf = calibration_function() + cf = calibration_function() where the required args are: @@ -21,120 +22,120 @@ arguments constructs a new instance from the arguments. ''' - def __init__(self): - self.descriptor = '' - self.scale_type = 'none' - self.scale = 1. - self.weight = 1. + def __init__(self): + self.descriptor = '' + self.scale_type = 'none' + self.scale = 1. + self.weight = 1. - @staticmethod - def calibration_function(*args): - nargin = len(args) + @staticmethod + def calibration_function(*args): + nargin = len(args) - # create a default object - if nargin == 0: - return calibration_function() + # create a default object + if nargin == 0: + return calibration_function() - # copy the object or create the object from the input - else: - if (nargin == 1) and isinstance(args[0],calibration_function): - cf = args[0] - else: - asizec = array_size(*args[0:min(nargin,4)]) - cf = [calibration_function() for i in range(asizec[0]) for j in range(asizec[1])] + # copy the object or create the object from the input + else: + if (nargin == 1) and isinstance(args[0], calibration_function): + cf = args[0] + else: + asizec = array_size(*args[0:min(nargin, 4)]) + cf = [calibration_function() for i in range(asizec[0]) for j in range(asizec[1])] - for i in range(np.size(cf)): - if (np.size(args[0]) > 1): - cf[i].descriptor = args[0][i] - else: - cf[i].descriptor = str(args[0])+string_dim(cf,i,'vector') + for i in range(np.size(cf)): + if (np.size(args[0]) > 1): + cf[i].descriptor = args[0][i] + else: + cf[i].descriptor = str(args[0]) + string_dim(cf, i, 'vector') - if nargin >= 2: - for i in range(np.size(cf)): - cf[i].scale_type = str(args[1]) - if nargin >= 3: - for i in range(np.size(cf)): - cf[i].scale = args[2] - if nargin >= 4: - for i in range(np.size(cf)): - cf[i].weight = args[3] - if nargin > 4: - print('WARNING: calibration_function:extra_arg: Extra arguments for object of class '+str(type(cf))+'.') + if nargin >= 2: + for i in range(np.size(cf)): + cf[i].scale_type = str(args[1]) + if nargin >= 3: + for i in range(np.size(cf)): + cf[i].scale = args[2] + if nargin >= 4: + for i in range(np.size(cf)): + cf[i].weight = args[3] + if nargin > 4: + print('WARNING: calibration_function:extra_arg: Extra arguments for object of class ' + str(type(cf)) + '.') - return cf + return cf - def __repr__(self): - # display the object - string = '\n' - string += 'class "calibration_function" object = \n' - string += ' descriptor: '+str(self.descriptor) + '\n' - string += ' scale_type: '+str(self.scale_type) + '\n' - string += ' scale: '+str(self.scale) + '\n' - string += ' weight: '+str(self.weight) + '\n' - return string + def __repr__(self): + # display the object + string = '\n' + string += 'class "calibration_function" object = \n' + string += ' descriptor: ' + str(self.descriptor) + '\n' + string += ' scale_type: ' + str(self.scale_type) + '\n' + string += ' scale: ' + str(self.scale) + '\n' + string += ' weight: ' + str(self.weight) + '\n' + return string - # from here on, cf is either a single, or a 1d vector of, calibration_function - @staticmethod - def prop_desc(cf,dstr): - if type(cf) not in [list,np.ndarray]: - if cf.descriptor != '' or type(cf.descriptor) != str: - desc = str(cf.descriptor) - elif dstr != '': - desc = str(dstr) - else: - desc = 'cf' - return desc + # from here on, cf is either a single, or a 1d vector of, calibration_function + @staticmethod + def prop_desc(cf, dstr): + if type(cf) not in [list, np.ndarray]: + if cf.descriptor != '' or type(cf.descriptor) != str: + desc = str(cf.descriptor) + elif dstr != '': + desc = str(dstr) + else: + desc = 'cf' + return desc - desc = ['' for i in range(np.size(cf))] - for i in range(np.size(cf)): - if cf[i].descriptor != '' or type(cf[i].descriptor) != str: - desc[i] = str(cf[i].descriptor) - elif dstr != '': - desc[i] = str(dstr)+str(string_dim(cf,i,'vector')) - else: - desc[i] = 'cf'+str(string_dim(cf,i,'vector')) + desc = ['' for i in range(np.size(cf))] + for i in range(np.size(cf)): + if cf[i].descriptor != '' or type(cf[i].descriptor) != str: + desc[i] = str(cf[i].descriptor) + elif dstr != '': + desc[i] = str(dstr) + str(string_dim(cf, i, 'vector')) + else: + desc[i] = 'cf' + str(string_dim(cf, i, 'vector')) - desc = allempty(desc) - return desc + desc = allempty(desc) + return desc - @staticmethod - def prop_stype(cf): - stype='' - return stype + @staticmethod + def prop_stype(cf): + stype = '' + return stype - @staticmethod - def prop_weight(cf): - weight=[] - return weight + @staticmethod + def prop_weight(cf): + weight = [] + return weight - @staticmethod - def prop_lower(cf): - lower=[] - return lower + @staticmethod + def prop_lower(cf): + lower = [] + return lower - @staticmethod - def prop_upper(cf): - upper=[] - return upper + @staticmethod + def prop_upper(cf): + upper = [] + return upper - @staticmethod - def prop_target(cf): - target=[] - return target + @staticmethod + def prop_target(cf): + target = [] + return target - @staticmethod - def prop_scale(cf): - scale=[] - return scale + @staticmethod + def prop_scale(cf): + scale = [] + return scale - @staticmethod - def dakota_write(fidi,dresp,rdesc): - # collect only the responses of the appropriate class - cf = [struc_class(i,'calibration_function','cf') for i in dresp] + @staticmethod + def dakota_write(fidi, dresp, rdesc): + # collect only the responses of the appropriate class + cf = [struc_class(i, 'calibration_function', 'cf') for i in dresp] - # write responses - rdesc = rlist_write(fidi,'calibration_terms','calibration_function',cf,rdesc) - return rdesc + # write responses + rdesc = rlist_write(fidi, 'calibration_terms', 'calibration_function', cf, rdesc) + return rdesc - @staticmethod - def dakota_rlev_write(fidi,dresp,params): - return + @staticmethod + def dakota_rlev_write(fidi, dresp, params): + return Index: /issm/trunk-jpl/src/m/classes/qmu/continuous_design.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/continuous_design.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/continuous_design.py (revision 24213) @@ -3,10 +3,11 @@ from MatlabArray import * + class continuous_design(object): - ''' + ''' definition for the continuous_design class. [cdv] = continuous_design.continuous_design(args) - cdv = continuous_design() + cdv = continuous_design() where the required args are: @@ -14,6 +15,6 @@ initpt (double, initial point, 0.) and the optional args and defaults are: - lower (double, lower bound, -Inf) - upper (double, upper bound, Inf) + lower (double, lower bound, - Inf) + upper (double, upper bound, Inf) scale_type (char, scaling type, 'none') scale (double, scaling factor, 1.) @@ -24,208 +25,205 @@ ''' - def __init__(self): - self.descriptor = '' - self.initpt = 0. - self.lower = -np.inf - self.upper = np.inf - self.scale_type = 'none' - self.scale = 1. - - @staticmethod - def continuous_design(*args): - nargin = len(args) - - # create a default object - if nargin == 0: - return continuous_design() - - # copy the object - if nargin == 1: - if isinstance(args[0],continuous_design): - cdv = args[0] - else: - raise RuntimeError('Object is a '+str(type(args[0]))+' class object, not "continuous_design".') - - # create the object from the input - else: - shapec = array_size(*args[0:min(nargin,6)]) - cdv = [continuous_design() for i in range(shapec[0]) for j in range(shapec[1])] - # in case cdv doesn't use array-like args - #cdv = continuous_design() - - for i in range(np.size(cdv)): - if (np.size(args[0]) > 1): - cdv[i].descriptor = args[0][i] - else: - cdv[i].descriptor = str(args[0])+string_dim(cdv,i,'vector') - - if (nargin >= 2): - for i in range(np.size(cdv)): - if (np.size(args[1]) > 1): - cdv[i].initpt = args[1][i] - else: - cdv[i].initpt = args[1] - - if (nargin >= 3): - for i in range(np.size(cdv)): - if (np.size(args[2]) > 1): - cdv[i].lower = args[2][i] - else: - cdv[i].lower = args[2] - - if (nargin >= 4): - for i in range(np.size(cdv)): - if (np.size(args[3]) > 1): - cdv[i].upper = args[3][i] - else: - cdv[i].upper = args[3] - - if (nargin >= 5): - for i in range(np.size(cdv)): - if (np.size(args[4]) > 1): - cdv[i].scale_type = args[4][i] - else: - cdv[i].scale_type = str(args[4]) - - if (nargin >= 6): - for i in range(np.size(cdv)): - if (np.size(args[5]) > 1): - cdv[i].scale = args[5][i] - else: - cdv[i].scale = args[5] - - if (nargin > 6): - print('WARNING: continuous_design:extra_arg: Extra arguments for object of class '+str(type(cdv))+'.') - - return cdv - - - def __repr__(self): - # display the object - string = '\n' - string += 'class "continuous_design" object = \n' - string += ' descriptor: ' +str(self.descriptor) + '\n' - string += ' initpt: ' +str(self.initpt) + '\n' - string += ' lower: ' +str(self.lower) + '\n' - string += ' upper: ' +str(self.upper) + '\n' - string += ' scale_type: ' +str(self.scale_type) + '\n' - string += ' scale: ' +str(self.scale) + '\n' - - return string - - @staticmethod - def prop_desc(cdv,dstr): - if type(cdv) not in [list,np.ndarray]: - cdv = [cdv] - # in case cdv doesn't use array-like args - #if cdv.descriptor != '' or type(cdv.descriptor) != str: - #desc = str(cdv.descriptor) - #elif dstr != '': - #desc = str(dstr) - #else: - #desc = 'cdv' - #return desc - - desc = ['' for i in range(np.size(cdv))] - for i in range(np.size(cdv)): - if cdv[i].descriptor != '' or type(cdv[i].descriptor) != str: - desc[i] = str(cdv[i].descriptor) - elif dstr != '': - desc[i] = str(dstr)+str(string_dim(cdv,i,'vector')) - else: - desc[i] = 'cdv'+str(string_dim(cdv,i,'vector')) - - desc = allempty(desc) - - return desc - - @staticmethod - def prop_initpt(cdv): - if type(cdv) not in [list,np.ndarray]: - return cdv.initpt - - initpt = np.zeros(np.size(cdv)) - for i in range(np.size(cdv)): - initpt[i] = cdv[i].initpt - - initpt = allequal(initpt,0.) - - return initpt - - @staticmethod - def prop_lower(cdv): - if type(cdv) not in [list,np.ndarray]: - return cdv.lower - - lower = np.zeros(np.size(cdv)) - for i in range(np.size(cdv)): - lower[i] = cdv[i].lower - - lower = allequal(lower,-np.inf) - - return lower - - @staticmethod - def prop_upper(cdv): - if type(cdv) not in [list,np.ndarray]: - return cdv.upper - - upper = np.zeros(np.size(cdv)) - for i in range(np.size(cdv)): - upper[i] = cdv[i].upper - - upper = allequal(upper, np.inf) - - return upper - - @staticmethod - def prop_mean(cdv): - mean=[] - return mean - - @staticmethod - def prop_stddev(cdv): - stddev=[] - return sttdev - - @staticmethod - def prop_initst(cdv): - initst=[] - return initst - - @staticmethod - def prop_stype(cdv): - if type(cdv) not in [list,np.ndarray]: - return str(cdv.scale_type) - - stype = np.empty(np.size(cdv)) - stype.fill(0.0) - for i in range(np.size(cdv)): - stype[i] = str(cdv[i].scale_type) - - stype = allequal(stype,'none') - - return stype - - @staticmethod - def prop_scale(cdv): - if type(cdv) not in [list,np.ndarray]: - return cdv.scale - - scale = np.zeros(np.size(cdv)) - for i in range(np.size(cdv)): - scale[i] = cdv[i].scale - - scale = allequal(scale,1.) - - return scale - - - @staticmethod - def dakota_write(fidi,dvar): - # collect only the variables of the appropriate class - cdv = [struc_class(i,'continuous_design','cdv') for i in dvar] - - # write variables - vlist_write(fidi,'continuous_design','cdv',cdv) - + def __init__(self): + self.descriptor = '' + self.initpt = 0. + self.lower = - np.inf + self.upper = np.inf + self.scale_type = 'none' + self.scale = 1. + + @staticmethod + def continuous_design(*args): + nargin = len(args) + + # create a default object + if nargin == 0: + return continuous_design() + + # copy the object + if nargin == 1: + if isinstance(args[0], continuous_design): + cdv = args[0] + else: + raise RuntimeError('Object is a ' + str(type(args[0])) + ' class object, not "continuous_design".') + + # create the object from the input + else: + shapec = array_size(*args[0:min(nargin, 6)]) + cdv = [continuous_design() for i in range(shapec[0]) for j in range(shapec[1])] + # in case cdv doesn't use array - like args + #cdv = continuous_design() + + for i in range(np.size(cdv)): + if (np.size(args[0]) > 1): + cdv[i].descriptor = args[0][i] + else: + cdv[i].descriptor = str(args[0]) + string_dim(cdv, i, 'vector') + + if (nargin >= 2): + for i in range(np.size(cdv)): + if (np.size(args[1]) > 1): + cdv[i].initpt = args[1][i] + else: + cdv[i].initpt = args[1] + + if (nargin >= 3): + for i in range(np.size(cdv)): + if (np.size(args[2]) > 1): + cdv[i].lower = args[2][i] + else: + cdv[i].lower = args[2] + + if (nargin >= 4): + for i in range(np.size(cdv)): + if (np.size(args[3]) > 1): + cdv[i].upper = args[3][i] + else: + cdv[i].upper = args[3] + + if (nargin >= 5): + for i in range(np.size(cdv)): + if (np.size(args[4]) > 1): + cdv[i].scale_type = args[4][i] + else: + cdv[i].scale_type = str(args[4]) + + if (nargin >= 6): + for i in range(np.size(cdv)): + if (np.size(args[5]) > 1): + cdv[i].scale = args[5][i] + else: + cdv[i].scale = args[5] + + if (nargin > 6): + print('WARNING: continuous_design:extra_arg: Extra arguments for object of class ' + str(type(cdv)) + '.') + + return cdv + + def __repr__(self): + # display the object + string = '\n' + string += 'class "continuous_design" object = \n' + string += ' descriptor: ' + str(self.descriptor) + '\n' + string += ' initpt: ' + str(self.initpt) + '\n' + string += ' lower: ' + str(self.lower) + '\n' + string += ' upper: ' + str(self.upper) + '\n' + string += ' scale_type: ' + str(self.scale_type) + '\n' + string += ' scale: ' + str(self.scale) + '\n' + + return string + + @staticmethod + def prop_desc(cdv, dstr): + if type(cdv) not in [list, np.ndarray]: + cdv = [cdv] + # in case cdv doesn't use array - like args + #if cdv.descriptor != '' or type(cdv.descriptor) != str: + #desc = str(cdv.descriptor) + #elif dstr != '': + #desc = str(dstr) + #else: + #desc = 'cdv' + #return desc + + desc = ['' for i in range(np.size(cdv))] + for i in range(np.size(cdv)): + if cdv[i].descriptor != '' or type(cdv[i].descriptor) != str: + desc[i] = str(cdv[i].descriptor) + elif dstr != '': + desc[i] = str(dstr) + str(string_dim(cdv, i, 'vector')) + else: + desc[i] = 'cdv' + str(string_dim(cdv, i, 'vector')) + + desc = allempty(desc) + + return desc + + @staticmethod + def prop_initpt(cdv): + if type(cdv) not in [list, np.ndarray]: + return cdv.initpt + + initpt = np.zeros(np.size(cdv)) + for i in range(np.size(cdv)): + initpt[i] = cdv[i].initpt + + initpt = allequal(initpt, 0.) + + return initpt + + @staticmethod + def prop_lower(cdv): + if type(cdv) not in [list, np.ndarray]: + return cdv.lower + + lower = np.zeros(np.size(cdv)) + for i in range(np.size(cdv)): + lower[i] = cdv[i].lower + + lower = allequal(lower, - np.inf) + + return lower + + @staticmethod + def prop_upper(cdv): + if type(cdv) not in [list, np.ndarray]: + return cdv.upper + + upper = np.zeros(np.size(cdv)) + for i in range(np.size(cdv)): + upper[i] = cdv[i].upper + + upper = allequal(upper, np.inf) + + return upper + + @staticmethod + def prop_mean(cdv): + mean = [] + return mean + + @staticmethod + def prop_stddev(cdv): + stddev = [] + return stddev + + @staticmethod + def prop_initst(cdv): + initst = [] + return initst + + @staticmethod + def prop_stype(cdv): + if type(cdv) not in [list, np.ndarray]: + return str(cdv.scale_type) + + stype = np.empty(np.size(cdv)) + stype.fill(0.0) + for i in range(np.size(cdv)): + stype[i] = str(cdv[i].scale_type) + + stype = allequal(stype, 'none') + + return stype + + @staticmethod + def prop_scale(cdv): + if type(cdv) not in [list, np.ndarray]: + return cdv.scale + + scale = np.zeros(np.size(cdv)) + for i in range(np.size(cdv)): + scale[i] = cdv[i].scale + + scale = allequal(scale, 1.) + + return scale + + @staticmethod + def dakota_write(fidi, dvar): + # collect only the variables of the appropriate class + cdv = [struc_class(i, 'continuous_design', 'cdv') for i in dvar] + + # write variables + vlist_write(fidi, 'continuous_design', 'cdv', cdv) Index: /issm/trunk-jpl/src/m/classes/qmu/continuous_state.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/continuous_state.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/continuous_state.py (revision 24213) @@ -3,10 +3,11 @@ from MatlabArray import * + class continuous_state(object): - ''' + ''' definition for the continuous_state class. [csv] = continuous_state.continuous_state(args) - csv = continuous_state() + csv = continuous_state() where the required args are: @@ -14,6 +15,6 @@ initst (double, initial state, 0.) and the optional args and defaults are: - lower (double, lower bound, -Inf) - upper (double, upper bound, Inf) + lower (double, lower bound, - Inf) + upper (double, upper bound, Inf) note that zero arguments constructs a default instance, one @@ -22,161 +23,160 @@ ''' - def __init__(self): - self.descriptor = '' - self.initst = 0. - self.lower = -np.inf - self.upper = np.inf - - @staticmethod - def continuous_state(*args): - nargin = len(args) + def __init__(self): + self.descriptor = '' + self.initst = 0. + self.lower = - np.inf + self.upper = np.inf - # create a default object - if nargin == 0: - return continuous_state() + @staticmethod + def continuous_state(*args): + nargin = len(args) - # copy the object - if nargin == 1: - if isinstance(args[0],continuous_state): - csv = args[0] - else: - raise RuntimeError('Object is a '+str(type(args[0]))+' class object, not "continuous_state".') - - # create the object from the input - else: - shapec = np.shape(*args[0:min(nargin,4)]) - csv = [continuous_state() for i in range(shapec[0]) for j in range(shapec[1])] - - for i in range(np.size(csv)): - if (np.size(args[0]) > 1): - csv[i].descriptor = args[0][i] - else: - csv[i].descriptor = str(args[0])+string_dim(csv,i,'vector') + # create a default object + if nargin == 0: + return continuous_state() - if (nargin >= 2): - for i in range(np.size(csv)): - if (np.size(args[1]) > 1): - csv[i].initst = args[1][i] - else: - csv[i].initst = args[1] + # copy the object + if nargin == 1: + if isinstance(args[0], continuous_state): + csv = args[0] + else: + raise RuntimeError('Object is a ' + str(type(args[0])) + ' class object, not "continuous_state".') - if (nargin >= 3): - for i in range(np.size(csv)): - if (np.size(args[2]) > 1): - csv[i].lower = args[2][i] - else: - csv[i].lower = args[2] - - if (nargin >= 4): - for i in range(np.size(csv)): - if (np.size(args[3]) > 1): - csv[i].upper = args[3][i] - else: - csv[i].upper = args[3] + # create the object from the input + else: + shapec = np.shape(*args[0:min(nargin, 4)]) + csv = [continuous_state() for i in range(shapec[0]) for j in range(shapec[1])] - if (nargin > 4): - print('continuous_state:extra_arg','Extra arguments for object of class '+str(type(csv))+'.') + for i in range(np.size(csv)): + if (np.size(args[0]) > 1): + csv[i].descriptor = args[0][i] + else: + csv[i].descriptor = str(args[0]) + string_dim(csv, i, 'vector') - return csv - - def __repr__(self): - # display the object - string = '\n' - string += 'class "continuous_state" object = \n' - string += ' descriptor: ' +str(self.descriptor) + '\n' - string += ' initst: ' +str(self.initst) + '\n' - string += ' lower: ' +str(self.lower) + '\n' - string += ' upper: ' +str(self.upper) + '\n' + if (nargin >= 2): + for i in range(np.size(csv)): + if (np.size(args[1]) > 1): + csv[i].initst = args[1][i] + else: + csv[i].initst = args[1] - return string + if (nargin >= 3): + for i in range(np.size(csv)): + if (np.size(args[2]) > 1): + csv[i].lower = args[2][i] + else: + csv[i].lower = args[2] - @staticmethod - def prop_desc(csv,dstr): - if type(csv) not in [list,np.ndarray]: - csv = [csv] + if (nargin >= 4): + for i in range(np.size(csv)): + if (np.size(args[3]) > 1): + csv[i].upper = args[3][i] + else: + csv[i].upper = args[3] - desc = ['' for i in range(np.size(csv))] - for i in range(np.size(csv)): - if csv[i].descriptor != '' or type(cdv[i].descriptor) != str: - desc[i] = str(csv[i].descriptor) - elif dstr != '': - desc[i] = str(dstr)+str(string_dim(csv,i,'vector')) - else: - desc[i] = 'csv'+str(string_dim(csv,i,'vector')) - - desc = allempty(desc) + if (nargin > 4): + print('continuous_state:extra_arg', 'Extra arguments for object of class ' + str(type(csv)) + '.') - return desc + return csv - @staticmethod - def prop_initpt(csv): - initpt=[] - return initpt + def __repr__(self): + # display the object + string = '\n' + string += 'class "continuous_state" object = \n' + string += ' descriptor: ' + str(self.descriptor) + '\n' + string += ' initst: ' + str(self.initst) + '\n' + string += ' lower: ' + str(self.lower) + '\n' + string += ' upper: ' + str(self.upper) + '\n' - @staticmethod - def prop_lower(csv): - if type(csv) not in [list,np.ndarray]: - return csv.lower + return string - lower = np.zeros(np.size(csv)) - for i in range(np.size(csv)): - lower[i] = csv[i].lower - - lower = allequal(lower,-np.inf) + @staticmethod + def prop_desc(csv, dstr): + if type(csv) not in [list, np.ndarray]: + csv = [csv] - return lower + desc = ['' for i in range(np.size(csv))] + for i in range(np.size(csv)): + if csv[i].descriptor != '' or type(cdv[i].descriptor) != str: + desc[i] = str(csv[i].descriptor) + elif dstr != '': + desc[i] = str(dstr) + str(string_dim(csv, i, 'vector')) + else: + desc[i] = 'csv' + str(string_dim(csv, i, 'vector')) - @staticmethod - def prop_upper(csv): - if type(csv) not in [list,np.ndarray]: - return csv.upper + desc = allempty(desc) - upper = np.zeros(np.size(csv)) - for i in range(np.size(csv)): - upper[i] = csv[i].upper + return desc - upper = allequal(upper, np.inf) + @staticmethod + def prop_initpt(csv): + initpt = [] + return initpt - return upper + @staticmethod + def prop_lower(csv): + if type(csv) not in [list, np.ndarray]: + return csv.lower - @staticmethod - def prop_mean(csv): - mean=[] - return mean + lower = np.zeros(np.size(csv)) + for i in range(np.size(csv)): + lower[i] = csv[i].lower - @staticmethod - def prop_stddev(csv): - stddev=[] - return sttdev + lower = allequal(lower, - np.inf) - @staticmethod - def prop_initst(csv): - if type(csv) not in [list,np.ndarray]: - return csv.initst + return lower - initst = np.zeros(np.size(csv)) - for i in range(np.size(csv)): - initst[i] = csv[i].initst + @staticmethod + def prop_upper(csv): + if type(csv) not in [list, np.ndarray]: + return csv.upper - initst = allequal(initst,0.) + upper = np.zeros(np.size(csv)) + for i in range(np.size(csv)): + upper[i] = csv[i].upper - return initst + upper = allequal(upper, np.inf) - @staticmethod - def prop_stype(csv): - stype='' - return stype + return upper - @staticmethod - def prop_scale(csv): - scale=[] - return scale + @staticmethod + def prop_mean(csv): + mean = [] + return mean - @staticmethod - def dakota_write(fidi,dvar): - # collect only the variables of the appropriate class - csv = [struc_class(i,'continuous_state','csv') for i in dvar] + @staticmethod + def prop_stddev(csv): + stddev = [] + return stddev - # write variables - vlist_write(fidi,'continuous_state','csv',csv) + @staticmethod + def prop_initst(csv): + if type(csv) not in [list, np.ndarray]: + return csv.initst + initst = np.zeros(np.size(csv)) + for i in range(np.size(csv)): + initst[i] = csv[i].initst + + initst = allequal(initst, 0.) + + return initst + + @staticmethod + def prop_stype(csv): + stype = '' + return stype + + @staticmethod + def prop_scale(csv): + scale = [] + return scale + + @staticmethod + def dakota_write(fidi, dvar): + # collect only the variables of the appropriate class + csv = [struc_class(i, 'continuous_state', 'csv') for i in dvar] + + # write variables + vlist_write(fidi, 'continuous_state', 'csv', csv) Index: /issm/trunk-jpl/src/m/classes/qmu/least_squares_term.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/least_squares_term.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/least_squares_term.py (revision 24213) @@ -3,10 +3,11 @@ from MatlabArray import * + class least_squares_term(object): - ''' + ''' definition for the least_squares_term class. [lst] = least_squares_term.least_squares_term(args) - lst = least_squares_term() + lst = least_squares_term() where the required args are: @@ -21,146 +22,146 @@ arguments constructs a new instance from the arguments. ''' - def __init__(self): - self.descriptor = '' - self.scale_type = 'none' - self.scale = 1. - self.weight = 1. + def __init__(self): + self.descriptor = '' + self.scale_type = 'none' + self.scale = 1. + self.weight = 1. - @staticmethod - def least_squares_term(*args): - nargin = len(args) + @staticmethod + def least_squares_term(*args): + nargin = len(args) - #create a default object - if nargin == 0: - return least_squares_term() + #create a default object + if nargin == 0: + return least_squares_term() - #copy the object or create the object from the input - else: - if (nargin == 1) and isinstance(args[0],least_squares_term): - lst = args[0] - else: - asizec = np.shape(*args[0:min(nargin,4)]) - lst = [least_squares_term() for i in range(asizec[0]) for j in range(asizec[1])] + #copy the object or create the object from the input + else: + if (nargin == 1) and isinstance(args[0], least_squares_term): + lst = args[0] + else: + asizec = np.shape(*args[0:min(nargin, 4)]) + lst = [least_squares_term() for i in range(asizec[0]) for j in range(asizec[1])] - for i in range(np.size(lst)): - if (np.size(args[0]) > 1): - lst[i].descriptor = args[0][i] - else: - lst[i].descriptor = str(args[0])+string_dim(lst,i,'vector') + for i in range(np.size(lst)): + if (np.size(args[0]) > 1): + lst[i].descriptor = args[0][i] + else: + lst[i].descriptor = str(args[0]) + string_dim(lst, i, 'vector') - if (nargin >= 2): - for i in range(np.size(lst)): - if (np.size(args[1]) > 1): - lst[i].scale_type = args[1][i] - else: - lst[i].scale_type = str(args[1]) + if (nargin >= 2): + for i in range(np.size(lst)): + if (np.size(args[1]) > 1): + lst[i].scale_type = args[1][i] + else: + lst[i].scale_type = str(args[1]) - if (nargin >= 3): - for i in range(np.size(lst)): - if (np.size(args[2]) > 1): - lst[i].scale = args[2][i] - else: - lst[i].scale = args[2] + if (nargin >= 3): + for i in range(np.size(lst)): + if (np.size(args[2]) > 1): + lst[i].scale = args[2][i] + else: + lst[i].scale = args[2] - if (nargin >= 4): - for i in range(np.size(lst)): - if (np.size(args[3]) > 1): - lst[i].weight = args[3][i] - else: - lst[i].weight = args[3] + if (nargin >= 4): + for i in range(np.size(lst)): + if (np.size(args[3]) > 1): + lst[i].weight = args[3][i] + else: + lst[i].weight = args[3] - if (nargin > 4): - print('WARNING: least_squares_term:extra_arg Extra arguments for object of class '+str(type(lst))+'.') + if (nargin > 4): + print('WARNING: least_squares_term:extra_arg Extra arguments for object of class ' + str(type(lst)) + '.') - return lst + return lst - def __repr__(self): - # display the object - string = '\n' - string += 'class "least_squares_term" object = \n' - string += ' descriptor: '+str(self.descriptor) + '\n' - string += ' scale_type: '+str(self.scale_type) + '\n' - string += ' scale: '+str(self.scale) + '\n' - string += ' weight: '+str(self.weight) + '\n' - return string + def __repr__(self): + # display the object + string = '\n' + string += 'class "least_squares_term" object = \n' + string += ' descriptor: ' + str(self.descriptor) + '\n' + string += ' scale_type: ' + str(self.scale_type) + '\n' + string += ' scale: ' + str(self.scale) + '\n' + string += ' weight: ' + str(self.weight) + '\n' + return string - @staticmethod - def prop_desc(lst,dstr): - if type(lst) not in [list,np.ndarray]: - lst = [lst] + @staticmethod + def prop_desc(lst, dstr): + if type(lst) not in [list, np.ndarray]: + lst = [lst] - desc = ['' for i in range(np.size(lst))] - for i in range(np.size(lst)): - if lst[i].descriptor != '' or type(cdv[i].descriptor) != str: - desc[i] = str(lst[i].descriptor) - elif dstr != '': - desc[i] = str(dstr)+str(string_dim(lst,i,'vector')) - else: - desc[i] = 'lst'+str(string_dim(lst,i,'vector')) + desc = ['' for i in range(np.size(lst))] + for i in range(np.size(lst)): + if lst[i].descriptor != '' or type(cdv[i].descriptor) != str: + desc[i] = str(lst[i].descriptor) + elif dstr != '': + desc[i] = str(dstr) + str(string_dim(lst, i, 'vector')) + else: + desc[i] = 'lst' + str(string_dim(lst, i, 'vector')) - desc = allempty(desc) - return desc + desc = allempty(desc) + return desc - @staticmethod - def prop_stype(lst): - if type(lst) not in [list,np.ndarray]: - return str(lst.scale_type) + @staticmethod + def prop_stype(lst): + if type(lst) not in [list, np.ndarray]: + return str(lst.scale_type) - stype = ['' for i in range(np.size(lst))] - for i in range(np.size(lst)): - stype[i] = str(lst[i].scale_type) + stype = ['' for i in range(np.size(lst))] + for i in range(np.size(lst)): + stype[i] = str(lst[i].scale_type) - stype = allequal(stype,'none') - return stype + stype = allequal(stype, 'none') + return stype - @staticmethod - def prop_scale(lst): - if type(lst) not in [list,np.ndarray]: - return lst.scale + @staticmethod + def prop_scale(lst): + if type(lst) not in [list, np.ndarray]: + return lst.scale - scale = np.zeros(np.size(lst)) - for i in range(np.size(lst)): - scale[i] = lst[i].scale + scale = np.zeros(np.size(lst)) + for i in range(np.size(lst)): + scale[i] = lst[i].scale - scale = allequal(scale,1.) - return scale + scale = allequal(scale, 1.) + return scale - @staticmethod - def prop_weight(lst): - if type(lst) not in [list,np.ndarray]: - return lst.weight + @staticmethod + def prop_weight(lst): + if type(lst) not in [list, np.ndarray]: + return lst.weight - weight = np.zeros(np.size(lst)) - for i in range(np.size(lst)): - weight[i] = lst[i].weight + weight = np.zeros(np.size(lst)) + for i in range(np.size(lst)): + weight[i] = lst[i].weight - weight = allequal(weight,1.) - return weight + weight = allequal(weight, 1.) + return weight - @staticmethod - def prop_lower(lst): - lower=[] - return lower + @staticmethod + def prop_lower(lst): + lower = [] + return lower - @staticmethod - def prop_upper(lst): - upper=[] - return upper + @staticmethod + def prop_upper(lst): + upper = [] + return upper - @staticmethod - def prop_target(lst): - target=[] - return target + @staticmethod + def prop_target(lst): + target = [] + return target - @staticmethod - def dakota_write(fidi,dresp,rdesc): - #collect only the responses of the appropriate class - lst = [struc_class(i,'least_squares_term','lst') for i in dresp] + @staticmethod + def dakota_write(fidi, dresp, rdesc): + #collect only the responses of the appropriate class + lst = [struc_class(i, 'least_squares_term', 'lst') for i in dresp] - #write responses - rdesc = rlist_write(fidi,'least_squares_terms','least_squares_term',lst,rdesc) - return rdesc + #write responses + rdesc = rlist_write(fidi, 'least_squares_terms', 'least_squares_term', lst, rdesc) + return rdesc - @staticmethod - def dakota_rlev_write(fidi,dresp,params): - return + @staticmethod + def dakota_rlev_write(fidi, dresp, params): + return Index: /issm/trunk-jpl/src/m/classes/qmu/linear_equality_constraint.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/linear_equality_constraint.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/linear_equality_constraint.py (revision 24213) @@ -3,10 +3,11 @@ from MatlabArray import * + class linear_equality_constraint: - ''' + ''' constructor for the linear_equality_constraint class. [lec] = linear_equality_constraint.linear_equality_constraint(args) - lec = linear_equality_constraint() + lec = linear_equality_constraint() where the required args are: @@ -21,145 +22,144 @@ arguments constructs a new instance from the arguments. ''' - def __init__(self): - self.matrix = np.array([[float('NaN')]]) - self.target = 0. - self.scale_type = 'none' - self.scale = 1. + def __init__(self): + self.matrix = np.array([[float('NaN')]]) + self.target = 0. + self.scale_type = 'none' + self.scale = 1. - @staticmethod - def linear_equality_constraint(*args): - nargin = len(args) + @staticmethod + def linear_equality_constraint(*args): + nargin = len(args) - # create a default object - if nargin == 0: - return linear_equality_constraint() + # create a default object + if nargin == 0: + return linear_equality_constraint() - # copy the object - elif nargin == 1: - if isinstance(args[0],linear_equality_constraint): - lec = args[0] - else: - raise RuntimeError('Object is a '+str(type(args[0]))+' class object, not "linear_equality_constraint"') + # copy the object + elif nargin == 1: + if isinstance(args[0], linear_equality_constraint): + lec = args[0] + else: + raise RuntimeError('Object is a ' + str(type(args[0])) + ' class object, not "linear_equality_constraint"') - # create the object from the input - else: - if (np.shape(args[0],1) == array_np.size(args[1:min(nargin,4)]) or np.shape(args[0],1) == 1): - asizec = np.shape(args[1:min(nargin,4)]) - elif (array_np.size(args[1:min(nargin,4)]) == 1): - asizec = [np.shape(args[0],1),1] - else: - raise RuntimeError('Matrix for object of class '+str(type(lec))+' has inconsistent number of rows.') + # create the object from the input + else: + if (np.shape(args[0], 1) == array_np.size(args[1:min(nargin, 4)]) or np.shape(args[0], 1) == 1): + asizec = np.shape(args[1:min(nargin, 4)]) + elif (array_np.size(args[1:min(nargin, 4)]) == 1): + asizec = [np.shape(args[0], 1), 1] + else: + raise RuntimeError('Matrix for object of class ' + str(type(lec)) + ' has inconsistent number of rows.') - lec = [linear_equality_constraint() for i in range(asizec[0]) for j in range(asizec[1])] + lec = [linear_equality_constraint() for i in range(asizec[0]) for j in range(asizec[1])] - for i in range(np.size(lec)): - if (np.shape(args[0])[0] > 1): - lec[i].matrix = args[0][i,:] - else: - lec[i].matrix = args[0] + for i in range(np.size(lec)): + if (np.shape(args[0])[0] > 1): + lec[i].matrix = args[0][i, :] + else: + lec[i].matrix = args[0] - if (nargin >= 2): - for i in range(np.size(lec)): - if (np.size(args[1]) > 1): - lec[i].target = args[1][i] - else: - lec[i].target = args[1] + if (nargin >= 2): + for i in range(np.size(lec)): + if (np.size(args[1]) > 1): + lec[i].target = args[1][i] + else: + lec[i].target = args[1] - if (nargin >= 3): - for i in range(np.size(lec)): - if (np.size(args[2]) > 1): - lec[i].scale_type = args[2][i] - else: - lec[i].scale_type = str(args[2]) - - if (nargin >= 4): - for i in range(np.size(lec)): - if (np.size(args[3]) > 1): - lec[i].scale = args[3][i] - else: - lec[i].scale = args[3] + if (nargin >= 3): + for i in range(np.size(lec)): + if (np.size(args[2]) > 1): + lec[i].scale_type = args[2][i] + else: + lec[i].scale_type = str(args[2]) - if (nargin > 4): - print('WARNING: linear_equality_constraint:extra_arg: Extra arguments for object of class '+str(type(lec))+'.') + if (nargin >= 4): + for i in range(np.size(lec)): + if (np.size(args[3]) > 1): + lec[i].scale = args[3][i] + else: + lec[i].scale = args[3] - return lec - + if (nargin > 4): + print('WARNING: linear_equality_constraint:extra_arg: Extra arguments for object of class ' + str(type(lec)) + '.') - def __repr__(self): - # display the object - string = '\n' - string += 'class "linear_equality_constraint" object = \n' - string += ' matrix: ' +str(self.matrix) + '\n' - string += ' target: ' +str(self.target) + '\n' - string += ' scale_type: ' +str(self.scale_type) + '\n' - string += ' scale: ' +str(self.scale) + '\n' + return lec - return string + def __repr__(self): + # display the object + string = '\n' + string += 'class "linear_equality_constraint" object = \n' + string += ' matrix: ' + str(self.matrix) + '\n' + string += ' target: ' + str(self.target) + '\n' + string += ' scale_type: ' + str(self.scale_type) + '\n' + string += ' scale: ' + str(self.scale) + '\n' - @staticmethod - def prop_matrix(lec): - if type(lec) not in [list,np.ndarray]: - return lec.matrix + return string - matrix = np.zeros(np.size(lec)) - for i in range(np.size(lec)): - matrix[i,0:np.shape(lec[i].matrix)[1]] = lec[i].matrix[0,:] + @staticmethod + def prop_matrix(lec): + if type(lec) not in [list, np.ndarray]: + return lec.matrix - return matrix + matrix = np.zeros(np.size(lec)) + for i in range(np.size(lec)): + matrix[i, 0:np.shape(lec[i].matrix)[1]] = lec[i].matrix[0, :] - @staticmethod - def prop_lower(lec): - lower=[] - return lower + return matrix - @staticmethod - def prop_upper(lec): - upper=[] - return upper + @staticmethod + def prop_lower(lec): + lower = [] + return lower - @staticmethod - def prop_target(lec): - if type(lec) not in [list,np.ndarray]: - return lec.target + @staticmethod + def prop_upper(lec): + upper = [] + return upper - target = np.zeros(np.shape(lec)) - for i in range(np.size(lec)): - target[i] = lec[i].target - - target = allequal(target,0.) + @staticmethod + def prop_target(lec): + if type(lec) not in [list, np.ndarray]: + return lec.target - return target + target = np.zeros(np.shape(lec)) + for i in range(np.size(lec)): + target[i] = lec[i].target - @staticmethod - def prop_stype(lec): - if type(lec) not in [list,np.ndarray]: - return lec.scale_type + target = allequal(target, 0.) - stype = ['' for i in range(np.size(lec))] - for i in range(np.size(lec)): - stype[i] = str(lec[i].scale_type) - - stype = allequal(stype,'none') + return target - return stype + @staticmethod + def prop_stype(lec): + if type(lec) not in [list, np.ndarray]: + return lec.scale_type - @staticmethod - def prop_scale(lec): - if type(lec) not in [list,np.ndarray]: - return lec.scale + stype = ['' for i in range(np.size(lec))] + for i in range(np.size(lec)): + stype[i] = str(lec[i].scale_type) - scale = np.zeros(np.shape(lec)) - for i in range(np.size(lec)): - scale[i] = lec[i].scale - - scale = allequal(scale,1.) + stype = allequal(stype, 'none') - return scale - - @staticmethod - def dakota_write(fidi,dvar): - # collect only the variables of the appropriate class - lec = [struc_type(i,'linear_equality_constraint','lec') for i in dvar] + return stype - # write constraints - lclist_write(fidi,'linear_equality_constraints','linear_equality',lec) + @staticmethod + def prop_scale(lec): + if type(lec) not in [list, np.ndarray]: + return lec.scale + + scale = np.zeros(np.shape(lec)) + for i in range(np.size(lec)): + scale[i] = lec[i].scale + + scale = allequal(scale, 1.) + + return scale + + @staticmethod + def dakota_write(fidi, dvar): + # collect only the variables of the appropriate class + lec = [struc_type(i, 'linear_equality_constraint', 'lec') for i in dvar] + + # write constraints + lclist_write(fidi, 'linear_equality_constraints', 'linear_equality', lec) Index: /issm/trunk-jpl/src/m/classes/qmu/linear_inequality_constraint.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/linear_inequality_constraint.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/linear_inequality_constraint.py (revision 24213) @@ -3,14 +3,15 @@ from MatlabArray import * + class linear_inequality_constraint: - ''' + ''' constructor for the linear_inequality_constraint class. [lic] = linear_inequality_constraint.linear_inequality_constraint(args) - lic = linear_inequality_constraint() + lic = linear_inequality_constraint() where the required args are: matrix (double row, variable coefficients, float('NaN')) - lower (double vector, lower bounds, -np.Inf) + lower (double vector, lower bounds, - np.Inf) upper (double vector, upper bounds, 0.) and the optional args and defaults are: @@ -22,166 +23,165 @@ arguments constructs a new instance from the arguments. ''' - def __init__(self): - self.matrix = np.array([[float('NaN')]]) - self.lower = -np.Inf - self.upper = 0. - self.scale_type = 'none' - self.scale = 1. + def __init__(self): + self.matrix = np.array([[float('NaN')]]) + self.lower = - np.Inf + self.upper = 0. + self.scale_type = 'none' + self.scale = 1. - @staticmethod - def linear_inequality_constraint(*args): - nargin = len(args) + @staticmethod + def linear_inequality_constraint(*args): + nargin = len(args) - # create a default object - if nargin == 0: - return linear_inequality_constraint() + # create a default object + if nargin == 0: + return linear_inequality_constraint() - # copy the object - if nargin == 1: - if isinstance(args[0],linear_inequality_constraint): - lic = args[0] - else: - raise RuntimeError('Object is a '+str(type(args[0]))+' class object, not "linear_inequality_constraint".') + # copy the object + if nargin == 1: + if isinstance(args[0], linear_inequality_constraint): + lic = args[0] + else: + raise RuntimeError('Object is a ' + str(type(args[0])) + ' class object, not "linear_inequality_constraint".') - # not enough arguments - if nargin == 2: - raise RuntimeError('Construction of linear_inequality_constraint class object requires at least 3 inputs.') + # not enough arguments + if nargin == 2: + raise RuntimeError('Construction of linear_inequality_constraint class object requires at least 3 inputs.') - # create the object from the input - else: - if (np.shape(args[0],1) == array_numel(args[1:min(nargin,5)]) or np.shape(args[0],1) == 1): - asizec = array_size(args[1:min(nargin,5)]) - elif (array_numel(args[1:min(nargin,5)]) == 1): - asizec = [array_size(args[0],1),1] - else: - raise RuntimeError('Matrix for object of class '+str(type(lic))+' has inconsistent number of rows.') - - lic = [linear_inequality_constraint() for i in range(asizec[0]) for j in range(asizec[1])] + # create the object from the input + else: + if (np.shape(args[0], 1) == array_numel(args[1:min(nargin, 5)]) or np.shape(args[0], 1) == 1): + asizec = array_size(args[1:min(nargin, 5)]) + elif (array_numel(args[1:min(nargin, 5)]) == 1): + asizec = [array_size(args[0], 1), 1] + else: + raise RuntimeError('Matrix for object of class ' + str(type(lic)) + ' has inconsistent number of rows.') - for i in range(np.size(lic)): - if (np.shape(args[0],1) > 1): - lic[i].matrix = args[0][i,:] - else: - lic[i].matrix = args[0] + lic = [linear_inequality_constraint() for i in range(asizec[0]) for j in range(asizec[1])] - if (nargin >= 2): - for i in range(np.size(lic)): - if (np.size(args[1]) > 1): - lic[i].lower = args[1][i] - else: - lic[i].lower = args[1] + for i in range(np.size(lic)): + if (np.shape(args[0], 1) > 1): + lic[i].matrix = args[0][i, :] + else: + lic[i].matrix = args[0] - if (nargin >= 3): - for i in range(np.size(lic)): - if (np.size(args[2]) > 1): - lic[i].upper = args[2][i] - else: - lic[i].upper = args[2] - - if (nargin >= 4): - for i in range(np.size(lic)): - if (np.size(args[3]) > 1): - lic[i].scale_type = args[3][i] - else: - lic[i].scale_type = str(args[3]) - - if (nargin >= 5): - for i in range(np.size(lic)): - if (np.size(args[4]) > 1): - lic[i].scale = args[4][i] - else: - lic[i].scale = args[4] + if (nargin >= 2): + for i in range(np.size(lic)): + if (np.size(args[1]) > 1): + lic[i].lower = args[1][i] + else: + lic[i].lower = args[1] - if (nargin > 5): - print('WARNING: linear_inequality_constraint:extra_arg: Extra arguments for object of class '+str(type(lic))+'.') + if (nargin >= 3): + for i in range(np.size(lic)): + if (np.size(args[2]) > 1): + lic[i].upper = args[2][i] + else: + lic[i].upper = args[2] - return lic + if (nargin >= 4): + for i in range(np.size(lic)): + if (np.size(args[3]) > 1): + lic[i].scale_type = args[3][i] + else: + lic[i].scale_type = str(args[3]) + if (nargin >= 5): + for i in range(np.size(lic)): + if (np.size(args[4]) > 1): + lic[i].scale = args[4][i] + else: + lic[i].scale = args[4] - def __repr__(self): - # display the object - string = '\n' - string += 'class "linear_inequality_constraint" object = \n' - string += ' matrix: ' +str(string_vec(self.matrix)) + '\n' - string += ' lower: ' +str(self.lower) + '\n' - string += ' upper: ' +str(self.upper) + '\n' - string += ' scale_type: ' +str(self.scale_type) + '\n' - string += ' scale: ' +str(self.scale) + '\n' + if (nargin > 5): + print('WARNING: linear_inequality_constraint:extra_arg: Extra arguments for object of class ' + str(type(lic)) + '.') - return string + return lic - @staticmethod - def prop_matrix(lic): - if type(lic) not in [list,np.ndarray]: - return lic.matrix + def __repr__(self): + # display the object + string = '\n' + string += 'class "linear_inequality_constraint" object = \n' + string += ' matrix: ' + str(string_vec(self.matrix)) + '\n' + string += ' lower: ' + str(self.lower) + '\n' + string += ' upper: ' + str(self.upper) + '\n' + string += ' scale_type: ' + str(self.scale_type) + '\n' + string += ' scale: ' + str(self.scale) + '\n' - matrix = np.zeros(np.size(lic)) - for i in range(np.size(lic)): - matrix[i,0:np.shape(lic[i].matrix)[1]] = lic[i].matrix[0,:] + return string - return matrix + @staticmethod + def prop_matrix(lic): + if type(lic) not in [list, np.ndarray]: + return lic.matrix - @staticmethod - def prop_lower(lic): - if type(lic) not in [list,np.ndarray]: - return lic.lower + matrix = np.zeros(np.size(lic)) + for i in range(np.size(lic)): + matrix[i, 0:np.shape(lic[i].matrix)[1]] = lic[i].matrix[0, :] - lower = np.zeros(np.shape(lic)) - for i in range(np.size(lic)): - lower[i] = lic[i].lower - - lower = allequal(lower,-np.Inf) + return matrix - return lower + @staticmethod + def prop_lower(lic): + if type(lic) not in [list, np.ndarray]: + return lic.lower - @staticmethod - def prop_upper(lic): - if type(lic) not in [list,np.ndarray]: - return lic.upper + lower = np.zeros(np.shape(lic)) + for i in range(np.size(lic)): + lower[i] = lic[i].lower - upper = np.zeros(np.shape(lic)) - for i in range(np.size(lic)): - upper[i] = lic[i].upper - - upper = allequal(upper,0.) + lower = allequal(lower, - np.Inf) - return upper + return lower - @staticmethod - def prop_target(lic): - target=[] - return target + @staticmethod + def prop_upper(lic): + if type(lic) not in [list, np.ndarray]: + return lic.upper - @staticmethod - def prop_stype(lic): - if type(lic) not in [list,np.ndarray]: - return lic.scale_type + upper = np.zeros(np.shape(lic)) + for i in range(np.size(lic)): + upper[i] = lic[i].upper - stype = ['' for i in range(np.size(lic))] - for i in range(np.size(lic)): - stype[i] = str(lic[i].scale_type) - - stype = allequal(stype,'none') + upper = allequal(upper, 0.) - return stype + return upper - @staticmethod - def prop_scale(lic): - if type(lic) not in [list,np.ndarray]: - return lic.scale + @staticmethod + def prop_target(lic): + target = [] + return target - scale = np.zeros(np.shape(lic)) - for i in range(np.size(lic)): - scale[i] = lic[i].scale - - scale = allequal(scale,1.) + @staticmethod + def prop_stype(lic): + if type(lic) not in [list, np.ndarray]: + return lic.scale_type - return scale - - @staticmethod - def dakota_write(fidi,dvar): - # collect only the variables of the appropriate class - lic = [struc_class(i,'linear_inequality_constraint','lic') for i in dvar] + stype = ['' for i in range(np.size(lic))] + for i in range(np.size(lic)): + stype[i] = str(lic[i].scale_type) - # write constraints - lclist_write(fidi,'linear_inequality_constraints','linear_inequality',lic) + stype = allequal(stype, 'none') + + return stype + + @staticmethod + def prop_scale(lic): + if type(lic) not in [list, np.ndarray]: + return lic.scale + + scale = np.zeros(np.shape(lic)) + for i in range(np.size(lic)): + scale[i] = lic[i].scale + + scale = allequal(scale, 1.) + + return scale + + @staticmethod + def dakota_write(fidi, dvar): + # collect only the variables of the appropriate class + lic = [struc_class(i, 'linear_inequality_constraint', 'lic') for i in dvar] + + # write constraints + lclist_write(fidi, 'linear_inequality_constraints', 'linear_inequality', lic) Index: /issm/trunk-jpl/src/m/classes/qmu/nonlinear_equality_constraint.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/nonlinear_equality_constraint.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/nonlinear_equality_constraint.py (revision 24213) @@ -3,10 +3,11 @@ from MatlabArray import * + class nonlinear_equality_constraint: - ''' + ''' constructor for the nonlinear_equality_constraint class. [nec] = nonlinear_equality_constraint.nonlinear_equality_constraint(args) - nec = nonlinear_equality_constraint() + nec = nonlinear_equality_constraint() where the required args are: @@ -21,159 +22,158 @@ arguments constructs a new instance from the arguments. ''' - def __init__(self): - self.descriptor = '' - self.target = 0. - self.scale_type = 'none' - self.scale = 1. + def __init__(self): + self.descriptor = '' + self.target = 0. + self.scale_type = 'none' + self.scale = 1. - @staticmethod - def nonlinear_equality_constraint(*args): - nargin = len(args) + @staticmethod + def nonlinear_equality_constraint(*args): + nargin = len(args) - # create a default object - if nargin == 0: - return nonlinear_equality_constraint() + # create a default object + if nargin == 0: + return nonlinear_equality_constraint() - # copy the object - elif nargin == 1: - if isinstance(args[0],nonlinear_equality_constraint): - nec = args[0] - else: - raise RuntimeError('Object is a '+str(type(args[0]))+' class object, not "nonlinear_equality_constraint"') + # copy the object + elif nargin == 1: + if isinstance(args[0], nonlinear_equality_constraint): + nec = args[0] + else: + raise RuntimeError('Object is a ' + str(type(args[0])) + ' class object, not "nonlinear_equality_constraint"') - # create the object from the input - else: - asizec = array_size(*args[0:min(nargin,4)]) - nec = [nonlinear_equality_constraint() for i in range(asizec[0]) for j in range(asizec[1])] + # create the object from the input + else: + asizec = array_size(*args[0:min(nargin, 4)]) + nec = [nonlinear_equality_constraint() for i in range(asizec[0]) for j in range(asizec[1])] - for i in range(np.size(nec)): - if (np.shape(args[0])[0] > 1): - nec[i].descriptor = args[0][i] - else: - nec[i].descriptor = str(args[0]) - if (np.size(args[1]) > 1): - nec[i].target = args[1][i] - else: - nec[i].target = args[1] + for i in range(np.size(nec)): + if (np.shape(args[0])[0] > 1): + nec[i].descriptor = args[0][i] + else: + nec[i].descriptor = str(args[0]) + if (np.size(args[1]) > 1): + nec[i].target = args[1][i] + else: + nec[i].target = args[1] - if (nargin >= 3): - for i in range(np.size(nec)): - if (np.size(args[2]) > 1): - nec[i].scale_type = args[2][i] - else: - nec[i].scale_type = str(args[2]) - - if (nargin >= 4): - for i in range(np.size(nec)): - if (np.size(args[3]) > 1): - nec[i].scale =args[3][i] - else: - nec[i].scale =args[3] + if (nargin >= 3): + for i in range(np.size(nec)): + if (np.size(args[2]) > 1): + nec[i].scale_type = args[2][i] + else: + nec[i].scale_type = str(args[2]) - if (nargin > 4): - print('WARNING: nonlinear_equality_constraint:extra_arg: Extra arguments for object of class '+str(type(nec))+'.') + if (nargin >= 4): + for i in range(np.size(nec)): + if (np.size(args[3]) > 1): + nec[i].scale = args[3][i] + else: + nec[i].scale = args[3] - return nec - + if (nargin > 4): + print('WARNING: nonlinear_equality_constraint:extra_arg: Extra arguments for object of class ' + str(type(nec)) + '.') - def __repr__(self): - # display the object - string = '\n' - string += 'class "nonlinear_equality_constraint" object = \n' - string += ' descriptor: ' +str(self.descriptor) + '\n' - string += ' target: ' +str(self.target) + '\n' - string += ' scale_type: ' +str(self.scale_type) + '\n' - string += ' scale: ' +str(self.scale) + '\n' + return nec - return string + def __repr__(self): + # display the object + string = '\n' + string += 'class "nonlinear_equality_constraint" object = \n' + string += ' descriptor: ' + str(self.descriptor) + '\n' + string += ' target: ' + str(self.target) + '\n' + string += ' scale_type: ' + str(self.scale_type) + '\n' + string += ' scale: ' + str(self.scale) + '\n' - @staticmethod - def prop_desc(nec,dstr): - if type(nec) not in [list,np.ndarray]: - if nec.descriptor != '' or type(nec.descriptor) != str: - desc = str(nec.descriptor) - elif dstr != '': - desc = str(dstr) - else: - desc = 'nec' - return desc + return string - desc=['' for i in range(np.size(nec))] - for i in range(np.size(nec)): - if nec[i].descriptor != '' or type(nec[i].descriptor) != str: - desc[i] = str(nec[i].descriptor) - elif dstr != '': - desc[i] = str(dstr)+str(string_dim(nec,i,'vector')) - else: - desc[i] = 'nec'+str(string_dim(nec,i,'vector')) - - desc=allempty(desc) + @staticmethod + def prop_desc(nec, dstr): + if type(nec) not in [list, np.ndarray]: + if nec.descriptor != '' or type(nec.descriptor) != str: + desc = str(nec.descriptor) + elif dstr != '': + desc = str(dstr) + else: + desc = 'nec' + return desc - return desc + desc = ['' for i in range(np.size(nec))] + for i in range(np.size(nec)): + if nec[i].descriptor != '' or type(nec[i].descriptor) != str: + desc[i] = str(nec[i].descriptor) + elif dstr != '': + desc[i] = str(dstr) + str(string_dim(nec, i, 'vector')) + else: + desc[i] = 'nec' + str(string_dim(nec, i, 'vector')) - @staticmethod - def prop_lower(nec): - lower=[] - return lower + desc = allempty(desc) - @staticmethod - def prop_upper(nec): - upper=[] - return upper + return desc - @staticmethod - def prop_weight(nec): - weight=[] - return weight + @staticmethod + def prop_lower(nec): + lower = [] + return lower - @staticmethod - def prop_target(nec): - if type(nec) not in [list,np.ndarray]: - return nec.target + @staticmethod + def prop_upper(nec): + upper = [] + return upper - target = np.zeros(np.shape(nec)) - for i in range(np.size(nec)): - target[i] = nec[i].target - - target = allequal(target,0.) + @staticmethod + def prop_weight(nec): + weight = [] + return weight - return target + @staticmethod + def prop_target(nec): + if type(nec) not in [list, np.ndarray]: + return nec.target - @staticmethod - def prop_stype(nec): - if type(nec) not in [list,np.ndarray]: - return nec.scale_type + target = np.zeros(np.shape(nec)) + for i in range(np.size(nec)): + target[i] = nec[i].target - stype = ['' for i in range(np.size(nec))] - for i in range(np.size(nec)): - stype[i] = str(nec[i].scale_type) - - stype = allequal(stype,'none') + target = allequal(target, 0.) - return stype + return target - @staticmethod - def prop_scale(nec): - if type(nec) not in [list,np.ndarray]: - return nec.scale + @staticmethod + def prop_stype(nec): + if type(nec) not in [list, np.ndarray]: + return nec.scale_type - scale = np.zeros(np.shape(nec)) - for i in range(np.size(nec)): - scale[i] = nec[i].scale - - scale = allequal(scale,1.) + stype = ['' for i in range(np.size(nec))] + for i in range(np.size(nec)): + stype[i] = str(nec[i].scale_type) - return scale - - @staticmethod - def dakota_write(fidi,dresp,rdesc): - # colnect only the variables of the appropriate class - nec = [struc_type(i,'nonlinear_equality_constraint','nec') for i in dresp] + stype = allequal(stype, 'none') - # write constraints - rdesc = rlist_write(fidi,'nonlinear_equality_constraints','nonlinear_equality',nec,rdesc) - return rdesc + return stype - @staticmethod - def dakota_rlev_write(fidi,dresp,params): - return + @staticmethod + def prop_scale(nec): + if type(nec) not in [list, np.ndarray]: + return nec.scale + + scale = np.zeros(np.shape(nec)) + for i in range(np.size(nec)): + scale[i] = nec[i].scale + + scale = allequal(scale, 1.) + + return scale + + @staticmethod + def dakota_write(fidi, dresp, rdesc): + # colnect only the variables of the appropriate class + nec = [struc_type(i, 'nonlinear_equality_constraint', 'nec') for i in dresp] + + # write constraints + rdesc = rlist_write(fidi, 'nonlinear_equality_constraints', 'nonlinear_equality', nec, rdesc) + return rdesc + + @staticmethod + def dakota_rlev_write(fidi, dresp, params): + return Index: /issm/trunk-jpl/src/m/classes/qmu/nonlinear_inequality_constraint.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/nonlinear_inequality_constraint.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/nonlinear_inequality_constraint.py (revision 24213) @@ -3,14 +3,15 @@ from MatlabArray import * + class nonlinear_inequality_constraint: - ''' + ''' constructor for the nonlinear_inequality_constraint class. [nic] = nonlinear_inequality_constraint.nonlinear_inequality_constraint(args) - nic = nonlinear_inequality_constraint() + nic = nonlinear_inequality_constraint() where the required args are: descriptor (char, description, '') - lower (double, lower bound, -np.inf) + lower (double, lower bound, - np.inf) upper (double, upper bound, 0.) and the optional args and defaults are: @@ -22,177 +23,177 @@ arguments constructs a new instance from the arguments. ''' - def __init__(self): - self.descriptor = '' - self.lower = -np.inf - self.upper = 0. - self.scale_type = 'none' - self.scale = 1. + def __init__(self): + self.descriptor = '' + self.lower = - np.inf + self.upper = 0. + self.scale_type = 'none' + self.scale = 1. - @staticmethod - def nonlinear_inequality_constraint(*args): - nargin = len(args) + @staticmethod + def nonlinear_inequality_constraint(*args): + nargin = len(args) - # create a default object - if nargin == 0: - return nonlinear_inequality_constraint() + # create a default object + if nargin == 0: + return nonlinear_inequality_constraint() - # copy the object - if nargin == 1: - if isinstance(args[0],nonlinear_inequality_constraint): - nic = args[0] - else: - raise RuntimeError('Object is a '+str(type(args[0]))+' class object, not "nonlinear_inequality_constraint".') + # copy the object + if nargin == 1: + if isinstance(args[0], nonlinear_inequality_constraint): + nic = args[0] + else: + raise RuntimeError('Object is a ' + str(type(args[0])) + ' class object, not "nonlinear_inequality_constraint".') - # not enough arguments - if nargin == 2: - raise RuntimeError('Construction of nonlinear_inequality_constraint class object requires at least 3 inputs.') + # not enough arguments + if nargin == 2: + raise RuntimeError('Construction of nonlinear_inequality_constraint class object requires at least 3 inputs.') - # create the object from the input - else: - asizec = array_size(*args[0:min(nargin,3)]) - nic = [nonlinear_inequality_constraint() for i in range(asizec[0]) for j in range(asizec[1])] + # create the object from the input + else: + asizec = array_size(*args[0:min(nargin, 3)]) + nic = [nonlinear_inequality_constraint() for i in range(asizec[0]) for j in range(asizec[1])] - for i in range(np.size(nic)): - if (np.size(args[0]) > 1): - nic[i].descriptor = args[0][i]; - else: - nic[i].descriptor = str(args[0])+string_dim(nic,i,'vector') - if (np.size(args[1]) > 1): - nic[i].lower = args[1][i] - else: - nic[i].lower = args[1] + for i in range(np.size(nic)): + if (np.size(args[0]) > 1): + nic[i].descriptor = args[0][i] + else: + nic[i].descriptor = str(args[0]) + string_dim(nic, i, 'vector') + if (np.size(args[1]) > 1): + nic[i].lower = args[1][i] + else: + nic[i].lower = args[1] - if (np.size(args[2]) > 1): - nic[i].upper = args[2][i] - else: - nic[i].upper = args[2] + if (np.size(args[2]) > 1): + nic[i].upper = args[2][i] + else: + nic[i].upper = args[2] - if (nargin >= 4): - for i in range(np.size(nic)): - if (np.size(args[3]) > 1): - nic[i].scale_type = args[3][i] - else: - nic[i].scale_type = str(args[3]) + if (nargin >= 4): + for i in range(np.size(nic)): + if (np.size(args[3]) > 1): + nic[i].scale_type = args[3][i] + else: + nic[i].scale_type = str(args[3]) - if (nargin >= 5): - for i in range(np.size(nic)): - if (np.size(args[4]) > 1): - nic[i].upper = args[4][i] - else: - nic[i].upper = args[4] - - if (nargin > 5): - print('WARNING: nonlinear_inequality_constraint:extra_arg: Extra arguments for object of class '+str(type(nic))+'.') + if (nargin >= 5): + for i in range(np.size(nic)): + if (np.size(args[4]) > 1): + nic[i].upper = args[4][i] + else: + nic[i].upper = args[4] - return nic + if (nargin > 5): + print('WARNING: nonlinear_inequality_constraint:extra_arg: Extra arguments for object of class ' + str(type(nic)) + '.') - def __repr__(self): - # display the object - string = '\n' - string += 'class "nonlinear_inequality_constraint" object = \n' - string += ' descriptor: ' +str(self.descriptor) + '\n' - string += ' lower: ' +str(self.lower) + '\n' - string += ' upper: ' +str(self.upper) + '\n' - string += ' scale_type: ' +str(self.scale_type) + '\n' - string += ' scale: ' +str(self.scale) + '\n' + return nic - return string + def __repr__(self): + # display the object + string = '\n' + string += 'class "nonlinear_inequality_constraint" object = \n' + string += ' descriptor: ' + str(self.descriptor) + '\n' + string += ' lower: ' + str(self.lower) + '\n' + string += ' upper: ' + str(self.upper) + '\n' + string += ' scale_type: ' + str(self.scale_type) + '\n' + string += ' scale: ' + str(self.scale) + '\n' - @staticmethod - def prop_desc(nic,dstr): - if type(nic) not in [list,np.ndarray]: - if nic.descriptor != '' or type(nic.descriptor) != str: - desc = str(nic.descriptor) - elif dstr != '': - desc = str(dstr) - else: - desc = 'nic' - return desc + return string - desc = ['' for i in range(np.size(nic))] - for i in range(np.size(nic)): - if nic[i].descriptor != '' or type(nic[i].descriptor) != str: - desc[i] = str(nic[i].descriptor) - elif dstr != '': - desc[i] = str(dstr)+str(string_dim(nic,i,'vector')) - else: - desc[i] = 'nic'+str(string_dim(nic,i,'vector')) - - desc = allempty(desc) + @staticmethod + def prop_desc(nic, dstr): + if type(nic) not in [list, np.ndarray]: + if nic.descriptor != '' or type(nic.descriptor) != str: + desc = str(nic.descriptor) + elif dstr != '': + desc = str(dstr) + else: + desc = 'nic' + return desc - return desc + desc = ['' for i in range(np.size(nic))] + for i in range(np.size(nic)): + if nic[i].descriptor != '' or type(nic[i].descriptor) != str: + desc[i] = str(nic[i].descriptor) + elif dstr != '': + desc[i] = str(dstr) + str(string_dim(nic, i, 'vector')) + else: + desc[i] = 'nic' + str(string_dim(nic, i, 'vector')) - @staticmethod - def prop_stype(nic): - if type(nic) not in [list,np.ndarray]: - return nic.scale_type + desc = allempty(desc) - stype = ['' for i in range(np.size(nic))] - for i in range(np.size(nic)): - stype[i] = str(nic[i].scale_type) - - stype = allequal(stype,'none') + return desc - return stype + @staticmethod + def prop_stype(nic): + if type(nic) not in [list, np.ndarray]: + return nic.scale_type - @staticmethod - def prop_scale(nic): - if type(nic) not in [list,np.ndarray]: - return nic.scale + stype = ['' for i in range(np.size(nic))] + for i in range(np.size(nic)): + stype[i] = str(nic[i].scale_type) - scale = np.zeros(np.shape(nic)) - for i in range(np.size(nic)): - scale[i] = nic[i].scale - - scale = allequal(scale,1.) + stype = allequal(stype, 'none') - return scale + return stype - @staticmethod - def prop_weight(nic): - weight=[] - return weight + @staticmethod + def prop_scale(nic): + if type(nic) not in [list, np.ndarray]: + return nic.scale - @staticmethod - def prop_lower(nic): - if type(nic) not in [list,np.ndarray]: - return nic.lower + scale = np.zeros(np.shape(nic)) + for i in range(np.size(nic)): + scale[i] = nic[i].scale - lower = np.zeros(np.shape(nic)) - for i in range(np.size(nic)): - lower[i] = nic[i].lower - - lower = allequal(lower,-np.inf) + scale = allequal(scale, 1.) - return lower + return scale - @staticmethod - def prop_upper(nic): - if type(nic) not in [list,np.ndarray]: - return nic.upper + @staticmethod + def prop_weight(nic): + weight = [] + return weight - upper = np.zeros(np.shape(nic)) - for i in range(np.size(nic)): - upper[i] = nic[i].upper - - upper = allequal(upper,0.) + @staticmethod + def prop_lower(nic): + if type(nic) not in [list, np.ndarray]: + return nic.lower - return upper + lower = np.zeros(np.shape(nic)) + for i in range(np.size(nic)): + lower[i] = nic[i].lower - @staticmethod - def prop_target(nic): - target=[] - return target - - @staticmethod - def dakota_write(fidi,dresp,rdesc): - # collect only the variables of the appropriate class - nic = [struc_class(i,'nonlinear_inequality_constraint','nic') for i in dresp] + lower = allequal(lower, - np.inf) - # write constraints - rdesc = rlist_write(fidi,'nonlinear_inequality_constrants','nonlinear_inequality',nic,rdesc) - return rdesc + return lower - @staticmethod - def dakota_rlev_write(fidi,dresp,params): - return + @staticmethod + def prop_upper(nic): + if type(nic) not in [list, np.ndarray]: + return nic.upper + + upper = np.zeros(np.shape(nic)) + for i in range(np.size(nic)): + upper[i] = nic[i].upper + + upper = allequal(upper, 0.) + + return upper + + @staticmethod + def prop_target(nic): + target = [] + return target + + @staticmethod + def dakota_write(fidi, dresp, rdesc): + # collect only the variables of the appropriate class + nic = [struc_class(i, 'nonlinear_inequality_constraint', 'nic') for i in dresp] + + # write constraints + rdesc = rlist_write(fidi, 'nonlinear_inequality_constrants', 'nonlinear_inequality', nic, rdesc) + return rdesc + + @staticmethod + def dakota_rlev_write(fidi, dresp, params): + return Index: /issm/trunk-jpl/src/m/classes/qmu/normal_uncertain.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/normal_uncertain.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/normal_uncertain.py (revision 24213) @@ -1,12 +1,12 @@ import numpy as np -#from vlist_write import * from MatlabArray import * + class normal_uncertain(object): - ''' + ''' definition for the normal_uncertain class. [nuv] = normal_uncertain.normal_uncertain(args) - nuv = normal_uncertain() + nuv = normal_uncertain() where the required args are: @@ -15,6 +15,6 @@ stddev (float, standard deviation, float('NaN')) and the optional args and defaults are: - lower (float, lower bound, -np.Inf) - upper (float, upper bound, np.Inf) + lower (float, lower bound, - np.Inf) + upper (float, upper bound, np.Inf) note that zero arguments constructs a default instance, one @@ -22,158 +22,158 @@ arguments constructs a new instance from the arguments. ''' - def __init__(self): - self.descriptor = '' - self.mean = float('NaN') - self.stddev = float('NaN') - self.lower =-np.Inf - self.upper = np.Inf + def __init__(self): + self.descriptor = '' + self.mean = float('NaN') + self.stddev = float('NaN') + self.lower = - np.Inf + self.upper = np.Inf - @staticmethod - def normal_uncertain(*args): - nargin = len(args) + @staticmethod + def normal_uncertain(*args): + nargin = len(args) - # create a default object - if nargin == 0: - return normal_uncertain() + # create a default object + if nargin == 0: + return normal_uncertain() - # copy the object - elif nargin == 1: - if isinstance(args[0],normal_uncertain): - nuv = args[0] - else: - raise RuntimeError('Object '+str(args[0])+' is a '+str(type(args[0]))+' class object, not "normal_uncertain".') + # copy the object + elif nargin == 1: + if isinstance(args[0], normal_uncertain): + nuv = args[0] + else: + raise RuntimeError('Object ' + str(args[0]) + ' is a ' + str(type(args[0])) + ' class object, not "normal_uncertain".') - # not enough arguments - elif nargin == 2: - raise RuntimeError('Construction of "normal_uncertain" class object requires at least 3 inputs.') + # not enough arguments + elif nargin == 2: + raise RuntimeError('Construction of "normal_uncertain" class object requires at least 3 inputs.') - # create the object from the input - else: - # lines differ here in other classes/tests; see asizec problem in notes - nuv=normal_uncertain() - nuv.descriptor = str(args[0]) - nuv.mean = args[1] - nuv.stddev = args[2] - if nargin >= 4: - nuv.lower = args[3] - if nargin >= 5: - nuv.upper = args[4] - if nargin > 5: - print('WARNING: normal_uncertain:extra_arg: Extra arguments for object of class '+str(type(nuv))+'.') + # create the object from the input + else: + # lines differ here in other classes / tests; see asizec problem in notes + nuv = normal_uncertain() + nuv.descriptor = str(args[0]) + nuv.mean = args[1] + nuv.stddev = args[2] + if nargin >= 4: + nuv.lower = args[3] + if nargin >= 5: + nuv.upper = args[4] + if nargin > 5: + print('WARNING: normal_uncertain:extra_arg: Extra arguments for object of class ' + str(type(nuv)) + '.') - return [nuv] + return [nuv] - def __repr__(self): - # display an individual object - string = '\n' - string += 'class "normal_uncertain" object = \n' - string += ' descriptor: '+str(self.descriptor) + '\n' - string += ' mean: '+str(self.mean) + '\n' - string += ' stddev: '+str(self.stddev) + '\n' - string += ' lower: '+str(self.lower) + '\n' - string += ' upper: '+str(self.upper) + '\n' + def __repr__(self): + # display an individual object + string = '\n' + string += 'class "normal_uncertain" object = \n' + string += ' descriptor: ' + str(self.descriptor) + '\n' + string += ' mean: ' + str(self.mean) + '\n' + string += ' stddev: ' + str(self.stddev) + '\n' + string += ' lower: ' + str(self.lower) + '\n' + string += ' upper: ' + str(self.upper) + '\n' - return string + return string - # from here on, nuv is either a single, or a 1d vector of, normal_uncertain + # from here on, nuv is either a single, or a 1d vector of, normal_uncertain - @staticmethod - def prop_desc(nuv,dstr): - if type(nuv) not in [list,np.ndarray]: - if nuv.descriptor != '' or type(nuv.descriptor) != str: - desc = str(nuv.descriptor) - elif dstr != '': - desc = str(dstr) - else: - desc = 'nuv' - return desc + @staticmethod + def prop_desc(nuv, dstr): + if type(nuv) not in [list, np.ndarray]: + if nuv.descriptor != '' or type(nuv.descriptor) != str: + desc = str(nuv.descriptor) + elif dstr != '': + desc = str(dstr) + else: + desc = 'nuv' + return desc - desc = ['' for i in range(np.size(nuv))] - for i in range(np.size(nuv)): - if nuv[i].descriptor != '' or type(nuv[i].descriptor) != str: - desc[i] = str(nuv[i].descriptor) - elif dstr != '': - desc[i] = str(dstr)+str(string_dim(nuv,i,'vector')) - else: - desc[i] = 'nuv'+str(string_dim(nuv,i,'vector')) + desc = ['' for i in range(np.size(nuv))] + for i in range(np.size(nuv)): + if nuv[i].descriptor != '' or type(nuv[i].descriptor) != str: + desc[i] = str(nuv[i].descriptor) + elif dstr != '': + desc[i] = str(dstr) + str(string_dim(nuv, i, 'vector')) + else: + desc[i] = 'nuv' + str(string_dim(nuv, i, 'vector')) - desc = allempty(desc) + desc = allempty(desc) - return desc + return desc - @staticmethod - def prop_initpt(nuv): - initpt=[] - return initpt + @staticmethod + def prop_initpt(nuv): + initpt = [] + return initpt - @staticmethod - def prop_lower(nuv): - if type(nuv) not in [list,np.ndarray]: - return nuv.lower + @staticmethod + def prop_lower(nuv): + if type(nuv) not in [list, np.ndarray]: + return nuv.lower - lower = np.zeros(np.size(nuv)) - for i in range(np.size(nuv)): - lower[i] = nuv[i].lower + lower = np.zeros(np.size(nuv)) + for i in range(np.size(nuv)): + lower[i] = nuv[i].lower - lower = allequal(lower,-np.inf) + lower = allequal(lower, - np.inf) - return lower + return lower - @staticmethod - def prop_upper(nuv): - if type(nuv) not in [list,np.ndarray]: - return nuv.upper + @staticmethod + def prop_upper(nuv): + if type(nuv) not in [list, np.ndarray]: + return nuv.upper - upper = np.zeros(np.size(nuv)) - for i in range(np.size(nuv)): - upper[i] = nuv[i].upper + upper = np.zeros(np.size(nuv)) + for i in range(np.size(nuv)): + upper[i] = nuv[i].upper - upper = allequal(upper,-np.inf) - return upper + upper = allequal(upper, - np.inf) + return upper - @staticmethod - def prop_mean(nuv): - if type(nuv) not in [list,np.ndarray]: - return nuv.mean + @staticmethod + def prop_mean(nuv): + if type(nuv) not in [list, np.ndarray]: + return nuv.mean - mean = np.zeros(np.size(nuv)) - for i in range(np.size(nuv)): - mean[i] = nuv[i].mean + mean = np.zeros(np.size(nuv)) + for i in range(np.size(nuv)): + mean[i] = nuv[i].mean - return mean + return mean - @staticmethod - def prop_stddev(nuv): - if type(nuv) not in [list,np.ndarray]: - return nuv.stddev + @staticmethod + def prop_stddev(nuv): + if type(nuv) not in [list, np.ndarray]: + return nuv.stddev - stddev = np.zeros(np.size(nuv)) - for i in range(np.size(nuv)): - stddev[i] = nuv[i].stddev + stddev = np.zeros(np.size(nuv)) + for i in range(np.size(nuv)): + stddev[i] = nuv[i].stddev - return stddev + return stddev - @staticmethod - def prop_initst(nuv): - initst=[] - return initst + @staticmethod + def prop_initst(nuv): + initst = [] + return initst - @staticmethod - def prop_stype(nuv): - stype=[] - return stype + @staticmethod + def prop_stype(nuv): + stype = [] + return stype - @staticmethod - def prop_scale(nuv): - scale=[] - return scale + @staticmethod + def prop_scale(nuv): + scale = [] + return scale - @staticmethod - def dakota_write(fidi,dvar): - # collect only the variables of the appropriate class - nuv = [struc_class(i,'normal_uncertain','nuv') for i in dvar] + @staticmethod + def dakota_write(fidi, dvar): + # collect only the variables of the appropriate class + nuv = [struc_class(i, 'normal_uncertain', 'nuv') for i in dvar] - # possible namespace pollution, the above import seems not to work - from vlist_write import vlist_write - # write variables - vlist_write(fidi,'normal_uncertain','nuv',nuv) + # possible namespace pollution, the above import seems not to work + from vlist_write import vlist_write + # write variables + vlist_write(fidi, 'normal_uncertain', 'nuv', nuv) Index: /issm/trunk-jpl/src/m/classes/qmu/objective_function.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/objective_function.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/objective_function.py (revision 24213) @@ -3,10 +3,11 @@ from MatlabArray import * + class objective_function(object): - ''' + ''' definition for the objective_function class. [of] = objective_function.objective_function(args) - of = objective_function() + of = objective_function() where the required args are: @@ -21,153 +22,152 @@ arguments constructs a new instance from the arguments. ''' - def __init__(self): - self.descriptor = '' - self.scale_type = 'none' - self.scale = 1. - self.weight = 1. + def __init__(self): + self.descriptor = '' + self.scale_type = 'none' + self.scale = 1. + self.weight = 1. - @staticmethod - def objective_function(*args): - nargin = len(args) + @staticmethod + def objective_function(*args): + nargin = len(args) - # create a default object - if nargin == 0: - return objective_function() + # create a default object + if nargin == 0: + return objective_function() - # copy the object or create the object from the input - else: - if (nargin == 1) and isinstance(args[0],objective_function): - of = args[0] - else: - shapec = array_size(*args[0:min(nargin,4)]) - of = [objective_function() for i in range(shapec[0]) for j in range(shapec[1])] + # copy the object or create the object from the input + else: + if (nargin == 1) and isinstance(args[0], objective_function): + of = args[0] + else: + shapec = array_size(*args[0:min(nargin, 4)]) + of = [objective_function() for i in range(shapec[0]) for j in range(shapec[1])] - for i in range(np.size(of)): - if (np.size(args[0]) > 1): - of[i].descriptor = args[0][i] - else: - of[i].descriptor = str(args[0])+string_dim(of,i,'vector') + for i in range(np.size(of)): + if (np.size(args[0]) > 1): + of[i].descriptor = args[0][i] + else: + of[i].descriptor = str(args[0]) + string_dim(of, i, 'vector') - if (nargin >= 2): - for i in range(np.size(of)): - if (np.size(args[1]) > 1): - of[i].scale_type = args[1][i] - else: - of[i].scale_type = str(args[1]) + if (nargin >= 2): + for i in range(np.size(of)): + if (np.size(args[1]) > 1): + of[i].scale_type = args[1][i] + else: + of[i].scale_type = str(args[1]) - if (nargin >= 3): - for i in range(np.size(of)): - if (np.size(args[2]) > 1): - of[i].scale = args[2][i] - else: - of[i].scale = args[2] + if (nargin >= 3): + for i in range(np.size(of)): + if (np.size(args[2]) > 1): + of[i].scale = args[2][i] + else: + of[i].scale = args[2] - if (nargin >= 4): - for i in range(np.size(of)): - if (np.size(args[3]) > 1): - of[i].weight = args[3][i] - else: - of[i].weight = args[3] + if (nargin >= 4): + for i in range(np.size(of)): + if (np.size(args[3]) > 1): + of[i].weight = args[3][i] + else: + of[i].weight = args[3] - if (nargin > 4): - print('WARNING: objective_function:extra_arg Extra arguments for object of class '+str(type(of))+'.') + if (nargin > 4): + print('WARNING: objective_function:extra_arg Extra arguments for object of class ' + str(type(of)) + '.') - return of + return of + def __repr__(self): + # display the object + string = '\n' + string += 'class "objective_function" object = \n' + string += ' descriptor: ' + str(self.descriptor) + '\n' + string += ' scale_type: ' + str(self.scale_type) + '\n' + string += ' scale: ' + str(self.scale) + '\n' + string += ' weight: ' + str(self.weight) + '\n' + return string - def __repr__(self): - # display the object - string = '\n' - string += 'class "objective_function" object = \n' - string += ' descriptor: ' +str(self.descriptor) + '\n' - string += ' scale_type: ' +str(self.scale_type) + '\n' - string += ' scale: ' +str(self.scale) + '\n' - string += ' weight: ' +str(self.weight) + '\n' - return string + @staticmethod + def prop_desc(of, dstr): + if type(of) not in [list, np.ndarray]: + if of.descriptor != '' or type(of.descriptor) != str: + desc = str(of.descriptor) + elif dstr != '': + desc = str(dstr) + else: + desc = 'of' + return desc - @staticmethod - def prop_desc(of,dstr): - if type(of) not in [list,np.ndarray]: - if of.descriptor != '' or type(of.descriptor) != str: - desc = str(of.descriptor) - elif dstr != '': - desc = str(dstr) - else: - desc = 'of' - return desc + desc = ['' for i in range(np.size(of))] + for i in range(np.size(of)): + if of[i].descriptor != '' or type(of[i].descriptor) != str: + desc[i] = str(of[i].descriptor) + elif dstr != '': + desc[i] = str(dstr) + str(string_dim(of, i, 'vector')) + else: + desc[i] = 'of' + str(string_dim(of, i, 'vector')) - desc = ['' for i in range(np.size(of))] - for i in range(np.size(of)): - if of[i].descriptor != '' or type(of[i].descriptor) != str: - desc[i] = str(of[i].descriptor) - elif dstr != '': - desc[i] = str(dstr)+str(string_dim(of,i,'vector')) - else: - desc[i] = 'of'+str(string_dim(of,i,'vector')) + desc = allempty(desc) + return desc - desc = allempty(desc) - return desc + @staticmethod + def prop_lower(of): + lower = [] + return lower - @staticmethod - def prop_lower(of): - lower=[] - return lower + @staticmethod + def prop_upper(of): + upper = [] + return upper - @staticmethod - def prop_upper(of): - upper=[] - return upper + @staticmethod + def prop_target(of): + target = [] + return target - @staticmethod - def prop_target(of): - target=[] - return target + @staticmethod + def prop_weight(of): + if type(of) not in [list, np.ndarray]: + return of.weight - @staticmethod - def prop_weight(of): - if type(of) not in [list,np.ndarray]: - return of.weight + weight = np.zeros(np.shape(of)) + for i in range(np.size(of)): + weight[i] = of[i].weight - weight = np.zeros(np.shape(of)) - for i in range(np.size(of)): - weight[i] = of[i].weight + weight = allequal(weight, 1.) + return weight - weight = allequal(weight,1.) - return weight + @staticmethod + def prop_stype(of): + if type(of) not in [list, np.ndarray]: + return of.scale_type - @staticmethod - def prop_stype(of): - if type(of) not in [list,np.ndarray]: - return of.scale_type + stype = ['' for i in range(np.size(of))] + for i in range(np.size(of)): + stype[i] = str(of[i].scale_type) - stype = ['' for i in range(np.size(of))] - for i in range(np.size(of)): - stype[i] = str(of[i].scale_type) + stype = allequal(stype, 'none') + return stype - stype = allequal(stype,'none') - return stype + @staticmethod + def prop_scale(of): + if type(of) not in [list, np.ndarray]: + return of.scale - @staticmethod - def prop_scale(of): - if type(of) not in [list,np.ndarray]: - return of.scale + scale = np.zeros(np.shape(of)) + for i in range(np.size(of)): + scale[i] = of[i].scale - scale = np.zeros(np.shape(of)) - for i in range(np.size(of)): - scale[i] = of[i].scale + scale = allequal(scale, 1.) + return scale - scale = allequal(scale,1.) - return scale + @staticmethod + def dakota_write(fidi, dresp, rdesc): + # coloft only the variables of the appropriate class + of = [struc_class(i, 'objective_functions', 'of') for i in dresp] - @staticmethod - def dakota_write(fidi,dresp,rdesc): - # coloft only the variables of the appropriate class - of = [struc_class(i,'objective_functions','of') for i in dresp] + # write constraints + rdesc = rlist_write(fidi, 'objective_functions', 'objective_function', of, rdesc) + return rdesc - # write constraints - rdesc = rlist_write(fidi,'objective_functions','objective_function',of,rdesc) - return rdesc - - @staticmethod - def dakota_rlev_write(fidi,dresp,params): - return + @staticmethod + def dakota_rlev_write(fidi, dresp, params): + return Index: /issm/trunk-jpl/src/m/classes/qmu/response_function.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/response_function.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/response_function.py (revision 24213) @@ -3,14 +3,14 @@ from rlev_write import * from MatlabArray import * - #move this later from helpers import * + class response_function(object): - ''' + ''' definition for the response_function class. [rf] = response_function.response_function(args) - rf = response_function() + rf = response_function() where the required args are: @@ -27,159 +27,159 @@ ''' - def __init__(self): - self.descriptor = '' - self.respl = [] - self.probl = [] - self.rell = [] - self.grell = [] + def __init__(self): + self.descriptor = '' + self.respl = [] + self.probl = [] + self.rell = [] + self.grell = [] - @staticmethod - def response_function(*args): + @staticmethod + def response_function(*args): - nargin = len(args) - # create a default object - if nargin == 0: - return response_function() + nargin = len(args) + # create a default object + if nargin == 0: + return response_function() - # copy the object or create the object from the input - else: - if nargin == 1 and isinstance(args[0],response_function): - rf = args[0] - else: - asizec = array_size(*args[0:min(nargin,1)]) - rf = [response_function() for i in range(asizec[0]) for j in range(asizec[1])] + # copy the object or create the object from the input + else: + if nargin == 1 and isinstance(args[0], response_function): + rf = args[0] + else: + asizec = array_size(*args[0:min(nargin, 1)]) + rf = [response_function() for i in range(asizec[0]) for j in range(asizec[1])] - for i in range(np.size(rf)): - if (np.size(args[0]) > 1): - rf[i].descriptor = args[0][i] - else: - rf[i].descriptor = str(args[0])+string_dim(rf,i,'vector') + for i in range(np.size(rf)): + if (np.size(args[0]) > 1): + rf[i].descriptor = args[0][i] + else: + rf[i].descriptor = str(args[0]) + string_dim(rf, i, 'vector') - if nargin >= 2: - for i in range(np.size(rf)): - rf[i].respl = args[1] + if nargin >= 2: + for i in range(np.size(rf)): + rf[i].respl = args[1] - if nargin >= 3: - for i in range(np.size(rf)): - rf[i].probl = args[2] + if nargin >= 3: + for i in range(np.size(rf)): + rf[i].probl = args[2] - if nargin >= 4: - for i in range(np.size(rf)): - rf[i].rell = args[3] + if nargin >= 4: + for i in range(np.size(rf)): + rf[i].rell = args[3] - if nargin >= 5: - for i in range(np.size(rf)): - rf[i].grell = args[4] + if nargin >= 5: + for i in range(np.size(rf)): + rf[i].grell = args[4] - if nargin > 5: - print('WARNING: response_function:extra_arg: Extra arguments for object of class '+str(type(rf))+'.') + if nargin > 5: + print('WARNING: response_function:extra_arg: Extra arguments for object of class ' + str(type(rf)) + '.') - return rf + return rf - def __repr__(self): - # display the object - string = '\n' - string += 'class "response_function" object = \n' - string += ' descriptor: ' +str(self.descriptor) + '\n' - string += ' respl: ' +str(self.respl) + '\n' - string += ' probl: ' +str(self.probl) + '\n' - string += ' rell: ' +str(self.rell) + '\n' - string += ' grell: ' +str(self.grell) + '\n' + def __repr__(self): + # display the object + string = '\n' + string += 'class "response_function" object = \n' + string += ' descriptor: ' + str(self.descriptor) + '\n' + string += ' respl: ' + str(self.respl) + '\n' + string += ' probl: ' + str(self.probl) + '\n' + string += ' rell: ' + str(self.rell) + '\n' + string += ' grell: ' + str(self.grell) + '\n' - return string + return string - def __len__(self): - return max(len(self.respl),len(self.probl),len(self.rell),len(self.grell)) + def __len__(self): + return max(len(self.respl), len(self.probl), len(self.rell), len(self.grell)) - # from here on, rf is either a single, or a 1d vector of, response_function + # from here on, rf is either a single, or a 1d vector of, response_function - @staticmethod - def prop_desc(rf,dstr): - # response_function is always a vector, or should be, even with just 1 - if type(rf) not in [list,np.ndarray]: - rf = [rf] + @staticmethod + def prop_desc(rf, dstr): + # response_function is always a vector, or should be, even with just 1 + if type(rf) not in [list, np.ndarray]: + rf = [rf] - desc = ['' for i in range(np.size(rf))] - for i in range(np.size(rf)): - if rf[i].descriptor != '' or type(rf[i].descriptor) != str: - desc[i] = str(rf[i].descriptor) - elif dstr != '': - desc[i] = str(dstr)+str(string_dim(rf,i,'vector')) - else: - desc[i] = 'rf'+str(string_dim(rf,i,'vector')) + desc = ['' for i in range(np.size(rf))] + for i in range(np.size(rf)): + if rf[i].descriptor != '' or type(rf[i].descriptor) != str: + desc[i] = str(rf[i].descriptor) + elif dstr != '': + desc[i] = str(dstr) + str(string_dim(rf, i, 'vector')) + else: + desc[i] = 'rf' + str(string_dim(rf, i, 'vector')) - desc = allempty(desc) - return desc + desc = allempty(desc) + return desc - @staticmethod - def prop_stype(rf): - stype=[] - return stype + @staticmethod + def prop_stype(rf): + stype = [] + return stype - @staticmethod - def prop_scale(rf): - scale=[] - return scale + @staticmethod + def prop_scale(rf): + scale = [] + return scale - @staticmethod - def prop_weight(rf): - weight=[] - return weight + @staticmethod + def prop_weight(rf): + weight = [] + return weight - @staticmethod - def prop_lower(rf): - lower=[] - return lower + @staticmethod + def prop_lower(rf): + lower = [] + return lower - @staticmethod - def prop_upper(rf): - upper=[] - return upper + @staticmethod + def prop_upper(rf): + upper = [] + return upper - @staticmethod - def prop_target(rf): - target=[] - return target + @staticmethod + def prop_target(rf): + target = [] + return target - @staticmethod - def prop_levels(rf): - # response_function is always a vector, or should be, even with just 1 - if type(rf) not in [list,np.ndarray]: - rf = [rf] + @staticmethod + def prop_levels(rf): + # response_function is always a vector, or should be, even with just 1 + if type(rf) not in [list, np.ndarray]: + rf = [rf] - respl = empty_nd_list(np.size(rf)) - probl = empty_nd_list(np.size(rf)) - rell = empty_nd_list(np.size(rf)) - grell = empty_nd_list(np.size(rf)) + respl = empty_nd_list(np.size(rf)) + probl = empty_nd_list(np.size(rf)) + rell = empty_nd_list(np.size(rf)) + grell = empty_nd_list(np.size(rf)) - for i in range(np.size(rf)): - respl[i] = rf[i].respl - probl[i] = rf[i].probl - rell [i] = rf[i].rell - grell[i] = rf[i].grell + for i in range(np.size(rf)): + respl[i] = rf[i].respl + probl[i] = rf[i].probl + rell[i] = rf[i].rell + grell[i] = rf[i].grell - respl = allempty(respl) - probl = allempty(probl) - rell = allempty(rell) - grell = allempty(grell) - return [respl,probl,rell,grell] + respl = allempty(respl) + probl = allempty(probl) + rell = allempty(rell) + grell = allempty(grell) + return [respl, probl, rell, grell] - @staticmethod - def dakota_write(fidi,dresp,rdesc): - # collect only the responses of the appropriate class - rf = [struc_class(vars(dresp)[i][j],'response_function','rf') for i in fieldnames(dresp) for j in range(len(vars(dresp)[i]))] + @staticmethod + def dakota_write(fidi, dresp, rdesc): + # collect only the responses of the appropriate class + rf = [struc_class(vars(dresp)[i][j], 'response_function', 'rf') for i in fieldnames(dresp) for j in range(len(vars(dresp)[i]))] - #possible namespace pollution here - from rlist_write import rlist_write - # write responses - rdesc = rlist_write(fidi,'response_function','rf',rf,rdesc) + #possible namespace pollution here + from rlist_write import rlist_write + # write responses + rdesc = rlist_write(fidi, 'response_function', 'rf', rf, rdesc) - return rdesc + return rdesc - @staticmethod - def dakota_rlev_write(fidi,dresp,params): - # collect only the responses of the appropriate class - rf = [struc_class(vars(dresp)[i][j],'response_function','rf') for i in fieldnames(dresp) for j in range(len(vars(dresp)[i]))] + @staticmethod + def dakota_rlev_write(fidi, dresp, params): + # collect only the responses of the appropriate class + rf = [struc_class(vars(dresp)[i][j], 'response_function', 'rf') for i in fieldnames(dresp) for j in range(len(vars(dresp)[i]))] - # write response levels - rlev_write(fidi,rf,'response_function',params) + # write response levels + rlev_write(fidi, rf, 'response_function', params) Index: /issm/trunk-jpl/src/m/classes/qmu/uniform_uncertain.py =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/uniform_uncertain.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/qmu/uniform_uncertain.py (revision 24213) @@ -3,15 +3,16 @@ from MatlabArray import * + class uniform_uncertain(object): - ''' + ''' definition for the uniform_uncertain class. [uuv] = uniform_uncertain.uniform_uncertain(args) - uuv = uniform_uncertain() + uuv = uniform_uncertain() where the required args are: descriptor (str, description, '') - lower (float, lower bound, -np.Inf) - upper (float, upper bound, np.Inf) + lower (float, lower bound, - np.Inf) + upper (float, upper bound, np.Inf) note that zero arguments constructs a default instance, one @@ -20,140 +21,140 @@ ''' - def __init__(self): - self.descriptor = '' - self.lower = -np.Inf - self.upper = np.Inf + def __init__(self): + self.descriptor = '' + self.lower = - np.Inf + self.upper = np.Inf - @staticmethod - def uniform_uncertain(*args): - nargin = len(args) + @staticmethod + def uniform_uncertain(*args): + nargin = len(args) - # create a default object - if nargin == 0: - return uniform_uncertain() + # create a default object + if nargin == 0: + return uniform_uncertain() - # copy the object - elif nargin == 1: - if isinstance(args[0],uniform_uncertain): - uuv = args[0] - else: - raise RuntimeError('Object '+str(args[0])+' is a '+str(type(args[0]))+' class object, not "uniform_uncertain".') + # copy the object + elif nargin == 1: + if isinstance(args[0], uniform_uncertain): + uuv = args[0] + else: + raise RuntimeError('Object ' + str(args[0]) + ' is a ' + str(type(args[0])) + ' class object, not "uniform_uncertain".') - # not enough arguments - elif nargin == 2: - raise RuntimeError('Construction of "uniform_uncertain" class object requires at least 3 inputs.') + # not enough arguments + elif nargin == 2: + raise RuntimeError('Construction of "uniform_uncertain" class object requires at least 3 inputs.') - # create the object from the input - else: - # leaving this here in case it becomes important in the future - #asizec=array_size(*args[0:min(nargin,3)]) - #uuv = [uniform_uncertain() for i in range(asizec[0]) for j in range(asizec[1])] - uuv = uniform_uncertain() - uuv.descriptor = str(args[0]) - uuv.lower = args[1] - uuv.upper = args[2] - if (nargin > 3): - print('WARNING: uniform_uncertain:extra_arg: Extra arguments for object of class '+type(uuv)+'.') + # create the object from the input + else: + # leaving this here in case it becomes important in the future + #asizec = array_size(*args[0:min(nargin, 3)]) + #uuv = [uniform_uncertain() for i in range(asizec[0]) for j in range(asizec[1])] + uuv = uniform_uncertain() + uuv.descriptor = str(args[0]) + uuv.lower = args[1] + uuv.upper = args[2] + if (nargin > 3): + print('WARNING: uniform_uncertain:extra_arg: Extra arguments for object of class ' + type(uuv) + '.') - return [uuv] + return [uuv] - def __repr__(self): - # display an individual object - string = '\n' - string += 'class "uniform_uncertain" object = \n' - string += ' descriptor: ' + str(self.descriptor) + '\n' - string += ' lower: ' + str(self.lower) + '\n' - string += ' upper: ' + str(self.upper) + '\n' + def __repr__(self): + # display an individual object + string = '\n' + string += 'class "uniform_uncertain" object = \n' + string += ' descriptor: ' + str(self.descriptor) + '\n' + string += ' lower: ' + str(self.lower) + '\n' + string += ' upper: ' + str(self.upper) + '\n' - return string + return string - # from here on, uuv is either a single, or a 1d vector of, uniform_uncertain + # from here on, uuv is either a single, or a 1d vector of, uniform_uncertain - @staticmethod - def prop_desc(uuv,dstr): - if type(uuv) not in [list,np.ndarray]: - if uuv.descriptor != '' or type(uuv.descriptor) != str: - desc = str(uuv.descriptor) - elif dstr != '': - desc = str(dstr) - else: - desc = 'uuv' - return desc + @staticmethod + def prop_desc(uuv, dstr): + if type(uuv) not in [list, np.ndarray]: + if uuv.descriptor != '' or type(uuv.descriptor) != str: + desc = str(uuv.descriptor) + elif dstr != '': + desc = str(dstr) + else: + desc = 'uuv' + return desc - desc = ['' for i in range(np.size(uuv))] - for i in range(np.size(uuv)): - if uuv[i].descriptor != '' or type(uuv[i].descriptor) != str: - desc[i] = str(uuv[i].descriptor) - elif dstr != '': - desc[i] = str(dstr)+str(string_dim(uuv,i,'vector')) - else: - desc[i] = 'uuv'+str(string_dim(uuv,i,'vector')) + desc = ['' for i in range(np.size(uuv))] + for i in range(np.size(uuv)): + if uuv[i].descriptor != '' or type(uuv[i].descriptor) != str: + desc[i] = str(uuv[i].descriptor) + elif dstr != '': + desc[i] = str(dstr) + str(string_dim(uuv, i, 'vector')) + else: + desc[i] = 'uuv' + str(string_dim(uuv, i, 'vector')) - desc = allempty(desc) + desc = allempty(desc) - return desc + return desc - @staticmethod - def prop_initpt(uuv): - initpt=[] - return initpt + @staticmethod + def prop_initpt(uuv): + initpt = [] + return initpt - @staticmethod - def prop_lower(uuv): - if type(uuv) not in [list,np.ndarray]: - return uuv.lower + @staticmethod + def prop_lower(uuv): + if type(uuv) not in [list, np.ndarray]: + return uuv.lower - lower = np.zeros(np.size(uuv)) - for i in range(np.size(uuv)): - lower[i] = uuv[i].lower + lower = np.zeros(np.size(uuv)) + for i in range(np.size(uuv)): + lower[i] = uuv[i].lower - lower = allequal(lower,-np.Inf) + lower = allequal(lower, - np.Inf) - return lower + return lower - @staticmethod - def prop_upper(uuv): - if type(uuv) not in [list,np.ndarray]: - return uuv.upper + @staticmethod + def prop_upper(uuv): + if type(uuv) not in [list, np.ndarray]: + return uuv.upper - upper = np.zeros(np.size(uuv)) - for i in range(np.size(uuv)): - upper[i] = uuv[i].upper + upper = np.zeros(np.size(uuv)) + for i in range(np.size(uuv)): + upper[i] = uuv[i].upper - upper = allequal(upper, np.Inf) + upper = allequal(upper, np.Inf) - return upper + return upper - @staticmethod - def prop_mean(uuv): - mean=[] - return mean + @staticmethod + def prop_mean(uuv): + mean = [] + return mean - @staticmethod - def prop_stddev(uuv): - stddev=[] - return stddev + @staticmethod + def prop_stddev(uuv): + stddev = [] + return stddev - @staticmethod - def prop_initst(uuv): - initst=[] - return initst + @staticmethod + def prop_initst(uuv): + initst = [] + return initst - @staticmethod - def prop_stype(uuv): - stype=[] - return stype + @staticmethod + def prop_stype(uuv): + stype = [] + return stype - @staticmethod - def prop_scale(uuv): - scale=[] - return scale + @staticmethod + def prop_scale(uuv): + scale = [] + return scale - @staticmethod - def dakota_write(fidi,dvar): - # collect only the variables of the appropriate class - uuv = [struc_class(i,'uniform_uncertain','uuv') for i in dvar] - # possible namespace pollution, the above import seems not to work - from vlist_write import vlist_write - # write variables - vlist_write(fidi,'uniform_uncertain','uuv',uuv) + @staticmethod + def dakota_write(fidi, dvar): + # collect only the variables of the appropriate class + uuv = [struc_class(i, 'uniform_uncertain', 'uuv') for i in dvar] + # possible namespace pollution, the above import seems not to work + from vlist_write import vlist_write + # write variables + vlist_write(fidi, 'uniform_uncertain', 'uuv', uuv) Index: /issm/trunk-jpl/src/m/classes/radaroverlay.py =================================================================== --- /issm/trunk-jpl/src/m/classes/radaroverlay.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/radaroverlay.py (revision 24213) @@ -1,29 +1,32 @@ from fielddisplay import fielddisplay + class radaroverlay(object): - """ - RADAROVERLAY class definition + """ + RADAROVERLAY class definition - Usage: - radaroverlay=radaroverlay(); - """ + Usage: + radaroverlay = radaroverlay() + """ - def __init__(self): # {{{ - self.pwr = float('NaN') - self.x = float('NaN') - self.y = float('NaN') + def __init__(self): # {{{ + self.pwr = float('NaN') + self.x = float('NaN') + self.y = float('NaN') - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' radaroverlay parameters:' - string="%s\n%s"%(string,fielddisplay(self,'pwr','radar power image (matrix)')) - string="%s\n%s"%(string,fielddisplay(self,'x','corresponding x coordinates [m]')) - string="%s\n%s"%(string,fielddisplay(self,'y','corresponding y coordinates [m]')) - return string - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} + #}}} + + def __repr__(self): # {{{ + string = ' radaroverlay parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'pwr', 'radar power image (matrix)')) + string = "%s\n%s" % (string, fielddisplay(self, 'x', 'corresponding x coordinates [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'y', 'corresponding y coordinates [m]')) + return string + #}}} + + def setdefaultparameters(self): # {{{ + return self + #}}} Index: /issm/trunk-jpl/src/m/classes/regionaloutput.py =================================================================== --- /issm/trunk-jpl/src/m/classes/regionaloutput.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/regionaloutput.py (revision 24213) @@ -4,106 +4,109 @@ from checkfield import checkfield from WriteData import WriteData -from MeshProfileIntersection import MeshProfileIntersection from ContourToMesh import ContourToMesh import numpy as np import os + class regionaloutput(object): - """ - REGIONALOUTPUT class definition - - Usage: - regionaloutput=regionaloutput(); - regionaloutput=regionaloutput('name','Volume1','definitionstring','Outputdefinition1','outputnamestring','IceVolume','mask',mask); - regionaloutput=regionaloutput('name','Volume1','definitionstring','Outputdefinition1','outputnamestring','IceVolume','maskexpstring','Exp/Mask.exp','model',md) - - where mask is a vectorial field of size md.mesh.numberofvertices,1 : where vertices with values > 1 are to be included in the calculated region. - Alternatively, the user can pass in an Argus file and model object instead of a mask, and mask will be calculated for the user - """ + """ + REGIONALOUTPUT class definition - def __init__(self,*args): # {{{ + Usage: + regionaloutput = regionaloutput() + regionaloutput = regionaloutput('name', 'Volume1', 'definitionstring', 'Outputdefinition1', 'outputnamestring', 'IceVolume', 'mask', mask) + regionaloutput = regionaloutput('name', 'Volume1', 'definitionstring', 'Outputdefinition1', 'outputnamestring', 'IceVolume', 'maskexpstring', 'Exp/Mask.exp', 'model', md) - self.name = '' - self.definitionstring = '' - self.outputnamestring = '' - self.mask = float('NaN') - self.maskexpstring = '' + where mask is a vectorial field of size md.mesh.numberofvertices, 1 : where vertices with values > 1 are to be included in the calculated region. + Alternatively, the user can pass in an Argus file and model object instead of a mask, and mask will be calculated for the user + """ - #set defaults - self.setdefaultparameters() + def __init__(self, *args): # {{{ - #use provided options to change fields - options=pairoptions(*args) + self.name = '' + self.definitionstring = '' + self.outputnamestring = '' + self.mask = float('NaN') + self.maskexpstring = '' - #OK get other fields - self=options.AssignObjectFields(self) + #set defaults + self.setdefaultparameters() - #get name - if options.getfieldvalue('model',0): - if options.getfieldvalue('maskexpstring',0): - modelname=options.getfieldvalue('model') - self.maskexpstring=options.getfieldvalue('maskexpstring') - self.setmaskfromexp(modelname) - - if (len(self.mask)<=1 & np.any(np.isnan(self.mask))): - error('regionaloutput error message: ''mask'' field or ''maskexpstring'' and ''model'' fields should be defined!'); + #use provided options to change fields + options = pairoptions(*args) - #}}} - def __repr__(self): # {{{ + #OK get other fields + self = options.AssignObjectFields(self) - string=" Regionaloutput:" - string="%s\n%s"%(string,fielddisplay(self,'name','identifier for this regional response')) - string="%s\n%s"%(string,fielddisplay(self,'definitionstring','string that identifies this output definition uniquely, from Outputdefinition[1-100]')) - string="%s\n%s"%(string,fielddisplay(self,'outputnamestring','string that identifies the type of output you want, eg. IceVolume, TotalSmb, GroudedArea')) - string="%s\n%s"%(string,fielddisplay(self,'mask','mask vectorial field which identifies the region of interest (value > 0 will be included)')) - string="%s\n%s"%(string,fielddisplay(self,'maskexpstring','name of Argus file that can be passed in to define the regional mask')) - return string - #}}} - def extrude(self,md): # {{{ - self.mask=project3d(md,'vector',self.mask,'type','node') - return self - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} - def setmaskfromexp(self,md): # {{{ - if len(self.maskexpstring) > 0: - self.mask=ContourToMesh(md.mesh.elements,md.mesh.x,md.mesh.y,self.maskexpstring,'node',1) - - return self - # }}} - def checkconsistency(self,md,solution,analyses): # {{{ - - if not isinstance(self.name, str): - raise RuntimeError("regionaloutput error message: 'name' field should be a string!") - - if not isinstance(self.outputnamestring, str): - raise RuntimeError("regionaloutput error message: 'outputnamestring' field should be a string!") - - if len(self.maskexpstring) > 0: - if not os.path.isfile(self.maskexpstring): - raise RuntimeError("regionaloutput error message: file name for mask exp does not point to a legitimate file on disk!") - else: - self.setmaskfromexp(md) + #get name + if options.getfieldvalue('model', 0): + if options.getfieldvalue('maskexpstring', 0): + modelname = options.getfieldvalue('model') + self.maskexpstring = options.getfieldvalue('maskexpstring') + self.setmaskfromexp(modelname) - OutputdefinitionStringArray=[] - for i in range(1,100): - x='Outputdefinition'+str(i) - OutputdefinitionStringArray.append(x) + if (len(self.mask) <= 1 & np.any(np.isnan(self.mask))): + error('regionaloutput error message: ''mask'' field or ''maskexpstring'' and ''model'' fields should be defined!') - md = checkfield(md,'field',self.definitionstring,'values',OutputdefinitionStringArray) - md = checkfield(md,'field',self.mask,'size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + #}}} - #before marshalling, make sure mask is set: - self.setmaskfromexp(md) + def __repr__(self): # {{{ + string = " Regionaloutput:" + string = "%s\n%s" % (string, fielddisplay(self, 'name', 'identifier for this regional response')) + string = "%s\n%s" % (string, fielddisplay(self, 'definitionstring', 'string that identifies this output definition uniquely, from Outputdefinition[1 - 100]')) + string = "%s\n%s" % (string, fielddisplay(self, 'outputnamestring', 'string that identifies the type of output you want, eg. IceVolume, TotalSmb, GroudedArea')) + string = "%s\n%s" % (string, fielddisplay(self, 'mask', 'mask vectorial field which identifies the region of interest (value > 0 will be included)')) + string = "%s\n%s" % (string, fielddisplay(self, 'maskexpstring', 'name of Argus file that can be passed in to define the regional mask')) + return string + #}}} - #ok, marshall strings and mask: - WriteData(fid,prefix,'data',self.name,'name','md.regionaloutput.name','format','String') - WriteData(fid,prefix,'data',self.definitionstring,'name','md.regionaloutput.definitionstring','format','String') - WriteData(fid,prefix,'data',self.outputnamestring,'name','md.regionaloutput.outputnamestring','format','String'); - WriteData(fid,prefix,'data',self.mask,'name','md.regionaloutput.mask','format','DoubleMat','mattype',1); + def extrude(self, md): # {{{ + self.mask = project3d(md, 'vector', self.mask, 'type', 'node') + return self + #}}} - # }}} + def setdefaultparameters(self): # {{{ + return self + #}}} + + def setmaskfromexp(self, md): # {{{ + if len(self.maskexpstring) > 0: + self.mask = ContourToMesh(md.mesh.elements, md.mesh.x, md.mesh.y, self.maskexpstring, 'node', 1) + + return self + # }}} + def checkconsistency(self, md, solution, analyses): # {{{ + + if not isinstance(self.name, str): + raise RuntimeError("regionaloutput error message: 'name' field should be a string!") + + if not isinstance(self.outputnamestring, str): + raise RuntimeError("regionaloutput error message: 'outputnamestring' field should be a string!") + + if len(self.maskexpstring) > 0: + if not os.path.isfile(self.maskexpstring): + raise RuntimeError("regionaloutput error message: file name for mask exp does not point to a legitimate file on disk!") + else: + self.setmaskfromexp(md) + + OutputdefinitionStringArray = [] + for i in range(1, 100): + x = 'Outputdefinition' + str(i) + OutputdefinitionStringArray.append(x) + + md = checkfield(md, 'field', self.definitionstring, 'values', OutputdefinitionStringArray) + md = checkfield(md, 'field', self.mask, 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + return md + # }}} + def marshall(self, prefix, md, fid): # {{{ + + #before marshalling, make sure mask is set: + self.setmaskfromexp(md) + + #ok, marshall strings and mask: + WriteData(fid, prefix, 'data', self.name, 'name', 'md.regionaloutput.name', 'format', 'String') + WriteData(fid, prefix, 'data', self.definitionstring, 'name', 'md.regionaloutput.definitionstring', 'format', 'String') + WriteData(fid, prefix, 'data', self.outputnamestring, 'name', 'md.regionaloutput.outputnamestring', 'format', 'String') + WriteData(fid, prefix, 'data', self.mask, 'name', 'md.regionaloutput.mask', 'format', 'DoubleMat', 'mattype', 1) + + # }}} Index: /issm/trunk-jpl/src/m/classes/results.py =================================================================== --- /issm/trunk-jpl/src/m/classes/results.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/results.py (revision 24213) @@ -1,52 +1,54 @@ -import numpy as np -from pairoptions import pairoptions from fielddisplay import fielddisplay -import MatlabFuncs as m + class results(object): - """ - RESULTS class definition + """ + RESULTS class definition - Usage: - results=results(); - """ + Usage: + results = results() + """ - def __init__(self,*args): # {{{ - pass - # }}} - def __repr__(self): # {{{ - s =" Model results:\n" + def __init__(self, *args): # {{{ + pass + # }}} - if 'step' in self.__dict__: - s+="%s\n" % fielddisplay(self,'step',"step number") - if 'time' in self.__dict__: - s+="%s\n" % fielddisplay(self,'time',"time value") - if 'SolutionType' in self.__dict__: - s+="%s\n" % fielddisplay(self,'SolutionType',"solution type") + def __repr__(self): # {{{ + s = " Model results:\n" - for name in list(self.__dict__.keys()): - if name not in ['step','time','SolutionType','errlog','outlog']: - if isinstance(getattr(self,name),list): - s+="%s\n" % fielddisplay(self,name,"model results list") - elif isinstance(getattr(self,name),results): - s+="%s\n" % fielddisplay(self,name,"model results case") - else: - s+="%s\n" % fielddisplay(self,name,"") + if 'step' in self.__dict__: + s += "%s\n" % fielddisplay(self, 'step', "step number") + if 'time' in self.__dict__: + s += "%s\n" % fielddisplay(self, 'time', "time value") + if 'SolutionType' in self.__dict__: + s += "%s\n" % fielddisplay(self, 'SolutionType', "solution type") - if 'errlog' in self.__dict__: - s+="%s\n" % fielddisplay(self,'errlog',"error log file") - if 'outlog' in self.__dict__: - s+="%s\n" % fielddisplay(self,'outlog',"output log file") + for name in list(self.__dict__.keys()): + if name not in ['step', 'time', 'SolutionType', 'errlog', 'outlog']: + if isinstance(getattr(self, name), list): + s += "%s\n" % fielddisplay(self, name, "model results list") + elif isinstance(getattr(self, name), results): + s += "%s\n" % fielddisplay(self, name, "model results case") + else: + s += "%s\n" % fielddisplay(self, name, "") - return s - # }}} - def setdefaultparameters(self): # {{{ - #do nothing - return self - # }}} - def checkconsistency(self,md,solution,analyses): # {{{ - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - pass - # }}} + if 'errlog' in self.__dict__: + s += "%s\n" % fielddisplay(self, 'errlog', "error log file") + if 'outlog' in self.__dict__: + s += "%s\n" % fielddisplay(self, 'outlog', "output log file") + + return s + # }}} + + def setdefaultparameters(self): # {{{ + #do nothing + return self + # }}} + + def checkconsistency(self, md, solution, analyses): # {{{ + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + pass + # }}} Index: /issm/trunk-jpl/src/m/classes/rifts.py =================================================================== --- /issm/trunk-jpl/src/m/classes/rifts.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/rifts.py (revision 24213) @@ -6,87 +6,91 @@ import MatlabFuncs as m + class rifts(object): - """ - RIFTS class definition + """ + RIFTS class definition - Usage: - rifts=rifts(); - """ + Usage: + rifts = rifts() + """ - def __init__(self): # {{{ - self.riftstruct = [] - self.riftproperties = [] + def __init__(self): # {{{ + self.riftstruct = [] + self.riftproperties = [] - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' rifts parameters:' + #}}} - string="%s\n%s"%(string,fielddisplay(self,'riftstruct','structure containing all rift information (vertices coordinates, segments, type of melange, ...)')) - string="%s\n%s"%(string,fielddisplay(self,'riftproperties','')) - return string - #}}} - def setdefaultparameters(self): # {{{ - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ - if (not self.riftstruct) or np.any(isnans(self.riftstruct)): - numrifts=0 - else: - numrifts=len(self.riftstruct) + def __repr__(self): # {{{ + string = ' rifts parameters:' - if numrifts: - if not m.strcmp(md.mesh.domaintype(),'2Dhorizontal'): - md.checkmessage("models with rifts are only supported in 2d for now!") - if not isinstance(self.riftstruct,list): - md.checkmessage("rifts.riftstruct should be a structure!") - if np.any(md.mesh.segmentmarkers>=2): - #We have segments with rift markers, but no rift structure! - md.checkmessage("model should be processed for rifts (run meshprocessrifts)!") - for i,rift in enumerate(self.riftstruct): - md = checkfield(md,'fieldname',"rifts.riftstruct[{}]['fill']".format(i),'values',['Water','Air','Ice','Melange',0,1,2,3]) - else: - if self.riftstruct and np.any(np.logical_not(isnans(self.riftstruct))): - md.checkmessage("riftstruct should be NaN since numrifts is 0!") + string = "%s\n%s" % (string, fielddisplay(self, 'riftstruct', 'structure containing all rift information (vertices coordinates, segments, type of melange, ...)')) + string = "%s\n%s" % (string, fielddisplay(self, 'riftproperties', '')) + return string + #}}} - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + def setdefaultparameters(self): # {{{ + return self + #}}} - #Process rift info - if (not self.riftstruct) or np.any(isnans(self.riftstruct)): - numrifts=0 - else: - numrifts=len(self.riftstruct) + def checkconsistency(self, md, solution, analyses): # {{{ + if (not self.riftstruct) or np.any(isnans(self.riftstruct)): + numrifts = 0 + else: + numrifts = len(self.riftstruct) - numpairs=0 - for rift in self.riftstruct: - numpairs+=np.size(rift['penaltypairs'],axis=0) + if numrifts: + if not m.strcmp(md.mesh.domaintype(), '2Dhorizontal'): + md.checkmessage("models with rifts are only supported in 2d for now!") + if not isinstance(self.riftstruct, list): + md.checkmessage("rifts.riftstruct should be a structure!") + if np.any(md.mesh.segmentmarkers >= 2): + #We have segments with rift markers, but no rift structure! + md.checkmessage("model should be processed for rifts (run meshprocessrifts)!") + for i, rift in enumerate(self.riftstruct): + md = checkfield(md, 'fieldname', "rifts.riftstruct[{}]['fill']".format(i), 'values', ['Water', 'Air', 'Ice', 'Melange', 0, 1, 2, 3]) + else: + if self.riftstruct and np.any(np.logical_not(isnans(self.riftstruct))): + md.checkmessage("riftstruct should be NaN since numrifts is 0!") - # Convert strings in riftstruct to hard coded numbers - FillDict={'Air':0, - 'Ice':1, - 'Melange':2, - 'Water':3} - for rift in self.riftstruct: - if rift['fill'] in ['Air','Ice','Melange','Water']: - rift['fill'] = FillDict[rift['fill']] + return md + # }}} - # 2 for nodes + 2 for elements+ 2 for normals + 1 for length + 1 for fill + 1 for friction + 1 for fraction + 1 for fractionincrement + 1 for state. - data=np.zeros((numpairs,12)) - count=0 - for rift in self.riftstruct: - numpairsforthisrift=np.size(rift['penaltypairs'],0) - data[count:count+numpairsforthisrift,0:7]=rift['penaltypairs'] - data[count:count+numpairsforthisrift,7]=rift['fill'] - data[count:count+numpairsforthisrift,8]=rift['friction'] - data[count:count+numpairsforthisrift,9]=rift['fraction'] - data[count:count+numpairsforthisrift,10]=rift['fractionincrement'] - data[count:count+numpairsforthisrift,11]=rift['state'].reshape(-1) - count+=numpairsforthisrift + def marshall(self, prefix, md, fid): # {{{ + #Process rift info + if (not self.riftstruct) or np.any(isnans(self.riftstruct)): + numrifts = 0 + else: + numrifts = len(self.riftstruct) - WriteData(fid,prefix,'data',numrifts,'name','md.rifts.numrifts','format','Integer') - WriteData(fid,prefix,'data',data,'name','md.rifts.riftstruct','format','DoubleMat','mattype',3) - # }}} + numpairs = 0 + for rift in self.riftstruct: + numpairs += np.size(rift['penaltypairs'], axis=0) + + # Convert strings in riftstruct to hard coded numbers + FillDict = {'Air': 0, + 'Ice': 1, + 'Melange': 2, + 'Water': 3} + for rift in self.riftstruct: + if rift['fill'] in ['Air', 'Ice', 'Melange', 'Water']: + rift['fill'] = FillDict[rift['fill']] + + # 2 for nodes + 2 for elements + 2 for normals + 1 for length + 1 for fill + 1 for friction + 1 for fraction + 1 for fractionincrement + 1 for state. + data = np.zeros((numpairs, 12)) + count = 0 + for rift in self.riftstruct: + numpairsforthisrift = np.size(rift['penaltypairs'], 0) + data[count:count + numpairsforthisrift, 0:7] = rift['penaltypairs'] + data[count:count + numpairsforthisrift, 7] = rift['fill'] + data[count:count + numpairsforthisrift, 8] = rift['friction'] + data[count:count + numpairsforthisrift, 9] = rift['fraction'] + data[count:count + numpairsforthisrift, 10] = rift['fractionincrement'] + data[count:count + numpairsforthisrift, 11] = rift['state'].reshape(- 1) + count += numpairsforthisrift + + WriteData(fid, prefix, 'data', numrifts, 'name', 'md.rifts.numrifts', 'format', 'Integer') + WriteData(fid, prefix, 'data', data, 'name', 'md.rifts.riftstruct', 'format', 'DoubleMat', 'mattype', 3) + # }}} Index: /issm/trunk-jpl/src/m/classes/slr.py =================================================================== --- /issm/trunk-jpl/src/m/classes/slr.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/slr.py (revision 24213) @@ -6,218 +6,207 @@ from WriteData import WriteData + class slr(object): - """ - SLR class definition - - Usage: - slr=slr() - """ - def __init__(self): # {{{ - self.deltathickness = float('NaN') - self.sealevel = float('NaN') - self.spcthickness = float('NaN') - self.maxiter = 0 - self.reltol = 0 - self.abstol = 0 - self.love_h = 0 #provided by PREM model() - self.love_k = 0 #ideam - self.love_l = 0 #ideam - self.tide_love_k = 0 #ideam - self.tide_love_h = 0 #ideam - self.fluid_love = 0 - self.equatorial_moi = 0 - self.polar_moi = 0 - self.angular_velocity = 0 - self.rigid = 0 - self.elastic = 0 - self.rotation = 0 - self.ocean_area_scaling = 0 - self.steric_rate = 0 #rate of ocean expansion from steric effects. - self.geodetic_run_frequency = 1 #how many time steps we skip before we run the geodetic part of the solver during transient - self.geodetic = 0 #compute geodetic SLR? (in addition to steric?) - self.degacc = 0 - self.loop_increment = 0 - self.horiz = 0 - self.Ngia = float('NaN') - self.Ugia = float('NaN') - self.requested_outputs = [] - self.transitions = [] - - #set defaults - self.setdefaultparameters() - #}}} - - def __repr__(self): # {{{ - string=' slr parameters:' - string="%s\n%s"%(string,fielddisplay(self,'deltathickness','thickness change: ice height equivalent [m]')) - string="%s\n%s"%(string,fielddisplay(self,'sealevel','current sea level (prior to computation) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'spcthickness','thickness constraints (NaN means no constraint) [m]')) - string="%s\n%s"%(string,fielddisplay(self,'reltol','sea level rise relative convergence criterion, (NaN: not applied)')) - string="%s\n%s"%(string,fielddisplay(self,'abstol','sea level rise absolute convergence criterion, (default, NaN: not applied)')) - string="%s\n%s"%(string,fielddisplay(self,'maxiter','maximum number of nonlinear iterations')) - string="%s\n%s"%(string,fielddisplay(self,'love_h','load Love number for radial displacement')) - string="%s\n%s"%(string,fielddisplay(self,'love_k','load Love number for gravitational potential perturbation')) - string="%s\n%s"%(string,fielddisplay(self,'love_l','load Love number for horizontal displaements')) - string="%s\n%s"%(string,fielddisplay(self,'tide_love_k','tidal load Love number (degree 2)')) - string="%s\n%s"%(string,fielddisplay(self,'tide_love_h','tidal load Love number (degree 2)')) - string="%s\n%s"%(string,fielddisplay(self,'fluid_love','secular fluid Love number')) - string="%s\n%s"%(string,fielddisplay(self,'equatorial_moi','mean equatorial moment of inertia [kg m^2]')) - string="%s\n%s"%(string,fielddisplay(self,'polar_moi','polar moment of inertia [kg m^2]')) - string="%s\n%s"%(string,fielddisplay(self,'angular_velocity','mean rotational velocity of earth [per second]')) - string="%s\n%s"%(string,fielddisplay(self,'ocean_area_scaling','correction for model representation of ocean area [default: No correction]')) - string="%s\n%s"%(string,fielddisplay(self,'steric_rate','rate of steric ocean expansion [mm/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'Ngia','rate of viscous (GIA) geoid expansion (in mm/yr)')) - string="%s\n%s"%(string,fielddisplay(self,'Ugia','rate of viscous (GIA) bedrock uplift (in mm/yr)')) - string="%s\n%s"%(string,fielddisplay(self,'loop_increment','vector assembly (in the convolution) framentation')) - string="%s\n%s"%(string,fielddisplay(self,'geodetic','compute geodetic SLR? ( in addition to steric?) default 0')) - string="%s\n%s"%(string,fielddisplay(self,'geodetic_run_frequency','how many time steps we skip before we run SLR solver during transient (default: 1)')) - string="%s\n%s"%(string,fielddisplay(self,'rigid','rigid earth graviational potential perturbation')) - string="%s\n%s"%(string,fielddisplay(self,'elastic','elastic earth graviational potential perturbation')) - string="%s\n%s"%(string,fielddisplay(self,'rotation','earth rotational potential perturbation')) - string="%s\n%s"%(string,fielddisplay(self,'degacc','accuracy (default .01 deg) for numerical discretization of the Green''s functions')) - string="%s\n%s"%(string,fielddisplay(self,'transitions','indices into parts of the mesh that will be icecaps')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) - - return string - # }}} - - def setdefaultparameters(self): # {{{ - #Convergence criterion: absolute, relative and residual - self.reltol = 0.01 #default - self.abstol = float('NaN') #1 mm of sea level rise - - #maximum of non-linear iterations. - self.maxiter = 5 - self.loop_increment = 200 - - #computational flags: - self.geodetic = 0 - self.rigid = 1 - self.elastic = 1 - self.ocean_area_scaling = 0 - self.rotation = 1 - - #tidal love numbers: - self.tide_love_h = 0.6149 #degree 2 - self.tide_love_k = 0.3055 #degree 2 - - #secular fluid love number: - self.fluid_love = 0.942 - - #moment of inertia: - self.equatorial_moi = 8.0077*10**37 # [kg m^2] - self.polar_moi = 8.0345*10**37 # [kg m^2] - - #mean rotational velocity of earth - self.angular_velocity = 7.2921*10**-5 # [s^-1] - - #numerical discretization accuracy - self.degacc = .01 - - #steric: - self.steric_rate = 0 - - #how many time steps we skip before we run SLR solver during transient - self.geodetic_run_frequency = 1 - - #output default: - self.requested_outputs = ['default'] - - #transitions should be a cell array of vectors: - self.transitions = [] - - #horizontal displacement? (not by default) - self.horiz = 0 - - return self - #}}} - - def checkconsistency(self,md,solution,analyses): # {{{ - #Early return - if (solution!='SealevelriseAnalysis'): - return md - - md = checkfield(md,'fieldname','slr.deltathickness','NaN',1,'Inf',1,'size',[md.mesh.numberofelements]) - md = checkfield(md,'fieldname','slr.sealevel','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','slr.spcthickness','Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','slr.love_h','NaN',1,'Inf',1) - md = checkfield(md,'fieldname','slr.love_k','NaN',1,'Inf',1) - md = checkfield(md,'fieldname','slr.love_l','NaN',1,'Inf',1) - md = checkfield(md,'fieldname','slr.tide_love_h','NaN',1,'Inf',1) - md = checkfield(md,'fieldname','slr.tide_love_k','NaN',1,'Inf',1) - md = checkfield(md,'fieldname','slr.fluid_love','NaN',1,'Inf',1) - md = checkfield(md,'fieldname','slr.equatorial_moi','NaN',1,'Inf',1) - md = checkfield(md,'fieldname','slr.polar_moi','NaN',1,'Inf',1) - md = checkfield(md,'fieldname','slr.angular_velocity','NaN',1,'Inf',1) - md = checkfield(md,'fieldname','slr.reltol','size',[1,1]) - md = checkfield(md,'fieldname','slr.abstol','size',[1,1]) - md = checkfield(md,'fieldname','slr.maxiter','size',[1,1],'>=',1) - md = checkfield(md,'fieldname','slr.geodetic_run_frequency','size',[1,1],'>=',1) - md = checkfield(md,'fieldname','slr.steric_rate','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','slr.degacc','size',[1,1],'>=',1e-10) - md = checkfield(md,'fieldname','slr.requested_outputs','stringrow',1) - md = checkfield(md,'fieldname','slr.loop_increment','NaN',1,'Inf',1,'>=',1) - md = checkfield(md,'fieldname','slr.horiz','NaN',1,'Inf',1,'values',[0,1]) - md = checkfield(md,'fieldname','slr.Ngia','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - md = checkfield(md,'fieldname','slr.Ugia','NaN',1,'Inf',1,'size',[md.mesh.numberofvertices]) - - #check that love numbers are provided at the same level of accuracy: - if (size(self.love_h,0) != size(self.love_k,0) | size(self.love_h,0) != size(self.love_l,0)): - error('slr error message: love numbers should be provided at the same level of accuracy') - - #cross check that whereever we have an ice load, the mask is <0 on each vertex: - pos=np.where(self.deltathickness) - maskpos=md.mask.ice_levelset[md.mesh.elements[pos,:]] - els=np.where(maskpos>0) - if len(els[0])>0: - warnings.warn('slr checkconsistency fail: there are elements with ice loads where some vertices are not on the ice!') - - #check that if geodetic is requested, we are a mesh3dsurface model (planet), or if we are not, - #a coupler to a planet model is provided. - if self.geodetic and not md.transient.iscoupler and domaintype(md.mesh)!='mesh3dsurface': - error('model is requesting geodetic computations without being a mesh3dsurface, or being coupled to one!') - return md - # }}} - - def defaultoutputs(self,md): # {{{ - return ['Sealevel'] - # }}} - - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','deltathickness','format','DoubleMat','mattype',2) - WriteData(fid,prefix,'object',self,'fieldname','sealevel','mattype',1,'format','DoubleMat','timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','spcthickness','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','reltol','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','abstol','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','maxiter','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','love_h','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','love_k','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','love_l','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'fieldname','tide_love_h','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','tide_love_k','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','fluid_love','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','equatorial_moi','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','polar_moi','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','angular_velocity','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','rigid','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','elastic','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','rotation','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','ocean_area_scaling','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','geodetic_run_frequency','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','steric_rate','format','DoubleMat','mattype',1,'scale',1e-3/md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','Ngia','format','DoubleMat','mattype',1,'scale',1e-3/md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','Ugia','format','DoubleMat','mattype',1,'scale',1e-3/md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','degacc','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','transitions','format','MatArray') - WriteData(fid,prefix,'object',self,'fieldname','loop_increment','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','horiz','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','geodetic','format','Integer') - - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.slr.requested_outputs','format','StringArray') - # }}} + """ + SLR class definition + + Usage: + slr = slr() + """ + def __init__(self): # {{{ + self.deltathickness = float('NaN') + self.sealevel = float('NaN') + self.spcthickness = float('NaN') + self.maxiter = 0 + self.reltol = 0 + self.abstol = 0 + self.love_h = 0 #provided by PREM model() + self.love_k = 0 #ideam + self.love_l = 0 #ideam + self.tide_love_k = 0 #ideam + self.tide_love_h = 0 #ideam + self.fluid_love = 0 + self.equatorial_moi = 0 + self.polar_moi = 0 + self.angular_velocity = 0 + self.rigid = 0 + self.elastic = 0 + self.rotation = 0 + self.ocean_area_scaling = 0 + self.steric_rate = 0 #rate of ocean expansion from steric effects. + self.geodetic_run_frequency = 1 #how many time steps we skip before we run the geodetic part of the solver during transient + self.geodetic = 0 #compute geodetic SLR? (in addition to steric?) + self.degacc = 0 + self.loop_increment = 0 + self.horiz = 0 + self.Ngia = float('NaN') + self.Ugia = float('NaN') + self.requested_outputs = [] + self.transitions = [] + + #set defaults + self.setdefaultparameters() + #}}} + + def __repr__(self): # {{{ + string = ' slr parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'deltathickness', 'thickness change: ice height equivalent [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'sealevel', 'current sea level (prior to computation) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'spcthickness', 'thickness constraints (NaN means no constraint) [m]')) + string = "%s\n%s" % (string, fielddisplay(self, 'reltol', 'sea level rise relative convergence criterion, (NaN: not applied)')) + string = "%s\n%s" % (string, fielddisplay(self, 'abstol', 'sea level rise absolute convergence criterion, (default, NaN: not applied)')) + string = "%s\n%s" % (string, fielddisplay(self, 'maxiter', 'maximum number of nonlinear iterations')) + string = "%s\n%s" % (string, fielddisplay(self, 'love_h', 'load Love number for radial displacement')) + string = "%s\n%s" % (string, fielddisplay(self, 'love_k', 'load Love number for gravitational potential perturbation')) + string = "%s\n%s" % (string, fielddisplay(self, 'love_l', 'load Love number for horizontal displaements')) + string = "%s\n%s" % (string, fielddisplay(self, 'tide_love_k', 'tidal load Love number (degree 2)')) + string = "%s\n%s" % (string, fielddisplay(self, 'tide_love_h', 'tidal load Love number (degree 2)')) + string = "%s\n%s" % (string, fielddisplay(self, 'fluid_love', 'secular fluid Love number')) + string = "%s\n%s" % (string, fielddisplay(self, 'equatorial_moi', 'mean equatorial moment of inertia [kg m^2]')) + string = "%s\n%s" % (string, fielddisplay(self, 'polar_moi', 'polar moment of inertia [kg m^2]')) + string = "%s\n%s" % (string, fielddisplay(self, 'angular_velocity', 'mean rotational velocity of earth [per second]')) + string = "%s\n%s" % (string, fielddisplay(self, 'ocean_area_scaling', 'correction for model representation of ocean area [default: No correction]')) + string = "%s\n%s" % (string, fielddisplay(self, 'steric_rate', 'rate of steric ocean expansion [mm / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'Ngia', 'rate of viscous (GIA) geoid expansion (in mm / yr)')) + string = "%s\n%s" % (string, fielddisplay(self, 'Ugia', 'rate of viscous (GIA) bedrock uplift (in mm / yr)')) + string = "%s\n%s" % (string, fielddisplay(self, 'loop_increment', 'vector assembly (in the convolution) framentation')) + string = "%s\n%s" % (string, fielddisplay(self, 'geodetic', 'compute geodetic SLR? (in addition to steric?) default 0')) + string = "%s\n%s" % (string, fielddisplay(self, 'geodetic_run_frequency', 'how many time steps we skip before we run SLR solver during transient (default: 1)')) + string = "%s\n%s" % (string, fielddisplay(self, 'rigid', 'rigid earth graviational potential perturbation')) + string = "%s\n%s" % (string, fielddisplay(self, 'elastic', 'elastic earth graviational potential perturbation')) + string = "%s\n%s" % (string, fielddisplay(self, 'rotation', 'earth rotational potential perturbation')) + string = "%s\n%s" % (string, fielddisplay(self, 'degacc', 'accuracy (default .01 deg) for numerical discretization of the Green''s functions')) + string = "%s\n%s" % (string, fielddisplay(self, 'transitions', 'indices into parts of the mesh that will be icecaps')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) + + return string + # }}} + + def setdefaultparameters(self): # {{{ + #Convergence criterion: absolute, relative and residual + self.reltol = 0.01 #default + self.abstol = float('NaN') #1 mm of sea level rise + #maximum of non - linear iterations. + self.maxiter = 5 + self.loop_increment = 200 + #computational flags: + self.geodetic = 0 + self.rigid = 1 + self.elastic = 1 + self.ocean_area_scaling = 0 + self.rotation = 1 + #tidal love numbers: + self.tide_love_h = 0.6149 #degree 2 + self.tide_love_k = 0.3055 #degree 2 + #secular fluid love number: + self.fluid_love = 0.942 + #moment of inertia: + self.equatorial_moi = 8.0077 * 1.0e37 # [kg m^2] + self.polar_moi = 8.0345 * 1.0e37 # [kg m^2] + #mean rotational velocity of earth + self.angular_velocity = 7.2921 * 1.0e-5 # [s^ - 1] + #numerical discretization accuracy + self.degacc = 0.01 + #steric: + self.steric_rate = 0 + #how many time steps we skip before we run SLR solver during transient + self.geodetic_run_frequency = 1 + #output default: + self.requested_outputs = ['default'] + #transitions should be a cell array of vectors: + self.transitions = [] + #horizontal displacement? (not by default) + self.horiz = 0 + + return self + #}}} + + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if (solution != 'SealevelriseAnalysis'): + return md + + md = checkfield(md, 'fieldname', 'slr.deltathickness', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofelements]) + md = checkfield(md, 'fieldname', 'slr.sealevel', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'slr.spcthickness', 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'slr.love_h', 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'slr.love_k', 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'slr.love_l', 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'slr.tide_love_h', 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'slr.tide_love_k', 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'slr.fluid_love', 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'slr.equatorial_moi', 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'slr.polar_moi', 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'slr.angular_velocity', 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'slr.reltol', 'size', [1, 1]) + md = checkfield(md, 'fieldname', 'slr.abstol', 'size', [1, 1]) + md = checkfield(md, 'fieldname', 'slr.maxiter', 'size', [1, 1], '>=', 1) + md = checkfield(md, 'fieldname', 'slr.geodetic_run_frequency', 'size', [1, 1], '>=', 1) + md = checkfield(md, 'fieldname', 'slr.steric_rate', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'slr.degacc', 'size', [1, 1], '>=', 1e-10) + md = checkfield(md, 'fieldname', 'slr.requested_outputs', 'stringrow', 1) + md = checkfield(md, 'fieldname', 'slr.loop_increment', 'NaN', 1, 'Inf', 1, '>=', 1) + md = checkfield(md, 'fieldname', 'slr.horiz', 'NaN', 1, 'Inf', 1, 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'slr.Ngia', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + md = checkfield(md, 'fieldname', 'slr.Ugia', 'NaN', 1, 'Inf', 1, 'size', [md.mesh.numberofvertices]) + + #check that love numbers are provided at the same level of accuracy: + if (size(self.love_h, 0) != size(self.love_k, 0) | size(self.love_h, 0) != size(self.love_l, 0)): + error('slr error message: love numbers should be provided at the same level of accuracy') + + #cross check that whereever we have an ice load, the mask is < 0 on each vertex: + pos = np.where(self.deltathickness) + maskpos = md.mask.ice_levelset[md.mesh.elements[pos, :]] + els = np.where(maskpos > 0) + if len(els[0]) > 0: + warnings.warn('slr checkconsistency fail: there are elements with ice loads where some vertices are not on the ice!') + + #check that if geodetic is requested, we are a mesh3dsurface model (planet), or if we are not, + #a coupler to a planet model is provided. + if self.geodetic and not md.transient.iscoupler and domaintype(md.mesh) != 'mesh3dsurface': + error('model is requesting geodetic computations without being a mesh3dsurface, or being coupled to one!') + return md + # }}} + + def defaultoutputs(self, md): # {{{ + return ['Sealevel'] + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'deltathickness', 'format', 'DoubleMat', 'mattype', 2) + WriteData(fid, prefix, 'object', self, 'fieldname', 'sealevel', 'mattype', 1, 'format', 'DoubleMat', 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'spcthickness', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'reltol', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'abstol', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'maxiter', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'love_h', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'love_k', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'love_l', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'fieldname', 'tide_love_h', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'tide_love_k', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'fluid_love', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'equatorial_moi', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'polar_moi', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'angular_velocity', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'rigid', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'elastic', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'rotation', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'ocean_area_scaling', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'geodetic_run_frequency', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'steric_rate', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1e-3 / md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'Ngia', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1e-3 / md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'Ugia', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1e-3 / md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'degacc', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'transitions', 'format', 'MatArray') + WriteData(fid, prefix, 'object', self, 'fieldname', 'loop_increment', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'horiz', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'geodetic', 'format', 'Integer') + + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.slr.requested_outputs', 'format', 'StringArray') + # }}} Index: /issm/trunk-jpl/src/m/classes/steadystate.py =================================================================== --- /issm/trunk-jpl/src/m/classes/steadystate.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/steadystate.py (revision 24213) @@ -4,71 +4,70 @@ from WriteData import WriteData + class steadystate(object): - """ - STEADYSTATE class definition + """ + STEADYSTATE class definition - Usage: - steadystate=steadystate(); - """ + Usage: + steadystate = steadystate() + """ - def __init__(self): # {{{ - self.reltol = 0 - self.maxiter = 0 - self.requested_outputs = [] + def __init__(self): # {{{ + self.reltol = 0 + self.maxiter = 0 + self.requested_outputs = [] - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' steadystate solution parameters:' - string="%s\n%s"%(string,fielddisplay(self,'reltol','relative tolerance criterion')) - string="%s\n%s"%(string,fielddisplay(self,'maxiter','maximum number of iterations')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional requested outputs')) - return string - #}}} - def defaultoutputs(self,md): # {{{ + #}}} + def __repr__(self): # {{{ + string = ' steadystate solution parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'reltol', 'relative tolerance criterion')) + string = "%s\n%s" % (string, fielddisplay(self, 'maxiter', 'maximum number of iterations')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional requested outputs')) + return string + #}}} - return md.stressbalance.defaultoutputs(md)+md.thermal.defaultoutputs(md) + def defaultoutputs(self, md): # {{{ + return md.stressbalance.defaultoutputs(md) + md.thermal.defaultoutputs(md) - #}}} - def setdefaultparameters(self): # {{{ - - #maximum of steady state iterations - self.maxiter=100 + #}}} + def setdefaultparameters(self): # {{{ + #maximum of steady state iterations + self.maxiter = 100 + #Relative tolerance for the steadystate convertgence + self.reltol = 0.01 + #default output + self.requested_outputs = ['default'] + return self + #}}} - #Relative tolerance for the steadystate convertgence - self.reltol=0.01 + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if not solution == 'SteadystateSolution': + return md - #default output - self.requested_outputs=['default'] - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + if not md.timestepping.time_step == 0: + md.checkmessage("for a steadystate computation, timestepping.time_step must be zero.") - #Early return - if not solution=='SteadystateSolution': - return md + if np.isnan(md.stressbalance.reltol): + md.checkmessage("for a steadystate computation, stressbalance.reltol (relative convergence criterion) must be defined!") - if not md.timestepping.time_step==0: - md.checkmessage("for a steadystate computation, timestepping.time_step must be zero.") + md = checkfield(md, 'fieldname', 'steadystate.requested_outputs', 'stringrow', 1) - if np.isnan(md.stressbalance.reltol): - md.checkmessage("for a steadystate computation, stressbalance.reltol (relative convergence criterion) must be defined!") + return md + # }}} - md = checkfield(md,'fieldname','steadystate.requested_outputs','stringrow',1) + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'reltol', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'maxiter', 'format', 'Integer') - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','reltol','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','maxiter','format','Integer') - - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.steadystate.requested_outputs','format','StringArray') - # }}} + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.steadystate.requested_outputs', 'format', 'StringArray') + # }}} Index: /issm/trunk-jpl/src/m/classes/stressbalance.py =================================================================== --- /issm/trunk-jpl/src/m/classes/stressbalance.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/stressbalance.py (revision 24213) @@ -1,5 +1,4 @@ import numpy as np import sys -import copy from project3d import project3d from fielddisplay import fielddisplay @@ -8,193 +7,191 @@ import MatlabFuncs as m + class stressbalance(object): - """ - STRESSBALANCE class definition + """ + STRESSBALANCE class definition - Usage: - stressbalance=stressbalance(); - """ + Usage: + stressbalance = stressbalance() + """ - def __init__(self): # {{{ - self.spcvx = float('NaN') - self.spcvy = float('NaN') - self.spcvz = float('NaN') - self.restol = 0 - self.reltol = 0 - self.abstol = 0 - self.isnewton = 0 - self.FSreconditioning = 0 - self.icefront = float('NaN') - self.maxiter = 0 - self.shelf_dampening = 0 - self.vertex_pairing = float('NaN') - self.penalty_factor = float('NaN') - self.rift_penalty_lock = float('NaN') - self.rift_penalty_threshold = 0 - self.referential = float('NaN') - self.loadingforce = float('NaN') - self.requested_outputs = [] + def __init__(self): # {{{ + self.spcvx = float('NaN') + self.spcvy = float('NaN') + self.spcvz = float('NaN') + self.restol = 0 + self.reltol = 0 + self.abstol = 0 + self.isnewton = 0 + self.FSreconditioning = 0 + self.icefront = float('NaN') + self.maxiter = 0 + self.shelf_dampening = 0 + self.vertex_pairing = float('NaN') + self.penalty_factor = float('NaN') + self.rift_penalty_lock = float('NaN') + self.rift_penalty_threshold = 0 + self.referential = float('NaN') + self.loadingforce = float('NaN') + self.requested_outputs = [] - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - - string=' StressBalance solution parameters:' - string="%s\n%s"%(string,' Convergence criteria:') - string="%s\n%s"%(string,fielddisplay(self,'restol','mechanical equilibrium residual convergence criterion')) - string="%s\n%s"%(string,fielddisplay(self,'reltol','velocity relative convergence criterion, NaN: not applied')) - string="%s\n%s"%(string,fielddisplay(self,'abstol','velocity absolute convergence criterion, NaN: not applied')) - string="%s\n%s"%(string,fielddisplay(self,'isnewton',"0: Picard's fixed point, 1: Newton's method, 2: hybrid")) - string="%s\n%s"%(string,fielddisplay(self,'maxiter','maximum number of nonlinear iterations')) + #}}} + def __repr__(self): # {{{ - string="%s\n%s"%(string,'\n boundary conditions:') - string="%s\n%s"%(string,fielddisplay(self,'spcvx','x-axis velocity constraint (NaN means no constraint) [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'spcvy','y-axis velocity constraint (NaN means no constraint) [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'spcvz','z-axis velocity constraint (NaN means no constraint) [m/yr]')) - string="%s\n%s"%(string,fielddisplay(self,'icefront','segments on ice front list (last column 0: Air, 1: Water, 2: Ice')) + string = ' StressBalance solution parameters:' + string = "%s\n%s" % (string, ' Convergence criteria:') + string = "%s\n%s" % (string, fielddisplay(self, 'restol', 'mechanical equilibrium residual convergence criterion')) + string = "%s\n%s" % (string, fielddisplay(self, 'reltol', 'velocity relative convergence criterion, NaN: not applied')) + string = "%s\n%s" % (string, fielddisplay(self, 'abstol', 'velocity absolute convergence criterion, NaN: not applied')) + string = "%s\n%s" % (string, fielddisplay(self, 'isnewton', "0: Picard's fixed point, 1: Newton's method, 2: hybrid")) + string = "%s\n%s" % (string, fielddisplay(self, 'maxiter', 'maximum number of nonlinear iterations')) - string="%s\n%s"%(string,'\n Rift options:') - string="%s\n%s"%(string,fielddisplay(self,'rift_penalty_threshold','threshold for instability of mechanical constraints')) - string="%s\n%s"%(string,fielddisplay(self,'rift_penalty_lock','number of iterations before rift penalties are locked')) + string = "%s\n%s" % (string, '\n boundary conditions:') + string = "%s\n%s" % (string, fielddisplay(self, 'spcvx', 'x - axis velocity constraint (NaN means no constraint) [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'spcvy', 'y - axis velocity constraint (NaN means no constraint) [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'spcvz', 'z - axis velocity constraint (NaN means no constraint) [m / yr]')) + string = "%s\n%s" % (string, fielddisplay(self, 'icefront', 'segments on ice front list (last column 0: Air, 1: Water, 2: Ice')) - string="%s\n%s"%(string,'\n Penalty options:') - string="%s\n%s"%(string,fielddisplay(self,'penalty_factor','offset used by penalties: penalty = Kmax*10^offset')) - string="%s\n%s"%(string,fielddisplay(self,'vertex_pairing','pairs of vertices that are penalized')) + string = "%s\n%s" % (string, '\n Rift options:') + string = "%s\n%s" % (string, fielddisplay(self, 'rift_penalty_threshold', 'threshold for instability of mechanical constraints')) + string = "%s\n%s" % (string, fielddisplay(self, 'rift_penalty_lock', 'number of iterations before rift penalties are locked')) - string="%s\n%s"%(string,'\n Other:') - string="%s\n%s"%(string,fielddisplay(self,'shelf_dampening','use dampening for floating ice ? Only for FS model')) - string="%s\n%s"%(string,fielddisplay(self,'FSreconditioning','multiplier for incompressibility equation. Only for FS model')) - string="%s\n%s"%(string,fielddisplay(self,'referential','local referential')) - string="%s\n%s"%(string,fielddisplay(self,'loadingforce','loading force applied on each point [N/m^3]')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) + string = "%s\n%s" % (string, '\n Penalty options:') + string = "%s\n%s" % (string, fielddisplay(self, 'penalty_factor', 'offset used by penalties: penalty = Kmax * 10^offset')) + string = "%s\n%s" % (string, fielddisplay(self, 'vertex_pairing', 'pairs of vertices that are penalized')) - return string - #}}} - def extrude(self,md): # {{{ - self.spcvx=project3d(md,'vector',self.spcvx,'type','node') - self.spcvy=project3d(md,'vector',self.spcvy,'type','node') - self.spcvz=project3d(md,'vector',self.spcvz,'type','node') - self.referential=project3d(md,'vector',self.referential,'type','node') - self.loadingforce=project3d(md,'vector',self.loadingforce,'type','node') + string = "%s\n%s" % (string, '\n Other:') + string = "%s\n%s" % (string, fielddisplay(self, 'shelf_dampening', 'use dampening for floating ice ? Only for FS model')) + string = "%s\n%s" % (string, fielddisplay(self, 'FSreconditioning', 'multiplier for incompressibility equation. Only for FS model')) + string = "%s\n%s" % (string, fielddisplay(self, 'referential', 'local referential')) + string = "%s\n%s" % (string, fielddisplay(self, 'loadingforce', 'loading force applied on each point [N / m^3]')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) - return self - #}}} - def setdefaultparameters(self): # {{{ - #maximum of non-linear iterations. - self.maxiter=100 + return string + #}}} - #Convergence criterion: absolute, relative and residual - self.restol=10**-4 - self.reltol=0.01 - self.abstol=10 + def extrude(self, md): # {{{ + self.spcvx = project3d(md, 'vector', self.spcvx, 'type', 'node') + self.spcvy = project3d(md, 'vector', self.spcvy, 'type', 'node') + self.spcvz = project3d(md, 'vector', self.spcvz, 'type', 'node') + self.referential = project3d(md, 'vector', self.referential, 'type', 'node') + self.loadingforce = project3d(md, 'vector', self.loadingforce, 'type', 'node') - self.FSreconditioning=10**13 - self.shelf_dampening=0 + return self + #}}} - #Penalty factor applied kappa=max(stiffness matrix)*10^penalty_factor - self.penalty_factor=3 + def setdefaultparameters(self): # {{{ + #maximum of non - linear iterations. + self.maxiter = 100 + #Convergence criterion: absolute, relative and residual + self.restol = 10**- 4 + self.reltol = 0.01 + self.abstol = 10 + self.FSreconditioning = 10**13 + self.shelf_dampening = 0 + #Penalty factor applied kappa = max(stiffness matrix) * 10^penalty_factor + self.penalty_factor = 3 + #Stop the iterations of rift if below a threshold + self.rift_penalty_threshold = 0 + #in some solutions, it might be needed to stop a run when only + #a few constraints remain unstable. For thermal computation, this + #parameter is often used. + self.rift_penalty_lock = 10 + #output default: + self.requested_outputs = ['default'] - #Stop the iterations of rift if below a threshold - self.rift_penalty_threshold=0 + return self + #}}} - #in some solutions, it might be needed to stop a run when only - #a few constraints remain unstable. For thermal computation, this - #parameter is often used. - self.rift_penalty_lock=10 + def defaultoutputs(self, md): # {{{ + if md.mesh.dimension() == 3: + list = ['Vx', 'Vy', 'Vz', 'Vel', 'Pressure'] + else: + list = ['Vx', 'Vy', 'Vel', 'Pressure'] + return list - #output default: - self.requested_outputs=['default'] + #}}} - return self - #}}} - def defaultoutputs(self,md): # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if 'StressbalanceAnalysis' not in analyses: + return md - if md.mesh.dimension()==3: - list = ['Vx','Vy','Vz','Vel','Pressure'] - else: - list = ['Vx','Vy','Vel','Pressure'] - return list + md = checkfield(md, 'fieldname', 'stressbalance.spcvx', 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'stressbalance.spcvy', 'Inf', 1, 'timeseries', 1) + if m.strcmp(md.mesh.domaintype(), '3D'): + md = checkfield(md, 'fieldname', 'stressbalance.spcvz', 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'stressbalance.restol', 'size', [1], '>', 0) + md = checkfield(md, 'fieldname', 'stressbalance.reltol', 'size', [1]) + md = checkfield(md, 'fieldname', 'stressbalance.abstol', 'size', [1]) + md = checkfield(md, 'fieldname', 'stressbalance.isnewton', 'numel', [1], 'values', [0, 1, 2]) + md = checkfield(md, 'fieldname', 'stressbalance.FSreconditioning', 'size', [1], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'stressbalance.maxiter', 'size', [1], '>=', 1) + md = checkfield(md, 'fieldname', 'stressbalance.referential', 'size', [md.mesh.numberofvertices, 6]) + md = checkfield(md, 'fieldname', 'stressbalance.loadingforce', 'size', [md.mesh.numberofvertices, 3]) + md = checkfield(md, 'fieldname', 'stressbalance.requested_outputs', 'stringrow', 1) - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + #singular solution + # if ~any((~isnan(md.stressbalance.spcvx) + ~isnan(md.stressbalance.spcvy)) == 2), + if not np.any(np.logical_and(np.logical_not(np.isnan(md.stressbalance.spcvx)), np.logical_not(np.isnan(md.stressbalance.spcvy)))): + print("\n !!! Warning: no spc applied, model might not be well posed if no basal friction is applied, check for solution crash\n") + #CHECK THAT EACH LINES CONTAINS ONLY NAN VALUES OR NO NAN VALUES + # if any(sum(isnan(md.stressbalance.referential), 2)~=0 & sum(isnan(md.stressbalance.referential), 2)~=6), + if np.any(np.logical_and(np.sum(np.isnan(md.stressbalance.referential), axis=1) != 0, np.sum(np.isnan(md.stressbalance.referential), axis=1) != 6)): + md.checkmessage("Each line of stressbalance.referential should contain either only NaN values or no NaN values") + #CHECK THAT THE TWO VECTORS PROVIDED ARE ORTHOGONAL + # if any(sum(isnan(md.stressbalance.referential), 2) == 0), + if np.any(np.sum(np.isnan(md.stressbalance.referential), axis=1) == 0): + pos = [i for i, item in enumerate(np.sum(np.isnan(md.stressbalance.referential), axis=1)) if item == 0] + # np.inner (and np.dot) calculate all the dot product permutations, resulting in a full matrix multiply + # if np.any(np.abs(np.inner(md.stressbalance.referential[pos, 0:2], md.stressbalance.referential[pos, 3:5]).diagonal()) > sys.float_info.epsilon): + # md.checkmessage("Vectors in stressbalance.referential (columns 1 to 3 and 4 to 6) must be orthogonal") + for item in md.stressbalance.referential[pos, :]: + if np.abs(np.inner(item[0:2], item[3:5])) > sys.float_info.epsilon: + md.checkmessage("Vectors in stressbalance.referential (columns 1 to 3 and 4 to 6) must be orthogonal") + #CHECK THAT NO rotation specified for FS Grounded ice at base + if m.strcmp(md.mesh.domaintype(), '3D') and md.flowequation.isFS: + pos = np.nonzero(np.logical_and(md.mask.groundedice_levelset, md.mesh.vertexonbase)) + if np.any(np.logical_not(np.isnan(md.stressbalance.referential[pos, :]))): + md.checkmessage("no referential should be specified for basal vertices of grounded ice") - #Early return - if 'StressbalanceAnalysis' not in analyses: - return md + return md + # }}} - md = checkfield(md,'fieldname','stressbalance.spcvx','Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','stressbalance.spcvy','Inf',1,'timeseries',1) - if m.strcmp(md.mesh.domaintype(),'3D'): - md = checkfield(md,'fieldname','stressbalance.spcvz','Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','stressbalance.restol','size',[1],'>',0) - md = checkfield(md,'fieldname','stressbalance.reltol','size',[1]) - md = checkfield(md,'fieldname','stressbalance.abstol','size',[1]) - md = checkfield(md,'fieldname','stressbalance.isnewton','numel',[1],'values',[0,1,2]) - md = checkfield(md,'fieldname','stressbalance.FSreconditioning','size',[1],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','stressbalance.maxiter','size',[1],'>=',1) - md = checkfield(md,'fieldname','stressbalance.referential','size',[md.mesh.numberofvertices,6]) - md = checkfield(md,'fieldname','stressbalance.loadingforce','size',[md.mesh.numberofvertices,3]) - md = checkfield(md,'fieldname','stressbalance.requested_outputs','stringrow',1); + def marshall(self, prefix, md, fid): # {{{ - #singular solution -# if ~any((~isnan(md.stressbalance.spcvx)+~isnan(md.stressbalance.spcvy))==2), - if not np.any(np.logical_and(np.logical_not(np.isnan(md.stressbalance.spcvx)),np.logical_not(np.isnan(md.stressbalance.spcvy)))): - print("\n !!! Warning: no spc applied, model might not be well posed if no basal friction is applied, check for solution crash\n") - #CHECK THAT EACH LINES CONTAINS ONLY NAN VALUES OR NO NAN VALUES -# if any(sum(isnan(md.stressbalance.referential),2)~=0 & sum(isnan(md.stressbalance.referential),2)~=6), - if np.any(np.logical_and(np.sum(np.isnan(md.stressbalance.referential),axis=1)!=0,np.sum(np.isnan(md.stressbalance.referential),axis=1)!=6)): - md.checkmessage("Each line of stressbalance.referential should contain either only NaN values or no NaN values") - #CHECK THAT THE TWO VECTORS PROVIDED ARE ORTHOGONAL -# if any(sum(isnan(md.stressbalance.referential),2)==0), - if np.any(np.sum(np.isnan(md.stressbalance.referential),axis=1)==0): - pos=[i for i,item in enumerate(np.sum(np.isnan(md.stressbalance.referential),axis=1)) if item==0] -# np.inner (and np.dot) calculate all the dot product permutations, resulting in a full matrix multiply -# if np.any(np.abs(np.inner(md.stressbalance.referential[pos,0:2],md.stressbalance.referential[pos,3:5]).diagonal())>sys.float_info.epsilon): -# md.checkmessage("Vectors in stressbalance.referential (columns 1 to 3 and 4 to 6) must be orthogonal") - for item in md.stressbalance.referential[pos,:]: - if np.abs(np.inner(item[0:2],item[3:5]))>sys.float_info.epsilon: - md.checkmessage("Vectors in stressbalance.referential (columns 1 to 3 and 4 to 6) must be orthogonal") - #CHECK THAT NO rotation specified for FS Grounded ice at base - if m.strcmp(md.mesh.domaintype(),'3D') and md.flowequation.isFS: - pos=np.nonzero(np.logical_and(md.mask.groundedice_levelset,md.mesh.vertexonbase)) - if np.any(np.logical_not(np.isnan(md.stressbalance.referential[pos,:]))): - md.checkmessage("no referential should be specified for basal vertices of grounded ice") + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'vertex_pairing', 'format', 'DoubleMat', 'mattype', 3) - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + yts = md.constants.yts - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','vertex_pairing','format','DoubleMat','mattype',3) + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'spcvx', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'spcvy', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'spcvz', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', yts) + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'restol', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'reltol', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'abstol', 'format', 'Double', 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'isnewton', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'FSreconditioning', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'maxiter', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'shelf_dampening', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'penalty_factor', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'rift_penalty_lock', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'rift_penalty_threshold', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'stressbalance', 'fieldname', 'referential', 'format', 'DoubleMat', 'mattype', 1) - yts=md.constants.yts + if isinstance(self.loadingforce, (list, tuple, np.ndarray)) and np.size(self.loadingforce, 1) == 3: + WriteData(fid, prefix, 'data', self.loadingforce[:, 0], 'format', 'DoubleMat', 'mattype', 1, 'name', 'md.stressbalance.loadingforcex') + WriteData(fid, prefix, 'data', self.loadingforce[:, 1], 'format', 'DoubleMat', 'mattype', 1, 'name', 'md.stressbalance.loadingforcey') + WriteData(fid, prefix, 'data', self.loadingforce[:, 2], 'format', 'DoubleMat', 'mattype', 1, 'name', 'md.stressbalance.loadingforcez') - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','spcvx','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','spcvy','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','spcvz','format','DoubleMat','mattype',1,'scale',1./yts,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','restol','format','Double') - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','reltol','format','Double') - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','abstol','format','Double','scale',1./yts) - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','isnewton','format','Integer') - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','FSreconditioning','format','Double') - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','maxiter','format','Integer') - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','shelf_dampening','format','Integer') - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','penalty_factor','format','Double') - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','rift_penalty_lock','format','Integer') - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','rift_penalty_threshold','format','Integer') - WriteData(fid,prefix,'object',self,'class','stressbalance','fieldname','referential','format','DoubleMat','mattype',1) - - if isinstance(self.loadingforce, (list, tuple, np.ndarray)) and np.size(self.loadingforce,1) == 3: - WriteData(fid,prefix,'data',self.loadingforce[:,0],'format','DoubleMat','mattype',1,'name','md.stressbalance.loadingforcex') - WriteData(fid,prefix,'data',self.loadingforce[:,1],'format','DoubleMat','mattype',1,'name','md.stressbalance.loadingforcey') - WriteData(fid,prefix,'data',self.loadingforce[:,2],'format','DoubleMat','mattype',1,'name','md.stressbalance.loadingforcez') - - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.stressbalance.requested_outputs','format','StringArray') - # }}} + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.stressbalance.requested_outputs', 'format', 'StringArray') + # }}} Index: /issm/trunk-jpl/src/m/classes/taoinversion.py =================================================================== --- /issm/trunk-jpl/src/m/classes/taoinversion.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/taoinversion.py (revision 24213) @@ -3,5 +3,4 @@ from WriteData import WriteData from checkfield import checkfield -from fielddisplay import fielddisplay from IssmConfig import IssmConfig from marshallcostfunctions import marshallcostfunctions @@ -9,191 +8,183 @@ from supportedcostfunctions import * + class taoinversion(object): - def __init__(self): - self.iscontrol = 0 - self.incomplete_adjoint = 0 - self.control_parameters = float('NaN') - self.maxsteps = 0 - self.maxiter = 0 - self.fatol = 0 - self.frtol = 0 - self.gatol = 0 - self.grtol = 0 - self.gttol = 0 - self.algorithm = '' - self.cost_functions = float('NaN') - self.cost_functions_coefficients = float('NaN') - self.min_parameters = float('NaN') - self.max_parameters = float('NaN') - self.vx_obs = float('NaN') - self.vy_obs = float('NaN') - self.vz_obs = float('NaN') - self.vel_obs = float('NaN') - self.thickness_obs = float('NaN') - self.surface_obs = float('NaN') - self.setdefaultparameters() + def __init__(self): + self.iscontrol = 0 + self.incomplete_adjoint = 0 + self.control_parameters = float('NaN') + self.maxsteps = 0 + self.maxiter = 0 + self.fatol = 0 + self.frtol = 0 + self.gatol = 0 + self.grtol = 0 + self.gttol = 0 + self.algorithm = '' + self.cost_functions = float('NaN') + self.cost_functions_coefficients = float('NaN') + self.min_parameters = float('NaN') + self.max_parameters = float('NaN') + self.vx_obs = float('NaN') + self.vy_obs = float('NaN') + self.vz_obs = float('NaN') + self.vel_obs = float('NaN') + self.thickness_obs = float('NaN') + self.surface_obs = float('NaN') + self.setdefaultparameters() - def __repr__(self): - string = ' taoinversion parameters:' - string = "%s\n\%s"%(string, fieldstring(self,'iscontrol','is inversion activated?')) - string="%s\n%s"%(string,fieldstring(self,'mantle_viscosity','mantle viscosity constraints (NaN means no constraint) (Pa s)')) - string="%s\n%s"%(string,fieldstring(self,'lithosphere_thickness','lithosphere thickness constraints (NaN means no constraint) (m)')) - string="%s\n%s"%(string,fieldstring(self,'cross_section_shape',"1: square-edged, 2: elliptical-edged surface")) - string="%s\n%s"%(string,fieldstring(self,'incomplete_adjoint','1: linear viscosity, 0: non-linear viscosity')) - string="%s\n%s"%(string,fieldstring(self,'control_parameters','ex: {''FrictionCoefficient''}, or {''MaterialsRheologyBbar''}')) - string="%s\n%s"%(string,fieldstring(self,'maxsteps','maximum number of iterations (gradient computation)')) - string="%s\n%s"%(string,fieldstring(self,'maxiter','maximum number of Function evaluation (forward run)')) - string="%s\n%s"%(string,fieldstring(self,'fatol','convergence criterion: f(X)-f(X*) (X: current iteration, X*: "true" solution, f: cost function)')) - string="%s\n%s"%(string,fieldstring(self,'frtol','convergence criterion: |f(X)-f(X*)|/|f(X*)|')) - string="%s\n%s"%(string,fieldstring(self,'gatol','convergence criterion: ||g(X)|| (g: gradient of the cost function)')) - string="%s\n%s"%(string,fieldstring(self,'grtol','convergence criterion: ||g(X)||/|f(X)|')) - string="%s\n%s"%(string,fieldstring(self,'gttol','convergence criterion: ||g(X)||/||g(X0)|| (g(X0): gradient at initial guess X0)')) - string="%s\n%s"%(string,fieldstring(self,'algorithm','minimization algorithm: ''tao_blmvm'', ''tao_cg'', ''tao_lmvm''')) - string="%s\n%s"%(string,fieldstring(self,'cost_functions','indicate the type of response for each optimization step')) - string="%s\n%s"%(string,fieldstring(self,'cost_functions_coefficients','cost_functions_coefficients applied to the misfit of each vertex and for each control_parameter')) - string="%s\n%s"%(string,fieldstring(self,'min_parameters','absolute minimum acceptable value of the inversed parameter on each vertex')) - string="%s\n%s"%(string,fieldstring(self,'max_parameters','absolute maximum acceptable value of the inversed parameter on each vertex')) - string="%s\n%s"%(string,fieldstring(self,'vx_obs','observed velocity x component [m/yr]')) - string="%s\n%s"%(string,fieldstring(self,'vy_obs','observed velocity y component [m/yr]')) - string="%s\n%s"%(string,fieldstring(self,'vel_obs','observed velocity magnitude [m/yr]')) - string="%s\n%s"%(string,fieldstring(self,'thickness_obs','observed thickness [m]')) - string="%s\n%s"%(string,fieldstring(self,'surface_obs','observed surface elevation [m]')) - string="%s\n%s"%(string,'Available cost functions:') - string="%s\n%s"%(string, ' 101: SurfaceAbsVelMisfit') - string="%s\n%s"%(string, ' 102: SurfaceRelVelMisfit') - string="%s\n%s"%(string, ' 103: SurfaceLogVelMisfit') - string="%s\n%s"%(string, ' 104: SurfaceLogVxVyMisfit') - string="%s\n%s"%(string, ' 105: SurfaceAverageVelMisfit') - string="%s\n%s"%(string, ' 201: ThicknessAbsMisfit') - string="%s\n%s"%(string, ' 501: DragCoefficientAbsGradient') - string="%s\n%s"%(string, ' 502: RheologyBbarAbsGradient') - string="%s\n%s"%(string, ' 503: ThicknessAbsGradient') - return string - def setdefaultparameters(self): + def __repr__(self): + string = ' taoinversion parameters:' + string = "%s\n%s" % (string, fieldstring(self, 'iscontrol', 'is inversion activated?')) + string = "%s\n%s" % (string, fieldstring(self, 'mantle_viscosity', 'mantle viscosity constraints (NaN means no constraint) (Pa s)')) + string = "%s\n%s" % (string, fieldstring(self, 'lithosphere_thickness', 'lithosphere thickness constraints (NaN means no constraint) (m)')) + string = "%s\n%s" % (string, fieldstring(self, 'cross_section_shape', "1: square-edged, 2: elliptical - edged surface")) + string = "%s\n%s" % (string, fieldstring(self, 'incomplete_adjoint', '1: linear viscosity, 0: non - linear viscosity')) + string = "%s\n%s" % (string, fieldstring(self, 'control_parameters', 'ex: {''FrictionCoefficient''}, or {''MaterialsRheologyBbar''}')) + string = "%s\n%s" % (string, fieldstring(self, 'maxsteps', 'maximum number of iterations (gradient computation)')) + string = "%s\n%s" % (string, fieldstring(self, 'maxiter', 'maximum number of Function evaluation (forward run)')) + string = "%s\n%s" % (string, fieldstring(self, 'fatol', 'convergence criterion: f(X) - f(X * ) (X: current iteration, X * : "true" solution, f: cost function)')) + string = "%s\n%s" % (string, fieldstring(self, 'frtol', 'convergence criterion: |f(X) - f(X * )| / |f(X * )|')) + string = "%s\n%s" % (string, fieldstring(self, 'gatol', 'convergence criterion: ||g(X)|| (g: gradient of the cost function)')) + string = "%s\n%s" % (string, fieldstring(self, 'grtol', 'convergence criterion: ||g(X)|| / |f(X)|')) + string = "%s\n%s" % (string, fieldstring(self, 'gttol', 'convergence criterion: ||g(X)|| / ||g(X0)|| (g(X0): gradient at initial guess X0)')) + string = "%s\n%s" % (string, fieldstring(self, 'algorithm', 'minimization algorithm: ''tao_blmvm'', ''tao_cg'', ''tao_lmvm''')) + string = "%s\n%s" % (string, fieldstring(self, 'cost_functions', 'indicate the type of response for each optimization step')) + string = "%s\n%s" % (string, fieldstring(self, 'cost_functions_coefficients', 'cost_functions_coefficients applied to the misfit of each vertex and for each control_parameter')) + string = "%s\n%s" % (string, fieldstring(self, 'min_parameters', 'absolute minimum acceptable value of the inversed parameter on each vertex')) + string = "%s\n%s" % (string, fieldstring(self, 'max_parameters', 'absolute maximum acceptable value of the inversed parameter on each vertex')) + string = "%s\n%s" % (string, fieldstring(self, 'vx_obs', 'observed velocity x component [m / yr]')) + string = "%s\n%s" % (string, fieldstring(self, 'vy_obs', 'observed velocity y component [m / yr]')) + string = "%s\n%s" % (string, fieldstring(self, 'vel_obs', 'observed velocity magnitude [m / yr]')) + string = "%s\n%s" % (string, fieldstring(self, 'thickness_obs', 'observed thickness [m]')) + string = "%s\n%s" % (string, fieldstring(self, 'surface_obs', 'observed surface elevation [m]')) + string = "%s\n%s" % (string, 'Available cost functions:') + string = "%s\n%s" % (string, ' 101: SurfaceAbsVelMisfit') + string = "%s\n%s" % (string, ' 102: SurfaceRelVelMisfit') + string = "%s\n%s" % (string, ' 103: SurfaceLogVelMisfit') + string = "%s\n%s" % (string, ' 104: SurfaceLogVxVyMisfit') + string = "%s\n%s" % (string, ' 105: SurfaceAverageVelMisfit') + string = "%s\n%s" % (string, ' 201: ThicknessAbsMisfit') + string = "%s\n%s" % (string, ' 501: DragCoefficientAbsGradient') + string = "%s\n%s" % (string, ' 502: RheologyBbarAbsGradient') + string = "%s\n%s" % (string, ' 503: ThicknessAbsGradient') + return string - #default is incomplete adjoint for now - self.incomplete_adjoint=1 + def setdefaultparameters(self): + #default is incomplete adjoint for now + self.incomplete_adjoint = 1 + #parameter to be inferred by control methods (only + #drag and B are supported yet) + self.control_parameters = ['FrictionCoefficient'] + #number of iterations and steps + self.maxsteps = 20 + self.maxiter = 30 + #default tolerances + self.fatol = 0 + self.frtol = 0 + self.gatol = 0 + self.grtol = 0 + self.gttol = 1e-4 + #minimization algorithm + PETSCMAJOR = IssmConfig('_PETSC_MAJOR_')[0] + PETSCMINOR = IssmConfig('_PETSC_MINOR_')[0] + if(PETSCMAJOR > 3 or (PETSCMAJOR == 3 and PETSCMINOR >= 5)): + self.algorithm = 'blmvm' + else: + self.algorithm = 'tao_blmvm' + #several responses can be used: + self.cost_functions = 101 + return self - #parameter to be inferred by control methods (only - #drag and B are supported yet) - self.control_parameters=['FrictionCoefficient'] + def extrude(self, md): + self.vx_obs = project3d(md, 'vector', self.vx_obs, 'type', 'node') + self.vy_obs = project3d(md, 'vector', self.vy_obs, 'type', 'node') + self.vel_obs = project3d(md, 'vector', self.vel_obs, 'type', 'node') + self.thickness_obs = project3d(md, 'vector', self.thickness_obs, 'type', 'node') - #number of iterations and steps - self.maxsteps=20; - self.maxiter =30; + if numel(self.cost_functions_coefficients) > 1: + self.cost_functions_coefficients = project3d(md, 'vector', self.cost_functions_coefficients, 'type', 'node') - #default tolerances - self.fatol = 0; - self.frtol = 0; - self.gatol = 0; - self.grtol = 0; - self.gttol = 1e-4; + if numel(self.min_parameters) > 1: + self.min_parameters = project3d(md, 'vector', self.min_parameters, 'type', 'node') - #minimization algorithm - PETSCMAJOR = IssmConfig('_PETSC_MAJOR_')[0] - PETSCMINOR = IssmConfig('_PETSC_MINOR_')[0] - if(PETSCMAJOR>3 or (PETSCMAJOR==3 and PETSCMINOR>=5)): - self.algorithm = 'blmvm'; - else: - self.algorithm = 'tao_blmvm'; + if numel(self.max_parameters) > 1: + self.max_parameters = project3d(md, 'vector', self.max_parameters, 'type', 'node') - #several responses can be used: - self.cost_functions=101; - return self + return self - def extrude(self,md): - self.vx_obs=project3d(md,'vector',self.vx_obs,'type','node') - self.vy_obs=project3d(md,'vector',self.vy_obs,'type','node') - self.vel_obs=project3d(md,'vector',self.vel_obs,'type','node') - self.thickness_obs=project3d(md,'vector',self.thickness_obs,'type','node') + def checkconsistency(self, md, solution, analyses): + if not self.iscontrol: + return md + if not IssmConfig('_HAVE_TAO_')[0]: + md = md.checkmessage('TAO has not been installed, ISSM needs to be reconfigured and recompiled with TAO') - if numel(self.cost_functions_coefficients) > 1: - self.cost_functions_coefficients=project3d(md,'vector',self.cost_functions_coefficients,'type','node') + num_controls = np.size(md.inversion.control_parameters) + num_costfunc = np.size(md.inversion.cost_functions) - if numel(self.min_parameters) > 1: - self.min_parameters=project3d(md,'vector',self.min_parameters,'type','node') + md = checkfield(md, 'fieldname', 'inversion.iscontrol', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'inversion.incomplete_adjoint', 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'inversion.control_parameters', 'cell', 1, 'values', supportedcontrols()) + md = checkfield(md, 'fieldname', 'inversion.maxsteps', 'numel', 1, '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.maxiter', 'numel', 1, '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.fatol', 'numel', 1, '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.frtol', 'numel', 1, '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.gatol', 'numel', 1, '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.grtol', 'numel', 1, '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.gttol', 'numel', 1, '>=', 0) - if numel(self.max_parameters)>1: - self.max_parameters=project3d(md,'vector',self.max_parameters,'type','node') + PETSCMAJOR = IssmConfig('_PETSC_MAJOR_')[0] + PETSCMINOR = IssmConfig('_PETSC_MINOR_')[0] + if(PETSCMAJOR > 3 or (PETSCMAJOR == 3 and PETSCMINOR >= 5)): + md = checkfield(md, 'fieldname', 'inversion.algorithm', 'values', ['blmvm', 'cg', 'lmvm']) + else: + md = checkfield(md, 'fieldname', 'inversion.algorithm', 'values', ['tao_blmvm', 'tao_cg', 'tao_lmvm']) - return self + md = checkfield(md, 'fieldname', 'inversion.cost_functions', 'size', [num_costfunc], 'values', supportedcostfunctions()) + md = checkfield(md, 'fieldname', 'inversion.cost_functions_coefficients', 'size', [md.mesh.numberofvertices, num_costfunc], '>=', 0) + md = checkfield(md, 'fieldname', 'inversion.min_parameters', 'size', [md.mesh.numberofvertices, num_controls]) + md = checkfield(md, 'fieldname', 'inversion.max_parameters', 'size', [md.mesh.numberofvertices, num_controls]) - def checkconsistency(self,md,solution,analyses): - if not self.iscontrol: - return md - if not IssmConfig('_HAVE_TAO_')[0]: - md = md.checkmessage('TAO has not been installed, ISSM needs to be reconfigured and recompiled with TAO') + if solution == 'BalancethicknessSolution': + md = checkfield(md, 'fieldname', 'inversion.thickness_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + elif solution == 'BalancethicknessSoftSolution': + md = checkfield(md, 'fieldname', 'inversion.thickness_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + else: + md = checkfield(md, 'fieldname', 'inversion.vx_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'inversion.vy_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1) + def marshall(self, prefix, md, fid): - num_controls= np.size(md.inversion.control_parameters) - num_costfunc= np.size(md.inversion.cost_functions) + yts = md.constants.yts + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'iscontrol', 'format', 'Boolean') + WriteData(fid, prefix, 'name', 'md.inversion.type', 'data', 1, 'format', 'Integer') + if not self.iscontrol: + return + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'incomplete_adjoint', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'maxsteps', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'maxiter', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'fatol', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'frtol', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'gatol', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'grtol', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'gttol', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'algorithm', 'format', 'String') + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'cost_functions_coefficients', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'min_parameters', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'max_parameters', 'format', 'DoubleMat', 'mattype', 3) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'vx_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'vy_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'vz_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'thickness_obs', 'format', 'DoubleMat', 'mattype', 1) + WriteData(fid, prefix, 'object', self, 'class', 'inversion', 'fieldname', 'surface_obs', 'format', 'DoubleMat', 'mattype', 1) - md = checkfield(md,'fieldname','inversion.iscontrol','values',[0, 1]) - md = checkfield(md,'fieldname','inversion.incomplete_adjoint','values',[0,1]) - md = checkfield(md,'fieldname','inversion.control_parameters','cell',1,'values',supportedcontrols()) - md = checkfield(md,'fieldname','inversion.maxsteps','numel',1,'>=',0) - md = checkfield(md,'fieldname','inversion.maxiter','numel',1,'>=',0) - md = checkfield(md,'fieldname','inversion.fatol','numel',1,'>=',0) - md = checkfield(md,'fieldname','inversion.frtol','numel',1,'>=',0) - md = checkfield(md,'fieldname','inversion.gatol','numel',1,'>=',0) - md = checkfield(md,'fieldname','inversion.grtol','numel',1,'>=',0) - md = checkfield(md,'fieldname','inversion.gttol','numel',1,'>=',0) + #process control parameters + num_control_parameters = np.size(self.control_parameters) + WriteData(fid, prefix, 'object', self, 'fieldname', 'control_parameters', 'format', 'StringArray') + WriteData(fid, prefix, 'data', num_control_parameters, 'name', 'md.inversion.num_control_parameters', 'format', 'Integer') - - PETSCMAJOR = IssmConfig('_PETSC_MAJOR_')[0] - PETSCMINOR = IssmConfig('_PETSC_MINOR_')[0] - if(PETSCMAJOR>3 or (PETSCMAJOR==3 and PETSCMINOR>=5)): - md = checkfield(md,'fieldname','inversion.algorithm','values',['blmvm','cg','lmvm']) - else: - md = checkfield(md,'fieldname','inversion.algorithm','values',['tao_blmvm','tao_cg','tao_lmvm']) - - - md = checkfield(md,'fieldname','inversion.cost_functions','size', [num_costfunc],'values',supportedcostfunctions()) - md = checkfield(md,'fieldname','inversion.cost_functions_coefficients','size',[md.mesh.numberofvertices, num_costfunc],'>=',0) - md = checkfield(md,'fieldname','inversion.min_parameters','size',[md.mesh.numberofvertices, num_controls]) - md = checkfield(md,'fieldname','inversion.max_parameters','size',[md.mesh.numberofvertices, num_controls]) - - - if solution=='BalancethicknessSolution': - md = checkfield(md,'fieldname','inversion.thickness_obs','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - elif solution=='BalancethicknessSoftSolution': - md = checkfield(md,'fieldname','inversion.thickness_obs','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - else: - md = checkfield(md,'fieldname','inversion.vx_obs','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','inversion.vy_obs','size',[md.mesh.numberofvertices],'NaN',1,'Inf',1) - - def marshall(self,prefix,md,fid): - - yts=md.constants.yts; - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','iscontrol','format','Boolean') - WriteData(fid,prefix,'name','md.inversion.type','data',1,'format','Integer') - if not self.iscontrol: - return - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','incomplete_adjoint','format','Boolean') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','maxsteps','format','Integer') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','maxiter','format','Integer') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','fatol','format','Double') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','frtol','format','Double') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','gatol','format','Double') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','grtol','format','Double') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','gttol','format','Double') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','algorithm','format','String') - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','cost_functions_coefficients','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','min_parameters','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','max_parameters','format','DoubleMat','mattype',3) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','vx_obs','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','vy_obs','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','vz_obs','format','DoubleMat','mattype',1,'scale',1./yts) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','thickness_obs','format','DoubleMat','mattype',1) - WriteData(fid,prefix,'object',self,'class','inversion','fieldname','surface_obs','format','DoubleMat','mattype',1) - - #process control parameters - num_control_parameters = np.size(self.control_parameters) - WriteData(fid,prefix,'object',self,'fieldname','control_parameters','format','StringArray') - WriteData(fid,prefix,'data',num_control_parameters,'name','md.inversion.num_control_parameters','format','Integer') - - #process cost functions - num_cost_functions = np.size(self.cost_functions) - data= marshallcostfunctions(self.cost_functions) - WriteData(fid,prefix,'data',data,'name','md.inversion.cost_functions','format','StringArray') - WriteData(fid,prefix,'data',num_cost_functions,'name','md.inversion.num_cost_functions','format','Integer') + #process cost functions + num_cost_functions = np.size(self.cost_functions) + data = marshallcostfunctions(self.cost_functions) + WriteData(fid, prefix, 'data', data, 'name', 'md.inversion.cost_functions', 'format', 'StringArray') + WriteData(fid, prefix, 'data', num_cost_functions, 'name', 'md.inversion.num_cost_functions', 'format', 'Integer') Index: /issm/trunk-jpl/src/m/classes/thermal.py =================================================================== --- /issm/trunk-jpl/src/m/classes/thermal.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/thermal.py (revision 24213) @@ -1,3 +1,3 @@ -import numpy as np +import numpy as np from project3d import project3d from fielddisplay import fielddisplay @@ -5,155 +5,146 @@ from WriteData import WriteData + class thermal(object): - """ - THERMAL class definition + """ + THERMAL class definition - Usage: - thermal=thermal(); - """ + Usage: + thermal = thermal() + """ - def __init__(self): # {{{ - self.spctemperature = float('NaN') - self.penalty_threshold = 0 - self.stabilization = 0 - self.reltol = 0 - self.maxiter = 0 - self.penalty_lock = 0 - self.penalty_factor = 0 - self.isenthalpy = 0 - self.isdynamicbasalspc = 0 - isdrainicecolumn = 0 - watercolumn_upperlimit = 0 - self.fe = 'P1' - self.requested_outputs = [] + def __init__(self): # {{{ + self.spctemperature = float('NaN') + self.penalty_threshold = 0 + self.stabilization = 0 + self.reltol = 0 + self.maxiter = 0 + self.penalty_lock = 0 + self.penalty_factor = 0 + self.isenthalpy = 0 + self.isdynamicbasalspc = 0 + self.isdrainicecolumn = 0 + self.watercolumn_upperlimit = 0 + self.fe = 'P1' + self.requested_outputs = [] - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' Thermal solution parameters:' - string="%s\n%s"%(string,fielddisplay(self,'spctemperature','temperature constraints (NaN means no constraint) [K]')) - string="%s\n%s"%(string,fielddisplay(self,'stabilization','0: no, 1: artificial_diffusivity, 2: SUPG')) - string="%s\n%s"%(string,fielddisplay(self,'maxiter','maximum number of non linear iterations')) - string="%s\n%s"%(string,fielddisplay(self,'reltol','relative tolerance criterion')) - string="%s\n%s"%(string,fielddisplay(self,'penalty_lock','stabilize unstable thermal constraints that keep zigzagging after n iteration (default is 0, no stabilization)')) - string="%s\n%s"%(string,fielddisplay(self,'penalty_threshold','threshold to declare convergence of thermal solution (default is 0)')) - string="%s\n%s"%(string,fielddisplay(self,'isenthalpy','use an enthalpy formulation to include temperate ice (default is 0)')) - string="%s\n%s"%(string,fielddisplay(self,'isdynamicbasalspc','enable dynamic setting of basal forcing. required for enthalpy formulation (default is 0)')) - string="%s\n%s"%(string,fielddisplay(self,'isdrainicecolumn','wether waterfraction drainage is enabled for enthalpy formulation (default is 1)')) - string="%s\n%s"%(string,fielddisplay(self,'watercolumn_upperlimit','upper limit of basal watercolumn for enthalpy formulation (default is 1000m)')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','additional outputs requested')) - return string - #}}} - def extrude(self,md): # {{{ - self.spctemperature=project3d(md,'vector',self.spctemperature,'type','node','layer',md.mesh.numberoflayers,'padding',np.nan) - if isinstance(md.initialization.temperature,np.ndarray) and np.size(md.initialization.temperature,axis=0)==md.mesh.numberofvertices: - self.spctemperature=float('NaN')*np.ones((md.mesh.numberofvertices)) - pos=np.where(md.mesh.vertexonsurface)[0] - self.spctemperature[pos]=md.initialization.temperature[pos] #impose observed temperature on surface - return self - #}}} - def defaultoutputs(self,md): # {{{ + #}}} - if self.isenthalpy: - return ['Enthalpy','Temperature','Waterfraction','Watercolumn','BasalforcingsGroundediceMeltingRate'] - else: - return ['Temperature','BasalforcingsGroundediceMeltingRate'] + def __repr__(self): # {{{ + string = ' Thermal solution parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'spctemperature', 'temperature constraints (NaN means no constraint) [K]')) + string = "%s\n%s" % (string, fielddisplay(self, 'stabilization', '0: no, 1: artificial_diffusivity, 2: SUPG')) + string = "%s\n%s" % (string, fielddisplay(self, 'maxiter', 'maximum number of non linear iterations')) + string = "%s\n%s" % (string, fielddisplay(self, 'reltol', 'relative tolerance criterion')) + string = "%s\n%s" % (string, fielddisplay(self, 'penalty_lock', 'stabilize unstable thermal constraints that keep zigzagging after n iteration (default is 0, no stabilization)')) + string = "%s\n%s" % (string, fielddisplay(self, 'penalty_threshold', 'threshold to declare convergence of thermal solution (default is 0)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isenthalpy', 'use an enthalpy formulation to include temperate ice (default is 0)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isdynamicbasalspc', 'enable dynamic setting of basal forcing. required for enthalpy formulation (default is 0)')) + string = "%s\n%s" % (string, fielddisplay(self, 'isdrainicecolumn', 'wether waterfraction drainage is enabled for enthalpy formulation (default is 1)')) + string = "%s\n%s" % (string, fielddisplay(self, 'watercolumn_upperlimit', 'upper limit of basal watercolumn for enthalpy formulation (default is 1000m)')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'additional outputs requested')) + return string + #}}} - #}}} - def setdefaultparameters(self): # {{{ - - #Number of unstable constraints acceptable - self.penalty_threshold=0 + def extrude(self, md): # {{{ + self.spctemperature = project3d(md, 'vector', self.spctemperature, 'type', 'node', 'layer', md.mesh.numberoflayers, 'padding', np.nan) + if isinstance(md.initialization.temperature, np.ndarray) and np.size(md.initialization.temperature, axis=0) == md.mesh.numberofvertices: + self.spctemperature = float('NaN') * np.ones((md.mesh.numberofvertices)) + pos = np.where(md.mesh.vertexonsurface)[0] + self.spctemperature[pos] = md.initialization.temperature[pos] #impose observed temperature on surface + return self + #}}} - #Type of stabilization used - self.stabilization=1 + def defaultoutputs(self, md): # {{{ + if self.isenthalpy: + return ['Enthalpy', 'Temperature', 'Waterfraction', 'Watercolumn', 'BasalforcingsGroundediceMeltingRate'] + else: + return ['Temperature', 'BasalforcingsGroundediceMeltingRate'] - #Relative tolerance for the enthalpy convergence - self.reltol=0.01 + #}}} - #Maximum number of iterations - self.maxiter=100 + def setdefaultparameters(self): # {{{ + #Number of unstable constraints acceptable + self.penalty_threshold = 0 + #Type of stabilization used + self.stabilization = 1 + #Relative tolerance for the enthalpy convergence + self.reltol = 0.01 + #Maximum number of iterations + self.maxiter = 100 + #factor used to compute the values of the penalties: kappa = max(stiffness matrix) * 10^penalty_factor + self.penalty_factor = 3 + #Should we use cold ice (default) or enthalpy formulation + self.isenthalpy = 0 + #will basal boundary conditions be set dynamically + self.isdynamicbasalspc = 0 + #wether waterfraction drainage is enabled + self.isdrainicecolumn = 1 + #set an upper limit for local stored watercolumn + self.watercolumn_upperlimit = 1000 + #Finite element interpolation + self.fe = 'P1' + #default output + self.requested_outputs = ['default'] + return self - #factor used to compute the values of the penalties: kappa=max(stiffness matrix)*10^penalty_factor - self.penalty_factor=3 + #}}} - #Should we use cold ice (default) or enthalpy formulation - self.isenthalpy=0 + def checkconsistency(self, md, solution, analyses): # {{{ + #Early return + if ('ThermalAnalysis' not in analyses and 'EnthalpyAnalysis' not in analyses) or (solution == 'TransientSolution' and not md.transient.isthermal): + return md - #will basal boundary conditions be set dynamically - self.isdynamicbasalspc=0 + md = checkfield(md, 'fieldname', 'thermal.stabilization', 'numel', [1], 'values', [0, 1, 2]) + md = checkfield(md, 'fieldname', 'thermal.spctemperature', 'Inf', 1, 'timeseries', 1) + md = checkfield(md, 'fieldname', 'thermal.requested_outputs', 'stringrow', 1) - #wether waterfraction drainage is enabled - self.isdrainicecolumn=1 + if 'EnthalpyAnalysis' in analyses and md.thermal.isenthalpy and md.mesh.dimension() == 3: + md = checkfield(md, 'fieldname', 'thermal.isdrainicecolumn', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'thermal.watercolumn_upperlimit', '>=', 0) - #set an upper limit for local stored watercolumn - self.watercolumn_upperlimit=1000 + TEMP = md.thermal.spctemperature[: - 1].flatten(- 1) + pos = np.where(~np.isnan(TEMP)) + try: + spccol = np.size(md.thermal.spctemperature, 1) + except IndexError: + spccol = 1 - #Finite element interpolation - self.fe='P1' + replicate = np.tile(md.geometry.surface - md.mesh.z, (spccol)).flatten(-1) + control = md.materials.meltingpoint - md.materials.beta * md.materials.rho_ice * md.constants.g * replicate + 1.0e-5 + md = checkfield(md, 'fieldname', 'thermal.spctemperature', 'field', md.thermal.spctemperature.flatten(- 1)[pos], '<=', control[pos], 'message', "spctemperature should be below the adjusted melting point") + md = checkfield(md, 'fieldname', 'thermal.isenthalpy', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'thermal.isdynamicbasalspc', 'numel', [1], 'values', [0, 1]) + if(md.thermal.isenthalpy): + if np.isnan(md.stressbalance.reltol): + md.checkmessage("for a steadystate computation, thermal.reltol (relative convergence criterion) must be defined!") + md = checkfield(md, 'fieldname', 'thermal.reltol', '>', 0., 'message', "reltol must be larger than zero") - #default output - self.requested_outputs=['default'] - return self + return md + # }}} - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'spctemperature', 'format', 'DoubleMat', 'mattype', 1, 'timeserieslength', md.mesh.numberofvertices + 1, 'yts', md.constants.yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'penalty_threshold', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'stabilization', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'reltol', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'maxiter', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'penalty_lock', 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'penalty_factor', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isenthalpy', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isdrainicecolumn', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'watercolumn_upperlimit', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'fieldname', 'fe', 'format', 'String') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isdynamicbasalspc', 'format', 'Boolean') - #Early return - if ('ThermalAnalysis' not in analyses and 'EnthalpyAnalysis' not in analyses) or (solution=='TransientSolution' and not md.transient.isthermal): - return md - - md = checkfield(md,'fieldname','thermal.stabilization','numel',[1],'values',[0,1,2]) - md = checkfield(md,'fieldname','thermal.spctemperature','Inf',1,'timeseries',1) - md = checkfield(md,'fieldname','thermal.requested_outputs','stringrow',1) - - if 'EnthalpyAnalysis' in analyses and md.thermal.isenthalpy and md.mesh.dimension()==3: - md = checkfield(md,'fieldname','thermal.isdrainicecolumn','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','thermal.watercolumn_upperlimit','>=',0) - - TEMP = md.thermal.spctemperature[:-1].flatten(-1) - pos=np.where(~np.isnan(TEMP)) - try: - spccol=np.size(md.thermal.spctemperature,1) - except IndexError: - spccol=1 - - replicate=np.tile(md.geometry.surface-md.mesh.z,(spccol)).flatten(-1) - - control=md.materials.meltingpoint-md.materials.beta*md.materials.rho_ice*md.constants.g*replicate+10**-5 - - md = checkfield(md,'fieldname','thermal.spctemperature','field',md.thermal.spctemperature.flatten(-1)[pos],'<=',control[pos],'message',"spctemperature should be below the adjusted melting point") - md = checkfield(md,'fieldname','thermal.isenthalpy','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','thermal.isdynamicbasalspc','numel',[1],'values',[0,1]) - if(md.thermal.isenthalpy): - if np.isnan(md.stressbalance.reltol): - md.checkmessage("for a steadystate computation, thermal.reltol (relative convergence criterion) must be defined!") - md = checkfield(md,'fieldname','thermal.reltol','>',0.,'message',"reltol must be larger than zero") - - - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','spctemperature','format','DoubleMat','mattype',1,'timeserieslength',md.mesh.numberofvertices+1,'yts',md.constants.yts) - WriteData(fid,prefix,'object',self,'fieldname','penalty_threshold','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','stabilization','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','reltol','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','maxiter','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','penalty_lock','format','Integer') - WriteData(fid,prefix,'object',self,'fieldname','penalty_factor','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','isenthalpy','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isdrainicecolumn','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','watercolumn_upperlimit','format','Double') - WriteData(fid,prefix,'object',self,'fieldname','fe','format','String') - WriteData(fid,prefix,'object',self,'fieldname','isdynamicbasalspc','format','Boolean') - - #process requested outputs - outputs = self.requested_outputs - indices = [i for i, x in enumerate(outputs) if x == 'default'] - if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.thermal.requested_outputs','format','StringArray') - # }}} + #process requested outputs + outputs = self.requested_outputs + indices = [i for i, x in enumerate(outputs) if x == 'default'] + if len(indices) > 0: + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.thermal.requested_outputs', 'format', 'StringArray') + # }}} Index: /issm/trunk-jpl/src/m/classes/timestepping.py =================================================================== --- /issm/trunk-jpl/src/m/classes/timestepping.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/timestepping.py (revision 24213) @@ -3,65 +3,67 @@ from WriteData import WriteData + class timestepping(object): - """ - TIMESTEPPING Class definition + """ + TIMESTEPPING Class definition - Usage: - timestepping=timestepping(); - """ + Usage: + timestepping = timestepping() + """ - def __init__(self): # {{{ - self.start_time = 0. - self.final_time = 0. - self.time_step = 0. - self.interp_forcings = 1 - self.coupling_time = 0. - - #set defaults - self.setdefaultparameters() + def __init__(self): # {{{ + self.start_time = 0. + self.final_time = 0. + self.time_step = 0. + self.interp_forcings = 1 + self.coupling_time = 0. - #}}} - def __repr__(self): # {{{ - string=" timestepping parameters:" - string="%s\n%s"%(string,fielddisplay(self,"start_time","simulation starting time [yr]")) - string="%s\n%s"%(string,fielddisplay(self,"final_time","final time to stop the simulation [yr]")) - string="%s\n%s"%(string,fielddisplay(self,"time_step","length of time steps [yr]")) - string="%s\n%s"%(string,fielddisplay(self,"interp_forcings","interpolate in time between requested forcing values ? (0 or 1)")) - string="%s\n%s"%(string,fielddisplay(self,"coupling_time","length of coupling time steps with ocean model [yr]")) - return string - #}}} - def setdefaultparameters(self): # {{{ - - #time between 2 time steps - self.time_step=1./2. + #set defaults + self.setdefaultparameters() - #final time - self.final_time=10.*self.time_step + #}}} - #should we interpolate forcings between timesteps? - self.interp_forcings=1 + def __repr__(self): # {{{ + string = " timestepping parameters:" + string = "%s\n%s" % (string, fielddisplay(self, "start_time", "simulation starting time [yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "final_time", "final time to stop the simulation [yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "time_step", "length of time steps [yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "interp_forcings", "interpolate in time between requested forcing values ? (0 or 1)")) + string = "%s\n%s" % (string, fielddisplay(self, "coupling_time", "length of coupling time steps with ocean model [yr]")) + return string + #}}} - return self - #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def setdefaultparameters(self): # {{{ + #time between 2 time steps + self.time_step = 1. / 2. + #final time + self.final_time = 10. * self.time_step + #should we interpolate forcings between timesteps? + self.interp_forcings = 1 - md = checkfield(md,'fieldname','timestepping.start_time','numel',[1],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','timestepping.final_time','numel',[1],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','timestepping.time_step','numel',[1],'>=',0,'NaN',1,'Inf',1) - if self.final_time-self.start_time<0: - md.checkmessage("timestepping.final_time should be larger than timestepping.start_time") - md = checkfield(md,'fieldname','timestepping.coupling_time','numel',[1],'>=',0,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','timestepping.interp_forcings','numel',[1],'values',[0,1]) + return self + #}}} - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ - yts=md.constants.yts - WriteData(fid,prefix,'name','md.timestepping.type','data',1,'format','Integer'); - WriteData(fid,prefix,'object',self,'fieldname','start_time','format','Double','scale',yts) - WriteData(fid,prefix,'object',self,'fieldname','final_time','format','Double','scale',yts) - WriteData(fid,prefix,'object',self,'fieldname','time_step','format','Double','scale',yts) - WriteData(fid,prefix,'object',self,'fieldname','interp_forcings','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','coupling_time','format','Double','scale',yts) - # }}} + md = checkfield(md, 'fieldname', 'timestepping.start_time', 'numel', [1], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'timestepping.final_time', 'numel', [1], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'timestepping.time_step', 'numel', [1], '>=', 0, 'NaN', 1, 'Inf', 1) + if self.final_time - self.start_time < 0: + md.checkmessage("timestepping.final_time should be larger than timestepping.start_time") + md = checkfield(md, 'fieldname', 'timestepping.coupling_time', 'numel', [1], '>=', 0, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'timestepping.interp_forcings', 'numel', [1], 'values', [0, 1]) + + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + + yts = md.constants.yts + WriteData(fid, prefix, 'name', 'md.timestepping.type', 'data', 1, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'fieldname', 'start_time', 'format', 'Double', 'scale', yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'final_time', 'format', 'Double', 'scale', yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'time_step', 'format', 'Double', 'scale', yts) + WriteData(fid, prefix, 'object', self, 'fieldname', 'interp_forcings', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'coupling_time', 'format', 'Double', 'scale', yts) + # }}} Index: /issm/trunk-jpl/src/m/classes/timesteppingadaptive.py =================================================================== --- /issm/trunk-jpl/src/m/classes/timesteppingadaptive.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/timesteppingadaptive.py (revision 24213) @@ -3,91 +3,87 @@ from WriteData import WriteData + class timesteppingadaptive(object): - """ - TIMESTEPPINGADAPTIVE Class definition + """ + TIMESTEPPINGADAPTIVE Class definition - Usage: - timesteppingadaptive=timesteppingadaptive(); - """ + Usage: + timesteppingadaptive = timesteppingadaptive() + """ - def __init__(self,*args): # {{{ - if not len(args): - self.start_time = 0. - self.final_time = 0. - self.time_step_min = 0. - self.time_step_max = 0. - self.cfl_coefficient = 0. - self.interp_forcings = 1 - self.coupling_time = 0. + def __init__(self, *args): # {{{ + if not len(args): + self.start_time = 0. + self.final_time = 0. + self.time_step_min = 0. + self.time_step_max = 0. + self.cfl_coefficient = 0. + self.interp_forcings = 1 + self.coupling_time = 0. - #set defaults - self.setdefaultparameters() + #set defaults + self.setdefaultparameters() - elif len(args)==1 and args[0].__module__=='timestepping': - old=args[0] - #first call setdefaultparameters: - self.setdefaultparameters() - self.start_time = old.start_time - self.final_time = old.final_time - self.interp_forcings = old.interp_forcings - self.coupling_time = old.coupling_time + elif len(args) == 1 and args[0].__module__ == 'timestepping': + old = args[0] + #first call setdefaultparameters: + self.setdefaultparameters() + self.start_time = old.start_time + self.final_time = old.final_time + self.interp_forcings = old.interp_forcings + self.coupling_time = old.coupling_time - else: - raise Exception('constructor not supported') - #}}} + else: + raise Exception('constructor not supported') + #}}} - def __repr__(self): # {{{ - string=" timesteppingadaptive parameters:" - string="%s\n%s"%(string,fielddisplay(self,"start_time","simulation starting time [yr]")) - string="%s\n%s"%(string,fielddisplay(self,"final_time","final time to stop the simulation [yr]")) - string="%s\n%s"%(string,fielddisplay(self,"time_step_min","minimum length of time steps [yr]")) - string="%s\n%s"%(string,fielddisplay(self,"time_step_max","maximum length of time steps [yr]")) - string="%s\n%s"%(string,fielddisplay(self,"cfl_coefficient","coefficient applied to cfl condition")) - string="%s\n%s"%(string,fielddisplay(self,"interp_forcings","interpolate in time between requested forcing values ? (0 or 1)")) - string="%s\n%s"%(string,fielddisplay(self,"coupling_time","coupling time steps with ocean model [yr]")) - return string - # }}} + def __repr__(self): # {{{ + string = " timesteppingadaptive parameters:" + string = "%s\n%s" % (string, fielddisplay(self, "start_time", "simulation starting time [yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "final_time", "final time to stop the simulation [yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "time_step_min", "minimum length of time steps [yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "time_step_max", "maximum length of time steps [yr]")) + string = "%s\n%s" % (string, fielddisplay(self, "cfl_coefficient", "coefficient applied to cfl condition")) + string = "%s\n%s" % (string, fielddisplay(self, "interp_forcings", "interpolate in time between requested forcing values ? (0 or 1)")) + string = "%s\n%s" % (string, fielddisplay(self, "coupling_time", "coupling time steps with ocean model [yr]")) + return string + # }}} - def setdefaultparameters(self): # {{{ + def setdefaultparameters(self): # {{{ + #time between 2 time steps + self.time_step_min = 0.01 + self.time_step_max = 10. + #final time + self.final_time = 10. * self.time_step_max + #time adaptation? + self.cfl_coefficient = 0.5 + #should we interpolate forcings between timesteps? + self.interp_forcings = 1 + return self + #}}} - #time between 2 time steps - self.time_step_min=0.01 - self.time_step_max=10. + def checkconsistency(self, md, solution, analyses): # {{{ + md = checkfield(md, 'fieldname', 'timestepping.start_time', 'numel', [1], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'timestepping.final_time', 'numel', [1], 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'timestepping.time_step_min', 'numel', [1], '>=', 0, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'timestepping.time_step_max', 'numel', [1], '>=', md.timestepping.time_step_min, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'timestepping.cfl_coefficient', 'numel', [1], '>', 0, '<=', 1) + if self.final_time - self.start_time < 0: + md.checkmessage("timestepping.final_time should be larger than timestepping.start_time") + md = checkfield(md, 'fieldname', 'timestepping.interp_forcings', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'timestepping.coupling_time', 'numel', [1], '>=', 0, 'NaN', 1, 'Inf', 1) - #final time - self.final_time=10.*self.time_step_max + return md + # }}} - #time adaptation? - self.cfl_coefficient=0.5 - - #should we interpolate forcings between timesteps? - self.interp_forcings=1 - - return self - #}}} - - def checkconsistency(self,md,solution,analyses): # {{{ - md = checkfield(md,'fieldname','timestepping.start_time','numel',[1],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','timestepping.final_time','numel',[1],'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','timestepping.time_step_min','numel',[1],'>=',0,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','timestepping.time_step_max','numel',[1],'>=',md.timestepping.time_step_min,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','timestepping.cfl_coefficient','numel',[1],'>',0,'<=',1) - if self.final_time-self.start_time<0: - md.checkmessage("timestepping.final_time should be larger than timestepping.start_time") - md = checkfield(md,'fieldname','timestepping.interp_forcings','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','timestepping.coupling_time','numel',[1],'>=',0,'NaN',1,'Inf',1) - - return md - # }}} - - def marshall(self,prefix,md,fid): # {{{ - yts=md.constants.yts - WriteData(fid,prefix,'name','md.timestepping.type','data',2,'format','Integer'); - WriteData(fid,prefix,'object',self,'class','timestepping','fieldname','start_time','format','Double','scale',yts) - WriteData(fid,prefix,'object',self,'class','timestepping','fieldname','final_time','format','Double','scale',yts) - WriteData(fid,prefix,'object',self,'class','timestepping','fieldname','time_step_min','format','Double','scale',yts) - WriteData(fid,prefix,'object',self,'class','timestepping','fieldname','time_step_max','format','Double','scale',yts) - WriteData(fid,prefix,'object',self,'class','timestepping','fieldname','cfl_coefficient','format','Double') - WriteData(fid,prefix,'object',self,'class','timestepping','fieldname','interp_forcings','format','Boolean') - WriteData(fid,prefix,'object',self,'class','timestepping','fieldname','coupling_time','format','Double','scale',yts) - # }}} + def marshall(self, prefix, md, fid): # {{{ + yts = md.constants.yts + WriteData(fid, prefix, 'name', 'md.timestepping.type', 'data', 2, 'format', 'Integer') + WriteData(fid, prefix, 'object', self, 'class', 'timestepping', 'fieldname', 'start_time', 'format', 'Double', 'scale', yts) + WriteData(fid, prefix, 'object', self, 'class', 'timestepping', 'fieldname', 'final_time', 'format', 'Double', 'scale', yts) + WriteData(fid, prefix, 'object', self, 'class', 'timestepping', 'fieldname', 'time_step_min', 'format', 'Double', 'scale', yts) + WriteData(fid, prefix, 'object', self, 'class', 'timestepping', 'fieldname', 'time_step_max', 'format', 'Double', 'scale', yts) + WriteData(fid, prefix, 'object', self, 'class', 'timestepping', 'fieldname', 'cfl_coefficient', 'format', 'Double') + WriteData(fid, prefix, 'object', self, 'class', 'timestepping', 'fieldname', 'interp_forcings', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'class', 'timestepping', 'fieldname', 'coupling_time', 'format', 'Double', 'scale', yts) + # }}} Index: /issm/trunk-jpl/src/m/classes/toolkits.py =================================================================== --- /issm/trunk-jpl/src/m/classes/toolkits.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/toolkits.py (revision 24213) @@ -12,8 +12,8 @@ Usage: - self=toolkits(); + self = toolkits() """ - def __init__(self): # {{{ + def __init__(self): # {{{ #default toolkits if IssmConfig('_HAVE_PETSC_')[0]: @@ -34,7 +34,8 @@ self.RecoveryAnalysis = self.DefaultAnalysis - #The other properties are dynamic + #The other properties are dynamic # }}} - def __repr__(self): # {{{ + + def __repr__(self): # {{{ s = "List of toolkits options per analysis:\n\n" for analysis in list(vars(self).keys()): @@ -44,8 +45,8 @@ # }}} - def addoptions(self, analysis, *args): # {{{ + def addoptions(self, analysis, *args): # {{{ # Usage example: - # md.toolkits=addoptions(md.toolkits,'StressbalanceAnalysis',FSoptions()); - # md.toolkits=addoptions(md.toolkits,'StressbalanceAnalysis'); + # md.toolkits = addoptions(md.toolkits, 'StressbalanceAnalysis', FSoptions()) + # md.toolkits = addoptions(md.toolkits, 'StressbalanceAnalysis') #Create dynamic property if property does not exist yet @@ -60,5 +61,5 @@ # }}} - def checkconsistency(self, md, solution, analyses): # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ for analysis in list(vars(self).keys()): if not getattr(self, analysis): @@ -68,44 +69,44 @@ # }}} - def ToolkitsFile(self, filename): # {{{ + def ToolkitsFile(self, filename): # {{{ """ - TOOLKITSFILE- build toolkits file + TOOLKITSFILE - build toolkits file - Build a Petsc compatible options file, from the toolkits model field + return options string + Build a Petsc compatible options file, from the toolkits model field + return options string This file will also be used when the toolkit used is 'issm' instead of 'petsc' - Usage: ToolkitsFile(toolkits,filename); + Usage: ToolkitsFile(toolkits, filename) """ - #open file for writing + #open file for writing try: fid = open(filename, 'w') except IOError as e: - raise IOError("ToolkitsFile error: could not open '%s' for writing." % filename) + raise IOError("ToolkitsFile error: could not open {}' for writing due to".format(filename), e) - #write header + #write header fid.write("%s%s%s\n" % ('%Toolkits options file: ', filename, ' written from Python toolkits array')) - #start writing options + #start writing options for analysis in list(vars(self).keys()): options = getattr(self, analysis) - #first write analysis: - fid.write("\n+%s\n" % analysis) #append a + to recognize it's an analysis enum - #now, write options + #first write analysis: + fid.write("\n+{}\n".format(analysis)) #append a + to recognize it's an analysis enum + #now, write options for optionname, optionvalue in list(options.items()): if not optionvalue: #this option has only one argument - fid.write("-%s\n" % optionname) + fid.write("-{}\n".format(optionname)) else: #option with value. value can be string or scalar if isinstance(optionvalue, (bool, int, float)): - fid.write("-%s %g\n" % (optionname, optionvalue)) + fid.write("-{} {}\n".format(optionname, optionvalue)) elif isinstance(optionvalue, str): - fid.write("-%s %s\n" % (optionname, optionvalue)) + fid.write("-{} {}\n".format(optionname, optionvalue)) else: - raise TypeError("ToolkitsFile error: option '%s' is not well formatted." % optionname) + raise TypeError("ToolkitsFile error: option '{}' is not well formatted.".format(optionname)) fid.close() Index: /issm/trunk-jpl/src/m/classes/transient.py =================================================================== --- /issm/trunk-jpl/src/m/classes/transient.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/transient.py (revision 24213) @@ -2,4 +2,5 @@ from checkfield import checkfield from WriteData import WriteData + class transient(object): @@ -8,48 +9,49 @@ Usage: - transient=transient(); + transient = transient() """ - def __init__(self): # {{{ - self.issmb = False - self.ismasstransport = False - self.isstressbalance = False - self.isthermal = False - self.isgroundingline = False - self.isgia = False - self.isesa = False + def __init__(self): # {{{ + self.issmb = False + self.ismasstransport = False + self.isstressbalance = False + self.isthermal = False + self.isgroundingline = False + self.isgia = False + self.isesa = False self.isdamageevolution = False - self.ismovingfront = False - self.ishydrology = False - self.isslr = False - self.iscoupler = False - self.amr_frequency = 0 - self.isoceancoupling = False + self.ismovingfront = False + self.ishydrology = False + self.isslr = False + self.iscoupler = False + self.amr_frequency = 0 + self.isoceancoupling = False self.requested_outputs = [] - #set defaults + #set defaults self.setdefaultparameters() - #}}} - def __repr__(self): # {{{ - string=' transient solution parameters:' - string="%s\n%s"%(string,fielddisplay(self,'issmb','indicates if a surface mass balance solution is used in the transient')) - string="%s\n%s"%(string,fielddisplay(self,'ismasstransport','indicates if a masstransport solution is used in the transient')) - string="%s\n%s"%(string,fielddisplay(self,'isstressbalance','indicates if a stressbalance solution is used in the transient')) - string="%s\n%s"%(string,fielddisplay(self,'isthermal','indicates if a thermal solution is used in the transient')) - string="%s\n%s"%(string,fielddisplay(self,'isgroundingline','indicates if a groundingline migration is used in the transient')) - string="%s\n%s"%(string,fielddisplay(self,'isgia','indicates if a postglacial rebound is used in the transient')) - string="%s\n%s"%(string,fielddisplay(self,'isesa','indicates whether an elastic adjustment model is used in the transient')) - string="%s\n%s"%(string,fielddisplay(self,'isdamageevolution','indicates whether damage evolution is used in the transient')) - string="%s\n%s"%(string,fielddisplay(self,'ismovingfront','indicates whether a moving front capability is used in the transient')) - string="%s\n%s"%(string,fielddisplay(self,'ishydrology','indicates whether an hydrology model is used')) - string="%s\n%s"%(string,fielddisplay(self,'isslr','indicates if a sea level rise solution is used in the transient')) - string="%s\n%s"%(string,fielddisplay(self,'isoceancoupling','indicates whether coupling with an ocean model is used in the transient')) - string="%s\n%s"%(string,fielddisplay(self,'iscoupler','indicates whether different models are being run with need for coupling')) - string="%s\n%s"%(string,fielddisplay(self,'amr_frequency','frequency at which mesh is refined in simulations with multiple time_steps')) - string="%s\n%s"%(string,fielddisplay(self,'requested_outputs','list of additional outputs requested')) + #}}} + def __repr__(self): # {{{ + string = ' transient solution parameters:' + string = "%s\n%s" % (string, fielddisplay(self, 'issmb', 'indicates if a surface mass balance solution is used in the transient')) + string = "%s\n%s" % (string, fielddisplay(self, 'ismasstransport', 'indicates if a masstransport solution is used in the transient')) + string = "%s\n%s" % (string, fielddisplay(self, 'isstressbalance', 'indicates if a stressbalance solution is used in the transient')) + string = "%s\n%s" % (string, fielddisplay(self, 'isthermal', 'indicates if a thermal solution is used in the transient')) + string = "%s\n%s" % (string, fielddisplay(self, 'isgroundingline', 'indicates if a groundingline migration is used in the transient')) + string = "%s\n%s" % (string, fielddisplay(self, 'isgia', 'indicates if a postglacial rebound is used in the transient')) + string = "%s\n%s" % (string, fielddisplay(self, 'isesa', 'indicates whether an elastic adjustment model is used in the transient')) + string = "%s\n%s" % (string, fielddisplay(self, 'isdamageevolution', 'indicates whether damage evolution is used in the transient')) + string = "%s\n%s" % (string, fielddisplay(self, 'ismovingfront', 'indicates whether a moving front capability is used in the transient')) + string = "%s\n%s" % (string, fielddisplay(self, 'ishydrology', 'indicates whether an hydrology model is used')) + string = "%s\n%s" % (string, fielddisplay(self, 'isslr', 'indicates if a sea level rise solution is used in the transient')) + string = "%s\n%s" % (string, fielddisplay(self, 'isoceancoupling', 'indicates whether coupling with an ocean model is used in the transient')) + string = "%s\n%s" % (string, fielddisplay(self, 'iscoupler', 'indicates whether different models are being run with need for coupling')) + string = "%s\n%s" % (string, fielddisplay(self, 'amr_frequency', 'frequency at which mesh is refined in simulations with multiple time_steps')) + string = "%s\n%s" % (string, fielddisplay(self, 'requested_outputs', 'list of additional outputs requested')) return string - #}}} - def defaultoutputs(self,md): # {{{ + #}}} + + def defaultoutputs(self, md): # {{{ if self.issmb: @@ -59,119 +61,121 @@ #}}} - def setallnullparameters(self): # {{{ - + + def setallnullparameters(self): # {{{ #Nothing done - self.issmb = False - self.ismasstransport = False - self.isstressbalance = False - self.isthermal = False - self.isgroundingline = False - self.isgia = False - self.isesa = False + self.issmb = False + self.ismasstransport = False + self.isstressbalance = False + self.isthermal = False + self.isgroundingline = False + self.isgia = False + self.isesa = False self.isdamageevolution = False - self.ismovingfront = False - self.ishydrology = False - self.isoceancoupling = False - self.isslr = False - self.iscoupler = False - self.amr_frequency = 0 + self.ismovingfront = False + self.ishydrology = False + self.isoceancoupling = False + self.isslr = False + self.iscoupler = False + self.amr_frequency = 0 - #default output - self.requested_outputs=[] + #default output + self.requested_outputs = [] return self #}}} - def deactivateall(self):#{{{ - self.issmb = False - self.ismasstransport = False - self.isstressbalance = False - self.isthermal = False - self.isgroundingline = False - self.isgia = False - self.isesa = False + + def deactivateall(self): #{{{ + self.issmb = False + self.ismasstransport = False + self.isstressbalance = False + self.isthermal = False + self.isgroundingline = False + self.isgia = False + self.isesa = False self.isdamageevolution = False - self.ismovingfront = False - self.ishydrology = False - self.isslr = False - self.isoceancoupling = False - self.iscoupler = False - self.amr_frequency = 0 + self.ismovingfront = False + self.ishydrology = False + self.isslr = False + self.isoceancoupling = False + self.iscoupler = False + self.amr_frequency = 0 - #default output - self.requested_outputs=[] + #default output + self.requested_outputs = [] return self #}}} - def setdefaultparameters(self): # {{{ - + + def setdefaultparameters(self): # {{{ #full analysis: Stressbalance, Masstransport and Thermal but no groundingline migration for now - self.issmb = True - self.ismasstransport = True - self.isstressbalance = True - self.isthermal = True - self.isgroundingline = False - self.isgia = False - self.isesa = False + self.issmb = True + self.ismasstransport = True + self.isstressbalance = True + self.isthermal = True + self.isgroundingline = False + self.isgia = False + self.isesa = False self.isdamageevolution = False - self.ismovingfront = False - self.ishydrology = False - self.isslr = False - self.isoceancoupling = False - self.iscoupler = False - self.amr_frequency = 0 + self.ismovingfront = False + self.ishydrology = False + self.isslr = False + self.isoceancoupling = False + self.iscoupler = False + self.amr_frequency = 0 - #default output - self.requested_outputs=['default'] + #default output + self.requested_outputs = ['default'] return self #}}} - def checkconsistency(self,md,solution,analyses): # {{{ + def checkconsistency(self, md, solution, analyses): # {{{ #Early return - if not solution=='TransientSolution': + if not solution == 'TransientSolution': return md - md = checkfield(md,'fieldname','transient.issmb','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','transient.ismasstransport','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','transient.isstressbalance','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','transient.isthermal','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','transient.isgroundingline','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','transient.isgia','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','transient.isesa','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','transient.isdamageevolution','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','transient.ishydrology','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','transient.ismovingfront','numel',[1],'values',[0,1]); - md = checkfield(md,'fieldname','transient.isslr','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','transient.isoceancoupling','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','transient.iscoupler','numel',[1],'values',[0,1]) - md = checkfield(md,'fieldname','transient.amr_frequency','numel',[1],'>=',0,'NaN',1,'Inf',1) - md = checkfield(md,'fieldname','transient.requested_outputs','stringrow',1) + md = checkfield(md, 'fieldname', 'transient.issmb', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.ismasstransport', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.isstressbalance', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.isthermal', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.isgroundingline', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.isgia', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.isesa', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.isdamageevolution', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.ishydrology', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.ismovingfront', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.isslr', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.isoceancoupling', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.iscoupler', 'numel', [1], 'values', [0, 1]) + md = checkfield(md, 'fieldname', 'transient.amr_frequency', 'numel', [1], '>=', 0, 'NaN', 1, 'Inf', 1) + md = checkfield(md, 'fieldname', 'transient.requested_outputs', 'stringrow', 1) - if (solution!='TransientSolution') and (md.transient.iscoupling): + if (solution != 'TransientSolution') and (md.transient.iscoupling): md.checkmessage("Coupling with ocean can only be done in transient simulations!") - if (md.transient.isdamageevolution and not hasattr(md.materials,'matdamageice')): + if (md.transient.isdamageevolution and not hasattr(md.materials, 'matdamageice')): md.checkmessage("requesting damage evolution but md.materials is not of class matdamageice") return md # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'object',self,'fieldname','issmb','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','ismasstransport','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isstressbalance','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isthermal','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isgroundingline','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isgia','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isesa','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isdamageevolution','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','ishydrology','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','ismovingfront','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isslr','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','isoceancoupling','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','iscoupler','format','Boolean') - WriteData(fid,prefix,'object',self,'fieldname','amr_frequency','format','Integer') - #process requested outputs + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'object', self, 'fieldname', 'issmb', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'ismasstransport', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isstressbalance', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isthermal', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isgroundingline', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isgia', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isesa', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isdamageevolution', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'ishydrology', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'ismovingfront', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isslr', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'isoceancoupling', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'iscoupler', 'format', 'Boolean') + WriteData(fid, prefix, 'object', self, 'fieldname', 'amr_frequency', 'format', 'Integer') + + #process requested outputs outputs = self.requested_outputs indices = [i for i, x in enumerate(outputs) if x == 'default'] if len(indices) > 0: - outputscopy=outputs[0:max(0,indices[0]-1)]+self.defaultoutputs(md)+outputs[indices[0]+1:] - outputs =outputscopy - WriteData(fid,prefix,'data',outputs,'name','md.transient.requested_outputs','format','StringArray') + outputscopy = outputs[0:max(0, indices[0] - 1)] + self.defaultoutputs(md) + outputs[indices[0] + 1:] + outputs = outputscopy + WriteData(fid, prefix, 'data', outputs, 'name', 'md.transient.requested_outputs', 'format', 'StringArray') # }}} Index: /issm/trunk-jpl/src/m/classes/verbose.py =================================================================== --- /issm/trunk-jpl/src/m/classes/verbose.py (revision 24212) +++ /issm/trunk-jpl/src/m/classes/verbose.py (revision 24213) @@ -1,137 +1,141 @@ from pairoptions import pairoptions -import MatlabFuncs as m from WriteData import WriteData + class verbose(object): - """ - VERBOSE class definition + """ + VERBOSE class definition - Available verbosity levels: - mprocessor : model processing - module : modules - solution : solution sequence - solver : solver info (extensive) - convergence : convergence criteria - control : control method - qmu : sensitivity analysis - autodiff : AD analysis - smb : SMB analysis + Available verbosity levels: + mprocessor : model processing + module : modules + solution : solution sequence + solver : solver info (extensive) + convergence : convergence criteria + control : control method + qmu : sensitivity analysis + autodiff : AD analysis + smb : SMB analysis - Usage: - verbose=verbose(); - verbose=verbose(3); - verbose=verbose('001100'); - verbose=verbose('module',True,'solver',False); + Usage: + verbose = verbose() + verbose = verbose(3) + verbose = verbose('001100') + verbose = verbose('module', True, 'solver', False) - WARNING: some parts of this file are Synchronized with src/c/shared/Numerics/Verbosity.h - Do not modify these sections. See src/c/shared/Numerics/README for more info - """ + WARNING: some parts of this file are Synchronized with src / c / shared / Numerics / Verbosity.h + Do not modify these sections. See src / c / shared / Numerics / README for more info + """ - def __init__(self,*args): # {{{ - #BEGINFIELDS - self.mprocessor = False - self.module = False - self.solution = False - self.solver = False - self.convergence = False - self.control = False - self.qmu = False - self.autodiff = False - self.smb = False - #ENDFIELDS + def __init__(self, *args): # {{{ + #BEGINFIELDS + self.mprocessor = False + self.module = False + self.solution = False + self.solver = False + self.convergence = False + self.control = False + self.qmu = False + self.autodiff = False + self.smb = False + #ENDFIELDS - if not len(args): - #Don't do anything - self.solution=True; - self.qmu=True; - self.control=True; - pass + if not len(args): + #Don't do anything + self.solution = True + self.qmu = True + self.control = True + pass - elif len(args) == 1: - binary=args[0] - if isinstance(binary,str): - if binary.lower()=='all': - binary=2**11-1 #all ones - self.BinaryToVerbose(binary) - self.solver=False #Do not use by default - else: - binary=int(binary,2) - self.BinaryToVerbose(binary) - elif isinstance(binary,(int,float)): - self.BinaryToVerbose(int(binary)) + elif len(args) == 1: + binary = args[0] + if isinstance(binary, str): + if binary.lower() == 'all': + binary = 2**11 - 1 #all ones + self.BinaryToVerbose(binary) + self.solver = False #Do not use by default + else: + binary = int(binary, 2) + self.BinaryToVerbose(binary) + elif isinstance(binary, (int, float)): + self.BinaryToVerbose(int(binary)) - else: - #Use options to initialize object - self=pairoptions(*args).AssignObjectFields(self) + else: + #Use options to initialize object + self = pairoptions(*args).AssignObjectFields(self) - #Cast to logicals - listproperties=vars(self) - for fieldname,fieldvalue in list(listproperties.items()): - if isinstance(fieldvalue,bool) or isinstance(fieldvalue,(int,float)): - setattr(self,fieldname,bool(fieldvalue)) - else: - raise TypeError("verbose supported field values are logicals only (True or False)") - # }}} - def __repr__(self): # {{{ - - #BEGINDISP - s ="class '%s' = \n" % type(self) - s+=" %15s : %s\n" % ('mprocessor',self.mprocessor) - s+=" %15s : %s\n" % ('module',self.module) - s+=" %15s : %s\n" % ('solution',self.solution) - s+=" %15s : %s\n" % ('solver',self.solver) - s+=" %15s : %s\n" % ('convergence',self.convergence) - s+=" %15s : %s\n" % ('control',self.control) - s+=" %15s : %s\n" % ('qmu',self.qmu) - s+=" %15s : %s\n" % ('autodiff',self.autodiff) - s+=" %15s : %s\n" % ('smb',self.smb) - #ENDDISP + #Cast to logicals + listproperties = vars(self) + for fieldname, fieldvalue in list(listproperties.items()): + if isinstance(fieldvalue, bool) or isinstance(fieldvalue, (int, float)): + setattr(self, fieldname, bool(fieldvalue)) + else: + raise TypeError("verbose supported field values are logicals only (True or False)") + # }}} - return s - # }}} - def VerboseToBinary(self): # {{{ + def __repr__(self): # {{{ - #BEGINVERB2BIN - binary=0 - if self.mprocessor: - binary=binary | 1 - if self.module: - binary=binary | 2 - if self.solution: - binary=binary | 4 - if self.solver: - binary=binary | 8 - if self.convergence: - binary=binary | 16 - if self.control: - binary=binary | 32 - if self.qmu: - binary=binary | 64 - if self.autodiff: - binary=binary | 128 - if self.smb: - binary=binary | 256 - #ENDVERB2BIN + #BEGINDISP + s = "class '%s' = \n" % type(self) + s += " %15s : %s\n" % ('mprocessor', self.mprocessor) + s += " %15s : %s\n" % ('module', self.module) + s += " %15s : %s\n" % ('solution', self.solution) + s += " %15s : %s\n" % ('solver', self.solver) + s += " %15s : %s\n" % ('convergence', self.convergence) + s += " %15s : %s\n" % ('control', self.control) + s += " %15s : %s\n" % ('qmu', self.qmu) + s += " %15s : %s\n" % ('autodiff', self.autodiff) + s += " %15s : %s\n" % ('smb', self.smb) + #ENDDISP - return binary - # }}} - def BinaryToVerbose(self,binary): # {{{ + return s + # }}} - #BEGINBIN2VERB - self.mprocessor =bool(binary & 1) - self.module =bool(binary & 2) - self.solution =bool(binary & 4) - self.solver =bool(binary & 8) - self.convergence=bool(binary & 16) - self.control =bool(binary & 32) - self.qmu =bool(binary & 64) - self.autodiff =bool(binary & 128) - self.smb =bool(binary & 256) - #ENDBIN2VERB - # }}} - def checkconsistency(self,md,solution,analyses): # {{{ - return md - # }}} - def marshall(self,prefix,md,fid): # {{{ - WriteData(fid,prefix,'data',self.VerboseToBinary(),'name','md.verbose','format','Integer') - # }}} + def VerboseToBinary(self): # {{{ + #BEGINVERB2BIN + binary = 0 + if self.mprocessor: + binary = binary | 1 + if self.module: + binary = binary | 2 + if self.solution: + binary = binary | 4 + if self.solver: + binary = binary | 8 + if self.convergence: + binary = binary | 16 + if self.control: + binary = binary | 32 + if self.qmu: + binary = binary | 64 + if self.autodiff: + binary = binary | 128 + if self.smb: + binary = binary | 256 + #ENDVERB2BIN + + return binary + # }}} + + def BinaryToVerbose(self, binary): # {{{ + + #BEGINBIN2VERB + self.mprocessor = bool(binary & 1) + self.module = bool(binary & 2) + self.solution = bool(binary & 4) + self.solver = bool(binary & 8) + self.convergence = bool(binary & 16) + self.control = bool(binary & 32) + self.qmu = bool(binary & 64) + self.autodiff = bool(binary & 128) + self.smb = bool(binary & 256) + #ENDBIN2VERB + # }}} + + def checkconsistency(self, md, solution, analyses): # {{{ + return md + # }}} + + def marshall(self, prefix, md, fid): # {{{ + WriteData(fid, prefix, 'data', self.VerboseToBinary(), 'name', 'md.verbose', 'format', 'Integer') + # }}} Index: /issm/trunk-jpl/src/m/consistency/QueueRequirements.py =================================================================== --- /issm/trunk-jpl/src/m/consistency/QueueRequirements.py (revision 24212) +++ /issm/trunk-jpl/src/m/consistency/QueueRequirements.py (revision 24213) @@ -1,20 +1,20 @@ -def QueueRequirements(queudict,queue,np,time): - #QUEUEREQUIREMENTS - queue requirements in time, number of cpus, by name of queue. - # - # Usage: - # QueueRequirements(available_queues,queue_requirements_time,queue_requirements_np,np,time) +def QueueRequirements(queudict, queue, np, time): + #QUEUEREQUIREMENTS - queue requirements in time, number of cpus, by name of queue. + # + # Usage: + # QueueRequirements(available_queues, queue_requirements_time, queue_requirements_np, np, time) - #Ok, go through requirements for current queue: - try: - rtime=queudict[queue][0] - except KeyError: - raise Exception('QueueRequirements error message: availables queues are '+ queuedict.keys) - - if time<=0: - raise Exception('QueueRequirements: time should be a positive number') - if time>rtime: - raise Exception('QueueRequirements: time should be < '+ str(rtime)+ ' for queue: '+ queue) + #Ok, go through requirements for current queue: + try: + rtime = queudict[queue][0] + except KeyError: + raise Exception('QueueRequirements error message: availables queues are ' + queudict.keys) - #check on np requirements - if np<=0: - raise Exception('QueueRequirements: np should be a positive number') + if time <= 0: + raise Exception('QueueRequirements: time should be a positive number') + if time > rtime: + raise Exception('QueueRequirements: time should be < ' + str(rtime) + ' for queue: ' + queue) + + #check on np requirements + if np <= 0: + raise Exception('QueueRequirements: np should be a positive number') Index: /issm/trunk-jpl/src/m/consistency/checkfield.py =================================================================== --- /issm/trunk-jpl/src/m/consistency/checkfield.py (revision 24212) +++ /issm/trunk-jpl/src/m/consistency/checkfield.py (revision 24213) @@ -1,10 +1,11 @@ import numpy as np import os -from re import findall,split +from re import findall, split from pairoptions import pairoptions from operator import attrgetter import MatlabFuncs as m -def checkfield(md,*args): + +def checkfield(md, *args): """ CHECKFIELD - check field consistency @@ -16,96 +17,94 @@ Available options: - - NaN: 1 if check that there is no NaN - - size: [lines cols], NaN for non checked dimensions, or 'universal' for any input type (nodal, element, time series, etc) - - >: greater than provided value - - >=: greater or equal to provided value - - <: smallerthan provided value - - <=: smaller or equal to provided value - - < vec: smallerthan provided values on each vertex - - timeseries: 1 if check time series consistency (size and time) - - values: cell of strings or vector of acceptable values - - numel: list of acceptable number of elements - - cell: 1 if check that is cell - - empty: 1 if check that non empty - - message: overloaded error message + - NaN: 1 if check that there is no NaN + - size: [lines cols], NaN for non checked dimensions, or 'universal' for any input type (nodal, element, time series, etc) + - > : greater than provided value + - >= : greater or equal to provided value + - < : smallerthan provided value + - <=: smaller or equal to provided value + - < vec: smallerthan provided values on each vertex + - timeseries: 1 if check time series consistency (size and time) + - values: cell of strings or vector of acceptable values + - numel: list of acceptable number of elements + - cell: 1 if check that is cell + - empty: 1 if check that non empty + - message: overloaded error message Usage: - md = checkfield(md,fieldname,options); + md = checkfield(md, fieldname, options) """ #get options - options=pairoptions(*args) + options = pairoptions(*args) #get field from model if options.exist('field'): - field=options.getfieldvalue('field') - fieldname=options.getfieldvalue('fieldname','no fieldname') + field = options.getfieldvalue('field') + fieldname = options.getfieldvalue('fieldname', 'no fieldname') else: - fieldname=options.getfieldvalue('fieldname') - fieldprefix=split(r'\[(.*?)\]',fieldname)[0] - fieldindexes=findall(r'\[(.*?)\]',fieldname) - field=attrgetter(fieldprefix)(md) + fieldname = options.getfieldvalue('fieldname') + fieldprefix = split(r'\[(.*?)\]', fieldname)[0] + fieldindexes = findall(r'\[(.*?)\]', fieldname) + field = attrgetter(fieldprefix)(md) for index in fieldindexes: try: - field=field[index.strip("\'")] + field = field[index.strip("\'")] except TypeError: - field=field[int(index)] #looking for an index and not a key - -# that works for py2 -# exec("field=md.{}".format(fieldname)) -# exec("field=md.{}".format(fieldname),namespace) - - - if isinstance(field,(bool,int,float)): - field=np.array([field]) + field = field[int(index)] #looking for an index and not a key + + # that works for py2 + # exec("field = md.{}".format(fieldname)) + # exec("field = md.{}".format(fieldname), namespace) + + if isinstance(field, (bool, int, float)): + field = np.array([field]) #check empty if options.exist('empty'): if not field: - md = md.checkmessage(options.getfieldvalue('message', - "field '%s' is empty" % fieldname)) + md = md.checkmessage(options.getfieldvalue('message', "field '{}' is empty".format(fieldname))) #Check size if options.exist('size'): - fieldsize=options.getfieldvalue('size') + fieldsize = options.getfieldvalue('size') if type(fieldsize) == str: - if m.strcmp(fieldsize,'universal'): + if m.strcmp(fieldsize, 'universal'): #Check that vector size will not be confusing for ModelProcessorx - if (md.mesh.numberofvertices==md.mesh.numberofelements): + if (md.mesh.numberofvertices == md.mesh.numberofelements): raise RuntimeError('number of vertices is the same as number of elements') - elif (md.mesh.numberofvertices+1==md.mesh.numberofelements): - raise RuntimeError('number of vertices +1 is the same as number of elements') - elif (md.mesh.numberofvertices==md.mesh.numberofelements+1): - raise RuntimeError('number of vertices is the same as number of elements +1') - + elif (md.mesh.numberofvertices + 1 == md.mesh.numberofelements): + raise RuntimeError('number of vertices + 1 is the same as number of elements') + elif (md.mesh.numberofvertices == md.mesh.numberofelements + 1): + raise RuntimeError('number of vertices is the same as number of elements + 1') + #Uniform field - if (np.size(field,0)==1): - if (np.shape(field)[1]!=1): - md = md.checkmessage(options.getfieldvalue('message',"field '{}' is not supported".format(fieldname))) + if (np.size(field, 0) == 1): + if (np.shape(field)[1] != 1): + md = md.checkmessage(options.getfieldvalue('message', "field '{}' is not supported".format(fieldname))) #vertex oriented input, only one column allowed - elif (np.shape(field)[0]==md.mesh.numberofvertices): - if (np.shape(field)[1]!=1): - md = md.checkmessage(options.getfieldvalue('message',"field '{}' is not supported".format(fieldname))) - - #element oriented input, one or more column (patch) is ok - elif (np.shape(field)[0]==md.mesh.numberofelements): + elif (np.shape(field)[0] == md.mesh.numberofvertices): + if (np.shape(field)[1] != 1): + md = md.checkmessage(options.getfieldvalue('message', "field '{}' is not supported".format(fieldname))) + + #element oriented input, one or more column (patch) is ok + elif (np.shape(field)[0] == md.mesh.numberofelements): + #nothing to do here (either constant per element, or defined on nodes) pass - #nothing to do here (either constant per element, or defined on nodes) #vertex time series - elif (np.shape(field)[0]==md.mesh.numberofvertices+1): - if (np.shape(field)[1]<=1): - md = md.checkmessage(options.getfieldvalue('message',"field '{}' is not supported".format(fieldname))) + elif (np.shape(field)[0] == md.mesh.numberofvertices + 1): + if (np.shape(field)[1] <= 1): + md = md.checkmessage(options.getfieldvalue('message', "field '{}' is not supported".format(fieldname))) #element time series - elif (np.shape(field)[0]==md.mesh.numberofelements+1): - if (np.shape(field)[1]<=1): - md = md.checkmessage(options.getfieldvalue('message',"field '{}' is not supported".format(fieldname))) + elif (np.shape(field)[0] == md.mesh.numberofelements + 1): + if (np.shape(field)[1] <= 1): + md = md.checkmessage(options.getfieldvalue('message', "field '{}' is not supported".format(fieldname))) #else not supported else: - md = md.checkmessage(options.getfieldvalue('message',"field '{}' is not supported".format(fieldname))) + md = md.checkmessage(options.getfieldvalue('message', "field '{}' is not supported".format(fieldname))) else: @@ -114,57 +113,46 @@ else: if len(np.shape(field)) < len(fieldsize): - md = md.checkmessage(options.getfieldvalue('message',"field {} has size {} but should be size {}".format(fieldname,np.shape(field),fieldsize))) + md = md.checkmessage(options.getfieldvalue('message', "field {} has size {} but should be size {}".format(fieldname, np.shape(field), fieldsize))) else: for i in range(np.size(fieldsize)): if (not np.isnan(fieldsize[i])) and (np.shape(field)[i] != fieldsize[i]): - md = md.checkmessage(options.getfieldvalue('message',"field {} dimension # {} should be of size {}".format(fieldname,i,fieldsize[i]))) + md = md.checkmessage(options.getfieldvalue('message', "field {} dimension # {} should be of size {}".format(fieldname, i, fieldsize[i]))) #Check numel if options.exist('numel'): - fieldnumel=options.getfieldvalue('numel') + fieldnumel = options.getfieldvalue('numel') if (type(fieldnumel) == int and np.size(field) != fieldnumel) or (type(fieldnumel) == list and np.size(field) not in fieldnumel): - if len(fieldnumel)==1: - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' size should be %d" % (fieldname,fieldnumel))) - elif len(fieldnumel)==2: - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' size should be %d or %d" % (fieldname,fieldnumel[0],fieldnumel[1]))) - else: - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' size should be %s" % (fieldname,fieldnumel))) + if len(fieldnumel) == 1: + md = md.checkmessage(options.getfieldvalue('message', "field '{}' size should be {}".format(fieldname, fieldnumel))) + elif len(fieldnumel) == 2: + md = md.checkmessage(options.getfieldvalue('message', "field '{}' size should be {} or {}".format(fieldname, fieldnumel[0], fieldnumel[1]))) + else: + md = md.checkmessage(options.getfieldvalue('message', "field '{}' size should be {}".format(fieldname, fieldnumel))) #check NaN - if options.getfieldvalue('NaN',0): + if options.getfieldvalue('NaN', 0): if np.any(np.isnan(field)): - md = md.checkmessage(options.getfieldvalue('message',\ - "NaN values found in field '%s'" % fieldname)) - + md = md.checkmessage(options.getfieldvalue('message', "NaN values found in field '{}'".format(fieldname))) #check Inf - if options.getfieldvalue('Inf',0): + if options.getfieldvalue('Inf', 0): if np.any(np.isinf(field)): - md = md.checkmessage(options.getfieldvalue('message',\ - "Inf values found in field '%s'" % fieldname)) - + md = md.checkmessage(options.getfieldvalue('message', "Inf values found in field '{}'".format(fieldname))) #check cell - if options.getfieldvalue('cell',0): - if not isinstance(field,(tuple,list,dict)): - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' should be a cell" % fieldname)) + if options.getfieldvalue('cell', 0): + if not isinstance(field, (tuple, list, dict)): + md = md.checkmessage(options.getfieldvalue('message', "field '{}' should be a cell".format(fieldname))) #check values if options.exist('values'): - fieldvalues=options.getfieldvalue('values') - if False in m.ismember(field,fieldvalues): - if len(fieldvalues)==1: - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' value should be '%s'" % (fieldname,fieldvalues[0]))) - elif len(fieldvalues)==2: - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' values should be '%s' or '%s'" % (fieldname,fieldvalues[0],fieldvalues[1]))) - else: - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' should have values in %s" % (fieldname,fieldvalues))) + fieldvalues = options.getfieldvalue('values') + if False in m.ismember(field, fieldvalues): + if len(fieldvalues) == 1: + md = md.checkmessage(options.getfieldvalue('message', "field '{}' value should be '{}'".format(fieldname, fieldvalues[0]))) + elif len(fieldvalues) == 2: + md = md.checkmessage(options.getfieldvalue('message', "field '{}' values should be '{}' or '%s'".format(fieldname, fieldvalues[0], fieldvalues[1]))) + else: + md = md.checkmessage(options.getfieldvalue('message', "field '{}' should have values in {}".format(fieldname, fieldvalues))) #check greater @@ -172,128 +160,119 @@ lowerbound = options.getfieldvalue('>=') if type(lowerbound) is str: - lowerbound=attrgetter(lowerbound)(md) - if np.size(lowerbound)>1: #checking elementwise - if any(field 1: #checking elementwise + if any(field < lowerbound): + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should have values above %d" % (fieldname, lowerbound))) + else: + minval = np.nanmin(field) + if options.getfieldvalue('timeseries', 0): + minval = np.nanmin(field[: - 1]) + elif options.getfieldvalue('singletimeseries', 0): + if np.size(field) == 1: #some singletimeseries are just one value + minval = field + else: + minval = np.nanmin(field[0]) + + if minval < lowerbound: + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should have values above %d" % (fieldname, lowerbound))) if options.exist('>'): - lowerbound=options.getfieldvalue('>') + lowerbound = options.getfieldvalue('>') if type(lowerbound) is str: - lowerbound=attrgetter(lowerbound)(md) - if np.size(lowerbound)>1: #checking elementwise - if any(field<=upperbound): - md = md.checkmessage(options.getfieldvalue('message',"field '%s' should have values below %d" % (fieldname,upperbound))) - else: - minval=np.nanmin(field) - if options.getfieldvalue('timeseries',0) : - minval=np.nanmin(field[:-1]) - elif options.getfieldvalue('singletimeseries',0): - if np.size(field)==1: #some singletimeseries are just one value - minval=field - else: - minval=np.nanmin(field[0]) - - if minval<=lowerbound: - md = md.checkmessage(options.getfieldvalue('message',"field '%s' should have values above %d" % (fieldname,lowerbound))) + lowerbound = attrgetter(lowerbound)(md) + if np.size(lowerbound) > 1: #checking elementwise + if any(field <= lowerbound): + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should have values above %d" % (fieldname, lowerbound))) + else: + minval = np.nanmin(field) + if options.getfieldvalue('timeseries', 0): + minval = np.nanmin(field[: - 1]) + elif options.getfieldvalue('singletimeseries', 0): + if np.size(field) == 1: #some singletimeseries are just one value + minval = field + else: + minval = np.nanmin(field[0]) + + if minval <= lowerbound: + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should have values above %d" % (fieldname, lowerbound))) #check smaller if options.exist('<='): - upperbound=options.getfieldvalue('<=') + upperbound = options.getfieldvalue('<=') if type(upperbound) is str: - upperbound=attrgetter(upperbound)(md) - if np.size(upperbound)>1: #checking elementwise - if any(field>upperbound): - md = md.checkmessage(options.getfieldvalue('message',"field '%s' should have values below %d" % (fieldname,upperbound))) - else: - maxval=np.nanmax(field) - if options.getfieldvalue('timeseries',0): - maxval=np.nanmax(field[:-1]) - elif options.getfieldvalue('singletimeseries',0): - if np.size(field)==1: #some singletimeseries are just one value - maxval=field - else: - maxval=np.nanmax(field[0]) + upperbound = attrgetter(upperbound)(md) + if np.size(upperbound) > 1: #checking elementwise + if any(field > upperbound): + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should have values below %d" % (fieldname, upperbound))) + else: + maxval = np.nanmax(field) + if options.getfieldvalue('timeseries', 0): + maxval = np.nanmax(field[: - 1]) + elif options.getfieldvalue('singletimeseries', 0): + if np.size(field) == 1: #some singletimeseries are just one value + maxval = field + else: + maxval = np.nanmax(field[0]) elif hasattr(field, 'fov_forward_indices'): - maxval=field.fov_forward_indices[0] - if maxval>upperbound: - md = md.checkmessage(options.getfieldvalue('message',"field '%s' should have values below %d" % (fieldname,upperbound))) + maxval = field.fov_forward_indices[0] + if maxval > upperbound: + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should have values below %d" % (fieldname, upperbound))) if options.exist('<'): - upperbound=options.getfieldvalue('<') + upperbound = options.getfieldvalue('<') if type(upperbound) is str: - upperbound=attrgetter(upperbound)(md) - if np.size(upperbound)>1: #checking elementwise - if any(field>=upperbound): - md = md.checkmessage(options.getfieldvalue('message',"field '%s' should have values below %d" % (fieldname,upperbound))) - - else: - maxval=np.nanmax(field) - if options.getfieldvalue('timeseries',0): - maxval=np.nanmax(field[:-1]) - elif options.getfieldvalue('singletimeseries',0): - if np.size(field)==1: #some singletimeseries are just one value - maxval=field.copy() - else: - maxval=np.nanmax(field[0]) - - if maxval>=upperbound: - md = md.checkmessage(options.getfieldvalue('message',"field '%s' should have values below %d" % (fieldname,upperbound))) + upperbound = attrgetter(upperbound)(md) + if np.size(upperbound) > 1: #checking elementwise + if any(field >= upperbound): + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should have values below %d" % (fieldname, upperbound))) + + else: + maxval = np.nanmax(field) + if options.getfieldvalue('timeseries', 0): + maxval = np.nanmax(field[: - 1]) + elif options.getfieldvalue('singletimeseries', 0): + if np.size(field) == 1: #some singletimeseries are just one value + maxval = field.copy() + else: + maxval = np.nanmax(field[0]) + + if maxval >= upperbound: + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should have values below %d" % (fieldname, upperbound))) #check file - if options.getfieldvalue('file',0): + if options.getfieldvalue('file', 0): if not os.path.exists(field): - md = md.checkmessage("file provided in '%s': '%s' does not exist" % (fieldname,field)) + md = md.checkmessage("file provided in '%s': '%s' does not exist" % (fieldname, field)) #Check row of strings if options.exist('stringrow'): - if not isinstance(field,list): - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' should be a list" %fieldname)) + if not isinstance(field, list): + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should be a list" % fieldname)) #Check forcings (size and times) - if options.getfieldvalue('timeseries',0): - if np.size(field,0)==md.mesh.numberofvertices or np.size(field,0)==md.mesh.numberofelements: - if np.ndim(field)>1 and not np.size(field,1)==1: - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' should have only one column as there are md.mesh.numberofvertices lines" % fieldname)) - elif np.size(field,0)==md.mesh.numberofvertices+1 or np.size(field,0)==md.mesh.numberofelements+1: - if np.ndim(field) > 1 and not all(field[-1,:]==np.sort(field[-1,:])): - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' columns should be sorted chronologically" % fieldname)) - if np.ndim(field) > 1 and any(field[-1,0:-1]==field[-1,1:]): - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' columns must not contain duplicate timesteps" % fieldname)) - else: - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' should have md.mesh.numberofvertices or md.mesh.numberofvertices+1 lines" % fieldname)) + if options.getfieldvalue('timeseries', 0): + if np.size(field, 0) == md.mesh.numberofvertices or np.size(field, 0) == md.mesh.numberofelements: + if np.ndim(field) > 1 and not np.size(field, 1) == 1: + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should have only one column as there are md.mesh.numberofvertices lines" % fieldname)) + elif np.size(field, 0) == md.mesh.numberofvertices + 1 or np.size(field, 0) == md.mesh.numberofelements + 1: + if np.ndim(field) > 1 and not all(field[-1, :] == np.sort(field[-1, :])): + md = md.checkmessage(options.getfieldvalue('message', "field '%s' columns should be sorted chronologically" % fieldname)) + if np.ndim(field) > 1 and any(field[-1, 0:-1] == field[-1, 1:]): + md = md.checkmessage(options.getfieldvalue('message', "field '%s' columns must not contain duplicate timesteps" % fieldname)) + else: + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should have md.mesh.numberofvertices or md.mesh.numberofvertices + 1 lines" % fieldname)) #Check single value forcings (size and times) - if options.getfieldvalue('singletimeseries',0): - if np.size(field,0)==2: - if not all(field[-1,:]==np.sort(field[-1,:])): - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' columns should be sorted chronologically" % fieldname)) - if any(field[-1,0:-1]==field[-1,1:]): - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' columns must not contain duplicate timesteps" % fieldname)) - elif np.size(field,0) == 1: - if np.ndim(field) > 1 and not np.size(field,1) == 1: - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' should be either a scalar or have 2 lines" % fieldname)) - else: - md = md.checkmessage(options.getfieldvalue('message',\ - "field '%s' should have 2 lines or be a scalar" % fieldname)) + if options.getfieldvalue('singletimeseries', 0): + if np.size(field, 0) == 2: + if not all(field[-1, :] == np.sort(field[-1, :])): + md = md.checkmessage(options.getfieldvalue('message', "field '%s' columns should be sorted chronologically" % fieldname)) + if any(field[-1, 0:-1] == field[-1, 1:]): + md = md.checkmessage(options.getfieldvalue('message', "field '%s' columns must not contain duplicate timesteps" % fieldname)) + elif np.size(field, 0) == 1: + if np.ndim(field) > 1 and not np.size(field, 1) == 1: + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should be either a scalar or have 2 lines" % fieldname)) + else: + md = md.checkmessage(options.getfieldvalue('message', "field '%s' should have 2 lines or be a scalar" % fieldname)) return md Index: /issm/trunk-jpl/src/m/consistency/ismodelselfconsistent.m =================================================================== --- /issm/trunk-jpl/src/m/consistency/ismodelselfconsistent.m (revision 24212) +++ /issm/trunk-jpl/src/m/consistency/ismodelselfconsistent.m (revision 24213) @@ -39,5 +39,5 @@ function [analyses]=AnalysisConfiguration(solutiontype), % {{{ -%ANALYSISCONFIGURATION - return type of analyses, number of analyses +%ANALYSISCONFIGURATION - return type of analyses, number of analyses % % Usage: @@ -71,5 +71,5 @@ analyses={'EsaAnalysis'}; elseif strcmp(solutiontype,'TransientSolution') - analyses={'StressbalanceAnalysis','StressbalanceVerticalAnalysis','StressbalanceSIAAnalysis','L2ProjectionBaseAnalysis','ThermalAnalysis','MeltingAnalysis','EnthalpyAnalysis','MasstransportAnalysis','HydrologyShaktiAnalysis','HydrologyGladsAnalysis'}; + analyses={'StressbalanceAnalysis','StressbalanceVerticalAnalysis','StressbalanceSIAAnalysis','L2ProjectionBaseAnalysis','ThermalAnalysis','MeltingAnalysis','EnthalpyAnalysis','MasstransportAnalysis','HydrologyShaktiAnalysis','HydrologyGladsAnalysis','HydrologyDCInefficientAnalysis','HydrologyDCEfficientAnalysis'}; elseif strcmp(solutiontype,'SealevelriseSolution') analyses={'SealevelriseAnalysis'}; Index: /issm/trunk-jpl/src/m/consistency/ismodelselfconsistent.py =================================================================== --- /issm/trunk-jpl/src/m/consistency/ismodelselfconsistent.py (revision 24212) +++ /issm/trunk-jpl/src/m/consistency/ismodelselfconsistent.py (revision 24213) @@ -4,5 +4,5 @@ Usage: - [analyses]=AnalysisConfiguration(solutiontype); + [analyses] = AnalysisConfiguration(solutiontype) """ @@ -28,5 +28,5 @@ analyses = ['LoveAnalysis'] elif solutiontype == 'TransientSolution': - analyses = ['StressbalanceAnalysis', 'StressbalanceVerticalAnalysis', 'StressbalanceSIAAnalysis', 'L2ProjectionBaseAnalysis', 'ThermalAnalysis', 'MeltingAnalysis', 'EnthalpyAnalysis', 'MasstransportAnalysis','HydrologyShaktiAnalysis','HydrologyGladsAnalysis'] + analyses = ['StressbalanceAnalysis', 'StressbalanceVerticalAnalysis', 'StressbalanceSIAAnalysis', 'L2ProjectionBaseAnalysis', 'ThermalAnalysis', 'MeltingAnalysis', 'EnthalpyAnalysis', 'MasstransportAnalysis', 'HydrologyShaktiAnalysis', 'HydrologyGladsAnalysis', 'HydrologyDCInefficientAnalysis', 'HydrologyDCEfficientAnalysis'] elif solutiontype == 'HydrologySolution': analyses = ['L2ProjectionBaseAnalysis', 'HydrologyShreveAnalysis', 'HydrologyDCInefficientAnalysis', 'HydrologyDCEfficientAnalysis'] @@ -38,5 +38,5 @@ return analyses -#}}} + #}}} @@ -55,10 +55,8 @@ solution = md.private.solution analyses = AnalysisConfiguration(solution) - - #Go through a model fields, check that it is a class, and call checkconsistency + #Go through a model fields, check that it is a class, and call checkconsistency #fields = vars(md) #for field in fields.iterkeys(): for field in md.properties(): - #Some properties do not need to be checked if field in ['results', 'debug', 'radaroverlay']: @@ -70,7 +68,7 @@ #Check consistency of the object - exec("md.{}.checkconsistency(md, solution, analyses)".format(field)) + exec("md.{}.checkconsistency(md, '{}', {})".format(field, solution, analyses)) #error message if mode is not consistent if not md.private.isconsistent: - raise RuntimeError('Model not consistent, see messages above.') + raise RuntimeError('Model not consistent, see messages above.') Index: /issm/trunk-jpl/src/m/contrib/defleurian/netCDF/export_netCDF.py =================================================================== --- /issm/trunk-jpl/src/m/contrib/defleurian/netCDF/export_netCDF.py (revision 24212) +++ /issm/trunk-jpl/src/m/contrib/defleurian/netCDF/export_netCDF.py (revision 24213) @@ -27,5 +27,5 @@ dimindex = 1 dimlist = [2, md.mesh.numberofelements, md.mesh.numberofvertices, np.shape(md.mesh.elements)[1]] - print('===Creating dimensions===') + print(' == =Creating dimensions == = ') for i in range(0, 4): if dimlist[i] not in list(DimDict.keys()): @@ -38,10 +38,10 @@ groups = dict.keys(md.__dict__) # get all model classes and create respective groups - print('===Creating and populating groups===') + print(' == =Creating and populating groups == = ') for group in groups: NCgroup = NCData.createGroup(str(group)) - # In each group gather the fields of the class + # In each group gather the fields of the class fields = dict.keys(md.__dict__[group].__dict__) - # looping on fields + # looping on fields for field in fields: # Special treatment for list fields @@ -80,5 +80,5 @@ Var = md.__dict__[group].__dict__[field].__getitem__(listindex)[subfield] DimDict = CreateVar(NCData, Var, subfield, Listgroup, DimDict, md.__dict__[group], field, listindex) - # No subgroup, we directly treat the variable + # No subgroup, we directly treat the variable elif type(md.__dict__[group].__dict__[field]) in typelist or field == 'bamg': NCgroup.__setattr__('classtype', md.__dict__[group].__class__.__name__) @@ -87,6 +87,6 @@ elif md.__dict__[group].__dict__[field] is None: print('field md.{}.{} is None'.format(group, field)) - # do nothing - # if it is a masked array + # do nothing + # if it is a masked array elif type(md.__dict__[group].__dict__[field]) is np.ma.core.MaskedArray: NCgroup.__setattr__('classtype', md.__dict__[group].__class__.__name__) @@ -104,9 +104,9 @@ NCData.close() -# ============================================================================ -# Define the variables - - -def CreateVar(NCData, var, field, Group, DimDict, *step_args): + # == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == + # Define the variables + + +def CreateVar(NCData, var, field, Group, DimDict, * step_args): # grab type try: @@ -136,5 +136,5 @@ elif val_type == list: dimensions, DimDict = GetDim(NCData, val_shape, val_type, DimDict, val_dim) - # try to get the type from the first element + # try to get the type from the first element try: nctype = TypeDict[type(var[0])] @@ -176,6 +176,6 @@ return DimDict -# ============================================================================ -# retriev the dimension tuple from a dictionnary + # == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == == + # retriev the dimension tuple from a dictionnary Index: /issm/trunk-jpl/src/m/contrib/defleurian/netCDF/read_netCDF.py =================================================================== --- /issm/trunk-jpl/src/m/contrib/defleurian/netCDF/read_netCDF.py (revision 24212) +++ /issm/trunk-jpl/src/m/contrib/defleurian/netCDF/read_netCDF.py (revision 24213) @@ -1,20 +1,22 @@ from netCDF4 import Dataset +from os import path + def netCDFRead(filename): - def walktree(data): - keys = list(data.groups.keys()) - yield keys - for key in keys: - for children in walktree(data.groups[str(key)]): - yield children + def walktree(data): + keys = list(data.groups.keys()) + yield keys + for key in keys: + for children in walktree(data.groups[str(key)]): + yield children - if path.exists(filename): - print(('Opening {} for reading '.format(filename))) - NCData=Dataset(filename, 'r') - class_dict={} + if path.exists(filename): + print(('Opening {} for reading '.format(filename))) + NCData = Dataset(filename, 'r') + class_dict = {} - for children in walktree(NCData): - for child in children: - class_dict[str(child)]=str(getattr(NCData.groups[str(child)],'classtype')+'()') + for children in walktree(NCData): + for child in children: + class_dict[str(child)] = str(getattr(NCData.groups[str(child)], 'classtype') + '()') - print(class_dict) + print(class_dict) Index: /issm/trunk-jpl/src/m/contrib/defleurian/paraview/enveloppeVTK.py =================================================================== --- /issm/trunk-jpl/src/m/contrib/defleurian/paraview/enveloppeVTK.py (revision 24212) +++ /issm/trunk-jpl/src/m/contrib/defleurian/paraview/enveloppeVTK.py (revision 24213) @@ -1,170 +1,171 @@ import numpy as np import os -import model import glob -def enveloppeVTK(filename,model,*args): - ''' - vtk export - function exportVTK(filename,model) - creates a directory with the vtk files for displays in paraview - (only work for triangle and wedges based on their number of nodes) - Give only the results for nw but could be extended to geometry, mask... - input: filename destination - (string) - ------------------------------------------------------------------ -model this is md - ------------------------------------------------------------------ - By default only the results are exported, you can add whichever - field you need as a string: - add 'geometry' to export md.geometry +def enveloppeVTK(filename, model, *args): + ''' + vtk export + function exportVTK(filename, model) + creates a directory with the vtk files for displays in paraview + (only work for triangle and wedges based on their number of nodes) - Basile de Fleurian: - ''' - Dir=os.path.basename(filename) - Path=filename[:-len(Dir)] + Give only the results for nw but could be extended to geometry, mask... - if os.path.exists(filename): - print(('File {} allready exist'.format(filename))) - newname=input('Give a new name or "delete" to replace: ') - if newname=='delete': - filelist = glob.glob(filename+'/*') - for oldfile in filelist: - os.remove(oldfile) - else: - print(('New file name is {}'.format(newname))) - filename=newname - os.mkdir(filename) - else: - os.mkdir(filename) + input: filename destination + (string) + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + model this is md + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + By default only the results are exported, you can add whichever + field you need as a string: + add 'geometry' to export md.geometry - # {{{get the element related variables - if 'z' in dict.keys(model.mesh.__dict__): - is_enveloppe=np.logical_or(model.mesh.vertexonbase,model.mesh.vertexonsurface) - enveloppe_index=np.where(is_enveloppe)[0] - convert_index=np.nan*np.ones(np.shape(model.mesh.x)) - convert_index=np.asarray([[i,np.where(enveloppe_index==i)[0][0]] for i,val in enumerate(convert_index) if any(enveloppe_index==i)]) - points=np.column_stack((model.mesh.x[enveloppe_index], - model.mesh.y[enveloppe_index], - model.mesh.z[enveloppe_index])) - low_elt_num=np.size(np.where(np.isnan(model.mesh.lowerelements))) - top_elt_num=np.size(np.where(np.isnan(model.mesh.upperelements))) - num_of_elt=low_elt_num+top_elt_num - connect=model.mesh.elements[np.where(is_enveloppe[model.mesh.elements-1])].reshape(int(num_of_elt),3)-1 - for elt in range(0, num_of_elt): - connect[elt,0]=convert_index[np.where(convert_index==connect[elt,0])[0],1][0] - connect[elt,1]=convert_index[np.where(convert_index==connect[elt,1])[0],1][0] - connect[elt,2]=convert_index[np.where(convert_index==connect[elt,2])[0],1][0] + Basile de Fleurian: + ''' + Dir = os.path.basename(filename) + Path = filename[: - len(Dir)] - else: - points=np.column_stack((model.mesh.x, - model.mesh.y, - np.zeros(np.shape(model.mesh.x)))) - num_of_elt=np.shape(model.mesh.elements)[0] - connect=model.mesh.elements-1 - enveloppe_index=np.arange(0,np.size(model.mesh.x)) + if os.path.exists(filename): + print(('File {} allready exist'.format(filename))) + newname = input('Give a new name or "delete" to replace: ') + if newname == 'delete': + filelist = glob.glob(filename + '/* ') + for oldfile in filelist: + os.remove(oldfile) + else: + print(('New file name is {}'.format(newname))) + filename = newname + os.mkdir(filename) + else: + os.mkdir(filename) - every_nodes=np.size(model.mesh.x) - num_of_points=np.size(enveloppe_index) - dim=3 - point_per_elt=3 - celltype=5 #triangles + # {{{get the element related variables + if 'z' in dict.keys(model.mesh.__dict__): + is_enveloppe = np.logical_or(model.mesh.vertexonbase, model.mesh.vertexonsurface) + enveloppe_index = np.where(is_enveloppe)[0] + convert_index = np.nan * np.ones(np.shape(model.mesh.x)) + convert_index = np.asarray([[i, np.where(enveloppe_index == i)[0][0]] for i, val in enumerate(convert_index) if any(enveloppe_index == i)]) + points = np.column_stack((model.mesh.x[enveloppe_index], + model.mesh.y[enveloppe_index], + model.mesh.z[enveloppe_index])) + low_elt_num = np.size(np.where(np.isnan(model.mesh.lowerelements))) + top_elt_num = np.size(np.where(np.isnan(model.mesh.upperelements))) + num_of_elt = low_elt_num + top_elt_num + connect = model.mesh.elements[np.where(is_enveloppe[model.mesh.elements - 1])].reshape(int(num_of_elt), 3) - 1 + for elt in range(0, num_of_elt): + connect[elt, 0] = convert_index[np.where(convert_index == connect[elt, 0])[0], 1][0] + connect[elt, 1] = convert_index[np.where(convert_index == connect[elt, 1])[0], 1][0] + connect[elt, 2] = convert_index[np.where(convert_index == connect[elt, 2])[0], 1][0] - # }}} - # {{{this is the result structure - res_struct=model.results - if (len(res_struct.__dict__)>0): - #Getting all the solutions of the model - solnames=(dict.keys(res_struct.__dict__)) - num_of_sols=len(solnames) - num_of_timesteps=1 - #%building solutionstructure - for solution in solnames: - #looking for multiple time steps - if (np.size(res_struct.__dict__[solution])>num_of_timesteps): - num_of_timesteps=np.size(res_struct.__dict__[solution]) - num_of_timesteps=int(num_of_timesteps) - else: - num_of_timesteps=1 - # }}} - # {{{write header and mesh - for step in range(0,num_of_timesteps): - timestep=step - fid=open((filename +'/Timestep.vtk'+str(timestep)+'.vtk'),'w+') - fid.write('# vtk DataFile Version 2.0 \n') - fid.write('Data for run %s \n' % model.miscellaneous.name) - fid.write('ASCII \n') - fid.write('DATASET UNSTRUCTURED_GRID \n') - fid.write('POINTS %d float\n' % num_of_points) - for point in points: - fid.write('%f %f %f \n'%(point[0], point[1], point[2])) + else: + points = np.column_stack((model.mesh.x, + model.mesh.y, + np.zeros(np.shape(model.mesh.x)))) + num_of_elt = np.shape(model.mesh.elements)[0] + connect = model.mesh.elements - 1 + enveloppe_index = np.arange(0, np.size(model.mesh.x)) - fid.write('CELLS %d %d\n' %(num_of_elt, num_of_elt*(point_per_elt+1))) + every_nodes = np.size(model.mesh.x) + num_of_points = np.size(enveloppe_index) + dim = 3 + point_per_elt = 3 + celltype = 5 #triangles - for elt in range(0, num_of_elt): - fid.write('3 %d %d %d\n' %(connect[elt,0], - connect[elt,1], - connect[elt,2])) + # }}} + # {{{this is the result structure + res_struct = model.results + if (len(res_struct.__dict__) > 0): + #Getting all the solutions of the model + solnames = (dict.keys(res_struct.__dict__)) + num_of_sols = len(solnames) + num_of_timesteps = 1 + #%building solutionstructure + for solution in solnames: + #looking for multiple time steps + if (np.size(res_struct.__dict__[solution]) > num_of_timesteps): + num_of_timesteps = np.size(res_struct.__dict__[solution]) + num_of_timesteps = int(num_of_timesteps) + else: + num_of_timesteps = 1 + # }}} + # {{{write header and mesh + for step in range(0, num_of_timesteps): + timestep = step + fid = open((filename + '/Timestep.vtk' + str(timestep) + '.vtk'), 'w + ') + fid.write(' # vtk DataFile Version 2.0 \n') + fid.write('Data for run %s \n' % model.miscellaneous.name) + fid.write('ASCII \n') + fid.write('DATASET UNSTRUCTURED_GRID \n') + fid.write('POINTS %d float\n' % num_of_points) + for point in points: + fid.write('%f %f %f \n' % (point[0], point[1], point[2])) - fid.write('CELL_TYPES %d\n' %num_of_elt) - for elt in range(0, num_of_elt): - fid.write('%d\n' %celltype) + fid.write('CELLS %d %d\n' % (num_of_elt, num_of_elt * (point_per_elt + 1))) - fid.write('POINT_DATA %s \n' %str(num_of_points)) - # }}} - # {{{loop over the different solution structures - if 'solnames' in locals(): - for sol in solnames: - #dealing with results on different timesteps - if(np.size(res_struct.__dict__[sol])>timestep): - timestep = step - else: - timestep = np.size(res_struct.__dict__[sol]) + for elt in range(0, num_of_elt): + fid.write('3 %d %d %d\n' % (connect[elt, 0], + connect[elt, 1], + connect[elt, 2])) - #getting the fields in the solution - if(type(res_struct.__dict__[sol])==list): - fieldnames=dict.keys(res_struct.__dict__[sol].__getitem__(timestep).__dict__) - else: - fieldnames=dict.keys(res_struct.__dict__[sol].__dict__) - #check which field is a real result and print - for field in fieldnames: - if(type(res_struct.__dict__[sol])==list): - fieldstruct=res_struct.__dict__[sol].__getitem__(timestep).__dict__[field] - else: - fieldstruct=res_struct.__dict__[sol].__dict__[field] + fid.write('CELL_TYPES %d\n' % num_of_elt) + for elt in range(0, num_of_elt): + fid.write('%d\n' % celltype) - if ((np.size(fieldstruct))==every_nodes): - fid.write('SCALARS %s float 1 \n' % field) - fid.write('LOOKUP_TABLE default\n') - for node in range(0,num_of_points): - #paraview does not like NaN, replacing - if np.isnan(fieldstruct[enveloppe_index[node]]): - fid.write('%e\n' % -9999.9999) - #also checking for verry small value that mess up - elif (abs(fieldstruct[enveloppe_index[node]])<1.0e-20): - fid.write('%e\n' % 0.0) - else: - fid.write('%e\n' % fieldstruct[enveloppe_index[node]]) - # }}} - # {{{loop on arguments, if something other than result is asked, do it now + fid.write('POINT_DATA %s \n' % str(num_of_points)) + # }}} + # {{{loop over the different solution structures + if 'solnames' in locals(): + for sol in solnames: + #dealing with results on different timesteps + if(np.size(res_struct.__dict__[sol]) > timestep): + timestep = step + else: + timestep = np.size(res_struct.__dict__[sol]) - for other in args: - other_struct=model.__dict__[other] - othernames=(dict.keys(other_struct.__dict__)) - for field in othernames: - if ((np.size(other_struct.__dict__[field]))==every_nodes): - fid.write('SCALARS %s float 1 \n' % field) - fid.write('LOOKUP_TABLE default\n') - for node in range(0,num_of_points): - #paraview does not like NaN, replacing - if np.isnan(other_struct.__dict__[field][enveloppe_index[node]]): - fid.write('%e\n' % -9999.9999) - #also checking for verry small value that mess up - elif (abs(other_struct.__dict__[field][enveloppe_index[node]])<1.0e-20): - fid.write('%e\n' % 0.0) - else: - fid.write('%e\n' % other_struct.__dict__[field][enveloppe_index[node]]) + #getting the fields in the solution + if(type(res_struct.__dict__[sol]) == list): + fieldnames = dict.keys(res_struct.__dict__[sol].__getitem__(timestep).__dict__) + else: + fieldnames = dict.keys(res_struct.__dict__[sol].__dict__) + #check which field is a real result and print + for field in fieldnames: + if(type(res_struct.__dict__[sol]) == list): + fieldstruct = res_struct.__dict__[sol].__getitem__(timestep).__dict__[field] + else: + fieldstruct = res_struct.__dict__[sol].__dict__[field] - # }}} - fid.close(); + if ((np.size(fieldstruct)) == every_nodes): + fid.write('SCALARS %s float 1 \n' % field) + fid.write('LOOKUP_TABLE default\n') + for node in range(0, num_of_points): + #paraview does not like NaN, replacing + if np.isnan(fieldstruct[enveloppe_index[node]]): + fid.write('%e\n' % - 9999.9999) + #also checking for verry small value that mess up + elif (abs(fieldstruct[enveloppe_index[node]]) < 1.0e-20): + fid.write('%e\n' % 0.0) + else: + fid.write('%e\n' % fieldstruct[enveloppe_index[node]]) + # }}} + # {{{loop on arguments, if something other than result is asked, do it now + + for other in args: + other_struct = model.__dict__[other] + othernames = (dict.keys(other_struct.__dict__)) + for field in othernames: + if ((np.size(other_struct.__dict__[field])) == every_nodes): + fid.write('SCALARS %s float 1 \n' % field) + fid.write('LOOKUP_TABLE default\n') + for node in range(0, num_of_points): + #paraview does not like NaN, replacing + if np.isnan(other_struct.__dict__[field][enveloppe_index[node]]): + fid.write('%e\n' % - 9999.9999) + #also checking for verry small value that mess up + elif (abs(other_struct.__dict__[field][enveloppe_index[node]]) < 1.0e-20): + fid.write('%e\n' % 0.0) + else: + fid.write('%e\n' % other_struct.__dict__[field][enveloppe_index[node]]) + + # }}} + fid.close() Index: /issm/trunk-jpl/src/m/contrib/defleurian/paraview/exportVTK.py =================================================================== --- /issm/trunk-jpl/src/m/contrib/defleurian/paraview/exportVTK.py (revision 24212) +++ /issm/trunk-jpl/src/m/contrib/defleurian/paraview/exportVTK.py (revision 24213) @@ -7,12 +7,12 @@ ''' vtk export - function exportVTK(filename,md) + function exportVTK(filename, md) creates a directory with the vtk files for displays in paraview (only work for triangle and wedges based on their number of nodes) Usage: - exportVTK('DirName',md) - exportVTK('DirName',md,'geometry','mesh') - exportVTK('DirName',md,'geometry','mesh',enveloppe=True) + exportVTK('DirName', md) + exportVTK('DirName', md, 'geometry', 'mesh') + exportVTK('DirName', md, 'geometry', 'mesh', enveloppe = True) DirName is the name of the output directory, each timestep then has it @@ -27,10 +27,10 @@ # File checking and creation {{{ Dir = path.basename(filename) - Path = filename[:-len(Dir)] + Path = filename[: - len(Dir)] if path.exists(filename): print(('File {} allready exist'.format(filename))) newname = input('Give a new name or "delete" to replace: ') if newname == 'delete': - filelist = glob(filename + '/*') + filelist = glob(filename + '/* ') for oldfile in filelist: remove(oldfile) @@ -102,5 +102,5 @@ else: - #we get all the mesh, mainly defining dummies + #we get all the mesh, mainly defining dummies num_of_elt = every_cells connect = md.mesh.elements - 1 @@ -120,11 +120,11 @@ saved_cells = {} timestep = step - fid = open((filename + '/Timestep.vtk' + str(timestep) + '.vtk'), 'w+') - fid.write('# vtk DataFile Version 3.0 \n') + fid = open((filename + '/Timestep.vtk' + str(timestep) + '.vtk'), 'w + ') + fid.write(' # vtk DataFile Version 3.0 \n') fid.write('Data for run {} \n'.format(md.miscellaneous.name)) fid.write('ASCII \n') fid.write('DATASET UNSTRUCTURED_GRID \n') fid.write('POINTS {:d} float\n'.format(num_of_points)) - #updating z for mesh evolution + #updating z for mesh evolution if moving_mesh: base = np.squeeze(res_struct.__dict__['TransientSolution'][step].__dict__['Base'][enveloppe_index]) @@ -157,11 +157,11 @@ fid.write('POINT_DATA {:s} \n'.format(str(num_of_points))) - # }}} - # loop over the different solution structures{{{ - # first check if there are solutions to grab + # }}} + # {{{loop over the different solution structures + # first check if there are solutions to grab if 'solnames' in locals(): for sol in solnames: treated_res = [] - #dealing with results on different timesteps + #dealing with results on different timesteps if(np.size(res_struct.__dict__[sol]) > timestep): timestep = step @@ -169,5 +169,5 @@ timestep = np.size(res_struct.__dict__[sol]) - #getting the fields in the solution + #getting the fields in the solution if(type(res_struct.__dict__[sol]) == list): spe_res_struct = res_struct.__dict__[sol].__getitem__(timestep) @@ -177,10 +177,10 @@ fieldnames = dict.keys(spe_res_struct.__dict__) - #Sorting scalars, vectors and tensors + #Sorting scalars, vectors and tensors tensors = [field for field in fieldnames if field[-2:] in ['xx', 'yy', 'xy', 'zz', 'xz', 'yz']] non_tensor = [field for field in fieldnames if field not in tensors] vectors = [field for field in non_tensor if field[-1] in ['x', 'y', 'z']] - #check which field is a real result and print + #check which field is a real result and print for field in fieldnames: if field in treated_res: @@ -214,10 +214,10 @@ Txystruct = np.squeeze(spe_res_struct.__dict__[field[:-2] + 'xy']) Tyystruct = np.squeeze(spe_res_struct.__dict__[field[:-2] + 'yy']) - treated_res += [field[:-2] + 'xx', field[:-2] + 'xy', field[:-2] + 'yy'] + treated_res += [field[: - 2] + 'xx', field[: - 2] + 'xy', field[: - 2] + 'yy'] if dim == 3: Tzzstruct = np.squeeze(spe_res_struct.__dict__[field[:-2] + 'zz']) Txzstruct = np.squeeze(spe_res_struct.__dict__[field[:-2] + 'xz']) Tyzstruct = np.squeeze(spe_res_struct.__dict__[field[:-2] + 'yz']) - treated_res += [field[:-2] + 'zz', field[:-2] + 'xz', field[:-2] + 'yz'] + treated_res += [field[: - 2] + 'zz', field[: - 2] + 'xz', field[: - 2] + 'yz'] except KeyError: @@ -225,5 +225,5 @@ tensors.remove(field) - fid.write('TENSORS {} float \n'.format(field[:-2])) + fid.write('TENSORS {} float \n'.format(field[: - 2])) for node in range(0, num_of_points): Txx = cleanOutliers(Txxstruct[enveloppe_index[node]]) @@ -250,6 +250,6 @@ elif ((np.size(spe_res_struct.__dict__[field])) == every_cells): saved_cells[field] = np.squeeze(spe_res_struct.__dict__[field]) - # }}} - # loop on arguments, if something other than result is asked, do it now {{{ + # }}} + # loop on arguments, if something other than result is asked, do it now {{{ for other in args: other_struct = md.__dict__[other] @@ -264,6 +264,6 @@ elif (np.size(other_struct.__dict__[field]) == every_cells): saved_cells[field] = other_struct.__dict__[field] - # }}} - # Now writting cell variables {{{ + # }}} + # Now writting cell variables {{{ if np.size(list(saved_cells.keys())) > 0: fid.write('CELL_DATA {:d} \n'.format(num_of_elt)) @@ -274,13 +274,13 @@ outval = cleanOutliers(saved_cells[key][cell]) fid.write('{:f}\n'.format(outval)) - # }}} + # }}} fid.close() def cleanOutliers(Val): - #paraview does not like NaN, replacing + #paraview does not like NaN, replacing if np.isnan(Val): - CleanVal = -9999.999 - #also checking for very small value that mess up + CleanVal = - 9999.999 + #also checking for very small value that mess up elif (abs(Val) < 1.0e-20): CleanVal = 0.0 Index: /issm/trunk-jpl/src/m/contrib/morlighem/bamg/YamsCall.py =================================================================== --- /issm/trunk-jpl/src/m/contrib/morlighem/bamg/YamsCall.py (revision 24212) +++ /issm/trunk-jpl/src/m/contrib/morlighem/bamg/YamsCall.py (revision 24213) @@ -1,3 +1,4 @@ import numpy as np +import MatlabFuncs as m import time import subprocess @@ -6,118 +7,118 @@ from ComputeMetric import ComputeMetric -def YamsCall(md,field,hmin,hmax,gradation,epsilon): - """ - YAMSCALL - call yams - build a metric using the Hessian of the given field - call Yams and the output mesh is plugged onto the model - -hmin = minimum edge length (m) - -hmax = maximum edge length (m) - -gradation = maximum edge length gradation between 2 elements - -epsilon = average error on each element (m/yr) +def YamsCall(md, field, hmin, hmax, gradation, epsilon): + """ + YAMSCALL - call yams - Usage: - md=YamsCall(md,field,hmin,hmax,gradation,epsilon); + build a metric using the Hessian of the given field + call Yams and the output mesh is plugged onto the model + - hmin = minimum edge length (m) + - hmax = maximum edge length (m) + - gradation = maximum edge length gradation between 2 elements + - epsilon = average error on each element (m / yr) - Example: - md=YamsCall(md,md.inversion.vel_obs,1500,10^8,1.3,0.9); - """ + Usage: + md = YamsCall(md, field, hmin, hmax, gradation, epsilon) - #2d geometric parameter (do not change) - scale=2./9. + Example: + md = YamsCall(md, md.inversion.vel_obs, 1500, 10^8, 1.3, 0.9) + """ - #Compute Hessian - t1=time.time() - print(("%s" % ' computing Hessian...')) - hessian=ComputeHessian(md.mesh.elements,md.mesh.x,md.mesh.y,field,'node') - t2=time.time() - print(("%s%d%s\n" % (' done (',t2-t1,' seconds)'))) + #2d geometric parameter (do not change) + scale = 2. / 9. - #Compute metric - t1=time.time() - print(("%s" % ' computing metric...')) - metric=ComputeMetric(hessian,scale,epsilon,hmin,hmax,np.empty(0,int)) - t2=time.time() - print(("%s%d%s\n" % (' done (',t2-t1,' seconds)'))) + #Compute Hessian + t1 = time.time() + print(("%s" % ' computing Hessian...')) + hessian = ComputeHessian(md.mesh.elements, md.mesh.x, md.mesh.y, field, 'node') + t2 = time.time() + print(("%s%d%s\n" % (' done (', t2 - t1, ' seconds)'))) - #write files - t1=time.time() - print(("%s" % ' writing initial mesh files...')) - np.savetxt('carre0.met',metric) + #Compute metric + t1 = time.time() + print(("%s" % ' computing metric...')) + metric = ComputeMetric(hessian, scale, epsilon, hmin, hmax, np.empty(0, int)) + t2 = time.time() + print(("%s%d%s\n" % (' done (', t2 - t1, ' seconds)'))) - f=open('carre0.mesh','w') + #write files + t1 = time.time() + print(("%s" % ' writing initial mesh files...')) + np.savetxt('carre0.met', metric) - #initialiation - f.write("\n%s\n%i\n" % ('MeshVersionFormatted',1)) + f = open('carre0.mesh', 'w') - #dimension - f.write("\n%s\n%i\n" % ('Dimension',2)) + #initialiation + f.write("\n%s\n%i\n" % ('MeshVersionFormatted', 1)) - #Vertices - f.write("\n%s\n%i\n\n" % ('Vertices',md.mesh.numberofvertices)) - for i in range(0,md.mesh.numberofvertices): - f.write("%8g %8g %i\n" % (md.mesh.x[i],md.mesh.y[i],0)) + #dimension + f.write("\n%s\n%i\n" % ('Dimension', 2)) - #Triangles - f.write("\n\n%s\n%i\n\n" % ('Triangles',md.mesh.numberofelements)) - for i in range(0,md.mesh.numberofelements): - f.write("%i %i %i %i\n" % (md.mesh.elements[i,0],md.mesh.elements[i,1],md.mesh.elements[i,2],0)) - numberofelements1=md.mesh.numberofelements + #Vertices + f.write("\n%s\n%i\n\n" % ('Vertices', md.mesh.numberofvertices)) + for i in range(0, md.mesh.numberofvertices): + f.write("%8g %8g %i\n" % (md.mesh.x[i], md.mesh.y[i], 0)) - #Deal with rifts - if np.any(not np.isnan(md.rifts.riftstruct)): + #Triangles + f.write("\n\n%s\n%i\n\n" % ('Triangles', md.mesh.numberofelements)) + for i in range(0, md.mesh.numberofelements): + f.write("%i %i %i %i\n" % (md.mesh.elements[i, 0], md.mesh.elements[i, 1], md.mesh.elements[i, 2], 0)) + numberofelements1 = md.mesh.numberofelements - #we have the list of triangles that make up the rift. keep those triangles around during refinement. - triangles=np.empty(0,int) - for riftstruct in md.rifts.riftstruct: - triangles=np.concatenate((triangles,riftstruct.segments[:,2])) + #Deal with rifts + if np.any(not np.isnan(md.rifts.riftstruct)): - f.write("\n\n%s\n%i\n\n" % ('RequiredTriangles',np.size(triangles))) - for triangle in triangles: - f.write("%i\n" % triangle) + #we have the list of triangles that make up the rift. keep those triangles around during refinement. + triangles = np.empty(0, int) + for riftstruct in md.rifts.riftstruct: + triangles = np.concatenate((triangles, riftstruct.segments[:, 2])) - #close - f.close() - t2=time.time() - print(("%s%d%s\n" % (' done (',t2-t1,' seconds)'))) + f.write("\n\n%s\n%i\n\n" % ('RequiredTriangles', np.size(triangles))) + for triangle in triangles: + f.write("%i\n" % triangle) - #call yams - print(("%s\n" % ' call Yams...')) - if m.ispc(): - #windows - subprocess.call('yams2-win -O 1 -v -0 -ecp -hgrad %g carre0 carre1' % gradation,shell=True) - elif ismac(): - #Macosx - subprocess.call('yams2-osx -O 1 -v -0 -ecp -hgrad %g carre0 carre1' % gradation,shell=True) - else: - #Linux - subprocess.call('yams2-linux -O 1 -v -0 -ecp -hgrad %g carre0 carre1' % gradation,shell=True) + #close + f.close() + t2 = time.time() + print(("%s%d%s\n" % (' done (', t2 - t1, ' seconds)'))) - #plug new mesh - t1=time.time() - print(("\n%s" % ' reading final mesh files...')) - Tria=np.loadtxt('carre1.tria',int) - Coor=np.loadtxt('carre1.coor',float) - md.mesh.x=Coor[:,0] - md.mesh.y=Coor[:,1] - md.mesh.z=np.zeros((np.size(Coor,axis=0),1)) - md.mesh.elements=Tria - md.mesh.numberofvertices=np.size(Coor,axis=0) - md.mesh.numberofelements=np.size(Tria,axis=0) - numberofelements2=md.mesh.numberofelements - t2=time.time() - print(("%s%d%s\n\n" % (' done (',t2-t1,' seconds)'))) + #call yams + print(("%s\n" % ' call Yams...')) + if m.ispc(): + #windows + subprocess.call('yams2 - win - O 1 - v - 0 - ecp - hgrad %g carre0 carre1' % gradation, shell=True) + elif m.ismac(): + #Macosx + subprocess.call('yams2 - osx - O 1 - v - 0 - ecp - hgrad %g carre0 carre1' % gradation, shell=True) + else: + #Linux + subprocess.call('yams2 - linux - O 1 - v - 0 - ecp - hgrad %g carre0 carre1' % gradation, shell=True) - #display number of elements - print(("\n%s %i" % (' inital number of elements:',numberofelements1))) - print(("\n%s %i\n\n" % (' new number of elements:',numberofelements2))) + #plug new mesh + t1 = time.time() + print(("\n%s" % ' reading final mesh files...')) + Tria = np.loadtxt('carre1.tria', int) + Coor = np.loadtxt('carre1.coor', float) + md.mesh.x = Coor[:, 0] + md.mesh.y = Coor[:, 1] + md.mesh.z = np.zeros((np.size(Coor, axis=0), 1)) + md.mesh.elements = Tria + md.mesh.numberofvertices = np.size(Coor, axis=0) + md.mesh.numberofelements = np.size(Tria, axis=0) + numberofelements2 = md.mesh.numberofelements + t2 = time.time() + print(("%s%d%s\n\n" % (' done (', t2 - t1, ' seconds)'))) - #clean up: - os.remove('carre0.mesh') - os.remove('carre0.met') - os.remove('carre1.tria') - os.remove('carre1.coor') - os.remove('carre1.meshb') + #display number of elements + print(("\n%s %i" % (' inital number of elements:', numberofelements1))) + print(("\n%s %i\n\n" % (' new number of elements:', numberofelements2))) - return md + #clean up: + os.remove('carre0.mesh') + os.remove('carre0.met') + os.remove('carre1.tria') + os.remove('carre1.coor') + os.remove('carre1.meshb') + return md Index: /issm/trunk-jpl/src/m/coordsystems/gmtmask.py =================================================================== --- /issm/trunk-jpl/src/m/coordsystems/gmtmask.py (revision 24212) +++ /issm/trunk-jpl/src/m/coordsystems/gmtmask.py (revision 24213) @@ -5,77 +5,77 @@ import subprocess -def gmtmask(lat,long,*varargin): -#GMTMASK - figure out which lat,long points are on the ocean -# -# Usage: -# mask.ocean = gmtmask(md.mesh.lat,md.mesh.long); -# - lenlat=len(lat) - mask=np.empty(lenlat) - - #are we doing a recursive call? - if len(varargin)==3: - recursive=1 - else: - recursive=0 - if recursive: - print((' recursing: num vertices #'+str(lenlat))) - else: - print(('gmtmask: num vertices #'+str(lenlat))) - - #Check lat and long size is not more than 50,000 If so, recursively call gmtmask: +def gmtmask(lat, long, * varargin): + '''GMTMASK - figure out which lat, long points are on the ocean - if lenlat>50000: - for i in range(int(ceil(lenlat/50000))): - j=(i+1)*50000-1 - if j>lenlat: - j=lenlat - mask[i:j]=gmtmask(lat[i:j],int[i:j],1) - return mask - - - #First, write our lat,long file for gmt: - nv=lenlat - #print(np.transpose([int, lat, np.arange(1,nv+1)])) - np.savetxt('./all_vertices.txt',np.transpose([long, lat, np.arange(1,nv+1)]),delimiter='\t',fmt='%.10f') + Usage: + mask.ocean = gmtmask(md.mesh.lat, md.mesh.long) + ''' + lenlat = len(lat) + mask = np.empty(lenlat) - #Avoid bypassing of the ld library path by Matlab (:() - try: - issmdir - except: - issmdir=getenv('ISSM_DIR') - try: - ismac - except: - ismac=False + #are we doing a recursive call? + if len(varargin) == 3: + recursive = 1 + else: + recursive = 0 - if ismac: - dyld_library_path_old=getenv('DYLD_LIBRARY_PATH') - putenv('DYLD_LIBRARY_PATH',issmdir+'/externalpackages/curl/install/lib:'+issmdir+'/externalpackages/hdf5/install/lib:'+issmdir+'/externalpackages/netcdf/install/lib') - - #figure out which vertices are on the ocean, which one on the continent: - subprocess.call(issmdir+'/externalpackages/gmt/install/bin/gmt gmtselect ./all_vertices.txt -h0 -Df -R0/360/-90/90 -A0 -JQ180/200 -Nk/s/s/k/s > ./oce_vertices.txt',shell=True) + if recursive: + print((' recursing: num vertices #' + str(lenlat))) + else: + print(('gmtmask: num vertices #' + str(lenlat))) - #reset DYLD_LIBRARY_PATH to what it was: - if ismac: - putenv('DYLD_LIBRARY_PATH',dyld_library_path_old) - - #read the con_vertices.txt file and flag our mesh vertices on the continent - fid=open('./oce_vertices.txt','r') - line=fid.readline() - line=fid.readline() - oce_vertices=[] - while line: - ind=int(float(line.split()[2]))-1; - oce_vertices.append(ind) - line=fid.readline() - fid.close() + #Check lat and long size is not more than 50, 000 If so, recursively call gmtmask: - mask=np.zeros(nv) - mask[oce_vertices]=1 - - subprocess.call('rm -rf ./all_vertices.txt ./oce_vertices.txt ./gmt.history',shell=True) - if not recursive: - print('gmtmask: done') - return mask + if lenlat > 50000: + for i in range(int(ceil(lenlat / 50000))): + j = (i + 1) * 50000 - 1 + if j > lenlat: + j = lenlat + mask[i:j] = gmtmask(lat[i:j], int[i:j], 1) + return mask + + #First, write our lat, long file for gmt: + nv = lenlat + #print(np.transpose([int, lat, np.arange(1, nv + 1)])) + np.savetxt('./all_vertices.txt', np.transpose([long, lat, np.arange(1, nv + 1)]), delimiter='\t', fmt='%.10f') + + #Avoid bypassing of the ld library path by Matlab (:() + try: + issmdir + except NameError: + issmdir = getenv('ISSM_DIR') + try: + ismac + except NameError: + ismac = False + + if ismac: + dyld_library_path_old = getenv('DYLD_LIBRARY_PATH') + putenv('DYLD_LIBRARY_PATH', issmdir + '/externalpackages/curl/install/lib:' + issmdir + '/externalpackages/hdf5/install/lib:' + issmdir + '/externalpackages/netcdf/install/lib') + + #figure out which vertices are on the ocean, which one on the continent: + subprocess.call(issmdir + '/externalpackages/gmt/install/bin/gmt gmtselect ./ all_vertices.txt -h0 -Df -R0/360/-90/90 -A0- JQ180/200 - Nk/s/s/k/s > ./oce_vertices.txt', shell=True) + + #reset DYLD_LIBRARY_PATH to what it was: + if ismac: + putenv('DYLD_LIBRARY_PATH', dyld_library_path_old) + + #read the con_vertices.txt file and flag our mesh vertices on the continent + fid = open('./oce_vertices.txt', 'r') + line = fid.readline() + line = fid.readline() + oce_vertices = [] + while line: + ind = int(float(line.split()[2])) - 1 + oce_vertices.append(ind) + line = fid.readline() + fid.close() + + mask = np.zeros(nv) + mask[oce_vertices] = 1 + + subprocess.call('rm -rf ./all_vertices.txt ./oce_vertices.txt ./gmt.history', shell=True) + if not recursive: + print('gmtmask: done') + return mask Index: /issm/trunk-jpl/src/m/coordsystems/ll2xy.py =================================================================== --- /issm/trunk-jpl/src/m/coordsystems/ll2xy.py (revision 24212) +++ /issm/trunk-jpl/src/m/coordsystems/ll2xy.py (revision 24213) @@ -1,62 +1,63 @@ -import numpy as np +import numpy as np -def ll2xy(lat,lon,sgn=-1,central_meridian=0,standard_parallel=71): - ''' - LL2XY - converts lat lon to polar stereographic - Converts from geodetic latitude and longitude to Polar - Stereographic (X,Y) coordinates for the polar regions. +def ll2xy(lat, lon, sgn=-1, central_meridian=0, standard_parallel=71): + ''' + LL2XY - converts lat lon to polar stereographic + + Converts from geodetic latitude and longitude to Polar + Stereographic (X, Y) coordinates for the polar regions. Author: Michael P. Schodlok, December 2003 (map2ll) Usage: - x,y = ll2xy(lat,lon,sgn) - x,y = ll2xy(lat,lon,sgn,central_meridian,standard_parallel) + x, y = ll2xy(lat, lon, sgn) + x, y = ll2xy(lat, lon, sgn, central_meridian, standard_parallel) - - sgn = Sign of latitude +1 : north latitude (default is mer=45 lat=70) - -1 : south latitude (default is mer=0 lat=71) - ''' + - sgn = Sign of latitude + 1 : north latitude (default is mer = 45 lat = 70) + - 1 : south latitude (default is mer = 0 lat = 71) + ''' - assert sgn==1 or sgn==-1, 'error: sgn should be either +1 or -1' + assert sgn == 1 or sgn == - 1, 'error: sgn should be either + 1 or - 1' - #Get central_meridian and standard_parallel depending on hemisphere - if sgn == 1: - delta = 45 - slat = 70 - print(' ll2xy: creating coordinates in north polar stereographic (Std Latitude: 70N Meridian: 45)') - else: - delta = central_meridian - slat = standard_parallel - print(' ll2xy: creating coordinates in south polar stereographic (Std Latitude: 71S Meridian: 0)') - - # Conversion constant from degrees to radians - cde = 57.29577951 - # Radius of the earth in meters - re = 6378.273*10**3 - # Eccentricity of the Hughes ellipsoid squared - ex2 = .006693883 - # Eccentricity of the Hughes ellipsoid - ex = np.sqrt(ex2) - - latitude = np.abs(lat) * np.pi/180. - longitude = (lon + delta) * np.pi/180. - - # compute X and Y in grid coordinates. - T = np.tan(np.pi/4-latitude/2) / ((1-ex*np.sin(latitude))/(1+ex*np.sin(latitude)))**(ex/2) - - if (90 - slat) < 1.e-5: - rho = 2.*re*T/np.sqrt((1.+ex)**(1.+ex)*(1.-ex)**(1.-ex)) - else: - sl = slat*np.pi/180. - tc = np.tan(np.pi/4.-sl/2.)/((1.-ex*np.sin(sl))/(1.+ex*np.sin(sl)))**(ex/2.) - mc = np.cos(sl)/np.sqrt(1.0-ex2*(np.sin(sl)**2)) - rho = re*mc*T/tc - - y = -rho * sgn * np.cos(sgn*longitude) - x = rho * sgn * np.sin(sgn*longitude) + #Get central_meridian and standard_parallel depending on hemisphere + if sgn == 1: + delta = 45 + slat = 70 + print(' ll2xy: creating coordinates in north polar stereographic (Std Latitude: 70N Meridian: 45)') + else: + delta = central_meridian + slat = standard_parallel + print(' ll2xy: creating coordinates in south polar stereographic (Std Latitude: 71S Meridian: 0)') - cnt1=np.nonzero(latitude>= np.pi/2.)[0] - - if cnt1: - x[cnt1,0] = 0.0 - y[cnt1,0] = 0.0 - return x,y + # Conversion constant from degrees to radians + #cde = 57.29577951 + # Radius of the earth in meters + re = 6378.273 * 10**3 + # Eccentricity of the Hughes ellipsoid squared + ex2 = .006693883 + # Eccentricity of the Hughes ellipsoid + ex = np.sqrt(ex2) + + latitude = np.abs(lat) * np.pi / 180. + longitude = (lon + delta) * np.pi / 180. + + # compute X and Y in grid coordinates. + T = np.tan(np.pi / 4 - latitude / 2) / ((1 - ex * np.sin(latitude)) / (1 + ex * np.sin(latitude)))**(ex / 2) + + if (90 - slat) < 1.e-5: + rho = 2. * re * T / np.sqrt((1. + ex)**(1. + ex) * (1. - ex)**(1. - ex)) + else: + sl = slat * np.pi / 180. + tc = np.tan(np.pi / 4. - sl / 2.) / ((1. - ex * np.sin(sl)) / (1. + ex * np.sin(sl)))**(ex / 2.) + mc = np.cos(sl) / np.sqrt(1.0 - ex2 * (np.sin(sl)**2)) + rho = re * mc * T / tc + + y = - rho * sgn * np.cos(sgn * longitude) + x = rho * sgn * np.sin(sgn * longitude) + + cnt1 = np.nonzero(latitude >= np.pi / 2.)[0] + + if cnt1: + x[cnt1, 0] = 0.0 + y[cnt1, 0] = 0.0 + return x, y Index: /issm/trunk-jpl/src/m/coordsystems/xy2ll.py =================================================================== --- /issm/trunk-jpl/src/m/coordsystems/xy2ll.py (revision 24212) +++ /issm/trunk-jpl/src/m/coordsystems/xy2ll.py (revision 24213) @@ -1,82 +1,81 @@ -import numpy as np +import numpy as np from math import pi + def xy2ll(x, y, sgn, *args): - ''' - XY2LL - converts xy to lat long - - Converts Polar Stereographic (X, Y) coordinates for the polar regions to - latitude and longitude Stereographic (X, Y) coordinates for the polar - regions. - Author: Michael P. Schodlok, December 2003 (map2xy.m) - - Usage: - [lat, lon] = xy2ll(x, y, sgn); - [lat, lon] = xy2ll(x, y, sgn, central_meridian, standard_parallel); - - - sgn = Sign of latitude +1 : north latitude (default is mer=45 lat=70) - -1 : south latitude (default is mer=0 lat=71) - ''' + ''' + XY2LL - converts xy to lat long - #Get central_meridian and standard_parallel depending on hemisphere - if len(args) == 2: - delta = args[0] - slat = args[1] - elif len(args) == 0: - if sgn == 1: - delta = 45. - slat = 70. - print(' xy2ll: creating coordinates in north polar stereographic (Std Latitude: 70degN Meridian: 45deg)') - elif sgn == -1: - delta = 0. - slat = 71. - print(' xy2ll: creating coordinates in south polar stereographic (Std Latitude: 71degS Meridian: 0deg)') - else: - raise ValueError('sgn should be either +1 or -1') - else: - raise Exception('bad usage: type "help(xy2ll)" for details') + Converts Polar Stereographic (X, Y) coordinates for the polar regions to + latitude and longitude Stereographic (X, Y) coordinates for the polar + regions. + Author: Michael P. Schodlok, December 2003 (map2xy.m) - # if x,y passed as lists, convert to np.arrays - if type(x) != "np.ndarray": - x=np.array(x) - if type(y) != "np.ndarray": - y=np.array(y) + Usage: + [lat, lon] = xy2ll(x, y, sgn) + [lat, lon] = xy2ll(x, y, sgn, central_meridian, standard_parallel) - ## Conversion constant from degrees to radians - cde = 57.29577951 - ## Radius of the earth in meters - re = 6378.273*10**3 - ## Eccentricity of the Hughes ellipsoid squared - ex2 = .006693883 - ## Eccentricity of the Hughes ellipsoid - ex = np.sqrt(ex2) - - sl = slat*pi/180. - rho = np.sqrt(x**2 + y**2) - cm = np.cos(sl) / np.sqrt(1.0 - ex2 * (np.sin(sl)**2)) - T = np.tan((pi/4.0) - (sl/2.0)) / ((1.0 - ex*np.sin(sl)) / (1.0 + ex*np.sin(sl)))**(ex / 2.0) - - if abs(slat-90.) < 1.e-5: - T = rho*np.sqrt((1. + ex)**(1. + ex) * (1. - ex)**(1. - ex)) / 2. / re - else: - T = rho * T / (re * cm) - - chi = (pi / 2.0) - 2.0 * np.arctan(T) - lat = chi + ((ex2 / 2.0) + (5.0 * ex2**2.0 / 24.0) + (ex2**3.0 / 12.0)) * \ - np.sin(2 * chi) + ((7.0 * ex2**2.0 / 48.0) + (29.0 * ex2**3 / 240.0)) * \ - np.sin(4.0 * chi) + (7.0 * ex2**3.0 / 120.0) * np.sin(6.0 * chi) - - lat = sgn * lat - lon = np.arctan2(sgn * x,-sgn * y) - lon = sgn * lon - - res1 = np.nonzero(rho <= 0.1)[0] - if len(res1) > 0: - lat[res1] = pi/2. * sgn - lon[res1] = 0.0 - - lon = lon * 180. / pi - lat = lat * 180. / pi - lon = lon - delta + - sgn = Sign of latitude + 1 : north latitude (default is mer = 45 lat = 70) + - 1 : south latitude (default is mer = 0 lat = 71) + ''' - return lat, lon + #Get central_meridian and standard_parallel depending on hemisphere + if len(args) == 2: + delta = args[0] + slat = args[1] + elif len(args) == 0: + if sgn == 1: + delta = 45. + slat = 70. + print(' xy2ll: creating coordinates in north polar stereographic (Std Latitude: 70degN Meridian: 45deg)') + elif sgn == - 1: + delta = 0. + slat = 71. + print(' xy2ll: creating coordinates in south polar stereographic (Std Latitude: 71degS Meridian: 0deg)') + else: + raise ValueError('sgn should be either + 1 or - 1') + else: + raise Exception('bad usage: type "help(xy2ll)" for details') + + # if x, y passed as lists, convert to np.arrays + if type(x) != "np.ndarray": + x = np.array(x) + if type(y) != "np.ndarray": + y = np.array(y) + + # Conversion constant from degrees to radians + #cde = 57.29577951 + # Radius of the earth in meters + re = 6378.273 * 10**3 + # Eccentricity of the Hughes ellipsoid squared + ex2 = .006693883 + # Eccentricity of the Hughes ellipsoid + ex = np.sqrt(ex2) + + sl = slat * pi / 180. + rho = np.sqrt(x**2 + y**2) + cm = np.cos(sl) / np.sqrt(1.0 - ex2 * (np.sin(sl)**2)) + T = np.tan((pi / 4.0) - (sl / 2.0)) / ((1.0 - ex * np.sin(sl)) / (1.0 + ex * np.sin(sl)))**(ex / 2.0) + + if abs(slat - 90.) < 1.e-5: + T = rho * np.sqrt((1. + ex)**(1. + ex) * (1. - ex)**(1. - ex)) / 2. / re + else: + T = rho * T / (re * cm) + + chi = (pi / 2.0) - 2.0 * np.arctan(T) + lat = chi + ((ex2 / 2.0) + (5.0 * ex2**2.0 / 24.0) + (ex2**3.0 / 12.0)) * np.sin(2 * chi) + ((7.0 * ex2**2.0 / 48.0) + (29.0 * ex2**3 / 240.0)) * np.sin(4.0 * chi) + (7.0 * ex2**3.0 / 120.0) * np.sin(6.0 * chi) + + lat = sgn * lat + lon = np.arctan2(sgn * x, - sgn * y) + lon = sgn * lon + + res1 = np.nonzero(rho <= 0.1)[0] + if len(res1) > 0: + lat[res1] = pi / 2. * sgn + lon[res1] = 0.0 + + lon = lon * 180. / pi + lat = lat * 180. / pi + lon = lon - delta + + return lat, lon Index: /issm/trunk-jpl/src/m/dev/ISSM.py =================================================================== --- /issm/trunk-jpl/src/m/dev/ISSM.py (revision 24212) +++ /issm/trunk-jpl/src/m/dev/ISSM.py (revision 24213) @@ -1,4 +1,3 @@ print('WARNING: EXPERIMENTAL FEATURE ISSM.py: universal Python ISSM import') - #Most common imports import numpy as np @@ -39,33 +38,37 @@ from dmeth_params_write import * + #Helper functions def python_help(): - '''Prints out key code fragments that may be useful to users''' - print('Differences between Python and Matlab code:') - #... + '''Prints out key code fragments that may be useful to users''' + print('Differences between Python and Matlab code:') + #... + def find(to_find): - '''analagous to matlab's find function but requires separate and/or functions''' - return np.array(np.where(to_find)) + '''analagous to matlab's find function but requires separate and / or functions''' + return np.array(np.where(to_find)) + def find_and(*args): - '''analagous to matlab's a & b functionality when used in conjunction with find(), - returns overlap across a and b - takes an arbitrary number of arguments of similar shape''' - result = args[0] - for arg in args[1:]: - if type(arg) != np.ndarray: - arg = np.array(arg) - result = np.intersect1d(result,arg) - return result + '''analagous to matlab's a & b functionality when used in conjunction with find(), + returns overlap across a and b + takes an arbitrary number of arguments of similar shape''' + result = args[0] + for arg in args[1:]: + if type(arg) != np.ndarray: + arg = np.array(arg) + result = np.intersect1d(result, arg) + return result + def find_or(*args): - '''analagous to matlab's a | b functionality when used in conjunction with find(), - returns all unique values across a and b - takes an arbitrary number of arguments of similar shape''' - result = args[0] - for arg in args[1:]: - if type(arg) != np.ndarray: - arg = np.array(arg) - result = np.unique(np.concatenate((result,arg))) - return result + '''analagous to matlab's a | b functionality when used in conjunction with find(), + returns all unique values across a and b + takes an arbitrary number of arguments of similar shape''' + result = args[0] + for arg in args[1:]: + if type(arg) != np.ndarray: + arg = np.array(arg) + result = np.unique(np.concatenate((result, arg))) + return result Index: /issm/trunk-jpl/src/m/dev/devpath.py =================================================================== --- /issm/trunk-jpl/src/m/dev/devpath.py (revision 24212) +++ /issm/trunk-jpl/src/m/dev/devpath.py (revision 24213) @@ -1,4 +1,5 @@ -#!/usr/bin/env python -import os, sys +#! / usr / bin / env python +import os +import sys import warnings @@ -10,15 +11,15 @@ raise NameError('"ISSM_DIR" environment variable is empty! You should define ISSM_DIR in your .cshrc or .bashrc!') -#Go through src/m and append any directory that contains a *.py file to PATH + #Go through src / m and append any directory that contains a * .py file to PATH for root, dirs, files in os.walk(ISSM_DIR + '/src/m'): if '.svn' in dirs: dirs.remove('.svn') for file in files: - if file.find(".py") != -1: - if file.find(".pyc") == -1: + if file.find(".py") != - 1: + if file.find(".pyc") == - 1: if root not in sys.path: sys.path.append(root) -#Also add the Nightly run directory + #Also add the Nightly run directory if ISSM_DIR + '/test/NightlyRun' not in sys.path: sys.path.append(ISSM_DIR + '/test/NightlyRun') @@ -27,5 +28,5 @@ if ISSM_DIR + '/src/wrappers/python/.libs' not in sys.path: sys.path.append(ISSM_DIR + '/src/wrappers/python/.libs') -# If using clusters, we need to have the path to the cluster settings directory + # If using clusters, we need to have the path to the cluster settings directory if JPL_SVN is not None: jpl_path = JPL_SVN + '/usr/' + USERNAME @@ -34,8 +35,8 @@ sys.path.append(jpl_path) else: - warnings.warn('cluster settings should be in, {}/usr/{}'.format(JPL_SVN, USERNAME)) + warnings.warn('cluster settings should be in, {} / usr / {}'.format(JPL_SVN, USERNAME)) -#Manual imports for commonly used functions -from runme import runme #first because plotmodel may fail + #Manual imports for commonly used functions +from runme import runme #first because plotmodel may fail from plotmodel import plotmodel Index: /issm/trunk-jpl/src/m/dev/issmversion.py =================================================================== --- /issm/trunk-jpl/src/m/dev/issmversion.py (revision 24212) +++ /issm/trunk-jpl/src/m/dev/issmversion.py (revision 24213) @@ -1,19 +1,20 @@ from IssmConfig import IssmConfig + def issmversion(): - """ - ISSMVERSION - display ISSM version + """ + ISSMVERSION - display ISSM version - Usage: - issmversion() - """ + Usage: + issmversion() + """ print(' ') -print((IssmConfig('PACKAGE_NAME')[0]+' Version '+IssmConfig('PACKAGE_VERSION')[0])) -print(('(website: '+IssmConfig('PACKAGE_URL')[0]+' contact: '+IssmConfig('PACKAGE_BUGREPORT')[0]+')')) +print((IssmConfig('PACKAGE_NAME')[0] + ' Version ' + IssmConfig('PACKAGE_VERSION')[0])) +print(('(website: ' + IssmConfig('PACKAGE_URL')[0] + ' contact: ' + IssmConfig('PACKAGE_BUGREPORT')[0] + ')')) print(' ') -print(('Build date: '+IssmConfig('PACKAGE_BUILD_DATE')[0])) -print('Copyright (c) 2009-2018 California Institute of Technology') +print(('Build date: ' + IssmConfig('PACKAGE_BUILD_DATE')[0])) +print('Copyright (c) 2009 - 2018 California Institute of Technology') print(' ') print(' to get started type: issmdoc') Index: /issm/trunk-jpl/src/m/exp/expcoarsen.py =================================================================== --- /issm/trunk-jpl/src/m/exp/expcoarsen.py (revision 24212) +++ /issm/trunk-jpl/src/m/exp/expcoarsen.py (revision 24213) @@ -1,77 +1,77 @@ import os.path -import numpy as np +import numpy as np from collections import OrderedDict from expread import expread from expwrite import expwrite -def expcoarsen(newfile,oldfile,resolution): - """ - EXPCOARSEN - coarsen an exp contour - This routine read an Argus file and remove points with respect to - the resolution (in meters) given in input. +def expcoarsen(newfile, oldfile, resolution): + """ + EXPCOARSEN - coarsen an exp contour - Usage: - expcoarsen(newfile,oldfile,resolution) + This routine read an Argus file and remove points with respect to + the resolution (in meters) given in input. - Example: - expcoarsen('DomainOutline.exp','Antarctica.exp',4000) - """ + Usage: + expcoarsen(newfile, oldfile, resolution) - #Some checks - if not os.path.exists(oldfile): - raise OSError("expcoarsen error message: file '%s' not found!" % oldfile) - if os.path.exists(newfile): - choice=eval(input('A file ' + newfile + ' already exists, do you want to modify it? (y/n)')) - if choice not in 'y': - print('no modification done ... exiting') - return 0 + Example: + expcoarsen('DomainOutline.exp', 'Antarctica.exp', 4000) + """ - #Get exp oldfile - contours=expread(oldfile) - newcontours=[] + #Some checks + if not os.path.exists(oldfile): + raise OSError("expcoarsen error message: file '%s' not found!" % oldfile) + if os.path.exists(newfile): + choice = eval(input('A file ' + newfile + ' already exists, do you want to modify it? (y / n)')) + if choice not in 'y': + print('no modification done ... exiting') + return 0 - for contour in contours: - - numpoints=np.size(contour['x']) + #Get exp oldfile + contours = expread(oldfile) + newcontours = [] - j=0 - x=contour['x'] - y=contour['y'] + for contour in contours: + numpoints = np.size(contour['x']) - #stop if we have reached end of profile (always keep the last point) - while j=2: - xi=np.linspace(x[j],x[j+1],division) - yi=np.linspace(y[j],y[j+1],division) - - x=np.hstack((x[0:j+1],xi[1:-1],x[j+1:])) - y=np.hstack((y[0:j+1],yi[1:-1],y[j+1:])) + #stop if we have reached end of profile (always keep the last point) + while j < numpoints - 1: - #update current point - j=j+1+division-2 - numpoints=numpoints+division-2 - else: - #update current point - j=j+1 - - if np.size(x)>1: - #keep the (x,y) contour arond - newcontour=OrderedDict() - newcontour['nods']=np.size(x) - newcontour['density']=contour['density'] - newcontour['x']=x - newcontour['y']=y - newcontours.append(newcontour) + #see whether we keep this point or not + distance = np.sqrt((x[j] - x[j + 1])**2 + (y[j] - y[j + 1])**2) + if distance < resolution and j < numpoints - 2: #do not remove last point + x = np.delete(x, j + 1, 0) + y = np.delete(y, j + 1, 0) + numpoints = numpoints - 1 + else: + division = int(np.floor(distance / resolution) + 1) + if division >= 2: + xi = np.linspace(x[j], x[j + 1], division) + yi = np.linspace(y[j], y[j + 1], division) - #write output - expwrite(newcontours,newfile) + x = np.hstack((x[0:j + 1], xi[1: - 1], x[j + 1:])) + y = np.hstack((y[0:j + 1], yi[1: - 1], y[j + 1:])) + + #update current point + j = j + 1 + division - 2 + numpoints = numpoints + division - 2 + else: + #update current point + j = j + 1 + + if np.size(x) > 1: + #keep the (x, y) contour arond + newcontour = OrderedDict() + newcontour['nods'] = np.size(x) + newcontour['density'] = contour['density'] + newcontour['x'] = x + newcontour['y'] = y + newcontours.append(newcontour) + + #write output + expwrite(newcontours, newfile) Index: /issm/trunk-jpl/src/m/exp/expdisp.py =================================================================== --- /issm/trunk-jpl/src/m/exp/expdisp.py (revision 24212) +++ /issm/trunk-jpl/src/m/exp/expdisp.py (revision 24213) @@ -1,59 +1,60 @@ from expread import expread -import numpy as np +import numpy as np from matplotlib.path import Path import matplotlib.patches as patches -def expdisp(ax,options): - ''' - plot the contents of a domain outline file - This routine reads in an exp file and plots all of the x,y points/lines/patches +def expdisp(ax, options): + ''' + plot the contents of a domain outline file - 'ax' is a handle to the current plot axes, onto which we want to plot + This routine reads in an exp file and plots all of the x, y points / lines / patches - Usage: - expdisp(ax,options) + 'ax' is a handle to the current plot axes, onto which we want to plot - List of options passable to plotmodel: - 'expdisp' : path (or list of paths) to the exp file to be plotted - 'explinewidth' : linewidth - 'explinestyle' : matplotlib linestyle string - 'explinecolor' : matplotlib color string - 'expfill' : (True/False) fill a closed contour - 'expfillcolor' : Color for a filled contour, only used if expfill is True - 'expfillalpha' : alpha transparency for filled contour + Usage: + expdisp(ax, options) - All options should be passed as lists of length len(number of exp files passed) - ''' + List of options passable to plotmodel: + 'expdisp' : path (or list of paths) to the exp file to be plotted + 'explinewidth' : linewidth + 'explinestyle' : matplotlib linestyle string + 'explinecolor' : matplotlib color string + 'expfill' : (True / False) fill a closed contour + 'expfillcolor' : Color for a filled contour, only used if expfill is True + 'expfillalpha' : alpha transparency for filled contour - filenames=options.getfieldvalue('expdisp') - linewidth=options.getfieldvalue('explinewidth',[1]*len(filenames)) - linestyle=options.getfieldvalue('explinestyle',['-']*len(filenames)) - linecolor=options.getfieldvalue('explinecolor',['k']*len(filenames)) - fill=options.getfieldvalue('expfill',[0]*len(filenames)) - alpha=options.getfieldvalue('expfillalpha',[1]*len(filenames)) - facecolor=options.getfieldvalue('expfillcolor',['r']*len(filenames)) - unitmultiplier=options.getfieldvalue('unit',1) - for i in range(len(filenames)): - linestylei=linestyle[i] - linecolori=linecolor[i] - linewidthi=linewidth[i] - alphai=alpha[i] - facecolori=facecolor[i] - filenamei=filenames[i] - filli=fill[i] - domain=expread(filenamei) - for j in range(len(domain)): - if domain[j]['nods']==1: - ax.plot(domain[j]['x']*unitmultiplier,domain[j]['y']*unitmultiplier,'o',mec='k',mfc='r',ms=10) - elif filli: - verts=np.column_stack((domain[j]['x'],domain[j]['y'])) - codes=[Path.MOVETO] + [Path.LINETO]*(len(domain[j]['x'])-2) + [Path.CLOSEPOLY] - path=Path(verts, codes) - patch=patches.PathPatch(path,facecolor=facecolori,edgecolor=linecolori,alpha=alphai, - lw=linewidthi) - ax.add_patch(patch) - else: - x=domain[j]['x'].tolist() # since expread returns a string representation of the arrays - y=domain[j]['y'].tolist() - ax.plot(x*unitmultiplier,y*unitmultiplier,ls=linestylei,lw=linewidthi,c=linecolori) + All options should be passed as lists of length len(number of exp files passed) + ''' + + filenames = options.getfieldvalue('expdisp') + linewidth = options.getfieldvalue('explinewidth', [1] * len(filenames)) + linestyle = options.getfieldvalue('explinestyle', ['-'] * len(filenames)) + linecolor = options.getfieldvalue('explinecolor', ['k'] * len(filenames)) + fill = options.getfieldvalue('expfill', [0] * len(filenames)) + alpha = options.getfieldvalue('expfillalpha', [1] * len(filenames)) + facecolor = options.getfieldvalue('expfillcolor', ['r'] * len(filenames)) + unitmultiplier = options.getfieldvalue('unit', 1) + for i in range(len(filenames)): + linestylei = linestyle[i] + linecolori = linecolor[i] + linewidthi = linewidth[i] + alphai = alpha[i] + facecolori = facecolor[i] + filenamei = filenames[i] + filli = fill[i] + domain = expread(filenamei) + for j in range(len(domain)): + if domain[j]['nods'] == 1: + ax.plot(domain[j]['x'] * unitmultiplier, domain[j]['y'] * unitmultiplier, 'o', mec='k', mfc='r', ms=10) + elif filli: + verts = np.column_stack((domain[j]['x'], domain[j]['y'])) + codes = [Path.MOVETO] + [Path.LINETO] * (len(domain[j]['x']) - 2) + [Path.CLOSEPOLY] + path = Path(verts, codes) + patch = patches.PathPatch(path, facecolor=facecolori, edgecolor=linecolori, alpha=alphai, + lw=linewidthi) + ax.add_patch(patch) + else: + x = domain[j]['x'].tolist() # since expread returns a string representation of the arrays + y = domain[j]['y'].tolist() + ax.plot(x * unitmultiplier, y * unitmultiplier, ls=linestylei, lw=linewidthi, c=linecolori) Index: /issm/trunk-jpl/src/m/exp/expread.py =================================================================== --- /issm/trunk-jpl/src/m/exp/expread.py (revision 24212) +++ /issm/trunk-jpl/src/m/exp/expread.py (revision 24213) @@ -4,91 +4,88 @@ import MatlabFuncs as m + def expread(filename): + """ - """ + EXPREAD - read a file exp and build a Structure - EXPREAD - read a file exp and build a Structure + This routine reads a file .exp and builds a list of dicts containing the + fields x and y corresponding to the coordinates, one for the filename of + the exp file, for the density, for the nodes, and a field closed to + indicate if the domain is closed. + The first argument is the .exp file to be read and the second one (optional) + indicate if the last point shall be read (1 to read it, 0 not to). - This routine reads a file .exp and builds a list of dicts containing the - fields x and y corresponding to the coordinates, one for the filename of - the exp file, for the density, for the nodes, and a field closed to - indicate if the domain is closed. - The first argument is the .exp file to be read and the second one (optional) - indicate if the last point shall be read (1 to read it, 0 not to). + Usage: + contours = expread(filename) - Usage: - contours=expread(filename) + Example: + contours = expread('domainoutline.exp') + contours = expread('domainoutline.exp') - Example: - contours=expread('domainoutline.exp') - contours=expread('domainoutline.exp') + See also EXPDOC, EXPWRITEASVERTICES - See also EXPDOC, EXPWRITEASVERTICES + """ + #some checks + if not os.path.exists(filename): + raise OSError("expread error message: file '%s' not found!" % filename) - """ - #some checks - if not os.path.exists(filename): - raise OSError("expread error message: file '%s' not found!" % filename) + #initialize number of profile + contours = [] + #open file + fid = open(filename, 'r') + #loop over the number of profiles + while True: + #update number of profiles + contour = OrderedDict() + #Get file name + A = fid.readline() + while A == '\n': + A = fid.readline() + if not A: + break + A = A.split(None, 1) + if not (len(A) == 2 and m.strcmp(A[0], '##') and m.strncmp(A[1], 'Name:', 5)): + break - #initialize number of profile - contours=[] - #open file - fid=open(filename,'r') - #loop over the number of profiles - while True: - #update number of profiles - contour=OrderedDict() - #Get file name - A=fid.readline() - while A=='\n': - A=fid.readline() - if not A: - break - A=A.split(None,1) - if not (len(A) == 2 and m.strcmp(A[0],'##') and m.strncmp(A[1],'Name:',5)): - break + if len(A[1]) > 5: + contour['name'] = A[1][5: - 1] + else: + contour['name'] = '' - if len(A[1])>5: - contour['name']=A[1][5:-1] - else: - contour['name']='' + #Get Icon + A = fid.readline().split(None, 1) + if not (len(A) == 2 and m.strcmp(A[0], '##') and m.strncmp(A[1], 'Icon:', 5)): + break + #Get Info + A = fid.readline().split() + if not (len(A) == 4 and m.strcmp(A[0], '#') and m.strcmp(A[1], 'Points')): + break - #Get Icon - A=fid.readline().split(None,1) - if not (len(A) == 2 and m.strcmp(A[0],'##') and m.strncmp(A[1],'Icon:',5)): - break - #Get Info - A=fid.readline().split() - if not (len(A) == 4 and m.strcmp(A[0],'#') and m.strcmp(A[1],'Points')): - break + #Get number of nodes and density + A = fid.readline().split() + contour['nods'] = int(A[0]) + contour['density'] = float(A[1]) - #Get number of nodes and density - A=fid.readline().split() - contour['nods']=int(A[0]) - contour['density']=float(A[1]) + #Get Info + A = fid.readline().split() + if not (len(A) == 5 and m.strcmp(A[0], '#') and m.strcmp(A[1], 'X') and m.strcmp(A[2], 'pos') and m.strcmp(A[3], 'Y') and m.strcmp(A[4], 'pos')): + break + #Get Coordinates + contour['x'] = np.empty(contour['nods']) + contour['y'] = np.empty(contour['nods']) + for i in range(int(contour['nods'])): + A = fid.readline().split() + contour['x'][i] = float(A[0]) + contour['y'][i] = float(A[1]) - #Get Info - A=fid.readline().split() - if not (len(A) == 5 and m.strcmp(A[0],'#') and m.strcmp(A[1],'X') and m.strcmp(A[2],'pos') - and m.strcmp(A[3],'Y') and m.strcmp(A[4],'pos')): - break - #Get Coordinates - contour['x']=np.empty(contour['nods']) - contour['y']=np.empty(contour['nods']) - for i in range(int(contour['nods'])): - A=fid.readline().split() - contour['x'][i]=float(A[0]) - contour['y'][i]=float(A[1]) + #Check if closed + if (contour['nods'] > 1) and (contour['x'][-1] == contour['x'][0]) and (contour['y'][-1] == contour['y'][0]): + contour['closed'] = True + else: + contour['closed'] = False - #Check if closed - if (contour['nods'] > 1) and \ - (contour['x'][-1] == contour['x'][0]) and \ - (contour['y'][-1] == contour['y'][0]): - contour['closed']=True - else: - contour['closed']=False - - contours.append(contour) - #close file - fid.close() - return contours + contours.append(contour) + #close file + fid.close() + return contours Index: /issm/trunk-jpl/src/m/exp/expwrite.py =================================================================== --- /issm/trunk-jpl/src/m/exp/expwrite.py (revision 24212) +++ /issm/trunk-jpl/src/m/exp/expwrite.py (revision 24213) @@ -1,47 +1,47 @@ import numpy as np -def expwrite(contours,filename): - """ - EXPWRITE - write an Argus file from a dictionary given in input - This routine writes an Argus file from a dict containing the fields: - x and y of the coordinates of the points. - The first argument is the list containing the points coordinates - and the second one the file to be written. +def expwrite(contours, filename): + """ + EXPWRITE - write an Argus file from a dictionary given in input - Usage: - expwrite(contours,filename) + This routine writes an Argus file from a dict containing the fields: + x and y of the coordinates of the points. + The first argument is the list containing the points coordinates + and the second one the file to be written. - Example: - expwrite(coordstruct,'domainoutline.exp') + Usage: + expwrite(contours, filename) - See also EXPDOC, EXPREAD, EXPWRITEASVERTICES - """ + Example: + expwrite(coordstruct, 'domainoutline.exp') - fid=open(filename,'w') - for x,y in zip(contours['x'],contours['y']): - #if np.size(contour['x'])!=np.size(contour['y']): - if len(x)!=len(y): - raise RuntimeError("contours x and y coordinates must be of identical size") - if 'name' in contours: - fid.write("%s%s\n" % ('## Name:',contours['name'])) - else: - fid.write("%s%s\n" % ('## Name:',filename)) - - #Add density if it's not there FIXME what is this ever used for? - #if 'density' not in contours: - # contours['density']=1 - density=1 + See also EXPDOC, EXPREAD, EXPWRITEASVERTICES + """ - fid.write("%s\n" % '## Icon:0') - fid.write("%s\n" % '# Points Count Value') - #fid.write("%i %f\n" % (np.size(contour['x']),contour['density'])) - fid.write("%i %f\n" % (np.size(x),density)) - fid.write("%s\n" % '# X pos Y pos') - #for x,y in zip(contour['x'],contour['y']): - for xi,yi in zip(x,y): - fid.write("%10.10f %10.10f\n" % (xi,yi)) - fid.write("\n") + fid = open(filename, 'w') + for x, y in zip(contours['x'], contours['y']): + #if np.size(contour['x']) != np.size(contour['y']): + if len(x) != len(y): + raise RuntimeError("contours x and y coordinates must be of identical size") + if 'name' in contours: + fid.write("%s%s\n" % (' # Name:', contours['name'])) + else: + fid.write("%s%s\n" % (' # Name:', filename)) - fid.close() + #Add density if it's not there FIXME what is this ever used for? + #if 'density' not in contours: + # contours['density'] = 1 + density = 1 + fid.write("%s\n" % ' # Icon:0') + fid.write("%s\n" % ' # Points Count Value') + #fid.write("%i %f\n" % (np.size(contour['x']), contour['density'])) + fid.write("%i %f\n" % (np.size(x), density)) + fid.write("%s\n" % ' # X pos Y pos') + #for x, y in zip(contour['x'], contour['y']): + for xi, yi in zip(x, y): + fid.write("%10.10f %10.10f\n" % (xi, yi)) + fid.write("\n") + + fid.close() Index: /issm/trunk-jpl/src/m/exp/flowlines.py =================================================================== --- /issm/trunk-jpl/src/m/exp/flowlines.py (revision 24212) +++ /issm/trunk-jpl/src/m/exp/flowlines.py (revision 24213) @@ -11,22 +11,22 @@ # # Usage: - # flowpath=flowlines(index,x,y,u,v,x0,y0,varargin) + # flowpath = flowlines(index, x, y, u, v, x0, y0, varargin) # - # the velocity field is given by the couple (u,v) and the coordinates - # of the seed points are (x0,y0). One can use one or several seed + # the velocity field is given by the couple (u, v) and the coordinates + # of the seed points are (x0, y0). One can use one or several seed # points # # Example: - # flowpath=flowlines(md.mesh.elements,md.mesh.x,md.mesh.y,md.initialization.vx,md.initialization.vy,x0,y0) + # flowpath = flowlines(md.mesh.elements, md.mesh.x, md.mesh.y, md.initialization.vx, md.initialization.vy, x0, y0) # # Options: - # - 'maxiter': how many steps upstream and downstream of the seed points (default: 200) - # - 'precision': division of each segment (higer precision increases number of segments, default: 1) - # - 'downstream':flow line upstream of the seed points (default: 1) - # - 'upstream': flow line upstream of the seed points (default: 1) + # - 'maxiter': how many steps upstream and downstream of the seed points (default: 200) + # - 'precision': division of each segment (higer precision increases number of segments, default: 1) + # - 'downstream':flow line upstream of the seed points (default: 1) + # - 'upstream': flow line upstream of the seed points (default: 1) #check input if (not len(x) == len(y) == len(u) == len(v)): - raise IOError('flowlines error message: x,y,u and v must have the same length') + raise IOError('flowlines error message: x, y, u and v must have the same length') if len(x) < 3: @@ -79,5 +79,5 @@ for flowdirection in ['downstream', 'upstream']: print('Dealing with the {} flowlines'.format(flowdirection)) - #initialization: + #initialization: counter = 1 treatdirection = options.getfieldvalue(flowdirection, 1) @@ -91,5 +91,5 @@ flowindex = 0 elif flowdirection == 'downstream': - flowindex = -1 + flowindex = - 1 while not all(done): @@ -112,6 +112,6 @@ #velocity of the current triangle and norm it if flowdirection == 'upstream': - ut = -u[tria] - vt = -v[tria] + ut = - u[tria] + vt = - v[tria] if flowdirection == 'downstream': ut = u[tria] Index: /issm/trunk-jpl/src/m/extrusion/DepthAverage.py =================================================================== --- /issm/trunk-jpl/src/m/extrusion/DepthAverage.py (revision 24212) +++ /issm/trunk-jpl/src/m/extrusion/DepthAverage.py (revision 24213) @@ -9,8 +9,8 @@ Usage: - vector_average=DepthAverage(md,vector) + vector_average = DepthAverage(md, vector) Example: - vel_bar=DepthAverage(md,md.initialization.vel) + vel_bar = DepthAverage(md, md.initialization.vel) ''' @@ -27,5 +27,5 @@ if vector.ndim == 2: vec2d = True - vector = vector.reshape(-1,) + vector = vector.reshape(- 1, ) #nods data @@ -43,9 +43,9 @@ elements_dz = vertices_dz.mean(1) vector_average = vector_average + project2d(md, vector, i) * elements_dz - #vector_average = vector_average + project2d(md, vector, i) * (project2d(md, md.mesh.z, i + 1) - project2d(md, md.mesh.z, i)) + #vector_average = vector_average + project2d(md, vector, i) * (project2d(md, md.mesh.z, i + 1) - project2d(md, md.mesh.z, i)) vertices_thickness = project2d(md, md.geometry.thickness, 1) elements_thickness = vertices_thickness.mean(1) vector_average = vector_average / elements_thickness - #vector_average = vector_average / project2d(md, md.geometry.thickness, 1) + #vector_average = vector_average / project2d(md, md.geometry.thickness, 1) else: @@ -53,5 +53,5 @@ if vec2d: - vector_average = vector_average.reshape(-1,) + vector_average = vector_average.reshape(- 1, ) return vector_average Index: /issm/trunk-jpl/src/m/extrusion/project2d.py =================================================================== --- /issm/trunk-jpl/src/m/extrusion/project2d.py (revision 24212) +++ /issm/trunk-jpl/src/m/extrusion/project2d.py (revision 24213) @@ -1,5 +1,6 @@ import numpy as np -def project2d(md3d,value,layer): + +def project2d(md3d, value, layer): ''' returns the value of a field for a given layer of the mesh @@ -10,8 +11,8 @@ Usage: - projection_value=project2d(md3d,value,layer) + projection_value = project2d(md3d, value, layer) Example: - vel2=project2d(md3d,md3d.initialization.vel,2); + vel2 = project2d(md3d, md3d.initialization.vel, 2) returns the velocity of the second layer (1 is the base) ''' @@ -30,5 +31,5 @@ vec2d = False if value.ndim == 2 and value.shape[1] == 1: - value = value.reshape(-1,) + value = value.reshape(- 1, ) vec2d = True @@ -36,5 +37,5 @@ projection_value = value[(layer - 1) * md3d.mesh.numberofelements2d:layer * md3d.mesh.numberofelements2d] elif value.shape[0] == md3d.mesh.numberofvertices: - #print 'indices: ', (layer-1)*md3d.mesh.numberofvertices2d, layer*md3d.mesh.numberofvertices2d + #print 'indices: ', (layer - 1) * md3d.mesh.numberofvertices2d, layer * md3d.mesh.numberofvertices2d projection_value = value[(layer - 1) * md3d.mesh.numberofvertices2d:layer * md3d.mesh.numberofvertices2d] elif value.shape[0] == md3d.mesh.numberofvertices + 1: @@ -44,5 +45,5 @@ if vec2d: - projection_value = projection_value.reshape(-1,) + projection_value = projection_value.reshape(- 1, ) return projection_value Index: /issm/trunk-jpl/src/m/extrusion/project3d.py =================================================================== --- /issm/trunk-jpl/src/m/extrusion/project3d.py (revision 24212) +++ /issm/trunk-jpl/src/m/extrusion/project3d.py (revision 24213) @@ -2,11 +2,12 @@ from pairoptions import pairoptions -def project3d(md,*args): + +def project3d(md, *args): """ PROJECT3D - vertically project a vector from 2d mesh vertically project a vector from 2d mesh (split in noncoll and coll areas) into a 3d mesh. - This vector can be a node vector of size (md.mesh.numberofvertices2d,N/A) or an - element vector of size (md.mesh.numberofelements2d,N/A). + This vector can be a node vector of size (md.mesh.numberofvertices2d, N / A) or an + element vector of size (md.mesh.numberofelements2d, N / A). arguments: 'vector': 2d vector @@ -18,7 +19,7 @@ Examples: - extruded_vector=project3d(md,'vector',vector2d,'type','node','layer',1,'padding',NaN) - extruded_vector=project3d(md,'vector',vector2d,'type','element','padding',0) - extruded_vector=project3d(md,'vector',vector2d,'type','node') + extruded_vector = project3d(md, 'vector', vector2d, 'type', 'node', 'layer', 1, 'padding', NaN) + extruded_vector = project3d(md, 'vector', vector2d, 'type', 'element', 'padding', 0) + extruded_vector = project3d(md, 'vector', vector2d, 'type', 'node') """ @@ -31,13 +32,13 @@ #retrieve parameters from options. options = pairoptions(*args) - vector2d = options.getfieldvalue('vector') #mandatory - vectype = options.getfieldvalue('type') #mandatory - layer = options.getfieldvalue('layer', 0) #optional (do all layers otherwise) - paddingvalue = options.getfieldvalue('padding', 0) #0 by default + vector2d = options.getfieldvalue('vector') #mandatory + vectype = options.getfieldvalue('type') #mandatory + layer = options.getfieldvalue('layer', 0) #optional (do all layers otherwise) + paddingvalue = options.getfieldvalue('padding', 0) #0 by default vector1d = False if isinstance(vector2d, np.ndarray) and np.ndim(vector2d) == 1: vector1d = True - vector2d = vector2d.reshape(-1,) + vector2d = vector2d.reshape(- 1, ) if isinstance(vector2d, (bool, int, float)) or np.size(vector2d) == 1: @@ -52,8 +53,8 @@ projected_vector = (paddingvalue * np.ones((md.mesh.numberofvertices + 1))).astype(vector2d.dtype) projected_vector[-1] = vector2d[-1] - vector2d = vector2d[:-1] + vector2d = vector2d[: - 1] else: raise TypeError("vector length not supported") - #Fill in + #Fill in if layer == 0: for i in range(md.mesh.numberoflayers): @@ -67,8 +68,8 @@ projected_vector = (paddingvalue * np.ones((md.mesh.numberofvertices + 1, np.size(vector2d, axis=1)))).astype(vector2d.dtype) projected_vector[-1, :] = vector2d[-1, :] - vector2d = vector2d[:-1, :] + vector2d = vector2d[: - 1, :] else: raise TypeError("vector length not supported") - #Fill in + #Fill in if layer == 0: for i in range(md.mesh.numberoflayers): @@ -85,8 +86,8 @@ projected_vector = (paddingvalue * np.ones((md.mesh.numberofelements + 1))).astype(vector2d.dtype) projected_vector[-1] = vector2d[-1] - vector2d = vector2d[:-1] + vector2d = vector2d[: - 1] else: raise TypeError("vector length not supported") - #Fill in + #Fill in if layer == 0: for i in range(md.mesh.numberoflayers - 1): @@ -100,8 +101,8 @@ projected_vector = (paddingvalue * np.ones((md.mesh.numberofelements + 1, np.size(vector2d, axis=1)))).astype(vector2d.dtype) projected_vector[-1, :] = vector2d[-1, :] - vector2d = vector2d[:-1, :] + vector2d = vector2d[: - 1, :] else: raise TypeError("vector length not supported") - #Fill in + #Fill in if layer == 0: for i in range(md.mesh.numberoflayers - 1): @@ -114,5 +115,5 @@ if vector1d: - projected_vector = projected_vector.reshape(-1,) + projected_vector = projected_vector.reshape(- 1, ) return projected_vector Index: /issm/trunk-jpl/src/m/geometry/FlagElements.py =================================================================== --- /issm/trunk-jpl/src/m/geometry/FlagElements.py (revision 24212) +++ /issm/trunk-jpl/src/m/geometry/FlagElements.py (revision 24213) @@ -1,67 +1,66 @@ import numpy as np import os -#from basinzoom import basinzoon from ContourToMesh import ContourToMesh import MatlabFuncs as m import PythonFuncs as p -def FlagElements(md,region): - """ - FLAGELEMENTS - flag the elements in an region - The region can be given with an exp file, a list of elements or vertices +def FlagElements(md, region): + """ + FLAGELEMENTS - flag the elements in an region - Usage: - flag=FlagElements(md,region); + The region can be given with an exp file, a list of elements or vertices - Example: - flag=FlagElements(md,'all'); - flag=FlagElements(md,''); - flag=FlagElements(md,'Domain.exp'); - flag=FlagElements(md,'~Domain.exp'); - """ + Usage: + flag = FlagElements(md, region) - if isinstance(region,str): - if not region: - flag=np.zeros(md.mesh.numberofelements,bool) - invert=0 - elif m.strcmpi(region,'all'): - flag=np.ones(md.mesh.numberofelements,bool) - invert=0 - else: - #make sure that we actually don't want the elements outside the domain outline! - if m.strcmpi(region[0],'~'): - region=region[1:] - invert=1 - else: - invert=0 + Example: + flag = FlagElements(md, 'all') + flag = FlagElements(md, '') + flag = FlagElements(md, 'Domain.exp') + flag = FlagElements(md, '~Domain.exp') + """ - #does the region domain outline exist or do we have to look for xlim,ylim in basinzoom? - if not os.path.exists(region): - if len(region)>3 and not m.strcmp(region[-4:],'.exp'): - raise IOError("Error: File 'region' not found!" % region) - raise RuntimeError("FlagElements.py calling basinzoom.py is not complete.") - xlim,ylim=basinzoom('basin',region) - flag_nodes=p.logical_and_n(md.mesh.xxlim[0],md.mesh.yylim[0]) - flag=np.prod(flag_nodes[md.mesh.elements],axis=1).astype(bool) - else: - #ok, flag elements - flag=ContourToMesh(md.mesh.elements[:,0:3].copy(),md.mesh.x,md.mesh.y,region,'element',1) - flag=flag.astype(bool) + if isinstance(region, str): + if not region: + flag = np.zeros(md.mesh.numberofelements, bool) + invert = 0 + elif m.strcmpi(region, 'all'): + flag = np.ones(md.mesh.numberofelements, bool) + invert = 0 + else: + #make sure that we actually don't want the elements outside the domain outline! + if m.strcmpi(region[0], '~'): + region = region[1:] + invert = 1 + else: + invert = 0 - if invert: - flag=np.logical_not(flag) + #does the region domain outline exist or do we have to look for xlim, ylim in basinzoom? + if not os.path.exists(region): + if len(region) > 3 and not m.strcmp(region[-4:], '.exp'): + raise IOError("Error: File 'region' not found!" % region) + raise RuntimeError("FlagElements.py calling basinzoom.py is not complete.") + xlim, ylim = basinzoom('basin', region) + flag_nodes = p.logical_and_n(md.mesh.x < xlim[1], md.mesh.x > xlim[0], md.mesh.y < ylim[1], md.mesh.y > ylim[0]) + flag = np.prod(flag_nodes[md.mesh.elements], axis=1).astype(bool) + else: + #ok, flag elements + flag = ContourToMesh(md.mesh.elements[:, 0:3].copy(), md.mesh.x, md.mesh.y, region, 'element', 1) + flag = flag.astype(bool) - elif isinstance(region,np.ndarray) or isinstance(region,bool): - if np.size(region,0)==md.mesh.numberofelements: - flag=region - elif np.size(region,0)==md.mesh.numberofvertices: - flag=(np.sum(region[md.mesh.elements-1]>0,axis=1)==np.size(md.mesh.elements,1)) - else: - raise TypeError("Flaglist for region must be of same size as number of elements in model.") + if invert: + flag = np.logical_not(flag) - else: - raise TypeError("Invalid region option") + elif isinstance(region, np.ndarray) or isinstance(region, bool): + if np.size(region, 0) == md.mesh.numberofelements: + flag = region + elif np.size(region, 0) == md.mesh.numberofvertices: + flag = (np.sum(region[md.mesh.elements - 1] > 0, axis=1) == np.size(md.mesh.elements, 1)) + else: + raise TypeError("Flaglist for region must be of same size as number of elements in model.") - return flag + else: + raise TypeError("Invalid region option") + return flag Index: /issm/trunk-jpl/src/m/geometry/GetAreas.py =================================================================== --- /issm/trunk-jpl/src/m/geometry/GetAreas.py (revision 24212) +++ /issm/trunk-jpl/src/m/geometry/GetAreas.py (revision 24213) @@ -1,52 +1,52 @@ import numpy as np -def GetAreas(index,x,y,z=np.array([])): - """ - GETAREAS - compute areas or volumes of elements - compute areas of triangular elements or volumes - of pentahedrons +def GetAreas(index, x, y, z=np.array([])): + """ + GETAREAS - compute areas or volumes of elements - Usage: - areas =GetAreas(index,x,y); - volumes=GetAreas(index,x,y,z); + compute areas of triangular elements or volumes + of pentahedrons - Examples: - areas =GetAreas(md.mesh.elements,md.mesh.x,md.mesh.y); - volumes=GetAreas(md.mesh.elements,md.mesh.x,md.mesh.y,md.z); - """ + Usage: + areas =GetAreas(index, x, y) + volumes = GetAreas(index, x, y, z) - #get number of elements and number of nodes - nels=np.size(index,axis=0) - nods=np.size(x) + Examples: + areas =GetAreas(md.mesh.elements, md.mesh.x, md.mesh.y) + volumes = GetAreas(md.mesh.elements, md.mesh.x, md.mesh.y, md.z) + """ - #some checks - if np.size(y)!=nods or (z and np.size(z)!=nods): - raise TypeError("GetAreas error message: x,y and z do not have the same length.") - if np.max(index)>nods: - raise TypeError("GetAreas error message: index should not have values above %d." % nods) - if (not z and np.size(index,axis=1)!=3): - raise TypeError("GetAreas error message: index should have 3 columns for 2d meshes.") - if (z and np.size(index,axis=1)!=6): - raise TypeError("GetAreas error message: index should have 6 columns for 3d meshes.") + #get number of elements and number of nodes + nels = np.size(index, axis=0) + nods = np.size(x) - #initialization - areas=np.zeros(nels) - x1=x[index[:,0]-1] - x2=x[index[:,1]-1] - x3=x[index[:,2]-1] - y1=y[index[:,0]-1] - y2=y[index[:,1]-1] - y3=y[index[:,2]-1] + #some checks + if np.size(y) != nods or (z and np.size(z) != nods): + raise TypeError("GetAreas error message: x, y and z do not have the same length.") + if np.max(index) > nods: + raise TypeError("GetAreas error message: index should not have values above %d." % nods) + if (not z and np.size(index, axis=1) != 3): + raise TypeError("GetAreas error message: index should have 3 columns for 2d meshes.") + if (z and np.size(index, axis=1) != 6): + raise TypeError("GetAreas error message: index should have 6 columns for 3d meshes.") - #compute the volume of each element - if not z: - #compute the surface of the triangle - areas=(0.5*((x2-x1)*(y3-y1)-(y2-y1)*(x3-x1))) - else: - #V=area(triangle)*1/3(z1+z2+z3) - thickness=np.mean(z[index[:,3:6]-1])-np.mean(z[index[:,0:3]-1]) - areas=(0.5*((x2-x1)*(y3-y1)-(y2-y1)*(x3-x1)))*thickness + #initialization + areas = np.zeros(nels) + x1 = x[index[:, 0] - 1] + x2 = x[index[:, 1] - 1] + x3 = x[index[:, 2] - 1] + y1 = y[index[:, 0] - 1] + y2 = y[index[:, 1] - 1] + y3 = y[index[:, 2] - 1] - return areas + #compute the volume of each element + if not z: + #compute the surface of the triangle + areas = (0.5 * ((x2 - x1) * (y3 - y1) - (y2 - y1) * (x3 - x1))) + else: + #V = area(triangle) * 1 / 3(z1 + z2 + z3) + thickness = np.mean(z[index[:, 3:6] - 1]) - np.mean(z[index[:, 0:3] - 1]) + areas = (0.5 * ((x2 - x1) * (y3 - y1) - (y2 - y1) * (x3 - x1))) * thickness + return areas Index: /issm/trunk-jpl/src/m/geometry/NowickiProfile.py =================================================================== --- /issm/trunk-jpl/src/m/geometry/NowickiProfile.py (revision 24212) +++ /issm/trunk-jpl/src/m/geometry/NowickiProfile.py (revision 24213) @@ -1,44 +1,44 @@ import numpy as np + def NowickiProfile(x): - """ - NOWICKIPROFILE - Create profile at the transition zone based on Sophie Nowicki's thesis + """ + NOWICKIPROFILE - Create profile at the transition zone based on Sophie Nowicki's thesis - Usage: - [b h] = NowickiProfile(x) + Usage: + [b h] = NowickiProfile(x) - - h = ice thickness - - b = ice base - - x = along flow coordinate - """ - #Constant for theoretical profile - delta = 0.1 #ratio of water density and ice density -1 - hg = 1. #ice thickness at grounding line - sea = hg / (1+delta) #sea level - lamda = 0.1 #ration of deviatoric stress and water pressure - beta = 5. #friction coefficient - ms = 0.005 #surface accumulation rat - mu = 5. #viscosity - q = 0.801 #ice mass flux + - h = ice thickness + - b = ice base + - x = along flow coordinate + """ + #Constant for theoretical profile + delta = 0.1 #ratio of water density and ice density - 1 + hg = 1. #ice thickness at grounding line + sea = hg / (1 + delta) #sea level + lamda = 0.1 #ration of deviatoric stress and water pressure + beta = 5. #friction coefficient + ms = 0.005 #surface accumulation rat + mu = 5. #viscosity + q = 0.801 #ice mass flux - #mesh parameters - b = np.zeros((np.size(x),)) - h = np.zeros((np.size(x),)) - s = np.zeros((np.size(x),)) + #mesh parameters + b = np.zeros((np.size(x), )) + h = np.zeros((np.size(x), )) + s = np.zeros((np.size(x), )) - #upstream of the GL - for i in range(int(np.size(x)/2)): - ss = np.roots([1, 4 * lamda * beta, 0, 0, 6 * lamda * ms * x[i]**2 + - 12 * lamda * q * x[i] - hg**4 - 4 * lamda * beta * hg**3]) - for j in range(4): - if (np.isreal(ss[j]) > 0) and (np.imag(ss[j]) == 0): - s[i] = ss[j] - h[i] = s[i] - b[i] = 0. + #upstream of the GL + for i in range(int(np.size(x) / 2)): + ss = np.roots([1, 4 * lamda * beta, 0, 0, 6 * lamda * ms * x[i]**2 + 12 * lamda * q * x[i] - hg**4 - 4 * lamda * beta * hg**3]) + for j in range(4): + if (np.isreal(ss[j]) > 0) and (np.imag(ss[j]) == 0): + s[i] = ss[j] + h[i] = s[i] + b[i] = 0. - #downstream of the GL - for i in range(int(np.size(x)/2), int(np.size(x))): - h[i] = (x[i] / (4. * (delta+1) * q) + hg**(-2))**(-0.5) # ice thickness for ice shelf from (3.1) - b[i] = sea - h[i] * (1. / (1+delta)) + #downstream of the GL + for i in range(int(np.size(x) / 2), int(np.size(x))): + h[i] = (x[i] / (4. * (delta + 1) * q) + hg**(- 2))**(- 0.5) # ice thickness for ice shelf from (3.1) + b[i] = sea - h[i] * (1. / (1 + delta)) - return [b, h, sea] + return [b, h, sea] Index: /issm/trunk-jpl/src/m/geometry/SegIntersect.py =================================================================== --- /issm/trunk-jpl/src/m/geometry/SegIntersect.py (revision 24212) +++ /issm/trunk-jpl/src/m/geometry/SegIntersect.py (revision 24213) @@ -1,82 +1,82 @@ import numpy as np -def SegIntersect(seg1,seg2): - """ - SEGINTERSECT - test of segments intersection - return 1 if the two segments intersect - seg1=[x1 y1; x2 y2] - seg2=[x1 y1; x2 y2] +def SegIntersect(seg1, seg2): + """ + SEGINTERSECT - test of segments intersection - Usage: - bval=SegIntersect(seg1,seg2) - """ + return 1 if the two segments intersect + seg1 = [x1 y1; x2 y2] + seg2 = [x1 y1; x2 y2] - bval=1 + Usage: + bval = SegIntersect(seg1, seg2) + """ - xA=seg1[0,0] - yA=seg1[0,1] - xB=seg1[1,0] - yB=seg1[1,1] - xC=seg2[0,0] - yC=seg2[0,1] - xD=seg2[1,0] - yD=seg2[1,1] + bval = 1 - O2A=np.array([xA,yA])-np.array([xD/2.+xC/2.,yD/2.+yC/2.]) - O2B=np.array([xB,yB])-np.array([xD/2.+xC/2.,yD/2.+yC/2.]) - O1C=np.array([xC,yC])-np.array([xA/2.+xB/2.,yB/2.+yA/2.]) - O1D=np.array([xD,yD])-np.array([xA/2.+xB/2.,yB/2.+yA/2.]) + xA = seg1[0, 0] + yA = seg1[0, 1] + xB = seg1[1, 0] + yB = seg1[1, 1] + xC = seg2[0, 0] + yC = seg2[0, 1] + xD = seg2[1, 0] + yD = seg2[1, 1] - n1=np.array([yA-yB,xB-xA]) #normal vector to segA - n2=np.array([yC-yD,xD-xC]) #normal vector to segB + O2A = np.array([xA, yA]) - np.array([xD / 2. + xC / 2., yD / 2. + yC / 2.]) + O2B = np.array([xB, yB]) - np.array([xD / 2. + xC / 2., yD / 2. + yC / 2.]) + O1C = np.array([xC, yC]) - np.array([xA / 2. + xB / 2., yB / 2. + yA / 2.]) + O1D = np.array([xD, yD]) - np.array([xA / 2. + xB / 2., yB / 2. + yA / 2.]) - test1=np.dot(n2,O2A) - test2=np.dot(n2,O2B) + n1 = np.array([yA - yB, xB - xA]) #normal vector to segA + n2 = np.array([yC - yD, xD - xC]) #normal vector to segB - if test1*test2>0: - bval=0 - return bval + test1 = np.dot(n2, O2A) + test2 = np.dot(n2, O2B) - test3=np.dot(n1,O1C) - test4=np.dot(n1,O1D) + if test1 * test2 > 0: + bval = 0 + return bval - if test3*test4>0: - bval=0 - return bval + test3 = np.dot(n1, O1C) + test4 = np.dot(n1, O1D) - #if colinear - if test1*test2==0 and test3*test4==0 and np.linalg.det(np.hstack((n1.reshape((-1,)),n2.reshape(-1,))))==0: + if test3 * test4 > 0: + bval = 0 + return bval - #projection on the axis O1O2 - O2O1=np.array([xA/2.+xB/2.,yB/2.+yA/2.])-np.array([xD/2.+xC/2.,yD/2.+yC/2.]) - O1A=np.dot(O2O1,(O2A-O2O1)) - O1B=np.dot(O2O1,(O2B-O2O1)) - O1C=np.dot(O2O1,O1C) - O1D=np.dot(O2O1,O1D) + #if colinear + if test1 * test2 == 0 and test3 * test4 == 0 and np.linalg.det(np.hstack((n1.reshape((- 1, )), n2.reshape(- 1, )))) == 0: - #test if one point is included in the other segment (->bval=1) - if (O1C-O1A)*(O1D-O1A)<0: - bval=1 - return bval - if (O1C-O1B)*(O1D-O1B)<0: - bval=1 - return bval - if (O1A-O1C)*(O1B-O1C)<0: - bval=1 - return bval - if (O1A-O1D)*(O1B-O1D)<0: - bval=1 - return bval + #projection on the axis O1O2 + O2O1 = np.array([xA / 2. + xB / 2., yB / 2. + yA / 2.]) - np.array([xD / 2. + xC / 2., yD / 2. + yC / 2.]) + O1A = np.dot(O2O1, (O2A - O2O1)) + O1B = np.dot(O2O1, (O2B - O2O1)) + O1C = np.dot(O2O1, O1C) + O1D = np.dot(O2O1, O1D) - #test if the 2 segments have the same middle (->bval=1) - if O2O1==0: - bval=1 - return bval + #test if one point is included in the other segment (- > bval = 1) + if (O1C - O1A) * (O1D - O1A) < 0: + bval = 1 + return bval + if (O1C - O1B) * (O1D - O1B) < 0: + bval = 1 + return bval + if (O1A - O1C) * (O1B - O1C) < 0: + bval = 1 + return bval + if (O1A - O1D) * (O1B - O1D) < 0: + bval = 1 + return bval - #else - bval=0 - return bval + #test if the 2 segments have the same middle (- > bval = 1) + if O2O1 == 0: + bval = 1 + return bval - return bval + #else + bval = 0 + return bval + return bval Index: /issm/trunk-jpl/src/m/geometry/slope.py =================================================================== --- /issm/trunk-jpl/src/m/geometry/slope.py (revision 24212) +++ /issm/trunk-jpl/src/m/geometry/slope.py (revision 24213) @@ -9,6 +9,6 @@ Usage: - sx,sy,s=slope(md) - sx,sy,s=slope(md,md.results.TransientSolution(1).Surface) + sx, sy, s = slope(md) + sx, sy, s = slope(md, md.results.TransientSolution(1).Surface) """ @@ -30,10 +30,10 @@ raise RuntimeError("slope.py usage error") - #%compute nodal functions coefficients N(x,y)=alpha x + beta y + gamma + #%compute nodal functions coefficients N(x, y)=alpha x + beta y + gamma alpha, beta = GetNodalFunctionsCoeff(index, x, y)[0:2] summation = np.array([[1], [1], [1]]) - sx = np.dot(surf[index - 1, 0] * alpha, summation).reshape(-1,) - sy = np.dot(surf[index - 1, 0] * beta, summation).reshape(-1,) + sx = np.dot(surf[index - 1, 0] * alpha, summation).reshape(- 1, ) + sy = np.dot(surf[index - 1, 0] * beta, summation).reshape(- 1, ) s = np.sqrt(sx**2 + sy**2) Index: /issm/trunk-jpl/src/m/interp/SectionValues.py =================================================================== --- /issm/trunk-jpl/src/m/interp/SectionValues.py (revision 24212) +++ /issm/trunk-jpl/src/m/interp/SectionValues.py (revision 24213) @@ -1,5 +1,5 @@ import os from expread import expread -import numpy as np +import numpy as np from project2d import project2d #from InterpFromMesh2d import InterpFromMesh2d @@ -7,133 +7,132 @@ from InterpFromMeshToMesh3d import InterpFromMeshToMesh3d -def SectionValues(md,data,infile,resolution): - ''' - compute the value of a field on a section - - This routine gets the value of a given field of the model on points - given in the file infile (Argus type file). Resolution must be a list - [horizontal_resolution, vertical_resolution] - - Usage: - [elements,x,y,z,s,data]=SectionValues(md,data,filename,resolution) - [elements,x,y,z,s,data]=SectionValues(md,data,profile_structure,resolution) - ''' - if os.path.isfile(infile): - profile=expread(infile)[0] - nods=profile['nods'] - x=profile['x'] - y=profile['y'] - else: - raise IOError('file %s not found' % infile) +def SectionValues(md, data, infile, resolution): + ''' + compute the value of a field on a section - #get the specified resolution - if len(resolution)!=2: - raise ValueError('SectionValues error message: Resolution must be a list [horizontal_resolution, vertical_resolution]') - else: - res_h=resolution[0] + This routine gets the value of a given field of the model on points + given in the file infile (Argus type file). Resolution must be a list + [horizontal_resolution, vertical_resolution] - if md.mesh.domaintype().lower() == '3d': - if isinstance(resolution[1],int) or isinstance(resolution[1],float): - res_v=resolution[1] - else: - raise ValueError('SectionValues error: resolution must be a length-2 list of integers or floats') + Usage: + [elements, x, y, z, s, data] = SectionValues(md, data, filename, resolution) + [elements, x, y, z, s, data] = SectionValues(md, data, profile_structure, resolution) + ''' - #initialization - X=np.array([]) #X-coordinate - Y=np.array([]) #Y-coordinate - S=np.array([0.]) #curvilinear coordinate - - for i in range(nods-1): - - x_start=x[i] - x_end=x[i+1] - y_start=y[i] - y_end=y[i+1] - s_start=S[-1] - - length_segment=np.sqrt((x_end-x_start)**2+(y_end-y_start)**2) - portion=np.ceil(length_segment/res_h) - - x_segment=np.zeros(portion) - y_segment=np.zeros(portion) - s_segment=np.zeros(portion) + if os.path.isfile(infile): + profile = expread(infile)[0] + nods = profile['nods'] + x = profile['x'] + y = profile['y'] + else: + raise IOError('file %s not found' % infile) - for j in range(int(portion)): - x_segment[j]=x_start+(j)*(x_end-x_start)/portion - y_segment[j]=y_start+(j)*(y_end-y_start)/portion - s_segment[j]=s_start+j*length_segment/portion - - #plug into X and Y - X=np.append(X,x_segment) - Y=np.append(Y,y_segment) - S=np.append(S,s_segment) + #get the specified resolution + if len(resolution) != 2: + raise ValueError('SectionValues error message: Resolution must be a list [horizontal_resolution, vertical_resolution]') + else: + res_h = resolution[0] - X=np.append(X,x[nods-1]) - Y=np.append(Y,y[nods-1]) - - #Number of nodes: - numberofnodes=X.shape[0] - - #Compute Z - Z=np.zeros(numberofnodes) - - #New mesh and Data interpolation - if '2d' in md.mesh.domaintype().lower(): - - #Interpolation of data on specified points - #data_interp=InterpFromMesh2d(md.mesh.elements,md.mesh.x,md.mesh.y,data,X,Y)[0] - data_interp=InterpFromMeshToMesh2d(md.mesh.elements,md.mesh.x,md.mesh.y,data,X,Y)[0] - #data_interp=griddata(md.mesh.x,md.mesh.y,data,X,Y) - - #Compute index - index=np.array([list(range(1,numberofnodes)),list(range(2,numberofnodes+1))]).T - - else: - - #vertically extrude mesh - - #Get base and surface for each 2d point, offset to make sure that it is inside the glacier system - offset=1.e-3 - base=InterpFromMeshToMesh2d(md.mesh.elements2d,md.mesh.x2d,md.mesh.y2d,project2d(md,md.geometry.base,1),X,Y)[0]+offset - base=base.reshape(-1,) - surface=InterpFromMeshToMesh2d(md.mesh.elements2d,md.mesh.x2d,md.mesh.y2d,project2d(md,md.geometry.surface,1),X,Y)[0]-offset - surface=surface.reshape(-1,) - - #Some useful parameters - layers=int(np.ceil(np.mean(md.geometry.thickness)/res_v)) - nodesperlayer=int(numberofnodes) - nodestot=int(nodesperlayer*layers) - elementsperlayer=int(nodesperlayer-1) - elementstot=int((nodesperlayer-1)*(layers-1)) - - #initialization - X3=np.zeros(nodesperlayer*layers) - Y3=np.zeros(nodesperlayer*layers) - Z3=np.zeros(nodesperlayer*layers) - S3=np.zeros(nodesperlayer*layers) - index3=np.zeros((elementstot,4)) - - #Get new coordinates in 3d - for i in range(1,layers+1): - X3[i-1::layers]=X - Y3[i-1::layers]=Y - Z3[i-1::layers]=base+(i-1)*(surface-base)/(layers-1) - S3[i-1::layers]=S - - if i1') + if type(knn) != int or knn < 1: + raise TypeError('nearestneighbors error: knn should be an integer > 1') - if len(x) != len(data) or len(y) != len(data): - raise Exception('nearestneighbors error: x and y should have the same length as "data"') + if len(x) != len(data) or len(y) != len(data): + raise Exception('nearestneighbors error: x and y should have the same length as "data"') - filled=data - - XYGood=np.dstack([x[goodids],y[goodids]])[0] - XYBad=np.dstack([x[badids],y[badids]])[0] - tree=cKDTree(XYGood) - nearest=tree.query(XYBad,k=knn)[1] - - if knn==1: - filled[badids]=filled[goodids][nearest] # can add k=N to return the N nearest neighbors - else: - for i in range(len(badids)): - neardat=[] - for j in range(knn): - neardat.append(filled[goodids][nearest[i][j]]) - filled[badids[i]]=np.mean(neardat) - - return filled + filled = data + + XYGood = np.dstack([x[goodids], y[goodids]])[0] + XYBad = np.dstack([x[badids], y[badids]])[0] + tree = cKDTree(XYGood) + nearest = tree.query(XYBad, k=knn)[1] + + if knn == 1: + filled[badids] = filled[goodids][nearest] # can add k = N to return the N nearest neighbors + else: + for i in range(len(badids)): + neardat = [] + for j in range(knn): + neardat.append(filled[goodids][nearest[i][j]]) + filled[badids[i]] = np.mean(neardat) + + return filled Index: /issm/trunk-jpl/src/m/interp/interp.py =================================================================== --- /issm/trunk-jpl/src/m/interp/interp.py (revision 24212) +++ /issm/trunk-jpl/src/m/interp/interp.py (revision 24213) @@ -1,240 +1,249 @@ -# module for inperpolating/smoothing data -import numpy as np +# module for inperpolating / smoothing data +import numpy as np from scipy.interpolate import CloughTocher2DInterpolator, Rbf from scipy.spatial import cKDTree try: - import matplotlib.pyplot as plt + import matplotlib.pyplot as plt except ImportError: - print('could not import matplotlib, no plotting functions enabled.\ - Set plotonly=False in function call') - -def MeshSplineToMesh2d(x,y,data,xi,yi,tol=1e-6,fill_nans=False,**kwargs):#{{{ - ''' - Piecewise cubic, C1 smooth, curvature-minimizing interpolant in 2D. - The interpolant is guaranteed to be continuously differentiable, - and the gradients are chosen such that the curvature of the interpolant - is approximately minimized. - - Uses scipy.interpolate.CloughTocher2DInterpolator - - x,y: data point coordinates - data: data to be interpolated (same length as x,y) - xi,yi: coordintes to interpolate data onto - tol: tolerance for gradient estimation (default 1e-6) - fill_nans: fill nan's (holes) in data using the spline fit? - **kwargs: optional keywork arguments: - maxiter: maximum iterations in gradient estimation - - Returns interpolated data at given x,y coordinates. - - Usage: - interpdata=CloughToucher2d(x,y,data) - - Examples: - interpdata=CloughToucher2d(md.mesh.x,md.mesh.y,data) - interpdata=CloughToucher2d(md.mesh.x,md.mesh.y,data,tol=1e-3,maxiter=100) - ''' - - # unpack kwargs - maxiter=kwargs.pop('maxiter',None) - if 'maxiter' in kwargs: del kwargs['maxiter'] - if maxiter: - assert type(maxiter)==int, 'error, maxiter should be an integer' - assert len(kwargs)==0, 'error, unexpected or misspelled kwargs' - - # create sub-vectors that just cover the limits of xi and yi - # TODO x,y not necessarily a grid, so need a better definition of dx,dy (e.g. average element size) - dx=500 - dy=500 - #dx=x[1]-x[0] - #dy=y[1]-y[0] - xlim=[min(xi)-dx,max(xi)+dx] - ylim=[min(yi)-dy,max(yi)+dy] - xflag=np.logical_and(x>xlim[0],xylim[0],yxlim[0],xylim[0],yxlim[0],xcenterylim[0],ycenter0, adjusts the amount of smoothing applied. Defaults to 0, - such that the function always passes through nodal points. - z: coordinate array if interpolating in 3 dimensions - zi: coordinate array if interpolating in 3 dimensions - - Usage: - interpdata=RadialInterp(x,y,data,**kwargs) - - Examples: - interpdata=RadialInterp(md.mesh.x,md.mesh.y,data) - interpdata=RadialInterp(md.mesh.x,md.mesh.y,data,function='gaussian',epsilon=100,smooth=1) - ''' - - # unpack kwargs - function=kwargs.pop('function','gaussian') - if 'function' in kwargs: del kwargs['function'] - epsilon=kwargs.pop('epsilon',None) - if 'epsilon' in kwargs: del kwargs['epsilon'] - smooth=kwargs.pop('smooth',0) - if 'smooth' in kwargs: del kwargs['smooth'] - z=kwargs.pop('z',None) - if 'z' in kwargs: del kwargs['z'] - assert len(kwargs)==0, 'error, unexpected or misspelled kwargs' - - if z: - if epsilon: - rbfi=Rbf(x,y,z,data,function=function,smooth=smooth,epsilon=epsilon) - else: - rbfi=Rbf(x,y,z,data,function=function,smooth=smooth) - interpdata=rbfi(xi,yi,zi) - else: - if epsilon: - rbfi=Rbf(x,y,data,function=function,smooth=smooth,epsilon=epsilon) - else: - rbfi=Rbf(x,y,data,function=function,smooth=smooth) - interpdata=rbfi(xi,yi) - - return interpdata -#}}} + print('could not import matplotlib, no plotting functions enabled. Set plotonly = False in function call') + + +def MeshSplineToMesh2d(x, y, data, xi, yi, tol=1e-6, fill_nans=False, **kwargs): #{{{ + ''' + Piecewise cubic, C1 smooth, curvature-minimizing interpolant in 2D. + The interpolant is guaranteed to be continuously differentiable, + and the gradients are chosen such that the curvature of the interpolant + is approximately minimized. + + Uses scipy.interpolate.CloughTocher2DInterpolator + + x, y: data point coordinates + data: data to be interpolated (same length as x, y) + xi, yi: coordintes to interpolate data onto + tol: tolerance for gradient estimation (default 1e-6) + fill_nans: fill nan's (holes) in data using the spline fit? + **kwargs: optional keywork arguments: + maxiter: maximum iterations in gradient estimation + + Returns interpolated data at given x, y coordinates. + + Usage: + interpdata = CloughToucher2d(x, y, data) + + Examples: + interpdata = CloughToucher2d(md.mesh.x, md.mesh.y, data) + interpdata = CloughToucher2d(md.mesh.x, md.mesh.y, data, tol = 1e-3, maxiter = 100) + ''' + + # unpack kwargs + maxiter = kwargs.pop('maxiter', None) + if 'maxiter' in kwargs: + del kwargs['maxiter'] + if maxiter: + assert type(maxiter) == int, 'error, maxiter should be an integer' + assert len(kwargs) == 0, 'error, unexpected or misspelled kwargs' + + # create sub - vectors that just cover the limits of xi and yi + # TODO x, y not necessarily a grid, so need a better definition of dx, dy (e.g. average element size) + dx = 500 + dy = 500 + #dx = x[1] - x[0] + #dy = y[1] - y[0] + xlim = [min(xi) - dx, max(xi) + dx] + ylim = [min(yi) - dy, max(yi) + dy] + xflag = np.logical_and(x > xlim[0], x < xlim[1]) + yflag = np.logical_and(y > ylim[0], y < ylim[1]) + bothind = np.nonzero(np.logical_and(xflag, yflag)) + subdata = data[bothind] + subx = x[bothind] + suby = y[bothind] + points = np.array([subx, suby]).T + + # mask out any nan's in the data and corresponding coordinate points + mask = np.isnan(subdata) + ind = np.nonzero(mask)[0] + if len(ind) and fill_nans: + print(" WARNING: filling nans using spline fit through good data points, which may or may not be appropriate. Check results carefully.") + subdata = np.delete(subdata, ind) + points = np.delete(points, ind, axis=0) + + if maxiter: + spline = CloughTocher2DInterpolator(points, subdata, tol, maxiter=maxiter) + else: + spline = CloughTocher2DInterpolator(points, subdata, tol) + + interpdata = spline(xi, yi) + + if not fill_nans: + # identify nan's in xi, yi using nearest neighbors + xyinterp = np.dstack([xi, yi])[0] + xg, yg = np.meshgrid(subx, suby) + xydata = np.dstack([subx, suby])[0] + tree = cKDTree(xydata) + nearest = tree.query(xyinterp)[1] + pos = np.nonzero(np.isnan(subdata[nearest])) + interpdata[pos] = subdata[nearest][pos] + + return interpdata + #}}} + + +def GridSplineToMesh2d(x, y, data, xi, yi, default_value=np.nan, plotonly=False, fill_nans=False): #{{{ + ''' + python analog to InterpFromGridToMesh. This routine uses + scipy.interpolate.CloughTocher2dInterpolator to create a bivariate spline + interpolation of the input data and then return values of the spline + on the x, y coordinates of the model mesh. The interpolant is piece-wise + cubic, C1 smooth (continuously differentiable) and has approximately + minimized curvature. See "help(scipy.interpolate.CloughTocher2dInterpolator)" + for more information on the routine. + + NOTE: this routine will not be appropriate if there are large holes (nan's) in + the input data. A non - spline interpolation scheme should be used in that case. + + x, y: vectors defining the coordinates of the input data + data: 2D array of input data + xi, yi: x and y coordinates to be interpolated onto + default_value: default value if points lie outside the convex hull of input + points (defaults to nan if not specified) + plotonly: plot the data to be interpolated using imshow (useful for + fill_nans: fill nan's (holes) in data using the spline fit? + + Usage: + interpdata = GridToMesh(x, y, data, xi, yi, default_value = np.nan, plotonly = False, fill_nans = False) + + Examples: + interpdata = GridToMesh(x_m, y_m, data, md.mesh.x, md.mesh.y, 0) + ''' + + if np.ndim(x) == 2: + x = x.reshape(- 1, ) + if np.ndim(y) == 2: + y = y.reshape(- 1, ) + if len(x) != data.shape[1] + 1 and len(x) != data.shape[1]: + raise ValueError('x should have same length as ncols(data) or ncols(data) + 1') + if len(y) != data.shape[0] + 1 and len(y) != data.shape[0]: + raise ValueError('y should have same length as nrows(data) or nrows(data) + 1') + + # create sub - grid that just covers the limits of xi and yi + dx = x[1] - x[0] + dy = y[1] - y[0] + xlim = [min(xi) - dx, max(xi) + dx] + ylim = [min(yi) - dy, max(yi) + dy] + + # TODO create grid differently depending on whether data is defined at x, y + # or at the center of a grid cell with corner coordinates defined by xi, yi + # create points array and flattened data array + if len(x) == data.shape[1] and len(y) == data.shape[0]: + print(' x, y taken to define the center of data grid cells') + xind = np.nonzero(np.logical_and(x > xlim[0], x < xlim[1]))[0] + yind = np.nonzero(np.logical_and(y > ylim[0], y < ylim[1]))[0] + xg, yg = np.meshgrid(x[xind], y[yind]) + subdata = data[yind[0]:yind[-1] + 1, xind[0]:xind[-1] + 1] + elif len(x) == data.shape[1] + 1 and len(y) == data.shape[0] + 1: + print(' x, y taken to define the corners of data grid cells') + xcenter = np.fromiter(((x[i] + x[i + 1]) / 2 for i in range(len(x) - 1)), np.float) + ycenter = np.fromiter(((y[i] + y[i + 1]) / 2 for i in range(len(y) - 1)), np.float) + xind = np.nonzero(np.logical_and(xcenter > xlim[0], xcenter < xlim[1]))[0] + yind = np.nonzero(np.logical_and(ycenter > ylim[0], ycenter < ylim[1]))[0] + xg, yg = np.meshgrid(xcenter[xind], ycenter[yind]) + subdata = data[yind[0]:yind[-1] + 1, xind[0]:xind[-1] + 1] + else: + raise ValueError('x and y have inconsistent sizes: both should have length ncols(data) / nrows(data) or ncols(data) + 1 / nrows(data) + 1') + + points = np.array([xg.ravel(), yg.ravel()]).T + flatsubdata = subdata.ravel() + + if plotonly: + plt.imshow(np.flipud(subdata), origin='upper') + plt.show() + return + + # mask out any nan's in the data and corresponding coordinate points + mask = np.isnan(flatsubdata) + ind = np.nonzero(mask)[0] + if len(ind) and fill_nans: + print(" WARNING: filling nans using spline fit through good data points, which may or may not be appropriate. Check results carefully.") + goodsubdata = np.delete(flatsubdata, ind) + goodpoints = np.delete(points, ind, axis=0) + + # create spline and index spline at mesh points + spline = CloughTocher2DInterpolator(goodpoints, goodsubdata) + interpdata = spline(xi, yi) + + if not fill_nans: + # identify nan's in xi, yi using nearest neighbors + xyinterp = np.dstack([xi, yi])[0] + xydata = np.dstack([xg.ravel(), yg.ravel()])[0] + tree = cKDTree(xydata) + nearest = tree.query(xyinterp)[1] + pos = np.nonzero(np.isnan(flatsubdata[nearest])) + interpdata[pos] = flatsubdata[nearest][pos] + + return interpdata + #}}} + + +def RadialInterp(x, y, data, xi, yi, **kwargs): #{{{ + ''' + Interpolation using a radial basis function in 2 or 3 dimensions. + Useful for smoothing input data after interpolation. + + Uses scipy.interpolate.Rbf + + x, y: data point coordinates + data: data to be interpolated (same length as x, y) + xi, yi: coordinates to interpolate onto + function: form of radial basis function for interpolation: + 'multiquadric': sqrt((r / self.epsilon)**2 + 1) (default) + 'inverse': 1.0 / sqrt((r / self.epsilon)**2 + 1) + 'gaussian': exp(- (r / self.epsilon)**2) + 'linear': r + 'cubic': r**3 + 'quintic': r**5 + 'thin_plate': r**2 * log(r) + epsilon: adjustable constant for scaling radial distance. Defaults to + approximate average distance between nodes. + smooth: float > 0, adjusts the amount of smoothing applied. Defaults to 0, + such that the function always passes through nodal points. + z: coordinate array if interpolating in 3 dimensions + zi: coordinate array if interpolating in 3 dimensions + + Usage: + interpdata = RadialInterp(x, y, data,**kwargs) + + Examples: + interpdata = RadialInterp(md.mesh.x, md.mesh.y, data) + interpdata = RadialInterp(md.mesh.x, md.mesh.y, data, function = 'gaussian', epsilon = 100, smooth = 1) + ''' + + # unpack kwargs + function = kwargs.pop('function', 'gaussian') + if 'function' in kwargs: + del kwargs['function'] + epsilon = kwargs.pop('epsilon', None) + if 'epsilon' in kwargs: + del kwargs['epsilon'] + smooth = kwargs.pop('smooth', 0) + if 'smooth' in kwargs: + del kwargs['smooth'] + z = kwargs.pop('z', None) + if 'z' in kwargs: + del kwargs['z'] + assert len(kwargs) == 0, 'error, unexpected or misspelled kwargs' + + if z: + if epsilon: + rbfi = Rbf(x, y, z, data, function=function, smooth=smooth, epsilon=epsilon) + else: + rbfi = Rbf(x, y, z, data, function=function, smooth=smooth) + interpdata = rbfi(xi, yi, zi) + else: + if epsilon: + rbfi = Rbf(x, y, data, function=function, smooth=smooth, epsilon=epsilon) + else: + rbfi = Rbf(x, y, data, function=function, smooth=smooth) + interpdata = rbfi(xi, yi) + + return interpdata + #}}} Index: /issm/trunk-jpl/src/m/inversions/marshallcostfunctions.py =================================================================== --- /issm/trunk-jpl/src/m/inversions/marshallcostfunctions.py (revision 24212) +++ /issm/trunk-jpl/src/m/inversions/marshallcostfunctions.py (revision 24213) @@ -1,45 +1,44 @@ -import copy def marshallcostfunctions(cost_functions): - cfDict={101:'SurfaceAbsVelMisfit', - 102:'SurfaceRelVelMisfit', - 103:'SurfaceLogVelMisfit', - 104:'SurfaceLogVxVyMisfit', - 105:'SurfaceAverageVelMisfit', - 201:'ThicknessAbsMisfit', - 501:'DragCoefficientAbsGradient', - 502:'RheologyBbarAbsGradient', - 503:'ThicknessAbsGradient', - 504:'ThicknessAlongGradient', - 505:'ThicknessAcrossGradient',} + cfDict = {101: 'SurfaceAbsVelMisfit', + 102: 'SurfaceRelVelMisfit', + 103: 'SurfaceLogVelMisfit', + 104: 'SurfaceLogVxVyMisfit', + 105: 'SurfaceAverageVelMisfit', + 201: 'ThicknessAbsMisfit', + 501: 'DragCoefficientAbsGradient', + 502: 'RheologyBbarAbsGradient', + 503: 'ThicknessAbsGradient', + 504: 'ThicknessAlongGradient', + 505: 'ThicknessAcrossGradient'} - data=[cfDict[cf] for cf in cost_functions] - # #copy list first - # data=copy.deepcopy(cost_functions) + data = [cfDict[cf] for cf in cost_functions] + # #copy list first + # data = copy.deepcopy(cost_functions) - # #convert to strings - # pos=[i for i,x in enumerate(cost_functions) if x==101]; - # for i in pos: data[i]='SurfaceAbsVelMisfit' - # pos=[i for i,x in enumerate(cost_functions) if x==102]; - # for i in pos: data[i]='SurfaceRelVelMisfit' - # pos=[i for i,x in enumerate(cost_functions) if x==103]; - # for i in pos: data[i]='SurfaceLogVelMisfit' - # pos=[i for i,x in enumerate(cost_functions) if x==104]; - # for i in pos: data[i]='SurfaceLogVxVyMisfit' - # pos=[i for i,x in enumerate(cost_functions) if x==105]; - # for i in pos: data[i]='SurfaceAverageVelMisfit' - # pos=[i for i,x in enumerate(cost_functions) if x==201]; - # for i in pos: data[i]='ThicknessAbsMisfit' - # pos=[i for i,x in enumerate(cost_functions) if x==501]; - # for i in pos: data[i]='DragCoefficientAbsGradient' - # pos=[i for i,x in enumerate(cost_functions) if x==502]; - # for i in pos: data[i]='RheologyBbarAbsGradient' - # pos=[i for i,x in enumerate(cost_functions) if x==503]; - # for i in pos: data[i]='ThicknessAbsGradient' - # pos=[i for i,x in enumerate(cost_functions) if x==504]; - # for i in pos: data[i]='ThicknessAlongGradient' - # pos=[i for i,x in enumerate(cost_functions) if x==505]; - # for i in pos: data[i]='ThicknessAcrossGradient' + # #convert to strings + # pos = [i for i, x in enumerate(cost_functions) if x == 101] + # for i in pos: data[i] = 'SurfaceAbsVelMisfit' + # pos = [i for i, x in enumerate(cost_functions) if x == 102] + # for i in pos: data[i] = 'SurfaceRelVelMisfit' + # pos = [i for i, x in enumerate(cost_functions) if x == 103] + # for i in pos: data[i] = 'SurfaceLogVelMisfit' + # pos = [i for i, x in enumerate(cost_functions) if x == 104] + # for i in pos: data[i] = 'SurfaceLogVxVyMisfit' + # pos = [i for i, x in enumerate(cost_functions) if x == 105] + # for i in pos: data[i] = 'SurfaceAverageVelMisfit' + # pos = [i for i, x in enumerate(cost_functions) if x == 201] + # for i in pos: data[i] = 'ThicknessAbsMisfit' + # pos = [i for i, x in enumerate(cost_functions) if x == 501] + # for i in pos: data[i] = 'DragCoefficientAbsGradient' + # pos = [i for i, x in enumerate(cost_functions) if x == 502] + # for i in pos: data[i] = 'RheologyBbarAbsGradient' + # pos = [i for i, x in enumerate(cost_functions) if x == 503] + # for i in pos: data[i] = 'ThicknessAbsGradient' + # pos = [i for i, x in enumerate(cost_functions) if x == 504] + # for i in pos: data[i] = 'ThicknessAlongGradient' + # pos = [i for i, x in enumerate(cost_functions) if x == 505] + # for i in pos: data[i] = 'ThicknessAcrossGradient' - return data + return data Index: /issm/trunk-jpl/src/m/inversions/parametercontroldrag.py =================================================================== --- /issm/trunk-jpl/src/m/inversions/parametercontroldrag.py (revision 24212) +++ /issm/trunk-jpl/src/m/inversions/parametercontroldrag.py (revision 24213) @@ -1,118 +1,120 @@ -def parametercontroldrag(md,*args): - """ - PARAMETERCONTROLDRAG - parameterization for control method on drag +import numpy as np +from pairoptions import pairoptions - It is possible to specify the number of steps, values for the - minimum and maximum values of the drag, the - kind of cm_responses to use or the the optscal. - Usage: - md=parametercontroldrag(md,varargin) +def parametercontroldrag(md, *args): + """ + PARAMETERCONTROLDRAG - parameterization for control method on drag - Example: - md=parametercontroldrag(md) - md=parametercontroldrag(md,'nsteps',20,'cm_responses',0) - md=parametercontroldrag(md,'cm_min',1,'cm_max',150,'cm_jump',0.99,'maxiter',20) - md=parametercontroldrag(md,eps_cm',10^-4,'optscal',[10^7 10^8]) + It is possible to specify the number of steps, values for the + minimum and maximum values of the drag, the + kind of cm_responses to use or the the optscal. - See also PARAMETERCONTROLB - """ + Usage: + md = parametercontroldrag(md, varargin) - #process options - options=pairoptions(*args) + Example: + md = parametercontroldrag(md) + md = parametercontroldrag(md, 'nsteps', 20, 'cm_responses', 0) + md = parametercontroldrag(md, 'cm_min', 1, 'cm_max', 150, 'cm_jump', 0.99, 'maxiter', 20) + md = parametercontroldrag(md, eps_cm', 10^ - 4, 'optscal', [10^7 10^8]) - #control type - md.inversion.control_parameters='FrictionCoefficient' + See also PARAMETERCONTROLB + """ - #weights - weights=options.getfieldvalue('weights',np.ones(md.mesh.numberofvertices)) - if np.size(weights)!=md.mesh.numberofvertices: - md.inversion.cost_functions_coefficients=ones(md.mesh.numberofvertices) - else: - md.inversion.cost_functions_coefficients=weights + #process options + options = pairoptions(*args) - #nsteps - nsteps=options.getfieldvalue('nsteps',100); - if (np.size(nsteps)!=1) | (nsteps<=0) | (floor(nsteps)!=nsteps): - md.inversion.nsteps=100 - else: - md.inversion.nsteps=nsteps + #control type + md.inversion.control_parameters = 'FrictionCoefficient' - #cm_min - cm_min=options.getfieldvalue('cm_min',ones(md.mesh.numberofvertices)) - if (np.size(cm_min)==1): - md.inversion.min_parameters=cm_min*ones(md.mesh.numberofvertices) - elif (np.size(cm_min)==md.mesh.numberofvertices): - md.inversion.min_parameters=cm_min - else: - md.inversion.min_parameters=cm_min; + #weights + weights = options.getfieldvalue('weights', np.ones(md.mesh.numberofvertices)) + if np.size(weights) != md.mesh.numberofvertices: + md.inversion.cost_functions_coefficients = np.ones(md.mesh.numberofvertices) + else: + md.inversion.cost_functions_coefficients = weights - #cm_max - cm_max=options.getfieldvalue('cm_max',250*ones(md.mesh.numberofvertices)) - if (np.size(cm_max)==1): - md.inversion.max_parameters=cm_max*ones(md.mesh.numberofvertices) - elif (np.size(cm_max)==md.mesh.numberofvertices): - md.inversion.max_parameters=cm_max - else: - md.inversion.max_parameters=cm_max + #nsteps + nsteps = options.getfieldvalue('nsteps', 100) + if (np.size(nsteps) != 1) | (nsteps <= 0) | (np.floor(nsteps) != nsteps): + md.inversion.nsteps = 100 + else: + md.inversion.nsteps = nsteps - #eps_cm - eps_cm=optoins.getfieldvalue('eps_cm',float('nan')) - if (np.size(eps_cm)~=1 | eps_cm<0 ): - md.inversion.cost_function_threshold=float('nan') - else: - md.inversion.cost_function_threshold=eps_cm + #cm_min + cm_min = options.getfieldvalue('cm_min', np.ones(md.mesh.numberofvertices)) + if (np.size(cm_min) == 1): + md.inversion.min_parameters = cm_min * np.ones(md.mesh.numberofvertices) + elif (np.size(cm_min) == md.mesh.numberofvertices): + md.inversion.min_parameters = cm_min + else: + md.inversion.min_parameters = cm_min - #maxiter - maxiter=options.getfieldvalue('maxiter',10*ones(md.inversion.nsteps)) - if (np.any(maxiter<0) | np.any(floor(maxiter)~=maxiter)): - md.inversion.maxiter_per_step=10*ones(md.inversion.nsteps) - else: - raise RuntimeError("not implemented yet, see below matlab lines") - #md.inversion.maxiter_per_step=repmat(maxiter(:),md.inversion.nsteps,1); - #md.inversion.maxiter_per_step(md.inversion.nsteps+1:end)=[]; + #cm_max + cm_max = options.getfieldvalue('cm_max', 250 * np.ones(md.mesh.numberofvertices)) + if (np.size(cm_max) == 1): + md.inversion.max_parameters = cm_max * np.ones(md.mesh.numberofvertices) + elif (np.size(cm_max) == md.mesh.numberofvertices): + md.inversion.max_parameters = cm_max + else: + md.inversion.max_parameters = cm_max - #cm_jump - cm_jump=options.getfieldvalue('cm_jump',0.8*ones(md.inversion.nsteps)) - if !np.isreal(cm_jump): - md.inversion.step_threshold=0.8*ones(md.inversion.nsteps) - else: - raise RuntimeError("not implemented yet, see below matlab lines") - #md.inversion.step_threshold=repmat(cm_jump(:),md.inversion.nsteps,1); - #md.inversion.step_threshold(md.inversion.nsteps+1:end)=[]; + #eps_cm + eps_cm = options.getfieldvalue('eps_cm', float('nan')) + if (np.size(eps_cm) != 1 | eps_cm < 0): + md.inversion.cost_function_threshold = float('nan') + else: + md.inversion.cost_function_threshold = eps_cm - #cm_responses - found=0; - if options.exist('cm_responses'): - cm_responses=options.getfieldvalue('cm_responses') - if ~any(~ismember(cm_responses,[101 105])): - md.inversion.cost_functions=repmat(cm_responses(:),md.inversion.nsteps,1); - md.inversion.cost_functions(md.inversion.nsteps+1:end)=[]; - found=1; - if ~found - third=ceil(md.inversion.nsteps/3); - md.inversion.cost_functions=[... - 103*ones(third,1);... - 101*ones(third,1);... - repmat([101;101;103;101],third,1)... - ]; - md.inversion.cost_functions(md.inversion.nsteps+1:end)=[]; - end + #maxiter + maxiter = options.getfieldvalue('maxiter', 10 * np.ones(md.inversion.nsteps)) + if (np.any(maxiter < 0) | np.any(np.floor(maxiter) != maxiter)): + md.inversion.maxiter_per_step = 10 * np.ones(md.inversion.nsteps) + else: + raise RuntimeError("not implemented yet, see below matlab lines") + #md.inversion.maxiter_per_step = repmat(maxiter(:), md.inversion.nsteps, 1) + #md.inversion.maxiter_per_step(md.inversion.nsteps + 1:end) = [] - %optscal - found=0; - if exist(options,'optscal'), - optscal=getfieldvalue(options,'optscal'); - if ~any(optscal<0), - md.inversion.gradient_scaling=repmat(optscal(:),md.inversion.nsteps,1); - md.inversion.gradient_scaling(md.inversion.nsteps+1:end)=[]; - found=1; - end - end - if ~found - third=ceil(md.inversion.nsteps/3); - md.inversion.gradient_scaling=[50*ones(3,1);15*ones(third-3,1);10*ones(third,1);repmat([10;10;20;10],third,1)]; - md.inversion.gradient_scaling(md.inversion.nsteps+1:end)=[]; - end + #cm_jump + cm_jump = options.getfieldvalue('cm_jump', 0.8 * np.ones(md.inversion.nsteps)) + if not np.isreal(cm_jump): + md.inversion.step_threshold = 0.8 * np.ones(md.inversion.nsteps) + else: + raise RuntimeError("not implemented yet, see below matlab lines") + #md.inversion.step_threshold = repmat(cm_jump(:), md.inversion.nsteps, 1) + #md.inversion.step_threshold(md.inversion.nsteps + 1:end) = [] - return md + #cm_responses + found = 0 + if options.exist('cm_responses'): + cm_responses = options.getfieldvalue('cm_responses') + if not any(cm_responses not in [101, 105]): + md.inversion.cost_functions = np.tile(cm_responses[:], (md.inversion.nsteps, 1)) + md.inversion.cost_functions[md.inversion.nsteps:] = [] + found = 1 + if not found: + third = np.ceil(md.inversion.nsteps / 3) + md.inversion.cost_functions = [103 * np.ones(third, 1), + 101 * np.ones(third, 1), + np.tile([101, 101, 103, 101], (third, 1))] + md.inversion.cost_functions[md.inversion.nsteps:] = [] + + #optscal + found = 0 + if options.exist('optscal'): + optscal = options.getfieldvalue('optscal') + if not any(optscal < 0): + md.inversion.gradient_scaling = np.tile(optscal[:], (md.inversion.nsteps, 1)) + md.inversion.gradient_scaling[md.inversion.nsteps:] = [] + found = 1 + + if not found: + third = np.ceil(md.inversion.nsteps / 3) + md.inversion.gradient_scaling = [50 * np.ones(3, 1), + 15 * np.ones(third - 3, 1), + 10 * np.ones(third, 1), + np.tile([10, 10, 20, 10], (third, 1))] + md.inversion.gradient_scaling[md.inversion.nsteps:] = [] + + return md Index: /issm/trunk-jpl/src/m/inversions/supportedcontrols.py =================================================================== --- /issm/trunk-jpl/src/m/inversions/supportedcontrols.py (revision 24212) +++ /issm/trunk-jpl/src/m/inversions/supportedcontrols.py (revision 24213) @@ -1,2 +1,2 @@ def supportedcontrols(): - return ['BalancethicknessThickeningRate','FrictionCoefficient','FrictionAs','MaterialsRheologyBbar','DamageDbar','Vx','Vy'] + return ['BalancethicknessThickeningRate', 'FrictionCoefficient', 'FrictionAs', 'MaterialsRheologyBbar', 'DamageDbar', 'Vx', 'Vy'] Index: /issm/trunk-jpl/src/m/inversions/supportedcostfunctions.py =================================================================== --- /issm/trunk-jpl/src/m/inversions/supportedcostfunctions.py (revision 24212) +++ /issm/trunk-jpl/src/m/inversions/supportedcostfunctions.py (revision 24213) @@ -1,2 +1,2 @@ def supportedcostfunctions(): - return [101,102,103,104,105,201,501,502,503,504,505] + return [101, 102, 103, 104, 105, 201, 501, 502, 503, 504, 505] Index: /issm/trunk-jpl/src/m/io/loadmodel.py =================================================================== --- /issm/trunk-jpl/src/m/io/loadmodel.py (revision 24212) +++ /issm/trunk-jpl/src/m/io/loadmodel.py (revision 24213) @@ -12,10 +12,10 @@ def loadmodel(path): """ - LOADMODEL - load a model using built-in load module + LOADMODEL - load a model using built - in load module check that model prototype has not changed. if so, adapt to new model prototype. Usage: - md=loadmodel(path) + md = loadmodel(path) """ @@ -31,5 +31,5 @@ except RuntimeError: raise IOError("loadmodel error message: file '%s' does not exist" % path) - # try: + # try: #recover model on file and name it md struc = loadvars(path) Index: /issm/trunk-jpl/src/m/io/loadvars.py =================================================================== --- /issm/trunk-jpl/src/m/io/loadvars.py (revision 24212) +++ /issm/trunk-jpl/src/m/io/loadvars.py (revision 24213) @@ -25,8 +25,8 @@ Usage: - a=loadvars('shelve.dat','a') - [a,b]=loadvars('shelve.dat',['a','b']) - nvdict=loadvars('shelve.dat',{'a':None,'b':None}) - nvdict=loadvars('shelve.dat') + a = loadvars('shelve.dat', 'a') + [a, b] = loadvars('shelve.dat', ['a', 'b']) + nvdict = loadvars('shelve.dat', {'a':None, 'b':None}) + nvdict = loadvars('shelve.dat') """ @@ -43,16 +43,16 @@ raise TypeError("Missing file name.") - if len(args) >= 2 and isinstance(args[1], str): # (filename,name) + if len(args) >= 2 and isinstance(args[1], str): # (filename, name) for name in args[1:]: nvdict[name] = None - elif len(args) == 2 and isinstance(args[1], list): # (filename,[names]) + elif len(args) == 2 and isinstance(args[1], list): # (filename, [names]) for name in args[1]: nvdict[name] = None - elif len(args) == 2 and isinstance(args[1], dict): # (filename,{names:values}) + elif len(args) == 2 and isinstance(args[1], dict): # (filename, {names:values}) nvdict = args[1] - elif len(args) == 1: # (filename) + elif len(args) == 1: # (filename) pass @@ -62,5 +62,5 @@ if whichdb(filename): print("Loading variables from file {}.".format(filename)) - my_shelf = shelve.open(filename, 'r') # 'r' for read-only + my_shelf = shelve.open(filename, 'r') # 'r' for read - only if nvdict: for name in list(nvdict.keys()): @@ -89,5 +89,5 @@ NCFile = Dataset(filename, mode='r') for mod in dict.keys(classtype): - #print('-Now treating classtype {}'.format(mod)) + #print(' - Now treating classtype {}'.format(mod)) if np.size(classtree[mod]) > 1: curclass = NCFile.groups[classtree[mod][0]].groups[classtree[mod][1]] @@ -97,5 +97,5 @@ steplist = [int(key) for key in curclass.groups] except ValueError: - steplist = [int(findall(r'\d+', key)[0]) for key in keylist] + steplist = [int(findall(r'\d + ', key)[0]) for key in keylist] indexlist = [index * (len(curclass.groups) - 1) / max(1, max(steplist)) for index in steplist] listtype = curclass.groups[keylist[0]].classtype @@ -112,5 +112,5 @@ nvdict['md'].__dict__[mod] = getattr(classtype[mod][1], classtype[mod][0])() Tree = nvdict['md'].__dict__[classtree[mod][0]] - #treating groups that are lists + #treating groups that are lists for i in range(0, max(1, len(curclass.groups))): if len(curclass.groups) > 0: @@ -180,5 +180,5 @@ #dealling with dict if varval.dtype == str: #that is for toolkits wich needs to be ordered - if any(varval[:, 0] == 'toolkit'): #toolkit definition have to be first + if any(varval[:, 0] == 'toolkit'): #toolkit definition have to be first Tree.__dict__[str(var)] = OrderedDict([('toolkit', str(varval[np.where(varval[:, 0] == 'toolkit')[0][0], 1]))]) strings1 = [str(arg[0]) for arg in varval if arg[0] != 'toolkits'] @@ -206,5 +206,5 @@ print('table dimension greater than 3 not implemented yet') for attr in listclass.ncattrs(): - if attr != 'classtype': #classtype is for treatment, don't get it back + if attr != 'classtype': #classtype is for treatment, don't get it back if type(Tree) == list: t = int(indexlist[i]) @@ -220,13 +220,13 @@ Tree.__dict__[str(attr).swapcase()] = False NCFile.close() - if len(args) >= 2 and isinstance(args[1], str): # (value) + if len(args) >= 2 and isinstance(args[1], str): # (value) value = [nvdict[name] for name in args[1:]] return value - elif len(args) == 2 and isinstance(args[1], list): # ([values]) + elif len(args) == 2 and isinstance(args[1], list): # ([values]) value = [nvdict[name] for name in args[1]] return value - elif (len(args) == 2 and isinstance(args[1], dict)) or (len(args) == 1): # ({names:values}) + elif (len(args) == 2 and isinstance(args[1], dict)) or (len(args) == 1): # ({names:values}) return nvdict Index: /issm/trunk-jpl/src/m/io/savevars.py =================================================================== --- /issm/trunk-jpl/src/m/io/savevars.py (revision 24212) +++ /issm/trunk-jpl/src/m/io/savevars.py (revision 24213) @@ -2,61 +2,61 @@ import os.path + def savevars(*args): - """ - SAVEVARS - function to save variables to a file. + """ + SAVEVARS - function to save variables to a file. - This function saves one or more variables to a file. The names of the variables - must be supplied. If more than one variable is specified, it may be done with - lists of names and values or a dictionary of name:value pairs. All the variables - in the workspace may be saved by specifying the globals() dictionary, but this - may include a lot of extraneous data. + This function saves one or more variables to a file. The names of the variables + must be supplied. If more than one variable is specified, it may be done with + lists of names and values or a dictionary of name:value pairs. All the variables + in the workspace may be saved by specifying the globals() dictionary, but this + may include a lot of extraneous data. - Usage: - savevars('shelve.dat','a',a) - savevars('shelve.dat',['a','b'],[a,b]) - savevars('shelve.dat',{'a':a,'b':b}) - savevars('shelve.dat',globals()) + Usage: + savevars('shelve.dat', 'a', a) + savevars('shelve.dat', ['a', 'b'], [a, b]) + savevars('shelve.dat', {'a':a, 'b':b}) + savevars('shelve.dat', globals()) - """ + """ - filename='' - nvdict={} + filename = '' + nvdict = {} - if len(args) >= 1 and isinstance(args[0],str): - filename=args[0] - if not filename: - filename='/tmp/shelve.dat' + if len(args) >= 1 and isinstance(args[0], str): + filename = args[0] + if not filename: + filename = '/tmp/shelve.dat' - else: - raise TypeError("Missing file name.") + else: + raise TypeError("Missing file name.") - if len(args) >= 3 and isinstance(args[1],str): # (filename,name,value) - for i in range(1,len(args),2): - nvdict[args[i]]=args[i+1] + if len(args) >= 3 and isinstance(args[1], str): # (filename, name, value) + for i in range(1, len(args), 2): + nvdict[args[i]] = args[i + 1] - elif len(args) == 3 and isinstance(args[1],list) and isinstance(args[2],list): # (filename,[names],[values]) - for name,value in zip(args[1],args[2]): - nvdict[name]=value + elif len(args) == 3 and isinstance(args[1], list) and isinstance(args[2], list): # (filename, [names], [values]) + for name, value in zip(args[1], args[2]): + nvdict[name] = value - elif len(args) == 2 and isinstance(args[1],dict): # (filename,{names:values}) - nvdict=args[1] + elif len(args) == 2 and isinstance(args[1], dict): # (filename, {names:values}) + nvdict = args[1] - else: - raise TypeError("Unrecognized input arguments.") + else: + raise TypeError("Unrecognized input arguments.") - if os.path.exists(filename): - print(("Shelving variables to existing file '%s'." % filename)) - else: - print(("Shelving variables to new file '%s'." % filename)) + if os.path.exists(filename): + print(("Shelving variables to existing file '%s'." % filename)) + else: + print(("Shelving variables to new file '%s'." % filename)) - my_shelf = shelve.open(filename,'c') # 'c' for create if not exist, else 'n' for new + my_shelf = shelve.open(filename, 'c') # 'c' for create if not exist, else 'n' for new - for name,value in list(nvdict.items()): - try: - my_shelf[name] = value - print(("Variable '%s' shelved." % name)) - except TypeError: - print(("Variable '%s' not shelved." % name)) + for name, value in list(nvdict.items()): + try: + my_shelf[name] = value + print(("Variable '%s' shelved." % name)) + except TypeError: + print(("Variable '%s' not shelved." % name)) - my_shelf.close() - + my_shelf.close() Index: /issm/trunk-jpl/src/m/materials/TMeltingPoint.py =================================================================== --- /issm/trunk-jpl/src/m/materials/TMeltingPoint.py (revision 24212) +++ /issm/trunk-jpl/src/m/materials/TMeltingPoint.py (revision 24213) @@ -1,21 +1,20 @@ -import numpy as np -def TMeltingPoint(reftemp,pressure): - ''' - Calculate the pressure melting point of ice at a given pressure +def TMeltingPoint(reftemp, pressure): + ''' + Calculate the pressure melting point of ice at a given pressure - reftemp is the melting temperature in K at atmospheric pressure (initialized in md.materials.meltingpoint) + reftemp is the melting temperature in K at atmospheric pressure (initialized in md.materials.meltingpoint) - pressure is in Pa + pressure is in Pa - Usage: - Tm=TMeltingPoint(md.materials.meltingpoint,pressure) - ''' + Usage: + Tm = TMeltingPoint(md.materials.meltingpoint, pressure) + ''' - #variables - beta=7.9e-8 + #variables + beta = 7.9e-8 - #ensure ref is same dimension as pressure - ref=reftemp*np.ones_like(pressure) + #ensure ref is same dimension as pressure + ref = reftemp - beta * pressure - return reftemp-beta*pressure + return ref Index: /issm/trunk-jpl/src/m/materials/cuffey.py =================================================================== --- /issm/trunk-jpl/src/m/materials/cuffey.py (revision 24212) +++ /issm/trunk-jpl/src/m/materials/cuffey.py (revision 24213) @@ -1,66 +1,66 @@ import numpy as np + def cuffey(temperature): - """ - CUFFEY - calculates ice rigidity as a function of temperature + """ + CUFFEY - calculates ice rigidity as a function of temperature - rigidity (in s^(1/3)Pa) is the flow law parameter in the flow law sigma=B*e(1/3) - (Cuffey and Paterson, p75). - temperature is in Kelvin degrees + rigidity (in s^(1 / 3)Pa) is the flow law parameter in the flow law sigma = B * e(1 / 3) + (Cuffey and Paterson, p75). + temperature is in Kelvin degrees - Usage: - rigidity=cuffey(temperature) - """ + Usage: + rigidity = cuffey(temperature) + """ - if np.any(temperature<0.): - raise RuntimeError("input temperature should be in Kelvin (positive)") + if np.any(temperature < 0.): + raise RuntimeError("input temperature should be in Kelvin (positive)") - if np.ndim(temperature)==2: - #T = temperature.reshape(-1,)-273.15 - T = temperature.flatten()-273.15 - elif isinstance(temperature,float) or isinstance(temperature,int): - T = np.array([temperature])-273.15 - else: - T = temperature-273.15 + if np.ndim(temperature) == 2: + #T = temperature.reshape(- 1, ) - 273.15 + T = temperature.flatten() - 273.15 + elif isinstance(temperature, float) or isinstance(temperature, int): + T = np.array([temperature]) - 273.15 + else: + T = temperature - 273.15 + rigidity = np.zeros_like(T) + pos = np.nonzero(T <= - 45) + if len(pos): + rigidity[pos] = 10**8 * (- 0.000396645116301 * (T[pos] + 50)**3 + 0.013345579471334 * (T[pos] + 50)**2 - 0.356868703259105 * (T[pos] + 50) + 7.272363035371383) + pos = np.nonzero(np.logical_and(- 45 <= T, T < - 40)) + if len(pos): + rigidity[pos] = 10**8 * (- 0.000396645116301 * (T[pos] + 45)**3 + 0.007395902726819 * (T[pos] + 45)**2 - 0.253161292268336 * (T[pos] + 45) + 5.772078366321591) + pos = np.nonzero(np.logical_and(- 40 <= T, T < - 35)) + if len(pos): + rigidity[pos] = 10**8 * (0.000408322072669 * (T[pos] + 40)**3 + 0.001446225982305 * (T[pos] + 40)**2 - 0.208950648722716 * (T[pos] + 40) + 4.641588833612773) + pos = np.nonzero(np.logical_and(- 35 <= T, T < - 30)) + if len(pos): + rigidity[pos] = 10**8 * (- 0.000423888728124 * (T[pos] + 35)**3 + 0.007571057072334 * (T[pos] + 35)**2 - 0.163864233449525 * (T[pos] + 35) + 3.684031498640382) + pos = np.nonzero(np.logical_and(- 30 <= T, T < - 25)) + if len(pos): + rigidity[pos] = 10**8 * (0.000147154327025 * (T[pos] + 30)**3 + 0.001212726150476 * (T[pos] + 30)**2 - 0.119945317335478 * (T[pos] + 30) + 3.001000667185614) + pos = np.nonzero(np.logical_and(- 25 <= T, T < - 20)) + if len(pos): + rigidity[pos] = 10**8 * (- 0.000193435838672 * (T[pos] + 25)**3 + 0.003420041055847 * (T[pos] + 25)**2 - 0.096781481303861 * (T[pos] + 25) + 2.449986525148220) + pos = np.nonzero(np.logical_and(- 20 <= T, T < - 15)) + if len(pos): + rigidity[pos] = 10**8 * (0.000219771255067 * (T[pos] + 20)**3 + 0.000518503475772 * (T[pos] + 20)**2 - 0.077088758645767 * (T[pos] + 20) + 2.027400665191131) + pos = np.nonzero(np.logical_and(- 15 <= T, T < - 10)) + if len(pos): + rigidity[pos] = 10**8 * (- 0.000653438900191 * (T[pos] + 15)**3 + 0.003815072301777 * (T[pos] + 15)**2 - 0.055420879758021 * (T[pos] + 15) + 1.682390865739973) + pos = np.nonzero(np.logical_and(- 10 <= T, T < - 5)) + if len(pos): + rigidity[pos] = 10**8 * (0.000692439419762 * (T[pos] + 10)**3 - 0.005986511201093 * (T[pos] + 10)**2 - 0.066278074254598 * (T[pos] + 10) + 1.418983411970382) + pos = np.nonzero(np.logical_and(- 5 <= T, T < - 2)) + if len(pos): + rigidity[pos] = 10**8 * (- 0.000132282004110 * (T[pos] + 5)**3 + 0.004400080095332 * (T[pos] + 5)**2 - 0.074210229783403 * (T[pos] + 5) + 1.024485188140279) + pos = np.nonzero(- 2 <= T) + if len(pos): + rigidity[pos] = 10**8 * (- 0.000132282004110 * (T[pos] + 2)**3 + 0.003209542058346 * (T[pos] + 2)**2 - 0.051381363322371 * (T[pos] + 2) + 0.837883605537096) - rigidity=np.zeros_like(T) - pos=np.nonzero(T<=-45) - if len(pos): - rigidity[pos]=10**8*(-0.000396645116301*(T[pos]+50)**3+ 0.013345579471334*(T[pos]+50)**2 -0.356868703259105*(T[pos]+50)+7.272363035371383) - pos=np.nonzero(np.logical_and(-45<=T,T<-40)) - if len(pos): - rigidity[pos]=10**8*(-0.000396645116301*(T[pos]+45)**3+ 0.007395902726819*(T[pos]+45)**2 -0.253161292268336*(T[pos]+45)+5.772078366321591) - pos=np.nonzero(np.logical_and(-40<=T,T<-35)) - if len(pos): - rigidity[pos]=10**8*(0.000408322072669*(T[pos]+40)**3+ 0.001446225982305*(T[pos]+40)**2 -0.208950648722716*(T[pos]+40)+4.641588833612773) - pos=np.nonzero(np.logical_and(-35<=T,T<-30)) - if len(pos): - rigidity[pos]=10**8*(-0.000423888728124*(T[pos]+35)**3+ 0.007571057072334*(T[pos]+35)**2 -0.163864233449525*(T[pos]+35)+3.684031498640382) - pos=np.nonzero(np.logical_and(-30<=T,T<-25)) - if len(pos): - rigidity[pos]=10**8*(0.000147154327025*(T[pos]+30)**3+ 0.001212726150476*(T[pos]+30)**2 -0.119945317335478*(T[pos]+30)+3.001000667185614) - pos=np.nonzero(np.logical_and(-25<=T,T<-20)) - if len(pos): - rigidity[pos]=10**8*(-0.000193435838672*(T[pos]+25)**3+ 0.003420041055847*(T[pos]+25)**2 -0.096781481303861*(T[pos]+25)+2.449986525148220) - pos=np.nonzero(np.logical_and(-20<=T,T<-15)) - if len(pos): - rigidity[pos]=10**8*(0.000219771255067*(T[pos]+20)**3+ 0.000518503475772*(T[pos]+20)**2 -0.077088758645767*(T[pos]+20)+2.027400665191131) - pos=np.nonzero(np.logical_and(-15<=T,T<-10)) - if len(pos): - rigidity[pos]=10**8*(-0.000653438900191*(T[pos]+15)**3+ 0.003815072301777*(T[pos]+15)**2 -0.055420879758021*(T[pos]+15)+1.682390865739973) - pos=np.nonzero(np.logical_and(-10<=T,T<-5)) - if len(pos): - rigidity[pos]=10**8*(0.000692439419762*(T[pos]+10)**3 -0.005986511201093 *(T[pos]+10)**2 -0.066278074254598*(T[pos]+10)+1.418983411970382) - pos=np.nonzero(np.logical_and(-5<=T,T<-2)) - if len(pos): - rigidity[pos]=10**8*(-0.000132282004110*(T[pos]+5)**3 +0.004400080095332*(T[pos]+5)**2 -0.074210229783403*(T[pos]+5)+ 1.024485188140279) - pos=np.nonzero(-2<=T) - if len(pos): - rigidity[pos]=10**8*(-0.000132282004110*(T[pos]+2)**3 +0.003209542058346*(T[pos]+2)**2 -0.051381363322371*(T[pos]+2)+ 0.837883605537096) + #Now make sure that rigidity is positive + pos = np.nonzero(rigidity < 0) + rigidity[pos] = 1**6 - #Now make sure that rigidity is positive - pos=np.nonzero(rigidity<0) - rigidity[pos]=1**6 - - return rigidity + return rigidity Index: /issm/trunk-jpl/src/m/materials/cuffeytemperate.py =================================================================== --- /issm/trunk-jpl/src/m/materials/cuffeytemperate.py (revision 24212) +++ /issm/trunk-jpl/src/m/materials/cuffeytemperate.py (revision 24213) @@ -2,28 +2,27 @@ import cuffey -def cuffeytemperate(temperature, waterfraction, stressexp) - """ - CUFFEYTEMPERATE - calculates ice rigidity as a function of temperature and waterfraction +def cuffeytemperate(temperature, waterfraction, stressexp): + ''' + CUFFEYTEMPERATE - calculates ice rigidity as a function of temperature and waterfraction - rigidity (in s^(1/3)Pa) is the flow law parameter in the flow law sigma=B*e(1/3) - (Cuffey and Paterson, p75). + rigidity (in s^(1 / 3)Pa) is the flow law parameter in the flow law sigma = B * e(1 / 3) + (Cuffey and Paterson, p75). temperature is in Kelvin degrees Usage: - rigidity=cuffeytemperate(temperature, waterfraction, stressexp) - """ + rigidity = cuffeytemperate(temperature, waterfraction, stressexp) + ''' - if np.any(temperature<0.): - raise RuntimeError("input temperature should be in Kelvin (positive)") + if np.any(temperature < 0.): + raise RuntimeError("input temperature should be in Kelvin (positive)") - if (np.any(temperature.shape~=waterfraction.shape)), - error('input temperature and waterfraction should have same size!'); - end - if np.any(waterfraction<0 | waterfraction>1) - error('input waterfraction should be between 0 and 1'); - end + if (np.any(temperature.shape in waterfraction.shape)): + error('input temperature and waterfraction should have same size!') - rigidity=np.multiply(cuffey(temperature), (1*np.ones(waterfraction.shape)+181.25*np.maximum(np.zeros(waterfraction.shape), np.minimum(0.01*np.ones(waterfraction.shape), waterfraction)))**(-1/stressexp)); + if np.any(waterfraction < 0 | waterfraction > 1): + error('input waterfraction should be between 0 and 1') - return rigidity + rigidity = np.multiply(cuffey(temperature), (1 * np.ones(waterfraction.shape) + 181.25 * np.maximum(np.zeros(waterfraction.shape), np.minimum(0.01 * np.ones(waterfraction.shape), waterfraction)))**(- 1 / stressexp)) + + return rigidity Index: /issm/trunk-jpl/src/m/materials/nye.py =================================================================== --- /issm/trunk-jpl/src/m/materials/nye.py (revision 24212) +++ /issm/trunk-jpl/src/m/materials/nye.py (revision 24213) @@ -1,51 +1,52 @@ import numpy as np + def nye(temperature, ice_type): - """ + """ NYE - figure out the rigidity of ice (either CO2 or H2O) for a given temperature - rigidity (in s^(1/n)Pa) is the flow law parameter in the flow law sigma=B*e(1/n) (Nye, p2000). - temperature is in Kelvin degrees + rigidity (in s^(1 / n)Pa) is the flow law parameter in the flow law sigma = B * e(1 / n) (Nye, p2000). + temperature is in Kelvin degrees Usage: - rigidity=nye(temperature,ice_type) % ice_type = 1: CO2 ice // ice_type = 2: H2O ice - """ + rigidity = nye(temperature, ice_type) % ice_type = 1: CO2 ice / / ice_type = 2: H2O ice + """ - # Declaring temperature and rigidity arrays - if np.ndim(temperature)==2: - T=temperature.flatten() - elif isinstance(temperature,float) or isinstance(temperature,int): - T=np.array([temperature]) - else: - T=temperature - rigidity=np.zeros_like(T) + # Declaring temperature and rigidity arrays + if np.ndim(temperature) == 2: + T = temperature.flatten() + elif isinstance(temperature, float) or isinstance(temperature, int): + T = np.array([temperature]) + else: + T = temperature + rigidity = np.zeros_like(T) - # Beyond-melting-point cases - if (ice_type==1): - for i in range(len(T)): - if (200=220).any()): - warnings.warn('CO2 ICE - GUARANTEED MELTING. Some temperature values are beyond 220K.') - elif (ice_type==2) and ((T>273.15).any()): - warnings.warn('H2O ICE - GUARANTEED MELTING. Some temperature values are beyond 273.15K.') + # Beyond - melting - point cases + if (ice_type == 1): + for i in range(len(T)): + if (200 < T[i] < 220): + warnings.warn('CO2 ICE - POSSIBLE MELTING. Some temperature values are between 200K and 220K.') + break + if ((T >= 220).any()): + warnings.warn('CO2 ICE - GUARANTEED MELTING. Some temperature values are beyond 220K.') + elif (ice_type == 2) and ((T > 273.15).any()): + warnings.warn('H2O ICE - GUARANTEED MELTING. Some temperature values are beyond 273.15K.') - Rg = 8.3144598 # J mol^-1 K^-1 + Rg = 8.3144598 # J mol^ - 1 K^ - 1 - if ice_type == 1: # CO2 ice - A_const = 10**(10.8) # s^-1 MPa - Q = 63000. # J mol^-1 - n = 7. # Glen's exponent - elif ice_type == 2: # H2O ice - A_const = 9*10**4 # s^-1 MPa - Q = 60000. # J mol^-1 - n = 3. # Glen's exponent - else: - raise RuntimeError('Ice type not supported') + if ice_type == 1: # CO2 ice + A_const = 10**(10.8) # s^ - 1 MPa + Q = 63000. # J mol^ - 1 + n = 7. # Glen's exponent + elif ice_type == 2: # H2O ice + A_const = 9 * 10**4 # s^ - 1 MPa + Q = 60000. # J mol^ - 1 + n = 3. # Glen's exponent + else: + raise RuntimeError('Ice type not supported') - # Arrhenius Law - A=A_const*np.exp(-1*Q/(T*Rg)) # s^-1 MPa - rigidity=A**(-1/n)*10**6 # s^(1/n) Pa + # Arrhenius Law + A = A_const * np.exp(- 1 * Q / (T * Rg)) # s^ - 1 MPa + rigidity = A**(- 1 / n) * 10**6 # s^(1 / n) Pa - # Return output - return rigidity + # Return output + return rigidity Index: /issm/trunk-jpl/src/m/materials/paterson.py =================================================================== --- /issm/trunk-jpl/src/m/materials/paterson.py (revision 24212) +++ /issm/trunk-jpl/src/m/materials/paterson.py (revision 24213) @@ -1,79 +1,79 @@ import numpy as np + def paterson(temperature): - """ - PATERSON - figure out the rigidity of ice for a given temperature + """ + PATERSON - figure out the rigidity of ice for a given temperature - rigidity (in s^(1/3)Pa) is the flow law paramter in the flow law sigma=B*e(1/3) (Paterson, p97). - temperature is in Kelvin degrees + rigidity (in s^(1 / 3)Pa) is the flow law paramter in the flow law sigma = B * e(1 / 3) (Paterson, p97). + temperature is in Kelvin degrees - Usage: - rigidity=paterson(temperature) - """ - - if np.any(temperature<0.): - raise RuntimeError("input temperature should be in Kelvin (positive)") + Usage: + rigidity = paterson(temperature) + """ - if np.ndim(temperature)==2: - #T = temperature.reshape(-1,)-273.15 - T = temperature.flatten()-273.15 - elif isinstance(temperature,float) or isinstance(temperature,int): - T = np.array([temperature])-273.15 - else: - T = temperature-273.15 + if np.any(temperature < 0.): + raise RuntimeError("input temperature should be in Kelvin (positive)") - #The routine below is equivalent to: + if np.ndim(temperature) == 2: + #T = temperature.reshape(- 1, ) - 273.15 + T = temperature.flatten() - 273.15 + elif isinstance(temperature, float) or isinstance(temperature, int): + T = np.array([temperature]) - 273.15 + else: + T = temperature - 273.15 - # n=3; T=temperature-273; - # %From paterson, - # Temp=[0;-2;-5;-10;-15;-20;-25;-30;-35;-40;-45;-50]; - # A=[6.8*10^-15;2.4*10^-15;1.6*10^-15;4.9*10^-16;2.9*10^-16;1.7*10^-16;9.4* - # 10^-17;5.1*10^-17;2.7*10^-17;1.4*10^-17;7.3*10^-18;3.6*10^-18];;%s-1(kPa-3) - # %Convert into rigidity B - # B=A.^(-1/n)*10^3; %s^(1/3)Pa - # %Now, do a cubic fit between Temp and B: - # fittedmodel=fit(Temp,B,'cubicspline'); - # rigidity=fittedmodel(temperature); + #The routine below is equivalent to: - rigidity=np.zeros_like(T) - pos1=np.nonzero(T<=-45)[0] - if len(pos1): - rigidity[pos1]=10**8*(-0.000292866376675*(T[pos1]+50)**3+ 0.011672640664130*(T[pos1]+50)**2 -0.325004442485481*(T[pos1]+50)+ 6.524779401948101) - pos2=np.nonzero(np.logical_and(-45<=T,T<-40))[0] - if len(pos2): - rigidity[pos2]=10**8*(-0.000292866376675*(T[pos2]+45)**3+ 0.007279645014004*(T[pos2]+45)**2 -0.230243014094813*(T[pos2]+45)+ 5.154964909039554) - pos3=np.nonzero(np.logical_and(-40<=T,T<-35))[0] - if len(pos3): - rigidity[pos3]=10**8*(0.000072737147457*(T[pos3]+40)**3+ 0.002886649363879*(T[pos3]+40)**2 -0.179411542205399*(T[pos3]+40)+ 4.149132666831214) - pos4=np.nonzero(np.logical_and(-35<=T,T<-30))[0] - if len(pos4): - rigidity[pos4]=10**8*(-0.000086144770023*(T[pos4]+35)**3+ 0.003977706575736*(T[pos4]+35)**2 -0.145089762507325*(T[pos4]+35)+ 3.333333333333331) - pos5=np.nonzero(np.logical_and(-30<=T,T<-25))[0] - if len(pos5): - rigidity[pos5]=10**8*(-0.000043984685769*(T[pos5]+30)**3+ 0.002685535025386*(T[pos5]+30)**2 -0.111773554501713*(T[pos5]+30)+ 2.696559088937191) - pos6=np.nonzero(np.logical_and(-25<=T,T<-20))[0] - if len(pos6): - rigidity[pos6]=10**8*(-0.000029799523463*(T[pos6]+25)**3+ 0.002025764738854*(T[pos6]+25)**2 -0.088217055680511*(T[pos6]+25)+ 2.199331606342181) - pos7=np.nonzero(np.logical_and(-20<=T,T<-15))[0] - if len(pos7): - rigidity[pos7]=10**8*(0.000136920904777*(T[pos7]+20)**3+ 0.001578771886910*(T[pos7]+20)**2 -0.070194372551690*(T[pos7]+20)+ 1.805165505978111) - pos8=np.nonzero(np.logical_and(-15<=T,T<-10))[0] - if len(pos8): - rigidity[pos8]=10**8*(-0.000899763781026*(T[pos8]+15)**3+ 0.003632585458564*(T[pos8]+15)**2 -0.044137585824322*(T[pos8]+15)+ 1.510778053489523) - pos9=np.nonzero(np.logical_and(-10<=T,T<-5))[0] - if len(pos9): - rigidity[pos9]=10**8*(0.001676964325070*(T[pos9]+10)**3- 0.009863871256831*(T[pos9]+10)**2 -0.075294014815659*(T[pos9]+10)+ 1.268434288203714) - pos10=np.nonzero(np.logical_and(-5<=T,T<-2))[0] - if len(pos10): - rigidity[pos10]=10**8*(-0.003748937622487*(T[pos10]+5)**3+0.015290593619213*(T[pos10]+5)**2 -0.048160403003748*(T[pos10]+5)+ 0.854987973338348) - pos11=np.nonzero(-2<=T)[0] - if len(pos11): - rigidity[pos11]=10**8*(-0.003748937622488*(T[pos11]+2)**3-0.018449844983174*(T[pos11]+2)**2 -0.057638157095631*(T[pos11]+2)+ 0.746900791092860) + # n = 3; T = temperature-273 + # %From paterson, + # Temp = [0; - 2; - 5; - 10; - 15; - 20; - 25; - 30; - 35; - 40; - 45; - 50] + # A = [6.8 * 10^ - 15;2.4 * 10^ - 15;1.6 * 10^ - 15;4.9 * 10^ - 16;2.9 * 10^ - 16;1.7 * 10^ - 16;9.4 * + # 10^ - 17;5.1 * 10^ - 17;2.7 * 10^ - 17;1.4 * 10^ - 17;7.3 * 10^ - 18;3.6 * 10^ - 18];;%s - 1(kPa - 3) + # %Convert into rigidity B + # B = A.^(- 1 / n) * 10^3; %s^(1 / 3)Pa + # %Now, do a cubic fit between Temp and B: + # fittedmodel = fit(Temp, B, 'cubicspline') + # rigidity = fittedmodel(temperature) - #Now make sure that rigidity is positive - pos=np.nonzero(rigidity<0)[0] - if len(pos): - rigidity[pos]=1.e6 + rigidity = np.zeros_like(T) + pos1 = np.nonzero(T <= - 45)[0] + if len(pos1): + rigidity[pos1] = 10**8 * (- 0.000292866376675 * (T[pos1] + 50)**3 + 0.011672640664130 * (T[pos1] + 50)**2 - 0.325004442485481 * (T[pos1] + 50) + 6.524779401948101) + pos2 = np.nonzero(np.logical_and(- 45 <= T, T < - 40))[0] + if len(pos2): + rigidity[pos2] = 10**8 * (- 0.000292866376675 * (T[pos2] + 45)**3 + 0.007279645014004 * (T[pos2] + 45)**2 - 0.230243014094813 * (T[pos2] + 45) + 5.154964909039554) + pos3 = np.nonzero(np.logical_and(- 40 <= T, T < - 35))[0] + if len(pos3): + rigidity[pos3] = 10**8 * (0.000072737147457 * (T[pos3] + 40)**3 + 0.002886649363879 * (T[pos3] + 40)**2 - 0.179411542205399 * (T[pos3] + 40) + 4.149132666831214) + pos4 = np.nonzero(np.logical_and(- 35 <= T, T < - 30))[0] + if len(pos4): + rigidity[pos4] = 10**8 * (- 0.000086144770023 * (T[pos4] + 35)**3 + 0.003977706575736 * (T[pos4] + 35)**2 - 0.145089762507325 * (T[pos4] + 35) + 3.333333333333331) + pos5 = np.nonzero(np.logical_and(- 30 <= T, T < - 25))[0] + if len(pos5): + rigidity[pos5] = 10**8 * (- 0.000043984685769 * (T[pos5] + 30)**3 + 0.002685535025386 * (T[pos5] + 30)**2 - 0.111773554501713 * (T[pos5] + 30) + 2.696559088937191) + pos6 = np.nonzero(np.logical_and(- 25 <= T, T < - 20))[0] + if len(pos6): + rigidity[pos6] = 10**8 * (- 0.000029799523463 * (T[pos6] + 25)**3 + 0.002025764738854 * (T[pos6] + 25)**2 - 0.088217055680511 * (T[pos6] + 25) + 2.199331606342181) + pos7 = np.nonzero(np.logical_and(- 20 <= T, T < - 15))[0] + if len(pos7): + rigidity[pos7] = 10**8 * (0.000136920904777 * (T[pos7] + 20)**3 + 0.001578771886910 * (T[pos7] + 20)**2 - 0.070194372551690 * (T[pos7] + 20) + 1.805165505978111) + pos8 = np.nonzero(np.logical_and(- 15 <= T, T < - 10))[0] + if len(pos8): + rigidity[pos8] = 10**8 * (- 0.000899763781026 * (T[pos8] + 15)**3 + 0.003632585458564 * (T[pos8] + 15)**2 - 0.044137585824322 * (T[pos8] + 15) + 1.510778053489523) + pos9 = np.nonzero(np.logical_and(- 10 <= T, T < - 5))[0] + if len(pos9): + rigidity[pos9] = 10**8 * (0.001676964325070 * (T[pos9] + 10)**3 - 0.009863871256831 * (T[pos9] + 10)**2 - 0.075294014815659 * (T[pos9] + 10) + 1.268434288203714) + pos10 = np.nonzero(np.logical_and(- 5 <= T, T < - 2))[0] + if len(pos10): + rigidity[pos10] = 10**8 * (- 0.003748937622487 * (T[pos10] + 5)**3 + 0.015290593619213 * (T[pos10] + 5)**2 - 0.048160403003748 * (T[pos10] + 5) + 0.854987973338348) + pos11 = np.nonzero(- 2 <= T)[0] + if len(pos11): + rigidity[pos11] = 10**8 * (- 0.003748937622488 * (T[pos11] + 2)**3 - 0.018449844983174 * (T[pos11] + 2)**2 - 0.057638157095631 * (T[pos11] + 2) + 0.746900791092860) - return rigidity + #Now make sure that rigidity is positive + pos = np.nonzero(rigidity < 0)[0] + if len(pos): + rigidity[pos] = 1.e6 + return rigidity Index: /issm/trunk-jpl/src/m/mech/analyticaldamage.py =================================================================== --- /issm/trunk-jpl/src/m/mech/analyticaldamage.py (revision 24212) +++ /issm/trunk-jpl/src/m/mech/analyticaldamage.py (revision 24213) @@ -1,106 +1,111 @@ -import numpy as np +import numpy as np from averaging import averaging #from plotmodel import plotmodel from thomasparams import thomasparams -def analyticaldamage(md,**kwargs): - ''' - ANALYTICALDAMAGE - compute damage for an ice shelf - - This routine computes damage as a function of water/ice - material properties, ice thickness, strain rate, and ice - rigidity. The model must contain computed strain rates, - either from observed or modeled ice velocities. - - Available options: - -eq : analytical equation to use in the calculation. Must be one of: - 'Weertman1D' for a confined ice shelf free to flow in one direction - 'Weertman2D' for an unconfined ice shelf free to spread in any direction - 'Thomas' for a 2D ice shelf, taking into account full strain rate tensor (default) - -smoothing : the amount of smoothing to be applied to the strain rate data. - Type 'help averaging' for more information on its usage. - -coordsys : coordinate system for calculating the strain rate - components. Must be one of: - -sigmab : a compressive backstress term to be subtracted from the driving stress - in the damage calculation - - Return values: - 'damage' which is truncated in the range [0,1-1e-9] - - 'B' is the rigidity, which is equal to md.materials.rheology_B in areas outside - those defined by 'mask.' Within areas defined by 'mask,' where negative damage - is inferred, 'B' is updated to make damage equal to zero. - - 'backstress' is the inferred backstress necessary to balance the analytical solution - (keeping damage within its appropriate limits, e.g. D in [0,1]). - - Usage: - damage,B,backstress=analyticaldamage(md,kwargs) - - Example: - damage,B,backstress=analyticaldamage(md,eq='Weertman2D',smoothing=2,sigmab=10e3) - ''' - #unpack kwargs - eq=kwargs.pop('eq','Thomas') - if 'eq' in kwargs: del kwargs['eq'] - smoothing=kwargs.pop('smoothing',0) - if 'smoothing' in kwargs: del kwargs['smoothing'] - coordsys=kwargs.pop('coordsys','longitudinal') - if 'coordsys' in kwargs: del kwargs['coordsys'] - sigmab=kwargs.pop('sigmab',0) - if 'sigmab' in kwargs: del kwargs['sigmab'] - assert len(kwargs)==0, 'error, unexpected or misspelled kwargs' +def analyticaldamage(md, **kwargs): + ''' + ANALYTICALDAMAGE - compute damage for an ice shelf - if isinstance(sigmab,(int,float)): - sigmab=sigmab*np.ones((md.mesh.numberofvertices,)) + This routine computes damage as a function of water / ice + material properties, ice thickness, strain rate, and ice + rigidity. The model must contain computed strain rates, + either from observed or modeled ice velocities. - # check inputs - if 'strainrate' not in md.results.__dict__: - raise Exception('md.results.strainrate not present. Calculate using md=mechanicalproperties(md,vx,vy)') - if not '2d' in md.mesh.__doc__: - raise Exception('only 2d (planview) model supported currently') - if np.any(md.flowequation.element_equation!=2): - print('Warning: the model has some non SSA elements. These will be treated like SSA elements') + Available options: + - eq : analytical equation to use in the calculation. Must be one of: + 'Weertman1D' for a confined ice shelf free to flow in one direction + 'Weertman2D' for an unconfined ice shelf free to spread in any direction + 'Thomas' for a 2D ice shelf, taking into account full strain rate tensor (default) + - smoothing : the amount of smoothing to be applied to the strain rate data. + Type 'help averaging' for more information on its usage. + - coordsys : coordinate system for calculating the strain rate + components. Must be one of: + - sigmab : a compressive backstress term to be subtracted from the driving stress + in the damage calculation - a,b,theta,ex=thomasparams(md,eq=eq,smoothing=smoothing,coordsys=coordsys) - - # spreading stress - rhoi=md.materials.rho_ice - rhow=md.materials.rho_water - C=0.5*rhoi*md.constants.g*(1.-rhoi/rhow) - T=C*md.geometry.thickness - - # rheology - B=md.materials.rheology_B - n=averaging(md,md.materials.rheology_n,0) - - D=1.-(1.+a+a**2+b**2)**((n-1.)/(2.*n))/np.abs(ex)**(1./n)*(T-sigmab)/B/(2.+a)/np.sign(ex) - - # D>1 where (2+a).*sign(ex)<0, compressive regions where high backstress needed - pos=np.nonzero(D>1) - D[pos]=0 - - backstress=np.zeros((md.mesh.numberofvertices,)) + Return values: + 'damage' which is truncated in the range [0, 1 - 1e-9] - # backstress to bring D down to one - backstress[pos]=T[pos]-(1.-D[pos])*B[pos]*np.sign(ex[pos])*(2.+a[pos])*np.abs(ex[pos])**(1./n[pos])/(1.+a[pos]+a[pos]**2)**((n[pos]-1.)/2./n[pos]) - - pos=np.nonzero(D<0) - #mask=ismember(1:md.mesh.numberofvertices,pos); - D[pos]=0 - - # backstress to bring negative damage to zero - backstress[pos]=T[pos]-(1.-D[pos])*B[pos]*np.sign(ex[pos])*(2.+a[pos])*np.abs(ex[pos])**(1./n[pos])/(1.+a[pos]+a[pos]**2)**((n[pos]-1.)/2./n[pos]) - - pos=np.nonzero(backstress<0) - backstress[pos]=0 - - # rigidity from Thomas relation for D=0 and backstress=0 - B=np.sign(ex)/(2.+a)*(1.+a+a**2)**((n-1.)/2./n)*T/(np.abs(ex)**(1./n)) - pos=np.nonzero(B<0) - B[pos]=md.materials.rheology_B[pos] - - damage=D - - return damage, B, backstress + 'B' is the rigidity, which is equal to md.materials.rheology_B in areas outside + those defined by 'mask.' Within areas defined by 'mask, ' where negative damage + is inferred, 'B' is updated to make damage equal to zero. + + 'backstress' is the inferred backstress necessary to balance the analytical solution + (keeping damage within its appropriate limits, e.g. D in [0, 1]). + + Usage: + damage, B, backstress = analyticaldamage(md, kwargs) + + Example: + damage, B, backstress = analyticaldamage(md, eq = 'Weertman2D', smoothing = 2, sigmab = 1.0e3) + ''' + + #unpack kwargs + eq = kwargs.pop('eq', 'Thomas') + if 'eq' in kwargs: + del kwargs['eq'] + smoothing = kwargs.pop('smoothing', 0) + if 'smoothing' in kwargs: + del kwargs['smoothing'] + coordsys = kwargs.pop('coordsys', 'longitudinal') + if 'coordsys' in kwargs: + del kwargs['coordsys'] + sigmab = kwargs.pop('sigmab', 0) + if 'sigmab' in kwargs: + del kwargs['sigmab'] + assert len(kwargs) == 0, 'error, unexpected or misspelled kwargs' + + if isinstance(sigmab, (int, float)): + sigmab = sigmab * np.ones((md.mesh.numberofvertices, )) + + # check inputs + if 'strainrate' not in md.results.__dict__: + raise Exception('md.results.strainrate not present. Calculate using md = mechanicalproperties(md, vx, vy)') + if '2d' not in md.mesh.__doc__: + raise Exception('only 2d (planview) model supported currently') + if np.any(md.flowequation.element_equation != 2): + print('Warning: the model has some non SSA elements. These will be treated like SSA elements') + + a, b, theta, ex = thomasparams(md, eq=eq, smoothing=smoothing, coordsys=coordsys) + + # spreading stress + rhoi = md.materials.rho_ice + rhow = md.materials.rho_water + C = 0.5 * rhoi * md.constants.g * (1. - rhoi / rhow) + T = C * md.geometry.thickness + + # rheology + B = md.materials.rheology_B + n = averaging(md, md.materials.rheology_n, 0) + + D = 1. - (1. + a + a**2 + b**2)**((n - 1.) / (2. * n)) / np.abs(ex)**(1. / n) * (T - sigmab) / B / (2. + a) / np.sign(ex) + + # D > 1 where (2 + a). * sign(ex) < 0, compressive regions where high backstress needed + pos = np.nonzero(D > 1) + D[pos] = 0 + + backstress = np.zeros((md.mesh.numberofvertices, )) + + # backstress to bring D down to one + backstress[pos] = T[pos] - (1. - D[pos]) * B[pos] * np.sign(ex[pos]) * (2. + a[pos]) * np.abs(ex[pos])**(1. / n[pos]) / (1. + a[pos] + a[pos]**2)**((n[pos] - 1.) / 2. / n[pos]) + + pos = np.nonzero(D < 0) + #mask = ismember(1:md.mesh.numberofvertices, pos) + D[pos] = 0 + + # backstress to bring negative damage to zero + backstress[pos] = T[pos] - (1. - D[pos]) * B[pos] * np.sign(ex[pos]) * (2. + a[pos]) * np.abs(ex[pos])**(1. / n[pos]) / (1. + a[pos] + a[pos]**2)**((n[pos] - 1.) / 2. / n[pos]) + + pos = np.nonzero(backstress < 0) + backstress[pos] = 0 + + # rigidity from Thomas relation for D = 0 and backstress = 0 + B = np.sign(ex) / (2. + a) * (1. + a + a**2)**((n - 1.) / 2. / n) * T / (np.abs(ex)**(1. / n)) + pos = np.nonzero(B < 0) + B[pos] = md.materials.rheology_B[pos] + + damage = D + + return damage, B, backstress Index: /issm/trunk-jpl/src/m/mech/backstressfrominversion.py =================================================================== --- /issm/trunk-jpl/src/m/mech/backstressfrominversion.py (revision 24212) +++ /issm/trunk-jpl/src/m/mech/backstressfrominversion.py (revision 24213) @@ -1,74 +1,77 @@ -import numpy as np +import numpy as np from averaging import averaging from thomasparams import thomasparams -def backstressfrominversion(md,**kwargs): - ''' - Compute ice shelf backstress from inversion results. - This routine computes backstress based on the analytical formalism of - Thomas (1973) and Borstad et al. (2013, The Cryosphere). The model - must contain inversion results for ice rigidity. Strain rates must - also be included, either from observed or modeled velocities. Ice - rigidity B is assumed to be parameterized by the ice temperature in - md.materials.rheology_B. +def backstressfrominversion(md, **kwargs): + ''' + Compute ice shelf backstress from inversion results. + + This routine computes backstress based on the analytical formalism of + Thomas (1973) and Borstad et al. (2013, The Cryosphere). The model + must contain inversion results for ice rigidity. Strain rates must + also be included, either from observed or modeled velocities. Ice + rigidity B is assumed to be parameterized by the ice temperature in + md.materials.rheology_B. Available options: - - 'tempmask' : mask the inverted rigidity to be no more than - appropriate for the temperature of the ice? - Boolean, defaults to false. - - 'smoothing' : the amount of smoothing to be applied to the strain rate data. - Type 'help averaging' for more information on its - usage. Defaults to 0. - - 'coordsys' : coordinate system for calculating the strain rate - components. Must be one of: - 'longitudinal': x axis aligned along a flowline at every point (default) - 'principal': x axis aligned along maximum principal strain rate - at every point - 'xy': x and y axes same as in polar stereographic projection + - 'tempmask' : mask the inverted rigidity to be no more than + appropriate for the temperature of the ice? + Boolean, defaults to false. + - 'smoothing' : the amount of smoothing to be applied to the strain rate data. + Type 'help averaging' for more information on its + usage. Defaults to 0. + - 'coordsys' : coordinate system for calculating the strain rate + components. Must be one of: + 'longitudinal': x axis aligned along a flowline at every point (default) + 'principal': x axis aligned along maximum principal strain rate + at every point + 'xy': x and y axes same as in polar stereographic projection Return values: - 'backstress' is the inferred backstress based on the analytical - solution for ice shelf creep + 'backstress' is the inferred backstress based on the analytical + solution for ice shelf creep Usage: - backstress=backstressfrominversion(md,options) + backstress = backstressfrominversion(md, options) Example: - backstress=backstressfrominversion(md,'smoothing',2,'coordsys','longitudinal','tempmask',true); - ''' + backstress = backstressfrominversion(md, 'smoothing', 2, 'coordsys', 'longitudinal', 'tempmask', true) + ''' - # unpack kwargs - tempmask=kwargs.pop('tempmask',False) - if 'tempmask' in kwargs: del kwargs['maxiter'] - smoothing=kwargs.pop('smoothing',0) - if 'smoothing' in kwargs: del kwargs['smoothing'] - coordsys=kwargs.pop('coordsys','longitudinal') - if 'coordsys' in kwargs: del kwargs['coordsys'] - assert len(kwargs)==0, 'error, unexpected or misspelled kwargs' + # unpack kwargs + tempmask = kwargs.pop('tempmask', False) + if 'tempmask' in kwargs: + del kwargs['maxiter'] + smoothing = kwargs.pop('smoothing', 0) + if 'smoothing' in kwargs: + del kwargs['smoothing'] + coordsys = kwargs.pop('coordsys', 'longitudinal') + if 'coordsys' in kwargs: + del kwargs['coordsys'] + assert len(kwargs) == 0, 'error, unexpected or misspelled kwargs' - # some checks - if not hasattr(md.results,'strainrate'): - raise Exception('md.results.strainrate not present. Calculate using md=mechanicalproperties(md,vx,vy)') - if not '2d' in md.mesh.__doc__: - raise Exception('only 2d (planview) model supported currently') - if any(md.flowequation.element_equation!=2): - raise Exception('Warning: the model has some non-SSA elements. These will be treated like SSA elements') + # some checks + if not hasattr(md.results, 'strainrate'): + raise Exception('md.results.strainrate not present. Calculate using md = mechanicalproperties(md, vx, vy)') + if '2d' not in md.mesh.__doc__: + raise Exception('only 2d (planview) model supported currently') + if any(md.flowequation.element_equation != 2): + raise Exception('Warning: the model has some non - SSA elements. These will be treated like SSA elements') - T=0.5*md.materials.rho_ice*md.constants.g*(1-md.materials.rho_ice/md.materials.rho_water)*md.geometry.thickness - n=averaging(md,md.materials.rheology_n,0) - B=md.materials.rheology_B - Bi=md.results.StressbalanceSolution.MaterialsRheologyBbar.reshape(-1,) - - a0,b0,theta0,ex0=thomasparams(md,eq='Thomas',smoothing=smoothing,coordsys=coordsys) - - if tempmask: - Bi=md.results.StressbalanceSolution.MaterialsRheologyBbar - pos=np.nonzero(Bi>md.materials.rheology_B) - Bi[pos]=md.materials.rheology_B[pos] - - # analytical backstress solution - backstress=T-Bi*np.sign(ex0)*(2+a0)*np.abs(ex0)**(1./n)/((1+a0+a0**2+b0**2)**((n-1.)/2./n)) - backstress[np.nonzero(backstress<0)]=0 + T = 0.5 * md.materials.rho_ice * md.constants.g * (1 - md.materials.rho_ice / md.materials.rho_water) * md.geometry.thickness + n = averaging(md, md.materials.rheology_n, 0) + Bi = md.results.StressbalanceSolution.MaterialsRheologyBbar.reshape(- 1, ) - return backstress + a0, b0, theta0, ex0 = thomasparams(md, eq='Thomas', smoothing=smoothing, coordsys=coordsys) + + if tempmask: + Bi = md.results.StressbalanceSolution.MaterialsRheologyBbar + pos = np.nonzero(Bi > md.materials.rheology_B) + Bi[pos] = md.materials.rheology_B[pos] + + # analytical backstress solution + backstress = T - Bi * np.sign(ex0) * (2 + a0) * np.abs(ex0)**(1. / n) / ((1 + a0 + a0**2 + b0**2)**((n - 1.) / 2. / n)) + backstress[np.nonzero(backstress < 0)] = 0 + + return backstress Index: /issm/trunk-jpl/src/m/mech/calcbackstress.py =================================================================== --- /issm/trunk-jpl/src/m/mech/calcbackstress.py (revision 24212) +++ /issm/trunk-jpl/src/m/mech/calcbackstress.py (revision 24213) @@ -1,66 +1,69 @@ -import numpy as np +import numpy as np from averaging import averaging from thomasparams import thomasparams -def calcbackstress(md,**kwargs): - ''' - Compute ice shelf backstress. - This routine computes backstress based on the analytical formalism of - Thomas (1973) and Borstad et al. (2013, The Cryosphere) based on the - ice rigidity, thickness, the densities of ice and seawater, and - (optionally) damage. Strain rates must also be included, either from - observed or modeled velocities. - - Available options: - - 'smoothing' : the amount of smoothing to be applied to the strain rate data. - Type 'help averaging' for more information on its - usage. Defaults to 0. - - 'coordsys' : coordinate system for calculating the strain rate - components. Must be one of: - 'longitudinal': x axis aligned along a flowline at every point (default) - 'principal': x axis aligned along maximum principal strain rate - at every point - 'xy': x and y axes same as in polar stereographic projection +def calcbackstress(md, **kwargs): + ''' + Compute ice shelf backstress. + + This routine computes backstress based on the analytical formalism of + Thomas (1973) and Borstad et al. (2013, The Cryosphere) based on the + ice rigidity, thickness, the densities of ice and seawater, and + (optionally) damage. Strain rates must also be included, either from + observed or modeled velocities. + + Available options: + - 'smoothing' : the amount of smoothing to be applied to the strain rate data. + Type 'help averaging' for more information on its + usage. Defaults to 0. + - 'coordsys' : coordinate system for calculating the strain rate + components. Must be one of: + 'longitudinal': x axis aligned along a flowline at every point (default) + 'principal': x axis aligned along maximum principal strain rate + at every point + 'xy': x and y axes same as in polar stereographic projection Return values: - 'backstress' is the inferred backstress based on the analytical - solution for ice shelf creep + 'backstress' is the inferred backstress based on the analytical + solution for ice shelf creep Usage: - backstress=calcbackstress(md,options) + backstress = calcbackstress(md, options) Example: - backstress=calcbackstress(md,'smoothing',2,'coordsys','longitudinal') - ''' + backstress = calcbackstress(md, 'smoothing', 2, 'coordsys', 'longitudinal') + ''' - # unpack kwargs - smoothing=kwargs.pop('smoothing',0) - if 'smoothing' in kwargs: del kwargs['smoothing'] - coordsys=kwargs.pop('coordsys','longitudinal') - if 'coordsys' in kwargs: del kwargs['coordsys'] - assert len(kwargs)==0, 'error, unexpected or misspelled kwargs' + # unpack kwargs + smoothing = kwargs.pop('smoothing', 0) + if 'smoothing' in kwargs: + del kwargs['smoothing'] + coordsys = kwargs.pop('coordsys', 'longitudinal') + if 'coordsys' in kwargs: + del kwargs['coordsys'] + assert len(kwargs) == 0, 'error, unexpected or misspelled kwargs' - # some checks - if not hasattr(md.results,'strainrate'): - raise Exception('md.results.strainrate not present. Calculate using md=mechanicalproperties(md,vx,vy)') - if not '2d' in md.mesh.__doc__: - raise Exception('only 2d (planview) model supported currently') - if any(md.flowequation.element_equation!=2): - raise Exception('Warning: the model has some non-SSA elements. These will be treated like SSA elements') + # some checks + if not hasattr(md.results, 'strainrate'): + raise Exception('md.results.strainrate not present. Calculate using md = mechanicalproperties(md, vx, vy)') + if '2d' not in md.mesh.__doc__: + raise Exception('only 2d (planview) model supported currently') + if any(md.flowequation.element_equation != 2): + raise Exception('Warning: the model has some non - SSA elements. These will be treated like SSA elements') - T=0.5*md.materials.rho_ice*md.constants.g*(1-md.materials.rho_ice/md.materials.rho_water)*md.geometry.thickness - n=averaging(md,md.materials.rheology_n,0) - B=md.materials.rheology_B - if md.damage.isdamage: - D=md.damage.D - else: - D=0. - - a0,b0,theta0,ex0=thomasparams(md,eq='Thomas',smoothing=smoothing,coordsys=coordsys) - - # analytical backstress solution - backstress=T-(1.-D)*B*np.sign(ex0)*(2+a0)*np.abs(ex0)**(1./n)/((1+a0+a0**2+b0**2)**((n-1.)/2./n)) - backstress[np.nonzero(backstress<0)]=0 + T = 0.5 * md.materials.rho_ice * md.constants.g * (1 - md.materials.rho_ice / md.materials.rho_water) * md.geometry.thickness + n = averaging(md, md.materials.rheology_n, 0) + B = md.materials.rheology_B + if md.damage.isdamage: + D = md.damage.D + else: + D = 0. - return backstress + a0, b0, theta0, ex0 = thomasparams(md, eq='Thomas', smoothing=smoothing, coordsys=coordsys) + + # analytical backstress solution + backstress = T - (1. - D) * B * np.sign(ex0) * (2 + a0) * np.abs(ex0)**(1. / n) / ((1 + a0 + a0**2 + b0**2)**((n - 1.) / 2. / n)) + backstress[np.nonzero(backstress < 0)] = 0 + + return backstress Index: /issm/trunk-jpl/src/m/mech/damagefrominversion.py =================================================================== --- /issm/trunk-jpl/src/m/mech/damagefrominversion.py (revision 24212) +++ /issm/trunk-jpl/src/m/mech/damagefrominversion.py (revision 24213) @@ -1,44 +1,45 @@ -import numpy as np +import numpy as np + def damagefrominversion(md): - ''' - compute ice shelf damage from inversion results + ''' + compute ice shelf damage from inversion results - This routine computes damage based on the analytical formalism of Borstad et - al. (2013, The Cryosphere). The model must contain inversion results for - ice rigidity. Ice rigidity B is assumed to be parameterized by the ice - temperature in md.materials.rheology_B. - - Usage: - damage=damagefrominversion(md) - - Example: - damage=damagefrominversion(md) - ''' + This routine computes damage based on the analytical formalism of Borstad et + al. (2013, The Cryosphere). The model must contain inversion results for + ice rigidity. Ice rigidity B is assumed to be parameterized by the ice + temperature in md.materials.rheology_B. - # check inputs - if not hasattr(md.results,'strainrate'): - raise Exception('md.results.strainrate is not present. Calculate using md=mechanicalproperties(md,vx,vy)') - if not '2d' in md.mesh.__doc__: - raise Exception('only 2d (planview) model supported currently') - if any(md.flowequation.element_equation!=2): - raise Exception('Warning: the model has some non-SSA elements. These will be treated like SSA elements') - if np.ndim(md.results.StressbalanceSolution.MaterialsRheologyBbar)==2: - Bi=md.results.StressbalanceSolution.MaterialsRheologyBbar.reshape(-1,) - else: - Bi=md.results.StressbalanceSolution.MaterialsRheologyBbar - if np.ndim(md.materials.rheology_B)==2: - BT=md.materials.rheology_B.reshape(-1,) - else: - BT=md.materials.rheology_B + Usage: + damage = damagefrominversion(md) - damage=np.zeros_like(Bi) + Example: + damage = damagefrominversion(md) + ''' - # Damage where Bi softer than B(T) - pos=np.nonzero(Bi=1e-4) # to avoid division by zero + temperature = steadystateiceshelftemp(md, surfacetemp, basaltemp) + """ + if len(md.geometry.thickness) != md.mesh.numberofvertices: + raise ValueError('steadystateiceshelftemp error message: thickness should have a length of ' + md.mesh.numberofvertices) - np.seterr(over='raise',divide='raise') # raise errors if floating point exceptions are encountered in following calculation - #calculate depth-averaged temperature (in Celsius) - try: - temperature[pos]=-( (Tb[pos]-Ts[pos])*ki/wi[pos] + Hi[pos]*Tb[pos] - (Hi[pos]*Ts[pos] + (Tb[pos]-Ts[pos])*ki/wi[pos])*np.exp(Hi[pos]*wi[pos]/ki) )/( Hi[pos]*(np.exp(Hi[pos]*wi[pos]/ki)-1)) - except FloatingPointError: - print('steadystateiceshelf warning: overflow encountered in multipy/divide/exp, trying another formulation.') - temperature[pos]=-( ((Tb[pos]-Ts[pos])*ki/wi[pos] + Hi[pos]*Tb[pos])/np.exp(Hi[pos]*wi[pos]/ki) - Hi[pos]*Ts[pos] + (Tb[pos]-Ts[pos])*ki/wi[pos])/( Hi[pos]*(1-np.exp(-Hi[pos]*wi[pos]/ki))) - - #temperature should not be less than surface temp - pos=np.nonzero(temperature= 1e-4) # to avoid division by zero + + np.seterr(over='raise', divide='raise') # raise errors if floating point exceptions are encountered in following calculation + #calculate depth - averaged temperature (in Celsius) + try: + temperature[pos] = -((Tb[pos] - Ts[pos]) * ki / wi[pos] + Hi[pos] * Tb[pos] - (Hi[pos] * Ts[pos] + (Tb[pos] - Ts[pos]) * ki / wi[pos]) * np.exp(Hi[pos] * wi[pos] / ki)) / (Hi[pos] * (np.exp(Hi[pos] * wi[pos] / ki) - 1)) + except FloatingPointError: + print('steadystateiceshelf warning: overflow encountered in multipy / divide / exp, trying another formulation.') + temperature[pos] = -(((Tb[pos] - Ts[pos]) * ki / wi[pos] + Hi[pos] * Tb[pos]) / np.exp(Hi[pos] * wi[pos] / ki) - Hi[pos] * Ts[pos] + (Tb[pos] - Ts[pos]) * ki / wi[pos]) / (Hi[pos] * (1 - np.exp(- Hi[pos] * wi[pos] / ki))) + + #temperature should not be less than surface temp + pos = np.nonzero(temperature < Ts) + temperature[pos] = Ts[pos] + + # NaN where melt rates are too high (infinity / infinity in exponential) + pos = np.nonzero(np.isnan(temperature)) + temperature[pos] = Ts[pos] + + #convert to Kelvin + temperature = temperature + 273.15 + + return temperature Index: /issm/trunk-jpl/src/m/mech/thomasparams.py =================================================================== --- /issm/trunk-jpl/src/m/mech/thomasparams.py (revision 24212) +++ /issm/trunk-jpl/src/m/mech/thomasparams.py (revision 24213) @@ -1,145 +1,149 @@ -import numpy as np +import numpy as np from averaging import averaging -def thomasparams(md,**kwargs): - ''' - compute Thomas' geometric parameters for an ice shelf - This routine computes geometric parameters representing ratios between - components of the horizontal strain rate tensor for an ice shelf, as - originally developed in Thomas (1973). The model must contain computed - strain rates, either from observed or modeled ice velocities. +def thomasparams(md, **kwargs): + ''' + compute Thomas' geometric parameters for an ice shelf + + This routine computes geometric parameters representing ratios between + components of the horizontal strain rate tensor for an ice shelf, as + originally developed in Thomas (1973). The model must contain computed + strain rates, either from observed or modeled ice velocities. Available options: - -eq : analytical equation to use in the calculation. Must be one of: - 'Thomas' for a 2D ice shelf, taking into account full strain rate - tensor (default) - 'Weertman1D' for a confined ice shelf free to flow in one direction - 'Weertman2D' for an unconfined ice shelf free to spread in any direction + - eq : analytical equation to use in the calculation. Must be one of: + 'Thomas' for a 2D ice shelf, taking into account full strain rate + tensor (default) + 'Weertman1D' for a confined ice shelf free to flow in one direction + 'Weertman2D' for an unconfined ice shelf free to spread in any direction - -smoothing : an integer smoothing parameter for the averaging function - (default 0) Type 'help averaging' for more information on its usage. + - smoothing : an integer smoothing parameter for the averaging function + (default 0) Type 'help averaging' for more information on its usage. - -coordsys : coordinate system for calculating the strain rate - components. Must be one of: - 'longitudinal': x axis aligned along a flowline at every point (default) - 'principal': x axis aligned along maximum principal strain rate - at every point - 'xy': x and y axes same as in polar stereographic projection + - coordsys : coordinate system for calculating the strain rate + components. Must be one of: + 'longitudinal': x axis aligned along a flowline at every point (default) + 'principal': x axis aligned along maximum principal strain rate + at every point + 'xy': x and y axes same as in polar stereographic projection - Return values: + Return values: - 'alpha' which is the ratio e_yy/e_xx between components of the strain - rate tensor + 'alpha' which is the ratio e_yy / e_xx between components of the strain + rate tensor - 'beta' which is the ratio e_xy/e_xx between components of the strain rate - tensor + 'beta' which is the ratio e_xy / e_xx between components of the strain rate + tensor - 'theta' which is a combination of alpha and beta arising from the form of - the equivalent stress + 'theta' which is a combination of alpha and beta arising from the form of + the equivalent stress - 'exx' is the strain rate along a coordinate system defined by 'coordsys' + 'exx' is the strain rate along a coordinate system defined by 'coordsys' - 'sigxx' is the deviatoric stress along a coordinate system defined by 'coordsys' + 'sigxx' is the deviatoric stress along a coordinate system defined by 'coordsys' - Usage: - alpha,beta,theta,exx,sigxx=thomasparams(md) + Usage: + alpha, beta, theta, exx, sigxx = thomasparams(md) - Example: - alpha,beta,theta,exx,sigxx=thomasparams(md,eq='Thomas',smoothing=2,coordsys='longitudinal') - ''' + Example: + alpha, beta, theta, exx, sigxx = thomasparams(md, eq = 'Thomas', smoothing = 2, coordsys = 'longitudinal') + ''' - #unpack kwargs - eq=kwargs.pop('eq','Thomas') - if 'eq' in kwargs: del kwargs['eq'] - smoothing=kwargs.pop('smoothing',0) - if 'smoothing' in kwargs: del kwargs['smoothing'] - coordsys=kwargs.pop('coordsys','longitudinal') - if 'coordsys' in kwargs: del kwargs['coordsys'] - assert len(kwargs)==0, 'error, unexpected or misspelled kwargs' + #unpack kwargs + eq = kwargs.pop('eq', 'Thomas') + if 'eq' in kwargs: + del kwargs['eq'] + smoothing = kwargs.pop('smoothing', 0) + if 'smoothing' in kwargs: + del kwargs['smoothing'] + coordsys = kwargs.pop('coordsys', 'longitudinal') + if 'coordsys' in kwargs: + del kwargs['coordsys'] + assert len(kwargs) == 0, 'error, unexpected or misspelled kwargs' - # some checks - if not hasattr(md.results,'strainrate'): - raise Exception('md.results.strainrate not present. Calculate using md=mechanicalproperties(md,vx,vy)') - if not '2d' in md.mesh.__doc__: - raise Exception('only 2d (planview) model supported currently') - if any(md.flowequation.element_equation!=2): - raise Exception('Warning: the model has some non-SSA elements. These will be treated like SSA elements') + # some checks + if not hasattr(md.results, 'strainrate'): + raise Exception('md.results.strainrate not present. Calculate using md = mechanicalproperties(md, vx, vy)') + if '2d' not in md.mesh.__doc__: + raise Exception('only 2d (planview) model supported currently') + if any(md.flowequation.element_equation != 2): + raise Exception('Warning: the model has some non - SSA elements. These will be treated like SSA elements') - # average element strain rates onto vertices - e1=averaging(md,md.results.strainrate.principalvalue1,smoothing)/md.constants.yts # convert to s^-1 - e2=averaging(md,md.results.strainrate.principalvalue2,smoothing)/md.constants.yts - exx=averaging(md,md.results.strainrate.xx,smoothing)/md.constants.yts - eyy=averaging(md,md.results.strainrate.yy,smoothing)/md.constants.yts - exy=averaging(md,md.results.strainrate.xy,smoothing)/md.constants.yts - - # checks: any of e1 or e2 equal to zero? - pos=np.nonzero(e1==0) - if np.any(pos==1): - print('WARNING: first principal strain rate equal to zero. Value set to 1e-13 s^-1') - e1[pos]=1.e-13 - pos=np.nonzero(e2==0) - if np.any(pos==1): - print('WARNING: second principal strain rate equal to zero. Value set to 1e-13 s^-1') - e2[pos]=1.e-13 - - # rheology - n=averaging(md,md.materials.rheology_n,0) - B=md.materials.rheology_B - - if coordsys=='principal': - b=np.zeros((md.mesh.numberofvertices,)) - ex=e1 - a=e2/e1 - pos=np.nonzero(np.logical_and(e1<0,e2>0)) # longitudinal compression and lateral tension - a[pos]=e1[pos]/e2[pos] - ex[pos]=e2[pos] - pos2=np.nonzero(e1<0 & e2<0 & np.abs(e1)0 & e2>0 & np.abs(e1)0: - print(('Warning: ', len(pos), ' vertices have alpha within 1e-3 of -2')) - a[pos]=-2+1e-3 + # average element strain rates onto vertices + e1 = averaging(md, md.results.strainrate.principalvalue1, smoothing) / md.constants.yts # convert to s^ - 1 + e2 = averaging(md, md.results.strainrate.principalvalue2, smoothing) / md.constants.yts + exx = averaging(md, md.results.strainrate.xx, smoothing) / md.constants.yts + eyy = averaging(md, md.results.strainrate.yy, smoothing) / md.constants.yts + exy = averaging(md, md.results.strainrate.xy, smoothing) / md.constants.yts - if eq=='Weertman1D': - theta=1./8 - a=np.zeros((md.mesh.numberofvertices,)) - elif eq=='Weertman2D': - theta=1./9 - a=np.ones((md.mesh.numberofvertices,)) - elif eq=='Thomas': - theta=((1.+a+a**2+b**2)**((n-1.)/2.))/(np.abs(2.+a)**n) - else: - raise ValueError('argument passed to "eq" not valid') + # checks: any of e1 or e2 equal to zero? + pos = np.nonzero(e1 == 0) + if np.any(pos == 1): + print('WARNING: first principal strain rate equal to zero. Value set to 1e-13 s^ - 1') + e1[pos] = 1.e-13 + pos = np.nonzero(e2 == 0) + if np.any(pos == 1): + print('WARNING: second principal strain rate equal to zero. Value set to 1e-13 s^ - 1') + e2[pos] = 1.e-13 - alpha=a - beta=b + # rheology + n = averaging(md, md.materials.rheology_n, 0) + B = md.materials.rheology_B - return alpha,beta,theta,ex + if coordsys == 'principal': + b = np.zeros((md.mesh.numberofvertices, )) + ex = e1 + a = e2 / e1 + pos = np.nonzero(np.logical_and(e1 < 0, e2 > 0)) # longitudinal compression and lateral tension + a[pos] = e1[pos] / e2[pos] + ex[pos] = e2[pos] + pos2 = np.nonzero(e1 < 0 & e2 < 0 & np.abs(e1) < np.abs(e2)) # lateral and longitudinal compression + a[pos2] = e1[pos2] / e2[pos2] + ex[pos2] = e2[pos2] + pos3 = np.nonzero(e1 > 0 & e2 > 0 & np.abs(e1) < np.abs(e2)) # lateral and longitudinal tension + a[pos3] = e1[pos3] / e2[pos3] + ex[pos3] = e2[pos3] + ind = np.nonzero(e1 < 0 & e2 < 0) + a[ind] = -a[ind] # where both strain rates are compressive, enforce negative alpha + sigxx = (np.abs(ex) / ((1. + a + a**2)**((n - 1.) / 2.)))**(1. / n) * B + elif coordsys == 'xy': + ex = exx + a = eyy / exx + b = exy / exx + elif coordsys == 'longitudinal': + # using longitudinal strain rates defined by observed velocity vector + velangle = np.arctan(md.initialization.vy / md.initialization.vx) + pos = np.nonzero(md.initialization.vx == 0) + velangle[pos] = np.pi / 2 + ex = 0.5 * (exx + eyy) + 0.5 * (exx - eyy) * np.cos(2. * velangle) + exy * np.sin(2. * velangle) + ey = exx + eyy - ex # trace of strain rate tensor is invariant + exy = - 0.5 * (exx - eyy) * np.sin(2. * velangle) + exy * np.cos(2. * velangle) + a = ey / ex + b = exy / ex + sigxx = abs(ex)**(1. / n - 1.) * ex / ((1. + a + a**2 + b**2)**((n - 1.) / (2. * n))) * B + else: + raise ValueError('argument passed to "coordsys" not valid') + + # a < - 1 in areas of strong lateral compression or longitudinal compression and + # theta flips sign at a = - 2 + pos = np.nonzero(np.abs((np.abs(a) - 2.)) < 1.e-3) + if len(pos) > 0: + print(('Warning: ', len(pos), ' vertices have alpha within 1e-3 of - 2')) + a[pos] = -2 + 1e-3 + + if eq == 'Weertman1D': + theta = 1. / 8 + a = np.zeros((md.mesh.numberofvertices, )) + elif eq == 'Weertman2D': + theta = 1. / 9 + a = np.ones((md.mesh.numberofvertices, )) + elif eq == 'Thomas': + theta = ((1. + a + a**2 + b**2)**((n - 1.) / 2.)) / (np.abs(2. + a)**n) + else: + raise ValueError('argument passed to "eq" not valid') + + alpha = a + beta = b + + return alpha, beta, theta, ex Index: /issm/trunk-jpl/src/m/mesh/ComputeHessian.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/ComputeHessian.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/ComputeHessian.py (revision 24213) @@ -4,62 +4,63 @@ import MatlabFuncs as m -def ComputeHessian(index,x,y,field,type): - """ - COMPUTEHESSIAN - compute hessian matrix from a field - Compute the hessian matrix of a given field - return the three components Hxx Hxy Hyy - for each element or each node +def ComputeHessian(index, x, y, field, type): + """ + COMPUTEHESSIAN - compute hessian matrix from a field - Usage: - hessian=ComputeHessian(index,x,y,field,type) + Compute the hessian matrix of a given field + return the three components Hxx Hxy Hyy + for each element or each node - Example: - hessian=ComputeHessian(md.mesh.elements,md.mesh.x,md.mesh.y,md.inversion.vel_obs,'node') - """ + Usage: + hessian = ComputeHessian(index, x, y, field, type) - #some variables - numberofnodes=np.size(x) - numberofelements=np.size(index,axis=0) + Example: + hessian = ComputeHessian(md.mesh.elements, md.mesh.x, md.mesh.y, md.inversion.vel_obs, 'node') + """ - #some checks - if np.size(field)!=numberofnodes and np.size(field)!=numberofelements: - raise TypeError("ComputeHessian error message: the given field size not supported yet") - if not m.strcmpi(type,'node') and not m.strcmpi(type,'element'): - raise TypeError("ComputeHessian error message: only 'node' or 'element' type supported yet") + #some variables + numberofnodes = np.size(x) + numberofelements = np.size(index, axis=0) - #initialization - line=index.reshape(-1,order='F') - linesize=3*numberofelements + #some checks + if np.size(field) != numberofnodes and np.size(field) != numberofelements: + raise TypeError("ComputeHessian error message: the given field size not supported yet") + if not m.strcmpi(type, 'node') and not m.strcmpi(type, 'element'): + raise TypeError("ComputeHessian error message: only 'node' or 'element' type supported yet") - #get areas and nodal functions coefficients N(x,y)=alpha x + beta y + gamma - [alpha,beta,dum]=GetNodalFunctionsCoeff(index,x,y) - areas=GetAreas(index,x,y) + #initialization + line = index.reshape(-1, order='F') + linesize = 3 * numberofelements - #compute weights that hold the volume of all the element holding the node i - weights=m.sparse(line,np.ones((linesize,1),dtype=int),np.tile(areas,(3,1)),numberofnodes,1) + #get areas and nodal functions coefficients N(x, y)=alpha x + beta y + gamma + [alpha, beta, dum] = GetNodalFunctionsCoeff(index, x, y) + areas = GetAreas(index, x, y) - #compute field on nodes if on elements - if np.size(field,axis=0)==numberofelements: - field=m.sparse(line,np.ones((linesize,1),dtype=int),np.tile(areas*field,(3,1)),numberofnodes,1)/weights + #compute weights that hold the volume of all the element holding the node i + weights = m.sparse(line, np.ones((linesize, 1), dtype=int), np.tile(areas, (3, 1)), numberofnodes, 1) - #Compute gradient for each element - grad_elx=np.sum(field[index-1]*alpha,axis=1) - grad_ely=np.sum(field[index-1]*beta,axis=1) + #compute field on nodes if on elements + if np.size(field, axis=0) == numberofelements: + field = m.sparse(line, np.ones((linesize, 1), dtype=int), np.tile(areas * field, (3, 1)), numberofnodes, 1) / weights - #Compute gradient for each node (average of the elements around) - gradx=m.sparse(line,np.ones((linesize,1),dtype=int),np.tile((areas*grad_elx),(3,1)),numberofnodes,1) - grady=m.sparse(line,np.ones((linesize,1),dtype=int),np.tile((areas*grad_ely),(3,1)),numberofnodes,1) - gradx=gradx/weights - grady=grady/weights + #Compute gradient for each element + grad_elx = np.sum(field[index - 1] * alpha, axis=1) + grad_ely = np.sum(field[index - 1] * beta, axis=1) - #Compute hessian for each element - hessian=np.vstack((np.sum(gradx[index-1,0]*alpha,axis=1),np.sum(grady[index-1,0]*alpha,axis=1),np.sum(grady[index-1,0]*beta,axis=1))).T + #Compute gradient for each node (average of the elements around) + gradx = m.sparse(line, np.ones((linesize, 1), dtype=int), np.tile((areas * grad_elx), (3, 1)), numberofnodes, 1) + grady = m.sparse(line, np.ones((linesize, 1), dtype=int), np.tile((areas * grad_ely), (3, 1)), numberofnodes, 1) + gradx = gradx / weights + grady = grady / weights - if m.strcmpi(type,'node'): - #Compute Hessian on the nodes (average of the elements around) - hessian=np.hstack((m.sparse(line,np.ones((linesize,1),dtype=int),np.tile((areas*hessian[:,0]),(3,1)),numberofnodes,1)/weights, - m.sparse(line,np.ones((linesize,1),dtype=int),np.tile((areas*hessian[:,1]),(3,1)),numberofnodes,1)/weights, - m.sparse(line,np.ones((linesize,1),dtype=int),np.tile((areas*hessian[:,2]),(3,1)),numberofnodes,1)/weights )) + #Compute hessian for each element + hessian = np.vstack((np.sum(gradx[index - 1, 0] * alpha, axis=1), np.sum(grady[index - 1, 0] * alpha, axis=1), np.sum(grady[index - 1, 0] * beta, axis=1))).T - return hessian + if m.strcmpi(type, 'node'): + #Compute Hessian on the nodes (average of the elements around) + hessian = np.hstack((m.sparse(line, np.ones((linesize, 1), dtype=int), np.tile((areas * hessian[:, 0]), (3, 1)), numberofnodes, 1) / weights, + m.sparse(line, np.ones((linesize, 1), dtype=int), np.tile((areas * hessian[:, 1]), (3, 1)), numberofnodes, 1) / weights, + m.sparse(line, np.ones((linesize, 1), dtype=int), np.tile((areas * hessian[:, 2]), (3, 1)), numberofnodes, 1) / weights)) + + return hessian Index: /issm/trunk-jpl/src/m/mesh/ComputeMetric.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/ComputeMetric.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/ComputeMetric.py (revision 24213) @@ -1,74 +1,75 @@ import numpy as np -def ComputeMetric(hessian,scale,epsilon,hmin,hmax,pos): - """ - COMPUTEMETRIC - compute metric from an Hessian - Usage: - metric=ComputeMetric(hessian,scale,epsilon,hmin,hmax,pos) - pos is contains the positions where the metric is wished to be maximized (water?) +def ComputeMetric(hessian, scale, epsilon, hmin, hmax, pos): + """ + COMPUTEMETRIC - compute metric from an Hessian - Example: - metric=ComputeMetric(hessian,2/9,10^-1,100,10^5,[]) - """ + Usage: + metric = ComputeMetric(hessian, scale, epsilon, hmin, hmax, pos) + pos is contains the positions where the metric is wished to be maximized (water?) - #first, find the eigen values of each line of H=[hessian(i,1) hessian(i,2); hessian(i,2) hessian(i,3)] - a=hessian[:,0] - b=hessian[:,1] - d=hessian[:,2] - lambda1=0.5*((a+d)+np.sqrt(4.*b**2+(a-d)**2)) - lambda2=0.5*((a+d)-np.sqrt(4.*b**2+(a-d)**2)) - pos1=np.nonzero(lambda1==0.)[0] - pos2=np.nonzero(lambda2==0.)[0] - pos3=np.nonzero(np.logical_and(b==0.,lambda1==lambda2))[0] + Example: + metric = ComputeMetric(hessian, 2 / 9, 10^ - 1, 100, 10^5, []) + """ - #Modify the eigen values to control the shape of the elements - lambda1=np.minimum(np.maximum(np.abs(lambda1)*scale/epsilon,1./hmax**2),1./hmin**2) - lambda2=np.minimum(np.maximum(np.abs(lambda2)*scale/epsilon,1./hmax**2),1./hmin**2) + #first, find the eigen values of each line of H = [hessian(i, 1) hessian(i, 2); hessian(i, 2) hessian(i, 3)] + a = hessian[:, 0] + b = hessian[:, 1] + d = hessian[:, 2] + lambda1 = 0.5 * ((a + d) + np.sqrt(4. * b**2 + (a - d)**2)) + lambda2 = 0.5 * ((a + d) - np.sqrt(4. * b**2 + (a - d)**2)) + pos1 = np.nonzero(lambda1 == 0.)[0] + pos2 = np.nonzero(lambda2 == 0.)[0] + pos3 = np.nonzero(np.logical_and(b == 0., lambda1 == lambda2))[0] - #compute eigen vectors - norm1=np.sqrt(8.*b**2+2.*(d-a)**2+2.*(d-a)*np.sqrt((a-d)**2+4.*b**2)) - v1x=2.*b/norm1 - v1y=((d-a)+np.sqrt((a-d)**2+4.*b**2))/norm1 - norm2=np.sqrt(8.*b**2+2.*(d-a)**2-2.*(d-a)*np.sqrt((a-d)**2+4.*b**2)) - v2x=2.*b/norm2 - v2y=((d-a)-np.sqrt((a-d)**2+4.*b**2))/norm2 + #Modify the eigen values to control the shape of the elements + lambda1 = np.minimum(np.maximum(np.abs(lambda1) * scale / epsilon, 1. / hmax**2), 1. / hmin**2) + lambda2 = np.minimum(np.maximum(np.abs(lambda2) * scale / epsilon, 1. / hmax**2), 1. / hmin**2) - v1x[pos3]=1. - v1y[pos3]=0. - v2x[pos3]=0. - v2y[pos3]=1. + #compute eigen vectors + norm1 = np.sqrt(8. * b**2 + 2. * (d - a)**2 + 2. * (d - a) * np.sqrt((a - d)**2 + 4. * b**2)) + v1x = 2. * b / norm1 + v1y = ((d - a) + np.sqrt((a - d)**2 + 4. * b**2)) / norm1 + norm2 = np.sqrt(8. * b**2 + 2. * (d - a)**2 - 2. * (d - a) * np.sqrt((a - d)**2 + 4. * b**2)) + v2x = 2. * b / norm2 + v2y = ((d - a) - np.sqrt((a - d)**2 + 4. * b**2)) / norm2 - #Compute new metric (for each node M=V*Lambda*V^-1) - metric=np.vstack((((v1x*v2y-v1y*v2x)**(-1)*( lambda1*v2y*v1x-lambda2*v1y*v2x)).reshape(-1,), - ((v1x*v2y-v1y*v2x)**(-1)*( lambda1*v1y*v2y-lambda2*v1y*v2y)).reshape(-1,), - ((v1x*v2y-v1y*v2x)**(-1)*(-lambda1*v2x*v1y+lambda2*v1x*v2y)).reshape(-1,))).T + v1x[pos3] = 1. + v1y[pos3] = 0. + v2x[pos3] = 0. + v2y[pos3] = 1. - #some corrections for 0 eigen values - metric[pos1,:]=np.tile(np.array([[1./hmax**2,0.,1./hmax**2]]),(np.size(pos1),1)) - metric[pos2,:]=np.tile(np.array([[1./hmax**2,0.,1./hmax**2]]),(np.size(pos2),1)) + #Compute new metric (for each node M = V * Lambda * V^ - 1) - #take care of water elements - metric[pos ,:]=np.tile(np.array([[1./hmax**2,0.,1./hmax**2]]),(np.size(pos ),1)) + metric = np.vstack((((v1x * v2y - v1y * v2x)**(- 1) * (lambda1 * v2y * v1x - lambda2 * v1y * v2x)).reshape(- 1, ), + ((v1x * v2y - v1y * v2x)**(- 1) * (lambda1 * v1y * v2y - lambda2 * v1y * v2y)).reshape(- 1, ), + ((v1x * v2y - v1y * v2x)**(- 1) * (- lambda1 * v2x * v1y + lambda2 * v1x * v2y)).reshape(- 1, ))).T - #take care of NaNs if any (use Numpy eig in a loop) - pos=np.nonzero(np.isnan(metric))[0] - if np.size(pos): - print((" %i NaN found in the metric. Use Numpy routine..." % np.size(pos))) - for posi in pos: - H=np.array([[hessian[posi,0],hessian[posi,1]],[hessian[posi,1],hessian[posi,2]]]) - [v,u]=np.linalg.eig(H) - v=np.diag(v) - lambda1=v[0,0] - lambda2=v[1,1] - v[0,0]=np.minimum(np.maximum(np.abs(lambda1)*scale/epsilon,1./hmax**2),1./hmin**2) - v[1,1]=np.minimum(np.maximum(np.abs(lambda2)*scale/epsilon,1./hmax**2),1./hmin**2) + #some corrections for 0 eigen values + metric[pos1, :] = np.tile(np.array([[1. / hmax**2, 0., 1. / hmax**2]]), (np.size(pos1), 1)) + metric[pos2, :] = np.tile(np.array([[1. / hmax**2, 0., 1. / hmax**2]]), (np.size(pos2), 1)) - metricTria=np.dot(np.dot(u,v),np.linalg.inv(u)) - metric[posi,:]=np.array([metricTria[0,0],metricTria[0,1],metricTria[1,1]]) + #take care of water elements + metric[pos, :] = np.tile(np.array([[1. / hmax**2, 0., 1. / hmax**2]]), (np.size(pos), 1)) - if np.any(np.isnan(metric)): - raise RunTimeError("ComputeMetric error message: NaN in the metric despite our efforts...") + #take care of NaNs if any (use Numpy eig in a loop) + pos = np.nonzero(np.isnan(metric))[0] + if np.size(pos): + print((" %i NaN found in the metric. Use Numpy routine..." % np.size(pos))) + for posi in pos: + H = np.array([[hessian[posi, 0], hessian[posi, 1]], [hessian[posi, 1], hessian[posi, 2]]]) + [v, u] = np.linalg.eig(H) + v = np.diag(v) + lambda1 = v[0, 0] + lambda2 = v[1, 1] + v[0, 0] = np.minimum(np.maximum(np.abs(lambda1) * scale / epsilon, 1. / hmax**2), 1. / hmin**2) + v[1, 1] = np.minimum(np.maximum(np.abs(lambda2) * scale / epsilon, 1. / hmax**2), 1. / hmin**2) - return metric + metricTria = np.dot(np.dot(u, v), np.linalg.inv(u)) + metric[posi, :] = np.array([metricTria[0, 0], metricTria[0, 1], metricTria[1, 1]]) + if np.any(np.isnan(metric)): + raise RunTimeError("ComputeMetric error message: NaN in the metric despite our efforts...") + + return metric Index: /issm/trunk-jpl/src/m/mesh/ElementsFromEdge.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/ElementsFromEdge.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/ElementsFromEdge.py (revision 24213) @@ -2,23 +2,22 @@ import PythonFuncs as p -def ElementsFromEdge(elements,A,B): - """ - ELEMENTSFROMEDGE: find elements connected to one edge defined by nodes A and B - Usage: edgeelements=ElementsFromEdge(elements,A,B) +def ElementsFromEdge(elements, A, B): + """ + ELEMENTSFROMEDGE: find elements connected to one edge defined by nodes A and B - Eg: edgeelements=ElementsFromEdge(md.mesh.elements,tip1,tip2) + Usage: edgeelements = ElementsFromEdge(elements, A, B) - """ + Eg: edgeelements = ElementsFromEdge(md.mesh.elements, tip1, tip2) - edgeelements=np.nonzero(\ - p.logical_or_n(np.logical_and(elements[:,0]==A,elements[:,1]==B), \ - np.logical_and(elements[:,0]==A,elements[:,2]==B), \ - np.logical_and(elements[:,1]==A,elements[:,2]==B), \ - np.logical_and(elements[:,1]==A,elements[:,0]==B), \ - np.logical_and(elements[:,2]==A,elements[:,0]==B), \ - np.logical_and(elements[:,2]==A,elements[:,1]==B), \ - ))[0]+1 + """ - return edgeelements + edgeelements = np.nonzero( + p.logical_or_n(np.logical_and(elements[:, 0] == A, elements[:, 1] == B), + np.logical_and(elements[:, 0] == A, elements[:, 2] == B), + np.logical_and(elements[:, 1] == A, elements[:, 2] == B), + np.logical_and(elements[:, 1] == A, elements[:, 0] == B), + np.logical_and(elements[:, 2] == A, elements[:, 0] == B), + np.logical_and(elements[:, 2] == A, elements[:, 1] == B)))[0] + 1 + return edgeelements Index: /issm/trunk-jpl/src/m/mesh/GetNodalFunctionsCoeff.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/GetNodalFunctionsCoeff.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/GetNodalFunctionsCoeff.py (revision 24213) @@ -7,19 +7,19 @@ Compute the coefficients alpha beta and optionaly gamma of - 2d triangular elements. For each element, the nodal function + 2d triangular elements. For each element, the nodal function is defined as: - N(x, y)=sum(i=1:3) alpha_i * x + beta_i * y + gamma_i + N(x, y)=sum(i = 1:3) alpha_i * x + beta_i * y + gamma_i Usage: - [alpha beta]=GetNodalFunctionsCoeff(index, x, y); - [alpha beta gamma]=GetNodalFunctionsCoeff(index, x, y); + [alpha beta] = GetNodalFunctionsCoeff(index, x, y) + [alpha beta gamma] = GetNodalFunctionsCoeff(index, x, y) Example: - [alpha beta gamma]=GetNodalFunctionsCoeff(md.mesh.elements, md.mesh.x, md.mesh.y); + [alpha beta gamma] = GetNodalFunctionsCoeff(md.mesh.elements, md.mesh.x, md.mesh.y) """ #make columns out of x and y - x = x.reshape(-1) - y = y.reshape(-1) + x = x.reshape(- 1) + y = y.reshape(- 1) #get nels and nods @@ -39,5 +39,5 @@ beta = np.zeros((nels, 3)) - #compute nodal functions coefficients N(x, y) = alpha x + beta y +gamma + #compute nodal functions coefficients N(x, y) = alpha x + beta y + gamma x1 = x[index[:, 0] - 1] x2 = x[index[:, 1] - 1] @@ -49,10 +49,10 @@ #get alpha and beta - alpha = np.vstack(((invdet * (y2 - y3)).reshape(-1,), (invdet * (y3 - y1)).reshape(-1,), (invdet * (y1 - y2)).reshape(-1,))).T - beta = np.vstack(((invdet * (x3 - x2)).reshape(-1,), (invdet * (x1 - x3)).reshape(-1,), (invdet * (x2 - x1)).reshape(-1,))).T + alpha = np.vstack(((invdet * (y2 - y3)).reshape(- 1, ), (invdet * (y3 - y1)).reshape(- 1, ), (invdet * (y1 - y2)).reshape(- 1, ))).T + beta = np.vstack(((invdet * (x3 - x2)).reshape(- 1, ), (invdet * (x1 - x3)).reshape(- 1, ), (invdet * (x2 - x1)).reshape(- 1, ))).T #get gamma if requested gamma = np.zeros((nels, 3)) - gamma = np.vstack(((invdet * (x2 * y3 - x3 * y2)).reshape(-1,), (invdet * (y1 * x3 - y3 * x1)).reshape(-1,), (invdet * (x1 * y2 - x2 * y1)).reshape(-1,))).T + gamma = np.vstack(((invdet * (x2 * y3 - x3 * y2)).reshape(- 1, ), (invdet * (y1 * x3 - y3 * x1)).reshape(- 1, ), (invdet * (x1 * y2 - x2 * y1)).reshape(- 1, ))).T return alpha, beta, gamma Index: /issm/trunk-jpl/src/m/mesh/bamg.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/bamg.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/bamg.py (revision 24213) @@ -9,5 +9,4 @@ from bamgmesh import bamgmesh from expread import expread -from expwrite import expwrite from SegIntersect import SegIntersect import MatlabFuncs as m @@ -20,46 +19,46 @@ BAMG - mesh generation - Available options (for more details see ISSM website http: / / issm.jpl.nasa.gov / ): - - - domain : followed by an ARGUS file that prescribes the domain outline - - holes : followed by an ARGUS file that prescribes the holes - - subdomains : followed by an ARGUS file that prescribes the list of - subdomains (that need to be inside domain) - - - hmin : minimum edge length (default is 10^ - 100) - - hmax : maximum edge length (default is 10^100) - - hVertices : imposed edge length for each vertex (geometry or mesh) - - hminVertices : minimum edge length for each vertex (mesh) - - hmaxVertices : maximum edge length for each vertex (mesh) - - - anisomax : maximum ratio between the smallest and largest edges (default is 10^30) - - coeff : coefficient applied to the metric (2 - > twice as many elements, default is 1) - - cutoff : scalar used to compute the metric when metric type 2 or 3 are applied - - err : error used to generate the metric from a field - - errg : geometric error (default is 0.1) - - field : field of the model that will be used to compute the metric + Available options (for more details see ISSM website http: / / issm.jpl.nasa.gov / ): + + - domain : followed by an ARGUS file that prescribes the domain outline + - holes : followed by an ARGUS file that prescribes the holes + - subdomains : followed by an ARGUS file that prescribes the list of + subdomains (that need to be inside domain) + + - hmin : minimum edge length (default is 10^ - 100) + - hmax : maximum edge length (default is 10^100) + - hVertices : imposed edge length for each vertex (geometry or mesh) + - hminVertices : minimum edge length for each vertex (mesh) + - hmaxVertices : maximum edge length for each vertex (mesh) + + - anisomax : maximum ratio between the smallest and largest edges (default is 10^30) + - coeff : coefficient applied to the metric (2 - > twice as many elements, default is 1) + - cutoff : scalar used to compute the metric when metric type 2 or 3 are applied + - err : error used to generate the metric from a field + - errg : geometric error (default is 0.1) + - field : field of the model that will be used to compute the metric to apply several fields, use one column per field - - gradation : maximum ratio between two adjacent edges - - Hessiantype : 0 - > use double P2 projection (default) - 1 - > use Green formula - - KeepVertices : try to keep initial vertices when adaptation is done on an existing mesh (default 1) - - maxnbv : maximum number of vertices used to allocate memory (default is 10^6) - - maxsubdiv : maximum subdivision of exisiting elements (default is 10) - - metric : matrix (numberofnodes x 3) used as a metric - - Metrictype : 1 - > absolute error c / (err coeff^2) * Abs(H) (default) + - gradation : maximum ratio between two adjacent edges + - Hessiantype : 0 - > use double P2 projection (default) + 1 - > use Green formula + - KeepVertices : try to keep initial vertices when adaptation is done on an existing mesh (default 1) + - maxnbv : maximum number of vertices used to allocate memory (default is 10^6) + - maxsubdiv : maximum subdivision of exisiting elements (default is 10) + - metric : matrix (numberofnodes x 3) used as a metric + - Metrictype : 1 - > absolute error c / (err coeff^2) * Abs(H) (default) 2 - > relative error c / (err coeff^2) * Abs(H) / max(s, cutoff * max(s)) 3 - > rescaled absolute error c / (err coeff^2) * Abs(H) / (smax - smin) - - nbjacoby : correction used by Hessiantype = 1 (default is 1) - - nbsmooth : number of metric smoothing procedure (default is 3) - - omega : relaxation parameter of the smoothing procedure (default is 1.8) - - power : power applied to the metric (default is 1) - - splitcorners : split triangles whuch have 3 vertices on the outline (default is 1) - - verbose : level of verbosity (default is 1) - - - rifts : followed by an ARGUS file that prescribes the rifts - - toltip : tolerance to move tip on an existing point of the domain outline - - tracks : followed by an ARGUS file that prescribes the tracks that the mesh will stick to - - RequiredVertices : mesh vertices that are required. [x, y, ref]; ref is optional - - tol : if the distance between 2 points of the domain outline is less than tol, they + - nbjacoby : correction used by Hessiantype = 1 (default is 1) + - nbsmooth : number of metric smoothing procedure (default is 3) + - omega : relaxation parameter of the smoothing procedure (default is 1.8) + - power : power applied to the metric (default is 1) + - splitcorners : split triangles whuch have 3 vertices on the outline (default is 1) + - verbose : level of verbosity (default is 1) + + - rifts : followed by an ARGUS file that prescribes the rifts + - toltip : tolerance to move tip on an existing point of the domain outline + - tracks : followed by an ARGUS file that prescribes the tracks that the mesh will stick to + - RequiredVertices : mesh vertices that are required. [x, y, ref]; ref is optional + - tol : if the distance between 2 points of the domain outline is less than tol, they will be merged @@ -80,5 +79,4 @@ subdomain_ref = 1 - hole_ref = 1 # Bamg Geometry parameters {{{ @@ -108,13 +106,12 @@ #Check orientation nods = domaini['nods'] - 1 #the domain are closed 1 = end - test = np.sum((domaini['x'][1:nods + 1] - domaini['x'][0:nods]) * (domaini['y'][1:nods + 1] + domaini['y'][0:nods])) if (i == 0 and test > 0) or (i > 0 and test < 0): - print('At least one contour was not correctly oriented and has been re - oriented') + print('At least one contour was not correctly oriented and has been re-oriented') domaini['x'] = np.flipud(domaini['x']) domaini['y'] = np.flipud(domaini['y']) #Add all points to bamg_geometry - nods = domaini['nods'] - 1 #the domain are closed 0 = end + nods = domaini['nods'] - 1 #the domain are closed 0 = end bamg_geometry.Vertices = np.vstack((bamg_geometry.Vertices, np.vstack((domaini['x'][0:nods], domaini['y'][0:nods], np.ones((nods)))).T)) bamg_geometry.Edges = np.vstack((bamg_geometry.Edges, np.vstack((np.arange(count + 1, count + nods + 1), np.hstack((np.arange(count + 2, count + nods + 1), count + 1)), 1. * np.ones((nods)))).T)) @@ -153,10 +150,10 @@ test = np.sum((holei['x'][1:nods + 1] - holei['x'][0:nods]) * (holei['y'][1:nods + 1] + holei['y'][0:nods])) if test < 0: - print('At least one hole was not correctly oriented and has been re - oriented') + print('At least one hole was not correctly oriented and has been re-oriented') holei['x'] = np.flipud(holei['x']) holei['y'] = np.flipud(holei['y']) #Add all points to bamg_geometry - nods = holei['nods'] - 1 #the hole are closed 0 = end + nods = holei['nods'] - 1 #the hole are closed 0 = end bamg_geometry.Vertices = np.vstack((bamg_geometry.Vertices, np.vstack((holei['x'][0:nods], holei['y'][0:nods], np.ones((nods)))).T)) bamg_geometry.Edges = np.vstack((bamg_geometry.Edges, np.vstack((np.arange(count + 1, count + nods + 1), np.hstack((np.arange(count + 2, count + nods + 1), count + 1)), 1. * np.ones((nods)))).T)) @@ -191,10 +188,10 @@ test = np.sum((subdomaini['x'][1:nods + 1] - subdomaini['x'][0:nods]) * (subdomaini['y'][1:nods + 1] + subdomaini['y'][0:nods])) if test > 0: - print('At least one subcontour was not correctly oriented and has been re - oriented') + print('At least one subcontour was not correctly oriented and has been re-oriented') subdomaini['x'] = np.flipud(subdomaini['x']) subdomaini['y'] = np.flipud(subdomaini['y']) #Add all points to bamg_geometry - nods = subdomaini['nods'] - 1 #the subdomain are closed 0 = end + nods = subdomaini['nods'] - 1 #the subdomain are closed 0 = end bamg_geometry.Vertices = np.vstack((bamg_geometry.Vertices, np.vstack((subdomaini['x'][0:nods], subdomaini['y'][0:nods], np.ones((nods)))).T)) bamg_geometry.Edges = np.vstack((bamg_geometry.Edges, np.vstack((np.arange(count + 1, count + nods + 1), np.hstack((np.arange(count + 2, count + nods + 1), count + 1)), 1. * np.ones((nods)))).T)) @@ -218,5 +215,4 @@ for i, rifti in enumerate(rift): - #detect whether all points of the rift are inside the domain flags = ContourToNodes(rifti['x'], rifti['y'], domain[0], 0)[0] @@ -227,5 +223,4 @@ #We LOTS of work to do print("Rift tip outside of or on the domain has been detected and is being processed...") - #check that only one point is outside (for now) if np.sum(np.logical_not(flags).astype(int)) != 1: @@ -255,5 +250,5 @@ #rift is crossing edge [i1 i2] of the domain - #Get coordinate of intersection point (http: / / mathworld.wolfram.com / Line - LineIntersection.html) + #Get coordinate of intersection point (http: / / mathworld.wolfram.com / Line-LineIntersection.html) x3 = domain[0]['x'][i1] y3 = domain[0]['y'][i1] @@ -285,5 +280,4 @@ np.hstack((np.arange(count + 1, count + nods).reshape(- 1, ), np.arange(count + 2, count + nods + 1).reshape(- 1, ), (1 + i) * np.ones((nods - 1, 1)))))) count += nods - break @@ -309,5 +303,4 @@ np.hstack((np.arange(count + 1, count + nods).reshape(- 1, ), np.arange(count + 2, count + nods + 1).reshape(- 1, ), (1 + i) * np.ones((nods - 1, 1)))))) count += nods - break @@ -327,7 +320,7 @@ track = np.hstack((A.x.reshape(- 1, ), A.y.reshape(- 1, ))) else: - track = float(track) #for some reason, it is of class "single" - if np.size(track, axis = 1) == 2: - track = np.hstack((track, 3. * np.ones((size(track, axis = 0), 1)))) + track = float(track) #for some reason, it is of class "single" + if np.size(track, axis=1) == 2: + track = np.hstack((track, 3. * np.ones((size(track, axis=0), 1)))) #only keep those inside @@ -336,7 +329,7 @@ #Add all points to bamg_geometry - nods = np.size(track, axis = 0) + nods = np.size(track, axis=0) bamg_geometry.Vertices = np.vstack((bamg_geometry.Vertices, track)) - bamg_geometry.Edges = np.vstack((bamg_geometry.Edges, np.hstack((np.arange(count + 1, count + nods).reshape(-1, ), np.arange(count + 2, count + nods + 1).reshape(-1, ), 3. * np.ones((nods - 1, 1)))))) + bamg_geometry.Edges = np.vstack((bamg_geometry.Edges, np.hstack((np.arange(count + 1, count + nods).reshape(- 1, ), np.arange(count + 2, count + nods + 1).reshape(- 1, ), 3. * np.ones((nods - 1, 1)))))) #update counter @@ -347,7 +340,7 @@ #recover RequiredVertices - requiredvertices = options.getfieldvalue('RequiredVertices') #for some reason, it is of class "single" - if np.size(requiredvertices, axis = 1) == 2: - requiredvertices = np.hstack((requiredvertices, 4. * np.ones((np.size(requiredvertices, axis = 0), 1)))) + requiredvertices = options.getfieldvalue('RequiredVertices') #for some reason, it is of class "single" + if np.size(requiredvertices, axis=1) == 2: + requiredvertices = np.hstack((requiredvertices, 4. * np.ones((np.size(requiredvertices, axis=0), 1)))) #only keep those inside @@ -355,5 +348,5 @@ requiredvertices = requiredvertices[np.nonzero(flags)[0], :] #Add all points to bamg_geometry - nods = np.size(requiredvertices, axis = 0) + nods = np.size(requiredvertices, axis=0) bamg_geometry.Vertices = np.vstack((bamg_geometry.Vertices, requiredvertices)) @@ -361,7 +354,6 @@ count += nods - #process geom - #bamg_geometry = processgeometry(bamg_geometry, options.getfieldvalue('tol', float(nan)), domain[0]) - + #process geom + #bamg_geometry = processgeometry(bamg_geometry, options.getfieldvalue('tol', float(nan)), domain[0]) elif isinstance(md.private.bamg, dict) and 'geometry' in md.private.bamg: bamg_geometry = bamggeom(md.private.bamg['geometry'].__dict__) @@ -386,5 +378,5 @@ bamg_options['anisomax'] = options.getfieldvalue('anisomax', 10.**18) bamg_options['coeff'] = options.getfieldvalue('coeff', 1.) - bamg_options['cutoff'] = options.getfieldvalue('cutoff', 10.**-5) + bamg_options['cutoff'] = options.getfieldvalue('cutoff', 10.**- 5) bamg_options['err'] = options.getfieldvalue('err', np.array([[0.01]])) bamg_options['errg'] = options.getfieldvalue('errg', 0.1) @@ -392,5 +384,5 @@ bamg_options['gradation'] = options.getfieldvalue('gradation', 1.5) bamg_options['Hessiantype'] = options.getfieldvalue('Hessiantype', 0) - bamg_options['hmin'] = options.getfieldvalue('hmin', 10.**-100) + bamg_options['hmin'] = options.getfieldvalue('hmin', 10.**- 100) bamg_options['hmax'] = options.getfieldvalue('hmax', 10.**100) bamg_options['hminVertices'] = options.getfieldvalue('hminVertices', np.empty((0, 1))) @@ -483,6 +475,5 @@ -def processgeometry(geom, tol, outline): # {{{ - +def processgeometry(geom, tol, outline): # {{{ raise RuntimeError("bamg.py / processgeometry is not complete.") #Deal with edges @@ -500,5 +491,5 @@ color1 = geom.Edges[i, 2] - j = i #test edges located AFTER i only + j = i #test edges located AFTER i only while (j < np.size(geom.Edges, axis=0)): #edge counter @@ -519,5 +510,5 @@ if SegIntersect(np.array([[x1, y1], [x2, y2]]), np.array([[x3, y3], [x4, y4]])): - #Get coordinate of intersection point (http: / / mathworld.wolfram.com / Line - LineIntersection.html) + #Get coordinate of intersection point (http: / / mathworld.wolfram.com / Line-LineIntersection.html) x = np.linalg.det(np.array([np.linalg.det(np.array([[x1, y1], [x2, y2]])), x1 - x2], [np.linalg.det(np.array([[x3, y3], [x4, y4]])), x3 - x4]) / np.linalg.det(np.array([[x1 - x2, y1 - y2], [x3 - x4, y3 - y4]]))) y = np.linalg.det(np.array([np.linalg.det(np.array([[x1, y1], [x2, y2]])), y1 - y2], [np.linalg.det(np.array([[x3, y3], [x4, y4]])), y3 - y4]) / np.linalg.det(np.array([[x1 - x2, y1 - y2], [x3 - x4, y3 - y4]]))) @@ -556,9 +547,9 @@ #Remove points from list of Vertices num += 1 - geom.Vertices[i, :]=[] + geom.Vertices[i, :] = [] #update edges posedges = np.nonzero(geom.Edges == i) - geom.Edges[posedges[0], :]=[] + geom.Edges[posedges[0], :] = [] posedges = np.nonzero(geom.Edges > i) geom.Edges[posedges] = geom.Edges[posedges] - 1 @@ -598,5 +589,5 @@ %Remove points from list of Vertices - geom.Vertices(j, :)=[] + geom.Vertices(j, :) = [] %update edges @@ -614,6 +605,6 @@ end %remove empty edges - geom.Edges(find(geom.Edges(:, 1) == geom.Edges(:, 2)), :)=[] + geom.Edges(find(geom.Edges(:, 1) == geom.Edges(:, 2)), :) = [] """ return geom -# }}} + # }}} Index: /issm/trunk-jpl/src/m/mesh/bamgflowband.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/bamgflowband.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/bamgflowband.py (revision 24213) @@ -1,3 +1,3 @@ -import numpy as np +import numpy as np from model import * from collections import OrderedDict @@ -5,43 +5,44 @@ from mesh2dvertical import * -def bamgflowband(md,x,surf,base,*args): - """ - BAMGFLOWBAND - create flowband mesh with bamg - Usage: - md=bamgflowband(md,x,surf,base,OPTIONS) +def bamgflowband(md, x, surf, base, *args): + """ + BAMGFLOWBAND - create flowband mesh with bamg - surf and bed are the surface elevation and base for each x provided - x must be increasing - OPTIONS are bamg options + Usage: + md = bamgflowband(md, x, surf, base, OPTIONS) - Example: - x =np.arrange(1,3001,100) - h=linspace(1000,300,numel(x)) - b=-917/1023*h - md=bamgflowband(model,b+h,b,'hmax',80,'vertical',1,'Markers',m) - """ + surf and bed are the surface elevation and base for each x provided + x must be increasing + OPTIONS are bamg options - #Write expfile with domain outline - A = OrderedDict() - A['x'] = np.concatenate((x,np.flipud(x),[x[0]])) - A['y'] = np.concatenate((base,np.flipud(surf),[base[0]])) - A['nods'] = np.size(A['x']) + Example: + x =np.arrange(1, 3001, 100) + h = linspace(1000, 300, numel(x)) + b= - 917 / 1023 * h + md = bamgflowband(model, b + h, b, 'hmax', 80, 'vertical', 1, 'Markers', m) + """ - #markers: - m = np.ones((np.size(A['x'])-1,)) # base = 1 - m[np.size(x) - 1] = 2 # right side = 2 - m[np.size(x):2 * np.size(x) - 1] = 3 # top surface = 3 - m[2 * np.size(x) - 1] = 4 # left side = 4 + #Write expfile with domain outline + A = OrderedDict() + A['x'] = np.concatenate((x, np.flipud(x), [x[0]])) + A['y'] = np.concatenate((base, np.flipud(surf), [base[0]])) + A['nods'] = np.size(A['x']) - #mesh domain - md = bamg(model(),'domain',[A],'vertical',1,'Markers',m,*args) - #print md.mesh.numberofvertices + #markers: + m = np.ones((np.size(A['x']) - 1, )) # base = 1 + m[np.size(x) - 1] = 2 # right side = 2 + m[np.size(x):2 * np.size(x) - 1] = 3 # top surface = 3 + m[2 * np.size(x) - 1] = 4 # left side = 4 - #Deal with vertices on bed - md.mesh.vertexonbase = np.zeros((md.mesh.numberofvertices,)) - md.mesh.vertexonbase[np.where(md.mesh.vertexflags(1))] = 1 - md.mesh.vertexonsurface = np.zeros((md.mesh.numberofvertices,)) - md.mesh.vertexonsurface[np.where(md.mesh.vertexflags(3))] = 1 + #mesh domain + md = bamg(model(), 'domain', [A], 'vertical', 1, 'Markers', m, *args) + #print md.mesh.numberofvertices - return md + #Deal with vertices on bed + md.mesh.vertexonbase = np.zeros((md.mesh.numberofvertices, )) + md.mesh.vertexonbase[np.where(md.mesh.vertexflags(1))] = 1 + md.mesh.vertexonsurface = np.zeros((md.mesh.numberofvertices, )) + md.mesh.vertexonsurface[np.where(md.mesh.vertexflags(3))] = 1 + + return md Index: /issm/trunk-jpl/src/m/mesh/meshconvert.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/meshconvert.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/meshconvert.py (revision 24213) @@ -1,52 +1,52 @@ import numpy as np from collections import OrderedDict -from BamgConvertMesh import BamgConvertMesh -from mesh2d import mesh2d +from BamgConvertMesh import BamgConvertMesh +from mesh2d import mesh2d from bamgmesh import bamgmesh from bamggeom import bamggeom -def meshconvert(md,*args): - """ - CONVERTMESH - convert mesh to bamg mesh - Usage: - md=meshconvert(md); - md=meshconvert(md,index,x,y); - """ +def meshconvert(md, *args): + """ + CONVERTMESH - convert mesh to bamg mesh - if not len(args)==0 and not len(args)==3: - raise TypeError("meshconvert error message: bad usage") + Usage: + md = meshconvert(md) + md = meshconvert(md, index, x, y) + """ - if not len(args): - index = md.mesh.elements - x = md.mesh.x - y = md.mesh.y - else: - index = args[0] - x = args[1] - y = args[2] + if not len(args) == 0 and not len(args) == 3: + raise TypeError("meshconvert error message: bad usage") - #call Bamg - bamgmesh_out,bamggeom_out=BamgConvertMesh(index,x,y) + if not len(args): + index = md.mesh.elements + x = md.mesh.x + y = md.mesh.y + else: + index = args[0] + x = args[1] + y = args[2] - # plug results onto model - md.private.bamg = OrderedDict() - md.private.bamg['mesh'] = bamgmesh(bamgmesh_out) - md.private.bamg['geometry'] = bamggeom(bamggeom_out) - md.mesh = mesh2d() - md.mesh.x = bamgmesh_out['Vertices'][:,0].copy() - md.mesh.y = bamgmesh_out['Vertices'][:,1].copy() - md.mesh.elements = bamgmesh_out['Triangles'][:,0:3].astype(int) - md.mesh.edges = bamgmesh_out['IssmEdges'].astype(int) - md.mesh.segments = bamgmesh_out['IssmSegments'][:,0:3].astype(int) - md.mesh.segmentmarkers = bamgmesh_out['IssmSegments'][:,3].astype(int) + #call Bamg + bamgmesh_out, bamggeom_out = BamgConvertMesh(index, x, y) - #Fill in rest of fields: - md.mesh.numberofelements = np.size(md.mesh.elements,axis=0) - md.mesh.numberofvertices = np.size(md.mesh.x) - md.mesh.numberofedges = np.size(md.mesh.edges,axis=0) - md.mesh.vertexonboundary = np.zeros(md.mesh.numberofvertices,bool) - md.mesh.vertexonboundary[md.mesh.segments[:,0:2]-1] = True + # plug results onto model + md.private.bamg = OrderedDict() + md.private.bamg['mesh'] = bamgmesh(bamgmesh_out) + md.private.bamg['geometry'] = bamggeom(bamggeom_out) + md.mesh = mesh2d() + md.mesh.x = bamgmesh_out['Vertices'][:, 0].copy() + md.mesh.y = bamgmesh_out['Vertices'][:, 1].copy() + md.mesh.elements = bamgmesh_out['Triangles'][:, 0:3].astype(int) + md.mesh.edges = bamgmesh_out['IssmEdges'].astype(int) + md.mesh.segments = bamgmesh_out['IssmSegments'][:, 0:3].astype(int) + md.mesh.segmentmarkers = bamgmesh_out['IssmSegments'][:, 3].astype(int) - return md + #Fill in rest of fields: + md.mesh.numberofelements = np.size(md.mesh.elements, axis=0) + md.mesh.numberofvertices = np.size(md.mesh.x) + md.mesh.numberofedges = np.size(md.mesh.edges, axis=0) + md.mesh.vertexonboundary = np.zeros(md.mesh.numberofvertices, bool) + md.mesh.vertexonboundary[md.mesh.segments[:, 0:2] - 1] = True + return md Index: /issm/trunk-jpl/src/m/mesh/planet/gmsh/gmshplanet.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/planet/gmsh/gmshplanet.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/planet/gmsh/gmshplanet.py (revision 24213) @@ -6,166 +6,166 @@ import subprocess -def gmshplanet(*varargin): -#GMSHPLANET - mesh generation for a sphere. Very specific code for gmsh. From demo/sphere.geo -# -# Available options (for more details see ISSM website http://issm.jpl.nasa.gov/): -# -# - radius: radius of the planet in km -# - resolution: resolution in km -# - refine: provide mesh -# - refinemetric: mesh quantity to specify resolution -# -# Returns 'mesh3dsurface' type mesh -# -# Examples: -# md.mesh=gmshplanet('radius',6000,'resolution',100); -# md.mesh=gmshplanet('radius',6000,'resolution',100); - #process options - options=pairoptions(*varargin) - #options=deleteduplicates(options,1) +def gmshplanet(* varargin): + #GMSHPLANET - mesh generation for a sphere. Very specific code for gmsh. From demo / sphere.geo + # + # Available options (for more details see ISSM website http: / / issm.jpl.nasa.gov / ): + # + # - radius: radius of the planet in km + # - resolution: resolution in km + # - refine: provide mesh + # - refinemetric: mesh quantity to specify resolution + # + # Returns 'mesh3dsurface' type mesh + # + # Examples: + # md.mesh = gmshplanet('radius', 6000, 'resolution', 100); + # md.mesh = gmshplanet('radius', 6000, 'resolution', 100); - #recover parameters: - radius=options.getfieldvalue('radius')*1000 - resolution=options.getfieldvalue('resolution')*1000 + #process options + options = pairoptions(* varargin) + #options = deleteduplicates(options, 1) - #initialize mesh: - mesh=mesh3dsurface() + #recover parameters: + radius = options.getfieldvalue('radius') * 1000 + resolution = options.getfieldvalue('resolution') * 1000 - #create .geo file: {{{ - fid=open('sphere.geo','w') + #initialize mesh: + mesh = mesh3dsurface() - fid.write('Mesh.Algorithm = 1;\n') - if options.exist('refine'): - fid.write('Mesh.Algorithm = 7;\n') - fid.write('Mesh.CharacteristicLengthFromPoints= 0;\n') - fid.write('Mesh.SmoothRatio= 3;\n') - fid.write('Mesh.RemeshAlgorithm= 1;\n') - fid.write('resolution=%g;\n'%resolution) - fid.write('radius=%g;\n'%radius) - fid.write('Point(1) = {0.0,0.0,0.0,resolution};\n') - fid.write('Point(2) = {radius,0.0,0.0,resolution};\n') - fid.write('Point(3) = {0,radius,0.0,resolution};\n') - fid.write('Circle(1) = {2,1,3};\n') - fid.write('Point(4) = {-radius,0,0.0,resolution};\n') - fid.write('Point(5) = {0,-radius,0.0,resolution};\n') - fid.write('Circle(2) = {3,1,4};\n') - fid.write('Circle(3) = {4,1,5};\n') - fid.write('Circle(4) = {5,1,2};\n') - fid.write('Point(6) = {0,0,-radius,resolution};\n') - fid.write('Point(7) = {0,0,radius,resolution};\n') - fid.write('Circle(5) = {3,1,6};\n') - fid.write('Circle(6) = {6,1,5};\n') - fid.write('Circle(7) = {5,1,7};\n') - fid.write('Circle(8) = {7,1,3};\n') - fid.write('Circle(9) = {2,1,7};\n') - fid.write('Circle(10) = {7,1,4};\n') - fid.write('Circle(11) = {4,1,6};\n') - fid.write('Circle(12) = {6,1,2};\n') - fid.write('Line Loop(13) = {2,8,-10};\n') - fid.write('Surface(14) = {13};\n') - fid.write('Line Loop(15) = {10,3,7};\n') - fid.write('Surface(16) = {15};\n') - fid.write('Line Loop(17) = {-8,-9,1};\n') - fid.write('Surface(18) = {17};\n') - fid.write('Line Loop(19) = {-11,-2,5};\n') - fid.write('Surface(20) = {19};\n') - fid.write('Line Loop(21) = {-5,-12,-1};\n') - fid.write('Surface(22) = {21};\n') - fid.write('Line Loop(23) = {-3,11,6};\n') - fid.write('Surface(24) = {23};\n') - fid.write('Line Loop(25) = {-7,4,9};\n') - fid.write('Surface(26) = {25};\n') - fid.write('Line Loop(27) = {-4,12,-6};\n') - fid.write('Surface(28) = {27};\n') - fid.write('Surface Loop(29) = {28,26,16,14,20,24,22,18};\n') - fid.write('Volume(30) = {29};\n') - fid.write('Physical Surface(1) = {28,26,16,14,20,24,22,18};\n') - fid.write('Physical Volume(2) = 30;\n') - fid.close() - #}}} + #create .geo file: {{{ + fid = open('sphere.geo', 'w') - if options.exist('refine'): - meshini=options.getfieldvalue('refine') - metric=options.getfieldvalue('refinemetric') + fid.write('Mesh.Algorithm = 1;\n') + if options.exist('refine'): + fid.write('Mesh.Algorithm = 7;\n') + fid.write('Mesh.CharacteristicLengthFromPoints= 0;\n') + fid.write('Mesh.SmoothRatio= 3;\n') + fid.write('Mesh.RemeshAlgorithm= 1;\n') + fid.write('resolution=%g;\n' % resolution) + fid.write('radius=%g;\n' % radius) + fid.write('Point(1) = {0.0, 0.0, 0.0, resolution};\n') + fid.write('Point(2) = {radius, 0.0, 0.0, resolution};\n') + fid.write('Point(3) = {0, radius, 0.0, resolution};\n') + fid.write('Circle(1) = {2, 1, 3};\n') + fid.write('Point(4) = { - radius, 0, 0.0, resolution};\n') + fid.write('Point(5) = {0, - radius, 0.0, resolution};\n') + fid.write('Circle(2) = {3, 1, 4};\n') + fid.write('Circle(3) = {4, 1, 5};\n') + fid.write('Circle(4) = {5, 1, 2};\n') + fid.write('Point(6) = {0, 0, - radius, resolution};\n') + fid.write('Point(7) = {0, 0, radius, resolution};\n') + fid.write('Circle(5) = {3, 1, 6};\n') + fid.write('Circle(6) = {6, 1, 5};\n') + fid.write('Circle(7) = {5, 1, 7};\n') + fid.write('Circle(8) = {7, 1, 3};\n') + fid.write('Circle(9) = {2, 1, 7};\n') + fid.write('Circle(10) = {7, 1, 4};\n') + fid.write('Circle(11) = {4, 1, 6};\n') + fid.write('Circle(12) = {6, 1, 2};\n') + fid.write('Line Loop(13) = {2, 8, - 10};\n') + fid.write('Surface(14) = {13};\n') + fid.write('Line Loop(15) = {10, 3, 7};\n') + fid.write('Surface(16) = {15};\n') + fid.write('Line Loop(17) = { - 8, - 9, 1};\n') + fid.write('Surface(18) = {17};\n') + fid.write('Line Loop(19) = { - 11, - 2, 5};\n') + fid.write('Surface(20) = {19};\n') + fid.write('Line Loop(21) = { - 5, - 12, - 1};\n') + fid.write('Surface(22) = {21};\n') + fid.write('Line Loop(23) = { - 3, 11, 6};\n') + fid.write('Surface(24) = {23};\n') + fid.write('Line Loop(25) = { - 7, 4, 9};\n') + fid.write('Surface(26) = {25};\n') + fid.write('Line Loop(27) = { - 4, 12, - 6};\n') + fid.write('Surface(28) = {27};\n') + fid.write('Surface Loop(29) = {28, 26, 16, 14, 20, 24, 22, 18};\n') + fid.write('Volume(30) = {29};\n') + fid.write('Physical Surface(1) = {28, 26, 16, 14, 20, 24, 22, 18};\n') + fid.write('Physical Volume(2) = 30;\n') + fid.close() + #}}} - #create .pos file with existing mesh and refining metric: {{{ - fid=open('sphere.pos','w') + if options.exist('refine'): + meshini = options.getfieldvalue('refine') + metric = options.getfieldvalue('refinemetric') - fid.write('View "background mesh" [;\n') - for i in range(meshini.numberofelements): - fid.write('ST(%g,%g,%g,%g,%g,%g,%g,%g,%g)[%g,%g,%g];\n', - meshini.x(meshini.elements(i,0)), meshini.y(meshini.elements(i,0)), meshini.z(meshini.elements(i,0)), - meshini.x(meshini.elements(i,1)), meshini.y(meshini.elements(i,1)), meshini.z(meshini.elements(i,1)), - meshini.x(meshini.elements(i,2)), meshini.y(meshini.elements(i,2)), meshini.z(meshini.elements(i,2)), - metric(meshini.elements(i,0)), metric(meshini.elements(i,1)), metric(meshini.elements(i,2))) - fid.write('];\n') - - fid.close() - # }}} + #create .pos file with existing mesh and refining metric: {{{ + fid = open('sphere.pos', 'w') - #call gmsh - if options.exist('refine'): - subprocess.call('gmsh -tol 1e-8 -2 sphere.geo -bgm sphere.pos',shell=True) - else: - #call gmsh - subprocess.call('gmsh -tol 1e-8 -2 sphere.geo',shell=True) + fid.write('View "background mesh" [;\n') + for i in range(meshini.numberofelements): + fid.write('ST(%g, %g, %g, %g, %g, %g, %g, %g, %g)[%g, %g, %g];\n', + meshini.x(meshini.elements(i, 0)), meshini.y(meshini.elements(i, 0)), meshini.z(meshini.elements(i, 0)), + meshini.x(meshini.elements(i, 1)), meshini.y(meshini.elements(i, 1)), meshini.z(meshini.elements(i, 1)), + meshini.x(meshini.elements(i, 2)), meshini.y(meshini.elements(i, 2)), meshini.z(meshini.elements(i, 2)), + metric(meshini.elements(i, 0)), metric(meshini.elements(i, 1)), metric(meshini.elements(i, 2))) + fid.write('];\n') + fid.close() + # }}} - #import mesh: {{{ - fid=open('sphere.msh','r') + #call gmsh + if options.exist('refine'): + subprocess.call('gmsh - tol 1e-8 - 2 sphere.geo - bgm sphere.pos', shell=True) + else: + #call gmsh + subprocess.call('gmsh - tol 1e-8 - 2 sphere.geo', shell=True) - #Get Mesh format - A=fid.readline().strip() - if not strcmp(A,'$MeshFormat'): - raise RuntimeError(['Expecting $MeshFormat (', A, ')']) + #import mesh: {{{ + fid = open('sphere.msh', 'r') - A=fid.readline().split() - A=fid.readline().strip() - if not strcmp(A,'$EndMeshFormat'): - raise RuntimeError(['Expecting $EndMeshFormat (', A, ')']) + #Get Mesh format + A = fid.readline().strip() + if not strcmp(A, '$MeshFormat'): + raise RuntimeError(['Expecting $MeshFormat (', A, ')']) - #Nodes - A=fid.readline().strip() - if not strcmp(A,'$Nodes'): - raise RuntimeError(['Expecting $Nodes (', A, ')']) + A = fid.readline().split() + A = fid.readline().strip() + if not strcmp(A, '$EndMeshFormat'): + raise RuntimeError(['Expecting $EndMeshFormat (', A, ')']) - mesh.numberofvertices=int(fid.readline().strip()) - mesh.x=np.empty(mesh.numberofvertices) - mesh.y=np.empty(mesh.numberofvertices) - mesh.z=np.empty(mesh.numberofvertices) - for i in range(mesh.numberofvertices): - A=fid.readline().split() - mesh.x[i]=float(A[1]) - mesh.y[i]=float(A[2]) - mesh.z[i]=float(A[3]) + #Nodes + A = fid.readline().strip() + if not strcmp(A, '$Nodes'): + raise RuntimeError(['Expecting $Nodes (', A, ')']) - A=fid.readline().strip() - if not strcmp(A,'$EndNodes'): - raise RuntimeError(['Expecting $EndNodes (', A, ')']) + mesh.numberofvertices = int(fid.readline().strip()) + mesh.x = np.empty(mesh.numberofvertices) + mesh.y = np.empty(mesh.numberofvertices) + mesh.z = np.empty(mesh.numberofvertices) + for i in range(mesh.numberofvertices): + A = fid.readline().split() + mesh.x[i] = float(A[1]) + mesh.y[i] = float(A[2]) + mesh.z[i] = float(A[3]) - #Elements - A=fid.readline().strip() - if not strcmp(A,'$Elements'): - raise RuntimeError(['Expecting $Elements (', A, ')']) - mesh.numberofelements=int(fid.readline().strip()) - mesh.elements=np.zeros([mesh.numberofelements,3]) - for i in range(mesh.numberofelements): - A=fid.readline().split() - mesh.elements[i]=[int(A[5]),int(A[6]),int(A[7])] - mesh.elements=mesh.elements.astype(int) - A=fid.readline().strip() - if not strcmp(A,'$EndElements'): - raise RuntimeError(['Expecting $EndElements (', A, ')']) - fid.close() - #}}} + A = fid.readline().strip() + if not strcmp(A, '$EndNodes'): + raise RuntimeError(['Expecting $EndNodes (', A, ')']) - #figure out other fields in mesh3dsurface: - mesh.r=np.sqrt(mesh.x**2+mesh.y**2+mesh.z**2) - mesh.lat=np.arcsin(mesh.z/mesh.r)/np.pi*180 - mesh.long=np.arctan2(mesh.y,mesh.x)/np.pi*180 + #Elements + A = fid.readline().strip() + if not strcmp(A, '$Elements'): + raise RuntimeError(['Expecting $Elements (', A, ')']) + mesh.numberofelements = int(fid.readline().strip()) + mesh.elements = np.zeros([mesh.numberofelements, 3]) + for i in range(mesh.numberofelements): + A = fid.readline().split() + mesh.elements[i] = [int(A[5]), int(A[6]), int(A[7])] + mesh.elements = mesh.elements.astype(int) + A = fid.readline().strip() + if not strcmp(A, '$EndElements'): + raise RuntimeError(['Expecting $EndElements (', A, ')']) + fid.close() + #}}} - #erase files: - subprocess.call('rm -rf sphere.geo sphere.msh sphere.pos',shell=True) + #figure out other fields in mesh3dsurface: + mesh.r = np.sqrt(mesh.x**2 + mesh.y**2 + mesh.z**2) + mesh.lat = np.arcsin(mesh.z / mesh.r) / np.pi * 180 + mesh.long = np.arctan2(mesh.y, mesh.x) / np.pi * 180 - #return mesh: - return mesh + #erase files: + subprocess.call('rm -rf sphere.geo sphere.msh sphere.pos', shell=True) + + #return mesh: + return mesh Index: /issm/trunk-jpl/src/m/mesh/rifts/meshprocessoutsiderifts.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/rifts/meshprocessoutsiderifts.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/rifts/meshprocessoutsiderifts.py (revision 24213) @@ -2,103 +2,104 @@ from ElementsFromEdge import ElementsFromEdge import MatlabFuncs as m +from ContourToMesh import ContourToMesh -def meshprocessoutsiderifts(md,domainoutline): - """ - MESHPROCESSOUTSIDERIFTS - process rifts when they touch the domain outline - Usage: - md=meshprocessoutsiderifts(md,domain) +def meshprocessoutsiderifts(md, domainoutline): + """ + MESHPROCESSOUTSIDERIFTS - process rifts when they touch the domain outline - """ + Usage: + md = meshprocessoutsiderifts(md, domain) - #go through rifts, and figure out which ones touch the domain outline - for rift in md.rifts.riftstruct: - - #first, flag nodes that belong to the domain outline - flags=ContourToMesh(md.mesh.elements,md.mesh.x,md.mesh.y,domainoutline,'node',0) + """ - tips=rift.tips - outsidetips=tips[np.nonzero(flags[rift.tips-1])[0]] + #go through rifts, and figure out which ones touch the domain outline + for rift in md.rifts.riftstruct: - #we have found outsidetips, tips that touch the domain outline. go through them - for tip in outsidetips: - - #find tip in the segments, take first segment (there should be 2) that holds tip, - #and node_connected_to_tip is the other node on this segment: - tipindex=np.nonzero(rift.segments[:,0]==tip)[0] - if tipindex: - tipindex=tipindex[0] - node_connected_to_tip=rift.segments[tipindex,1] - else: - tipindex=np.nonzero(rift.segments[:,1]==tip)[0] - tipindex=tipindex[0] - node_connected_to_tip=rift.segments[tipindex,1] + #first, flag nodes that belong to the domain outline + flags = ContourToMesh(md.mesh.elements, md.mesh.x, md.mesh.y, domainoutline, 'node', 0) - #ok, we have the tip node, and the first node connected to it, on the rift. Now, - #identify all the elements that are connected to the tip, and that are on the same - #side of the rift. - A=tip - B=node_connected_to_tip + tips = rift.tips + outsidetips = tips[np.nonzero(flags[rift.tips - 1])[0]] - elements=np.empty(0,int) + #we have found outsidetips, tips that touch the domain outline. go through them + for tip in outsidetips: + #find tip in the segments, take first segment (there should be 2) that holds tip, + #and node_connected_to_tip is the other node on this segment: + tipindex = np.nonzero(rift.segments[:, 0] == tip)[0] + if tipindex: + tipindex = tipindex[0] + node_connected_to_tip = rift.segments[tipindex, 1] + else: + tipindex = np.nonzero(rift.segments[:, 1] == tip)[0] + tipindex = tipindex[0] + node_connected_to_tip = rift.segments[tipindex, 1] - while flags(B): #as long as B does not belong to the domain outline, keep looking. - #detect elements on edge A,B: - edgeelements=ElementsFromEdge(md.mesh.elements,A,B) - #rule out those we already detected - already_detected=m.ismember(edgeelements,elements) - nextelement=edgeelements(np.nonzero(np.logical_not(already_detected))[0]) - #add new detected element to the list of elements we are looking for. - elements=np.concatenate((elements,nextelement)) - #new B: - B=md.mesh.elements[nextelement-1,np.nonzero(np.logical_not(m.ismember(md.mesh.elements[nextelement-1,:],np.array([A,B]))))] - - #take the list of elements on one side of the rift that connect to the tip, - #and duplicate the tip on them, so as to open the rift to the outside. - num=np.size(md.mesh.x)+1 - md.mesh.x=np.concatenate((md.mesh.x,md.mesh.x[tip])) - md.mesh.y=np.concatenate((md.mesh.y,md.mesh.y[tip])) - md.mesh.numberofvertices=num - - #replace tip in elements - newelements=md.mesh.elements[elements-1,:] - pos=np.nonzero(newelements==tip) - newelements[pos]=num - md.mesh.elements[elements-1,:]=newelements - rift.tips=np.concatenate((rift.tips,num)) + #ok, we have the tip node, and the first node connected to it, on the rift. Now, + #identify all the elements that are connected to the tip, and that are on the same + #side of the rift. + A = tip + B = node_connected_to_tip - #deal with segments - tipsegments=np.nonzero(np.logical_or(md.mesh.segments[:,0]==tip,md.mesh.segments[:,1]==tip))[0] - for segment_index in tipsegments: - pos=np.nonzero(md.mesh.segments[segment_index,0:2]!=tip)[0] - other_node=md.mesh.segments[segment_index,pos] - if not isconnected(md.mesh.elements,other_node,tip): - pos=np.nonzero(md.mesh.segments[segment_index,0:2]==tip)[0] - md.mesh.segments[segment_index,pos]=num + elements = np.empty(0, int) - #Fill in rest of fields: - md.mesh.numberofelements=np.size(md.mesh.elements,axis=0) - md.mesh.numberofvertices=np.size(md.mesh.x) - md.mesh.vertexonboundary=np.zeros(np.size(md.mesh.x),bool) - md.mesh.vertexonboundary[md.mesh.segments[:,0:2]-1]=True - md.rifts.numrifts=length(md.rifts.riftstruct) + while flags(B): #as long as B does not belong to the domain outline, keep looking. + #detect elements on edge A, B: + edgeelements = ElementsFromEdge(md.mesh.elements, A, B) + #rule out those we already detected + already_detected = m.ismember(edgeelements, elements) + nextelement = edgeelements(np.nonzero(np.logical_not(already_detected))[0]) + #add new detected element to the list of elements we are looking for. + elements = np.concatenate((elements, nextelement)) + #new B: + B = md.mesh.elements[nextelement - 1, np.nonzero(np.logical_not(m.ismember(md.mesh.elements[nextelement - 1, :], np.array([A, B]))))] - return md + #take the list of elements on one side of the rift that connect to the tip, + #and duplicate the tip on them, so as to open the rift to the outside. + num = np.size(md.mesh.x) + 1 + md.mesh.x = np.concatenate((md.mesh.x, md.mesh.x[tip])) + md.mesh.y = np.concatenate((md.mesh.y, md.mesh.y[tip])) + md.mesh.numberofvertices = num -def isconnected(elements,A,B): # {{{ - """ - ISCONNECTED: are two nodes connected by a triangulation? + #replace tip in elements + newelements = md.mesh.elements[elements - 1, :] + pos = np.nonzero(newelements == tip) + newelements[pos] = num + md.mesh.elements[elements - 1, :] = newelements + rift.tips = np.concatenate((rift.tips, num)) - Usage: flag=isconnected(elements,A,B) + #deal with segments + tipsegments = np.nonzero(np.logical_or(md.mesh.segments[:, 0] == tip, md.mesh.segments[:, 1] == tip))[0] + for segment_index in tipsegments: + pos = np.nonzero(md.mesh.segments[segment_index, 0:2] != tip)[0] + other_node = md.mesh.segments[segment_index, pos] + if not isconnected(md.mesh.elements, other_node, tip): + pos = np.nonzero(md.mesh.segments[segment_index, 0:2] == tip)[0] + md.mesh.segments[segment_index, pos] = num - """ + #Fill in rest of fields: + md.mesh.numberofelements = np.size(md.mesh.elements, axis=0) + md.mesh.numberofvertices = np.size(md.mesh.x) + md.mesh.vertexonboundary = np.zeros(np.size(md.mesh.x), bool) + md.mesh.vertexonboundary[md.mesh.segments[:, 0:2] - 1] = True + md.rifts.numrifts = np.length(md.rifts.riftstruct) - elements=ElementsFromEdge(elements,A,B) - if not elements: - flag=0 - else: - flag=1 + return md - return flag - # }}} +def isconnected(elements, A, B): # {{{ + """ + ISCONNECTED: are two nodes connected by a triangulation? + + Usage: flag = isconnected(elements, A, B) + + """ + + elements = ElementsFromEdge(elements, A, B) + if not elements: + flag = 0 + else: + flag = 1 + + return flag + # }}} Index: /issm/trunk-jpl/src/m/mesh/rifts/meshprocessrifts.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/rifts/meshprocessrifts.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/rifts/meshprocessrifts.py (revision 24213) @@ -5,60 +5,59 @@ from GetAreas import GetAreas -def meshprocessrifts(md,domainoutline): - """ - MESHPROCESSRIFTS - process mesh when rifts are present - split rifts inside mesh (rifts are defined by presence of - segments inside the domain outline) - if domain outline is provided, check for rifts that could touch it, and open them up. +def meshprocessrifts(md, domainoutline): + """ + MESHPROCESSRIFTS - process mesh when rifts are present - Usage: - md=meshprocessrifts(md,domainoutline) + split rifts inside mesh (rifts are defined by presence of + segments inside the domain outline) + if domain outline is provided, check for rifts that could touch it, and open them up. - Ex: - md=meshprocessrifts(md,'DomainOutline.exp'); - - """ + Usage: + md = meshprocessrifts(md, domainoutline) - #Call MEX file - md.mesh.elements,md.mesh.x,md.mesh.y,md.mesh.segments,md.mesh.segmentmarkers,md.rifts.riftstruct=ProcessRifts(md.mesh.elements,md.mesh.x,md.mesh.y,md.mesh.segments,md.mesh.segmentmarkers) - md.mesh.elements=md.mesh.elements.astype(int) - md.mesh.x=md.mesh.x.reshape(-1) - md.mesh.y=md.mesh.y.reshape(-1) - md.mesh.segments=md.mesh.segments.astype(int) - md.mesh.segmentmarkers=md.mesh.segmentmarkers.astype(int) - if not isinstance(md.rifts.riftstruct,list) or not md.rifts.riftstruct: - raise RuntimeError("ProcessRifts did not find any rift") + Ex: + md = meshprocessrifts(md, 'DomainOutline.exp') - #Fill in rest of fields: - numrifts=len(md.rifts.riftstruct) - md.mesh.numberofelements=np.size(md.mesh.elements,axis=0) - md.mesh.numberofvertices=np.size(md.mesh.x) - md.mesh.vertexonboundary=np.zeros(np.size(md.mesh.x),bool) - md.mesh.vertexonboundary[md.mesh.segments[:,0:2]-1]=True + """ - #get coordinates of rift tips - for rift in md.rifts.riftstruct: - rift['tip1coordinates']=np.hstack((md.mesh.x[rift['tips'][0,0].astype(int)-1].reshape(-1,),md.mesh.y[rift['tips'][0,0].astype(int)-1].reshape(-1,))) - rift['tip2coordinates']=np.hstack((md.mesh.x[rift['tips'][0,1].astype(int)-1].reshape(-1,),md.mesh.y[rift['tips'][0,1].astype(int)-1].reshape(-1,))) + #Call MEX file + md.mesh.elements, md.mesh.x, md.mesh.y, md.mesh.segments, md.mesh.segmentmarkers, md.rifts.riftstruct = ProcessRifts(md.mesh.elements, md.mesh.x, md.mesh.y, md.mesh.segments, md.mesh.segmentmarkers) + md.mesh.elements = md.mesh.elements.astype(int) + md.mesh.x = md.mesh.x.reshape(- 1) + md.mesh.y = md.mesh.y.reshape(- 1) + md.mesh.segments = md.mesh.segments.astype(int) + md.mesh.segmentmarkers = md.mesh.segmentmarkers.astype(int) + if not isinstance(md.rifts.riftstruct, list) or not md.rifts.riftstruct: + raise RuntimeError("ProcessRifts did not find any rift") - #In case we have rifts that open up the domain outline, we need to open them: - flags=ContourToMesh(md.mesh.elements,md.mesh.x,md.mesh.y,domainoutline,'node',0) - found=0 - for rift in md.rifts.riftstruct: - if flags[rift['tips'][0,0].astype(int)-1]==0: - found=1 - break - if flags[rift['tips'][0,1].astype(int)-1]==0: - found=1 - break - if found: - md=meshprocessoutsiderifts(md,domainoutline) + #Fill in rest of fields: + md.mesh.numberofelements = np.size(md.mesh.elements, axis=0) + md.mesh.numberofvertices = np.size(md.mesh.x) + md.mesh.vertexonboundary = np.zeros(np.size(md.mesh.x), bool) + md.mesh.vertexonboundary[md.mesh.segments[:, 0:2] - 1] = True - #get elements that are not correctly oriented in the correct direction: - aires=GetAreas(md.mesh.elements,md.mesh.x,md.mesh.y) - pos=np.nonzero(aires<0)[0] - md.mesh.elements[pos,:]=np.vstack((md.mesh.elements[pos,1],md.mesh.elements[pos,0],md.mesh.elements[pos,2])).T + #get coordinates of rift tips + for rift in md.rifts.riftstruct: + rift['tip1coordinates'] = np.hstack((md.mesh.x[rift['tips'][0, 0].astype(int) - 1].reshape(- 1, ), md.mesh.y[rift['tips'][0, 0].astype(int) - 1].reshape(- 1, ))) + rift['tip2coordinates'] = np.hstack((md.mesh.x[rift['tips'][0, 1].astype(int) - 1].reshape(- 1, ), md.mesh.y[rift['tips'][0, 1].astype(int) - 1].reshape(- 1, ))) - return md + #In case we have rifts that open up the domain outline, we need to open them: + flags = ContourToMesh(md.mesh.elements, md.mesh.x, md.mesh.y, domainoutline, 'node', 0) + found = 0 + for rift in md.rifts.riftstruct: + if flags[rift['tips'][0, 0].astype(int) - 1] == 0: + found = 1 + break + if flags[rift['tips'][0, 1].astype(int) - 1] == 0: + found = 1 + break + if found: + md = meshprocessoutsiderifts(md, domainoutline) + #get elements that are not correctly oriented in the correct direction: + aires = GetAreas(md.mesh.elements, md.mesh.x, md.mesh.y) + pos = np.nonzero(aires < 0)[0] + md.mesh.elements[pos, :] = np.vstack((md.mesh.elements[pos, 1], md.mesh.elements[pos, 0], md.mesh.elements[pos, 2])).T + + return md Index: /issm/trunk-jpl/src/m/mesh/roundmesh.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/roundmesh.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/roundmesh.py (revision 24213) @@ -5,4 +5,5 @@ from triangle import triangle + def roundmesh(md, radius, resolution): """ @@ -10,9 +11,9 @@ This script will generate a structured round mesh - - radius : specifies the radius of the circle in meters - - resolution : specifies the resolution in meters + - radius : specifies the radius of the circle in meters + - resolution : specifies the resolution in meters Usage: - md=roundmesh(md,radius,resolution) + md = roundmesh(md, radius, resolution) """ @@ -20,5 +21,5 @@ #Get number of points on the circle - pointsonedge = np.floor((2. * np.pi * radius) / resolution) + 1 #+1 to close the outline + pointsonedge = np.floor((2. * np.pi * radius) / resolution) + 1 # + 1 to close the outline #Calculate the cartesians coordinates of the points @@ -30,11 +31,9 @@ A['y'] = [y_list] A['density'] = 1. - print('now writing mesh') expwrite(A, 'RoundDomainOutline.exp') #Call Bamg - print('now meshing') md = triangle(md, 'RoundDomainOutline.exp', resolution) - #md = bamg(md,'domain','RoundDomainOutline.exp','hmin',resolution) + #md = bamg(md, 'domain', 'RoundDomainOutline.exp', 'hmin', resolution) #move the closest node to the center Index: /issm/trunk-jpl/src/m/mesh/squaremesh.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/squaremesh.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/squaremesh.py (revision 24213) @@ -1,76 +1,77 @@ import numpy as np from NodeConnectivity import NodeConnectivity -from ElementConnectivity import ElementConnectivity +from ElementConnectivity import ElementConnectivity from mesh2d import mesh2d -def squaremesh(md,Lx,Ly,nx,ny): - """ - SQUAREMESH - create a structured square mesh - This script will generate a structured square mesh - Lx and Ly are the dimension of the domain (in meters) - nx anx ny are the number of nodes in the x and y direction - The coordinates x and y returned are in meters. +def squaremesh(md, Lx, Ly, nx, ny): + """ + SQUAREMESH - create a structured square mesh - Usage: - [md]=squaremesh(md,Lx,Ly,nx,ny) - """ + This script will generate a structured square mesh + Lx and Ly are the dimension of the domain (in meters) + nx anx ny are the number of nodes in the x and y direction + The coordinates x and y returned are in meters. - #get number of elements and number of nodes - nel=(nx-1)*(ny-1)*2 - nods=nx*ny + Usage: + [md] = squaremesh(md, Lx, Ly, nx, ny) + """ - #initialization - index=np.zeros((nel,3),int) - x=np.zeros((nx*ny)) - y=np.zeros((nx*ny)) + #get number of elements and number of nodes + nel = (nx - 1) * (ny - 1) * 2 + nods = nx * ny - #create coordinates - for n in range(0,nx): - for m in range(0,ny): - x[n*ny+m]=float(n) - y[n*ny+m]=float(m) + #initialization + index = np.zeros((nel, 3), int) + x = np.zeros((nx * ny)) + y = np.zeros((nx * ny)) - #create index - for n in range(0,nx-1): - for m in range(0,ny-1): - A=n*ny+(m+1) - B=A+1 - C=(n+1)*ny+(m+1) - D=C+1 - index[n*(ny-1)*2+2*m,:]=[A,C,B] - index[n*(ny-1)*2+2*(m+1)-1,:]=[B,C,D] + #create coordinates + for n in range(0, nx): + for m in range(0, ny): + x[n * ny + m] = float(n) + y[n * ny + m] = float(m) - #Scale x and y - x=x/np.max(x)*Lx - y=y/np.max(y)*Ly + #create index + for n in range(0, nx - 1): + for m in range(0, ny - 1): + A = n * ny + (m + 1) + B = A + 1 + C = (n + 1) * ny + (m + 1) + D = C + 1 + index[n * (ny - 1) * 2 + 2 * m, :] = [A, C, B] + index[n * (ny - 1) * 2 + 2 * (m + 1) - 1, :] = [B, C, D] - #create segments - segments=np.zeros((2*(nx-1)+2*(ny-1),3),int) - #left edge: - segments[0:ny-1,:]=np.vstack((np.arange(2,ny+1),np.arange(1,ny),(2*np.arange(1,ny)-1))).T - #right edge: - segments[ny-1:2*(ny-1),:]=np.vstack((np.arange(ny*(nx-1)+1,nx*ny),np.arange(ny*(nx-1)+2,nx*ny+1),2*np.arange((ny-1)*(nx-2)+1,(nx-1)*(ny-1)+1))).T - #front edge: - segments[2*(ny-1):2*(ny-1)+(nx-1),:]=np.vstack((np.arange(2*ny,ny*nx+1,ny),np.arange(ny,ny*(nx-1)+1,ny),np.arange(2*(ny-1),2*(nx-1)*(ny-1)+1,2*(ny-1)))).T - #back edge - segments[2*(ny-1)+(nx-1):2*(nx-1)+2*(ny-1),:]=np.vstack((np.arange(1,(nx-2)*ny+2,ny),np.arange(ny+1,ny*(nx-1)+2,ny),np.arange(1,2*(nx-2)*(ny-1)+2,2*(ny-1)))).T + #Scale x and y + x = x / np.max(x) * Lx + y = y / np.max(y) * Ly - #plug coordinates and nodes - md.mesh=mesh2d() - md.mesh.x=x - md.mesh.y=y - md.mesh.numberofvertices=nods - md.mesh.vertexonboundary=np.zeros((nods),bool) - md.mesh.vertexonboundary[segments[:,0:2]-1]=True + #create segments + segments = np.zeros((2 * (nx - 1) + 2 * (ny - 1), 3), int) + #left edge: + segments[0:ny - 1, :] = np.vstack((np.arange(2, ny + 1), np.arange(1, ny), (2 * np.arange(1, ny) - 1))).T + #right edge: + segments[ny - 1:2 * (ny - 1), :] = np.vstack((np.arange(ny * (nx - 1) + 1, nx * ny), np.arange(ny * (nx - 1) + 2, nx * ny + 1), 2 * np.arange((ny - 1) * (nx - 2) + 1, (nx - 1) * (ny - 1) + 1))).T + #front edge: + segments[2 * (ny - 1):2 * (ny - 1) + (nx - 1), :] = np.vstack((np.arange(2 * ny, ny * nx + 1, ny), np.arange(ny, ny * (nx - 1) + 1, ny), np.arange(2 * (ny - 1), 2 * (nx - 1) * (ny - 1) + 1, 2 * (ny - 1)))).T + #back edge + segments[2 * (ny - 1) + (nx - 1):2 * (nx - 1) + 2 * (ny - 1), :] = np.vstack((np.arange(1, (nx - 2) * ny + 2, ny), np.arange(ny + 1, ny * (nx - 1) + 2, ny), np.arange(1, 2 * (nx - 2) * (ny - 1) + 2, 2 * (ny - 1)))).T - #plug elements - md.mesh.elements=index - md.mesh.segments=segments - md.mesh.numberofelements=nel + #plug coordinates and nodes + md.mesh = mesh2d() + md.mesh.x = x + md.mesh.y = y + md.mesh.numberofvertices = nods + md.mesh.vertexonboundary = np.zeros((nods), bool) + md.mesh.vertexonboundary[segments[:, 0:2] - 1] = True - #Now, build the connectivity tables for this mesh. - md.mesh.vertexconnectivity=NodeConnectivity(md.mesh.elements,md.mesh.numberofvertices)[0] - md.mesh.elementconnectivity=ElementConnectivity(md.mesh.elements,md.mesh.vertexconnectivity)[0] + #plug elements + md.mesh.elements = index + md.mesh.segments = segments + md.mesh.numberofelements = nel - return md + #Now, build the connectivity tables for this mesh. + md.mesh.vertexconnectivity = NodeConnectivity(md.mesh.elements, md.mesh.numberofvertices)[0] + md.mesh.elementconnectivity = ElementConnectivity(md.mesh.elements, md.mesh.vertexconnectivity)[0] + + return md Index: /issm/trunk-jpl/src/m/mesh/triangle.py =================================================================== --- /issm/trunk-jpl/src/m/mesh/triangle.py (revision 24212) +++ /issm/trunk-jpl/src/m/mesh/triangle.py (revision 24213) @@ -17,14 +17,14 @@ Usage: - md=triangle(md,domainname,resolution) - or md=triangle(md,domainname, resolution, riftname) + md = triangle(md, domainname, resolution) + or md = triangle(md, domainname, resolution, riftname) Examples: - md=triangle(md,'DomainOutline.exp',1000); - md=triangle(md,'DomainOutline.exp',1000,'Rifts.exp'); + md = triangle(md, 'DomainOutline.exp', 1000) + md = triangle(md, 'DomainOutline.exp', 1000, 'Rifts.exp') """ #Figure out a characteristic area. Resolution is a node oriented concept (ex a 1000m resolution node would - #be made of 1000*1000 area squares). + #be made of 1000 * 1000 area squares). if len(args) == 1: @@ -37,5 +37,5 @@ #Check that mesh was not already run, and warn user: if md.mesh.numberofelements: - choice = eval(input('This model already has a mesh. Are you sure you want to go ahead? (y/n)')) + choice = input('This model already has a mesh. Are you sure you want to go ahead? (y / n)') if choice not in ['y', 'n']: print("bad answer try you should use 'y' or 'n' ... exiting") Index: /issm/trunk-jpl/src/m/miscellaneous/MatlabFuncs.py =================================================================== --- /issm/trunk-jpl/src/m/miscellaneous/MatlabFuncs.py (revision 24212) +++ /issm/trunk-jpl/src/m/miscellaneous/MatlabFuncs.py (revision 24213) @@ -1,106 +1,115 @@ def oshostname(): - import socket + import socket - return socket.gethostname() + return socket.gethostname() + def ispc(): - import platform + import platform - if 'Windows' in platform.system(): - return True - else: - return False + if 'Windows' in platform.system(): + return True + else: + return False + def ismac(): - import platform + import platform - if 'Darwin' in platform.system(): - return True - else: - return False + if 'Darwin' in platform.system(): + return True + else: + return False -def strcmp(s1,s2): - if s1 == s2: - return True - else: - return False +def strcmp(s1, s2): -def strncmp(s1,s2,n): + if s1 == s2: + return True + else: + return False - if s1[0:n] == s2[0:n]: - return True - else: - return False -def strcmpi(s1,s2): +def strncmp(s1, s2, n): - if s1.lower() == s2.lower(): - return True - else: - return False + if s1[0:n] == s2[0:n]: + return True + else: + return False -def strncmpi(s1,s2,n): - if s1.lower()[0:n] == s2.lower()[0:n]: - return True - else: - return False +def strcmpi(s1, s2): -def ismember(a,s): - import numpy as np + if s1.lower() == s2.lower(): + return True + else: + return False - if not isinstance(s,(tuple,list,dict,np.ndarray)): - s=[s] - if not isinstance(a,(tuple,list,dict,np.ndarray)): - a=[a] +def strncmpi(s1, s2, n): - if not isinstance(a,np.ndarray): - b=[item in s for item in a] + if s1.lower()[0:n] == s2.lower()[0:n]: + return True + else: + return False - else: - if not isinstance(s,np.ndarray): - b=np.empty_like(a) - for i,item in enumerate(a.flat): - b.flat[i]=item in s - else: - b=np.in1d(a.flat,s.flat).reshape(a.shape) - return b +def ismember(a, s): + import numpy as np + + if not isinstance(s, (tuple, list, dict, np.ndarray)): + s = [s] + + if not isinstance(a, (tuple, list, dict, np.ndarray)): + a = [a] + + if not isinstance(a, np.ndarray): + b = [item in s for item in a] + + else: + if not isinstance(s, np.ndarray): + b = np.empty_like(a) + for i, item in enumerate(a.flat): + b.flat[i] = item in s + else: + b = np.in1d(a.flat, s.flat).reshape(a.shape) + + return b + def det(a): - import numpy as np - if a.shape==(1,): - return a[0] - elif a.shape==(1,1): - return a[0,0] - elif a.shape==(2,2): - return a[0,0]*a[1,1]-a[0,1]*a[1,0] - else: - raise TypeError("MatlabFunc.det only implemented for shape (2, 2), not for shape %s." % str(a.shape)) + if a.shape == (1, ): + return a[0] + elif a.shape == (1, 1): + return a[0, 0] + elif a.shape == (2, 2): + return a[0, 0] * a[1, 1] - a[0, 1] * a[1, 0] + else: + raise TypeError("MatlabFunc.det only implemented for shape (2, 2), not for shape %s." % str(a.shape)) -def sparse(ivec,jvec,svec,m=0,n=0,nzmax=0): - import numpy as np - if not m: - m=np.max(ivec) - if not n: - n=np.max(jvec) +def sparse(ivec, jvec, svec, m=0, n=0, nzmax=0): + import numpy as np - a=np.zeros((m,n)) + if not m: + m = np.max(ivec) + if not n: + n = np.max(jvec) - for i,j,s in zip(ivec.reshape(-1,order='F'),jvec.reshape(-1,order='F'),svec.reshape(-1,order='F')): - a[i-1,j-1]+=s + a = np.zeros((m, n)) - return a + for i, j, s in zip(ivec.reshape(-1, order='F'), jvec.reshape(-1, order='F'), svec.reshape(-1, order='F')): + a[i - 1, j - 1] += s + + return a + def heaviside(x): - import numpy as np + import numpy as np - y=np.zeros_like(x) - y[np.nonzero(x> 0.)]=1. - y[np.nonzero(x==0.)]=0.5 + y = np.zeros_like(x) + y[np.nonzero(x > 0.)] = 1. + y[np.nonzero(x == 0.)] = 0.5 - return y + return y Index: /issm/trunk-jpl/src/m/miscellaneous/PythonFuncs.py =================================================================== --- /issm/trunk-jpl/src/m/miscellaneous/PythonFuncs.py (revision 24212) +++ /issm/trunk-jpl/src/m/miscellaneous/PythonFuncs.py (revision 24213) @@ -1,24 +1,25 @@ import numpy as np -def logical_and_n(*arg): - - if len(arg): - result=arg[0] - for item in arg[1:]: - result=logical_and(result,item) - return result - else: - return None +def logical_and_n(* arg): -def logical_or_n(*arg): - - if len(arg): - result=arg[0] - for item in arg[1:]: - result=logical_or(result,item) - return result + if len(arg): + result = arg[0] + for item in arg[1:]: + result = np.logical_and(result, item) + return result - else: - return None + else: + return None + +def logical_or_n(* arg): + + if len(arg): + result = arg[0] + for item in arg[1:]: + result = np.logical_or(result, item) + return result + + else: + return None Index: /issm/trunk-jpl/src/m/miscellaneous/fielddisplay.py =================================================================== --- /issm/trunk-jpl/src/m/miscellaneous/fielddisplay.py (revision 24212) +++ /issm/trunk-jpl/src/m/miscellaneous/fielddisplay.py (revision 24213) @@ -1,140 +1,142 @@ -#Module import import numpy as np -from math import isnan import MatlabFuncs as m -def fielddisplay(md,name,comment): - """ - FIELDDISPLAY - display model field - Usage: - fielddisplay(md,name,comment) - """ +def fielddisplay(md, name, comment): + """ + FIELDDISPLAY - display model field - #get field - field=getattr(md,name) + Usage: + fielddisplay(md, name, comment) + """ - #disp corresponding line as a function of field type (offset set as 9 spaces) - return parsedisplay(" ",name,field,comment); + #get field + field = getattr(md, name) -def parsedisplay(offset,name,field,comment): # {{{ + #disp corresponding line as a function of field type (offset set as 9 spaces) + return parsedisplay(" ", name, field, comment) - #string - if isinstance(field,str): - if len(field)>30: - string=displayunit(offset,name,"not displayed",comment) - else: - string=displayunit(offset,name,"'%s'" % field,comment) +def parsedisplay(offset, name, field, comment): # {{{ - #numeric - elif isinstance(field,(int,float)): - string=displayunit(offset,name,str(field),comment) + #string + if isinstance(field, str): - #matrix - elif isinstance(field,np.ndarray): - string=displayunit(offset,name,str(field.shape),comment) + if len(field) > 30: + string = displayunit(offset, name, "not displayed", comment) + else: + string = displayunit(offset, name, "'%s'" % field, comment) - #logical - elif isinstance(field,bool): - if field: - string=displayunit(offset,name,"True",comment) - else: - string=displayunit(offset,name,"False",comment) - - #dictionary - elif isinstance(field,dict): - string=dict_display(offset,name,field,comment) + #numeric + elif isinstance(field, (int, float)): + string = displayunit(offset, name, str(field), comment) - #list or tuple - elif isinstance(field,(list,tuple)): - string=list_display(offset,name,field,comment) + #matrix + elif isinstance(field, np.ndarray): + string = displayunit(offset, name, str(field.shape), comment) - #None - elif field is None: - string=displayunit(offset,name,"None",comment) + #logical + elif isinstance(field, bool): + if field: + string = displayunit(offset, name, "True", comment) + else: + string = displayunit(offset, name, "False", comment) - else: - string=displayunit(offset,name,"not displayed",comment) - - return string - # }}} + #dictionary + elif isinstance(field, dict): + string = dict_display(offset, name, field, comment) -def dict_display(offset,name,field,comment): # {{{ + #list or tuple + elif isinstance(field, (list, tuple)): + string = list_display(offset, name, field, comment) - if field: - string =displayunit(offset,name,'{dictionary}',comment)+'\n' - offset+=' ' + #None + elif field is None: + string = displayunit(offset, name, "None", comment) - for structure_field,sfield in list(field.items()): - string+=parsedisplay(offset,str(structure_field),sfield,'')+'\n' + else: + string = displayunit(offset, name, "not displayed", comment) - if string and string[-1]=='\n': - string=string[:-1] + return string + # }}} - else: - string=displayunit(offset,name,'N/A',comment) - return string - # }}} +def dict_display(offset, name, field, comment): # {{{ -def list_display(offset,name,field,comment): # {{{ + if field: + string = displayunit(offset, name, '{dictionary}', comment) + '\n' + offset += ' ' - #initialization - if isinstance(field,list): - sbeg='[' - send=']' - elif isinstance(field,tuple): - sbeg='(' - send=')' - string=sbeg + for structure_field, sfield in list(field.items()): + string += parsedisplay(offset, str(structure_field), sfield, '') + '\n' - #go through the cell and fill string - if len(field)<5: - for fieldi in field: - if isinstance(fieldi,str): - string+="'%s'," % fieldi - elif isinstance(fieldi,(bool,int,float)): - string+="%s," % str(fieldi) - else: - string=sbeg - break + if string and string[-1] == '\n': + string = string[:-1] - if m.strcmp(string,sbeg): - string="%s%dx1%s" % (sbeg,len(field),send) - else: - string=string[:-1]+send + else: + string = displayunit(offset, name, 'N/A', comment) - #call displayunit - return displayunit(offset,name,string,comment) - # }}} + return string + # }}} -def displayunit(offset,name,characterization,comment): # {{{ - #take care of name - if len(name)>23: - name="%s..." % name[:20] - - #take care of characterization - if m.strcmp(characterization,"''") or m.strcmp(characterization,'""') or m.strcmpi(characterization,'nan'): - characterization="N/A" - - if len(characterization)>15: - characterization="%s..." % characterization[:12] - - #print - if not comment: - string="%s%-23s: %-15s" % (offset,name,characterization) - else: - if isinstance(comment,str): - string="%s%-23s: %-15s -- %s" % (offset,name,characterization,comment) - elif isinstance(comment,list): - string="%s%-23s: %-15s -- %s" % (offset,name,characterization,comment[0]) - for commenti in comment: - string+="\n%s%-23s %-15s %s" % (offset,'','',commenti) - else: - raise RuntimeError("fielddisplay error message: format for comment not supported yet") +def list_display(offset, name, field, comment): # {{{ - return string - # }}} + #initialization + if isinstance(field, list): + sbeg = '[' + send = ']' + elif isinstance(field, tuple): + sbeg = '(' + send = ')' + string = sbeg + #go through the cell and fill string + if len(field) < 5: + for fieldi in field: + if isinstance(fieldi, str): + string += "'%s', " % fieldi + elif isinstance(fieldi, (bool, int, float)): + string += "%s, " % str(fieldi) + else: + string = sbeg + break + + if m.strcmp(string, sbeg): + string = "%s%dx1%s" % (sbeg, len(field), send) + else: + string = string[: - 1] + send + + #call displayunit + return displayunit(offset, name, string, comment) + # }}} + + +def displayunit(offset, name, characterization, comment): # {{{ + + #take care of name + if len(name) > 23: + name = "%s..." % name[:20] + + #take care of characterization + if m.strcmp(characterization, "''") or m.strcmp(characterization, '""') or m.strcmpi(characterization, 'nan'): + characterization = "N / A" + + if len(characterization) > 15: + characterization = "%s..." % characterization[:12] + + #print + if not comment: + string = "%s% - 23s: % - 15s" % (offset, name, characterization) + else: + if isinstance(comment, str): + string = "%s% - 23s: % - 15s - - %s" % (offset, name, characterization, comment) + elif isinstance(comment, list): + string = "%s% - 23s: % - 15s - - %s" % (offset, name, characterization, comment[0]) + for commenti in comment: + string += "\n%s% - 23s % - 15s %s" % (offset, '', '', commenti) + else: + raise RuntimeError("fielddisplay error message: format for comment not supported yet") + + return string + # }}} Index: /issm/trunk-jpl/src/m/miscellaneous/isnans.py =================================================================== --- /issm/trunk-jpl/src/m/miscellaneous/isnans.py (revision 24212) +++ /issm/trunk-jpl/src/m/miscellaneous/isnans.py (revision 24213) @@ -1,18 +1,18 @@ import numpy as np + def isnans(array): - """ - ISNANS: figure out if an array is nan. wrapper to isnan from matlab which stupidly does not allow this test for structures! + """ + ISNANS: figure out if an array is nan. wrapper to isnan from matlab which stupidly does not allow this test for structures! - Usage: isnans(array) + Usage: isnans(array) - See also : ISNAN - """ + See also : ISNAN + """ - if isinstance(array,(tuple,list,dict)): - returnvalue=0 - else: - returnvalue=np.isnan(array) + if isinstance(array, (tuple, list, dict)): + returnvalue = 0 + else: + returnvalue = np.isnan(array) - return returnvalue - + return returnvalue Index: /issm/trunk-jpl/src/m/miscellaneous/normfit_issm.py =================================================================== --- /issm/trunk-jpl/src/m/miscellaneous/normfit_issm.py (revision 24212) +++ /issm/trunk-jpl/src/m/miscellaneous/normfit_issm.py (revision 24213) @@ -1,61 +1,53 @@ import numpy as np - -from scipy.stats import chi2,t - -# +from scipy.stats import chi2, t # wrapper for normfit to avoid using the matlab statistics toolbox. -# -def normfit_issm(x,alpha=None): - - if alpha == None: - alpha=0.05 - - - # check for any NaN in any columns - if not np.isnan(x).any(): - - # explicitly calculate the moments - muhat =np.mean(x,0) - # numpy defaults to 0 delta degrees of freedom; matlab uses 1 - sigmahat=np.std(x,0,ddof=1) - - # no way to ask this in python, assume 4 outputs - #if (nargout>2): - - prob=1.-alpha/2. - - if (np.size(x,0) == 1): - # operate like matlab normfit, mean, std, etc. - n=np.size(x) - else: - n=np.size(x,0) - - muci =np.zeros((2,np.size(muhat ))) - sigmaci =np.zeros((2,np.size(sigmahat))) - - try: - muci[0,:] =muhat-t.ppf(prob,n-1)*sigmahat/np.sqrt(n) - muci[1,:] =muhat+t.ppf(prob,n-1)*sigmahat/np.sqrt(n) - sigmaci[0,:]=sigmahat*np.sqrt((n-1)/chi2.ppf(prob ,n-1)) - sigmaci[1,:]=sigmahat*np.sqrt((n-1)/chi2.ppf(1.-prob,n-1)) - except: - muci[0,:] =muhat - muci[1,:] =muhat - sigmaci[0,:]=sigmahat - sigmaci[1,:]=sigmahat - else: - # must loop over columns, since number of elements could be different - muhat =np.zeros((1,np.size(x,1))) - sigmahat=np.zeros((1,np.size(x,1))) - muci =np.zeros((2,np.size(x,1))) - sigmaci =np.zeros((2,np.size(x,1))) - - # remove any NaN and recursively call column - for j in range(np.shape(x,1)): - [muhat[j],sigmahat[j],muci[:,j],sigmaci[:,j]]=normfit_issm(x[not np.isnan(x[:,j]),j],alpha) - - return [muhat,sigmahat,muci,sigmaci] - - +def normfit_issm(x, alpha=None): + + if alpha is None: + alpha = 0.05 + + # check for any NaN in any columns + if not np.isnan(x).any(): + + # explicitly calculate the moments + muhat = np.mean(x, 0) + # numpy defaults to 0 delta degrees of freedom; matlab uses 1 + sigmahat = np.std(x, 0, ddof=1) + + # no way to ask this in python, assume 4 outputs + #if (nargout > 2): + prob = 1. - alpha / 2. + + if (np.size(x, 0) == 1): + # operate like matlab normfit, mean, std, etc. + n = np.size(x) + else: + n = np.size(x, 0) + + muci = np.zeros((2, np.size(muhat))) + sigmaci = np.zeros((2, np.size(sigmahat))) + + try: + muci[0, :] = muhat - t.ppf(prob, n - 1) * sigmahat / np.sqrt(n) + muci[1, :] = muhat + t.ppf(prob, n - 1) * sigmahat / np.sqrt(n) + sigmaci[0, :] = sigmahat * np.sqrt((n - 1) / chi2.ppf(prob, n - 1)) + sigmaci[1, :] = sigmahat * np.sqrt((n - 1) / chi2.ppf(1. - prob, n - 1)) + except: + muci[0, :] = muhat + muci[1, :] = muhat + sigmaci[0, :] = sigmahat + sigmaci[1, :] = sigmahat + else: + # must loop over columns, since number of elements could be different + muhat = np.zeros((1, np.size(x, 1))) + sigmahat = np.zeros((1, np.size(x, 1))) + muci = np.zeros((2, np.size(x, 1))) + sigmaci = np.zeros((2, np.size(x, 1))) + + # remove any NaN and recursively call column + for j in range(np.shape(x, 1)): + [muhat[j], sigmahat[j], muci[:, j], sigmaci[:, j]] = normfit_issm(x[not np.isnan(x[:, j]), j], alpha) + + return [muhat, sigmahat, muci, sigmaci] Index: /issm/trunk-jpl/src/m/miscellaneous/parallelrange.py =================================================================== --- /issm/trunk-jpl/src/m/miscellaneous/parallelrange.py (revision 24212) +++ /issm/trunk-jpl/src/m/miscellaneous/parallelrange.py (revision 24213) @@ -1,25 +1,24 @@ -#! /usr/bin/env python -def parallelrange(rank,numprocs,globalsize): - """ - PARALLELRANGE - from a rank, and a number of processors, figure out a range, for parallel tasks. - - Usage: - i1,i2=parallelrange(rank,numprocs,globalsize) - """ +#! / usr / bin / env python +def parallelrange(rank, numprocs, globalsize): + """ + PARALLELRANGE - from a rank, and a number of processors, figure out a range, for parallel tasks. - #We use floor. we under distribute rows. The rows left are then redistributed, therefore resulting in a more even distribution. - num_local_rows=[int(globalsize/numprocs) for i in range(numprocs)] + Usage: + i1, i2 = parallelrange(rank, numprocs, globalsize) + """ - #There may be some rows left. Distribute evenly. - row_rest=globalsize - numprocs*int(globalsize/numprocs) + #We use floor. we under distribute rows. The rows left are then redistributed, therefore resulting in a more even distribution. + num_local_rows = [int(globalsize / numprocs) for i in range(numprocs)] - for i in range(row_rest): - num_local_rows[i]=num_local_rows[i]+1 + #There may be some rows left. Distribute evenly. + row_rest = globalsize - numprocs * int(globalsize / numprocs) - i1=0 - for i in range(rank-1): - i1+=num_local_rows[i] - i2=i1+num_local_rows[rank-1]-1 + for i in range(row_rest): + num_local_rows[i] = num_local_rows[i] + 1 - return i1,i2 + i1 = 0 + for i in range(rank - 1): + i1 += num_local_rows[i] + i2 = i1 + num_local_rows[rank - 1] - 1 + return i1, i2 Index: /issm/trunk-jpl/src/m/miscellaneous/prctile_issm.py =================================================================== --- /issm/trunk-jpl/src/m/miscellaneous/prctile_issm.py (revision 24212) +++ /issm/trunk-jpl/src/m/miscellaneous/prctile_issm.py (revision 24213) @@ -2,64 +2,62 @@ from scipy.interpolate import interp1d -# + # wrapper for prctile to avoid using the matlab statistics toolbox. -# -def prctile_issm(x,p,dim): +def prctile_issm(x, p, dim): - try: - raise RuntimeError('hello world') + try: + raise RuntimeError('hello world') - #numpy has no interpolation method that matches matlab's percentile function - #y = np.percentile(x,p,dim,interpolation='higher') - except: - if len(np.shape(x)) > 2: - raise RuntimeError('Number of dimensions #d not implemented.'+str(len(np.shape(x)))) + #numpy has no interpolation method that matches matlab's percentile function + #y = np.percentile(x, p, dim, interpolation = 'higher') + except: + if len(np.shape(x)) > 2: + raise RuntimeError('Number of dimensions #d not implemented.' + str(len(np.shape(x)))) - # presumably at least 1 input value has been given - # np.shape(integer) -> (), must be at least (1,) - psize=np.shape(p) or (1,) - if len(psize) > 1 and np.size(p,1)>1: - p=p.T - - xsize=np.shape(x) or (1,) - if dim==2: - x=x.T + # presumably at least 1 input value has been given + # np.shape(integer) - > (), must be at least (1, ) + psize = np.shape(p) or (1, ) + if len(psize) > 1 and np.size(p, 1) > 1: + p = p.T - # check for any NaN in any columns - if not np.isnan(x).any(): - x=np.sort(x,axis=0) - n=np.size(x,0) + xsize = np.shape(x) or (1, ) + if dim == 2: + x = x.T - # branch based on number of elements - if n>1: - # set up percent values and interpolate - xi=[((i+0.5)*100/n) for i in range(n)] - # scipy's interp1d returns a function - y=interp1d(xi,x,axis=dim,bounds_error=False) - y=y(p) + # check for any NaN in any columns + if not np.isnan(x).any(): + x = np.sort(x, axis=0) + n = np.size(x, 0) - # fill in high and low values outside of interp range - if p>xi[n-1]: - y=np.tile(x[n-1,:],1) - if p 1: + # set up percent values and interpolate + xi = [((i + 0.5) * 100 / n) for i in range(n)] + # scipy's interp1d returns a function + y = interp1d(xi, x, axis=dim, bounds_error=False) + y = y(p) - # if one value, just copy it - elif n==1: - y=np.tile(x[0,:],(len(p),1)) + # fill in high and low values outside of interp range + if p > xi[n - 1]: + y = np.tile(x[n - 1, :], 1) + if p < xi[0]: + y = np.tile(x[0, :], 1) - # if no values, use NaN - else: - y=np.tile(float('NaN'),(size(p,0),size(x,0))) - else: - # must loop over columns, since number of elements could be different - y=np.zeros((np.size(p,0),np.size(x,1))) - for j in range(np.size(x,1)): - # remove any NaN and recursively call column - y[:,j]=prctile_issm(x[np.where(not np.isnan(x[:,j]),j)],p) + # if one value, just copy it + elif n == 1: + y = np.tile(x[0, :], (len(p), 1)) - if (np.min(xsize)==1 and len(xsize) > 1 and xsize[dim]>1 and len(p) > 1 and psize[1]>1) or (np.min(xsize)> 1 and dim==2): - y=y.T + # if no values, use NaN + else: + y = np.tile(float('NaN'), (np.size(p, 0), np.size(x, 0))) + else: + # must loop over columns, since number of elements could be different + y = np.zeros((np.size(p, 0), np.size(x, 1))) + for j in range(np.size(x, 1)): + # remove any NaN and recursively call column + y[:, j] = prctile_issm(x[np.where(not np.isnan(x[:, j]), j)], p) - return y + if (np.min(xsize) == 1 and len(xsize) > 1 and xsize[dim] > 1 and len(p) > 1 and psize[1] > 1) or (np.min(xsize) > 1 and dim == 2): + y = y.T + return y Index: /issm/trunk-jpl/src/m/modules/BamgConvertMesh.py =================================================================== --- /issm/trunk-jpl/src/m/modules/BamgConvertMesh.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/BamgConvertMesh.py (revision 24213) @@ -1,17 +1,18 @@ from BamgConvertMesh_python import BamgConvertMesh_python -def BamgConvertMesh(index,x,y): - """ - BAMGCONVERTMESH - Convert [index, x, y] to a bamg geom and mesh geom - Usage: - bamggeom, bamgmesh = BamgConvertMesh(index, x, y) - index: index of the mesh - x,y: coordinates of the nodes - """ - - #Call mex module - bamggeom, bamgmesh = BamgConvertMesh_python(index,x,y) +def BamgConvertMesh(index, x, y): + """ + BAMGCONVERTMESH - Convert [index, x, y] to a bamg geom and mesh geom - #return - return bamggeom, bamgmesh + Usage: + bamggeom, bamgmesh = BamgConvertMesh(index, x, y) + index: index of the mesh + x, y: coordinates of the nodes + """ + + #Call mex module + bamggeom, bamgmesh = BamgConvertMesh_python(index, x, y) + + #return + return bamggeom, bamgmesh Index: /issm/trunk-jpl/src/m/modules/BamgMesher.py =================================================================== --- /issm/trunk-jpl/src/m/modules/BamgMesher.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/BamgMesher.py (revision 24213) @@ -7,5 +7,5 @@ Usage: - bamgmesh,bamggeom = BamgMesher(bamgmesh,bamggeom,bamgoptions); + bamgmesh, bamggeom = BamgMesher(bamgmesh, bamggeom, bamgoptions) bamgmesh: input bamg mesh Index: /issm/trunk-jpl/src/m/modules/BamgTriangulate.py =================================================================== --- /issm/trunk-jpl/src/m/modules/BamgTriangulate.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/BamgTriangulate.py (revision 24213) @@ -1,17 +1,18 @@ from BamgTriangulate_python import BamgTriangulate_python -def BamgTriangulate(x,y): - """ - BAMGTRIANGULATE - Usage: - index = BamgTriangulate(x,y) +def BamgTriangulate(x, y): + """ + BAMGTRIANGULATE - index: index of the triangulation - x,y: coordinates of the nodes - """ + Usage: + index = BamgTriangulate(x, y) - # Call mex module - index = BamgTriangulate_python(x,y) - # return - return index + index: index of the triangulation + x, y: coordinates of the nodes + """ + + # Call mex module + index = BamgTriangulate_python(x, y) + # return + return index Index: /issm/trunk-jpl/src/m/modules/Chaco.py =================================================================== --- /issm/trunk-jpl/src/m/modules/Chaco.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/Chaco.py (revision 24213) @@ -1,20 +1,20 @@ from Chaco_python import Chaco_python -def Chaco(A,vwgts,ewgts,x,y,z,options,nparts,goal): - '''CHACO + +def Chaco(A, vwgts, ewgts, x, y, z, options, nparts, goal): + '''CHACO Usage: - assgn = Chaco(A,vwgts,ewgts,x,y,z,options,nparts,goal); + assgn = Chaco(A, vwgts, ewgts, x, y, z, options, nparts, goal) - A: Input adjacency matrix - vwgts: weights for all vertices - ewgts: weights for all edges - x,y,z: coordinates for inertial method - options: architecture and partitioning options - nparts: number of parts options - goal: desired set sizes + A: Input adjacency matrix + vwgts: weights for all vertices + ewgts: weights for all edges + x, y, z: coordinates for inertial method + options: architecture and partitioning options + nparts: number of parts options + goal: desired set sizes ''' - # Call mex module - assgn = Chaco_python(A,vwgts,ewgts,x,y,z,options,nparts,goal) - - return assgn + # Call mex module + assgn = Chaco_python(A, vwgts, ewgts, x, y, z, options, nparts, goal) + return assgn Index: /issm/trunk-jpl/src/m/modules/ContourToMesh.py =================================================================== --- /issm/trunk-jpl/src/m/modules/ContourToMesh.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/ContourToMesh.py (revision 24213) @@ -1,35 +1,36 @@ from ContourToMesh_python import ContourToMesh_python -def ContourToMesh(index,x,y,contourname,interptype,edgevalue): - """ - - CONTOURTOMESH - Flag the elements or nodes inside a contour - Usage: - [in_nod,in_elem]=ContourToMesh(index,x,y,contourname,interptype,edgevalue) +def ContourToMesh(index, x, y, contourname, interptype, edgevalue): + """ - index,x,y: mesh triangulation. - contourname: name of .exp file containing the contours. - interptype: string defining type of interpolation ('element', or 'node'). - edgevalue: integer (0, 1 or 2) defining the value associated to the nodes on the edges of the polygons. - in_nod: vector of flags (0 or 1), of size nel if interptype is set to 'node' or 'element and node', - or of size 0 otherwise. - in_elem: vector of flags (0 or 1), of size nel if interptype is set to 'element' or 'element and node', - or of size 0 otherwise. + CONTOURTOMESH - Flag the elements or nodes inside a contour - Example: - in_nod=ContourToMesh(md.elements,md.x,md.y,'Contour.exp','node',1) - in_elements=ContourToMesh(md.elements,md.x,md.y,'Contour.exp','element',0) - [in_nodes,in_elements]=ContourToMesh(md.elements,md.x,md.y,'Contour.exp','element and node',0) - """ - #Call mex module - in_nod,in_elem = ContourToMesh_python(index,x,y,contourname,interptype,edgevalue) + Usage: + [in_nod, in_elem] = ContourToMesh(index, x, y, contourname, interptype, edgevalue) - if interptype=='element': - return in_elem - elif interptype=='node': - return in_nod - elif interptype=='element and node': - return in_nod,in_elem - else: - raise TypeError('interpolation type "{}" not supported yet'.format(interptype)) + index, x, y: mesh triangulation. + contourname: name of .exp file containing the contours. + interptype: string defining type of interpolation ('element', or 'node'). + edgevalue: integer (0, 1 or 2) defining the value associated to the nodes on the edges of the polygons. + in_nod: vector of flags (0 or 1), of size nel if interptype is set to 'node' or 'element and node', + or of size 0 otherwise. + in_elem: vector of flags (0 or 1), of size nel if interptype is set to 'element' or 'element and node', + or of size 0 otherwise. + + Example: + in_nod = ContourToMesh(md.elements, md.x, md.y, 'Contour.exp', 'node', 1) + in_elements = ContourToMesh(md.elements, md.x, md.y, 'Contour.exp', 'element', 0) + [in_nodes, in_elements] = ContourToMesh(md.elements, md.x, md.y, 'Contour.exp', 'element and node', 0) + """ + #Call mex module + in_nod, in_elem = ContourToMesh_python(index, x, y, contourname, interptype, edgevalue) + + if interptype == 'element': + return in_elem + elif interptype == 'node': + return in_nod + elif interptype == 'element and node': + return in_nod, in_elem + else: + raise TypeError('interpolation type "{}" not supported yet'.format(interptype)) Index: /issm/trunk-jpl/src/m/modules/ContourToNodes.py =================================================================== --- /issm/trunk-jpl/src/m/modules/ContourToNodes.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/ContourToNodes.py (revision 24213) @@ -1,20 +1,21 @@ from ContourToNodes_python import ContourToNodes_python -def ContourToNodes(x,y,contourname,edgevalue): - """ - CONTOURTONODES - flags vertices inside contour - Usage: - flags = ContourToNodes(x,y,contourname,edgevalue); +def ContourToNodes(x, y, contourname, edgevalue): + """ + CONTOURTONODES - flags vertices inside contour - x,y: list of nodes - contourname: name of .exp file containing the contours, or resulting structure from call to expread - edgevalue: integer (0, 1 or 2) defining the value associated to the nodes on the edges of the polygons - flags: vector of flags (0 or 1), of size nodes - """ + Usage: + flags = ContourToNodes(x, y, contourname, edgevalue) - #Call mex module - flags = ContourToNodes_python(x,y,contourname,edgevalue) + x, y: list of nodes + contourname: name of .exp file containing the contours, or resulting structure from call to expread + edgevalue: integer (0, 1 or 2) defining the value associated to the nodes on the edges of the polygons + flags: vector of flags (0 or 1), of size nodes + """ - #return - return flags + #Call mex module + flags = ContourToNodes_python(x, y, contourname, edgevalue) + + #return + return flags Index: /issm/trunk-jpl/src/m/modules/ElementConnectivity.py =================================================================== --- /issm/trunk-jpl/src/m/modules/ElementConnectivity.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/ElementConnectivity.py (revision 24213) @@ -1,14 +1,15 @@ from ElementConnectivity_python import ElementConnectivity_python -def ElementConnectivity(elements,nodeconnectivity): - """ - ELEMENTCONNECTIVITY - Build element connectivity using node connectivity and elements - Usage: - elementconnectivity = ElementConnectivity(elements,nodeconnectivity); - """ - #Call mex module - elementconnectivity = ElementConnectivity_python(elements,nodeconnectivity) - - #Return - return elementconnectivity +def ElementConnectivity(elements, nodeconnectivity): + """ + ELEMENTCONNECTIVITY - Build element connectivity using node connectivity and elements + + Usage: + elementconnectivity = ElementConnectivity(elements, nodeconnectivity) + """ + #Call mex module + elementconnectivity = ElementConnectivity_python(elements, nodeconnectivity) + + #Return + return elementconnectivity Index: /issm/trunk-jpl/src/m/modules/InterpFromGridToMesh.py =================================================================== --- /issm/trunk-jpl/src/m/modules/InterpFromGridToMesh.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/InterpFromGridToMesh.py (revision 24213) @@ -1,22 +1,23 @@ from InterpFromGridToMesh_python import InterpFromGridToMesh_python -def InterpFromGridToMesh(x,y,data,x_mesh,y_mesh,default_value): - """ - INTERPFROMGRIDTOMESH - Interpolation from a grid onto a list of points + +def InterpFromGridToMesh(x, y, data, x_mesh, y_mesh, default_value): + """ + INTERPFROMGRIDTOMESH - Interpolation from a grid onto a list of points Usage: - data_mesh=InterpFromGridToMesh(x,y,data,x_mesh,y_mesh,default_value); + data_mesh = InterpFromGridToMesh(x, y, data, x_mesh, y_mesh, default_value) - data: matrix holding the data to be interpolated onto the mesh - x,y: coordinates of matrix data (x and y must be in increasing order) - x_mesh,y_mesh: coordinates of the points onto which we interpolate - default_value: vector of mesh interpolated data + data: matrix holding the data to be interpolated onto the mesh + x, y: coordinates of matrix data (x and y must be in increasing order) + x_mesh, y_mesh: coordinates of the points onto which we interpolate + default_value: vector of mesh interpolated data - Example: - load('velocities.mat'); - md.inversion.vx_obs=InterpFromGridToMesh(x_n,y_m,vx,md.mesh.x,md.mesh.y,0); - """ - # Call mex module - data_mesh=InterpFromGridToMesh_python(x,y,data,x_mesh,y_mesh,default_value) - # Return - return data_mesh + Example: + load('velocities.mat') + md.inversion.vx_obs = InterpFromGridToMesh(x_n, y_m, vx, md.mesh.x, md.mesh.y, 0) + """ + # Call mex module + data_mesh = InterpFromGridToMesh_python(x, y, data, x_mesh, y_mesh, default_value) + # Return + return data_mesh Index: /issm/trunk-jpl/src/m/modules/InterpFromMeshToGrid.py =================================================================== --- /issm/trunk-jpl/src/m/modules/InterpFromMeshToGrid.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/InterpFromMeshToGrid.py (revision 24213) @@ -1,19 +1,20 @@ from InterpFromMeshToGrid_python import InterpFromMeshToGrid_python -def InterpFromMeshToGrid(index,x,y,data,xgrid,ygrid,default_value): - """ - INTERPFROMMESHTOGRID - Interpolation of a data defined on a mesh onto a grid - This function is a multi-threaded mex file that interpolates a field defined - on a triangular mesh onto a regular grid +def InterpFromMeshToGrid(index, x, y, data, xgrid, ygrid, default_value): + """ + INTERPFROMMESHTOGRID - Interpolation of a data defined on a mesh onto a grid - index,x,y: delaunay triangulation defining the mesh - meshdata: vertex values of data to be interpolated + This function is a multi - threaded mex file that interpolates a field defined + on a triangular mesh onto a regular grid - xgrid,ygrid,: parameters that define the grid - default_value: value of points located out of the mesh - """ - # Call mex module - grid=InterpFromMeshToGrid_python(index,x,y,data,xgrid,ygrid,default_value) - # Return - return grid + index, x, y: delaunay triangulation defining the mesh + meshdata: vertex values of data to be interpolated + + xgrid, ygrid, : parameters that define the grid + default_value: value of points located out of the mesh + """ + # Call mex module + grid = InterpFromMeshToGrid_python(index, x, y, data, xgrid, ygrid, default_value) + # Return + return grid Index: /issm/trunk-jpl/src/m/modules/InterpFromMeshToMesh2d.py =================================================================== --- /issm/trunk-jpl/src/m/modules/InterpFromMeshToMesh2d.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/InterpFromMeshToMesh2d.py (revision 24213) @@ -1,27 +1,28 @@ -from InterpFromMeshToMesh2d_python import InterpFromMeshToMesh2d_python +from InterpFromMeshToMesh2d_python import InterpFromMeshToMesh2d_python + def InterpFromMeshToMesh2d(*args): - """ - INTERPFROMMESHTOMESH2D - Interpolation from a 2d triangular mesh onto a list of points + """ + INTERPFROMMESHTOMESH2D - Interpolation from a 2d triangular mesh onto a list of points - Usage: - data_interp=InterpFromMeshToMesh2d(index,x,y,data,x_interp,y_interp); - or data_interp=InterpFromMeshToMesh2d(index,x,y,data,x_interp,y_interp,OPTIONS); - - index: index of the mesh where data is defined (e.g. md.mesh.elements) - x,y: coordinates of the nodes where data is defined - data: matrix holding the data to be interpolated onto the mesh (one column per field) - x_interp,y_interp: coordinates of the points onto which we interpolate - data_interp: vector of mesh interpolated data - Available options: - default: default value if point is outsite of triangulation (instead of linear interpolation) + Usage: + data_interp = InterpFromMeshToMesh2d(index, x, y, data, x_interp, y_interp) + or data_interp = InterpFromMeshToMesh2d(index, x, y, data, x_interp, y_interp, OPTIONS) - Example: - load('temperature.mat'); - md.initialization.temperature=InterpFromMeshToMesh2d(index,x,y,temperature,md.mesh.x,md.mesh.y); - md.initialization.temperature=InterpFromMeshToMesh2d(index,x,y,temperature,md.mesh.x,md.mesh.y,'default',253); - """ - # Call mex module - data_interp = InterpFromMeshToMesh2d_python(*args) - # Return - return data_interp + index: index of the mesh where data is defined (e.g. md.mesh.elements) + x, y: coordinates of the nodes where data is defined + data: matrix holding the data to be interpolated onto the mesh (one column per field) + x_interp, y_interp: coordinates of the points onto which we interpolate + data_interp: vector of mesh interpolated data + Available options: + default: default value if point is outsite of triangulation (instead of linear interpolation) + + Example: + load('temperature.mat') + md.initialization.temperature = InterpFromMeshToMesh2d(index, x, y, temperature, md.mesh.x, md.mesh.y) + md.initialization.temperature = InterpFromMeshToMesh2d(index, x, y, temperature, md.mesh.x, md.mesh.y, 'default', 253) + """ + # Call mex module + data_interp = InterpFromMeshToMesh2d_python(*args) + # Return + return data_interp Index: /issm/trunk-jpl/src/m/modules/InterpFromMeshToMesh3d.py =================================================================== --- /issm/trunk-jpl/src/m/modules/InterpFromMeshToMesh3d.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/InterpFromMeshToMesh3d.py (revision 24213) @@ -1,23 +1,24 @@ from InterpFromMeshToMesh3d_python import InterpFromMeshToMesh3d_python -def InterpFromMeshToMesh3d(index,x,y,z,data,x_prime,y_prime,z_prime,default_value): - """ - INTERPFROMMESHTOMESH3D - Interpolation from a 3d hexahedron mesh onto a list of points + +def InterpFromMeshToMesh3d(index, x, y, z, data, x_prime, y_prime, z_prime, default_value): + """ + INTERPFROMMESHTOMESH3D - Interpolation from a 3d hexahedron mesh onto a list of points Usage: - index: index of the mesh where data is defined - x,y,z: coordinates of the nodes where data is defined - data: matrix holding the data to be interpolated onto the mesh - x_prime,y_prime,z_prime: coordinates of the points onto which we interpolate - default_value: default value if no data is found (holes) - data_prime: vector of mesh interpolated data + index: index of the mesh where data is defined + x, y, z: coordinates of the nodes where data is defined + data: matrix holding the data to be interpolated onto the mesh + x_prime, y_prime, z_prime: coordinates of the points onto which we interpolate + default_value: default value if no data is found (holes) + data_prime: vector of mesh interpolated data Example: - load('temperature.mat'); - md.initialization.temperature=InterpFromMeshToMesh3d(index,x,y,z,temperature,md.mesh.x,md.mesh.y,md.mesh.z,253); - """ - # Call mex module - data_prime = InterpFromMeshToMesh3d_python(index,x,y,z,data,x_prime,y_prime,z_prime,default_value) - - # Return - return data_prime + load('temperature.mat') + md.initialization.temperature = InterpFromMeshToMesh3d(index, x, y, z, temperature, md.mesh.x, md.mesh.y, md.mesh.z, 253) + """ + # Call mex module + data_prime = InterpFromMeshToMesh3d_python(index, x, y, z, data, x_prime, y_prime, z_prime, default_value) + + # Return + return data_prime Index: /issm/trunk-jpl/src/m/modules/IssmConfig.py =================================================================== --- /issm/trunk-jpl/src/m/modules/IssmConfig.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/IssmConfig.py (revision 24213) @@ -1,15 +1,15 @@ from IssmConfig_python import IssmConfig_python + def IssmConfig(string): - """ - ISSMCONFIG + """ + ISSMCONFIG - Usage: - value = IssmConfig('string'); - """ + Usage: + value = IssmConfig('string') + """ - # Call mex module - value = IssmConfig_python(string) - # Return - return value - + # Call mex module + value = IssmConfig_python(string) + # Return + return value Index: /issm/trunk-jpl/src/m/modules/MeshPartition.py =================================================================== --- /issm/trunk-jpl/src/m/modules/MeshPartition.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/MeshPartition.py (revision 24213) @@ -1,42 +1,39 @@ from MeshPartition_python import MeshPartition_python - from mesh3dprisms import * from mesh2d import * from mesh2dvertical import * -def MeshPartition(md,numpartitions): - '''MESHPARTITION - Partition mesh according to the number of areas, using Metis library. - Usage: - [element_partitioning,node_partitioning]=MeshPartition(md.mesh,numpartitions) +def MeshPartition(md, numpartitions): + '''MESHPARTITION - Partition mesh according to the number of areas, using Metis library. - element_partitioning: Vector of partitioning area numbers, for every element. - node_partitioning: Vector of partitioning area numbers, for every node. + Usage: + [element_partitioning, node_partitioning] = MeshPartition(md.mesh, numpartitions) + + element_partitioning: Vector of partitioning area numbers, for every element. + node_partitioning: Vector of partitioning area numbers, for every node. ''' - if md == None or numpartitions == None: - print((MeshPartition.__doc__)) - raise RuntimeError('Wrong usage (see above)') + if md is None or numpartitions is None: + print((MeshPartition.__doc__)) + raise RuntimeError('Wrong usage (see above)') - #Get mesh info from md.mesh - numberofvertices = md.mesh.numberofvertices - numberofelements = md.mesh.numberofelements - elements = md.mesh.elements - numberofelements2d = 0 - numberofvertices2d = 0 - numberoflayers = 1 - elements2d = [] - if isinstance(md.mesh,mesh3dprisms): - elementtype = 'Penta' - numberofelements2d = md.mesh.numberofelements2d - numberofvertices2d = md.mesh.numberofvertices2d - numberoflayers = md.mesh.numberoflayers - elements2d = md.mesh.elements2d - elif isinstance(md.mesh,mesh2d): - elementtype = 'Tria' - elif isinstance(md.mesh,mesh2dvertical): - elementtype = 'Tria' + #Get mesh info from md.mesh + numberofvertices = md.mesh.numberofvertices + elements = md.mesh.elements + numberofvertices2d = 0 + numberoflayers = 1 + elements2d = [] + if isinstance(md.mesh, mesh3dprisms): + elementtype = 'Penta' + numberofvertices2d = md.mesh.numberofvertices2d + numberoflayers = md.mesh.numberoflayers + elements2d = md.mesh.elements2d + elif isinstance(md.mesh, mesh2d): + elementtype = 'Tria' + elif isinstance(md.mesh, mesh2dvertical): + elementtype = 'Tria' - #Call module - [element_partitioning, node_partitioning] = MeshPartition_python(numberofvertices, elements, numberofvertices2d, elements2d, numberoflayers,elementtype, numpartitions) + #Call module + [element_partitioning, node_partitioning] = MeshPartition_python(numberofvertices, elements, numberofvertices2d, elements2d, numberoflayers, elementtype, numpartitions) - return [element_partitioning, node_partitioning] + return [element_partitioning, node_partitioning] Index: /issm/trunk-jpl/src/m/modules/MeshProfileIntersection.py =================================================================== --- /issm/trunk-jpl/src/m/modules/MeshProfileIntersection.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/MeshProfileIntersection.py (revision 24213) @@ -1,23 +1,24 @@ from MeshProfileIntersection_python import MeshProfileIntersection_python -def MeshProfileIntersection(index,x,y,filename): - """ - MESHPROFILEINTERSECTION - Takes a .exp file (made of several profiles), and figures out its intersection with a mesh - Usage: - [segments]=MeshProfileIntersection(index,x,y,filename); - - input: - index,x,y is a triangulation - filename: name of Argus style .exp file containing the segments (can be groups of disconnected segments) - output: - segments: array made of x1,y1,x2,y2,element_id lines (x1,y1) and (x2,y2) are segment extremities for a segment - belonging to the elemnt_id element. there are as many lines in segments as there are segments intersecting the - mesh. - """ - - # Call mex module - segments = MeshProfileIntersection_python(index,x,y,filename) +def MeshProfileIntersection(index, x, y, filename): + """ + MESHPROFILEINTERSECTION - Takes a .exp file (made of several profiles), and figures out its intersection with a mesh + Usage: + [segments] = MeshProfileIntersection(index, x, y, filename) - # Return - return segments + input: + index, x, y is a triangulation + filename: name of Argus style .exp file containing the segments (can be groups of disconnected segments) + + output: + segments: array made of x1, y1, x2, y2, element_id lines (x1, y1) and (x2, y2) are segment extremities for a segment + belonging to the elemnt_id element. there are as many lines in segments as there are segments intersecting the + mesh. + """ + + # Call mex module + segments = MeshProfileIntersection_python(index, x, y, filename) + + # Return + return segments Index: /issm/trunk-jpl/src/m/modules/NodeConnectivity.py =================================================================== --- /issm/trunk-jpl/src/m/modules/NodeConnectivity.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/NodeConnectivity.py (revision 24213) @@ -1,15 +1,15 @@ from NodeConnectivity_python import NodeConnectivity_python -def NodeConnectivity(elements,numnodes): - """ - NODECONNECTIVITY - Build node connectivity from elements - Usage: - connectivity = NodeConnectivity(elements, numnodes); - """ - # Call mex module - connectivity = NodeConnectivity_python(elements,numnodes) +def NodeConnectivity(elements, numnodes): + """ + NODECONNECTIVITY - Build node connectivity from elements - # Return - return connectivity + Usage: + connectivity = NodeConnectivity(elements, numnodes) + """ + # Call mex module + connectivity = NodeConnectivity_python(elements, numnodes) + # Return + return connectivity Index: /issm/trunk-jpl/src/m/modules/ProcessRifts.py =================================================================== --- /issm/trunk-jpl/src/m/modules/ProcessRifts.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/ProcessRifts.py (revision 24213) @@ -1,16 +1,17 @@ from ProcessRifts_python import ProcessRifts_python -def ProcessRifts(index1,x1,y1,segments1,segmentmarkers1): - """ - TRIMESHPROCESSRIFTS - Split a mesh where a rift (or fault) is present - Usage: - [index2,x2,y2,segments2,segmentmarkers2,rifts2]=ProcessRifts(index1,x1,y1,segments1,segmentmarkers1); +def ProcessRifts(index1, x1, y1, segments1, segmentmarkers1): + """ + TRIMESHPROCESSRIFTS - Split a mesh where a rift (or fault) is present - (index1,x1,y1,segments1,segmentmarkers1): An initial triangulation. - [index2,x2,y2,segments2,segmentmarkers2,rifts2]: The resulting triangulation where rifts have been processed. - """ - # Call mex module - index2,x2,y2,segments2,segmentmarkers2,rifts2 = ProcessRifts_python(index1,x1,y1,segments1,segmentmarkers1) - # Return - return index2,x2,y2,segments2,segmentmarkers2,rifts2 + Usage: + [index2, x2, y2, segments2, segmentmarkers2, rifts2] = ProcessRifts(index1, x1, y1, segments1, segmentmarkers1) + + (index1, x1, y1, segments1, segmentmarkers1): An initial triangulation. + [index2, x2, y2, segments2, segmentmarkers2, rifts2]: The resulting triangulation where rifts have been processed. + """ + # Call mex module + index2, x2, y2, segments2, segmentmarkers2, rifts2 = ProcessRifts_python(index1, x1, y1, segments1, segmentmarkers1) + # Return + return index2, x2, y2, segments2, segmentmarkers2, rifts2 Index: /issm/trunk-jpl/src/m/modules/Scotch.py =================================================================== --- /issm/trunk-jpl/src/m/modules/Scotch.py (revision 24212) +++ /issm/trunk-jpl/src/m/modules/Scotch.py (revision 24213) @@ -1,12 +1,13 @@ from Scotch_python import Scotch_python -def Scotch(*varargin): - '''SCOTCH - Scotch partitioner + +def Scotch(* varargin): + '''SCOTCH - Scotch partitioner Usage: - maptab=Scotch(adjmat,vertlb,vertwt,edgewt,archtyp,archpar,Scotch-specific parameters) + maptab = Scotch(adjmat, vertlb, vertwt, edgewt, archtyp, archpar, Scotch - specific parameters) ''' - # Call mex module - maptab=Scotch_python(*varargin) + # Call mex module + maptab = Scotch_python(* varargin) - return maptab + return maptab Index: /issm/trunk-jpl/src/m/os/issmdir.py =================================================================== --- /issm/trunk-jpl/src/m/os/issmdir.py (revision 24212) +++ /issm/trunk-jpl/src/m/os/issmdir.py (revision 24213) @@ -2,22 +2,22 @@ import MatlabFuncs as m + def issmdir(): - """ - ISSMDIR - Get ISSM_DIR environment variable - - Usage: - ISSM_DIR=issmdir() - """ + """ + ISSMDIR - Get ISSM_DIR environment variable - if not m.ispc(): - ISSM_DIR =os.environ['ISSM_DIR'] - else: - ISSM_DIR =os.environ['ISSM_DIR_WIN'] - if m.strcmpi(ISSM_DIR[-1],'/') or m.strcmpi(ISSM_DIR[-1],'\\'): - ISSM_DIR = ISSM_DIR[:-1] #shave off the last '/' + Usage: + ISSM_DIR = issmdir() + """ - if not ISSM_DIR: - raise RuntimeError("issmdir error message: 'ISSM_DIR' environment variable is empty! You should define ISSM_DIR in your .cshrc or .bashrc!") + if not m.ispc(): + ISSM_DIR = os.environ['ISSM_DIR'] + else: + ISSM_DIR = os.environ['ISSM_DIR_WIN'] + if m.strcmpi(ISSM_DIR[-1], '/') or m.strcmpi(ISSM_DIR[-1], '\\'): + ISSM_DIR = ISSM_DIR[: - 1] #shave off the last '/' - return ISSM_DIR + if not ISSM_DIR: + raise RuntimeError("issmdir error message: 'ISSM_DIR' environment variable is empty! You should define ISSM_DIR in your .cshrc or .bashrc!") + return ISSM_DIR Index: /issm/trunk-jpl/src/m/os/issmscpin.py =================================================================== --- /issm/trunk-jpl/src/m/os/issmscpin.py (revision 24212) +++ /issm/trunk-jpl/src/m/os/issmscpin.py (revision 24213) @@ -5,59 +5,60 @@ import MatlabFuncs as m -def issmscpin(host, login,port,path, packages): - """ - ISSMSCPIN get packages from host, using scp on unix, and pscp on windows - usage: issmscpin(host,packages,path) - """ +def issmscpin(host, login, port, path, packages): + """ + ISSMSCPIN get packages from host, using scp on unix, and pscp on windows - #first get hostname - hostname=gethostname() + usage: issmscpin(host, packages, path) + """ - #first be sure packages are not in the current directory, this could conflict with pscp on windows. - #remove warnings in case the files do not exist - for package in packages: - try: - os.remove(package) - except OSError as e: - pass + #first get hostname + hostname = gethostname() - #if hostname and host are the same, do a simple copy - if m.strcmpi(hostname,host): + #first be sure packages are not in the current directory, this could conflict with pscp on windows. + #remove warnings in case the files do not exist + for package in packages: + try: + os.remove(package) + except OSError as e: + pass - for package in packages: - try: - shutil.copy(os.path.join(path,package),os.getcwd()) #keep going, even if success=0 - except OSError as e: - pass + #if hostname and host are the same, do a simple copy + if m.strcmpi(hostname, host): - else: - if m.ispc(): - #use the putty project pscp.exe: it should be in the path. - #get ISSM_DIR variable - if 'ISSM_DIR_WIN' in os.environ: - ISSM_DIR=os.environ['ISSM_DIR_WIN'][1:-2] - else: - raise OSError("issmscpin error message: could not find ISSM_DIR_WIN environment variable.") + for package in packages: + try: + shutil.copy(os.path.join(path, package), os.getcwd()) #keep going, even if success = 0 + except OSError as e: + pass - username=eval(input('Username: (quoted string) ')) - key=eval(input('Key: (quoted string) ')) + else: + if m.ispc(): + #use the putty project pscp.exe: it should be in the path. + #get ISSM_DIR variable + if 'ISSM_DIR_WIN' in os.environ: + ISSM_DIR = os.environ['ISSM_DIR_WIN'][1: - 2] + else: + raise OSError("issmscpin error message: could not find ISSM_DIR_WIN environment variable.") - for package in packages: - try: - subprocess.check_call('%s/externalpackages/ssh/pscp.exe -l "%s" -pw "%s" %s:%s %s' % (ISSM_DIR,username,key,host,os.path.join(path,package),os.getcwd()),shell=True) - except CalledProcessError as e: - raise CalledProcessError("issmscpin error message: could not call putty pscp.") + username = eval(input('Username: (quoted string) ')) + key = eval(input('Key: (quoted string) ')) - else: - #just use standard unix scp - #string to copy multiple files using scp: - string="'{"+','.join([str(x) for x in packages])+"}'" - if port: - subprocess.call('scp -P {} {}@localhost:{} {}/. '.format(port,login,os.path.join(path,string),os.getcwd()),shell=True) - else: - subprocess.call('scp -T {}@{}:{} {}/.'.format(login,host,os.path.join(path,string),os.getcwd()),shell=True) - #check scp worked - for package in packages: - if not os.path.exists(os.path.join('.',package)): - raise OSError("issmscpin error message: could not call scp on *nix system for file '{}'".format(package)) + for package in packages: + try: + subprocess.check_call('%s/externalpackages/ssh/pscp.exe -l "%s" -pw "%s" %s:%s %s' % (ISSM_DIR, username, key, host, os.path.join(path, package), os.getcwd()), shell=True) + except CalledProcessError as e: + raise CalledProcessError("issmscpin error message: could not call putty pscp.") + + else: + #just use standard unix scp + #string to copy multiple files using scp: + string = "'{" + ','.join([str(x) for x in packages]) + "}'" + if port: + subprocess.call('scp -P {} {}@localhost:{} {}/. '.format(port, login, os.path.join(path, string), os.getcwd()), shell=True) + else: + subprocess.call('scp -T {}@{}:{} {}/.'.format(login, host, os.path.join(path, string), os.getcwd()), shell=True) + #check scp worked + for package in packages: + if not os.path.exists(os.path.join('.', package)): + raise OSError("issmscpin error message: could not call scp on * nix system for file '{}'".format(package)) Index: /issm/trunk-jpl/src/m/os/issmscpout.py =================================================================== --- /issm/trunk-jpl/src/m/os/issmscpout.py (revision 24212) +++ /issm/trunk-jpl/src/m/os/issmscpout.py (revision 24213) @@ -1,59 +1,58 @@ -from socket import gethostname +from socket import gethostname import subprocess import os import MatlabFuncs as m -def issmscpout(host,path,login,port,packages): - """ - ISSMSCPOUT send packages to a host, using scp on unix, and pscp on windows - - usage: issmscpout(host,path,packages) - """ - #get hostname - hostname=gethostname(); +def issmscpout(host, path, login, port, packages): + """ + ISSMSCPOUT send packages to a host, using scp on unix, and pscp on windows - #if hostname and host are the same, do a simple copy + usage: issmscpout(host, path, packages) + """ - if m.strcmpi(host,hostname): - for package in packages: - here=os.getcwd() - os.chdir(path) - try: - os.remove(package) - except OSError as e: - pass - subprocess.call('ln -s %s %s' % (os.path.join(here,package),path),shell=True) - os.chdir(here) - else: - if m.ispc(): - #use the putty project pscp.exe: it should be in the path. - - #get ISSM_DIR variable - if 'ISSM_DIR_WIN' in os.environ: - ISSM_DIR=os.environ['ISSM_DIR_WIN'][1:-2] - else: - raise OSError("issmscpout error message: could not find ISSM_DIR_WIN environment variable.") + #get hostname + hostname = gethostname() - username=eval(input('Username: (quoted string) ')) - key=eval(input('Key: (quoted string) ')) + #if hostname and host are the same, do a simple copy - for package in packages: - try: - subprocess.check_call('%s/externalpackages/ssh/pscp.exe -l "%s" -pw "%s" %s %s:%s' % (ISSM_DIR,username,key,package,host,path),shell=True) - except CalledProcessError as e: - raise CalledProcessError("issmscpout error message: could not call putty pscp.") + if m.strcmpi(host, hostname): + for package in packages: + here = os.getcwd() + os.chdir(path) + try: + os.remove(package) + except OSError: + pass + subprocess.call('ln -s %s %s' % (os.path.join(here, package), path), shell=True) + os.chdir(here) + else: + if m.ispc(): + #use the putty project pscp.exe: it should be in the path. + #get ISSM_DIR variable + if 'ISSM_DIR_WIN' in os.environ: + ISSM_DIR = os.environ['ISSM_DIR_WIN'][1: - 2] + else: + raise OSError("issmscpout error message: could not find ISSM_DIR_WIN environment variable.") - else: - #just use standard unix scp - #create string of packages being sent - string='' - for package in packages: - string+=' '+package - string+=' ' - - if port: - subprocess.call('scp -P %d %s %s@localhost:%s' % (port,string,login,path),shell=True) - else: - subprocess.call('scp %s %s@%s:%s' % (string,login,host,path),shell=True) + username = eval(input('Username: (quoted string) ')) + key = eval(input('Key: (quoted string) ')) + for package in packages: + try: + subprocess.check_call('%s/externalpackages/ssh/pscp.exe -l "%s" -pw "%s" %s %s:%s' % (ISSM_DIR, username, key, package, host, path), shell=True) + except CalledProcessError as e: + raise CalledProcessError("issmscpout error message: could not call putty pscp.") + + else: + #just use standard unix scp + #create string of packages being sent + string = '' + for package in packages: + string += ' ' + package + string += ' ' + + if port: + subprocess.call('scp - P %d %s %s@localhost:%s' % (port, string, login, path), shell=True) + else: + subprocess.call('scp %s %s@%s:%s' % (string, login, host, path), shell=True) Index: /issm/trunk-jpl/src/m/os/issmssh.py =================================================================== --- /issm/trunk-jpl/src/m/os/issmssh.py (revision 24212) +++ /issm/trunk-jpl/src/m/os/issmssh.py (revision 24213) @@ -5,57 +5,55 @@ import MatlabFuncs as m -def issmssh(host,login,port,command): - """ - ISSMSSH - wrapper for OS independent ssh command. - - usage: - issmssh(host,command) - """ - #first get hostname - hostname=gethostname() +def issmssh(host, login, port, command): + """ + ISSMSSH - wrapper for OS independent ssh command. - #if same as host, just run the command. - if m.strcmpi(host,hostname): - subprocess.call(command,shell=True) - else: - if m.ispc(): - #use the putty project plink.exe: it should be in the path. - - #get ISSM_DIR variable - if 'ISSM_DIR_WIN' in os.environ: - ISSM_DIR=os.environ['ISSM_DIR_WIN'][1:-2] - else: - raise OSError("issmssh error message: could not find ISSM_DIR_WIN environment variable.") + usage: + issmssh(host, command) + """ - username=eval(input('Username: (quoted string) ')) - key=eval(input('Key: (quoted string) ')) + #first get hostname + hostname = gethostname() - subprocess.call('%s/externalpackages/ssh/plink.exe -ssh -l "%s" -pw "%s" %s "%s"' % (ISSM_DIR,username,key,host,command),shell=True); + #if same as host, just run the command. + if m.strcmpi(host, hostname): + subprocess.call(command, shell=True) + else: + if m.ispc(): + #use the putty project plink.exe: it should be in the path. + #get ISSM_DIR variable + if 'ISSM_DIR_WIN' in os.environ: + ISSM_DIR = os.environ['ISSM_DIR_WIN'][1: - 2] + else: + raise OSError("issmssh error message: could not find ISSM_DIR_WIN environment variable.") - else: - #just use standard unix ssh - if port: - subprocess.call('ssh -l %s -p %d localhost "%s"' % (login,port,command),shell=True) - else: - subprocess.call('ssh -l %s %s "%s"' % (login,host,command),shell=True) + username = eval(input('Username: (quoted string) ')) + key = eval(input('Key: (quoted string) ')) - # The following code was added to fix: - # "IOError: [Errno 35] Resource temporarily unavailable" - # on the Mac when trying to display md after the solution. - # (from http://code.google.com/p/robotframework/issues/detail?id=995) + subprocess.call('%s/externalpackages/ssh/plink.exe-ssh - l "%s" - pw "%s" %s "%s"' % (ISSM_DIR, username, key, host, command), shell=True) - if _platform == "darwin": - # Make FreeBSD use blocking I/O like other platforms - import sys - import fcntl - from os import O_NONBLOCK - - fd = sys.stdin.fileno() - flags = fcntl.fcntl(fd, fcntl.F_GETFL) - fcntl.fcntl(fd, fcntl.F_SETFL, flags & ~O_NONBLOCK) - - fd = sys.stdout.fileno() - flags = fcntl.fcntl(fd, fcntl.F_GETFL) - fcntl.fcntl(fd, fcntl.F_SETFL, flags & ~O_NONBLOCK) + else: + #just use standard unix ssh + if port: + subprocess.call('ssh - l %s - p %d localhost "%s"' % (login, port, command), shell=True) + else: + subprocess.call('ssh - l %s %s "%s"' % (login, host, command), shell=True) + # The following code was added to fix: + # "IOError: [Errno 35] Resource temporarily unavailable" + # on the Mac when trying to display md after the solution. + # (from http: / / code.google.com / p / robotframework / issues / detail?id = 995) + if _platform == "darwin": + # Make FreeBSD use blocking I / O like other platforms + import sys + import fcntl + from os import O_NONBLOCK + + fd = sys.stdin.fileno() + flags = fcntl.fcntl(fd, fcntl.F_GETFL) + fcntl.fcntl(fd, fcntl.F_SETFL, flags & ~O_NONBLOCK) + + fd = sys.stdout.fileno() + flags = fcntl.fcntl(fd, fcntl.F_GETFL) + fcntl.fcntl(fd, fcntl.F_SETFL, flags & ~O_NONBLOCK) Index: /issm/trunk-jpl/src/m/parameterization/contourenvelope.py =================================================================== --- /issm/trunk-jpl/src/m/parameterization/contourenvelope.py (revision 24212) +++ /issm/trunk-jpl/src/m/parameterization/contourenvelope.py (revision 24213) @@ -4,132 +4,131 @@ from NodeConnectivity import NodeConnectivity from ElementConnectivity import ElementConnectivity -from mesh2d import mesh2d -from mesh3dprisms import mesh3dprisms +from ContourToMesh import ContourToMesh import MatlabFuncs as m -def contourenvelope(md,*args): - """ - CONTOURENVELOPE - build a set of segments enveloping a contour .exp - Usage: - segments=contourenvelope(md,varargin) +def contourenvelope(md, *args): + """ + CONTOURENVELOPE - build a set of segments enveloping a contour .exp - Example: - segments=contourenvelope(md,'Stream.exp'); - segments=contourenvelope(md); - """ + Usage: + segments = contourenvelope(md, varargin) - #some checks - if len(args)>1: - raise RuntimeError("contourenvelope error message: bad usage") + Example: + segments = contourenvelope(md, 'Stream.exp') + segments = contourenvelope(md) + """ - if len(args)==1: - flags=args[0] + #some checks + if len(args) > 1: + raise RuntimeError("contourenvelope error message: bad usage") - if isinstance(flags,str): - file=flags - if not os.path.exists(file): - raise IOError("contourenvelope error message: file '%s' not found" % file) - isfile=1 - elif isinstance(flags,(bool,int,float)): - #do nothing for now - isfile=0 - else: - raise TypeError("contourenvelope error message: second argument should be a file or an elements flag") + if len(args) == 1: + flags = args[0] - #Now, build the connectivity tables for this mesh. - #Computing connectivity - if np.size(md.mesh.vertexconnectivity,axis=0)!=md.mesh.numberofvertices and np.size(md.mesh.vertexconnectivity,axis=0)!=md.mesh.numberofvertices2d: - md.mesh.vertexconnectivity=NodeConnectivity(md.mesh.elements,md.mesh.numberofvertices)[0] - if np.size(md.mesh.elementconnectivity,axis=0)!=md.mesh.numberofelements and np.size(md.mesh.elementconnectivity,axis=0)!=md.mesh.numberofelements2d: - md.mesh.elementconnectivity=ElementConnectivity(md.mesh.elements,md.mesh.vertexconnectivity)[0] + if isinstance(flags, str): + file = flags + if not os.path.exists(file): + raise IOError("contourenvelope error message: file '%s' not found" % file) + isfile = 1 + elif isinstance(flags, (bool, int, float)): + #do nothing for now + isfile = 0 + else: + raise TypeError("contourenvelope error message: second argument should be a file or an elements flag") - #get nodes inside profile - elementconnectivity=copy.deepcopy(md.mesh.elementconnectivity) - if md.mesh.dimension()==2: - elements=copy.deepcopy(md.mesh.elements) - x=copy.deepcopy(md.mesh.x) - y=copy.deepcopy(md.mesh.y) - numberofvertices=copy.deepcopy(md.mesh.numberofvertices) - numberofelements=copy.deepcopy(md.mesh.numberofelements) - else: - elements=copy.deepcopy(md.mesh.elements2d) - x=copy.deepcopy(md.mesh.x2d) - y=copy.deepcopy(md.mesh.y2d) - numberofvertices=copy.deepcopy(md.mesh.numberofvertices2d) - numberofelements=copy.deepcopy(md.mesh.numberofelements2d) + #Now, build the connectivity tables for this mesh. + #Computing connectivity + if np.size(md.mesh.vertexconnectivity, axis=0) != md.mesh.numberofvertices and np.size(md.mesh.vertexconnectivity, axis=0) != md.mesh.numberofvertices2d: + md.mesh.vertexconnectivity = NodeConnectivity(md.mesh.elements, md.mesh.numberofvertices)[0] + if np.size(md.mesh.elementconnectivity, axis=0) != md.mesh.numberofelements and np.size(md.mesh.elementconnectivity, axis=0) != md.mesh.numberofelements2d: + md.mesh.elementconnectivity = ElementConnectivity(md.mesh.elements, md.mesh.vertexconnectivity)[0] - if len(args)==1: + #get nodes inside profile + elementconnectivity = copy.deepcopy(md.mesh.elementconnectivity) + if md.mesh.dimension() == 2: + elements = copy.deepcopy(md.mesh.elements) + x = copy.deepcopy(md.mesh.x) + y = copy.deepcopy(md.mesh.y) + numberofvertices = copy.deepcopy(md.mesh.numberofvertices) + numberofelements = copy.deepcopy(md.mesh.numberofelements) + else: + elements = copy.deepcopy(md.mesh.elements2d) + x = copy.deepcopy(md.mesh.x2d) + y = copy.deepcopy(md.mesh.y2d) + numberofvertices = copy.deepcopy(md.mesh.numberofvertices2d) + numberofelements = copy.deepcopy(md.mesh.numberofelements2d) - if isfile: - #get flag list of elements and nodes inside the contour - nodein=ContourToMesh(elements,x,y,file,'node',1) - elemin=(np.sum(nodein(elements),axis=1)==np.size(elements,axis=1)) - #modify element connectivity - elemout=np.nonzero(np.logical_not(elemin))[0] - elementconnectivity[elemout,:]=0 - elementconnectivity[np.nonzero(m.ismember(elementconnectivity,elemout+1))]=0 - else: - #get flag list of elements and nodes inside the contour - nodein=np.zeros(numberofvertices) - elemin=np.zeros(numberofelements) + if len(args) == 1: - pos=np.nonzero(flags) - elemin[pos]=1 - nodein[elements[pos,:]-1]=1 + if isfile: + #get flag list of elements and nodes inside the contour + nodein = ContourToMesh(elements, x, y, file, 'node', 1) + elemin = (np.sum(nodein(elements), axis=1) == np.size(elements, axis=1)) + #modify element connectivity + elemout = np.nonzero(np.logical_not(elemin))[0] + elementconnectivity[elemout, :] = 0 + elementconnectivity[np.nonzero(m.ismember(elementconnectivity, elemout + 1))] = 0 + else: + #get flag list of elements and nodes inside the contour + nodein = np.zeros(numberofvertices) + elemin = np.zeros(numberofelements) - #modify element connectivity - elemout=np.nonzero(np.logical_not(elemin))[0] - elementconnectivity[elemout,:]=0 - elementconnectivity[np.nonzero(m.ismember(elementconnectivity,elemout+1))]=0 + pos = np.nonzero(flags) + elemin[pos] = 1 + nodein[elements[pos, :] - 1] = 1 - #Find element on boundary - #First: find elements on the boundary of the domain - flag=copy.deepcopy(elementconnectivity) - if len(args)==1: - flag[np.nonzero(flag)]=elemin[flag[np.nonzero(flag)]] - elementonboundary=np.logical_and(np.prod(flag,axis=1)==0,np.sum(flag,axis=1)>0) + #modify element connectivity + elemout = np.nonzero(np.logical_not(elemin))[0] + elementconnectivity[elemout, :] = 0 + elementconnectivity[np.nonzero(m.ismember(elementconnectivity, elemout + 1))] = 0 - #Find segments on boundary - pos=np.nonzero(elementonboundary)[0] - num_segments=np.size(pos) - segments=np.zeros((num_segments*3,3),int) - count=0 + #Find element on boundary + #First: find elements on the boundary of the domain + flag = copy.deepcopy(elementconnectivity) + if len(args) == 1: + flag[np.nonzero(flag)] = elemin[flag[np.nonzero(flag)]] + elementonboundary = np.logical_and(np.prod(flag, axis=1) == 0, np.sum(flag, axis=1) > 0) - for el1 in pos: - els2=elementconnectivity[el1,np.nonzero(elementconnectivity[el1,:])[0]]-1 - if np.size(els2)>1: - flag=np.intersect1d(np.intersect1d(elements[els2[0],:],elements[els2[1],:]),elements[el1,:]) - nods1=elements[el1,:] - nods1=np.delete(nods1,np.nonzero(nods1==flag)) - segments[count,:]=[nods1[0],nods1[1],el1+1] + #Find segments on boundary + pos = np.nonzero(elementonboundary)[0] + num_segments = np.size(pos) + segments = np.zeros((num_segments * 3, 3), int) + count = 0 - ord1=np.nonzero(nods1[0]==elements[el1,:])[0][0] - ord2=np.nonzero(nods1[1]==elements[el1,:])[0][0] + for el1 in pos: + els2 = elementconnectivity[el1, np.nonzero(elementconnectivity[el1, :])[0]] - 1 + if np.size(els2) > 1: + flag = np.intersect1d(np.intersect1d(elements[els2[0], :], elements[els2[1], :]), elements[el1, :]) + nods1 = elements[el1, :] + nods1 = np.delete(nods1, np.nonzero(nods1 == flag)) + segments[count, :] = [nods1[0], nods1[1], el1 + 1] - #swap segment nodes if necessary - if ( (ord1==0 and ord2==1) or (ord1==1 and ord2==2) or (ord1==2 and ord2==0) ): - temp=segments[count,0] - segments[count,0]=segments[count,1] - segments[count,1]=temp - segments[count,0:2]=np.flipud(segments[count,0:2]) - count+=1 - else: - nods1=elements[el1,:] - flag=np.setdiff1d(nods1,elements[els2,:]) - for j in range(0,3): - nods=np.delete(nods1,j) - if np.any(m.ismember(flag,nods)): - segments[count,:]=[nods[0],nods[1],el1+1] - ord1=np.nonzero(nods[0]==elements[el1,:])[0][0] - ord2=np.nonzero(nods[1]==elements[el1,:])[0][0] - if ( (ord1==0 and ord2==1) or (ord1==1 and ord2==2) or (ord1==2 and ord2==0) ): - temp=segments[count,0] - segments[count,0]=segments[count,1] - segments[count,1]=temp - segments[count,0:2]=np.flipud(segments[count,0:2]) - count+=1 - segments=segments[0:count,:] + ord1 = np.nonzero(nods1[0] == elements[el1, :])[0][0] + ord2 = np.nonzero(nods1[1] == elements[el1, :])[0][0] - return segments + #swap segment nodes if necessary + if ((ord1 == 0 and ord2 == 1) or (ord1 == 1 and ord2 == 2) or (ord1 == 2 and ord2 == 0)): + temp = segments[count, 0] + segments[count, 0] = segments[count, 1] + segments[count, 1] = temp + segments[count, 0:2] = np.flipud(segments[count, 0:2]) + count += 1 + else: + nods1 = elements[el1, :] + flag = np.setdiff1d(nods1, elements[els2, :]) + for j in range(0, 3): + nods = np.delete(nods1, j) + if np.any(m.ismember(flag, nods)): + segments[count, :] = [nods[0], nods[1], el1 + 1] + ord1 = np.nonzero(nods[0] == elements[el1, :])[0][0] + ord2 = np.nonzero(nods[1] == elements[el1, :])[0][0] + if ((ord1 == 0 and ord2 == 1) or (ord1 == 1 and ord2 == 2) or (ord1 == 2 and ord2 == 0)): + temp = segments[count, 0] + segments[count, 0] = segments[count, 1] + segments[count, 1] = temp + segments[count, 0:2] = np.flipud(segments[count, 0:2]) + count += 1 + segments = segments[0:count, :] + return segments Index: /issm/trunk-jpl/src/m/parameterization/parameterize.py =================================================================== --- /issm/trunk-jpl/src/m/parameterization/parameterize.py (revision 24212) +++ /issm/trunk-jpl/src/m/parameterization/parameterize.py (revision 24213) @@ -2,32 +2,32 @@ import datetime -def parameterize(md,parametername): - """ - PARAMETERIZE - parameterize a model - from a parameter python file, start filling in all the model fields that were not - filled in by the mesh.py and mask.py model methods. - Warning: the parameter file must be able to be run in Python +def parameterize(md, parametername): + """ + PARAMETERIZE - parameterize a model - Usage: - md=parameterize(md,parametername) + from a parameter python file, start filling in all the model fields that were not + filled in by the mesh.py and mask.py model methods. + Warning: the parameter file must be able to be run in Python - Example: - md=parameterize(md,'Square.par'); - """ + Usage: + md = parameterize(md, parametername) - #some checks - if not os.path.exists(parametername): - raise IOError("parameterize error message: file '%s' not found!" % parametername) + Example: + md = parameterize(md, 'Square.par') + """ - #Try and run parameter file. - exec(compile(open(parametername).read(), parametername, 'exec')) + #some checks + if not os.path.exists(parametername): + raise IOError("parameterize error message: file '%s' not found!" % parametername) - #Name and notes - if not md.miscellaneous.name: - md.miscellaneous.name=os.path.basename(parametername).split('.')[0] + #Try and run parameter file. + exec(compile(open(parametername).read(), parametername, 'exec')) - md.miscellaneous.notes="Model created by using parameter file: '%s' on: %s." % (parametername,datetime.datetime.strftime(datetime.datetime.now(),'%c')) + #Name and notes + if not md.miscellaneous.name: + md.miscellaneous.name = os.path.basename(parametername).split('.')[0] - return md + md.miscellaneous.notes = "Model created by using parameter file: '%s' on: %s." % (parametername, datetime.datetime.strftime(datetime.datetime.now(), '%c')) + return md Index: /issm/trunk-jpl/src/m/parameterization/setflowequation.py =================================================================== --- /issm/trunk-jpl/src/m/parameterization/setflowequation.py (revision 24212) +++ /issm/trunk-jpl/src/m/parameterization/setflowequation.py (revision 24213) @@ -4,284 +4,285 @@ from FlagElements import FlagElements -def setflowequation(md,*args): - """ - SETFLOWEQUATION - associate a solution type to each element - - This routine works like plotmodel: it works with an even number of inputs - 'SIA','SSA','HO','L1L2','FS' and 'fill' are the possible options - that must be followed by the corresponding exp file or flags list - It can either be a domain file (argus type, .exp extension), or an array of element flags. - If user wants every element outside the domain to be - setflowequationd, add '~' to the name of the domain file (ex: '~HO.exp'); - an empty string '' will be considered as an empty domain - a string 'all' will be considered as the entire domain - You can specify the type of coupling, 'penalties' or 'tiling', to use with the input 'coupling' - - Usage: - md=setflowequation(md,varargin) - - Example: - md=setflowequation(md,'HO','HO.exp',fill','SIA','coupling','tiling'); - """ - - #some checks on list of arguments - if not isinstance(md,model) or not len(args): - raise TypeError("setflowequation error message") - - #process options - options=pairoptions(*args) - # options=deleteduplicates(options,1); - - #Find_out what kind of coupling to use - coupling_method=options.getfieldvalue('coupling','tiling') - if not coupling_method in ['tiling','penalties']: - raise TypeError("coupling type can only be: tiling or penalties") - - #recover elements distribution - SIAflag = FlagElements(md,options.getfieldvalue('SIA','')) - SSAflag = FlagElements(md,options.getfieldvalue('SSA','')) - HOflag = FlagElements(md,options.getfieldvalue('HO','')) - L1L2flag = FlagElements(md,options.getfieldvalue('L1L2','')) - FSflag = FlagElements(md,options.getfieldvalue('FS','')) - filltype = options.getfieldvalue('fill','none') - #Flag the elements that have not been flagged as filltype - if 'SIA' in filltype: - SIAflag= ~SSAflag & ~HOflag - elif 'SSA' in filltype: - SSAflag=~SIAflag & ~HOflag & ~FSflag - elif 'HO' in filltype: - HOflag=~SIAflag & ~SSAflag & ~FSflag - #check that each element has at least one flag - if not any(SIAflag+SSAflag+L1L2flag+HOflag+FSflag): - raise TypeError("elements type not assigned, supported models are 'SIA','SSA','HO' and 'FS'") - - #check that each element has only one flag - if any(SIAflag+SSAflag+L1L2flag+HOflag+FSflag>1): - print("setflowequation warning message: some elements have several types, higher order type is used for them") - SIAflag[np.where(np.logical_and(SIAflag,SSAflag))]=False - SIAflag[np.where(np.logical_and(SIAflag,HOflag))]=False - SSAflag[np.where(np.logical_and(SSAflag,HOflag))]=False - - #check that L1L2 is not coupled to any other model for now - if any(L1L2flag) and any(SIAflag+SSAflag+HOflag+FSflag): - raise TypeError('L1L2 cannot be coupled to any other model') - - #Check that no HO or FS for 2d mesh - if domaintype(md.mesh)=='2Dhorizontal': - if any(FSflag+HOflag): - raise TypeError('FS and HO elements not allowed in 2d mesh, extrude it first') - - #FS can only be used alone for now: - if any(FSflag) and any(SIAflag): - raise TypeError("FS cannot be used with any other model for now, put FS everywhere") - - #Initialize node fields - nodeonSIA=np.zeros(md.mesh.numberofvertices,bool) - nodeonSIA[md.mesh.elements[np.where(SIAflag),:]-1]=True - nodeonSSA=np.zeros(md.mesh.numberofvertices,bool) - nodeonSSA[md.mesh.elements[np.where(SSAflag),:]-1]=True - nodeonL1L2=np.zeros(md.mesh.numberofvertices,bool) - nodeonL1L2[md.mesh.elements[np.where(L1L2flag),:]-1]=True - nodeonHO=np.zeros(md.mesh.numberofvertices,bool) - nodeonHO[md.mesh.elements[np.where(HOflag),:]-1]=True - nodeonFS=np.zeros(md.mesh.numberofvertices,bool) - noneflag=np.zeros(md.mesh.numberofelements,bool) - - #First modify FSflag to get rid of elements contrained everywhere (spc + border with HO or SSA) - if any(FSflag): - fullspcnodes=np.logical_or(~np.isnan(md.stressbalance.spcvx)+~np.isnan(md.stressbalance.spcvy)+~np.isnan(md.stressbalance.spcvz),np.logical_and(nodeonHO,nodeonFS)) #find all the nodes on the boundary of the domain without icefront - fullspcelems=np.sum(fullspcnodes[md.mesh.elements-1],axis=1)==6 #find all the nodes on the boundary of the domain without icefront - FSflag[np.where(fullspcelems.reshape(-1))]=False - nodeonFS[md.mesh.elements[np.where(FSflag),:]-1]=True - - #Then complete with NoneApproximation or the other model used if there is no FS - if any(FSflag): - if any(HOflag): #fill with HO - HOflag[~FSflag]=True - nodeonHO[md.mesh.elements[np.where(HOflag),:]-1]=True - elif any(SSAflag): #fill with SSA - SSAflag[~FSflag]=True - nodeonSSA[md.mesh.elements[np.where(SSAflag),:]-1]=True - else: #fill with none - noneflag[np.where(~FSflag)]=True - - #Now take care of the coupling between SSA and HO - if not coupling_method in ['penalties']: - md.stressbalance.vertex_pairing=np.array([]) - nodeonSSAHO=np.zeros(md.mesh.numberofvertices,bool) - nodeonHOFS=np.zeros(md.mesh.numberofvertices,bool) - nodeonSSAFS=np.zeros(md.mesh.numberofvertices,bool) - SSAHOflag=np.zeros(md.mesh.numberofelements,bool) - SSAFSflag=np.zeros(md.mesh.numberofelements,bool) - HOFSflag=np.zeros(md.mesh.numberofelements,bool) - if coupling_method=='penalties': - #Create the border nodes between HO and SSA and extrude them - numnodes2d=md.mesh.numberofvertices2d - numlayers=md.mesh.numberoflayers - bordernodes2d=np.where(np.logical_and(nodeonHO[0:numnodes2d],nodeonSSA[0:numnodes2d]))[0]+1 #Nodes connected to two different types of elements - - #initialize and fill in penalties structure - if np.all(np.logical_not(np.isnan(bordernodes2d))): - penalties=np.zeros((0,2)) - for i in range(1,numlayers): - penalties=np.vstack((penalties,np.vstack((bordernodes2d,bordernodes2d+md.mesh.numberofvertices2d*(i))).T)) - md.stressbalance.vertex_pairing=penalties - - elif coupling_method=='tiling': - if any(SSAflag) and any(HOflag): #coupling SSA HO - #Find node at the border - nodeonSSAHO[np.where(np.logical_and(nodeonSSA,nodeonHO))]=True - #SSA elements in contact with this layer become SSAHO elements - matrixelements=nodeonSSAHO[md.mesh.elements-1] - commonelements=np.sum(matrixelements,axis=1)!=0 - commonelements[np.where(HOflag)]=False #only one layer: the elements previously in SSA - SSAflag[np.where(commonelements)]=False #these elements are now SSAHOelements - SSAHOflag[np.where(commonelements)]=True - nodeonSSA[:]=False - nodeonSSA[md.mesh.elements[np.where(SSAflag),:]-1]=True - - #rule out elements that don't touch the 2 boundaries - pos=np.where(SSAHOflag)[0] - elist=np.zeros(np.size(pos),dtype=int) - elist = elist + np.sum(nodeonSSA[md.mesh.elements[pos,:]-1],axis=1).astype(bool) - elist = elist - np.sum(nodeonHO[md.mesh.elements[pos,:]-1] ,axis=1).astype(bool) - pos1=np.where(elist==1)[0] - SSAflag[pos[pos1]]=True - SSAHOflag[pos[pos1]]=False - pos2=np.where(elist==-1)[0] - HOflag[pos[pos2]]=True - SSAHOflag[pos[pos2]]=False - - #Recompute nodes associated to these elements - nodeonSSA[:]=False - nodeonSSA[md.mesh.elements[np.where(SSAflag),:]-1]=True - nodeonHO[:]=False - nodeonHO[md.mesh.elements[np.where(HOflag),:]-1]=True - nodeonSSAHO[:]=False - nodeonSSAHO[md.mesh.elements[np.where(SSAHOflag),:]-1]=True - - elif any(HOflag) and any(FSflag): #coupling HO FS - #Find node at the border - nodeonHOFS[np.where(np.logical_and(nodeonHO,nodeonFS))]=True - #FS elements in contact with this layer become HOFS elements - matrixelements=nodeonHOFS[md.mesh.elements-1] - commonelements=np.sum(matrixelements,axis=1)!=0 - commonelements[np.where(HOflag)]=False #only one layer: the elements previously in SSA - FSflag[np.where(commonelements)]=False #these elements are now SSAHOelements - HOFSflag[np.where(commonelements)]=True - nodeonFS=np.zeros(md.mesh.numberofvertices,bool) - nodeonFS[md.mesh.elements[np.where(FSflag),:]-1]=True - - #rule out elements that don't touch the 2 boundaries - pos=np.where(HOFSflag)[0] - elist=np.zeros(np.size(pos),dtype=int) - elist = elist + np.sum(nodeonFS[md.mesh.elements[pos,:]-1],axis=1).astype(bool) - elist = elist - np.sum(nodeonHO[md.mesh.elements[pos,:]-1],axis=1).astype(bool) - pos1=np.where(elist==1)[0] - FSflag[pos[pos1]]=True - HOFSflag[pos[pos1]]=False - pos2=np.where(elist==-1)[0] - HOflag[pos[pos2]]=True - HOFSflag[pos[pos2]]=False - - #Recompute nodes associated to these elements - nodeonFS[:]=False - nodeonFS[md.mesh.elements[np.where(FSflag),:]-1]=True - nodeonHO[:]=False - nodeonHO[md.mesh.elements[np.where(HOflag),:]-1]=True - nodeonHOFS[:]=False - nodeonHOFS[md.mesh.elements[np.where(HOFSflag),:]-1]=True - elif any(FSflag) and any(SSAflag): - #Find node at the border - nodeonSSAFS[np.where(np.logical_and(nodeonSSA,nodeonFS))]=True - #FS elements in contact with this layer become SSAFS elements - matrixelements=nodeonSSAFS[md.mesh.elements-1] - commonelements=np.sum(matrixelements,axis=1)!=0 - commonelements[np.where(SSAflag)]=False #only one layer: the elements previously in SSA - FSflag[np.where(commonelements)]=False #these elements are now SSASSAelements - SSAFSflag[np.where(commonelements)]=True - nodeonFS=np.zeros(md.mesh.numberofvertices,bool) - nodeonFS[md.mesh.elements[np.where(FSflag),:]-1]=True - - #rule out elements that don't touch the 2 boundaries - pos=np.where(SSAFSflag)[0] - elist=np.zeros(np.size(pos),dtype=int) - elist = elist + np.sum(nodeonSSA[md.mesh.elements[pos,:]-1],axis=1).astype(bool) - elist = elist - np.sum(nodeonFS[md.mesh.elements[pos,:]-1],axis=1).astype(bool) - pos1=np.where(elist==1)[0] - SSAflag[pos[pos1]]=True - SSAFSflag[pos[pos1]]=False - pos2=np.where(elist==-1)[0] - FSflag[pos[pos2]]=True - SSAFSflag[pos[pos2]]=False - - #Recompute nodes associated to these elements - nodeonSSA[:]=False - nodeonSSA[md.mesh.elements[np.where(SSAflag),:]-1]=True - nodeonFS[:]=False - nodeonFS[md.mesh.elements[np.where(FSflag),:]-1]=True - nodeonSSAFS[:]=False - nodeonSSAFS[md.mesh.elements[np.where(SSAFSflag),:]-1]=True - - elif any(FSflag) and any(SIAflag): - raise TypeError("type of coupling not supported yet") - - #Create SSAHOApproximation where needed - md.flowequation.element_equation=np.zeros(md.mesh.numberofelements,int) - md.flowequation.element_equation[np.where(noneflag)]=0 - md.flowequation.element_equation[np.where(SIAflag)]=1 - md.flowequation.element_equation[np.where(SSAflag)]=2 - md.flowequation.element_equation[np.where(L1L2flag)]=3 - md.flowequation.element_equation[np.where(HOflag)]=4 - md.flowequation.element_equation[np.where(FSflag)]=5 - md.flowequation.element_equation[np.where(SSAHOflag)]=6 - md.flowequation.element_equation[np.where(SSAFSflag)]=7 - md.flowequation.element_equation[np.where(HOFSflag)]=8 - - #border - md.flowequation.borderHO=nodeonHO - md.flowequation.borderSSA=nodeonSSA - md.flowequation.borderFS=nodeonFS - - #Create vertices_type - md.flowequation.vertex_equation=np.zeros(md.mesh.numberofvertices,int) - pos=np.where(nodeonSSA) - md.flowequation.vertex_equation[pos]=2 - pos=np.where(nodeonL1L2) - md.flowequation.vertex_equation[pos]=3 - pos=np.where(nodeonHO) - md.flowequation.vertex_equation[pos]=4 - pos=np.where(nodeonFS) - md.flowequation.vertex_equation[pos]=5 - #DO SIA LAST! Otherwise spcs might not be set up correctly (SIA should have priority) - pos=np.where(nodeonSIA) - md.flowequation.vertex_equation[pos]=1 - if any(FSflag): - pos=np.where(np.logical_not(nodeonFS)) - if not (any(HOflag) or any(SSAflag)): - md.flowequation.vertex_equation[pos]=0 - pos=np.where(nodeonSSAHO) - md.flowequation.vertex_equation[pos]=6 - pos=np.where(nodeonHOFS) - md.flowequation.vertex_equation[pos]=7 - pos=np.where(nodeonSSAFS) - md.flowequation.vertex_equation[pos]=8 - - #figure out solution types - md.flowequation.isSIA=any(md.flowequation.element_equation==1) - md.flowequation.isSSA=any(md.flowequation.element_equation==2) - md.flowequation.isL1L2=any(md.flowequation.element_equation==3) - md.flowequation.isHO=any(md.flowequation.element_equation==4) - md.flowequation.isFS=any(md.flowequation.element_equation==5) - - return md - - #Check that tiling can work: - if any(md.flowequation.borderSSA) and any(md.flowequation.borderHO) and any(md.flowequation.borderHO + md.flowequation.borderSSA !=1): - raise TypeError("error coupling domain too irregular") - if any(md.flowequation.borderSSA) and any(md.flowequation.borderFS) and any(md.flowequation.borderFS + md.flowequation.borderSSA !=1): - raise TypeError("error coupling domain too irregular") - if any(md.flowequation.borderFS) and any(md.flowequation.borderHO) and any(md.flowequation.borderHO + md.flowequation.borderFS !=1): - raise TypeError("error coupling domain too irregular") - - return md + +def setflowequation(md, *args): + """ + SETFLOWEQUATION - associate a solution type to each element + + This routine works like plotmodel: it works with an even number of inputs + 'SIA', 'SSA', 'HO', 'L1L2', 'FS' and 'fill' are the possible options + that must be followed by the corresponding exp file or flags list + It can either be a domain file (argus type, .exp extension), or an array of element flags. + If user wants every element outside the domain to be + setflowequationd, add '~' to the name of the domain file (ex: '~HO.exp') + an empty string '' will be considered as an empty domain + a string 'all' will be considered as the entire domain + You can specify the type of coupling, 'penalties' or 'tiling', to use with the input 'coupling' + + Usage: + md = setflowequation(md, varargin) + + Example: + md = setflowequation(md, 'HO', 'HO.exp', fill', 'SIA', 'coupling', 'tiling') + """ + + #some checks on list of arguments + if not isinstance(md, model) or not len(args): + raise TypeError("setflowequation error message") + + #process options + options = pairoptions(*args) + # options = deleteduplicates(options, 1) + + #Find_out what kind of coupling to use + coupling_method = options.getfieldvalue('coupling', 'tiling') + if coupling_method not in ['tiling', 'penalties']: + raise TypeError("coupling type can only be: tiling or penalties") + + #recover elements distribution + SIAflag = FlagElements(md, options.getfieldvalue('SIA', '')) + SSAflag = FlagElements(md, options.getfieldvalue('SSA', '')) + HOflag = FlagElements(md, options.getfieldvalue('HO', '')) + L1L2flag = FlagElements(md, options.getfieldvalue('L1L2', '')) + FSflag = FlagElements(md, options.getfieldvalue('FS', '')) + filltype = options.getfieldvalue('fill', 'none') + #Flag the elements that have not been flagged as filltype + if 'SIA' in filltype: + SIAflag = ~SSAflag & ~HOflag + elif 'SSA' in filltype: + SSAflag = ~SIAflag & ~HOflag & ~FSflag + elif 'HO' in filltype: + HOflag = ~SIAflag & ~SSAflag & ~FSflag + #check that each element has at least one flag + if not any(SIAflag + SSAflag + L1L2flag + HOflag + FSflag): + raise TypeError("elements type not assigned, supported models are 'SIA', 'SSA', 'HO' and 'FS'") + + #check that each element has only one flag + if any(SIAflag + SSAflag + L1L2flag + HOflag + FSflag > 1): + print("setflowequation warning message: some elements have several types, higher order type is used for them") + SIAflag[np.where(np.logical_and(SIAflag, SSAflag))] = False + SIAflag[np.where(np.logical_and(SIAflag, HOflag))] = False + SSAflag[np.where(np.logical_and(SSAflag, HOflag))] = False + + #check that L1L2 is not coupled to any other model for now + if any(L1L2flag) and any(SIAflag + SSAflag + HOflag + FSflag): + raise TypeError('L1L2 cannot be coupled to any other model') + + #Check that no HO or FS for 2d mesh + if md.mesh.domaintype == '2Dhorizontal': + if any(FSflag + HOflag): + raise TypeError('FS and HO elements not allowed in 2d mesh, extrude it first') + + #FS can only be used alone for now: + if any(FSflag) and any(SIAflag): + raise TypeError("FS cannot be used with any other model for now, put FS everywhere") + + #Initialize node fields + nodeonSIA = np.zeros(md.mesh.numberofvertices, bool) + nodeonSIA[md.mesh.elements[np.where(SIAflag), :] - 1] = True + nodeonSSA = np.zeros(md.mesh.numberofvertices, bool) + nodeonSSA[md.mesh.elements[np.where(SSAflag), :] - 1] = True + nodeonL1L2 = np.zeros(md.mesh.numberofvertices, bool) + nodeonL1L2[md.mesh.elements[np.where(L1L2flag), :] - 1] = True + nodeonHO = np.zeros(md.mesh.numberofvertices, bool) + nodeonHO[md.mesh.elements[np.where(HOflag), :] - 1] = True + nodeonFS = np.zeros(md.mesh.numberofvertices, bool) + noneflag = np.zeros(md.mesh.numberofelements, bool) + + #First modify FSflag to get rid of elements contrained everywhere (spc + border with HO or SSA) + if any(FSflag): + fullspcnodes = np.logical_or(~np.isnan(md.stressbalance.spcvx) + ~np.isnan(md.stressbalance.spcvy) + ~np.isnan(md.stressbalance.spcvz), np.logical_and(nodeonHO, nodeonFS)) #find all the nodes on the boundary of the domain without icefront + fullspcelems = np.sum(fullspcnodes[md.mesh.elements - 1], axis=1) == 6 #find all the nodes on the boundary of the domain without icefront + FSflag[np.where(fullspcelems.reshape(- 1))] = False + nodeonFS[md.mesh.elements[np.where(FSflag), :] - 1] = True + + #Then complete with NoneApproximation or the other model used if there is no FS + if any(FSflag): + if any(HOflag): #fill with HO + HOflag[~FSflag] = True + nodeonHO[md.mesh.elements[np.where(HOflag), :] - 1] = True + elif any(SSAflag): #fill with SSA + SSAflag[~FSflag] = True + nodeonSSA[md.mesh.elements[np.where(SSAflag), :] - 1] = True + else: #fill with none + noneflag[np.where(~FSflag)] = True + + #Now take care of the coupling between SSA and HO + if coupling_method not in ['penalties']: + md.stressbalance.vertex_pairing = np.array([]) + nodeonSSAHO = np.zeros(md.mesh.numberofvertices, bool) + nodeonHOFS = np.zeros(md.mesh.numberofvertices, bool) + nodeonSSAFS = np.zeros(md.mesh.numberofvertices, bool) + SSAHOflag = np.zeros(md.mesh.numberofelements, bool) + SSAFSflag = np.zeros(md.mesh.numberofelements, bool) + HOFSflag = np.zeros(md.mesh.numberofelements, bool) + if coupling_method == 'penalties': + #Create the border nodes between HO and SSA and extrude them + numnodes2d = md.mesh.numberofvertices2d + numlayers = md.mesh.numberoflayers + bordernodes2d = np.where(np.logical_and(nodeonHO[0:numnodes2d], nodeonSSA[0:numnodes2d]))[0] + 1 #Nodes connected to two different types of elements + + #initialize and fill in penalties structure + if np.all(np.logical_not(np.isnan(bordernodes2d))): + penalties = np.zeros((0, 2)) + for i in range(1, numlayers): + penalties = np.vstack((penalties, np.vstack((bordernodes2d, bordernodes2d + md.mesh.numberofvertices2d * (i))).T)) + md.stressbalance.vertex_pairing = penalties + + elif coupling_method == 'tiling': + if any(SSAflag) and any(HOflag): #coupling SSA HO + #Find node at the border + nodeonSSAHO[np.where(np.logical_and(nodeonSSA, nodeonHO))] = True + #SSA elements in contact with this layer become SSAHO elements + matrixelements = nodeonSSAHO[md.mesh.elements - 1] + commonelements = np.sum(matrixelements, axis=1) != 0 + commonelements[np.where(HOflag)] = False #only one layer: the elements previously in SSA + SSAflag[np.where(commonelements)] = False #these elements are now SSAHOelements + SSAHOflag[np.where(commonelements)] = True + nodeonSSA[:] = False + nodeonSSA[md.mesh.elements[np.where(SSAflag), :] - 1] = True + + #rule out elements that don't touch the 2 boundaries + pos = np.where(SSAHOflag)[0] + elist = np.zeros(np.size(pos), dtype=int) + elist = elist + np.sum(nodeonSSA[md.mesh.elements[pos, :] - 1], axis=1).astype(bool) + elist = elist - np.sum(nodeonHO[md.mesh.elements[pos, :] - 1], axis=1).astype(bool) + pos1 = np.where(elist == 1)[0] + SSAflag[pos[pos1]] = True + SSAHOflag[pos[pos1]] = False + pos2 = np.where(elist == - 1)[0] + HOflag[pos[pos2]] = True + SSAHOflag[pos[pos2]] = False + + #Recompute nodes associated to these elements + nodeonSSA[:] = False + nodeonSSA[md.mesh.elements[np.where(SSAflag), :] - 1] = True + nodeonHO[:] = False + nodeonHO[md.mesh.elements[np.where(HOflag), :] - 1] = True + nodeonSSAHO[:] = False + nodeonSSAHO[md.mesh.elements[np.where(SSAHOflag), :] - 1] = True + + elif any(HOflag) and any(FSflag): #coupling HO FS + #Find node at the border + nodeonHOFS[np.where(np.logical_and(nodeonHO, nodeonFS))] = True + #FS elements in contact with this layer become HOFS elements + matrixelements = nodeonHOFS[md.mesh.elements - 1] + commonelements = np.sum(matrixelements, axis=1) != 0 + commonelements[np.where(HOflag)] = False #only one layer: the elements previously in SSA + FSflag[np.where(commonelements)] = False #these elements are now SSAHOelements + HOFSflag[np.where(commonelements)] = True + nodeonFS = np.zeros(md.mesh.numberofvertices, bool) + nodeonFS[md.mesh.elements[np.where(FSflag), :] - 1] = True + + #rule out elements that don't touch the 2 boundaries + pos = np.where(HOFSflag)[0] + elist = np.zeros(np.size(pos), dtype=int) + elist = elist + np.sum(nodeonFS[md.mesh.elements[pos, :] - 1], axis=1).astype(bool) + elist = elist - np.sum(nodeonHO[md.mesh.elements[pos, :] - 1], axis=1).astype(bool) + pos1 = np.where(elist == 1)[0] + FSflag[pos[pos1]] = True + HOFSflag[pos[pos1]] = False + pos2 = np.where(elist == - 1)[0] + HOflag[pos[pos2]] = True + HOFSflag[pos[pos2]] = False + + #Recompute nodes associated to these elements + nodeonFS[:] = False + nodeonFS[md.mesh.elements[np.where(FSflag), :] - 1] = True + nodeonHO[:] = False + nodeonHO[md.mesh.elements[np.where(HOflag), :] - 1] = True + nodeonHOFS[:] = False + nodeonHOFS[md.mesh.elements[np.where(HOFSflag), :] - 1] = True + elif any(FSflag) and any(SSAflag): + #Find node at the border + nodeonSSAFS[np.where(np.logical_and(nodeonSSA, nodeonFS))] = True + #FS elements in contact with this layer become SSAFS elements + matrixelements = nodeonSSAFS[md.mesh.elements - 1] + commonelements = np.sum(matrixelements, axis=1) != 0 + commonelements[np.where(SSAflag)] = False #only one layer: the elements previously in SSA + FSflag[np.where(commonelements)] = False #these elements are now SSASSAelements + SSAFSflag[np.where(commonelements)] = True + nodeonFS = np.zeros(md.mesh.numberofvertices, bool) + nodeonFS[md.mesh.elements[np.where(FSflag), :] - 1] = True + + #rule out elements that don't touch the 2 boundaries + pos = np.where(SSAFSflag)[0] + elist = np.zeros(np.size(pos), dtype=int) + elist = elist + np.sum(nodeonSSA[md.mesh.elements[pos, :] - 1], axis=1).astype(bool) + elist = elist - np.sum(nodeonFS[md.mesh.elements[pos, :] - 1], axis=1).astype(bool) + pos1 = np.where(elist == 1)[0] + SSAflag[pos[pos1]] = True + SSAFSflag[pos[pos1]] = False + pos2 = np.where(elist == - 1)[0] + FSflag[pos[pos2]] = True + SSAFSflag[pos[pos2]] = False + + #Recompute nodes associated to these elements + nodeonSSA[:] = False + nodeonSSA[md.mesh.elements[np.where(SSAflag), :] - 1] = True + nodeonFS[:] = False + nodeonFS[md.mesh.elements[np.where(FSflag), :] - 1] = True + nodeonSSAFS[:] = False + nodeonSSAFS[md.mesh.elements[np.where(SSAFSflag), :] - 1] = True + + elif any(FSflag) and any(SIAflag): + raise TypeError("type of coupling not supported yet") + + #Create SSAHOApproximation where needed + md.flowequation.element_equation = np.zeros(md.mesh.numberofelements, int) + md.flowequation.element_equation[np.where(noneflag)] = 0 + md.flowequation.element_equation[np.where(SIAflag)] = 1 + md.flowequation.element_equation[np.where(SSAflag)] = 2 + md.flowequation.element_equation[np.where(L1L2flag)] = 3 + md.flowequation.element_equation[np.where(HOflag)] = 4 + md.flowequation.element_equation[np.where(FSflag)] = 5 + md.flowequation.element_equation[np.where(SSAHOflag)] = 6 + md.flowequation.element_equation[np.where(SSAFSflag)] = 7 + md.flowequation.element_equation[np.where(HOFSflag)] = 8 + + #border + md.flowequation.borderHO = nodeonHO + md.flowequation.borderSSA = nodeonSSA + md.flowequation.borderFS = nodeonFS + + #Create vertices_type + md.flowequation.vertex_equation = np.zeros(md.mesh.numberofvertices, int) + pos = np.where(nodeonSSA) + md.flowequation.vertex_equation[pos] = 2 + pos = np.where(nodeonL1L2) + md.flowequation.vertex_equation[pos] = 3 + pos = np.where(nodeonHO) + md.flowequation.vertex_equation[pos] = 4 + pos = np.where(nodeonFS) + md.flowequation.vertex_equation[pos] = 5 + #DO SIA LAST! Otherwise spcs might not be set up correctly (SIA should have priority) + pos = np.where(nodeonSIA) + md.flowequation.vertex_equation[pos] = 1 + if any(FSflag): + pos = np.where(np.logical_not(nodeonFS)) + if not (any(HOflag) or any(SSAflag)): + md.flowequation.vertex_equation[pos] = 0 + pos = np.where(nodeonSSAHO) + md.flowequation.vertex_equation[pos] = 6 + pos = np.where(nodeonHOFS) + md.flowequation.vertex_equation[pos] = 7 + pos = np.where(nodeonSSAFS) + md.flowequation.vertex_equation[pos] = 8 + + #figure out solution types + md.flowequation.isSIA = any(md.flowequation.element_equation == 1) + md.flowequation.isSSA = any(md.flowequation.element_equation == 2) + md.flowequation.isL1L2 = any(md.flowequation.element_equation == 3) + md.flowequation.isHO = any(md.flowequation.element_equation == 4) + md.flowequation.isFS = any(md.flowequation.element_equation == 5) + + return md + + #Check that tiling can work: + if any(md.flowequation.borderSSA) and any(md.flowequation.borderHO) and any(md.flowequation.borderHO + md.flowequation.borderSSA != 1): + raise TypeError("error coupling domain too irregular") + if any(md.flowequation.borderSSA) and any(md.flowequation.borderFS) and any(md.flowequation.borderFS + md.flowequation.borderSSA != 1): + raise TypeError("error coupling domain too irregular") + if any(md.flowequation.borderFS) and any(md.flowequation.borderHO) and any(md.flowequation.borderHO + md.flowequation.borderFS != 1): + raise TypeError("error coupling domain too irregular") + + return md Index: /issm/trunk-jpl/src/m/parameterization/sethydrostaticmask.py =================================================================== --- /issm/trunk-jpl/src/m/parameterization/sethydrostaticmask.py (revision 24212) +++ /issm/trunk-jpl/src/m/parameterization/sethydrostaticmask.py (revision 24213) @@ -1,35 +1,31 @@ import numpy as np -import os -from model import model -from FlagElements import FlagElements -import pairoptions -from ContourToMesh import ContourToMesh -def setmask(md) - """ - SETHYDROSTATICMASK - establish groundedice_levelset field - Determines grounded and floating ice position based on +def setmask(md): + """ + SETHYDROSTATICMASK - establish groundedice_levelset field + + Determines grounded and floating ice position based on md.geometry.bed and md.geometry.thickness Usage: - md=sethydrostaticmask(md) + md = sethydrostaticmask(md) Examples: - md=sethydrostaticmask(md); + md = sethydrostaticmask(md) """ - if np.size(md.geometry.bed,axis=0)!=md.mesh.numberofvertices or np.size(md.geometry.base,axis=0)!=md.mesh.numberofvertices or np.size(md.geometry.thickness,axis=0)!=md.mesh.numberofvertices: - raise IOError("hydrostaticmask error message: fields in md.geometry do not have the right size.") + if np.size(md.geometry.bed, axis=0) != md.mesh.numberofvertices or np.size(md.geometry.base, axis=0) != md.mesh.numberofvertices or np.size(md.geometry.thickness, axis=0) != md.mesh.numberofvertices: + raise IOError("hydrostaticmask error message: fields in md.geometry do not have the right size.") - # grounded ice level set - md.mask.groundedice_levelset=md.geometry.thickness+md.geometry.bed*md.materials.rho_water/md.materials.rho_ice + # grounded ice level set + md.mask.groundedice_levelset = md.geometry.thickness + md.geometry.bed * md.materials.rho_water / md.materials.rho_ice - #Check consistency of geometry - if any(md.geometry.base[np.nonzero(md.mask.groundedice_levelset>0.)]!=md.geometry.bed[np.nonzero(md.mask.groundedice_levelset>0.)]): - print "WARNING: md.geometry.bed and md.geometry.base not equal on grounded ice" + #Check consistency of geometry + if any(md.geometry.base[np.nonzero(md.mask.groundedice_levelset > 0.)] != md.geometry.bed[np.nonzero(md.mask.groundedice_levelset > 0.)]): + print("WARNING: md.geometry.bed and md.geometry.base not equal on grounded ice") - if any(md.geometry.base[np.nonzero(md.mask.groundedice_levelset<=0.)]0: - lims=[data.min(),data.max()] - else: - lims=[0,1] + if len(data) > 0: + lims = [data.min(), data.max()] + else: + lims = [0, 1] # }}} # {{{ shading TODO @@ -174,59 +173,60 @@ # {{{ grid if options.exist('grid'): - if 'on' in options.getfieldvalue('grid','on'): + if 'on' in options.getfieldvalue('grid', 'on'): ax.grid() # }}} # {{{ colormap if options.exist('colornorm'): - norm=options.getfieldvalue('colornorm') + norm = options.getfieldvalue('colornorm') if options.exist('colormap'): - cmap=getcolormap(options) - cbar_extend=0 + cmap = getcolormap(options) + cbar_extend = 0 if options.exist('cmap_set_over'): - cbar_extend+=1 + cbar_extend += 1 if options.exist('cmap_set_under'): - cbar_extend+=2 + cbar_extend += 2 # }}} # {{{ contours if options.exist('contourlevels'): - plot_contour(md,data,options,ax) + plot_contour(md, data, options, ax) # }}} # {{{ wrapping TODO # }}} # {{{ colorbar - if options.getfieldvalue('colorbar',1)==1: - if cbar_extend==0: - extend='neither' - elif cbar_extend==1: - extend='max' - elif cbar_extend==2: - extend='min' - elif cbar_extend==3: - extend='both' - - cb = mpl.colorbar.ColorbarBase(ax.cax,cmap=cmap, norm=norm, extend=extend) + if options.getfieldvalue('colorbar', 1) == 1: + if cbar_extend == 0: + extend = 'neither' + elif cbar_extend == 1: + extend = 'max' + elif cbar_extend == 2: + extend = 'min' + elif cbar_extend == 3: + extend = 'both' + + cb = mpl.colorbar.ColorbarBase(ax.cax, cmap=cmap, norm=norm, extend=extend) if options.exist('alpha'): cb.set_alpha(options.getfieldvalue('alpha')) if options.exist('colorbarnumticks'): - cb.locator=MaxNLocator(nbins=options.getfieldvalue('colorbarnumticks',5)) - else: - cb.locator=MaxNLocator(nbins=5) # default 5 ticks + cb.locator = MaxNLocator(nbins=options.getfieldvalue('colorbarnumticks', 5)) + else: + cb.locator = MaxNLocator(nbins=5) # default 5 ticks if options.exist('colorbartickspacing'): - locs=np.arange(lims[0],lims[1]+1,options.getfieldvalue('colorbartickspacing')) + locs = np.arange(lims[0], lims[1] + 1, options.getfieldvalue('colorbartickspacing')) cb.set_ticks(locs) if options.exist('colorbarlines'): - locs=np.arange(lims[0],lims[1]+1,options.getfieldvalue('colorbarlines')) - cb.add_lines(locs,['k' for i in range(len(locs))],np.ones_like(locs)) + locs = np.arange(lims[0], lims[1] + 1, options.getfieldvalue('colorbarlines')) + cb.add_lines(locs, ['k' for i in range(len(locs))], np.ones_like(locs)) if options.exist('colorbarlineatvalue'): - locs=options.getfieldvalue('colorbarlineatvalue') - colors=options.getfieldvalue('colorbarlineatvaluecolor',['k' for i in range (len(locs))]) - widths=options.getfieldvalue('colorbarlineatvaluewidth',np.ones_like(locs)) - cb.add_lines(locs,colors,widths) + locs = options.getfieldvalue('colorbarlineatvalue') + colors = options.getfieldvalue('colorbarlineatvaluecolor', ['k' for i in range(len(locs))]) + widths = options.getfieldvalue('colorbarlineatvaluewidth', np.ones_like(locs)) + cb.add_lines(locs, colors, widths) if options.exist('colorbartitle'): if options.exist('colorbartitlepad'): cb.set_label(options.getfieldvalue('colorbartitle'), - labelpad=options.getfieldvalue('colorbartitlepad'),fontsize=fontsize) + labelpad=options.getfieldvalue('colorbartitlepad'), + fontsize=fontsize) else: - cb.set_label(options.getfieldvalue('colorbartitle'),fontsize=fontsize) + cb.set_label(options.getfieldvalue('colorbartitle'), fontsize=fontsize) cb.ax.tick_params(labelsize=fontsize) cb.solids.set_rasterized(True) @@ -234,16 +234,16 @@ cb.draw_all() if options.exist('colorbarfontsize'): - colorbarfontsize=options.getfieldvalue('colorbarfontsize') + colorbarfontsize = options.getfieldvalue('colorbarfontsize') cb.ax.tick_params(labelsize=colorbarfontsize) - # cb.set_ticks([0,-10]) - # cb.set_ticklabels([-10,0,10]) + # cb.set_ticks([0, - 10]) + # cb.set_ticklabels([-10, 0, 10]) if options.exist('colorbarticks'): - colorbarticks=options.getfieldvalue('colorbarticks') + colorbarticks = options.getfieldvalue('colorbarticks') cb.set_ticks(colorbarticks) - plt.sca(ax) # return to original axes control + plt.sca(ax) # return to original axes control # }}} # {{{ expdisp if options.exist('expdisp'): - expdisp(ax,options) + expdisp(ax, options) # }}} # {{{ area TODO @@ -251,13 +251,13 @@ # {{{ text if options.exist('text'): - text=options.getfieldvalue('text') - textx=options.getfieldvalue('textx') - texty=options.getfieldvalue('texty') - textcolor=options.getfieldvalue('textcolor') - textweight=options.getfieldvalue('textweight') - textrotation=options.getfieldvalue('textrotation') - textfontsize=options.getfieldvalue('textfontsize') - for label,x,y,size,color,weight,rotation in zip(text,textx,texty,textfontsize,textcolor,textweight,textrotation): - ax.text(x,y,label,transform=ax.transAxes,fontsize=size,color=color,weight=weight,rotation=rotation) + text = options.getfieldvalue('text') + textx = options.getfieldvalue('textx') + texty = options.getfieldvalue('texty') + textcolor = options.getfieldvalue('textcolor') + textweight = options.getfieldvalue('textweight') + textrotation = options.getfieldvalue('textrotation') + textfontsize = options.getfieldvalue('textfontsize') + for label, x, y, size, color, weight, rotation in zip(text, textx, texty, textfontsize, textcolor, textweight, textrotation): + ax.text(x, y, label, transform=ax.transAxes, fontsize=size, color=color, weight=weight, rotation=rotation) # }}} # {{{ north arrow TODO @@ -267,5 +267,5 @@ # {{{ streamlines TOFIX if options.exist('streamlines'): - plot_streamlines(md,options,ax) + plot_streamlines(md, options, ax) # }}} # {{{ axis positions TODO Index: /issm/trunk-jpl/src/m/plot/checkplotoptions.py =================================================================== --- /issm/trunk-jpl/src/m/plot/checkplotoptions.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/checkplotoptions.py (revision 24213) @@ -1,162 +1,170 @@ -import numpy as np +import numpy as np -def checkplotoptions(md,options): - ''' - CHECKPLOTOPTIONS - build a structure that holds all plot options - Usage: - options=checkplotoptions(md,options) +def checkplotoptions(md, options): + ''' + CHECKPLOTOPTIONS - build a structure that holds all plot options - See also: PLOTMODEL + Usage: + options = checkplotoptions(md, options) - NOTE: not fully implemented yet - ''' + See also: PLOTMODEL - # {{{ units - if options.exist('unit'): - if 'km' in options.getfieldvalue('unit','km'): - options.changefieldvalue('unit',10**-3) - elif '100km' in options.getfieldvalue('unit','100km'): - options.changefieldvalue('unit',10**-5) - # }}} - # {{{ density - if options.exist('density'): - density=options.getfieldvalue('density') - options.changefieldvalue('density',abs(ceil(density))) - # }}} - # {{{ show section - if options.exist('showsection'): - if 'on' in options.getfieldvalue('showsection','on'): - options.changefieldvalue('showsection',4) - # }}} - # {{{ smooth values - if options.exist('smooth'): - if 'on' in options.getfieldvalue('smooth','on'): - options.changefieldvalue('smooth',0) - # }}} - # {{{ contouronly values - if options.exist('contouronly'): - if 'on' in options.getfieldvalue('contouronly','on'): - options.changefieldvalue('contouronly',1) - # }}} - # {{{ colorbar - if options.exist('colorbar'): - if 'on' in options.getfieldvalue('colorbar','on'): - options.changefieldvalue('colorbar',1) - elif 'off' in options.getfieldvalue('colorbar','off'): - options.changefieldvalue('colorbar',0) - # }}} - # {{{ text - if options.exist('text'): - # text values (coerce to list for consistent functionality) - textlist=[] - text=options.getfieldvalue('text','default text') - textlist.extend([text] if isinstance(text,str) else text) - numtext=len(textlist) - # text position - textpos=options.getfieldvalue('textposition',[0.5,0.5]) - if not isinstance(textpos,list): - raise Exception('textposition should be passed as a list') - if any(isinstance(i,list) for i in textpos): - textx=[item[0] for item in textpos] - texty=[item[1] for item in textpos] - else: - textx=[textpos[0]] - texty=[textpos[1]] - if len(textx)!=numtext or len(texty)!=numtext: - raise Exception('textposition should contain one list of x,y vertices for every text instance') + NOTE: not fully implemented yet + ''' - # font size - if options.exist('textfontsize'): - textfontsize=options.getfieldvalue('textfontsize',12) - sizelist=[] - sizelist.extend(textsize if isinstance(textfontsize,list) else [textfontsize]) - else: - sizelist=[12] - if len(sizelist)==1: - sizelist=np.tile(sizelist,numtext) + # {{{ units + if options.exist('unit'): + if 'km' in options.getfieldvalue('unit', 'km'): + options.changefieldvalue('unit', 10**- 3) + elif '100km' in options.getfieldvalue('unit', '100km'): + options.changefieldvalue('unit', 10**- 5) + # }}} + # {{{ density + if options.exist('density'): + density = options.getfieldvalue('density') + options.changefieldvalue('density', abs(np.ceil(density))) + # }}} + # {{{ show section + if options.exist('showsection'): + if 'on' in options.getfieldvalue('showsection', 'on'): + options.changefieldvalue('showsection', 4) + # }}} + # {{{ smooth values + if options.exist('smooth'): + if 'on' in options.getfieldvalue('smooth', 'on'): + options.changefieldvalue('smooth', 0) + # }}} + # {{{ contouronly values + if options.exist('contouronly'): + if 'on' in options.getfieldvalue('contouronly', 'on'): + options.changefieldvalue('contouronly', 1) + # }}} + # {{{ colorbar + if options.exist('colorbar'): + if 'on' in options.getfieldvalue('colorbar', 'on'): + options.changefieldvalue('colorbar', 1) + elif 'off' in options.getfieldvalue('colorbar', 'off'): + options.changefieldvalue('colorbar', 0) + # }}} + # {{{ layer + if options.exist('layer'): + if options.getfieldvalue('layer') == 0: + raise Exception('Due to Matlab history first layer is numbered 1') + if options.getfieldvalue('layer') == md.mesh.numberoflayers - 1: + print('WARNING : you are plotting layer {}, surface is layer{}.'.format(md.mesh.numberoflayers - 1, md.mesh.numberoflayers)) + # }}} + # {{{ text + if options.exist('text'): + # text values (coerce to list for consistent functionality) + textlist = [] + text = options.getfieldvalue('text', 'default text') + textlist.extend([text] if isinstance(text, str) else text) + numtext = len(textlist) + # text position + textpos = options.getfieldvalue('textposition', [0.5, 0.5]) + if not isinstance(textpos, list): + raise Exception('textposition should be passed as a list') + if any(isinstance(i, list) for i in textpos): + textx = [item[0] for item in textpos] + texty = [item[1] for item in textpos] + else: + textx = [textpos[0]] + texty = [textpos[1]] + if len(textx) != numtext or len(texty) != numtext: + raise Exception('textposition should contain one list of x, y vertices for every text instance') - # font color - if options.exist('textcolor'): - textcolor=options.getfieldvalue('textcolor','k') - colorlist=[] - colorlist.extend(textcolor if isinstance(textcolor,list) else [textcolor]) - else: - colorlist=['k'] - if len(colorlist)==1: - colorlist=np.tile(colorlist,numtext) + # font size + if options.exist('textfontsize'): + textfontsize = options.getfieldvalue('textfontsize', 12) + sizelist = [] + sizelist.extend(textfontsize if isinstance(textfontsize, list) else [textfontsize]) + else: + sizelist = [12] + if len(sizelist) == 1: + sizelist = np.tile(sizelist, numtext) - # textweight - if options.exist('textweight'): - textweight=options.getfieldvalue('textweight') - weightlist=[] - weightlist.extend(textweight if isinstance(textweight,list) else [textweight]) - else: - weightlist=['normal'] - if len(weightlist)==1: - weightlist=np.tile(weightlist,numtext) + # font color + if options.exist('textcolor'): + textcolor = options.getfieldvalue('textcolor', 'k') + colorlist = [] + colorlist.extend(textcolor if isinstance(textcolor, list) else [textcolor]) + else: + colorlist = ['k'] + if len(colorlist) == 1: + colorlist = np.tile(colorlist, numtext) - # text rotation - if options.exist('textrotation'): - textrotation=options.getfieldvalue('textrotation',0) - rotationlist=[] - rotationlist.extend(textrotation if isinstance(textrotation,list) else [textrotation]) - else: - rotationlist=[0] - if len(rotationlist)==1: - rotationlist=np.tile(rotationlist,numtext) + # textweight + if options.exist('textweight'): + textweight = options.getfieldvalue('textweight') + weightlist = [] + weightlist.extend(textweight if isinstance(textweight, list) else [textweight]) + else: + weightlist = ['normal'] + if len(weightlist) == 1: + weightlist = np.tile(weightlist, numtext) - options.changefieldvalue('text',textlist) - options.addfield('textx',textx) - options.addfield('texty',texty) - options.changefieldvalue('textfontsize',sizelist) - options.changefieldvalue('textcolor',colorlist) - options.changefieldvalue('textweight',weightlist) - options.changefieldvalue('textrotation',rotationlist) - # }}} - # {{{ expdisp - expdispvaluesarray=[] - expstylevaluesarray=[] - expstylevalues=[] - if options.exist('expstyle'): - expstylevalues=options.getfieldvalue('expstyle') - if type(expstylevalues)==str: - expstylevalues=[expstylevalues] - if options.exist('expdisp'): - expdispvalues=options.getfieldvalue('expdisp') - if type(expdispvalues)==str: - expdispvalues=[expdispvalues] - for i in np.arange(len(expdispvalues)): - expdispvaluesarray.append(expdispvalues[i]) - if len(expstylevalues)>i: - expstylevaluesarray.append(expstylevalues[i]) - else: - expstylevaluesarray.append('-k') - options.changefieldvalue('expstyle',expstylevaluesarray) - options.changefieldvalue('expdisp',expdispvaluesarray) - # }}} - # {{{ latlonnumbering - if options.exist('latlonclick'): - if 'on' in options.getfieldvalue('latlonclick','on'): - options.changefieldvalue('latlonclick',1) - # }}} - # {{{ northarrow - if options.exist('northarrow'): - if 'on' in options.getfieldvalue('northarrow','on'): - #default values - Lx=max(md.mesh.x)-min(md.mesh.x) - Ly=max(md.mesh.y)-min(md.mesh.y) - options.changefieldvalue('northarrow',[min(md.mesh.x)+1./6.*Lx, min(md.mesh.y)+5./6.*Ly, 1./15.*Ly, 0.25, 1./250.*Ly]) - # }}} - # {{{ scale ruler - if options.exist('scaleruler'): - if 'on' in options.getfieldvalue('scaleruler','off'): - Lx=max(md.mesh.x)-min(md.mesh.x) - Ly=max(md.mesh.y)-min(md.mesh.y) - options.changefieldvalue('scaleruler',[min(md.mesh.x)+6./8.*Lx, min(md.mesh.y)+1./10.*Ly, 10**(np.ceil(np.log10(Lx)))/5, np.floor(Lx/100), 5]) - # }}} - # {{{ log scale - if options.exist('log'): - options.changefieldvalue('cutoff',np.log10(options.getfieldvalue('cutoff',1.5))/np.log10(options.getfieldvalue('log'))) - # }}} - return options + # text rotation + if options.exist('textrotation'): + textrotation = options.getfieldvalue('textrotation', 0) + rotationlist = [] + rotationlist.extend(textrotation if isinstance(textrotation, list) else [textrotation]) + else: + rotationlist = [0] + if len(rotationlist) == 1: + rotationlist = np.tile(rotationlist, numtext) + + options.changefieldvalue('text', textlist) + options.addfield('textx', textx) + options.addfield('texty', texty) + options.changefieldvalue('textfontsize', sizelist) + options.changefieldvalue('textcolor', colorlist) + options.changefieldvalue('textweight', weightlist) + options.changefieldvalue('textrotation', rotationlist) + # }}} + # {{{ expdisp + expdispvaluesarray = [] + expstylevaluesarray = [] + expstylevalues = [] + if options.exist('expstyle'): + expstylevalues = options.getfieldvalue('expstyle') + if type(expstylevalues) == str: + expstylevalues = [expstylevalues] + if options.exist('expdisp'): + expdispvalues = options.getfieldvalue('expdisp') + if type(expdispvalues) == str: + expdispvalues = [expdispvalues] + for i in np.arange(len(expdispvalues)): + expdispvaluesarray.append(expdispvalues[i]) + if len(expstylevalues) > i: + expstylevaluesarray.append(expstylevalues[i]) + else: + expstylevaluesarray.append(' - k') + options.changefieldvalue('expstyle', expstylevaluesarray) + options.changefieldvalue('expdisp', expdispvaluesarray) + # }}} + # {{{ latlonnumbering + if options.exist('latlonclick'): + if 'on' in options.getfieldvalue('latlonclick', 'on'): + options.changefieldvalue('latlonclick', 1) + # }}} + # {{{ northarrow + if options.exist('northarrow'): + if 'on' in options.getfieldvalue('northarrow', 'on'): + #default values + Lx = max(md.mesh.x) - min(md.mesh.x) + Ly = max(md.mesh.y) - min(md.mesh.y) + options.changefieldvalue('northarrow', [min(md.mesh.x) + 1. / 6. * Lx, min(md.mesh.y) + 5. / 6. * Ly, 1. / 15. * Ly, 0.25, 1. / 250. * Ly]) + # }}} + # {{{ scale ruler + if options.exist('scaleruler'): + if 'on' in options.getfieldvalue('scaleruler', 'off'): + Lx = max(md.mesh.x) - min(md.mesh.x) + Ly = max(md.mesh.y) - min(md.mesh.y) + options.changefieldvalue('scaleruler', [min(md.mesh.x) + 6. / 8. * Lx, min(md.mesh.y) + 1. / 10. * Ly, 10**(np.ceil(np.log10(Lx))) / 5, np.floor(Lx / 100), 5]) + # }}} + # {{{ log scale + if options.exist('log'): + options.changefieldvalue('cutoff', np.log10(options.getfieldvalue('cutoff', 1.5)) / np.log10(options.getfieldvalue('log'))) + # }}} + return options Index: /issm/trunk-jpl/src/m/plot/colormaps/cmaptools.py =================================================================== --- /issm/trunk-jpl/src/m/plot/colormaps/cmaptools.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/colormaps/cmaptools.py (revision 24213) @@ -1,30 +1,30 @@ -import numpy as np -from demmap import * +import numpy as np try: - import matplotlib as mpl - import matplotlib.pyplot as plt - from matplotlib.colors import ListedColormap, rgb_to_hsv, hsv_to_rgb + import matplotlib as mpl + import matplotlib.pyplot as plt + from matplotlib.colors import ListedColormap, hsv_to_rgb except ImportError: - print('cannot import matplotlib, no plotting capabilities enabled') + print('cannot import matplotlib, no plotting capabilities enabled') + def getcolormap(options): ''' get colormap from options and apply - + default: viridis supported: matplotlib defaults (see: pyplot.colormaps()) Rignot - demmap(50,-300,1200) - demmap(50,-300,1200,'ibcao') - + demmap(50, - 300, 1200) + demmap(50, - 300, 1200, 'ibcao') + Usage: cmap = getcolormap(options) ''' - + map_name = options.getfieldvalue('colormap') cmap = 'viridis' - + # already a valid colormap, the name of a valid colormap, or empty (use default) if type(map_name) == mpl.colors.ListedColormap: @@ -34,16 +34,16 @@ elif map_name == '': return cmap - + # if we don't have a matching colormap, build one if map_name == 'Rignot': - alpha=options.getfieldvalue('alpha',1) - cmap = np.array((np.linspace(0,1,128,False),np.ones(128,),np.ones(128,))).T - cmap[:,1] =np.maximum(np.minimum((0.1+cmap[:,0]**(1/alpha)),1),0) + alpha = options.getfieldvalue('alpha', 1) + cmap = np.array((np.linspace(0, 1, 128, False), np.ones(128, ), np.ones(128, ))).T + cmap[:, 1] = np.maximum(np.minimum((0.1 + cmap[:, 0]**(1 / alpha)), 1), 0) cmap = hsv_to_rgb(cmap) - # construct a colormap object from an array of shape (n,3/4) + # construct a colormap object from an array of shape (n, 3 / 4) cmap = ListedColormap(cmap) - + #elif map_name == 'Ala': - + else: # map is a library or executable function that constructs a colormap, @@ -52,5 +52,5 @@ cmap = ListedColormap(eval(map_name)) except: - raise RuntimeError("getcolormap: Error: provided colormap must be supported map or map-constructing function with syntax: 'jet' or 'function(args)'") + raise RuntimeError("getcolormap: Error: provided colormap must be supported map or map - constructing function with syntax: 'jet' or 'function(args)'") return cmap @@ -58,19 +58,18 @@ def truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100): - ''' - truncate a colormap within normalized limits [0,1] + ''' + truncate a colormap within normalized limits [0, 1] - cmap - a matplotlib colormap - minval - minimum value, normalized, of cmap to be returned. - maxval - maximum value, normalized, of cmap to be returned. - n - number of levels to use in constructing the new colormap + cmap - a matplotlib colormap + minval - minimum value, normalized, of cmap to be returned. + maxval - maximum value, normalized, of cmap to be returned. + n - number of levels to use in constructing the new colormap - Example: - newcmap=truncate_colormap(oldcmap,minval=0.2,maxval=0.8,n=128) + Example: + newcmap = truncate_colormap(oldcmap, minval = 0.2, maxval = 0.8, n = 128) - ''' + ''' - new_cmap = mpl.colors.LinearSegmentedColormap.from_list('trunc({n},{a:.2f},{b:.2f})'.format(n=cmap.name, - a=minval, b=maxval), cmap(np.linspace(minval, maxval, n))) - - return new_cmap + new_cmap = mpl.colors.LinearSegmentedColormap.from_list('trunc({n}, {a:.2f}, {b:.2f})'.format(n=cmap.name, a=minval, b=maxval), cmap(np.linspace(minval, maxval, n))) + + return new_cmap Index: /issm/trunk-jpl/src/m/plot/colormaps/demmap.py =================================================================== --- /issm/trunk-jpl/src/m/plot/colormaps/demmap.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/colormaps/demmap.py (revision 24213) @@ -5,22 +5,23 @@ from ibcao import ibcao -def demmap(ncolors,minZ,maxZ,colorscheme='dem'): + +def demmap(ncolors, minZ, maxZ, colorscheme='dem'): '''DEMMAP - concatenate sea and land color deping on zmin and zmax Usage: - cmap = demmap(n,zmin,zmax,colorscheme) + cmap = demmap(n, zmin, zmax, colorscheme) Example: - cmap = demmap(50,-300,1200) - cmap = demmap(50,-300,1200,'dem') - cmap = demmap(50,-300,1200,'ibcao') + cmap = demmap(50, - 300, 1200) + cmap = demmap(50, - 300, 1200, 'dem') + cmap = demmap(50, - 300, 1200, 'ibcao') ''' if type(colorscheme) != str: - raise RuntimeError('demmap: Error: optional argument "colorscheme" should be a string') + raise RuntimeError('demmap: Error: optional argument "colorscheme" should be a string') # determine appropriate number of sea and land colors if minZ == maxZ: - maxZ = minZ+1 + maxZ = minZ + 1 cmn = minZ @@ -36,15 +37,15 @@ else: # find optimal ratio of land to sea colors - maxminratio = maxZ/abs(minZ) - n1 = np.floor(ncolors/2) - n2 = np.ceil(ncolors/2) - if maxminratio>1: - sea = np.arange(1,n1+1) - land = np.arange(ncolors-1,n2-1,-1) + maxminratio = maxZ / abs(minZ) + n1 = np.floor(ncolors / 2) + n2 = np.ceil(ncolors / 2) + if maxminratio > 1: + sea = np.arange(1, n1 + 1) + land = np.arange(ncolors - 1, n2 - 1, - 1) else: - land = np.arange(1,n1+1) - sea = np.arange(ncolors-1,n2-1,-1) - - ratio = land/sea + land = np.arange(1, n1 + 1) + sea = np.arange(ncolors - 1, n2 - 1, - 1) + + ratio = land / sea errors = abs(ratio - maxminratio) / maxminratio indx = np.where(errors == min(errors)) @@ -52,24 +53,22 @@ nland = land[indx] - # determine color limits - seaint = abs(minZ)/nsea - landint = maxZ/nland + # determine color limits + seaint = abs(minZ) / nsea + landint = maxZ / nland if seaint >= landint: interval = seaint else: interval = landint - - cmn = -nsea*interval*(1 + 1e-9) # zero values treated as land - cmx = nland*interval + cmn = - nsea * interval * (1 + 1e-9) # zero values treated as land + cmx = nland * interval - clim = [cmn,cmx] + clim = [cmn, cmx] - if strcmpi(colorscheme,'dem'): + if strcmpi(colorscheme, 'dem'): # concatenate and transpose to match matplotlib's colormap format - cmap = np.concatenate((seacolor(nsea),landcolor(nland)**1.3),axis=1).T - elif strcmpi(colorscheme,'ibcao'): - cmap = ibcao(nsea,nland) - + cmap = np.concatenate((seacolor(nsea), landcolor(nland)**1.3), axis=1).T + elif strcmpi(colorscheme, 'ibcao'): + cmap = ibcao(nsea, nland) + return cmap - Index: /issm/trunk-jpl/src/m/plot/colormaps/ibcao.py =================================================================== --- /issm/trunk-jpl/src/m/plot/colormaps/ibcao.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/colormaps/ibcao.py (revision 24213) @@ -1,82 +1,79 @@ import numpy as np -def ibcao(nsea,nland): + +def ibcao(nsea, nland): '''IBCAO - IBCAO color map Usage: - map = ibcap(nsea,nland) + map = ibcap(nsea, nland) ''' - Jsea = [ - 0.18039,0.29020,0.57255, - 0.18039,0.29020,0.57255, - 0.05882,0.44314,0.65490, - 0.05882,0.44314,0.65490, - 0.02745,0.49804,0.73725, - 0.02745,0.49804,0.73725, - 0.01176,0.54510,0.78824, - 0.01176,0.54510,0.78824, - 0.00784,0.63529,0.83922, - 0.00784,0.63529,0.83922, - 0.06667,0.71765,0.86667, - 0.06667,0.71765,0.86667, - 0.17647,0.75294,1.00000, - 0.17647,0.75294,1.00000, - 0.23529,0.76471,0.85882, - 0.23529,0.76471,0.85882, - 0.24314,0.76471,0.83922, - 0.24314,0.76471,0.83922, - 0.25882,0.76078,0.81176, - 0.25882,0.76078,0.81176, - 0.27451,0.76078,0.76078, - 0.27451,0.76078,0.76078, - 0.41961,0.78431,0.74902, - 0.41961,0.78431,0.74902, - 0.60000,0.83137,0.74902, - 0.60000,0.83137,0.74902 - ] + Jsea = [0.18039, 0.29020, 0.57255, + 0.18039, 0.29020, 0.57255, + 0.05882, 0.44314, 0.65490, + 0.05882, 0.44314, 0.65490, + 0.02745, 0.49804, 0.73725, + 0.02745, 0.49804, 0.73725, + 0.01176, 0.54510, 0.78824, + 0.01176, 0.54510, 0.78824, + 0.00784, 0.63529, 0.83922, + 0.00784, 0.63529, 0.83922, + 0.06667, 0.71765, 0.86667, + 0.06667, 0.71765, 0.86667, + 0.17647, 0.75294, 1.00000, + 0.17647, 0.75294, 1.00000, + 0.23529, 0.76471, 0.85882, + 0.23529, 0.76471, 0.85882, + 0.24314, 0.76471, 0.83922, + 0.24314, 0.76471, 0.83922, + 0.25882, 0.76078, 0.81176, + 0.25882, 0.76078, 0.81176, + 0.27451, 0.76078, 0.76078, + 0.27451, 0.76078, 0.76078, + 0.41961, 0.78431, 0.74902, + 0.41961, 0.78431, 0.74902, + 0.60000, 0.83137, 0.74902, + 0.60000, 0.83137, 0.74902] - Jland = [ - 0.85098,0.84314,0.30588, - 0.85098,0.84314,0.30588, - 0.93333,0.89020,0.41961, - 0.93333,0.89020,0.41961, - 0.93725,0.80784,0.35686, - 0.93725,0.80784,0.35686, - 0.89804,0.74510,0.31765, - 0.89804,0.74510,0.31765, - 0.85098,0.63922,0.21961, - 0.85098,0.63922,0.21961, - 0.75686,0.55294,0.22353, - 0.75686,0.55294,0.22353, - 0.71765,0.50980,0.22353, - 0.71765,0.50980,0.22353, - 0.68627,0.48235,0.21961, - 0.68627,0.48235,0.21961, - 0.65490,0.45882,0.21569, - 0.65490,0.45882,0.21569, - 0.58824,0.39608,0.20392, - 0.58824,0.39608,0.20392, - 1.00000,1.00000,1.00000 - ] + Jland = [0.85098, 0.84314, 0.30588, + 0.85098, 0.84314, 0.30588, + 0.93333, 0.89020, 0.41961, + 0.93333, 0.89020, 0.41961, + 0.93725, 0.80784, 0.35686, + 0.93725, 0.80784, 0.35686, + 0.89804, 0.74510, 0.31765, + 0.89804, 0.74510, 0.31765, + 0.85098, 0.63922, 0.21961, + 0.85098, 0.63922, 0.21961, + 0.75686, 0.55294, 0.22353, + 0.75686, 0.55294, 0.22353, + 0.71765, 0.50980, 0.22353, + 0.71765, 0.50980, 0.22353, + 0.68627, 0.48235, 0.21961, + 0.68627, 0.48235, 0.21961, + 0.65490, 0.45882, 0.21569, + 0.65490, 0.45882, 0.21569, + 0.58824, 0.39608, 0.20392, + 0.58824, 0.39608, 0.20392, + 1.00000, 1.00000, 1.00000] - # Jsea and Jland are each a series of r,g,b triples, reshape them as such - - lsea = int(len(Jsea)/3) - Jsea = np.array(Jsea).reshape(lsea,3) - a = np.linspace(1,lsea,nsea) - b = np.arange(1,lsea+1) - # interpolate color on each channel r,g,b - ysea = np.array([np.interp(a, b, Jsea[:,i]) for i in range(3)]) + # Jsea and Jland are each a series of r, g, b triples, reshape them as such - lland = int(len(Jland)/3) - Jland = np.array(Jland).reshape(lland,3) - a = np.linspace(1,lland,nland) - b = np.arange(1,lland+1) - # interpolate color on each channel r,g,b - yland = np.array([np.interp(a, b, Jland[:,i]) for i in range(3)]) + lsea = int(len(Jsea) / 3) + Jsea = np.array(Jsea).reshape(lsea, 3) + a = np.linspace(1, lsea, nsea) + b = np.arange(1, lsea + 1) + # interpolate color on each channel r, g, b + ysea = np.array([np.interp(a, b, Jsea[:, i]) for i in range(3)]) + + lland = int(len(Jland) / 3) + Jland = np.array(Jland).reshape(lland, 3) + a = np.linspace(1, lland, nland) + b = np.arange(1, lland + 1) + # interpolate color on each channel r, g, b + yland = np.array([np.interp(a, b, Jland[:, i]) for i in range(3)]) # concatenate and transpose to match matplotlib's colormap format - map = np.concatenate((ysea,yland),axis=1).T + map = np.concatenate((ysea, yland), axis=1).T return map Index: /issm/trunk-jpl/src/m/plot/colormaps/landcolor.py =================================================================== --- /issm/trunk-jpl/src/m/plot/colormaps/landcolor.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/colormaps/landcolor.py (revision 24213) @@ -1,81 +1,80 @@ import numpy as np + def landcolor(n=256): '''LANDCOLOR Land colormap''' - J = [ - 0.095678,0.53427,0.21682, - 0.15785,0.5979,0.23274, - 0.21286,0.64673,0.2514, - 0.26411,0.68789,0.27268, - 0.32959,0.72416,0.31308, - 0.39794,0.75695,0.36038, - 0.46153,0.7871,0.40624, - 0.52108,0.81516,0.45135, - 0.57702,0.84152,0.49547, - 0.62973,0.86645,0.53891, - 0.67946,0.89016,0.58187, - 0.72647,0.91282,0.62427, - 0.77095,0.93455,0.66619, - 0.81306,0.95546,0.70772, - 0.85292,0.97563,0.7489, - 0.89066,0.99514,0.78976, - 0.88379,0.98595,0.77038, - 0.86389,0.96758,0.73236, - 0.84615,0.94972,0.69623, - 0.8303,0.93233,0.66186, - 0.81612,0.91536,0.6291, - 0.80341,0.8988,0.59784, - 0.79201,0.8826,0.56795, - 0.78191,0.86676,0.53946, - 0.7729,0.85123,0.51224, - 0.76479,0.83602,0.48615, - 0.75747,0.8211,0.46111, - 0.75084,0.80645,0.43704, - 0.74506,0.79206,0.41414, - 0.73981,0.77792,0.39211, - 0.73501,0.76401,0.37089, - 0.73068,0.75033,0.35052, - 0.72683,0.73685,0.33106, - 0.72042,0.72074,0.31228, - 0.71032,0.70085,0.29417, - 0.69761,0.67821,0.27694, - 0.68489,0.65558,0.26026, - 0.67235,0.63313,0.24418, - 0.65997,0.61082,0.22889, - 0.64775,0.58874,0.21406, - 0.63568,0.56689,0.19983, - 0.62376,0.54527,0.18622, - 0.61197,0.52391,0.17299, - 0.60033,0.50283,0.16046, - 0.58881,0.48203,0.14832, - 0.57742,0.46151,0.13667, - 0.56616,0.44133,0.12555, - 0.55502,0.4214,0.11472, - 0.54398,0.4019,0.10456, - 0.53306,0.38266,0.094633, - 0.52226,0.36382,0.085242, - 0.51155,0.3453,0.076179, - 0.50095,0.32714,0.067515, - 0.49045,0.30938,0.059259, - 0.48005,0.29193,0.051294, - 0.46973,0.27495,0.043796, - 0.45951,0.25823,0.0365, - 0.44938,0.24206,0.029715, - 0.43934,0.22609,0.023063, - 0.42938,0.21074,0.016949, - 0.41951,0.19556,0.010917, - 0.40971,0.18105,0.0054326, - 0.4,0.16667,0 - ] + J = [0.095678, 0.53427, 0.21682, + 0.15785, 0.5979, 0.23274, + 0.21286, 0.64673, 0.2514, + 0.26411, 0.68789, 0.27268, + 0.32959, 0.72416, 0.31308, + 0.39794, 0.75695, 0.36038, + 0.46153, 0.7871, 0.40624, + 0.52108, 0.81516, 0.45135, + 0.57702, 0.84152, 0.49547, + 0.62973, 0.86645, 0.53891, + 0.67946, 0.89016, 0.58187, + 0.72647, 0.91282, 0.62427, + 0.77095, 0.93455, 0.66619, + 0.81306, 0.95546, 0.70772, + 0.85292, 0.97563, 0.7489, + 0.89066, 0.99514, 0.78976, + 0.88379, 0.98595, 0.77038, + 0.86389, 0.96758, 0.73236, + 0.84615, 0.94972, 0.69623, + 0.8303, 0.93233, 0.66186, + 0.81612, 0.91536, 0.6291, + 0.80341, 0.8988, 0.59784, + 0.79201, 0.8826, 0.56795, + 0.78191, 0.86676, 0.53946, + 0.7729, 0.85123, 0.51224, + 0.76479, 0.83602, 0.48615, + 0.75747, 0.8211, 0.46111, + 0.75084, 0.80645, 0.43704, + 0.74506, 0.79206, 0.41414, + 0.73981, 0.77792, 0.39211, + 0.73501, 0.76401, 0.37089, + 0.73068, 0.75033, 0.35052, + 0.72683, 0.73685, 0.33106, + 0.72042, 0.72074, 0.31228, + 0.71032, 0.70085, 0.29417, + 0.69761, 0.67821, 0.27694, + 0.68489, 0.65558, 0.26026, + 0.67235, 0.63313, 0.24418, + 0.65997, 0.61082, 0.22889, + 0.64775, 0.58874, 0.21406, + 0.63568, 0.56689, 0.19983, + 0.62376, 0.54527, 0.18622, + 0.61197, 0.52391, 0.17299, + 0.60033, 0.50283, 0.16046, + 0.58881, 0.48203, 0.14832, + 0.57742, 0.46151, 0.13667, + 0.56616, 0.44133, 0.12555, + 0.55502, 0.4214, 0.11472, + 0.54398, 0.4019, 0.10456, + 0.53306, 0.38266, 0.094633, + 0.52226, 0.36382, 0.085242, + 0.51155, 0.3453, 0.076179, + 0.50095, 0.32714, 0.067515, + 0.49045, 0.30938, 0.059259, + 0.48005, 0.29193, 0.051294, + 0.46973, 0.27495, 0.043796, + 0.45951, 0.25823, 0.0365, + 0.44938, 0.24206, 0.029715, + 0.43934, 0.22609, 0.023063, + 0.42938, 0.21074, 0.016949, + 0.41951, 0.19556, 0.010917, + 0.40971, 0.18105, 0.0054326, + 0.4, 0.16667, 0] - # J is a series of r,g,b triples, reshape it as such - l = int(len(J)/3) - J = np.array(J).reshape(l,3) - a = np.linspace(1,l,n) - b = np.arange(1,l+1) + # J is a series of r, g, b triples, reshape it as such + length = int(len(J) / 3) + J = np.array(J).reshape(length, 3) + a = np.linspace(1, length, n) + b = np.arange(1, length + 1) - # interpolate color on each channel r,g,b - y = np.array([np.interp(a, b, J[:,i]) for i in range(3)]) + # interpolate color on each channel r, g, b + y = np.array([np.interp(a, b, J[:, i]) for i in range(3)]) return y Index: /issm/trunk-jpl/src/m/plot/colormaps/seacolor.py =================================================================== --- /issm/trunk-jpl/src/m/plot/colormaps/seacolor.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/colormaps/seacolor.py (revision 24213) @@ -1,62 +1,61 @@ import numpy as np + def seacolor(n=256): '''SEACOLOR Sea colormap''' - J = [ - 0.0392, 0, 0.4745, - 0.1020, 0, 0.5373, - 0.1020, 0, 0.5373, - 0.1490, 0, 0.5961, - 0.1490, 0, 0.5961, - 0.1059, 0.0118, 0.6510, - 0.1059, 0.0118, 0.6510, - 0.0627, 0.0235, 0.7059, - 0.0627, 0.0235, 0.7059, - 0.0196, 0.0353, 0.7569, - 0.0196, 0.0353, 0.7569, - 0, 0.0549, 0.7961, - 0, 0.0549, 0.7961, - 0, 0.0863, 0.8235, - 0, 0.0863, 0.8235, - 0, 0.1176, 0.8471, - 0, 0.1176, 0.8471, - 0, 0.1529, 0.8745, - 0, 0.1529, 0.8745, - 0.0471, 0.2667, 0.9059, - 0.0471, 0.2667, 0.9059, - 0.1020, 0.4000, 0.9412, - 0.1020, 0.4000, 0.9412, - 0.0745, 0.4588, 0.9569, - 0.0745, 0.4588, 0.9569, - 0.0549, 0.5216, 0.9765, - 0.0549, 0.5216, 0.9765, - 0.0824, 0.6196, 0.9882, - 0.0824, 0.6196, 0.9882, - 0.1176, 0.6980, 1.0000, - 0.1176, 0.6980, 1.0000, - 0.1686, 0.7294, 1.0000, - 0.1686, 0.7294, 1.0000, - 0.2157, 0.7569, 1.0000, - 0.2157, 0.7569, 1.0000, - 0.2549, 0.7843, 1.0000, - 0.2549, 0.7843, 1.0000, - 0.3098, 0.8235, 1.0000, - 0.3098, 0.8235, 1.0000, - 0.3686, 0.8745, 1.0000, - 0.3686, 0.8745, 1.0000, - 0.5412, 0.8902, 1.0000, - 0.5412, 0.8902, 1.0000, - 0.7373, 0.9020, 1.0000 - ] + J = [0.0392, 0, 0.4745, + 0.1020, 0, 0.5373, + 0.1020, 0, 0.5373, + 0.1490, 0, 0.5961, + 0.1490, 0, 0.5961, + 0.1059, 0.0118, 0.6510, + 0.1059, 0.0118, 0.6510, + 0.0627, 0.0235, 0.7059, + 0.0627, 0.0235, 0.7059, + 0.0196, 0.0353, 0.7569, + 0.0196, 0.0353, 0.7569, + 0, 0.0549, 0.7961, + 0, 0.0549, 0.7961, + 0, 0.0863, 0.8235, + 0, 0.0863, 0.8235, + 0, 0.1176, 0.8471, + 0, 0.1176, 0.8471, + 0, 0.1529, 0.8745, + 0, 0.1529, 0.8745, + 0.0471, 0.2667, 0.9059, + 0.0471, 0.2667, 0.9059, + 0.1020, 0.4000, 0.9412, + 0.1020, 0.4000, 0.9412, + 0.0745, 0.4588, 0.9569, + 0.0745, 0.4588, 0.9569, + 0.0549, 0.5216, 0.9765, + 0.0549, 0.5216, 0.9765, + 0.0824, 0.6196, 0.9882, + 0.0824, 0.6196, 0.9882, + 0.1176, 0.6980, 1.0000, + 0.1176, 0.6980, 1.0000, + 0.1686, 0.7294, 1.0000, + 0.1686, 0.7294, 1.0000, + 0.2157, 0.7569, 1.0000, + 0.2157, 0.7569, 1.0000, + 0.2549, 0.7843, 1.0000, + 0.2549, 0.7843, 1.0000, + 0.3098, 0.8235, 1.0000, + 0.3098, 0.8235, 1.0000, + 0.3686, 0.8745, 1.0000, + 0.3686, 0.8745, 1.0000, + 0.5412, 0.8902, 1.0000, + 0.5412, 0.8902, 1.0000, + 0.7373, 0.9020, 1.0000] - # J is a series of r,g,b triples, reshape it as such - l = int(len(J)/3) - J = np.array(J).reshape(l,3) - a = np.linspace(1,l,n) - b = np.arange(1,l+1) + # J is a series of r, g, b triples, reshape it as such + length = int(len(J) / 3) + J = np.array(J).reshape(length, 3) + a = np.linspace(1, length, n) + b = np.arange(1, length + 1) - # interpolate color on each channel r,g,b - y = np.array([np.interp(a, b, J[:,i]) for i in range(3)]) + # interpolate color on each channel r, g, b + y = np.array([np.interp(a, b, J[:, i]) for i in range(3)]) return y Index: /issm/trunk-jpl/src/m/plot/export_gl.py =================================================================== --- /issm/trunk-jpl/src/m/plot/export_gl.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/export_gl.py (revision 24213) @@ -2,123 +2,124 @@ from checkplotoptions import checkplotoptions from model import model -import numpy as np +import numpy as np import math from writejsfile import writejsfile -def export_gl(md,*varargin): - class ResultObj(object): - def __getattr__(self, attr): - return self.__dict__.get(attr) - print ('getting options') - templist=plotoptions(varargin); - optionslist=templist.list; - options=optionslist[1]; - options=checkplotoptions(md,options); - #print (templist,options) - #templist contains options 0-3. Use in the future to rework. - - #Setup unique directory in present dir: - print ('setting directory') - directory=optionslist[0].getfieldvalue('directory'); - databasename=optionslist[0].getfieldvalue('database'); - - #scaling factor: - print ('setting scaling factor') - scaling_factor=optionslist[0].getfieldvalue('scaling_factor'); +def export_gl(md, * varargin): + class ResultObj(object): + def __getattr__(self, attr): + return self.__dict__.get(attr) - #Deal with title: - print ('setting title') - if optionslist[0].exist('title'): - title=optionslist[0].getfieldvalue('title'); - else: - title=''; + print('getting options') + templist = plotoptions(varargin) + optionslist = templist.list + options = optionslist[1] + options = checkplotoptions(md, options) + #print (templist, options) + #templist contains options 0 - 3. Use in the future to rework. - #initialize model: - print ('initializing model') - model.title=title; - model.initialZoomFactor=options.getfieldvalue('zoom',-.25); + #Setup unique directory in present dir: + print('setting directory') + directory = optionslist[0].getfieldvalue('directory') + databasename = optionslist[0].getfieldvalue('database') - #Deal with contour {{{ - print ('getting contour') - print((md.mesh.segments)) - segmenets0 = [s - 1 for s in md.mesh.segments[:,0]]; - segmenets1 = [s - 1 for s in md.mesh.segments[:,1]]; - - contour_lat1=md.mesh.lat.take(segmenets0) - contour_lat2=md.mesh.lat.take(segmenets1); - contour_long1=md.mesh.long.take(segmenets0); - contour_long2=md.mesh.long.take(segmenets1); - contour_surface1=md.geometry.surface.take(segmenets0); - contour_surface2=md.geometry.surface.take(segmenets1); + #scaling factor: + print('setting scaling factor') + scaling_factor = optionslist[0].getfieldvalue('scaling_factor') - R1=6371000*np.ones(len(contour_surface1))+scaling_factor*contour_surface1; - R2=6371000*np.ones(len(contour_surface2))+scaling_factor*contour_surface2; + #Deal with title: + print('setting title') + if optionslist[0].exist('title'): + title = optionslist[0].getfieldvalue('title') + else: + title = '' - model.contourx1 = list(map(lambda r, lat, int: r * math.cos(math.radians(lat)) * math.cos(math.radians(int)), R1, contour_lat1, contour_long1)); - model.contoury1 = list(map(lambda r, lat, int: r * math.cos(math.radians(lat)) * math.sin(math.radians(int)), R1, contour_lat1, contour_long1)); - model.contourz1 = list(map(lambda r, lat: r * math.sin(math.radians(lat)), R1, contour_lat1)); - - model.contourx2 = list(map(lambda r, lat, int: r * math.cos(math.radians(lat)) * math.cos(math.radians(int)), R2, contour_lat2, contour_long2)); - model.contoury2 = list(map(lambda r, lat, int: r * math.cos(math.radians(lat)) * math.sin(math.radians(int)), R2, contour_lat2, contour_long2)); - model.contourz2 = list(map(lambda r, lat: r * math.sin(math.radians(lat)), R2, contour_lat2)); + #initialize model: + print('initializing model') + model.title = title + model.initialZoomFactor = options.getfieldvalue('zoom', - .25) - #}}} - #Deal with mesh and results {{{ - print ('getting mesh') - surface=md.geometry.surface.flatten(); - numberofelements=md.mesh.numberofelements; - numberofvertices=md.mesh.numberofvertices; - R=6371000*np.ones(len(md.mesh.lat))+scaling_factor*surface; - - x = list(map(lambda r, lat, int: r * math.cos(math.radians(lat)) * math.cos(math.radians(int)), R, md.mesh.lat,md.mesh.long)); - y = list(map(lambda r, lat, int: r * math.cos(math.radians(lat)) * math.sin(math.radians(int)), R, md.mesh.lat,md.mesh.long)); - z = list(map(lambda r, lat: r * math.sin(math.radians(lat)), R, md.mesh.lat)); - - #Deal with triangulation: - print('getting triangulation') - model.index=md.mesh.elements; - model.x=x; - model.y=y; - model.z=z; - model.surface=surface; - - results = [] - print(optionslist) - #Deal with data: - print('getting data') - for i in range(0,len(optionslist)): - options=optionslist[i]; - options=checkplotoptions(md,options); - data=options.getfieldvalue('data').flatten(); - results.append(ResultObj()) - results[i].data=data; - results[i].caxis=options.getfieldvalue('caxis',[min(data), max(data)]); + #Deal with contour {{{ + print('getting contour') + print(md.mesh.segments) + segmenets0 = [s - 1 for s in md.mesh.segments[:, 0]] + segmenets1 = [s - 1 for s in md.mesh.segments[:, 1]] - label=options.getfieldvalue('label',''); - if label=='': - #create generic label: - label=['data', str(i)]; - results[i].label=label; + contour_lat1 = md.mesh.lat.take(segmenets0) + contour_lat2 = md.mesh.lat.take(segmenets1) + contour_long1 = md.mesh.long.take(segmenets0) + contour_long2 = md.mesh.long.take(segmenets1) + contour_surface1 = md.geometry.surface.take(segmenets0) + contour_surface2 = md.geometry.surface.take(segmenets1) - shortlabel=options.getfieldvalue('shortlabel',''); - if shortlabel=='': - #create generic short label: - shortlabel=['data', str(i)]; - results[i].shortlabel=shortlabel; + R1 = 6371000 * np.ones(len(contour_surface1)) + scaling_factor * contour_surface1 + R2 = 6371000 * np.ones(len(contour_surface2)) + scaling_factor * contour_surface2 - if type(data[2])!=np.float64: - time_range=options.getfieldvalue('time_range',[0, 100]); - results[i].time_range=time_range; + model.contourx1 = list(map(lambda r, lat, int: r * math.cos(math.radians(lat)) * math.cos(math.radians(int)), R1, contour_lat1, contour_long1)) + model.contoury1 = list(map(lambda r, lat, int: r * math.cos(math.radians(lat)) * math.sin(math.radians(int)), R1, contour_lat1, contour_long1)) + model.contourz1 = list(map(lambda r, lat: r * math.sin(math.radians(lat)), R1, contour_lat1)) - unit=options.getfieldvalue('unit',''); - if unit=='': - #create generic unit: - unit='SI'; - results[i].unit=unit; - model.results=results; - - #Write model to javascript database file: - print('writing to file') - writejsfile(directory + databasename + '.js',model,databasename); -#}}} + model.contourx2 = list(map(lambda r, lat, int: r * math.cos(math.radians(lat)) * math.cos(math.radians(int)), R2, contour_lat2, contour_long2)) + model.contoury2 = list(map(lambda r, lat, int: r * math.cos(math.radians(lat)) * math.sin(math.radians(int)), R2, contour_lat2, contour_long2)) + model.contourz2 = list(map(lambda r, lat: r * math.sin(math.radians(lat)), R2, contour_lat2)) + + #}}} + #Deal with mesh and results {{{ + print('getting mesh') + surface = md.geometry.surface.flatten() + numberofelements = md.mesh.numberofelements + numberofvertices = md.mesh.numberofvertices + R = 6371000 * np.ones(len(md.mesh.lat)) + scaling_factor * surface + + x = list(map(lambda r, lat, int: r * math.cos(math.radians(lat)) * math.cos(math.radians(int)), R, md.mesh.lat, md.mesh.long)) + y = list(map(lambda r, lat, int: r * math.cos(math.radians(lat)) * math.sin(math.radians(int)), R, md.mesh.lat, md.mesh.long)) + z = list(map(lambda r, lat: r * math.sin(math.radians(lat)), R, md.mesh.lat)) + + #Deal with triangulation: + print('getting triangulation') + model.index = md.mesh.elements + model.x = x + model.y = y + model.z = z + model.surface = surface + + results = [] + print(optionslist) + #Deal with data: + print('getting data') + for i in range(0, len(optionslist)): + options = optionslist[i] + options = checkplotoptions(md, options) + data = options.getfieldvalue('data').flatten() + results.append(ResultObj()) + results[i].data = data + results[i].caxis = options.getfieldvalue('caxis', [min(data), max(data)]) + + label = options.getfieldvalue('label', '') + if label == '': + #create generic label: + label = ['data', str(i)] + results[i].label = label + + shortlabel = options.getfieldvalue('shortlabel', '') + if shortlabel == '': + #create generic short label: + shortlabel = ['data', str(i)] + results[i].shortlabel = shortlabel + + if type(data[2]) != np.float64: + time_range = options.getfieldvalue('time_range', [0, 100]) + results[i].time_range = time_range + + unit = options.getfieldvalue('unit', '') + if unit == '': + #create generic unit: + unit = 'SI' + results[i].unit = unit + model.results = results + + #Write model to javascript database file: + print('writing to file') + writejsfile(directory + databasename + '.js', model, databasename) + #}}} Index: /issm/trunk-jpl/src/m/plot/plot_BC.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plot_BC.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plot_BC.py (revision 24213) @@ -1,63 +1,70 @@ -try: - import pylab as p -except ImportError: - print("could not import pylab, matplotlib has not been installed, no plotting capabilities enabled") - -import numpy as np +import numpy as np from processmesh import processmesh from applyoptions import applyoptions from plot_icefront import plot_icefront +from hydrologydc import hydrologydc from mpl_toolkits.mplot3d import Axes3D +from mpl_toolkits.axes_grid1.inset_locator import inset_axes -def plot_BC(md,options,fig,axgrid,gridindex): - ''' - PLOT_BC - plot model boundary conditions - Usage: - plot_BC(md,options,fig,axes) +def plot_BC(md, options, fig, axgrid, gridindex): + ''' + PLOT_BC - plot model boundary conditions - See also: PLOTMODEL - ''' - x,y,z,elements,is2d,isplanet=processmesh(md,[],options) - - ax=axgrid[gridindex] - fig.delaxes(axgrid.cbar_axes[gridindex]) + Usage: + plot_BC(md, options, fig, axes) - if not is2d: - ax=inset_locator.inset_axes(axgrid[gridindex],width='100%',height='100%',loc=3,borderpad=0,axes_class=Axes3D) + See also: PLOTMODEL + ''' + x, y, z, elements, is2d, isplanet = processmesh(md, [], options) - #plot neuman - plot_icefront(md,options,fig,ax) + ax = axgrid[gridindex] + fig.delaxes(axgrid.cbar_axes[gridindex]) - XLims=[np.min(x),np.max(x)] - YLims=[np.min(y),np.max(y)] - #plot dirichlets - dirichleton=options.getfieldvalue('dirichlet','on') - if dirichleton=='on': - ax.scatter(x[np.where(~np.isnan(md.stressbalance.spcvx))], - y[np.where(~np.isnan(md.stressbalance.spcvx))], - marker='o',c='r',s=240,label='vx Dirichlet',linewidth=0) - ax.scatter(x[np.where(~np.isnan(md.stressbalance.spcvy))], - y[np.where(~np.isnan(md.stressbalance.spcvy))], - marker='o',c='b',s=160,label='vy Dirichlet',linewidth=0) - ax.scatter(x[np.where(~np.isnan(md.stressbalance.spcvz))], - y[np.where(~np.isnan(md.stressbalance.spcvz))], - marker='o',c='y',s=80,label='vz Dirichlet',linewidth=0) - try: - ax.scatter(x[np.where(~np.isnan(md.hydrology.spcepl_head))], - y[np.where(~np.isnan(md.hydrology.spcepl_head))], - marker='v',c='r',s=240,label='EPL Head',linewidth=0) - ax.scatter(x[np.where(~np.isnan(md.hydrology.spcsediment_head))], - y[np.where(~np.isnan(md.hydrology.spcsediment_head))], - marker='^',c='b',s=240,label='IDS head',linewidth=0) - except AttributeError: - print ('Not treating Hydrologydc, skipping these boundaries') - ax.set_xlim(XLims) - ax.set_ylim(YLims) - ax.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3, - ncol=3, mode="expand", borderaxespad=0.) - #apply options - options.addfielddefault('title','Boundary conditions') - options.addfielddefault('colorbar','off') - applyoptions(md,[],options,fig,axgrid,gridindex) - + if not is2d: + ax = inset_axes(axgrid[gridindex], width='100%', height='100%', loc=3, borderpad=0, axes_class=Axes3D) + + #plot neuman + plot_icefront(md, options, fig, ax) + + XLims = [np.min(x), np.max(x)] + YLims = [np.min(y), np.max(y)] + #plot dirichlets + dirichleton = options.getfieldvalue('dirichlet', 'on') + + if dirichleton == 'on': + #define what to plot with plot style + spc_dict = {'spcvx': ['stressbalance', 'o', 'r', 240, 'vx Dirichlet'], + 'spcvy': ['stressbalance', 'o', 'b', 160, 'vy Dirichlet']} + if not is2d: + spc_dict['spcvz'] = ['stressbalance', 'o', 'y', 80, 'vy Dirichlet'] + + if isinstance(md.hydrology, hydrologydc): + spc_dict['spcepl_head'] = ['hydrology', 'v', 'r', 240, 'EPL Head'] + if md.hydrology.isefficientlayer: + spc_dict['spcsediment_head'] = ['hydrology', '^', 'b', 240, 'IDS Head'] + + for key in spc_dict: + #first reduce vectors if layer is used + if options.getfieldvalue('layer', 0) >= 1: + plotlayer = options.getfieldvalue('layer', 0) + slicesize = len(x) + fulldata = md.__dict__[str(spc_dict[str(key)][0])].__dict__[str(key)] + print(key) + data = fulldata[(plotlayer - 1) * slicesize:plotlayer * slicesize] + print(np.shape(data)) + mark = spc_dict[str(key)][1] + color = spc_dict[str(key)][2] + size = spc_dict[str(key)][3] + name = spc_dict[str(key)][4] + ax.scatter(x[np.where(~np.isnan(data))], + y[np.where(~np.isnan(data))], + marker=mark, c=color, s=size, label=name, linewidth=0) + ax.set_xlim(XLims) + ax.set_ylim(YLims) + ax.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3, + ncol=3, mode="expand", borderaxespad=0.) + #apply options + options.addfielddefault('title', 'Boundary conditions') + options.addfielddefault('colorbar', 'off') + applyoptions(md, [], options, fig, axgrid, gridindex) Index: /issm/trunk-jpl/src/m/plot/plot_contour.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plot_contour.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plot_contour.py (revision 24213) @@ -1,41 +1,39 @@ +import numpy as np from averaging import averaging from processmesh import processmesh from processdata import processdata -try: - import matplotlib.pyplot as plt -except ImportError: - print("could not import pylab, matplotlib has not been installed, no plotting capabilities enabled") -def plot_contour(md,datain,options,ax): - ''' - plot contours of a given field (called within plotmodel) - Usage: - plot_contour(md,data,options) +def plot_contour(md, datain, options, ax): + ''' + plot contours of a given field (called within plotmodel) - See also: plotmodel - ''' + Usage: + plot_contour(md, data, options) - x,y,z,elements,is2d,isplanet=processmesh(md,datain,options) - data,datatype=processdata(md,datain,options) + See also: plotmodel + ''' - # process data: must be on nodes - if datatype==1: # element data - data=averaging(md,data,0) - elif datatype==2: - pass - elif datatype==3: # quiver (vector) data - data=np.sqrt(datain**2) - else: - raise ValueError('datatype not supported in call to plot_contour') + x, y, z, elements, is2d, isplanet = processmesh(md, datain, options) + data, datatype = processdata(md, datain, options) - # contouronly TODO (cla will also clear an overlay image) + # process data: must be on nodes + if datatype == 1: # element data + data = averaging(md, data, 0) + elif datatype == 2: + pass + elif datatype == 3: # quiver (vector) data + data = np.sqrt(datain**2) + else: + raise ValueError('datatype not supported in call to plot_contour') - # retrieve necessary options - levels=options.getfieldvalue('contourlevels') - norm=options.getfieldvalue('colornorm') - colors=options.getfieldvalue('contourcolors','y') - linestyles=options.getfieldvalue('contourlinestyles','-') - linewidths=options.getfieldvalue('contourlinewidths',1) + # contouronly TODO (cla will also clear an overlay image) - ax.tricontour(x,y,elements,data,levels,colors=colors,norm=norm,linestyles=linestyles,linewidths=linewidths) + # retrieve necessary options + levels = options.getfieldvalue('contourlevels') + norm = options.getfieldvalue('colornorm') + colors = options.getfieldvalue('contourcolors', 'y') + linestyles = options.getfieldvalue('contourlinestyles', ' - ') + linewidths = options.getfieldvalue('contourlinewidths', 1) + + ax.tricontour(x, y, elements, data, levels, colors=colors, norm=norm, linestyles=linestyles, linewidths=linewidths) Index: /issm/trunk-jpl/src/m/plot/plot_elementnumbering.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plot_elementnumbering.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plot_elementnumbering.py (revision 24213) @@ -1,51 +1,43 @@ -try: - import pylab as p -except ImportError: - print("could not import pylab, matplotlib has not been installed, no plotting capabilities enabled") - -import numpy as np +import numpy as np from processmesh import processmesh from applyoptions import applyoptions -from plot_icefront import plot_icefront -def plot_elementnumbering(md,options,fig,axgrid,gridindex): - ''' - plot_elementnumbering - plot element numberign (starting at 1 matlab and c convention) - Usage: - plot_elementnumbering(md,options,fig,axes) +def plot_elementnumbering(md, options, fig, axgrid, gridindex): + ''' + plot_elementnumbering - plot element numberign (starting at 1 matlab and c convention) - See also: PLOTMODEL - ''' - x,y,z,elements,is2d,isplanet=processmesh(md,[],options) + Usage: + plot_elementnumbering(md, options, fig, axes) - ax=axgrid[gridindex] - fig.delaxes(axgrid.cbar_axes[gridindex]) - - if is2d: - ax.triplot(x,y,elements) - else: - print('Not Implemented Yet') + See also: PLOTMODEL + ''' + x, y, z, elements, is2d, isplanet = processmesh(md, [], options) - XLims=[np.min(x),np.max(x)] - YLims=[np.min(y),np.max(y)] - #plot mesh - ax.triplot(x,y,elements) - highlightpos=options.getfieldvalue('highlight','none') - if highlightpos!='none': - #if just one element duplicate it to avoid coloring issues - if type(highlightpos)==int: - highlightpos=[highlightpos,highlightpos] - #convert from to matlab numbering - highlightpos=[pos-1 for pos in highlightpos] - colors=np.asarray([0.5 for element in elements[highlightpos]]) - ax.tripcolor(x,y,elements[highlightpos],facecolors=colors,alpha=0.5) - # and numbers - for i,element in enumerate(elements): - ax.text(np.mean(x[element]),np.mean(y[element]),str(i+1),ha='center',va='center',clip_on=True) - - #apply options - options.addfielddefault('title','Element numbers (matlab indexation)') - options.addfielddefault('colorbar','off') - applyoptions(md,[],options,fig,axgrid,gridindex) - + ax = axgrid[gridindex] + fig.delaxes(axgrid.cbar_axes[gridindex]) + + if is2d: + ax.triplot(x, y, elements) + else: + print('Not Implemented Yet') + + #plot mesh + ax.triplot(x, y, elements) + highlightpos = options.getfieldvalue('highlight', 'none') + if highlightpos != 'none': + #if just one element duplicate it to avoid coloring issues + if type(highlightpos) == int: + highlightpos = [highlightpos, highlightpos] + #convert from to matlab numbering + highlightpos = [pos - 1 for pos in highlightpos] + colors = np.asarray([0.5 for element in elements[highlightpos]]) + ax.tripcolor(x, y, elements[highlightpos], facecolors=colors, alpha=0.5) + # and numbers + for i, element in enumerate(elements): + ax.text(np.mean(x[element]), np.mean(y[element]), str(i + 1), ha='center', va='center', clip_on=True) + + #apply options + options.addfielddefault('title', 'Element numbers (matlab indexation)') + options.addfielddefault('colorbar', 'off') + applyoptions(md, [], options, fig, axgrid, gridindex) Index: /issm/trunk-jpl/src/m/plot/plot_icefront.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plot_icefront.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plot_icefront.py (revision 24213) @@ -1,34 +1,67 @@ -try: - import pylab as p -except ImportError: - print("could not import pylab, matplotlib has not been installed, no plotting capabilities enabled") -import numpy as np +import numpy as np from processmesh import processmesh -from applyoptions import applyoptions +from mpl_toolkits.mplot3d.art3d import Line3DCollection +from mpl_toolkits.axes_grid1.inset_locator import inset_axes +from mpl_toolkits.mplot3d import Axes3D -def plot_icefront(md,options,fig,ax): - #PLOT_ICEFRONT - plot segment on neumann BC - # - # Usage: - # plot_icefront(md,options,width,i) - # - # See also: PLOTMODEL -#process mesh and data - x,y,z,elements,is2d,isplanet=processmesh(md,[],options) - #icefront check - icefront=np.where(np.abs(np.sum(md.mask.ice_levelset[elements],1))!=3) - onlyice=np.where(np.sum(md.mask.ice_levelset[elements],1)==-3) - noice=np.where(np.sum(md.mask.ice_levelset[elements],1)==3) +def plot_icefront(md, options, fig, ax): + #PLOT_ICEFRONT - plot segment on neumann BC + # + # Usage: + # plot_icefront(md, options, width, i) + # + # See also: PLOTMODEL + #process mesh and data + x, y, z, elements, is2d, isplanet = processmesh(md, [], options) - #plot mesh - ax.triplot(x,y,elements) + if options.exist('layer'): + nodes_per_elt = np.shape(md.mesh.elements2d)[1] + else: + nodes_per_elt = np.shape(md.mesh.elements)[1] + #icefront check + icefront = np.where(np.abs(np.sum(md.mask.ice_levelset[elements], 1)) != nodes_per_elt) - #highlight elements on neumann - if len(icefront[0])>0: - colors=np.asarray([0.5 for element in elements[icefront]]) - ax.tripcolor(x,y,elements[icefront],facecolors=colors,alpha=0.5,label='elements on ice front') + #plot mesh + if is2d: + ax.triplot(x, y, elements) - #apply options - options.addfielddefault('title','Neumann boundary conditions') - options.addfielddefault('colorbar','off') + #highlight elements on neumann + if len(icefront[0]) > 0: + colors = np.asarray([0.5 for element in elements[icefront]]) + ax.tripcolor(x, y, elements[icefront], facecolors=colors, alpha=0.5, label='elements on ice front') + else: + ax = inset_axes(ax, width='100%', height='100%', loc=3, borderpad=0, axes_class=Axes3D) + + AB = elements[:, 0:2] + BC = elements[:, 1:3] + CA = np.vstack((elements[:, 2], elements[:, 0])).T + DE = elements[:, 3:5] + EF = elements[:, 4:] + FD = np.vstack((elements[:, 5], elements[:, 3])).T + AD = np.vstack((elements[:, 0], elements[:, 3])).T + BE = np.vstack((elements[:, 1], elements[:, 4])).T + CF = np.vstack((elements[:, 2], elements[:, 5])).T + + tmpa = np.vstack((AB, BC, CA, DE, EF, FD, AD, BE, CF)) + #deleting segments that appear multiple times + tmpb = np.ascontiguousarray(tmpa).view(np.dtype((np.void, tmpa.dtype.itemsize * tmpa.shape[1]))) + _, idx = np.unique(tmpb, return_index=True) + triel = tmpa[idx] + + for t, triangle in enumerate(triel): + tri = list(zip(x[triangle], y[triangle], z[triangle])) + facecolor = [0, 0, 0] + if t in icefront: + facecolor = [0.5, 0.5, 0.5] + pl3 = Line3DCollection([tri], edgecolor='r', facecolor=facecolor) + ax.add_collection3d(pl3) + + ax.set_xlim([min(x), max(x)]) + ax.set_ylim([min(y), max(y)]) + ax.set_zlim([min(z), max(z)]) + #highlight elements on neumann + + #apply options + options.addfielddefault('title', 'Neumann boundary conditions') + options.addfielddefault('colorbar', 'off') Index: /issm/trunk-jpl/src/m/plot/plot_manager.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plot_manager.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plot_manager.py (revision 24213) @@ -1,7 +1,2 @@ -try: - import pylab as p - import matplotlib.pyplot as plt -except ImportError: - print("could not import pylab, matplotlib has not been installed, no plotting capabilities enabled") from checkplotoptions import checkplotoptions @@ -16,99 +11,100 @@ try: - from osgeo import gdal - overlaysupport=True + from osgeo import gdal + overlaysupport = True except ImportError: - print('osgeo/gdal for python not installed, overlay plots are not enabled') - overlaysupport=False + print('osgeo/gdal for python not installed, overlay plots are not enabled') + overlaysupport = False if overlaysupport: - from plot_overlay import plot_overlay + from plot_overlay import plot_overlay -def plot_manager(md,options,fig,axgrid,gridindex): - ''' - PLOT_MANAGER - distribute the plots called by plotmodel - 'fig' is a handle to the figure instance created by plotmodel. +def plot_manager(md, options, fig, axgrid, gridindex): + ''' + PLOT_MANAGER - distribute the plots called by plotmodel - 'ax' is a handle to the axes instance created by plotmodel. This is - currently generated using matplotlib's AxesGrid toolkit. + 'fig' is a handle to the figure instance created by plotmodel. - Usage: - plot_manager(md,options,fig,ax); + 'ax' is a handle to the axes instance created by plotmodel. This is + currently generated using matplotlib's AxesGrid toolkit. - See also: PLOTMODEL, PLOT_UNIT - ''' + Usage: + plot_manager(md, options, fig, ax) - #parse options and get a structure of options - options=checkplotoptions(md,options) - #get data to be plotted - data=options.getfieldvalue('data') - #add ticklabel has a default option - options.addfielddefault('ticklabels','on') + See also: PLOTMODEL, PLOT_UNIT + ''' - ax=axgrid[gridindex] - # {{{ basemap plot TOFIX - #if options.exist('basemap'): - # plot_basemap(md,data,options,nrows,ncols,i) - # }}} - # {{{ overlay plot - if options.exist('overlay') and overlaysupport: - plot_overlay(md,data,options,ax) - options.addfielddefault('alpha',0.5) - options.addfielddefault('xlim',[min(md.mesh.x),max(md.mesh.x)]) - options.addfielddefault('ylim',[min(md.mesh.y),max(md.mesh.y)]) - # }}} - # {{{ dealing with special plot - if isinstance(data,str): - if data=='mesh': - plot_mesh(md,options,fig,axgrid,gridindex) + #parse options and get a structure of options + options = checkplotoptions(md, options) + #get data to be plotted + data = options.getfieldvalue('data') + #add ticklabel has a default option + options.addfielddefault('ticklabels', 'on') - #fig.delaxes(fig.axes[1]) # hack to remove colorbar after the fact - return - elif data=='BC': - plot_BC(md,options,fig,axgrid,gridindex) - return - elif data=='elementnumbering': - plot_elementnumbering(md,options,fig,axgrid,gridindex) - return - elif data=='vertexnumbering': - plot_vertexnumbering(md,options,fig,axgrid,gridindex) - return - elif data=='none': - print('no data provided to plot (TODO: write plot_none.py)') - applyoptions(md,[],options,fig,axgrid,gridindex) - return - else: - print(("WARNING: '%s' is not implemented or is not a valid string for option 'data'" % data)) - # }}} - # {{{ Gridded plot TODO - # }}} - # {{{ Section plot TODO - # }}} - # {{{ Profile plot TODO - # }}} + ax = axgrid[gridindex] + # {{{ basemap plot TOFIX + #if options.exist('basemap'): + # plot_basemap(md, data, options, nrows, ncols, i) + # }}} + # {{{ overlay plot + if options.exist('overlay') and overlaysupport: + plot_overlay(md, data, options, ax) + options.addfielddefault('alpha', 0.5) + options.addfielddefault('xlim', [min(md.mesh.x), max(md.mesh.x)]) + options.addfielddefault('ylim', [min(md.mesh.y), max(md.mesh.y)]) + # }}} + # {{{ dealing with special plot + if isinstance(data, str): + if data == 'mesh': + plot_mesh(md, options, fig, axgrid, gridindex) - #process data and model - x,y,z,elements,is2d,isplanet=processmesh(md,data,options) - data2,datatype=processdata(md,data,options) - #plot unit - plot_unit(x,y,z,elements,data2,is2d,isplanet,datatype,options,fig,axgrid,gridindex) - #apply all options - applyoptions(md,data2,options,fig,axgrid,gridindex) + #fig.delaxes(fig.axes[1]) # hack to remove colorbar after the fact + return + elif data == 'BC': + plot_BC(md, options, fig, axgrid, gridindex) + return + elif data == 'elementnumbering': + plot_elementnumbering(md, options, fig, axgrid, gridindex) + return + elif data == 'vertexnumbering': + plot_vertexnumbering(md, options, fig, axgrid, gridindex) + return + elif data == 'none': + print('no data provided to plot (TODO: write plot_none.py)') + applyoptions(md, [], options, fig, axgrid, gridindex) + return + else: + print(("WARNING: '%s' is not implemented or is not a valid string for option 'data'" % data)) + # }}} + # {{{ Gridded plot TODO + # }}} + # {{{ Section plot TODO + # }}} + # {{{ Profile plot TODO + # }}} - #ground overlay on kml plot_unit + #process data and model + x, y, z, elements, is2d, isplanet = processmesh(md, data, options) + data2, datatype = processdata(md, data, options) + #plot unit + plot_unit(x, y, z, elements, data2, is2d, isplanet, datatype, options, fig, axgrid, gridindex) + #apply all options + applyoptions(md, data2, options, fig, axgrid, gridindex) - # Bits and pieces - #initialize plot handle variable - #handle=None + #ground overlay on kml plot_unit - # initialize subplot - #p.subplot(nrows,ncols,i,aspect='equal') + # Bits and pieces + #initialize plot handle variable + #handle = None - #standard plot - #if not handle: - # p.subplot(nrows,ncols,i,aspect='equal') + # initialize subplot + #p.subplot(nrows, ncols, i, aspect = 'equal') - #elif data in vars(md): - #else: - #print "'data' not a string, plotting model properties yet to be implemented..." + #standard plot + #if not handle: + # p.subplot(nrows, ncols, i, aspect = 'equal') + + #elif data in vars(md): + #else: + #print "'data' not a string, plotting model properties yet to be implemented..." Index: /issm/trunk-jpl/src/m/plot/plot_mesh.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plot_mesh.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plot_mesh.py (revision 24213) @@ -1,59 +1,56 @@ -try: - import pylab as p -except ImportError: - print("could not import pylab, matplotlib has not been installed, no plotting capabilities enabled") - import numpy as np from processmesh import processmesh from applyoptions import applyoptions from mpl_toolkits.mplot3d.art3d import Line3DCollection -from mpl_toolkits.axes_grid1 import inset_locator +from mpl_toolkits.axes_grid1.inset_locator import inset_axes from mpl_toolkits.mplot3d import Axes3D -def plot_mesh(md,options,fig,axgrid,gridindex): - ''' - PLOT_MESH - plot model mesh - Usage: - plot_mesh(md,options,nlines,ncols,i) - See also: PLOTMODEL - ''' - x,y,z,elements,is2d,isplanet=processmesh(md,'mesh',options) +def plot_mesh(md, options, fig, axgrid, gridindex): + ''' + PLOT_MESH - plot model mesh - ax=axgrid[gridindex] - fig.delaxes(axgrid.cbar_axes[gridindex]) - - if is2d: - ax.triplot(x,y,elements) - else: - ax=inset_locator.inset_axes(axgrid[gridindex],width='100%',height='100%',loc=3,borderpad=0,axes_class=Axes3D) - - AB=elements[:,0:2] - BC=elements[:,1:3] - CA=np.vstack((elements[:,2],elements[:,0])).T - DE=elements[:,3:5] - EF=elements[:,4:] - FD=np.vstack((elements[:,5],elements[:,3])).T - AD=np.vstack((elements[:,0],elements[:,3])).T - BE=np.vstack((elements[:,1],elements[:,4])).T - CF=np.vstack((elements[:,2],elements[:,5])).T - - tmpa=np.vstack((AB,BC,CA,DE,EF,FD,AD,BE,CF)) - #deleting segments that appear multiple times - tmpb = np.ascontiguousarray(tmpa).view(np.dtype((np.void, tmpa.dtype.itemsize * tmpa.shape[1]))) - _, idx = np.unique(tmpb, return_index=True) - triel= tmpa[idx] - - for triangle in triel: - tri=list(zip(x[triangle],y[triangle],z[triangle])) - pl3=Line3DCollection([tri],edgecolor='r') - ax.add_collection3d(pl3) - - ax.set_xlim([min(x),max(x)]) - ax.set_ylim([min(y),max(y)]) - ax.set_zlim([min(z),max(z)]) - #apply options - options.addfielddefault('title','Mesh') - options.addfielddefault('colorbar','off') - options.addfielddefault('ticklabels','on') - applyoptions(md,[],options,fig,axgrid,gridindex) + Usage: + plot_mesh(md, options, nlines, ncols, i) + + See also: PLOTMODEL + ''' + x, y, z, elements, is2d, isplanet = processmesh(md, 'mesh', options) + + ax = axgrid[gridindex] + fig.delaxes(axgrid.cbar_axes[gridindex]) + + if is2d: + ax.triplot(x, y, elements) + else: + ax = inset_axes(axgrid[gridindex], width='100%', height='100%', loc=3, borderpad=0, axes_class=Axes3D) + + AB = elements[:, 0:2] + BC = elements[:, 1:3] + CA = np.vstack((elements[:, 2], elements[:, 0])).T + DE = elements[:, 3:5] + EF = elements[:, 4:] + FD = np.vstack((elements[:, 5], elements[:, 3])).T + AD = np.vstack((elements[:, 0], elements[:, 3])).T + BE = np.vstack((elements[:, 1], elements[:, 4])).T + CF = np.vstack((elements[:, 2], elements[:, 5])).T + + tmpa = np.vstack((AB, BC, CA, DE, EF, FD, AD, BE, CF)) + #deleting segments that appear multiple times + tmpb = np.ascontiguousarray(tmpa).view(np.dtype((np.void, tmpa.dtype.itemsize * tmpa.shape[1]))) + _, idx = np.unique(tmpb, return_index=True) + triel = tmpa[idx] + + for triangle in triel: + tri = list(zip(x[triangle], y[triangle], z[triangle])) + pl3 = Line3DCollection([tri], edgecolor='r') + ax.add_collection3d(pl3) + + ax.set_xlim([min(x), max(x)]) + ax.set_ylim([min(y), max(y)]) + ax.set_zlim([min(z), max(z)]) + #apply options + options.addfielddefault('title', 'Mesh') + options.addfielddefault('colorbar', 'off') + options.addfielddefault('ticklabels', 'on') + applyoptions(md, [], options, fig, axgrid, gridindex) Index: /issm/trunk-jpl/src/m/plot/plot_overlay.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plot_overlay.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plot_overlay.py (revision 24213) @@ -1,3 +1,3 @@ -import numpy as np +import numpy as np from processmesh import processmesh from processdata import processdata @@ -7,126 +7,126 @@ import os try: - from mpl_toolkits.basemap import Basemap + from mpl_toolkits.basemap import Basemap except ImportError: - print('Basemap toolkit not installed') + print('Basemap toolkit not installed') try: - from osgeo import gdal + from osgeo import gdal except ImportError: - print('osgeo/gdal for python not installed, plot_overlay is disabled') + print('osgeo/gdal for python not installed, plot_overlay is disabled') -def plot_overlay(md,data,options,ax): - ''' - Function for plotting a georeferenced image. This function is called - from within the plotmodel code. - ''' +def plot_overlay(md, data, options, ax): + ''' + Function for plotting a georeferenced image. This function is called + from within the plotmodel code. + ''' - x,y,z,elements,is2d,isplanet=processmesh(md,[],options) - try: - data,datatype=processdata(md,data,options) - imageonly=0 - except (TypeError,ValueError):#that should catch None and 'none' but may also catch unwanted errors - imageonly=1 - data=np.float('nan')*np.ones((md.mesh.numberofvertices,)) - datatype=1 + x, y, z, elements, is2d, isplanet = processmesh(md, [], options) + try: + data, datatype = processdata(md, data, options) + imageonly = 0 + except (TypeError, ValueError): #that should catch None and 'none' but may also catch unwanted errors + imageonly = 1 + data = np.float('nan') * np.ones((md.mesh.numberofvertices, )) + datatype = 1 - if not is2d: - raise Exception('overlay plot not supported for 3D meshes, project on a 2D layer first') + if not is2d: + raise Exception('overlay plot not supported for 3D meshes, project on a 2D layer first') - if not options.exist('overlay_image'): - raise Exception('overlay error: provide overlay_image with path to geotiff file') - image=options.getfieldvalue('overlay_image') + if not options.exist('overlay_image'): + raise Exception('overlay error: provide overlay_image with path to geotiff file') + image = options.getfieldvalue('overlay_image') - xlim=options.getfieldvalue('xlim',[min(md.mesh.x),max(md.mesh.x)]) - ylim=options.getfieldvalue('ylim',[min(md.mesh.y),max(md.mesh.y)]) + xlim = options.getfieldvalue('xlim', [min(md.mesh.x), max(md.mesh.x)]) + ylim = options.getfieldvalue('ylim', [min(md.mesh.y), max(md.mesh.y)]) - gtif=gdal.Open(image) - trans=gtif.GetGeoTransform() - xmin=trans[0] - xmax=trans[0]+gtif.RasterXSize*trans[1] - ymin=trans[3]+gtif.RasterYSize*trans[5] - ymax=trans[3] - # allow supplied image to have limits smaller than basemap or model limits - x0=max(min(xlim),xmin) - x1=min(max(xlim),xmax) - y0=max(min(ylim),ymin) - y1=min(max(ylim),ymax) - inputname='temp.tif' - os.system('gdal_translate -quiet -projwin ' + str(x0) + ' ' + str(y1) + ' ' + str(x1) + ' ' + str(y0) + ' ' + image+ ' ' + inputname) + gtif = gdal.Open(image) + trans = gtif.GetGeoTransform() + xmin = trans[0] + xmax = trans[0] + gtif.RasterXSize * trans[1] + ymin = trans[3] + gtif.RasterYSize * trans[5] + ymax = trans[3] + # allow supplied image to have limits smaller than basemap or model limits + x0 = max(min(xlim), xmin) + x1 = min(max(xlim), xmax) + y0 = max(min(ylim), ymin) + y1 = min(max(ylim), ymax) + inputname = 'temp.tif' + os.system('gdal_translate-quiet - projwin ' + str(x0) + ' ' + str(y1) + ' ' + str(x1) + ' ' + str(y0) + ' ' + image + ' ' + inputname) - gtif=gdal.Open(inputname) - arr=gtif.ReadAsArray() - #os.system('rm -rf ./temp.tif') + gtif = gdal.Open(inputname) + arr = gtif.ReadAsArray() + #os.system('rm -rf . / temp.tif') - if gtif.RasterCount>=3: # RGB array - r=gtif.GetRasterBand(1).ReadAsArray() - g=gtif.GetRasterBand(2).ReadAsArray() - b=gtif.GetRasterBand(3).ReadAsArray() - arr=0.299*r+0.587*g+0.114*b + if gtif.RasterCount >= 3: # RGB array + r = gtif.GetRasterBand(1).ReadAsArray() + g = gtif.GetRasterBand(2).ReadAsArray() + b = gtif.GetRasterBand(3).ReadAsArray() + arr = 0.299 * r + 0.587 * g + 0.114 * b - # normalize array - arr=arr/np.float(np.max(arr.ravel())) - arr=1.-arr # somehow the values got flipped + # normalize array + arr = arr / np.float(np.max(arr.ravel())) + arr = 1. - arr # somehow the values got flipped - if options.getfieldvalue('overlayhist',0)==1: - ax=plt.gca() - num=2 - while True: - if not plt.fignum_exists(num): - break - else: - num+=1 - plt.figure(num) - plt.hist(arr.flatten(),bins=256,range=(0.,1.)) - plt.title('histogram of overlay image, use for setting overlaylims') - plt.show() - plt.sca(ax) # return to original axes/figure + if options.getfieldvalue('overlayhist', 0) == 1: + ax = plt.gca() + num = 2 + while True: + if not plt.fignum_exists(num): + break + else: + num += 1 + plt.figure(num) + plt.hist(arr.flatten(), bins=256, range=(0., 1.)) + plt.title('histogram of overlay image, use for setting overlaylims') + plt.show() + plt.sca(ax) # return to original axes / figure - # get parameters from cropped geotiff - trans=gtif.GetGeoTransform() - xmin=trans[0] - xmax=trans[0]+gtif.RasterXSize*trans[1] - ymin=trans[3]+gtif.RasterYSize*trans[5] - ymax=trans[3] - dx=trans[1] - dy=trans[5] + # get parameters from cropped geotiff + trans = gtif.GetGeoTransform() + xmin = trans[0] + xmax = trans[0] + gtif.RasterXSize * trans[1] + ymin = trans[3] + gtif.RasterYSize * trans[5] + ymax = trans[3] + dx = trans[1] + dy = trans[5] - xarr=np.arange(xmin,xmax,dx) - yarr=np.arange(ymin,ymax,-dy) # -dy since origin='upper' (not sure how robust this is) - xg,yg=np.meshgrid(xarr,yarr) - overlaylims=options.getfieldvalue('overlaylims',[min(arr.ravel()),max(arr.ravel())]) - norm=mpl.colors.Normalize(vmin=overlaylims[0],vmax=overlaylims[1]) + xarr = np.arange(xmin, xmax, dx) + yarr = np.arange(ymin, ymax, - dy) # - dy since origin = 'upper' (not sure how robust this is) + xg, yg = np.meshgrid(xarr, yarr) + overlaylims = options.getfieldvalue('overlaylims', [min(arr.ravel()), max(arr.ravel())]) + norm = mpl.colors.Normalize(vmin=overlaylims[0], vmax=overlaylims[1]) - pc=ax.pcolormesh(xg, yg, np.flipud(arr), cmap=mpl.cm.Greys, norm=norm) + pc = ax.pcolormesh(xg, yg, np.flipud(arr), cmap=mpl.cm.Greys, norm=norm) - if options.exist('basemap'): - # create coordinate grid in map projection units (for plotting) - if md.mesh.epsg==3413: - hemisphere=1 - st_lat=70 - lon_0=45 - elif md.mesh.epsg==3031: - hemisphere=-1 - st_lat=71 - lon_0=0 - else: - hemisphere=eval(input('epsg code {} is not supported chose your hemisphere (1 for North, -1 for south)'.format(mesh.epsg))) + if options.exist('basemap'): + # create coordinate grid in map projection units (for plotting) + if md.mesh.epsg == 3413: + hemisphere = 1 + st_lat = 70 + lon_0 = 45 + elif md.mesh.epsg == 3031: + hemisphere = -1 + st_lat = 71 + lon_0 = 0 + else: + hemisphere = eval(input('epsg code {} is not supported chose your hemisphere (1 for North, - 1 for south)'.format(md.mesh.epsg))) - lat,lon=xy2ll(xlim,ylim,hemisphere,lon_0,st_lat) - extent=[np.diff(xlim)[0],np.diff(ylim)[0]] - center=[lon[0]+np.diff(lon)[0]*0.5,lat[0]+np.diff(lat)[0]*0.5] - m=Basemap(llcrnrlon=lon[0],llcrnrlat=lat[0],urcrnrlon=lon[1],urcrnrlat=lat[1], - lon_0=center[0],lat_0=center[1],#width=extent[0],height=extent[1],# - epsg=md.mesh.epsg,anchor='NW', - resolution='i',ax=ax) + lat, lon = xy2ll(xlim, ylim, hemisphere, lon_0, st_lat) + extent = [np.diff(xlim)[0], np.diff(ylim)[0]] + center = [lon[0] + np.diff(lon)[0] * 0.5, lat[0] + np.diff(lat)[0] * 0.5] + m = Basemap(llcrnrlon=lon[0], llcrnrlat=lat[0], urcrnrlon=lon[1], urcrnrlat=lat[1], + lon_0=center[0], lat_0=center[1], width=extent[0], height=extent[1], + epsg=md.mesh.epsg, anchor='NW', + resolution='i', ax=ax) - meridians=np.arange(np.floor(lon[0]),np.ceil(lon[1]),1.) - parallels=np.arange(np.floor(lat[0]),np.ceil(lat[1]),1.) - m.drawparallels(parallels,labels=[1,0,0,0],ax=ax) # labels=[left,right,top,bottom] - m.drawmeridians(meridians,labels=[0,0,1,0],ax=ax) - m.drawcoastlines(ax=ax) - m.drawmapboundary(ax=ax) + meridians = np.arange(np.floor(lon[0]), np.ceil(lon[1]), 1.) + parallels = np.arange(np.floor(lat[0]), np.ceil(lat[1]), 1.) + m.drawparallels(parallels, labels=[1, 0, 0, 0], ax=ax) # labels = [left, right, top, bottom] + m.drawmeridians(meridians, labels=[0, 0, 1, 0], ax=ax) + m.drawcoastlines(ax=ax) + m.drawmapboundary(ax=ax) - #rasterization? - if options.getfieldvalue('rasterized',0): - pc.set_rasterized(True) + #rasterization? + if options.getfieldvalue('rasterized', 0): + pc.set_rasterized(True) Index: /issm/trunk-jpl/src/m/plot/plot_quiver.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plot_quiver.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plot_quiver.py (revision 24213) @@ -1,42 +1,43 @@ -import numpy as np +import numpy as np -def plot_quiver(x,y,data,options,ax): - vx=data[:,0] - vy=data[:,1] - Xdist=max(x)-min(x) - Ydist=max(y)-min(y) - datanorm=np.sqrt(vx**2+vy**2) - scaler=max(datanorm)/(np.sqrt(Xdist*Ydist/len(x))) - #define colors, unicolor or value codded - color=options.getfieldvalue('quivercol','k') - if color=='values': - color=datanorm - #scaling of arrow length (giving info to change as it seems that there is no better way to work arround it) - scale=options.getfieldvalue('scaling',scaler) - print(('the current value for "scaling" is {}, increase it to shorten the arrows'.format(scale))) - #sizing of the arrows - width=options.getfieldvalue('width',5.0e-3) - headwidth=options.getfieldvalue('headwidth',6) - headlength=options.getfieldvalue('headlength',headwidth) - #set the unit to the smaller of the two axes - if Xdist>Ydist: - units='height' - else: - units='width' - - if type(color)==str: - Q=ax.quiver(x,y,vx,vy,color=color, - scale=scale,scale_units='xy', - units=units,headwidth=headwidth,headlength=headlength,width=width, - angles='xy') - else: - if options.exist('colornorm'): - norm=options.getfieldvalue('colornorm') - if options.exist('colormap'): - cmap=options.getfieldvalue('colormap') - Q=ax.quiver(x,y,vx,vy,color,cmap=cmap,norm=norm, - scale=scale,scale_units='xy', - units=units,headwidth=headwidth,headlength=headlength,width=width, - angles='xy') - return Q +def plot_quiver(x, y, data, options, ax): + vx = data[:, 0] + vy = data[:, 1] + Xdist = max(x) - min(x) + Ydist = max(y) - min(y) + datanorm = np.sqrt(vx**2 + vy**2) + scaler = max(datanorm) / (np.sqrt(Xdist * Ydist / len(x))) + + #define colors, unicolor or value codded + color = options.getfieldvalue('quivercol', 'k') + if color == 'values': + color = datanorm + #scaling of arrow length (giving info to change as it seems that there is no better way to work arround it) + scale = options.getfieldvalue('scaling', scaler) + print(('the current value for "scaling" is {}, increase it to shorten the arrows'.format(scale))) + #sizing of the arrows + width = options.getfieldvalue('width', 5.0e-3) + headwidth = options.getfieldvalue('headwidth', 6) + headlength = options.getfieldvalue('headlength', headwidth) + #set the unit to the smaller of the two axes + if Xdist > Ydist: + units = 'height' + else: + units = 'width' + + if type(color) == str: + Q = ax.quiver(x, y, vx, vy, color=color, + scale=scale, scale_units='xy', + units=units, headwidth=headwidth, headlength=headlength, width=width, + angles='xy') + else: + if options.exist('colornorm'): + norm = options.getfieldvalue('colornorm') + if options.exist('colormap'): + cmap = options.getfieldvalue('colormap') + Q = ax.quiver(x, y, vx, vy, color, cmap=cmap, norm=norm, + scale=scale, scale_units='xy', + units=units, headwidth=headwidth, headlength=headlength, width=width, + angles='xy') + return Q Index: /issm/trunk-jpl/src/m/plot/plot_streamlines.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plot_streamlines.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plot_streamlines.py (revision 24213) @@ -1,21 +1,20 @@ -import numpy as np +import numpy as np from processmesh import processmesh from processdata import processdata -from ContourToMesh import ContourToMesh try: - import matplotlib.pyplot as plt - import matplotlib.tri as tri - from scipy.interpolate import griddata + import matplotlib.tri as tri + from scipy.interpolate import griddata except ImportError: - print("could not import pylab, matplotlib has not been installed, no plotting capabilities enabled") + print("could not import pylab, matplotlib has not been installed, no plotting capabilities enabled") -def plot_streamlines(md,options,ax): + +def plot_streamlines(md, options, ax): ''' plot streamlines on a figure, using by default vx and vy components in md.initialization. Usage: - plot_streamlines(md,options,ax) + plot_streamlines(md, options, ax) - available options, to be passed to plotmodel as a string-value pair: + available options, to be passed to plotmodel as a string - value pair: streamlinesvx : vx component (default md.initialization.vx) streamlinesvy : vy component (default md.initialization.vy) @@ -29,15 +28,15 @@ # retrieve options - vx=options.getfieldvalue('streamlinesvx',md.initialization.vx) - vy=options.getfieldvalue('streamlinesvy',md.initialization.vy) - color=options.getfieldvalue('streamlinescolor','k') - linewidth=options.getfieldvalue('streamlineswidth',1) - density=options.getfieldvalue('streamlinesdensity',1) - arrowsize=options.getfieldvalue('streamlinesarrowsize',1) + vx = options.getfieldvalue('streamlinesvx', md.initialization.vx) + vy = options.getfieldvalue('streamlinesvy', md.initialization.vy) + color = options.getfieldvalue('streamlinescolor', 'k') + linewidth = options.getfieldvalue('streamlineswidth', 1) + density = options.getfieldvalue('streamlinesdensity', 1) + arrowsize = options.getfieldvalue('streamlinesarrowsize', 1) #process mesh and data - x,y,z,elements,is2d,isplanet=processmesh(md,vx,options) - u,datatype=processdata(md,vx,options) - v,datatype=processdata(md,vy,options) + x, y, z, elements, is2d, isplanet = processmesh(md, vx, options) + u, datatype = processdata(md, vx, options) + v, datatype = processdata(md, vy, options) if not is2d: @@ -45,23 +44,23 @@ # format data for matplotlib streamplot function - yg,xg=np.mgrid[min(md.mesh.y):max(md.mesh.y):100j,min(md.mesh.x):max(md.mesh.x):100j] - ug=griddata((x,y),u,(xg,yg),method='linear') - vg=griddata((x,y),v,(xg,yg),method='linear') + yg, xg = np.mgrid[min(md.mesh.y):max(md.mesh.y):100j, min(md.mesh.x):max(md.mesh.x):100j] + ug = griddata((x, y), u, (xg, yg), method='linear') + vg = griddata((x, y), v, (xg, yg), method='linear') # create triangulation instance - triang=tri.Triangulation(md.mesh.x,md.mesh.y,md.mesh.elements-1) + triang = tri.Triangulation(md.mesh.x, md.mesh.y, md.mesh.elements - 1) # interpolate to regularly spaced quad grid - interp_lin_u=tri.LinearTriInterpolator(triang,u) - interp_lin_v=tri.LinearTriInterpolator(triang,v) - ug=interp_lin_u(xg,yg) - vg=interp_lin_v(xg,yg) + interp_lin_u = tri.LinearTriInterpolator(triang, u) + interp_lin_v = tri.LinearTriInterpolator(triang, v) + ug = interp_lin_u(xg, yg) + vg = interp_lin_v(xg, yg) - if linewidth=='vel': - scale=options.getfieldvalue('streamlineswidthscale',3) - vel=np.sqrt(ug**2+vg**2) - linewidth=scale*vel/np.amax(vel) - linewidth[linewidth<0.5]=0.5 + if linewidth == 'vel': + scale = options.getfieldvalue('streamlineswidthscale', 3) + vel = np.sqrt(ug**2 + vg**2) + linewidth = scale * vel / np.amax(vel) + linewidth[linewidth < 0.5] = 0.5 # plot streamlines - ax.streamplot(xg,yg,ug,vg,color=color,linewidth=linewidth,density=density,arrowsize=arrowsize) + ax.streamplot(xg, yg, ug, vg, color=color, linewidth=linewidth, density=density, arrowsize=arrowsize) Index: /issm/trunk-jpl/src/m/plot/plot_unit.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plot_unit.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plot_unit.py (revision 24213) @@ -9,17 +9,18 @@ from mpl_toolkits.mplot3d.art3d import Poly3DCollection except ImportError: - print("could not import pylab, matplotlib has not been installed, no plotting capabilities enabled") + print("could not import pylab, matplotlib has not been installed, no plotting capabilities enabled") def plot_unit(x, y, z, elements, data, is2d, isplanet, datatype, options, fig, axgrid, gridindex): """ - PLOT_UNIT - unit plot, display data + PLOT_UNIT - unit plot, display data Usage: plot_unit(x, y, z, elements, data, is2d, isplanet, datatype, options) - See also: PLOTMODEL, PLOT_MANAGER + See also: PLOTMODEL, PLOT_MANAGER """ #if we are plotting 3d replace the current axis + print(is2d) if not is2d: axgrid[gridindex].axis('off') @@ -59,5 +60,5 @@ options.addfield('colormap', cmap) # }}} - # {{{ if plotting only one of several layers reduce dataset, same for surface + # {{{ if plotting only one of several layers reduce dataset, same for surface if options.getfieldvalue('layer', 0) >= 1: plotlayer = options.getfieldvalue('layer', 0) @@ -104,8 +105,8 @@ #first deal with colormap loccmap = plt.cm.ScalarMappable(cmap=cmap) - loccmap.set_array([min(data), max(data)]) - loccmap.set_clim(vmin=min(data), vmax=max(data)) - - #dealing with prism sides + loccmap.set_array([np.nanmin(data), np.nanmax(data)]) + loccmap.set_clim(vmin=np.nanmin(data), vmax=np.nanmax(data)) + + #dealing with prism sides recface = np.vstack((elements[:, 0], elements[:, 1], elements[:, 4], elements[:, 3])).T eltind = np.arange(0, np.shape(elements)[0]) @@ -126,5 +127,5 @@ ax.add_collection3d(pl3) - #dealing with prism bases + #dealing with prism bases triface = np.vstack((elements[:, 0:3], elements[:, 3:6])) eltind = np.arange(0, np.shape(elements)[0]) @@ -132,5 +133,5 @@ tmp = np.ascontiguousarray(triface).view(np.dtype((np.void, triface.dtype.itemsize * triface.shape[1]))) _, idx, recur = np.unique(tmp, return_index=True, return_counts=True) - #we keep only top and bottom elements + #we keep only top and bottom elements triel = triface[idx[np.where(recur == 1)]] triindex = eltind[idx[np.where(recur == 1)]] @@ -147,5 +148,5 @@ ax.set_zlim([min(z), max(z)]) - #raise ValueError('plot_unit error: 3D element plot not supported yet') + #raise ValueError('plot_unit error: 3D element plot not supported yet') return @@ -160,5 +161,5 @@ else: triangles = mpl.tri.Triangulation(x, y, elements) - #tri = ax.tricontourf(triangles, data, colorlevels, cmap = cmap, norm = norm, alpha = alpha) + #tri = ax.tricontourf(triangles, data, colorlevels, cmap = cmap, norm=norm, alpha = alpha) if options.exist('log'): if alpha < 1: #help with antialiasing @@ -174,8 +175,8 @@ #first deal with the colormap loccmap = plt.cm.ScalarMappable(cmap=cmap) - loccmap.set_array([min(data), max(data)]) - loccmap.set_clim(vmin=min(data), vmax=max(data)) - - #deal with prism sides + loccmap.set_array([np.nanmin(data), np.nanmax(data)]) + loccmap.set_clim(vmin=np.nanmin(data), vmax=np.nanmax(data)) + + #deal with prism sides recface = np.vstack((elements[:, 0], elements[:, 1], elements[:, 4], elements[:, 3])).T recface = np.vstack((recface, np.vstack((elements[:, 1], elements[:, 2], elements[:, 5], elements[:, 4])).T)) @@ -192,9 +193,9 @@ ax.add_collection3d(pl3) - #deal with prism faces + #deal with prism faces triface = np.vstack((elements[:, 0:3], elements[:, 3:6])) tmp = np.ascontiguousarray(triface).view(np.dtype((np.void, triface.dtype.itemsize * triface.shape[1]))) _, idx, recur = np.unique(tmp, return_index=True, return_counts=True) - #we keep only top and bottom elements + #we keep only top and bottom elements triel = triface[idx[np.where(recur == 1)]] for triangle in triel: @@ -209,5 +210,5 @@ ax.set_ylim([min(y), max(y)]) ax.set_zlim([min(z), max(z)]) - #raise ValueError('plot_unit error: 3D element plot not supported yet') + #raise ValueError('plot_unit error: 3D element plot not supported yet') return Index: /issm/trunk-jpl/src/m/plot/plot_vertexnumbering.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plot_vertexnumbering.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plot_vertexnumbering.py (revision 24213) @@ -1,58 +1,53 @@ -try: - import pylab as p -except ImportError: - print("could not import pylab, matplotlib has not been installed, no plotting capabilities enabled") - -import numpy as np +import numpy as np from processmesh import processmesh from applyoptions import applyoptions -from plot_icefront import plot_icefront -def plot_vertexnumbering(md,options,fig,axgrid,gridindex): - ''' - PLOT_VERTEXNUMBERING - plot vertex numbering - - Usage: - plot_vertexnumbering(md,options,fig,axes); - - See also: PLOTMODEL - - ''' - #process data and model - x,y,z,elements,is2d,isplanet=processmesh(md,[],options) - ax=axgrid[gridindex] - fig.delaxes(axgrid.cbar_axes[gridindex]) - - if is2d: - ax.triplot(x,y,elements) - else: - print('Not Implemented Yet') +def plot_vertexnumbering(md, options, fig, axgrid, gridindex): + ''' + PLOT_VERTEXNUMBERING - plot vertex numbering - XPad=0.1*(np.max(x)-np.min(x)) - YPad=0.1*(np.max(y)-np.min(y)) - #plot mesh - ax.triplot(x,y,elements) - ax.set_xlim((np.min(x)-XPad,np.max(x)+XPad)) - ax.set_ylim((np.min(y)-XPad,np.max(y)+XPad)) + Usage: + plot_vertexnumbering(md, options, fig, axes) - highlightpos=options.getfieldvalue('highlight',[]) - if highlightpos!='none': - #if just one element duplicate it to avoid coloring issues - if type(highlightpos)==int: - highlightpos=[highlightpos,highlightpos] - #convert from to matlab numbering - highlightpos=[pos-1 for pos in highlightpos] + See also: PLOTMODEL - # and numbers - for i,Xcoord in enumerate(x): - if i in highlightpos: - props = dict(boxstyle='circle', pad=0.1,color='r') - else: - props = dict(boxstyle='circle', pad=0.1,color='w') - ax.text(x[i],y[i],str(i+1),ha='center',va='center',backgroundcolor='w',clip_on=True,bbox=props) - - #apply options - options.addfielddefault('title','Vertex numbers (matlab indexation)') - options.addfielddefault('colorbar','off') - applyoptions(md,[],options,fig,axgrid,gridindex) + ''' + #process data and model + x, y, z, elements, is2d, isplanet = processmesh(md, [], options) + + ax = axgrid[gridindex] + fig.delaxes(axgrid.cbar_axes[gridindex]) + + if is2d: + ax.triplot(x, y, elements) + else: + print('Not Implemented Yet') + + XPad = 0.1 * (np.nanmax(x) - np.nanmin(x)) + YPad = 0.1 * (np.nanmax(y) - np.nanmin(y)) + #plot mesh + ax.triplot(x, y, elements) + ax.set_xlim((np.min(x) - XPad, np.max(x) + XPad)) + ax.set_ylim((np.min(y) - YPad, np.max(y) + YPad)) + + highlightpos = options.getfieldvalue('highlight', []) + if highlightpos != 'none': + #if just one element duplicate it to avoid coloring issues + if type(highlightpos) == int: + highlightpos = [highlightpos, highlightpos] + #convert from to matlab numbering + highlightpos = [pos - 1 for pos in highlightpos] + + # and numbers + for i, Xcoord in enumerate(x): + if i in highlightpos: + props = dict(boxstyle='circle', pad=0.1, color='r') + else: + props = dict(boxstyle='circle', pad=0.1, color='w') + ax.text(x[i], y[i], str(i + 1), ha='center', va='center', backgroundcolor='w', clip_on=True, bbox=props) + + #apply options + options.addfielddefault('title', 'Vertex numbers (matlab indexation)') + options.addfielddefault('colorbar', 'off') + applyoptions(md, [], options, fig, axgrid, gridindex) Index: /issm/trunk-jpl/src/m/plot/plotdoc.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plotdoc.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plotdoc.py (revision 24213) @@ -1,178 +1,176 @@ def plotdoc(): - '''PLOTDOC - plot documentation - %As of now it is more a TODO list - % Usage: - % plotdoc() - ''' - pydata={'quiver':' quiver plot give data and a vector array [Vx,Vy]', - 'mesh':' draw mesh using trisurf', - 'BC':' this will draw all the boundary conditions (Dirichlet and Neumann).', - 'elementnumbering':' numbering of elements (matlab indices)', - '3D disclaimer':'3D is implemented with plot3d for now this is not optimal and may change to mayavi at some point. The impelementation is on the development side for now so expect some issue and question your plotting before you results.'} - TODOdata={'basal_drag':' plot the basal drag on the bed (in kPa) based on the velocity in md.initialization', - 'basal_dragx or basal_dragy' :' plot a component of the basal drag on the bed (in kPa)', - 'boundaries':' this will draw all the segment boundaries to the model, including rifts.', - 'icefront':' this will show segments that are used to define the icefront of the model (Neumann boundary conditions).', - 'deviatoricstress_tensor':' plot the components of the deviatoric stress tensor (tauxx,tauyy,tauzz,tauxy,tauxz,tauyz, if computed', - 'deviatoricstress_principal':' plot the deviatoricstress tensor principal axis and principal values', - 'deviatoricstress_principalaxis1':' arrow plot the first principal axis of the deviatoricstress tensor(replace 1 by 2 or 3 if needed)', - 'driving_stress':' plot the driving stress (in kPa)', - 'elements_type':' model used for each element', - 'highlightvertices':' to highlight vertices (use highlight option to enter the vertex list', - 'referential':' stressbalance referential', - 'riftvel':' velocities along rifts', - 'riftrelvel':' relative velocities along rifts', - 'riftpenetration':' penetration levels for a fault', - 'riftfraction':' fill fractions for every node of the rifts', - 'rifts':' plot mesh with an offset so that rifts are visible', - 'strainrate_tensor':' plot the components of the strainrate tensor (exx,eyy,ezz,exy,exz,eyz) if computed', - 'strainrate_principal':' plot the strainrate tensor principal axis and principal values)', - 'strainrate_principalaxis1':' arrow plot the first principal axis of the strainrate tensor(replace 1 by 2 or 3 if needed)', - 'stress_tensor':' plot the components of stress tensor (sxx,syy,szz,sxy,sxz,syz) if computed', - 'stress_principal':' plot the stress tensor principal axis and principal values', - 'stress_principalaxis1':' arrow plot the first principal axis of the stress tensor(replace 1 by 2 or 3 if needed)', - 'transient_results':' this will printlay all the time steps of a transient run (use steps to specify the steps requested)', - 'transient_vel':' this will printlay the velocity for the time steps requested in ''steps'' of a transient run', - 'transient_vel':' vel can be by any field of the transient results (vx, vy, vz, vel, temperature, melting, pressure, bed, thickness, surface)', - 'transient_field':' dynamic plot of results. specify ''steps'' option, as fell as ''field'' (defaults are all steps, for ''Vel'' field)', - 'transient_movie':' this will printlay the time steps of a given field of a transient run', - 'transient_movie_field':' field to be printlayed when doing transient_movie data printlay', - 'transient_movie_output':' filename if output is desired for movie', - 'transient_movie_time':' time for each image (default 2 seconds)', - 'thermaltransient_results':' this will printlay all the time steps of a thermal transient run', - 'qmuhistnorm':' histogram normal distribution. needs option qmudata', - 'qmumean':' plot of mean distribution in sampling analysis with scaled response. needs option qmudata for descriptor', - 'qmustddev':' plot of stddev distribution in sampling analysis with scaled response. needs option qmudata for descriptor', - 'part_hist':' partitioning node and area histogram'} - - pyoptions={'axis':" show ('on') or hide ('off') axes", - 'caxis':" modify colorbar range. (array of type [a b] where b>=a)", - 'colorlevels':" N, number of levels to use", - 'colorbar':" add colorbar (string 'on','off' or 'one')", - 'axes_pad':" spacing between axes (default is 0.25)", - 'colorbartitle':" colorbar title (string)", - 'colorbarticks':" set colorbar ticks manually (list)", - 'colorbarfontsize':" specify colorbar fontsize", - 'colormap':" change the default colormap ('viridis' is the default)", - 'contourlevels':" N or [value1,...] add the contours of the specified values or N contours", - 'streamlines':" TOFIX argument does nothing", - 'edgecolor':" color of mesh edges. RGB tuple or standard string", - 'fontsize':" fontsize for the title", - 'fontweight':" fontweight for the title 'normal', 'bold'", - 'fontcolor':" TODO", - 'highlight':" highlights certain nodes or elements when using 'vetrexnumbering' or 'elementnumbering' or 'highlightvertices ' or 'highlightelements' option", - 'title':" subplot title (string)", - 'xlim':" limits of X axis (all subplots) (ex: [0,500])", - 'ylim':" limits of Y axis (all subplots) (ex: [0,500])", - 'xlabel':" X axis title", - 'ylabel':" Y axis title", - 'scaling':" scaling factor used by quiver plots.", - 'quivercol':" color of quiver arrows, 'values' give value colored arrows", - 'text':" print string or list of strings", - 'textposition':" [x,y] position of text, list if several texts (position betwee 0 and 1)", - 'textsize':" text fontsize TOFIX ", - 'textweight':" text fontweight", - 'textcolor':" text color", - 'textrotation':" text rotation angle", - 'mask':" condition. Only 'true' values are plotted ", - 'log':" cutoff value for log", - 'backgroundcolor':" plot background color. RGB tuple or standard string", - 'expdisp':" path (or list of paths) to the exp file to be plotted ", - 'explinewidth':" linewidth ", - 'explinestyle':" matplotlib linestyle string ", - 'explinecolor':" matplotlib color string ", - 'expfill':" (True/False) fill a closed contour ", - 'expfillcolor':" Color for a filled contour, only used if expfill is True ", - 'expfillalpha':" alpha transparency for filled contour ", - 'overlay':" True/False. Overlay a georeferenced image (radar/visible) ", - 'overlay_image':" path to overlay image ", - 'overlayhist':" plot a histogram of overlay image, used for setting overlaylims ", - 'overlaylims':" normalized limits to clip and stretch contrast of overlay image (in [0,1], ex. [0.25,0.75]) ", - 'alpha':" set transparency of plotted data (in [0,1]) ", - 'vertexnumbering':' numbering of vertices', - 'elementnumbering':' numbering of elements (matlab indices)', - 'highlightelements':' to highlight elements to highlight the element list', - 'layer':"number of the layer to display for 3D runs"} + '''PLOTDOC - plot documentation + %As of now it is more a TODO list + % Usage: + % plotdoc() + ''' + pydata = {'quiver': ' quiver plot give data and a vector array [Vx, Vy]', + 'mesh': ' draw mesh using trisurf', + 'BC': ' this will draw all the boundary conditions (Dirichlet and Neumann).', + 'elementnumbering': ' numbering of elements (matlab indices)', + '3D disclaimer': '3D is implemented with plot3d for now this is not optimal and may change to mayavi at some point. The impelementation is on the development side for now so expect some issue and question your plotting before you results.'} + # TODOdata = {'basal_drag': ' plot the basal drag on the bed (in kPa) based on the velocity in md.initialization', + # 'basal_dragx or basal_dragy': ' plot a component of the basal drag on the bed (in kPa)', + # 'boundaries': ' this will draw all the segment boundaries to the model, including rifts.', + # 'icefront': ' this will show segments that are used to define the icefront of the model (Neumann boundary conditions).', + # 'deviatoricstress_tensor': ' plot the components of the deviatoric stress tensor (tauxx, tauyy, tauzz, tauxy, tauxz, tauyz, if computed', + # 'deviatoricstress_principal': ' plot the deviatoricstress tensor principal axis and principal values', + # 'deviatoricstress_principalaxis1': ' arrow plot the first principal axis of the deviatoricstress tensor(replace 1 by 2 or 3 if needed)', + # 'driving_stress': ' plot the driving stress (in kPa)', + # 'elements_type': ' model used for each element', + # 'highlightvertices': ' to highlight vertices (use highlight option to enter the vertex list', + # 'referential': ' stressbalance referential', + # 'riftvel': ' velocities along rifts', + # 'riftrelvel': ' relative velocities along rifts', + # 'riftpenetration': ' penetration levels for a fault', + # 'riftfraction': ' fill fractions for every node of the rifts', + # 'rifts': ' plot mesh with an offset so that rifts are visible', + # 'strainrate_tensor': ' plot the components of the strainrate tensor (exx, eyy, ezz, exy, exz, eyz) if computed', + # 'strainrate_principal': ' plot the strainrate tensor principal axis and principal values)', + # 'strainrate_principalaxis1': ' arrow plot the first principal axis of the strainrate tensor(replace 1 by 2 or 3 if needed)', + # 'stress_tensor': ' plot the components of stress tensor (sxx, syy, szz, sxy, sxz, syz) if computed', + # 'stress_principal': ' plot the stress tensor principal axis and principal values', + # 'stress_principalaxis1': ' arrow plot the first principal axis of the stress tensor(replace 1 by 2 or 3 if needed)', + # 'transient_results': ' this will printlay all the time steps of a transient run (use steps to specify the steps requested)', + # 'transient_vel': ' vel can be by any field of the transient results (vx, vy, vz, vel, temperature, melting, pressure, bed, thickness, surface)', + # 'transient_field': ' dynamic plot of results. specify ''steps'' option, as fell as ''field'' (defaults are all steps, for ''Vel'' field)', + # 'transient_movie': ' this will printlay the time steps of a given field of a transient run', + # 'transient_movie_field': ' field to be printlayed when doing transient_movie data printlay', + # 'transient_movie_output': ' filename if output is desired for movie', + # 'transient_movie_time': ' time for each image (default 2 seconds)', + # 'thermaltransient_results': ' this will printlay all the time steps of a thermal transient run', + # 'qmuhistnorm': ' histogram normal distribution. needs option qmudata', + # 'qmumean': ' plot of mean distribution in sampling analysis with scaled response. needs option qmudata for descriptor', + # 'qmustddev': ' plot of stddev distribution in sampling analysis with scaled response. needs option qmudata for descriptor', + # 'part_hist': ' partitioning node and area histogram'} - TODOoptions={'basin':" zoom on a given basin ('pineislandglacier','ronneiceshelf', use isbasin to identify a basin", - 'figurebackgroundcolor':" figure background color. (default is 'none',", - 'coord':" 'xy' (default) or 'latlon'", - 'colorbarpos':" [x,y,dx,dy] where x,y,dx and dy are within [0 1]", - 'colorbarcornerposition':" 'West','North',etc ...", - 'colorbartitlerotation':" -90, etc ...", - 'colorbarwidth':" multiplier (default 1) to the default width colorbar", - 'colorbarheight':" multiplier (default 1) to the default height colorbar", - 'contourticks':" 'on' or 'off' to printlay the ticks of the contours", - 'contouronly':" 'on' or 'off' to printlay the contours on a white background", - 'contourcolor':" ticks and contour color", - 'density':" density of quivers (one arrow every N nodes, N integer)", - 'inset':" add an inset (zoom) of the current figure if 1 (use 'insetx', 'insety' and 'insetpos' to determine the inset position and content)", - 'insetx':" [min(x) max(x)] where min(x) and max(x) are values determining the inset content", - 'insety':" [min(y) max(y)] where min(y) and max(y) are values determining the inset content", - 'insetpos':" [x,y,dx,dy] where x,y,dx and dy are within [0 1]", - 'resolution':" resolution used by section value (array of type [horizontal_resolution vertical_resolution])", - 'showsection':" show section used by 'sectionvalue' (string 'on' or a number of labels)", - 'sectionvalue':" give the value of data on a profile given by an Argus file (string 'Argusfile_name.exp',", - 'profile':" give the value of data along a vertical profile ([xlocation ylocation])", - 'smooth':" smooth element data (string 'yes' or integer)", - 'view':" same as standard matlab option (ex: 2, 3 or [90 180]", - 'zlim':" same as standard matlab option", - 'xticklabel':" specifiy xticklabel", - 'yticklabel':" specifiy yticklabel", - 'contrast':" (default 1) coefficient to add contrast to the radar amplitude image used in overlays", - 'highres':" resolution of overlayed radar amplitude image (default is 0, high resolution is 1).", - 'alpha':" transparency coefficient (the higher, the more transparent). Default is 1.5", - 'scaling':" scaling factor used by quiver plots. Default is 0.4", - 'autoscale':" set to 'off' to have all the quivers with the same size. Default is 'on'", - 'linewidth':" line width for expprint plot (use a cell of strings if more than one)", - 'border':" size of printlay border (in pixels). active only for overlay plots", - 'nan':" value assigned to NaNs (convenient when plotting BC)", - 'partitionedges':" 'off' by default. overlay plot of partition edges", - 'latlon':" 'on' or {latstep lonstep [resolution [color]]} where latstep,longstep and resolution are in degrees, color is a [r g b] array", - 'latlonnumbering':" 'on' or {latgap longap colornumber latangle lonangle} where latgap and longap are pixel gaps for the numbers", - 'latlonclick':" 'on' to click on latlon ticks positions colornumber is a [r g b] array and latangle and lonangle are angles to flip the numbers", - 'northarrow':" add an arrow pointing north, 'on' for default value or [x0 y0 length [ratio width fontsize]] where (x0,y0) are the coordinates of the base, ratio=headlength/length", - 'offset':" mesh offset used by 'rifts', default is 500", - 'scaleruler':" add a scale ruler, 'on' for default value or [x0 y0 length width numberofticks] where (x0,y0) are the coordinates of the lower left corner", - 'showregion':" show domain in Antarctica on an inset, use 'insetpos' properties", - 'visible':" 'off' to make figure unvisible, default is 'on'", - 'wrapping':" repeat 'n' times the colormap ('n' must be an integer)", - 'unit':" by default, in m, otherwise, 'km' is available", - 'legend_position':" by default, 'NorthEasth'", - 'qmudata':" ", - 'figposition':" position of figure: 'fullscreen', 'halfright', 'halfleft', 'portrait', 'landscape',... (hardcoded in applyoptions.m)", - 'offsetaxispos':" offset of current axis position to get more space (ex: [-0.02 0 0.04 0])", - 'axispos':" axis position to get more space", - 'hmin':" (numeric, minimum for histogram)", - 'hmax':" (numeric, maximum for histogram)", - 'hnint':" (numeric, number of intervals for histogram)", - 'ymin1':" (numeric, minimum of histogram y-axis)", - 'ymax1':" (numeric, maximum of histogram y-axis)", - 'ymin2':" (numeric, minimum of cdf y-axis)", - 'ymax2':" (numeric, maximum of cdf y-axis)", - 'cdfplt':" (char, 'off' to turn off cdf line plots)", - 'cdfleg':" (char, 'off' to turn off cdf legends)", - 'segmentnumbering':" ('off' by default)", - 'kmlgroundoverlay':" ('off' by default)", - 'kmlfilename':" ('tempfile.kml' by default)", - 'kmlroot':" ('./' by default)", - 'kmlimagename':" ('tempimage' by default)", - 'kmlimagetype':" ('png' by default)", - 'kmlresolution':" (1 by default)", - 'kmlfolder':" ('Ground Overlay' by default)", - 'kmlfolderdescription':" ('' by default)", - 'kmlgroundoverlayname':" ('' by default)", - 'kmlgroundoverlaydescription':"N/A by default')"} + pyoptions = {'axis': " show ('on') or hide ('off') axes", + 'caxis': " modify colorbar range. (array of type [a b] where b >= a)", + 'colorlevels': " N, number of levels to use", + 'colorbar': " add colorbar (string 'on', 'off' or 'one')", + 'axes_pad': " spacing between axes (default is 0.25)", + 'colorbartitle': " colorbar title (string)", + 'colorbarticks': " set colorbar ticks manually (list)", + 'colorbarfontsize': " specify colorbar fontsize", + 'colormap': " change the default colormap ('viridis' is the default)", + 'contourlevels': " N or [value1, ...] add the contours of the specified values or N contours", + 'streamlines': " TOFIX argument does nothing", + 'edgecolor': " color of mesh edges. RGB tuple or standard string", + 'fontsize': " fontsize for the title", + 'fontweight': " fontweight for the title 'normal', 'bold'", + 'fontcolor': " TODO", + 'highlight': " highlights certain nodes or elements when using 'vetrexnumbering' or 'elementnumbering' or 'highlightvertices ' or 'highlightelements' option", + 'title': " subplot title (string)", + 'xlim': " limits of X axis (all subplots) (ex: [0, 500])", + 'ylim': " limits of Y axis (all subplots) (ex: [0, 500])", + 'xlabel': " X axis title", + 'ylabel': " Y axis title", + 'scaling': " scaling factor used by quiver plots.", + 'quivercol': " color of quiver arrows, 'values' give value colored arrows", + 'text': " print string or list of strings", + 'textposition': " [x, y] position of text, list if several texts (position betwee 0 and 1)", + 'textsize': " text fontsize TOFIX ", + 'textweight': " text fontweight", + 'textcolor': " text color", + 'textrotation': " text rotation angle", + 'mask': " condition. Only 'true' values are plotted ", + 'log': " cutoff value for log", + 'backgroundcolor': " plot background color. RGB tuple or standard string", + 'expdisp': " path (or list of paths) to the exp file to be plotted ", + 'explinewidth': " linewidth ", + 'explinestyle': " matplotlib linestyle string ", + 'explinecolor': " matplotlib color string ", + 'expfill': " (True / False) fill a closed contour ", + 'expfillcolor': " Color for a filled contour, only used if expfill is True ", + 'expfillalpha': " alpha transparency for filled contour ", + 'overlay': " True / False. Overlay a georeferenced image (radar / visible) ", + 'overlay_image': " path to overlay image ", + 'overlayhist': " plot a histogram of overlay image, used for setting overlaylims ", + 'overlaylims': " normalized limits to clip and stretch contrast of overlay image (in [0, 1], ex. [0.25, 0.75]) ", + 'alpha': " set transparency of plotted data (in [0, 1]) ", + 'vertexnumbering': ' numbering of vertices', + 'elementnumbering': ' numbering of elements (matlab indices)', + 'highlightelements': ' to highlight elements to highlight the element list', + 'layer': "number of the layer to display for 3D runs"} + # TODOoptions = {'basin': " zoom on a given basin ('pineislandglacier', 'ronneiceshelf', use isbasin to identify a basin", + # 'figurebackgroundcolor': " figure background color. (default is 'none', ", + # 'coord': " 'xy' (default) or 'latlon'", + # 'colorbarpos': " [x, y, dx, dy] where x, y, dx and dy are within [0 1]", + # 'colorbarcornerposition': " 'West', 'North', etc ...", + # 'colorbartitlerotation': " - 90, etc ...", + # 'colorbarwidth': " multiplier (default 1) to the default width colorbar", + # 'colorbarheight': " multiplier (default 1) to the default height colorbar", + # 'contourticks': " 'on' or 'off' to printlay the ticks of the contours", + # 'contouronly': " 'on' or 'off' to printlay the contours on a white background", + # 'contourcolor': " ticks and contour color", + # 'density': " density of quivers (one arrow every N nodes, N integer)", + # 'inset': " add an inset (zoom) of the current figure if 1 (use 'insetx', 'insety' and 'insetpos' to determine the inset position and content)", + # 'insetx': " [min(x) max(x)] where min(x) and max(x) are values determining the inset content", + # 'insety': " [min(y) max(y)] where min(y) and max(y) are values determining the inset content", + # 'insetpos': " [x, y, dx, dy] where x, y, dx and dy are within [0 1]", + # 'resolution': " resolution used by section value (array of type [horizontal_resolution vertical_resolution])", + # 'showsection': " show section used by 'sectionvalue' (string 'on' or a number of labels)", + # 'sectionvalue': " give the value of data on a profile given by an Argus file (string 'Argusfile_name.exp', ", + # 'profile': " give the value of data along a vertical profile ([xlocation ylocation])", + # 'smooth': " smooth element data (string 'yes' or integer)", + # 'view': " same as standard matlab option (ex: 2, 3 or [90 180]", + # 'zlim': " same as standard matlab option", + # 'xticklabel': " specifiy xticklabel", + # 'yticklabel': " specifiy yticklabel", + # 'contrast': " (default 1) coefficient to add contrast to the radar amplitude image used in overlays", + # 'highres': " resolution of overlayed radar amplitude image (default is 0, high resolution is 1).", + # 'alpha': " transparency coefficient (the higher, the more transparent). Default is 1.5", + # 'scaling': " scaling factor used by quiver plots. Default is 0.4", + # 'autoscale': " set to 'off' to have all the quivers with the same size. Default is 'on'", + # 'linewidth': " line width for expprint plot (use a cell of strings if more than one)", + # 'border': " size of printlay border (in pixels). active only for overlay plots", + # 'nan': " value assigned to NaNs (convenient when plotting BC)", + # 'partitionedges': " 'off' by default. overlay plot of partition edges", + # 'latlon': " 'on' or {latstep lonstep [resolution [color]]} where latstep, longstep and resolution are in degrees, color is a [r g b] array", + # 'latlonnumbering': " 'on' or {latgap longap colornumber latangle lonangle} where latgap and longap are pixel gaps for the numbers", + # 'latlonclick': " 'on' to click on latlon ticks positions colornumber is a [r g b] array and latangle and lonangle are angles to flip the numbers", + # 'northarrow': " add an arrow pointing north, 'on' for default value or [x0 y0 length [ratio width fontsize]] where (x0, y0) are the coordinates of the base, ratio = headlength / length", + # 'offset': " mesh offset used by 'rifts', default is 500", + # 'scaleruler': " add a scale ruler, 'on' for default value or [x0 y0 length width numberofticks] where (x0, y0) are the coordinates of the lower left corner", + # 'showregion': " show domain in Antarctica on an inset, use 'insetpos' properties", + # 'visible': " 'off' to make figure unvisible, default is 'on'", + # 'wrapping': " repeat 'n' times the colormap ('n' must be an integer)", + # 'unit': " by default, in m, otherwise, 'km' is available", + # 'legend_position': " by default, 'NorthEasth'", + # 'qmudata': " ", + # 'figposition': " position of figure: 'fullscreen', 'halfright', 'halfleft', 'portrait', 'landscape', ... (hardcoded in applyoptions.m)", + # 'offsetaxispos': " offset of current axis position to get more space (ex: [ - 0.02 0 0.04 0])", + # 'axispos': " axis position to get more space", + # 'hmin': " (numeric, minimum for histogram)", + # 'hmax': " (numeric, maximum for histogram)", + # 'hnint': " (numeric, number of intervals for histogram)", + # 'ymin1': " (numeric, minimum of histogram y - axis)", + # 'ymax1': " (numeric, maximum of histogram y - axis)", + # 'ymin2': " (numeric, minimum of cdf y - axis)", + # 'ymax2': " (numeric, maximum of cdf y - axis)", + # 'cdfplt': " (char, 'off' to turn off cdf line plots)", + # 'cdfleg': " (char, 'off' to turn off cdf legends)", + # 'segmentnumbering': " ('off' by default)", + # 'kmlgroundoverlay': " ('off' by default)", + # 'kmlfilename': " ('tempfile.kml' by default)", + # 'kmlroot': " ('./' by default)", + # 'kmlimagename': " ('tempimage' by default)", + # 'kmlimagetype': " ('png' by default)", + # 'kmlresolution': " (1 by default)", + # 'kmlfolder': " ('Ground Overlay' by default)", + # 'kmlfolderdescription': " ('' by default)", + # 'kmlgroundoverlayname': " ('' by default)", + # 'kmlgroundoverlaydescription': "N/A by default')"} - print(" Plot usage: plotmodel(model,varargin)") - print(" plotting is done with couples of keywords values, the type and style of data to display is given by one (or several) of the followings") - print(" Options: ") - print(" 'data' : and a model field or one of the following options.") - for key in list(pydata.keys()): - print((" - {} : {}".format(key,pydata[key]))) - print("") - print(" The general look of the plot is then given by the following keywords") - for key in sorted(pyoptions): - print((" - {} : {}".format(key,pyoptions[key]))) - print(" any options (except 'data') can be followed by '#i' where 'i' is the subplot number, or '#all' if applied to all plots") + print(" Plot usage: plotmodel(model, varargin)") + print(" plotting is done with couples of keywords values, the type and style of data to display is given by one (or several) of the followings") + print(" Options: ") + print(" 'data' : and a model field or one of the following options.") + for key in list(pydata.keys()): + print((" - {} : {}".format(key, pydata[key]))) + print("") + print(" The general look of the plot is then given by the following keywords") + for key in sorted(pyoptions): + print((" - {} : {}".format(key, pyoptions[key]))) + print(" any options (except 'data') can be followed by ' #i' where 'i' is the subplot number, or ' #all' if applied to all plots") Index: /issm/trunk-jpl/src/m/plot/plotmodel.py =================================================================== --- /issm/trunk-jpl/src/m/plot/plotmodel.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/plotmodel.py (revision 24213) @@ -1,3 +1,3 @@ -import numpy as np +import numpy as np from plotoptions import plotoptions from plot_manager import plot_manager @@ -27,5 +27,5 @@ hold = options.list[0].getfieldvalue('hold', False) - #if nrows and ncols specified, then bypass + #if nrows and ncols specified, then bypass if options.list[0].exist('nrows'): nrows = options.list[0].getfieldvalue('nrows') @@ -46,5 +46,5 @@ #check that nrows and ncols were given at the same time! if not nr == nc: - raise Exception('error: nrows and ncols need to be specified together, or not at all') + raise Exception('error: nrows and ncols need to be specified together, or not at all') #Go through plots @@ -67,5 +67,5 @@ 'off': 'None', 'one': 'single'} - # options needed to define plot grid + # options needed to define plot grid plotnum = options.numberofplots if plotnum == 1: @@ -76,5 +76,5 @@ share_all = options.list[0].getfieldvalue('share_all', True) # True, False label_mode = options.list[0].getfieldvalue('label_mode', 'L') # 1, L, all - colorbar = options.list[0].getfieldvalue('colorbar', 'on') # on, off (single) + colorbar = options.list[0].getfieldvalue('colorbar', 'on') # on, off (single) cbar_mode = translator[colorbar] cbar_location = options.list[0].getfieldvalue('colorbarpos', 'right') # right, top @@ -84,5 +84,4 @@ axgrid = ImageGrid(fig, 111, nrows_ncols=(nrows, ncols), - #ngrids=plotnum, direction=direction, axes_pad=axes_pad, Index: /issm/trunk-jpl/src/m/plot/processdata.py =================================================================== --- /issm/trunk-jpl/src/m/plot/processdata.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/processdata.py (revision 24213) @@ -1,138 +1,139 @@ -import numpy as np +import numpy as np -def processdata(md,data,options): - """ - PROCESSDATA - process data to be plotted - - datatype = 1 -> elements - datatype = 2 -> nodes - datatype = 3 -> node quivers - datatype = 4 -> patch - - Usage: - data,datatype=processdata(md,data,options); - - See also: PLOTMODEL, PROCESSMESH - """ - # {{{ Initialisation and grabbing auxiliaries - # check format - if (len(data)==0 or (len(data)==1 and not isinstance(data,dict) and np.isnan(data).all())): - raise ValueError("processdata error message: 'data' provided is empty") - # get the shape - if 'numberofvertices2d' in dir(md.mesh): - numberofvertices2d=md.mesh.numberofvertices2d - numberofelements2d=md.mesh.numberofelements2d - else: - numberofvertices2d=np.nan - numberofelements2d=np.nan - procdata=np.copy(data) - #initialize datatype - datatype=0 - # get datasize - if np.ndim(procdata)==1: - datasize=(np.shape(procdata)[0],1) - elif np.ndim(procdata)==2: - datasize=np.shape(procdata) - elif np.ndim(procdata)==3: - if np.shape(procdata)[0]==2: - #treating a dim two list that needs to be stacked - procdata=np.hstack((procdata[0,:,:],procdata[1,:,:])) - datasize=np.shape(procdata) - else: - raise ValueError('data list contains more than two vectore, we can not cope with that') - else: - raise ValueError('data passed to plotmodel has bad dimensions; check that column vectors are rank-1') - # }}} - # {{{ process NaN's if any - nanfill=options.getfieldvalue('nan',-9999) - if np.any(np.isnan(procdata)): - lb=np.nanmin(procdata) - ub=np.nanmax(procdata) - if lb==ub: - lb=lb-0.5 - ub=ub+0.5 - nanfill=lb-1 - #procdata[np.isnan(procdata)]=nanfill - procdata=np.ma.array(procdata,mask=np.isnan(procdata)) - options.addfielddefault('clim',[lb,ub]) - options.addfielddefault('cmap_set_under','1') - print(("WARNING: nan's treated as", nanfill, "by default. Change using pairoption 'nan',nan_fill_value in plotmodel call")) - # }}} - # {{{ log - if options.exist('log'): - cutoff=options.getfieldvalue('log',1) - procdata[np.where(procdata1 and datasize[0]!= md.mesh.numberofvertices+1: - if datasize[0]==md.mesh.numberofvertices and datasize[1]==2: - datatype=3 - else: - raise ValueError('plotmodel error message: data should have two columns of length md.mesh.numberofvertices for a quiver plot') - # }}} - # {{{ element data - if datasize[0]==md.mesh.numberofelements and datasize[1]==1: - #initialize datatype if non patch - if datatype!=4 and datatype!=5: - datatype=1 - # {{{mask - if options.exist('mask'): - flags=options.getfieldvalue('mask') - hide=np.invert(flags) - if np.size(flags)==md.mesh.numberofvertices: - EltMask=np.asarray([np.any(np.in1d(index,np.where(hide))) for index in md.mesh.elements-1]) - procdata=np.ma.array(procdata,mask=EltMask) - options.addfielddefault('cmap_set_bad','w') - elif np.size(flags)==md.mesh.numberofelements: - procdata=np.ma.array(procdata,mask=hide) - options.addfielddefault('cmap_set_bad','w') - else: - print('plotmodel warning: mask length not supported yet (supported length are md.mesh.numberofvertices and md.mesh.numberofelements') - # }}} +def processdata(md, data, options): + """ + PROCESSDATA - process data to be plotted - # }}} - # {{{ node data - if datasize[0]==md.mesh.numberofvertices and datasize[1]==1: - datatype=2 - # {{{ Mask - if options.exist('mask'): - flags=options.getfieldvalue('mask') - hide=np.invert(flags) - if np.size(flags)==md.mesh.numberofvertices: - procdata=np.ma.array(procdata,mask=hide) - options.addfielddefault('cmap_set_bad','w') - elif np.size(flags)==md.mesh.numberofelements: - NodeMask=np.zeros(np.shape(md.mesh.x),dtype=bool) - HideElt=md.mesh.elements[np.where(hide)[0]]-1 - NodeMask[HideElt]=True - procdata=np.ma.array(procdata,mask=NodeMask) - options.addfielddefault('cmap_set_bad','w') - else: - print('plotmodel warning: mask length not supported yet (supported length are md.mesh.numberofvertices and md.mesh.numberofelements') - # }}} - # }}} - # {{{ spc time series - if datasize[0]==md.mesh.numberofvertices+1: - datatype=2 - spccol=options.getfieldvalue('spccol',0) - print('multiple-column spc field; specify column to plot using option "spccol"') - print(('column ', spccol, ' plotted for time: ', procdata[-1,spccol])) - procdata=procdata[0:-1,spccol] - - #mask? - + datatype = 1 - > elements + datatype = 2 - > nodes + datatype = 3 - > node quivers + datatype = 4 - > patch + + Usage: + data, datatype = processdata(md, data, options) + + See also: PLOTMODEL, PROCESSMESH + """ + # {{{ Initialisation and grabbing auxiliaries + # check format + if (len(data) == 0 or (len(data) == 1 and not isinstance(data, dict) and np.isnan(data).all())): + raise ValueError("processdata error message: 'data' provided is empty") + # get the shape + if 'numberofvertices2d' in dir(md.mesh): + numberofvertices2d = md.mesh.numberofvertices2d + numberofelements2d = md.mesh.numberofelements2d + else: + numberofvertices2d = np.nan + numberofelements2d = np.nan + procdata = np.copy(data) + #initialize datatype + datatype = 0 + # get datasize + if np.ndim(procdata) == 1: + datasize = (np.shape(procdata)[0], 1) + elif np.ndim(procdata) == 2: + datasize = np.shape(procdata) + elif np.ndim(procdata) == 3: + if np.shape(procdata)[0] == 2: + #treating a dim two list that needs to be stacked + procdata = np.hstack((procdata[0, :, :], procdata[1, :, :])) + datasize = np.shape(procdata) + else: + raise ValueError('data list contains more than two vectore, we can not cope with that') + else: + raise ValueError('data passed to plotmodel has bad dimensions; check that column vectors are rank - 1') + # }}} + # {{{ process NaN's if any + nanfill = options.getfieldvalue('nan', - 9999) + if np.any(np.isnan(procdata)): + lb = np.nanmin(procdata) + ub = np.nanmax(procdata) + if lb == ub: + lb = lb - 0.5 + ub = ub + 0.5 + nanfill = lb - 1 + #procdata[np.isnan(procdata)] = nanfill + procdata = np.ma.array(procdata, mask=np.isnan(procdata)) + options.addfielddefault('clim', [lb, ub]) + options.addfielddefault('cmap_set_under', '1') + print(("WARNING: nan's treated as", nanfill, "by default. Change using pairoption 'nan', nan_fill_value in plotmodel call")) + # }}} + # {{{ log + if options.exist('log'): + cutoff = options.getfieldvalue('log', 1) + procdata[np.where(procdata < cutoff)] = cutoff + # }}} + # {{{ quiver plot + if datasize[1] > 1 and datasize[0] != md.mesh.numberofvertices + 1: + if datasize[0] == md.mesh.numberofvertices and datasize[1] == 2: + datatype = 3 + else: + raise ValueError('plotmodel error message: data should have two columns of length md.mesh.numberofvertices for a quiver plot') + # }}} + # {{{ element data + + if datasize[0] == md.mesh.numberofelements and datasize[1] == 1: + #initialize datatype if non patch + if datatype != 4 and datatype != 5: + datatype = 1 + # {{{mask + if options.exist('mask'): + flags = options.getfieldvalue('mask') + hide = np.invert(flags) + if np.size(flags) == md.mesh.numberofvertices: + EltMask = np.asarray([np.any(np.in1d(index, np.where(hide))) for index in md.mesh.elements - 1]) + procdata = np.ma.array(procdata, mask=EltMask) + options.addfielddefault('cmap_set_bad', 'w') + elif np.size(flags) == md.mesh.numberofelements: + procdata = np.ma.array(procdata, mask=hide) + options.addfielddefault('cmap_set_bad', 'w') + else: + print('plotmodel warning: mask length not supported yet (supported length are md.mesh.numberofvertices and md.mesh.numberofelements') + # }}} + + # }}} + # {{{ node data + if datasize[0] == md.mesh.numberofvertices and datasize[1] == 1: + datatype = 2 + # {{{ Mask + if options.exist('mask'): + flags = options.getfieldvalue('mask') + hide = np.invert(flags) + if np.size(flags) == md.mesh.numberofvertices: + procdata = np.ma.array(procdata, mask=hide) + options.addfielddefault('cmap_set_bad', 'w') + elif np.size(flags) == md.mesh.numberofelements: + NodeMask = np.zeros(np.shape(md.mesh.x), dtype=bool) + HideElt = md.mesh.elements[np.where(hide)[0]] - 1 + NodeMask[HideElt] = True + procdata = np.ma.array(procdata, mask=NodeMask) + options.addfielddefault('cmap_set_bad', 'w') + else: + print('plotmodel warning: mask length not supported yet (supported length are md.mesh.numberofvertices and md.mesh.numberofelements') + # }}} + # }}} + # {{{ spc time series + if datasize[0] == md.mesh.numberofvertices + 1: + datatype = 2 + spccol = options.getfieldvalue('spccol', 0) + print('multiple-column spc field; specify column to plot using option "spccol"') + print(('column ', spccol, ' plotted for time: ', procdata[-1, spccol])) + procdata = procdata[0: - 1, spccol] + + #mask? + #layer projection? - + #control arrow density if quiver plot - # }}} - # {{{ convert rank-2 array to rank-1 - if np.ndim(procdata)==2 and np.shape(procdata)[1]==1: - procdata=procdata.reshape(-1,) - # }}} - # {{{ if datatype is still zero, error out - if datatype==0: - raise ValueError("processdata error: data provided not recognized or not supported") - else: - return procdata, datatype - # }}} + # }}} + # {{{ convert rank - 2 array to rank - 1 + if np.ndim(procdata) == 2 and np.shape(procdata)[1] == 1: + procdata = procdata.reshape(- 1, ) + # }}} + # {{{ if datatype is still zero, error out + if datatype == 0: + raise ValueError("processdata error: data provided not recognized or not supported") + else: + return procdata, datatype + # }}} Index: /issm/trunk-jpl/src/m/plot/processmesh.py =================================================================== --- /issm/trunk-jpl/src/m/plot/processmesh.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/processmesh.py (revision 24213) @@ -1,59 +1,59 @@ -from math import isnan -import numpy as np +import numpy as np -def processmesh(md,data,options): - """ - PROCESSMESH - process the mesh for plotting - - Usage: - x,y,z,elements,is2d=processmech(md,data,options) - - See also: PLOTMODEL, PROCESSDATA - """ - - # {{{ check mesh size parameters - if md.mesh.numberofvertices==0: - raise ValueError('processmesh error: mesh is empty') - if md.mesh.numberofvertices==md.mesh.numberofelements: - raise ValueError('processmesh error: the number of elements is the same as the number of nodes') - # }}} - # {{{ treating coordinates - try: - z=md.mesh.z - except AttributeError: - z=np.zeros(np.shape(md.mesh.x)) - elements=md.mesh.elements-1 - - if options.getfieldvalue('layer',0)>=1: - x=md.mesh.x2d - y=md.mesh.y2d - z=np.zeros(np.shape(x)) - elements=md.mesh.elements2d-1 - elif 'latlon' in options.getfieldvalue('coord','xy'): - x=md.mesh.long - y=md.mesh.lat - else: - x=md.mesh.x - y=md.mesh.y +def processmesh(md, data, options): + """ + PROCESSMESH - process the mesh for plotting - #is it a 2D plot? - if md.mesh.dimension()==2 or options.getfieldvalue('layer',0)>=1: - is2d=1 - else: - is2d=0 - - #units - if options.exist('unit'): - unit=options.getfieldvalue('unit') - x=x*unit - y=y*unit - z=z*unit + Usage: + x, y, z, elements, is2d = processmech(md, data, options) - #is model a member of planet class? (workaround until planet class defined) - if md.__class__.__name__!='model': - isplanet=1 - else: - isplanet=0 + See also: PLOTMODEL, PROCESSDATA + """ - return x,y,z,elements,is2d,isplanet + # {{{ check mesh size parameters + if md.mesh.numberofvertices == 0: + raise ValueError('processmesh error: mesh is empty') + if md.mesh.numberofvertices == md.mesh.numberofelements: + raise ValueError('processmesh error: the number of elements is the same as the number of nodes') + # }}} + # {{{ treating coordinates + + try: + z = md.mesh.z + except AttributeError: + z = np.zeros(np.shape(md.mesh.x)) + elements = md.mesh.elements - 1 + + if options.getfieldvalue('layer', 0) >= 1: + x = md.mesh.x2d + y = md.mesh.y2d + z = np.zeros(np.shape(x)) + elements = md.mesh.elements2d - 1 + elif 'latlon' in options.getfieldvalue('coord', 'xy'): + x = md.mesh.long + y = md.mesh.lat + else: + x = md.mesh.x + y = md.mesh.y + + #is it a 2D plot? + if md.mesh.dimension() == 2 or options.getfieldvalue('layer', 0) >= 1: + is2d = 1 + else: + is2d = 0 + + #units + if options.exist('unit'): + unit = options.getfieldvalue('unit') + x = x * unit + y = y * unit + z = z * unit + + #is model a member of planet class? (workaround until planet class defined) + if md.__class__.__name__ != 'model': + isplanet = 1 + else: + isplanet = 0 + + return x, y, z, elements, is2d, isplanet Index: /issm/trunk-jpl/src/m/plot/writejsfield.py =================================================================== --- /issm/trunk-jpl/src/m/plot/writejsfield.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/writejsfield.py (revision 24213) @@ -1,26 +1,28 @@ import numpy as np -def writejsfield(fid,name,variable,nods): -#WRITEJSFIELD - write variable to javascript file -# -# Usage: -# writejsfield(fid,name,variable) -# - #write array: - #if not isinstance(variable, list): - if type(variable[0])==np.float64: - fid.write('\n'.format(name)) - fid.write('{0}=['.format(name)) - for i in range(0, nods-1): - fid.write('{0},'.format(variable[i])) - fid.write('{0}];\n'.format(variable[-1])) - fid.write('\n') - else: - #multi-sized array: - fid.write('\n'.format(name)) - fid.write('{0}=[]\n'.format(name)) - for i in range(0, len(variable[2])): - fid.write('{0}["{1}"]=['.format(name,i)) - for j in range(1, nods-1): - fid.write('{0},'.format(variable[j][i])) - fid.write('{0}];\n'.format(variable[-1][i])) - fid.write('\n') + + +def writejsfield(fid, name, variable, nods): + #WRITEJSFIELD - write variable to javascript file + # + # Usage: + # writejsfield(fid, name, variable) + # + #write array: + #if not isinstance(variable, list): + if type(variable[0]) == np.float64: + fid.write('\n'.format(name)) + fid.write('{0}=['.format(name)) + for i in range(0, nods - 1): + fid.write('{0}, '.format(variable[i])) + fid.write('{0}];\n'.format(variable[-1])) + fid.write('\n') + else: + #multi - sized array: + fid.write('\n'.format(name)) + fid.write('{0} = []\n'.format(name)) + for i in range(0, len(variable[2])): + fid.write('{0}["{1}"] = ['.format(name, i)) + for j in range(1, nods - 1): + fid.write('{0}, '.format(variable[j][i])) + fid.write('{0}];\n'.format(variable[-1][i])) + fid.write('\n') Index: /issm/trunk-jpl/src/m/plot/writejsfile.py =================================================================== --- /issm/trunk-jpl/src/m/plot/writejsfile.py (revision 24212) +++ /issm/trunk-jpl/src/m/plot/writejsfile.py (revision 24213) @@ -1,57 +1,59 @@ import numpy as np from writejsfield import writejsfield -def writejsfile(filename,model,keyname): -#WRITEJSFILE - write model file to javascript database -# -# Usage: -# writejsfile(filename,model,keyname) -# - nods=len(model.x) - nel=len(model.index) - nx=len(model.contourx1) - print(filename) - fid=open(filename,'w', 0) - fid.write('model = {};\n') - fid.write('model["title"]="{0}";\n'.format(model.title)) - fid.write('model["initialZoomFactor"]={0};\n'.format(model.initialZoomFactor)) - #write index: - fid.write('\n') - fid.write('model["index"]=[') - for i in range(0, nel-1): - fid.write('[{0}, {1}, {2}],'.format(model.index[i][0],model.index[i][1],model.index[i][2])) - fid.write('[{0}, {1}, {2}]];\n'.format(model.index[-1][0],model.index[-1][1],model.index[-1][2])) - fid.write('\n') - print('writing model coordinates') - writejsfield(fid,'model["x"]',model.x,nods) - writejsfield(fid,'model["y"]',model.y,nods) - writejsfield(fid,'model["z"]',model.z,nods) - writejsfield(fid,'model["surface"]',model.surface,nods) - writejsfield(fid,'model["contourx1"]',model.contourx1,nx) - writejsfield(fid,'model["contoury1"]',model.contoury1,nx) - writejsfield(fid,'model["contourz1"]',model.contourz1,nx) - writejsfield(fid,'model["contourx2"]',model.contourx2,nx) - writejsfield(fid,'model["contoury2"]',model.contoury2,nx) - writejsfield(fid,'model["contourz2"]',model.contourz2,nx) +def writejsfile(filename, model, keyname): + #WRITEJSFILE - write model file to javascript database + # + # Usage: + # writejsfile(filename, model, keyname) + # - print('writing results') - results=model.results - fid.write('results={};\n') + nods = len(model.x) + nel = len(model.index) + nx = len(model.contourx1) + print(filename) + fid = open(filename, 'w', 0) - for i in range(0,len(results)): - fid.write('result={};\n') - writejsfield(fid,'result["data"]',results[i].data,nods) - fid.write('\n') - fid.write('result["caxis"]=[{0},{1}];\n'.format(results[i].caxis[0],results[i].caxis[1])) - fid.write('result["label"]="{0}";\n'.format(results[i].label)) - fid.write('result["shortlabel"]="{0}";\n'.format(results[i].shortlabel)) - fid.write('result["unit"]="{0}";\n'.format(results[i].unit)) - if type(results[i].data)==np.float64: - fid.write('result["time_range"]=[{0},{1}];\n'.format(results[i].time_range[0],results[i].time_range[1])) - fid.write('results["{0}"]=result;\n'.format(i)) - fid.write('\n') - fid.write('model.results=results;\n') - fid.write('models["{0}"]=model;\n'.format(keyname)) + fid.write('model = {};\n') + fid.write('model["title"] = "{0}";\n'.format(model.title)) + fid.write('model["initialZoomFactor"]={0};\n'.format(model.initialZoomFactor)) + #write index: + fid.write(' < ! - - model["index"]{{{ - - > \n') + fid.write('model["index"] = [') + for i in range(0, nel - 1): + fid.write('[{0}, {1}, {2}], '.format(model.index[i][0], model.index[i][1], model.index[i][2])) + fid.write('[{0}, {1}, {2}]];\n'.format(model.index[-1][0], model.index[-1][1], model.index[-1][2])) + fid.write(' < ! - - }}} - - > \n') + print('writing model coordinates') + writejsfield(fid, 'model["x"]', model.x, nods) + writejsfield(fid, 'model["y"]', model.y, nods) + writejsfield(fid, 'model["z"]', model.z, nods) + writejsfield(fid, 'model["surface"]', model.surface, nods) + writejsfield(fid, 'model["contourx1"]', model.contourx1, nx) + writejsfield(fid, 'model["contoury1"]', model.contoury1, nx) + writejsfield(fid, 'model["contourz1"]', model.contourz1, nx) + writejsfield(fid, 'model["contourx2"]', model.contourx2, nx) + writejsfield(fid, 'model["contoury2"]', model.contoury2, nx) + writejsfield(fid, 'model["contourz2"]', model.contourz2, nx) - fid.close() + print('writing results') + results = model.results + fid.write('results={};\n') + + for i in range(0, len(results)): + fid.write('result={};\n') + writejsfield(fid, 'result["data"]', results[i].data, nods) + fid.write(' < ! - - {{{ - - > \n') + fid.write('result["caxis"] = [{0}, {1}];\n'.format(results[i].caxis[0], results[i].caxis[1])) + fid.write('result["label"] = "{0}";\n'.format(results[i].label)) + fid.write('result["shortlabel"] = "{0}";\n'.format(results[i].shortlabel)) + fid.write('result["unit"] = "{0}";\n'.format(results[i].unit)) + if type(results[i].data) == np.float64: + fid.write('result["time_range"] = [{0}, {1}];\n'.format(results[i].time_range[0], results[i].time_range[1])) + fid.write('results["{0}"] = result;\n'.format(i)) + fid.write(' < ! - - }}} - - > \n') + fid.write('model.results = results;\n') + fid.write('models["{0}"] = model;\n'.format(keyname)) + + fid.close() Index: /issm/trunk-jpl/src/m/qmu/dakota_in_data.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/dakota_in_data.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/dakota_in_data.py (revision 24213) @@ -6,9 +6,10 @@ from MatlabFuncs import * -def dakota_in_data(dmeth,variables,responses,dparams,filei,*args): - ''' + +def dakota_in_data(dmeth, variables, responses, dparams, filei, *args): + ''' define the data to write the dakota .in and .m files. - []=dakota_in_data(dmeth,variables,responses,dparams,filei,*args) + [] = dakota_in_data(dmeth, variables, responses, dparams, filei, *args) where the required input is: @@ -16,5 +17,5 @@ variables (structure array, variable class objects) responses (structure array, response class objects) - dparams (structure array, method-independent parameters) + dparams (structure array, method - independent parameters) filei (character, name of .in and .m files) @@ -29,5 +30,5 @@ it collects the parameters and applies some defaults that are unique to the environment. second, some analysis package - variables and/or responses may be treated differently by + variables and / or responses may be treated differently by dakota. for example, an analysis package variable may be defined as an array, so the QmuSetupDesign brancher will @@ -42,47 +43,46 @@ ''' - ## parameters - # get default set of parameters - params=dakota_in_params(struct()) - # merge specified parameters into default set, whether or not - # they already exist - fnames=fieldnames(dparams) + # parameters + # get default set of parameters + params = dakota_in_params(struct()) + # merge specified parameters into default set, whether or not + # they already exist + fnames = fieldnames(dparams) - for fieldname in fnames: - if not isfield(params,fieldname): - print('WARNING: dakota_in_data:unknown_param: No parameter {} in default parameter set.'.format(str(fieldname))) - exec('params.{} = vars(dparams)[fieldname]'.format(fieldname)) + for fieldname in fnames: + if not isfield(params, fieldname): + print('WARNING: dakota_in_data:unknown_param: No parameter {} in default parameter set.'.format(str(fieldname))) + exec('params.{} = vars(dparams)[fieldname]'.format(fieldname)) - # use matlab even though we are running python - if params.direct and params.analysis_driver == '': - params.analysis_driver='matlab' + # use matlab even though we are running python + if params.direct and params.analysis_driver == '': + params.analysis_driver = 'matlab' - if strcmpi(params.analysis_driver,'matlab') and params.analysis_components == '': - [pathstr,name,ext] = fileparts(filei) - params.analysis_components=fullfile(pathstr,name+'.py') + if strcmpi(params.analysis_driver, 'matlab') and params.analysis_components == '': + [pathstr, name, ext] = fileparts(filei) + params.analysis_components = fullfile(pathstr, name + '.py') - # merge method parameters, though they shouldn't be in dparams - # dmeth=dmeth_params_merge(dmeth,dparams) + # merge method parameters, though they shouldn't be in dparams + # dmeth = dmeth_params_merge(dmeth, dparams) - ## variables - fnames=fieldnames(variables) + # variables + fnames = fieldnames(variables) - # works like matlab arbitrary structs/classes, remembers order of input attributes - dvar = OrderedStruct() - dresp = OrderedStruct() + # works like matlab arbitrary structs / classes, remembers order of input attributes + dvar = OrderedStruct() + dresp = OrderedStruct() - for i in range(len(fnames)): - # currently all variable types can just be copied - exec(('dvar.%s = vars(variables)[fnames[i]]')%(fnames[i])) + for i in range(len(fnames)): + # currently all variable types can just be copied + exec(('dvar.%s = vars(variables)[fnames[i]]') % (fnames[i])) - ## responses - fnames=fieldnames(responses) + # responses + fnames = fieldnames(responses) - for i in range(len(fnames)): - # currently all response types can just be copied - exec(('dresp.%s = vars(responses)[fnames[i]]')%(fnames[i])) + for i in range(len(fnames)): + # currently all response types can just be copied + exec(('dresp.%s = vars(responses)[fnames[i]]') % (fnames[i])) - - ## write files - #Write in file - dakota_in_write(dmeth,dvar,dresp,params,filei,*args) + # write files + #Write in file + dakota_in_write(dmeth, dvar, dresp, params, filei, *args) Index: /issm/trunk-jpl/src/m/qmu/dakota_in_params.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/dakota_in_params.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/dakota_in_params.py (revision 24213) @@ -1,19 +1,19 @@ from dakota_in_data import * - #move this later: from helpers import * + def dakota_in_params(params): - ''' + ''' populate a Dakota parameter structure. - params=dakota_in_params(params) + params = dakota_in_params(params) where the optional input is: - params (structure array, method-independent parameters) + params (structure array, method - independent parameters) and the output is the same. - this function takes a structure of method-independent dakota + this function takes a structure of method - independent dakota parameters, which may be empty, and adds default parameters for those parameters which do not exist. @@ -25,159 +25,159 @@ or absence. - note that the method-dependent parameters are contained in + note that the method - dependent parameters are contained in the dakota_method class object. ''' - if params == None: - help(dakota_in_params) - return + if params is None: + help(dakota_in_params) + return - ## process the input parameters - if len(fieldnames(params)) == 0: - params=struct() + # process the input parameters + if len(fieldnames(params)) == 0: + params = struct() - ## strategy section - if not isfield(params,'graphics'): - params.graphics=False + # strategy section + if not isfield(params, 'graphics'): + params.graphics = False - if not isfield(params,'tabular_graphics_data'): - params.tabular_graphics_data=False + if not isfield(params, 'tabular_graphics_data'): + params.tabular_graphics_data = False - # could use unique file name rather than 'dakota_tabular.dat' - if not isfield(params,'tabular_graphics_file'): - params.tabular_graphics_file=False + # could use unique file name rather than 'dakota_tabular.dat' + if not isfield(params, 'tabular_graphics_file'): + params.tabular_graphics_file = False - ## method section - # nearly all method parameters are in the dakota_method class - # or result from the response level lists - if not isfield(params,'compute'): - params.compute='probabilities' + # method section + # nearly all method parameters are in the dakota_method class + # or result from the response level lists + if not isfield(params, 'compute'): + params.compute = 'probabilities' - if not isfield(params,'distribution'): - params.distribution='cumulative' + if not isfield(params, 'distribution'): + params.distribution = 'cumulative' - ## model section + # model section - ## interface section - if not isfield(params,'system'): - params.system=False + # interface section + if not isfield(params, 'system'): + params.system = False - if not isfield(params,'fork'): - params.fork=False + if not isfield(params, 'fork'): + params.fork = False - if not isfield(params,'direct'): - params.direct=False + if not isfield(params, 'direct'): + params.direct = False - # interface parallelism controls - if not isfield(params,'asynchronous'): - params.asynchronous=True + # interface parallelism controls + if not isfield(params, 'asynchronous'): + params.asynchronous = True - if not isfield(params,'evaluation_concurrency'): - params.evaluation_concurrency=False + if not isfield(params, 'evaluation_concurrency'): + params.evaluation_concurrency = False - if not isfield(params,'analysis_concurrency'): - params.analysis_concurrency=False + if not isfield(params, 'analysis_concurrency'): + params.analysis_concurrency = False - if not isfield(params,'evaluation_servers'): - params.evaluation_servers=False + if not isfield(params, 'evaluation_servers'): + params.evaluation_servers = False - if not isfield(params,'evaluation_self_scheduling'): - params.evaluation_self_scheduling=False + if not isfield(params, 'evaluation_self_scheduling'): + params.evaluation_self_scheduling = False - if not isfield(params,'evaluation_static_scheduling'): - params.evaluation_static_scheduling=True + if not isfield(params, 'evaluation_static_scheduling'): + params.evaluation_static_scheduling = True - if not isfield(params,'evaluation_scheduling'): - params.evaluation_scheduling=False + if not isfield(params, 'evaluation_scheduling'): + params.evaluation_scheduling = False - if not isfield(params,'processors_per_evaluation'): - params.processors_per_evaluation=False + if not isfield(params, 'processors_per_evaluation'): + params.processors_per_evaluation = False - if not isfield(params,'analysis_servers'): - params.analysis_servers=False + if not isfield(params, 'analysis_servers'): + params.analysis_servers = False - if not isfield(params,'analysis_self_scheduling'): - params.analysis_self_scheduling=False + if not isfield(params, 'analysis_self_scheduling'): + params.analysis_self_scheduling = False - if not isfield(params,'analysis_static_scheduling'): - params.analysis_static_scheduling=False + if not isfield(params, 'analysis_static_scheduling'): + params.analysis_static_scheduling = False - # algebraic mappings - if not isfield(params,'algebraic_mappings'): - params.algebraic_mappings=False + # algebraic mappings + if not isfield(params, 'algebraic_mappings'): + params.algebraic_mappings = False - # simulation interface controls - if not isfield(params,'analysis_driver'): - params.analysis_driver='' + # simulation interface controls + if not isfield(params, 'analysis_driver'): + params.analysis_driver = '' - if not isfield(params,'analysis_components'): - params.analysis_components='' + if not isfield(params, 'analysis_components'): + params.analysis_components = '' - if not isfield(params,'input_filter'): - params.input_filter='' + if not isfield(params, 'input_filter'): + params.input_filter = '' - if not isfield(params,'output_filter'): - params.output_filter='' + if not isfield(params, 'output_filter'): + params.output_filter = '' - if not isfield(params,'failure_capture'): - params.failure_capture='abort' + if not isfield(params, 'failure_capture'): + params.failure_capture = 'abort' - if not isfield(params,'deactivate'): - params.deactivate='evaluation_cache restart_file' + if not isfield(params, 'deactivate'): + params.deactivate = 'evaluation_cache restart_file' - # system call or fork interface - if not isfield(params,'parameters_file'): - params.parameters_file='params.in' + # system call or fork interface + if not isfield(params, 'parameters_file'): + params.parameters_file = 'params.in' - if not isfield(params,'results_file'): - params.results_file='results.out' + if not isfield(params, 'results_file'): + params.results_file = 'results.out' - if not isfield(params,'verbatim'): - params.verbatim=False + if not isfield(params, 'verbatim'): + params.verbatim = False - if not isfield(params,'aprepro'): - params.aprepro=False + if not isfield(params, 'aprepro'): + params.aprepro = False - if not isfield(params,'file_tag'): - params.file_tag=True + if not isfield(params, 'file_tag'): + params.file_tag = True - if not isfield(params,'file_save'): - params.file_save=True + if not isfield(params, 'file_save'): + params.file_save = True - # direct function interface - if not isfield(params,'processors_per_analysis'): - params.processors_per_analysis=False + # direct function interface + if not isfield(params, 'processors_per_analysis'): + params.processors_per_analysis = False - ## responses section - if not isfield(params,'numerical_gradients'): - params.numerical_gradients=False + # responses section + if not isfield(params, 'numerical_gradients'): + params.numerical_gradients = False - if not isfield(params,'method_source'): - params.method_source='dakota' + if not isfield(params, 'method_source'): + params.method_source = 'dakota' - if not isfield(params,'interval_type'): - params.interval_type='forward' + if not isfield(params, 'interval_type'): + params.interval_type = 'forward' - if not isfield(params,'fd_gradient_step_size'): - params.fd_gradient_step_size=0.001 + if not isfield(params, 'fd_gradient_step_size'): + params.fd_gradient_step_size = 0.001 - if not isfield(params,'analytic_gradients'): - params.analytic_gradients=False + if not isfield(params, 'analytic_gradients'): + params.analytic_gradients = False - # mixed_gradients not fully implemented - if not isfield(params,'mixed_gradients'): - params.mixed_gradients=False + # mixed_gradients not fully implemented + if not isfield(params, 'mixed_gradients'): + params.mixed_gradients = False - if not isfield(params,'id_analytic_gradients'): - params.id_analytic_gradients=False + if not isfield(params, 'id_analytic_gradients'): + params.id_analytic_gradients = False - if not isfield(params,'id_numerical_gradients'): - params.id_numerical_gradients=False + if not isfield(params, 'id_numerical_gradients'): + params.id_numerical_gradients = False - # hessians not fully implemented - if not isfield(params,'numerical_hessians'): - params.numerical_hessians=True + # hessians not fully implemented + if not isfield(params, 'numerical_hessians'): + params.numerical_hessians = True - if not isfield(params,'hessian_gradient_step_size'): - params.hessian_gradient_step_size=0.001 + if not isfield(params, 'hessian_gradient_step_size'): + params.hessian_gradient_step_size = 0.001 - return params + return params Index: /issm/trunk-jpl/src/m/qmu/dakota_in_write.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/dakota_in_write.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/dakota_in_write.py (revision 24213) @@ -11,10 +11,11 @@ import itertools -def dakota_in_write(method,dvar,dresp,params,filei,*args): - ''' + +def dakota_in_write(method, dvar, dresp, params, filei, *args): + ''' write a Dakota .in input file. - []=dakota_in_write(method,dvar,dresp,params,filei,args) - []=dakota_in_write(dmeth ,dvar,dresp,params,filei,args) + [] = dakota_in_write(method, dvar, dresp, params, filei, args) + [] = dakota_in_write(dmeth , dvar, dresp, params, filei, args) where the required input is: @@ -23,5 +24,5 @@ dvar (structure array, variable class objects) dresp (structure array, response class objects) - params (structure array, method-indepent parameters) + params (structure array, method - indepent parameters) filei (character, name of .in file) @@ -41,289 +42,277 @@ ''' - # process the input parameters - if len(fieldnames(method)) == 0: - method=str(eval(input('Method? '))) - - if type(method) == str: - dmeth=dakota_method(method) - elif isinstance(method,dakota_method): - dmeth=method - else: - raise RuntimeError('Method '+str(method)+' is unrecognized class '+str(type(method))+'. (should be either "str" or "dakota_method")') - - if len(filei) == 0: - filei=str(eval(input('Dakota input file to write? '))) - - [pathstr,name,ext] = fileparts(filei) - if len(ext) == 0: - # fileparts only considers '.in' to be the extension, not '.qmu.in' - ext='.qmu.in' - - filei2=fullfile(pathstr,name+ext) - - print('Opening Dakota input file \''+filei2 + '\'.') - try: - with open(filei2,'w+') as fidi: - - if len(fieldnames(params)) == 0: - params=struct() - - params=dakota_in_params(params) - - # write the strategy section - if float(IssmConfig('_DAKOTA_VERSION_')[0]) < 6: - strategy_write(fidi,params) - else: - environment_write(fidi,params) - - # write the method section - method_write(fidi,dmeth,dresp,params) - - # write the model section - model_write(fidi) - - # write the variables section - variables_write(fidi,dmeth,dvar) - - # write the interface section - interface_write(fidi,params) - - # write the responses section - responses_write(fidi,dmeth,dresp,params) - - except IOError: - print(filei2 + ' could not be opened.') - - print('End of file successfully written.') - - -## function to write the strategy section of the file - -def strategy_write(fidi,params): - - print('Writing strategy section of Dakota input file.') - - fidi.write('strategy,\n') - fidi.write('\tsingle_method\n\n') - param_write(fidi,'\t ','graphics','','\n',params) - param_write(fidi,'\t ','tabular_graphics_data','','\n',params) - param_write(fidi,'\t ','tabular_graphics_file',' ','\n',params) - fidi.write('\n') - - -## function to write the environment section of the file - -def environment_write(fidi,params): - - print('Writing environment section of Dakota input file.') - - fidi.write('environment,\n') - param_write(fidi,'\t ','graphics','','\n',params) - param_write(fidi,'\t ','tabular_graphics_data','','\n',params) - param_write(fidi,'\t ','tabular_graphics_file',' ','\n',params) - fidi.write('\n') - - -## function to write the method section of the file - -def method_write(fidi,dmeth,dresp,params): - - print('Writing method section of Dakota input file.') - - fidi.write('method,\n') - fidi.write('\t'+str(dmeth.method)+'\n') - - dmeth_params_write(dmeth,fidi) - - # write response levels - - if strcmp(dmeth.type,'nond'): - for i in range(len(dmeth.responses)): - str_name = dmeth.responses[i] - resp = eval("{}.{}()".format(str_name,str_name)) - resp.dakota_rlev_write(fidi,dresp,params) - - fidi.write('\n') - - -## function to write the model section of the file - + # process the input parameters + if len(fieldnames(method)) == 0: + method = str(eval(input('Method? '))) + + if type(method) == str: + dmeth = dakota_method(method) + elif isinstance(method, dakota_method): + dmeth = method + else: + raise RuntimeError('Method ' + str(method) + ' is unrecognized class ' + str(type(method)) + '. (should be either "str" or "dakota_method")') + + if len(filei) == 0: + filei = str(eval(input('Dakota input file to write? '))) + + [pathstr, name, ext] = fileparts(filei) + if len(ext) == 0: + # fileparts only considers '.in' to be the extension, not '.qmu.in' + ext = '.qmu.in' + + filei2 = fullfile(pathstr, name + ext) + + print('Opening Dakota input file \'' + filei2 + '\'.') + try: + with open(filei2, 'w+') as fidi: + + if len(fieldnames(params)) == 0: + params = struct() + + params = dakota_in_params(params) + + # write the strategy section + if float(IssmConfig('_DAKOTA_VERSION_')[0]) < 6: + strategy_write(fidi, params) + else: + environment_write(fidi, params) + + # write the method section + method_write(fidi, dmeth, dresp, params) + # write the model section + model_write(fidi) + # write the variables section + variables_write(fidi, dmeth, dvar) + # write the interface section + interface_write(fidi, params) + # write the responses section + responses_write(fidi, dmeth, dresp, params) + + except IOError: + print(filei2 + ' could not be opened.') + + print('End of file successfully written.') + + +# function to write the strategy section of the file +def strategy_write(fidi, params): + + print('Writing strategy section of Dakota input file.') + + fidi.write('strategy, \n') + fidi.write('\tsingle_method\n\n') + param_write(fidi, '\t ', 'graphics', '', '\n', params) + param_write(fidi, '\t ', 'tabular_graphics_data', '', '\n', params) + param_write(fidi, '\t ', 'tabular_graphics_file', ' ', '\n', params) + fidi.write('\n') + + +# function to write the environment section of the file +def environment_write(fidi, params): + + print('Writing environment section of Dakota input file.') + + fidi.write('environment, \n') + param_write(fidi, '\t ', 'graphics', '', '\n', params) + param_write(fidi, '\t ', 'tabular_graphics_data', '', '\n', params) + param_write(fidi, '\t ', 'tabular_graphics_file', ' ', '\n', params) + fidi.write('\n') + + +# function to write the method section of the file +def method_write(fidi, dmeth, dresp, params): + + print('Writing method section of Dakota input file.') + + fidi.write('method, \n') + fidi.write('\t' + str(dmeth.method) + '\n') + + dmeth_params_write(dmeth, fidi) + + # write response levels + + if strcmp(dmeth.type, 'nond'): + for i in range(len(dmeth.responses)): + str_name = dmeth.responses[i] + resp = eval("{}.{}()".format(str_name, str_name)) + resp.dakota_rlev_write(fidi, dresp, params) + + fidi.write('\n') + + +# function to write the model section of the file def model_write(fidi): - print('Writing model section of Dakota input file.') - - fidi.write('model,\n') - fidi.write('\tsingle\n\n') - - -## function to write the variables section of the file - -def variables_write(fidi,dmeth,dvar): - - print('Writing variables section of Dakota input file.') - - fidi.write('variables,\n') - - # variables vary by method - fd = fieldnames(dvar) - types = [] - var = [] - for i in range(len(fd)): - i_type = eval('dvar.{}[0].__class__.__name__'.format(fd[i])) - j = dmeth.variables.index(i_type) - str_name = dmeth.variables[j] - - # organize so that multiple instances of the same qmu class - # (2 different variable instances of "normal_uncertain" for example) - # are in the same dakota_write call regardless of individual size; - # but that each class has its own dakota_write call - if str_name not in types: - types.append(str_name) - var.append(eval('dvar.{}'.format(fd[i]))) - else: - t = types.index(str_name) - var[t].extend(eval('dvar.{}'.format(fd[i]))) - - for t in range(len(types)): - v = eval('{}.{}()'.format(types[t],types[t])) - v.dakota_write(fidi,var[t]) - - # linear constraints vary by method - fc = dmeth.lcspec - - for i in range(len(dmeth.lcspec)): - str_name = dmeth.lcspec[i] - var = eval('{}.{}()'.format(str_name,str_name)) - # check that str_name is correct against matlab version which has no argument there - var.dakota_write(fidi,eval('dvar.{}[i]'.format(j)),str_name) - - fidi.write('\n') - - -## function to write the interface section of the file - -def interface_write(fidi,params): - - print('Writing interface section of Dakota input file.') - - fidi.write('interface,\n') - - if (not params.system) and (not params.fork) and (not params.direct): - params.fork=True - elif params.system+params.fork+params.direct > 1: - raise RuntimeError('Too many interfaces selected.') - if params.system or params.fork: - param_write(fidi,'\t','asynchronous','','\n',params) - param_write(fidi,'\t ','evaluation_concurrency',' = ','\n',params) - param_write(fidi,'\t ','analysis_concurrency',' = ','\n',params) - param_write(fidi,'\t ','evaluation_servers',' = ','\n',params) - param_write(fidi,'\t ','evaluation_self_scheduling','','\n',params) - param_write(fidi,'\t ','evaluation_static_scheduling','','\n',params) - param_write(fidi,'\t ','analysis_servers',' = ','\n',params) - param_write(fidi,'\t ','analysis_self_scheduling','','\n',params) - param_write(fidi,'\t ','analysis_static_scheduling','','\n',params) - param_write(fidi,'\t','algebraic_mappings',' = ','\n',params) - param_write(fidi,'\t','system','','\n',params) - param_write(fidi,'\t','fork','','\n',params) - param_write(fidi,'\t ','analysis_driver',' = \'','\'\n',params) - if len(params.input_filter) != 0: - param_write(fidi,'\t ','input_filter',' = ','\n',params) - - if len(params.output_filter) != 0: - param_write(fidi,'\t ','output_filter',' = ','\n',params) - - param_write(fidi,'\t ','failure_capture',' ','\n',params) - param_write(fidi,'\t ','deactivate',' ','\n',params) - param_write(fidi,'\t ','parameters_file',' = \'','\'\n',params) - param_write(fidi,'\t ','results_file',' = \'','\'\n',params) - param_write(fidi,'\t ','verbatim', '','\n',params) - param_write(fidi,'\t ','aprepro', '','\n',params) - param_write(fidi,'\t ','file_tag', '','\n',params) - param_write(fidi,'\t ','file_save','','\n',params) - elif params.direct: - # Error: asynchronous capability not yet supported in direct interfaces. - # Update: it is now possible to run in parallel in direct interfaces. - param_write(fidi,'\t','algebraic_mappings',' = ','\n',params) - param_write(fidi,'\t','direct','','\n',params) - param_write(fidi,'\t ','analysis_driver',' = \'','\'\n',params) - if float(IssmConfig('_DAKOTA_VERSION_')[0]) < 6: - param_write(fidi,'\t ','evaluation_static_scheduling','','\n',params) - else: - param_write(fidi,'\t ','evaluation_scheduling',' ','\n',params) - param_write(fidi,'\t ','processors_per_evaluation',' = ','\n',params) - if len(params.analysis_components) != 0: - [pathstr,name,ext] = fileparts(params.analysis_components) - if ext != '': - ext='.py' - - params.analysis_components=fullfile(pathstr,name+ext) - param_write(fidi,'\t ','analysis_components',' = \'','\'\n',params) - - if len(params.input_filter) != 0: - param_write(fidi,'\t ','input_filter',' = ','\n',params) - - if len(params.output_filter) != 0: - param_write(fidi,'\t ','output_filter',' = ','\n',params) - - param_write(fidi,'\t ','failure_capture',' ','\n',params) - param_write(fidi,'\t ','deactivate',' ','\n',params) - param_write(fidi,'\t ','processors_per_analysis',' = ','\n',params) - - fidi.write('\n') - - -## function to write the responses section of the file - -def responses_write(fidi,dmeth,dresp,params): - - print('Writing responses section of Dakota input file.') - - fidi.write('responses,\n') - #fidi.write('calibration_terms = 1 \n') - - # functions, gradients, and hessians vary by method - - rdesc=[] - - for i in range(len(dmeth.responses)): - resp = eval(dmeth.responses[i]) - rdesc = resp.dakota_write(fidi,dresp,rdesc) - - # write accumulated response descriptors for all response classes - - if len(rdesc) != 0: - fidi.write('\tresponse_descriptors =\n') - vector_write(fidi,'\t ',rdesc,6,76) - - ghspec_write(fidi,params,dmeth.ghspec) - - fidi.write('\n') - - -## function to write gradient and hessian specifications - -def ghspec_write(fidi,params,ghspec): - - # gradients - if 'grad' in ghspec: - if (not params.numerical_gradients) and (not params.analytic_gradients): - params.numerical_gradients=True - elif (params.numerical_gradients+params.analytic_gradients > 1): - raise RuntimeError('Too many gradients selected.') - - if params.numerical_gradients: - param_write(fidi,'\t','numerical_gradients','','\n',params) - param_write(fidi,'\t ','method_source',' ','\n',params) - param_write(fidi,'\t ','interval_type',' ','\n',params) - param_write(fidi,'\t ','fd_gradient_step_size',' = ','\n',params) - elif params.analytic_gradients: - param_write(fidi,'\t','analytic_gradients','','\n',params) - # elif params.mixed_gradients - else: - fidi.write('\tno_gradients\n') - - # hessians (no implemented methods use them yet) - if 'hess' in ghspec: - raise RuntimeError('Hessians needed by method but not provided.') - else: - fidi.write('\tno_hessians\n') + print('Writing model section of Dakota input file.') + + fidi.write('model, \n') + fidi.write('\tsingle\n\n') + + +# function to write the variables section of the file +def variables_write(fidi, dmeth, dvar): + + print('Writing variables section of Dakota input file.') + + fidi.write('variables, \n') + + # variables vary by method + fd = fieldnames(dvar) + types = [] + var = [] + for i in range(len(fd)): + i_type = eval('dvar.{}[0].__class__.__name__'.format(fd[i])) + j = dmeth.variables.index(i_type) + str_name = dmeth.variables[j] + + # organize so that multiple instances of the same qmu class + # (2 different variable instances of "normal_uncertain" for example) + # are in the same dakota_write call regardless of individual size + # but that each class has its own dakota_write call + if str_name not in types: + types.append(str_name) + var.append(eval('dvar.{}'.format(fd[i]))) + else: + t = types.index(str_name) + var[t].extend(eval('dvar.{}'.format(fd[i]))) + + for t in range(len(types)): + v = eval('{}.{}()'.format(types[t], types[t])) + v.dakota_write(fidi, var[t]) + + # linear constraints vary by method + fc = dmeth.lcspec + + for i in range(len(dmeth.lcspec)): + str_name = dmeth.lcspec[i] + var = eval('{}.{}()'.format(str_name, str_name)) + # check that str_name is correct against matlab version which has no argument there + var.dakota_write(fidi, eval('dvar.{}[i]'.format(j)), str_name) + + fidi.write('\n') + + +# function to write the interface section of the file +def interface_write(fidi, params): + + print('Writing interface section of Dakota input file.') + + fidi.write('interface, \n') + + if (not params.system) and (not params.fork) and (not params.direct): + params.fork = True + elif params.system + params.fork + params.direct > 1: + raise RuntimeError('Too many interfaces selected.') + if params.system or params.fork: + param_write(fidi, '\t', 'asynchronous', '', '\n', params) + param_write(fidi, '\t ', 'evaluation_concurrency', '=', '\n', params) + param_write(fidi, '\t ', 'analysis_concurrency', '=', '\n', params) + param_write(fidi, '\t ', 'evaluation_servers', '=', '\n', params) + param_write(fidi, '\t ', 'evaluation_self_scheduling', '', '\n', params) + param_write(fidi, '\t ', 'evaluation_static_scheduling', '', '\n', params) + param_write(fidi, '\t ', 'analysis_servers', '=', '\n', params) + param_write(fidi, '\t ', 'analysis_self_scheduling', '', '\n', params) + param_write(fidi, '\t ', 'analysis_static_scheduling', '', '\n', params) + param_write(fidi, '\t', 'algebraic_mappings', '=', '\n', params) + param_write(fidi, '\t', 'system', '', '\n', params) + param_write(fidi, '\t', 'fork', '', '\n', params) + param_write(fidi, '\t ', 'analysis_driver', ' = \'', '\'\n', params) + if len(params.input_filter) != 0: + param_write(fidi, '\t ', 'input_filter', '=', '\n', params) + + if len(params.output_filter) != 0: + param_write(fidi, '\t ', 'output_filter', '=', '\n', params) + + param_write(fidi, '\t ', 'failure_capture', ' ', '\n', params) + param_write(fidi, '\t ', 'deactivate', ' ', '\n', params) + param_write(fidi, '\t ', 'parameters_file', ' = \'', '\'\n', params) + param_write(fidi, '\t ', 'results_file', ' = \'', '\'\n', params) + param_write(fidi, '\t ', 'verbatim', '', '\n', params) + param_write(fidi, '\t ', 'aprepro', '', '\n', params) + param_write(fidi, '\t ', 'file_tag', '', '\n', params) + param_write(fidi, '\t ', 'file_save', '', '\n', params) + elif params.direct: + # Error: asynchronous capability not yet supported in direct interfaces. + # Update: it is now possible to run in parallel in direct interfaces. + param_write(fidi, '\t', 'algebraic_mappings', '=', '\n', params) + param_write(fidi, '\t', 'direct', '', '\n', params) + param_write(fidi, '\t ', 'analysis_driver', ' = \'', '\'\n', params) + if float(IssmConfig('_DAKOTA_VERSION_')[0]) < 6: + param_write(fidi, '\t ', 'evaluation_static_scheduling', '', '\n', params) + else: + param_write(fidi, '\t ', 'evaluation_scheduling', ' ', '\n', params) + param_write(fidi, '\t ', 'processors_per_evaluation', '=', '\n', params) + if len(params.analysis_components) != 0: + [pathstr, name, ext] = fileparts(params.analysis_components) + if ext != '': + ext = '.py' + + params.analysis_components = fullfile(pathstr, name + ext) + param_write(fidi, '\t ', 'analysis_components', ' = \'', '\'\n', params) + + if len(params.input_filter) != 0: + param_write(fidi, '\t ', 'input_filter', '=', '\n', params) + + if len(params.output_filter) != 0: + param_write(fidi, '\t ', 'output_filter', '=', '\n', params) + + param_write(fidi, '\t ', 'failure_capture', ' ', '\n', params) + param_write(fidi, '\t ', 'deactivate', ' ', '\n', params) + param_write(fidi, '\t ', 'processors_per_analysis', '=', '\n', params) + + fidi.write('\n') + + +# function to write the responses section of the file +def responses_write(fidi, dmeth, dresp, params): + + print('Writing responses section of Dakota input file.') + + fidi.write('responses, \n') + #fidi.write('calibration_terms = 1 \n') + + # functions, gradients, and hessians vary by method + + rdesc = [] + + for i in range(len(dmeth.responses)): + resp = eval(dmeth.responses[i]) + rdesc = resp.dakota_write(fidi, dresp, rdesc) + + # write accumulated response descriptors for all response classes + + if len(rdesc) != 0: + fidi.write('\tresponse_descriptors =\n') + vector_write(fidi, '\t ', rdesc, 6, 76) + + ghspec_write(fidi, params, dmeth.ghspec) + + fidi.write('\n') + + +# function to write gradient and hessian specifications +def ghspec_write(fidi, params, ghspec): + + # gradients + if 'grad' in ghspec: + if (not params.numerical_gradients) and (not params.analytic_gradients): + params.numerical_gradients = True + elif (params.numerical_gradients + params.analytic_gradients > 1): + raise RuntimeError('Too many gradients selected.') + + if params.numerical_gradients: + param_write(fidi, '\t', 'numerical_gradients', '', '\n', params) + param_write(fidi, '\t ', 'method_source', ' ', '\n', params) + param_write(fidi, '\t ', 'interval_type', ' ', '\n', params) + param_write(fidi, '\t ', 'fd_gradient_step_size', '=', '\n', params) + elif params.analytic_gradients: + param_write(fidi, '\t', 'analytic_gradients', '', '\n', params) + # elif params.mixed_gradients + else: + fidi.write('\tno_gradients\n') + + # hessians (no implemented methods use them yet) + if 'hess' in ghspec: + raise RuntimeError('Hessians needed by method but not provided.') + else: + fidi.write('\tno_hessians\n') Index: /issm/trunk-jpl/src/m/qmu/dakota_out_parse.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/dakota_out_parse.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/dakota_out_parse.py (revision 24213) @@ -1,7 +1,5 @@ import numpy as np - -from os.path import isfile,getsize +from os.path import isfile, getsize import re - from MatlabFuncs import * from prctile_issm import * @@ -10,13 +8,14 @@ from helpers import * -#Note: this may be re-written later to take advantage of Python's file i/o mechanics -# as it is written now it is often difficult to work with, but is analagous to -# the Matlab version of dakota_out_parse - -def dakota_out_parse(filei): # [[[ - ''' +#Note: this may be re-written later to take advantage of Python's file i / o mechanics +# as it is written now it is often difficult to work with, but is analagous to +# the Matlab version of dakota_out_parse + + +def dakota_out_parse(filei): # {{{ + ''' read a Dakota .out or .dat output file and parse it. - [method,dresp,scm,pcm,srcm,prcm]=dakota_out_parse(filei) + [method, dresp, scm, pcm, srcm, prcm] = dakota_out_parse(filei) where the required input is: @@ -39,5 +38,5 @@ this function reads a dakota .out output file and parses it - into the matlab workspace. it operates in a content-driven + into the matlab workspace. it operates in a content - driven fashion, where it skips the intermediate data and then parses whatever output data it encounters in the order in which it @@ -47,924 +46,902 @@ this data would typically be used for plotting and other - post-processing within matlab or excel. + post - processing within matlab or excel. ''' - if filei == None: - help(dakota_out_parse) - return - - if not isfile(filei) or getsize(filei) == 0: - filei=str(eval(input('Input file? '))) - - #fidi=fopen(sprintf('%s',filei),'r') - #try: - with open(filei, 'r') as fidi: - ## check the first line for the Dakota tabular output file - method=[] - fline=fidi.readline() - if getsize(filei) == 0 or fline == '': - raise RuntimeError('File '+filei+' is empty.') - - dresp=[] # of struct() - scm =struct() - pcm =struct() - srcm=struct() - prcm=struct() - - if strncmpi(fline,'%eval_id',8): - method='unknown' - dresp=dak_tab_out(fidi,fline) - return [method,dresp,scm,pcm,srcm,prcm] - else: - fidi.seek(0,0) - - ## loop through the file to find the Dakota method name - fline=findline(fidi,'method',True) - if fline == None: - #do nothing - pass - else: - if fline[6] == ',': - fline = fidi.readline() - [ntokens,tokens]=fltokens(fline) - method=tokens[0].strip() - print('Dakota method =\''+method+'\'.') - elif fline[6] in ['N','n']: - fline=findline(fidi,'methodName = '); - [ntokens,tokens]=fltokens(fline) - method=tokens[2].strip() - print('Dakota methodName="'+method+'".') - - ## loop through the file to find the function evaluation summary - counter = 0 - fline='' - nfeval=nfeval_read(fidi,fline) - - ## process each results section based on content of the file - while counter < 10: - # because python makes file i/o difficult - # if we see 10+ blank lines in a row then we have reached EOF - # (tests show actual maximum number of blank lines is around 5) - if counter >= 10: - break - if fline == '' or fline.isspace(): - counter += 1 - else: - counter = 0 - - #print fline - # ipos=ftell(fidi) - fline = fidi.readline() - if fline == '' or fline.isspace(): - pass - elif strncmp(fline,'<<<<< Function evaluation summary',33): - nfeval=nfeval_read(fidi,fline) - elif strncmp(fline,'Statistics based on ',20): - nsamp=nsamp_read(fidi,fline) - elif strncmp(fline,'Moments for each response function',34): - dresp=moments_read(fidi,dresp,fline) - elif strncmp(fline,'Moment-based statistics for each response function',50): - dresp=mbstats_read(fidi,dresp,fline) - elif strncmp(fline,'95% confidence intervals for each response function',51): - dresp=cis_read(fidi,dresp,fline) - elif strncmp(fline,'Probabilities for each response function',40) or strncmp(fline,'Level mappings for each response function',41): - dresp=cdfs_read(fidi,dresp,fline) - elif strncmp(fline,'Probability Density Function (PDF) histograms for each response function',72): - dresp=pdfs_read(fidi,dresp,fline) - elif strncmp(fline,'Simple Correlation Matrix',25): - scm=corrmat_read(fidi,'Simple Correlation Matrix',fline) - elif strncmp(fline,'Partial Correlation Matrix',26): - pcm=corrmat_read(fidi,'Partial Correlation Matrix',fline) - elif strncmp(fline,'Simple Rank Correlation Matrix',30): - srcm=corrmat_read(fidi,'Simple Rank Correlatio:n Matrix',fline) - elif strncmp(fline,'Partial Rank Correlation Matrix',31): - prcm=corrmat_read(fidi,'Partial Rank Correlation Matrix',fline) - elif strncmp(fline,'MV Statistics for ',18): - dresp=mvstats_read(fidi,dresp,fline) - elif strncmp(fline,'<<<<< Best ',11): - dresp=best_read(fidi,dresp,fline) - elif strncmp(fline,'The following lists volumetric uniformity measures',50): - dresp=vum_read(fidi,dresp,fline) - elif strncmp(fline,'<<<<< Iterator ',15) and (len(fline) > 26) and (' completed.' in fline[15:]): - method=itcomp_read(fidi,fline) - elif strncmp(fline,'-----',5): - pass - else: - 'Unexpected line: '+str(fline) - - # fidi.seek(ipos,0) - - ## loop through the file to verify the end - - # fline=findline(fidi,'<<<<< Single Method Strategy completed') - # if not ischar(fline) - # return - # - print('End of file successfully reached.') - #close(fidi) - #except Exception as err: - #print "ERROR in dakota_out_parse: " + err - #raise err - #raise RuntimeError(filei+' could not be opened.') - - return [method,dresp,scm,pcm,srcm,prcm] - # ]]] - -def dak_tab_out(fidi,fline): # [[[ -## function to parse the dakota tabular output file - - print('Reading Dakota tabular output file.') - - # process column headings of matrix (skipping eval_id) - [ntokens,tokens]=fltokens(fline) - - # New file DAKOTA versions>6 - if strncmpi(fline,'%eval_id interface',18): - offset=2 - else: #DAKOTA versions<6 - offset=1 - - desc=[['' for i in range(ntokens-offset)]] - data=np.zeros((1,ntokens-offset)) - - for i in range(ntokens-offset): - desc[0][i]=str(tokens[i+offset]) - - print("Number of columns (Dakota V+R)="+str(ntokens-2)+'.') - - # process rows of matrix - nrow=0 - while True: - - fline=fidi.readline() - - if fline == '' or fline.isspace(): - break - - if nrow > 0: - data = np.concatenate((data,[np.zeros(ntokens-offset)])) - - [ntokens,tokens]=fltokens(fline) - - # add row values to matrix (skipping eval_id) - - for i in range(ntokens-offset): - data[nrow,i] = tokens[i+offset] - - nrow=nrow+1 - - print('Number of rows (Dakota func evals)='+str(nrow)+'.') - - # calculate statistics - - # since normfit doesn't have a dim argument, and matlab isvector is True - # for a 1xn matrix, handle the case of one row explicitly - - # Update: normfit_issm.py does handle this case - if (np.size(data,0) > 1): - #dmean =mean (data) - #dstddev=std (data,0) - [dmean,dstddev,dmeanci,dstddevci]=normfit_issm(data,0.05) - else: - dmean =np.zeros((1,np.size(data,1))) - dstddev =np.zeros((1,np.size(data,1))) - dmeanci =np.zeros((2,np.size(data,1))) - dstddevci=np.zeros((2,np.size(data,1))) - for i in range(np.size(data,1)): - [dmean[0,i],dstddev[0,i],dmeanci[:,i],dstddevci[:,i]]=normfit_issm(data[:,i],0.05) - - dmin =data.min(0) - dquart1=prctile_issm(data,25,0) - dmedian=np.median(data,0) - dquart3=prctile_issm(data,75,0) - dmax =data.max(0) - dmin95 =prctile_issm(data,5,0) - dmax95 =prctile_issm(data,95,0) - - # Note: the following line may cause the following warning - # (should not crash or invalidate results) when one of - # the inputs does not change with respect to the - # other/s causing an internal divide-by-zero error - - #/usr/local/lib/python2.7/dist-packages/numpy/lib/function_base.py:3163: - # RuntimeWarning: invalid value encountered in true_divide - # c /= stddev[:,None] - - # (and/or the same but with "c /= stddev[None, :]") - - dcorrel=np.corrcoef(data.T) - - # divide the data into structures for consistency - dresp = [] - - for i in range(len(desc)): - dresp.append(struct()) - dresp[i].descriptor=str(desc[i]) - dresp[i].sample =data[:,i] - dresp[i].mean =dmean[i] - dresp[i].stddev =dstddev[i] - dresp[i].meanci =dmeanci[:,i] - dresp[i].stddevci =dstddevci[:,i] - dresp[i].min =dmin[i] - dresp[i].quart1 =dquart1[i] - dresp[i].median =dmedian[i] - dresp[i].quart3 =dquart3[i] - dresp[i].max =dmax[i] - dresp[i].dmin95 =dmin95[i] - dresp[i].dmax95 =dmax95[i] - - # draw box plot - - # figure - # subplot(2,1,1) - # plot_boxplot(dresp) - - # draw normal probability plot - - # subplot(2,1,2) - # plot_normplot(dresp) - - return dresp - # ]]] - -def nfeval_read(fidi,fline): # [[[ -## function to find and read the number of function evaluations - - if fline == None or fline == '' or fline.isspace(): - fline=findline(fidi,'<<<<< Function evaluation summary') - nfeval = 0 - return - - [ntokens,tokens]=fltokens(fline) - nfeval=tokens[4] - print(' Dakota function evaluations='+str(int(nfeval))+'.') - - return nfeval - # ]]] - -def nsamp_read(fidi,fline): # [[[ -## function to find and read the number of samples - - if fline == None or fline == '' or fline.isspace(): - fline=findline(fidi,'Statistics based on ') - return - - [ntokens,tokens]=fltokens(fline) - nsamp=tokens[3] - print(' Dakota samples='+str(int(nsamp))+'.') - - return nsamp - # ]]] - -def moments_read(fidi,dresp,fline): # [[[ -## function to find and read the moments - - if fline == None or fline == '' or fline.isspace(): - fline=findline(fidi,'Moments for each response function') - return - - print('Reading moments for response functions:') - - while True: - fline=fidi.readline() - if fline == '' or fline.isspace(): - break - - [ntokens,tokens]=fltokens(fline) - - # add new response function and moments - - dresp.append(struct()) - dresp[-1].descriptor=tokens[ 0] - print(' '+str(dresp[-1].descriptor)) - dresp[-1].mean =tokens[ 3] - dresp[-1].stddev =tokens[ 6] - dresp[-1].coefvar =tokens[12] - - print(' Number of Dakota response functions='+str(len(dresp))+'.') - - return dresp - # ]]] - -def mbstats_read(fidi,dresp,fline): # [[[ -## function to find and read the moment-based statistics - - if fline == None or fline == '' or fline.isspace(): - fline=findline(fidi,'Moment-based statistics for each response function') - return - - print('Reading moment-based statistics for response functions:') - - # skip column headings of moment-based statistics - - fline=fidi.readline() - - while True: - fline=fidi.readline() - if fline == '' or fline.isspace(): - break - - [ntokens,tokens]=fltokens(fline) - - # add new response function and moment-based statistics - - dresp.append(struct()) - dresp[-1].descriptor=tokens[ 0] - print(' '+str(dresp[-1].descriptor)) - dresp[-1].mean =tokens[ 1] - dresp[-1].stddev =tokens[ 2] - dresp[-1].skewness =tokens[ 3] - dresp[-1].kurtosis =tokens[ 4] - - print(' Number of Dakota response functions='+str(len(dresp))+'.') - - return dresp - # ]]] - -def cis_read(fidi,dresp,fline): # [[[ -## function to find and read the confidence intervals - - if fline == None or fline == '' or fline.isspace(): - fline=findline(fidi,'95% confidence intervals for each response function') - return - - print('Reading 95% confidence intervals for response functions:') - - while True: - fline=fidi.readline() - if fline == '' or fline.isspace(): - break - - [ntokens,tokens]=fltokens(fline) - - # check for column headings in Dakota 5.2 - - if (ntokens == 4): - fline=fidi.readline() - if fline == '' or fline.isspace(): - break - - [ntokens,tokens]=fltokens(fline) - - # find response function associated with confidence intervals - - idresp=-1 - for i in range(len(dresp)): - if strcmpi(tokens[0],dresp[i].descriptor): - idresp=i - break - - if idresp < 0: - idresp=len(dresp) - dresp.append(struct()) - dresp[idresp].descriptor=tokens[0] - print(' '+str(dresp[idresp].descriptor)) - - # add confidence intervals to response functions - dresp[i].meanci = np.array([[np.nan],[np.nan]]) - dresp[i].stddevci = np.array([[np.nan],[np.nan]]) - - if (ntokens == 14): - dresp[i].meanci [0,0]=tokens[ 4] - dresp[i].meanci [1,0]=tokens[ 5] - dresp[i].stddevci[0,0]=tokens[11] - dresp[i].stddevci[1,0]=tokens[12] - else: - dresp[i].meanci [0,0]=tokens[ 1] - dresp[i].meanci [1,0]=tokens[ 2] - dresp[i].stddevci[0,0]=tokens[ 3] - dresp[i].stddevci[1,0]=tokens[ 4] - - print(' Number of Dakota response functions='+str(len(dresp))+'.') - - return dresp - # ]]] - -def cdfs_read(fidi,dresp,fline): # [[[ -## function to find and read the cdf's - - if fline == None or fline == '' or fline.isspace(): - fline=findline(fidi,'Probabilities for each response function') - if fline == None: - fline=findline(fidi,'Level mappings for each response function') - if fline == None: - return - - print('Reading CDF''s for response functions:') - - while fline == '' or fline.isspace(): - fline=fidi.readline() - if fline == '' or fline.isspace(): - break - - # process header line of cdf - - while (fline != '' and not fline.isspace()): - [ntokens,tokens]=fltokens(fline) - - # find response function associated with cdf - # idresp is an index, so it can be 0, default to -1 - idresp=-1 - for i in range(len(dresp)): - if strcmpi(tokens[ 5],dresp[i].descriptor): - idresp=i - break - - - if idresp < 0: - idresp=len(dresp) - dresp.append(struct()) - dresp[idresp].descriptor=tokens[ 5] - print(' '+str(dresp(idresp).descriptor)) - - - # skip column headings of cdf - - fline=fidi.readline() - fline=fidi.readline() - - # read and add cdf table to response function - - fline=fidi.readline() - icdf=0 - while (fline != '' and not fline.isspace()) and not strncmpi(fline,'Cumulative Distribution Function',32): - [ntokens,tokens]=fltokens(fline) - icdf=icdf+1 - dresp[idresp].cdf = np.zeros((icdf,4)) - dresp[idresp].cdf[icdf-1,0:4]=np.nan - # in later versions of Dakota, uncalculated columns are now blank - itoken=0 - for i in range(len(fline)/19): - if not isempty(fline[(i-1)*19:i*19]): - itoken=itoken+1 - dresp[idresp].cdf[icdf-1,i]=tokens[itoken] - - fline=fidi.readline() - - print(' Number of Dakota response functions='+str(len(dresp))+'.') - - return dresp - # ]]] - -def pdfs_read(fidi,dresp,fline): # [[[ -## function to find and read the pdf's - - if fline == None or fline == '' or fline.isspace(): - fline=findline(fidi,'Probability Density Function (PDF) histograms for each response function') - return - - print('Reading PDF''s for response functions:') - - while (fline != '' and not fline.isspace()): - fline=fidi.readline() - if fline == '' or fline.isspace(): - break - - - # process header line of pdf - - while (fline != '' and not fline.isspace()): - [ntokens,tokens]=fltokens(fline) - - # find response function associated with pdf - # idresp is an index, so it can be 0, default to -1 - idresp=-1 - for i in range(len(dresp)): - if strcmpi(tokens[ 2],dresp[i].descriptor): - idresp=i - break - - - if idresp < 0: - idresp=len(dresp) - dresp.append(struct) - dresp[idresp].descriptor=tokens[ 2] - print(' '+str(dresp[idresp].descriptor)) - - - # skip column headings of pdf - - fline=fidi.readline() - fline=fidi.readline() - - # read and add pdf table to response function - - fline=fidi.readline() - ipdf=0 - while (fline != '' and not fline.isspace()) and not strncmpi(fline,'PDF for', 7): - [ntokens,tokens]=fltokens(fline) - ipdf=ipdf+1 - dresp[idresp].pdf = np.zeros((ipdf,4)) - dresp[idresp].pdf[ipdf-1,0:3]=np.nan - for i in range(3): - dresp[idresp].pdf[ipdf-1,i]=tokens[i] - - fline=fidi.readline() - - print(' Number of Dakota response functions='+str(len(dresp))+'.') - - return dresp - # ]]] - -def corrmat_read(fidi,cmstr,fline): # [[[ -## function to find and read a correlation matrix - - if fline == None or fline == '' or fline.isspace(): - fline=findline(fidi,cmstr) - if fline == '' or fline.isspace(): - cmat=struct() - return - - print('Reading ' +fline+ '.') - - cmat.title=fline - - while (fline != '' and not fline.isspace()): - fline=fidi.readline() - if fline == '' or fline.isspace(): - break - - # process column headings of matrix - - [ntokens,tokens]=fltokens(fline) - cmat.column= np.empty((1,ntokens)) - cmat.column.fill(0.0) - cmat.row = np.empty((1,1)) - cmat.row.fill(0.0) - cmat.matrix=np.zeros((1,ntokens)) - - for i in range(ntokens): - cmat.column[1,i]=str(tokens[i]) - - # process rows of matrix, reading until blank line - - nrow=0 - while True: - fline=fidi.readline() - if fline == '' or fline.isspace(): - break - - [ntokens,tokens]=fltokens(fline) - - # add row heading to matrix - - nrow=nrow+1 - cmat.row[nrow-1,0]=str(tokens[0]) - - # add row values to matrix - - for i in range(1,ntokens): - cmat.matrix[nrow-1,i-1]=tokens[i] - - return cmat - # ]]] - -def mvstats_read(fidi,dresp,fline): # [[[ -## function to find and read the MV statistics - - if fline == None or fline == '' or fline.isspace(): - fline=findline(fidi,'MV Statistics for ') - if fline == None: - return - - print('Reading MV statistics for response functions:') - - ndresp=0 - - while (fline != '' and not fline.isspace()) and strncmpi(fline,'MV Statistics for ',18): - - # add new response function and moments - - [ntokens,tokens]=fltokens(fline) - dresp.append(struct()) - dresp[-1].descriptor=tokens[3] - print(' '+str(dresp[-1].descriptor)) - fline=fidi.readline() - [ntokens,tokens]=fltokens(fline) - dresp[-1].mean =tokens[4] - fline=fidi.readline() - [ntokens,tokens]=fltokens(fline) - dresp[-1].stddev =tokens[6] - - # read and add importance factors to response function - - idvar=0 - fline=fidi.readline() - if fline == '' or fline.isspace(): - break - - # shape: [[0],[0],[0]...] - dresp[-1].var = [] - dresp[-1].impfac = [] - dresp[-1].sens = [] - - while (fline != '' and not fline.isspace()) and strncmpi(fline,' Importance Factor for variable ',33): - [ntokens,tokens]=fltokens(fline) - idvar=idvar+1 - dresp[-1].var.append(str(tokens[4])) - dresp[-1].impfac.append(tokens[6]) - if (ntokens >= 10): - dresp[-1].sens.append(tokens[9]) - else: - dresp[-1].sens.append(np.nan) - - - fline=fidi.readline() - - # if importance factors missing, skip to cdf - - if not idvar: - print(' Importance Factors not available.') - dresp[-1].var =[] - dresp[-1].impfac=[] - dresp[-1].sens =[] - while type(fline) == str and (fline != '' and not fline.isspace()) and not strncmpi(fline,'Cumulative Distribution Function',32) and not strncmpi(fline,'MV Statistics for ',18) and not strncmp(fline,'-',1): - fline=fidi.readline() - - # process header line of cdf - - icdf=0 - - # If there is a warning it MAY involve a lot of spaces; skip over them - if fline == '' or fline.isspace(): - fline=fidi.readline() - # Usually: "Warning: negligible standard deviation renders CDF results suspect." - if strncmpi(fline,'Warn',4): - fline = fidi.readline() - if fline == '' or fline.isspace(): - fline = fidi.readline() - - while (fline != '' and not fline.isspace()) and strncmpi(fline,'Cumulative Distribution Function',32): - [ntokens,tokens]=fltokens(fline) - - # find response function associated with cdf - # idresp is an index, so it can be 0, default to -1 - idresp=-1 - for i in range(len(dresp)): - if strcmpi(tokens[ 5],dresp[i].descriptor): - idresp=i - break - - if idresp < 0: - idresp=len(dresp) - dresp.append(struct()) - dresp[idresp].descriptor=tokens[ 5] - print(' '+str(dresp[idresp].descriptor)) - - # skip column headings of cdf - fline=fidi.readline() - fline=fidi.readline() - - # read and add cdf table to response function - - fline=fidi.readline() - while (fline != '' and not fline.isspace()) and not strncmpi(fline,'MV Statistics for ',18) and not strncmp (fline,'-',1): - [ntokens,tokens]=fltokens(fline) - icdf=icdf+1 - dresp[idresp].cdf = np.zeros((icdf,4)) - dresp[idresp].cdf[icdf-1,0]=tokens[0] - dresp[idresp].cdf[icdf-1,1]=tokens[1] - if (ntokens == 4): - dresp[idresp].cdf[icdf-1,2]=tokens[2] - dresp[idresp].cdf[icdf-1,3]=tokens[3] - else: - dresp[idresp].cdf[icdf-1,2]=np.nan - dresp[idresp].cdf[icdf-1,3]=np.nan - - fline=fidi.readline() - - # if cdf missing, skip to end of response function - - if not icdf: - print(' Cumulative Distribution Function not available.') - dresp[ndresp].cdf=[] - while (fline != '' and not fline.isspace()) and not strncmpi(fline,'MV Statistics for ',18) and not strncmp (fline,'-',1): - fline=fidi.readline() - - print(' Number of Dakota response functions='+str(len(dresp))+'.') - - return dresp - # ]]] - -def best_read(fidi,dresp,fline): # [[[ -## function to find and read the best evaluation - - if fline == None or fline == '' or fline.isspace(): - fline=findline(fidi,'<<<<< Best ') - if fline == None: - return - - if isempty(dresp): - dresp.append(struct()) - dresp[-1].best=struct() - - print('Reading values for best function evaluation:') - - while (fline != '' and not fline.isspace()) and strncmpi(fline,'<<<<< Best ',11): - [ntokens,tokens]=fltokens(fline) - - # read and add best parameter(s) - - if strncmpi(str(tokens[2]),'parameter', 9): - print(' '+fline) - - fline=fidi.readline() - dresp.best.param =[] - dresp.best.descriptor='' - - while (fline != '' and not fline.isspace()) and not strncmpi(fline,'<<<<< Best ',11): - [ntokens,tokens]=fltokens(fline) - dresp.best.param.append([0]) - dresp.best.param[-1]= tokens[0] - dresp.best.descriptor= str(tokens[1]) - fline=fidi.readline() - - # read and add best objective function(s) - - elif strncmpi(str(tokens[2]),'objective', 9) and strncmpi(str(tokens[3]),'function' , 8): - print(' '+fline) - - fline=fidi.readline() - dresp.best.of=[] - - while (fline != '' and not fline.isspace()) and not strncmpi(fline,'<<<<< Best ',11): - [ntokens,tokens]=fltokens(fline) - dresp.best.of.append(0) - dresp.best.of[-1]=tokens[0] - fline=fidi.readline() - - # read and add best residual norms - - elif strncmpi(str(tokens[2]),'residual', 8) and strncmpi(str(tokens[3]),'norm' , 4): - print(' '+fline) - dresp.best.norm = tokens[ 5] - dresp.best.hnormsq= tokens[10] - - fline=fidi.readline() - - while (fline != '' and not fline.isspace()) and not strncmpi(fline,'<<<<< Best ',11): - fline=fidi.readline() - - # read and add best residual term(s) - - elif strncmpi(str(tokens[2]),'residual', 8) and strncmpi(str(tokens[3]),'term' , 4): - print(' '+fline) - - fline=fidi.readline() - dresp.best.res=[] - - while (fline != '' and not fline.isspace()) and not strncmpi(fline,'<<<<< Best ',11): - [ntokens,tokens]=fltokens(fline) - dresp.best.res.append(0) - dresp.best.res[-1]= tokens[0] - fline=fidi.readline() - - # read and add best constraint value(s) - - elif strncmpi(str(tokens[2]),'constraint',10) and strncmpi(str(tokens[3]),'value' , 5): - print(' '+fline) - - fline=fidi.readline() - dresp.best.nc=[] - - while (fline != '' and not fline.isspace()) and not strncmpi(fline,'<<<<< Best ',11): - [ntokens,tokens]=fltokens(fline) - dresp.best.nc.append(0) - dresp.best.nc[-1]= tokens[0] - fline=fidi.readline() - - # read and add best data captured - - elif strncmpi(str(tokens[2]),'data' , 4) and strncmpi(str(tokens[3]),'captured', 8): - print(' '+fline) - dresp.best.eval= tokens[7] - - fline=fidi.readline() - - while (fline != '' and not fline.isspace()) and not strncmpi(fline,'<<<<< Best ',11): - fline=fidi.readline() - - # read until next best or blank or end - else: - print(' '+fline+' (ignored)') - - fline=fidi.readline() - - while (fline != '' and not fline.isspace()) and not strncmpi(fline,'<<<<< Best ',11): - fline=fidi.readline() - - return dresp - # ]]] - -def vum_read(fidi,dresp,fline): # [[[ -## function to find and read the volumetric uniformity measures - - if fline == None or fline == '' or fline.isspace(): - fline=findline(fidi,'The following lists volumetric uniformity measures') - if fline == None: - return - - if isempty(dresp): - dresp.append(struct()) - dresp[-1].vum=[] - - print('Reading measures for volumetric uniformity.') - - fline=fidi.readline() - fline=fidi.readline() - - while (fline != '' and not fline.isspace()): - [ntokens,tokens]=fltokens(fline) - check = tokens[0].lower() - if check == 'chi': - dresp.vum.chi=tokens[3] - elif check == 'd': - dresp.vum.d =tokens[3] - elif check == 'h': - dresp.vum.h =tokens[3] - elif check == 'tau': - dresp.vum.tau=tokens[3] - - fline=fidi.readline() - - return dresp - # ]]] - -def itcomp_read(fidi,fline): # [[[ -## function to find and read the iterator completion - - if fline == None or fline == '' or fline.isspace(): - while True: - fline=findline(fidi,'<<<<< Iterator ') - if fline == None: - return - - if (len(fline) > 26) and not (' completed.' in fline[15:]): - break - - [ntokens,tokens]=fltokens(fline) - method=tokens[2] - print('Dakota iterator \''+str(method)+'\' completed.') - - return method - # ]]] - -def findline(fidi,string,goto_line=False): # [[[ -## function to find a file line starting with a specified string -## by default, return to previous position, before search -## if final argument is True, return such that fidi.readline() will read the line -## immediately after the searched line (or the first line if the search failed) - - ipos=fidi.tell() - npos = 0 - for fline in fidi: - npos += len(fline) - if (strncmpi(fline,string,len(string))): - if goto_line: - fidi.seek(npos,0) - else: - fidi.seek(ipos,0) - return fline - - # issue warning and reset file position - print('Warning: findline:str_not_found: String '+str(string)+' not found in file.') - fidi.seek(ipos,0) - return None - # ]]] - -def fltokens(fline): # [[[ - ## function to parse a file line into tokens - if fline == None: - ntokens=-1 - tokens=[] - return [None,None] - - if fline == '' or fline.isspace(): - ntokens=0 - tokens=[] - return [None,None] - - # split wherever ' ' (space) or ':' occur - strings = re.split(':| ',fline) - # remove blank strings - strings = [a for a in strings if (a != '' and not a.isspace())] - - ntokens=0 - tokens = ['' for i in range(len(strings))] - - # try to format substrings to float where possible and count tokens and ignore invalid values - for i in range(len(strings)): - if isempty(strings[i]): - continue - - # if the string is a number, make it a float, otherwise leave it alone - try: - tokens[ntokens] = float(strings[i]) - except ValueError: - tokens[ntokens] = strings[i] - - ntokens=ntokens+1 - - return [ntokens,tokens] - # ]]] - - + if filei is None: + help(dakota_out_parse) + return + + if not isfile(filei) or getsize(filei) == 0: + filei = str(eval(input('Input file? '))) + + #fidi = fopen(sprintf('%s', filei), 'r') + #try: + with open(filei, 'r') as fidi: + # check the first line for the Dakota tabular output file + method = [] + fline = fidi.readline() + if getsize(filei) == 0 or fline == '': + raise RuntimeError('File ' + filei + ' is empty.') + + dresp = [] # of struct() + scm = struct() + pcm = struct() + srcm = struct() + prcm = struct() + + if '%eval_id' in fline: + method = 'unknown' + dresp = dak_tab_out(fidi, fline) + return [method, dresp, scm, pcm, srcm, prcm] + else: + fidi.seek(0, 0) + + # loop through the file to find the Dakota method name + fline = findline(fidi, 'method', True) + if fline is None: + #do nothing + pass + else: + if fline[6] == ',': + fline = fidi.readline() + [ntokens, tokens] = fltokens(fline) + method = tokens[0].strip() + print('Dakota method =\'' + method + '\'.') + elif fline[6] in ['N', 'n']: + fline = findline(fidi, 'methodName = ') + [ntokens, tokens] = fltokens(fline) + method = tokens[2].strip() + print('Dakota methodName = "' + method + '".') + + # loop through the file to find the function evaluation summary + counter = 0 + fline = '' + nfeval = nfeval_read(fidi, fline) + + # process each results section based on content of the file + while counter < 10: + # because python makes file i / o difficult + # if we see 10 + blank lines in a row then we have reached EOF + # (tests show actual maximum number of blank lines is around 5) + if fline == '' or fline.isspace(): + counter += 1 + else: + counter = 0 + # ipos = ftell(fidi) + fline = fidi.readline() + if fline == '' or fline.isspace(): + pass + elif '<<<<< Function evaluation summary' in fline: + nfeval = nfeval_read(fidi, fline) + elif 'Statistics based on ' in fline: + nsamp = nsamp_read(fidi, fline) + elif 'Moments for each response function' in fline: + dresp = moments_read(fidi, dresp, fline) + elif 'Moment-based statistics for each response function' in fline: + dresp = mbstats_read(fidi, dresp, fline) + elif '95% confidence intervals for each response function' in fline: + dresp = cis_read(fidi, dresp, fline) + elif 'Probabilities for each response function' in fline or 'Level mappings for each response function' in fline: + dresp = cdfs_read(fidi, dresp, fline) + elif 'Probability Density Function (PDF) histograms for each response function' in fline: + dresp = pdfs_read(fidi, dresp, fline) + elif 'Simple Correlation Matrix' in fline: + scm = corrmat_read(fidi, 'Simple Correlation Matrix', fline) + elif 'Partial Correlation Matrix' in fline: + pcm = corrmat_read(fidi, 'Partial Correlation Matrix', fline) + elif 'Simple Rank Correlation Matrix' in fline: + srcm = corrmat_read(fidi, 'Simple Rank Correlatio:n Matrix', fline) + elif 'Partial Rank Correlation Matrix' in fline: + prcm = corrmat_read(fidi, 'Partial Rank Correlation Matrix', fline) + elif 'MV Statistics for ' in fline: + dresp = mvstats_read(fidi, dresp, fline) + elif '<<<<< Best ' in fline: + dresp = best_read(fidi, dresp, fline) + elif 'The following lists volumetric uniformity measures' in fline: + dresp = vum_read(fidi, dresp, fline) + elif '<<<<< Iterator ' in fline and (len(fline) > 26) and (' completed.' in fline[15:]): + method = itcomp_read(fidi, fline) + elif '-----' in fline: + pass + else: + 'Unexpected line: ' + str(fline) + + # fidi.seek(ipos, 0) + + # loop through the file to verify the end + + # fline = findline(fidi, '<<<<< Single Method Strategy completed') + # if not ischar(fline) + # return + # + print('End of file successfully reached.') + #close(fidi) + #except Exception as err: + #print "ERROR in dakota_out_parse: " + err + #raise err + #raise RuntimeError(filei + ' could not be opened.') + + return [method, dresp, scm, pcm, srcm, prcm] + # }}} + + +def dak_tab_out(fidi, fline): # {{{ + # function to parse the dakota tabular output file + + print('Reading Dakota tabular output file.') + + # process column headings of matrix (skipping eval_id) + [ntokens, tokens] = fltokens(fline) + + # New file DAKOTA versions > 6 + if strncmpi(fline, '%eval_id interface', 18): + offset = 2 + else: #DAKOTA versions < 6 + offset = 1 + + desc = [['' for i in range(ntokens - offset)]] + data = np.zeros((1, ntokens - offset)) + + for i in range(ntokens - offset): + desc[0][i] = str(tokens[i + offset]) + + print("Number of columns (Dakota V + R)=" + str(ntokens - 2) + '.') + + # process rows of matrix + nrow = 0 + while True: + + fline = fidi.readline() + + if fline == '' or fline.isspace(): + break + + if nrow > 0: + data = np.concatenate((data, [np.zeros(ntokens - offset)])) + + [ntokens, tokens] = fltokens(fline) + + # add row values to matrix (skipping eval_id) + + for i in range(ntokens - offset): + data[nrow, i] = tokens[i + offset] + + nrow = nrow + 1 + + print('Number of rows (Dakota func evals) = ' + str(nrow) + '.') + + # calculate statistics + + # since normfit doesn't have a dim argument, and matlab isvector is True + # for a 1xn matrix, handle the case of one row explicitly + + # Update: normfit_issm.py does handle this case + if (np.size(data, 0) > 1): + #dmean =mean (data) + #dstddev = std (data, 0) + [dmean, dstddev, dmeanci, dstddevci] = normfit_issm(data, 0.05) + else: + dmean = np.zeros((1, np.size(data, 1))) + dstddev = np.zeros((1, np.size(data, 1))) + dmeanci = np.zeros((2, np.size(data, 1))) + dstddevci = np.zeros((2, np.size(data, 1))) + for i in range(np.size(data, 1)): + [dmean[0, i], dstddev[0, i], dmeanci[:, i], dstddevci[:, i]] = normfit_issm(data[:, i], 0.05) + + dmin = data.min(0) + dquart1 = prctile_issm(data, 25, 0) + dmedian = np.median(data, 0) + dquart3 = prctile_issm(data, 75, 0) + dmax = data.max(0) + dmin95 = prctile_issm(data, 5, 0) + dmax95 = prctile_issm(data, 95, 0) + + # Note: the following line may cause the following warning + # (should not crash or invalidate results) when one of + # the inputs does not change with respect to the + # other / s causing an internal divide-by - zero error + + # / usr / local / lib / python2.7 / dist - packages / numpy / lib / function_base.py:3163: + # RuntimeWarning: invalid value encountered in true_divide + # c / = stddev[:, None] + + # (and / or the same but with "c / = stddev[None, :]") + + dcorrel = np.corrcoef(data.T) + + # divide the data into structures for consistency + dresp = [] + + for i in range(len(desc)): + dresp.append(struct()) + dresp[i].descriptor = str(desc[i]) + dresp[i].sample = data[:, i] + dresp[i].mean = dmean[i] + dresp[i].stddev = dstddev[i] + dresp[i].meanci = dmeanci[:, i] + dresp[i].stddevci = dstddevci[:, i] + dresp[i].min = dmin[i] + dresp[i].quart1 = dquart1[i] + dresp[i].median = dmedian[i] + dresp[i].quart3 = dquart3[i] + dresp[i].max = dmax[i] + dresp[i].dmin95 = dmin95[i] + dresp[i].dmax95 = dmax95[i] + + # draw box plot + + # figure + # subplot(2, 1, 1) + # plot_boxplot(dresp) + + # draw normal probability plot + + # subplot(2, 1, 2) + # plot_normplot(dresp) + + return dresp + # }}} + + +def nfeval_read(fidi, fline): # {{{ + # function to find and read the number of function evaluations + + if fline is None or fline == '' or fline.isspace(): + fline = findline(fidi, '<<<<< Function evaluation summary') + nfeval = 0 + return + + [ntokens, tokens] = fltokens(fline) + nfeval = tokens[4] + print(' Dakota function evaluations = ' + str(int(nfeval)) + '.') + + return nfeval + # }}} + + +def nsamp_read(fidi, fline): # {{{ + # function to find and read the number of samples + + if fline is None or fline == '' or fline.isspace(): + fline = findline(fidi, 'Statistics based on ') + return + + [ntokens, tokens] = fltokens(fline) + nsamp = tokens[3] + print(' Dakota samples = ' + str(int(nsamp)) + '.') + + return nsamp + # }}} + + +def moments_read(fidi, dresp, fline): # {{{ + # function to find and read the moments + + if fline is None or fline == '' or fline.isspace(): + fline = findline(fidi, 'Moments for each response function') + return + + print('Reading moments for response functions:') + + while True: + fline = fidi.readline() + if fline == '' or fline.isspace(): + break + + [ntokens, tokens] = fltokens(fline) + + # add new response function and moments + + dresp.append(struct()) + dresp[-1].descriptor = tokens[0] + print(' ' + str(dresp[-1].descriptor)) + dresp[-1].mean = tokens[3] + dresp[-1].stddev = tokens[6] + dresp[-1].coefvar = tokens[12] + + print(' Number of Dakota response functions = ' + str(len(dresp)) + '.') + + return dresp + # }}} + + +def mbstats_read(fidi, dresp, fline): # {{{ + # function to find and read the moment - based statistics + + if fline is None or fline == '' or fline.isspace(): + fline = findline(fidi, 'Moment - based statistics for each response function') + return + + print('Reading moment - based statistics for response functions:') + + # skip column headings of moment - based statistics + + fline = fidi.readline() + + while True: + fline = fidi.readline() + if fline == '' or fline.isspace(): + break + + [ntokens, tokens] = fltokens(fline) + + # add new response function and moment - based statistics + + dresp.append(struct()) + dresp[-1].descriptor = tokens[0] + print(' ' + str(dresp[-1].descriptor)) + dresp[-1].mean = tokens[1] + dresp[-1].stddev = tokens[2] + dresp[-1].skewness = tokens[3] + dresp[-1].kurtosis = tokens[4] + + print(' Number of Dakota response functions = ' + str(len(dresp)) + '.') + + return dresp + # }}} + + +def cis_read(fidi, dresp, fline): # {{{ + # function to find and read the confidence intervals + + if fline is None or fline == '' or fline.isspace(): + fline = findline(fidi, '95% confidence intervals for each response function') + return + + print('Reading 95% confidence intervals for response functions:') + + while True: + fline = fidi.readline() + if fline == '' or fline.isspace(): + break + + [ntokens, tokens] = fltokens(fline) + # check for column headings in Dakota 5.2 + if (ntokens == 4): + fline = fidi.readline() + if fline == '' or fline.isspace(): + break + + [ntokens, tokens] = fltokens(fline) + + # find response function associated with confidence intervals + idresp = -1 + for i in range(len(dresp)): + if strcmpi(tokens[0], dresp[i].descriptor): + idresp = i + break + + if idresp < 0: + idresp = len(dresp) + dresp.append(struct()) + dresp[idresp].descriptor = tokens[0] + print(' ' + str(dresp[idresp].descriptor)) + + # add confidence intervals to response functions + dresp[i].meanci = np.array([[np.nan], [np.nan]]) + dresp[i].stddevci = np.array([[np.nan], [np.nan]]) + + if (ntokens == 14): + dresp[i].meanci[0, 0] = tokens[4] + dresp[i].meanci[1, 0] = tokens[5] + dresp[i].stddevci[0, 0] = tokens[11] + dresp[i].stddevci[1, 0] = tokens[12] + else: + dresp[i].meanci[0, 0] = tokens[1] + dresp[i].meanci[1, 0] = tokens[2] + dresp[i].stddevci[0, 0] = tokens[3] + dresp[i].stddevci[1, 0] = tokens[4] + + print(' Number of Dakota response functions = ' + str(len(dresp)) + '.') + + return dresp + # }}} + + +def cdfs_read(fidi, dresp, fline): # {{{ + # function to find and read the cdf's + + if fline is None or fline == '' or fline.isspace(): + fline = findline(fidi, 'Probabilities for each response function') + if fline is None: + fline = findline(fidi, 'Level mappings for each response function') + if fline is None: + return + + print('Reading CDF''s for response functions:') + + while fline == '' or fline.isspace(): + fline = fidi.readline() + if fline == '' or fline.isspace(): + break + + # process header line of cdf + + while (fline != '' and not fline.isspace()): + [ntokens, tokens] = fltokens(fline) + + # find response function associated with cdf + # idresp is an index, so it can be 0, default to - 1 + idresp = -1 + for i in range(len(dresp)): + if strcmpi(tokens[5], dresp[i].descriptor): + idresp = i + break + if idresp < 0: + idresp = len(dresp) + dresp.append(struct()) + dresp[idresp].descriptor = tokens[5] + print(' ' + str(dresp(idresp).descriptor)) + + # skip column headings of cdf + fline = fidi.readline() + fline = fidi.readline() + + # read and add cdf table to response function + fline = fidi.readline() + icdf = 0 + while (fline != '' and not fline.isspace()) and not strncmpi(fline, 'Cumulative Distribution Function', 32): + [ntokens, tokens] = fltokens(fline) + icdf = icdf + 1 + dresp[idresp].cdf = np.zeros((icdf, 4)) + dresp[idresp].cdf[icdf - 1, 0:4] = np.nan + # in later versions of Dakota, uncalculated columns are now blank + itoken = 0 + for i in range(len(fline) / 19): + if not isempty(fline[(i - 1) * 19:i * 19]): + itoken = itoken + 1 + dresp[idresp].cdf[icdf - 1, i] = tokens[itoken] + + fline = fidi.readline() + + print(' Number of Dakota response functions = ' + str(len(dresp)) + '.') + + return dresp + # }}} + + +def pdfs_read(fidi, dresp, fline): # {{{ + # function to find and read the pdf's + + if fline is None or fline == '' or fline.isspace(): + fline = findline(fidi, 'Probability Density Function (PDF) histograms for each response function') + return + + print('Reading PDF''s for response functions:') + + while (fline != '' and not fline.isspace()): + fline = fidi.readline() + if fline == '' or fline.isspace(): + break + + # process header line of pdf + while (fline != '' and not fline.isspace()): + [ntokens, tokens] = fltokens(fline) + + # find response function associated with pdf + # idresp is an index, so it can be 0, default to - 1 + idresp = -1 + for i in range(len(dresp)): + if strcmpi(tokens[2], dresp[i].descriptor): + idresp = i + break + + if idresp < 0: + idresp = len(dresp) + dresp.append(struct) + dresp[idresp].descriptor = tokens[2] + print(' ' + str(dresp[idresp].descriptor)) + + # skip column headings of pdf + fline = fidi.readline() + fline = fidi.readline() + + # read and add pdf table to response function + fline = fidi.readline() + ipdf = 0 + while (fline != '' and not fline.isspace()) and not strncmpi(fline, 'PDF for', 7): + [ntokens, tokens] = fltokens(fline) + ipdf = ipdf + 1 + dresp[idresp].pdf = np.zeros((ipdf, 4)) + dresp[idresp].pdf[ipdf - 1, 0:3] = np.nan + for i in range(3): + dresp[idresp].pdf[ipdf - 1, i] = tokens[i] + + fline = fidi.readline() + + print(' Number of Dakota response functions = ' + str(len(dresp)) + '.') + + return dresp + # }}} + + +def corrmat_read(fidi, cmstr, fline): # {{{ + # function to find and read a correlation matrix + + if fline is None or fline == '' or fline.isspace(): + fline = findline(fidi, cmstr) + if fline == '' or fline.isspace(): + cmat = struct() + return + + print('Reading ' + fline + '.') + + cmat.title = fline + + while (fline != '' and not fline.isspace()): + fline = fidi.readline() + if fline == '' or fline.isspace(): + break + + # process column headings of matrix + [ntokens, tokens] = fltokens(fline) + cmat.column = np.empty((1, ntokens)) + cmat.column.fill(0.0) + cmat.row = np.empty((1, 1)) + cmat.row.fill(0.0) + cmat.matrix = np.zeros((1, ntokens)) + + for i in range(ntokens): + cmat.column[1, i] = str(tokens[i]) + + # process rows of matrix, reading until blank line + nrow = 0 + while True: + fline = fidi.readline() + if fline == '' or fline.isspace(): + break + + [ntokens, tokens] = fltokens(fline) + + # add row heading to matrix + nrow = nrow + 1 + cmat.row[nrow - 1, 0] = str(tokens[0]) + + # add row values to matrix + for i in range(1, ntokens): + cmat.matrix[nrow - 1, i - 1] = tokens[i] + + return cmat + # }}} + + +def mvstats_read(fidi, dresp, fline): # {{{ + # function to find and read the MV statistics + + if fline is None or fline == '' or fline.isspace(): + fline = findline(fidi, 'MV Statistics for ') + if fline is None: + return + + print('Reading MV statistics for response functions:') + + ndresp = 0 + + while (fline != '' and not fline.isspace()) and strncmpi(fline, 'MV Statistics for ', 18): + + # add new response function and moments + [ntokens, tokens] = fltokens(fline) + dresp.append(struct()) + dresp[-1].descriptor = tokens[3] + print(' ' + str(dresp[-1].descriptor)) + fline = fidi.readline() + [ntokens, tokens] = fltokens(fline) + dresp[-1].mean = tokens[4] + fline = fidi.readline() + [ntokens, tokens] = fltokens(fline) + dresp[-1].stddev = tokens[6] + + # read and add importance factors to response function + idvar = 0 + fline = fidi.readline() + if fline == '' or fline.isspace(): + break + + # shape: [[0], [0], [0]...] + dresp[-1].var = [] + dresp[-1].impfac = [] + dresp[-1].sens = [] + + while (fline != '' and not fline.isspace()) and strncmpi(fline, ' Importance Factor for variable ', 33): + [ntokens, tokens] = fltokens(fline) + idvar = idvar + 1 + dresp[-1].var.append(str(tokens[4])) + dresp[-1].impfac.append(tokens[6]) + if (ntokens >= 10): + dresp[-1].sens.append(tokens[9]) + else: + dresp[-1].sens.append(np.nan) + + fline = fidi.readline() + + # if importance factors missing, skip to cdf + if not idvar: + print(' Importance Factors not available.') + dresp[-1].var = [] + dresp[-1].impfac = [] + dresp[-1].sens = [] + while type(fline) == str and (fline != '' and not fline.isspace()) and not strncmpi(fline, 'Cumulative Distribution Function', 32) and not strncmpi(fline, 'MV Statistics for ', 18) and not strncmp(fline, ' - ', 1): + fline = fidi.readline() + + # process header line of cdf + icdf = 0 + + # If there is a warning it MAY involve a lot of spaces; skip over them + if fline == '' or fline.isspace(): + fline = fidi.readline() + # Usually: "Warning: negligible standard deviation renders CDF results suspect." + if strncmpi(fline, 'Warn', 4): + fline = fidi.readline() + if fline == '' or fline.isspace(): + fline = fidi.readline() + + while (fline != '' and not fline.isspace()) and strncmpi(fline, 'Cumulative Distribution Function', 32): + [ntokens, tokens] = fltokens(fline) + + # find response function associated with cdf + # idresp is an index, so it can be 0, default to - 1 + idresp = -1 + for i in range(len(dresp)): + if strcmpi(tokens[5], dresp[i].descriptor): + idresp = i + break + + if idresp < 0: + idresp = len(dresp) + dresp.append(struct()) + dresp[idresp].descriptor = tokens[5] + print(' ' + str(dresp[idresp].descriptor)) + + # skip column headings of cdf + fline = fidi.readline() + fline = fidi.readline() + + # read and add cdf table to response function + fline = fidi.readline() + while (fline != '' and not fline.isspace()) and not strncmpi(fline, 'MV Statistics for ', 18) and not strncmp(fline, ' - ', 1): + [ntokens, tokens] = fltokens(fline) + icdf = icdf + 1 + dresp[idresp].cdf = np.zeros((icdf, 4)) + dresp[idresp].cdf[icdf - 1, 0] = tokens[0] + dresp[idresp].cdf[icdf - 1, 1] = tokens[1] + if (ntokens == 4): + dresp[idresp].cdf[icdf - 1, 2] = tokens[2] + dresp[idresp].cdf[icdf - 1, 3] = tokens[3] + else: + dresp[idresp].cdf[icdf - 1, 2] = np.nan + dresp[idresp].cdf[icdf - 1, 3] = np.nan + + fline = fidi.readline() + + # if cdf missing, skip to end of response function + if not icdf: + print(' Cumulative Distribution Function not available.') + dresp[ndresp].cdf = [] + while (fline != '' and not fline.isspace()) and not strncmpi(fline, 'MV Statistics for ', 18) and not strncmp(fline, ' - ', 1): + fline = fidi.readline() + + print(' Number of Dakota response functions = ' + str(len(dresp)) + '.') + + return dresp + # }}} + + +def best_read(fidi, dresp, fline): # {{{ + # function to find and read the best evaluation + + if fline is None or fline == '' or fline.isspace(): + fline = findline(fidi, ' < < < < < Best ') + if fline is None: + return + + if isempty(dresp): + dresp.append(struct()) + dresp[-1].best = struct() + + print('Reading values for best function evaluation:') + + while (fline != '' and not fline.isspace()) and strncmpi(fline, ' < < < < < Best ', 11): + [ntokens, tokens] = fltokens(fline) + + # read and add best parameter(s) + + if strncmpi(str(tokens[2]), 'parameter', 9): + print(' ' + fline) + + fline = fidi.readline() + dresp.best.param = [] + dresp.best.descriptor = '' + + while (fline != '' and not fline.isspace()) and not strncmpi(fline, ' < < < < < Best ', 11): + [ntokens, tokens] = fltokens(fline) + dresp.best.param.append([0]) + dresp.best.param[-1] = tokens[0] + dresp.best.descriptor = str(tokens[1]) + fline = fidi.readline() + + # read and add best objective function(s) + elif strncmpi(str(tokens[2]), 'objective', 9) and strncmpi(str(tokens[3]), 'function', 8): + print(' ' + fline) + + fline = fidi.readline() + dresp.best.of = [] + + while (fline != '' and not fline.isspace()) and not strncmpi(fline, ' < < < < < Best ', 11): + [ntokens, tokens] = fltokens(fline) + dresp.best.of.append(0) + dresp.best.of[-1] = tokens[0] + fline = fidi.readline() + + # read and add best residual norms + elif strncmpi(str(tokens[2]), 'residual', 8) and strncmpi(str(tokens[3]), 'norm', 4): + print(' ' + fline) + dresp.best.norm = tokens[5] + dresp.best.hnormsq = tokens[10] + + fline = fidi.readline() + + while (fline != '' and not fline.isspace()) and not strncmpi(fline, ' < < < < < Best ', 11): + fline = fidi.readline() + + # read and add best residual term(s) + elif strncmpi(str(tokens[2]), 'residual', 8) and strncmpi(str(tokens[3]), 'term', 4): + print(' ' + fline) + + fline = fidi.readline() + dresp.best.res = [] + + while (fline != '' and not fline.isspace()) and not strncmpi(fline, '<<<< 26) and not (' completed.' in fline[15:]): + break + + [ntokens, tokens] = fltokens(fline) + method = tokens[2] + print('Dakota iterator \'' + str(method) + '\' completed.') + + return method + # }}} + + +def findline(fidi, string, goto_line=False): # {{{ + # function to find a file line starting with a specified string + # by default, return to previous position, before search + # if final argument is True, return such that fidi.readline() will read the line + # immediately after the searched line (or the first line if the search failed) + + ipos = fidi.tell() + npos = 0 + for fline in fidi: + npos += len(fline) + if (strncmpi(fline, string, len(string))): + if goto_line: + fidi.seek(npos, 0) + else: + fidi.seek(ipos, 0) + return fline + + # issue warning and reset file position + print('Warning: findline:str_not_found: String ' + str(string) + ' not found in file.') + fidi.seek(ipos, 0) + return None + # }}} + + +def fltokens(fline): # {{{ + # function to parse a file line into tokens + if fline is None: + ntokens = -1 + tokens = [] + return [None, None] + + if fline == '' or fline.isspace(): + ntokens = 0 + tokens = [] + return [None, None] + + # split wherever ' ' (space) or ':' occur + strings = re.split(':| ', fline) + # remove blank strings + strings = [a for a in strings if (a != '' and not a.isspace())] + + ntokens = 0 + tokens = ['' for i in range(len(strings))] + + # try to format substrings to float where possible and count tokens and ignore invalid values + for i in range(len(strings)): + if isempty(strings[i]): + continue + + # if the string is a number, make it a float, otherwise leave it alone + try: + tokens[ntokens] = float(strings[i]) + except ValueError: + tokens[ntokens] = strings[i] + + ntokens = ntokens + 1 + + return [ntokens, tokens] + # }}} Index: /issm/trunk-jpl/src/m/qmu/expandresponses.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/expandresponses.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/expandresponses.py (revision 24213) @@ -2,18 +2,19 @@ from helpers import * -def expandresponses(md,responses): - #EXPANDRESPONSES - expand responses - fnames=fieldnames(responses) +def expandresponses(md, responses): + #EXPANDRESPONSES - expand responses - # maintain order attributes were added - dresp = OrderedStruct() - - for k in fnames: - v = eval('responses.{}'.format(k)) - exec('dresp.{} = type(v)()'.format(k)) - for j in range(len(v)): - #call setupdesign - exec('dresp.{}=QmuSetupResponses(md,dresp.{},v[j])'.format(k,k)) + fnames = fieldnames(responses) - return dresp + # maintain order attributes were added + dresp = OrderedStruct() + + for k in fnames: + v = eval('responses.{}'.format(k)) + exec('dresp.{} = type(v)()'.format(k)) + for j in range(len(v)): + #call setupdesign + exec('dresp.{}=QmuSetupResponses(md, dresp.{}, v[j])'.format(k, k)) + + return dresp Index: /issm/trunk-jpl/src/m/qmu/expandvariables.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/expandvariables.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/expandvariables.py (revision 24213) @@ -4,25 +4,24 @@ from qmu_classes import * -def expandvariables(md,variables): - fnames=fieldnames(variables) +def expandvariables(md, variables): - # maintain order attributes were added - dvar = OrderedStruct() + fnames = fieldnames(variables) - for k in fnames: - v = eval('variables.{}'.format(k)) + # maintain order attributes were added + dvar = OrderedStruct() - # for linear constraints, just copy - if isinstance(v,linear_inequality_constraint) or isinstance(v,linear_equality_constraint): - exec('dvar.{} = v'.format(k)) + for k in fnames: + v = eval('variables.{}'.format(k)) - # for variables, call the setup function - else: - exec('dvar.{} = type(v)()'.format(k)) - for j in range(len(v)): - #call setupdesign - exec('dvar.{}=QmuSetupVariables(md,dvar.{},v[j])'.format(k,k)) + # for linear constraints, just copy + if isinstance(v, linear_inequality_constraint) or isinstance(v, linear_equality_constraint): + exec('dvar.{} = v'.format(k)) - - return dvar + # for variables, call the setup function + else: + exec('dvar.{} = type(v)()'.format(k)) + for j in range(len(v)): + #call setupdesign + exec('dvar.{}=QmuSetupVariables(md, dvar.{}, v[j])'.format(k, k)) + return dvar Index: /issm/trunk-jpl/src/m/qmu/helpers.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/helpers.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/helpers.py (revision 24213) @@ -3,337 +3,349 @@ from copy import deepcopy + class struct(object): - '''An empty struct that can be assigned arbitrary attributes''' - pass + '''An empty struct that can be assigned arbitrary attributes''' + pass + class Lstruct(list): - ''' -An empty struct that can be assigned arbitrary attributes; - but can also be accesed as a list. Eg. x.y = 'hello', x[:] = ['w','o','r','l','d'] + ''' +An empty struct that can be assigned arbitrary attributes + but can also be accesed as a list. Eg. x.y = 'hello', x[:] = ['w', 'o', 'r', 'l', 'd'] Note that 'x' returns the array and x.__dict__ will only return - attributes other than the array - -List-based and struct-based behaviors work normally, however they are referenced - as if the other does not exist; len(x) corresponds only to - the list component of x, len(x.a) corresponds to x.a, x.__dict__ - corresponds only to the non-x-list attributes + attributes other than the array + +List - based and struct - based behaviors work normally, however they are referenced + as if the other does not exist; len(x) corresponds only to + the list component of x, len(x.a) corresponds to x.a, x.__dict__ + corresponds only to the non - x - list attributes Example uses: -x = Lstruct(1,2,3,4) -> [1,2,3,4] - x.a = 'hello' - len(x) -> 4 - x.append(5) - len(x) -> 5 - x[2] -> 3 - x.a -> 'hello' - print x -> [1,2,3,4,5] - x.__dict__ -> {'a': 'hello'} - x.b = [6,7,8,9] - x.b[-1] -> 9 - len(x.b) -> 4 - -Other valid constructors: - x = Lstruct(1,2,3,a='hello') -> x.a -> 'hello', x -> [1,2,3] - x = Lstruct(1,2,3)(a='hello') - x = Lstruct([1,2,3],x='hello') - x = Lstruct((1,2,3),a='hello') - -Credit: https://github.com/Vectorized/Python-Attribute-List +x = Lstruct(1, 2, 3, 4) - > [1, 2, 3, 4] + x.a = 'hello' + len(x) - > 4 + x.append(5) + len(x) - > 5 + x[2] - > 3 + x.a - > 'hello' + print x - > [1, 2, 3, 4, 5] + x.__dict__ - > {'a': 'hello'} + x.b = [6, 7, 8, 9] + x.b[-1] - > 9 + len(x.b) - > 4 + +Other valid constructors: + x = Lstruct(1, 2, 3, a = 'hello') - > x.a - > 'hello', x - > [1, 2, 3] + x = Lstruct(1, 2, 3)(a = 'hello') + x = Lstruct([1, 2, 3], x = 'hello') + x = Lstruct((1, 2, 3), a = 'hello') + +Credit: https: / / github.com / Vectorized / Python - Attribute-List ''' - def __new__(self, *args, **kwargs): - return super(Lstruct, self).__new__(self, args, kwargs) - - def __init__(self, *args, **kwargs): - if len(args) == 1 and hasattr(args[0], '__iter__'): - list.__init__(self, args[0]) - else: - list.__init__(self, args) - self.__dict__.update(kwargs) - - def __call__(self, **kwargs): - self.__dict__.update(kwargs) - return self + def __new__(self, *args, **kwargs): + return super(Lstruct, self).__new__(self, args, kwargs) + + def __init__(self, *args, **kwargs): + if len(args) == 1 and hasattr(args[0], '__iter__'): + list.__init__(self, args[0]) + else: + list.__init__(self, args) + self.__dict__.update(kwargs) + + def __call__(self, **kwargs): + self.__dict__.update(kwargs) + return self + class OrderedStruct(object): - ''' -A form of dictionary-like structure that maintains the - ordering in which its fields/attributes and their - corresponding values were added. + ''' +A form of dictionary - like structure that maintains the + ordering in which its fields / attributes and their + corresponding values were added. OrderedDict is a similar device, however this class - can be used as an "ordered struct/class" giving - it much more flexibility in practice. It is - also easier to work with fixed valued keys in-code. + can be used as an "ordered struct / class" giving + it much more flexibility in practice. It is + also easier to work with fixed valued keys in - code. Eg: -OrderedDict: # a bit clumsy to use and look at - x['y'] = 5 - -OrderedStruct: # nicer to look at, and works the same way - x.y = 5 - OR - x['y'] = 5 # supports OrderedDict-style usage - -Supports: len(x), str(x), for-loop iteration. +OrderedDict: # a bit clumsy to use and look at + x['y'] = 5 + +OrderedStruct: # nicer to look at, and works the same way + x.y = 5 + OR + x['y'] = 5 # supports OrderedDict - style usage + +Supports: len(x), str(x), for - loop iteration. Has methods: x.keys(), x.values(), x.items(), x.iterkeys() Usage: - x = OrderedStruct() - x.y = 5 - x.z = 6 - OR - x = OrderedStruct('y',5,'z',6) - - # note below that the output fields as iterables are always - # in the same order as the inputs - - x.keys() -> ['y','z'] - x.values() -> [5,6] - x.items() -> [('y',6),('z',6)] - x.__dict__ -> [('y',6),('z',6)] - vars(x) -> [('y',6),('z',6)] - - x.y -> 5 - x['y'] -> 5 - x.z -> 6 - x['z'] -> 6 - - for i in x: # same as x.items() - print i - -> - ('x',5) - ('y',6) - - Note: to access internal fields use dir(x) - (input fields will be included, but - are not technically internals) - ''' - - def __init__(self,*args): - '''Provided either nothing or a series of strings, construct a structure that will, + x = OrderedStruct() + x.y = 5 + x.z = 6 + OR + x = OrderedStruct('y', 5, 'z', 6) + + # note below that the output fields as iterables are always + # in the same order as the inputs + + x.keys() - > ['y', 'z'] + x.values() - > [5, 6] + x.items() - > [('y', 6), ('z', 6)] + x.__dict__ - > [('y', 6), ('z', 6)] + vars(x) - > [('y', 6), ('z', 6)] + + x.y - > 5 + x['y'] - > 5 + x.z - > 6 + x['z'] - > 6 + + for i in x: # same as x.items() + print i + - > + ('x', 5) + ('y', 6) + + Note: to access internal fields use dir(x) + (input fields will be included, but + are not technically internals) + ''' + + def __init__(self, *args): + '''Provided either nothing or a series of strings, construct a structure that will, when accessed as a list, return its fields in the same order in which they were provided''' - # keys and values - self._k = [] - self._v = [] - - if len(args) == 0: - return - - if len(args) % 2 != 0: - raise RuntimeError('OrderedStruct input error: OrderedStruct(*args) call must have an even number of inputs, in key/value pairs') - - for a,b in zip(args[0::2],args[1::2]): - exec(('self.%s = b')%(a)) - return - - def __repr__(self): - s = 'OrderedStruct:\n\t' - for a,b in zip(self._k,self._v): - s += str(a) + ' : ' + str(b) + '\n\t' - return s - - def __len__(self): - return len(self._k) - - def __getattr__(self, attr): - # called when __getattribute__ fails - try: - # check if in keys, then access - _k = object.__getattribute__(self, '_k') - _v = object.__getattribute__(self, '_v') - pos = _k.index(attr) - return _v[pos] - except ValueError: - # not in keys, not a valid attribute, raise error - raise AttributeError('Attribute "'+str(attr)+'" does not exist.') - - def __getattribute__(self, attr): - # re-route calls to vars(x) and x.__dict__ - if attr == '__dict__': - return OrderedDict(list(self.items())) - else: - return object.__getattribute__(self, attr) - - def __getitem__(self, key): - return self._v[self._k.index(key)] - - def __setattr__(self, name, value): - #super(OrderedStruct, self).__setattr__(name,value) - if name in ['_k','_v']: - object.__setattr__(self, name, value) - elif name not in self._k: - self._k.append(name) - self._v.append(value) - else: - self._v[self._k.index(name)] = value - - def __delattr__(self, key): - if name not in self._k: - raise AttributeError('Attribute "'+str(attr)+'" does not exist or is an internal field and therefore cannot be deleted safely.') - self.pop(key) - - def __iter__(self): - for a,b in zip(self._k,self._v): - yield(a,b) - - def __copy__(self): - # shallow copy, hard copies of trivial attributes, - # references to structures like lists/OrderedDicts - # unless redefined as an entirely different structure - newInstance = type(self)() - for k,v in list(self.items()): - exec(('newInstance.%s = v')%(k)) - return newInstance - - def __deepcopy__(self,memo=None): - # hard copy of all attributes - # same thing but call deepcopy recursively - # technically not how it should be done, - # (see https://docs.python.org/2/library/copy.html#copy.deepcopy ) - # but will generally work in this case - newInstance = type(self)() - for k,v in list(self.items()): - exec(('newInstance.%s = deepcopy(v)')%(k)) - return newInstance - - def iterkeys(self): - for k in self._k: - yield k - - def pop(self,key): - i = self._k.index(key) - k = self._k.pop(i) - v = self._v.pop(i) - #exec('del self.%s')%(key) - return (k,v) - - def keys(self): - return self._k - def values(self): - return self._v - def items(self): - return list(zip(self._k,self._v)) + # keys and values + self._k = [] + self._v = [] + + if len(args) == 0: + return + + if len(args) % 2 != 0: + raise RuntimeError('OrderedStruct input error: OrderedStruct(*args) call must have an even number of inputs, in key / value pairs') + + for a, b in zip(args[0::2], args[1::2]): + exec(('self.%s = b') % (a)) + return + + def __repr__(self): + s = 'OrderedStruct:\n\t' + for a, b in zip(self._k, self._v): + s += str(a) + ' : ' + str(b) + '\n\t' + return s + + def __len__(self): + return len(self._k) + + def __getattr__(self, attr): + # called when __getattribute__ fails + try: + # check if in keys, then access + _k = object.__getattribute__(self, '_k') + _v = object.__getattribute__(self, '_v') + pos = _k.index(attr) + return _v[pos] + except ValueError: + # not in keys, not a valid attribute, raise error + raise AttributeError('Attribute "' + str(attr) + '" does not exist.') + + def __getattribute__(self, attr): + # re-route calls to vars(x) and x.__dict__ + if attr == '__dict__': + return OrderedDict(list(self.items())) + else: + return object.__getattribute__(self, attr) + + def __getitem__(self, key): + return self._v[self._k.index(key)] + + def __setattr__(self, name, value): + #super(OrderedStruct, self).__setattr__(name, value) + if name in ['_k', '_v']: + object.__setattr__(self, name, value) + elif name not in self._k: + self._k.append(name) + self._v.append(value) + else: + self._v[self._k.index(name)] = value + + def __delattr__(self, key): + if name not in self._k: + raise AttributeError('Attribute "' + str(attr) + '" does not exist or is an internal field and therefore cannot be deleted safely.') + self.pop(key) + + def __iter__(self): + for a, b in zip(self._k, self._v): + yield(a, b) + + def __copy__(self): + # shallow copy, hard copies of trivial attributes, + # references to structures like lists / OrderedDicts + # unless redefined as an entirely different structure + newInstance = type(self)() + for k, v in list(self.items()): + exec(('newInstance.%s = v') % (k)) + return newInstance + + def __deepcopy__(self, memo=None): + # hard copy of all attributes + # same thing but call deepcopy recursively + # technically not how it should be done, + # (see https: / / docs.python.org / 2 / library / copy.html #copy.deepcopy ) + # but will generally work in this case + newInstance = type(self)() + for k, v in list(self.items()): + exec(('newInstance.%s = deepcopy(v)') % (k)) + return newInstance + + def iterkeys(self): + for k in self._k: + yield k + + def pop(self, key): + i = self._k.index(key) + k = self._k.pop(i) + v = self._v.pop(i) + #exec('del self.%s')%(key) + return (k, v) + + def keys(self): + return self._k + + def values(self): + return self._v + + def items(self): + return list(zip(self._k, self._v)) + def isempty(x): - '''returns true if object is +\-infinity, NaN, None, '', has length 0, or is an - array/matrix composed only of such components (includes mixtures of "empty" types)''' - - if type(x) in [list,np.ndarray,tuple]: - if np.size(x) == 0: - return True - - # if anything in that array/matrix is not empty, the whole thing is not empty - try: - x = np.concatenate(x) - except (ValueError): - pass - for i in x: - if not isempty(i): - return False - # the array isn't empty but is full of "empty" type objects, so return True - return True - - if x == None: - return True - if type(x) == str and x.lower() in ['','nan','none','inf','infinity','-inf','-infinity']: - return True - - # type may not be understood by numpy, in which case it definitely is NOT NaN or infinity - try: - if np.isnan(x) or np.isinf(x): - return True - except (TypeError): - pass - - # if all of that fails, then it is not empty - return False - -def fieldnames(x,ignore_internals = True): - '''returns a list of fields of x - ignore_internals ignores all fieldnames starting with '_' and is True by default''' - result = list(vars(x).keys()) - - if ignore_internals: - result = [i for i in result if i[0] != '_'] - - return result - -def isfield(x,y,ignore_internals=True): - '''is y is a field of x? - ignore_internals ignores all fieldnames starting with '_' and is True by default''' - return str(y) in fieldnames(x,ignore_internals) + ''' + returns true if object is + - infinity, NaN, None, '', has length 0, or is an + array / matrix composed only of such components (includes mixtures of "empty" types)''' + + if type(x) in [list, np.ndarray, tuple]: + if np.size(x) == 0: + return True + + # if anything in that array / matrix is not empty, the whole thing is not empty + try: + x = np.concatenate(x) + except (ValueError): + pass + for i in x: + if not isempty(i): + return False + # the array isn't empty but is full of "empty" type objects, so return True + return True + + if x is None: + return True + if type(x) == str and x.lower() in ['', 'nan', 'none', 'inf', 'infinity', ' - inf', ' - infinity']: + return True + + # type may not be understood by numpy, in which case it definitely is NOT NaN or infinity + try: + if np.isnan(x) or np.isinf(x): + return True + except (TypeError): + pass + + # if all of that fails, then it is not empty + return False + + +def fieldnames(x, ignore_internals=True): + '''returns a list of fields of x + ignore_internals ignores all fieldnames starting with '_' and is True by default''' + result = list(vars(x).keys()) + + if ignore_internals: + result = [i for i in result if i[0] != '_'] + + return result + + +def isfield(x, y, ignore_internals=True): + '''is y is a field of x? + ignore_internals ignores all fieldnames starting with '_' and is True by default''' + return str(y) in fieldnames(x, ignore_internals) + def fileparts(x): - ''' - given: "path/path/.../file_name.ext" - returns: [path,file_name,ext] (list of strings)''' - try: - a = x[:x.rindex('/')] #path - b = x[x.rindex('/')+1:] #full filename - except ValueError: #no path provided - a = '' - b = x - try: - c,d = b.split('.') #file name, extension - except ValueError: #no extension provided - return [a,b,''] - return [a,c,'.'+d] + ''' + given: "path / path / ... / file_name.ext" + returns: [path, file_name, ext] (list of strings)''' + try: + a = x[:x.rindex('/')] #path + b = x[x.rindex('/') + 1:] #full filename + except ValueError: #no path provided + a = '' + b = x + try: + c, d = b.split('.') #file name, extension + except ValueError: #no extension provided + return [a, b, ''] + return [a, c, '.' + d] + def fullfile(*args): - ''' - use: - - fullfile(path, path, ... , file_name+ext) - returns: "path/path/.../file_name.ext" - - with all arguments as strings with no "/"s - - regarding extensions and the '.': - as final arguments ('file.doc') or ('file'+'.doc') will work; - ('final','.doc'), and the like, will not (you'd get 'final/.doc') + ''' + use: + + fullfile(path, path, ... , file_name + ext) + returns: "path / path / ... / file_name.ext" + + with all arguments as strings with no " / "s + + regarding extensions and the '.': + as final arguments ('file.doc') or ('file' + '.doc') will work + ('final', '.doc'), and the like, will not (you'd get 'final/.doc') ''' - result = str(args[0]) - for i in range(len(args[1:])): - # if last argument wasn't empty, add a '/' between it and the next argument - if len(args[i]) != 0: - result += '/'+str(args[i+1]) - else: - result += str(args[i+1]) - return result - -def findline(fidi,s): - ''' - returns full first line containing s (as a string), or None - Note: will include any newlines or tabs that occur in that line, - use str(findline(f,s)).strip() to remove these, str() in case result is None''' - for line in fidi: - if s in line: - return line - return None - -def empty_nd_list(shape,filler=0.,as_numpy_ndarray=False): - ''' -returns a python list of the size/shape given (shape must be int or tuple) - the list will be filled with the optional second argument - - filler is 0.0 by default - - as_numpy_ndarray will return the result as a numpy.ndarray and is False by default - - Note: the filler must be either None/np.nan/float('NaN'), float/double, or int - other numpy and float values such as +/- np.inf will also work + result = str(args[0]) + for i in range(len(args[1:])): + # if last argument wasn't empty, add a '/' between it and the next argument + if len(args[i]) != 0: + result += '/' + str(args[i + 1]) + else: + result += str(args[i + 1]) + return result + + +def findline(fidi, s): + ''' + returns full first line containing s (as a string), or None + Note: will include any newlines or tabs that occur in that line, + use str(findline(f, s)).strip() to remove these, str() in case result is None''' + for line in fidi: + if s in line: + return line + return None + + +def empty_nd_list(shape, filler=0., as_numpy_ndarray=False): + ''' +returns a python list of the size / shape given (shape must be int or tuple) + the list will be filled with the optional second argument + + filler is 0.0 by default + + as_numpy_ndarray will return the result as a numpy.ndarray and is False by default + + Note: the filler must be either None / np.nan / float('NaN'), float / double, or int + other numpy and float values such as + / - np.inf will also work use: - empty_nd_list((5,5), 0.0) # returns a 5x5 matrix of 0.0's - empty_nd_list(5, None) # returns a 5 long array of NaN + empty_nd_list((5, 5), 0.0) # returns a 5x5 matrix of 0.0's + empty_nd_list(5, None) # returns a 5 long array of NaN ''' - result = np.empty(shape) - result.fill(filler) - if not as_numpy_ndarray: - return result.tolist() - return result - + result = np.empty(shape) + result.fill(filler) + if not as_numpy_ndarray: + return result.tolist() + return result Index: /issm/trunk-jpl/src/m/qmu/importancefactors.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/importancefactors.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/importancefactors.py (revision 24213) @@ -2,66 +2,67 @@ from MatlabFuncs import * -def importancefactors(md,variablename,responsename): - '''IMPORTANCEFACTORS - compute importance factors for a certain variable and response. - + +def importancefactors(md, variablename, responsename): + '''IMPORTANCEFACTORS - compute importance factors for a certain variable and response. + Usage: - factors=importancefactors(md,variablename,responsename) - - Example: factors=importancefactors(md,'drag','max_vel') + factors = importancefactors(md, variablename, responsename) + + Example: factors = importancefactors(md, 'drag', 'max_vel') ''' - variablenamelength=len(variablename) + variablenamelength = len(variablename) - #go through all response functions and find the one corresponding to the correct responsename - responsefunctions=md.qmu.results.dresp_out - found=-1 - for i in range(len(responsefunctions)): - if strcmpi(responsefunctions[i].descriptor,responsename): - found=i - break - if found < 0: - raise RuntimeError('importancefactors error message: could not find correct response function') + #go through all response functions and find the one corresponding to the correct responsename + responsefunctions = md.qmu.results.dresp_out + found = -1 + for i in range(len(responsefunctions)): + if strcmpi(responsefunctions[i].descriptor, responsename): + found = i + break + if found < 0: + raise RuntimeError('importancefactors error message: could not find correct response function') - responsefunctions=responsefunctions[found] - nfun=np.size(responsefunctions.var) + responsefunctions = responsefunctions[found] + nfun = np.size(responsefunctions.var) - #Now recover response to the correct design variable - importancefactors=[] - count=0 - for i in range(nfun): - desvar=responsefunctions.var[i] - if strncmpi(desvar,variablename,variablenamelength): - importancefactors.append(responsefunctions.impfac[i]) - count=count+1 - - if count==0: - raise RuntimeError('importancefactors error message: either response does not exist, or importancefactors are empty') + #Now recover response to the correct design variable + importancefactors = [] + count = 0 + for i in range(nfun): + desvar = responsefunctions.var[i] + if strncmpi(desvar, variablename, variablenamelength): + importancefactors.append(responsefunctions.impfac[i]) + count = count + 1 - importancefactors = np.array(importancefactors) + if count == 0: + raise RuntimeError('importancefactors error message: either response does not exist, or importancefactors are empty') - if count==1: #we have scalar - factors=importancefactors - return factors - elif count==np.max(md.qmu.epartition+1): - #distribute importance factor - factors=importancefactors[(md.qmu.epartition.conj().T).flatten().astype(int)] - #md.qmu.partition was created to index "c" style - else: - #distribute importance factor - factors=importancefactors[(md.qmu.vpartition.conj().T).flatten().astype(int)] - #md.qmu.partition was created to index "c" style + importancefactors = np.array(importancefactors) - #weight importancefactors by area - #if numel(factors)==md.mesh.numberofvertices, - # #get areas for each vertex. - # aire=GetAreas(md.mesh.elements,md.mesh.x,md.mesh.y) - # num_elements_by_node=md.nodeconnectivity(:,) - # grid_aire=zeros(md.mesh.numberofvertices,1) - # for i=1:md.mesh.numberofvertices, - # for j=1:num_elements_by_node(i), - # grid_aire(i)=grid_aire(i)+aire(md.nodeconnectivity(i,j)) - # - # - # factors=factors./grid_aire - # - return factors + if count == 1: #we have scalar + factors = importancefactors + return factors + elif count == np.max(md.qmu.epartition + 1): + #distribute importance factor + factors = importancefactors[(md.qmu.epartition.conj().T).flatten().astype(int)] + #md.qmu.partition was created to index "c" style + else: + #distribute importance factor + factors = importancefactors[(md.qmu.vpartition.conj().T).flatten().astype(int)] + #md.qmu.partition was created to index "c" style + + #weight importancefactors by area + #if numel(factors) == md.mesh.numberofvertices, + # #get areas for each vertex. + # aire = GetAreas(md.mesh.elements, md.mesh.x, md.mesh.y) + # num_elements_by_node = md.nodeconnectivity(:, ) + # grid_aire = zeros(md.mesh.numberofvertices, 1) + # for i = 1:md.mesh.numberofvertices, + # for j = 1:num_elements_by_node(i), + # grid_aire(i)=grid_aire(i) + aire(md.nodeconnectivity(i, j)) + # + # + # factors = factors. / grid_aire + # + return factors Index: /issm/trunk-jpl/src/m/qmu/lclist_write.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/lclist_write.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/lclist_write.py (revision 24213) @@ -8,60 +8,56 @@ from linear_inequality_constraint import * -def lclist_write(fidi,cstring,cstring2,dvar): - ''' + +def lclist_write(fidi, cstring, cstring2, dvar): + ''' function to write linear constraint list ''' - if dvar == None: - return + if dvar is None: + return - # put linear constraints into lists for writing + # put linear constraints into lists for writing - nvar=0 - pmatrix=[] - plower =[] - pupper =[] - ptarget=[] - pstype =[] - pscale =[] + nvar = 0 + pmatrix = [] + plower = [] + pupper = [] + ptarget = [] + pstype = [] + pscale = [] - fnames=fieldnames(dvar) - for i in range(np.size(fnames)): - nvar=nvar+np.size(vars(dvar)[fnames[i]]) - pmatrix=[pmatrix,prop_matrix(vars(dvar)[fnames[i]])] - plower =[plower ,prop_lower(vars(dvar)[fnames[i]]) ] - pupper =[pupper ,prop_upper(vars(dvar)[fnames[i]]) ] - ptarget=[ptarget,prop_target(vars(dvar)[fnames[i]])] - pstype =[pstype ,prop_stype(vars(dvar)[fnames[i]]) ] - pscale =[pscale ,prop_scale(vars(dvar)[fnames[i]]) ] + fnames = fieldnames(dvar) + for i in range(np.size(fnames)): + nvar = nvar + np.size(vars(dvar)[fnames[i]]) + pmatrix = [pmatrix, prop_matrix(vars(dvar)[fnames[i]])] + plower = [plower, prop_lower(vars(dvar)[fnames[i]])] + pupper = [pupper, prop_upper(vars(dvar)[fnames[i]])] + ptarget = [ptarget, prop_target(vars(dvar)[fnames[i]])] + pstype = [pstype, prop_stype(vars(dvar)[fnames[i]])] + pscale = [pscale, prop_scale(vars(dvar)[fnames[i]])] + # write linear constraints + print(' Writing ' + str(nvar) + ' ' + cstring + ' linear constraints.') - # write linear constraints + if len(pmatrix) != 0: + fidi.write('\t ' + cstring2 + '_matrix =\n') + vector_write(fidi, '\t ', pmatrix, 6, 76) - print(' Writing '+str(nvar)+' '+cstring+' linear constraints.') + if len(plower) != 0: + fidi.write('\t ' + cstring2 + '_lower_bounds =\n') + vector_write(fidi, '\t ', plower, 6, 76) - if len(pmatrix) != 0: - fidi.write('\t '+cstring2+'_matrix =\n') - vector_write(fidi,'\t ',pmatrix,6,76) + if len(pupper) != 0: + fidi.write('\t ' + cstring2 + '_upper_bounds =\n') + vector_write(fidi, '\t ', pupper, 6, 76) - if len(plower) != 0: - fidi.write('\t '+cstring2+'_lower_bounds =\n') - vector_write(fidi,'\t ',plower ,6,76) + if len(ptarget) != 0: + fidi.write('\t ' + cstring2 + '_targets =\n') + vector_write(fidi, '\t ', ptarget, 6, 76) - if len(pupper) != 0: - fidi.write('\t '+cstring2+'_upper_bounds =\n') - vector_write(fidi,'\t ',pupper ,6,76) + if len(pstype) != 0: + fidi.write('\t ' + cstring2 + '_scale_types =\n') + vector_write(fidi, '\t ', pstype, 6, 76) - if len(ptarget) != 0: - fidi.write('\t '+cstring2+'_targets =\n') - vector_write(fidi,'\t ',ptarget,6,76) - - if len(pstype) != 0: - fidi.write('\t '+cstring2+'_scale_types =\n') - vector_write(fidi,'\t ',pstype ,6,76) - - if len(pscale) != 0: - fidi.write('\t '+cstring2+'_scales =\n') - vector_write(fidi,'\t ',pscale ,6,76) - - - + if len(pscale) != 0: + fidi.write('\t ' + cstring2 + '_scales =\n') + vector_write(fidi, '\t ', pscale, 6, 76) Index: /issm/trunk-jpl/src/m/qmu/param_write.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/param_write.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/param_write.py (revision 24213) @@ -2,23 +2,24 @@ from helpers import * -def param_write(fidi,sbeg,pname,smid,s,params): - ''' + +def param_write(fidi, sbeg, pname, smid, s, params): + ''' function to write a parameter ''' - if not isfield(params,pname): - print('WARNING: param_write:param_not_found: Parameter {} not found in structure.'.format(pname)) - return + if not isfield(params, pname): + print('WARNING: param_write:param_not_found: Parameter {} not found in structure.'.format(pname)) + return - params_pname = vars(params)[pname] + params_pname = vars(params)[pname] - if type(params_pname) == bool and (not params_pname): - return + if type(params_pname) == bool and (not params_pname): + return - if type(params_pname) == bool: - fidi.write(sbeg+str(pname)+s) + if type(params_pname) == bool: + fidi.write(sbeg + str(pname) + s) - elif type(params_pname) in [str]: - fidi.write(sbeg+pname+smid+params_pname+s) + elif type(params_pname) in [str]: + fidi.write(sbeg + pname + smid + params_pname + s) - elif type(params_pname) in [int, float]: - fidi.write(sbeg+str(pname)+smid+str(params_pname)+s) + elif type(params_pname) in [int, float]: + fidi.write(sbeg + str(pname) + smid + str(params_pname) + s) Index: /issm/trunk-jpl/src/m/qmu/postqmu.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/postqmu.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/postqmu.py (revision 24213) @@ -1,60 +1,60 @@ -from os import system,getpid,stat +from os import getpid, stat from os.path import isfile from subprocess import Popen - from dakota_out_parse import * from helpers import * -def postqmu(md,qmufile,qmudir='qmu'+str(getpid())): - ''' -Deal with dakota output results in files. -INPUT function - md=postqmu(md,qmufile,qmudir) +def postqmu(md, qmufile, qmudir='qmu' + str(getpid())): + ''' + Deal with dakota output results in files. -By default: qmudir = 'qmu'+pid (eg. 'qmu2189') -''' + INPUT function + md = postqmu(md, qmufile, qmudir) - # check to see if dakota returned errors in the err file - qmuerrfile=str(md.miscellaneous.name)+'.qmu.err' + By default: qmudir = 'qmu' + pid (eg. 'qmu2189') + ''' - if isfile(qmuerrfile) and stat(qmuerrfile).st_size > 0: - with open(qmuerrfile,'r') as fide: - fline=fide.read() - print(fline) + # check to see if dakota returned errors in the err file + qmuerrfile = str(md.miscellaneous.name) + '.qmu.err' - raise RuntimeError('Dakota returned error in '+str(qmuerrfile)+' file. '+str(qmudir)+' directory retained.') + if isfile(qmuerrfile) and stat(qmuerrfile).st_size > 0: + with open(qmuerrfile, 'r') as fide: + fline = fide.read() + print(fline) - # parse inputs and results from dakota - qmuinfile=str(md.miscellaneous.name)+'.qmu.in' - qmuoutfile=str(md.miscellaneous.name)+'.qmu.out' + raise RuntimeError('Dakota returned error in ' + str(qmuerrfile) + ' file. ' + str(qmudir) + ' directory retained.') - # unused and unimplemented - #[method,dvar,dresp_in]=dakota_in_parse(qmuinfile) - #dakotaresults.method =method - #dakotaresults.dvar =dvar - #dakotaresults.dresp_in =dresp_in + # parse inputs and results from dakota + qmuinfile = str(md.miscellaneous.name) + '.qmu.in' + qmuoutfile = str(md.miscellaneous.name) + '.qmu.out' - [method,dresp_out,scm,pcm,srcm,prcm]=dakota_out_parse(qmuoutfile) - dakotaresults = struct() - dakotaresults.dresp_out=dresp_out - dakotaresults.scm =scm - dakotaresults.pcm =pcm - dakotaresults.srcm =srcm - dakotaresults.prcm =prcm + # unused and unimplemented + #[method, dvar, dresp_in] = dakota_in_parse(qmuinfile) + #dakotaresults.method =method + #dakotaresults.dvar =dvar + #dakotaresults.dresp_in =dresp_in - if isfile('dakota_tabular.dat'): - # only need a subset of the outputs; dakota_out_parse handles .dat seperately - [method,dresp_dat,_,_,_,_]=dakota_out_parse('dakota_tabular.dat') - dakotaresults.dresp_dat=dresp_dat + [method, dresp_out, scm, pcm, srcm, prcm] = dakota_out_parse(qmuoutfile) + dakotaresults = struct() + dakotaresults.dresp_out = dresp_out + dakotaresults.scm = scm + dakotaresults.pcm = pcm + dakotaresults.srcm = srcm + dakotaresults.prcm = prcm - # put dakotaresults in their right location. - md.results.dakota=dakotaresults + if isfile('dakota_tabular.dat'): + # only need a subset of the outputs; dakota_out_parse handles .dat seperately + [method, dresp_dat, _, _, _, _] = dakota_out_parse('dakota_tabular.dat') + dakotaresults.dresp_dat = dresp_dat - # move all the individual function evalutations into zip files - if not md.qmu.isdakota: - Popen('zip -mq params.in.zip params.in.[1-9]*',shell=True) - Popen('zip -mq results.out.zip results.out.[1-9]*',shell=True) - Popen('zip -mq matlab.out.zip matlab*.out.[1-9]*',shell=True) + # put dakotaresults in their right location. + md.results.dakota = dakotaresults - return md + # move all the individual function evalutations into zip files + if not md.qmu.isdakota: + Popen('zip - mq params.in.zip params.in.[1 - 9] * ', shell=True) + Popen('zip - mq results.out.zip results.out.[1 - 9] * ', shell=True) + Popen('zip - mq matlab.out.zip matlab * .out.[1 - 9] * ', shell=True) + + return md Index: /issm/trunk-jpl/src/m/qmu/preqmu.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/preqmu.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/preqmu.py (revision 24213) @@ -7,137 +7,135 @@ from process_qmu_response_data import * -def preqmu(md,options): - '''QMU - apply Quantification of Margins and Uncertainties techniques - to a solution sequence (like stressbalance.py, progonstic.py, etc ...), - using the Dakota software from Sandia. + +def preqmu(md, options): + '''QMU - apply Quantification of Margins and Uncertainties techniques + to a solution sequence (like stressbalance.py, progonstic.py, etc ...), + using the Dakota software from Sandia. options come from the solve.py routine. They can include Dakota options: - qmudir: any directory where to run the qmu analysis - qmufile: input file for Dakota + qmudir: any directory where to run the qmu analysis + qmufile: input file for Dakota - (ivap, iresp, imethod, and iparams are currently unimplemented) - ivar: selection number for variables input (if several are specified in variables) - iresp: same thing for response functions - imethod: same thing for methods - iparams: same thing for params + (ivap, iresp, imethod, and iparams are currently unimplemented) + ivar: selection number for variables input (if several are specified in variables) + iresp: same thing for response functions + imethod: same thing for methods + iparams: same thing for params - overwrite: overwrite qmudir before analysis + overwrite: overwrite qmudir before analysis ''' - print('preprocessing dakota inputs') - qmudir = options.getfieldvalue('qmudir','qmu'+str(os.getpid())) - # qmudir = ['qmu_' datestr(now,'yyyymmdd_HHMMSS')] - qmufile = options.getfieldvalue('qmufile','qmu') - # qmufile cannot be changed unless ????script.sh is also changed - overwrite = options.getfieldvalue('overwrite','n') - ivar = options.getfieldvalue('ivar',0) - iresp = options.getfieldvalue('iresp',0) - imethod = options.getfieldvalue('imethod',0) - iparams = options.getfieldvalue('iparams',0) + print('preprocessing dakota inputs') + qmudir = options.getfieldvalue('qmudir', 'qmu' + str(os.getpid())) + # qmudir = ['qmu_' datestr(now, 'yyyymmdd_HHMMSS')] + qmufile = options.getfieldvalue('qmufile', 'qmu') + # qmufile cannot be changed unless ????script.sh is also changed + overwrite = options.getfieldvalue('overwrite', 'n') + options.addfielddefault('ivar', 0) + options.addfielddefault('iresp', 0) + options.addfielddefault('imethod', 0) + options.addfielddefault('iparams', 0) - # first create temporary directory in which we will work - if strncmpi(overwrite,'y',1): - os.system('rm -rf '+qmudir+'/*') - else: - # does the directory exist? if so, then error out - if os.path.isdir(qmudir): - raise RuntimeError('Existing '+str(options.qmudir)+' directory, cannot overwrite. Specify "overwrite","y" option in solve arguments.') - - # os.makedirs() raises error when dir exists, matlab's mkdir() does not - if not os.path.isdir(qmudir): - os.makedirs(qmudir) - os.chdir(qmudir) + # first create temporary directory in which we will work + if strncmpi(overwrite, 'y', 1): + os.system('rm -rf ' + qmudir + '/* ') + else: + # does the directory exist? if so, then error out + if os.path.isdir(qmudir): + raise RuntimeError('Existing ' + str(options.qmudir) + ' directory, cannot overwrite. Specify "overwrite", "y" option in solve arguments.') - # when running in library mode, the in file needs to be called md.miscellaneous.name.qmu.in - qmufile=md.miscellaneous.name + # os.makedirs() raises error when dir exists, matlab's mkdir() does not + if not os.path.isdir(qmudir): + os.makedirs(qmudir) + os.chdir(qmudir) - # retrieve variables and resposnes for this particular analysis. - #print type(md.qmu.variables) - #print md.qmu.variables.__dict__ - #print ivar - variables=md.qmu.variables#[ivar] - responses=md.qmu.responses#[iresp] + # when running in library mode, the in file needs to be called md.miscellaneous.name.qmu.in + qmufile = md.miscellaneous.name - # expand variables and responses - #print variables.__dict__ - #print responses.__dict__ - variables=expandvariables(md,variables) - responses=expandresponses(md,responses) + # retrieve variables and resposnes for this particular analysis. + #print type(md.qmu.variables) + #print md.qmu.variables.__dict__ + #print ivar + variables = md.qmu.variables #[ivar] + responses = md.qmu.responses #[iresp] - # go through variables and responses, and check they don't have more than - # md.qmu.numberofpartitions values. Also determine numvariables and numresponses - #[[[ - numvariables=0 - variable_fieldnames=fieldnames(variables) - for i in range(len(variable_fieldnames)): - field_name=variable_fieldnames[i] - fieldvariables=vars(variables)[field_name] - for j in range(np.size(fieldvariables)): - if strncmpi(fieldvariables[j].descriptor,'\'scaled_',8) and str2int(fieldvariables[j].descriptor,'last')>md.qmu.numberofpartitions: - raise RuntimeError('preqmu error message: one of the expanded variables has more values than the number of partitions (setup in md.qmu.numberofpartitions)') + # expand variables and responses + #print variables.__dict__ + #print responses.__dict__ + variables = expandvariables(md, variables) + responses = expandresponses(md, responses) - numvariables=numvariables+np.size(vars(variables)[field_name]) + # go through variables and responses, and check they don't have more than + # md.qmu.numberofpartitions values. Also determine numvariables and numresponses + #[[[ + numvariables = 0 + variable_fieldnames = fieldnames(variables) + for i in range(len(variable_fieldnames)): + field_name = variable_fieldnames[i] + fieldvariables = vars(variables)[field_name] + for j in range(np.size(fieldvariables)): + if strncmpi(fieldvariables[j].descriptor, '\'scaled_', 8) and str2int(fieldvariables[j].descriptor, 'last') > md.qmu.numberofpartitions: + raise RuntimeError('preqmu error message: one of the expanded variables has more values than the number of partitions (setup in md.qmu.numberofpartitions)') - numresponses=0 - response_fieldnames=fieldnames(responses) - for i in range(len(response_fieldnames)): - field_name=response_fieldnames[i] - fieldresponses=vars(responses)[field_name] - for j in range(np.size(fieldresponses)): - if strncmpi(fieldresponses[j].descriptor,'\'scaled_',8) and str2int(fieldresponses[j].descriptor,'last')>md.qmu.numberofpartitions: - raise RuntimeError('preqmu error message: one of the expanded responses has more values than the number of partitions (setup in md.qmu.numberofpartitions)') + numvariables = numvariables + np.size(vars(variables)[field_name]) - numresponses=numresponses+np.size(vars(responses)[field_name]) + numresponses = 0 + response_fieldnames = fieldnames(responses) + for i in range(len(response_fieldnames)): + field_name = response_fieldnames[i] + fieldresponses = vars(responses)[field_name] + for j in range(np.size(fieldresponses)): + if strncmpi(fieldresponses[j].descriptor, '\'scaled_', 8) and str2int(fieldresponses[j].descriptor, 'last') > md.qmu.numberofpartitions: + raise RuntimeError('preqmu error message: one of the expanded responses has more values than the number of partitions (setup in md.qmu.numberofpartitions)') - #]]] + numresponses = numresponses + np.size(vars(responses)[field_name]) - # create in file for dakota - #dakota_in_data(md.qmu.method[imethod],variables,responses,md.qmu.params[iparams],qmufile) - dakota_in_data(md.qmu.method,variables,responses,md.qmu.params,qmufile) + #]]] -#====================================================================================# - #REMOVED FOR DEBUGGING ONLY: - #os.system('rm -rf '+str(md.miscellaneous.name)+'.py') -#====================================================================================# + # create in file for dakota + #dakota_in_data(md.qmu.method[imethod], variables, responses, md.qmu.params[iparams], qmufile) + dakota_in_data(md.qmu.method, variables, responses, md.qmu.params, qmufile) - # build a list of variables and responses descriptors. the list is not expanded. - #[[[ - variabledescriptors=[] - # variable_fieldnames=fieldnames(md.qmu.variables[ivar]) - variable_fieldnames=fieldnames(md.qmu.variables) - for i in range(len(variable_fieldnames)): - field_name=variable_fieldnames[i] - #fieldvariables=vars(md.qmu.variables[ivar])[field_name] - fieldvariables=vars(md.qmu.variables)[field_name] - if type(fieldvariables) in [list,np.ndarray]: - for j in range(np.size(fieldvariables)): - variabledescriptors.append(fieldvariables[j].descriptor) - else: - variabledescriptors.append(fieldvariables.descriptor) + #==================================================================================== # + #REMOVED FOR DEBUGGING ONLY: + #os.system('rm -rf ' + str(md.miscellaneous.name) + '.py') + #==================================================================================== # + # build a list of variables and responses descriptors. the list is not expanded. + #{{{ + variabledescriptors = [] + # variable_fieldnames = fieldnames(md.qmu.variables[ivar]) + variable_fieldnames = fieldnames(md.qmu.variables) + for i in range(len(variable_fieldnames)): + field_name = variable_fieldnames[i] + #fieldvariables = vars(md.qmu.variables[ivar])[field_name] + fieldvariables = vars(md.qmu.variables)[field_name] + if type(fieldvariables) in [list, np.ndarray]: + for j in range(np.size(fieldvariables)): + variabledescriptors.append(fieldvariables[j].descriptor) + else: + variabledescriptors.append(fieldvariables.descriptor) - responsedescriptors=[] - # response_fieldnames=fieldnames(md.qmu.responses[iresp]) - response_fieldnames=fieldnames(md.qmu.responses) - for i in range(len(response_fieldnames)): - field_name=response_fieldnames[i] - #fieldresponses=vars(md.qmu.responses[iresp])[field_name] - fieldresponses=vars(md.qmu.responses)[field_name] - for j in range(np.size(fieldresponses)): - responsedescriptors.append(fieldresponses[j].descriptor) - + responsedescriptors = [] + # response_fieldnames = fieldnames(md.qmu.responses[iresp]) + response_fieldnames = fieldnames(md.qmu.responses) + for i in range(len(response_fieldnames)): + field_name = response_fieldnames[i] + #fieldresponses = vars(md.qmu.responses[iresp])[field_name] + fieldresponses = vars(md.qmu.responses)[field_name] + for j in range(np.size(fieldresponses)): + responsedescriptors.append(fieldresponses[j].descriptor) + #}}} - #]]] + # register the fields that will be needed by the Qmu model. + md.qmu.numberofresponses = numresponses + md.qmu.variabledescriptors = variabledescriptors + md.qmu.responsedescriptors = responsedescriptors - # register the fields that will be needed by the Qmu model. - md.qmu.numberofresponses=numresponses - md.qmu.variabledescriptors=variabledescriptors - md.qmu.responsedescriptors=responsedescriptors + # now, we have to provide all the info necessary for the solutions to compute the + # responses. For ex, if mass_flux is a response, we need a profile of points. + # For a misfit, we need the observed velocity, etc ... + md = process_qmu_response_data(md) - # now, we have to provide all the info necessary for the solutions to compute the - # responses. For ex, if mass_flux is a response, we need a profile of points. - # For a misfit, we need the observed velocity, etc ... - md=process_qmu_response_data(md) - - return md + return md Index: /issm/trunk-jpl/src/m/qmu/process_qmu_response_data.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/process_qmu_response_data.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/process_qmu_response_data.py (revision 24213) @@ -2,50 +2,49 @@ import numpy as np from MeshProfileIntersection import * - from helpers import empty_nd_list + def process_qmu_response_data(md): - ''' -PROCESS_QMU_RESPONSE_DATA - process any data necessary for the solutions to process the data. + ''' +PROCESS_QMU_RESPONSE_DATA - process any data necessary for the solutions to process the data. - Usage: md=process_qmu_response_data(md) - - See also PREQMU, PRESOLVE + Usage: md = process_qmu_response_data(md) + + See also PREQMU, PRESOLVE ''' - # preliminary data - process_mass_flux_profiles=0 - num_mass_flux=0 + # preliminary data + process_mass_flux_profiles = 0 + num_mass_flux = 0 - # loop through response descriptors, and act accordingly - for i in range(np.size(md.qmu.responsedescriptors)): + # loop through response descriptors, and act accordingly + for i in range(np.size(md.qmu.responsedescriptors)): - # Do we have to process mass flux profiles? - if strncmpi(md.qmu.responsedescriptors[i],'indexed_MassFlux',16): - num_mass_flux+=1 - process_mass_flux_profiles=1 + # Do we have to process mass flux profiles? + if strncmpi(md.qmu.responsedescriptors[i], 'indexed_MassFlux', 16): + num_mass_flux += 1 + process_mass_flux_profiles = 1 - # deal with mass flux profiles - if process_mass_flux_profiles: - # we need a profile of points on which to compute the mass_flux, is it here? - if type(md.qmu.mass_flux_profiles) == float and np.isnan(md.qmu.mass_flux_profiles): - raise RuntimeError('process_qmu_response_data error message: could not find a mass_flux exp profile!') - - if type(md.qmu.mass_flux_profiles) != list: - raise RuntimeError('process_qmu_response_data error message: qmu_mass_flux_profiles field should be a list of domain outline names') - - if np.size(md.qmu.mass_flux_profiles) == 0: - raise RuntimeError('process_qmu_response_data error message: qmu_mass_flux_profiles cannot be empty!') - - if num_mass_flux!=np.size(md.qmu.mass_flux_profiles): - raise RuntimeError('process_qmu_response_data error message: qmu_mass_flux_profiles should be of the same size as the number of MassFlux responses asked for in the Qmu analysis') - - # ok, process the domains named in qmu_mass_flux_profiles, - # to build a list of segments (MatArray) - md.qmu.mass_flux_segments = empty_nd_list((num_mass_flux,1)) + # deal with mass flux profiles + if process_mass_flux_profiles: + # we need a profile of points on which to compute the mass_flux, is it here? + if type(md.qmu.mass_flux_profiles) == float and np.isnan(md.qmu.mass_flux_profiles): + raise RuntimeError('process_qmu_response_data error message: could not find a mass_flux exp profile!') - for i in range(num_mass_flux): - md.qmu.mass_flux_segments[i]=np.array(MeshProfileIntersection(md.mesh.elements,md.mesh.x,md.mesh.y,md.qmu.mass_flux_profile_directory+'/'+md.qmu.mass_flux_profiles[i])[0]) + if type(md.qmu.mass_flux_profiles) != list: + raise RuntimeError('process_qmu_response_data error message: qmu_mass_flux_profiles field should be a list of domain outline names') - return md + if np.size(md.qmu.mass_flux_profiles) == 0: + raise RuntimeError('process_qmu_response_data error message: qmu_mass_flux_profiles cannot be empty!') + if num_mass_flux != np.size(md.qmu.mass_flux_profiles): + raise RuntimeError('process_qmu_response_data error message: qmu_mass_flux_profiles should be of the same size as the number of MassFlux responses asked for in the Qmu analysis') + + # ok, process the domains named in qmu_mass_flux_profiles, + # to build a list of segments (MatArray) + md.qmu.mass_flux_segments = empty_nd_list((num_mass_flux, 1)) + + for i in range(num_mass_flux): + md.qmu.mass_flux_segments[i] = np.array(MeshProfileIntersection(md.mesh.elements, md.mesh.x, md.mesh.y, md.qmu.mass_flux_profile_directory + '/' + md.qmu.mass_flux_profiles[i])[0]) + + return md Index: /issm/trunk-jpl/src/m/qmu/rlev_write.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/rlev_write.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/rlev_write.py (revision 24213) @@ -4,101 +4,100 @@ from vector_write import * from param_write import * - #import relevent qmu classes from MatlabArray import * -def rlevi_write(fidi,ltype,levels): - ''' + +def rlevi_write(fidi, ltype, levels): + ''' function to each type of response level ''' - fidi.write('\t num_'+str(ltype)+' =') - levels = np.array(levels) + fidi.write('\t num_' + str(ltype) + ' = ') + levels = np.array(levels) - if len(levels) > 0 and type(levels[0]) in [list,np.ndarray]: - for i in range(len(levels)): - fidi.write(' ' + str(len(levels[i]))) - else: - fidi.write(' ' + str(len(levels))) + if len(levels) > 0 and type(levels[0]) in [list, np.ndarray]: + for i in range(len(levels)): + fidi.write(' ' + str(len(levels[i]))) + else: + fidi.write(' ' + str(len(levels))) - fidi.write('\n') - fidi.write('\t '+str(ltype)+' =\n') + fidi.write('\n') + fidi.write('\t ' + str(ltype) + ' =\n') - # check if we have a vector of vectors, or just 1 vector - if np.size(levels) > 0 and type(levels[0]) in [list,np.ndarray]: - for i in range(len(levels)): - if len(levels[i]) != 0: - vector_write(fidi,'\t ',levels[i],8,76) - else: - vector_write(fidi,'\t ',levels,8,76) + # check if we have a vector of vectors, or just 1 vector + if np.size(levels) > 0 and type(levels[0]) in [list, np.ndarray]: + for i in range(len(levels)): + if len(levels[i]) != 0: + vector_write(fidi, '\t ', levels[i], 8, 76) + else: + vector_write(fidi, '\t ', levels, 8, 76) - return + return -def rlev_write(fidi,dresp,cstring,params): - ''' + +def rlev_write(fidi, dresp, cstring, params): + ''' function to write response levels ''' - from response_function import response_function + from response_function import response_function - if len(dresp) == 0 or len(fieldnames(dresp[0])) == 0: - return + if len(dresp) == 0 or len(fieldnames(dresp[0])) == 0: + return - if type(dresp) in [list,np.ndarray]: - if len(dresp) > 0 and type(dresp[0]) == struct: - func = eval(cstring) - else: - func = type(dresp[0]) - elif type(dresp) == struct: - # type is defined within struct's contents - func = None - dresp = [dresp] - else: - func = type(dresp) - dresp = [dresp] + if type(dresp) in [list, np.ndarray]: + if len(dresp) > 0 and type(dresp[0]) == struct: + func = eval(cstring) + else: + func = type(dresp[0]) + elif type(dresp) == struct: + # type is defined within struct's contents + func = None + dresp = [dresp] + else: + func = type(dresp) + dresp = [dresp] - # put responses into lists for writing + # put responses into lists for writing - nresp = 0 - respl = [] - probl = [] - rell = [] - grell = [] + nresp = 0 + respl = [] + probl = [] + rell = [] + grell = [] - # assume all fields in dvar[0:n] are consistent (ex. all are normal_uncertain) - # which will always be true since this is called per field - fnames=fieldnames(dresp[0]) - for j in range(len(dresp)): - for i in range(np.size(fnames)): - if func == None: - func = type(vars(dresp[j])[fnames[i]]) + # assume all fields in dvar[0:n] are consistent (ex. all are normal_uncertain) + # which will always be true since this is called per field + fnames = fieldnames(dresp[0]) + for j in range(len(dresp)): + for i in range(np.size(fnames)): + if func is None: + func = type(vars(dresp[j])[fnames[i]]) - nresp+=1 - [respli,probli,relli,grelli]=func.prop_levels([vars(dresp[j])[fnames[i]]]) - respl.extend(respli) - probl.extend(probli) - rell.extend(relli) - grell.extend(grelli) + nresp += 1 + [respli, probli, relli, grelli] = func.prop_levels([vars(dresp[j])[fnames[i]]]) + respl.extend(respli) + probl.extend(probli) + rell.extend(relli) + grell.extend(grelli) + # write response levels + respl = allempty(respl) + probl = allempty(probl) + rell = allempty(rell) + grell = allempty(grell) - # write response levels + param_write(fidi, '\t ', 'distribution', ' ', '\n', params) + if len(respl) != 0: + rlevi_write(fidi, 'response_levels', respl) + param_write(fidi, '\t ', 'compute', ' ', '\n', params) - respl=allempty(respl) - probl=allempty(probl) - rell =allempty(rell) - grell=allempty(grell) + if len(probl) != 0: + rlevi_write(fidi, 'probability_levels', probl) - param_write(fidi,'\t ','distribution',' ','\n',params) - if len(respl) != 0: - rlevi_write(fidi,'response_levels',respl) - param_write(fidi,'\t ','compute',' ','\n',params) + if len(rell) != 0: + rlevi_write(fidi, 'reliability_levels', rell) - if len(probl) != 0: - rlevi_write(fidi,'probability_levels',probl) + if len(grell) != 0: + rlevi_write(fidi, 'gen_reliability_levels', grell) - if len(rell) != 0: - rlevi_write(fidi,'reliability_levels',rell) - - if len(grell) != 0: - rlevi_write(fidi,'gen_reliability_levels',grell) - - return + return Index: /issm/trunk-jpl/src/m/qmu/rlist_write.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/rlist_write.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/rlist_write.py (revision 24213) @@ -1,4 +1,3 @@ import numpy as np - #move this later from helpers import * @@ -7,88 +6,87 @@ from response_function import * -def rlist_write(fidi,cstring,cstring2,dresp,rdesc): - ''' + +def rlist_write(fidi, cstring, cstring2, dresp, rdesc): + ''' function to write response list ''' - if dresp == None: - return + if dresp is None: + return - func = eval(cstring) + func = eval(cstring) - if type(dresp) not in [list,np.ndarray]: - dresp = [dresp] + if type(dresp) not in [list, np.ndarray]: + dresp = [dresp] - # put responses into lists for writing - # (and accumulate descriptors into list for subsequent writing) + # put responses into lists for writing + # (and accumulate descriptors into list for subsequent writing) - nresp=0 - pstype =[] - pscale =[] - pweight=[] - plower =[] - pupper =[] - ptarget=[] + nresp = 0 + pstype = [] + pscale = [] + pweight = [] + plower = [] + pupper = [] + ptarget = [] - # assume all fields in dvar[0:n] are consistent (ex. all are normal_uncertain) - # which will always be true since this is called per field - fnames=fieldnames(dresp[0]) - for j in range(len(dresp)): - for i in range(np.size(fnames)): - nresp=nresp+np.size(vars(dresp[j])[fnames[i]]) - pstype.extend( func.prop_stype( vars(dresp[j])[fnames[i]])) - pscale.extend( func.prop_scale( vars(dresp[j])[fnames[i]])) - pweight.extend(func.prop_weight(vars(dresp[j])[fnames[i]])) - plower.extend( func.prop_lower( vars(dresp[j])[fnames[i]])) - pupper.extend( func.prop_upper( vars(dresp[j])[fnames[i]])) - ptarget.extend(func.prop_target(vars(dresp[j])[fnames[i]])) - rdesc.extend( func.prop_desc( vars(dresp[j])[fnames[i]],fnames[i])) + # assume all fields in dvar[0:n] are consistent (ex. all are normal_uncertain) + # which will always be true since this is called per field + fnames = fieldnames(dresp[0]) + for j in range(len(dresp)): + for i in range(np.size(fnames)): + nresp = nresp + np.size(vars(dresp[j])[fnames[i]]) + pstype.extend(func.prop_stype(vars(dresp[j])[fnames[i]])) + pscale.extend(func.prop_scale(vars(dresp[j])[fnames[i]])) + pweight.extend(func.prop_weight(vars(dresp[j])[fnames[i]])) + plower.extend(func.prop_lower(vars(dresp[j])[fnames[i]])) + pupper.extend(func.prop_upper(vars(dresp[j])[fnames[i]])) + ptarget.extend(func.prop_target(vars(dresp[j])[fnames[i]])) + rdesc.extend(func.prop_desc(vars(dresp[j])[fnames[i]], fnames[i])) + # write responses + print(' Writing ' + str(nresp) + ' ' + cstring + ' responses.') - # write responses + if strcmp(cstring, 'calibration_terms') == 1: + fidi.write('\t' + cstring + ' = ' + str(nresp) + '\n') - print(' Writing '+str(nresp)+' '+cstring+' responses.') + else: + fidi.write('\tnum_' + cstring + 's = ' + str(nresp) + '\n') - if strcmp(cstring,'calibration_terms')==1: - fidi.write('\t'+cstring+' = '+str(nresp)+'\n') - - else: - fidi.write('\tnum_'+cstring+'s = '+str(nresp)+'\n') + if not isempty(pstype): + fidi.write('\t ' + cstring2 + '_scale_types =\n') + vector_write(fidi, '\t ', pstype, 6, 76) - if not isempty(pstype): - fidi.write('\t '+cstring2+'_scale_types =\n') - vector_write(fidi,'\t ',pstype ,6,76) + if not isempty(pscale): + fidi.write('\t ' + cstring2 + '_scales =\n') + vector_write(fidi, '\t ', pscale, 6, 76) - if not isempty(pscale): - fidi.write('\t '+cstring2+'_scales =\n') - vector_write(fidi,'\t ',pscale ,6,76) + if not isempty(pweight): + if cstring2 == 'objective_function': + fidi.write('\t multi_objective_weights =\n') + vector_write(fidi, '\t ', pweight, 6, 76) + elif cstring2 == 'least_squares_term': + fidi.write('\t least_squares_weights =\n') + vector_write(fidi, '\t ', pweight, 6, 76) - if not isempty(pweight): - if cstring2 == 'objective_function': - fidi.write('\t multi_objective_weights =\n') - vector_write(fidi,'\t ',pweight,6,76) - elif cstring2 == 'least_squares_term': - fidi.write('\t least_squares_weights =\n') - vector_write(fidi,'\t ',pweight,6,76) + if not isempty(plower): + fidi.write('\t ' + cstring2 + '_lower_bounds =\n') + vector_write(fidi, '\t ', plower, 6, 76) - if not isempty(plower): - fidi.write('\t '+cstring2+'_lower_bounds =\n') - vector_write(fidi,'\t ',plower ,6,76) + if not isempty(pupper): + fidi.write('\t ' + cstring2 + '_upper_bounds =\n') + vector_write(fidi, '\t ', pupper, 6, 76) - if not isempty(pupper): - fidi.write('\t '+cstring2+'_upper_bounds =\n') - vector_write(fidi,'\t ',pupper ,6,76) + if not isempty(ptarget): + fidi.write('\t ' + cstring2 + '_targets =\n') + vector_write(fidi, '\t ', ptarget, 6, 76) - if not isempty(ptarget): - fidi.write('\t '+cstring2+'_targets =\n') - vector_write(fidi,'\t ',ptarget,6,76) + # because qmu in files need '' for strings + for i in range(len(rdesc)): + if type(rdesc[i]) in [list, np.ndarray]: + for j in range(len(rdesc[i])): + rdesc[i][j] = "'" + rdesc[i][j] + "'" + else: + rdesc[i] = "'" + rdesc[i] + "'" - # because qmu in files need '' for strings - for i in range(len(rdesc)): - if type(rdesc[i]) in [list,np.ndarray]: - for j in range(len(rdesc[i])): - rdesc[i][j] = "'" + rdesc[i][j] + "'" - else: - rdesc[i] = "'" + rdesc[i] + "'" - - return rdesc + return rdesc Index: /issm/trunk-jpl/src/m/qmu/setupdesign/QmuSetupResponses.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/setupdesign/QmuSetupResponses.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/setupdesign/QmuSetupResponses.py (revision 24213) @@ -2,22 +2,23 @@ from copy import deepcopy -def QmuSetupResponses(md,dresp,responses): - #get descriptor - descriptor=responses.descriptor +def QmuSetupResponses(md, dresp, responses): - #decide whether this is a distributed response, which will drive whether we expand it into npart values, - #or if we just carry it forward as is. + #get descriptor + descriptor = responses.descriptor - #ok, key off according to type of descriptor: - if strncmp(descriptor,'scaled_',7): - #we have a scaled response, expand it over the partition. - #ok, dealing with semi-discrete distributed response. Distribute according to how many - #partitions we want - for j in range(md.qmu.numberofpartitions): - dresp.append(deepcopy(responses)) - dresp[-1].descriptor=str(responses.descriptor)+'_'+str(j+1) - else: - dresp.append(responses) + #decide whether this is a distributed response, which will drive whether we expand it into npart values, + #or if we just carry it forward as is. - return dresp + #ok, key off according to type of descriptor: + if strncmp(descriptor, 'scaled_', 7): + #we have a scaled response, expand it over the partition. + #ok, dealing with semi - discrete distributed response. Distribute according to how many + #partitions we want + for j in range(md.qmu.numberofpartitions): + dresp.append(deepcopy(responses)) + dresp[-1].descriptor = str(responses.descriptor) + '_' + str(j + 1) + else: + dresp.append(responses) + + return dresp Index: /issm/trunk-jpl/src/m/qmu/setupdesign/QmuSetupVariables.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/setupdesign/QmuSetupVariables.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/setupdesign/QmuSetupVariables.py (revision 24213) @@ -1,79 +1,76 @@ from MatlabFuncs import * -from uniform_uncertain import* +from uniform_uncertain import * from normal_uncertain import * from copy import deepcopy -def QmuSetupVariables(md,dvar,variables): - #get descriptor - descriptor=variables.descriptor +def QmuSetupVariables(md, dvar, variables): - #decide whether this is a distributed variable, which will drive whether we expand it into npart values, - #or if we just carry it forward as is. + #get descriptor + descriptor = variables.descriptor - #ok, key off according to type of descriptor: - if strncmp(descriptor,'scaled_',7): - #we have a scaled variable, expand it over the partition. + #decide whether this is a distributed variable, which will drive whether we expand it into npart values, + #or if we just carry it forward as is. - if isinstance(variables,uniform_uncertain): - if ((type(variables.lower) in [list,np.ndarray] and len(variables.lower) > md.qmu.numberofpartitions) or (type(variables.upper) in [list,np.ndarray] and len(variables.upper) > md.qmu.numberofpartitions)): - raise RuntimeError('QmuSetupDesign error message: upper and lower should be either a scalar or a "npart" length vector') - - elif isinstance(variables,normal_uncertain): - if type(variables.stddev) in [list,np.ndarray] and len(variables.stddev) > md.qmu.numberofpartitions: - raise RuntimeError('QmuSetupDesign error message: stddev should be either a scalar or a "npart" length vector') + #ok, key off according to type of descriptor: + if strncmp(descriptor, 'scaled_', 7): + #we have a scaled variable, expand it over the partition. + if isinstance(variables, uniform_uncertain): + if ((type(variables.lower) in [list, np.ndarray] and len(variables.lower) > md.qmu.numberofpartitions) or (type(variables.upper) in [list, np.ndarray] and len(variables.upper) > md.qmu.numberofpartitions)): + raise RuntimeError('QmuSetupDesign error message: upper and lower should be either a scalar or a "npart" length vector') - #ok, dealing with semi-discrete distributed variable. Distribute according to how many - #partitions we want + elif isinstance(variables, normal_uncertain): + if type(variables.stddev) in [list, np.ndarray] and len(variables.stddev) > md.qmu.numberofpartitions: + raise RuntimeError('QmuSetupDesign error message: stddev should be either a scalar or a "npart" length vector') - for j in range(md.qmu.numberofpartitions): - dvar.append(deepcopy(variables)) - # "'" is because qmu.in files need for strings to be in actual '' - # must also account for whether we are given 1 instance or an array of instances + #ok, dealing with semi - discrete distributed variable. Distribute according to how many + #partitions we want + for j in range(md.qmu.numberofpartitions): + dvar.append(deepcopy(variables)) + # "'" is because qmu.in files need for strings to be in actual '' + # must also account for whether we are given 1 instance or an array of instances + # handle descriptors for everything + if type(dvar[-1].descriptor) in [list, np.ndarray] and len(variables.descriptor) > 1 and len(variables.upper) != md.qmu.numberofpartitions: + if type(variables.descriptor) == np.ndarray: + dvar[-1].descriptor = np.append(dvar[-1].descriptor, "'" + str(variables.descriptor) + '_' + str(j + 1) + "'") + else: + dvar[-1].descriptor.append("'" + str(variables.descriptor) + '_' + str(j + 1) + "'") + else: + dvar[-1].descriptor = "'" + str(variables.descriptor) + '_' + str(j + 1) + "'" - # handle descriptors for everything - if type(dvar[-1].descriptor) in [list,np.ndarray] and len(variables.descriptor) > 1 and len(variables.upper) != md.qmu.numberofpartitions: - if type(variables.descriptor) == np.ndarray: - dvar[-1].descriptor = np.append(dvar[-1].descriptor,"'"+str(variables.descriptor)+'_'+str(j+1)+"'") - else: - dvar[-1].descriptor.append("'"+str(variables.descriptor)+'_'+str(j+1)+"'") - else: - dvar[-1].descriptor = "'"+str(variables.descriptor)+'_'+str(j+1)+"'" + # handle uniform_uncertain + if isinstance(variables, uniform_uncertain): + if type(variables.lower) in [list, np.ndarray] and len(variables.lower) > 1 and len(variables.upper) != md.qmu.numberofpartitions: + if type(variables.lower) == np.ndarray: + dvar[-1].lower = np.append(dvar[-1].lower, variables.lower[j]) + else: + dvar[-1].lower.append(variables.lower[j]) + else: + dvar[-1].lower = variables.lower - # handle uniform_uncertain - if isinstance(variables,uniform_uncertain): - if type(variables.lower) in [list,np.ndarray] and len(variables.lower) > 1 and len(variables.upper) != md.qmu.numberofpartitions: - if type(variables.lower) == np.ndarray: - dvar[-1].lower = np.append(dvar[-1].lower, variables.lower[j]) - else: - dvar[-1].lower.append(variables.lower[j]) - else: - dvar[-1].lower = variables.lower + if type(variables.upper) in [list, np.ndarray] and len(variables.upper) > 1 and len(variables.upper) != md.qmu.numberofpartitions: + if type(variables.upper) == np.ndarray: + dvar[-1].upper = np.append(dvar[-1].upper, variables.upper[j]) + else: + dvar[-1].upper.append(variables.upper[j]) + else: + dvar[-1].upper = variables.upper - if type(variables.upper) in [list,np.ndarray] and len(variables.upper) > 1 and len(variables.upper) != md.qmu.numberofpartitions: - if type(variables.upper) == np.ndarray: - dvar[-1].upper = np.append(dvar[-1].upper, variables.upper[j]) - else: - dvar[-1].upper.append(variables.upper[j]) - else: - dvar[-1].upper = variables.upper + # handle normal_uncertain + elif isinstance(variables, normal_uncertain): + if type(variables.stddev) in [list, np.ndarray] and len(variables.stddev) > 1 and len(variables.upper) != md.qmu.numberofpartitions: + if type(variables.stddev) == np.ndarray: + dvar[-1].stddev = np.append(dvar[-1].stddev, variables.stddev[j]) + else: + dvar[-1].stddev.append(variables.stddev[j]) + else: + dvar[-1].stddev = variables.stddev - # handle normal_uncertain - elif isinstance(variables,normal_uncertain): - if type(variables.stddev) in [list,np.ndarray] and len(variables.stddev) > 1 and len(variables.upper) != md.qmu.numberofpartitions: - if type(variables.stddev) == np.ndarray: - dvar[-1].stddev = np.append(dvar[-1].stddev, variables.stddev[j]) - else: - dvar[-1].stddev.append(variables.stddev[j]) - else: - dvar[-1].stddev = variables.stddev + # running with a single instance, and therefore length 1 arrays of qmu classes + else: + dvar.append(variables) + # text parsing in dakota requires literal "'identifier'" not just "identifier" + for v in dvar: + v.descriptor = "'" + str(v.descriptor) + "'" - # running with a single instance, and therefore length 1 arrays of qmu classes - else: - dvar.append(variables) - # text parsing in dakota requires literal "'identifier'" not just "identifier" - for v in dvar: - v.descriptor = "'"+str(v.descriptor)+"'" - - return dvar - + return dvar Index: /issm/trunk-jpl/src/m/qmu/vector_write.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/vector_write.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/vector_write.py (revision 24213) @@ -1,47 +1,48 @@ import numpy as np -def vector_write(fidi,sbeg,vec,nmax,cmax): - ''' + +def vector_write(fidi, sbeg, vec, nmax, cmax): + ''' function to write a vector on multiple lines ''' - if nmax == None: - nmax=np.inf + if nmax is None: + nmax = np.inf - if cmax == None: - cmax=np.inf + if cmax is None: + cmax = np.inf - # set up first iteration - svec =[] - nitem=nmax - lsvec=cmax + # set up first iteration + svec = [] + nitem = nmax + lsvec = cmax - # transpose vector from column-wise to row-wise - vec=np.array(vec).conj().T + # transpose vector from column - wise to row - wise + vec = np.array(vec).conj().T - # assemble each line, flushing when necessary - for i in range(np.size(vec,0)): + # assemble each line, flushing when necessary + for i in range(np.size(vec, 0)): - # [[1],[1],[1]...] should be [1,1,1,...] - if type(vec[i]) in [list,np.ndarray] and len(vec[i]) == 1: - sitem = str(vec[i][0]) - else: - sitem = str(vec[i]) + # [[1], [1], [1]...] should be [1, 1, 1, ...] + if type(vec[i]) in [list, np.ndarray] and len(vec[i]) == 1: + sitem = str(vec[i][0]) + else: + sitem = str(vec[i]) - nitem=nitem+1 - lsvec=lsvec+1+len(sitem) + nitem = nitem + 1 + lsvec = lsvec + 1 + len(sitem) - if (nitem <= nmax) and (lsvec <= cmax): - svec=str(svec)+' '+str(sitem) - else: - if len(svec) > 0: - fidi.write(str(svec)+'\n') - - svec=str(sbeg)+str(sitem) - nitem=1 - lsvec=len(svec) - - # flush buffer at , if necessary - if len(svec) > 0: - fidi.write(str(svec)+'\n') + if (nitem <= nmax) and (lsvec <= cmax): + svec = str(svec) + ' ' + str(sitem) + else: + if len(svec) > 0: + fidi.write(str(svec) + '\n') - return + svec = str(sbeg) + str(sitem) + nitem = 1 + lsvec = len(svec) + + # flush buffer at , if necessary + if len(svec) > 0: + fidi.write(str(svec) + '\n') + + return Index: /issm/trunk-jpl/src/m/qmu/vlist_write.py =================================================================== --- /issm/trunk-jpl/src/m/qmu/vlist_write.py (revision 24212) +++ /issm/trunk-jpl/src/m/qmu/vlist_write.py (revision 24213) @@ -2,129 +2,129 @@ #move this later from helpers import * - from vector_write import * - from uniform_uncertain import * from normal_uncertain import * -def check(a,l,p): - '''in the event that a and b are equal, return a; -in the event that a and b are not equal, return their concatenation - This is used for when both the input dvar and the 'cstring' variables have non-1 length -''' +def check(a, l, p): + '''in the event that a and b are equal, return a + in the event that a and b are not equal, return their concatenation - if np.size(a) == l: - if p == 0: - if type(a) in [list,np.ndarray]: - return a - else: - return [a] - else: - return [] - elif np.size(a) == 1: - if type(a) in [list,np.ndarray]: - return a - else: - return [a] - elif np.size(a) == 0: - return [] - else: - raise RuntimeError('ERROR vlist_write: input field had size '+str(np.size(a))+'; must have size of 0, 1, or match size of provided dvar ('+str(l)+').') + This is used for when both the input dvar and the 'cstring' variables have non - 1 length + ''' - return + if np.size(a) == l: + if p == 0: + if type(a) in [list, np.ndarray]: + return a + else: + return [a] + else: + return [] + elif np.size(a) == 1: + if type(a) in [list, np.ndarray]: + return a + else: + return [a] + elif np.size(a) == 0: + return [] + else: + raise RuntimeError('ERROR vlist_write: input field had size ' + str(np.size(a)) + '; must have size of 0, 1, or match size of provided dvar (' + str(l) + ').') -def vlist_write(fidi,cstring,cstring2,dvar): - ''' -function to write variable list -''' - if dvar == None: - return - #from uniform_uncertain import * - func = eval(cstring) + return - # put variables into lists for writing - if type(dvar) not in [list,np.ndarray]: - dvar = [dvar] +def vlist_write(fidi, cstring, cstring2, dvar): + ''' + function to write variable list + ''' + if dvar is None: + return + #from uniform_uncertain import * + func = eval(cstring) - # assume all fields in dvar[0:n] are consistent (ex. all are normal_uncertain) - # which will always be true since this vlist_write is called per field - fnames=fieldnames(dvar[0]) + # put variables into lists for writing - nvar=0 - pinitpt=[[] for i in range(len(fnames))] - plower =[[] for i in range(len(fnames))] - pupper =[[] for i in range(len(fnames))] - pmean =[[] for i in range(len(fnames))] - pstddev=[[] for i in range(len(fnames))] - pinitst=[[] for i in range(len(fnames))] - pstype =[[] for i in range(len(fnames))] - pscale =[[] for i in range(len(fnames))] - pdesc =[[] for i in range(len(fnames))] + if type(dvar) not in [list, np.ndarray]: + dvar = [dvar] - for i in range(len(fnames)): - nvar += len(dvar) - for j in dvar: - j = vars(j)[fnames[i]] - pinitpt[i].extend(check(func.prop_initpt(j),len(dvar),len(pinitpt[i]))) - plower[i].extend(check(func.prop_lower(j),len(dvar),len(plower[i]))) - pupper[i].extend(check(func.prop_upper(j),len(dvar),len(pupper[i]))) - pmean[i].extend(check(func.prop_mean(j),len(dvar),len(pmean[i]))) - pstddev[i].extend(check(func.prop_stddev(j),len(dvar),len(pstddev[i]))) - pinitst[i].extend(check(func.prop_initst(j),len(dvar),len(pinitst[i]))) - pstype[i].extend(check(func.prop_stype(j),len(dvar),len(pstype[i]))) - pscale[i].extend(check(func.prop_scale(j),len(dvar),len(pscale[i]))) - pdesc[i].extend(check(func.prop_desc(j,fnames[i]),len(dvar),len(pdesc[i]))) + # assume all fields in dvar[0:n] are consistent (ex. all are normal_uncertain) + # which will always be true since this vlist_write is called per field + fnames = fieldnames(dvar[0]) - pinitpt=allempty(pinitpt) - plower =allempty(plower) - pupper =allempty(pupper) - pmean =allempty(pmean) - pstddev=allempty(pstddev) - pinitst=allempty(pinitst) - pstype =allempty(pstype) - pscale =allempty(pscale) - pdesc =allempty(pdesc) + nvar = 0 + pinitpt = [[] for i in range(len(fnames))] + plower = [[] for i in range(len(fnames))] + pupper = [[] for i in range(len(fnames))] + pmean = [[] for i in range(len(fnames))] + pstddev = [[] for i in range(len(fnames))] + pinitst = [[] for i in range(len(fnames))] + pstype = [[] for i in range(len(fnames))] + pscale = [[] for i in range(len(fnames))] + pdesc = [[] for i in range(len(fnames))] - # write variables - print(' Writing '+str(nvar)+' '+cstring+' variables.') + for i in range(len(fnames)): + nvar += len(dvar) + for j in dvar: + j = vars(j)[fnames[i]] + pinitpt[i].extend(check(func.prop_initpt(j), len(dvar), len(pinitpt[i]))) + plower[i].extend(check(func.prop_lower(j), len(dvar), len(plower[i]))) + pupper[i].extend(check(func.prop_upper(j), len(dvar), len(pupper[i]))) + pmean[i].extend(check(func.prop_mean(j), len(dvar), len(pmean[i]))) + pstddev[i].extend(check(func.prop_stddev(j), len(dvar), len(pstddev[i]))) + pinitst[i].extend(check(func.prop_initst(j), len(dvar), len(pinitst[i]))) + pstype[i].extend(check(func.prop_stype(j), len(dvar), len(pstype[i]))) + pscale[i].extend(check(func.prop_scale(j), len(dvar), len(pscale[i]))) + pdesc[i].extend(check(func.prop_desc(j, fnames[i]), len(dvar), len(pdesc[i]))) - fidi.write('\t'+cstring+' = '+str(nvar)+'\n') - if not isempty(pinitpt): - fidi.write('\t '+cstring2+'_initial_point =\n') - vector_write(fidi,'\t ',pinitpt,6,76) + pinitpt = allempty(pinitpt) + plower = allempty(plower) + pupper = allempty(pupper) + pmean = allempty(pmean) + pstddev = allempty(pstddev) + pinitst = allempty(pinitst) + pstype = allempty(pstype) + pscale = allempty(pscale) + pdesc = allempty(pdesc) - if not isempty(plower): - fidi.write('\t '+cstring2+'_lower_bounds =\n') - vector_write(fidi,'\t ',plower ,6,76) + # write variables + print(' Writing ' + str(nvar) + ' ' + cstring + ' variables.') - if not isempty(pupper): - fidi.write('\t '+cstring2+'_upper_bounds =\n') - vector_write(fidi,'\t ',pupper ,6,76) + fidi.write('\t' + cstring + ' = ' + str(nvar) + '\n') + if not isempty(pinitpt): + fidi.write('\t ' + cstring2 + '_initial_point =\n') + vector_write(fidi, '\t ', pinitpt, 6, 76) - if not isempty(pmean): - fidi.write('\t '+cstring2+'_means =\n') - vector_write(fidi,'\t ',pmean ,6,76) + if not isempty(plower): + fidi.write('\t ' + cstring2 + '_lower_bounds =\n') + vector_write(fidi, '\t ', plower, 6, 76) - if not isempty(pstddev): - fidi.write('\t '+cstring2+'_std_deviations =\n') - vector_write(fidi,'\t ',pstddev,6,76) + if not isempty(pupper): + fidi.write('\t ' + cstring2 + '_upper_bounds =\n') + vector_write(fidi, '\t ', pupper, 6, 76) - if not isempty(pinitst): - fidi.write('\t '+cstring2+'_initial_state =\n') - vector_write(fidi,'\t ',pinitst,6,76) + if not isempty(pmean): + fidi.write('\t ' + cstring2 + '_means =\n') + vector_write(fidi, '\t ', pmean, 6, 76) - if not isempty(pstype): - fidi.write('\t '+cstring2+'_scale_types =\n') - vector_write(fidi,'\t ',pstype ,6,76) + if not isempty(pstddev): + fidi.write('\t ' + cstring2 + '_std_deviations =\n') + vector_write(fidi, '\t ', pstddev, 6, 76) - if not isempty(pscale): - fidi.write('\t '+cstring2+'_scales =\n') - vector_write(fidi,'\t ',pscale ,6,76) + if not isempty(pinitst): + fidi.write('\t ' + cstring2 + '_initial_state =\n') + vector_write(fidi, '\t ', pinitst, 6, 76) - if not isempty(pdesc): - fidi.write('\t '+cstring2+'_descriptors =\n') - vector_write(fidi,'\t ',pdesc ,6,76) + if not isempty(pstype): + fidi.write('\t ' + cstring2 + '_scale_types =\n') + vector_write(fidi, '\t ', pstype, 6, 76) - return + if not isempty(pscale): + fidi.write('\t ' + cstring2 + '_scales =\n') + vector_write(fidi, '\t ', pscale, 6, 76) + + if not isempty(pdesc): + fidi.write('\t ' + cstring2 + '_descriptors =\n') + vector_write(fidi, '\t ', pdesc, 6, 76) + + return Index: /issm/trunk-jpl/src/m/shp/shp2exp.py =================================================================== --- /issm/trunk-jpl/src/m/shp/shp2exp.py (revision 24212) +++ /issm/trunk-jpl/src/m/shp/shp2exp.py (revision 24213) @@ -3,51 +3,52 @@ from expwrite import expwrite -def shp2exp(shapefilename,*expfilename): - ''' - Convert a shapefile to an .exp file. Optionally, expfilename can be - specified to give a name for the .exp file to be created, otherwise the - .exp file will have the same prefix as the .shp file. - Usage: - shp2exp(shapefilename) - shp2exp(shapefilename,expfilename) +def shp2exp(shapefilename, * expfilename): + ''' + Convert a shapefile to an .exp file. Optionally, expfilename can be + specified to give a name for the .exp file to be created, otherwise the + .exp file will have the same prefix as the .shp file. - Examples: - shp2exp('Domain.shp') % creates Domain.exp - shp2exp('Domain.shp','DomainForISSM.exp') - ''' - - if not os.path.exists(shapefilename): - raise IOError("shp2exp error message: file '%s' not found!" % parametername) - if not len(expfilename): - expfile=os.path.splitext(shapefilename)[0]+'.exp' - else: - expfile=expfilename[0] + Usage: + shp2exp(shapefilename) + shp2exp(shapefilename, expfilename) - shp=shapefile.Reader(shapefilename) - expdict=dict(density=1) + Examples: + shp2exp('Domain.shp') % creates Domain.exp + shp2exp('Domain.shp', 'DomainForISSM.exp') + ''' - x=[] - y=[] - for i in range(len(shp.shapes())): - geom=shp.shapes()[i].shapeType - if geom==5: # polygon - expdict['closed']=1 - tmpx=[p[0] for p in shp.shapes()[i].points] - tmpy=[q[1] for q in shp.shapes()[i].points] - x.append(tmpx) - y.append(tmpy) - elif geom==3: # line - expdict['closed']=0 - tmpx=[p[0] for p in shp.shapes()[i].points] - tmpy=[q[1] for q in shp.shapes()[i].points] - x.append(tmpx) - y.append(tmpy) - elif geom==1: # point - expdict['closed']=0 - x.append(shp.shapes()[i].points[0][0]) - y.append(shp.shapes()[i].points[0][1]) + if not os.path.exists(shapefilename): + raise IOError("shp2exp error message: file '%s' not found!" % shapefilename) + if not len(expfilename): + expfile = os.path.splitext(shapefilename)[0] + '.exp' + else: + expfile = expfilename[0] - expdict['x']=x - expdict['y']=y - expwrite(expdict,expfile) + shp = shapefile.Reader(shapefilename) + expdict = dict(density=1) + + x = [] + y = [] + for i in range(len(shp.shapes())): + geom = shp.shapes()[i].shapeType + if geom == 5: # polygon + expdict['closed'] = 1 + tmpx = [p[0] for p in shp.shapes()[i].points] + tmpy = [q[1] for q in shp.shapes()[i].points] + x.append(tmpx) + y.append(tmpy) + elif geom == 3: # line + expdict['closed'] = 0 + tmpx = [p[0] for p in shp.shapes()[i].points] + tmpy = [q[1] for q in shp.shapes()[i].points] + x.append(tmpx) + y.append(tmpy) + elif geom == 1: # point + expdict['closed'] = 0 + x.append(shp.shapes()[i].points[0][0]) + y.append(shp.shapes()[i].points[0][1]) + + expdict['x'] = x + expdict['y'] = y + expwrite(expdict, expfile) Index: /issm/trunk-jpl/src/m/solve/WriteData.py =================================================================== --- /issm/trunk-jpl/src/m/solve/WriteData.py (revision 24212) +++ /issm/trunk-jpl/src/m/solve/WriteData.py (revision 24213) @@ -31,11 +31,11 @@ datatype = options.getfieldvalue('format') - mattype = options.getfieldvalue('mattype', 0) #only required for matrices - timeserieslength = options.getfieldvalue('timeserieslength', -1) + mattype = options.getfieldvalue('mattype', 0) #only required for matrices + timeserieslength = options.getfieldvalue('timeserieslength', - 1) #Process sparse matrices -# if issparse(data), -# data = full(data); -# end + # if issparse(data), + # data = full(data) + # end #Scale data if necesarry @@ -44,5 +44,5 @@ scale = options.getfieldvalue('scale') if np.size(data) > 1 and np.ndim(data) > 1 and np.size(data, 0) == timeserieslength: - data[0:-1, :] = scale * data[0:-1, :] + data[0: - 1, :] = scale * data[0: - 1, :] else: data = scale * data @@ -75,8 +75,6 @@ #first write length of record fid.write(pack('q', 4 + 4)) #1 integer + code - #write data code: fid.write(pack('i', FormatToCode(datatype))) - #now write integer try: @@ -90,21 +88,19 @@ fid.write(pack('q', 8 + 4)) #1 double + code - #write data code: - fid.write(pack('i', FormatToCode(datatype))) - - #now write double + #write data code: + fid.write(pack('i', FormatToCode(datatype))) + + #now write double try: fid.write(pack('d', data)) except error as Err: raise ValueError('field {} cannot be marshaled, {}'.format(name, Err)) - # }}} + # }}} elif datatype == 'String': # {{{ #first write length of record fid.write(pack('q', len(data) + 4 + 4)) #string + string size + code - #write data code: fid.write(pack('i', FormatToCode(datatype))) - #now write string fid.write(pack('i', len(data))) @@ -116,26 +112,26 @@ data = np.array([data]) elif isinstance(data, (list, tuple)): - data = np.array(data).reshape(-1,) + data = np.array(data).reshape(- 1, ) if np.ndim(data) == 1: if np.size(data): - data = data.reshape(np.size(data),) + data = data.reshape(np.size(data), ) else: data = data.reshape(0, 0) - #Get size + #Get size s = data.shape - #if matrix = NaN, then do not write anything + #if matrix = NaN, then do not write anything if np.ndim(data) == 2 and np.product(s) == 1 and np.all(np.isnan(data)): s = (0, 0) - #first write length of record - recordlength = 4 + 4 + 8 * np.product(s) + 4 + 4 #2 integers (32 bits) + the double matrix + code + matrix type + #first write length of record + recordlength = 4 + 4 + 8 * np.product(s) + 4 + 4 #2 integers (32 bits) + the double matrix + code + matrix type fid.write(pack('q', recordlength)) - #write data code and matrix type: + #write data code and matrix type: fid.write(pack('i', FormatToCode(datatype))) fid.write(pack('i', mattype)) - #now write matrix + #now write matrix fid.write(pack('i', s[0])) try: @@ -145,8 +141,8 @@ for i in range(s[0]): if np.ndim(data) == 1: - fid.write(pack('d', float(data[i]))) #get to the "c" convention, hence the transpose + fid.write(pack('d', float(data[i]))) #get to the "c" convention, hence the transpose else: for j in range(s[1]): - fid.write(pack('d', float(data[i][j]))) #get to the "c" convention, hence the transpose + fid.write(pack('d', float(data[i][j]))) #get to the "c" convention, hence the transpose # }}} @@ -156,19 +152,19 @@ data = np.array([data]) elif isinstance(data, (list, tuple)): - data = np.array(data).reshape(-1,) + data = np.array(data).reshape(- 1, ) if np.ndim(data) == 1: if np.size(data): - data = data.reshape(np.size(data),) + data = data.reshape(np.size(data), ) else: data = data.reshape(0, 0) - #Get size + #Get size s = data.shape - #if matrix = NaN, then do not write anything + #if matrix = NaN, then do not write anything if np.ndim(data) == 1 and np.product(s) == 1 and np.all(np.isnan(data)): s = (0, 0) - #first write length of record - recordlength = 4 + 4 + 8 * np.product(s) + 4 + 4 #2 integers (32 bits) + the double matrix + code + matrix type + #first write length of record + recordlength = 4 + 4 + 8 * np.product(s) + 4 + 4 #2 integers (32 bits) + the double matrix + code + matrix type try: @@ -177,8 +173,8 @@ raise ValueError('Field {} can not be marshaled, {}, with "number" the lenght of the record.'.format(name, Err)) - #write data code and matrix type: + #write data code and matrix type: fid.write(pack('i', FormatToCode(datatype))) fid.write(pack('i', mattype)) - #now write matrix + #now write matrix fid.write(pack('i', s[0])) try: @@ -188,22 +184,22 @@ for i in range(s[0]): if np.ndim(data) == 1: - fid.write(pack('d', float(data[i]))) #get to the "c" convention, hence the transpose + fid.write(pack('d', float(data[i]))) #get to the "c" convention, hence the transpose else: for j in range(s[1]): - fid.write(pack('d', float(data[i][j]))) #get to the "c" convention, hence the transpose - # }}} - - elif datatype == 'CompressedMat': # {{{ + fid.write(pack('d', float(data[i][j]))) #get to the "c" convention, hence the transpose + # }}} + + elif datatype == 'CompressedMat': # {{{ if isinstance(data, (bool, int, float)): data = np.array([data]) elif isinstance(data, (list, tuple)): - data = np.array(data).reshape(-1,) + data = np.array(data).reshape(- 1, ) if np.ndim(data) == 1: if np.size(data): - data = data.reshape(np.size(data),) + data = data.reshape(np.size(data), ) else: data = data.reshape(0, 0) - #Get size + #Get size s = data.shape if np.ndim(data) == 1: @@ -212,10 +208,10 @@ n2 = s[1] - #if matrix = NaN, then do not write anything + #if matrix = NaN, then do not write anything if np.ndim(data) == 1 and np.product(s) == 1 and np.all(np.isnan(data)): s = (0, 0) n2 = 0 - #first write length of record + #first write length of record recordlength = 4 + 4 + 8 + 8 + 1 * (s[0] - 1) * n2 + 8 * n2 + 4 + 4 #2 integers (32 bits) + the matrix + code + matrix type try: @@ -224,9 +220,9 @@ raise ValueError('Field {} can not be marshaled, {}, with "number" the lenght of the record.'.format(name, Err)) - #write data code and matrix type: + #write data code and matrix type: fid.write(pack('i', FormatToCode(datatype))) fid.write(pack('i', mattype)) - #Write offset and range + #Write offset and range A = data[0:s[0] - 1] offsetA = A.min() @@ -238,5 +234,5 @@ A = (A - offsetA) / rangeA * 255. - #now write matrix + #now write matrix fid.write(pack('i', s[0])) try: @@ -249,10 +245,10 @@ for i in range(s[0] - 1): fid.write(pack('B', int(A[i]))) - fid.write(pack('d', float(data[s[0] - 1]))) #get to the "c" convention, hence the transpose + fid.write(pack('d', float(data[s[0] - 1]))) #get to the "c" convention, hence the transpose elif np.product(s) > 0: for i in range(s[0] - 1): for j in range(s[1]): - fid.write(pack('B', int(A[i][j]))) #get to the "c" convention, hence the transpose + fid.write(pack('B', int(A[i][j]))) #get to the "c" convention, hence the transpose for j in range(s[1]): @@ -261,29 +257,28 @@ # }}} - elif datatype == 'MatArray': # {{{ - + elif datatype == 'MatArray': # {{{ #first get length of record - recordlength = 4 + 4 #number of records + code + recordlength = 4 + 4 #number of records + code for matrix in data: if isinstance(matrix, (bool, int, float)): matrix = np.array([matrix]) elif isinstance(matrix, (list, tuple)): - matrix = np.array(matrix).reshape(-1,) + matrix = np.array(matrix).reshape(- 1, ) if np.ndim(matrix) == 1: if np.size(matrix): - matrix = matrix.reshape(np.size(matrix),) + matrix = matrix.reshape(np.size(matrix), ) else: matrix = matrix.reshape(0, 0) s = matrix.shape - recordlength += 4 * 2 + np.product(s) * 8 #row and col of matrix + matrix of doubles - - #write length of record + recordlength += 4 * 2 + np.product(s) * 8 #row and col of matrix + matrix of doubles + + #write length of record fid.write(pack('q', recordlength)) - #write data code: - fid.write(pack('i', FormatToCode(datatype))) - - #write data, first number of records + #write data code: + fid.write(pack('i', FormatToCode(datatype))) + + #write data, first number of records fid.write(pack('i', len(data))) @@ -292,7 +287,7 @@ matrix = np.array([matrix]) elif isinstance(matrix, (list, tuple)): - matrix = np.array(matrix).reshape(-1,) + matrix = np.array(matrix).reshape(- 1, ) if np.ndim(matrix) == 1: - matrix = matrix.reshape(np.size(matrix),) + matrix = matrix.reshape(np.size(matrix), ) s = matrix.shape @@ -305,5 +300,5 @@ for i in range(s[0]): if np.ndim(matrix) == 1: - fid.write(pack('d', float(matrix[i]))) #get to the "c" convention, hence the transpose + fid.write(pack('d', float(matrix[i]))) #get to the "c" convention, hence the transpose else: for j in range(s[1]): @@ -311,19 +306,16 @@ # }}} - elif datatype == 'StringArray': # {{{ + elif datatype == 'StringArray': # {{{ #first get length of record - recordlength = 4 + 4 #for length of array + code + recordlength = 4 + 4 #for length of array + code for string in data: - recordlength += 4 + len(string) #for each string + recordlength += 4 + len(string) #for each string #write length of record fid.write(pack('q', recordlength)) - #write data code: fid.write(pack('i', FormatToCode(datatype))) - #now write length of string array fid.write(pack('i', len(data))) - #now write the strings for string in data: @@ -332,5 +324,5 @@ # }}} - else: # {{{ + else: # {{{ raise TypeError('WriteData error message: data type: {} not supported yet! ({})'.format(datatype, name)) # }}} @@ -366,3 +358,3 @@ raise IOError('FormatToCode error message: data type not supported yet!') return code -# }}} + # }}} Index: /issm/trunk-jpl/src/m/solve/loadresultsfromcluster.py =================================================================== --- /issm/trunk-jpl/src/m/solve/loadresultsfromcluster.py (revision 24212) +++ /issm/trunk-jpl/src/m/solve/loadresultsfromcluster.py (revision 24213) @@ -3,88 +3,89 @@ import platform from loadresultsfromdisk import loadresultsfromdisk - from helpers import * -def loadresultsfromcluster(md,runtimename=False): - """ - LOADRESULTSFROMCLUSTER - load results of solution sequence from cluster - Usage: - md=loadresultsfromcluster(md,runtimename); - """ +def loadresultsfromcluster(md, runtimename=False): + """ + LOADRESULTSFROMCLUSTER - load results of solution sequence from cluster - #retrieve cluster, to be able to call its methods - cluster=md.cluster + Usage: + md = loadresultsfromcluster(md, runtimename) + """ - if runtimename: - md.private.runtimename=runtimename + #retrieve cluster, to be able to call its methods + cluster = md.cluster - #Download outputs from the cluster - filelist=[md.miscellaneous.name+'.outlog',md.miscellaneous.name+'.errlog'] + if runtimename: + md.private.runtimename = runtimename + + #Download outputs from the cluster + filelist = [md.miscellaneous.name + '.outlog', md.miscellaneous.name + '.errlog'] + if md.qmu.isdakota: + filelist.append(md.miscellaneous.name + '.qmu.err') + filelist.append(md.miscellaneous.name + '.qmu.out') + if 'tabular_graphics_data' in fieldnames(md.qmu.params): + if md.qmu.params.tabular_graphics_data: + filelist.append('dakota_tabular.dat') + else: + filelist.append(md.miscellaneous.name + '.outbin') + cluster.Download(md.private.runtimename, filelist) + + #If we are here, no errors in the solution sequence, call loadresultsfromdisk. + if os.path.exists(md.miscellaneous.name + '.outbin'): + if os.path.getsize(md.miscellaneous.name + '.outbin') > 0: + md = loadresultsfromdisk(md, md.miscellaneous.name + '.outbin') + else: + print(('WARNING, outbin file is empty for run ' + md.miscellaneous.name)) + elif not md.qmu.isdakota: + print(('WARNING, outbin file does not exist ' + md.miscellaneous.name)) + + #erase the log and output files + if md.qmu.isdakota: + #filename = os.path.join('qmu' + str(os.getpid()), md.miscellaneous.name) + filename = md.miscellaneous.name + + # this will not work like normal as dakota doesn't generate outbin files, + # instead calls postqmu to store results directly in the model + # at md.results.dakota via dakota_out_parse + md = loadresultsfromdisk(md, md.miscellaneous.name + '.outbin') + else: + filename = md.miscellaneous.name + TryRem('.outbin', filename) + if not platform.system() == 'Windows': + TryRem('.tar.gz', md.private.runtimename) + + TryRem('.errlog', filename) + TryRem('.outlog', filename) + + #erase input file if run was carried out on same platform. + hostname = socket.gethostname() + if hostname == cluster.name: if md.qmu.isdakota: - filelist.append(md.miscellaneous.name+'.qmu.err') - filelist.append(md.miscellaneous.name+'.qmu.out') - if 'tabular_graphics_data' in fieldnames(md.qmu.params): - if md.qmu.params.tabular_graphics_data: - filelist.append('dakota_tabular.dat') + #filename = os.path.join('qmu' + str(os.getpid()), md.miscellaneous.name) + filename = md.miscellaneous.name + TryRem('.queue', filename) else: - filelist.append(md.miscellaneous.name+'.outbin') - cluster.Download(md.private.runtimename,filelist) + filename = md.miscellaneous.name + TryRem('.toolkits', filename) + if not platform.system() == 'Windows': + TryRem('.queue', filename) + else: + TryRem('.bat', filename) - #If we are here, no errors in the solution sequence, call loadresultsfromdisk. - if os.path.exists(md.miscellaneous.name+'.outbin'): - if os.path.getsize(md.miscellaneous.name+'.outbin')>0: - md=loadresultsfromdisk(md,md.miscellaneous.name+'.outbin') - else: - print(('WARNING, outbin file is empty for run '+md.miscellaneous.name)) - elif not md.qmu.isdakota: - print(('WARNING, outbin file does not exist '+md.miscellaneous.name)) + # remove this for bin file debugging + TryRem('.bin', filename) - #erase the log and output files - if md.qmu.isdakota: - #filename=os.path.join('qmu'+str(os.getpid()),md.miscellaneous.name) - filename = md.miscellaneous.name + #cwd = os.getcwd().split('/')[-1] + if md.qmu.isdakota: + os.chdir('..') + #TryRem('', cwd) - # this will not work like normal as dakota doesn't generate outbin files, - # instead calls postqmu to store results directly in the model - # at md.results.dakota via dakota_out_parse - md=loadresultsfromdisk(md,md.miscellaneous.name+'.outbin') - else: - filename=md.miscellaneous.name - TryRem('.outbin',filename) - if not platform.system()=='Windows': - TryRem('.tar.gz',md.private.runtimename) + return md - TryRem('.errlog',filename) - TryRem('.outlog',filename) - #erase input file if run was carried out on same platform. - hostname=socket.gethostname() - if hostname==cluster.name: - if md.qmu.isdakota: - #filename=os.path.join('qmu'+str(os.getpid()),md.miscellaneous.name) - filename = md.miscellaneous.name - TryRem('.queue',filename) - else: - filename=md.miscellaneous.name - TryRem('.toolkits',filename) - if not platform.system()=='Windows': - TryRem('.queue',filename) - else: - TryRem('.bat',filename) - - # remove this for bin file debugging - TryRem('.bin',filename) - - #cwd = os.getcwd().split('/')[-1] - if md.qmu.isdakota: - os.chdir('..') - #TryRem('',cwd) - - return md - -def TryRem(extension,filename): - try: - os.remove(filename+extension) - except OSError: - print(('WARNING, no '+extension+' is present for run '+filename)) +def TryRem(extension, filename): + try: + os.remove(filename + extension) + except OSError: + print(('WARNING, no ' + extension + ' is present for run ' + filename)) Index: /issm/trunk-jpl/src/m/solve/loadresultsfromdisk.py =================================================================== --- /issm/trunk-jpl/src/m/solve/loadresultsfromdisk.py (revision 24212) +++ /issm/trunk-jpl/src/m/solve/loadresultsfromdisk.py (revision 24213) @@ -5,13 +5,13 @@ -def loadresultsfromdisk(md,filename): +def loadresultsfromdisk(md, filename): """ LOADRESULTSFROMDISK - load results of solution sequence from disk file "filename" Usage: - md=loadresultsfromdisk(md=False,filename=False); + md = loadresultsfromdisk(md = False, filename = False) """ - #check number of inputs/outputs + #check number of inputs / outputs if not md or not filename: raise ValueError("loadresultsfromdisk: error message.") @@ -24,40 +24,40 @@ #initialize md.results if not a structure yet - if not isinstance(md.results,results): - md.results=results() + if not isinstance(md.results, results): + md.results = results() - #load results onto model - structure=parseresultsfromdisk(md,filename,not md.settings.io_gather) + #load results onto model + structure = parseresultsfromdisk(md, filename, not md.settings.io_gather) if not len(structure): raise RuntimeError("No result found in binary file '{}'. Check for solution crash.".format(filename)) - setattr(md.results,structure[0].SolutionType,structure) + setattr(md.results, structure[0].SolutionType, structure) #recover solution_type from results - md.private.solution=structure[0].SolutionType + md.private.solution = structure[0].SolutionType #read log files onto fields - if os.path.exists(md.miscellaneous.name+'.errlog'): - with open(md.miscellaneous.name+'.errlog','r') as f: - setattr(getattr(md.results,structure[0].SolutionType)[0],'errlog',[line[:-1] for line in f]) + if os.path.exists(md.miscellaneous.name + '.errlog'): + with open(md.miscellaneous.name + '.errlog', 'r') as f: + setattr(getattr(md.results, structure[0].SolutionType)[0], 'errlog', [line[: - 1] for line in f]) else: - setattr(getattr(md.results,structure[0].SolutionType)[0],'errlog',[]) + setattr(getattr(md.results, structure[0].SolutionType)[0], 'errlog', []) - if os.path.exists(md.miscellaneous.name+'.outlog'): - with open(md.miscellaneous.name+'.outlog','r') as f: - setattr(getattr(md.results,structure[0].SolutionType)[0],'outlog',[line[:-1] for line in f]) + if os.path.exists(md.miscellaneous.name + '.outlog'): + with open(md.miscellaneous.name + '.outlog', 'r') as f: + setattr(getattr(md.results, structure[0].SolutionType)[0], 'outlog', [line[: - 1] for line in f]) else: - setattr(getattr(md.results,structure[0].SolutionType)[0],'outlog',[]) + setattr(getattr(md.results, structure[0].SolutionType)[0], 'outlog', []) - if len(getattr(md.results,structure[0].SolutionType)[0].errlog): - print ("loadresultsfromcluster info message: error during solution. Check your errlog and outlog model fields.") + if len(getattr(md.results, structure[0].SolutionType)[0].errlog): + print("loadresultsfromcluster info message: error during solution. Check your errlog and outlog model fields.") #if only one solution, extract it from list for user friendliness - if len(structure) == 1 and not structure[0].SolutionType=='TransientSolution': - setattr(md.results,structure[0].SolutionType,structure[0]) + if len(structure) == 1 and not structure[0].SolutionType == 'TransientSolution': + setattr(md.results, structure[0].SolutionType, structure[0]) #post processes qmu results if necessary else: - md=postqmu(md,filename) + md = postqmu(md, filename) return md Index: /issm/trunk-jpl/src/m/solve/marshall.py =================================================================== --- /issm/trunk-jpl/src/m/solve/marshall.py (revision 24212) +++ /issm/trunk-jpl/src/m/solve/marshall.py (revision 24213) @@ -7,5 +7,5 @@ The routine creates a compatible binary file from @model md - This binary file will be used for parallel runs in JPL-package + This binary file will be used for parallel runs in JPL - package Usage: @@ -19,19 +19,18 @@ fid = open(md.miscellaneous.name + '.bin', 'wb') except IOError as e: - raise IOError("marshall error message: could not open '%s.bin' file for binary writing." % md.miscellaneous.name) + raise IOError("marshall error message: could not open '%s.bin' file for binary writing. Due to: ".format(md.miscellaneous.name), e) for field in md.properties(): - #Some properties do not need to be marshalled if field in ['results', 'radaroverlay', 'toolkits', 'cluster', 'private']: continue - #Check that current field is an object + #Check that current field is an object if not hasattr(getattr(md, field), 'marshall'): raise TypeError("field '{}' is not an object.".format(field)) - #Marshall current object - #print "marshalling %s ..." % field - exec("md.{}.marshall('md.{}',md,fid)".format(field, field)) + #Marshall current object + #print "marshalling %s ..." % field + exec("md.{}.marshall('md.{}', md, fid)".format(field, field)) #Last, write "md.EOF" to make sure that the binary file is not corrupt @@ -42,3 +41,3 @@ fid.close() except IOError as e: - raise IOError("marshall error message: could not close file '%s.bin'." % md.miscellaneous.name) + print("marshall error message: could not close file '{}.bin' due to:".format(md.miscellaneous.name), e) Index: /issm/trunk-jpl/src/m/solve/parseresultsfromdisk.py =================================================================== --- /issm/trunk-jpl/src/m/solve/parseresultsfromdisk.py (revision 24212) +++ /issm/trunk-jpl/src/m/solve/parseresultsfromdisk.py (revision 24213) @@ -13,5 +13,5 @@ -def parseresultsfromdiskioserial(md, filename): # {{{ +def parseresultsfromdiskioserial(md, filename): # {{{ #Open file try: @@ -31,10 +31,10 @@ while loadres: - #check that the new result does not add a step, which would be an error: + #check that the new result does not add a step, which would be an error: if check_nomoresteps: if loadres['step'] >= 1: - raise TypeError("parsing results for a steady-state core, which incorporates transient results!") - - #Check step, increase counter if this is a new step + raise TypeError("parsing results for a steady - state core, which incorporates transient results!") + + #Check step, increase counter if this is a new step if(step != loadres['step'] and loadres['step'] > 1): counter = counter + 1 @@ -43,5 +43,5 @@ #Add result if loadres['step'] == 0: - #if we have a step = 0, this is a steady state solution, don't expect more steps. + #if we have a step = 0, this is a steady state solution, don't expect more steps. index = 0 check_nomoresteps = 1 @@ -58,14 +58,14 @@ saveres[index] = resultsclass.results() - #Get time and step - if loadres['step'] != -9999.: + #Get time and step + if loadres['step'] != - 9999.: saveres[index].__dict__['step'] = loadres['step'] - if loadres['time'] != -9999.: + if loadres['time'] != - 9999.: saveres[index].__dict__['time'] = loadres['time'] - #Add result + #Add result saveres[index].__dict__[loadres['fieldname']] = loadres['field'] - #read next result + #read next result loadres = ReadData(fid, md) @@ -76,5 +76,5 @@ -def parseresultsfromdiskiosplit(md, filename): # {{{ +def parseresultsfromdiskiosplit(md, filename): # {{{ #Open file try: @@ -85,6 +85,6 @@ saveres = [] - #if we have done split I/O, ie, we have results that are fragmented across patches, - #do a first pass, and figure out the structure of results + #if we have done split I / O, ie, we have results that are fragmented across patches, + #do a first pass, and figure out the structure of results loadres = ReadDataDimensions(fid) while loadres: @@ -98,20 +98,20 @@ setattr(saveres[loadres['step'] - 1], 'time', loadres['time']) - #Add result + #Add result setattr(saveres[loadres['step'] - 1], loadres['fieldname'], float('NaN')) + + #read next result + loadres = ReadDataDimensions(fid) + + #do a second pass, and figure out the size of the patches + fid.seek(0) #rewind + loadres = ReadDataDimensions(fid) + while loadres: #read next result loadres = ReadDataDimensions(fid) - #do a second pass, and figure out the size of the patches - fid.seek(0) #rewind - loadres = ReadDataDimensions(fid) - while loadres: - - #read next result - loadres = ReadDataDimensions(fid) - - #third pass, this time to read the real information - fid.seek(0) #rewind + #third pass, this time to read the real information + fid.seek(0) #rewind loadres = ReadData(fid, md) while loadres: @@ -125,8 +125,8 @@ setattr(saveres[loadres['step'] - 1], 'time', loadres['time']) - #Add result + #Add result setattr(saveres[loadres['step'] - 1], loadres['fieldname'], loadres['field']) - #read next result + #read next result loadres = ReadData(fid, md) @@ -138,5 +138,5 @@ -def ReadData(fid, md): # {{{ +def ReadData(fid, md): # {{{ """ READDATA - @@ -149,5 +149,5 @@ try: length = struct.unpack('i', fid.read(struct.calcsize('i')))[0] - fieldname = struct.unpack('{}s'.format(length), fid.read(length))[0][:-1] + fieldname = struct.unpack('{}s'.format(length), fid.read(length))[0][: - 1] fieldname = fieldname.decode() #strings are binaries when stored so need to be converted back time = struct.unpack('d', fid.read(struct.calcsize('d')))[0] @@ -159,10 +159,10 @@ elif datatype == 2: - field = struct.unpack('{}s'.format(M), fid.read(M))[0][:-1] + field = struct.unpack('{}s'.format(M), fid.read(M))[0][: - 1] field = field.decode() elif datatype == 3: N = struct.unpack('i', fid.read(struct.calcsize('i')))[0] - #field = transpose(fread(fid, [N M], 'double')); + #field = transpose(fread(fid, [N M], 'double')) field = np.zeros(shape=(M, N), dtype=float) for i in range(M): @@ -171,5 +171,5 @@ elif datatype == 4: N = struct.unpack('i', fid.read(struct.calcsize('i')))[0] - # field = transpose(fread(fid, [N M], 'int')); + # field = transpose(fread(fid, [N M], 'int')) field = np.zeros(shape=(M, N), dtype=int) for i in range(M): @@ -179,5 +179,5 @@ raise TypeError("cannot read data of datatype {}".format(datatype)) - #Process units here FIXME: this should not be done here! + #Process units here FIXME: this should not be done here! yts = md.constants.yts if fieldname == 'BalancethicknessThickeningRate': @@ -200,21 +200,21 @@ field = field * yts elif fieldname == 'TotalFloatingBmb': - field = field / 10.**12 * yts #(GigaTon/year) + field = field / 10.**12 * yts #(GigaTon / year) elif fieldname == 'TotalFloatingBmbScaled': - field = field / 10.**12 * yts #(GigaTon/year) + field = field / 10.**12 * yts #(GigaTon / year) elif fieldname == 'TotalGroundedBmb': - field = field / 10.**12 * yts #(GigaTon/year) + field = field / 10.**12 * yts #(GigaTon / year) elif fieldname == 'TotalGroundedBmbScaled': - field = field / 10.**12 * yts #(GigaTon/year) + field = field / 10.**12 * yts #(GigaTon / year) elif fieldname == 'TotalSmb': - field = field / 10.**12 * yts #(GigaTon/year) + field = field / 10.**12 * yts #(GigaTon / year) elif fieldname == 'TotalSmbScaled': - field = field / 10.**12 * yts #(GigaTon/year) + field = field / 10.**12 * yts #(GigaTon / year) elif fieldname == 'GroundinglineMassFlux': - field = field /10.**12 * yts #(GigaTon/year) + field = field / 10.**12 * yts #(GigaTon / year) elif fieldname == 'IcefrontMassFlux': - field = field /10.**12 * yts #(GigaTon/year) + field = field / 10.**12 * yts #(GigaTon / year) elif fieldname == 'IcefrontMassFluxLevelset': - field = field /10.**12 * yts #(GigaTon/year) + field = field / 10.**12 * yts #(GigaTon / year) elif fieldname == 'SmbMassBalance': field = field * yts @@ -241,6 +241,6 @@ degmax = md.love.sh_nmax nfreq = md.love.nfreq - #for numpy 1.8+ only - #temp_field = np.full((degmax+1, nfreq, nlayer+1, 6), 0.0) + #for numpy 1.8 + only + #temp_field = np.full((degmax + 1, nfreq, nlayer + 1, 6), 0.0) temp_field = np.empty((degmax + 1, nfreq, nlayer + 1, 6)) temp_field.fill(0.0) @@ -253,5 +253,5 @@ field = temp_field - if time != -9999: + if time != - 9999: time = time / yts @@ -269,7 +269,7 @@ -def ReadDataDimensions(fid): # {{{ +def ReadDataDimensions(fid): # {{{ """ - READDATADIMENSIONS - read data dimensions, step and time, but not the data itself. + READDATADIMENSIONS - read data dimensions, step and time, but not the data itself. Usage: @@ -280,10 +280,10 @@ try: length = struct.unpack('i', fid.read(struct.calcsize('i')))[0] - fieldname = struct.unpack('{}s'.format(length), fid.read(length))[0][:-1] + fieldname = struct.unpack('{}s'.format(length), fid.read(length))[0][: - 1] time = struct.unpack('d', fid.read(struct.calcsize('d')))[0] step = struct.unpack('i', fid.read(struct.calcsize('i')))[0] datatype = struct.unpack('i', fid.read(struct.calcsize('i')))[0] M = struct.unpack('i', fid.read(struct.calcsize('i')))[0] - N = 1 #default + N = 1 #default if datatype == 1: fid.seek(M * 8, 1) Index: /issm/trunk-jpl/src/m/solve/solve.py =================================================================== --- /issm/trunk-jpl/src/m/solve/solve.py (revision 24212) +++ /issm/trunk-jpl/src/m/solve/solve.py (revision 24213) @@ -10,151 +10,151 @@ #from MatlabFuncs import * -def solve(md,solutionstring,*args): - """ - SOLVE - apply solution sequence for this model - Usage: - md=solve(md,solutionstring,varargin) - where varargin is a list of paired arguments of string OR enums +def solve(md, solutionstring, *args): + """ + SOLVE - apply solution sequence for this model - solution types available comprise: - - 'Stressbalance' or 'sb' - - 'Masstransport' or 'mt' - - 'Thermal' or 'th' - - 'Steadystate' or 'ss' - - 'Transient' or 'tr' - - 'Balancethickness' or 'mc' - - 'Balancevelocity' or 'bv' - - 'BedSlope' or 'bsl' - - 'SurfaceSlope' or 'ssl' - - 'Hydrology' or 'hy' - - 'DamageEvolution' or 'da' - - 'Gia' or 'gia' - - 'Esa' or 'esa' - - 'Sealevelrise' or 'slr' - - 'Love' or 'lv' + Usage: + md = solve(md, solutionstring, varargin) + where varargin is a list of paired arguments of string OR enums - extra options: - - loadonly : does not solve. only load results - - checkconsistency : 'yes' or 'no' (default is 'yes'), ensures checks on consistency of model - - restart: 'directory name (relative to the execution directory) where the restart file is located. + solution types available comprise: + - 'Stressbalance' or 'sb' + - 'Masstransport' or 'mt' + - 'Thermal' or 'th' + - 'Steadystate' or 'ss' + - 'Transient' or 'tr' + - 'Balancethickness' or 'mc' + - 'Balancevelocity' or 'bv' + - 'BedSlope' or 'bsl' + - 'SurfaceSlope' or 'ssl' + - 'Hydrology' or 'hy' + - 'DamageEvolution' or 'da' + - 'Gia' or 'gia' + - 'Esa' or 'esa' + - 'Sealevelrise' or 'slr' + - 'Love' or 'lv' - Examples: - md=solve(md,'Stressbalance'); - md=solve(md,'sb'); - """ + extra options: + - loadonly : does not solve. only load results + - checkconsistency : 'yes' or 'no' (default is 'yes'), ensures checks on consistency of model + - restart: 'directory name (relative to the execution directory) where the restart file is located. - #recover and process solve options - if solutionstring.lower() == 'sb' or solutionstring.lower() == 'stressbalance': - solutionstring = 'StressbalanceSolution'; - elif solutionstring.lower() == 'mt' or solutionstring.lower() == 'masstransport': - solutionstring = 'MasstransportSolution'; - elif solutionstring.lower() == 'th' or solutionstring.lower() == 'thermal': - solutionstring = 'ThermalSolution'; - elif solutionstring.lower() == 'st' or solutionstring.lower() == 'steadystate': - solutionstring = 'SteadystateSolution'; - elif solutionstring.lower() == 'tr' or solutionstring.lower() == 'transient': - solutionstring = 'TransientSolution'; - elif solutionstring.lower() == 'mc' or solutionstring.lower() == 'balancethickness': - solutionstring = 'BalancethicknessSolution'; - elif solutionstring.lower() == 'bv' or solutionstring.lower() == 'balancevelocity': - solutionstring = 'BalancevelocitySolution'; - elif solutionstring.lower() == 'bsl' or solutionstring.lower() == 'bedslope': - solutionstring = 'BedSlopeSolution'; - elif solutionstring.lower() == 'ssl' or solutionstring.lower() == 'surfaceslope': - solutionstring = 'SurfaceSlopeSolution'; - elif solutionstring.lower() == 'hy' or solutionstring.lower() == 'hydrology': - solutionstring = 'HydrologySolution'; - elif solutionstring.lower() == 'da' or solutionstring.lower() == 'damageevolution': - solutionstring = 'DamageEvolutionSolution'; - elif solutionstring.lower() == 'gia' or solutionstring.lower() == 'gia': - solutionstring = 'GiaSolution'; - elif solutionstring.lower() == 'lv' or solutionstring.lower() == 'love': - solutionstring = 'LoveSolution'; - elif solutionstring.lower() == 'esa': - solutionstring = 'EsaSolution'; - elif solutionstring.lower() == 'slr' or solutionstring.lower() == 'sealevelrise': - solutionstring = 'SealevelriseSolution'; - else: - raise ValueError("solutionstring '%s' not supported!" % solutionstring) - options=pairoptions('solutionstring',solutionstring,*args) + Examples: + md = solve(md, 'Stressbalance') + md = solve(md, 'sb') + """ - #recover some fields - md.private.solution=solutionstring - cluster=md.cluster - if options.getfieldvalue('batch','no')=='yes': - batch=1 - else: - batch=0; + #recover and process solve options + if solutionstring.lower() == 'sb' or solutionstring.lower() == 'stressbalance': + solutionstring = 'StressbalanceSolution' + elif solutionstring.lower() == 'mt' or solutionstring.lower() == 'masstransport': + solutionstring = 'MasstransportSolution' + elif solutionstring.lower() == 'th' or solutionstring.lower() == 'thermal': + solutionstring = 'ThermalSolution' + elif solutionstring.lower() == 'st' or solutionstring.lower() == 'steadystate': + solutionstring = 'SteadystateSolution' + elif solutionstring.lower() == 'tr' or solutionstring.lower() == 'transient': + solutionstring = 'TransientSolution' + elif solutionstring.lower() == 'mc' or solutionstring.lower() == 'balancethickness': + solutionstring = 'BalancethicknessSolution' + elif solutionstring.lower() == 'bv' or solutionstring.lower() == 'balancevelocity': + solutionstring = 'BalancevelocitySolution' + elif solutionstring.lower() == 'bsl' or solutionstring.lower() == 'bedslope': + solutionstring = 'BedSlopeSolution' + elif solutionstring.lower() == 'ssl' or solutionstring.lower() == 'surfaceslope': + solutionstring = 'SurfaceSlopeSolution' + elif solutionstring.lower() == 'hy' or solutionstring.lower() == 'hydrology': + solutionstring = 'HydrologySolution' + elif solutionstring.lower() == 'da' or solutionstring.lower() == 'damageevolution': + solutionstring = 'DamageEvolutionSolution' + elif solutionstring.lower() == 'gia' or solutionstring.lower() == 'gia': + solutionstring = 'GiaSolution' + elif solutionstring.lower() == 'lv' or solutionstring.lower() == 'love': + solutionstring = 'LoveSolution' + elif solutionstring.lower() == 'esa': + solutionstring = 'EsaSolution' + elif solutionstring.lower() == 'slr' or solutionstring.lower() == 'sealevelrise': + solutionstring = 'SealevelriseSolution' + else: + raise ValueError("solutionstring '%s' not supported!" % solutionstring) + options = pairoptions('solutionstring', solutionstring, *args) - #check model consistency - if options.getfieldvalue('checkconsistency','yes')=='yes': - if md.verbose.solution: - print("checking model consistency") - ismodelselfconsistent(md) + #recover some fields + md.private.solution = solutionstring + cluster = md.cluster + if options.getfieldvalue('batch', 'no') == 'yes': + batch = 1 + else: + batch = 0 - #First, build a runtime name that is unique - restart=options.getfieldvalue('restart','') - if restart == 1: - pass #do nothing - else: - if restart: - md.private.runtimename=restart - else: - if options.getfieldvalue('runtimename',True): - c=datetime.datetime.now() - md.private.runtimename="%s-%02i-%02i-%04i-%02i-%02i-%02i-%i" % (md.miscellaneous.name,c.month,c.day,c.year,c.hour,c.minute,c.second,os.getpid()) - else: - md.private.runtimename=md.miscellaneous.name + #check model consistency + if options.getfieldvalue('checkconsistency', 'yes') == 'yes': + if md.verbose.solution: + print("checking model consistency") + ismodelselfconsistent(md) - #if running qmu analysis, some preprocessing of dakota files using models - #fields needs to be carried out. - if md.qmu.isdakota: - md=preqmu(md,options) + #First, build a runtime name that is unique + restart = options.getfieldvalue('restart', '') + if restart == 1: + pass #do nothing + else: + if restart: + md.private.runtimename = restart + else: + if options.getfieldvalue('runtimename', True): + c = datetime.datetime.now() + md.private.runtimename = "%s-%02i-%02i-%04i-%02i-%02i-%02i-%i" % (md.miscellaneous.name, c.month, c.day, c.year, c.hour, c.minute, c.second, os.getpid()) + else: + md.private.runtimename = md.miscellaneous.name - #Do we load results only? - if options.getfieldvalue('loadonly',False): - md=loadresultsfromcluster(md) - return md + #if running qmu analysis, some preprocessing of dakota files using models + #fields needs to be carried out. + if md.qmu.isdakota: + md = preqmu(md, options) + #Do we load results only? + if options.getfieldvalue('loadonly', False): + md = loadresultsfromcluster(md) + return md - #Write all input files - marshall(md) # bin file - md.toolkits.ToolkitsFile(md.miscellaneous.name+'.toolkits') # toolkits file - cluster.BuildQueueScript(md.private.runtimename,md.miscellaneous.name,md.private.solution,md.settings.io_gather,md.debug.valgrind,md.debug.gprof,md.qmu.isdakota,md.transient.isoceancoupling) # queue file + #Write all input files + marshall(md) # bin file + md.toolkits.ToolkitsFile(md.miscellaneous.name + '.toolkits') # toolkits file + cluster.BuildQueueScript(md.private.runtimename, md.miscellaneous.name, md.private.solution, md.settings.io_gather, md.debug.valgrind, md.debug.gprof, md.qmu.isdakota, md.transient.isoceancoupling) # queue file - #Stop here if batch mode - if options.getfieldvalue('batch','no')=='yes': - print('batch mode requested: not launching job interactively') - print('launch solution sequence on remote cluster by hand') - return md + #Stop here if batch mode + if options.getfieldvalue('batch', 'no') == 'yes': + print('batch mode requested: not launching job interactively') + print('launch solution sequence on remote cluster by hand') + return md - #Upload all required files: - modelname = md.miscellaneous.name - filelist = [modelname+'.bin ',modelname+'.toolkits ',modelname+'.queue '] - if md.qmu.isdakota: - filelist.append(modelname+'.qmu.in') + #Upload all required files: + modelname = md.miscellaneous.name + filelist = [modelname + '.bin ', modelname + '.toolkits ', modelname + '.queue '] + if md.qmu.isdakota: + filelist.append(modelname + '.qmu.in') - if not restart: - cluster.UploadQueueJob(md.miscellaneous.name,md.private.runtimename,filelist) + if not restart: + cluster.UploadQueueJob(md.miscellaneous.name, md.private.runtimename, filelist) - #Launch job - cluster.LaunchQueueJob(md.miscellaneous.name,md.private.runtimename,filelist,restart,batch) + #Launch job + cluster.LaunchQueueJob(md.miscellaneous.name, md.private.runtimename, filelist, restart, batch) - #wait on lock - if md.settings.waitonlock>0: - #we wait for the done file - islock=waitonlock(md) - if islock==0: #no results to be loaded - print('The results must be loaded manually with md=loadresultsfromcluster(md).') - else: #load results - if md.verbose.solution: - print('loading results from cluster') - md=loadresultsfromcluster(md) + #wait on lock + if md.settings.waitonlock > 0: + #we wait for the done file + islock = waitonlock(md) + if islock == 0: #no results to be loaded + print('The results must be loaded manually with md = loadresultsfromcluster(md).') + else: #load results + if md.verbose.solution: + print('loading results from cluster') + md = loadresultsfromcluster(md) - #post processes qmu results if necessary - if md.qmu.isdakota: - if not strncmpi(options.getfieldvalue('keep','y'),'y',1): - shutil.rmtree('qmu'+str(os.getpid())) + #post processes qmu results if necessary + if md.qmu.isdakota: + if not strncmpi(options.getfieldvalue('keep', 'y'), 'y', 1): + shutil.rmtree('qmu' + str(os.getpid())) - return md + return md Index: /issm/trunk-jpl/src/m/solve/waitonlock.py =================================================================== --- /issm/trunk-jpl/src/m/solve/waitonlock.py (revision 24212) +++ /issm/trunk-jpl/src/m/solve/waitonlock.py (revision 24213) @@ -4,61 +4,59 @@ import MatlabFuncs as m + def waitonlock(md): - """ - WAITONLOCK - wait for a file - - This routine will return when a file named 'filename' is written to disk. - If the time limit given in input is exceeded, return 0 - - Usage: - flag=waitonlock(md) - """ + """ + WAITONLOCK - wait for a file - #Get filename (lock file) and options - executionpath=md.cluster.executionpath - cluster=md.cluster.name - login=md.cluster.login - port=md.cluster.port - timelimit=md.settings.waitonlock - filename=os.path.join(executionpath,md.private.runtimename,md.miscellaneous.name+'.lock') + This routine will return when a file named 'filename' is written to disk. + If the time limit given in input is exceeded, return 0 - #waitonlock will work if the lock is on the same machine only: - if not m.strcmpi(gethostname(),cluster): + Usage: + flag = waitonlock(md) + """ - print('solution launched on remote cluster. log in to detect job completion.') - choice=eval(input('Is the job successfully completed? (y/n) ')) - if not m.strcmp(choice,'y'): - print('Results not loaded... exiting') - flag=0 - else: - flag=1 + #Get filename (lock file) and options + executionpath = md.cluster.executionpath + cluster = md.cluster.name + timelimit = md.settings.waitonlock + filename = os.path.join(executionpath, md.private.runtimename, md.miscellaneous.name + '.lock') - #job is running on the same machine - else: + #waitonlock will work if the lock is on the same machine only: + if not m.strcmpi(gethostname(), cluster): - if 'interactive' in vars(md.cluster) and md.cluster.interactive: - #We are in interactive mode, no need to check for job completion - flag=1 - return flag - #initialize time and file presence test flag - etime=0 - ispresent=0 - print(("waiting for '%s' hold on... (Ctrl+C to exit)" % filename)) + print('solution launched on remote cluster. log in to detect job completion.') + choice = eval(input('Is the job successfully completed? (y / n) ')) + if not m.strcmp(choice, 'y'): + print('Results not loaded... exiting') + flag = 0 + else: + flag = 1 - #loop till file .lock exist or time is up - while ispresent==0 and etimetimelimit: - print('Time limit exceeded. Increase md.settings.waitonlock') - print('The results must be loaded manually with md=loadresultsfromcluster(md).') - raise RuntimeError('waitonlock error message: time limit exceeded.') - flag=0 - else: - flag=1 + if 'interactive' in vars(md.cluster) and md.cluster.interactive: + #We are in interactive mode, no need to check for job completion + flag = 1 + return flag + #initialize time and file presence test flag + etime = 0 + ispresent = 0 + print(("waiting for '%s' hold on... (Ctrl + C to exit)" % filename)) - return flag + #loop till file .lock exist or time is up + while ispresent == 0 and etime < timelimit: + ispresent = os.path.exists(filename) + time.sleep(1) + etime += 1 / 60 + #build output + if etime > timelimit: + print('Time limit exceeded. Increase md.settings.waitonlock') + print('The results must be loaded manually with md = loadresultsfromcluster(md).') + raise RuntimeError('waitonlock error message: time limit exceeded.') + flag = 0 + else: + flag = 1 + + return flag Index: /issm/trunk-jpl/src/m/solvers/asmoptions.py =================================================================== --- /issm/trunk-jpl/src/m/solvers/asmoptions.py (revision 24212) +++ /issm/trunk-jpl/src/m/solvers/asmoptions.py (revision 24213) @@ -1,29 +1,37 @@ import pairoptions + def asmoptions(*args): - #ASMOPTIONS - return ASM petsc options - # - # Usage: - # options=asmoptions; - - #retrieve options provided in varargin - arguments=pairoptions.pairoptions(*args) - - options=[['toolkit','petsc'],['mat_type','mpiaij'],['ksp_type','gmres'],['pc_type','asm'],['sub_pc_type','lu'],['pc_asm_overlap',3],['ksp_max_it',100],['ksp_rtol',1e-30]]; + #ASMOPTIONS - return ASM petsc options + # + # Usage: + # options = asmoptions - #now, go through our arguments, and write over default options. - for i in range(len(arguments.list)): - arg1=arguments.list[i][0] - arg2=arguments.list[i][1] - found=0; - for j in range(len(options)): - joption=options[j][0] - if joption==arg1: - joption[1]=arg2; - options[j]=joption; - found=1; - break - if not found: - #this option did not exist, add it: - options.append([arg1,arg2]) - return options + #retrieve options provided in varargin + arguments = pairoptions.pairoptions(*args) + + options = [['toolkit', 'petsc'], + ['mat_type', 'mpiaij'], + ['ksp_type', 'gmres'], + ['pc_type', 'asm'], + ['sub_pc_type', 'lu'], + ['pc_asm_overlap', 3], + ['ksp_max_it', 100], + ['ksp_rtol', 1e-30]] + + #now, go through our arguments, and write over default options. + for i in range(len(arguments.list)): + arg1 = arguments.list[i][0] + arg2 = arguments.list[i][1] + found = 0 + for j in range(len(options)): + joption = options[j][0] + if joption == arg1: + joption[1] = arg2 + options[j] = joption + found = 1 + break + if not found: + #this option did not exist, add it: + options.append([arg1, arg2]) + return options Index: /issm/trunk-jpl/src/m/solvers/iluasmoptions.py =================================================================== --- /issm/trunk-jpl/src/m/solvers/iluasmoptions.py (revision 24212) +++ /issm/trunk-jpl/src/m/solvers/iluasmoptions.py (revision 24213) @@ -2,26 +2,26 @@ import pairoptions + def iluasmoptions(*args): - """ - ILUASMOPTIONS - + """ + ILUASMOPTIONS - - Usage: - options=iluasmoptions; - """ - - #retrieve options provided in varargin - options=pairoptions.pairoptions(*args) - iluasm=OrderedDict() + Usage: + options = iluasmoptions + """ - #default iluasm options - iluasm['toolkit']='petsc' - iluasm['mat_type']=options.getfieldvalue('mat_type','aij') - iluasm['ksp_type']=options.getfieldvalue('ksp_type','gmres') - iluasm['pc_type']=options.getfieldvalue('pc_type','asm') - iluasm['sub_pc_type']=options.getfieldvalue('sub_pc_type','ilu') - iluasm['pc_asm_overlap']=options.getfieldvalue('pc_asm_overlap',5) - iluasm['ksp_max_it']=options.getfieldvalue('ksp_max_it',100) - iluasm['ksp_rtol']=options.getfieldvalue('ksp_rtol',1e-15) + #retrieve options provided in varargin + options = pairoptions.pairoptions(*args) + iluasm = OrderedDict() - return iluasm + #default iluasm options + iluasm['toolkit'] = 'petsc' + iluasm['mat_type'] = options.getfieldvalue('mat_type', 'aij') + iluasm['ksp_type'] = options.getfieldvalue('ksp_type', 'gmres') + iluasm['pc_type'] = options.getfieldvalue('pc_type', 'asm') + iluasm['sub_pc_type'] = options.getfieldvalue('sub_pc_type', 'ilu') + iluasm['pc_asm_overlap'] = options.getfieldvalue('pc_asm_overlap', 5) + iluasm['ksp_max_it'] = options.getfieldvalue('ksp_max_it', 100) + iluasm['ksp_rtol'] = options.getfieldvalue('ksp_rtol', 1e-15) + return iluasm Index: /issm/trunk-jpl/src/m/solvers/issmgslsolver.py =================================================================== --- /issm/trunk-jpl/src/m/solvers/issmgslsolver.py (revision 24212) +++ /issm/trunk-jpl/src/m/solvers/issmgslsolver.py (revision 24213) @@ -2,33 +2,34 @@ import pairoptions + def issmgslsolver(*args): - #ISSMSOLVE - return issm solver options - # - # Usage: - # options=issmsolver; - - #retrieve options provided in varargin - arguments=pairoptions.pairoptions(*args) - - options=OrderedDict() - options['toolkit'] = 'issm' - options['mat_type'] = 'dense' - options['vec_type'] = 'seq' - options['solver_type'] = 'gsl' + #ISSMSOLVE - return issm solver options + # + # Usage: + # options = issmsolver - #now, go through our arguments, and write over default options. - for i in range(len(arguments.list)): - arg1=arguments.list[i][0] - arg2=arguments.list[i][1] - found=0; - for j in range(len(options)): - joption=options[j][0] - if joption==arg1: - joption[1]=arg2; - options[j]=joption; - found=1; - break - if not found: - #this option did not exist, add it: - options.append([arg1,arg2]) - return options + #retrieve options provided in varargin + arguments = pairoptions.pairoptions(*args) + + options = OrderedDict() + options['toolkit'] = 'issm' + options['mat_type'] = 'dense' + options['vec_type'] = 'seq' + options['solver_type'] = 'gsl' + + #now, go through our arguments, and write over default options. + for i in range(len(arguments.list)): + arg1 = arguments.list[i][0] + arg2 = arguments.list[i][1] + found = 0 + for j in range(len(options)): + joption = options[j][0] + if joption == arg1: + joption[1] = arg2 + options[j] = joption + found = 1 + break + if not found: + #this option did not exist, add it: + options.append([arg1, arg2]) + return options Index: /issm/trunk-jpl/src/m/solvers/issmmumpssolver.py =================================================================== --- /issm/trunk-jpl/src/m/solvers/issmmumpssolver.py (revision 24212) +++ /issm/trunk-jpl/src/m/solvers/issmmumpssolver.py (revision 24213) @@ -2,33 +2,34 @@ import pairoptions + def issmmumpssolver(*args): - #ISSMSOLVE - return issm solver options - # - # Usage: - # options=issmsolver; + #ISSMSOLVE - return issm solver options + # + # Usage: + # options = issmsolver - #retrieve options provided in varargin - arguments=pairoptions.pairoptions(*args) + #retrieve options provided in varargin + arguments = pairoptions.pairoptions(*args) - options=OrderedDict() - options['toolkit'] = 'issm' - options['mat_type'] = 'mpisparse' - options['vec_type'] = 'mpi' - options['solver_type'] = 'mumps' + options = OrderedDict() + options['toolkit'] = 'issm' + options['mat_type'] = 'mpisparse' + options['vec_type'] = 'mpi' + options['solver_type'] = 'mumps' - #now, go through our arguments, and write over default options. - for i in range(len(arguments.list)): - arg1=arguments.list[i][0] - arg2=arguments.list[i][1] - found=0; - for j in range(len(options)): - joption=options[j][0] - if joption==arg1: - joption[1]=arg2; - options[j]=joption; - found=1; - break - if not found: - #this option did not exist, add it: - options.append([arg1,arg2]) - return options + #now, go through our arguments, and write over default options. + for i in range(len(arguments.list)): + arg1 = arguments.list[i][0] + arg2 = arguments.list[i][1] + found = 0 + for j in range(len(options)): + joption = options[j][0] + if joption == arg1: + joption[1] = arg2 + options[j] = joption + found = 1 + break + if not found: + #this option did not exist, add it: + options.append([arg1, arg2]) + return options Index: /issm/trunk-jpl/src/m/solvers/jacobiasmoptions.py =================================================================== --- /issm/trunk-jpl/src/m/solvers/jacobiasmoptions.py (revision 24212) +++ /issm/trunk-jpl/src/m/solvers/jacobiasmoptions.py (revision 24213) @@ -1,29 +1,37 @@ import pairoptions + def jacobiasmoptions(*args): - #ASMOPTIONS - return Additive Shwartz Method with Jacobi preconditioner petsc options - # - # Usage: - # options=jacobiasmoptions; - - #retrieve options provided in varargin - arguments=pairoptions.pairoptions(*args) - - options=[['toolkit','petsc'],['mat_type','mpiaij'],['ksp_type','gmres'],['pc_type','asm'],['sub_pc_type','jacobi'],['pc_asm_overlap',3],['ksp_max_it',100],['ksp_rtol',1e-15]]; + #ASMOPTIONS - return Additive Shwartz Method with Jacobi preconditioner petsc options + # + # Usage: + # options = jacobiasmoptions - #now, go through our arguments, and write over default options. - for i in range(len(arguments.list)): - arg1=arguments.list[i][0] - arg2=arguments.list[i][1] - found=0; - for j in range(len(options)): - joption=options[j][0] - if joption==arg1: - joption[1]=arg2; - options[j]=joption; - found=1; - break - if not found: - #this option did not exist, add it: - options.append([arg1,arg2]) - return options + #retrieve options provided in varargin + arguments = pairoptions.pairoptions(*args) + + options = [['toolkit', 'petsc'], + ['mat_type', 'mpiaij'], + ['ksp_type', 'gmres'], + ['pc_type', 'asm'], + ['sub_pc_type', 'jacobi'], + ['pc_asm_overlap', 3], + ['ksp_max_it', 100], + ['ksp_rtol', 1e-15]] + + #now, go through our arguments, and write over default options. + for i in range(len(arguments.list)): + arg1 = arguments.list[i][0] + arg2 = arguments.list[i][1] + found = 0 + for j in range(len(options)): + joption = options[j][0] + if joption == arg1: + joption[1] = arg2 + options[j] = joption + found = 1 + break + if not found: + #this option did not exist, add it: + options.append([arg1, arg2]) + return options Index: /issm/trunk-jpl/src/m/solvers/jacobicgoptions.py =================================================================== --- /issm/trunk-jpl/src/m/solvers/jacobicgoptions.py (revision 24212) +++ /issm/trunk-jpl/src/m/solvers/jacobicgoptions.py (revision 24213) @@ -1,29 +1,34 @@ -import pairoptions +import pairoptions + def jacobicgoptions(*args): - #ASMOPTIONS - return Additive Shwartz Method with Jacobi preconditioner petsc options - # - # Usage: - # options=jacobicgoptions; - - #retrieve options provided in varargin - arguments=pairoptions.pairoptions(*args) - - options=[['toolkit','petsc'],['mat_type','mpiaij'],['ksp_type','cg'],['ksp_max_it',100],['ksp_rtol',1e-15]]; + #ASMOPTIONS - return Additive Shwartz Method with Jacobi preconditioner petsc options + # + # Usage: + # options = jacobicgoptions - #now, go through our arguments, and write over default options. - for i in range(len(arguments.list)): - arg1=arguments.list[i][0] - arg2=arguments.list[i][1] - found=0; - for j in range(len(options)): - joption=options[j][0] - if joption==arg1: - joption[1]=arg2; - options[j]=joption; - found=1; - break - if not found: - #this option did not exist, add it: - options.append([arg1,arg2]) - return options + #retrieve options provided in varargin + arguments = pairoptions.pairoptions(*args) + + options = [['toolkit', 'petsc'], + ['mat_type', 'mpiaij'], + ['ksp_type', 'cg'], + ['ksp_max_it', 100], + ['ksp_rtol', 1e-15]] + + #now, go through our arguments, and write over default options. + for i in range(len(arguments.list)): + arg1 = arguments.list[i][0] + arg2 = arguments.list[i][1] + found = 0 + for j in range(len(options)): + joption = options[j][0] + if joption == arg1: + joption[1] = arg2 + options[j] = joption + found = 1 + break + if not found: + #this option did not exist, add it: + options.append([arg1, arg2]) + return options Index: /issm/trunk-jpl/src/m/solvers/matlaboptions.py =================================================================== --- /issm/trunk-jpl/src/m/solvers/matlaboptions.py (revision 24212) +++ /issm/trunk-jpl/src/m/solvers/matlaboptions.py (revision 24213) @@ -1,29 +1,31 @@ import pairoptions + def matlaboptions(*args): - #MATLABOPTIONS - return Matlab petsc options - # - # Usage: - # options=matlaboptions; - - #retrieve options provided in varargin - arguments=pairoptions.pairoptions(*args) - - options=[['toolkit','petsc'],['ksp_type','matlab']]; + #MATLABOPTIONS - return Matlab petsc options + # + # Usage: + # options = matlaboptions - #now, go through our arguments, and write over default options. - for i in range(len(arguments.list)): - arg1=arguments.list[i][0] - arg2=arguments.list[i][1] - found=0; - for j in range(len(options)): - joption=options[j][0] - if joption==arg1: - joption[1]=arg2; - options[j]=joption; - found=1; - break - if not found: - #this option did not exist, add it: - options.append([arg1,arg2]) - return options + #retrieve options provided in varargin + arguments = pairoptions.pairoptions(*args) + + options = [['toolkit', 'petsc'], + ['ksp_type', 'matlab']] + + #now, go through our arguments, and write over default options. + for i in range(len(arguments.list)): + arg1 = arguments.list[i][0] + arg2 = arguments.list[i][1] + found = 0 + for j in range(len(options)): + joption = options[j][0] + if joption == arg1: + joption[1] = arg2 + options[j] = joption + found = 1 + break + if not found: + #this option did not exist, add it: + options.append([arg1, arg2]) + return options Index: /issm/trunk-jpl/src/m/solvers/mumpsoptions.py =================================================================== --- /issm/trunk-jpl/src/m/solvers/mumpsoptions.py (revision 24212) +++ /issm/trunk-jpl/src/m/solvers/mumpsoptions.py (revision 24213) @@ -3,35 +3,36 @@ from IssmConfig import IssmConfig + def mumpsoptions(*args): - """ - MUMPSOPTIONS - return MUMPS direct solver petsc options + """ + MUMPSOPTIONS - return MUMPS direct solver petsc options - Usage: - options=mumpsoptions; - """ + Usage: + options = mumpsoptions + """ - #retrieve options provided in varargin - options=pairoptions.pairoptions(*args) - mumps=OrderedDict() + #retrieve options provided in varargin + options = pairoptions.pairoptions(*args) + mumps = OrderedDict() - #default mumps options - PETSC_MAJOR=IssmConfig('_PETSC_MAJOR_')[0] - PETSC_MINOR=IssmConfig('_PETSC_MINOR_')[0] - if PETSC_MAJOR==2.: - mumps['toolkit']='petsc' - mumps['mat_type']=options.getfieldvalue('mat_type','aijmumps') - mumps['ksp_type']=options.getfieldvalue('ksp_type','preonly') - mumps['pc_type']=options.getfieldvalue('pc_type','lu') - mumps['mat_mumps_icntl_14']=options.getfieldvalue('mat_mumps_icntl_14',120) - if PETSC_MAJOR==3.: - mumps['toolkit']='petsc' - mumps['mat_type']=options.getfieldvalue('mat_type','mpiaij') - mumps['ksp_type']=options.getfieldvalue('ksp_type','preonly') - mumps['pc_type']=options.getfieldvalue('pc_type','lu') - if PETSC_MINOR>8.: - mumps['pc_factor_mat_solver_type']=options.getfieldvalue('pc_factor_mat_solver_type','mumps') - else: - mumps['pc_factor_mat_solver_package']=options.getfieldvalue('pc_factor_mat_solver_package','mumps') - mumps['mat_mumps_icntl_14']=options.getfieldvalue('mat_mumps_icntl_14',120) + #default mumps options + PETSC_MAJOR = IssmConfig('_PETSC_MAJOR_')[0] + PETSC_MINOR = IssmConfig('_PETSC_MINOR_')[0] + if PETSC_MAJOR == 2.: + mumps['toolkit'] = 'petsc' + mumps['mat_type'] = options.getfieldvalue('mat_type', 'aijmumps') + mumps['ksp_type'] = options.getfieldvalue('ksp_type', 'preonly') + mumps['pc_type'] = options.getfieldvalue('pc_type', 'lu') + mumps['mat_mumps_icntl_14'] = options.getfieldvalue('mat_mumps_icntl_14', 120) + if PETSC_MAJOR == 3.: + mumps['toolkit'] = 'petsc' + mumps['mat_type'] = options.getfieldvalue('mat_type', 'mpiaij') + mumps['ksp_type'] = options.getfieldvalue('ksp_type', 'preonly') + mumps['pc_type'] = options.getfieldvalue('pc_type', 'lu') + if PETSC_MINOR > 8.: + mumps['pc_factor_mat_solver_type'] = options.getfieldvalue('pc_factor_mat_solver_type', 'mumps') + else: + mumps['pc_factor_mat_solver_package'] = options.getfieldvalue('pc_factor_mat_solver_package', 'mumps') + mumps['mat_mumps_icntl_14'] = options.getfieldvalue('mat_mumps_icntl_14', 120) - return mumps + return mumps Index: /issm/trunk-jpl/src/m/solvers/soroptions.py =================================================================== --- /issm/trunk-jpl/src/m/solvers/soroptions.py (revision 24212) +++ /issm/trunk-jpl/src/m/solvers/soroptions.py (revision 24213) @@ -1,29 +1,35 @@ import pairoptions + def soroptions(*args): - #SOROPTIONS - return Relaxation Solver petsc options - # - # Usage: - # options=soroptions; - - #retrieve options provided in varargin - arguments=pairoptions.pairoptions(*args) - - options=[['toolkit','petsc'],['mat_type','mpiaij'],['ksp_type','cg'],['pc_type','sor'],['pc_sor_omega',1.1],['pc_sor_its',2]]; + #SOROPTIONS - return Relaxation Solver petsc options + # + # Usage: + # options = soroptions - #now, go through our arguments, and write over default options. - for i in range(len(arguments.list)): - arg1=arguments.list[i][0] - arg2=arguments.list[i][1] - found=0; - for j in range(len(options)): - joption=options[j][0] - if joption==arg1: - joption[1]=arg2; - options[j]=joption; - found=1; - break - if not found: - #this option did not exist, add it: - options.append([arg1,arg2]) - return options + #retrieve options provided in varargin + arguments = pairoptions.pairoptions(*args) + + options = [['toolkit', 'petsc'], + ['mat_type', 'mpiaij'], + ['ksp_type', 'cg'], + ['pc_type', 'sor'], + ['pc_sor_omega', 1.1], + ['pc_sor_its', 2]] + + #now, go through our arguments, and write over default options. + for i in range(len(arguments.list)): + arg1 = arguments.list[i][0] + arg2 = arguments.list[i][1] + found = 0 + for j in range(len(options)): + joption = options[j][0] + if joption == arg1: + joption[1] = arg2 + options[j] = joption + found = 1 + break + if not found: + #this option did not exist, add it: + options.append([arg1, arg2]) + return options Index: /issm/trunk-jpl/src/m/solvers/stokesoptions.py =================================================================== --- /issm/trunk-jpl/src/m/solvers/stokesoptions.py (revision 24212) +++ /issm/trunk-jpl/src/m/solvers/stokesoptions.py (revision 24213) @@ -2,38 +2,44 @@ from IssmConfig import IssmConfig + def stokesoptions(*args): - #STOKESOPTIONS - return STOKES multi-physics solver petsc options - # - # Usage: - # options=stokesoptions; - - #retrieve options provided in varargin - arguments=pairoptions.pairoptions(*args) + #STOKESOPTIONS - return STOKES multi - physics solver petsc options + # + # Usage: + # options = stokesoptions + #retrieve options provided in varargin + arguments = pairoptions.pairoptions(*args) - #default stokes options - PETSC_VERSION=IssmConfig('_PETSC_MAJOR_')[0] + #default stokes options + PETSC_VERSION = IssmConfig('_PETSC_MAJOR_')[0] - if PETSC_VERSION==2.: - raise RuntimeError('stokesoptions error message: multi-physics options not supported in Petsc 2') - if PETSC_VERSION==3.: - options=[['toolkit','petsc'],['mat_type','mpiaij'],['ksp_type','cr'],['pc_type','bjacobi'],['tol',0.6],\ - ['elltol',5e-5],['schur_pc',1],\ - ['max_iter',10000],['issm_option_solver','stokes']] + if PETSC_VERSION == 2.: + raise RuntimeError('stokesoptions error message: multi-physics options not supported in Petsc 2') + if PETSC_VERSION == 3.: + options = [['toolkit', 'petsc'], + ['mat_type', 'mpiaij'], + ['ksp_type', 'cr'], + ['pc_type', 'bjacobi'], + ['tol', 0.6], + ['elltol', 5e-5], + ['schur_pc', 1], + ['max_iter', 10000], + ['issm_option_solver', 'stokes']] - #now, go through our arguments, and write over default options. - for i in range(len(arguments.list)): - arg1=arguments.list[i][0] - arg2=arguments.list[i][1] - found=0; - for j in range(len(options)): - joption=options[j][0] - if joption==arg1: - joption[1]=arg2; - options[j]=joption; - found=1; - break - if not found: - #this option did not exist, add it: - options.append([arg1,arg2]) - return options + #now, go through our arguments, and write over default options. + for i in range(len(arguments.list)): + arg1 = arguments.list[i][0] + arg2 = arguments.list[i][1] + found = 0 + for j in range(len(options)): + joption = options[j][0] + if joption == arg1: + joption[1] = arg2 + options[j] = joption + found = 1 + break + if not found: + #this option did not exist, add it: + options.append([arg1, arg2]) + return options