Index: /issm/trunk-jpl/src/m/contrib/defleurian/netCDF/export_netCDF.m =================================================================== --- /issm/trunk-jpl/src/m/contrib/defleurian/netCDF/export_netCDF.m (revision 27263) +++ /issm/trunk-jpl/src/m/contrib/defleurian/netCDF/export_netCDF.m (revision 27264) @@ -41,11 +41,18 @@ DimValue(2)=DimSize(2).value; % adding mesh related dimensions - dimlist=[2,40,md.mesh.numberofelements,md.mesh.numberofvertices,size(md.mesh.elements,2)]; + dimlist=[2 40 md.mesh.numberofelements md.mesh.numberofvertices size(md.mesh.elements,2)]; dimnames=["DictDummy" "StringLength" "EltNum" "VertNum" "VertPerElt"]; + if isprop(md.mesh, 'edges'), + dimlist(end+1)=md.mesh.numberofedges; + dimnames(end+1)="EdgeNum"; + else + dimlist(end+1)=0; + dimnames(end+1)="EdgeNum"; + end if verbose > 0, disp('===Creating dimensions ==='); end %define netcdf dimensions - for i=1:5 + for i=1:length(dimlist) % do not add the dimension if it exists already if sum(dimlist(i) == DimValue) == 0 @@ -61,8 +68,12 @@ for cl=1:length(issmclasses), - subclasses=fieldnames(md.(issmclasses{cl}))'; - for sc=1:length(subclasses), - if sum(strcmp(class(md.(issmclasses{cl}).(subclasses{sc})), typelist)) == 0, - issmclasses = [issmclasses class(md.(issmclasses{cl}).(subclasses{sc}))]; + if isempty(md.(issmclasses{cl})), + disp(sprintf("md.%s is empty and will be left as default",issmclasses{cl})); + else + subclasses=fieldnames(md.(issmclasses{cl}))'; + for sc=1:length(subclasses), + if sum(strcmp(class(md.(issmclasses{cl}).(subclasses{sc})), typelist)) == 0, + issmclasses = [issmclasses class(md.(issmclasses{cl}).(subclasses{sc}))]; + end end end @@ -83,4 +94,8 @@ groupID=netcdf.defGrp(ncid,groups{i}); %In each group gather the fields of the class + if isempty(md.(groups{i})), + disp(sprintf("WARNING: md.%s is empty, we skip it.",groups{i})) + continue + end fields=fieldnames(md.(groups{i})); if isempty(fields), @@ -169,5 +184,5 @@ elseif isa(Var,'struct') % structures need special treatment if strcmp(groups{i}, 'results'), - klasstring='results.results'; + klasstring=strcat(groups{i} ,'.', groups{i}); netcdf.putAtt(groupID,netcdf.getConstant('NC_GLOBAL'),'classtype',klasstring); Listsize= length(md.(groups{i}).(fields{j})); @@ -212,4 +227,16 @@ end end + elseif strcmp(groups{i}, 'toolkits'), + klasstring=strcat(groups{i} ,'.', groups{i}); + netcdf.putAtt(groupID,netcdf.getConstant('NC_GLOBAL'),'classtype',klasstring); + if verbose > 4, + disp(sprintf("=}{=creating var for %s.%s",groups{i}, fields{j})); + end + + [DimSize,DimValue,varid]=CreateVar(ncid,Var,groupID,fields{j},DimSize,DimValue); + if ~isempty(varid), + FillVar(Var,groupID,varid); + end + elseif isempty(fieldnames(md.(groups{i}).(fields{j}))) % this is an empty struct, jus treat it as normal klass=class(md.(groups{i})); @@ -399,26 +426,27 @@ elseif isa(Var,'struct'), %Start by getting the structure fields and size - locfields=fieldnames(Var) + locfields=fieldnames(Var); for i=1:length(locfields), for j=1:2, if j==1, - CharVar=locfields{i}; + CharVar=locfields{i}'; + disp(size(CharVar)) if length(CharVar)==0 CharVar='emptystruct'; end - startpoint=[i-1,0,0]; + startpoint=[0,0,i-1] else if isa(Var.(locfields{i}),'char'), - CharVar=Var.(locfields{i}); + CharVar=Var.(locfields{i})'; else - CharVar=num2str(Var.(locfields{i})); + CharVar=num2str(Var.(locfields{i}))'; end if length(CharVar)==0 CharVar='emptystruct'; end - startpoint=[i-1,1,0]; - end - - extent=[1,1,min(length(CharVar),40)]; + startpoint=[0,1,i-1] + end + + extent=[min(length(CharVar),40), 1, 1] if length(CharVar)>40, netcdf.putVar(groupID,varid,startpoint,extent,CharVar(1:40)); @@ -458,5 +486,5 @@ if dim>0, for i=1:alldim, - if size(Var, i)>1 || i>dim, %we skip dimensions with zero lenght but want to add dimensions from cells + if size(Var, i)>1 || i>dim || isa(Var, 'struct'), %we skip dimensions with zero lenght but want to add dimensions from cells indsize=find(varsize(i)==DimValue); if length(indsize)>0 @@ -478,5 +506,5 @@ % struct also need an extra dimension 2, but only if non empty if isa(Var,'struct'), - dims=[dims DimSize(3).index DimSize(4).index]; + dims=[DimSize(4).index DimSize(3).index, dims]; end end Index: /issm/trunk-jpl/src/m/contrib/defleurian/netCDF/export_netCDF.py =================================================================== --- /issm/trunk-jpl/src/m/contrib/defleurian/netCDF/export_netCDF.py (revision 27263) +++ /issm/trunk-jpl/src/m/contrib/defleurian/netCDF/export_netCDF.py (revision 27264) @@ -99,4 +99,11 @@ dimlist = [2, 40, md.mesh.numberofelements, md.mesh.numberofvertices, np.shape(md.mesh.elements)[1]] dimnames = ['DictDummy', 'StringLength', 'EltNum', 'VertNum', 'VertPerElt'] + try: + dimlist = dimlist + [md.mesh.numberofedges] + dimnames = dimnames + ['EdgeNum'] + except AttributeError: + #no edges on this mesh, we fix it at 0 + dimlist += [0] + dimnames += ['EdgeNum'] if verbose > 0: print('===Creating dimensions ===') @@ -315,5 +322,4 @@ if val_type.startswith(' 0: @@ -184,6 +192,10 @@ else: groupclass = [curclass] - #==== We deal with Variables {{{ for groupindex, listclass in enumerate(groupclass): + try: + soltype = str(getattr(listclass, 'SolutionType')) + except AttributeError: + soltype = 'NoSol' + #==== We deal with Variables {{{ for var in listclass.variables: if not resname or var == resname: @@ -217,9 +229,11 @@ else: print('table dimension greater than 3 not implemented yet') + elif soltype in SteadySols: + Tree.__dict__[str(var)] = varval[:].data else: #old format had step sorted in difeerent group so last group is last time Tree[0].__dict__[str(var)] = varval[:].data else: if NewFormat: - incomplete = 'Time' not in varval.dimensions + incomplete = 'Time' not in varval.dimensions and soltype not in SteadySols if incomplete: try: @@ -230,22 +244,27 @@ #just one step, so no dimension, we just put it on the first solutionstep timelist = [0] + elif soltype in SteadySols: + timelist = [0] else: timelist = np.arange(0, len(NCFile.dimensions['Time'])) - for t in timelist: - if verbose > 5: - print("filing step {} for {}".format(t, var)) - if vardim == 0: - Tree[t].__dict__[str(var)] = varval[:].data - elif vardim == 1: - stepval = ma.masked_array(varval[t].data, mask=np.where(np.isnan(varval[t]), 1, 0)) - Tree[t].__dict__[str(var)] = ma.compressed(stepval) - elif vardim == 2: - stepval = ma.masked_array(varval[t, :].data, mask=np.where(np.isnan(varval[t, :]), 1, 0)) - Tree[t].__dict__[str(var)] = ma.compressed(stepval) - elif vardim == 3: - stepval = ma.masked_array(varval[t, :, :].data, mask=np.where(np.isnan(varval[t, :, :]), 1, 0)) - Tree[t].__dict__[str(var)] = ma.compressed(stepval).reshape((stepval.count(0)[0], stepval.count(1)[0])) - else: - print('table dimension greater than 3 not implemented yet') + if soltype in SteadySols: + Tree.__dict__[str(var)] = varval[:].data + else: + for t in timelist: + if verbose > 5: + print("filing step {} for {}".format(t, var)) + if vardim == 0: + Tree[t].__dict__[str(var)] = varval[:].data + elif vardim == 1: + stepval = ma.masked_array(varval[t].data, mask=np.where(np.isnan(varval[t]), 1, 0)) + Tree[t].__dict__[str(var)] = ma.compressed(stepval) + elif vardim == 2: + stepval = ma.masked_array(varval[t, :].data, mask=np.where(np.isnan(varval[t, :]), 1, 0)) + Tree[t].__dict__[str(var)] = ma.compressed(stepval) + elif vardim == 3: + stepval = ma.masked_array(varval[t, :, :].data, mask=np.where(np.isnan(varval[t, :, :]), 1, 0)) + Tree[t].__dict__[str(var)] = ma.compressed(stepval).reshape((stepval.count(0)[0], stepval.count(1)[0])) + else: + print('table dimension greater than 3 not implemented yet') else: if verbose > 0: @@ -315,5 +334,17 @@ Tree.__dict__[str(var)] = varval[:, :].data elif vardim == 3: - Tree.__dict__[str(var)] = varval[:, :, :].data + if varval.dtype == "|S1": #that is for matlab chararcter arrays + #most likely that is a toolkit dictionar so should be treated as such + #first we convert the character table to strings + stringtable = [] + for i in range(np.shape(varval)[0]): + stringtable.append([chartostring(varval[i, 0, :]), chartostring(varval[i, 1, :])]) + stringtable = np.asarray(stringtable, dtype=str) + Tree.__dict__[str(var)] = OrderedDict([('toolkit', str(varval[np.where(stringtable[:, 0] == 'toolkit')[0][0], 1]))]) + strings1 = [str(arg[0]) for arg in stringtable if arg[0] != 'toolkits'] + strings2 = [str(arg[1]) for arg in stringtable if arg[0] != 'toolkits'] + Tree.__dict__[str(var)].update(list(zip(strings1, strings2))) + else: + Tree.__dict__[str(var)] = varval[:, :, :].data else: print('table dimension greater than 3 not implemented yet') @@ -387,9 +418,10 @@ if class_dict[classe][0] not in ['dict', 'list', 'cell']: modulename = split(r'\.', class_dict[classe][0])[0] - if modulename == "giaivins": - print("WARNING: module {} does not exist anymore and is skipped".format(modulename)) - else: + try: class_dict[classe].append(import_module(modulename)) class_tree[classe] = [group, ] + except ModuleNotFoundError: + print("WARNING: module {} does not exist anymore and is skipped".format(modulename)) + except AttributeError: print(('group {} is empty'.format(group)))