source: issm/trunk/src/m/qmu/setupdesign/QmuSetupVariables.py@ 23189

from MatlabFuncs import *
from uniform_uncertain import*
from normal_uncertain import *
from copy import deepcopy

def QmuSetupVariables(md,dvar,variables):

        #get descriptor
        descriptor=variables.descriptor

        #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. 

        #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')
                        
                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, 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 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

                        # 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)+"'"

        return dvar