#!/usr/bin/env python import os,re,sys,math,numpy,string,damask from optparse import OptionParser, Option scriptID = '$Id$' scriptName = scriptID.split()[1] # ----------------------------- class extendableOption(Option): # ----------------------------- # used for definition of new option parser action 'extend', which enables to take multiple option arguments # taken from online tutorial http://docs.python.org/library/optparse.html ACTIONS = Option.ACTIONS + ("extend",) STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",) TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",) ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",) def take_action(self, action, dest, opt, value, values, parser): if action == "extend": lvalue = value.split(",") values.ensure_value(dest, []).extend(lvalue) else: Option.take_action(self, action, dest, opt, value, values, parser) def operator(stretch,strain,eigenvalues): return { \ 'V#ln': numpy.log(eigenvalues) , 'U#ln': numpy.log(eigenvalues) , 'V#Biot': ( numpy.ones(3,'d') - 1.0/eigenvalues ) , 'U#Biot': ( eigenvalues - numpy.ones(3,'d') ) , 'V#Green': ( numpy.ones(3,'d') - 1.0/eigenvalues*eigenvalues) *0.5, 'U#Green': ( eigenvalues*eigenvalues - numpy.ones(3,'d')) *0.5, }[stretch+'#'+strain] # -------------------------------------------------------------------- # MAIN # -------------------------------------------------------------------- parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """ Add column(s) containing given strains based on given stretches of requested deformation gradient column(s). """ + string.replace(scriptID,'\n','\\n') ) parser.add_option('-u','--right', action='store_true', dest='right', \ help='material strains based on right Cauchy--Green deformation, i.e., C and U') parser.add_option('-v','--left', action='store_true', dest='left', \ help='spatial strains based on left Cauchy--Green deformation, i.e., B and V') parser.add_option('-l','-0','--logarithmic', action='store_true', dest='logarithmic', \ help='calculate logarithmic strain tensor') parser.add_option('-b','-1','--biot', action='store_true', dest='biot', \ help='calculate biot strain tensor') parser.add_option('-g','-2','--green', action='store_true', dest='green', \ help='calculate green strain tensor') parser.add_option('-f','--deformation', dest='defgrad', action='extend', type='string', \ help='heading(s) of columns containing deformation tensor values [f]') parser.set_defaults(right = False) parser.set_defaults(left = False) parser.set_defaults(logarithmic = False) parser.set_defaults(biot = False) parser.set_defaults(green = False) parser.set_defaults(defgrad = []) (options,filenames) = parser.parse_args() stretches = [] stretch = {} strains = [] if options.right: stretches.append('U') if options.left: stretches.append('V') if options.logarithmic: strains.append('ln') if options.biot: strains.append('Biot') if options.green: strains.append('Green') datainfo = { # list of requested labels per datatype 'defgrad': {'len':9, 'label':[]}, } if options.defgrad == []: datainfo['defgrad']['label'] = ['f'] else: datainfo['defgrad']['label'] = options.defgrad # ------------------------------------------ setup file handles --------------------------------------- files = [] if filenames == []: files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout, 'croak':sys.stderr}) else: for name in filenames: if os.path.exists(name): files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w'), 'croak':sys.stderr}) # ------------------------------------------ loop over input files --------------------------------------- for file in files: if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n') else: file['croak'].write('\033[1m'+scriptName+'\033[0m\n') table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table table.head_read() # read ASCII header info table.info_append(string.replace(scriptID,'\n','\\n') + '\t' + ' '.join(sys.argv[1:])) active = {} column = {} head = [] for datatype,info in datainfo.items(): for label in info['label']: key = {True :'1_%s', False:'%s' }[info['len']>1]%label if key not in table.labels: sys.stderr.write('column %s not found...\n'%key) else: if datatype not in active: active[datatype] = [] if datatype not in column: column[datatype] = {} active[datatype].append(label) column[datatype][label] = table.labels.index(key) for theStretch in stretches: for theStrain in strains: table.labels_append(['%i_%s(%s)%s'%(i+1,theStrain,theStretch, {True: label,False: ''}[label!='f']) for i in xrange(datainfo['defgrad']['len'])]) # extend ASCII header with new labels # ------------------------------------------ assemble header --------------------------------------- table.head_write() # ------------------------------------------ process data --------------------------------------- while table.data_read(): # read next data line of ASCII table for datatype,labels in active.items(): # loop over vector,tensor for label in labels: # loop over all requested norms F = numpy.array(map(float,table.data[column['defgrad'][active['defgrad'][0]]: column['defgrad'][active['defgrad'][0]]+datainfo['defgrad']['len']]),'d').reshape(3,3) (U,S,Vh) = numpy.linalg.svd(F) R = numpy.dot(U,Vh) stretch['U'] = numpy.dot(numpy.linalg.inv(R),F) stretch['V'] = numpy.dot(F,numpy.linalg.inv(R)) for theStretch in stretches: for i in range(9): if abs(stretch[theStretch][i%3,i//3]) < 1e-12: # kill nasty noisy data stretch[theStretch][i%3,i//3] = 0.0 (D,V) = numpy.linalg.eig(stretch[theStretch]) # eigen decomposition (of symmetric matrix) for i,eigval in enumerate(D): if eigval < 0.0: # flip negative eigenvalues D[i] = -D[i] V[:,i] = -V[:,i] if numpy.dot(V[:,i],V[:,(i+1)%3]) != 0.0: # check each vector for orthogonality V[:,(i+1)%3] = numpy.cross(V[:,(i+2)%3],V[:,i]) # correct next vector V[:,(i+1)%3] /= numpy.sqrt(numpy.dot(V[:,(i+1)%3],V[:,(i+1)%3].conj())) # and renormalize (hyperphobic?) for theStrain in strains: d = operator(theStretch,theStrain,D) # operate on eigenvalues of U or V eps = (numpy.dot(V,numpy.dot(numpy.diag(d),V.T)).real).reshape(9) # build tensor back from eigenvalue/vector basis table.data_append(list(eps)) table.data_write() # output processed line # ------------------------------------------ output result --------------------------------------- table.output_flush() # just in case of buffered ASCII table file['input'].close() # close input ASCII table if file['name'] != 'STDIN': file['output'].close # close output ASCII table os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new