#!/usr/bin/python import os,re,sys,math,numpy,string from optparse import OptionParser, Option def operator(how,vector): return { \ 'ln': numpy.log(vector)*1.0,\ 'Biot': vector *1.0,\ 'Green': vector*vector *0.5,\ }[how] # ----------------------------- 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 prefixMultiply(what,len): return {True: ['%i_%s'%(i+1,what) for i in range(len)], False:[what]}[len>1] # -------------------------------------------------------------------- # 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('$Id$','\n','\\n') ) parser.add_option('-m','--memory', dest='memory', action='store_true', \ help='load complete file into memory [%default]') parser.add_option('-u','--right', action='store_true', dest='right', \ help='calculate strains based on right Cauchy--Green deformation, i.e., C and U') parser.add_option('-v','--left', action='store_true', dest='left', \ help='calculate strains based on left Cauchy--Green deformation, i.e., B and V') parser.add_option('-l','--logarithmic', action='store_true', dest='logarithmic', \ help='calculate logarithmic strain tensor') parser.add_option('-b','--biot', action='store_true', dest='biot', \ help='calculate biot strain tensor') parser.add_option('-g','--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 %default') parser.set_defaults(memory = False) 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 = ['f']) (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 != None: datainfo['defgrad']['label'] += options.defgrad # ------------------------------------------ setup file handles --------------------------------------- files = [] if filenames == []: files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout}) else: for name in filenames: if os.path.exists(name): files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w')}) # ------------------------------------------ loop over input files --------------------------------------- for file in files: print file['name'] # get labels by either read the first row, or - if keyword header is present - the last line of the header firstline = file['input'].readline() m = re.search('(\d+)\s*head', firstline.lower()) if m: headerlines = int(m.group(1)) passOn = [file['input'].readline() for i in range(1,headerlines)] headers = file['input'].readline().split() else: headerlines = 1 passOn = [] headers = firstline.split() if options.memory: data = file['input'].readlines() else: data = [] for i,l in enumerate(headers): if l.startswith('1_'): if re.match('\d+_',l[2:]) or i == len(headers)-1 or not headers[i+1].endswith(l[2:]): headers[i] = l[2:] 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 headers: 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] = headers.index(key) for theStretch in stretches: for theStrain in strains: head += prefixMultiply('%s(%s)'%(theStrain,theStretch), 9) # ------------------------------------------ assemble header --------------------------------------- output = '%i\theader'%(headerlines+1) + '\n' + \ ''.join(passOn) + \ string.replace('$Id$','\n','\\n')+ '\t' + \ ' '.join(sys.argv[1:]) + '\n' + \ '\t'.join(headers + head) + '\n' # build extended header if not options.memory: file['output'].write(output) output = '' # ------------------------------------------ read file --------------------------------------- for line in {True : data, False : file['input']}[options.memory]: items = line.split()[:len(headers)] if len(items) < len(headers): continue output += '\t'.join(items) for datatype,labels in active.items(): for label in labels: defgrad = numpy.array(map(float,items[column[datatype][label]: column[datatype][label]+datainfo[datatype]['len']]),'d').reshape(3,3) (U,S,Vh) = numpy.linalg.svd(defgrad) R = numpy.dot(U,Vh) stretch['U'] = numpy.dot(numpy.linalg.inv(R),defgrad) stretch['V'] = numpy.dot(defgrad,numpy.linalg.inv(R)) for theStretch in stretches: for i in range(9): if stretch[theStretch][i%3,i//3] < 1e-15: 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(theStrain,D) # operate on eigenvalues of U or V I = operator(theStrain,numpy.ones(3)) # operate on eigenvalues of I (i.e. [1,1,1]) eps = (numpy.dot(V,numpy.dot(numpy.diag(d),V.T)).real-numpy.diag(I)).reshape(9) # build tensor back from eigenvalue/vector basis output += '\t'+'\t'.join(map(str,eps)) output += '\n' if not options.memory: file['output'].write(output) output = '' file['input'].close() # ------------------------------------------ output result --------------------------------------- if options.memory: file['output'].write(output) if file['name'] != 'STDIN': file['output'].close os.rename(file['name']+'_tmp',file['name'])