216 lines
8.2 KiB
Python
216 lines
8.2 KiB
Python
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#!/usr/bin/python
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import os,re,sys,math,numpy,string
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from optparse import OptionParser, Option
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def operator(how,vector):
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return { \
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'ln': numpy.log(vector)*1.0,\
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'Biot': vector *1.0,\
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'Green': vector*vector *0.5,\
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}[how]
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# -----------------------------
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class extendableOption(Option):
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# -----------------------------
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# used for definition of new option parser action 'extend', which enables to take multiple option arguments
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# taken from online tutorial http://docs.python.org/library/optparse.html
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ACTIONS = Option.ACTIONS + ("extend",)
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STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
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TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
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ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
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def take_action(self, action, dest, opt, value, values, parser):
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if action == "extend":
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lvalue = value.split(",")
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values.ensure_value(dest, []).extend(lvalue)
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else:
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Option.take_action(self, action, dest, opt, value, values, parser)
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def prefixMultiply(what,len):
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return {True: ['%i_%s'%(i+1,what) for i in range(len)],
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False:[what]}[len>1]
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
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Add column(s) containing given strains based on given stretches of requested deformation gradient column(s).
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""" + string.replace('$Id$','\n','\\n')
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)
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parser.add_option('-m','--memory', dest='memory', action='store_true', \
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help='load complete file into memory [%default]')
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parser.add_option('-u','--right', action='store_true', dest='right', \
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help='calculate strains based on right Cauchy--Green deformation, i.e., C and U')
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parser.add_option('-v','--left', action='store_true', dest='left', \
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help='calculate strains based on left Cauchy--Green deformation, i.e., B and V')
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parser.add_option('-l','--logarithmic', action='store_true', dest='logarithmic', \
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help='calculate logarithmic strain tensor')
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parser.add_option('-b','--biot', action='store_true', dest='biot', \
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help='calculate biot strain tensor')
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parser.add_option('-g','--green', action='store_true', dest='green', \
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help='calculate green strain tensor')
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parser.add_option('-f','--deformation', dest='defgrad', action='extend', type='string', \
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help='heading(s) of columns containing deformation tensor values %default')
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parser.set_defaults(memory = False)
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parser.set_defaults(right = False)
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parser.set_defaults(left = False)
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parser.set_defaults(logarithmic = False)
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parser.set_defaults(biot = False)
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parser.set_defaults(green = False)
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parser.set_defaults(defgrad = ['f'])
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(options,filenames) = parser.parse_args()
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stretches = []
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stretch = {}
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strains = []
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if options.right: stretches.append('U')
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if options.left: stretches.append('V')
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if options.logarithmic: strains.append('ln')
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if options.biot: strains.append('Biot')
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if options.green: strains.append('Green')
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datainfo = { # list of requested labels per datatype
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'defgrad': {'len':9,
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'label':[]},
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}
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if options.defgrad != None: datainfo['defgrad']['label'] += options.defgrad
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# ------------------------------------------ setup file handles ---------------------------------------
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files = []
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if filenames == []:
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files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout})
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else:
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for name in filenames:
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if os.path.exists(name):
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files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w')})
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# ------------------------------------------ loop over input files ---------------------------------------
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for file in files:
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print file['name']
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# get labels by either read the first row, or - if keyword header is present - the last line of the header
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firstline = file['input'].readline()
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m = re.search('(\d+)\s*head', firstline.lower())
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if m:
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headerlines = int(m.group(1))
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passOn = [file['input'].readline() for i in range(1,headerlines)]
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headers = file['input'].readline().split()
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else:
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headerlines = 1
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passOn = []
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headers = firstline.split()
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if options.memory:
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data = file['input'].readlines()
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else:
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data = []
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for i,l in enumerate(headers):
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if l.startswith('1_'):
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if re.match('\d+_',l[2:]) or i == len(headers)-1 or not headers[i+1].endswith(l[2:]):
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headers[i] = l[2:]
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active = {}
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column = {}
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head = []
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for datatype,info in datainfo.items():
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for label in info['label']:
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key = {True :'1_%s',
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False:'%s' }[info['len']>1]%label
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if key not in headers:
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sys.stderr.write('column %s not found...\n'%key)
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else:
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if datatype not in active: active[datatype] = []
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if datatype not in column: column[datatype] = {}
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active[datatype].append(label)
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column[datatype][label] = headers.index(key)
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for theStretch in stretches:
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for theStrain in strains:
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head += prefixMultiply('%s(%s)'%(theStrain,theStretch), 9)
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# ------------------------------------------ assemble header ---------------------------------------
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output = '%i\theader'%(headerlines+1) + '\n' + \
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''.join(passOn) + \
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string.replace('$Id$','\n','\\n')+ '\t' + \
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' '.join(sys.argv[1:]) + '\n' + \
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'\t'.join(headers + head) + '\n' # build extended header
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if not options.memory:
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file['output'].write(output)
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output = ''
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# ------------------------------------------ read file ---------------------------------------
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for line in {True : data,
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False : file['input']}[options.memory]:
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items = line.split()[:len(headers)]
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if len(items) < len(headers):
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continue
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output += '\t'.join(items)
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for datatype,labels in active.items():
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for label in labels:
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defgrad = numpy.array(map(float,items[column[datatype][label]:
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column[datatype][label]+datainfo[datatype]['len']]),'d').reshape(3,3)
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(U,S,Vh) = numpy.linalg.svd(defgrad)
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R = numpy.dot(U,Vh)
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stretch['U'] = numpy.dot(numpy.linalg.inv(R),defgrad)
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stretch['V'] = numpy.dot(defgrad,numpy.linalg.inv(R))
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for theStretch in stretches:
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for i in range(9):
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if stretch[theStretch][i%3,i//3] < 1e-15:
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stretch[theStretch][i%3,i//3] = 0.0
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(D,V) = numpy.linalg.eig(stretch[theStretch]) # eigen decomposition (of symmetric matrix)
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for i,eigval in enumerate(D):
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if eigval < 0.0: # flip negative eigenvalues
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D[i] = -D[i]
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V[:,i] = -V[:,i]
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if numpy.dot(V[:,i],V[:,(i+1)%3]) != 0.0: # check each vector for orthogonality
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V[:,(i+1)%3] = numpy.cross(V[:,(i+2)%3],V[:,i]) # correct next vector
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V[:,(i+1)%3] /= numpy.sqrt(numpy.dot(V[:,(i+1)%3],V[:,(i+1)%3].conj())) # and renormalize (hyperphobic?)
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for theStrain in strains:
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d = operator(theStrain,D) # operate on eigenvalues of U or V
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I = operator(theStrain,numpy.ones(3)) # operate on eigenvalues of I (i.e. [1,1,1])
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eps = (numpy.dot(V,numpy.dot(numpy.diag(d),V.T)).real-numpy.diag(I)).reshape(9) # build tensor back from eigenvalue/vector basis
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output += '\t'+'\t'.join(map(str,eps))
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output += '\n'
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if not options.memory:
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file['output'].write(output)
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output = ''
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file['input'].close()
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# ------------------------------------------ output result ---------------------------------------
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if options.memory:
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file['output'].write(output)
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if file['name'] != 'STDIN':
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file['output'].close
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os.rename(file['name']+'_tmp',file['name'])
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