#!/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'])