DAMASK_EICMD/processing/post/addStrainTensors.py

#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-

import os,sys,string
import numpy as np
from collections import defaultdict
from optparse import OptionParser
import damask

scriptID   = string.replace('$Id$','\n','\\n')
scriptName = os.path.splitext(scriptID.split()[1])[0]

def operator(stretch,strain,eigenvalues):
  return {
    'V#ln':    np.log(eigenvalues)                                 ,
    'U#ln':    np.log(eigenvalues)                                 ,
    'V#Biot':  ( np.ones(3,'d') - 1.0/eigenvalues )                ,
    'U#Biot':  ( eigenvalues - np.ones(3,'d') )                    ,
    'V#Green': ( np.ones(3,'d') - 1.0/eigenvalues*eigenvalues) *0.5,
    'U#Green': ( eigenvalues*eigenvalues - np.ones(3,'d'))     *0.5,
         }[stretch+'#'+strain]


# --------------------------------------------------------------------
#                                MAIN
# --------------------------------------------------------------------

parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Add column(s) containing given strains based on given stretches of requested deformation gradient column(s).

""", version = scriptID)

parser.add_option('-u','--right',       dest='right', action='store_true',
                  help='material strains based on right Cauchy--Green deformation, i.e., C and U')
parser.add_option('-v','--left',        dest='left', action='store_true',
                  help='spatial strains based on left Cauchy--Green deformation, i.e., B and V')
parser.add_option('-0','--logarithmic', dest='logarithmic', action='store_true',
                  help='calculate logarithmic strain tensor')
parser.add_option('-1','--biot',   dest='biot', action='store_true',
                  help='calculate biot strain tensor')
parser.add_option('-2','--green',  dest='green', action='store_true',
                  help='calculate green strain tensor')
parser.add_option('-f','--defgrad',     dest='defgrad', action='extend', metavar = '<string LIST>',
                  help='heading(s) of columns containing deformation tensor values [%default]')
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')

# ------------------------------------------ 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(scriptID + '\t' + ' '.join(sys.argv[1:]))

# --------------- figure out columns to process  ---------------------------------------------------

  errors = []
  active = []
  for i,length in enumerate(table.label_dimension(options.defgrad)):
    if length == 9:
      active.append(options.defgrad[i])
    else:
      errors.append('no deformation gradient tensor (1..9_%s) found...'%options.defgrad[i])

  if errors != []:
    file['croak'].write('\n'.join(errors)+'\n')
    table.close(dismiss = True)
    continue

# ------------------------------------------ assemble header ---------------------------------------

  for label in active:
    for theStretch in stretches:
      for theStrain in strains:
        table.labels_append(['%i_%s(%s)%s'%(i+1,
                                            theStrain,
                                            theStretch,
                                            label if label != 'f' else '') for i in xrange(9)])               # extend ASCII header with new labels  
  table.head_write()

# ------------------------------------------ process data ------------------------------------------
  outputAlive = True
  while outputAlive and table.data_read():                                                          # read next data line of ASCII table
    for column in table.label_index(active):                                                        # loop over all requested norms
      F = np.array(map(float,table.data[column:column+9]),'d').reshape(3,3)
      (U,S,Vh) = np.linalg.svd(F)
      R = np.dot(U,Vh)
      stretch['U'] = np.dot(np.linalg.inv(R),F)
      stretch['V'] = np.dot(F,np.linalg.inv(R))
      for theStretch in stretches:
        for i in xrange(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) = np.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 np.dot(V[:,i],V[:,(i+1)%3]) != 0.0:                                                      # check each vector for orthogonality
            V[:,(i+1)%3] = np.cross(V[:,(i+2)%3],V[:,i])                                            # correct next vector
            V[:,(i+1)%3] /= np.sqrt(np.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 = (np.dot(V,np.dot(np.diag(d),V.T)).real).reshape(9)                                  # build tensor back from eigenvalue/vector basis

          table.data_append(list(eps))
    outputAlive = table.data_write()                                                                # output processed line

# ------------------------------------------ output result -----------------------------------------
  outputAlive and table.output_flush()                                                              # just in case of buffered ASCII table

  table.close()                                                                                     # close ASCII table
  if file['name'] != 'STDIN':
    os.rename(file['name']+'_tmp',file['name'])                                                     # overwrite old one with tmp new