DAMASK_EICMD/processing/post/addStrainTensors.py

159 lines
6.7 KiB
Python
Executable File

#!/usr/bin/env python3
import os
import sys
from optparse import OptionParser
import numpy as np
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
def operator(stretch,strain,eigenvalues):
"""Albrecht Bertram: Elasticity and Plasticity of Large Deformations An Introduction (3rd Edition, 2012), p. 102."""
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 [ASCIItable(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(
defgrad = ['f'],
)
(options,filenames) = parser.parse_args()
if len(options.defgrad) > 1:
options.defgrad = options.defgrad[1:]
stretches = []
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')
if options.defgrad is None:
parser.error('no data column specified.')
# --- loop over input files -------------------------------------------------------------------------
if filenames == []: filenames = [None]
for name in filenames:
try:
table = damask.ASCIItable(name = name,
buffered = False)
except IOError: continue
damask.util.report(scriptName,name)
# ------------------------------------------ read header ------------------------------------------
table.head_read()
# ------------------------------------------ sanity checks ----------------------------------------
items = {
'tensor': {'dim': 9, 'shape': [3,3], 'labels':options.defgrad, 'column': []},
}
errors = []
remarks = []
for type, data in items.items():
for what in data['labels']:
dim = table.label_dimension(what)
if dim != data['dim']: remarks.append('column {} is not a {}...'.format(what,type))
else:
items[type]['column'].append(table.label_index(what))
for theStretch in stretches:
for theStrain in strains:
table.labels_append(['{}_{}({}){}'.format(i+1, # extend ASCII header with new labels
theStrain,
theStretch,
what if what != 'f' else '') for i in range(9)])
if remarks != []: damask.util.croak(remarks)
if errors != []:
damask.util.croak(errors)
table.close(dismiss = True)
continue
# ------------------------------------------ assemble header --------------------------------------
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
table.head_write()
# ------------------------------------------ process data ------------------------------------------
stretch = {}
outputAlive = True
while outputAlive and table.data_read(): # read next data line of ASCII table
for column in items['tensor']['column']: # loop over all requested defgrads
F = np.array(list(map(float,table.data[column:column+items['tensor']['dim']])),'d').reshape(items['tensor']['shape'])
(U,S,Vh) = np.linalg.svd(F) # singular value decomposition
R_inv = np.dot(U,Vh).T # rotation of polar decomposition
stretch['U'] = np.dot(R_inv,F) # F = RU
stretch['V'] = np.dot(F,R_inv) # F = VR
for theStretch in stretches:
stretch[theStretch] = np.where(abs(stretch[theStretch]) < 1e-12, 0, stretch[theStretch]) # kill nasty noisy data
(D,V) = np.linalg.eigh((stretch[theStretch]+stretch[theStretch].T)*0.5) # eigen decomposition (of symmetric(ed) matrix)
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)).reshape(9) # build tensor back from eigenvalue/vector basis
table.data_append(list(eps))
# ------------------------------------------ output result -----------------------------------------
outputAlive = table.data_write() # output processed line
# ------------------------------------------ output finalization -----------------------------------
table.close() # close ASCII tables