better use centralized code
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7d4b982c73
commit
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@ -2,10 +2,9 @@
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import os
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import sys
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from io import StringIO
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from optparse import OptionParser
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import numpy as np
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import damask
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@ -36,53 +35,16 @@ parser.set_defaults(defgrad = 'f',
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)
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(options,filenames) = parser.parse_args()
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# --- loop over input files -------------------------------------------------------------------------
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if filenames == []: filenames = [None]
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for name in filenames:
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try:
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table = damask.ASCIItable(name = name,
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buffered = False)
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except: continue
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damask.util.report(scriptName,name)
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damask.util.report(scriptName,name)
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# ------------------------------------------ read header ------------------------------------------
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table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
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table.head_read()
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table.add_array('S',
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damask.mechanics.PK2(table.get_array(options.defgrad).reshape(-1,3,3),
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table.get_array(options.stress).reshape(-1,3,3)).reshape(-1,9),
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scriptID+' '+' '.join(sys.argv[1:]))
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# ------------------------------------------ sanity checks ----------------------------------------
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errors = []
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column = {}
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for tensor in [options.defgrad,options.stress]:
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dim = table.label_dimension(tensor)
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if dim < 0: errors.append('column {} not found.'.format(tensor))
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elif dim != 9: errors.append('column {} is not a tensor.'.format(tensor))
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else:
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column[tensor] = table.label_index(tensor)
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if errors != []:
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damask.util.croak(errors)
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table.close(dismiss = True)
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continue
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# ------------------------------------------ assemble header --------------------------------------
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table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
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table.labels_append(['{}_S'.format(i+1) for i in range(9)]) # extend ASCII header with new labels
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table.head_write()
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# ------------------------------------------ process data ------------------------------------------
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outputAlive = True
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while outputAlive and table.data_read(): # read next data line of ASCII table
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F = np.array(list(map(float,table.data[column[options.defgrad]:column[options.defgrad]+9])),'d').reshape(3,3)
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P = np.array(list(map(float,table.data[column[options.stress ]:column[options.stress ]+9])),'d').reshape(3,3)
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table.data_append(list(np.dot(np.linalg.inv(F),P).reshape(9))) # [S] =[P].[F-1]
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outputAlive = table.data_write() # output processed line
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# ------------------------------------------ output finalization -----------------------------------
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table.close() # close input ASCII table (works for stdin)
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table.to_ASCII(sys.stdout if name is None else name)
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@ -2,10 +2,9 @@
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import os
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import sys
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from io import StringIO
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from optparse import OptionParser
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import numpy as np
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import damask
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@ -19,7 +19,26 @@ def Cauchy(F,P):
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else:
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sigma = np.einsum('i,ijk,ilk->ijl',1.0/np.linalg.det(F),P,F)
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return symmetric(sigma)
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def PK2(F,P):
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"""
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Return 2. Piola-Kirchhoff stress calculated from 1. Piola-Kirchhoff stress and deformation gradient.
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Parameters
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----------
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F : numpy.array of shape (:,3,3) or (3,3)
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Deformation gradient.
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P : numpy.array of shape (:,3,3) or (3,3)
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1. Piola-Kirchhoff stress.
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"""
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if np.shape(F) == np.shape(P) == (3,3):
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S = np.dot(np.linalg.inv(F),P)
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else:
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S = np.einsum('ijk,ikl->ijl',np.linalg.inv(F),P)
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return S
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def strain_tensor(F,t,m):
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"""
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