DAMASK_EICMD/processing/post/addCompatibilityMismatch.py

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#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
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import os,sys,string
import numpy as np
from optparse import OptionParser
import damask
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scriptID = string.replace('$Id$','\n','\\n')
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scriptName = os.path.splitext(scriptID.split()[1])[0]
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# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options file[s]', description = """
Add column containing debug information.
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Operates on periodic ordered three-dimensional data sets.
""", version = scriptID)
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parser.add_option('--no-shape','-s', dest='noShape', action='store_false',
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help='do not calcuate shape mismatch')
parser.add_option('--no-volume','-v', dest='noVolume', action='store_false',
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help='do not calculate volume mismatch')
parser.add_option('-c','--coordinates', dest='coords', metavar='string',
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help='column heading for coordinates [%default]')
parser.add_option('-f','--defgrad', dest='defgrad', metavar='string',
help='column heading for coordinates [%defgrad]')
parser.set_defaults(noVolume = False)
parser.set_defaults(noShape = False)
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parser.set_defaults(coords = 'ipinitialcoord')
parser.set_defaults(defgrad = 'f')
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(options,filenames) = parser.parse_args()
datainfo = { # list of requested labels per datatype
'defgrad': {'len':9,
'label':[]},
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}
datainfo['defgrad']['label'].append(options.defgrad)
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# ------------------------------------------ setup file handles ------------------------------------
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files = []
for name in filenames:
if os.path.exists(name):
files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w'), 'croak':sys.stderr})
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#--- loop over input files -------------------------------------------------------------------------
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for file in files:
file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\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 size and grid ---------------------------------------------------------
try:
locationCol = table.labels.index('1_%s'%options.coords) # columns containing location data
except ValueError:
try:
locationCol = table.labels.index('%s.x'%options.coords) # columns containing location data (legacy naming scheme)
except ValueError:
file['croak'].write('no coordinate data (1_%s/%s.x) found...\n'%(options.coords,options.coords))
continue
coords = [{},{},{}]
while table.data_read(): # read next data line of ASCII table
for j in xrange(3):
coords[j][str(table.data[locationCol+j])] = True # remember coordinate along x,y,z
grid = np.array([len(coords[0]),\
len(coords[1]),\
len(coords[2]),],'i') # grid is number of distinct coordinates found
size = grid/np.maximum(np.ones(3,'d'),grid-1.0)* \
np.array([max(map(float,coords[0].keys()))-min(map(float,coords[0].keys())),\
max(map(float,coords[1].keys()))-min(map(float,coords[1].keys())),\
max(map(float,coords[2].keys()))-min(map(float,coords[2].keys())),\
],'d') # size from bounding box, corrected for cell-centeredness
for i, points in enumerate(grid):
if points == 1:
options.packing[i] = 1
options.shift[i] = 0
mask = np.ones(3,dtype=bool)
mask[i]=0
size[i] = min(size[mask]/grid[mask]) # third spacing equal to smaller of other spacing
N = grid.prod()
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# --------------- figure out columns to process ---------------------------------------------------
key = '1_%s'%datainfo['defgrad']['label'][0]
if key not in table.labels:
file['croak'].write('column %s not found...\n'%key)
continue
else:
column = table.labels.index(key) # remember columns of requested data
# ------------------------------------------ assemble header ---------------------------------------
if not options.noShape: table.labels_append(['shapeMismatch(%s)' %options.defgrad])
if not options.noVolume: table.labels_append(['volMismatch(%s)'%options.defgrad])
table.head_write()
# ------------------------------------------ read deformation gradient field -----------------------
table.data_rewind()
F = np.zeros(N*9,'d').reshape([3,3]+list(grid))
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idx = 0
while table.data_read():
(x,y,z) = damask.util.gridLocation(idx,grid) # figure out (x,y,z) position from line count
idx += 1
F[0:3,0:3,x,y,z] = np.array(map(float,table.data[column:column+9]),'d').reshape(3,3)
Favg = damask.core.math.tensorAvg(F)
centres = damask.core.mesh.deformedCoordsFFT(size,F,Favg,[1.0,1.0,1.0])
nodes = damask.core.mesh.nodesAroundCentres(size,Favg,centres)
if not options.noShape: shapeMismatch = damask.core.mesh.shapeMismatch( size,F,nodes,centres)
if not options.noVolume: volumeMismatch = damask.core.mesh.volumeMismatch(size,F,nodes)
# ------------------------------------------ process data ------------------------------------------
table.data_rewind()
idx = 0
outputAlive = True
while outputAlive and table.data_read(): # read next data line of ASCII table
(x,y,z) = damask.util.gridLocation(idx,grid) # figure out (x,y,z) position from line count
idx += 1
if not options.noShape: table.data_append( shapeMismatch[x,y,z])
if not options.noVolume: table.data_append(volumeMismatch[x,y,z])
outputAlive = table.data_write() # output processed line
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# ------------------------------------------ output result ---------------------------------------
outputAlive and table.output_flush() # just in case of buffered ASCII table
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table.input_close() # close input ASCII table
table.output_close() # close output ASCII table
os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new