use central functionality
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@ -2,6 +2,7 @@
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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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@ -33,69 +34,27 @@ parser.add_option('--no-check',
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parser.set_defaults(rh = True,
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)
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(options,filenames) = parser.parse_args()
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if options.tensor is None:
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parser.error('no data column specified.')
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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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for tensor in options.tensor:
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t = table.get(tensor).reshape(-1,3,3)
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(u,v) = np.linalg.eigh(damask.mechanics.symmetric(t))
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if options.rh: v[np.linalg.det(v) < 0.0,:,2] *= -1.0
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# ------------------------------------------ assemble header 1 ------------------------------------
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for i,o in enumerate(['Min','Mid','Max']):
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table.add('eigval{}({})'.format(o,tensor),u[:,i],
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scriptID+' '+' '.join(sys.argv[1:]))
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items = {
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'tensor': {'dim': 9, 'shape': [3,3], 'labels':options.tensor, 'column': []},
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}
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errors = []
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remarks = []
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for type, data in items.items():
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for what in data['labels']:
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dim = table.label_dimension(what)
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if dim != data['dim']: remarks.append('column {} is not a {}...'.format(what,type))
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else:
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items[type]['column'].append(table.label_index(what))
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for order in ['Min','Mid','Max']:
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table.labels_append(['eigval{}({})'.format(order,what)]) # extend ASCII header with new labels
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for order in ['Min','Mid','Max']:
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table.labels_append(['{}_eigvec{}({})'.format(i+1,order,what) for i in range(3)]) # extend ASCII header with new labels
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if remarks != []: damask.util.croak(remarks)
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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 2 ------------------------------------
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table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
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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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for type, data in items.items():
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for column in data['column']:
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(u,v) = np.linalg.eigh(np.array(list(map(float,table.data[column:column+data['dim']]))).reshape(data['shape']))
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if options.rh and np.dot(np.cross(v[:,0], v[:,1]), v[:,2]) < 0.0 : v[:, 2] *= -1.0 # ensure right-handed eigenvector basis
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table.data_append(list(u)) # vector of max,mid,min eigval
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table.data_append(list(v.transpose().reshape(data['dim']))) # 3x3=9 combo vector of max,mid,min eigvec coordinates
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outputAlive = table.data_write() # output processed line in accordance with column labeling
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# ------------------------------------------ output finalization -----------------------------------
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table.close() # close input ASCII table (works for stdin)
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for i,o in enumerate(['Min','Mid','Max']):
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table.add('eigvec{}({})'.format(o,tensor),v[:,:,i],
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scriptID+' '+' '.join(sys.argv[1:]))
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table.to_ASCII(sys.stdout if name is None else name)
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