87 lines
4.3 KiB
Python
Executable File
87 lines
4.3 KiB
Python
Executable File
#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,string
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import numpy as np
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from collections import defaultdict
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from optparse import OptionParser
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import damask
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scriptID = string.replace('$Id$','\n','\\n')
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scriptName = scriptID.split()[1][:-3]
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
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Add column(s) containing eigenvalues and eigenvectors of requested tensor column(s).
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""", version = scriptID)
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parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string', metavar='<string LIST>',
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help='heading of columns containing tensor field values')
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parser.set_defaults(tensor = [])
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(options,filenames) = parser.parse_args()
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if len(options.tensor) == 0:
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parser.error('no data column specified...')
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datainfo = { # list of requested labels per datatype
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'tensor': {'len':9,
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'label':[]},
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}
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datainfo['tensor']['label'] += options.tensor
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# ------------------------------------------ setup file handles ------------------------------------
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files = []
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for name in filenames:
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if os.path.exists(name):
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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:
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file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
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table = damask.ASCIItable(file['input'],file['output'],True) # make unbuffered ASCII_table
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table.head_read() # read ASCII header info
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table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
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active = []
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column = defaultdict(dict)
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for label in datainfo['tensor']['label']:
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key = '1_%s'%label
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if key not in table.labels:
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file['croak'].write('column %s not found...\n'%key)
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else:
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active.append(label)
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column[label] = table.labels.index(key) # remember columns of requested data
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# ------------------------------------------ assemble header ---------------------------------------
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for labels in active:
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table.labels_append(['%i_eigval(%s)'%(i+1,label) for i in xrange(3)]) # extend ASCII header with new labels
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table.labels_append(['%i_eigvec(%s)'%(i+1,label) for i in xrange(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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for labels in active: # loop over requested data
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tensor = np.array(map(float,table.data[column[label]:column[label]+datainfo['tensor']['len']])).\
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reshape((datainfo['tensor']['len']//3,3))
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(u,v) = np.linalg.eig(tensor)
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table.data_append(list(u))
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table.data_append(list(v.transpose().reshape(datainfo['tensor']['len'])))
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outputAlive = table.data_write() # output processed line
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# ------------------------------------------ output result -----------------------------------------
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outputAlive and table.output_flush() # just in case of buffered ASCII table
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table.input_close() # close input ASCII table (works for stdin)
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table.output_close() # close output ASCII table (works for stdout)
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if file['name'] != 'STDIN':
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os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new
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