117 lines
4.7 KiB
Python
Executable File
117 lines
4.7 KiB
Python
Executable File
#!/usr/bin/env python2.7
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,math
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import numpy as np
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from optparse import OptionParser
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import damask
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scriptName = os.path.splitext(os.path.basename(__file__))[0]
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scriptID = ' '.join([scriptName,damask.version])
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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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Rotate vector and/or tensor column data by given angle around given axis.
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""", version = scriptID)
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parser.add_option('-v','--vector',
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dest = 'vector',
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action = 'extend', metavar = '<string LIST>',
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help = 'column heading of vector(s) to rotate')
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parser.add_option('-t','--tensor',
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dest = 'tensor',
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action = 'extend', metavar = '<string LIST>',
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help = 'column heading of tensor(s) to rotate')
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parser.add_option('-r', '--rotation',
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dest = 'rotation',
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type = 'float', nargs = 4, metavar = ' '.join(['float']*4),
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help = 'angle and axis to rotate data [%default]')
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parser.add_option('-d', '--degrees',
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dest = 'degrees',
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action = 'store_true',
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help = 'angles are given in degrees [%default]')
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parser.set_defaults(rotation = (0.,1.,1.,1.), # no rotation about 1,1,1
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degrees = False,
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)
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(options,filenames) = parser.parse_args()
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if options.vector is None and options.tensor is None:
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parser.error('no data column specified.')
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toRadians = math.pi/180.0 if options.degrees else 1.0 # rescale degrees to radians
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q = damask.Quaternion().fromAngleAxis(toRadians*options.rotation[0],options.rotation[1:])
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R = q.asMatrix()
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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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# ------------------------------------------ read header ------------------------------------------
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table.head_read()
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# ------------------------------------------ sanity checks ----------------------------------------
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items = {
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'tensor': {'dim': 9, 'shape': [3,3], 'labels':options.tensor, 'active':[], 'column': []},
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'vector': {'dim': 3, 'shape': [3], 'labels':options.vector, 'active':[], 'column': []},
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}
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errors = []
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remarks = []
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column = {}
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for type, data in items.iteritems():
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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]['active'].append(what)
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items[type]['column'].append(table.label_index(what))
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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 --------------------------------------
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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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datatype = 'vector'
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for column in items[datatype]['column']: # loop over all requested labels
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table.data[column:column+items[datatype]['dim']] = \
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q * np.array(map(float,table.data[column:column+items[datatype]['dim']]))
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datatype = 'tensor'
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for column in items[datatype]['column']: # loop over all requested labels
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table.data[column:column+items[datatype]['dim']] = \
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np.dot(R,np.dot(np.array(map(float,table.data[column:column+items[datatype]['dim']])).\
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reshape(items[datatype]['shape']),R.transpose())).reshape(items[datatype]['dim'])
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outputAlive = table.data_write() # output processed line
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# ------------------------------------------ output finalization -----------------------------------
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table.close() # close ASCII tables
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