132 lines
4.9 KiB
Python
Executable File
132 lines
4.9 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
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import numpy as np
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from optparse import OptionParser
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from scipy import ndimage
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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 option(s) [ASCIItable(s)]', description = """
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Add column(s) containing Gaussian filtered values of requested column(s).
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Operates on periodic and non-periodic ordered three-dimensional data sets.
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For details see scipy.ndimage documentation.
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""", version = scriptID)
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parser.add_option('-p','--pos','--periodiccellcenter',
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dest = 'pos',
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type = 'string', metavar = 'string',
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help = 'label of coordinates [%default]')
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parser.add_option('-s','--scalar',
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dest = 'scalar',
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action = 'extend', metavar = '<string LIST>',
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help = 'label(s) of scalar field values')
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parser.add_option('-o','--order',
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dest = 'order',
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type = int,
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metavar = 'int',
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help = 'order of the filter')
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parser.add_option('--sigma',
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dest = 'sigma',
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type = float,
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metavar = 'float',
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help = 'standard deviation')
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parser.add_option('--periodic',
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dest = 'periodic',
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action = 'store_true',
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help = 'assume periodic grain structure')
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parser.set_defaults(pos = 'pos',
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order = 0,
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sigma = 1,
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periodic = False,
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)
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(options,filenames) = parser.parse_args()
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if options.scalar 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: table = damask.ASCIItable(name = name,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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'scalar': {'dim': 1, 'shape': [1], 'labels':options.scalar, '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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if table.label_dimension(options.pos) != 3: errors.append('coordinates {} are not a vector.'.format(options.pos))
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else: colCoord = table.label_index(options.pos)
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for type, data in items.iteritems():
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for what in (data['labels'] if data['labels'] is not None else []):
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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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for type, data in items.iteritems():
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for label in data['active']:
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table.labels_append(['Gauss{}({})'.format(options.sigma,label)]) # extend ASCII header with new labels
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table.head_write()
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# --------------- figure out size and grid ---------------------------------------------------------
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table.data_readArray()
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grid,size = damask.util.coordGridAndSize(table.data[:,table.label_indexrange(options.pos)])
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# ------------------------------------------ process value field -----------------------------------
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stack = [table.data]
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for type, data in items.iteritems():
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for i,label in enumerate(data['active']):
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stack.append(ndimage.filters.gaussian_filter(table.data[:,data['column'][i]],
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options.sigma,options.order,
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mode = 'wrap' if options.periodic else 'nearest'
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).reshape([table.data.shape[0],1])
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)
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# ------------------------------------------ output result -----------------------------------------
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if len(stack) > 1: table.data = np.hstack(tuple(stack))
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table.data_writeArray('%.12g')
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# ------------------------------------------ output finalization -----------------------------------
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table.close() # close input ASCII table (works for stdin)
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