122 lines
4.6 KiB
Python
Executable File
122 lines
4.6 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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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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def derivative(coordinates,what):
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result = np.empty_like(what)
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# use differentiation by interpolation
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# as described in http://www2.math.umd.edu/~dlevy/classes/amsc466/lecture-notes/differentiation-chap.pdf
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result[1:-1,:] = + what[1:-1,:] * (2.*coordinates[1:-1]-coordinates[:-2]-coordinates[2:]) / \
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((coordinates[1:-1]-coordinates[:-2])*(coordinates[1:-1]-coordinates[2:])) \
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+ what[2:,:] * (coordinates[1:-1]-coordinates[:-2]) / \
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((coordinates[2:]-coordinates[1:-1])*(coordinates[2:]-coordinates[:-2])) \
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+ what[:-2,:] * (coordinates[1:-1]-coordinates[2:]) / \
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((coordinates[:-2]-coordinates[1:-1])*(coordinates[:-2]-coordinates[2:])) \
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result[0,:] = (what[0,:] - what[1,:]) / \
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(coordinates[0] - coordinates[1])
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result[-1,:] = (what[-1,:] - what[-2,:]) / \
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(coordinates[-1] - coordinates[-2])
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return result
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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 numerical derivative of requested column(s) with respect to given coordinates.
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""", version = scriptID)
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parser.add_option('-c','--coordinates',
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dest = 'coordinates',
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type = 'string', metavar='string',
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help = 'heading of coordinate column')
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parser.add_option('-l','--label',
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dest = 'label',
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action = 'extend', metavar = '<string LIST>',
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help = 'heading of column(s) to differentiate')
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(options,filenames) = parser.parse_args()
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if options.coordinates is None:
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parser.error('no coordinate column specified.')
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if options.label 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,
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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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errors = []
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remarks = []
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columns = []
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dims = []
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if table.label_dimension(options.coordinates) != 1:
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errors.append('coordinate column {} is not scalar.'.format(options.coordinates))
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for what in options.label:
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dim = table.label_dimension(what)
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if dim < 0: remarks.append('column {} not found...'.format(what))
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else:
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dims.append(dim)
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columns.append(table.label_index(what))
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table.labels_append('d({})/d({})'.format(what,options.coordinates) if dim == 1 else
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['{}_d({})/d({})'.format(i+1,what,options.coordinates) for i in range(dim)] ) # 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 --------------------------------------
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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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table.data_readArray()
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mask = []
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for col,dim in zip(columns,dims): mask += range(col,col+dim) # isolate data columns to differentiate
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differentiated = derivative(table.data[:,table.label_index(options.coordinates)].reshape((len(table.data),1)),
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table.data[:,mask]) # calculate numerical derivative
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table.data = np.hstack((table.data,differentiated))
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# ------------------------------------------ output result -----------------------------------------
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table.data_writeArray()
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# ------------------------------------------ output finalization -----------------------------------
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table.close() # close ASCII tables
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