89 lines
3.1 KiB
Python
Executable File
89 lines
3.1 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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# --------------------------------------------------------------------
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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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Uniformly scale column values by given factor.
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""", version = scriptID)
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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 ='column(s) to scale')
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parser.add_option('-f','--factor',
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dest = 'factor',
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action = 'extend', metavar='<float LIST>',
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help = 'factor(s) per column')
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parser.set_defaults(label = [],
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)
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(options,filenames) = parser.parse_args()
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if len(options.label) != len(options.factor):
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parser.error('number of column labels and factors do not match.')
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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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errors = []
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remarks = []
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columns = []
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dims = []
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factors = []
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for what,factor in zip(options.label,options.factor):
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col = table.label_index(what)
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if col < 0: remarks.append('column {} not found...'.format(what,type))
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else:
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columns.append(col)
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factors.append(float(factor))
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dims.append(table.label_dimension(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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for col,dim,factor in zip(columns,dims,factors): # loop over items
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table.data[col:col+dim] = factor * np.array(table.data[col:col+dim],'d')
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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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