143 lines
5.2 KiB
Python
Executable File
143 lines
5.2 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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Generate histogram of N bins in given data range.
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""", version = scriptID)
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parser.add_option('-d','--data',
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dest = 'data',
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type = 'string', metavar = 'string',
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help = 'column heading for data')
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parser.add_option('-w','--weights',
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dest = 'weights',
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type = 'string', metavar = 'string',
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help = 'column heading for weights')
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parser.add_option('--range',
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dest = 'range',
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type = 'float', nargs = 2, metavar = 'float float',
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help = 'data range of histogram [min - max]')
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parser.add_option('-N',
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dest = 'N',
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type = 'int', metavar = 'int',
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help = 'number of bins')
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parser.add_option('--density',
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dest = 'density',
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action = 'store_true',
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help = 'report probability density')
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parser.add_option('--logarithmic',
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dest = 'log',
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action = 'store_true',
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help = 'logarithmically spaced bins')
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parser.set_defaults(data = None,
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weights = None,
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range = None,
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N = None,
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density = False,
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log = False,
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)
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(options,filenames) = parser.parse_args()
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if not options.data: parser.error('no data specified.')
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if not options.N: parser.error('no bin number specified.')
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if options.log:
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def forward(x):
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return np.log(x)
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def reverse(x):
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return np.exp(x)
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else:
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def forward(x):
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return x
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def reverse(x):
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return x
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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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readonly = True)
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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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if table.label_dimension(options.data) != 1: errors.append('data {} are not scalar.'.format(options.data))
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if options.weights and \
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table.label_dimension(options.data) != 1: errors.append('weights {} are not scalar.'.format(options.weights))
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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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# --------------- read data ----------------------------------------------------------------
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table.data_readArray([options.data,options.weights])
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# --------------- auto range ---------------------------------------------------------------
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if options.range is None:
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rangeMin,rangeMax = min(table.data[:,0]),max(table.data[:,0])
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else:
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rangeMin,rangeMax = min(options.range),max(options.range)
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# --------------- bin data ----------------------------------------------------------------
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count,edges = np.histogram(table.data[:,0],
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bins = reverse(forward(rangeMin) + np.arange(options.N+1) *
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(forward(rangeMax)-forward(rangeMin))/options.N),
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range = (rangeMin,rangeMax),
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weights = None if options.weights is None else table.data[:,1],
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density = options.density,
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)
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bincenter = reverse(forward(rangeMin) + (0.5+np.arange(options.N)) *
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(forward(rangeMax)-forward(rangeMin))/options.N) # determine center of bins
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# ------------------------------------------ assemble header ---------------------------------------
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table.info_clear()
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table.info_append([scriptID + '\t' + ' '.join(sys.argv[1:]),
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scriptID + ':\t' +
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'data range {} -- {}'.format(rangeMin,rangeMax) +
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(' (log)' if options.log else ''),
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])
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table.labels_clear()
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table.labels_append(['bincenter','count'])
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table.head_write()
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# ------------------------------------------ output result -----------------------------------------
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table.data = np.squeeze(np.dstack((bincenter,count)))
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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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