Generate histogram of N bins in given data range.

This commit is contained in:
Philip Eisenlohr 2016-03-27 13:32:08 -04:00
parent c24a9f8244
commit 0d93a47c71
1 changed files with 128 additions and 0 deletions

128
processing/post/histogram.py Executable file
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#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
import os,sys
import numpy as np
from optparse import OptionParser
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Generate histogram of N bins in given data range.
""", version = scriptID)
parser.add_option('-d','--data',
dest = 'data',
type = 'string', metavar = 'string',
help = 'column heading for data')
parser.add_option('--range',
dest = 'range',
type = 'float', nargs = 2, metavar = 'float float',
help = 'data range of histogram [min - max]')
parser.add_option('-N',
dest = 'N',
type = 'int', metavar = 'int',
help = 'number of bins')
parser.add_option('-l', '--logarithmic',
dest = 'log',
action = 'store_true',
help = 'logarithmically spaced bins')
parser.set_defaults(data = None,
range = None,
N = None,
log = False,
)
(options,filenames) = parser.parse_args()
if not options.data: parser.error('no data specified.')
if not options.N: parser.error('no bin number specified.')
if options.log:
def forward(x):
return np.log(x)
def reverse(x):
return np.exp(x)
else:
def forward(x):
return x
def reverse(x):
return x
# --- loop over input files ------------------------------------------------------------------------
if filenames == []: filenames = [None]
for name in filenames:
try: table = damask.ASCIItable(name = name,
buffered = False,
readonly = True)
except: continue
damask.util.report(scriptName,name)
# ------------------------------------------ read header ------------------------------------------
table.head_read()
# ------------------------------------------ sanity checks ----------------------------------------
errors = []
remarks = []
if table.label_dimension(options.data) != 1: errors.append('data {} is not a scalar.'.format(options.data))
if remarks != []: damask.util.croak(remarks)
if errors != []:
damask.util.croak(errors)
table.close(dismiss = True)
continue
# --------------- read data ----------------------------------------------------------------
table.data_readArray(options.data)
bincenter = np.zeros(options.N,'f')
# --------------- auto range ---------------------------------------------------------------
if options.range is None:
rangeMin,rangeMax = min(table.data[:,0]),max(table.data[:,0])
else:
rangeMin,rangeMax = min(options.range),max(options.range)
# --------------- bin data ----------------------------------------------------------------
count,edges = np.histogram(table.data[:,0],
bins = reverse(forward(rangeMin) + np.arange(options.N+1) *
(forward(rangeMax)-forward(rangeMin))/options.N),
range = (rangeMin,rangeMax))
bincenter = reverse(forward(rangeMin) + (0.5+np.arange(options.N)) *
(forward(rangeMax)-forward(rangeMin))/options.N) # determine center of bins
# ------------------------------------------ assemble header ---------------------------------------
table.info_clear()
table.info_append([scriptID + '\t' + ' '.join(sys.argv[1:]),
scriptID + ':\t' +
'data range {} -- {}'.format(rangeMin,rangeMax) +
(' (log)' if options.log else ''),
])
table.labels_clear()
table.labels_append(['bincenter','count'])
table.head_write()
# ------------------------------------------ output result -----------------------------------------
table.data = np.squeeze(np.dstack((bincenter,count)))
table.data_writeArray()
# ------------------------------------------ output finalization -----------------------------------
table.close() # close ASCII tables