Generate histogram of N bins in given data range.

processing/post/histogram.py

@@ -0,0 +1,128 @@
+#!/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