added option for periodic averaging

processing/post/groupTable.py

@@ -4,9 +4,18 @@
 import os,sys
 import math                                                                                       # noqa
 import numpy as np
-from optparse import OptionParser
+from optparse import OptionParser, OptionGroup
 import damask
 
+#"https://en.wikipedia.org/wiki/Center_of_mass#Systems_with_periodic_boundary_conditions"
+def periodicAverage(Points, Box):
+  theta = (Points/Box[1]) * (2.0*np.pi)
+  xi    = np.cos(theta)
+  zeta  = np.sin(theta)
+  theta_avg = np.arctan2(-1.0*zeta.mean(), -1.0*xi.mean()) + np.pi
+  Pmean = Box[1] * theta_avg/(2.0*np.pi)
+  return Pmean
+
 scriptName = os.path.splitext(os.path.basename(__file__))[0]
 scriptID   = ' '.join([scriptName,damask.version])
 
@@ -35,7 +44,23 @@ parser.add_option('-a','--all',
                   action = 'store_true',
                   help = 'apply mapping function also to grouping column')
 
-parser.set_defaults(function = 'np.average')
+group = OptionGroup(parser, "periodic averaging", "")
+
+group.add_option('-p','--periodic',
+                  dest = 'periodic',
+                  action = 'store_true',
+                  help = 'calculate average in periodic space defined by periodic length [%default]')
+group.add_option('--boundary',
+                 dest = 'boundary', metavar = 'MIN MAX',
+                 type = 'float', nargs = 2,
+                 help = 'define periodic box end points %default')
+
+parser.add_option_group(group)
+
+parser.set_defaults(function = 'np.average',
+                    all      = False,
+                    periodic = False,
+                    boundary = [0.0, 1.0])
 
 (options,filenames) = parser.parse_args()
 
@@ -92,6 +117,9 @@ for name in filenames:
   grpTable = np.empty((len(values), cols))                                                        # initialize output
   
   for i in xrange(len(values)):                                                                   # iterate over groups (unique values in grpColumn)
+    if options.periodic :
+       grpTable[i] = periodicAverage(table.data[index[i]:index[i+1]],options.boundary)           # apply periodicAverage mapping function
+    else :
        grpTable[i] = np.apply_along_axis(mapFunction,0,table.data[index[i]:index[i+1]])           # apply mapping function
     if not options.all: grpTable[i,grpColumn] = table.data[index[i],grpColumn]                    # restore grouping column value