improved help for automatic documentation and simplified some scripts

processing/post/addCalculation.py

@@ -30,12 +30,12 @@ parser.add_option('-l','--label',   dest='labels', action='extend', metavar='<st
                   help='(list of) new column labels')
 parser.add_option('-f','--formula', dest='formulas', action='extend', metavar='<string LIST>',
                   help='(list of) formulas corresponding to labels')
-parser.set_defaults(labels= [])
-parser.set_defaults(formulas= [])
 
 (options,filenames) = parser.parse_args()
 
-if len(options.labels) != len(options.formulas):
+if options.labels == None or options.formulas == None:
+  parser.error('no formulas and/or labels specified')
+elif len(options.labels) != len(options.formulas):
   parser.error('number of labels (%i) and formulas (%i) do not match'%(len(options.labels),len(options.formulas)))
 
 for i in xrange(len(options.formulas)):
@@ -104,8 +104,8 @@ for file in files:
         if labelLen[label] == 0:
           brokenFormula[label] = True
         if label not in brokenFormula:
-          table.labels_append({True:['%i_%s'%(i+1,label) for i in xrange(labelLen[label])],
+          table.labels_append(['%i_%s'%(i+1,label) for i in xrange(labelLen[label])] if labelLen[label]>1
-                               False:label}[labelLen[label]>1] )
+                               else label)
       table.head_write()
       firstLine = False
 

processing/post/addCauchy.py

@@ -3,7 +3,6 @@
 
 import os,sys,string
 import numpy as np
-from collections import defaultdict
 from optparse import OptionParser
 import damask
 
@@ -28,16 +27,6 @@ parser.set_defaults(stress = 'p')
 
 (options,filenames) = parser.parse_args()
 
-datainfo = {                                                                                        # list of requested labels per datatype
-             'defgrad':    {'len':9,
-                            'label':[]},
-             'stress':     {'len':9,
-                            'label':[]},
-           }
-
-datainfo['defgrad']['label'].append(options.defgrad)
-datainfo['stress']['label'].append(options.stress)
-
 # ------------------------------------------ setup file handles ------------------------------------
 files = []
 if filenames == []:
@@ -57,22 +46,14 @@ for file in files:
   table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
 
 # --------------- figure out columns to process  ---------------------------------------------------
-  active = defaultdict(list)
-  column = defaultdict(dict)
   missingColumns = False
-  
+  column={ 'defgrad': table.labels.index('1_'+options.defgrad), 
-  for datatype,info in datainfo.items():
+           'stress':  table.labels.index('1_'+options.stress)}
-    for label in info['label']:
+  for key in column:
-      key = '1_%s'%label
+    if column[key]<1:
-      if key not in table.labels:
       file['croak'].write('column %s not found...\n'%key)
-        missingColumns = True                                                                       # break if label not found
+      missingColumns=True
-      else:
+  if missingColumns: continue
-        active[datatype].append(label)
-        column[datatype][label] = table.labels.index(key)                                           # remember columns of requested data
-
-  if missingColumns:
-    continue
 
 # ------------------------------------------ assemble header --------------------------------------
   table.labels_append(['%i_Cauchy'%(i+1) for i in xrange(9)])                                       # extend ASCII header with new labels
@@ -81,12 +62,8 @@ for file in files:
 # ------------------------------------------ process data ------------------------------------------
   outputAlive = True
   while outputAlive and table.data_read():                                                          # read next data line of ASCII table
-    F = np.array(map(float,table.data[column['defgrad'][active['defgrad'][0]]:
+    F = np.array(map(float,table.data[column['defgrad']:column['defgrad']+9]),'d').reshape(3,3)
-                                      column['defgrad'][active['defgrad'][0]]+datainfo['defgrad']['len']]),\
+    P = np.array(map(float,table.data[column['stress'] :column['stress']+9]),'d').reshape(3,3)
-                                                                                      'd').reshape(3,3)
-    P = np.array(map(float,table.data[column['stress'][active['stress'][0]]:
-                                      column['stress'][active['stress'][0]]+datainfo['stress']['len']]),\
-                                                                                     'd').reshape(3,3)
     table.data_append(list(1.0/np.linalg.det(F)*np.dot(P,F.T).reshape(9)))                          # [Cauchy] = (1/det(F)) * [P].[F_transpose]
     outputAlive = table.data_write()                                                                # output processed line
 

processing/post/addDeformedConfiguration.py

@@ -23,7 +23,7 @@ Operates on periodic ordered three-dimensional data sets.
 parser.add_option('-c','--coordinates', dest='coords', metavar='string',
                   help='column heading for coordinates [%default]')
 parser.add_option('-f','--defgrad',     dest='defgrad', metavar='string',
-                                        help='heading of columns containing tensor field values')
+                  help='heading of columns containing tensor field values [%default]')
 parser.set_defaults(coords  = 'ipinitialcoord')
 parser.set_defaults(defgrad = 'f' )
 

processing/post/addDeterminant.py

@@ -28,11 +28,10 @@ Add column(s) containing determinant of requested tensor column(s).
 
 parser.add_option('-t','--tensor',      dest='tensor', action='extend', metavar='<string LIST>',
                   help='heading of columns containing tensor field values')
-parser.set_defaults(tensor = [])
 
 (options,filenames) = parser.parse_args()
 
-if len(options.tensor) == 0:
+if options.tensor == None:
   parser.error('no data column specified...')
 
 datainfo = {                                                                                        # list of requested labels per datatype
@@ -60,10 +59,9 @@ for file in files:
   table.head_read()                                                                                 # read ASCII header info
   table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
 
+# --------------- figure out columns to process  ---------------------------------------------------
   active = []
   column = defaultdict(dict)
-
-# --------------- figure out columns to process  ---------------------------------------------------
   for label in datainfo['tensor']['label']:
     key = '1_%s'%label
     if key not in table.labels:

processing/post/addDeviator.py

@@ -30,12 +30,10 @@ parser.add_option('-t','--tensor',      dest='tensor', action='extend', metavar=
                   help='heading of columns containing tensor field values')
 parser.add_option('-s','--spherical',   dest='hydrostatic', action='store_true',
                   help='also add sperical part of tensor (hydrostatic component, pressure)')
-parser.set_defaults(hydrostatic = False)
-parser.set_defaults(tensor = [])
 
 (options,filenames) = parser.parse_args()
 
-if len(options.tensor) == 0:
+if options.tensor == None:
   parser.error('no data column specified...')
 
 datainfo = {                                                                                        # list of requested labels per datatype

processing/post/addDivergence.py

@@ -10,11 +10,6 @@ import damask
 scriptID   = string.replace('$Id$','\n','\\n')
 scriptName = os.path.splitext(scriptID.split()[1])[0]
 
-#--------------------------------------------------------------------------------------------------
-#> @brief calculates curl field using differentation in Fourier space
-#> @todo enable odd resolution
-#--------------------------------------------------------------------------------------------------
-
 def divFFT(geomdim,field):
  grid = np.array(np.shape(field)[0:3])
  wgt = 1.0/np.array(grid).prod()
@@ -73,12 +68,10 @@ parser.add_option('-v','--vector',      dest='vector', action='extend', metavar=
 parser.add_option('-t','--tensor',      dest='tensor', action='extend', metavar='<string LIST>',
                   help='heading of columns containing tensor field values')
 parser.set_defaults(coords = 'ipinitialcoord')
-parser.set_defaults(vector = [])
-parser.set_defaults(tensor = [])
 
 (options,filenames) = parser.parse_args()
 
-if len(options.vector) + len(options.tensor) == 0:
+if (options.vector == None) and (options.tensor == None):
   parser.error('no data column specified...')
 
 datainfo = {                                                                                         # list of requested labels per datatype