Removed hard requirement of 3D dataset. Fills in necessary dimensions.

processing/post/vtk_rectilinearGrid.py

@@ -38,9 +38,9 @@ parser.set_defaults(position ='ipinitialcoord',
 if filenames == []: filenames = [None]
 
 for name in filenames:
-  try:
-    table = damask.ASCIItable(name = name,
-                              buffered = False, readonly = True)
+  try:    table = damask.ASCIItable(name = name,
+                                    buffered = False,
+                                    readonly = True)
   except: continue
   damask.util.report(scriptName,name)
 
@@ -48,10 +48,13 @@ for name in filenames:
 
   table.head_read()
 
-  errors =  []
-  if table.label_dimension(options.position) != 3:
-    errors.append('coordinates {} are not a vector.'.format(options.position))
+  remarks = []
+  errors  = []
+  coordDim = table.label_dimension(options.position)
+  if not 3 >= coordDim >= 1: errors.append('coordinates "{}" need to have one, two, or three dimensions.'.format(options.position))
+  elif coordDim < 3:         remarks.append('appending {} dimensions to coordinates "{}"...'.format(3-coordDim,options.position))
 
+  if remarks != []: damask.util.croak(remarks)
   if errors  != []:
     damask.util.croak(errors)
     table.close(dismiss=True)
@@ -60,6 +63,11 @@ for name in filenames:
 # --------------- figure out size and grid ---------------------------------------------------------
 
   table.data_readArray(options.position)
+  if len(table.data.shape) < 2: table.data.shape += (1,)                                            # expand to 2D shape
+  if table.data.shape[1] < 3:
+    table.data = np.hstack((table.data,
+                            np.zeros((table.data.shape[0],
+                                      3-table.data.shape[1]),dtype='f')))                           # fill coords up to 3D with zeros
 
   coords = [np.unique(table.data[:,i]) for i in xrange(3)]
   if options.mode == 'cell':