fix for scalar datasets

processing/post/DADF5_postResults.py

@@ -73,8 +73,11 @@ for filename in options.filenames:
           array = np.reshape(array,[np.product(results.grid),d])
           data = np.concatenate((data,array),1)
           
-          header+= ''.join([' {}_{}'.format(j+1,label) for j in range(d)])
-    
+          if d>1:
+            header+= ''.join([' {}_{}'.format(j+1,label) for j in range(d)])
+          else:
+            header+=' '+label
+            
     for label in options.mat:     
       for o in results.m_output_types:
         results.active['m_output_types'] = [o]
@@ -89,7 +92,10 @@ for filename in options.filenames:
           array = np.reshape(array,[np.product(results.grid),d])
           data = np.concatenate((data,array),1)
           
-          header+= ''.join([' {}_{}'.format(j+1,label) for j in range(d)])
+          if d>1:
+            header+= ''.join([' {}_{}'.format(j+1,label) for j in range(d)])
+          else:
+            header+=' '+label
 
     dirname  = os.path.abspath(os.path.join(os.path.dirname(filename),options.dir))
     try:

python/damask/dadf5.py

@@ -126,19 +126,26 @@ class DADF5():
     """
     with h5py.File(self.filename,'r') as f:
       shape = (self.Nmaterialpoints,) + np.shape(f[path[0]])[1:]
+      if len(shape) == 1: shape = shape +(1,)
       dataset = np.full(shape,np.nan)
       for pa in path:
         label   = pa.split('/')[2]
         try:
           p = np.where(f['mapping/cellResults/constituent'][:,c]['Name'] == str.encode(label))[0]
           u = (f['mapping/cellResults/constituent'][p,c]['Position'])
-          dataset[p,:] = f[pa][u,:] # does not work for scalar datasets
+          a = np.array(f[pa])
+          if len(a.shape) == 1:
+            a=a.reshape([a.shape[0],1])
+          dataset
         except:
           pass
         try:
           p = np.where(f['mapping/cellResults/materialpoint']['Name'] == str.encode(label))[0]
           u = (f['mapping/cellResults/materialpoint'][p.tolist()]['Position'])
-          dataset[p,:] = f[pa][u,:] # does not work for scalar datasets
+          a = np.array(f[pa])
+          if len(a.shape) == 1:
+            a=a.reshape([a.shape[0],1])
+          dataset[p,:] = a[u,:]
         except:
           pass