support for string arrays

allows to add phase label from mapping. Only scalar string arrays are
allowed (no real restriction)

python/damask/_result.py

@@ -1352,12 +1352,12 @@ class Result:
             at_cell_ph = []
             in_data_ph = []
             for c in range(self.N_constituents):
-                at_cell_ph.append({label: np.where(f['/'.join(['cell_to','phase'])][:,c]['label'] == label.encode())[0] \
+                at_cell_ph.append({label: np.where(self.phase[:,c] == label)[0] \
                                           for label in self.visible['phases']})
                 in_data_ph.append({label: f['/'.join(['cell_to','phase'])]['entry'][at_cell_ph[c][label]][:,c] \
                                           for label in self.visible['phases']})
 
-            at_cell_ho = {label: np.where(f['/'.join(['cell_to','homogenization'])][:]['label'] == label.encode())[0] \
+            at_cell_ho = {label: np.where(self.homogenization[:] == label)[0] \
                                  for label in self.visible['homogenizations']}
             in_data_ho = {label: f['/'.join(['cell_to','homogenization'])]['entry'][at_cell_ho[label]] \
                                  for label in self.visible['homogenizations']}

python/damask/_vtk.py

@@ -265,10 +265,18 @@ class VTK:
                 raise ValueError('No label defined for numpy.ndarray')
 
             N_data = data.shape[0]
-            data_ = np.where(data.mask,data.fill_value,data) if isinstance(data,np.ma.MaskedArray) else\
-                    data
-            d = np_to_vtk((data_.astype(np.single) if data_.dtype in [np.double, np.longdouble] else
-                           data_).reshape(N_data,-1),deep=True)                                      # avoid large files
+            data_ = (data if not isinstance(data,np.ma.MaskedArray) else
+                     np.where(data.mask,data.fill_value,data)).reshape(N_data,-1)
+
+            if data_.dtype in [np.double,np.longdouble]:
+                d = np_to_vtk(data_.astype(np.single),deep=True)                                    # avoid large files
+            elif data_.dtype.type is np.str_:
+                d = vtk.vtkStringArray()
+                for s in np.squeeze(data_):
+                    d.InsertNextValue(s)
+            else:
+                d = np_to_vtk(data_,deep=True)
+
             d.SetName(label)
 
             if   N_data == N_points:
@@ -305,13 +313,23 @@ class VTK:
         cell_data = self.vtk_data.GetCellData()
         for a in range(cell_data.GetNumberOfArrays()):
             if cell_data.GetArrayName(a) == label:
+                try:
                     return vtk_to_np(cell_data.GetArray(a))
+                except AttributeError:
+                    vtk_array = cell_data.GetAbstractArray(a)                                       # string array
 
         point_data = self.vtk_data.GetPointData()
         for a in range(point_data.GetNumberOfArrays()):
             if point_data.GetArrayName(a) == label:
+                try:
                     return vtk_to_np(point_data.GetArray(a))
+                except AttributeError:
+                    vtk_array = point_data.GetAbstractArray(a)                                      # string array
 
+        try:
+            # string array
+            return np.array([vtk_array.GetValue(i) for i in range(vtk_array.GetNumberOfValues())]).astype(str)
+        except UnboundLocalError:
             raise ValueError(f'Array "{label}" not found.')
 
 

python/tests/test_VTK.py

@@ -135,6 +135,18 @@ class TestVTK:
         with pytest.raises(TypeError):
             default.add('invalid_type','valid')
 
+    @pytest.mark.parametrize('data_type,shape',[(float,(3,)),
+                                                (float,(3,3)),
+                                                (float,(1,)),
+                                                (int,(4,)),
+                                                (str,(1,))])
+    @pytest.mark.parametrize('N_values',[5*6*7,6*7*8])
+    def test_add_get(self,default,data_type,shape,N_values):
+        data = np.squeeze(np.random.randint(0,100,(N_values,)+shape)).astype(data_type)
+        default.add(data,'data')
+        assert (np.squeeze(data.reshape(N_values,-1)) == default.get('data')).all()
+
+
     def test_add_masked(self,default):
         data = np.random.rand(5*6*7,3)
         masked = ma.MaskedArray(data,mask=data<.4,fill_value=42.)