use None for no selection, empty list is 'nothing'

python/damask/_grid.py

@@ -958,7 +958,7 @@ class Grid:
         """
         def mostFrequent(arr: np.ndarray, selection: List, invert: bool):
             me = arr[arr.size//2]
-            if len(selection) == 0 or np.isin(me,selection,invert=invert):
+            if selection is None or np.isin(me,selection,invert=invert):
                 unique, inverse = np.unique(arr, return_inverse=True)
                 return unique[np.argmax(np.bincount(inverse))]
             else:
@@ -1179,7 +1179,7 @@ class Grid:
         """
         def tainted_neighborhood(stencil: np.ndarray, selection):
             me = stencil[stencil.shape[0]//2]
-            return np.any(stencil != me if len(selection) == 0 else
+            return np.any(stencil != me if selection is None else
                           np.in1d(stencil,np.array(list(set(selection) - {me}))))
 
         offset_ = np.nanmax(self.material)+1 if offset is None else offset

python/damask/seeds.py

@@ -135,7 +135,7 @@ def from_grid(grid,
     """
     material = grid.material.reshape((-1,1),order='F')
     selection_ = _util.tbd(selection)
-    mask = _np.full(grid.cells.prod(),True,dtype=bool) if len(selection_) == 0 else \
+    mask = _np.full(grid.cells.prod(),True,dtype=bool) if selection_ is None else \
            _np.isin(material,selection_,invert=invert_selection).flatten()
     coords = _grid_filters.coordinates0_point(grid.cells,grid.size).reshape(-1,3,order='F')
 

python/damask/util.py

@@ -754,7 +754,7 @@ def tail_repack(extended: Union[str, Sequence[str]],
 
 def tbd(arg) -> List:
     if arg is None:
-        return []
+        return None
     elif isinstance(arg,(np.ndarray,Collection)):
         return list(arg)
     else:

python/tests/test_Grid.py

@@ -182,6 +182,11 @@ class TestGrid:
         assert random.clean(selection=selection,invert_selection=invert) == \
                random.clean(selection=selection_inverse,invert_selection=not invert)
 
+    def test_clean_selection_empty(self,random):
+        assert random.clean(selection=[],invert_selection=False) == random and \
+               random.clean(selection=[],invert_selection=True) == random.clean()
+
+
     @pytest.mark.parametrize('cells',[
                                      (10,11,10),
                                      [10,13,10],
@@ -319,7 +324,7 @@ class TestGrid:
         assert grid_equal(G_1,G_2)
 
 
-    @pytest.mark.parametrize('selection',[1,[]])
+    @pytest.mark.parametrize('selection',[1,None])
     def test_vicinity_offset(self,selection):
         offset = np.random.randint(2,4)
         vicinity = np.random.randint(2,4)
@@ -346,6 +351,10 @@ class TestGrid:
         assert random.vicinity_offset(selection=selection,invert_selection=invert) == \
                random.vicinity_offset(selection=selection_inverse,invert_selection=not invert)
 
+    def test_vicinity_offset_selection_empty(self,random):
+        assert random.vicinity_offset(selection=[],invert_selection=False) == random and \
+               random.vicinity_offset(selection=[],invert_selection=True) == random.vicinity_offset()
+
 
     @pytest.mark.parametrize('periodic',[True,False])
     def test_vicinity_offset_invariant(self,default,periodic):