BF: handle empty BrainModelAxis masks and selections

nibabel/cifti2/cifti2_axes.py

@@ -481,6 +481,8 @@ def iter_structures(self):
         - slice to select the data associated with the brain structure from the tensor
         - :class:`BrainModelAxis` covering that specific brain structure
         """
+        if self.size == 0:
+            return
         idx_start = 0
         start_name = self.name[idx_start]
         for idx_current, name in enumerate(self.name):
@@ -567,14 +569,16 @@ def surface_mask(self):
         """
         (N, ) boolean array which is true for any element on the surface
         """
-        return np.vectorize(lambda name: name in self.nvertices.keys())(self.name)
+        return np.vectorize(lambda name: name in self.nvertices.keys(), otypes=[bool])(self.name)
 
     @property
     def volume_mask(self):
         """
         (N, ) boolean array which is true for any element on the surface
         """
-        return np.vectorize(lambda name: name not in self.nvertices.keys())(self.name)
+        return np.vectorize(lambda name: name not in self.nvertices.keys(), otypes=[bool])(
+            self.name
+        )
 
     _affine = None
 

nibabel/cifti2/tests/test_axes.py

@@ -12,6 +12,27 @@
 use_label = {0: ('something', (0.2, 0.4, 0.1, 0.5)), 1: ('even better', (0.3, 0.8, 0.43, 0.9))}
 
 
+@pytest.mark.parametrize('shape', [(4,), (2, 3, 4)])
+def test_empty_brain_model_mask(shape):
+    axis = axes.BrainModelAxis.from_mask(np.zeros(shape, dtype=bool), name='CortexLeft')
+    assert len(axis) == 0
+    assert axis.surface_mask.shape == (0,)
+    assert axis.volume_mask.shape == (0,)
+    assert axis.surface_mask.dtype == bool
+    assert axis.volume_mask.dtype == bool
+    assert list(axis.iter_structures()) == []
+
+
+@pytest.mark.parametrize('selection', [slice(0, 0), np.array([False, False])])
+def test_empty_brain_model_selection(selection):
+    axis = axes.BrainModelAxis.from_surface([0, 1], 4, name='CortexLeft')
+    empty = axis[selection]
+    assert len(empty) == 0
+    assert list(empty.iter_structures()) == []
+    assert empty + axis == axis
+    assert axis + empty == axis
+
+
 def get_brain_models():
     """
     Generates a set of practice BrainModelAxis axes