specialize for 1D

Author: jcapriot

discretize/tensor_mesh.py

@@ -774,11 +774,14 @@ def point2index(self, locs):  # NOQA D102
         # at index 1 to maintain the sorted list, but that corresponds to cell 0.
         # clipping here ensures that anything outside the mesh will return the nearest cell.
         multi_inds = tuple(
-            np.clip(np.searchsorted(n, p) - 1, 0, len(n) - 1)
+            np.clip(np.searchsorted(n, p) - 1, 0, len(n) - 2)
             for n, p in zip(cell_bounds, locs.T)
         )
         # and of course, we are fortran ordered in a tensor mesh.
-        return np.ravel_multi_index(multi_inds, self.shape_cells, order="F")
+        if self.dim == 1:
+            return multi_inds[0]
+        else:
+            return np.ravel_multi_index(multi_inds, self.shape_cells, order="F")
 
     def _repr_attributes(self):
         """Represent attributes of the mesh."""

tests/base/test_tensor.py

@@ -337,7 +337,7 @@ def test_tensor_point2index_inside_points(random_tensor_mesh):
     mesh = random_tensor_mesh
     dim = mesh.dim
     m_origin = mesh.origin
-    m_extent = np.max(mesh.nodes, axis=0)
+    m_extent = np.atleast_1d(np.max(mesh.nodes, axis=0))
 
     nd = 15
     points = np.stack(np.meshgrid(*np.linspace(m_origin, m_extent, nd).T), axis=-1)
@@ -357,7 +357,7 @@ def test_tensor_point2index_outside_points(random_tensor_mesh):
     mesh = random_tensor_mesh
     dim = mesh.dim
     m_origin = mesh.origin
-    m_extent = np.max(mesh.nodes, axis=0)
+    m_extent = np.atleast_1d(np.max(mesh.nodes, axis=0))
     m_width = m_extent - m_origin
 
     nd = 15