coverage: return to 100% coverage

src/cr/cube/cubepart.py

@@ -70,7 +70,7 @@ def cube_is_mr_by_itself(self):
         return False
 
     @lazyproperty
-    def cube_row_dimension(self):
+    def cube_row_dimension_type(self):
         """Member of `cr.cube.enum.DIMENSION_TYPE` for cube row dimension"""
         return self._cube.dimensions[0].dimension_type
 

tests/unit/test_cubepart.py

@@ -10,6 +10,7 @@
 from cr.cube.cube import Cube
 from cr.cube.cubepart import CubePartition, _Slice, _Strand, _Nub
 from cr.cube.dimension import Dimension
+from cr.cube.enum import DIMENSION_TYPE as DT
 from cr.cube.matrix import TransformedMatrix, _VectorAfterHiding
 from cr.cube.stripe import _BaseStripeRow, TransformedStripe
 
@@ -67,6 +68,26 @@ def it_knows_if_cube_is_mr_by_itself(self):
         # --- default of False is overridden by subclasses when appropriate ---
         assert CubePartition(None).cube_is_mr_by_itself is False
 
+    @pytest.mark.parametrize(
+        "dims, expected_value",
+        (
+            ((DT.CAT, DT.MR, DT.MR_CAT), DT.CAT),
+            ((DT.MR, DT.MR_CAT), DT.MR),
+            ((DT.MR_CAT,), DT.MR_CAT),
+        ),
+    )
+    def it_knows_cube_row_dimension_type(self, request, cube_, dims, expected_value):
+        all_dimensions_ = tuple(
+            instance_mock(request, Dimension, name="dim-%d" % idx, dimension_type=dt)
+            for idx, dt in enumerate(dims)
+        )
+        cube_.dimensions = all_dimensions_
+        cube_partition = CubePartition(cube_)
+
+        cube_row_dimension_type = cube_partition.cube_row_dimension_type
+
+        assert cube_row_dimension_type == expected_value
+
     def it_knows_the_primary_alpha_value_to_help(self, _alpha_values_prop_):
         """alpha is the primary confidence-interval threshold specified by the user."""
         _alpha_values_prop_.return_value = (0.042, 0.084)