fix: Python3, Black, and numpy fixes

src/cr/cube/matrix.py

@@ -30,7 +30,7 @@ def __init__(self, unordered_matrix):
 
     @classmethod
     def matrix(cls, cube, dimensions, slice_idx):
-        """-> TransformedMatrix object constructed from values of `cube`.
+        """Return TransformedMatrix object constructed from values of `cube`.
 
         `cube` is the `cr.cube.Cube` object containing the data for this matrix. Note
         that not all the data in `cube` will necessarily be used by this matrix. When
@@ -280,7 +280,7 @@ def _columns_dimension(self):
 
     @lazyproperty
     def _inserted_columns(self):
-        """-> tuple of _InsertedColumn objects representing subtotal columns.
+        """tuple of _InsertedColumn objects representing subtotal columns.
 
         The returned vectors are in the order subtotals were specified in the cube
         result, which is no particular order. All subtotals defined on the column
@@ -308,7 +308,7 @@ def _inserted_columns(self):
 
     @lazyproperty
     def _inserted_rows(self):
-        """-> tuple of _InsertedRow objects representing inserted subtotal rows.
+        """tuple of _InsertedRow objects representing inserted subtotal rows.
 
         The returned vectors are in the order subtotals were specified in the cube
         result, which is no particular order.
@@ -331,7 +331,7 @@ def _inserted_rows(self):
 
     @lazyproperty
     def _row_order(self):
-        """ -> 1D ndarray of int row idx specifying order of unordered-array rows."""
+        """1D ndarray of int row idx specifying order of unordered-array rows."""
         dimension = self._rows_dimension
         collation_method = dimension.collation_method
 
@@ -436,7 +436,7 @@ def table_margin(self):
         )  # pragma: no cover
 
     def _array_type_std_res(self, counts, total, colsum, rowsum):
-        """-> 2D ndarray of np.float64 std-res value for each cell of MR matrix.
+        """Return 2D np.float64 ndarray of std-res value for each cell of MR matrix.
 
         This is a utility method used by a matrix with one or more MR dimensions. The
         caller forms the input arrays based on which of its dimensions are MR.
@@ -1963,7 +1963,17 @@ def base(self):
         because each MR_SUBVAR element has a distinct unweighted N. A vector opposing
         a CAT dimension produces a scalar value.
         """
-        return self._unassembled_vector.base
+        unassembled_base = self._unassembled_vector.base
+
+        # --- `base` is an ndarray when opposing dimension is MR or CA_SUBVAR.
+        # --- Neither of these can have subtotals (subvars don't add), so no
+        # --- interleaving is necessary.
+        if isinstance(unassembled_base, np.ndarray):
+            return unassembled_base[self._opposing_order]
+
+        # --- otherwise it's a scalar value and neither interleaving nor ordering
+        # --- is required
+        return unassembled_base
 
     @lazyproperty
     def column_index(self):
@@ -1973,7 +1983,7 @@ def column_index(self):
         """
 
         def fsubtot(inserted_vector):
-            """-> np.nan as unconditional col-index value for `inserted_vector`.
+            """Return np.nan as unconditional col-index value for `inserted_vector`.
 
             Called by ._apply_interleaved() to compute inserted value which it places
             in the right vector position.
@@ -2035,7 +2045,17 @@ def margin(self):
         dimension produces a scalar value. Values are np.int64 if the cube-result is
         unweighted.
         """
-        return self._unassembled_vector.margin
+        unassembled_margin = self._unassembled_vector.margin
+
+        # --- `margin` is an ndarray when opposing dimension is MR or CA_SUBVAR.
+        # --- Neither of these can have subtotals (subvars don't add), so no
+        # --- interleaving is necessary.
+        if isinstance(unassembled_margin, np.ndarray):
+            return unassembled_margin[self._opposing_order]
+
+        # --- otherwise it's a scalar value and neither interleaving nor ordering
+        # --- is required
+        return unassembled_margin
 
     @lazyproperty
     def means(self):
@@ -2045,7 +2065,7 @@ def means(self):
         """
 
         def fsubtot(inserted_vector):
-            """-> np.nan as unconditional mean value for `inserted_vector`.
+            """Return np.nan as unconditional mean value for `inserted_vector`.
 
             Passed to and called by ._apply_interleaved() to compute inserted value
             which it places in the right vector position.
@@ -2157,7 +2177,7 @@ def zscores(self):
         """
 
         def fsubtot(inserted_vector):
-            """-> np.float64 zscore for `inserted_vector`.
+            """Return np.float64 zscore for `inserted_vector`.
 
             Passed to and called by ._apply_interleaved() to compute inserted value
             which it places in the right vector position.
@@ -2187,7 +2207,7 @@ def fsubtot(inserted_vector):
         return self._apply_interleaved(self._unassembled_vector.zscores, fsubtot)
 
     def _apply_interleaved(self, unassembled_values, fsubtot):
-        """-> 1D array of result of applying fbase or fsubtot to each interleaved item.
+        """Return 1D array result of applying fbase or fsubtot to each interleaved item.
 
         `unassembled_values` is the "unassembled" vector measure values. This vector can
         be a base vector or an inserted vector.

tests/integration/test_cubepart.py

@@ -702,7 +702,6 @@ def it_places_insertions_on_a_reordered_dimension_in_the_right_position(self):
             ],
         )
 
-    @pytest.mark.xfail(reason="WIP", raises=AssertionError, strict=True)
     def it_provides_same_proportions_without_explicit_order(self):
         transforms = TR.TEST_DASHBOARD_TRANSFORM_SINGLE_EL_VISIBLE
         slice_ = Cube(CR.TEST_DASHBOARD_FIXTURE, transforms=transforms).partitions[0]