Merge 0d50fd9 into d7ea279

src/cr/cube/cubepart.py

@@ -69,6 +69,11 @@ def cube_index(self):
     def cube_is_mr_by_itself(self):
         return False
 
+    @lazyproperty
+    def cube_row_dimension_type(self):
+        """Member of `cr.cube.enum.DIMENSION_TYPE` for cube row dimension"""
+        return self._cube.dimensions[0].dimension_type
+
     @lazyproperty
     def dimension_types(self):
         """Sequence of member of `cr.cube.enum.DIMENSION_TYPE` for each dimension.

src/cr/cube/matrix.py

@@ -876,12 +876,19 @@ class _MrXMrMatrix(_MatrixWithMR):
     """
 
     def __init__(
-        self, dimensions, counts, base_counts, counts_with_missings, overlaps=None
+        self,
+        dimensions,
+        counts,
+        base_counts,
+        counts_with_missings,
+        overlaps=None,
+        overlaps_margin=None,
     ):
         super(_MrXMrMatrix, self).__init__(
             dimensions, counts, base_counts, counts_with_missings
         )
         self._overlaps = overlaps
+        self._overlaps_margin = overlaps_margin
 
     @lazyproperty
     def columns(self):
@@ -948,24 +955,27 @@ def tstats_overlap(self):
         """
 
         # Subtraction of the proportions foreach observation
-        diff = np.subtract.outer(
-            self._mr_shadow_proportions.diagonal(),
-            self._mr_shadow_proportions.diagonal(),
+        diff = (
+            np.subtract.outer(
+                self._mr_shadow_proportions.diagonal(),
+                self._mr_shadow_proportions.diagonal(),
+            )
+            * -1
         )
 
         se_pi_pj = np.add.outer(
             self._mr_shadow_proportions.diagonal()
             * (1 - self._mr_shadow_proportions.diagonal())
-            / self._pairwise_overlap_total.diagonal(),
+            / self._overlaps_margin.diagonal(),
             self._mr_shadow_proportions.diagonal()
             * (1 - self._mr_shadow_proportions.diagonal())
-            / self._pairwise_overlap_total.diagonal(),
+            / self._overlaps_margin.diagonal(),
         )
 
         # Correction factor considering the overlap
         correction_factor = (
             2
-            * self._pairwise_overlap_total
+            * self._overlaps_margin
             * (
                 self._mr_shadow_proportions
                 - np.multiply.outer(
@@ -974,8 +984,7 @@ def tstats_overlap(self):
                 )
             )
         ) / np.multiply.outer(
-            self._pairwise_overlap_total.diagonal(),
-            self._pairwise_overlap_total.diagonal(),
+            self._overlaps_margin.diagonal(), self._overlaps_margin.diagonal()
         )
         se_diff = np.sqrt(se_pi_pj - correction_factor)
         np.fill_diagonal(diff, 0)
@@ -1018,17 +1027,7 @@ def _mr_shadow_proportions(self):
         element of any prepended dimensions:
         A 1d interface to a 4d hypercube of underlying counts.
         """
-        return self._counts[:, 0, :, 0] / self._pairwise_overlap_total
-
-    @lazyproperty
-    def _pairwise_overlap_total(self):
-        """Return 2D ndarray symmetric-square matrix of valid observations.
-
-        Given a 4d hypercube of multiple response items, return the
-        symmetric square matrix of valid observations between all pairs.
-        n1 = 2; n2 = 2; n12 = 1; overlap total = 3
-        """
-        return np.sum(self._counts, axis=(1, 3))
+        return self._counts[:, 0, :, 0] / self._overlaps_margin
 
     @lazyproperty
     def _row_generator(self):

src/cr/cube/util.py

@@ -30,7 +30,19 @@ def calculate_overlap_tstats(
             if offset != 0
             else mr_counts_with_missings[slice_index]
         )
-        overlap_slice = cls(mr_dimensions, counts, base_counts, counts_with_missings)
+        overlap_margins = (
+            np.sum(mr_counts[slice_index], axis=0)[:, 0, :, 0]
+            if offset != 0
+            else np.sum(mr_counts, axis=0)[:, 0, :, 0]
+        )
+        overlap_slice = cls(
+            mr_dimensions,
+            counts,
+            base_counts,
+            counts_with_missings,
+            None,
+            overlap_margins,
+        )
         diff, se_diff = overlap_slice.tstats_overlap
         numerator[slice_index] = diff
         standard_error[slice_index] = se_diff

tests/expectations/cat-x-mr-aug-pw-idxs-alt.py

@@ -1,6 +1,6 @@
 (
-    ((2, 4), (2, 4), (4,), (2, 4), ()),
-    ((1, 2, 3, 4), (2, 4), (), (2, 4), ()),
-    ((1, 2, 3, 4), (2, 4), (), (2, 4), ()),
-    ((1, 2, 3, 4), (2, 4), (), (2, 4), ()),
+    ((1, 2, 3), (), (), (), (1, 2, 3)),
+    ((), (), (1, 3, 4), (), (3,)),
+    ((), (0, 4), (4,), (0,), ()),
+    ((), (0, 2, 4), (4,), (0, 2, 4), ()),
 )

tests/expectations/cat-x-mr-aug-pw-idxs-recip.py

@@ -1,6 +1,6 @@
 (
-    ((2, 4), (2, 4), (0, 1, 3, 4), (2, 4), (0, 1, 2, 3)),
-    ((1, 2, 4), (0, 2, 4), (0, 1, 3), (2, 4), (0, 1, 3)),
-    ((1, 2, 3, 4), (0, 2, 4), (0, 1, 3), (0, 2, 4), (0, 1, 3)),
-    ((1, 2, 3, 4), (0, 2, 4), (0, 1, 3), (0, 2, 4), (0, 1, 3)),
+    ((1, 2, 3), (0,), (0, 4), (0, 4), (2, 3)),
+    ((), (2,), (1, 3), (2,), ()),
+    ((), (), (), (), ()),
+    ((1, 3), (0, 4), (3,), (0, 2, 4), (1, 3)),
 )

tests/expectations/cat-x-mr-aug-pw-idxs.py

@@ -1,6 +1,6 @@
 (
-    ((2, 4), (2, 4), (4,), (2, 4), ()),
-    ((1, 2, 4), (2, 4), (), (2, 4), ()),
-    ((1, 2, 3, 4), (2, 4), (), (2, 4), ()),
-    ((1, 2, 3, 4), (2, 4), (), (2, 4), ()),
+    ((1, 2, 3), (), (), (), (2, 3)),
+    ((), (), (1, 3), (), ()),
+    ((), (), (), (), ()),
+    ((), (0, 4), (), (0, 2, 4), ()),
 )