[178390751]: fix after rebase

Crunch-io · Oct 8, 2021 · ea06064 · ea06064
1 parent f9a67d7
commit ea06064
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Showing 4 changed files with 2 additions and 105 deletions.
diff --git a/src/cr/cube/matrix/assembler.py b/src/cr/cube/matrix/assembler.py
@@ -616,6 +616,7 @@ def rows_scale_median(self):
         """Optional 1D Row scale median marginal for this cube-result"""
         return self._assemble_marginal(self._measures.rows_scale_median)
 
+    @lazyproperty
     def scale_mean_pairwise_indices(self):
         """1D ndarray of tuple of int pairwise-t threshold for scale means."""
         marginal = self._measures.scale_mean_pairwise_indices

diff --git a/src/cr/cube/matrix/measure.py b/src/cr/cube/matrix/measure.py
@@ -493,6 +493,7 @@ def rows_weighted_base(self):
         """
         return _MarginWeightedBase(self._dimensions, self, self._cube_measures, MO.ROWS)
 
+    @lazyproperty
     def scale_mean_pairwise_indices(self):
         """_ScaleMeanPairwiseIndices measure object for this cube-result"""
         return _ScaleMeanPairwiseIndices(

diff --git a/src/cr/cube/measures/pairwise_significance.py b/src/cr/cube/measures/pairwise_significance.py
diff --git a/tests/unit/test_cubepart.py b/tests/unit/test_cubepart.py
@@ -60,111 +60,6 @@ def it_knows_the_index_of_its_cube_in_the_cube_set(self, cube_):
 
         assert cube_index == 42
 
-    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)
-        assert CubePartition(None)._alpha == 0.042
-
-    @pytest.mark.parametrize(
-        "alpha_values, expected_value", (((0.042, 0.084), 0.084), ((0.042, None), None))
-    )
-    def it_knows_the_secondary_alpha_value_to_help(
-        self, _alpha_values_prop_, alpha_values, expected_value
-    ):
-        _alpha_values_prop_.return_value = alpha_values
-        assert CubePartition(None)._alpha_alt == expected_value
-
-    @pytest.mark.parametrize(
-        "pw_indices_dict, expected_value",
-        (
-            # --- default value is .05 ---
-            ({}, (0.05, None)),
-            ({"alpha": {}}, (0.05, None)),
-            ({"alpha": []}, (0.05, None)),
-            # --- scalar (float) value sets alpha and sets alpha_alt to None ---
-            ({"alpha": 0.025}, (0.025, None)),
-            # --- single (float) value sets alpha and sets alpha_alt to None ---
-            ({"alpha": [0.03]}, (0.03, None)),
-            # --- two values sets alpha to lesser and alpha_alt to greater ---
-            ({"alpha": [0.07, 0.03]}, (0.03, 0.07)),
-            # --- third and later values are ignored ---
-            ({"alpha": (0.07, 0.03, "foobar")}, (0.03, 0.07)),
-        ),
-    )
-    def it_interprets_the_provided_alpha_values_to_help(
-        self, pw_indices_dict, expected_value
-    ):
-        cube_partition = CubePartition(None, {"pairwise_indices": pw_indices_dict})
-
-        alpha_values = cube_partition._alpha_values
-
-        assert alpha_values == expected_value
-
-    @pytest.mark.parametrize(
-        "pw_indices_dict, exception_type, expected_message",
-        (
-            # --- type errors ---
-            (
-                {"alpha": {"al": "pha"}},
-                TypeError,
-                "transforms.pairwise_indices.alpha, when defined, must be a list of 1 "
-                "or 2 float values between 0.0 and 1.0 exclusive. Got %s"
-                % repr({"al": "pha"}),
-            ),
-            (
-                {"alpha": "0.05"},
-                TypeError,
-                "transforms.pairwise_indices.alpha, when defined, must be a list of 1 "
-                "or 2 float values between 0.0 and 1.0 exclusive. Got %s"
-                % repr("0.05"),
-            ),
-            # --- scalar out-of-range errors ---
-            (
-                {"alpha": -0.1},
-                ValueError,
-                "alpha value, when provided, must be between 0.0 and 1.0 exclusive. "
-                "Got %s" % repr(-0.1),
-            ),
-            (
-                {"alpha": 1.0},
-                ValueError,
-                "alpha value, when provided, must be between 0.0 and 1.0 exclusive. "
-                "Got %s" % repr(1.0),
-            ),
-            # --- sequence value errors ---
-            (
-                {"alpha": [0.01, ".05"]},
-                ValueError,
-                "transforms.pairwise_indices.alpha must be a list of 1 or 2 float "
-                "values between 0.0 and 1.0 exclusive. Got %s" % repr([0.01, ".05"]),
-            ),
-        ),
-    )
-    def but_it_raises_on_invalid_alpha_values(
-        self, pw_indices_dict, exception_type, expected_message
-    ):
-        cube_partition = CubePartition(None, {"pairwise_indices": pw_indices_dict})
-
-        with pytest.raises(exception_type) as e:
-            cube_partition._alpha_values
-
-        assert str(e.value) == expected_message
-
-    @pytest.mark.parametrize(
-        "pw_indices_dict, expected_value",
-        (
-            # --- default value is True ---
-            ({}, True),
-            ({"only_larger": "foobar"}, True),
-            ({"only_larger": False}, False),
-        ),
-    )
-    def it_knows_the_only_larger_flag_state_to_help(
-        self, _transforms_dict_prop_, pw_indices_dict, expected_value
-    ):
-        _transforms_dict_prop_.return_value = {"pairwise_indices": pw_indices_dict}
-        assert CubePartition(None)._only_larger == expected_value
-
     # fixture components ---------------------------------------------
 
     @pytest.fixture