adding tests that fail dch

Author: agoscinski

tests/test_dch.py

@@ -103,6 +103,41 @@ def test_negative_score(self):
         )[0]
         self.assertTrue(distance < 0.0)
 
+    def test_positive_score(self):
+        """
+        Ensure that when we score on the points we fitted that we obtain only >= 0 distances
+        In an old implementation we observed this bug for the dataset we use in this test
+        (see issue #162)
+        """
+        X = [[1.88421449, 0.86675162],
+             [1.88652863, 0.86577001],
+             [1.89200182, 0.86573224],
+             [1.89664107, 0.86937211],
+             [1.90181908, 0.85964603],
+             [1.90313135, 0.85695238],
+             [1.90063025, 0.84948309],
+             [1.90929015, 0.87526563],
+             [1.90924666, 0.85509754],
+             [1.91139146, 0.86115512],
+             [1.91199225, 0.8681867 ],
+             [1.90681563, 0.85036791],
+             [1.90193881, 0.84168907],
+             [1.90544262, 0.84451744],
+             [1.91498802, 0.86010812],
+             [1.91305204, 0.85333203],
+             [1.89779902, 0.83731807],
+             [1.91725967, 0.86630218],
+             [1.91309514, 0.85046796],
+             [1.89822103, 0.83522425]]
+        y = [-2.69180967, -2.72443825, -2.77293913, -2.797828  , -2.12097652, -2.69428482,
+             -2.70275134, -2.80617667, -2.79199375, -2.01707974, -2.74203922, -2.24217962,
+             -2.03472   , -2.72612763, -2.7071123 , -2.75706683, -2.68925596, -2.77160335,
+             -2.69528665, -2.70911598]
+        selector = DirectionalConvexHull(low_dim_idx=[0, 1])
+        selector.fit(X, y)
+        distances = selector.score_samples(X, y)
+        self.assertTrue(np.all(distances >= -1e-12))
+
     def test_score_function_warnings(self):
         """
         Ensure that calling `score_samples` with points outside the range causes an error
@@ -128,7 +163,7 @@ def test_score_function_warnings(self):
             self.assertTrue(len(warning) == 1)
             self.assertTrue(issubclass(warning[0].category, UserWarning))
             self.assertTrue(
-                "There are samples in X with a low-dimensional part that is outside of the range of the convex surface. Distance will contain nans."
+                "There are samples in X with a low-dimensional part that is outside of the range of the convex surface.  Distance will contain nans."
                 == str(warning[0].message)
             )