Fix tests by removing duplicates

Author: William de Vazelhes

test/test_mahalanobis_mixin.py

@@ -284,5 +284,14 @@ def test_transformer_is_2D(estimator, build_dataset):
 
     # test that it works for 1 feature
     trunc_data = input_data[..., :1]
+    # we drop duplicates that might have been formed, i.e. of the form
+    # aabc or abcc or aabb for quadruplets, and aa for pairs.
+    slices = {4: [slice(0, 2), slice(2, 4)], 2: [slice(0, 2)]}
+    if trunc_data.ndim == 3:
+      for slice_idx in slices[trunc_data.shape[1]]:
+        _, indices = np.unique(trunc_data[:, slice_idx, :], axis=2,
+                               return_index=True)
+        trunc_data = trunc_data[indices]
+        labels = labels[indices]
     model.fit(trunc_data, labels)
     assert model.transformer_.shape == (1, 1)  # the transformer must be 2D