TST upgrade trivial (single-class) k-NN problems to binary ones

XXX should we raise a warning/exception when there is only one class in y?

Author: larsmans

sklearn/neighbors/tests/test_neighbors.py

@@ -174,7 +174,7 @@ def test_kneighbors_classifier(n_samples=40,
     """Test k-neighbors classification"""
     rng = np.random.RandomState(random_state)
     X = 2 * rng.rand(n_samples, n_features) - 1
-    y = ((X ** 2).sum(axis=1) < .25).astype(np.int)
+    y = ((X ** 2).sum(axis=1) < .5).astype(np.int)
 
     weight_func = _weight_func
 
@@ -218,7 +218,7 @@ def test_radius_neighbors_classifier(n_samples=40,
     """Test radius-based classification"""
     rng = np.random.RandomState(random_state)
     X = 2 * rng.rand(n_samples, n_features) - 1
-    y = ((X ** 2).sum(axis=1) < .25).astype(np.int)
+    y = ((X ** 2).sum(axis=1) < .5).astype(np.int)
 
     weight_func = _weight_func
 
@@ -312,7 +312,7 @@ def test_kneighbors_classifier_sparse(n_samples=40,
     # Like the above, but with various types of sparse matrices
     rng = np.random.RandomState(random_state)
     X = 2 * rng.rand(n_samples, n_features) - 1
-    y = ((X ** 2).sum(axis=1) < .25).astype(np.int)
+    y = ((X ** 2).sum(axis=1) < .5).astype(np.int)
 
     SPARSE_TYPES = (bsr_matrix, coo_matrix, csc_matrix, csr_matrix,
                     dok_matrix, lil_matrix)