Merge pull request #3025 from ogrisel/remove-unstable-lobpcg-test

ogrisel · ogrisel · commit 42663e4a738e · 2014-04-02T19:10:25.000+02:00
[MRG] Remove redundant yet unstable test_spectral_lobpcg_mode
diff --git a/sklearn/cluster/tests/test_spectral.py b/sklearn/cluster/tests/test_spectral.py
@@ -52,28 +52,6 @@ def test_spectral_clustering():
                 assert_array_equal(model_copy.labels_, model.labels_)
 
 
-def test_spectral_lobpcg_mode():
-    # Test the lobpcg mode of SpectralClustering
-    # We need a fairly big data matrix, as lobpcg does not work with
-    # small data matrices
-    centers = np.array([
-        [0., 0.],
-        [10., 10.],
-    ])
-    # The cluster_std parameter has been selected to have the blob close enough
-    # to get stable results both with the ATLAS and the reference
-    # implementations of LAPACK.
-    X, true_labels = make_blobs(n_samples=300, centers=centers,
-                                cluster_std=20.0, random_state=42)
-    D = pairwise_distances(X)  # Distance matrix
-    S = np.max(D) - D  # Similarity matrix
-    labels = spectral_clustering(S, n_clusters=len(centers),
-                                 random_state=0, eigen_solver="lobpcg")
-    # We don't care too much that it's good, just that it *worked*.
-    # There does have to be some lower limit on the performance though.
-    assert_greater(np.mean(labels == true_labels), .3)
-
-
 def test_spectral_amg_mode():
     # Test the amg mode of SpectralClustering
     centers = np.array([
