def test_parallel_clustering_bad_input():
pc = ParallelClustering(sk.cluster.DBSCAN())
X = [np.random.random((5, 4)), np.random.random((5, 4))]
with pytest.raises(TypeError, match="`masks` must be a boolean array."):
pc.fit(X)
X[1] = np.ones((6, 4), dtype=bool)
with pytest.raises(ValueError,
match="`X_tot` and `masks` must have the same number"):
pc.fit(X)
def test_parallel_clustering_metric_affinity_precomputed_not_implemented():
class DummyClusterer(sk.base.BaseEstimator, sk.base.ClusterMixin):
def __init__(self, metric="precomputed", affinity="precomputed"):
self.metric = metric
self.affinity = affinity
pc = ParallelClustering(DummyClusterer())
X = [np.random.random((5, 4)), np.ones((5, 4), dtype=bool)]
with pytest.raises(NotImplementedError,
match="Behaviour when metric and affinity"):
pc.fit(X)
def test_parallel_clustering_bad_clusterer():
pc = ParallelClustering(sk.decomposition.PCA())
X = [np.random.random((5, 4)), np.ones((5, 4), dtype=bool)]
with pytest.raises(TypeError, match="`clusterer` must be an instance of"):
pc.fit(X)