def test_clustering_AffinityPropagationNative_direct(self, ens1):
method = encore.AffinityPropagationNative()
distance_matrix = encore.get_distance_matrix(ens1)
cluster_assignment, details = method(distance_matrix)
expected_value = 7
assert len(set(cluster_assignment)) == expected_value, \
"Unexpected result: {0}".format(cluster_assignment)
def test_clustering_AffinityPropagationNative_direct(self, ens1):
method = encore.AffinityPropagationNative()
distance_matrix = encore.get_distance_matrix(ens1)
cluster_assignment, details = method(distance_matrix)
expected_value = 7
assert len(set(cluster_assignment)) == expected_value, \
"Unexpected result: {0}".format(cluster_assignment)
def test_clustering_DBSCAN_direct(self, ens1):
pytest.importorskip('sklearn')
method = encore.DBSCAN(eps=0.5, min_samples=2)
distance_matrix = encore.get_distance_matrix(ens1)
cluster_assignment, details = method(distance_matrix)
expected_value = 2
assert len(set(cluster_assignment)) == expected_value, \
"Unexpected result: {0}".format(cluster_assignment)
def test_dimensionality_reduction_SPENative_direct(self, ens1):
dimension = 2
method = encore.StochasticProximityEmbeddingNative(dimension=dimension)
distance_matrix = encore.get_distance_matrix(ens1)
coordinates, details = method(distance_matrix)
assert_equal(coordinates.shape[0], dimension,
err_msg="Unexpected result in dimensionality reduction: {0}".format(
coordinates))
def test_clustering_DBSCAN_direct(self, ens1):
pytest.importorskip('sklearn')
method = encore.DBSCAN(eps=0.5, min_samples=2)
distance_matrix = encore.get_distance_matrix(ens1)
cluster_assignment, details = method(distance_matrix)
expected_value = 2
assert len(set(cluster_assignment)) == expected_value, \
"Unexpected result: {0}".format(cluster_assignment)
def test_clustering_AffinityPropagation_direct(self, ens1):
pytest.importorskip('sklearn')
method = encore.AffinityPropagation()
distance_matrix = encore.get_distance_matrix(ens1)
cluster_assignment = method(distance_matrix)
expected_value = 7
assert len(set(cluster_assignment)) == expected_value, \
"Unexpected result: {0}".format(cluster_assignment)
def test_clustering_DBSCAN_direct(self):
method = encore.DBSCAN(eps=0.5, min_samples=2)
distance_matrix = encore.get_distance_matrix(self.ens1)
cluster_assignment, details = method(distance_matrix)
expected_value = 2
assert_equal(
len(set(cluster_assignment)),
expected_value,
err_msg="Unexpected result: {0}".format(cluster_assignment))
def test_clustering_AffinityPropagation_direct(self):
method = encore.AffinityPropagation()
distance_matrix = encore.get_distance_matrix(self.ens1)
cluster_assignment, details = method(distance_matrix)
expected_value = 7
assert_equal(
len(set(cluster_assignment)),
expected_value,
err_msg="Unexpected result: {0}".format(cluster_assignment))
def test_dimensionality_reduction_SPENative_direct(self, ens1):
dimension = 2
method = encore.StochasticProximityEmbeddingNative(dimension=dimension)
distance_matrix = encore.get_distance_matrix(ens1)
coordinates, details = method(distance_matrix)
assert_equal(
coordinates.shape[0],
dimension,
err_msg="Unexpected result in dimensionality reduction: {0}".
format(coordinates))
def test_dres_without_superimposition(self, ens1, ens2):
distance_matrix = encore.get_distance_matrix(
encore.merge_universes([ens1, ens2]),
superimpose=False)
results, details = encore.dres([ens1, ens2],
distance_matrix = distance_matrix)
result_value = results[0,1]
expected_value = 0.68
assert_almost_equal(result_value, expected_value, decimal=1,
err_msg="Unexpected value for Dim. reduction Ensemble Similarity: {0:f}. Expected {1:f}.".format(result_value, expected_value))
def test_dres_without_superimposition(self, ens1, ens2):
distance_matrix = encore.get_distance_matrix(encore.merge_universes(
[ens1, ens2]),
superimpose=False)
results, details = encore.dres([ens1, ens2],
distance_matrix=distance_matrix)
result_value = results[0, 1]
expected_value = 0.68
assert_almost_equal(
result_value,
expected_value,
decimal=1,
err_msg=
"Unexpected value for Dim. reduction Ensemble Similarity: {0:f}. Expected {1:f}."
.format(result_value, expected_value))
