def test_clustering_two_methods(self, ens1):
cluster_collection = encore.cluster(
[ens1],
method=[
encore.AffinityPropagationNative(),
encore.AffinityPropagationNative()
])
assert len(cluster_collection[0]) == len(cluster_collection[1]), \
"Unexpected result: {0}".format(cluster_collection)
def test_clustering_two_methods(self):
cluster_collection = encore.cluster(
[self.ens1],
method=[
encore.AffinityPropagationNative(),
encore.AffinityPropagationNative()
])
assert_equal(
len(cluster_collection[0]),
len(cluster_collection[1]),
err_msg="Unexpected result: {0}".format(cluster_collection))
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_ces_error_estimation(self, ens1):
expected_average = 0.03
expected_stdev = 0.31
averages, stdevs = encore.ces(
[ens1, ens1],
estimate_error=True,
bootstrapping_samples=10,
clustering_method=encore.AffinityPropagationNative(
preference=-2.0),
selection="name CA and resnum 1-10")
average = averages[0, 1]
stdev = stdevs[0, 1]
assert_almost_equal(
average,
expected_average,
decimal=1,
err_msg=
"Unexpected average value for bootstrapped samples in Clustering Ensemble similarity"
)
assert_almost_equal(
stdev,
expected_stdev,
decimal=0,
err_msg=
"Unexpected standard daviation for bootstrapped samples in Clustering Ensemble similarity"
)
def test_clustering_two_methods_one_w_no_distance_matrix(self, ens1):
pytest.importorskip('sklearn')
cluster_collection = encore.cluster(
[ens1],
method=[encore.KMeans(17),
encore.AffinityPropagationNative()])
assert len(cluster_collection[0]) == len(cluster_collection[0]), \
"Unexpected result: {0}".format(cluster_collection)
def test_one(self, distance_matrix):
preference = -float(np.median(distance_matrix.as_array()) * 10.)
clustering_method = encore.AffinityPropagationNative(
preference=preference)
ccs = encore.cluster(None,
distance_matrix=distance_matrix,
method=clustering_method)
assert self.n_clusters == len(ccs), \
"Basic clustering test failed to give the right"\
"number of clusters: {0} vs {1}".format(self.n_clusters, len(ccs))
def test_clustering_two_methods_one_w_no_distance_matrix(self):
cluster_collection = encore.cluster(
[self.ens1],
method=[encore.KMeans(17),
encore.AffinityPropagationNative()])
print(cluster_collection)
assert_equal(
len(cluster_collection[0]),
len(cluster_collection[0]),
err_msg="Unexpected result: {0}".format(cluster_collection))
def test_ces_to_self(self, ens1):
results, details = \
encore.ces([ens1, ens1],
clustering_method=encore.AffinityPropagationNative(preference = -3.0))
result_value = results[0, 1]
expected_value = 0.
assert_almost_equal(
result_value,
expected_value,
err_msg="ClusteringEnsemble Similarity to itself not zero: {0:f}".
format(result_value))
