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import numpy as np
import pytest
from scipy.sparse.csgraph import connected_components
from sklearn.metrics.pairwise import pairwise_distances
from sklearn.neighbors import kneighbors_graph
from sklearn.utils.graph import _fix_connected_components
def test_fix_connected_components():
# Test that _fix_connected_components reduces the number of component to 1.
X = np.array([0, 1, 2, 5, 6, 7])[:, None]
graph = kneighbors_graph(X, n_neighbors=2, mode="distance")
n_connected_components, labels = connected_components(graph)
assert n_connected_components > 1
graph = _fix_connected_components(X, graph, n_connected_components, labels)
n_connected_components, labels = connected_components(graph)
assert n_connected_components == 1
def test_fix_connected_components_precomputed():
# Test that _fix_connected_components accepts precomputed distance matrix.
X = np.array([0, 1, 2, 5, 6, 7])[:, None]
graph = kneighbors_graph(X, n_neighbors=2, mode="distance")
n_connected_components, labels = connected_components(graph)
assert n_connected_components > 1
distances = pairwise_distances(X)
graph = _fix_connected_components(
distances, graph, n_connected_components, labels, metric="precomputed"
)
n_connected_components, labels = connected_components(graph)
assert n_connected_components == 1
# but it does not work with precomputed neighbors graph
with pytest.raises(RuntimeError, match="does not work with a sparse"):
_fix_connected_components(
graph, graph, n_connected_components, labels, metric="precomputed"
)
def test_fix_connected_components_wrong_mode():
# Test that the an error is raised if the mode string is incorrect.
X = np.array([0, 1, 2, 5, 6, 7])[:, None]
graph = kneighbors_graph(X, n_neighbors=2, mode="distance")
n_connected_components, labels = connected_components(graph)
with pytest.raises(ValueError, match="Unknown mode"):
graph = _fix_connected_components(
X, graph, n_connected_components, labels, mode="foo"
)
def test_fix_connected_components_connectivity_mode():
# Test that the connectivity mode fill new connections with ones.
X = np.array([0, 1, 6, 7])[:, None]
graph = kneighbors_graph(X, n_neighbors=1, mode="connectivity")
n_connected_components, labels = connected_components(graph)
graph = _fix_connected_components(
X, graph, n_connected_components, labels, mode="connectivity"
)
assert np.all(graph.data == 1)
def test_fix_connected_components_distance_mode():
# Test that the distance mode does not fill new connections with ones.
X = np.array([0, 1, 6, 7])[:, None]
graph = kneighbors_graph(X, n_neighbors=1, mode="distance")
assert np.all(graph.data == 1)
n_connected_components, labels = connected_components(graph)
graph = _fix_connected_components(
X, graph, n_connected_components, labels, mode="distance"
)
assert not np.all(graph.data == 1)
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