def test_custom_adjacency():
class CustomAdjacency(Adjacency):
name = "custom"
def adjacency_graph(self, X):
return squareform(pdist(X))
rand = np.random.RandomState(42)
X = rand.rand(10, 2)
D = compute_adjacency_matrix(X, method='custom', radius=1)
assert_allclose(D, cdist(X, X))
Adjacency._remove_from_registry("custom")
def test_adjacency():
rng = np.random.RandomState(36)
X = rng.rand(100, 3)
Gtrue = {}
exact_methods = [m for m in Adjacency.methods()
if not m.endswith('flann')]
def check_kneighbors(n_neighbors, method):
if method == 'pyflann' and NO_PYFLANN:
raise SkipTest("pyflann not installed")
G = compute_adjacency_matrix(X, method=method,
n_neighbors=n_neighbors)
assert isspmatrix(G)
assert G.shape == (X.shape[0], X.shape[0])
if method in exact_methods:
assert_allclose(G.toarray(), Gtrue[n_neighbors].toarray())
def check_radius(radius, method):
if method == 'pyflann' and NO_PYFLANN:
raise SkipTest("pyflann not installed")
G = compute_adjacency_matrix(X, method=method,
radius=radius)
assert isspmatrix(G)
assert G.shape == (X.shape[0], X.shape[0])
if method in exact_methods:
assert_allclose(G.toarray(), Gtrue[radius].toarray())
for n_neighbors in [5, 10, 15]:
Gtrue[n_neighbors] = compute_adjacency_matrix(X, method='brute',
n_neighbors=n_neighbors)
for method in Adjacency.methods():
yield check_kneighbors, n_neighbors, method
for radius in [0.1, 0.5, 1.0]:
Gtrue[radius] = compute_adjacency_matrix(X, method='brute',
radius=radius)
for method in Adjacency.methods():
yield check_radius, radius, method