def test_clustered_subset_separation():
"""[Base] SubsetIndex: test the array shape on generation."""
classes = cl_2.predict(X)
for partition in ClusteredSubsetIndex(
cl_2, 2, 2, X=X).partition(as_array=True):
pc = np.unique(classes[partition])
assert len(pc) == 1
def test_clustered_subset_partition():
"""[Base] ClusteredSubsetIndex: test partition indexing on tuples."""
parts = list()
for part in ClusteredSubsetIndex(cl, X=X).partition():
parts.append(part)
assert parts == [[(0, 2)], [(2, 5)]]
def test_clustered_subset_tuple_shape():
"""[Base] ClusteredSubsetIndex: test the tuple shape on generation."""
tup = [(tri, tei)
for tri, tei in ClusteredSubsetIndex(cl, 2, 2).generate(X)]
assert tup == [([(0, 1)], [(1, 5)]), ([(1, 2)], [(0, 1), (2, 5)]),
([(2, 4)], [(0, 2), (4, 5)]), ([(4, 5)], [(0, 4)])]
def test_clustered_subset_partition_array():
"""[Base] ClusteredSubsetIndex: test partition indexing on arrays."""
parts = list()
for part in ClusteredSubsetIndex(cl, X=X).partition(as_array=True):
parts.append(part)
np.testing.assert_array_equal(parts[0], np.array([0, 1]))
np.testing.assert_array_equal(parts[1], np.array([2, 3, 4]))
def test_clustered_subset_array_shape():
"""[Base] ClusteredSubsetIndex: test the array shape on generation."""
t = list()
e = list()
for tri, tei in ClusteredSubsetIndex(cl,
2, 2, X=X).generate(as_array=True):
t.append(tri.tolist())
e.append(tei.tolist())
assert t == [[0], [1], [2, 3], [4]]
assert e == [[1, 2, 3, 4], [0, 2, 3, 4], [0, 1, 4], [0, 1, 2, 3]]