def test_build_sparse_knn_kernel_to_data():
G = build_graph(data, decay=None, sparse=True)
n = G.data.shape[0]
K = G.build_kernel_to_data(data[:n // 2, :])
assert(K.shape == (n // 2, n))
K = G.build_kernel_to_data(G.data)
assert(np.sum(G.kernel != (K + K.T) / 2) == 0)
K = G.build_kernel_to_data(G.data_nu)
assert(np.sum(G.kernel != (K + K.T) / 2) == 0)
def test_build_sparse_exact_kernel_to_data(**kwargs):
G = build_graph(data, decay=10, thresh=0, sparse=True)
n = G.data.shape[0]
K = G.build_kernel_to_data(data[:n // 2, :])
assert (K.shape == (n // 2, n))
K = G.build_kernel_to_data(G.data)
assert (np.sum(G.kernel != (K + K.T) / 2) == 0)
K = G.build_kernel_to_data(G.data_nu)
assert (np.sum(G.kernel != (K + K.T) / 2) == 0)
def test_inverse_transform_sparse_no_pca():
G = build_graph(data, sparse=True, n_pca=None)
assert np.sum(G.data != G.inverse_transform(G.data_nu)) == 0
with assert_raises_message(
ValueError,
"data of shape ({0}, 1) cannot be inverse transformed from graph built on reduced data of shape ({0}, {1})".format(
G.data.shape[0], G.data.shape[1]
),
):
G.inverse_transform(sp.csr_matrix(G.data)[:, 0])
with assert_raises_message(
ValueError,
"data of shape ({0}, 15) cannot be inverse transformed from graph built on reduced data of shape ({0}, {1})".format(
G.data.shape[0], G.data.shape[1]
),
):
G.inverse_transform(sp.csr_matrix(G.data)[:, :15])
def test_transform_sparse_no_pca():
G = build_graph(data, sparse=True, n_pca=None)
assert np.sum(G.data_nu != G.transform(G.data)) == 0
with assert_raises_message(
ValueError,
"data of shape {} cannot be transformed to graph built on data of shape {}".format(
G.data.tocsr()[:, 0].shape, G.data.shape
),
):
G.transform(sp.csr_matrix(G.data)[:, 0])
with assert_raises_message(
ValueError,
"data of shape {} cannot be transformed to graph built on data of shape {}".format(
G.data.tocsr()[:, :15].shape, G.data.shape
),
):
G.transform(sp.csr_matrix(G.data)[:, :15])
def test_inverse_transform_sparse_no_pca():
G = build_graph(data, sparse=True, n_pca=None)
assert np.sum(G.data != G.inverse_transform(G.data_nu)) == 0
assert_raises(ValueError, G.inverse_transform, sp.csr_matrix(G.data)[:, 0])
assert_raises(ValueError, G.inverse_transform,
sp.csr_matrix(G.data)[:, :15])