def test_copy_palantir_kernel(self, adata: AnnData):
pk1 = PalantirKernel(adata).compute_transition_matrix()
pk2 = pk1.copy()
np.testing.assert_array_equal(pk1.transition_matrix.A,
pk2.transition_matrix.A)
assert pk1.params == pk2.params
assert pk1.backward == pk2.backward
def test_not_none_transition_matrix_accessor(self, adata: AnnData):
vk = VelocityKernel(adata)
ck = ConnectivityKernel(adata)
pk = PalantirKernel(adata, time_key="latent_time")
assert vk.transition_matrix is not None
assert ck.transition_matrix is not None
assert pk.transition_matrix is not None
def test_palantir_inverse(self, adata: AnnData):
pk = PalantirKernel(adata, time_key="latent_time")
pt = pk.pseudotime.copy()
pk_inv = ~pk
assert pk_inv is pk
assert pk_inv.backward
np.testing.assert_allclose(pt, 1 - pk_inv.pseudotime)
def test_not_none_transition_matrix_compute(self, adata: AnnData):
vk = VelocityKernel(adata).compute_transition_matrix(softmax_scale=4)
ck = ConnectivityKernel(adata).compute_transition_matrix()
pk = PalantirKernel(
adata, time_key="latent_time").compute_transition_matrix()
assert vk.transition_matrix is not None
assert ck.transition_matrix is not None
assert pk.transition_matrix is not None
def test_palantir(self, adata: AnnData):
conn = _get_neighs(adata, "connectivities")
n_neighbors = _get_neighs_params(adata)["n_neighbors"]
pseudotime = adata.obs["latent_time"]
conn_biased = bias_knn(conn, pseudotime, n_neighbors)
T_1 = _normalize(conn_biased)
pk = PalantirKernel(adata,
time_key="latent_time").compute_transition_matrix(
density_normalize=False)
T_2 = pk.transition_matrix
np.testing.assert_allclose(T_1.A, T_2.A, rtol=_rtol)