def create_kernels(
adata: AnnData,
velocity_variances: Optional[str] = None,
connectivity_variances: Optional[str] = None,
) -> Tuple[VelocityKernel, ConnectivityKernel]:
vk = VelocityKernel(adata)
vk._mat_scaler = adata.uns.get(
velocity_variances, np.random.normal(size=(adata.n_obs, adata.n_obs))
)
ck = ConnectivityKernel(adata)
ck._mat_scaler = adata.uns.get(
connectivity_variances, np.random.normal(size=(adata.n_obs, adata.n_obs))
)
vk._transition_matrix = csr_matrix(np.eye(adata.n_obs))
ck._transition_matrix = np.eye(adata.n_obs, k=1) / 2 + np.eye(adata.n_obs) / 2
ck._transition_matrix[-1, -1] = 1
ck._transition_matrix = csr_matrix(ck._transition_matrix)
np.testing.assert_allclose(
np.sum(ck._transition_matrix.A, axis=1), 1
) # sanity check
return vk, ck
def test_addition_3_kernels(self, adata: AnnData):
vk, ck = create_kernels(adata) # diagonal + upper diag
vk1 = VelocityKernel(adata)
vk1._transition_matrix = np.eye(adata.n_obs, k=-1) / 2 + np.eye(
adata.n_obs) / 2
vk1._transition_matrix[0, 0] = 1
np.testing.assert_allclose(np.sum(ck._transition_matrix, axis=1),
1) # sanity check
k = (vk + ck + vk1).compute_transition_matrix()
expected = (np.eye(adata.n_obs) * (1 / 3 + 1 / 6 + 1 / 6) +
np.eye(adata._n_obs, k=1) * 1 / 6 +
np.eye(adata.n_obs, k=-1) * 1 / 6)
expected[0, 0] = expected[-1, -1] = 2 / 3 + 1 / 3 * 0.5
expected[0, 1] = expected[-1, -2] = 1 - expected[0, 0]
np.testing.assert_allclose(k.transition_matrix.A, expected)
