def _create_cflare(n_obs: int,
*,
backward: bool = False) -> Tuple[AnnData, CFLARE]:
adata = _create_dummy_adata(n_obs)
sc.tl.paga(adata, groups="clusters")
try:
vk = VelocityKernel(adata,
backward=backward).compute_transition_matrix()
ck = ConnectivityKernel(adata,
backward=backward).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.CFLARE(final_kernel)
mc.compute_partition()
mc.compute_eig()
mc.compute_metastable_states(use=2) # can fail for small #cells
mc.compute_lin_probs()
mc.compute_lineage_drivers(cluster_key="clusters", use_raw=False)
assert adata is mc.adata
if backward:
assert str(LinKey.BACKWARD) in adata.obsm
else:
assert str(LinKey.FORWARD) in adata.obsm
except:
mc = None
return adata, mc
def test_backward_manual_dense_norm(self, adata):
backward = True
vk = VelocityKernel(adata, backward=backward).compute_transition_matrix(
density_normalize=False
)
ck = ConnectivityKernel(adata, backward=backward).compute_transition_matrix(
density_normalize=False
)
# combine the kernels
comb = 0.8 * vk + 0.2 * ck
T_1 = comb.transition_matrix
conn = get_neighs(adata, "connectivities")
T_1 = density_normalization(T_1, conn)
T_1 = _normalize(T_1)
transition_matrix(
adata,
diff_kernel="sum",
weight_diffusion=0.2,
density_normalize=True,
backward=backward,
)
T_2 = adata.uns[_transition(Direction.BACKWARD)]["T"]
np.testing.assert_allclose(T_1.A, T_2.A, rtol=_rtol)
def test_inversion_propagation(self, adata):
c = ConnectivityKernel(adata, backward=False)
v = VelocityKernel(adata, backward=False)
k = ~(c + v)
assert c.backward
assert v.backward
assert k.backward
def test_initialized(self, adata):
k = (
VelocityKernel(adata).compute_transition_matrix()
+ ConnectivityKernel(adata).compute_transition_matrix()
)
k.compute_transition_matrix()
assert k.transition_matrix is not None
def test_constant_normalize_2(self, adata):
k = (9 * VelocityKernel(adata).compute_transition_matrix() +
1 * ConnectivityKernel(adata).compute_transition_matrix())
k.compute_transition_matrix()
c1, c2 = _is_bin_mult(k[0]), _is_bin_mult(k[1])
assert c1.transition_matrix == 9 / 10
assert c2.transition_matrix == 1 / 10
def create_kernels(
adata: AnnData,
var_key_connectivities: str = "connectivity_variances",
var_key_velocities: str = "velocity_variances",
) -> Tuple[VelocityKernel, ConnectivityKernel]:
vk = VelocityKernel(adata, var_key=var_key_velocities)
ck = ConnectivityKernel(adata, var_key=var_key_connectivities)
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_compute_schur_invalid_eig_sort(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.GPCCA(final_kernel)
with pytest.raises(ValueError):
mc.compute_schur(which="foobar", method="brandts")
def test_compute_lin_probs_no_arcs(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.CFLARE(final_kernel)
with pytest.raises(RuntimeError):
mc.compute_lin_probs()
def test_uninitialized_one(self, adata):
k = (
VelocityKernel(adata)
+ ConnectivityKernel(adata).compute_transition_matrix()
)
with pytest.raises(RuntimeError):
k.compute_transition_matrix()
def test_backward_negate_differ(self, adata):
backward = True
backward_mode = "negate"
vk = VelocityKernel(adata, backward=backward)
vk.compute_transition_matrix(density_normalize=True,
backward_mode=backward_mode)
T_1 = vk.transition_matrix
transition_matrix(
adata,
density_normalize=False,
backward=backward,
backward_mode=backward_mode,
)
T_2 = adata.uns["T_bwd"]["T"]
assert not np.allclose(T_1.A, T_2.A, rtol=_rtol)
def test_not_none_transition_matrix_accessor(self, adata):
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_compute_metastable_states_no_eig(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.GPCCA(final_kernel)
with pytest.raises(RuntimeError):
mc.compute_metastable_states(n_states=None)
def test_addition_3_kernels(self, adata):
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)
def test_parent(self, adata):
vk = VelocityKernel(adata)
ck = ConnectivityKernel(adata)
k = vk + ck
assert vk._parent._parent is k # invisible constants
assert ck._parent._parent is k
assert k._parent is None
def test_compute_approx_rcs_no_eig(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.MarkovChain(final_kernel)
with pytest.raises(RuntimeError):
mc.compute_approx_rcs(use=2)
def test_compute_schur_write_eigvals(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.GPCCA(final_kernel)
mc.compute_schur(n_components=10, method="brandts")
_check_eigdecomposition(mc)
def test_backward_negate_dense_norm(self, adata):
backward = True
dense_norm = True
backward_mode = "negate"
vk = VelocityKernel(adata, backward=backward)
vk.compute_transition_matrix(density_normalize=dense_norm,
backward_mode=backward_mode)
T_1 = vk.transition_matrix
transition_matrix(
adata,
density_normalize=dense_norm,
backward=backward,
backward_mode=backward_mode,
)
T_2 = adata.uns["T_bwd"]["T"]
np.testing.assert_allclose(T_1.A, T_2.A, rtol=_rtol)
def test_compute_gdpt_invalid_n_comps(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.GPCCA(final_kernel)
with pytest.raises(ValueError):
mc.compute_gdpt(n_components=1)
def test_compute_metastable_invalid_cluster_key(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.GPCCA(final_kernel)
mc.compute_schur(n_components=10, method="brandts")
with pytest.raises(KeyError):
mc.compute_metastable_states(n_states=2, cluster_key="foobar")
def test_constant_normalize_3(self, adata):
k = (VelocityKernel(adata).compute_transition_matrix() +
ConnectivityKernel(adata).compute_transition_matrix() +
ConnectivityKernel(adata).compute_transition_matrix())
k.compute_transition_matrix()
c1, c2, c3 = _is_bin_mult(k[0]), _is_bin_mult(k[1]), _is_bin_mult(k[2])
assert c1.transition_matrix == 1 / 3
assert c2.transition_matrix == 1 / 3
assert c3.transition_matrix == 1 / 3
def test_compute_gdpt_no_iroot(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.GPCCA(final_kernel)
mc.adata.uns.pop("iroot", None)
with pytest.raises(KeyError):
mc.compute_gdpt()
def test_compute_gdpt_no_schur(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.GPCCA(final_kernel)
mc.compute_gdpt(method="brandts")
assert "gdpt_pseudotime" in mc.adata.obs
def test_compute_metastable_states_schur(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.GPCCA(final_kernel)
mc.compute_schur(n_components=10, method="brandts")
mc.compute_metastable_states(n_states=2)
_check_compute_meta(mc)
def test_compute_metastable_none_states(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.GPCCA(final_kernel)
mc.compute_eig()
mc.compute_metastable_states(n_states=None)
_check_compute_meta(mc)
def test_comp_cond_num_or_policy(self, adata):
vk = VelocityKernel(adata,
compute_cond_num=True).compute_transition_matrix()
ck = ConnectivityKernel(
adata, compute_cond_num=False).compute_transition_matrix()
v = (vk + ck).compute_transition_matrix()
assert isinstance(vk.condition_number, float)
assert ck.condition_number is None
assert isinstance(v.condition_number, float)
def test_compute_lineage_drivers_no_lineages(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.CFLARE(final_kernel)
mc.compute_eig(k=5)
mc.compute_metastable_states(use=2)
with pytest.raises(RuntimeError):
mc.compute_lineage_drivers()
def test_compute_metastable_states_too_large_use(self,
adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.CFLARE(final_kernel)
mc.compute_eig(k=2)
with pytest.raises(ValueError):
mc.compute_metastable_states(use=1000)
def foo(self, adata):
vk = VelocityKernel(adata).compute_transition_matrix()
ck = ConnectivityKernel(adata).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc_fwd = cr.tl.MarkovChain(final_kernel)
mc_fwd.compute_lin_probs()
mc_fwd.compute_lineage_drivers(cluster_key="clusters", use_raw=False)
def test_compute_lineage_drivers_no_lineages(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.GPCCA(final_kernel)
mc.compute_schur(n_components=10, method="brandts")
mc.compute_metastable_states(n_states=2)
with pytest.raises(RuntimeError):
mc.compute_lineage_drivers()
def test_compute_gdpt_cellname_iroot(self, adata_large: AnnData):
vk = VelocityKernel(adata_large).compute_transition_matrix()
ck = ConnectivityKernel(adata_large).compute_transition_matrix()
final_kernel = 0.8 * vk + 0.2 * ck
mc = cr.tl.GPCCA(final_kernel)
mc.adata.uns["iroot"] = mc.adata.obs_names[0]
mc.compute_gdpt()
assert "gdpt_pseudotime" in mc.adata.obs