def test_manual_combination_no_precomputed(self, adata):
density_normalize = False
vk = VelocityKernel(adata).compute_transition_matrix(
density_normalize=density_normalize
)
ck = ConnectivityKernel(adata).compute_transition_matrix(
density_normalize=density_normalize
)
T_vk = vk.transition_matrix
T_ck = ck.transition_matrix
T_comb_manual = 0.8 * T_vk + 0.2 * T_ck
vk = VelocityKernel(adata).compute_transition_matrix(
density_normalize=density_normalize
)
ck = ConnectivityKernel(adata).compute_transition_matrix(
density_normalize=density_normalize
)
comb_kernel = 0.8 * vk + 0.2 * ck
comb_kernel.compute_transition_matrix()
T_comb_kernel = comb_kernel.transition_matrix
np.testing.assert_allclose(T_comb_manual.A, T_comb_kernel.A, rtol=_rtol)
def test_adaptive_kernel_constants(self, adata):
k = (3 * ConnectivityKernel(adata).compute_transition_matrix()) ^ (
1 * ConnectivityKernel(adata).compute_transition_matrix()
)
k.compute_transition_matrix()
assert k[0][0]._value == 3 / 4
assert k[1][0]._value == 1 / 4
def test_constant_wrong_parentheses(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_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_inversion_preservation_of_constants(self, adata):
c = ConnectivityKernel(adata).compute_transition_matrix()
a = (3 * c + 1 * c).compute_transition_matrix()
b = ~a
c.compute_transition_matrix()
assert a[0][0].transition_matrix == 3 / 4
assert b[0][0].transition_matrix == 3 / 4
assert a[1][0].transition_matrix == 1 / 4
assert b[1][0].transition_matrix == 1 / 4
def test_adaptive_kernel_complex(self, adata):
k = (4 *
((3 * ConnectivityKernel(adata, var_key="connectivity_variances").
compute_transition_matrix()) ^
(1 * ConnectivityKernel(adata, var_key="connectivity_variances").
compute_transition_matrix())) +
2 * ConnectivityKernel(adata).compute_transition_matrix())
k.compute_transition_matrix()
assert k[0][0].transition_matrix == 4 / 6
assert k[1][0].transition_matrix == 2 / 6
assert k[0][1][0][0]._value == 3 / 4
assert k[0][1][1][0]._value == 1 / 4
def test_constant_correct_parentheses(self, adata):
k = 1 * VelocityKernel(adata).compute_transition_matrix() + 1 * (
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][1][0]),
_is_bin_mult(k[1][1][1]),
)
assert c1.transition_matrix == 1 / 2
assert c2.transition_matrix == 1 / 2
assert c3.transition_matrix == 1 / 2
def _create_gpcca(n_obs: int,
*,
backward: bool = False) -> Tuple[AnnData, CFLARE]:
adata = _create_dummy_adata(n_obs)
sc.tl.paga(adata, groups="clusters")
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.GPCCA(final_kernel)
mc.compute_partition()
mc.compute_eig()
mc.compute_schur(method="brandts")
mc.compute_metastable_states(n_states=2)
mc.set_main_states()
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
return adata, mc
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_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_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 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_uninitialized_one(self, adata):
k = (
VelocityKernel(adata)
+ ConnectivityKernel(adata).compute_transition_matrix()
)
with pytest.raises(RuntimeError):
k.compute_transition_matrix()