def test_pipeline():
adata = scv.datasets.simulation(random_seed=0, n_vars=10)
scv.pp.filter_and_normalize(adata)
scv.pp.moments(adata)
scv.tl.recover_dynamics(adata)
scv.tl.velocity(adata)
adata.var.velocity_genes = True
scv.tl.velocity_graph(adata)
scv.tl.velocity_embedding(adata)
scv.tl.velocity_confidence(adata)
scv.tl.latent_time(adata)
with scv.GridSpec() as pl:
pl.velocity_graph(adata)
pl.velocity_embedding(adata,
arrow_length=3,
arrow_size=3,
c='latent_time')
pl.velocity_embedding_grid(adata,
scale=.5,
density=.5,
c='latent_time',
cmap='gnuplot')
pl.velocity_embedding_stream(adata,
c=adata.var_names[0],
layer='velocity')
pl.scatter(adata, basis=adata.var_names[0], c='velocity', use_raw=True)
pl.hist(
[adata.obs.initial_size_spliced, adata.obs.initial_size_unspliced])
def test_pipeline():
adata = scv.datasets.simulation(random_seed=0, n_vars=10)
scv.pp.filter_and_normalize(adata, n_top_genes=5)
scv.pp.pca(adata)
scv.pp.moments(adata)
scv.tl.recover_dynamics(adata)
scv.tl.velocity(adata)
scv.tl.velocity(adata, vkey="dynamical_velocity", mode="dynamical")
adata.var.velocity_genes = True
scv.tl.velocity_graph(adata)
scv.tl.velocity_embedding(adata)
scv.tl.velocity_confidence(adata)
scv.tl.latent_time(adata)
with scv.GridSpec() as pl:
pl.velocity_graph(adata)
pl.velocity_embedding(adata,
arrow_length=3,
arrow_size=3,
c="latent_time")
pl.velocity_embedding_grid(adata,
scale=0.5,
c="latent_time",
cmap="gnuplot")
pl.velocity_embedding_stream(adata,
c=adata.var_names[0],
layer="velocity")
pl.scatter(adata, basis=adata.var_names[0], c="velocity", use_raw=True)
pl.hist(
[adata.obs.initial_size_spliced, adata.obs.initial_size_unspliced])
Ms, Mu = adata.layers["Ms"][0], adata.layers["Mu"][0]
Vs, Vd = adata.layers["velocity"][0], adata.layers["dynamical_velocity"][0]
Vpca, Vgraph = adata.obsm["velocity_pca"][0], adata.uns[
"velocity_graph"].data[:5]
pars = adata[:, 0].var[["fit_alpha", "fit_gamma"]].values
assert np.allclose(Ms, [0.8269, 1.0772, 0.9396, 1.0846, 1.0398], rtol=1e-2)
assert np.allclose(Mu, [3.8412, 3.1976, 3.5523, 3.3433, 3.8006], rtol=1e-2)
assert np.allclose(adata.X[0], [0.0, 0.0, 0.0, 0.4981, 0.0], rtol=1e-2)
# assert np.allclose(Vpca, [0.0163, 0.0185, 0.0472, 0.0025], rtol=1e-2)
assert np.allclose(Vd, [1.7582, 2.0214, 1.73, 0.6615, 1.5118], rtol=1e-2)
assert np.allclose(Vs, [3.2961, 2.5254, 2.9926, 2.634, 3.1352], rtol=1e-2)
assert np.allclose(Vgraph, [0.915, 0.5997, 0.8494, 0.1615, 0.7708],
rtol=1e-2)
assert np.allclose(pars, [4.9257, 0.3239], rtol=1e-2)