def test_non_unique_names(self, adata: AnnData, path: Path, lin_key: str, _: int):
names_key = _lin_names(lin_key)
adata.uns[names_key][0] = adata.uns[names_key][1]
sc.write(path, adata)
with pytest.raises(ValueError):
_ = cr.read(path)
def test_no_lineage(self, adata: AnnData, path: Path, lin_key: str, _: int):
del adata.obsm[lin_key]
sc.write(path, adata)
adata_new = cr.read(path)
assert adata_new is not adata # sanity check
assert lin_key not in adata_new.obsm.keys()
def test_no_colors(self, adata: AnnData, path: Path, lin_key: str, n_lins: int):
colors_key = _colors(lin_key)
del adata.uns[colors_key]
sc.write(path, adata)
adata_new = cr.read(path)
lins = adata_new.obsm[lin_key]
assert isinstance(lins, Lineage)
np.testing.assert_array_equal(lins.colors, _create_categorical_colors(n_lins))
np.testing.assert_array_equal(lins.colors, adata_new.uns[colors_key])
def test_no_names(self, adata: AnnData, path: Path, lin_key: str,
n_lins: int):
names_key = _lin_names(lin_key)
del adata.uns[names_key]
sc.write(path, adata)
adata_new = cr.read(path)
lins = adata_new.obsm[lin_key]
assert isinstance(lins, Lineage)
np.testing.assert_array_equal(lins.names,
[f"Lineage {i}" for i in range(n_lins)])
np.testing.assert_array_equal(lins.names, adata_new.uns[names_key])
def test_normal_run(self, adata: AnnData, path: Path, lin_key: str, n_lins: int):
colors = _create_categorical_colors(10)[-n_lins:]
names = [f"foo {i}" for i in range(n_lins)]
adata.uns[_colors(lin_key)] = colors
adata.uns[_lin_names(lin_key)] = names
sc.write(path, adata)
adata_new = cr.read(path)
lins_new = adata_new.obsm[lin_key]
np.testing.assert_array_equal(lins_new.colors, colors)
np.testing.assert_array_equal(lins_new.names, names)
def test_wrong_names_length(self, adata: AnnData, path: Path, lin_key: str,
n_lins: int):
names_key = _lin_names(lin_key)
adata.uns[names_key] = list(adata.uns[names_key])
adata.uns[names_key] += ["foo", "bar", "baz"]
sc.write(path, adata)
adata_new = cr.read(path)
lins = adata_new.obsm[lin_key]
assert isinstance(lins, Lineage)
np.testing.assert_array_equal(lins.names,
[f"Lineage {i}" for i in range(n_lins)])
np.testing.assert_array_equal(lins.names, adata_new.uns[names_key])
n_jobs = 16
n_samples = 50_000
cr.logging.print_versions()
scv.settings.set_figure_params("scvelo",
dpi_save=400,
dpi=80,
transparent=True,
fontsize=20,
color_map="viridis")
if os.path.isfile(ROOT / "adata_preprocessed.h5ad") and os.path.isfile(
ROOT / "terminal_states.csv"):
print(f"Loading data from `{ROOT}`")
adata = cr.read(ROOT / "adata_preprocessed.h5ad")
terminal_states = pd.read_csv(ROOT / "terminal_states.csv",
index_col=0)["0"]
terminal_states = terminal_states.astype("category")
else:
print("Preprocessing")
adata = cr.datasets.pancreas(DATA_DIR / "pancreas" / "pancreas.h5ad")
scv.pp.filter_and_normalize(adata,
min_shared_counts=20,
n_top_genes=2000,
log=True)
sc.tl.pca(adata)
sc.pp.neighbors(adata, n_pcs=30, n_neighbors=30)
scv.pp.moments(adata, n_pcs=30, n_neighbors=30)
