def test_run_mock_cells():
aname = 'Darmanis_2015_nofetal'
atlas = AtlasFetcher().fetch_atlas(aname, kind='average')
ind = [0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 4, 5]
matrix = atlas[ind]
cell_types = atlas.obs_names.values[ind]
sa = Averages(
aname,
n_pcs=10,
)
sa.fit(matrix)
assert ((cell_types == sa.membership).mean() > 0.9)
def test_embed_averages():
aname = 'Darmanis_2015_nofetal'
atlas = AtlasFetcher().fetch_atlas(aname, kind='subsample')
ind = [
0, 2, 5, 8, 10, 15, 20, 25, 28, 30, 35, 38, 40, 45, 50, 60, 70, 75, 80,
90
]
matrix = atlas[ind].copy()
sa = Averages(
aname,
n_features_per_cell_type=2,
n_features_overdispersed=5,
n_pcs=9,
)
sa.fit(matrix)
vs = sa.embed()
assert (vs.shape[1] == 4)
def test_run_within_atlas():
aname = 'Darmanis_2015_nofetal'
atlas = AtlasFetcher().fetch_atlas(aname, kind='subsample')
ind = [
0, 2, 5, 8, 10, 15, 20, 25, 28, 30, 35, 38, 40, 45, 50, 60, 70, 75, 80,
90
]
matrix = atlas[ind]
cell_types = atlas.obs['CellType'].values[ind]
sa = Averages(
aname,
n_features_per_cell_type=2,
n_features_overdispersed=5,
n_pcs=9,
)
sa.fit(matrix)
for i in range(len(cell_types)):
print('{:10s} {:10s}'.format(cell_types[i], sa.membership[i]))
print((cell_types == sa.membership).mean())
assert ((cell_types == sa.membership).mean() >= 0.5)