def test_numpy_dense_matrix(self):
m, g, t = _prepare_input(expression_data=df.to_numpy(),
gene_names=list(df.columns),
tf_names=tfs)
self.assertTrue(isinstance(m, np.ndarray))
self.assertEquals((500, 50), m.shape)
self.assertEquals(50, len(g))
self.assertEquals(4, len(t))
def test_DataFrame(self):
m, g, t = _prepare_input(expression_data=df,
gene_names=None,
tf_names=tfs)
self.assertTrue(isinstance(m, np.ndarray))
self.assertEquals((500, 50), m.shape)
self.assertEquals(50, len(g))
self.assertEquals(4, len(t))
def test_scipy_csc_matrix(self):
csc = csc_matrix(df.to_numpy())
m, g, t = _prepare_input(expression_data=csc,
gene_names=list(df.columns),
tf_names=tfs)
self.assertTrue(isinstance(m, csc_matrix))
self.assertEquals((500, 50), m.shape)
self.assertEquals(50, len(g))
self.assertEquals(4, len(t))
#cells = ds.ca[args.cell_id_attribute]
else:
ex_matrix = pd.DataFrame(data=ds[:, :],
index=ds.ra[args.gene_attribute],
columns=ds.ca[args.cell_id_attribute]).T
gene_names = pd.Series(ds.ra[args.gene_attribute])
end_time = time.time()
print(
f'Loaded expression matrix of {ex_matrix.shape[0]} cells and {ex_matrix.shape[1]} genes in {end_time - start_time} seconds...',
file=sys.stderr)
tf_names = load_tf_names(args.tfs_fname.name)
print(f'Loaded {len(tf_names)} TFs...', file=sys.stderr)
ex_matrix, gene_names, tf_names = _prepare_input(ex_matrix, gene_names,
tf_names)
tf_matrix, tf_matrix_gene_names = to_tf_matrix(ex_matrix, gene_names,
tf_names)
print(f'starting {args.method} using {args.num_workers} processes...',
file=sys.stderr)
start_time = time.time()
with Pool(args.num_workers) as p:
adjs = list(
tqdm.tqdm(p.imap(run_infer_partial_network,
target_gene_indices(gene_names,
target_genes='all'),
chunksize=1),
total=len(gene_names)))