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import loompy
import numpy as np
from typing import *
import scipy.sparse as sparse
def test_new() -> None:
with loompy.new("test.loom") as ds:
m = np.zeros((20, 100))
ra = {"Gene": [x for x in "ABCDEFGHILJKLMNOPQRS"]}
ca = {"Cell": np.arange(100)}
ds.add_columns(m, ca, row_attrs=ra)
ds.add_columns(m, ca, row_attrs=ra)
with loompy.connect("test.loom") as ds:
assert(ds.shape == (20, 200))
def test_sparse() -> None:
G = 1000
C = 100
S = sparse.eye(G, C)
loompy.create('test.loom', S, {'g_id': np.arange(G)}, {'c_id': np.arange(C)})
with loompy.connect("test.loom") as ds:
ds["layer"] = S
assert(np.all(ds[:, :] == S.toarray()))
assert(np.all(ds.sparse().data == S.tocoo().data))
assert(np.all(ds.layers["layer"][:, :] == S.toarray()))
assert(np.all(ds.layers["layer"].sparse().data == S.tocoo().data))
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