70 lines
2 KiB
Python
70 lines
2 KiB
Python
|
from __future__ import division, print_function, absolute_import
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
from numpy.testing import assert_array_almost_equal
|
||
|
|
from scipy.sparse import csr_matrix
|
||
|
|
from scipy.sparse.csgraph import csgraph_from_dense, csgraph_to_dense
|
||
|
|
|
||
|
|
|
||
|
|
def test_csgraph_from_dense():
|
||
|
|
np.random.seed(1234)
|
||
|
|
G = np.random.random((10, 10))
|
||
|
|
some_nulls = (G < 0.4)
|
||
|
|
all_nulls = (G < 0.8)
|
||
|
|
|
||
|
|
for null_value in [0, np.nan, np.inf]:
|
||
|
|
G[all_nulls] = null_value
|
||
|
|
olderr = np.seterr(invalid="ignore")
|
||
|
|
try:
|
||
|
|
G_csr = csgraph_from_dense(G, null_value=0)
|
||
|
|
finally:
|
||
|
|
np.seterr(**olderr)
|
||
|
|
|
||
|
|
G[all_nulls] = 0
|
||
|
|
assert_array_almost_equal(G, G_csr.toarray())
|
||
|
|
|
||
|
|
for null_value in [np.nan, np.inf]:
|
||
|
|
G[all_nulls] = 0
|
||
|
|
G[some_nulls] = null_value
|
||
|
|
olderr = np.seterr(invalid="ignore")
|
||
|
|
try:
|
||
|
|
G_csr = csgraph_from_dense(G, null_value=0)
|
||
|
|
finally:
|
||
|
|
np.seterr(**olderr)
|
||
|
|
|
||
|
|
G[all_nulls] = 0
|
||
|
|
assert_array_almost_equal(G, G_csr.toarray())
|
||
|
|
|
||
|
|
|
||
|
|
def test_csgraph_to_dense():
|
||
|
|
np.random.seed(1234)
|
||
|
|
G = np.random.random((10, 10))
|
||
|
|
nulls = (G < 0.8)
|
||
|
|
G[nulls] = np.inf
|
||
|
|
|
||
|
|
G_csr = csgraph_from_dense(G)
|
||
|
|
|
||
|
|
for null_value in [0, 10, -np.inf, np.inf]:
|
||
|
|
G[nulls] = null_value
|
||
|
|
assert_array_almost_equal(G, csgraph_to_dense(G_csr, null_value))
|
||
|
|
|
||
|
|
|
||
|
|
def test_multiple_edges():
|
||
|
|
# create a random sqare matrix with an even number of elements
|
||
|
|
np.random.seed(1234)
|
||
|
|
X = np.random.random((10, 10))
|
||
|
|
Xcsr = csr_matrix(X)
|
||
|
|
|
||
|
|
# now double-up every other column
|
||
|
|
Xcsr.indices[::2] = Xcsr.indices[1::2]
|
||
|
|
|
||
|
|
# normal sparse toarray() will sum the duplicated edges
|
||
|
|
Xdense = Xcsr.toarray()
|
||
|
|
assert_array_almost_equal(Xdense[:, 1::2],
|
||
|
|
X[:, ::2] + X[:, 1::2])
|
||
|
|
|
||
|
|
# csgraph_to_dense chooses the minimum of each duplicated edge
|
||
|
|
Xdense = csgraph_to_dense(Xcsr)
|
||
|
|
assert_array_almost_equal(Xdense[:, 1::2],
|
||
|
|
np.minimum(X[:, ::2], X[:, 1::2]))
|