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from __future__ import division, print_function, absolute_import
import numpy as np
from numpy.testing import assert_array_almost_equal, run_module_suite, assert_
from scipy.sparse import csr_matrix
def _check_csr_rowslice(i, sl, X, Xcsr):
np_slice = X[i, sl]
csr_slice = Xcsr[i, sl]
assert_array_almost_equal(np_slice, csr_slice.toarray()[0])
assert_(type(csr_slice) is csr_matrix)
def test_csr_rowslice():
N = 10
np.random.seed(0)
X = np.random.random((N, N))
X[X > 0.7] = 0
Xcsr = csr_matrix(X)
slices = [slice(None, None, None),
slice(None, None, -1),
slice(1, -2, 2),
slice(-2, 1, -2)]
for i in range(N):
for sl in slices:
yield _check_csr_rowslice, i, sl, X, Xcsr
def test_csr_getrow():
N = 10
np.random.seed(0)
X = np.random.random((N, N))
X[X > 0.7] = 0
Xcsr = csr_matrix(X)
for i in range(N):
arr_row = X[i:i + 1, :]
csr_row = Xcsr.getrow(i)
assert_array_almost_equal(arr_row, csr_row.toarray())
assert_(type(csr_row) is csr_matrix)
def test_csr_getcol():
N = 10
np.random.seed(0)
X = np.random.random((N, N))
X[X > 0.7] = 0
Xcsr = csr_matrix(X)
for i in range(N):
arr_col = X[:, i:i + 1]
csr_col = Xcsr.getcol(i)
assert_array_almost_equal(arr_col, csr_col.toarray())
assert_(type(csr_col) is csr_matrix)
if __name__ == "__main__":
run_module_suite()
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