110 lines
3.2 KiB
Python
110 lines
3.2 KiB
Python
|
import os
|
||
|
|
import numpy as np
|
||
|
|
import tempfile
|
||
|
|
|
||
|
|
from pytest import raises as assert_raises
|
||
|
|
from numpy.testing import assert_equal, assert_
|
||
|
|
|
||
|
|
from scipy.sparse import (sparray, csc_matrix, csr_matrix, bsr_matrix, dia_matrix,
|
||
|
|
coo_matrix, dok_matrix, csr_array, save_npz, load_npz)
|
||
|
|
|
||
|
|
|
||
|
|
DATA_DIR = os.path.join(os.path.dirname(__file__), 'data')
|
||
|
|
|
||
|
|
|
||
|
|
def _save_and_load(matrix):
|
||
|
|
fd, tmpfile = tempfile.mkstemp(suffix='.npz')
|
||
|
|
os.close(fd)
|
||
|
|
try:
|
||
|
|
save_npz(tmpfile, matrix)
|
||
|
|
loaded_matrix = load_npz(tmpfile)
|
||
|
|
finally:
|
||
|
|
os.remove(tmpfile)
|
||
|
|
return loaded_matrix
|
||
|
|
|
||
|
|
def _check_save_and_load(dense_matrix):
|
||
|
|
for matrix_class in [csc_matrix, csr_matrix, bsr_matrix, dia_matrix, coo_matrix]:
|
||
|
|
matrix = matrix_class(dense_matrix)
|
||
|
|
loaded_matrix = _save_and_load(matrix)
|
||
|
|
assert_(type(loaded_matrix) is matrix_class)
|
||
|
|
assert_(loaded_matrix.shape == dense_matrix.shape)
|
||
|
|
assert_(loaded_matrix.dtype == dense_matrix.dtype)
|
||
|
|
assert_equal(loaded_matrix.toarray(), dense_matrix)
|
||
|
|
|
||
|
|
def test_save_and_load_random():
|
||
|
|
N = 10
|
||
|
|
np.random.seed(0)
|
||
|
|
dense_matrix = np.random.random((N, N))
|
||
|
|
dense_matrix[dense_matrix > 0.7] = 0
|
||
|
|
_check_save_and_load(dense_matrix)
|
||
|
|
|
||
|
|
def test_save_and_load_empty():
|
||
|
|
dense_matrix = np.zeros((4,6))
|
||
|
|
_check_save_and_load(dense_matrix)
|
||
|
|
|
||
|
|
def test_save_and_load_one_entry():
|
||
|
|
dense_matrix = np.zeros((4,6))
|
||
|
|
dense_matrix[1,2] = 1
|
||
|
|
_check_save_and_load(dense_matrix)
|
||
|
|
|
||
|
|
def test_sparray_vs_spmatrix():
|
||
|
|
#save/load matrix
|
||
|
|
fd, tmpfile = tempfile.mkstemp(suffix='.npz')
|
||
|
|
os.close(fd)
|
||
|
|
try:
|
||
|
|
save_npz(tmpfile, csr_matrix([[1.2, 0, 0.9], [0, 0.3, 0]]))
|
||
|
|
loaded_matrix = load_npz(tmpfile)
|
||
|
|
finally:
|
||
|
|
os.remove(tmpfile)
|
||
|
|
|
||
|
|
#save/load array
|
||
|
|
fd, tmpfile = tempfile.mkstemp(suffix='.npz')
|
||
|
|
os.close(fd)
|
||
|
|
try:
|
||
|
|
save_npz(tmpfile, csr_array([[1.2, 0, 0.9], [0, 0.3, 0]]))
|
||
|
|
loaded_array = load_npz(tmpfile)
|
||
|
|
finally:
|
||
|
|
os.remove(tmpfile)
|
||
|
|
|
||
|
|
assert not isinstance(loaded_matrix, sparray)
|
||
|
|
assert isinstance(loaded_array, sparray)
|
||
|
|
assert_(loaded_matrix.dtype == loaded_array.dtype)
|
||
|
|
assert_equal(loaded_matrix.toarray(), loaded_array.toarray())
|
||
|
|
|
||
|
|
def test_malicious_load():
|
||
|
|
class Executor:
|
||
|
|
def __reduce__(self):
|
||
|
|
return (assert_, (False, 'unexpected code execution'))
|
||
|
|
|
||
|
|
fd, tmpfile = tempfile.mkstemp(suffix='.npz')
|
||
|
|
os.close(fd)
|
||
|
|
try:
|
||
|
|
np.savez(tmpfile, format=Executor())
|
||
|
|
|
||
|
|
# Should raise a ValueError, not execute code
|
||
|
|
assert_raises(ValueError, load_npz, tmpfile)
|
||
|
|
finally:
|
||
|
|
os.remove(tmpfile)
|
||
|
|
|
||
|
|
|
||
|
|
def test_py23_compatibility():
|
||
|
|
# Try loading files saved on Python 2 and Python 3. They are not
|
||
|
|
# the same, since files saved with SciPy versions < 1.0.0 may
|
||
|
|
# contain unicode.
|
||
|
|
|
||
|
|
a = load_npz(os.path.join(DATA_DIR, 'csc_py2.npz'))
|
||
|
|
b = load_npz(os.path.join(DATA_DIR, 'csc_py3.npz'))
|
||
|
|
c = csc_matrix([[0]])
|
||
|
|
|
||
|
|
assert_equal(a.toarray(), c.toarray())
|
||
|
|
assert_equal(b.toarray(), c.toarray())
|
||
|
|
|
||
|
|
def test_implemented_error():
|
||
|
|
# Attempts to save an unsupported type and checks that an
|
||
|
|
# NotImplementedError is raised.
|
||
|
|
|
||
|
|
x = dok_matrix((2,3))
|
||
|
|
x[0,1] = 1
|
||
|
|
|
||
|
|
assert_raises(NotImplementedError, save_npz, 'x.npz', x)
|