def test_symmetric_tools_symmetric():
rnd = np.random.RandomState(0)
# generate random symmetric matrix
for size in [4, 6, 11]:
x = rnd.normal(size=(size, size))
x = x + x.T
compressed = compress_sym(x, make_symmetric=False)
assert_equal(compressed.shape, (size * (size + 1) / 2, ))
uncompressed = expand_sym(compressed)
assert_array_equal(x, uncompressed)
def test_symmetric_tools_symmetric():
rnd = np.random.RandomState(0)
# generate random symmetric matrix
for size in [4, 6, 11]:
x = rnd.normal(size=(size, size))
x = x + x.T
compressed = compress_sym(x, make_symmetric=False)
assert_equal(compressed.shape, (size * (size + 1) / 2, ))
uncompressed = expand_sym(compressed)
assert_array_equal(x, uncompressed)
def test_symmetric_tools_upper():
rnd = np.random.RandomState(0)
# generate random matrix with only upper triangle.
# expected result is full symmetric matrix
for size in [4, 6, 11]:
x = rnd.normal(size=(size, size))
x = x + x.T
x_ = x.copy()
x[np.tri(size, k=-1, dtype=np.bool)] = 0
compressed = compress_sym(x, make_symmetric=True)
assert_equal(compressed.shape, (size * (size + 1) / 2, ))
uncompressed = expand_sym(compressed)
assert_array_equal(x_, uncompressed)
def test_symmetric_tools_upper():
rnd = np.random.RandomState(0)
# generate random matrix with only upper triangle.
# expected result is full symmetric matrix
for size in [4, 6, 11]:
x = rnd.normal(size=(size, size))
x = x + x.T
x_ = x.copy()
x[np.tri(size, k=-1, dtype=np.bool)] = 0
compressed = compress_sym(x, make_symmetric=True)
assert_equal(compressed.shape, (size * (size + 1) / 2, ))
uncompressed = expand_sym(compressed)
assert_array_equal(x_, uncompressed)
