def test_integer_perfect_recon():
# Check that an integer input is correctly coerced into a floating point
# array and reconstructed
A = np.array([[1,2,3,4], [5,6,7,8]], dtype=np.int32)
Yl, Yh = dtwavexfm2(A)
B = dtwaveifm2(Yl, Yh)
assert np.max(np.abs(A-B)) < 1e-5
def test_integer_perfect_recon():
# Check that an integer input is correctly coerced into a floating point
# array and reconstructed
A = np.array([[1,2,3,4], [5,6,7,8]], dtype=np.int32)
Yl, Yh = dtwavexfm2(A)
B = dtwaveifm2(Yl, Yh)
assert np.max(np.abs(A-B)) < 1e-5
def test_float32_input():
# Check that an float32 input is correctly output as float32
Yl, Yh = dtwavexfm2(mandrill.astype(np.float32))
assert np.issubsctype(Yl.dtype, np.float32)
assert np.all(list(np.issubsctype(x.dtype, np.complex64) for x in Yh))
mandrill_recon = dtwaveifm2(Yl, Yh)
assert np.issubsctype(mandrill_recon.dtype, np.float32)
def test_float32_input():
# Check that an float32 input is correctly output as float32
Yl, Yh = dtwavexfm2(lena.astype(np.float32))
assert np.issubsctype(Yl.dtype, np.float32)
assert np.all(list(np.issubsctype(x.dtype, np.complex64) for x in Yh))
lena_recon = dtwaveifm2(Yl, Yh)
assert np.issubsctype(lena_recon.dtype, np.float32)
def test_dtwavexfm2():
Yl, Yh, Yscale = dtwavexfm2(mandrill, 4, 'near_sym_a', 'qshift_a', include_scale=True)
assert_almost_equal_to_summary(Yl, verif['mandrill_Yl'], tolerance=TOLERANCE)
for idx, a in enumerate(Yh):
assert_almost_equal_to_summary(a, verif['mandrill_Yh_{0}'.format(idx)], tolerance=TOLERANCE)
for idx, a in enumerate(Yscale):
assert_almost_equal_to_summary(a, verif['mandrill_Yscale_{0}'.format(idx)], tolerance=TOLERANCE)
def test_dtwavexfm2():
Yl, Yh, Yscale = dtwavexfm2(mandrill,
4,
'near_sym_a',
'qshift_a',
include_scale=True)
assert_almost_equal_to_summary(Yl,
verif['mandrill_Yl'],
tolerance=TOLERANCE)
for idx, a in enumerate(Yh):
assert_almost_equal_to_summary(a,
verif['mandrill_Yh_{0}'.format(idx)],
tolerance=TOLERANCE)
for idx, a in enumerate(Yscale):
assert_almost_equal_to_summary(
a, verif['mandrill_Yscale_{0}'.format(idx)], tolerance=TOLERANCE)
def test_odd_rows_and_cols_w_scale():
Yl, Yh, Yscale = dtwavexfm2(mandrill[:509,:509], include_scale=True)
def test_odd_rows():
Yl, Yh = dtwavexfm2(mandrill[:509,:])
def test_3d():
with raises(ValueError):
Yl, Yh = dtwavexfm2(np.dstack((mandrill, mandrill)))
def test_specific_wavelet():
Yl, Yh = dtwavexfm2(mandrill, biort=biort('antonini'), qshift=qshift('qshift_06'))
def test_1d():
Yl, Yh = dtwavexfm2(mandrill[0, :])
def test_0_levels_w_scale():
Yl, Yh, Yscale = dtwavexfm2(lena, nlevels=0, include_scale=True)
assert np.all(np.abs(Yl - lena) < TOLERANCE)
assert len(Yh) == 0
assert len(Yscale) == 0
def test_odd_rows_and_cols():
Yl, Yh = dtwavexfm2(mandrill[:, :509])
def test_reconstruct_custom_filter():
# Reconstruction up to tolerance
Yl, Yh = dtwavexfm2(lena, 4, biort('legall'), qshift('qshift_06'))
lena_recon = dtwaveifm2(Yl, Yh, biort('legall'), qshift('qshift_06'))
assert np.all(np.abs(lena_recon - lena) < TOLERANCE)
def test_reconstruct_crop():
# Reconstruction up to tolerance
Yl_crop, Yh_crop = dtwavexfm2(lena_crop)
lena_recon = dtwaveifm2(Yl_crop, Yh_crop)[:lena_crop.shape[0], :lena_crop.shape[1]]
assert np.all(np.abs(lena_recon - lena_crop) < TOLERANCE)
def test_reconstruct():
# Reconstruction up to tolerance
Yl, Yh = dtwavexfm2(lena)
lena_recon = dtwaveifm2(Yl, Yh)
assert np.all(np.abs(lena_recon - lena) < TOLERANCE)
def test_reconstruct_custom_filter():
# Reconstruction up to tolerance
Yl, Yh = dtwavexfm2(mandrill, 4, biort("legall"), qshift("qshift_06"))
mandrill_recon = dtwaveifm2(Yl, Yh, biort("legall"), qshift("qshift_06"))
assert np.all(np.abs(mandrill_recon - mandrill) < TOLERANCE)
def test_reconstruct_crop():
# Reconstruction up to tolerance
Yl_crop, Yh_crop = dtwavexfm2(mandrill_crop)
mandrill_recon = dtwaveifm2(Yl_crop, Yh_crop)[: mandrill_crop.shape[0], : mandrill_crop.shape[1]]
assert np.all(np.abs(mandrill_recon - mandrill_crop) < TOLERANCE)
def test_reconstruct():
# Reconstruction up to tolerance
Yl, Yh = dtwavexfm2(mandrill)
mandrill_recon = dtwaveifm2(Yl, Yh)
assert np.all(np.abs(mandrill_recon - mandrill) < TOLERANCE)
def test_0_levels():
Yl, Yh = dtwavexfm2(mandrill, nlevels=0)
assert np.all(np.abs(Yl - mandrill) < TOLERANCE)
assert len(Yh) == 0
def test_0_levels():
Yl, Yh = dtwavexfm2(mandrill, nlevels=0)
assert np.all(np.abs(Yl - mandrill) < TOLERANCE)
assert len(Yh) == 0
def test_integer_input():
# Check that an integer input is correctly coerced into a floating point
# array
Yl, Yh = dtwavexfm2([[1,2,3,4], [1,2,3,4]])
assert np.any(Yl != 0)
def test_odd_rows():
Yl, Yh = dtwavexfm2(mandrill[:509, :])
def test_0_levels():
Yl, Yh = dtwavexfm2(lena, nlevels=0)
assert np.all(np.abs(Yl - lena) < TOLERANCE)
assert len(Yh) == 0
def test_simple():
Yl, Yh = dtwavexfm2(lena)
def test_integer_input():
# Check that an integer input is correctly coerced into a floating point
# array
Yl, Yh = dtwavexfm2([[1,2,3,4], [1,2,3,4]])
assert np.any(Yl != 0)
def test_specific_wavelet():
Yl, Yh = dtwavexfm2(lena, biort=biort('antonini'), qshift=qshift('qshift_06'))
def test_simple():
Yl, Yh = dtwavexfm2(mandrill)
def test_1d():
Yl, Yh = dtwavexfm2(lena[0,:])
def test_1d():
Yl, Yh = dtwavexfm2(mandrill[0,:])
def test_3d():
Yl, Yh = dtwavexfm2(np.dstack((lena, lena)))
def test_simple_w_scale():
Yl, Yh, Yscale = dtwavexfm2(mandrill, include_scale=True)
assert len(Yscale) > 0
for x in Yscale:
assert x is not None
def test_simple_w_scale():
Yl, Yh, Yscale = dtwavexfm2(lena, include_scale=True)
assert len(Yscale) > 0
for x in Yscale:
assert x is not None
def test_odd_rows_and_cols():
Yl, Yh = dtwavexfm2(mandrill[:,:509])
def test_reconstruct_crop():
# Reconstruction up to tolerance
Yl_crop, Yh_crop = dtwavexfm2(mandrill_crop)
mandrill_recon = dtwaveifm2(
Yl_crop, Yh_crop)[:mandrill_crop.shape[0], :mandrill_crop.shape[1]]
assert np.all(np.abs(mandrill_recon - mandrill_crop) < TOLERANCE)
def test_rot_symm_modified():
# This test only checks there is no error running these functions, not that they work
Yl, Yh, Yscale = dtwavexfm2(mandrill, biort='near_sym_b_bp', qshift='qshift_b_bp', include_scale=True)
Z = dtwaveifm2(Yl, Yh, biort='near_sym_b_bp', qshift='qshift_b_bp')
def test_3d():
with raises(ValueError):
Yl, Yh = dtwavexfm2(np.dstack((mandrill, mandrill)))
def test_0_levels_w_scale():
Yl, Yh, Yscale = dtwavexfm2(mandrill, nlevels=0, include_scale=True)
assert np.all(np.abs(Yl - mandrill) < TOLERANCE)
assert len(Yh) == 0
assert len(Yscale) == 0
def test_specific_wavelet():
Yl, Yh = dtwavexfm2(mandrill, biort=biort("antonini"), qshift=qshift("qshift_06"))
def test_odd_rows():
Yl, Yh = dtwavexfm2(lena[:509,:])
def test_odd_cols_w_scale():
Yl, Yh, Yscale = dtwavexfm2(mandrill[:509, :509], include_scale=True)
def test_reconstruct():
# Reconstruction up to tolerance
Yl, Yh = dtwavexfm2(mandrill)
mandrill_recon = dtwaveifm2(Yl, Yh)
assert np.all(np.abs(mandrill_recon - mandrill) < TOLERANCE)
def test_odd_rows_and_cols():
Yl, Yh = dtwavexfm2(lena[:,:509])
def test_reconstruct_custom_filter():
# Reconstruction up to tolerance
Yl, Yh = dtwavexfm2(mandrill, 4, biort('legall'), qshift('qshift_06'))
mandrill_recon = dtwaveifm2(Yl, Yh, biort('legall'), qshift('qshift_06'))
assert np.all(np.abs(mandrill_recon - mandrill) < TOLERANCE)
def test_odd_rows_and_cols_w_scale():
Yl, Yh, Yscale = dtwavexfm2(lena[:509,:509], include_scale=True)
def test_rot_symm_modified():
# This test only checks there is no error running these functions, not that they work
Yl, Yh, Yscale = dtwavexfm2(lena, biort='near_sym_b_bp', qshift='qshift_b_bp', include_scale=True)
Z = dtwaveifm2(Yl, Yh, biort='near_sym_b_bp', qshift='qshift_b_bp')
def test_simple():
Yl, Yh = dtwavexfm2(mandrill)