def test_multilevel_recon_inverts_decomp(shape_setup, floating_dtype):
"""Test that reco is the inverse of decomp."""
wavelet, pywt_mode, nlevels, image_shape, coeff_shapes = shape_setup
image = np.random.uniform(size=image_shape).astype(floating_dtype)
wave_decomp = pywt_multi_level_decomp(image, wavelet, nlevels, pywt_mode)
wave_recon = pywt_multi_level_recon(wave_decomp, wavelet, pywt_mode,
image_shape)
assert wave_recon.shape == image.shape
assert all_almost_equal(wave_recon, image)
def test_multilevel_recon_inverts_decomp(shape_setup, floating_dtype):
"""Test that reco is the inverse of decomp."""
wavelet, pywt_mode, nlevels, image_shape, coeff_shapes = shape_setup
image = np.random.uniform(size=image_shape).astype(floating_dtype)
wave_decomp = pywt_multi_level_decomp(image, wavelet, nlevels, pywt_mode)
wave_recon = pywt_multi_level_recon(wave_decomp, wavelet, pywt_mode,
image_shape)
assert wave_recon.shape == image.shape
assert all_almost_equal(wave_recon, image)
def _call(self, coeffs):
"""Return the inverse wavelet transform of ``coeffs``."""
if self.impl == 'pywt':
shapes = pywt_coeff_shapes(self.range.shape, self.pywt_wavelet,
self.nlevels, self.pywt_pad_mode)
coeff_list = pywt_coeffs_from_flat_array(coeffs, shapes)
return pywt_multi_level_recon(
coeff_list, recon_shape=self.range.shape,
wavelet=self.pywt_wavelet, mode=self.pywt_pad_mode)
else:
raise RuntimeError("bad `impl` '{}'".format(self.impl))
def _call(self, coeffs):
"""Return the inverse wavelet transform of ``coeffs``."""
if self.impl == 'pywt':
shapes = pywt_coeff_shapes(self.range.shape, self.pywt_wavelet,
self.nlevels, self.pywt_pad_mode)
coeff_list = pywt_coeffs_from_flat_array(coeffs, shapes)
return pywt_multi_level_recon(
coeff_list, recon_shape=self.range.shape,
wavelet=self.pywt_wavelet, mode=self.pywt_pad_mode)
else:
raise RuntimeError("bad `impl` '{}'".format(self.impl))
def test_multilevel_decomp_inverts_recon(shape_setup):
"""Test that decomp is the inverse of recon."""
dtype = 'float64' # when fixed, use dtype fixture instead
wavelet, pywt_mode, nlevels, image_shape, coeff_shapes = shape_setup
if not ((ndim == 1 and wavelet == 'sym2' and pywt_mode == 'periodization')
or (ndim == 1 and wavelet == 'db1'
and pywt_mode in ('zero', 'periodization'))):
# The reverse invertibility is not given since the wavelet
# decomposition as implemented in PyWavelets, is not left-invertible.
# Only some setups work by miracle.
# TODO: investigate further
pytest.xfail('not left-invertible')
coeffs, _ = _grouped_and_flat_arrays(coeff_shapes, dtype)
wave_recon = pywt_multi_level_recon(coeffs,
wavelet,
pywt_mode,
recon_shape=image_shape)
wave_decomp = pywt_multi_level_decomp(wave_recon, wavelet, nlevels,
pywt_mode)
assert all_almost_equal(coeffs, wave_decomp)
def test_multilevel_decomp_inverts_recon(shape_setup):
"""Test that decomp is the inverse of recon."""
dtype = 'float64' # when fixed, use dtype fixture instead
wavelet, pywt_mode, nlevels, image_shape, coeff_shapes = shape_setup
if not ((ndim == 1 and
wavelet == 'sym2' and
pywt_mode == 'periodization') or
(ndim == 1 and
wavelet == 'db1' and
pywt_mode in ('zero', 'periodization'))):
# The reverse invertibility is not given since the wavelet
# decomposition as implemented in PyWavelets, is not left-invertible.
# Only some setups work by miracle.
# TODO: investigate further
pytest.xfail('not left-invertible')
coeffs, _ = _grouped_and_flat_arrays(coeff_shapes, dtype)
wave_recon = pywt_multi_level_recon(coeffs, wavelet, pywt_mode,
recon_shape=image_shape)
wave_decomp = pywt_multi_level_decomp(wave_recon, wavelet, nlevels,
pywt_mode)
assert all_almost_equal(coeffs, wave_decomp)
