def scales(self):
"""Get the scales of each coefficient.
Returns
-------
scales : ``range`` element
The scale of each coefficient, given by an integer. 0 for the
lowest resolution and self.nlevels for the highest.
"""
if self.impl == 'pywt':
if self.__variant == 'forward':
discr_space = self.domain
wavelet_space = self.range
else:
discr_space = self.range
wavelet_space = self.domain
shapes = pywt_coeff_shapes(discr_space.shape, self.pywt_wavelet,
self.nlevels, self.pywt_pad_mode)
coeff_list = [np.ones(shapes[0]) * 0]
dcoeffs_per_scale = 2**discr_space.ndim - 1
for i in range(1, 1 + len(shapes[1:])):
coeff_list.append(
(np.ones(shapes[i]) * i, ) * dcoeffs_per_scale)
coeffs = pywt_flat_array_from_coeffs(coeff_list)
return wavelet_space.element(coeffs)
else:
raise RuntimeError("bad `impl` '{}'".format(self.impl))
def scales(self):
"""Get the scales of each coefficient.
Returns
-------
scales : ``range`` element
The scale of each coefficient, given by an integer. 0 for the
lowest resolution and self.nlevels for the highest.
"""
if self.impl == 'pywt':
if self.__variant == 'forward':
discr_space = self.domain
wavelet_space = self.range
else:
discr_space = self.range
wavelet_space = self.domain
shapes = pywt_coeff_shapes(discr_space.shape, self.pywt_wavelet,
self.nlevels, self.pywt_pad_mode)
coeff_list = [np.ones(shapes[0]) * 0]
dcoeffs_per_scale = 2 ** discr_space.ndim - 1
for i in range(1, 1 + len(shapes[1:])):
coeff_list.append(
(np.ones(shapes[i]) * i,) * dcoeffs_per_scale)
coeffs = pywt_flat_array_from_coeffs(coeff_list)
return wavelet_space.element(coeffs)
else:
raise RuntimeError("bad `impl` '{}'".format(self.impl))
def _call(self, x):
"""Return wavelet transform of ``x``."""
if self.impl == 'pywt':
coeff_list = pywt_multi_level_decomp(
x, wavelet=self.pywt_wavelet, nlevels=self.nlevels,
mode=self.pywt_pad_mode)
return pywt_flat_array_from_coeffs(coeff_list)
else:
raise RuntimeError("bad `impl` '{}'".format(self.impl))
def _call(self, x):
"""Return wavelet transform of ``x``."""
if self.impl == 'pywt':
coeff_list = pywt_multi_level_decomp(
x, wavelet=self.pywt_wavelet, nlevels=self.nlevels,
mode=self.pywt_pad_mode)
return pywt_flat_array_from_coeffs(coeff_list)
else:
raise RuntimeError("bad `impl` '{}'".format(self.impl))
def test_pywt_coeff_list_conversion(small_shapes, floating_dtype):
"""Test if converstion flat array <-> coefficient list works."""
ndim, shapes = small_shapes
grouped_list, flat_list = _grouped_and_flat_arrays(shapes, dtype=float)
true_flat_array = np.hstack(flat_list)
flat_array = pywt_flat_array_from_coeffs(grouped_list)
assert all_equal(flat_array, true_flat_array)
coeff_list = pywt_coeffs_from_flat_array(flat_array, shapes)
true_coeff_list = grouped_list
assert all_equal(coeff_list, true_coeff_list)
def test_pywt_coeff_list_conversion(small_shapes, floating_dtype):
"""Test if converstion flat array <-> coefficient list works."""
ndim, shapes = small_shapes
grouped_list, flat_list = _grouped_and_flat_arrays(shapes, dtype=float)
true_flat_array = np.hstack(flat_list)
flat_array = pywt_flat_array_from_coeffs(grouped_list)
assert all_equal(flat_array, true_flat_array)
coeff_list = pywt_coeffs_from_flat_array(flat_array, shapes)
true_coeff_list = grouped_list
assert all_equal(coeff_list, true_coeff_list)
