def test_fwt_iwt(self):
for n in range(5, 11):
input = np.zeros(n, dtype=np.float)
input[0] = 1
_, coeff_slices = wavelet.get_wavelet_shape([n])
npt.assert_allclose(
wavelet.iwt(wavelet.fwt(input), [n], coeff_slices), input)
def _apply(self, input):
device = backend.get_device(input)
with device:
return wavelet.fwt(input,
wave_name=self.wave_name,
axes=self.axes,
level=self.level)
def _apply(self, input):
return wavelet.fwt(input,
wave_name=self.wave_name,
axes=self.axes,
level=self.level)
def test_fwt(self):
n = 8
input = np.zeros(n, dtype=np.float)
input[0] = 1
npt.assert_allclose(wavelet.fwt(input, level=1, wave_name='haar'),
[1 / 2**0.5, 0, 0, 0, 1 / 2**0.5, 0, 0, 0])