def test_cube2array2cube():
cube = np.zeros((2, 10, 10))
ns, nx, ny = np.shape(cube)
assert nx == ny # condition required
nxy = nx * ny
cube[1, 2, 2] = 1
array = util.cube2array(cube)
cube_new = util.array2cube(array, ns, nxy)
assert cube_new[1, 2, 2] == cube[1, 2, 2]
def decomposition(self, image, n_scales):
"""
1D starlet transform from starlet coefficients stored in coeffs
:param image: 2D image to be decomposed, ndarray with shape (sqrt(n_pixels), sqrt(n_pixels))
:param n_scales: number of decomposition scales
:return: reconstructed signal as 1D array of shape (n_scales*n_pixels,)
"""
if len(image.shape) == 1:
image_2d = util.array2image(image)
elif len(image.shape) == 2:
image_2d = image
else:
raise ValueError("image has not the right shape (1D or 2D arrays are supported for starlets decomposition)")
return util.cube2array(self.decomposition_2d(image_2d, n_scales))
def test_cube2array():
sube = np.zeros((2, 10, 10))
sube[1, 2, 2] = 1
array = util.cube2array(sube)
assert array[122] == 1