def convolution_3d(picture: CachingDataStructure, kernel: np.ndarray,
cval: float = 0.0) -> CachingDataStructure:
"""Performs convolution for a 3D image. Pads borders with cval"""
assert picture.dim == 3
ret_data = picture.empty_of_same_shape()
kernel_dim = kernel.shape[0]
pad = kernel_dim // 2
for (x, y, z) in picture.iter_keys():
ret_data[x, y, z] = convolve_voxel(picture, kernel, kernel_dim,
pad, x, y, z, cval)
return ret_data
def bit_rev_inplace(arr: CachingDataStructure, axis: int) \
-> CachingDataStructure:
"""
Swaps the values along a given axis according to the reversed bit value
of that index
"""
N = arr.shape[0]
bitlen = int(np.log2(N))
for key in arr.iter_keys():
rev_bit_idx = rev_bit_str(key[axis], bitlen)
if key[axis] >= rev_bit_idx: # Make sure to only swap elements once
continue
new_key = tuple_gen(rev_bit_idx, key, axis)
arr[key], arr[new_key] = arr[new_key], arr[key]
return arr