Interpretation of query
# precomputed permutation: perm is array of shape (6,n,n,2) giving source coords for each target def apply_move(cube_facelets, perm): src = cube_facelets[perm[...,0], perm[...,1], perm[...,2]] # vectorized gather return src.reshape(cube_facelets.shape) nxnxn rubik 39-s-cube algorithm github python
(Implement with careful indexing or flattened linear indices for speed.) Interpretation of query # precomputed permutation: perm is
def apply_algorithm(self, moves): for move in moves: # parse move like "U", "U'", "2U" (for wide moves), "3R" self.execute_move(move) perm): src = cube_facelets[perm[...
import numpy as np