grid of colored stickers. We can represent the entire cube state using a 3D NumPy array or a dictionary of 2D matrices:
Execute an orientation flip sequence on the target slot: R U R' F R' F' R .
pip install kociemba
A move can be defined as a tuple: (face, layer_index, direction) . 2. Python Data Structure Implementation
def rotate_f_layer(self, layer_idx): if layer_idx == 0: self.faces['F'] = np.rot90(self.faces['F'], -1) elif layer_idx == self.n - 1: self.faces['B'] = np.rot90(self.faces['B'], 1) # Temporal storage of the shifting rows/columns n = self.n idx = layer_idx # Save top adjacent row (from U face) temp = self.faces['U'][n - 1 - idx, :].copy() # Left (L) column moves to Top (U) row self.faces['U'][n - 1 - idx, :] = np.flip(self.faces['L'][:, n - 1 - idx]) # Bottom (D) row moves to Left (L) column self.faces['L'][:, n - 1 - idx] = self.faces['D'][idx, :] # Right (R) column moves to Bottom (D) row self.faces['D'][idx, :] = np.flip(self.faces['R'][:, idx]) # Saved Top (U) row moves to Right (R) column self.faces['R'][:, idx] = temp Use code with caution. 3. The Reduction Paradigm (The Core Algorithm) nxnxn rubik 39scube algorithm github python full
def apply_move(self, move): # Apply a move to the cube if move == 'U': # Rotate top face clockwise self.cube[:, :, 0, :] = np.rot90(self.cube[:, :, 0, :], -1) elif move == 'D': # Rotate bottom face clockwise self.cube[:, :, -1, :] = np.rot90(self.cube[:, :, -1, :], -1) # ... implement other moves ...
Move the N²-4 pieces in the center of each face to their correct positions. grid of colored stickers
nxnxn-cube-solver/ │ ├── README.md ├── requirements.txt ├── main.py └── src/ ├── __init__.py ├── cube.py ├── solver.py └── utils.py Use code with caution. Modeling the State: cube.py
If you are working with larger cubes, you would first import and call its reduction and solving functions, which internally call a 3×3×3 solver like Kociemba's for the final phase. Try again later.
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