diff --git a/iq_mini_4489/src/main.py b/iq_mini_4489/src/main.py
deleted file mode 100644
index dff506f..0000000
--- a/iq_mini_4489/src/main.py
+++ /dev/null
@@ -1,96 +0,0 @@
-from board import Board, generate_orientations
-from typing import Tuple, List
-import pieces
-import numpy as np
-import colorama
-
-def backtrack(board: Board, pieces_list: List[str], piece_index: int,
- orientations: dict, solutions: List[np.ndarray]) -> None:
- """
- Backtracking to place each piece in the board in all possible ways.
- """
-
- # if full, check if solution
- if piece_index == len(pieces_list):
- if board.is_full():
- solutions.append(board.grid.copy())
- return
-
- piece_name = pieces_list[piece_index]
- all_orientations = orientations[piece_name]
-
- for orientation in all_orientations:
- rows, cols = orientation.shape
- for row in range(board.rows - rows + 1):
- for col in range(board.cols - cols + 1):
- if board.placeable(orientation, (row, col)):
- board.place(orientation, (row, col), piece_index + 1)
- backtrack(board, pieces_list, piece_index + 1, orientations, solutions)
- board.remove(orientation, (row, col))
-
-
-def colorful_solution(solution: np.ndarray) -> str:
- """
- Return a colorful representation of the solution.
- """
- rows, cols = solution.shape
- result = ""
- piece_id_to_color = {
- -1: colorama.Back.BLACK,
- 1: colorama.Back.GREEN,
- 2: colorama.Back.BLUE,
- 3: colorama.Back.YELLOW,
- 4: colorama.Back.MAGENTA,
- 5: colorama.Back.CYAN,
- 6: colorama.Back.RED,
- }
- for r in range(rows):
- for c in range(cols):
- piece_id = solution[r, c]
- if piece_id == 0:
- result += colorama.Back.LIGHTWHITE_EX + " "
- else:
- result += piece_id_to_color[piece_id] + " "
-
- result += colorama.Back.RESET
- result += "\n"
- return result
-
-def solve(xPin: Tuple[int, int], yPin: Tuple[int, int], zPin: Tuple[int, int]):
- """
- solve the puzzle, avoiding the pins at the specified positions.
-
- Args:
- xPin (Tuple[int, int]): row, col of the 'x' pin
- yPin (Tuple[int, int]): row, col of the 'y' pin
- zPin (Tuple[int, int]): row, col of the 'z' pin
- """
-
- board = Board((5, 5))
-
- pinned_positions = [xPin, yPin, zPin]
- for (pr, pc) in pinned_positions:
- board.grid[pr, pc] = -1
-
- orientations_map = {}
- for piece_name, piece_matrix in pieces.all_pieces.items():
- orientations_map[piece_name] = generate_orientations(piece_matrix)
- piece_names = list(pieces.all_pieces.keys())
- solutions = []
- backtrack(board, piece_names, 0, orientations_map, solutions)
- if solutions:
- print(f"Found {len(solutions)} solution(s).")
- for idx, sol in enumerate(solutions, start=1):
- print(f"Solution #{idx}:")
- print(colorful_solution(sol))
- print("------------------")
- print(f"Total: {len(solutions)} solution{"s" if len(solutions) else ""}.")
- return
-
- print("No solution found.")
-
-
-
-
-if __name__ == "__main__":
- solve((0, 2), (2, 0), (3, 3))
\ No newline at end of file
diff --git a/iq_mini_4489/src/solver.py b/iq_mini_4489/src/solver.py
index 59ade47..0868376 100644
--- a/iq_mini_4489/src/solver.py
+++ b/iq_mini_4489/src/solver.py
@@ -99,11 +99,11 @@ def try_all_pegs():
all_solutions = []
# Solution entry {x: (row, col), y: (row, col), z: (row, col), solution_count: int}
- for xPinA in tqdm(range(5)):
+ for xPinA in (range(5)):
for yPinA in range(5):
for xPinB in range(5):
for yPinB in range(5):
- for xPinC in range(5):
+ for xPinC in tqdm(range(5)):
for yPinC in range(5):
if (xPinA, yPinA) == (xPinB, yPinB) or (xPinA, yPinA) == (xPinC, yPinC) or (xPinB, yPinB) == (xPinC, yPinC):
continue
diff --git a/out.json b/out.json
new file mode 100644
index 0000000..6b84a8a
--- /dev/null
+++ b/out.json
@@ -0,0 +1,62 @@
+[
+ { "x": [0, 0], "y": [1, 4], "z": [2, 2], "solution_count": 12 },
+ { "x": [0, 0], "y": [1, 4], "z": [3, 2], "solution_count": 15 },
+ { "x": [0, 0], "y": [1, 4], "z": [4, 2], "solution_count": 12 },
+ { "x": [0, 0], "y": [2, 4], "z": [1, 2], "solution_count": 21 },
+ { "x": [0, 0], "y": [2, 4], "z": [3, 2], "solution_count": 20 },
+ { "x": [0, 0], "y": [2, 4], "z": [4, 2], "solution_count": 28 },
+ { "x": [0, 0], "y": [3, 4], "z": [1, 2], "solution_count": 24 },
+ { "x": [0, 0], "y": [3, 4], "z": [2, 2], "solution_count": 16 },
+ { "x": [0, 0], "y": [3, 4], "z": [4, 2], "solution_count": 26 },
+ { "x": [0, 0], "y": [4, 4], "z": [1, 2], "solution_count": 31 },
+ { "x": [0, 0], "y": [4, 4], "z": [2, 2], "solution_count": 52 },
+ { "x": [0, 0], "y": [4, 4], "z": [3, 2], "solution_count": 31 },
+ { "x": [1, 0], "y": [0, 4], "z": [2, 2], "solution_count": 12 },
+ { "x": [1, 0], "y": [0, 4], "z": [3, 2], "solution_count": 15 },
+ { "x": [1, 0], "y": [0, 4], "z": [4, 2], "solution_count": 12 },
+ { "x": [1, 0], "y": [2, 4], "z": [0, 2], "solution_count": 9 },
+ { "x": [1, 0], "y": [2, 4], "z": [3, 2], "solution_count": 14 },
+ { "x": [1, 0], "y": [2, 4], "z": [4, 2], "solution_count": 5 },
+ { "x": [1, 0], "y": [3, 4], "z": [0, 2], "solution_count": 7 },
+ { "x": [1, 0], "y": [3, 4], "z": [2, 2], "solution_count": 6 },
+ { "x": [1, 0], "y": [3, 4], "z": [4, 2], "solution_count": 7 },
+ { "x": [1, 0], "y": [4, 4], "z": [0, 2], "solution_count": 26 },
+ { "x": [1, 0], "y": [4, 4], "z": [2, 2], "solution_count": 16 },
+ { "x": [1, 0], "y": [4, 4], "z": [3, 2], "solution_count": 24 },
+ { "x": [2, 0], "y": [0, 4], "z": [1, 2], "solution_count": 21 },
+ { "x": [2, 0], "y": [0, 4], "z": [3, 2], "solution_count": 20 },
+ { "x": [2, 0], "y": [0, 4], "z": [4, 2], "solution_count": 28 },
+ { "x": [2, 0], "y": [1, 4], "z": [0, 2], "solution_count": 9 },
+ { "x": [2, 0], "y": [1, 4], "z": [3, 2], "solution_count": 14 },
+ { "x": [2, 0], "y": [1, 4], "z": [4, 2], "solution_count": 5 },
+ { "x": [2, 0], "y": [3, 4], "z": [0, 2], "solution_count": 5 },
+ { "x": [2, 0], "y": [3, 4], "z": [1, 2], "solution_count": 14 },
+ { "x": [2, 0], "y": [3, 4], "z": [4, 2], "solution_count": 9 },
+ { "x": [2, 0], "y": [4, 4], "z": [0, 2], "solution_count": 28 },
+ { "x": [2, 0], "y": [4, 4], "z": [1, 2], "solution_count": 20 },
+ { "x": [2, 0], "y": [4, 4], "z": [3, 2], "solution_count": 21 },
+ { "x": [3, 0], "y": [0, 4], "z": [1, 2], "solution_count": 24 },
+ { "x": [3, 0], "y": [0, 4], "z": [2, 2], "solution_count": 16 },
+ { "x": [3, 0], "y": [0, 4], "z": [4, 2], "solution_count": 26 },
+ { "x": [3, 0], "y": [1, 4], "z": [0, 2], "solution_count": 7 },
+ { "x": [3, 0], "y": [1, 4], "z": [2, 2], "solution_count": 6 },
+ { "x": [3, 0], "y": [1, 4], "z": [4, 2], "solution_count": 7 },
+ { "x": [3, 0], "y": [2, 4], "z": [0, 2], "solution_count": 5 },
+ { "x": [3, 0], "y": [2, 4], "z": [1, 2], "solution_count": 14 },
+ { "x": [3, 0], "y": [2, 4], "z": [4, 2], "solution_count": 9 },
+ { "x": [3, 0], "y": [4, 4], "z": [0, 2], "solution_count": 12 },
+ { "x": [3, 0], "y": [4, 4], "z": [1, 2], "solution_count": 15 },
+ { "x": [3, 0], "y": [4, 4], "z": [2, 2], "solution_count": 12 },
+ { "x": [4, 0], "y": [0, 4], "z": [1, 2], "solution_count": 31 },
+ { "x": [4, 0], "y": [0, 4], "z": [2, 2], "solution_count": 52 },
+ { "x": [4, 0], "y": [0, 4], "z": [3, 2], "solution_count": 31 },
+ { "x": [4, 0], "y": [1, 4], "z": [0, 2], "solution_count": 26 },
+ { "x": [4, 0], "y": [1, 4], "z": [2, 2], "solution_count": 16 },
+ { "x": [4, 0], "y": [1, 4], "z": [3, 2], "solution_count": 24 },
+ { "x": [4, 0], "y": [2, 4], "z": [0, 2], "solution_count": 28 },
+ { "x": [4, 0], "y": [2, 4], "z": [1, 2], "solution_count": 20 },
+ { "x": [4, 0], "y": [2, 4], "z": [3, 2], "solution_count": 21 },
+ { "x": [4, 0], "y": [3, 4], "z": [0, 2], "solution_count": 12 },
+ { "x": [4, 0], "y": [3, 4], "z": [1, 2], "solution_count": 15 },
+ { "x": [4, 0], "y": [3, 4], "z": [2, 2], "solution_count": 12 }
+]