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https://github.com/kristoferssolo/Tetris.git
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feat(ai): add algorithm
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from .ai import run
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__all__ = ["run"]
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src/ai/ai.py
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35
src/ai/ai.py
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from game import Main
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from game.sprites import Tetromino
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from loguru import logger
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from utils import BestMove, GameMode
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from .move import get_best_move
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def run() -> None:
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app = Main(GameMode.AI_TRAINING)
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game = app.game
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if not game:
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return
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tetris = game.tetris
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while True:
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app.handle_events()
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app.run_game_loop()
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phantom_tetermino = Tetromino(tetris.phantom_sprites, None, tetris.field, tetris.tetromino.figure, True)
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best_move: BestMove = get_best_move(app, game.tetris, phantom_tetermino)
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figure = game.tetris.tetromino.figure
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logger.debug(f"{figure.name=} {best_move=}")
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for rotation in range(best_move.rotation):
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tetris.tetromino.rotate()
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for _ in range(abs(best_move.x_axis_offset)):
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if best_move.x_axis_offset > 0:
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tetris.move_right()
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elif best_move.x_axis_offset < 0:
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tetris.move_left()
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tetris.drop()
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55
src/ai/move.py
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55
src/ai/move.py
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from typing import Optional
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from game import Main, Tetris
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from game.sprites import Tetromino
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from loguru import logger
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from utils import CONFIG, BestMove, Direction, Figure
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from .score import calculate_score
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NUM_ROTATIONS: dict[Figure, int] = {
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Figure.I: 2,
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Figure.O: 1,
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Figure.T: 4,
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Figure.S: 2,
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Figure.Z: 2,
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Figure.J: 4,
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Figure.L: 4,
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}
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def get_best_move(app: Main, game: Tetris, tetermino: Tetromino) -> BestMove:
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best_move: Optional[BestMove] = None
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best_score: Optional[float] = None
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for rotation in range(NUM_ROTATIONS[tetermino.figure]):
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for i in range(CONFIG.game.columns):
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x_axis_movement: int = 0
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for _ in range(rotation):
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tetermino.rotate()
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while tetermino.move_horizontal(Direction.LEFT): # move maximaly to the left
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x_axis_movement -= 1
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for _ in range(i):
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if tetermino.move_horizontal(Direction.RIGHT): # slowly move to the right
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x_axis_movement += 1
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tetermino.drop()
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score: float = calculate_score(game)
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logger.debug(
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f"{tetermino.figure.name=:3} {score=:6.6f} {best_score=:6.6f} {rotation=:1} {x_axis_movement=:1}"
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)
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tetermino.kill()
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tetermino = Tetromino(game.phantom_sprites, None, game.field, game.tetromino.figure, True)
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if best_score is None or score > best_score:
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best_score = score
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best_move = BestMove(rotation, x_axis_movement)
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if not best_move:
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best_move = BestMove(0, 0)
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return best_move
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17
src/ai/score.py
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17
src/ai/score.py
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import numpy as np
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from game import Tetris
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from .heuristics import aggregate_height, complete_lines, count_holes, get_bumpiness
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def calculate_score(game: Tetris) -> float:
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field: np.ndarray[int, np.dtype[np.uint8]] = np.where(game.field != None, 1, 0)
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for block in game.tetromino.blocks:
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field[int(block.pos.y), int(block.pos.x)] = 1
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height = aggregate_height(field) * -0.510066
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lines = complete_lines(field) * 0.760666
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holes = count_holes(field) * -0.35663
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bumpiness = get_bumpiness(field) * -0.184483
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return height + lines + holes + bumpiness
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from .figure import Figure, FigureConfig
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from .figure import Figure, FigureConfig
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from .path import BASE_PATH
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from .path import BASE_PATH
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from .settings import read_settings, save_settings
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from .settings import read_settings, save_settings
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from .tuples import Size
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from .tuples import BestMove, Size
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__all__ = [
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__all__ = [
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"BASE_PATH",
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"BASE_PATH",
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"GameMode",
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"GameMode",
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"read_settings",
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"read_settings",
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"save_settings",
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"save_settings",
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"BestMove",
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]
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]
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if isinstance(other, Size):
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if isinstance(other, Size):
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return Size(self.width - other.width, self.height - other.height)
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return Size(self.width - other.width, self.height - other.height)
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return Size(self.width - other, self.height - other)
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return Size(self.width - other, self.height - other)
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class BestMove(NamedTuple):
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"""
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A best move object.
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Attributes:
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rotation: The rotation of the best move.
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x_axis_offset: The x-axis offset of the best move.
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"""
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rotation: int
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x_axis_offset: int
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help="Run app with GUI [Default]",
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help="Run app with GUI [Default]",
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)
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parser.add_argument(
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"-t",
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"--train",
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action="store_true",
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help="Train AI",
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)
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def setup_logger(level: str = "warning") -> None:
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def setup_logger(level: str = "warning") -> None:
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from utils import BASE_PATH
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from utils import BASE_PATH
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level = "info"
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level = "info"
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else:
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else:
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level = "warning"
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level = "warning"
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setup_logger(level)
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setup_logger(level)
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run()
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if args.train: # type: ignore
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import ai
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ai.train()
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else:
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run()
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if __name__ == "__main__":
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if __name__ == "__main__":
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