Add classes and method documentation
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2 changed files with 169 additions and 10 deletions
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@ -1,6 +1,17 @@
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import random, math, time, signal
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"""
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Base player engine
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"""
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class PlayerEngine:
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"""
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init
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@param player: black or white player
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@param logger: loggig object (display verbose / debug messages
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@param heuristic: HeuristicClass object to calculate tree heuristic
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@param options: hashtable containing options
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"""
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def __init__(self, player, logger, heuristic, options: dict = {}):
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# init logger do display informations
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self.player = player
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@ -13,29 +24,65 @@ class PlayerEngine:
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self.options
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))
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"""
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get move
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@param board: Board
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"""
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def get_move(self, board):
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self.logger.info("engine: {} - player:{}".format(
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self.__class__.__name__,
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self.get_player_name(self.player)
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))
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"""
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Get possibles player move an apply a Random.shuffle on it (if needed)
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@param none
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@return: array
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"""
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def get_player_moves(self, board):
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moves = board.legal_moves()
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if self.options['randomize_moves'] is True:
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random.shuffle(moves)
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return moves
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"""
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Get player name based on his number
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@param player: int
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@return: string
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"""
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@staticmethod
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def get_player_name(player):
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return 'White (O)' if player == 2 else 'Black (X)'
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"""
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Random game engine
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"""
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class RandomPlayerEngine(PlayerEngine):
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"""
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Get move return a random move based on Board.legal_moves
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@param player: int
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@return: array
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"""
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def get_move(self, board):
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super().get_move(board)
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moves = board.legal_moves()
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return random.choice(moves)
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"""
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Human player engine.
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"""
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class HumanPlayerEngine(PlayerEngine):
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"""
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Get move return a move based on user input
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@param board: Board
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@return: array
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"""
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def get_move(self, board):
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super()
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move = None
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@ -46,6 +93,12 @@ class HumanPlayerEngine(PlayerEngine):
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move = self.validate_input(user_input, board)
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return move
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"""
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Validate user input an verify than the move is possible
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@param input: string
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@return: array
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"""
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@staticmethod
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def validate_input(input, board):
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if input == 'print':
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@ -66,13 +119,31 @@ class HumanPlayerEngine(PlayerEngine):
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return [board._nextPlayer, x, y]
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"""
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MinMax player engine
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"""
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class MinmaxPlayerEngine(PlayerEngine):
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"""
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Get move based on minmax algorithm
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@param board: Board
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@return: array
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"""
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def get_move(self, board):
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super().get_move(board)
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move, score = self._call(board, self.options['depth'])
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return move
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"""
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First part of the minmax algorithm, it get the best player move based on
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max value
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@param board: Board
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@param depth: search depth
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@return: move and max heuristic
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"""
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def _call(self, board, depth):
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value = -math.inf
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nodes = 1
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@ -100,6 +171,13 @@ class MinmaxPlayerEngine(PlayerEngine):
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))
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return move, value
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"""
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recursive function to apply minmax
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@param board: Board
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@param friend_move: boolean does function maximise (player turn) or not (opponent turn)
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@param depth: search depth
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@return: heuristic score, nodes ans leafs processed
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"""
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def checkMinMax(self, board, friend_move:bool, depth :int = 2):
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nodes = 1
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leafs = 0
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@ -140,6 +218,13 @@ class AlphabetaPlayerEngine(PlayerEngine):
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move, heuristic = self._call(board, self.options['depth'])
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return move
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"""
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First part of the alphabeta algorithm, it get the best player move based on
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max value
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@param board: Board
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@param depth: search depth
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@return: move and max heuristic
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"""
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def _call(self, board, depth):
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self.logger.debug("Enter AlphaBeta function")
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alpha = -math.inf
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@ -169,7 +254,13 @@ class AlphabetaPlayerEngine(PlayerEngine):
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))
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return move, alpha
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"""
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recursive function to apply alphabeta
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@param board: Board
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@param friend_move: boolean does function maximise (player turn) or not (opponent turn)
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@param depth: search depth
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@return: heuristic score, nodes ans leafs processed
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"""
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def checkAlphaBeta(self, board, friend_move : bool, depth, alpha, beta):
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nodes = 1
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leafs = 0
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@ -206,7 +297,11 @@ class AlphabetaPlayerEngine(PlayerEngine):
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class MinmaxDeepeningPlayerEngine(MinmaxPlayerEngine):
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"""
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Get move based on minmax algorithm with iterative deepening
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@param board: Board
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@return: array
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"""
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def get_move(self, board):
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super().get_move(board)
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self.interrupt_search = False
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@ -251,7 +346,11 @@ class MinmaxDeepeningPlayerEngine(MinmaxPlayerEngine):
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class AlphaBetaDeepeningPlayerEngine(AlphabetaPlayerEngine):
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"""
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Get move based on alphabeta algorithm with iterative deepening
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@param board: Board
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@return: array
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"""
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def get_move(self, board):
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self.interrupt_search = False
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@ -284,6 +383,9 @@ class AlphaBetaDeepeningPlayerEngine(AlphabetaPlayerEngine):
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))
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return move
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"""
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define an handler for the alarm signal
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"""
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def alarm_handler(self, signal, frame):
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self.logger.debug("Raise SIGALMR Signal")
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self.interrupt_search = True
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@ -1,4 +1,14 @@
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"""
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Base class for heuristic object
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"""
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class HeuristicEngine:
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"""
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Init method
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@param logger: logging object (display verbose and debug messages)
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@param options: hashtable contains options like board size or heuristic weight
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"""
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def __init__(self, logger, options):
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self.logger = logger
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self.options = options
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@ -10,22 +20,52 @@ class HeuristicEngine:
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def get():
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raise NotImplementedError
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"""
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Score based heuristic class
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"""
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class ScoreHeuristicEngine(HeuristicEngine):
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"""
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Get score
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@param board: reversi board object
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@return score: int
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"""
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def get(self, board, player):
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return board.heuristique(player)
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"""
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Weight based heuristic class
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"""
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class WeightHeuristicEngine(HeuristicEngine):
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"""
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Init method
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@param logger: logging object (display verbose and debug messages)
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@param options: hashtable contains options like board size or heuristic weight
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"""
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def __init__(self, logger, options):
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super().__init__(logger, options)
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self.weights = self._get_weight_array()
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self.logger.debug("{}".format(self.show_weights()))
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"""
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Get score
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@param board: reversi board object
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@param player: int concerned player
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@return int
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"""
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def get(self, board, player):
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score = self.get_weight(board, player)
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return score
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"""
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Get score based on weight based on a weight-table built on object creation
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@param board: reversi board object
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@param player: int concerned player
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@return int
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"""
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def get_weight(self, board, player):
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score = 0
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size = self.options['size']
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@ -42,6 +82,11 @@ class WeightHeuristicEngine(HeuristicEngine):
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w[pos_x][pos_y] = -self.weights[pos_x][pos_y]
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return score
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"""
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Get weight array calculated with weight given with options
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@param : none
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@return 2D array
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"""
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def _get_weight_array(self):
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size = self.options['size']
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w = [[ 0 for _ in range(size)] for _ in range(size)]
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@ -85,7 +130,11 @@ class WeightHeuristicEngine(HeuristicEngine):
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return w
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"""
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Create a "displayable" array of value dor the calculated weight table
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@input none
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@return string
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"""
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def show_weights(self):
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display = "\n |"
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sep = "\n----"
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display += "\n"
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return display
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"""
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Full heuristic class
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"""
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class FullHeuristicEngine(WeightHeuristicEngine):
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"""
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Get score
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@param board: reversi board object
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@param player: int concerned player
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@return int
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"""
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def get(self, board, player):
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return self.get_weight(board, player) + board.heuristique(player)
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