示例#1
0
def mobility(board: Board):
    mobility = 0
    if board.turn == WHITE:
        mobility -= sum(1 for m in board.generate_pseudo_legal_moves()
                        if not board.is_into_check(m))
        board.push(Move.null())
        mobility += sum(1 for m in board.generate_pseudo_legal_moves()
                        if not board.is_into_check(m))
        board.pop()
    else:
        mobility += sum(1 for m in board.generate_pseudo_legal_moves()
                        if not board.is_into_check(m))
        board.push(Move.null())
        mobility -= sum(1 for m in board.generate_pseudo_legal_moves()
                        if not board.is_into_check(m))
        board.pop()
    return mobility
示例#2
0
def slide_move(board: chess.Board, move: chess.Move) -> Optional[chess.Move]:
    psuedo_legal_moves = list(board.generate_pseudo_legal_moves())
    squares = list(
        chess.SquareSet(chess.BB_BETWEEN[move.from_square][
            move.to_square])) + [move.to_square]
    squares = sorted(squares,
                     key=lambda s: chess.square_distance(s, move.from_square),
                     reverse=True)
    for slide_square in squares:
        revised = chess.Move(move.from_square, slide_square, move.promotion)
        if revised in psuedo_legal_moves:
            return revised
    return None
示例#3
0
class Viridithas():
    def __init__(
        self,
        human: bool = False,
        fen: str = 'rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1',
        pgn: str = '',
        time_limit: float = 15,
        fun: bool = False,
        contempt: int = 3000,
        book: bool = True,
        advancedTC: list = [],
    ):
        if pgn == '':
            self.node = Board(fen)
        else:
            self.node = Board()
            for move in pgn.split():
                try:
                    self.node.push_san(move)
                except Exception:
                    continue
        self.time_limit = time_limit
        if advancedTC:
            self.endpoint = time.time()+advancedTC[0]*60
            self.increment = advancedTC[1]
        else:
            self.endpoint = 0
            self.increment = 0
        self.fun = fun
        self.contempt = contempt
        self.human = human
        self.nodes = 0
        self.advancedTC = advancedTC
        self.hashtable: dict[Hashable, TTEntry] = dict()
        self.inbook = book

    def set_position(self, fen):
        self.node = Board(fen)

    def __repr__(self) -> str:
        return str(self.node) + '\n' + self.__class__.__name__+"-engine at position " + str(self.node.fen())

    def __str__(self) -> str:
        return self.__class__.__name__

    def user_setup(self):
        if input("Do you want to configure the bot? (Y/N) ").upper() != 'Y':
            return

        myname = self.__class__.__name__.upper()

        print(f"BEGINNING USER CONFIGURATION OF {myname}-BOT")

        datadict = get_engine_parameters()

        self.__init__(
            human=datadict["human"],
            fen=datadict["fen"],
            pgn=datadict["pgn"],
            time_limit=datadict["time_limit"],
            fun=datadict["fun"],
            contempt=datadict["contempt"],
            book=datadict["book"],
            advancedTC=datadict["advancedTC"]
        )

    def gameover_check_info(self):
        checkmate = self.node.is_checkmate()
        draw = self.node.is_stalemate() or \
            self.node.is_insufficient_material( ) or \
            self.node.is_repetition(2) or self.node.is_seventyfive_moves() or not any(self.node.generate_legal_moves())
        return checkmate or draw, checkmate, draw

    # @profile
    def evaluate(self, depth: float, checkmate: bool, draw: bool) -> float:
        self.nodes += 1

        if checkmate:
            return MATE_VALUE * int(max(depth+1, 1)) * (1 if self.node.turn else -1)
        if draw:
            return -self.contempt * (1 if self.node.turn else -1)

        rating: float = 0

        rating += pst_eval(self.node)
        # rating += see_eval(self.node)

        # rating += mobility(self.node) * MOBILITY_FACTOR
        
        # rating += piece_attack_counts(self.node) * ATTACK_FACTOR

        # rating += king_safety(self.node) * KING_SAFETY_FACTOR

        # rating += space(self.node) * SPACE_FACTOR

        return rating

    def single_hash_iterator(self, best):
        yield best

    def captures_piece(self, p):  # concentrate on MVV, then LVA
        return itertools.chain(
            self.node.generate_pseudo_legal_moves(self.node.pawns, p),
            self.node.generate_pseudo_legal_moves(self.node.knights, p),
            self.node.generate_pseudo_legal_moves(self.node.bishops, p),
            self.node.generate_pseudo_legal_moves(self.node.rooks, p),
            self.node.generate_pseudo_legal_moves(self.node.queens, p),
            self.node.generate_pseudo_legal_moves(self.node.kings, p),
        )

    #@profile
    def captures(self):  # (MVV/LVA)
        return (m for m in itertools.chain(
            self.captures_piece(
                self.node.occupied_co[not self.node.turn] & self.node.queens),
            self.captures_piece(
                self.node.occupied_co[not self.node.turn] & self.node.rooks),
            self.captures_piece(
                self.node.occupied_co[not self.node.turn] & self.node.bishops),
            self.captures_piece(
                self.node.occupied_co[not self.node.turn] & self.node.knights),
            self.captures_piece(
                self.node.occupied_co[not self.node.turn] & self.node.pawns),
        ) if self.node.is_legal(m))

    def winning_captures(self):  # (MVV/LVA)
        target_all = self.node.occupied_co[not self.node.turn]
        target_3 = target_all & ~self.node.pawns
        target_5 = target_3 & (~self.node.bishops | ~self.node.knights)
        target_9 = target_5 & ~self.node.rooks
        return itertools.chain(
            self.node.generate_pseudo_legal_moves(self.node.pawns, target_all),
            self.node.generate_pseudo_legal_moves(self.node.knights, target_3),
            self.node.generate_pseudo_legal_moves(self.node.bishops, target_3),
            self.node.generate_pseudo_legal_moves(self.node.rooks, target_5),
            self.node.generate_pseudo_legal_moves(self.node.queens, target_9),
            self.node.generate_pseudo_legal_moves(self.node.kings, target_9),
        )

    def losing_captures(self):  # (MVV/LVA)
        target_pawns = self.node.pawns
        target_pnb = target_pawns | self.node.bishops | self.node.knights
        target_pnbr = target_pnb | self.node.rooks
        return itertools.chain(
            self.node.generate_pseudo_legal_moves(self.node.knights, target_pawns),
            self.node.generate_pseudo_legal_moves(self.node.bishops, target_pawns),
            self.node.generate_pseudo_legal_moves(self.node.rooks, target_pnb),
            self.node.generate_pseudo_legal_moves(self.node.queens, target_pnbr),
            self.node.generate_pseudo_legal_moves(self.node.kings, target_pnbr),
        )

    def ordered_moves(self):
        return (m for m in itertools.chain(
            # self.winning_captures(),
            self.captures_piece(
                self.node.occupied_co[not self.node.turn] & self.node.queens),
            self.captures_piece(
                self.node.occupied_co[not self.node.turn] & self.node.rooks),
            self.captures_piece(
                self.node.occupied_co[not self.node.turn] & self.node.bishops),
            self.captures_piece(
                self.node.occupied_co[not self.node.turn] & self.node.knights),
            self.captures_piece(
                self.node.occupied_co[not self.node.turn] & self.node.pawns),
            self.node.generate_pseudo_legal_moves(
                0xffff_ffff_ffff_ffff, ~self.node.occupied_co[not self.node.turn]),
            # self.losing_captures()
        ) if self.node.is_legal(m))

    def pass_turn(self) -> None:
        self.node.push(Move.from_uci("0000"))

    #@profile
    def qsearch(self, alpha: float, beta: float, depth: float, colour: int, gameover: bool, checkmate: bool, draw: bool) -> float:

        val = self.evaluate(1, checkmate, draw) * colour
        if gameover:
            return val
        if val >= beta:
            return beta
        if (val < alpha - QUEEN_VALUE):
            return alpha
        
        alpha = max(val, alpha)

        for capture in self.captures():
            self.node.push(capture)
            gameover, checkmate, draw = self.gameover_check_info()
            score = -self.qsearch(-beta, -alpha, depth - 1, -colour, gameover, checkmate, draw)
            self.node.pop()
            if score >= beta:
                return score
            alpha = max(score, alpha)

        return alpha

    def tt_lookup(self, board: Board) -> "TTEntry":
        key = board._transposition_key()
        return self.hashtable.get(key, TTEntry.default())

    def tt_store(self, board: Board, entry: TTEntry):
        key = board._transposition_key()    
        self.hashtable[key] = entry

    #@profile
    def negamax(self, depth: float, colour: int, alpha: float, beta: float) -> float:
        initial_alpha = alpha

        # (* Transposition Table Lookup; self.node is the lookup key for ttEntry *)
        tt_entry = self.tt_lookup(self.node)
        if not tt_entry.is_null() and tt_entry.depth >= depth:
            if tt_entry.type == EXACT:
                return tt_entry.value
            elif tt_entry.type == LOWERBOUND:
                alpha = max(alpha, tt_entry.value)
            elif tt_entry.type == UPPERBOUND:
                beta = min(beta, tt_entry.value)

            if alpha >= beta:
                return tt_entry.value
            
            if self.node.is_legal(tt_entry.best):
                moves = itertools.chain([tt_entry.best], filter(lambda x: x != tt_entry.best, self.ordered_moves()))
            else:
                moves = self.ordered_moves()
        else:
            moves = self.ordered_moves()

        gameover, checkmate, draw = self.gameover_check_info()

        if gameover:
            return colour * self.evaluate(depth, checkmate, draw)

        if depth < 1:
            return self.qsearch(alpha, beta, depth, colour, gameover, checkmate, draw)

        current_pos_is_check = self.node.is_check()
        if not current_pos_is_check and depth >= 3 and abs(alpha) < MATE_VALUE and abs(beta) < MATE_VALUE:
            # MAKE A NULL MOVE
            self.node.push(Move.null())  
            # PERFORM A LIMITED SEARCH
            value = - self.negamax(depth - 3, -colour, -beta, -beta + 1)
            # UNMAKE NULL MOVE
            self.node.pop()

            if value >= beta:
                return beta

        do_prune = self.pruning(depth, colour, alpha, beta, current_pos_is_check)

        best_move = Move.null()
        search_pv = True
        value = float("-inf")
        for move_idx, move in enumerate(moves):
            if move_idx == 0:
                best_move = move
            gives_check = self.node.gives_check(move)
            is_capture = self.node.is_capture(move)
            is_promo = bool(move.promotion)
            depth_reduction = search_reduction_factor(
                move_idx, current_pos_is_check, gives_check, is_capture, is_promo, depth)
                
            if do_prune:
                if not gives_check and not is_capture: 
                    continue

            self.node.push(move)
            
            if search_pv:
                r = -self.negamax(depth - depth_reduction, -colour, -beta, -alpha)
                value = max(value, r)
            else:
                r = -self.negamax(depth - depth_reduction, -colour, -alpha-1, -alpha)
                if (r > alpha): # // in fail-soft ... & & value < beta) is common
                    r = -self.negamax(depth - depth_reduction, -colour, -beta, -alpha) #// re-search
                value = max(value, r)

            self.node.pop()

            if value > alpha:
                alpha = value
                best_move = move
            alpha = max(alpha, value)
            if alpha >= beta:
                break
            search_pv = False

        # (* Transposition Table Store; self.node is the lookup key for ttEntry *)
        # ttEntry = TTEntry()
        tt_entry.value = value
        if value <= initial_alpha:
            tt_entry.type = UPPERBOUND
        elif value >= beta:
            tt_entry.type = LOWERBOUND
        else:
            tt_entry.type = EXACT
        tt_entry.depth = depth
        tt_entry.best = best_move
        tt_entry.null = False
        self.tt_store(self.node, tt_entry)

        return value

    def pruning(self, depth, colour, alpha, beta, current_pos_is_check):
        if not (not current_pos_is_check and abs(
                alpha) < MATE_VALUE / 2 and abs(beta) < MATE_VALUE / 2) or depth > 2:
            return False

        see = see_eval(self.node) * colour

        DO_D1_PRUNING = depth <= 1 and see + FUTILITY_MARGIN < alpha

        DO_D2_PRUNING = depth <= 2 and see + FUTILITY_MARGIN_2 < alpha

        return DO_D1_PRUNING or DO_D2_PRUNING

    def move_sort(self, moves: list, ratings: list):
        pairs = zip(*sorted(zip(moves, ratings), key=operator.itemgetter(1)))
        moves, ratings = [list(pair) for pair in pairs]
        return moves, ratings

    def pv_string(self):
        count = 0
        moves = []
        while True:
            e = self.tt_lookup(self.node)
            if e.is_null() or not self.node.is_legal(e.best):
                break

            # print(self.node.__str__())
            # print(self.node.__repr__())
            # print(e.best)
            # print(self.node.san(e.best))

            moves.append(self.node.san(e.best))
            self.node.push(e.best)
            count += 1
        
        for _ in moves:
            self.node.pop()

        if count == 0: return ""
        return " ".join(moves)

    def turnmod(self) -> int:
        return -1 if self.node.turn else 1

    def show_iteration_data(self, moves: list, values: list, depth: float, start: float) -> tuple:
        t = round(time.time()-start, 2)
        print(f"{self.node.san(moves[0])} | {-round((self.turnmod()*values[0])/1000, 3)} | {str(t)}s at depth {str(depth + 1)}, {str(self.nodes)} nodes processed, at {str(int(self.nodes / (t+0.00001)))}NPS.\n", f"PV: {self.pv_string()}\n", end="")
        return (self.node.san(moves[0]), self.turnmod()*values[0], self.nodes, depth+1, t)

    def search(self, ponder: bool = False, readout: bool = True):
        val = float("-inf")
        start_time = time.time()
        self.nodes = 0
        moves = [next(self.ordered_moves())]
        saved_position = deepcopy(self.node)

        alpha, beta = float("-inf"), float("inf")
        valWINDOW = PAWN_VALUE / 4

        WINDOW_FAILED = False

        try:
            depth = 1
            while depth < 40:
                best = self.tt_lookup(self.node).best
                time_elapsed = time.time() - start_time
                # check if we aren't going to finish the next search in time
                if time_elapsed > 0.5 * self.time_limit and not ponder and not WINDOW_FAILED:
                    return best, val

                val = self.negamax(
                    depth, self.turnmod(), alpha=alpha, beta=beta)
                # print(val)
                if ((val <= alpha) or (val >= beta)):
                    # We fell outside the window, so try again with a
                    # full-width window (and the same depth).
                    alpha = float("-inf")
                    beta = float("inf")
                    WINDOW_FAILED = True
                    continue
                WINDOW_FAILED = False

                best = self.tt_lookup(self.node).best
                # check if we've run out of time
                if time_elapsed > self.time_limit and not ponder:
                    return best, val

                moves = [self.tt_lookup(self.node).best]
                values = [self.tt_lookup(self.node).value]

                if readout:
                    self.show_iteration_data(moves, values, depth, start_time)

                alpha = val - valWINDOW # Set up the window for the next iteration.
                beta = val + valWINDOW
                depth += 1
        except KeyboardInterrupt:
            self.node = saved_position
            pass
        return moves[0], val

    def ponder(self) -> None:
        self.origin = self.node.copy()
        self.search(ponder=True)

    def get_book_move(self):
        # book = chess.polyglot.open_reader(
        #     r"ProDeo292/ProDeo292/books/elo2500.bin")
        book = chess.polyglot.open_reader(
            r"books/elo2500.bin")
        main_entry = book.find(self.node)
        choice = book.weighted_choice(self.node)
        book.close()
        return main_entry.move, choice.move

    def engine_move(self) -> Move:
        # add flag_func for egtb mode
        if self.advancedTC:
            self.time_limit = (self.endpoint-time.time())/20
        print("Time for move: " + str(round(self.time_limit, 2)) + "s")
        if self.inbook:
            try:
                best, choice = self.get_book_move()
                if self.fun:
                    self.node.push(choice)
                    return choice
                else:
                    self.node.push(best)
                print(chess.pgn.Game.from_board(self.node)[-1])
            except IndexError:
                self.time_limit = self.time_limit*2
                best, _ = self.search()
                self.node.push(best)
                print(chess.pgn.Game.from_board(self.node)[-1])
                self.inbook = False
                self.time_limit = self.time_limit/2
        else:
            best, _ = self.search()
            self.node.push(best)
            print(chess.pgn.Game.from_board(self.node)[-1])
        # self.record_stack()
        self.endpoint += self.increment
        return best

    def user_move(self) -> str:
        move = input("enter move: ")
        while True:
            try:
                self.node.push_san(move)
                break
            except Exception:
                move = input("enter move: ")
        return move

    def display_ending(self) -> None:
        if self.node.is_stalemate():
            print('END BY STALEMATE')
        elif self.node.is_insufficient_material():
            print('END BY INSUFFICIENT MATERIAL')
        elif self.node.is_fivefold_repetition():
            print('END BY FIVEFOLD REPETITION')
        elif self.node.is_checkmate:
            print("BLACK" if self.node.turn == BLACK else "WHITE", 'WINS ON TURN',
                  self.node.fullmove_number)
        else:
            print('END BY UNKNOWN REASON')

    def run_game(self, indefinite=True) -> str:
        while not self.node.is_game_over():
            print(self.__repr__())
            if self.human and self.node.turn:
                try:
                    self.ponder()
                except KeyboardInterrupt:
                    self.node = self.origin
                    self.user_move()

            else:  # SWAP THESE ASAP

                self.engine_move()
            if not indefinite:
                break
        self.display_ending()
        try:
            return str(chess.pgn.Game.from_board(self.node)[-1])
        except Exception:
            return "PGN ERROR"

    def play_viri(self, fen=None):
        player_colour = input(
            "Enter the human player's colour in the form b/w\n--> ")
        while player_colour not in ['b', 'w']:
            player_colour = input(
                "Enter the human player's colour in the form b/w\n--> ")
        player_colour = WHITE if player_colour == 'w' else BLACK
        timeControl = int(
            input("how many seconds should viri get per move?\n--> "))
        self.__init__(human=True, time_limit=timeControl, fen=fen, book=True, fun=False)
        self.fun = False
        while not self.node.is_game_over():
            print(self.__repr__())
            if player_colour == self.node.turn:
                # try:
                #     self.ponder()
                # except KeyboardInterrupt:
                #     self.node = self.origin
                #     self.user_move()
                self.user_move()
            else:
                self.engine_move()
        self.display_ending()

    def perftx(self, n):
        if n == 0:
            self.nodes += 1
        else:
            for move in self.ordered_moves():
                self.node.push(move)
                self.perftx(n - 1)
                self.node.pop()

    def perft(self, n):
        self.nodes = 0
        self.perftx(n)
        print(self.nodes)

    def uci(self):
        start = input()
        while start != "uci":
            start = input()
        print("id", end="")
        while True:
            command = input()
            if command == "ucinewgame":
                board = Board()
            elif command.split()[0] == "position":
                fen = command[command.index(
                    "fen") + 3: command.index("moves") - 1]
                moves = command[command.index("moves"):].split()
                if fen == "startpos":
                    fen = 'rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1'
                board = Board(fen)
                for move in moves:
                    board.push(Move.from_uci(move))