[+] A2 Starter files

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 """CSC111 Winter 2021 Assignment 2: Trees, Chess, and Artificial Intelligence (Game Tree)
 Instructions (READ THIS FIRST!)
 ===============================
 This Python module contains the start of a GameTree class that you'll be working with
 and modifying in this assignment. You WILL be submitting this file!
 Copyright and Usage Information
 ===============================
 This file is provided solely for the personal and private use of students
 taking CSC111 at the University of Toronto St. George campus. All forms of
 distribution of this code, whether as given or with any changes, are
 expressly prohibited. For more information on copyright for CSC111 materials,
 please consult our Course Syllabus.
 This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
 """
 from __future__ import annotations
 from typing import Optional
 GAME_START_MOVE = '*'
 class GameTree:
    """A decision tree for Minichess moves.
    Each node in the tree stores a Minichess move and a boolean representing whether
    the current player (who will make the next move) is White or Black.
    Instance Attributes:
      - move: the current chess move (expressed in chess notation), or '*' if this tree
              represents the start of a game
      - is_white_move: True if White is to make the next move after this, False otherwise
    Representation Invariants:
        - self.move == GAME_START_MOVE or self.move is a valid Minichess move
        - self.move != GAME_START_MOVE or self.is_white_move == True
    """
    move: str
    is_white_move: bool
    # Private Instance Attributes:
    #  - _subtrees:
    #      the subtrees of this tree, which represent the game trees after a possible
    #      move by the current player
    _subtrees: list[GameTree]
    def __init__(self, move: str = GAME_START_MOVE,
                 is_white_move: bool = True) -> None:
        """Initialize a new game tree.
        Note that this initializer uses optional arguments, as illustrated below.
        >>> game = GameTree()
        >>> game.move == GAME_START_MOVE
        True
        >>> game.is_white_move
        True
        """
        self.move = move
        self.is_white_move = is_white_move
        self._subtrees = []
    def get_subtrees(self) -> list[GameTree]:
        """Return the subtrees of this game tree."""
        return self._subtrees
    def find_subtree_by_move(self, move: str) -> Optional[GameTree]:
        """Return the subtree corresponding to the given move.
        Return None if no subtree corresponds to that move.
        """
        for subtree in self._subtrees:
            if subtree.move == move:
                return subtree
        return None
    def add_subtree(self, subtree: GameTree) -> None:
        """Add a subtree to this game tree."""
        self._subtrees.append(subtree)
    def __str__(self) -> str:
        """Return a string representation of this tree.
        """
        return self._str_indented(0)
    def _str_indented(self, depth: int) -> str:
        """Return an indented string representation of this tree.
        The indentation level is specified by the <depth> parameter.
        """
        if self.is_white_move:
            turn_desc = "White's move"
        else:
            turn_desc = "Black's move"
        move_desc = f'{self.move} -> {turn_desc}\n'
        s = '  ' * depth + move_desc
        if self._subtrees == []:
            return s
        else:
            for subtree in self._subtrees:
                s += subtree._str_indented(depth + 1)
            return s
    ############################################################################
    # Part 1: Loading and "Replaying" Minichess games
    ############################################################################
    def insert_move_sequence(self, moves: list[str]) -> None:
        """Insert the given sequence of moves into this tree.
        The inserted moves form a chain of descendants, where:
            - moves[0] is a child of this tree's root
            - moves[1] is a child of moves[0]
            - moves[2] is a child of moves[1]
            - etc.
        Do not create duplicate moves that share the same parent; for example, if moves[0] is
        already a child of this tree's root, you should recurse into that existing subtree rather
        than create a new subtree with moves[0].
        But if moves[0] is not a child of this tree's root, create a new subtree for it
        and append it to the existing list of subtrees.
        Implementation Notes:
            - Your implementation must use recursion, and NOT use any loops to "go down" the tree.
            - Your implementation must have a worst-case running time of Theta(m + n) time,
              where m is the length of moves and n is the size of this tree.
              This means you shouldn't use list slicing to access the "rest" of the list of moves,
              like in Tutorial 4. Instead, you can use one of the following approaches:
              i) Use a recursive helper method that takes an extra "current index" argument to
                 keep track of the next move in the list.
              ii) First reverse the list, and then use a recursive helper method that calls
                 `list.pop` on the list of moves. Just make sure the original list isn't changed
                 when the function ends!
        """
    ############################################################################
    # Part 2: Complete Game Trees and Win Probabilities
    ############################################################################
    def _update_white_win_probability(self) -> None:
        """Recalculate the white win probability of this tree.
        Note: like the "_length" Tree attribute from tutorial, you should only need
        to update self here, not any of its subtrees. (You should *assume* that each
        subtree has the correct white win probability already.)
        Use the following definition for the white win probability of self:
            - if self is a leaf, don't change the white win probability
              (leave the current value alone)
            - if self is not a leaf and self.is_white_move is True, the white win probability
              is equal to the MAXIMUM of the white win probabilities of its subtrees
            - if self is not a leaf and self.is_white_move is False, the white win probability
              is equal to the AVERAGE of the white win probabilities of its subtrees
        """
 if __name__ == '__main__':
    import python_ta.contracts
    python_ta.contracts.check_all_contracts()
    import doctest
    doctest.testmod()
    import python_ta
    python_ta.check_all(config={
        'max-line-length': 100,
        'disable': ['E1136'],
    })
@@ -0,0 +1,483 @@
 """CSC111 Winter 2021 Assignment 2: Trees, Chess, and Artificial Intelligence (Minichess Library)
 Module Description
 ==================
 This module contains a collection of Python classes and functions that you'll use on
 this assignment to represent games of Minichess. You are responsible for reading the
 *docstrings* of this file to understand how to use these classes and functions,
 but should not modify anything in this file. It will not be submitted, and we will
 supply our own copy for grading purposes.
 Note: as is standard for CSC111, we use a leading underscore to indicate private
 functions, methods, and instance attributes. You don't have to worry about any of these,
 and in fact shouldn't use them in this assignment!
 Disclaimer: we didn't have time to make this file fully PythonTA-compliant!
 Copyright and Usage Information
 ===============================
 This file is provided solely for the personal and private use of students
 taking CSC111 at the University of Toronto St. George campus. All forms of
 distribution of this code, whether as given or with any changes, are
 expressly prohibited. For more information on copyright for CSC111 materials,
 please consult our Course Syllabus.
 This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
 """
 from __future__ import annotations
 import copy
 import random
 import time
 from typing import Optional
 import plotly.graph_objects as go
 from plotly.subplots import make_subplots
 import chessboard.display as display
 ################################################################################
 # Representing Minichess
 ################################################################################
 _FILE_TO_INDEX = {'a': 0, 'b': 1, 'c': 2, 'd': 3}
 _INDEX_TO_FILE = {i: f for f, i in _FILE_TO_INDEX.items()}
 _RANK_TO_INDEX = {'1': 0, '2': 1, '3': 2, '4': 3}
 _INDEX_TO_RANK = {i: r for r, i in _RANK_TO_INDEX.items()}
 _MAX_MOVES = 50
 class MinichessGame:
    """A class representing a state of a game of Minichess.
    >>> game = MinichessGame()
    >>> # Get all valid moves for white at the start of the game.
    >>> game.get_valid_moves()
    ['a2b3', 'b2c3', 'b2a3', 'c2d3', 'c2b3', 'd2c3']
    >>> # Make a move. This method mutates the state of the game.
    >>> game.make_move('a2b3')
    >>> game.get_valid_moves()  # Now, black only has one valid move
    ['b4b3']
    >>> # If you try to make an invalid move, a ValueError is raised.
    >>> game.make_move('a4d1')
    Traceback (most recent call last):
    ValueError: Move "a4d1" is not valid
    >>> # This move is okay.
    >>> game.make_move('b4b3')
    >>> game.get_url()
    'https://lichess.org/analysis/standard/8/8/8/8/r1kr4/pqpp4/1PPP4/RQKR4'
    """
    # Private Instance Attributes:
    #   - _board: a two-dimensional representation of a Minichess board
    #   - _valid_moves: a list of the valid moves of the current player
    #   - _is_white_active: a boolean representing whether white is the current player
    #   - _move_count: the number of moves that have been made in the current game
    _board: list[list[Optional[_Piece]]]
    _valid_moves: list[str]
    _is_white_active: bool
    _move_count: int
    def __init__(self, board: list[list[Optional[_Piece]]] = None,
                 white_active: bool = True, move_count: int = 0) -> None:
        if board is not None:
            self._board = board
        else:
            self._board = [
                [_Piece('r', True), _Piece('q', True), _Piece('k', True), _Piece('r', True)],
                [_Piece('p', True), _Piece('p', True), _Piece('p', True), _Piece('p', True)],
                [_Piece('p', False), _Piece('p', False), _Piece('p', False), _Piece('p', False)],
                [_Piece('r', False), _Piece('q', False), _Piece('k', False), _Piece('r', False)]
            ]
        self._is_white_active = white_active
        self._move_count = move_count
        self._valid_moves = []
        self._recalculate_valid_moves()
    def get_valid_moves(self) -> list[str]:
        """Return a list of the valid moves for the active player."""
        return self._valid_moves
    def make_move(self, move: str) -> None:
        """Make the given chess move. This instance of Minichess will be mutated, and will
        afterwards represent the game state after move is made.
        If move is not a currently valid move, raise a ValueError.
        """
        if move not in self._valid_moves:
            raise ValueError(f'Move "{move}" is not valid')
        self._board = self._board_after_move(move)
        self._is_white_active = not self._is_white_active
        self._move_count += 1
        self._recalculate_valid_moves()
    def copy_and_make_move(self, move: str) -> MinichessGame:
        """Make the given chess move in a copy of this MinichessGame, and return that copy.
        If move is not a currently valid move, raise a ValueError.
        """
        if move not in self._valid_moves:
            raise ValueError(f'Move "{move}" is not valid')
        return MinichessGame(board=self._board_after_move(move),
                             white_active=not self._is_white_active,
                             move_count=self._move_count + 1)
    def is_white_move(self) -> bool:
        """Return whether the white player is to move next."""
        return self._is_white_active
    def get_winner(self) -> Optional[str]:
        """Return the winner of the game (black or white) or 'draw' if the game ended in a draw.
        Return None if the game is not over.
        """
        if self._move_count >= _MAX_MOVES:
            return 'Draw'
        elif len(self._valid_moves) == 0:
            return 'Black' if self._is_white_active else 'White'
        else:
            return None
    def _calculate_moves_for_board(self, board: list[list[Optional[_Piece]]],
                                   is_white_active: bool) -> tuple:
        """Return all possible moves on a given board with a given active player."""
        moves = []
        # Used to calculate whether the other players' king is in check
        # (i.e. the black king if is_white_active, otherwise the white king)
        check = []
        for pos in [(y, x) for y in range(0, 4) for x in range(0, 4)]:
            piece = board[pos[0]][pos[1]]
            if piece is None or piece.is_white != is_white_active:
                continue
            kind, is_white = piece.kind, piece.is_white
            if kind == 'p':
                # Pawns can only move towards the opponent's end of the board.
                direction = 1 if is_white else -1
                check += self._find_moves_in_direction(board, moves, pos, is_white, (direction, 0),
                                                       limit=1, capture=False)
                check += self._find_moves_in_direction(board, moves, pos, is_white, (direction, 1),
                                                       limit=1, capture=True)
                check += self._find_moves_in_direction(board, moves, pos, is_white, (direction, -1),
                                                       limit=1, capture=True)
            if kind == 'r' or kind == 'q':
                check += self._find_moves_in_direction(board, moves, pos, is_white, (0, 1))
                check += self._find_moves_in_direction(board, moves, pos, is_white, (1, 0))
                check += self._find_moves_in_direction(board, moves, pos, is_white, (0, -1))
                check += self._find_moves_in_direction(board, moves, pos, is_white, (-1, 0))
            if kind == 'q':
                for y, x in [(y, x) for y in [-1, 1] for x in [-1, 1]]:
                    check += self._find_moves_in_direction(board, moves, pos, is_white, (y, x))
            if kind == 'k':
                for y, x in [(y, x) for y in [-1, 0, 1] for x in [-1, 0, 1]]:
                    check += self._find_moves_in_direction(board, moves, pos, is_white, (y, x),
                                                           limit=1)
        return moves, check
    def _find_moves_in_direction(self, board, moves, pos, is_white, direction, limit=None,
                                 capture=None):
        """Find valid moves moving in a given direction from a certain position.
        capture: True if must capture, False if must not capture, None otherwise.
        """
        move_start = _index_to_algebraic(pos)
        stop = False
        i = 1
        check = []
        while not stop:
            y, x = pos[0] + direction[0] * i, pos[1] + direction[1] * i
            if x < 0 or y < 0 or x > 3 or y > 3:
                break  # Out of bounds
            contents = board[y][x]
            move = move_start + _index_to_algebraic((y, x))
            if contents is not None:
                # Square contains piece
                stop = True
                if contents.is_white != is_white and contents.kind == 'k' \
                        and capture is not False:
                    # Cannot capture king, but they are in check
                    check.append(move)
                elif contents.is_white != is_white and capture is not False:
                    # Capture
                    moves.append(move)
            else:
                # Empty square
                if capture is not True:
                    moves.append(move)
            i += 1
            if limit is not None and i > limit:
                stop = True
        return check
    def _board_after_move(self, move: str) -> list[list[Optional[_Piece]]]:
        """Return a copy of self._board representing the state of the board after making move.
        """
        board_copy = copy.deepcopy(self._board)
        start_pos = _algebraic_to_index(move[0:2])
        end_pos = _algebraic_to_index(move[2:])
        board_copy[end_pos[0]][end_pos[1]] = board_copy[start_pos[0]][start_pos[1]]
        board_copy[start_pos[0]][start_pos[1]] = None
        return board_copy
    def _recalculate_valid_moves(self) -> None:
        """Update the valid moves for this game board."""
        moves, check = self._calculate_moves_for_board(self._board, self._is_white_active)
        assert len(check) == 0, \
            "The other player's king can never be in check at the start of your turn."
        # Filter moves that would leave the current player's king in check
        valid_moves = []
        for move in moves:
            board_copy = self._board_after_move(move)
            _, check = self._calculate_moves_for_board(board_copy, not self._is_white_active)
            if len(check) == 0:
                valid_moves.append(move)
        self._valid_moves = valid_moves
    def get_fen(self) -> str:
        """Return a string description of the current game state in Forsyth-Edwards Notation.
        Reference: https://en.wikipedia.org/wiki/Forsyth%E2%80%93Edwards_Notation.
        This method is used to visualize the game board using Pygame---you won't need to call it
        directly.
        """
        rows = [''.join([(p.fen() if p is not None else '1') for p in row]) + '4' for row in
                self._board]
        return '/'.join(reversed(rows))
    def get_url(self) -> str:
        """Return a URL to a web page where you can examine the current state of the board."""
        return "https://lichess.org/analysis/standard/8/8/8/8/" + self.get_fen()
 def _algebraic_to_index(move: str) -> tuple[int, int]:
    """Convert coordinates in algebraic format ex. 'a2' to array indices (y, x)."""
    return (_RANK_TO_INDEX[move[1]], _FILE_TO_INDEX[move[0]])
 def _index_to_algebraic(pos: tuple[int, int]) -> str:
    """Convert coordinates in array indices (y, x) to algebraic format."""
    return _INDEX_TO_FILE[pos[1]] + _INDEX_TO_RANK[pos[0]]
 class _Piece:
    """Represents a single piece in Minichess.
    Instance Attributes:
        - kind: the type of piece
        - is_white: whether the piece belongs to the white player
    """
    kind: str  # One of 'rqkp' (rook, queen, king, pawn)
    is_white: bool
    def __init__(self, kind: str, is_white: bool) -> None:
        """Initialize a new piece."""
        self.kind = kind
        self.is_white = is_white
    def fen(self) -> str:
        """Return the string representing this piece in FEN."""
        if self.is_white:
            return self.kind.upper()
        else:
            return self.kind
    def __str__(self) -> str:
        return self.fen()
 ################################################################################
 # Chess player classes
 ################################################################################
 class Player:
    """An abstract class representing a Minichess AI.
    This class can be subclassed to implement different strategies for playing chess.
    """
    def make_move(self, game: MinichessGame, previous_move: Optional[str]) -> str:
        """Make a move given the current game.
        previous_move is the opponent player's most recent move, or None if no moves
        have been made.
        Preconditions:
            - There is at least one valid move for the given game
        """
        raise NotImplementedError
 class RandomPlayer(Player):
    """A Minichess AI whose strategy is always picking a random move."""
    def make_move(self, game: MinichessGame, previous_move: Optional[str]) -> str:
        """Make a move given the current game.
        previous_move is the opponent player's most recent move, or None if no moves
        have been made.
        Preconditions:
            - There is at least one valid move for the given game
        """
        possible_moves = game.get_valid_moves()
        return random.choice(possible_moves)
 ################################################################################
 # Functions for running games
 ################################################################################
 DEFAULT_FPS = 6  # Default number of moves per second to display in the visualization
 def run_games(n: int, white: Player, black: Player,
              visualize: bool = False, fps: int = DEFAULT_FPS,
              show_stats: bool = False) -> None:
    """Run n games using the given Players.
    Optional arguments:
        - visualize: whether to use Pygame to visualize the games
        - fps: the number of moves per second to display (only relevant if visualize is True)
        - show_stats: whether to use Plotly to display statistics for the game runs
    Preconditions:
        - n >= 1
        - fps >= 1
    """
    if visualize:
        _initialize_display()
    stats = {'White': 0, 'Black': 0, 'Draw': 0}
    results = []
    for i in range(0, n):
        white_copy = copy.deepcopy(white)
        black_copy = copy.deepcopy(black)
        winner, _ = run_game(white_copy, black_copy, visualize, fps)
        stats[winner] += 1
        results.append(winner)
        print(f'Game {i} winner: {winner}')
    for outcome in stats:
        print(f'{outcome}: {stats[outcome]}/{n} ({100.0 * stats[outcome] / n:.2f}%)')
    if visualize:
        _terminate_display()
    if show_stats:
        plot_game_statistics(results)
 def run_game(white: Player, black: Player,
             visualize: bool = False, fps: int = DEFAULT_FPS) -> tuple[str, list[str]]:
    """Run a Minichess game between the two given players.
    Return the winner and list of moves made in the game.
    """
    game = MinichessGame()
    move_sequence = []
    previous_move = None
    current_player = white
    while game.get_winner() is None:
        previous_move = current_player.make_move(game, previous_move)
        game.make_move(previous_move)
        move_sequence.append(previous_move)
        if visualize:
            display.update(game.get_fen(), game.get_winner())
            time.sleep(1 / fps)
        if current_player is white:
            current_player = black
        else:
            current_player = white
    if visualize:
        # Give slightly more time to the victory visualization
        time.sleep(4 / fps)
    return game.get_winner(), move_sequence
 def _initialize_display() -> None:
    """Initialize the Minichess visualization pygame window."""
    display.start('8/8/8/8', size=4)
 def _terminate_display() -> None:
    """Close the Minichess visualization pygame window."""
    display.terminate()
 def plot_game_statistics(results: list[str]) -> None:
    """Plot the outcomes and win probabilities for a given list of Minichess game results.
    Preconditions:
        - all(r in {'White', 'Black', 'Draw'} for r in results)
    """
    outcomes = [1 if result == 'White' else 0 for result in results]
    cumulative_win_probability = [sum(outcomes[0:i]) / i for i in range(1, len(outcomes) + 1)]
    rolling_win_probability = \
        [sum(outcomes[max(i - 50, 0):i]) / min(50, i) for i in range(1, len(outcomes) + 1)]
    fig = make_subplots(rows=2, cols=1)
    fig.add_trace(go.Scatter(y=outcomes, mode='markers',
                             name='Outcome (1 = White win, 0 = Draw/Black win)'),
                  row=1, col=1)
    fig.add_trace(go.Scatter(y=cumulative_win_probability, mode='lines',
                             name='White win percentage (cumulative)'),
                  row=2, col=1)
    fig.add_trace(go.Scatter(y=rolling_win_probability, mode='lines',
                             name='White win percentage (most recent 50 games)'),
                  row=2, col=1)
    fig.update_yaxes(range=[0.0, 1.0], row=2, col=1)
    fig.update_layout(title='Minichess Game Results', xaxis_title='Game')
    fig.show()
    # fig.write_image('stats.png')
 if __name__ == '__main__':
    import doctest
    doctest.testmod()
    # Demo running Minichess games being played between two random players
    # run_games(100, RandomPlayer(), RandomPlayer(), show_stats=True)
    # Try running this to visualize games (takes longer)
    # run_games(20, RandomPlayer(), RandomPlayer(), visualize=True, fps=10, show_stats=True)
@@ -0,0 +1,43 @@
 """CSC111 Winter 2021 Assignment 2: Trees, Chess, and Artificial Intelligence (Part 0)
 Module Description
 ===============================
 This Python module contains a sample GameTree that matches an example from the assignment
 handout. Please feel free to modify this file to experiment with the code found in
 a2_game_tree.py and a2_minichess.py. You won't be submitting this file for grading (nor
 will this file affect other parts of this assignment).
 Copyright and Usage Information
 ===============================
 This file is provided solely for the personal and private use of students
 taking CSC111 at the University of Toronto St. George campus. All forms of
 distribution of this code, whether as given or with any changes, are
 expressly prohibited. For more information on copyright for CSC111 materials,
 please consult our Course Syllabus.
 This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
 """
 from a2_game_tree import GameTree, GAME_START_MOVE
 def build_sample_game_tree() -> GameTree:
    """Create an example game tree."""
    game_tree = GameTree(GAME_START_MOVE, True)
    game_tree.add_subtree(GameTree('a2b3', False))
    game_tree.add_subtree(GameTree('b2c3', False))
    game_tree.add_subtree(GameTree('b2a3', False))
    sub1 = GameTree('c2d3', False)
    sub2 = GameTree('d4d3', True)
    sub2.add_subtree(GameTree('d2c3', False))
    sub2.add_subtree(GameTree('b1d3', False))
    sub1.add_subtree(sub2)
    game_tree.add_subtree(sub1)
    game_tree.add_subtree(GameTree('c2b3', False))
    game_tree.add_subtree(GameTree('d2c3', False))
    return game_tree
@@ -0,0 +1,112 @@
 """CSC111 Winter 2021 Assignment 2: Trees, Chess, and Artificial Intelligence (Part 1)
 Instructions (READ THIS FIRST!)
 ===============================
 This Python module contains the start of functions and/or classes you'll define
 for Part 1 of this assignment. Please note that in addition to this file, you will
 also need to modify a2_game_tree.py by following the instructions on the assignment
 handout. You should NOT make any changes to a2_minichess.py.
 Copyright and Usage Information
 ===============================
 This file is provided solely for the personal and private use of students
 taking CSC111 at the University of Toronto St. George campus. All forms of
 distribution of this code, whether as given or with any changes, are
 expressly prohibited. For more information on copyright for CSC111 materials,
 please consult our Course Syllabus.
 This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
 """
 import csv
 import random
 from typing import Optional
 import a2_game_tree
 import a2_minichess
 ################################################################################
 # Loading Minichess datasets
 ################################################################################
 def load_game_tree(games_file: str) -> a2_game_tree.GameTree:
    """Create a game tree based on games_file.
    Preconditions:
        - games_file refers to a csv file in the format described on the assignment handout
    Implementation hints:
        - You can review Tutorial 4 for how we read CSV files in Python.
    """
 ################################################################################
 # Minichess AI that uses a GameTree
 ################################################################################
 class RandomTreePlayer(a2_minichess.Player):
    """A Minichess player that plays randomly based on a given GameTree.
    This player uses a game tree to make moves, descending into the tree as the game is played.
    On its turn:
        1. First it updates its game tree to its subtree corresponding to the move made by
           its opponent. If no subtree is found, its game tree is set to None.
        2. Then, if its game tree is not None, it picks its next move randomly from among
           the subtrees of its game tree, and then reassigns its game tree to that subtree.
           But if its game tree is None or has no subtrees, the player picks its next move randomly,
           and then sets its game tree to None.
    """
    # Private Instance Attributes:
    #   - _game_tree:
    #       The GameTree that this player uses to make its moves. If None, then this
    #       player just makes random moves.
    _game_tree: Optional[a2_game_tree.GameTree]
    def __init__(self, game_tree: a2_game_tree.GameTree) -> None:
        """Initialize this player.
        Preconditions:
            - game_tree represents a game tree at the initial state (root is '*')
        """
        self._game_tree = game_tree
    def make_move(self, game: a2_minichess.MinichessGame, previous_move: Optional[str]) -> str:
        """Make a move given the current game.
        previous_move is the opponent player's most recent move, or None if no moves
        have been made.
        Preconditions:
            - There is at least one valid move for the given game
        """
 def part1_runner(games_file: str, n: int, black_random: bool) -> None:
    """Create a game tree from the given file, and run n games where White is a RandomTreePlayer.
    The White player is a RandomTreePlayer whose game tree is the one generated from games_file.
    The Black player is a RandomPlayer if black_random is True, otherwise it is a RandomTreePlayer
    using the SAME game tree as White.
    Preconditions:
        - n >= 1
        - games_file refers to a csv file in the format described on the assignment handout
    Implementation notes:
        - Your implementation MUST correctly call a2_minichess.run_games. You may choose
          the values for the optional arguments passed to the function.
    """
 if __name__ == '__main__':
    import python_ta
    python_ta.check_all(config={
        'max-line-length': 100,
        'disable': ['E1136'],
        'extra-imports': ['a2_minichess', 'a2_game_tree', 'random', 'csv'],
        'allowed-io': ['load_game_tree']
    })
    # Sample call to part1_runner (you can change this, just keep it in the main block!)
    # part1_runner('data/white_wins.csv', 50, True)
@@ -0,0 +1,119 @@
 """CSC111 Winter 2021 Assignment 2: Trees, Chess, and Artificial Intelligence (Part 2)
 Instructions (READ THIS FIRST!)
 ===============================
 This Python module contains the start of functions and/or classes you'll define
 for Part 2 of this assignment. Please note that in addition to this file, you will
 also need to modify a2_game_tree.py by following the instructions on the assignment
 handout. You should NOT make any changes to a2_minichess.py.
 Copyright and Usage Information
 ===============================
 This file is provided solely for the personal and private use of students
 taking CSC111 at the University of Toronto St. George campus. All forms of
 distribution of this code, whether as given or with any changes, are
 expressly prohibited. For more information on copyright for CSC111 materials,
 please consult our Course Syllabus.
 This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
 """
 import random
 from typing import Optional
 import a2_game_tree
 import a2_minichess
 def generate_complete_game_tree(root_move: str, game_state: a2_minichess.MinichessGame,
                                d: int) -> a2_game_tree.GameTree:
    """Generate a complete game tree of depth d for all valid moves from the current game_state.
    For the returned GameTree:
        - Its root move is root_move.
        - Its `is_white_move` attribute is set using the current game_state.
        - It contains all possible move sequences of length <= d from game_state.
          For each node in the tree, its subtrees appear in the same order that their
          moves were returned by game_state.get_valid_moves(),
        - If d == 0, a size-one GameTree is returned.
    Note that some paths down the tree may have length < d, because they result in an end state
    (win or draw) from game_state in fewer than d moves.
    Preconditions:
        - d >= 0
        - root_move == GAME_START_MOVE or root_move is a valid chess move
        - if root_move == GAME_START_MOVE, then game_state is in the initial game state
    Implementation hints:
        - This function must be implemented recursively.
        - In the recursive step, use the MinichessGame.copy_and_make_move method to create
          a copy of the game state with one new move made.
        - You'll need to review the public interface of the MinichessGame class to see what
          methods are available to help implement this function.
    WARNING: we recommend not calling this function with depth greater than 6, as this will
    likely take a very long time on your computer.
    """
 class GreedyTreePlayer(a2_minichess.Player):
    """A Minichess player that plays greedily based on a given GameTree.
    See assignment handout for description of its strategy.
    """
    # Private Instance Attributes:
    #   - _game_tree:
    #       The GameTree that this player uses to make its moves. If None, then this
    #       player just makes random moves.
    _game_tree: Optional[a2_game_tree.GameTree]
    def __init__(self, game_tree: a2_game_tree.GameTree) -> None:
        """Initialize this player.
        Preconditions:
            - game_tree represents a game tree at the initial state (root is '*')
        """
        self._game_tree = game_tree
    def make_move(self, game: a2_minichess.MinichessGame, previous_move: Optional[str]) -> str:
        """Make a move given the current game.
        previous_move is the opponent player's most recent move, or None if no moves
        have been made.
        Preconditions:
            - There is at least one valid move for the given game
        """
 def part2_runner(d: int, n: int, white_greedy: bool) -> None:
    """Create a complete game tree with the given depth, and run n games where
    one player is a GreedyTreePlayer and the other is a RandomPlayer.
    The GreedyTreePlayer uses the complete game tree with the given depth.
    If white_greedy is True, the White player is the GreedyTreePlayer and Black is a RandomPlayer.
    This is switched when white_greedy is False.
    Precondtions:
        - d >= 0
        - n >= 1
    Implementation notes:
        - Your implementation MUST correctly call a2_minichess.run_games. You may choose
          the values for the optional arguments passed to the function.
    """
 if __name__ == '__main__':
    import python_ta
    python_ta.check_all(config={
        'max-line-length': 100,
        'max-nested-blocks': 4,
        'disable': ['E1136'],
        'extra-imports': ['random', 'a2_minichess', 'a2_game_tree']
    })
    # Sample call to part2_runner (you can change this, just keep it in the main block!)
    # part2_runner(5, 50, False)
@@ -0,0 +1,120 @@
 """CSC111 Winter 2021 Assignment 2: Trees, Chess, and Artificial Intelligence (Part 3)
 Instructions (READ THIS FIRST!)
 ===============================
 This Python module contains the start of functions and/or classes you'll define
 for Part 3 of this assignment. You should NOT make any changes to a2_minichess.py.
 Copyright and Usage Information
 ===============================
 This file is provided solely for the personal and private use of students
 taking CSC111 at the University of Toronto St. George campus. All forms of
 distribution of this code, whether as given or with any changes, are
 expressly prohibited. For more information on copyright for CSC111 materials,
 please consult our Course Syllabus.
 This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
 """
 import random
 from typing import Optional
 import a2_game_tree
 import a2_minichess
 class ExploringPlayer(a2_minichess.Player):
    """A Minichess player that plays greedily some of the time, and randomly some of the time.
    See assignment handout for details.
    """
    # Private Instance Attributes:
    #   - _game_tree:
    #       The GameTree that this player uses to make its moves. If None, then this
    #       player just makes random moves.
    _game_tree: Optional[a2_game_tree.GameTree]
    _exploration_probability: float
    def __init__(self, game_tree: a2_game_tree.GameTree, exploration_probability: float) -> None:
        """Initialize this player."""
        self._game_tree = game_tree
        self._exploration_probability = exploration_probability
    def make_move(self, game: a2_minichess.MinichessGame, previous_move: Optional[str]) -> str:
        """Make a move given the current game.
        previous_move is the opponent player's most recent move, or None if no moves
        have been made.
        Preconditions:
            - There is at least one valid move for the given game
        """
 def run_learning_algorithm(exploration_probabilities: list[float],
                           show_stats: bool = True) -> a2_game_tree.GameTree:
    """Play a sequence of Minichess games using an ExploringPlayer as the White player.
    This algorithm first initializes an empty GameTree. All ExploringPlayers will use this
    SAME GameTree object, which will be mutated over the course of the algorithm!
    Return this object.
    There are len(exploration_probabilities) games played, where at game i (starting at 0):
        - White is an ExploringPlayer (using the game tree) whose exploration probability
            is equal to exploration_probabilities[i]
        - Black is a RandomPlayer
        - AFTER the game, the move sequence from the game is inserted into the game tree,
          with a white win probability of 1.0 if White won the game, and 0.0 otherwise.
    Implementation note:
        - A NEW ExploringPlayer instance should be created for each loop iteration.
          However, each one should use the SAME GameTree object.
        - You should call run_game, NOT run_games, from a2_minichess. This is because you
          need more control over what happens after each game runs, which you can get by
          writing your own loop that calls run_game. However, you can base your loop on
          the implementation of run_games.
        - Note that run_game from a2_minichess returns both the winner and the move sequence
          after the game ends.
        - You may call print in this function to report progress made in each game.
        - Note that this function returns the final GameTree object. You can inspect the
          white_win_probability of its nodes, calculate its size, or and use it in a
          RandomTreePlayer or GreedyTreePlayer to see how they do with it.
    """
    # Start with a GameTree in the initial state
    game_tree = a2_game_tree.GameTree()
    # Play games using the ExploringPlayer and update the GameTree after each one
    results_so_far = []
    # Write your loop here, according to the description above.
    if show_stats:
        a2_minichess.plot_game_statistics(results_so_far)
    return game_tree
 def part3_runner() -> a2_game_tree.GameTree:
    """Run example for Part 3.
    Please note that unlike part1_runner and part2_runner, this function is NOT graded.
    We encourage you to experiment with different exploration probability sequences
    to see how quickly you can develop a "winning" GameTree!
    """
    probabilities = [0.0] * 700
    return run_learning_algorithm(probabilities)
 if __name__ == '__main__':
    import python_ta
    python_ta.check_all(config={
        'max-line-length': 100,
        'max-nested-blocks': 4,
        'disable': ['E1136'],
        'extra-imports': ['random', 'a2_minichess', 'a2_game_tree'],
        'allowed-io': ['run_learning_algorithm']
    })
    part3_runner()
@@ -0,0 +1,2 @@
 *.pyc
 __pycache__/
@@ -0,0 +1,674 @@
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 Also add information on how to contact you by electronic and paper mail.
  If the program does terminal interaction, make it output a short
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 The hypothetical commands `show w' and `show c' should show the appropriate
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  You should also get your employer (if you work as a programmer) or school,
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  The GNU General Public License does not permit incorporating your program
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@@ -0,0 +1,76 @@
 # chess-board
 ## What is chess-board?
 chess-board is a Python chessboard package with a flexible "just a board" API for graphically representing game positions.
 ## What chess-board is **not**
 - A chess engine
 - A legal move validator
 - A PGN parser
 While chess-board is designed to work well with any of these, the idea behind chess-board is that the logic that controls the board should be independent of those other problems.
 ## Usage
 **test.py** - _example_
 ```sh
 from chessboard import display
 position = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkq - 1 2'
 while True:
    display.start(position)
 ```
 ## Entry Points
 ```sh
 from chessboard import display
 validfen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkq - 1 2'
 # Initialization
 display.start()
 # Position change/update
 display.update(validfen)
 # Checking GUI window for QUIT event. (Esc or GUI CANCEL)
 display.checkForQuit()
 # Close window
 display.terminate()
 ```
 ## Installation
 Download and install the latest release:
 ```sh
 # install into virtualenv
 pip install chess-board
 or 
 # install with pipenv
 pipenv install chess-board
 or
 # install system-wide (windows), run cmd[powershell] as administrator
 pip install chess-board
 ```
 Alternatively, you could **git clone** this repo and add the directory to your package.
 ```sh
 git clone https://github.com/ahira-justice/chess-board.git
 ```
 ## Dependencies
 ```sh
 pygame
 ```
 **chess-board** installation automatically installs latest **pygame** version.
 ## License
 [GNU GENERAL PUBLIC LICENSE](LICENSE)
@@ -0,0 +1,208 @@
 """
    Ahira Justice, ADEFOKUN
    justiceahira@gmail.com
 """
 import os
 import pygame
 from . import pieces
 from . import fenparser
 BASE_DIR = os.path.dirname(os.path.abspath(__file__))
 IMAGE_DIR = os.path.join(BASE_DIR, 'images')
 class Board:
    btile = pygame.image.load(os.path.join(IMAGE_DIR, 'btile.png'))
    wtile = pygame.image.load(os.path.join(IMAGE_DIR, 'wtile.png'))
    def __init__(self, colors, BGCOLOR, DISPLAYSURF, size=8):
        self.colors = colors
        self.BGCOLOR = BGCOLOR
        self.DISPLAYSURF = DISPLAYSURF
        self.font = pygame.font.Font(pygame.font.get_default_font(), 24)
        self.pieceRect = []
        self.boardRect, self.tile_size = self._generate_board_rect(size)
    def _generate_board_rect(self, size):
        start = 100
        end = 500
        stride = (end - start) // size
        board_rect = []
        for column in range(0, size):
            board_rect.append(tuple([(start + row * stride, start + column * stride) for row in range(0, size)]))
        return board_rect, stride
    def displayBoard(self):
        self.DISPLAYSURF.fill(self.BGCOLOR)
        pygame.draw.rect(self.DISPLAYSURF, self.colors['Black'], (95, 95, 410, 410), 10)
        self.drawTiles()
    def drawTiles(self):
        wtile = pygame.transform.scale(Board.wtile, (self.tile_size, self.tile_size))
        btile = pygame.transform.scale(Board.btile, (self.tile_size, self.tile_size))
        for i in range(1, len(self.boardRect)+1):
            for j in range(1, len(self.boardRect[i-1])+1):
                if self.isOdd(i):
                    if self.isOdd(j):
                        self.DISPLAYSURF.blit(wtile, self.boardRect[i-1][j-1])
                    elif self.isEven(j):
                        self.DISPLAYSURF.blit(btile, self.boardRect[i-1][j-1])
                elif self.isEven(i):
                    if self.isOdd(j):
                        self.DISPLAYSURF.blit(btile, self.boardRect[i-1][j-1])
                    elif self.isEven(j):
                        self.DISPLAYSURF.blit(wtile, self.boardRect[i-1][j-1])
        # draw letters
        files = 'abcdefgh'
        ranks = '12345678'
        size = len(self.boardRect)
        for i in range(0, len(self.boardRect)):
            text_surface = self.font.render(ranks[size - i - 1], True, (200, 200, 200))
            rect = self.boardRect[i][-1]
            rect = (rect[0] + self.tile_size + 20, rect[1] + 40)
            self.DISPLAYSURF.blit(text_surface, dest=rect)
        for i in range(0, len(self.boardRect)):
            text_surface = self.font.render(files[i], True, (200, 200, 200))
            rect = self.boardRect[-1][i]
            rect = (rect[0] + 40, rect[1] + self.tile_size + 15)
            self.DISPLAYSURF.blit(text_surface, dest=rect)
    def isOdd(self, number):
        if number % 2 == 1:
            return True
    def isEven(self, number):
        if number % 2 == 0:
            return True
    def drawPieces(self):
        self.mapPieces()
        for piece in self.pieceRect:
            piece.displayPiece()
    def mapPieces(self):
        for i in range(len(Board.posb)):
            if i in [0, 1, 2, 3, 4, 5, 6, 7]:
                piece = self.createPiece(pieces.BLACK, pieces.PAWN, Board.posb[i])
                self.pieceRect.append(piece)
            elif i in [8, 15]:
                piece = self.createPiece(pieces.BLACK, pieces.ROOK, Board.posb[i])
                self.pieceRect.append(piece)
            elif i in [9, 14]:
                piece = self.createPiece(pieces.BLACK, pieces.KNGHT, Board.posb[i])
                self.pieceRect.append(piece)
            elif i in [10, 13]:
                piece = self.createPiece(pieces.BLACK, pieces.BISHOP, Board.posb[i])
                self.pieceRect.append(piece)
            elif i in [11]:
                piece = self.createPiece(pieces.BLACK, pieces.QUEEN, Board.posb[i])
                self.pieceRect.append(piece)
            elif i in [12]:
                piece = self.createPiece(pieces.BLACK, pieces.KING, Board.posb[i])
                self.pieceRect.append(piece)
        for i in range(len(Board.posw)):
            if i in [0, 1, 2, 3, 4, 5, 6, 7]:
                piece = self.createPiece(pieces.WHITE, pieces.PAWN, Board.posw[i])
                self.pieceRect.append(piece)
            elif i in [8, 15]:
                piece = self.createPiece(pieces.WHITE, pieces.ROOK, Board.posw[i])
                self.pieceRect.append(piece)
            elif i in [9, 14]:
                piece = self.createPiece(pieces.WHITE, pieces.KNGHT, Board.posw[i])
                self.pieceRect.append(piece)
            elif i in [10, 13]:
                piece = self.createPiece(pieces.WHITE, pieces.BISHOP, Board.posw[i])
                self.pieceRect.append(piece)
            elif i in [11]:
                piece = self.createPiece(pieces.WHITE, pieces.QUEEN, Board.posw[i])
                self.pieceRect.append(piece)
            elif i in [12]:
                piece = self.createPiece(pieces.WHITE, pieces.KING, Board.posw[i])
                self.pieceRect.append(piece)
    def createPiece(self, color, type, position):
        piece = pieces.Piece(color, type, self.DISPLAYSURF, self.tile_size)
        piece.setPosition(position)
        return piece
    def updatePieces(self, fen):
        self.pieceRect = []
        fp = fenparser.FenParser(fen)
        fenboard = fp.parse()
        for i in range(len(fenboard)):
            for j in range(len(fenboard[i])):
                if fenboard[i][j] in ['b', 'B']:
                    if fenboard[i][j] == 'b':
                        piece = self.createPiece(pieces.BLACK, pieces.BISHOP, self.boardRect[i][j])
                        self.pieceRect.append(piece)
                    elif fenboard[i][j] == 'B':
                        piece = self.createPiece(pieces.WHITE, pieces.BISHOP, self.boardRect[i][j])
                        self.pieceRect.append(piece)
                elif fenboard[i][j] in ['k', 'K']:
                    if fenboard[i][j] == 'k':
                        piece = self.createPiece(pieces.BLACK, pieces.KING, self.boardRect[i][j])
                        self.pieceRect.append(piece)
                    elif fenboard[i][j] == 'K':
                        piece = self.createPiece(pieces.WHITE, pieces.KING, self.boardRect[i][j])
                        self.pieceRect.append(piece)
                elif fenboard[i][j] in ['n', 'N']:
                    if fenboard[i][j] == 'n':
                        piece = self.createPiece(pieces.BLACK, pieces.KNGHT, self.boardRect[i][j])
                        self.pieceRect.append(piece)
                    elif fenboard[i][j] == 'N':
                        piece = self.createPiece(pieces.WHITE, pieces.KNGHT, self.boardRect[i][j])
                        self.pieceRect.append(piece)
                elif fenboard[i][j] in ['p', 'P']:
                    if fenboard[i][j] == 'p':
                        piece = self.createPiece(pieces.BLACK, pieces.PAWN, self.boardRect[i][j])
                        self.pieceRect.append(piece)
                    elif fenboard[i][j] == 'P':
                        piece = self.createPiece(pieces.WHITE, pieces.PAWN, self.boardRect[i][j])
                        self.pieceRect.append(piece)
                elif fenboard[i][j] in ['q', 'Q']:
                    if fenboard[i][j] == 'q':
                        piece = self.createPiece(pieces.BLACK, pieces.QUEEN, self.boardRect[i][j])
                        self.pieceRect.append(piece)
                    elif fenboard[i][j] == 'Q':
                        piece = self.createPiece(pieces.WHITE, pieces.QUEEN, self.boardRect[i][j])
                        self.pieceRect.append(piece)
                elif fenboard[i][j] in ['r', 'R']:
                    if fenboard[i][j] == 'r':
                        piece = self.createPiece(pieces.BLACK, pieces.ROOK, self.boardRect[i][j])
                        self.pieceRect.append(piece)
                    elif fenboard[i][j] == 'R':
                        piece = self.createPiece(pieces.WHITE, pieces.ROOK, self.boardRect[i][j])
                        self.pieceRect.append(piece)
        for piece in self.pieceRect:
            piece.displayPiece()
@@ -0,0 +1,99 @@
 """
    Ahira Justice, ADEFOKUN
    justiceahira@gmail.com
 """
 import os
 import sys
 import pygame
 from pygame.locals import *
 from . import board
 os.environ['SDL_VIDEO_CENTERED'] = '1' # Centre display window.
 FPS = 30
 FPSCLOCK = pygame.time.Clock()
 DISPLAYSURF = None
 BASICFONT = None
 gameboard = None
 colors = {
    'Ash':  ( 50,  50,  50),
    'White':(255, 255, 255),
    'Black':(  0,   0,   0),
 }
 BGCOLOR = colors['Ash']
 WINDOWWIDTH, WINDOWHEIGHT = 600, 600
 BASICFONTSIZE = 30
 def terminate():
    pygame.display.quit()
    # sys.exit()
 def checkForQuit():
    for event in pygame.event.get(QUIT): # get all the QUIT events
        terminate() #terminate if any QUIT events are present
        return
    for event in pygame.event.get(KEYUP): # get all the KEYUP events
        if event.key == K_ESCAPE:
            terminate() # terminate if the KEYUP event was for the Esc key
            return
        pygame.event.post(event) # put the other KEYUP event objects back
    return False
 def start(fen='', size=8):
    global gameboard, font, DISPLAYSURF
    if not pygame.get_init():
        pygame.init()
    # Setting up the GUI window.
    DISPLAYSURF = pygame.display.set_mode((WINDOWWIDTH, WINDOWHEIGHT))
    pygame.display.set_caption('Python Chess')
    font = pygame.font.Font(pygame.font.get_default_font(), 48)
    checkForQuit()
    DISPLAYSURF.fill(BGCOLOR)
    gameboard = board.Board(colors, BGCOLOR, DISPLAYSURF, size=size)
    gameboard.displayBoard()
    if (fen):
        gameboard.updatePieces(fen)
    else:
        gameboard.drawPieces()
    pygame.display.update()
    # FPSCLOCK.tick(FPS)
 def update(fen, winner):
    global font, DISPLAYSURF
    checkForQuit()
    gameboard.displayBoard()
    gameboard.updatePieces(fen)
    if winner is not None:
        if winner == 'White':
            text_surface = font.render('White wins!', True, (50, 168, 82))
        elif winner == 'Draw':
            text_surface = font.render('Draw!', True, (255, 255, 255))
        elif winner == 'Black':
            text_surface = font.render('Black wins!', True, (168, 60, 50))
        DISPLAYSURF.blit(text_surface, dest=(25, 25))
    pygame.display.update()
    # FPSCLOCK.tick(FPS)
@@ -0,0 +1,43 @@
 """
    https://github.com/tlehman/fenparser
 """
 import re
 from itertools import chain
 class FenParser():
  def __init__(self, fen_str):
    self.fen_str = fen_str
  def parse(self):
    ranks = self.fen_str.split(" ")[0].split("/")
    pieces_on_all_ranks = [self.parse_rank(rank) for rank in ranks]
    return pieces_on_all_ranks
  def parse_rank(self, rank):
    rank_re = re.compile(r"(\d|[kqbnrpKQBNRP])")
    piece_tokens = rank_re.findall(rank)
    pieces = self.flatten(map(self.expand_or_noop, piece_tokens))
    return pieces
  def flatten(self, lst):
    return list(chain(*lst))
  def expand_or_noop(self, piece_str):
    piece_re = re.compile(r"([kqbnrpKQBNRP])")
    retval = ""
    if piece_re.match(piece_str):
      retval = piece_str
    else:
      retval = self.expand(piece_str)
    return retval
  def expand(self, num_str):
    return int(num_str)*" "
@@ -0,0 +1,95 @@
 """
    Ahira Justice, ADEFOKUN
    justiceahira@gmail.com
 """
 import os
 import pygame
 BASE_DIR = os.path.dirname(os.path.abspath(__file__))
 IMAGE_DIR = os.path.join(BASE_DIR, 'images')
 BLACK = 'BLACK'
 WHITE = 'WHITE'
 BISHOP = 'BISHOP'
 KING = 'KING'
 KNGHT = 'KNIGHT'
 PAWN = 'PAWN'
 QUEEN = 'QUEEN'
 ROOK = 'ROOK'
 class Piece:
    bBishop = pygame.image.load(os.path.join(IMAGE_DIR, 'bB.png'))
    bKing = pygame.image.load(os.path.join(IMAGE_DIR, 'bK.png'))
    bKnight = pygame.image.load(os.path.join(IMAGE_DIR, 'bN.png'))
    bPawn = pygame.image.load(os.path.join(IMAGE_DIR, 'bP.png'))
    bQueen = pygame.image.load(os.path.join(IMAGE_DIR, 'bQ.png'))
    bRook = pygame.image.load(os.path.join(IMAGE_DIR, 'bR.png'))
    wBishop = pygame.image.load(os.path.join(IMAGE_DIR, 'wB.png'))
    wKing = pygame.image.load(os.path.join(IMAGE_DIR, 'wK.png'))
    wKnight = pygame.image.load(os.path.join(IMAGE_DIR, 'wN.png'))
    wPawn = pygame.image.load(os.path.join(IMAGE_DIR, 'wP.png'))
    wQueen = pygame.image.load(os.path.join(IMAGE_DIR, 'wQ.png'))
    wRook = pygame.image.load(os.path.join(IMAGE_DIR, 'wR.png'))
    def __init__(self, color, piece, DISPLAYSURF, size):
        self.position = None
        self.sprite = None
        self.DISPLAYSURF = DISPLAYSURF
        self.size = size
        self.color = color
        self.piece = piece
        self.setSprite()
    def setPosition(self, position):
        self.position = position
    def setSprite(self):
        if self.piece == BISHOP:
            if self.color == BLACK:
                self.sprite = Piece.bBishop
            elif self.color == WHITE:
                self.sprite = Piece.wBishop
        elif self.piece == KING:
            if self.color == BLACK:
                self.sprite = Piece.bKing
            elif self.color == WHITE:
                self.sprite = Piece.wKing
        elif self.piece == KNGHT:
            if self.color == BLACK:
                self.sprite = Piece.bKnight
            if self.color == WHITE:
                self.sprite = Piece.wKnight
        elif self.piece == PAWN:
            if self.color == BLACK:
                self.sprite = Piece.bPawn
            elif self.color == WHITE:
                self.sprite = Piece.wPawn
        elif self.piece == QUEEN:
            if self.color == BLACK:
                self.sprite = Piece.bQueen
            elif self.color == WHITE:
                self.sprite = Piece.wQueen
        elif self.piece == ROOK:
            if self.color == BLACK:
                self.sprite = Piece.bRook
            elif self.color == WHITE:
                self.sprite = Piece.wRook
    def displayPiece(self):
        sprite = pygame.transform.scale(self.sprite, (self.size, self.size))
        self.DISPLAYSURF.blit(sprite, self.position)
@@ -0,0 +1,7 @@
 a2b3
 b2c3
 b2a3
 c2d3,d4d3,d2c3
 c2b3
 d2c3
 c2d3,d4d3,b1d3