def order_moves_by_warnsdorff_tuples(self, board, move_tuples):
""" Order moves by Warnsdorff algorithm (minimum neighbors) one level
:board: current board
:move_tuples: sorted list of 3-tuples
(number-of follow-on moves,
move,
list of this move's follow-on
)
:returns: list with moves of decreasing number of follow-on's folow-on moves
of 3-tuples (number-of follow-on folow-on's moves,
move,
list of this move's follow-on's follow-ons
)
"""
ffon_tuples = [
] # list of (follow-on's follow-on cnt, move, ffon_list)
for move_tuple in move_tuples:
follow_ons = move_tuple[2]
follow_board = ChessBoard(board)
follow_board.set_piece('N', move_tuple[1])
follow_on_tuples = self.order_moves_by_warnsdorff_1(
follow_board, follow_ons)
ffon_moves = []
for follow_on_tuple in follow_on_tuples:
ffon_moves.extend(follow_on_tuple[2])
ffon_tuples.append((len(ffon_moves), move_tuple[1], ffon_moves))
ffon_tuples_sorted = sorted(ffon_tuples, key=by_first)
return ffon_tuples_sorted
def build_chess(size, pieces, verbose):
width, height = size
# assert len(pieces) <= (width * height) / 2
board = ChessBoard(width, height, pieces, verbose=verbose)
t = datetime.now()
board.find_combinations()
print(board.get_combinations_number(), datetime.now() - t)
def __init__(self,
locs=None,
ncol=None,
nrow=None,
piece=None,
closed_tours=True):
""" Set up validation constraints on which validation is made
:locs: squares for which possible tour default ncolxnrow
:ncol: number of columns default: nrow if nrow is not None else 8
:nrow: number of rows default: ncol if ncol is not None else 8
:piece: Chess piece letter e.g. 'K' for black king default: 'N' - black knight
:closed_tours: Check for closed tour (ending square is one piece move from start)
default: True
"""
if ncol is None:
ncol = 8 if nrow is None else nrow
self.ncol = ncol
if nrow is None:
nrow = 8 if ncol is None else ncol
self.nrow = nrow
if locs is None:
locs = []
for ic in range(ncol):
for ir in range(nrow):
locs.append((ic, ir))
self.locs = locs
if piece is None:
piece = 'N'
self.piece = piece
self.closed_tours = closed_tours
self.cb = ChessBoard(ncol=self.ncol,
nrow=self.nrow) # For acces to basic fns
def can_an_passant(piece, move, board: ChessBoard):
left_neighbor_pos = Vec2(move.old.x - 1, move.old.y)
right_neighbor_pos = Vec2(move.old.x + 1, move.old.y)
global left_neighbor
global right_neighbor
if move.old.x != 0:
left_neighbor = board.get_piece(left_neighbor_pos)
if move.old.x != 7:
right_neighbor = board.get_piece(right_neighbor_pos)
if piece.team == 1:
if move.old.y == 3:
if left_neighbor is not None:
if left_neighbor.name == "Pawn" and left_neighbor.move_counter == 1 and left_neighbor.team != piece.team:
an_passant(move, "left", board)
return True
elif right_neighbor is not None:
if right_neighbor.name == "Pawn" and right_neighbor.move_counter == 1 and right_neighbor.team != piece.team:
an_passant(move, "right", board)
return True
elif piece.team == 2:
if move.old.y == 4:
if left_neighbor is not None:
if left_neighbor.name == "Pawn" and left_neighbor.move_counter == 1 and left_neighbor.team != piece.team:
an_passant(move, "left", board)
return True
elif right_neighbor is not None:
if right_neighbor.name == "Pawn" and right_neighbor.move_counter == 1 and right_neighbor.team != piece.team:
an_passant(move, "right", board)
return True
return False
def test_check_board_for_b(self):
cells = {
(0, 0): 'K',
(0, 1): None,
(1, 0): None,
(1, 1): None,
}
board = ChessBoard(3, 3, [])
self.assertIsNone(board.check_board_for_b(2, 2, cells))
self.assertEqual(board.check_board_for_b(2, 1, cells), {(1, 2)})
self.assertEqual(board.check_board_for_b(0, 2, cells), {(2, 0)})
def display_path(cls, path,
desc=None, nrow=8, ncol=8,
width=400, height=400):
""" Display board with path squares labeled
:desc: text description
:path: list of squares in order
returns ChssBoardDisplay of displayed board
"""
if not hasattr(cls, 'wm'):
cls.wm = Tk()
wm_base = cls.wm
wm = Toplevel(wm_base)
wm_base.withdraw()
wm.geometry("%dx%d" % (width, height))
frame = Frame(wm, width=width, height=height, bg="", colormap="new")
frame.pack(fill=BOTH, expand=True)
wm.title(desc)
#creation of an instance
cb = ChessBoard(nrow=nrow, ncol=ncol)
cbd = ChessBoardDisplay(wm=wm, frame=frame, board=cb, path=path,
desc=desc,
width=width, height=height, nrow=nrow, ncol=ncol)
if path is None:
SlTrace.lg("No path")
return
for loc in path:
loc = cb.loc2tuple(loc)
cbd.label_square(loc)
cbd.display()
wd = 7
if len(path) == 0:
return
loc_start = path[0]
sq1 = cbd.get_square(loc_start)
cbd.draw_outline(sq1, color="green", width=wd)
loc_end = path[-1]
sq2 = cbd.get_square(loc_end)
cbd.draw_outline(sq2, color="red", width=wd)
if cb.is_neighbor(loc_end, loc_start):
p1 = sq1.get_center()
p2 = sq2.get_center()
cbd.draw_line(p1,p2, color="blue", width=wd)
prev_loc = None
for loc in path:
loc = cb.loc2tuple(loc)
if prev_loc is not None:
cbd.display_connected_moves(loc, prev_loc)
prev_loc = loc
wm.lift()
cbd.update_display()
return cbd
def __init__(self):
self.board = ChessBoard(self)
self.pieces = [Pawn(self, "white", item) for item in [i + "2" for i in "abcdefgh"]]
self.pieces.extend([Pawn(self, "black", item) for item in [i + "7" for i in "abcdefgh"]])
self.pieces.extend([Rook(self, "white", item) for item in ("a1", "h1")])
self.pieces.extend([Rook(self, "black", item) for item in ("a8", "h8")])
self.pieces.extend([Bishop(self, "white", item) for item in ("c1", "f1")])
self.pieces.extend([Bishop(self, "black", item) for item in ("c8", "f8")])
self.pieces.extend([Knight(self, "white", item) for item in ("b1", "g1")])
self.pieces.extend([Knight(self, "black", item) for item in ("b8", "g8")])
self.pieces.extend([King(self, "white", "e1"), King(self, "black", "e8"), Queen(self, "white", "d1"), Queen(self, "black", "d8")])
self.players = []
def __init__(self, setup_pieces=False):
self.board = ChessBoard()
self.highness = None
self.p1_king = None
self.p2_king = None
self.player_turn = 1
self.other_player_turn = 2
self.turn_counter = 0
self.move_history = []
self.player_1_color = "yellow"
self.player_2_color = "magenta"
if setup_pieces:
self.setup_pieces()
def test_check_board_general(self):
cells = {
(0, 0): 'K',
(0, 1): None,
(1, 0): None,
(1, 1): None,
}
board = ChessBoard(3, 3, [])
br1 = board.check_board(1, 1, cells, 'R')
br2 = board.check_board_for_r(1, 1, cells)
bk1 = board.check_board(1, 1, cells, 'K')
bk2 = board.check_board_for_k(1, 1, cells)
self.assertEqual(br1, br2)
self.assertEqual(bk1, bk2)
self.assertNotEqual(br2, bk2)
def prepare_sim_ann():
global solver, board_data
basic_prepare()
prepare_generator()
board = ChessBoard.load_board(board_data)
solver = SolverModelFactory.create_model("simulated_annealing", board,
generator)
def test_decide_next_step():
cb = ChessBoard(WIDTH, HEIGHT, ROW_NUM)
tiles = Tiles(cb)
gm = GameManager(cb, tiles)
y, x = gm.decide_next_step()
assert y == 2 and x == 4
def __init__(self):
QMainWindow.__init__(self)
self.ui = Ui_MainWindow()
self.ui.setupUi(self)
self.ui.graphicsView.setMouseTracking(True)
self.filter = Filter()
#self.ui.graphicsView.installEventFilter(self.filter)
self.installEventFilter(self.filter)
#### Black and White
self.setCursor(Qt.PointingHandCursor)
self.mouse_point = LaBel(self) # 将鼠标图片改为棋子
self.mouse_point.setScaledContents(True)
self.mouse_point.setPixmap(
self.ui.graphicsView.black) # Black chess piece, human always hold
self.mouse_point.setGeometry(270, 270, PIECE, PIECE)
# settings for the mouse
self.mouse_point.raise_()
self.setMouseTracking(True)
self.AI_down = True
self.chess_board = ChessBoard()
self.pieces = [LaBel(self) for i in range(361)
] # All the chess pieces , 19*19 chess board
for piece in self.pieces:
piece.setVisible(True) # Set Picture Visible
piece.setScaledContents(True) #
def __init__(self, path_starts=None, arrange=None,
time_out=None,
closed_tours=None,
display_move=False,
pW=None,
move_time=.5,
width=400,
height=400,
nrow = 8,
ncol = 8,
max_look_ahead=5):
self.display_move = display_move
self.pW = pW
self.move_time = move_time
self.width = width
self.height = height
self.nrow = nrow
self.ncol = ncol
self.board = ChessBoard(ncol=ncol, nrow=nrow)
self.len_ckt = nrow*ncol
if display_move:
time_out = None # Disable time_out if displaying moves
self.time_out = time_out
self.path_starts = path_starts
self.closed_tours = closed_tours
self.max_look_ahead = max_look_ahead
self.arrange = arrange
self.sqno = 0 # number within list
self.displayed_paths = [] # Repository of displayed paths
self.kpths = None # Current path, if any
self.ipstart = 0 # current start loc index
def test_constructor():
cb = ChessBoard(WIDTH, HEIGHT, ROW_NUM)
tile = Tile(cb, 'black')
assert tile.color == 'black'
assert tile.CLEARANCE == 10
assert tile.width == 90
assert tile.height == 90
def test_constructor():
cb = ChessBoard(WIDTH, HEIGHT, ROW_NUM)
tiles = Tiles(cb)
gm = GameManager(cb, tiles)
assert gm.black_turn == True
assert gm.WIDTH == 800
assert gm.HEIGHT == 800
for y in range(ROW_NUM):
for x in range(ROW_NUM):
if y == 3 and x == 3:
assert gm.tile_list[y][x].color == 'white'
elif y == 4 and x == 4:
assert gm.tile_list[y][x].color == 'white'
elif y == 4 and x == 3:
assert gm.tile_list[y][x].color == 'black'
elif y == 3 and x == 4:
assert gm.tile_list[y][x].color == 'black'
else:
assert gm.tile_list[y][x] == None
assert gm.black_count == 2
assert gm.white_count == 2
assert gm.X_ADD == [0, 1, -1, 0, 1, -1, 1, -1]
assert gm.Y_ADD == [1, 0, 0, -1, 1, -1, -1, 1]
assert gm.has_input_name == False
assert gm.TIME_DURATION == 1500
assert gm.FILE_NAME == 'scores.txt'
def test_get_legal_move_list():
cb = ChessBoard(WIDTH, HEIGHT, ROW_NUM)
tiles = Tiles(cb)
gm = GameManager(cb, tiles)
white_move_list = gm.get_legal_move_list('black')
assert white_move_list == {(2, 3): 1, (3, 2): 1, (4, 5): 1, (5, 4): 1}
def test_black_make_move():
cb = ChessBoard(WIDTH, HEIGHT, ROW_NUM)
tiles = Tiles(cb)
gm = GameManager(cb, tiles)
gm.black_make_move(324, 234)
assert gm.tile_list[2][3].color == 'black'
assert gm.black_count == 4
def test_white_make_move():
cb = ChessBoard(WIDTH, HEIGHT, ROW_NUM)
tiles = Tiles(cb)
gm = GameManager(cb, tiles)
gm.white_make_move()
assert gm.tile_list[2][4].color == 'white'
def __init__(self,
frame=None, wm=None,
desc="",
x=None, y=None,
width=400, height=400, # REQUIRED, if window not expanded
board=None,
move_time = .5,
path=None,
nrow=8,
ncol=8,
):
""" Set up board display
:frame: if one
:wm: if one
:desc: description if one
:x: board x position default: tkinter default
:y: board y position
:width: board width default: 400 pixels
:height: board height default: 400 pixels
:board: ChessBoard default: created
:path: path to display
:nrow: number of rows default: 8
:ncol: number of columns default: 8
"""
self.label_number = 0 # Number for default square labeling
self.desc = desc
if board is None:
board = ChessBoard(nrow=nrow, ncol=ncol)
self.path = path # Path, if associated, may be placed here
self.board = board
self.width = width
self.height = height
if board is not None:
nrow = board.nrow
ncol = board.ncol
self.nrow = nrow
self.ncol = ncol
if wm is None:
wm = Tk()
self.wm = wm
width = int(width)
height = int(height)
geo = f"{width}x{height}"
if x is not None or y is not None:
geo += f"+{x}+{y}"
wm.geometry(geo)
if frame is None:
frame = Frame(master=wm, width=width, height=height, bg="", colormap="new")
frame.pack(fill=BOTH, expand=YES)
self.frame = frame
select_dots = self.create_board(frame, wm, width=width, height=height,
nrow=nrow, ncol=ncol)
self.select_dots = select_dots
self.prev_loc = None # previous move location for path viewing
self.move_time = move_time
self.display_move_stack = [] # (loc, line)
self.display_move_no = 0
def test_check_board_for_n(self):
cells_1 = {
(0, 0): 'K',
(0, 1): None,
(1, 0): None,
(1, 1): None,
}
cells_2 = {
(2, 2): 'K',
(1, 1): None,
(1, 2): None,
(2, 1): None,
}
board = ChessBoard(3, 3, [])
self.assertIsNone(board.check_board_for_n(2, 1, cells_1))
self.assertIsNone(board.check_board_for_n(1, 2, cells_1))
self.assertIsNone(board.check_board_for_n(0, 1, cells_2))
self.assertEqual(board.check_board_for_n(2, 0, cells_1), {(1, 2)})
def next_move(self):
""" Execute the next (currenly set) move, updating the path stack
and displaying move if appropriate
:returns: True iff at end of path search
"""
if self.closed_tours:
self.prune_not_closed()
stke = self.path_stack[-1]
next_move = stke.loc
board = stke.board
best_moves = stke.best_moves
SlTrace.lg(f"best_moves = {best_moves}", "stack_build")
if best_moves is None:
SlTrace.lg(f"best_moves tested is None", "stack_build")
best_moves = self.get_best_moves(board, next_move)
SlTrace.lg(f"best_moves = {best_moves}", "stack_build")
SlTrace.lg(f"len(best_moves)={len(best_moves)}", "stack_build")
if len(best_moves) == 0:
SlTrace.lg("tested as 0", "stack_build")
self.ntry += 1
if SlTrace.trace("no_more_moves"):
SlTrace.lg("{:d}: No more moves at {} len_stk={:d}".format(
self.ntry, loc2desc(next_move), len_stk))
if self.max_try is not None and self.ntry > self.max_try:
SlTrace.lg("Giving up this search")
return True
if SlTrace.trace("no_more_moves"):
self.display_stack_path("no_more_moves")
if (self.last_complete_path is None
or len(self.path_stack) > len(self.last_complete_path)):
self.last_complete_path = self.path_stack_path()
if len(self.path_stack) <= self.track_level:
self.track_level = len(self.path_stack)
if SlTrace.trace("back_off_trace"):
if self.track_level > 0:
stke = self.path_stack[-1]
nxt_move, board, bst_moves = stke.loc, stke.board, stke.best_moves
self.board = board
SlTrace.lg(
"back_off_trace stk_len={:d} start={} at {} best_moves={}"
.format(self.track_level, loc2desc(self.loc_start),
loc2desc(nxt_move), path_desc(bst_moves)))
self.display_stack_path("back_off_trace")
self.widen_search()
return False # Backup
else:
SlTrace.lg(f"len(best_moves)={len(best_moves)} failed test for 0",
"stack_build")
follow_move = best_moves.pop(0)
stke = self.path_stack[-1]
stke.best_moves = best_moves # Update best moves
new_board = ChessBoard(base_board=board)
self.make_move(loc=follow_move, board=new_board)
return False
def test_in_bound():
cb = ChessBoard(WIDTH, HEIGHT, ROW_NUM)
tiles = Tiles(cb)
gm = GameManager(cb, tiles)
assert gm.in_bound(4, 4) == True
assert gm.in_bound(1, 8) == False
assert gm.in_bound(2, -1) == False
assert gm.in_bound(-1, 7) == False
assert gm.in_bound(9, 3) == False
def test_flip_color():
# please comment the first line in flip_color
# function. millis() is not a python statement that can
# casue error in py test. it is basically a timer recording
# time and will not effect the test result.
cb = ChessBoard(WIDTH, HEIGHT, ROW_NUM)
tiles = Tiles(cb)
gm = GameManager(cb, tiles)
gm.flip_color('white', 3, 2)
assert gm.tile_list[3][3].color == 'black'
def can_castle(move, board: ChessBoard):
king = board.get_piece(move.old)
king.is_castling_move(move, board)
if king.is_castling:
if not board.is_path_clear(move):
return False
if king.has_moved:
return False
if king.team == 1:
if move.new == Vec2(6, 7):
if board.get_piece(Vec2(7, 7)) is not None:
if board.get_piece(Vec2(7, 7)).has_moved is False:
return True
elif move.new == Vec2(2, 7):
if board.get_piece(Vec2(0, 7)) is not None:
if board.get_piece(Vec2(0, 7)).has_moved is False:
return True
else:
if move.new == Vec2(6, 0):
if board.get_piece(Vec2(7, 0)) is not None:
if board.get_piece(Vec2(7, 0)).has_moved is False:
return True
elif move.new == Vec2(2, 0):
if board.get_piece(Vec2(0, 0)) is not None:
if board.get_piece(Vec2(0, 0)).has_moved is False:
return True
# if board.is_space_safe(move.old, king.team):
# return False
return False
return False
def is_castling(move, board: ChessBoard):
king = board.get_piece(move.old)
if king.team == 1:
if move.new == Vec2(6, 7) or move.new == Vec2(2, 7):
return True
else:
if move.new == Vec2(6, 0) or move.new == Vec2(2, 0):
return True
return False
def solve_many_boards(seed_list, dim_each = 8, n_moves = 50,
verbose = False, stop_each = None):
'''Given a list of queen positioning seeds, a size for each board, and
a maximum number of moves to attempt before giving up, run your
columnwise CSP eight queens solver on each board configuration.
Don't hate the playa, hate the game'''
bcount = len(seed_list)
if bcount > 1:
print(f"Working on {bcount} test cases...")
for i, s in enumerate(seed_list):
if bcount > 1:
print(f"Case {i+1} of {bcount} (seed {s})")
game = ChessBoard(dimension = dim_each, queen_seed = s)
player = MinConflictColumnSolver(board_object = game, max_moves = n_moves)
player.solve(verbose = verbose, stop_each = stop_each)
print(player.solution_shortdoc())
print("-" * bcount, "\n")
def solve_puzzle():
'''Accessing args with [] indicates a required param (we throw a
400-BAD REQUEST if it isn't included).
TODO A: Should I made the Bad Request case more explicit?
TODO B: CORS????
example usage: "http://localhost:5000/solve?dimension=8&state_string=1525384358627583"
'''
board_dim = int(request.args["dimension"])
board_state = request.args["state"]
move_arg = request.args.get("max_moves")
max_moves = 50 if move_arg is None else int(move_arg)
cboard = ChessBoard(dimension = board_dim, state_string = board_state)
solver = MinConflictColumnSolver(board_object = cboard, max_moves = max_moves)
solver.solve()
rsp_data = solver.get_solution()
rsp_headers = {"Content-Type":"application/json"}
return make_response(rsp_data, 200, rsp_headers)
def test_constructor():
row_num = 4
cb = ChessBoard(WIDTH, HEIGHT, row_num)
tiles = Tiles(cb)
tile_list = []
for x in range(row_num):
tile_list.append([])
for y in range(row_num):
if tiles.tile_list[y][x] == None:
tile_list[x].append(None)
else:
tile_list[x].append(tiles.tile_list[y][x].color)
assert tile_list == [[None, None, None, None],
[None, 'white', 'black', None],
[None, 'black', 'white', None],
[None, None, None, None]]
def CnnVsMonteCarlo(self, nb_iter):
"""player 0 => play game using CNN
player 1 => play game using random method
"""
moves=[]
winner=[]
print('The number of iteration is %s' %(str(nb_iter)))
for i in range(nb_iter):
print(str(i) + " iterations is done")
player=0
board=ChessBoard(8).getChessBoard()
list_best_move=[]
while len(Playout().getPossibleMove(board, player))>0:
# make sure which player
# CNN player
if player==0:
X=np.concatenate((board, 1-board, np.zeros((8,8), dtype=int)+player), axis=0).reshape(1,3,8,8)
y=self.cnn.predict(X).reshape(64)
# y=y_predict
is_finished=False
max_value=-1
counter=0
while is_finished==False & counter<64:
counter+=1
for i in range(64):
if y[i]>max_value:
max_value=y[i]
move=i
if move in Playout().getPossibleMove(board, player):
list_best_move.append(move)
board=Playout().play(board, move, player)
player=1-player
is_finished=True
else:
y[move]=0
max_value=-1
elif player==1:
possible_moves=Playout().getPossibleMove(board, player)
list_mean_playout=[]
list_move=[]
for i in range(len(possible_moves)):
copy_board=np.copy(board)
copy_board=Playout().play(copy_board, possible_moves[i], player)
list_mean_playout.append(Playout().getMeanOfPlayout(copy_board, 1-player, 10))
list_move.append(possible_moves[i])
best_playout=-1
for i in range(len(list_mean_playout)):
if list_mean_playout[i]>best_playout:
best_playout=list_mean_playout[i]
best_move=list_move[i]
list_best_move.append(best_move)
board=Playout().play(board, best_move, player)
player=1-player
moves.append(list_best_move)
winner.append(1-player)
return moves, winner
from chess_board import ChessBoard
from stochastic_hill_c import stochastic_hill_climbing as shc
b = ChessBoard() # criação do tabuleiro
print("ORIGINAL: ", b.fitness)
print(b)
b.queens = shc(b) # aplicação do hill climbing
b.update_board()
print("ALTERADO: ", b.fitness)
print(b)
def main():
# Argument variable defaults
mutation_chance_def = 0.02
children_per_gen_def = 400
pop_size_def = 1000
thread_count_def = 1
n_queens_def = 8
reset_def = 250
# Setup argument variable parser
parser = argparse.ArgumentParser(
description=
'Runs the n-queen problem with given values, or defaults in case of '
'missing values')
parser.add_argument(
'-m',
'--mutation_chance',
help='the mutation chance to use, which defaults to {}'.format(
mutation_chance_def))
parser.add_argument(
'-c',
'--children_per_gen',
help=
'the number of children to create each generation, which must be less than half of the '
'given population. Defaults to {}'.format(children_per_gen_def))
parser.add_argument(
'-p',
'--pop_size',
help='the size of populations to create, defaulting to {}'.format(
pop_size_def))
parser.add_argument(
'-t',
'--thread_count',
help='the number of threads to create, defaulting to {}'.format(
thread_count_def))
parser.add_argument(
'-n',
'--n_queens',
help='the number of queens in the problem, defaulting to {}'.format(
n_queens_def))
parser.add_argument(
'-r',
'--reset',
help=
'the number of generations to run in a population before resetting to a '
'new population, defaulting to {}'.format(reset_def))
# Parse argument variables
args = parser.parse_args()
# Set mutation chance
if args.mutation_chance:
try:
mutation_chance = float(args.mutation_chance)
if mutation_chance <= 0 or mutation_chance > 1:
raise ValueError
except ValueError:
print(
'mutation chance must be a float such that 0 < mutation chance <= 1'
)
exit(-1)
else:
mutation_chance = mutation_chance_def
# Set population size
if args.pop_size:
try:
pop_size = int(args.pop_size)
if pop_size <= 1:
raise ValueError
except ValueError:
print('population size must be greater than 1')
exit(-2)
else:
pop_size = pop_size_def
# Set children per gen
if args.children_per_gen:
try:
children_per_gen = int(args.children_per_gen)
if children_per_gen * 2 > pop_size or children_per_gen <= 0:
raise ValueError
except ValueError:
print(
'the number of children to generate must be less than half the population size and greater than 0'
)
exit(-3)
else:
children_per_gen = children_per_gen_def
# Set dimension of the problem
if args.n_queens:
try:
n_queens = int(args.n_queens)
if n_queens <= 0:
raise ValueError
except ValueError:
print(
'the dimension of the problem must be greater than 0, and must be passed as an int'
)
exit(-4)
else:
n_queens = n_queens_def
# Set the number of threads to use
if args.thread_count:
try:
thread_count = int(args.thread_count)
if thread_count <= 0:
raise ValueError
except ValueError:
print('the thread count must be greater than 0')
exit(-5)
else:
thread_count = thread_count_def
if args.reset:
try:
reset = int(args.reset)
if reset <= 0:
raise ValueError
except ValueError:
print(
'the number of generations to reset after must be greater than 0'
)
exit(-6)
else:
reset = reset_def
# Setup static variables for the ChessBoard
ChessBoard.setup_statics(dimensions=n_queens,
mutation_chance=mutation_chance)
# Genetic algorithm starts now, so the timer should start
start_time = time()
# Create threads for the different populations equal to the number requested
threads = []
for i in range(thread_count):
new_thread = Thread(target=run_genetic_algorithm,
args=(pop_size, children_per_gen, reset))
# Start the thread, and add it to the thread list
new_thread.start()
threads.append(new_thread)
# This loop will be exited after enough time has passed without a solution being found, terminating the
# program
finding_solutions = True
while finding_solutions:
# Save the size of the list to use to check if the solution list size has changed, to exit the program
num_solutions = len(solutions)
# Sleep to allow new updates
sleep(120)
# If the number of solutions hasn't increased, then end the program
if num_solutions == len(solutions):
finding_solutions = False
# The program has finished
print('The program found {} solutions, with these being the solutions:'.
format(len(solutions)))
for solution in solutions:
print(solution)
print('The program finished in approximately {} seconds'.format(
last_solution - start_time))
exit(0)
def run_genetic_algorithm(population_size, number_of_children, reset):
"""Runs a genetic algorithm.
Args:
population_size (int): The size of the population to create.
number_of_children (int): The number of children to breed each round.
reset (int): The number of generations to reset after.
"""
# Loop endlessly
while True:
# Create the initial population
population = []
for i in range(population_size):
population.append(ChessBoard())
generation_num = 1
# Loop until the reset number is reached
while generation_num <= reset:
# Sort population by fitness, with most fit candidates first in the list
population.sort(reverse=True)
# Check the list to see if any of the population is a solution
for board in population:
# Checks to see if the board is a solution
if bool(board):
add_solution(board.chromosome, generation_num)
# Breaks if the current board was not a solution, as nothing after it in the sorted list will be
else:
break
# Pick the parents for the next generation
parents = []
for i in range(number_of_children * 2):
# Select the portion of the population to grab a parent from
portion = np.random.choice([0, 1, 2, 3, 4], p=breed_weights)
# Select the parent from the designated portion
parent_index = np.random.choice(
range(int(portion * len(population) / 5),
int((portion + 1) * len(population) / 5)))
# Parents are removed so they cannot be selected again, and will be added back later
parents.append(population.pop(parent_index))
# Breed new children with the parents
children = []
for i in range(number_of_children):
# Create the new child
children.append(
ChessBoard(parent1=parents[i],
parent2=parents[0 - (i + 1)]))
# Add the parents back into the population
population += parents
# Delete a number of boards from the population equal to the number of children to be added from the bottom
# half
for i in range(number_of_children):
population.pop(np.random.randint(-int(len(population) / 2),
-1))
# Add the children to the population to replace the killed population
population += children
# Increase generation number
generation_num += 1
def test_unique_result(self):
board = ChessBoard(3, 3, ['K', 'K', 'R'])
board.find_combinations()
self.assertEqual(board.get_combinations_number(), 4)
def test_validation(self):
self.assertEqual(ChessBoard.validation(1), 1)
self.assertEqual(ChessBoard.validation(1.0), 1)
self.assertEqual(ChessBoard.validation(-1), 1)
self.assertRaises(TypeError, ChessBoard.validation, '1', 0)
def generate_population(self, orders):
for _ in range(self.population_count):
chess_board = ChessBoard.load_board(orders)
individual = Individual(chess_board)
self.population.append(individual)
