def main():
key = GameBoard.Board()
board = GameBoard.Board(bombs=0)
# GameBoard.printBoard(board)
while (not gameWon(key, board)):
GameBoard.printBoard(board)
# get guess
g = getGuess(key.gridSize)
i = g[0]
j = g[1]
f = input("enter f to place a flag: ")
if (f in 'fF'):
flag(i, j, board)
else:
guess(i, j, board, key)
print("NICE WORK")
print("---------")
GameBoard.printBoard(key)
# TicTacToe Neural Network
# Eduardo B <*****@*****.**>
import BackPropagation
import Player
import GameBoard
import GameRegister
#Crea una red neuronal de 9 entradas 9 salidas
neuralNetwork = BackPropagation.NN(9, 9, 9)
#prepara el tablero
board = GameBoard.Board()
#para el registro de movimientos
register = GameRegister.Register()
# Entrena a la red neuronal con las jugadas realizadas
def Learn():
global neuralNetwork
global register
train = raw_input("\n Do I need to train more? (y/n): ")
if train == "y":
print "\n Training with %s movements madafaka..." % (register.Len())
neuralNetwork.train(register.GetGame())
def Play():
global neuralNetwork
global register
global board
def __init__(self):
self.board = GameBoard.Board(CheckerBoard.BOARD_SIZE,
CheckerBoard.BOARD_SIZE)
self.place_starting_pieces()
def print_knowledge(self):
for x in self.knowledge:
x.print_sentence()
print('Enter height: ', end='')
height = int(input())
print('Enter width: ', end='')
width = int(input())
print('Enter number of mines: ', end='')
mineNumber = int(input())
pygame.init()
screen = pygame.display.set_mode([21 * width, 21 * height])
board = GameBoard.Board(height, width, mineNumber, screen)
running = True
while running:
# Did the user click the window close button?
for event in pygame.event.get():
if event.type == pygame.QUIT:
running = False
if event.type == MOUSEBUTTONDOWN and event.button == BUTTON_LEFT:
mouse_x, mouse_y = event.pos # Now it will have the coordinates of click point.
board.clear_cell(int(mouse_y / 21), int(mouse_x / 21))
board_knowledge = Knowledge(board)
board_knowledge.refine_knowledge()
if board.game_state == 1 or board.game_state == 0:
