GenericAI_Sweeper/main.py
eugenep ce3ea0c15e implement neural network learning
Co-authored-by: Sebastian Piotrowski <sebpio@st.amu.edu.pl>
Co-authored-by: Marcin Matoga <marmat35@st.amu.edu.pl>
Co-authored-by: Ladislaus3III <Ladislaus3III@users.noreply.github.com>
2021-05-31 02:28:13 +02:00

246 lines
8.0 KiB
Python

import pygame as pg
import sys
import ctypes
from os import path
from matplotlib import pyplot
from sklearn import datasets
from sklearn.tree import DecisionTreeClassifier
from sklearn import tree
from maze import *
from grid import *
from settings import *
from sprites import *
from graphsearch import *
from astar2 import *
from pizza import *
from learning import *
from nn import *
#from csv_writer import *
class Game:
def __init__(self):
pg.init()
self.screen = pg.display.set_mode((WIDTH, HEIGHT))
pg.display.set_caption(TITLE)
self.clock = pg.time.Clock()
pg.key.set_repeat(500, 100)
self.load_data()
self.wentyl_bezpieczenstwa = 0
#ExampleGenerator.generate(ExampleGenerator)
def load_data(self):
game_folder = path.dirname(__file__)
self.map_data = []
with open(path.join(game_folder, 'main_map.txt'), 'rt') as f:
for line in f:
self.map_data.append(line)
def new(self):
# initialize all variables and do all the setup for a new game
#glebokosc rozmiar masa moc szkodliwosc zabawka stan teledysk
# x0 = glebokosc x1 = rozmiar x2 = masa x3 = moc x4 = szkodliwosc x5 = zabawka x6 = stan x7 = teledysk
# oflagowac, zdetonowac, sprzedac na allegro, sprzedac na czarnym rynku, obejrzec
self.all_sprites = pg.sprite.Group()
self.walls = pg.sprite.Group()
self.mines = pg.sprite.Group()
self.puddles = pg.sprite.Group()
for row, tiles in enumerate(self.map_data):
for col, tile in enumerate(tiles):
if tile == '2':
Mine(self, col, row)
Mine.set_parameters(Mine,18,32,6,7,0,1,0,0)
if tile == '3':
Bomb(self, col, row)
if tile == '4':
Grenade(self, col, row)
if tile == "#":
Wall(self, col, row)
if tile == 'p':
Puddle(self, col, row)
if tile == '>':
self.player = Player(self, col, row, Direction.Right.name)
if tile == '^':
self.player = Player(self, col, row, Direction.Up.name)
if tile == '<':
self.player = Player(self, col, row, Direction.Left.name)
if tile == 'v':
self.player = Player(self, col, row, Direction.Down.name)
def run(self):
# game loop - set self.playing = False to end the game
self.playing = True
while self.playing:
self.events()
self.update()
self.draw()
def quit(self):
pg.quit()
sys.exit()
def update(self):
# update portion of the game loop
self.all_sprites.update()
def draw_grid(self):
for x in range(0, WIDTH, TILESIZE):
pg.draw.line(self.screen, LIGHTGREY, (x, 0), (x, HEIGHT))
for y in range(0, HEIGHT, TILESIZE):
pg.draw.line(self.screen, LIGHTGREY, (0, y), (WIDTH, y))
def draw(self):
self.screen.fill(BGCOLOR)
self.draw_grid()
self.all_sprites.draw(self.screen)
pg.display.flip()
def events(self):
# catch all events here
for event in pg.event.get():
if event.type == pg.QUIT:
self.quit()
if event.type == pg.KEYDOWN:
if event.key == pg.K_ESCAPE:
self.quit()
if event.key == pg.K_LEFT:
self.player.move(dx=0, move='Left')
if event.key == pg.K_RIGHT:
self.player.move(dx=0, move='Right')
if event.key == pg.K_UP:
self.player.move(dy=0, move='Forward')
if event.key == pg.K_F2 and self.wentyl_bezpieczenstwa == 0:
self.player.maze.run()
self.player.parse_maze_moves()
self.i_like_to_move_it()
self.wentyl_bezpieczenstwa = 1
if event.key == pg.K_F3:
pg.event.clear()
player_moves = BFS.run()
self.graph_move(player_moves)
#self.wentyl_bezpieczenstwa = 1
if event.key == pg.K_F4 and self.wentyl_bezpieczenstwa == 0:
pg.event.clear()
#print("test1")
agent = SweeperAgent()
player_moves = SweeperAgent.run(agent)
self.graph_move(player_moves)
self.wentyl_bezpieczenstwa = 1
# Test.run()
if event.key == pg.K_F5:
self.player.decision_tree_learning()
#print("lol xD")
pg.event.clear()
if event.key == pg.K_F6 and self.wentyl_bezpieczenstwa == 0:
#LabelSetter.set_labels()
self.player.ai_mode = "tree"
agent = SweeperAgent()
player_moves = SweeperAgent.run(agent)
self.graph_move(player_moves)
self.wentyl_bezpieczenstwa = 1
if event.key == pg.K_F7 and self.wentyl_bezpieczenstwa == 0:
#net_runner = NetRunner()
#net_runner.prepare_data()
self.player.ai_mode = "neural"
agent = SweeperAgent()
player_moves = SweeperAgent.run(agent)
self.graph_move(player_moves)
self.wentyl_bezpieczenstwa = 1
def graph_move(self, moves):
for i in moves:
if i == 'Right':
self.player.move(dx=0, move='Right')
self.update()
self.draw()
pg.time.delay(250)
if i == 'Left':
self.player.move(dx=0, move='Left')
self.update()
self.draw()
pg.time.delay(250)
if i == 'Forward':
self.player.move(dx=0, move='Forward')
self.update()
self.draw()
pg.time.delay(250)
def i_like_to_move_it(self):
for i in self.player.moves:
if i == 'Right':
self.player.move(dx=1, direction='Right')
self.update()
self.draw()
pg.time.delay(250)
if i == 'Turn Right':
self.player.move(0, 0, direction='Right')
self.update()
self.draw()
pg.time.delay(250)
if i == 'Left':
self.player.move(dx=-1, direction='Left')
self.update()
self.draw()
pg.time.delay(250)
if i == 'Turn Left':
self.player.move(0, 0, direction='Left')
self.update()
self.draw()
pg.time.delay(250)
if i == 'Down':
self.player.move(dy=1, direction='Down')
self.update()
self.draw()
pg.time.delay(250)
if i == 'Turn Down':
self.player.move(0, 0, direction='Down')
self.update()
self.draw()
pg.time.delay(250)
if i == 'Up':
self.player.move(dy=-1, direction='Up')
self.update()
self.draw()
pg.time.delay(250)
if i == 'Turn Up':
self.player.move(0, 0, direction='Up')
self.update()
self.draw()
pg.time.delay(250)
def show_start_screen(self):
pass
def show_go_screen(self):
pass
# create the game object
g = Game()
g.show_start_screen()
#m = Maze()
#m.run()
while True:
g.new()
g.run()
g.show_go_screen()