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test.py 6.96 KiB
import matplotlib
matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
from tkinter import *
from logic import *
from random import *
from agent import *
from agent_afterstate import *
import numpy as np
import pickle
import time
import sys
from optparse import OptionParser
import os
TRAIN = 2000
SIZE = 500
GRID_LEN = 4
GRID_PADDING = 10
BACKGROUND_COLOR_GAME = "#92877d"
BACKGROUND_COLOR_CELL_EMPTY = "#9e948a"
BACKGROUND_COLOR_DICT = { 2:"#eee4da", 4:"#ede0c8", 8:"#f2b179", 16:"#f59563", \
32:"#f67c5f", 64:"#f65e3b", 128:"#edcf72", 256:"#edcc61", \
512:"#edc850", 1024:"#edc53f", 2048:"#edc22e" }
CELL_COLOR_DICT = { 2:"#776e65", 4:"#776e65", 8:"#f9f6f2", 16:"#f9f6f2", \
32:"#f9f6f2", 64:"#f9f6f2", 128:"#f9f6f2", 256:"#f9f6f2", \
512:"#f9f6f2", 1024:"#f9f6f2", 2048:"#f9f6f2" }
FONT = ("Verdana", 40, "bold")
class GameGrid(Frame):
def __init__(self,args=None):
for k in list(args.keys()):
if args[k] == None:
args.pop(k)
else :
args[k] = float(args[k])
if "train" in args.keys():
self.train = args["train"]
args.pop("train")
else:
self.train = TRAIN
self.DISPLAY = True
if self.DISPLAY:
Frame.__init__(self)
self.commands = { Action.UP: up, Action.DOWN: down, Action.LEFT: left, Action.RIGHT: right}
self.grid_cells = []
if self.DISPLAY:
self.grid()
self.master.title('2048')
self.init_grid()
self.reset()
self.history = []
self.count = 0
# self.agent = RandomAgent()
self.agent = afterstateAgent(self.matrix,**args)
f = open("train_0.0025_0.5_0.0_result_after_2000.txt",'rb')
self.agent.W = pickle.load(f)
if self.DISPLAY:
self.key_down()
self.mainloop()
else:
while self.count<=self.train:
self.key_down()
def reset(self):
self.init_matrix()
if self.DISPLAY:
self.update_grid_cells()
def init_grid(self):
background = Frame(self, bg=BACKGROUND_COLOR_GAME, width=SIZE, height=SIZE)
background.grid()
for i in range(GRID_LEN):
grid_row = []
for j in range(GRID_LEN):
cell = Frame(background, bg=BACKGROUND_COLOR_CELL_EMPTY, width=SIZE/GRID_LEN, height=SIZE/GRID_LEN)
cell.grid(row=i, column=j, padx=GRID_PADDING, pady=GRID_PADDING)
# font = Font(size=FONT_SIZE, family=FONT_FAMILY, weight=FONT_WEIGHT)
t = Label(master=cell, text="", bg=BACKGROUND_COLOR_CELL_EMPTY, justify=CENTER, font=FONT, width=4, height=2)
t.grid()
grid_row.append(t)
self.grid_cells.append(grid_row)
def gen(self):
return randint(0, GRID_LEN - 1)
def init_matrix(self):
self.matrix = new_game(4)
self.matrix=add_two(self.matrix)
self.matrix=add_two(self.matrix)
def update_grid_cells(self):
for i in range(GRID_LEN):
for j in range(GRID_LEN):
new_number = self.matrix[i][j]
if new_number == 0:
self.grid_cells[i][j].configure(text="", bg=BACKGROUND_COLOR_CELL_EMPTY)
else:
self.grid_cells[i][j].configure(text=str(new_number), bg=BACKGROUND_COLOR_DICT[new_number], fg=CELL_COLOR_DICT[new_number])
self.update_idletasks()
def key_down(self):
if self.count>=1:
self.agent.verbose = False
if self.agent.count >10000:
self.agent.verbose = True
self.agent.set_state(self.matrix)
key = self.agent.act()
self.matrix,done = self.commands[key](self.matrix)
reward = 0
if done:
self.matrix = add_two(self.matrix)
if self.DISPLAY:
self.update_grid_cells()
if done!=1:
reward += done
# print(reward)
# else:
# reward = -0.5
if game_state(self.matrix)=='win':
print("win")
# self.grid_cells[1][1].configure(text="You",bg=BACKGROUND_COLOR_CELL_EMPTY)
# self.grid_cells[1][2].configure(text="Win!",bg=BACKGROUND_COLOR_CELL_EMPTY)
if game_state(self.matrix)=='lose':
if self.agent.explore>0:
print("explore: "+ str(self.agent.explore))
# reward = -10
# reward = np.log(np.max(self.matrix))
# self.grid_cells[1][1].configure(text="You",bg=BACKGROUND_COLOR_CELL_EMPTY)
# self.grid_cells[1][2].configure(text="Lose!",bg=BACKGROUND_COLOR_CELL_EMPTY)
print(str(self.count) + " : " + str(np.max(self.matrix)))
# self.agent.update(self.matrix, reward)
if (game_state(self.matrix)=='win' ) or (game_state(self.matrix)=='lose'):
# print(self.agent.W)
if (self.count == self.train):
f = open("train_" +str(self.agent.alpha) +"_"+str(self.agent.TD_lambda)+"_"+str(self.agent.symmetric)+"_result_after_"+str(self.count)+".txt",'wb')
pickle.dump(self.agent.W ,f)
f.close()
f = open("train_" +str(self.agent.alpha) +"_"+str(self.agent.TD_lambda)+"_"+str(self.agent.symmetric)+"_history_after_"+str(self.count)+".txt",'wb')
np.savetxt(f, self.history)
f.close()
self.history += [np.max(self.matrix)]
self.agent.reset()
self.count += 1
self.reset()
# plt.plot(self.history)
# plt.show()
# print(reward)
# self.matrix
if (self.DISPLAY):
# Tell Tkinter to wait DELTA_TIME seconds before next iteration
self.after(50, self.key_down)
def generate_next(self):
index = (self.gen(), self.gen())
while self.matrix[index[0]][index[1]] != 0:
index = (self.gen(), self.gen())
self.matrix[index[0]][index[1]] = 2
if __name__ == '__main__':
parser = OptionParser()
parser.add_option("-g", "--TD", dest="TD_lambda", help ="TD_lambda the forget coefficient")
parser.add_option("-a", "--alpha", dest="alpha", help ="alpha the learning rate")
parser.add_option("-t", "--train", dest="train", help ="training episodes")
parser.add_option("-s", "--symmetric", dest="symmetric", help ="symmetric sampling")
parser.add_option("-e", "--epsilon", dest="epsilon", help ="epsilon the exploration")
parser.add_option("-u", "--tuple", dest="tuple", help ="the tuple to use")
(options,args)= parser.parse_args()
print(vars(options))
f = open("train_0.0025_0.5_0.0_history_after_2000.txt",'rb')
history = np.loadtxt(f)
f.close()
plt.plot(history)
plt.show()
start_time = time.time()
gamegrid = GameGrid(vars(options))
print("--- %s seconds ---" % (time.time() - start_time))