import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

from ReinforcmentLearning.game import start_try
import data.conf as conf



def multipleTries(EPSILON, ALPHA, GAMMA):
    conf.show_game = False
    conf.plot_result = False
    
    wins_per_try = []
    
    for x in range(conf.AMOUNT_TRIES):
        cookies_per_run = oneTry(EPSILON, ALPHA, GAMMA)

        results_last_700 = cookies_per_run[-700:]
        wins_in_last_700 = sum(1 for result in results_last_700 if result == 20)
        win_probalitiy_last_700 = (wins_in_last_700 / 700)
        wins_per_try.append(win_probalitiy_last_700)

        # print(f"Finished try {x+1}\n")

    return wins_per_try



def oneTry(EPSILON, ALPHA, GAMMA):
    """
    state: (x_distance_to_ghost, y_distance_to_ghost, next_cookie_Direction)
    action: Direction
    q_value: (state, action)
    """

    cookies_per_run, iterations = start_try(EPSILON, ALPHA, GAMMA)

    if conf.plot_result:
        wins = sum(1 for result in cookies_per_run if result == 20)
        print(f"Win percentage overall: {(wins/conf.AMOUNT_RUNS)*100}%")

        last_700_results = cookies_per_run[-700:]
        wins_in_last_700 = sum(1 for result in last_700_results if result == 20)
        win_percentage = (wins_in_last_700 / 700) * 100
        print(f"Win percentage in the last 700: {win_percentage:.2f}%\n")

        plot_results(cookies_per_run, iterations)

    return cookies_per_run



def plot_results(cookies_per_run, iterations):
    wins = []
    losses = []
    win_count = 0

    for i, r in enumerate(cookies_per_run):
        if r == 20:
            win_count += 1
        wins.append(win_count)
        losses.append((i + 1) - win_count)  # Losses count down from top

    # Create figure with 2 subplots (wins/losses and iterations)
    fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8))

    # Plot 1: Wins vs Losses
    ax1.plot(range(1, len(wins)+1), wins, 'b-', linewidth=1.5, label='Wins')
    ax1.plot(range(1, len(losses)+1), losses, 'orange', linewidth=1.5, label='Losses')
    ax1.set_xlabel('Attempt')
    ax1.set_ylabel('Count')
    ax1.set_title('Wins vs Losses Over Time')
    ax1.legend()

    # Plot 2: Iterations per run
    ax2.plot(range(1, len(iterations)+1), iterations, 'g-', linewidth=1.5)
    ax2.set_xlabel('Run Number')
    ax2.set_ylabel('Iterations')
    ax2.set_title('Iterations per Run')

    plt.tight_layout()
    plt.show()