import json
from mpl_toolkits.mplot3d import Axes3D
from pprint import pprint
import matplotlib.pyplot as plt
import numpy as np
#import pandas as pd
import pygal

p1_x = []
p1_y = []
p2_x = []
p2_y = []

with open('games_results.json', 'r') as f:
    file = json.load(f)

    dos_1 = list(set([result["player_1"]["minmax_dept_of_search"] for result in file['results']]))
    iter_1 = list(set([result["player_1"]["montecarlo_iter_max"] for result in file['results']]))
    dos_1.sort()
    iter_1.sort()
    print(dos_1, iter_1)

mc_i1 = []
whiteWins = []
blackWins = []
draw_l = []
for iter in iter_1:
    a = 0
    whitewon, blackwon, draw = 0, 0, 0
    for result in file["results"]:
        if result["player_1"]["montecarlo_iter_max"] == iter and result["player_1"]["player_type"] == "MonteCarlo" and \
                result["board_size"] == 6 and result["player_2"]["montecarlo_iter_max"] == iter:
            if result["winner"] == "White":
                whitewon += 1
            elif result["winner"] == "Black":
                blackwon += 1
            else:
                draw += 1
            a += 1
    mc_i1.append(a)
    whiteWins.append(whitewon)
    blackWins.append(blackwon)
    draw_l.append(draw)

mc_i2 = []
for iter in iter_1:
    a = 0
    for result in file["results"]:
        if result["player_2"]["montecarlo_iter_max"] == iter and result["player_2"]["player_type"] == "MonteCarlo":
            a += 1
    mc_i2.append(a)

# print(mc_i1, mc_i2)

print(whiteWins, blackWins, draw_l)

ind_1 = [1, 100] + [i*100 for i in range(2, 11, 2)] + [10000]
ind = np.arange(len(ind_1))# the x locations for the groups
width = 0.35  # the width of the bars: can also be len(x) sequence

fig, ax = plt.subplots()

p1 = ax.bar(ind, whiteWins, width, color='w', bottom=0)
p2 = plt.bar(ind + width, blackWins, width, color='k', bottom=0)
p3 = plt.bar(ind + width, draw_l, width, color='b', bottom=0)

ax.set_facecolor('g')
ax.set_title('Scores by number of simulations (board size 6x6)')
ax.set_xticks(ind + width / 2)
ax.set_xlabel('Number of simulations')
ax.set_ylabel('Number of Wins')
ax.set_xticklabels(ind_1)
ax.legend((p1[0], p2[0], p3[0]), ('Whites', 'Blacks', "Draws"))
# plt.yticks(np.arange(0, 81, 10))
#plt.savefig('Summary_SOB=' + str(SOB) + '.png')
plt.show()