import json
import matplotlib.pyplot as plt
import numpy as np
with open("record_random.json",'r',encoding='utf-8') as load_f:
    load_dict = json.load(load_f)
    action_random = load_dict['record_random']
    grade_random = load_dict['record_random2']

with open("record_learned.json",'r',encoding='utf-8') as load_f:
    load_dict = json.load(load_f)
    action_learned = load_dict['record_learned']
    grade_learned = load_dict['record_learned2']

for i in range(len(action_random)):
    plt.figure()
    attack = np.ma.masked_where(np.array(action_random[i]) == 0, grade_random[i])
    sleep = np.ma.masked_where(np.array(action_random[i]) == 1, grade_random[i])
    plt.scatter(range(len(grade_random[i])), attack, color = 'blue', label = 'attack')
    plt.scatter(range(len(grade_random[i])), sleep, color = 'orange', label = 'sleep')
    # plt.plot(range(len(grade_random[i])), grade_random[i])
    plt.title('Score vs Iteration')
    plt.xlabel('iteration')
    plt.ylabel('score')
    plt.legend()
    name = 'record_random' + str(i) + '.jpg'
    plt.savefig(name)
    plt.close()

for i in range(len(action_learned)):
    plt.figure()
    attack = np.ma.masked_where(np.array(action_learned[i]) == 0, grade_learned[i])
    sleep = np.ma.masked_where(np.array(action_learned[i]) == 1, grade_learned[i])
    plt.scatter(range(len(grade_learned[i])), attack, color = 'blue', label = 'attack')
    plt.scatter(range(len(grade_learned[i])), sleep, color = 'orange', label = 'sleep')
        # plt.plot(range(len(grade_learned[i])), grade_learned[i])
    plt.title('Score vs Iteration')
    plt.xlabel('iteration')
    plt.ylabel('score')
    plt.legend()
    name = 'record_learned' + str(i) + '.jpg'
    plt.savefig(name)
    plt.close()