import matplotlib.pyplot as plt
from matplotlib.pyplot import MultipleLocator

i = 0
total_loss = []
total_val_loss = []
with open('total.txt', encoding='utf-8') as result_file:
    for line in result_file.readlines():
        if i % 2 == 1:
            result_list = line.split(' - ')
            total_loss.append(float(result_list[2].split()[1]))
            total_val_loss.append(float(result_list[9].split()[1]))
        i = i + 1

result_file.close()
print(total_loss)
print(len(total_loss))
print(total_val_loss)
#
# fig, ax = plt.subplots()
# ax.plot(total_loss)
# plt.show()
# plt.figure(figsize=(6, 4.5))

plt.style.use('seaborn-whitegrid')
palette = plt.get_cmap('Set1')
plt.rcParams.update({'font.size': 12})
plt.xlim(0, 100)  # 限定横轴的范围
plt.ylim(0, 50)  # 限定纵轴的范围
x_major_locator = MultipleLocator(20)
# 把x轴的刻度间隔设置为1，并存在变量里
y_major_locator = MultipleLocator(5)
# 把y轴的刻度间隔设置为10，并存在变量里

ax = plt.gca()
# ax为两条坐标轴的实例
ax.xaxis.set_major_locator(x_major_locator)
# 把x轴的主刻度设置为1的倍数
ax.yaxis.set_major_locator(y_major_locator)
# 把y轴的主刻度设置为10的倍数

# plt.plot(x, y_Supervised, marker='o', mec='r',label='Supervised')
plt.plot(total_loss, color=palette(3), marker='*', label='train_loss')
plt.plot(total_val_loss, color=palette(1), marker='^', label='val_loss')
plt.legend()  # 让图例生效
plt.margins(0)
plt.subplots_adjust(bottom=0.10)

plt.xlabel('epoch')  # X轴标签
plt.ylabel("loss")  # Y轴标签
plt.savefig('loss_result.png')
plt.show()