画loss曲线并平滑

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import matplotlib.pyplot as plt
from matplotlib.pyplot import MultipleLocator
import json
import numpy as np
data_path_1 = ""
data_path_2 = ""
def read_json(data_path, stage, key_1, key_2):
    i = 0
    iter, loss = [], []
    with open(data_path, 'r') as f:
        content = f.readlines()
        for line in content:
            if json.loads(line)["mode"] == stage:
                i=i+1
                iter.append(i)
                loss.append(json.loads(line)[key_2])
    return iter, loss
iter_1, loss_seg_1 = read_json(data_path_1, "train", "iter", "loss")
np.savetxt('test1.csv', loss_seg_1, delimiter=',')

last1 = loss_seg_1[0]
loss1=loss_seg_1
weight=0.9
for i in range(len(loss_seg_1)):
    smoothed_val1 = last1 * weight + (1 - weight) * loss_seg_1[i]
    loss1[i]=smoothed_val1
    last1= smoothed_val1


iter_2, loss_seg_2 = read_json(data_path_2, "train", "iter", "loss")
np.savetxt('test2.csv', loss_seg_2, delimiter=',')

last2 = loss_seg_2[0]
loss2=loss_seg_2
weight=0.9
for j in range(len(loss_seg_2)):
    smoothed_val2 = last2 * weight + (1 - weight) * loss_seg_2[j]
    loss2[j]=smoothed_val2
    last2 = smoothed_val2

#设置横纵坐标的名称以及对应字体格式
font = {'family' : 'Times New Roman',
'weight' : 'normal',
'size' : 10,
}
index = 0
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
plt.xlim(0, 1000)
ax.set_xlabel('iteration', font)
ax.set_ylabel('loss %', font)
ax.set_title('Seg Loss',size=10)
ax.plot(iter_1[index:], loss1[index:], label = "model_1")
ax.plot(iter_2[index:], loss2[index:], label = "model_2")
#ax.scatter(iter_1[index:], loss_seg_1[index:], marker='.', color='black', s=8)
#ax.scatter(iter_2[index:], loss_seg_2[index:], marker='.', color='red', s=8)
plt.legend(loc='upper right')
plt.show()