zlwl-algos-new/USER/limingze/Inconsistency/plot_incon.py

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

plt.rcParams['font.sans-serif']=['SimHei']
plt.rcParams['axes.unicode_minus']=False
# 生成曲线数据
x = np.linspace(-5, 20, 10000)
y = -0.002 * x + 0.999

# 生成散点数据
data = pd.read_csv('/home/limingze/zlwl-algos/USER/limingze/Inconsistency/result/dis.csv')
x_scatter = data['pca'].values
y_scatter = data['cell_pack'].values
y_pred = -0.002 * x_scatter + 0.999

# 计算置信区间
slope, intercept = np.polyfit(x_scatter, y_scatter, 1)
y_pred = slope * x + intercept
residuals = y_scatter - (slope * x_scatter + intercept)
mse = np.mean(residuals**2)
std_err = np.sqrt(mse)
t_value = 2.093  # 自由度为 n-2，置信水平为95%，查表得到对应的t值
ci_lower = slope - t_value * std_err
ci_upper = slope + t_value * std_err

# 绘制曲线和散点图
plt.title('放电验证')
plt.xlabel('pca')
plt.ylabel('E_real/E_theo')
plt.plot(x, y, label='True Line')
plt.scatter(x_scatter, y_scatter, label='Scatter Points')
# plt.plot(x, y_pred, label='Fitted Line')

iii = 0
diff_list = []

for i in range(len(data['cell_pack'].values)):
    if (data['cell_pack'].values[i] > -0.002*data['pca'].values[i]+0.999+0.1) | (data['cell_pack'].values[i] < -0.002*data['pca'].values[i]+0.999-0.1):
        iii+=1
        if (data['cell_pack'].values[i] > -0.002*data['pca'].values[i]+0.999+0.1):
            diff_list.append((data['cell_pack'].values[i]) - (-0.002*data['pca'].values[i]+0.999+0.1))
        elif (data['cell_pack'].values[i] < -0.002*data['pca'].values[i]+0.999-0.1):
            diff_list.append((-0.002*data['pca'].values[i]+0.999+0.1) - (data['cell_pack'].values[i]))
print(sum(diff_list)/len(diff_list))
print(iii/len(data['cell_pack'].values))
# 绘制置信区间
# plt.fill_between(x, 0.011*x+1.008+t_value*std_err, 0.011*x+1.008-t_value*std_err, alpha=0.3, label='95%置信区间')
plt.fill_between(x, -0.002*x+0.999+0.1, -0.002*x+0.999-0.1, alpha=0.3, label='10%误差区间')

plt.legend()
plt.show()