import numpy as np import pandas as pd import matplotlib.pyplot as plt import pyhht # 读取csv文件数据 data = pd.read_csv('77.csv', header=None) time = data.iloc[:, 0].values charge = data.iloc[:, 1].values # EMD分解 decomposer = pyhht.EMD(charge) imfs = decomposer.decompose()fig, axs = plt.subplots(nrows=imfs.shape[0]+1, ncols=1, figsize=(10, 15)) axs[0].plot(time, charge, label='Original') axs[0].set_xlabel('Time') axs[0].set_ylabel('Charge') axs[0].legend() for i in range(imfs.shape[0]): axs[i+1].plot(time, imfs[i], label=f'IMF{i+1}') axs[i+1].set_xlabel('Time') axs[i+1].set_ylabel('Charge') axs[i+1].legend() residuals = charge - np.sum(imfs, axis=0) axs[imfs.shape[0]+1].plot(time, residuals, label='Residuals') axs[imfs.shape[0]+1].set_xlabel('Time') axs[imfs.shape[0]+1].set_ylabel('Charge') axs[imfs.shape[0]+1].legend() axs[0].set_title('Original Signal') for i in range(imfs.shape[0]): axs[i+1].set_title(f'IMF {i+1}') axs[imfs.shape[0]+1].set_title('Residuals') plt.tight_layout() plt.show()以上代码运行时报出以下错误IndexError: index 4 is out of bounds for axis 0 with size 请修改

可以尝试检查一下数据的维度，看看是否符合预期。同时也可以将代码中的行数和列数调整一下，确保能够正确显示图像。示例代码如下：

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

# 读取csv文件数据 
data = pd.read_csv('77.csv', header=None) 
time = data.iloc[:, 0].values 
charge = data.iloc[:, 1].values 

# EMD分解 
decomposer = pyhht.EMD() 
imfs = decomposer.decompose(charge)

fig, axs = plt.subplots(nrows=imfs.shape[0]+2, ncols=1, figsize=(10, 15)) 

axs[0].plot(time, charge, label='Original') 
axs[0].set_xlabel('Time') 
axs[0].set_ylabel('Charge') 
axs[0].legend() 

for i in range(imfs.shape[0]): 
    axs[i+1].plot(time, imfs[i], label=f'IMF{i+1}') 
    axs[i+1].set_xlabel('Time') 
    axs[i+1].set_ylabel('Charge') 
    axs[i+1].legend() 

residuals = charge - np.sum(imfs, axis=0) 
axs[imfs.shape[0]+1].plot(time, residuals, label='Residuals') 
axs[imfs.shape[0]+1].set_xlabel('Time') 
axs[imfs.shape[0]+1].set_ylabel('Charge') 
axs[imfs.shape[0]+1].legend() 

axs[0].set_title('Original Signal') 

for i in range(imfs.shape[0]): 
    axs[i+1].set_title(f'IMF {i+1}') 

axs[imfs.shape[0]+1].set_title('Residuals') 
plt.tight_layout() 
plt.show()

另外需要注意的是，EMD分解需要先初始化一个EMD对象，然后再调用decompose方法进行处理，因此示例代码中对EMD对象的初始化进行了修正。