python怎样借助neurokit2包，读取已下载好的MIT-BIH 数据库心电数据，并定位和标记P波、T波、Q波、S波。请说明详细步骤和代码。

首先，确保已经安装了`neurokit2`和`wfdb`包。然后，可以按照以下步骤读取MIT-BIH数据库中的心电数据并定位波形：

1. 导入所需的包：

import wfdb
import neurokit2 as nk
import matplotlib.pyplot as plt

2. 下载MIT-BIH数据库中的数据：

record = wfdb.rdrecord('100', sampfrom=0, sampto=None, channels=[0], pbdir=None, m2s=True, smoothframes=False)

其中，`'100'`表示数据集中的一条记录，可以根据需要更改为其他记录号。

3. 提取心电信号：

ecg_signal = record.p_signal.flatten()

4. 滤波：

ecg_clean = nk.ecg_clean(ecg_signal, method='neurokit')

5. 心电信号预处理：

processed_signal, info = nk.ecg_process(ecg_clean, sampling_rate=record.fs)

6. 定位和标记P波、T波、Q波、S波：

rpeaks = nk.ecg_find_peaks(processed_signal, sampling_rate=record.fs)['ECG_R_Peaks']
waves = nk.ecg_delineate(ecg_clean, rpeaks, sampling_rate=record.fs, method='dwt')

其中，`rpeaks`为R峰位置数组，`waves`为包含所有波形位置和幅度信息的字典。

7. 可视化结果：

fig, axs = plt.subplots(2, 1, figsize=(12, 6), sharex=True)

axs[0].plot(ecg_clean)
axs[0].plot(waves['ECG_R_Peaks'], ecg_clean[waves['ECG_R_Peaks']], 'x', label='R-peaks')
axs[0].plot(waves['ECG_P_Onsets'], ecg_clean[waves['ECG_P_Onsets']], 'o', label='P-onsets')
axs[0].plot(waves['ECG_P_Peaks'], ecg_clean[waves['ECG_P_Peaks']], '.', label='P-peaks')
axs[0].plot(waves['ECG_P_Offsets'], ecg_clean[waves['ECG_P_Offsets']], 'o', label='P-offsets')
axs[0].plot(waves['ECG_T_Onsets'], ecg_clean[waves['ECG_T_Onsets']], '*', label='T-onsets')
axs[0].plot(waves['ECG_T_Peaks'], ecg_clean[waves['ECG_T_Peaks']], '.', label='T-peaks')
axs[0].plot(waves['ECG_T_Offsets'], ecg_clean[waves['ECG_T_Offsets']], '*', label='T-offsets')
axs[0].set_title('ECG signal with R-Peaks and Waves')
axs[0].set_xlabel('Sample #')
axs[0].set_ylabel('Amplitude')
axs[0].legend()

axs[1].plot(processed_signal['ECG_Raw'])
axs[1].plot(waves['ECG_R_Peaks'], processed_signal['ECG_Raw'][waves['ECG_R_Peaks']], 'x', label='R-peaks')
axs[1].plot(waves['ECG_P_Onsets'], processed_signal['ECG_Raw'][waves['ECG_P_Onsets']], 'o', label='P-onsets')
axs[1].plot(waves['ECG_P_Peaks'], processed_signal['ECG_Raw'][waves['ECG_P_Peaks']], '.', label='P-peaks')
axs[1].plot(waves['ECG_P_Offsets'], processed_signal['ECG_Raw'][waves['ECG_P_Offsets']], 'o', label='P-offsets')
axs[1].plot(waves['ECG_T_Onsets'], processed_signal['ECG_Raw'][waves['ECG_T_Onsets']], '*', label='T-onsets')
axs[1].plot(waves['ECG_T_Peaks'], processed_signal['ECG_Raw'][waves['ECG_T_Peaks']], '.', label='T-peaks')
axs[1].plot(waves['ECG_T_Offsets'], processed_signal['ECG_Raw'][waves['ECG_T_Offsets']], '*', label='T-offsets')
axs[1].set_title('ECG signal with R-Peaks and Waves (zoomed)')
axs[1].set_xlabel('Sample #')
axs[1].set_ylabel('Amplitude')
axs[1].set_xlim(500, 1000)
axs[1].set_ylim(-0.6, 0.6)
axs[1].legend()

plt.show()

这样就可以得到定位和标记好波形的心电图了。