分析下这段代码：from mne import Epochs, pick_types, events_from_annotations from mne.io import concatenate_raws from mne.io import read_raw_edf from mne.datasets import eegbci import mne import numpy as np import pandas as pd import glob import numpy as np import os from scipy import signal, fft import matplotlib.pyplot as plt path_time = "ttt.csv" # 患者发病发病起止时间表 file_dir = "chb01" path_save = "data" # 选择患者共有的通道 ch = ['FP1-F7', 'F7-T7', 'T7-P7', 'P7-O1', 'FP1-F3', 'F3-C3', 'C3-P3', 'P3-O1', 'FP2-F4', 'F4-C4', 'C4-P4', 'P4-O2', 'FP2-F8', 'F8-T8', 'T8-P8-0', 'P8-O2', 'FZ-CZ', 'CZ-PZ', 'P7-T7', 'T7-FT9', 'FT9-FT10', 'FT10-T8'] sfreq = 256 bandFreqs = [ {'name': 'Delta', 'fmin': 1, 'fmax': 3}, {'name': 'Theta', 'fmin': 4, 'fmax': 7}, {'name': 'Alpha', 'fmin': 8, 'fmax': 13}, {'name': 'Beta', 'fmin': 14, 'fmax': 31}, {'name': 'Gamma', 'fmin': 31, 'fmax': 40} ] # 定义STFT函数 def STFT(epochsData, sfreq, band=bandFreqs): f, t, Zxx = signal.stft(epochsData, fs=sfreq) bandResult = [] for iter_freq in band: index = np.where((iter_freq['fmin'] < f) & (f < iter_freq['fmax'])) portion = np.zeros(Zxx.shape, dtype=np.complex_) portion[:, :, index, :] = Zxx[:, :, index, :] _, xrec = signal.istft(portion, fs=sfreq) # 保存滤波后的结果 bandResult.append(xrec) return bandResult time = pd.read_csv(path_time,index_col="chb") files = sorted(os.listdir(file_dir)) for file in files: if os.path.splitext(file)[1] == '.edf': f = os.path.splitext(file)[0] f_str = str(os.path.splitext(os.path.splitext(file)[0])[0]) if i == 0: raws = mne.io.read_raw_edf(file_dir+"/" + file,preload=True,verbose=False) raws.pick_channels(ch) raws.filter(0.1,50.,method='iir') raw_d,raw_t = raws[:,:] i+=1 else: i+=1 if f_str in time.index: time.loc[f_str]['start'] = time.loc[f_str]['start'] * 256 + len(raw_t) time.loc[f_str]['end'] = time.loc[f_str]['end']*256 + len(raw_t) raw = mne.io.read_raw_edf(file_dir+"/" + file, preload=True,verbose=False) raw.pick_channels(ch) raw.filter(0.1,50.,method='iir') raws = concatenate_raws([raws,raw]) raws_d, raw_t = raws[:,:] d, t = raws[:,:] data = d*1e6 stft = STFT(d, sfreq) pointNum = d.shape[0] stftFreq = np.abs(fft.fft(stft[:pointNum])) data = np.transpose(stftFreq, axes=(1,3,2,0)) np.save(path_save+"/"+file_dir+".npy",data)

这段代码主要是导入了需要用到的一些Python库和函数，并定义了一个字符串变量path_time。其中，import语句用于导入特定的Python库和其函数或变量；from语句用于从Python库中导入特定的函数或变量；字符串变量path_time用于存储CSV文件的路径。此外，这段代码还没有执行任何具体的操作或功能，只是声明了准备要使用的工具。