从瞳孔的扩张收缩提取大脑EEG的delta，theta，alpha，beta，gamma等信号信息

展示得到的结果图

直接上代码

import pandas as pd
from scipy.signal import find_peaks
from scipy.fftpack import fft, fftshift, ifft
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
from scipy import signal
from scipy.signal import butter, lfilter

def Data():
    # data = pd.DataFrame(pd.read_csv(path + name[n] + '_'+str(num[j])+'.csv', encoding='CP949', engine='python'))
    data = pd.DataFrame(pd.read_csv(raw_path + str(num[j]) + '_all_gaze.csv', encoding='CP949', engine='python'))
    LPMM = np.array(data['LPMM'])
    # return LPMM
    for i in range(len(LPMM)):
        X= LPMM[i:i +59]
        return X
#delta
def butter_bandpass_delta(lowcut_delta, highcut_delta, fs, order=5):
    nyq = 0.5 * fs
    low = lowcut_delta / nyq
    high = highcut_delta / nyq
    b, a = butter(order, [low, high], btype='band')
    return b, a
def butter_bandpass_filter_delta(lowcut_delta, highcut_delta, fs, order=5):
    b, a = butter_bandpass_delta(lowcut_delta, highcut_delta, fs, order=order)
    data = Data()
    delta = signal.filtfilt(b, a, data)
    return delta
#theta
def butter_bandpass_theta(highcut_delta, highcut_theta, fs, order=5):
    nyq = 0.5 * fs
    low = highcut_delta / nyq
    high = highcut_theta / nyq
    b, a = butter(order, [low, high], btype='band')
    return b, a
def butter_bandpass_filter_theta(highcut_delta, highcut_theta, fs, order=5):
    b, a = butter_bandpass_theta(highcut_delta, highcut_theta, fs, order=order)
    data = Data()
    theta = signal.filtfilt(b, a, data)
    return theta
#alpha
def