eeg-101/python_tools/SamplingRateTest.py at master · NeuroTechX/eeg-101 · GitHub

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import pandas as pd

import numpy as np

import matplotlib.pyplot as plt

import argparse

import sys

# Calculates sampling rate and plots 4 channel specgram of EEG data.csv passed in as in command line arg

eegData = pd.read_csv(sys.argv[1])

#eegData = pd.read_csv('Filtered_EEG3.csv')

time = (eegData['Timestamp (ms)'][eegData.shape[0] - 1] - eegData['Timestamp (ms)'][0]) / 1000

samples = eegData.shape[0] - 1

samplingRate = samples/time

print('estimated sampling rate: ', samplingRate)

plt.figure()

plt.subplot(2,2,1)

plt.specgram(eegData['Electrode 1'], Fs=samplingRate, interpolation='bilinear', noverlap=198)

plt.ylim(0,65)

plt.subplot(2,2,2)

plt.specgram(eegData['Electrode 2'], Fs=samplingRate, interpolation='bilinear', noverlap=198)

plt.ylim(0,65)

plt.subplot(2,2,3)

plt.specgram(eegData['Electrode 3'], Fs=samplingRate, interpolation='bilinear', noverlap=198)

plt.ylim(0,65)

plt.subplot(2,2,4)

plt.specgram(eegData['Electrode 4'], Fs=samplingRate, interpolation='bilinear', noverlap=198)

plt.ylim(0,65)

plt.show()