46 lines
926 B
Python
46 lines
926 B
Python
import matplotlib.pyplot as plt
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import os
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import glob
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import IPython
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import numpy as np
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from IPython import embed
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from jar_functions import parse_dataset
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datasets = [(os.path.join('D:\\jar_project\\JAR\\2020-06-22-ab\\beats-eod.dat'))]
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# (os.path.join('D:\\jar_project\\JAR\\2020-06-22-ac\\beats-eod.dat'))]
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eodf = []
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deltaf = []
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stimulusf = []
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time = []
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frequency = []
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amplitude = []
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for dataset in datasets:
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t, f, a, e, d, s= parse_dataset(dataset)
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time.append(t)
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frequency.append(f)
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amplitude.append(a)
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eodf.append(e)
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deltaf.append(d)
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stimulusf.append(s)
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mean = np.mean(frequency, axis=0)
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#embed()
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#evtl. normiert darstellen (frequency / baseline frequency?)?
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#Zeitkonstante: von sec. 0 bis 63%? relative JAR
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plt.plot(time, frequency)
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plt.xlabel('time [s]')
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plt.ylabel('frequency [Hz]')
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plt.xlim([-10,200])
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plt.title('second try because first try was sold out')
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plt.show()
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