42 lines
776 B
Python
42 lines
776 B
Python
import os
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import numpy as np
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from IPython import embed
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from jar_functions import mean_noise_cut
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datasets = [(os.path.join('D:\\jar_project\\JAR\\2020-06-22-ac\\beats-eod.dat'))]
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"""
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#second_try scratch
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minimum = min(len(frequency[0]), len(frequency[1]))
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f1 = frequency[0][:minimum]
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f2 = frequency[1][:minimum]
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frequency = np.array(frequency)
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mean = np.mean(frequency, axis=0)
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for i in range(len(minimum)):
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mean(frequency[0][i], frequency[1][i])
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for f in frequency:
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print(np.mean(f))
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# mean_f = np.mean(x) for x in zip(freqeuncies1, frequencies2)
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"""
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'''
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g = [1, 2]
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h = [3, 4]
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z = np.array([[g], [h]])
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mean0 = np.mean(z, axis=0)
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mean1 = np.mean(z, axis=1)
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print(mean0)
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print(mean1)
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'''
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for dataset in datasets:
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cf = noise_reduce(dataset, 10)
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embed() |