import os
import numpy as np
from IPython import embed
from jar_functions import mean_noise_cut

datasets = [(os.path.join('D:\\jar_project\\JAR\\2020-06-22-ac\\beats-eod.dat'))]

"""
#second_try scratch
minimum = min(len(frequency[0]), len(frequency[1]))
f1 = frequency[0][:minimum]
f2 = frequency[1][:minimum]

frequency = np.array(frequency)

mean = np.mean(frequency, axis=0)

for i in range(len(minimum)):
    mean(frequency[0][i], frequency[1][i])

for f in frequency:
    print(np.mean(f))

# mean_f = np.mean(x) for x in zip(freqeuncies1, frequencies2)
"""

'''
g = [1, 2]

h = [3, 4]

z = np.array([[g], [h]])

mean0 = np.mean(z, axis=0)
mean1 = np.mean(z, axis=1)

print(mean0)
print(mean1)
'''
for dataset in datasets:
    cf = noise_reduce(dataset, 10)
    embed()