Created
July 25, 2017 10:06
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Visualization of a moving average
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from __future__ import division | |
import pylab | |
import numpy as np | |
""" | |
This script visualizes a trend in linear-like-shaped data | |
generated with random noise. | |
""" | |
# generate linear like function (with noise) | |
x = np.arange(100) | |
delta = np.random.uniform(-10,10, size=(100,)) | |
y = .4 * x +3 + delta | |
def movingaverage(interval, window_size): | |
window= np.ones(int(window_size))/float(window_size) | |
return np.convolve(interval, window, 'same') | |
pylab.plot(x,y,"k.") | |
y_av_5 = movingaverage(y, 2) | |
y_av_20 = movingaverage(y, 10) | |
pylab.plot(x, y_av_5,"--", label=r"$n=20$") | |
pylab.plot(x, y_av_20, label=r"$n=20$") | |
pylab.legend(loc='upper left') | |
pylab.xlim(0,100) | |
pylab.xlabel("time") | |
pylab.ylabel("data") | |
#pylab.grid(True) | |
pylab.show() | |
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