dingo_d - 1 year ago 148

Python Question

I am playing in Python a bit again, and I found a neat book with examples. One of the examples is to plot some data. I have a .txt file with two columns and I have the data. I plotted the data just fine, but in the exercise it says: Modify your program further to calculate and plot the running average of the data, defined by:

`$Y_k=\frac{1}{2r}\sum_{m=-r}^r y_{k+m}$`

where

`r=5`

`y_k`

So far I have this:

`from pylab import plot, ylim, xlim, show, xlabel, ylabel`

from numpy import linspace, loadtxt

data = loadtxt("sunspots.txt", float)

r=5.0

x = data[:,0]

y = data[:,1]

plot(x,y)

xlim(0,1000)

xlabel("Months since Jan 1749.")

ylabel("No. of Sun spots")

show()

So how do I calculate the sum? In Mathematica it's simple since it's symbolic manipulation (Sum[i, {i,0,10}] for example), but how to calculate sum in python which takes every ten points in the data and averages it, and does so until the end of points?

I looked at the book, but found nothing that would explain this :\

heltonbiker's code did the trick ^^ :D

`from __future__ import division`

from pylab import plot, ylim, xlim, show, xlabel, ylabel, grid

from numpy import linspace, loadtxt, ones, convolve

import numpy as numpy

data = loadtxt("sunspots.txt", float)

def movingaverage(interval, window_size):

window= numpy.ones(int(window_size))/float(window_size)

return numpy.convolve(interval, window, 'same')

x = data[:,0]

y = data[:,1]

plot(x,y,"k.")

y_av = movingaverage(y, 10)

plot(x, y_av,"r")

xlim(0,1000)

xlabel("Months since Jan 1749.")

ylabel("No. of Sun spots")

grid(True)

show()

And I got this:

Thank you very much ^^ :)

Recommended for you: Get network issues from **WhatsUp Gold**. **Not end users.**

Answer Source

~~Best~~ One common way to apply a moving/sliding average (or any other sliding window function) to a signal is by using `numpy.convolve()`

.

```
def movingaverage(interval, window_size):
window = numpy.ones(int(window_size))/float(window_size)
return numpy.convolve(interval, window, 'same')
```

Here, interval is your `x`

array, and `window_size`

is the number of samples to consider. The window will be centered on each sample, so it takes samples before and after the current sample in order to calculate the average. Your code would become:

```
plot(x,y)
xlim(0,1000)
x_av = movingaverage(interval, r)
plot(x_av, y)
xlabel("Months since Jan 1749.")
ylabel("No. of Sun spots")
show()
```

Hope this helps!

Recommended from our users: **Dynamic Network Monitoring from WhatsUp Gold from IPSwitch**. ** Free Download**