Comments on: Python numpy moving average for data

By: Simple moving average and the swiss franc « quantathoughts

Simple moving average and the swiss franc « quantathoughts — Sun, 11 Sep 2011 16:37:51 +0000

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By: Greg Haskins

Greg Haskins — Thu, 16 Jun 2011 00:03:25 +0000

Nice tip, thanks. I knew there had to be an optimized way for numpy to compute rolling averages.

From the docs (http://docs.scipy.org/doc/numpy/reference/generated/numpy.convolve.html), it looks like your recipe could be even more concise by using the mode=”valid” keyword instead of slicing:

>>> WINDOW = 10
>>> data = [1,2,3,4,5,5,5,5,5,5,5,5,5,5,5]
>>> weightings = numpy.repeat(1.0, WINDOW) / WINDOW
>>> numpy.convolve(data, weightings)[WINDOW-1:-(WINDOW-1)]
array([ 4. , 4.4, 4.7, 4.9, 5. , 5. ])
>>> numpy.convolve(data, weightings, ‘valid’)
array([ 4. , 4.4, 4.7, 4.9, 5. , 5. ])

By: Anon

Anon — Tue, 26 Apr 2011 18:20:41 +0000

Thanks for spotting that! I’ve amended the example.

By: Christian

Christian — Tue, 26 Apr 2011 16:47:03 +0000

Thanks for the tip, I found it useful!

You have a slight error in your fixed initial value example: “extended_data” should be the one being convolved, not “data”.