Mean of NxM elements of array

Question

I want to average each NxM elements in the AxB array and that the dimension of the output matrix to be (A/N)x(B/M).

For example, let us suppose that I have:

a = np.arange(24).reshape((4,6))

array([[ 0,  1,  2,  3,  4,  5],
       [ 6,  7,  8,  9, 10, 11],
       [12, 13, 14, 15, 16, 17],
       [18, 19, 20, 21, 22, 23]])

I want to average each 2x3 elements of "a" array and that the output to be:

array([[av1, av2],
       [av3, av4]])

where:

av1 = (0+1+2+6+7+8)/6

av2 = (3+4+5+9+10+11)/6

av3 = (12+13+14+18+19+20)/6

av4 = (15+16+17+21+22+23)/6

What is the most efficient method to do that in python? I want to do that with an array of 5424x5424 elements.

Perhaps you should show what you've already tried and then seek help or improvements? It's always easier for users to help when they can see your own efforts first — Martin, Oct 22 '19 at 16:19

Mad Physicist · Accepted Answer · 2019-10-22T19:16:20.813

0

As of version 1.7, np.mean accepts multiple axes to average. This makes your task easier because you can create as many extra dimensions as you need and process all of them without having to do any extra work.

 np.mean(a.reshape(2, 2, 2, 3), axis=(1, 3))

edited Oct 22 '19 at 19:16

answered Oct 22 '19 at 16:46

Mad Physicist

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Thank you for your answer, it help me alot. I only modified some numbers and I got the result that I wanted: a.reshape((2,2,2,3)).mean(axis=(1,3)) array([[ 4., 7.], [16., 19.]]) – joaohenry23 Oct 22 '19 at 17:55
@joaohenry23. Please do not make substantial edits to answers other than your own. – Mad Physicist Oct 23 '19 at 00:05

Mean of NxM elements of array

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