Question

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Grouping 2D numpy array in average

I need to ‘down-sample’ a 2d array of shape (2880, 5760) to shape (360, 720) by averageing over blocks of 8×8 elements of the original array. Which would be an efficient way of doing that using NumPy?

EDIT
I just realize I need to do this on masked_arrays, so the chained mean() won’t do.

Answer 1

Here is the way which works for masked arrays as well

import numpy as np, numpy.random
nx = 100
ny = 101
bx = 3
by = 4
arr = np.random.uniform(size = (nx * bx, ny * by))
arr = np.ma.masked_array(arr,arr<.1)
rebinarr = np.swapaxes(arr.reshape(nx, bx, ny, by), 1, 2).reshape(nx, ny, bx * by).mean(axis=2)
print rebinarr.shape
>> (100,101)