I have a 3D numpy array and I want to shuffle it block wise in a particular axis while keeping the data in that block in it's original state. For instance I have an np array of shape (50, 140, 23) and I want to shuffle by making blocks of (50, 1, 23) on axis=1. So 140 blocks will be created and blocks should be shuffled on axis=1 while maintaining the data in blocks in it's original order. I read documentation about np.random.shuffle(x) but this only shuffles in first axis and we can't provide a block size to it.
Is there any function in numpy or a quick way to do this?
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2 Answers
You can use a random permutation:
A = sum(np.ogrid[0:0:50j,:140,0:0:23j])
rng = np.random.default_rng()
Ashuff = A[:,rng.permutation(140),:]
Comments
Perhaps swapping axis, shuffling and swapping back might do the trick for you?
a = np.random.random((50,140,23))
b = np.swapaxes(a, 0, 1)
np.random.shuffle(b)
c = np.swapaxes(b, 0, 1)
