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Home/ Questions/Q 7009469
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Editorial Team
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Editorial Team
Asked: May 27, 20262026-05-27T21:51:58+00:00 2026-05-27T21:51:58+00:00

Let’s say I have an numpy array A of size n x m x

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Let’s say I have an numpy array A of size n x m x k and another array B of size n x m that has indices from 1 to k.
I want to access each n x m slice of A using the index given at this place in B,
giving me an array of size n x m.

Edit: that is apparently not what I want!
[[ I can achieve this using take like this:

A.take(B)
]] end edit

Can this be achieved using fancy indexing?
I would have thought A[B] would give the same result, but that results
in an array of size n x m x m x k (which I don’t really understand).

The reason I don’t want to use take is that I want to be able to assign this portion something, like

A[B] = 1

The only working solution that I have so far is

A.reshape(-1, k)[np.arange(n * m), B.ravel()].reshape(n, m)

but surely there has to be an easier way?

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1 Answer

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  1. Editorial Team
    Editorial Team
    2026-05-27T21:51:59+00:00Added an answer on May 27, 2026 at 9:51 pm

    Suppose

    import numpy as np
    np.random.seed(0)
    
    n,m,k = 2,3,5
    A = np.arange(n*m*k,0,-1).reshape((n,m,k))
    print(A)
    # [[[30 29 28 27 26]
    #   [25 24 23 22 21]
    #   [20 19 18 17 16]]
    
    #  [[15 14 13 12 11]
    #   [10  9  8  7  6]
    #   [ 5  4  3  2  1]]]
    
    B = np.random.randint(k, size=(n,m))
    print(B)
    # [[4 0 3]
    #  [3 3 1]]
    

    To create this array,

    print(A.reshape(-1, k)[np.arange(n * m), B.ravel()])
    # [26 25 17 12  7  4]
    

    as a nxm array using fancy indexing:

    i,j = np.ogrid[0:n, 0:m]
    print(A[i, j, B])
    # [[26 25 17]
    #  [12  7  4]]
    
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