Access multiple columns in a 3D numpy array without looping

Question

I have a large 3D array A with shape (N, M, L).

I have a list of coordinates of columns I want to access stored in a 2D array B:

[[i1 j1]
 [i2 j2]
 [i3 j3]
 ....   ]

I have something that works OK but involves looping over B and accessing A multiple times. Is there a way to avoid this using slicing or another method?

My code so far:

data_out = []
for p in B:
    i, j = p
    col = A[:, i, j]
    data_out.append(col)

Mad Physicist · Accepted Answer · 2020-09-29 12:20:40Z

2

Use fancy indexing:

A[(slice(None), *B.T)].T

The explicit parentheses are necessary to use star expansion, which means that you have to write out : explicitly as slice(None). You can also do

A[:, B[:, 0], B[:, 1]].T

edited Sep 29, 2020 at 12:20

answered Sep 29, 2020 at 12:09

Mad Physicist

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1 Comment

Mad Physicist Over a year ago

@Divakar. Fixed. I forgot that B was being split into 1D and relied on its shape :)

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