How to replace elements of one array with rows of another array in Numpy

Question

I have two arrays of variable length and content (simplified example):

A = np.array([[0.25, 0.25], [0.25, 0.75], [0.75, 0.25], [0.75, 0.75], [0.8, 0.9] ...]) 
B = np.array([0, 1, 2, 4, 0, 3, 3, ...])

What is the best/fastest way to get an array where every element of B is replaced with the corresponding row from A (B as index) so that the result would be:

C = [[0.25, 0.25], [0.25, 0.75], [0.75, 0.25], [0.8, 0.9], [0.25, 0.25], [0.75, 0.75], [0.75, 0.75], ...]

I am somehow at a loss (still a beginner with problems getting my head around numpy).

Edit/addendum: Forgot to mention: I would like to avoid loops since the arrays are big and time is critical.

Mad Physicist · Accepted Answer · 2018-02-16 03:12:52Z

2

You can just use direct indexing:

C = A[B, :]

Results in

[[ 0.25  0.25]
 [ 0.25  0.75]
 [ 0.75  0.25]
 [ 0.8   0.9 ]
 [ 0.25  0.25]
 [ 0.75  0.75]
 [ 0.75  0.75]]

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edited Feb 16, 2018 at 3:12

answered Feb 16, 2018 at 3:07

Mad Physicist

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2 Comments

Koyagi Over a year ago

Thx, exactly what i was looking for. Hope i will some day get a better grasp of Numpy. :)

Mad Physicist Over a year ago

@kukuschi. Keep using it and you will. It's inevitable.

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