Replace values in NumPy array using indices given by another array [duplicate]

Question

I'm imagining something like this:

import numpy as np

a = np.arange(12).reshape(4,3)
rows = np.asarray([1,2,3])
cols = np.argmax(a[rows], axis=1)
indices = np.stack((rows, cols)).T
a[indices] = 1

The desired output for a would then be

[[ 0  1  2]
 [ 3  4  1]
 [ 6  7  1]
 [ 9 10  1]]

However, this doesn't work and doesn't change a. How does it work?

And what is b?

yatu
– yatu

2019-09-13 08:15:53 +00:00
Commented Sep 13, 2019 at 8:15 — yatu
– yatu, Commented Sep 13, 2019 at 8:15
Oops sorry, I forgot to rename it, too.

Rani
– Rani

2019-09-13 08:20:23 +00:00
Commented Sep 13, 2019 at 8:20 — Rani
– Rani, Commented Sep 13, 2019 at 8:20
a[rows,cols] = 1?

Divakar
– Divakar

2019-09-13 08:21:46 +00:00
Commented Sep 13, 2019 at 8:21 — Divakar
– Divakar, Commented Sep 13, 2019 at 8:21

Matt Hall · Accepted Answer · 2019-09-13 08:23:14Z

3

You are almost there. Change the penultimate line:

import numpy as np

a = np.arange(12).reshape(4,3)
rows = np.asarray([1,2,3])
cols = np.argmax(a[rows], axis=1)
a[rows, cols] = 1

answered Sep 13, 2019 at 8:23

Matt Hall

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Comments

myrtlecat · Accepted Answer · 2019-09-13 08:24:35Z

1

You can use multidimensional "fancy indexing":

import numpy as np

a = np.arange(12).reshape(4,3)
rows = np.asarray([1,2,3])
cols = np.argmax(a[rows], axis=1)
indices = np.stack((rows, cols)).T
a[rows, cols] = 1

answered Sep 13, 2019 at 8:24

myrtlecat

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