Apply numpy index to matrix

Question

I have spent the last hour trying to figure this out

Suppose we have

import numpy as np
a = np.random.rand(5, 20) - 0.5
amin_index = np.argmin(np.abs(a), axis=1)
print(amin_index)
> [ 0 12  5 18  1] # or something similar

this does not work:

a[amin_index]

So, in essence, I need to find the minima along a certain axis for the array np.abs(a), but then extract the values from the array a at these positions. How can I apply an index to just one axis?

Probably very simple, but I can't get it figured out. Also, I can't use any loops since I have to do this for arrays with several million entries. thanks 😊

Alex Riley · Accepted Answer · 2014-12-23 22:49:01Z

1

One way is to pass in the array of row indexes (e.g. [0,1,2,3,4]) and the list of column indexes for the minimum in each corresponding row (your list amin_index).

This returns an array containing the value at [i, amin_index[i]] for each row i:

>>> a[np.arange(a.shape[0]), amin_index]
array([-0.0069325 ,  0.04268358, -0.00128002, -0.01185333, -0.00389487])

This is basic indexing (rather than advanced indexing), so the returned array is actually a view of a rather than a new array in memory.

edited Dec 23, 2014 at 22:49

answered Dec 23, 2014 at 22:22

Alex Riley

178k46 gold badges274 silver badges247 bronze badges

Sign up to request clarification or add additional context in comments.

1 Comment

HansSnah Over a year ago

Thats it, thanks so much. I finally can go to sleep 😊

Imanol Luengo · Accepted Answer · 2014-12-23 22:21:58Z

1

Is because argmin returns indexes of columns for each of the rows (with axis=1), therefore you need to access to each row at those particular columns:

a[range(a.shape[0]), amin_index]

answered Dec 23, 2014 at 22:21

Imanol Luengo

16k3 gold badges52 silver badges68 bronze badges

Comments

score 0 · Accepted Answer · 2014-12-23 22:56:36Z

0

Why not simply do np.amin(np.abs(a), axis=1), it's much simpler if you don't need the intermediate amin_index array via argmin?

Numpy's reference page is an excellent resource, see "Indexing".

Edits: Timing is always useful:

In [3]: a=np.random.rand(4000, 4000)-.5

In [4]: %timeit np.amin(np.abs(a), axis=1)
10 loops, best of 3: 128 ms per loop

In [5]: %timeit a[np.arange(a.shape[0]), np.argmin(np.abs(a), axis=1)]
10 loops, best of 3: 135 ms per loop

edited Dec 23, 2014 at 22:56

answered Dec 23, 2014 at 22:24

user3407196

1 Comment

HansSnah Over a year ago

Hey. I can't use that since I am not looking for the minima in the np.abs(a) array. I am only interested in these positions and then get the minima from a itself. ;)

Collectives™ on Stack Overflow

Apply numpy index to matrix

3 Answers 3

1 Comment

Comments

1 Comment

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

3 Answers 3

1 Comment

Comments

1 Comment

Your Answer

Sign up or log in

Post as a guest

Related