numpy matrix minimum applied to second array

Question

I really want to avoid looping for this simple problem...

import numpy as np

x = np.array([[1,2,3,4], [5,6,1,2], [7,4,9,1]])
y = np.array([[2,5,6,7], [1,2,3,4], [1,2,3,4]])
print(x)
[[1 2 3 4]
 [5 6 1 2]
 [7 4 9 1]]

maxidx = np.argmax(x, axis=0)
print(maxidx)
[2 1 2 0]

So far so good. Now all I want it the entries in the y array for these indices. Since I get the index for each column only, I am not sure how to apply this correctly without looping or creating a list...thanks! 😊

What's your expected output?

Kasravnd
– Kasravnd

2015-08-24 09:44:08 +00:00
Commented Aug 24, 2015 at 9:44 — Kasravnd
– Kasravnd, Commented Aug 24, 2015 at 9:44
The output should be [1 2 3 7]

HansSnah
– HansSnah

2015-08-24 09:49:18 +00:00
Commented Aug 24, 2015 at 9:49 — HansSnah
– HansSnah, Commented Aug 24, 2015 at 9:49

Ashwini Chaudhary · Accepted Answer · 2015-08-24 09:59:37Z

2

Use multidimensional-indexing:

>>> indices = np.argmax(x, axis=0)
>>> y[indices, np.arange(x.shape[1])]
array([1, 2, 3, 7])

edited Aug 24, 2015 at 9:59

answered Aug 24, 2015 at 9:56

Ashwini Chaudhary

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