Trying to understand numpy array negative index

Question

I'm trying to understand some code and I've encountered a negative index in a 3d array and I'm confused.

First a toy example:

import numpy as np
mis = np.random.rand(2, 3, 4)

np.sort(mis, axis=2)[:, :, -2]
Out[428]: 
array([[0.409, 0.406, 0.668],
       [0.806, 0.715, 0.442]])

Ok. so playing around with this toy example I changed -2 to +2:

np.sort(mis, axis=2)[:, :, 2]
Out[429]: 
array([[0.409, 0.406, 0.668],
       [0.806, 0.715, 0.442]])

Whats going on here, why is the answer the same ? In my real data the size of mis in all 3 dimensions could be much larger so I want to understand this properly. Thanks!

Edit: Note I've tried the toy with mis having dimension (2,3,20) and the results are not the same from that - but this just confuses me more!

Edoardo Pericoli · Accepted Answer · 2020-08-09 10:39:03Z

1

It returns the same result because -2 represents the second element starting from the end, and 2 represents the 3rd element starting from the beginning (the first element is indexed to zero). Therefore it returns always the third element of the array.

In the examples below I put between asteriscs the elements involved.

[[[0.22370153 0.26788364 **0.29264144** 0.83075949]
  [0.16376808 0.25345179 **0.26835547** 0.62549444]
  [0.37718569 0.61648076 **0.65733173** 0.68745722]]

[[0.1519311  0.44252181 **0.67729233** 0.83835924]
  [0.11297116 0.11889391 **0.26749958** 0.98031619]
  [0.03599794 0.35117534 **0.88740645** 0.93831347]]]

answered Aug 9, 2020 at 10:39

Edoardo Pericoli

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Comments

Mohd Kashif · Accepted Answer · 2020-08-09 10:43:25Z

1

In this problem your third dimension is of size 4 with indexes [0,1,2,3] and you have choosen -2 index which means 2nd from last which is basically your 3rd index from starting which is 2 that is why both are same

answered Aug 9, 2020 at 10:43

Mohd Kashif

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