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How to find maximum negative and minimum positive number in a numpy array?

I am given an array containing both positive and negative numbers.

import numpy as np
arr = np.array([-10.2, -5.3, -2.1, 0, 1.2, 3.4])

I would like to find the index corresponding to the maximum negative number and to a minimum positive number. In the above, my expected outcome is 2 and 4. Is there any numpy trick to achieve this? I have found a solution in this link, but I would like to know how this could be done through numpy functions: Finding index of largest negative and smallest positive element in array

like image 985
matttree Avatar asked Sep 19 '25 05:09

matttree


2 Answers

Replace non negative values with -inf, then use argmax to find the largest negative:

np.where(arr < 0, arr, -np.inf).argmax()
# 2

Similarly replace non positive values with inf then use argmin to find the smallest positive:

np.where(arr > 0, arr, np.inf).argmin()
# 4
like image 194
Psidom Avatar answered Sep 21 '25 20:09

Psidom


If your array is always sorted (as in the provided example), then:

# input
Out[66]: array([-10.2,  -5.3,  -2.1,   0. ,   1.2,   3.4])

# obtain a `signed` boolean mask 
In [75]: sign_mask = np.sign(arr)

# compute derivative and obtain index for max_negative element
In [76]: max_neg_idx = np.where(np.diff(sign_mask, append=1) == 1)[0][0]

# add +2 to that to get index for min_positive element
In [77]: min_pos_idx = max_neg_idx + 2
like image 20
kmario23 Avatar answered Sep 21 '25 20:09

kmario23