numpy.isneginf() in Python

Last Updated : 23 Oct, 2020

The numpy.isneginf() function tests element-wise whether it is negative infinity or not, and returns the result as a boolean array.
Syntax :

numpy.isneginf(array, y = None)

Parameters :

array : [array_like]Input array or object whose elements, we need to test for infinity.
y     : [array_like]A boolean array with the same shape and type as x to store the result.

Return :

boolean array containing the result. For scalar input, the result is a new boolean with value
True if the input is positive or negative infinity; otherwise the value is False.
For array input, the result is a boolean array with the same shape as the input and the values
are True where the corresponding element of the input is positive or negative infinity; 
elsewhere the values are False.

Code 1 :

# Python Program illustrating 
# numpy.isneginf() method 
   
import numpy as geek  
  
print("Negative : ", geek.isneginf(1), "\n") 
  
print("Negative : ", geek.isneginf(0), "\n") 
  
# not a number 
print("Negative : ", geek.isneginf(geek.nan), "\n") 
  
#  infinity 
print("Negative : ", geek.isneginf(geek.inf), "\n") 
  
print("Negative : ", geek.isneginf(geek.NINF), "\n")  
  
x = geek.array([-geek.inf, 0., geek.inf]) 
y = geek.array([2, 2, 2]) 
print("Checking for negativity : ", geek.isneginf(x, y))  

Output :

Negative :  False 

Negative :  False 

Negative :  False 

Negative :  False 

Negative :  True 

Checking for negativity :  [1 0 0]

Code 2 :

# Python Program illustrating 
# numpy.isneginf() method 
    
import numpy as geek  
   
# Returns True/False value for each element  
b = geek.arange(18).reshape(3, 6) 
                 
print("\n",b) 
print("\nIs Negative Infifnity : \n", geek.isneginf(b)) 
  
# geek.inf  : Positive Infinity 
# geek.NINF : negative Infinity 
b = [[geek.inf],  
     [geek.NINF]] 
print("\nIs Negative Infifnity : \n", geek.isneginf(b)) 

Output :


 [[ 0  1  2  3  4  5]
 [ 6  7  8  9 10 11]
 [12 13 14 15 16 17]]

Is Negative Infifnity : 
 [[False False False False False False]
 [False False False False False False]
 [False False False False False False]]

Is Negative Infifnity : 
 [[False]
 [ True]]

References :
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.isneginf.html

Note :
These codes won’t run on online-ID. Please run them on your systems to explore the working.
.
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