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 wonβt run on online-ID. Please run them on your systems to explore the working.
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