The numpy.isposinf() function tests element-wise whether it is positive infinity or not and returns the result as a boolean array.
Syntax :
numpy.isposinf(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
# Python Program illustrating # numpy.isposinf() method import numpy as geek print ( "Positive : " , geek.isposinf( 1 ), "\n" ) print ( "Positive : " , geek.isposinf( 0 ), "\n" ) # not a number print ( "Positive : " , geek.isposinf(geek.nan), "\n" ) # infinity print ( "Positive : " , geek.isposinf(geek.inf), "\n" ) print ( "Positive : " , geek.isposinf(geek.NINF), "\n" ) x = geek.array([ - geek.inf, 0. , geek.inf]) y = geek.array([ 2 , 2 , 2 ]) print ( "Checking for positivity : " , geek.isposinf(x, y)) |
Output :
Positive : False Positive : False Positive : False Positive : True Positive : False Checking for positivity : [0 0 1]
Code 2 :
Python
# Python Program illustrating # numpy.isposinf() method import numpy as geek # Returns True/False value for each element b = geek.arange( 18 ).reshape( 3 , 6 ) print ( "\n" ,b) print ( "\nIs Positive Infinity : \n" , geek.isposinf(b)) # geek.inf means Infinity # geek.NINF means negative infinity b = [[geek.inf], [geek.NINF]] print ( "\nIs Positive Infinity : \n" , geek.isposinf(b)) |
Output :
[[ 0 1 2 3 4 5] [ 6 7 8 9 10 11] [12 13 14 15 16 17]] Is Positive Infinity : [[False False False False False False] [False False False False False False] [False False False False False False]] Is Positive Infinity : [[ True] [False]]
References :
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.isposinf.html#numpy.isposinf
Note :
These codes won’t run on online IDE’s. So please, run them on your systems to explore the working.
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