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numpy.isposinf() in Python

  • Last Updated : 23 Oct, 2020

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 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 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 Infifnity : \n", geek.isposinf(b))
  
# geek.inf means Infinity
# geek.NINF means negative infinity
b = [[geek.inf], 
     [geek.NINF]]
print("\nIs Positive Infifnity : \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 Infifnity : 
 [[False False False False False False]
 [False False False False False False]
 [False False False False False False]]

Is Positive Infifnity : 
 [[ 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-ID. Please run them on your systems to explore the working.
.
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