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Numpy isposinf: How to Use np isposinf() Method

The isposinf() function is defined under numpy, which can be imported as import numpy as np, and we can create multidimensional arrays.

Numpy isposinf()

The isposinf() function in Numpy tests if an element is a positive infinity or not. We have already written an article about whether an element is negative infinity or not using the Numpy isneginf() function.

The numpy isposinf() function returns the result in Boolean values for scalar values and  Boolean array for boolean array inputs.

Syntax

numpy.isposinf(array or the scalar value, out(output array))

Parameters

The isposinf() function takes two parameters out of which 1 parameter is optional.

The first parameter is an input array or the input for which we want to check whether it is +ve infinity

The second one is the n-dimensional array, which is optional. It is an output array that is placed with the result.

Return Value

The function returns the Boolean array, which has the result if we pass the array and Boolean value True or False if we pass a scalar value according to the value passed.

Example programs on isposinf() method in Python

Write a program to show the working of isposinf() function in Python.

# app.py

import numpy as np

# Scalar Values
print("Positive Infinity - : ", np.isposinf(933), "\n")
print("Positive Infinity - : ", np.isposinf(444), "\n")

# checking for infinity value
print("Positive Infinity - : ", np.isposinf(np.inf), "\n")
print("Positive Infinity - : ", np.isposinf(np.NINF), "\n")

Output

python3 app.py
Positive Infinity -:  False

Positive Infinity -:  False

Positive Infinity -:  True

Positive Infinity -:  False

In this example, we have seen that bypassing two scalar values in the function isposinf() we get False as it doesn’t represent any positive infinity. Still, using +ve infinite values, we’re getting True

Write a program to use arange() function and create an array then check for each value of the elements if it’s positive infinity or not.

See the following code.

# app.py

import numpy as np

a = np.arange(24).reshape(6, 4)
print("List: ")
print(a)
print("\n")
print("Positive Infinity: ")
print(np.isposinf(a))

Output

python3 app.py
List:
[[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]
 [12 13 14 15]
 [16 17 18 19]
 [20 21 22 23]]


Positive Infinity:
[[False False False False]
 [False False False False]
 [False False False False]
 [False False False False]
 [False False False False]
 [False False False False]]

In the above code example, we can see that after creating an array using the np.arange() function, we have checked for each element if it’s positive infinity or not.

That’s it for this tutorial.

See also

Numpy isinf()

Numpy isnan()

Numpy isscalar()

Numpy iscomplex()

Numpy isrealobj()

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