What is numpy.isinf() in Python?
Python’s numpy.isinf() is used to test if an element is a positive/negative infinity or not. It tests an array element-wise and returns a Boolean array as the output.
Syntax
numpy.isinf() is declared as follows:
numpy.isinf(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'isinf'>
In the syntax above, x is the non-optional parameter and the rest are optional parameters.
A universal function (ufunc) is a function that operates on ndarrays in an element-by-element fashion. The
inf()method is a universal function.
Parameters
The numpy.isinf() method takes the following compulsory parameter:
x[array-like] - input array.
The numpy.isinf() method takes the following optional parameters:
Parameter | Description |
out | represents the location into which the output of the method is stored. |
where | True value indicates that a universal function should be calculated at this position. |
casting | controls the type of datacasting that should occur. The same_kind option indicates that safe casting or casting within the same kind should take place. |
dtype | represents the desired data type of the array. |
order | controls the memory layout order of the output function. The option K means reading the elements in the order they occur in memory. |
subok | decides if subclasses should be made or not. If True, subclasses will be passed through. |
Return value
numpy.isinf() returns Boolean values True or False depending on the following:
-
It returns
Trueifxis positive infinity or negative infinity -
It returns
Falsein all other cases
If
xis scalar, the return type is also scalar. Else return type is a boolean array.
Examples
The example below shows the use of numpy.isinf() on the elements a and b:
import numpy as npa = 23b = np.infprint (np.isinf(a))print (np.isinf(b))
The following example shows the use of numpy.isinf() on the array arr1:
import numpy as nparr1 = np.array([2, -np.inf, 0, np.nan])print (np.isinf(arr1))
The following example shows the use of numpy.isinf() on the array arr2:
import numpy as nparr2 = np.array([[1, 2, 3], [np.inf, np.nan, -np.inf]])print (np.isinf(arr2))
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