NumPy Logic functions: isinf() function

Last update on August 19 2022 21:51:10 (UTC/GMT +8 hours)

numpy.isinf() function

The isinf() function is used to test element-wise for positive or negative infinity.

Returns a boolean array of the same shape as x, True where x == +/-inf, otherwise False.

Syntax:

numpy.isinf(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'isinf'>

Version: 1.15.0

Parameter:

Name	Description	Required / Optional
x	Input values array_like	Required
out	A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. ndarray, None, or tuple of ndarray and None	Optional
where	Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. array_like	Optional
**kwargs	For other keyword-only arguments	Required

Returns:
y : bool (scalar) or boolean ndarray - True where x is positive or negative infinity, false otherwise. This is a scalar if x is a scalar.

Notes:
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754).

Errors result if the second argument is supplied when the first argument is a scalar, or if the first and second arguments have different shapes.

NumPy.isinf() method Example-1:

>>> import numpy as np
>>> np.isinf(np.inf)

Output:

True

NumPy.isinf() method Example-2:

>>> import numpy as np
>>> np.isinf(np.nan)

Output:

False

NumPy.isinf() method Example-3:

>>> import numpy as np
>>> np.isinf(np.NINF)

Output:

True

NumPy.isinf() method Example-4:

>>> import numpy as np
>>> np.isinf([np.inf, -np.inf, 1.0, np.nan])

Output:

array([ True,  True, False, False])

NumPy.isinf() method Example-5:

>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([3, 3, 3])
>>> np.isinf(x, y)

Output:

array([1, 0, 1])

NumPy.isinf() method Example-6:

>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([3, 3, 3])
>>> np.isinf(x, y)
>>> y

Output:

array([1, 0, 1])

Python - NumPy Code Editor:

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