NumPy logic functions: logical_or() function
numpy.logical_or() function
The logical_or() function is used to compute the truth value of x1 OR x2 element-wise.
Syntax:
numpy.logical_or(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'logical_or'>
Version: 1.15.0
Parameter:
Name | Description | Required / Optional |
---|---|---|
x1, x2 | Logical OR is applied to the elements of x1 and x2. They have to be of the same shape. 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 : ndarray or bool - Boolean result with the same shape as x1 and x2 of the logical OR operation on elements of x1 and x2.
This is a scalar if both x1 and x2 are scalars.
NumPy.logical_or() method Example-1:
>>> import numpy as np
>>> np.logical_or(True, False)
Output:
True
NumPy.logical_or() method Example-2:
>>> import numpy as np
>>> np.logical_or([True, False], [False, False])
Output:
array([ True, False])
NumPy.logical_or() method Example-3:
>>> import numpy as np
>>> x = np.arange(7)
>>> np.logical_or(x < 2, x > 4)
Output:
array([ True, True, False, False, False, True, True])
Python - NumPy Code Editor:
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