numpy.logical_or¶

numpy.
logical_or
(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'logical_or'>¶ Compute the truth value of x1 OR x2 elementwise.
Parameters:  x1, x2 : array_like
Logical OR is applied to the elements of x1 and x2. If
x1.shape != x2.shape
, they must be broadcastable to a common shape (which becomes the shape of the output). out : ndarray, None, or tuple of ndarray and None, optional
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 freshlyallocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.
 where : array_like, optional
Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.
 **kwargs
For other keywordonly arguments, see the ufunc docs.
Returns:  y : ndarray or bool
Boolean result of the logical OR operation applied to the elements of x1 and x2; the shape is determined by broadcasting. This is a scalar if both x1 and x2 are scalars.
See also
Examples
>>> np.logical_or(True, False) True >>> np.logical_or([True, False], [False, False]) array([ True, False])
>>> x = np.arange(5) >>> np.logical_or(x < 1, x > 3) array([ True, False, False, False, True])