numpy.bitwise_or¶
-
numpy.
bitwise_or
(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'bitwise_or'>¶ Compute the bit-wise OR of two arrays element-wise.
Computes the bit-wise OR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator
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.Parameters: x1, x2 : array_like
Only integer and boolean types are handled.
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 freshly-allocated 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 keyword-only arguments, see the ufunc docs.
Returns: out : array_like
Result.
See also
logical_or
,bitwise_and
,bitwise_xor
binary_repr
- Return the binary representation of the input number as a string.
Examples
The number 13 has the binaray representation
00001101
. Likewise, 16 is represented by00010000
. The bit-wise OR of 13 and 16 is then000111011
, or 29:>>> np.bitwise_or(13, 16) 29 >>> np.binary_repr(29) '11101'
>>> np.bitwise_or(32, 2) 34 >>> np.bitwise_or([33, 4], 1) array([33, 5]) >>> np.bitwise_or([33, 4], [1, 2]) array([33, 6])
>>> np.bitwise_or(np.array([2, 5, 255]), np.array([4, 4, 4])) array([ 6, 5, 255]) >>> np.array([2, 5, 255]) | np.array([4, 4, 4]) array([ 6, 5, 255]) >>> np.bitwise_or(np.array([2, 5, 255, 2147483647L], dtype=np.int32), ... np.array([4, 4, 4, 2147483647L], dtype=np.int32)) array([ 6, 5, 255, 2147483647]) >>> np.bitwise_or([True, True], [False, True]) array([ True, True])