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 bitwise OR of two arrays elementwise.
Computes the bitwise OR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator 
.
Parameters: 


Returns: 

See also
logical_or
, bitwise_and
, bitwise_xor
binary_repr
The number 13 has the binaray representation 00001101
. Likewise, 16 is represented by 00010000
. The bitwise OR of 13 and 16 is then 000111011
, 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, 2147483647], dtype=np.int32), ... np.array([4, 4, 4, 2147483647], dtype=np.int32)) array([ 6, 5, 255, 2147483647]) >>> np.bitwise_or([True, True], [False, True]) array([ True, True])
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https://docs.scipy.org/doc/numpy1.17.0/reference/generated/numpy.bitwise_or.html