Compute bitwise OR of two arrays, elementwise.
When calculating the bitwise OR between two elements, x and y, each element is first converted to its binary representation (which works just like the decimal system, only now we’re using 2 instead of 10):
where W is the bitwidth of the type (i.e., 8 for a byte or uint8), and each and is either 0 or 1. For example, 13 is represented as 00001101, which translates to .
The bitwise operator is the result of
where is the OR operator, which yields one whenever either or is 1.
Parameters:  x1, x2 : array_like


Returns:  out : array_like

See also
bitwise_and, bitwise_xor, logical_or
Examples
We’ve seen that 13 is represented by 00001101. Similary, 16 is represented by 00010000. The bitwise OR of 13 and 16 is therefore 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.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], dtype=bool)