SciPy

numpy.bitwise_or

numpy.bitwise_or(x1, x2[, out]) = <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 |.

Parameters:

x1, x2 : array_like

Only integer and boolean types are handled.

out : ndarray, optional

Array into which the output is placed. Its type is preserved and it must be of the right shape to hold the output. See doc.ufuncs.

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 by 00010000. The bit-wise 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, 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)

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