numpy.bitwise_or()

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

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:

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.

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.

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)

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.bitwise_or.html

doc_NumPy

2025-01-10 15:47:30

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