jax.numpy.bitwise_or¶
-
jax.numpy.
bitwise_or
(x1, x2)¶ Compute the bit-wise OR of two arrays element-wise.
LAX-backend implementation of
bitwise_or()
. Original docstring below.bitwise_or(x1, x2, /, out=None, *, where=True, casting=’same_kind’, order=’K’, dtype=None, subok=True[, signature, extobj])
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
x2 (x1,) – Only integer and boolean types are handled. If
x1.shape != x2.shape
, they must be broadcastable to a common shape (which becomes the shape of the output).- Returns
out – Result. This is a scalar if both x1 and x2 are scalars.
- Return type
ndarray or scalar
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, 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])