jax.numpy.bitwise_and¶
-
jax.numpy.
bitwise_and
(x1, x2)¶ Compute the bit-wise AND of two arrays element-wise.
LAX-backend implementation of
bitwise_and()
. Original docstring below.bitwise_and(x1, x2, /, out=None, *, where=True, casting=’same_kind’, order=’K’, dtype=None, subok=True[, signature, extobj])
Computes the bit-wise AND of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator
&
.- 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_and()
,bitwise_or()
,bitwise_xor()
binary_repr()
Return the binary representation of the input number as a string.
Examples
The number 13 is represented by
00001101
. Likewise, 17 is represented by00010001
. The bit-wise AND of 13 and 17 is therefore000000001
, or 1:>>> np.bitwise_and(13, 17) 1
>>> np.bitwise_and(14, 13) 12 >>> np.binary_repr(12) '1100' >>> np.bitwise_and([14,3], 13) array([12, 1])
>>> np.bitwise_and([11,7], [4,25]) array([0, 1]) >>> np.bitwise_and(np.array([2,5,255]), np.array([3,14,16])) array([ 2, 4, 16]) >>> np.bitwise_and([True, True], [False, True]) array([False, True])