# jax.numpy.bitwise_andÂ¶

jax.numpy.bitwise_and(x1, x2)Â¶

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=â€™same_kindâ€™, order=â€™Kâ€™, 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,) â€“ 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 â€“ Result. This is a scalar if both x1 and x2 are scalars.

Return type

ndarray or scalar

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 by 00010001. The bit-wise AND of 13 and 17 is therefore 000000001, 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])