numpy.logical_and

numpy.logical_and(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'logical_and'>

Compute the truth value of x1 AND x2 element-wise.

Parameters:

x1, x2 : array_like

Input arrays. x1 and x2 must be of the same shape.

out : ndarray, None, or tuple of ndarray and None, optional

A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

where : array_like, optional

Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.

**kwargs

For other keyword-only arguments, see the ufunc docs.

Returns:

y : ndarray or bool

Boolean result with the same shape as x1 and x2 of the logical AND operation on corresponding elements of x1 and x2. This is a scalar if both x1 and x2 are scalars.

See also

logical_or, logical_not, logical_xor, bitwise_and

Examples

>>> np.logical_and(True, False)
False
>>> np.logical_and([True, False], [False, False])
array([False, False])

>>> x = np.arange(5)
>>> np.logical_and(x>1, x<4)
array([False, False,  True,  True, False])