- 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.
- x1, x2array_like
Input arrays. If
x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).
- outndarray, None, or tuple of ndarray and None, optional
- wherearray_like, optional
out=None, locations within it where the condition is False will remain uninitialized.
For other keyword-only arguments, see the ufunc docs.
- yndarray or bool
Boolean result of the logical AND operation applied to the elements of x1 and x2; the shape is determined by broadcasting. This is a scalar if both x1 and x2 are scalars.
>>> 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])
&operator can be used as a shorthand for
np.logical_andon boolean ndarrays.
>>> a = np.array([True, False]) >>> b = np.array([False, False]) >>> a & b array([False, False])