numpy.logical_and — NumPy v1.13 Manual (original) (raw)

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 theufunc 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.

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 theufunc 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.

Examples

np.logical_and(True, False) False np.logical_and([True, False], [False, False]) array([False, False], dtype=bool)

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