dpnp.logical_not

dpnp.logical_not = <DPNPUnaryFunc 'logical_not'>

Computes the logical NOT for each element \(x_i\) of input array x.

For full documentation refer to numpy.logical_not.

Parameters:

x{dpnp.ndarray, usm_ndarray}

Input array, may have any data type.

out{None, dpnp.ndarray, usm_ndarray, tuple of ndarray}, optional

Output array to populate. Array must have the correct shape and the expected data type. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

Default: None.

order{None, "C", "F", "A", "K"}, optional

Memory layout of the newly output array, if parameter out is None.

Default: "K".

Returns:

outdpnp.ndarray of bool dtype

An array containing the element-wise logical NOT results.

Limitations

Parameters where and subok are supported with their default values. Otherwise NotImplementedError exception will be raised.

See also

dpnp.logical_and

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

dpnp.logical_or

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

dpnp.logical_xor

Compute the truth value of x1 XOR x2, element-wise.

Notes

At least one of x1 or x2 must be an array.

If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).

Examples

>>> import dpnp as np
>>> x = np.array([True, False, 0, 1])
>>> np.logical_not(x)
array([False,  True,  True, False])

>>> x = np.arange(5)
>>> np.logical_not(x < 3)
array([False, False, False,  True,  True])