dpnp.sign

dpnp.sign = <DPNPUnaryFunc 'sign'>

Returns an indication of the sign of a number for each element \(x_i\) of the input array x.

The sign function (also known as the signum function) of a number \(x_i\) is defined as

\[\begin{split}\operatorname{sign}(x_i) = \begin{cases} 0 & \textrm{if } x_i = 0 \\ \frac{x_i}{|x_i|} & \textrm{otherwise} \end{cases}\end{split}\]

where \(|x_i|\) is the absolute value of \(x_i\).

For full documentation refer to numpy.sign.

Parameters:

x{dpnp.ndarray, usm_ndarray}

Input array, expected to have a numeric 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

An array containing the element-wise result of the signum function. The data type of the returned array is determined by the Type Promotion Rules.

Limitations

Parameters where and subok are supported with their default values. Keyword argument kwargs is currently unsupported. Otherwise NotImplementedError exception will be raised.

See also

dpnp.signbit

Returns element-wise True where signbit is set (less than zero).

Examples

>>> import dpnp as np
>>> np.sign(np.array([-5., 4.5]))
array([-1.0, 1.0])
>>> np.sign(np.array(0))
array(0)
>>> np.sign(np.array(5-2j))
array([1+0j])