dpnp.heaviside

dpnp.heaviside(x1, x2, out=None, where=True, order='K', dtype=None, subok=True, **kwargs)

Compute the Heaviside step function.

The Heaviside step function is defined as:

                      0   if x1 < 0
heaviside(x1, x2) =  x2   if x1 == 0
                      1   if x1 > 0

where x2 is often taken to be 0.5, but 0 and 1 are also sometimes used.

Parameters:

  • x1 ({dpnp.ndarray, usm_ndarray, scalar}) -- Input values. Both inputs x1 and x2 can not be scalars at the same time.

  • x2 ({dpnp.ndarray, usm_ndarray, scalar}) -- The value of the function when x1 is 0. Both inputs x1 and x2 can not be scalars at the same time. If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).

  • out ({None, dpnp.ndarray, usm_ndarray}, optional) --

    Output array to populate. Array must have the correct shape and the expected data type.

    Default: None.

  • order ({None, "C", "F", "A", "K"}, optional) --

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

    Default: "K".

Returns:

out -- The output array, element-wise Heaviside step function of x1.

Return type:

dpnp.ndarray

Limitations

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

Examples

>>> import dpnp as np
>>> a = np.array([-1.5, 0, 2.0])
>>> np.heaviside(a, 0.5)
array([0. , 0.5, 1. ])
>>> np.heaviside(a, 1)
array([0., 1., 1.])