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. Ifx1.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 ({"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.])