jax.numpy.heaviside

jax.numpy.heaviside(x1, x2, /)

Compute the Heaviside step function.

LAX-backend implementation of numpy.heaviside().

Original docstring below.

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 (array_like) – Input values.

• x2 (array_like) – The value of the function when x1 is 0. If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).

Returns:

out – The output array, element-wise Heaviside step function of x1. This is a scalar if both x1 and x2 are scalars.

Return type:

ndarray or scalar

References