flopscope.

flopscope.numpy.heaviside

fnp.heaviside(*args, **kwargs)[flopscope source][numpy source]

Compute the Heaviside step function.

Adapted from NumPy docs np.heaviside

Areacore
Typecounted
NumPy Refnp.heaviside
Cost
numel(output)\text{numel}(\text{output})
Flopscope Context

Heaviside step function element-wise.

The Heaviside step function [1]_ 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).

out:ndarray, None, or tuple of ndarray and None, optional

A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

where:array_like, optional

This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.

**kwargs

For other keyword-only arguments, see the ufunc docs.

Returns

out:ndarray or scalar

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

References

footnote
1

Wikipedia, "Heaviside step function",
https://en.wikipedia.org/wiki/Heaviside_step_function

Examples

>>> import flopscope.numpy as fnp
>>> flops.heaviside([-1.5, 0, 2.0], 0.5)
array([ 0. ,  0.5,  1. ])
>>> flops.heaviside([-1.5, 0, 2.0], 1)
array([ 0.,  1.,  1.])