numpy.heaviside¶

numpy.
heaviside
(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'heaviside'>¶ Compute the Heaviside step function.
The Heaviside step function is defined as:
0 if x < 0 heaviside(x, h0) = h0 if x == 0 1 if x > 0
where h0 is often taken to be 0.5, but 0 and 1 are also sometimes used.
Parameters: x : array_like
Input values.
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 freshlyallocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.
where : array_like, optional
Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.
**kwargs
For other keywordonly arguments, see the ufunc docs.
h0 : array_like
The value of the function at x = 0.
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 freshlyallocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.
where : array_like, optional
Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.
**kwargs
For other keywordonly arguments, see the ufunc docs.
Returns: out : ndarray
The output array, elementwise Heaviside step function of x.
Notes
New in version 1.13.0.
References
Examples
>>> np.heaviside([1.5, 0, 2.0], 0.5) array([ 0. , 0.5, 1. ]) >>> np.heaviside([1.5, 0, 2.0], 1) array([ 0., 1., 1.])