Stairs.
sample
(x, how='right', aggfunc=None, window=(0, 0), lower_how='right', upper_how='left')¶Evaluates the value of the step function at one, or more, points.
This method can be used to directly sample values of the corresponding step function at the points provided, or alternatively calculate aggregations over some window around each point. The first of these is performed when aggfunc is None.
If aggfunc is None then the results of this function should be considered as \(\lim_{x \to z^{}} f(x)\) or \(\lim_{x \to z^{+}} f(x)\), when how = ‘left’ or how = ‘right’ respectively. See A note on interval endpoints for an explanation.
If aggfunc is not None then a window, around each point x (referred to as the focal point), over which to aggregate is required. The window is defined by two values paired into an arraylike parameter called window. These two scalars are the distance from the focal point to the left boundary of the window, and the right boundary of the window respectively.
The function can be called using parentheses. See example below.
Parameters: 


Returns:  
Return type:  float, or list of floats 
See also
Examples
>>> s1.plot()
>>> s1(3.5)
1
>>> s1([1, 2, 4.5, 6])
[1, 0, 1, 0]
>>> s1([1, 2, 4.5, 6], how="left")
[0, 1, 1, 0]
>>> s1([1, 2, 4.5], aggfunc="mean", window=(0.5, 0.5))
[0.5, 0.5, 1.0]
>>> s1([1, 2, 4.5], aggfunc="max", window=(0.5, 0.5))
[1, 1, 1]
>>> s1([1, 2, 4.5], aggfunc="max", window=(0.5, 0.5), lower_how="left")
[1, 1, 1]
>>> s1([1, 2, 4.5], aggfunc="max", window=(0.5, 0.5), upper_how="right")
[1, 1, 0]