staircase.hist_from_ecdf¶
-
staircase.
hist_from_ecdf
(ecdf, bin_edges=None, closed='left')¶ Calculates a histogram from a Stairs instance corresponding to an empirical cumulative distribution function.
Such ecdf stair instances are returned from
Stairs.ecdf_stairs()
. This function predominantly exists to allow users to store the result of a ecdf stairs instance locally, and experiment with bin_edges without requiring the recalculation of the ecdf.Parameters: - ecdf (
Stairs
) – lower bound of the step-function domain on which to perform the calculation - bin_edges (int, float, optional) – defines the bin edges for the histogram (it is the domain of the ecdf that is being binned). If not specified the bin_edges will be assumed to be the integers which cover the domain of the ecdf
- closed ({'left', 'right'}, default 'left') – determines whether the bins, which are half-open intervals, are left-closed , or right-closed
Returns: A Series, with a
pandas.IntervalIndex
, representing the values of the histogramReturn type: pandas.Series
See also
Examples
>>> import staircase as sc >>> s1_ecdf_stairs = s1.ecdf_stairs() >>> fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8,5), sharey=False, sharex=False) >>> for ax, title, stair_instance in zip(axes, ("s1", "s1 ecdf"), (s1, s1_ecdf_stairs)): ... stair_instance.plot(ax) ... ax.set_title(title)
>>> sc.hist_from_ecdf(s1_ecdf_stairs) [-1, 0) 0.25 [0, 1) 0.25 [1, 2) 0.50 dtype: float64
>>> sc.hist_from_ecdf(s1_ecdf_stairs, bin_edges=(-1,1,3)) [-1, 1) 0.5 [1, 3) 0.5 dtype: float64
- ecdf (