code: def decimate_percentile(self, a, maxpoints, **kwargs):
          
          return self._decimate(numkit.timeseries.percentile_histogrammed_function, a, maxpoints, **kwargs)
docs: Return data *a* percentile-decimated on *maxpoints*.
  
          Histograms each column into *maxpoints* bins and calculates
          the percentile *per* in each bin as the decimated data, using
          :func:`numkit.timeseries.percentile_histogrammed_function`. The
          coarse grained time in the first column contains the centers
          of the histogram time.
  
          If *a* contains <= *maxpoints* then *a* is simply returned;
          otherwise a new array of the same dimensions but with a
          reduced number of  *maxpoints* points is returned.
  
          .. Note::
  
             Assumes that the first column is time.
  
          :Keywords:
  
          *per*
              percentile as a percentage, e.g. 75 is the value that splits
              the data into the lower 75% and upper 25%; 50 is the median [50.0]
  
          .. SeeAlso:: :func:`numkit.timeseries.regularized_function` with :func:`scipy.stats.scoreatpercentile`