code: def set_correlparameters(self, **kwargs):
          
          self.ncorrel = kwargs.pop('ncorrel', self.ncorrel) or 25000
          nstep = kwargs.pop('nstep', None)
          if nstep is None:
              # good step size leads to ~25,000 data points
              nstep = len(self.array[0])/float(self.ncorrel)
              nstep = int(numpy.ceil(nstep))  # catch small data sets
          kwargs['nstep'] = nstep
          self.__correlkwargs.update(kwargs)  # only contains legal kw for numkit.timeseries.tcorrel or force
          return self.__correlkwargs
docs: Set and change the parameters for calculations with  correlation functions.
  
          The parameters persist until explicitly changed.
  
          :Keywords:
             *nstep*
                 only process every *nstep* data point to speed up the FFT; if
                 left empty a default is chosen that produces roughly 25,000 data
                 points (or whatever is set in *ncorrel*)
             *ncorrel*
                 If no *nstep* is supplied, aim at using *ncorrel* data points for
                 the FFT; sets :attr:`XVG.ncorrel` [25000]
             *force*
                 force recalculating correlation data even if cached values are
                 available
             *kwargs*
                 see :func:`numkit.timeseries.tcorrel` for other options
  
          .. SeeAlso: :attr:`XVG.error` for details and references.