pysteps.postprocessing.probmatching.shift_scale(R, f, rain_fraction_trg, second_moment_trg, **kwargs)#

Find shift and scale that is needed to return the required second_moment and rain area. The optimization is performed with the Nelder-Mead algorithm available in scipy. It assumes a forward transformation ln_rain = ln(rain)-ln(min_rain) if rain > min_rain, else 0.

  • R (array_like) – The initial array to be shift and scaled.

  • f (function) – The inverse transformation that is applied after the shift and scale.

  • rain_fraction_trg (float) – The required rain fraction to be matched by shifting.

  • second_moment_trg (float) – The required second moment to be matched by scaling. The second_moment is defined as second_moment = var + mean^2.

  • scale (float) – Optional initial value of the scale parameter for the Nelder-Mead optimisation. Typically, this would be the scale parameter estimated the previous time step. Default: 1.

  • max_iterations (int) – Maximum allowed number of iterations and function evaluations. More details: Deafult: 100.

  • tol (float) – Tolerance for termination. More details: Default: 0.05*second_moment_trg, i.e. terminate the search if the error is less than 5% since the second moment is a bit unstable.


  • shift (float) – The shift value that produces the required rain fraction.

  • scale (float) – The scale value that produces the required second_moment.

  • R (array_like) – The shifted, scaled and back-transformed array.