pysteps.postprocessing.probmatching.shift_scale¶
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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.
Parameters: - 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.
Returns: - 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.
Other Parameters: - 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: https://docs.scipy.org/doc/scipy/reference/optimize.minimize-neldermead.html Deafult: 100.
- tol : float
Tolerance for termination. More details: https://docs.scipy.org/doc/scipy/reference/optimize.minimize-neldermead.html 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.