The idea is to make it possible to switch easily between scaled and unscaled parameter values:
- read in the unscaled parameter values from the MC data
- interpolate and minimize with scaled parameters
- print out the unscaled minimization result
unscaled refers here to the "raw" parameter values used for controlling the generator. scaled parameters are calculated from the unscaled parameters and given upper and lower boundaries so that the resulting parameters lie between 0 and 1.
We do this to avoid numerical precision problems during interpolation/minimization.
The corresponding code is in source:trunk/professor/tools/parameter.py. The idea is that the unscaled parametervalues never change, but the scaling boundaries can change.
- register each ParameterPoint with its Scaler instance during ParameterPoint.__init__(...) and add a method to the Scaler class.