reisecker
commented
2 years ago Hi,
while you are right that duplicating the Proksch routines is not much work (in fact Calonne was available quite early) a little care had to be given that did require a solid effort.
First, of course it would be nice to offer all parameterizations in the graphical interface without having to rework the GUI every time. Second, one really has to watch it a little concerning the internal properties of the algorithms; first of all in order not to introduce and propagate a bias the moving window properties must be set according to the respective publications in the GUI plots, the csv export, and the API calls. With hasty work it is easy to neglect this as there were a couple of places SMPyn would fetch these values from.
Anyway, the Calonne/RIchter and King parameterizations are now available, and the interface to add new coefficient sets was much improved. From now on this will be as easy as you say (see e. g. commit 353f998).
v1.1.0 is out and we would be happy if you would give the official package another try and come back with further feedback.
Some pages to get you started: Using different parameterizations Developing new parameterizations
Regards
Hi,
I was wondering if different parameterizations could be implemented to choose in snowmicropyn. So besides Proksch2015 in addition Calonne2020 (Alpine snowpack) and King2020 (Arctic sea ice). It wouldn't be much work, but probably a nice addition. Locally, I have in principle only used proksch2015.py as base and exchanged the coefficients and names/references to create calonne2020.py and king2020.py.