I am back at considering what kind of default amplitude model is suitable for nifty. I think the current
SLAmplitude operator does not provide a sensible prior on the zeromode. Therefore, I think we should change it.
What I do for Lognormal problems is the following: set the zeromode of the amplitude operator A constantly to one and have as sky model: exp(ht @ U @ (A*xi)), where U is an operator which turns a standard normal distribution into a flat distribution with a lower and an upper bound.
My problem is that
demos/getting_started_3.py does not show how to properly set up a prior on the zero mode.