zclaytor
commented
1 year ago Thanks for pointing this out. I can give some quick explanations of the parameters here, and promise that Butterpy 1.0 (coming very soon) will be more clearly documented :-)
tau1 and tau2 define a time window for correlated emergence of active regions. Active regions are (if I recall correctly) more likely to emerge where active regions already exist, or recently existed. This is hard-coded into Butterpy with tau1=5 and tau2=15 days, meaning correlated regions can emerge between 5 and 15 days after a previous region emerges. I inherited the numbers from the code Butterpy is based on, but I believe they're roughly based on solar observations. I don't have a good reference I'm afraid.
prob sets the rate at which correlated active regions emerge, relative to the uncorrelated regions. By default it's pretty low (note that this means tau1 and tau2 effectively don't matter unless you turn prob up), and I've only recently begun turning it up to try and calibrate its effect in the regions output.
fact is related to the distribution of active region areas. The areas array (in square degrees) is constructed by areas = 100 / fact, and fact is constructed to draw areas from a log-uniform distribution from ~10 to 100 square degrees, which is based on observations of solar active regions. Hathaway (2015) "The Solar Cycle" has some information and references about sunspot areas.
Let me know if you have more questions, and thanks for your interest in butterpy!
At the beginning of regions.py, some constants are defined, but I didn't find specific explanations in your paper, why are they given these values ? Could you give some explanations or reference? Those constants includes tau1, tau2, prob, fact ... Thanks!