search

jmackereth / asteroestimate

python-based detection probabilities and scaling relations for asteroseismology (Work In Progress!)
MIT License
3 stars 4 forks source link

Implement the scatter in the intrinsic mapping function as part of the Monte Carlo process over the input values. #6

Open grd349 opened 4 years ago

grd349 commented 4 years ago

The function that maps the observables to Numax is uncertain. We don't know how much by. There is an issue to decide what the magnitude of this uncertainty is. Here we need to decide how to include the uncertainty into the Monte Carlo process.

grd349 commented 4 years ago

Probably the simplest way to proceed is to add a keyword to the Monte Carlo wrapper function that adds a little extra noise on to each numax value in the Monte Carlo samples. This is probably OK for starters.

alexlyttle commented 4 years ago

I'm happy to take this on considering it's a "good first issue" and will fork the repo now to get to know it a little! I'll start with your simple suggestion and see where things go from there?

grd349 commented 4 years ago

Great @alexlyttle . Thinking about it, I think the intrinsic scatter should be some percentage of the numax predicted value. @jmackereth are discussing this on slack. I think I would be tempted to start with adding 1% scatter to all predicted values. You might want to branch off of @jmackereth 's branch that is adding in the Monte Carlo over the input parameters.

alexlyttle commented 4 years ago

Thanks @grd349, I see now this goes hand-in-hand with Ted's MC branch. I have forked the repo so will give that a go now!