Working on the RV challenge in Torino
The goal of this project is to analyse the RV challenge data.
Right now the repository has a template implementation of the RJ-DNest code, which includes a quasi-periodic GP to model the stellar activity RV signal. Ideally this can be easily applied to the RV challenge data, but some practicalities have to be taken into account, mainly linear trends and the fact that each data set has around 500 points.
- implement a linear trend
went ahead and added a quadratic trend. So far so good but I'm not sure about the interaction with the GP - implement HODLR inversion (issue #1)
issue is closed - implement celerite
All data is in the data folder and some metadata is in the docs and reports folders.
On Apr 22 I decided to include DNest4, eigen and celerite as submodules within the bicerin tree.
Hopefully this makes it easier and faster to get this project set up and running.
- Compile with
make - Change
OPTIONS - Run
./mainor./run - Analyse with
scripts/showresults.pyandscripts/display.py