search

LSSTScienceCollaborations / StackClub

Learning the LSST software Stack, by writing jupyter notebook tutorials.
https://stackclub.readthedocs.io/
MIT License
45 stars 17 forks source link

Project : Intro To Background Models #146

Open ih64 opened 5 years ago

ih64 commented 5 years ago

Background estimation and subtraction is intimately related to science cases like source detection and measurement. I would like to understand how it is implemented in the stack, and how choices in configuration parameters impact the background model it gives.

Following discussions from Alex Drlica-Wagner and Jim Bosch, a notebook that mimics the detection-background subtraction-detection-background subtraction iterative process in processCcd can be helpful in guiding users through inner workings of the stack and flesh out bg estimation.

drphilmarshall commented 5 years ago

Sounds good, Imran! Looking fwd to learning how it works from your notebook :-)

johannct commented 5 years ago

I found the following (old!) resource with python scripts, and one of them (http://hsca.ipmu.jp/public/scripts/showBackground.html) might make for an relevant prerequisite to this project. It could be added to https://github.com/LSSTScienceCollaborations/StackClub/blob/master/Visualization/AFW_Display_Demo.ipynb. Of course I mean basically the call to butler.get("calexpBackground", dataId), not the imshow ndarray visualisation option (though this could be proposed as an alternative viz procedure in a separate notebook I presume)