I have built out a lot of infrastructure for gravitational waves, and I think this first version is ready to merge into develop. For some examples, the list is on the webserver. There are five parts:
common/schema: Schema for mma_area (django model) and mma_area_hits (connects a GW and OT)
services/externalBrokers/gw: cron job to read GW alerts as soon as they appear, make an image, and insert them into the main database. Also finds OT between GW time and now to insert as hits.
pipeline/filter/mmagw.py: runs on each batch on the filter node to extract relevant OT, and insert hits (as above)
common/src/skymaps.py: Main code for pulling OT from local or main database, finding which lie in the 90% contour and have a detection after the GW, then computing probailities (2D and 3D) and inserting into the database. This is shared by the above two functions.
webserver/lasair/apps/mma_watchmap: run two queries in the webserver, one for hosted OT and one for unhosted, then display as two tables with 3D and 2D (resp.) probability density.
I have built out a lot of infrastructure for gravitational waves, and I think this first version is ready to merge into develop. For some examples, the list is on the webserver. There are five parts:
common/schema: Schema formma_area(django model) andmma_area_hits(connects a GW and OT)services/externalBrokers/gw: cron job to read GW alerts as soon as they appear, make an image, and insert them into the main database. Also finds OT between GW time and now to insert as hits.pipeline/filter/mmagw.py: runs on each batch on the filter node to extract relevant OT, and insert hits (as above)common/src/skymaps.py: Main code for pulling OT from local or main database, finding which lie in the 90% contour and have a detection after the GW, then computing probailities (2D and 3D) and inserting into the database. This is shared by the above two functions.webserver/lasair/apps/mma_watchmap: run two queries in the webserver, one for hosted OT and one for unhosted, then display as two tables with 3D and 2D (resp.) probability density.