{"id":21494177,"url":"https://github.com/grburgess/gbm_kitty","last_synced_at":"2025-06-29T06:34:23.422Z","repository":{"id":37443566,"uuid":"327824286","full_name":"grburgess/gbm_kitty","owner":"grburgess","description":"Database, reduce, and analyze GBM data without having to know anything. 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Curiosity killed the catalog. \n\n\u003cbr/\u003e\n\u003c/div\u003e\n\n\n\n## What is this?\n\n* Creates a MongoDB database of GRBs observed by GBM. \n* Heuristic algorithms are applied to search for the background regions in the time series of GBM light curves. \n* Analysis notebooks can be generated on the fly for both time-instegrated and time-resolved spectral fitting. \n\n \u003cp style=\"color: red;\"\u003e Of course, this analysis is highly opinionated.\u003c/p\u003e\n\n## What this is not\n\nAnimal cruelty. \n\n## What can you do?\n\nAssuming you have built a local database (tis possible, see below), just type:\n\n```bash\n$\u003e get_grb_analysis --grb GRBYYMMDDxxx\n\n```\n\n\u003cimg src=\"https://raw.githubusercontent.com/grburgess/gbm_kitty/master/media/nfit.gif\" alt=\"drawing\" width=\"800\" align=\"center\"/\u003e\n\n\nmagic happens, and then you can look at your locally built GRB analysis notebook. \n\nIf you want to do more, go ahead and fit the spectra:\n\n```bash\n$\u003e get_grb_analysis --grb GRBYYMMDDxxx --run-fit\n\n```\n\n\u003cimg src=\"https://raw.githubusercontent.com/grburgess/gbm_kitty/master/media/fit.gif\" alt=\"drawing\" width=\"800\" align=\"center\"/\u003e\n\n\nAnd your automatic (but mutable) analysis is ready:\n\n\u003cimg src=\"https://raw.githubusercontent.com/grburgess/gbm_kitty/master/media/nb.gif\" alt=\"drawing\" width=\"800\" align=\"center\"/\u003e\n\n\n\n\n## Building the database\n\nThe concept behind this is to query the Fermi GBM database for basic trigger info, use this in combination tools such as [gbmgeometry](https://gbmgeometry.readthedocs.io/en/latest/) to figure out which detectors produce the best data for each GRB, and then figure out preliminary selections / parameters / setups for subsequent analysis. \n\n\n```bash\n$\u003e build_catalog --n_grbs 100 --port 8989\n\n```\n\n\nThis process starts with launching [luigi](https://luigi.readthedocs.io/en/stable/) which mangages the pipline:\n\n\n\u003cimg src=\"https://raw.githubusercontent.com/grburgess/gbm_kitty/master/media/demo.png\" alt=\"drawing\" width=\"800\" align=\"center\"/\u003e\n\nAll the of the metadata about the process is stored in a [mondoDB](https://www.mongodb.com) database which can be referenced later when building analyses.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgrburgess%2Fgbm_kitty","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgrburgess%2Fgbm_kitty","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgrburgess%2Fgbm_kitty/lists"}