{"id":21375458,"url":"https://github.com/lsst/fgcmcal","last_synced_at":"2025-07-13T09:33:19.251Z","repository":{"id":38429576,"uuid":"90074525","full_name":"lsst/fgcmcal","owner":"lsst","description":"Global Photometric Calibration in LSST with FGCM","archived":false,"fork":false,"pushed_at":"2025-07-01T16:40:59.000Z","size":1538,"stargazers_count":3,"open_issues_count":5,"forks_count":4,"subscribers_count":57,"default_branch":"main","last_synced_at":"2025-07-01T17:42:13.952Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lsst.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2017-05-02T20:21:05.000Z","updated_at":"2025-05-23T01:20:26.000Z","dependencies_parsed_at":"2023-11-10T10:47:36.831Z","dependency_job_id":"e2e5e515-4dfe-4ad9-af6a-0b2012ffef2c","html_url":"https://github.com/lsst/fgcmcal","commit_stats":null,"previous_names":[],"tags_count":465,"template":false,"template_full_name":null,"purl":"pkg:github/lsst/fgcmcal","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lsst%2Ffgcmcal","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lsst%2Ffgcmcal/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lsst%2Ffgcmcal/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lsst%2Ffgcmcal/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lsst","download_url":"https://codeload.github.com/lsst/fgcmcal/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lsst%2Ffgcmcal/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265120579,"owners_count":23714492,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-22T09:11:05.430Z","updated_at":"2025-07-13T09:33:18.858Z","avatar_url":"https://github.com/lsst.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"fgcmcal: Global Photometric Calibration in LSST with FGCM\n=========================================================\n\nThis is the LSST stack code to interface with the Forward Global Calibration\nMethod (FGCM) third-party package to perform global photometric survey\ncalibration.  Please see [Burke, Rykoff, et\nal. 2018](http://adsabs.harvard.edu/abs/2018AJ....155...41B) for the paper\ndescribing the method, and https://github.com/lsst/fgcm/tree/lsst-dev (the LSST\nfork of https://github.com/erykoff/fgcm) for the Python implementation that is\nused by this `fgcmcal` package.\n\nFGCM performs a global photometric calibration, starting with instrumental\nfluxes and producing top-of-the-atmosphere standard fluxes by forward modeling\nthe atmosphere and instrument, including chromatic corrections.  Overall\nabsolute calibration is reduced to the computation of one offset per band,\nwhich `fgcmcal` can optionally compute based on a reference catalog.\n\nCurrently, the `fgcmcal` package will only run on HSC data within the stack,\nbut this is being actively worked on.  In general, the FGCM code should be\ncompatible with any survey with the following requirements:\n\n* Visit/CCD based observations\n* Transmission curves for each filter, preferably for each CCD\n* MODTRAN4 is required to generate new atmosphere tables.\n* Atmosphere tables for the following telescope locations are included:\n    - Blanco telescope at CTIO (DES)\n    - Subaru telescope at Mauna Kea (HSC)\n    - LSST telescope at Cerro Pachon (LSST)\n* Enough memory to hold all the observations in memory at once.\n    - A full run of four years of DES survey data can be run on a machine\n      with 128 Gb RAM and 32 processors in less than a day.\n\n\nInstalling the `fgcm` and `fgcmcal` Packages\n--------------------------------------------\n\nAs of DM-16128, both `fgcm` (the third-party package) and `fgcmcal` (the stack\ninterface) are distributed with `lsst_distrib`.  Therefore, with a stack\ninstallation after `w_2018_47` or v17.0 or later, setting up\n`fgcmcal` is as simple as:\n\n```\nsetup lsst_distrib\n```\n\nOr, to only get `fgcmcal` and required dependencies:\n\n```\nsetup fgcmcal\n```\n\nFGCM Cookbook\n-------------\n\nPlease see [the FGCM Cookbook](cookbook/README.md) for doing a test run on HSC\nRC data on `lsst-dev` and to learn the control flow of `fgcmcal`.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flsst%2Ffgcmcal","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flsst%2Ffgcmcal","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flsst%2Ffgcmcal/lists"}