| Abstract | To automate source detection, two-dimensional light profile Sérsic modelling and catalogue compilation in large survey applications, we introduce a new code Galaxy Analysis over Large Areas: Parameter Assessment by galfitting Objects from SExtractor (galapagos). Based on a single set-up, galapagos can process a complete set of survey images. It detects sources in the data, estimates a local sky background, cuts postage stamp images for all sources, prepares object masks, performs Sérsic fitting including neighbours and compiles all objects in a final output catalogue. For the initial source detection, galapagos applies SExtractor, while galfit is incorporated for modelling Sérsic profiles. It measures the background sky involved in the Sérsic fitting by means of a flux growth curve. galapagos determines postage stamp sizes based on SExtractor shape parameters. In order to obtain precise model parameters, galapagos incorporates a complex sorting mechanism and makes use of modern CPU's multiplexing capabilities. It combines SExtractor and galfit data in a single output table. When incorporating information from overlapping tiles, galapagos automatically removes multiple entries from identical sources. galapagos is programmed in the Interactive Data Language (idl). We test the stability and the ability to properly recover structural parameters extensively with artificial image simulations. Moreover, we apply galapagos successfully to the STAGES data set. For one-orbit Hubble Space Telescope data, a single 2.2-GHz CPU processes about 1000 primary sources per 24h. Note that galapagos results depend critically on the user-defined parameter set-up. This paper provides useful guidelines to help the user make sensible choices. |
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