Once the associations are made, the FittedStarList is matched to a reference external catalog (the USNO-A2 by default), and the objects on common are put into a a RefStarList. Each MeasuredStar holds a pointer to a FittedStar, which materializes the association. The outcome is a set of MeasuredStarList's (one per CcdImage) and a list of common objects (a FittedStarList containing FittedStar s). Those are then projected on some tangent plane for matching. ![]() It relies on WCS's of the input images to convert the pixel-unit coordinates for the input catalogs into sidereal coordinates. The Associations class aims at linking together measurements of the same object from the input catalogs, using spatial proximity on the sky. In the short term, we are considering adding the support for SIP WCS's. Wa also rely on some extra informations form the chip header such as an identifier for the exposure (for multi-chip imagers). Scamp produces and swarp reads) are properly handled. The gnomonic WCS's with distortions encoded using the "PV" scheme (what e.g. Not all WCS types are properly decoded, because we do not rely on the wcslib. The input images have to provide measurements of astronomical objects with a position expressed in pixels, together with a WCS read from a fits image header (on an ascii version thereof). All the routines that only deal with geometry (such as matching two lists based on spatial proximity) are coded for BaseStarList's and work for anything that derives from BaseStar (as long as BaseStar is the first on the inheritance list). All stars used here derive from BaseStar which contains a point with its errors (FatPoint), and a flux. The astronomical objects are presented to the code in the form of std::list's of SomethingStar (which can as well be galaxies). In the last version of this task, Gastro has only been used to associate the measurements of the same object, and the associations were written to disk and processed in python. Gastro has been used for this task in the context of the CFHTLS where sets of dithered exposures on dense stellar fields were taken in order to evaluate non-uniformities of he photometric response after flatfielding. to measure the lightcurve of a transient, or to measure the ellipticipty of galaxies on a set of exposures without stacking, but with a common position estimation.Īveraging photometric measurements of the same objects, possibly adjusting some parameters describing the photometric response of the instrument. This is typically used prior to carrying out simultaneous measurements in the image set, e.g. ![]() ![]() ![]() This is what Scamp (from the Astromatix suite) does, with however a slightly different approach.Įstablishing transformations from image to image within an image set. This is typically used prior to stacking. It then contains several possible uses of these associations :Įstablishing a global astrometric solution for a set of images using both the objects in common and a reference catalog. Gastro rather uses the input image WCS's to associate measurements of the same object. Gastro does not aim at setting up WCS's of individual images using some reference catalog (this is part of Poloka). It heavily relies on the Poloka software. It aims at providing an environment for fitting WCS's and geometrical transformations between astronomical images. Date May 2015 Attention This document is not complete!
0 Comments
Leave a Reply. |