The astrometry function
in the astronomy & astrophysics toolbox for MATLAB
Table of Contents
Description
The astrometry function is a method in the SIM class that solve for the astrometry of astronomical images. The function attempts to find matches between stellar patterns in the image and in a reference catalog, and use it to fit an astrometric solution to the image. The code put emphesize on robustness and to find solutions which are good over the entire field of view. The code is described in Ofek et al. (2018).
This file is accessible through the manual package (i.e. manual.mextractor).
Credit
If you are using this code or products in your scientific publication please give a reference to Ofek (2014; ascl.soft 07005) and Ofek et al. (2018).
License
Unless specified otherwise this code and products are released under the GNU general public license version 3.
Installation
See http://weizmann.ac.il/home/eofek/matlab/doc/install.html for installation instruction and additional documentation.
Examples
Tips: The astrometry function has many parameters and for some images/instruments fine tunning of these paramaeters is required. Therefore, we suggest starting by reading the help pages and inspecting the examples
First, select an image to work on - for example - download an image from the PTF archive using VO.PTF.wget_corrim.m:
!wget http://irsa.ipac.caltech.edu/ibe/data/ptf/images/level1/proc/2012/04/29/f2/c0/p5/v1/PTF_201204293281_i_p_scie_t075231_u013181106_f02_p100019_c00.fits
S = FITS.read2sim('PTF_2012*.fits');
S = S(1);
The astrometry command can run on multiple images, but here for simplicity we use a single image.
You can start by extracting sources in the image using (e.g., mextractor or ImUtil.Im.sextractor). Note that this step is optional and if the catalog is not provided in the SIM object (S), then astrometry will execute mextractor (or sextractor; see input parameters):
S = mextractor(S);
Now, the catalog of sources identifyied in the image are stored in S.Cat and the catalog column names are in S.Col and S.ColCell.
Next you can execute the astrometry function:
[R, S] = astrometry(S,'Flip',[1 -1;1 1; -1 -1]);
The first input argument is alawys a SIM object (astrometry is a SIM method). The SIM object is followed by pairs of keyword, value. In this case the 'Flip' keyword indicate which coordinates flip should be attempted. Each row in the 'Flip' keyword value (e.g., [1 -1]), indicate how to flip the X and Y coordinates of the image, respectively, prior for matching the image sources with the reference catalog.
By default astrometry will attempt to read the approximate coordinate and scale of the image from the header, however, the use can also provide these parameters directly using the syntax:
[R,S]=astrometry(S,'Scale',1,'RA',3.14,'Dec',0.1); % coordinates in radians
To see a full list of keywords and their default value type
help astrometry
In these examples astrometry returns two output arguments. The second output argument is a SIM object with the input image (or catalog) and an updated header, with the new WCS values.
To inspect the image and its WCS you can display the image in ds9:
ds9(S)
The first output argument (R) is a structure array that contains the details of the solution:
R
This structure contains a lot of meta data on the solution and its quality.
For example 'MinAssymErr' is the asymptotic rms in the units specified in the 'CooUnits' field. You can use this information to verify the quality of the solution:
% show the number of fitted stars in each 512x512 pix sub images
R.Block_NsrcN
% show the robust rms in each subimage
R.Block_rmsN
% plot the residuals(arcsec) as a function of magnitude
semilogy(R.RefMag(R.FlagG),R.Resid(R.FlagG).*3600,'.')
Note the 'FlagG' field contains a vector of logical indicating the stars used in the solution (after sigma clipping). By default all the stars vectors (e.g., 'Resid', 'RefMag', 'RefColor', ...) contains all the stars and not only the stars used in the solution.