GSFC/UMd RATIR Pipeline Repository

Directories:

• code/

• images/

• sandbox/

1. Setup

2. Reduction

3. Photometry

4. Setup

1. Dependencies:

   • IDL

   • Python

     • ADD PACKAGE DEPENDENCIES?

   • SExtractor

   • SWarp

   • Scamp (INSERT DETAILS FOR INSTALL)

   • cdsclient package

   Most can be installed using Macports.

2. Run startup.sh in Unix shell to source code:

   source startup.sh

3. Alter pipeautoproc.par to point to full path of autoastrometry.py on individual computer (under code/reduction/ratauto)

4. Reduction

1. Enter python environment.

2. Load the preprocessing commands (this will also load astro_functs.py as af):

   In [1]: from rat_preproc import *

3. Create lists of fits files for specified cameras (must be done for each directory containing FITs files you'll be using):

   In [2]: ratlist( workdir = 'path/to/FITS/files/', cams = [0,1,2,3] )

4. Select calibration frames you want to use:

   In [3]: ratdisp_calib( ftype=af.FLAT_NAME or af.BIAS_NAME, workdir='path/to/FITS/flats/', cams=[0,1,2,3], auto=True, amin=0.1, amax=0.8 )

5. Select science frames you want to use:

   In [4]: ratdisp( workdir='path/to/FITS/files/', targetdir='path/to/new/FITS/files/', cams=[0,1,2,3], auto=True )

6. Make master bias or flat frame:

   In [5]: mkmaster( af.BIAS_NAME or af.FLAT_NAME, bands='ALL', workdir='.', fmin=5 )

More detailed instructions can be found in reduction_instructions.rtf or code comments in rat_preproc.py and astro_functs.py.

This IDL script should be run from the data directory (the directory above processed data and reduction folder)

ratautoproc, datadir='raw/', redo=1

• datadir specifies where processed data is stored (should be in lower directory), will run all data in this directory

• Will save to specified directory (imworkingdir) in pipeautoproc.par

• redo keyword overwrites previously reduction processed files

• Additional keywords:

  • start

  • stop

  • step

  • only (allows you to run particular steps if you don't want to run full reduction)

  • nocrclean (if set skips cosmic ray cleaning)

• Runs these steps in this order unless specified:

  • steps = ['prepare', 'flatten', 'makesky', 'skysub', 'crclean', 'astrometry', 'stack']

Description of each step:

1. Prepare (autopipeprepare.pro, pipeprepare.pro)

   • Header information manipulation and bias subtraction for images with master bias files

2. Flatten (autopipeimflatten.pro, flatpipeproc.pro)

   • Divides master flat for each filter

3. Makesky (autopipemakesky.pro, skypipecombine.pro)

   • Creates master sky by removing sources (using outlier rejection) and then median iterative sigma clipping for each pixel

4. Skysub (autopipeskysub.pro, skypipeproc.pro)

   • Subtracts sky, then subtracts median, then adds 1000

5. Crclean (autopipecrcleanim.pro, pzap_perley.pro)

   • Cosmic ray cleaning, details fuzzy

6. Astrometry (autopipeastrometry.pro, vlt_autoastrometry.py)

   • Fixes WCS coordinates by using pair-distance matching and asterism matching (also runs Scamp for extra astrometry correction)

7. Stack (autopipestack.pro)

   • Uses SWarp to stack images with same filter and calculates both relative and absolute zeropoint info (absolute only for coadded)

8. Photometry

Run this python script from the photometry folder.

Can automatically run full photometry reduction using autoredux.py
Needs to run inside directory with coadd*.fits files:

from autoredux import *
autoredux()

autoredux.py runs the following programs in this order:

1. Creates same sampling and crop for all files, creates multicolor image and using multicolor image to find all sources, then finds photometry of these sources for each (resampled) file using sextractor (with corrected zeropoint).

   • photom.py

   • Output: aperture photometry

     • *.am (absolute magnitude) files for w/ RA and DEC identified by sextractor

2. create webpage

   • plotratir.py

The sandbox was meant as a place to test new code development. Note that any changes made to this directory will not be reflected in the repository.