sndrizpipe

Image registration, combination and subtraction with astrodrizzle+tweakreg. Aimed at simple processing of supernova imaging from HST.

Cite it using the v1.0 DOI :

---

Dependencies

Requires drizzlepac from STScI. Recommended installation method: use the AstroConda package, which provides python, numpy, pyraf, drizzlepac, etc., with mutually compatible versions. Maintained by STScI.

https://astroconda.readthedocs.io/en/latest/

---

Environment variables

You must set up some environment variables before running sndrizpipe, using either setenv or export or the equivalent (depending on your shell type). Here is an example of how I've set this up in my .zshrc file:

# ============================================================
#  IRAF cdbs directories : 


export CDBS=$HOME/Dropbox/cdbs/
export iref=$CDBS/iref/
export jref=$CDBS/jref/
export mtab=$CDBS/mtab/
export cracscomp=$CDBS/comp/acs/
export crotacomp=$CDBS/comp/ota/
export crwfc3comp=$CDBS/comp/wfc3/
export crnicmoscomp=$CDBS/comp/nicmos/
export crrefer=$CDBS/
export PYSYN_CDBS=$CDBS/

Directory Setup

This pipeline is designed to process multi-epoch data for a single target. The target name is used to define where the input flt files are stored, and then becomes the prefix for sub-directories and output image products.

In your working directory, make a <name>.flt directory to hold all the pristine straight-from-the-archive flt files.

For a list of options :

sndrizpipe --help

if you don't give --ra --dec then the center position of the first image will be used.

use --imsize to give the width and height of the final output image in arcsec

if you don't set --pixscale and --pixfrac then the defaults are designed for 2-exposure image sets (i.e. 0.09" per pixel for IR, 0.04" for ACS)

Defining epochs

The first time you run sndrizpipe it will sort the flt files from the <name>.flt dir into epochs and generate a file <name>_epochs.txt containing the sorted list of exposures. Subsequent runs will adopt the epochs sorting in that file, if present.

You must specify --mjdmin and/or --mjdmax to get images sorted into epoch 0. If present, epoch 0 is assumed to be the template epoch for differencing.

Without --mjdmin or --mjdmax you will get epochs 1,2,... and you then need to specify --tempepoch 1 or --tempepoch 2 to tell the pipeline which epoch is the template.

FLT files that do not include the given target ra,dec will be sorted into epoch -1. That epoch never gets any further processing.

You can generate and check the <name>_epochs.txt file by first running without any --do commands. For example:

sndrizpipe --ra 189.156538   --dec 62.309147 --mjdmin 56010 --mjdmax 56300 colfax

If you want to remake the epochs list, just delete the <name>_epochs.txt file and re-run.

The command-line options for the 6 processing stages are:

1. --dosetup copy flt files into epoch subdirs
2. --dorefim build the WCS ref image
3. --dodriz1 first astrodrizzle pass (pre-registration)
4. --doreg run tweakreg to align with refimage
5. --dodriz2 second astrodrizzle pass (registered)
6. --dodiff subtract and mask to make diff images

• --doall Run all necessary processing stages

(1) Copy FLTs to sub-directories

Each epoch gets a sub-directory called <name>.e00, <name>.e01, etc.

All filters go into the same subdir. The FLT files are copied into the sub-directory (so the originals in <name>.flt remain pristine). Subsequent astrodrizzle and tweakreg stages will make further copies and modifications to those FLTs within the subdirs.

(2) WCS Ref image construction

The pipeline makes a reference image that is subsequently used with TweakReg to set a common WCS for all epochs and filters and cameras. If you are going to have parallel processes for the same target then you have to make this reference image first, before you start parallel processing, because each parallel process will try to generate the same ref image as the first step.

If you don't specify --refepoch, --reffilter, and --refvisit then the defaults are first epoch, first filter, deepest available visit. You can specify 1, 2 or all 3 of those refimage constraints, or none.

When possible, you should choose a filter, epoch and visit that put the target near the center of the field, and will provide a deep, CR-clean image with lots of sources for registration. WFC3-IR is good when available. In principle you could use a cutout from a deep mosaic image, though at present there is no tool for generating that.

(3) First drizzle pass

The first astrodrizzle pass operates on each HST visit separately. All files within the visit and from the same filter are drizzled together into the natural rotation frame (i.e. adopting the HST orientation instead of putting north up and east to the left). If the --drizcr flag is set, then this pass will also set new cosmic ray flags in the FLT data quality arrays. Otherwise, the CR flagging from the HST archive is left in place. This first pass will set the output pixel scale automatically based on the number of FLT files in each filter+visit group. By improving the PSF sampling, this can sometimes deliver better CR rejection than the automated pipeline, if you have more than 2 exposures.

The output products from this stage have the suffix _nat_drz_sci.fits (or _nat_drc_sci.fits for CTE-corrected ACS and UVIS files.)

(4) Registration

Each FLT file is registered to the WCS ref image with tweakreg. Tweakreg finds sources in the natural-rotation drizzled image products and compares them to a source catalog drawn from the WCS refimage. Using the --interactive mode, the user can see tweakreg 2D histograms and residual plots, and can modify the tweakreg parameters on-the-fly.

When registrations go really awry, the current best practice is to just wipe out all the affected products and restart from the top. A future version will provide a more efficient option to restart only the registration stage.

The user may provide a reference catalog using the --refcat option, in which case the tweakreg registration will only use detected sources that have a match in that catalog. The reference catalog must have RA and DEC as the first two columns, and may optionally include a third FLUX column. An existing catalog in Sextractor or commented_header format can be converted to this tweakreg format using mkrefcat.py as follows:

mkrefcat.py incatfile outcatfile

Use mkrefcat.py --help for more options.

(5) Second (final) drizzle pass

After the WCS parameters in the FLT file headers have been updated, the final astrodrizzle run will create drizzled image products, rotated with north up and east to the left. All filters from each camera are drizzled to the same pixel scale and all output images have the same image size in arcseconds. To explicitly specify a different pixel scale for the different cameras, the corresponding filters and epochs should be run with separate processes, and different values given for --pixscale and --pixfrac.

ACS or UVIS images that started as CTE-corrected flt files (_flc.fits) will end as reg_drc_sci.fits, and IR images will be reg_drz_sci.fits. This stage also produces drz_wht.fits files with the inverse variance map weight images, and drz_bpx.fits files with the bad pixel masks. These mask out only those pixels that have zero weight in the output sci.fits images (i.e. there was no good pixel from any input image at that location).

(6) Template Subtraction

If a template image is available, this final stage will generate sub_sci.fits difference images. These are straight subtractions, without any psf convolution.

The accompanying sub_wht.fits files are the inverse of the combined variance from the template and the target epochs, and sub_bpx.fits are the union of the two contributing bad pixel masks. Applying the badpix mask to the diff image then produces the final sub_masked.fits product.

In the current version, lots of cruft is left behind in the sub-directories (intermeidate flt files, ctx.fits, etc). A future version will have a --docleanup stage to remove them.

Building and using sndrizpipe with docker

To build sndrizpipe as a docker container run:

docker build -t sndrizpipe .

To run the test, change directorty to the folder with the extracted sndrizpipe/colfax_test.tgz data. Then the docker image can be run with:

docker run -v$PWD:/work -it --rm sndrizpipe --filters F160W  --doall --mjdmin 56010 --mjdmax 56300 --ra 189.156538 --dec 62.309147  --refcat 'goodsn_mosaic.cat' colfax

You can also create a bash/zsh function to seem as if you're running sndrizpipe nativly by adding this to your .bashrc/.zshrc file:

sndrizpipe () {
	docker run -v$PWD:/work -it --rm sndrizpipe $@
}