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SWIMS Imaging Data Reduction Pipeline, written in Python, processes SWSB*/SWSR* FITS data to produce a final stacked image in a standard manner.
| Reduction Flow Chart |
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| File | Contents |
 swsred_20210712.tgz | Python core scripts (swsred/*py) and configuration/utility files |
May 26, 2021: BPM file on B1 detector for S21A April is found to be incorrect. Please download newer files created on May 26.
Put files you need on swsred/calib/bpm/ directory.
Put files you need on swsred/calib/flat/ directory.
| File | Contents |
| swsred_calib_mosaic_s18a_20210131.tgz | Mosaic parameter files for S18A data |
| swsred_calib_mosaic_s18b_20210131.tgz | Mosaic parameter files for S18B data |
| swsred_calib_mosaic_s21a_20210413.tgz | Tentative use only!! Mosaic parameter files for S21A data |
Use these test data (taken in S18B) to check if your swsred works.
| File | Contents |
| swsred_sample_b.tgz | J1-band data (4 frames x 2 arrays) |
| swsred_sample_r.tgz | H1-band data (4 frames x 2 arrays) |
The reduced images produced with two iterations (n_iter=2) using swsred version 20210712 and the execution log (swsred.log) should be like these.
| File | Contents |
| fs12_j1_b1_stack1.fits | Stacked image (after two iterations) on the blue array #1 |
| fs12_j1_b2_stack1.fits | Stacked image (after two iterations) on the blue array #2 |
| fs12_h1_r1_stack1.fits | Stacked image (after two iterations) on the red array #1 |
| fs12_h1_r2_stack1.fits | Stacked image (after two iterations) on the red array #2 |
| fs12_j1.fits | Mosaicked image (after two iterations) on the blue arrays Mosaicking methods still under verification. Use this image only to check if swsred works correctly. |
| fs12_h1.fits | Mosaicked image (after two iterations) on the red arrays Mosaicking methods still under verification. Use this image only to check if swsred works correctly. |
| swsred_j1.log | logs on reducing J1 data. |
| swsred_h1.log | logs on reducing H1 data. |
SWSRED requires the following python packages and astrOmatic softwares.
| Package | Tested version | |
| Python | 2.7.17 | 3.7.7 |
| astropy | 2.0.9 | 4.0 |
| numpy | 1.16.6 | 1.18.1 |
| scipy | 1.2.1 | 1.4.1 |
| matplotlib | 2.2.3 | 3.1.3 |
| astroquery | 0.4 | 0.4.1 |
| sextractor | 2.19.5 | 2.19.5 |
| scamp | 2.7.8 | 2.7.8 |
| swarp | 2.38.0 | 2.38.0 |
Also, Internet connection is required during reducing data to access Pan-STARRS/2MASS catalogs.
% cd SWSRED_DIRECTORY % tar xvf swsred_20210527.tgz % tar xvf swsred_calib_mosaic_s21a_20210413.tgz % mkdir -p swsred/calib/bpm swsred/calib/flat
% export PYTHONPATH="SWSRED_DIRECTORY:${PYTHONPATH}
SWSRED has no documentations yet, but you can use a dirty script 'swsred/reduce_all.py' as a quick tutorial to learn how to use the software.
Be sure to use SWSRED within python interpreter (e.g., in ipython or jupyter, etc.), not via the command line as no command-line interfaces prepared.
Here is a quick introduction to use SWSRED.
> import glob
> in_arr1 = glob.glob("DATA/PATH/SWSB*1.fits") # blue chip1 data
> in_arr1.sort() # must be sorted before using.
import glob
import astropy.io.fits
dct1 = {}
dct2 = {}
infiles = glob.glob("SWS*fits")
infiles.sort()
for infile in infiles:
hdr = astropy.io.fits.getheader(infile)
ch = hdr["2_DETCH"]
if ch == 1:
dct = dct1
else:
dct = dct2
if hdr["2_DSETID"] not in dct.keys():
dct[hdr["2_DSETID"]] = []
dct[hdr["2_DSETID"]].append(infile)
> import swsred.make_file_lst > file_lst1 = swsred.make_file_lst.make_file_lst(in_arr1)
| Key | Value | Description |
| in | data/path/SWSB00000001.fits | input filename |
| ff | ffSWSB00000001.fits | filename of flat-fielded data |
| ms | msSWSB00000001.fits | filename of self-sky data |
| ss | ssSWSB00000001.fits | filename of sky-subtracted data |
| wc | wcSWSB00000001.fits | filename of WCS-corrected data |
| bpm | /SWSRED_DIRECTORY/calib/bpm/bpm_sXXY_b1.fits | filename of Bad-pixel mask (XXY denotes a semester) |
| wht | SWSB00000001_wht.fits | filename of weight map (created by make_weight_map module) |
| omsk | SWSB00000001_omsk.fits | filename of object mask |
| ldac | ssSWSB00000001.ldac | filename of SExtractor LDAC catalog |
| ascii | ssSWSB00000001.ascii | filename of SExtractor ASCII catalog |
| head | ssSWSB00000001.head | filename of SExtractor HEAD file |
> import swsred.flat_field > swsred.flat_field.flat_field(file_lst1["in"], file_lst1["ff"])
Refer to 'swsred/reduce_all.py' for all the procedures.
Please send your bug reports or questions to konishi__at__ioa.s.u-tokyo.ac.jp.
