SWIMS Imaging Data Reduction Pipeline, written in Python, processes SWSB*/SWSR* FITS data to produce a final stacked image in a standard manner.
File | Contents |
swsred_20210131.tgz | Python core scripts (swsred/*py) and configuration/utility files |
File | Contents |
swsred_calib_bpm_s18a_20210131.tgz | Bad pixel mask files for S18A data |
swsred_calib_bpm_s18b_20210131.tgz | Bad pixel mask files for S18B data |
swsred_calib_bpm_s20b_20210131.tgz | Bad pixel mask files for S20B data |
swsred_calib_bpm_s21a_20210413.tgz | Tentative use only!! Bad pixel mask files for S21A data |
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 |
BBF: Broad-band filters, MBF: Medium-band filters, NBF: Narrow-band filters
File | Contents |
swsred_calib_flat_bbf_s18a_20210131.tgz | Flat files for S18A BBF data |
swsred_calib_flat_bbf_s18b_20210131.tgz | Flat files for S18B BBF data |
swsred_calib_flat_mbf_s18b_20210131.tgz | Flat files for S18B MBF data |
swsred_calib_flat_nbf_blue_s18b_20210131.tgz | Flat files for S18B Blue NBF data |
swsred_calib_flat_nbf_red_s18b_20210131.tgz | Flat files for S18B Red NBF data |
swsred_calib_flat_bbf_s20b_20210131.tgz | Flat files for S20B BBF data |
swsred_calib_flat_bbf_s21a_20210413.tgz | Tentative use only!! Flat files for S21A BBF data |
swsred_calib_flat_mbf_s21a_20210413.tgz | Tentative use only!! Flat files for S21A MBF data |
Use these test data 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) 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 redarray #2 |
fs12_j1.fits | Mosaicked image (after two iterations) on the blue arrays Mosaicking parameters still under verification. Use this image (and mosaicking methods) only to check if swsred works correcctly. |
fs12_h1.fits | Mosaicked image (after two iterations) on the red arrays Mosaicking parameters still under verification. Use this image (and mosaicking methods) only to check if swsred works correctly. |
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 |
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_20210131.tgz % tar xvf swsred_calib_bpm_s18a_20210131.tgz % tar xvf swsred_calib_bpm_s18b_20210131.tgz % tar xvf swsred_calib_bpm_s20b_20210131.tgz % tar xvf swsred_calib_mosaic_s18a_20210131.tgz % tar xvf swsred_calib_mosaic_s18b_20210131.tgz % tar xvf swsred_calib_flat_s18a_20210131.tgz % tar xvf swsred_calib_flat_s18b_20210131.tgz % tar xvf swsred_calib_flat_s20b_20210131.tgz
% 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 (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
> 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_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.