| name | mockgal |
| description | Generate mock galaxy images with multi-component Sersic profiles using the mockgal.py engine from isophote_test. Use when you need realistic synthetic data for isophote fitting tests or benchmarking stability in LSB regimes. |
MockGal Skill
This skill provides a standardized way to generate mock galaxy images using the mockgal.py engine and profit-cli backend.
Environment
- Engine:
../isophote_test/mockgal.py
- Backend:
libprofit (via profit-cli at ../isophote_test/libprofit/mbp)
- Models: Huang+2013 multi-Sersic models are available at
../isophote_test/inputs/huang2013/models/huang2013_models.yaml.
Usage
Use the provided wrapper script to run mockgal.py with the correct environment variables set.
Single Galaxy Generation
./mockgal/scripts/mockgal_wrapper.sh --single \
--name my_galaxy \
-z 0.2 \
--r-eff 5.0 \
--abs-mag -21.0 \
--sersic-n 4.0 \
--psf --psf-type gaussian --psf-fwhm 0.7 \
--sky-sb-limit 24.5 \
-o output/
Batch Generation from Huang2013
./mockgal/scripts/mockgal_wrapper.sh \
--models ../isophote_test/inputs/huang2013/models/huang2013_models.yaml \
--config ../isophote_test/inputs/huang2013/configs/huang2013_test_config.yaml \
--galaxy "NGC 1453" "NGC 3585" \
-o outputs/mock_galaxies
Recommended HSC Configuration
For realistic HSC-like mock images (z=0.2):
pixel_scale: 0.168
psf_fwhm: 0.7
sky_sb_limit: 24.5 (Wide survey) or 27.0 (Reference/Deep)
size_factor: 15 (to cover outer disks)