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)