This release introduces broadband (polychromatic) PSF inference from trained models and significantly refactors the optimizer and configuration systems. It also improves modularity, dependency management, and documentation.
Highlights
- Added PSF inference capabilities for generating broadband PSFs from star positions and SEDs
- Added
run_typesupport inDataHandlerand implementedZernikeInputsFactoryfor buildingZernikeInputsinstances - Introduced configurable optimizer system via
get_optimizer()with YAML/programmatic overrides - Removed TensorFlow Addons as a required dependency (now optional for RectifiedAdam)
- Training now runs on TensorFlow 2.11 without requiring TFA
Improvements
- Refactored physical model to separate training and inference behaviour
- Centralized PSF data handling and model loading
- Added unit tests for optimizer and interpolation modules
- Updated packaging (
pyproject.toml) and documentation structure - Added pre-commit hooks for formatting, linting, and changelog enforcement
- See the full changelog for complete details.
Full Changelog: https://github.com/CosmoStat/wf-psf/blob/main/CHANGELOG.md