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This milestone focuses on adapting WaveDiff for real data processing. Objectives: - Add train-test split function to `wf_psf.data` package (either to `data_handler.py` or other module) - Update `SHE_PSF_WaveDiff_Utils/image_processing_utils` module with flux normalisation function - Add a dedicated module(s) : `star_select_outlier_removal.py` to the `wf_psf.data `package with method(s) (including helper methods) to perform heavy Central Masking detection and outlier detection (using trained model) and Removal - Parent config file specifying outlier removal methods to execute at run-time
Overdue by 9 day(s)•Due by February 6, 2026•0/4 issues closedThis milestone covers the modernization of the wf-psf package to ensure compliance with EDEN 3.1 runtime environments and compatibility with Euclid Science Ground Segment (SGS) software standards. Objectives: - Remove unsupported TensorFlow Addons dependencies, or move them to optional extras. - Implement configurable optimizer selection (e.g., Adam, RectifiedAdam) to allow flexible experimentation while maintaining a fully compliant default configuration. - Validate reproducibility and performance on simulated datasets, ensuring consistency with baseline results.
Overdue by 3 month(s)•Due by November 14, 2025•3/8 issues closed