Release 1.0#177
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…to a new pure rust crates; seeds done
…l recomputing for deactivated edges
…d also the struct managing the track hypothesis
…e missing test file of metrics
…ding of fink-fat-engine. add a first seeding evaluation reports on the seeding parameters
…the ephemeris file written by outfit
* add support for file compression, add progress bar as a cli option * run cargo fmt * clippy fixes * fix doc * fix ci for coverage report * fix non positive log score, add tests for log score, make edge new return a result instead of assert * fix error message * fix edge_builder progress bar, fix manifest test * fix multiple seed building over night of the build_edge stage for single night mode * improve progress bar of loading data stage * optimize save edge compaction * optimize loading and saving by doing async and concurrency * add solver and fit orbit stage to the command line * add new cost function for edges * add new cost function for edges * precision on doc * change pre-commit to trigger workspace doc * add logging * add logging and tests * add new config parameters to control edge generation * fix chi2 position blow-up, replace gnomonic residuals for spherical residuals * add data volume logs * deactivate edges after successfull fit orbit, add unit and integration tests for that * fix a huge bug regarding edge generation * optimize memory consumption for edges
… the runtime_state instead (#181)
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* big refactor of the fink-fat-eval crate * update gitignore * enabling seed parallel construction * add seeding evaluation * add plots for seeding * fix an overflow error bug * add edges stats * move dev profile in the workspace cargo toml * improve edge generation * forgotten files * optimize edge generation * add tests, add solver evaluation * add an edge features exporter * fix docs and missing system dep * clean edge ml prediction project, add a ml model evaluation in rust * add rust ml eval plots * add optuna optimization * add fink-fat-eval readme * add evaluation compilation profile note in readme * add a new edges generation benchmark * change ml behavior in the pipeline, ml is not a ranking anymore, it is now a filtering * add engine readme, remove units file, put content in lib.rs * add main doc page * refactor fink fat main * skip code coverage for fink-fat-eval
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Complete rewrite of Fink-FAT in Rust
The previous Python implementation relied heavily on Pandas and lacked the
performance and architectural clarity needed to scale to the volumes produced
by ZTF and Vera Rubin. This rewrite is a clean break from that codebase —
nothing has been carried over as-is.
What changed
alerts are modeled as nodes, and candidate trajectories emerge from edge
construction and resolution across nightly observation windows.
Why a full rewrite
The Python version was not salvageable for the target scale. Rewriting in Rust
allows tight control over memory, parallelism (via Rayon), and latency — all
of which matter when processing millions of alerts per night.