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https://img.shields.io/crates/l/specs.svg?maxAge=2592000\n\n[di]: https://docs.rs/levenberg-marquardt/badge.svg\n[dl]: https://docs.rs/levenberg-marquardt/\n\n[lo]: https://tokei.rs/b1/github/rust-cv/levenberg-marquardt?category=code\n\n[dci]: https://img.shields.io/discord/550706294311485440.svg?logo=discord\u0026colorB=7289DA\n[dcl]: https://discord.gg/d32jaam\n\n[bci]: https://github.com/rust-cv/levenberg-marquardt/workflows/ci/badge.svg\n\nSolver for nonlinear least squares problems\n\nThe implementation is a port of the classic MINPACK implementation of the\nLevenberg-Marquardt (LM) algorithm. This version of the algorithm is sometimes referred\nto as _exact_ LM.\n\nAll current unit tests indicate that we achieved _identical_ output (on a floating-point level)\nto the MINPACK implementation, especially for rank deficient unstable problems.\nThis was mainly useful for testing.\nThe Fortran algorithm was extended with `NaN` and `inf` handling, similar to what [lmfit][lmfit] does.\n\nThe crate offers a feature called `minpack-compat` which sets floating-point constants\nto the ones used by MINPACK and removes the termination criterion of \"zero residuals\".\nThis is necessary for identical output to MINPACK but generally not recommended.\n\n# Usage\n\nSee the [docs](https://docs.rs/levenberg-marquardt/) for detailed information.\n\n```rust\nimpl LeastSquaresProblem\u003cf64\u003e for Problem {\n    // define this trait for the problem you want to solve\n}\nlet problem = Problem::new(initial_params);\nlet (problem, report) = LevenbergMarquardt::new().minimize(problem);\nassert!(report.termination.was_successful());\n```\n\n# References\n\nSoftware:\n\n- The [MINPACK](https://www.netlib.org/minpack/) Fortran implementation.\n- A C version/update, [lmfit][lmfit].\n- A Python implementation in [pwkit](https://github.com/pkgw/pwkit/blob/master/pwkit/lmmin.py).\n\nOne original reference for the algorithm seems to be\n\n\u003e Moré J.J. (1978) The Levenberg-Marquardt algorithm: Implementation and theory. In: Watson G.A. (eds) Numerical Analysis. Lecture Notes in Mathematics, vol 630. Springer, Berlin, Heidelberg.\n\nby one of the authors of MINPACK.\n\nThe algorithm is also described in the form as\nimplemented by this crate in the [book \"Numerical Optimization\"](https://link.springer.com/book/10.1007%2F978-0-387-40065-5) by Nocedal and Wright, chapters 4 and 10.\n\n[lmfit]: https://jugit.fz-juelich.de/mlz/lmfit\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frust-cv%2Flevenberg-marquardt","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frust-cv%2Flevenberg-marquardt","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frust-cv%2Flevenberg-marquardt/lists"}