A comprehensive OCaml library for mathematical and statistical analysis with descriptive, typed APIs.
OML (OCaml Math Library) is an open-source library that provides a comprehensive set of mathematical and statistical functions for OCaml developers. It solves the problem of performing data analysis and numerical computations directly within OCaml, offering both pure OCaml implementations and enhanced performance through external C/Fortran dependencies.
OCaml developers and data scientists who need to integrate mathematical modeling, statistical analysis, or optimization routines into their applications.
Developers choose OML for its descriptive, typed API that prioritizes clarity and simplicity, along with robust testing and the flexibility of optional high-performance dependencies through Oml_full.
OCaml Math Library
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Functions are named and typed for clarity, adhering to the goal of making code easy to understand from type and name, as stated in the README's emphasis on descriptive and simple design.
Uses Kaputt for testing and Bisect_ppx for code coverage, ensuring reliability and handling floating-point subtleties, with tests found in *.mlt files and commands like 'make test' for execution.
Oml_full includes bindings to BLAS/LAPACK via Lacaml and LBFGS for optimization, providing enhanced functionality for linear algebra and sophisticated computations beyond pure OCaml.
Integrates ocephes for advanced mathematical special functions, extending OCaml's capabilities with bindings to C libraries for more complex calculations.
Oml_full requires installing multiple C/Fortran packages like Lacaml, LBFGS, and ocephes via opam, which can be challenging and adds overhead, especially in restricted or cross-platform environments.
As an OCaml-specific library, it lacks the extensive community, tutorials, and third-party integrations of mainstream data science languages, potentially hindering adoption and resource availability.
Focused solely on computational functions with no mention of plotting or GUI tools, requiring additional libraries for data presentation and analysis workflows.