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A collection of OCaml Math and Statistics functions.The API is availableonline.

1. Perform simple and sophisticated mathematical and statistical analysisinside of (mostly) OCaml. Please seeOml_full sectionfor details.
2. Have a descriptive, simple, and typed approach to those algorithms.
   • descriptive: what a function does should be easy to understand fromthe type and name.
   • simple: don't worry about the corner cases of the algorithms, untilyou have to.
   • typed: obviously.
3. Well tested. There are a subtle dependency betweenfloat capabilitiesand these algorithms. The test suite aims to provide bounds as well as abenchmark for comparing algorithms.
4. Informative examples.

• make setup willopam install the necessary packages forOml_full.
• make build will compile source.
• make test for tests.- We useKaputt as the testing framework. Testsare found in*.mlt files and are joined with their respective sourcefiles only when building a test target.-make TEST={ModuleName} test will run the test inModuleName,exmake TEST=Descriptive test-make setup_test will install packages necessary for testing.
• make covered_test forBisect_ppxinstrumented test coverage.

Oml_full is a superset of Oml that includesC and/orFortran dependencies.It is generally more useful and incorporatesOml in a typed equivalent way.The goal is to provide a flexible end-user target for those who don't needC dependent functionality.

For the "full" Oml packagemake setup willopam install these:

• Lacaml for BLAS/LAPACK bindings.
• LBFGS for bindings to LBFGSoptimization routines.
• ocephes for special functions.

And for testing:

• Kaputt for testing.
• Bisect_ppx for code coverage.

Anything within the problem domain is welcome.

The best place to discuss Oml is within Github'sissues (even for questions).

"Favor readers over writers" andFavor users over readers.