# mathnet/mathnet-numerics

Math.NET Numerics

Repository: https://github.com/mathnet/mathnet-numerics
Canonical: https://ross.abutalabs.com/products/mathnet-numerics
Homepage: http://numerics.mathdotnet.com
Language: C#
License: MIT
License Family: permissive
Topics: math, numerics, linear-algebra, fsharp, matrix, random, mathnet, csharp, interpolation, regression, statistics, integration, fft, differentiation
Last push: 2025-03-03T21:39:46+00:00

## Health v2 (maintenance only)
Score: 36/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 9, release rhythm 35, longevity 100
- inputs: {"age_days": 6279, "days_push": 548, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3765, forks 939 (observed 2026-08-28T04:08:18.038888+00:00)

## What it is
Math.NET Numerics is an open-source numerical library for .NET and Mono, providing methods and algorithms for numerical computation in science and engineering. It covers special functions, linear algebra, probability models, random numbers, statistics, interpolation, integration, regression, and FFT, with optional native providers like Intel MKL for performance.

## Use cases
- perform linear algebra and matrix decompositions in C#
- compute statistics and probability distributions in .NET
- fit curves and run regression analysis
- compute FFT and integral transforms
- generate random numbers from probability models
- solve interpolation and numerical integration problems
- use numerical computing from F# with idiomatic modules

## When to choose
- you need numerical computation in a .NET or Mono application
- you want a managed library with optional native MKL/OpenBLAS acceleration
- you need MIT-licensed math routines usable in proprietary software
- you work in both C# and F# and want idiomatic support for both

## When to avoid
- you need GPU-accelerated deep learning rather than general numerics
- your project is not on the .NET platform
- you need symbolic math rather than numerical computation

## Facets
- artifact type: library
- maturity: stable
- function: math, data-science, machine-learning
- domain: mathematics, data-science
- platform: dotnet, cross-platform, windows
- tags: linear-algebra, statistics, fft, regression, interpolation, numerical-computation, fsharp, csharp, mkl, openblas, algorithms, linux, macos

## Member repositories
- mathnet/mathnet-numerics (main) score 36

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:18.038888+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:28:36.662299+00:00, confidence not recorded.
  - readme: https://github.com/mathnet/mathnet-numerics (fetched 2026-08-28T04:08:18.038888+00:00, sha abceeeabdf1e)
  - homepage: http://numerics.mathdotnet.com (fetched 2026-08-29T09:22:43.412612+00:00, sha 969fca15dafe)
- Data as of 2026-08-30T08:39:29.467469+00:00.