# PX4/eigen

Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms.

Repository: https://github.com/PX4/eigen
Canonical: https://ross.abutalabs.com/products/px4-eigen
Homepage: http://eigen.tuxfamily.org/
Language: C++
License: NOASSERTION
License Family: other
Last push: 2023-10-18T12:45:56+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4187, "days_push": 1050, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1140, forks 188 (observed 2026-08-28T04:03:44.062117+00:00)

## What it is
PX4/eigen is a fork of Eigen, a C++ template library for linear algebra providing matrices, vectors, numerical solvers, and related algorithms. It supports dense and sparse matrices of all sizes, multiple numeric types, matrix decompositions, and SIMD vectorization across x86, ARM, and PowerPC instruction sets.

## Use cases
- do matrix and vector math in C++
- solve linear systems and least squares in C++
- perform matrix decompositions like SVD, QR, LU
- work with sparse matrices efficiently
- write SIMD-optimized numerical code without assembly
- port MATLAB linear algebra code to C++
- use linear algebra in robotics flight control software

## When to choose
- you need a mature, header-only C++ linear algebra library with no heavy dependencies
- you need high performance via expression templates and explicit SIMD vectorization
- you need both dense and sparse matrix support with many decompositions
- you are working in the PX4/robotics ecosystem and need compatibility with its fork

## When to avoid
- you need GPU-accelerated linear algebra at large scale (consider cuBLAS or similar)
- you want a high-level interactive numerical environment (use NumPy or MATLAB)
- you need a permissively-licensed library and cannot accept Eigen's MPL2/custom licensing terms
- you need deep learning tensor operations with autodiff (use PyTorch or TensorFlow)

## Facets
- artifact type: library
- maturity: stable
- function: math
- domain: robotics, developer-tools
- platform: cpp, cross-platform
- tags: linear-algebra, matrices, sparse-matrices, simd, header-only, eigen-fork, numerical-solvers, algorithms

## Member repositories
- PX4/eigen (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:44.062117+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 2026-08-30T06:35:26.296716+00:00, confidence not recorded.
  - readme: https://github.com/PX4/eigen (fetched 2026-08-28T04:03:44.062117+00:00, sha facdc4414ea3)
  - homepage: http://eigen.tuxfamily.org/ (fetched 2026-08-29T12:40:54.163391+00:00, sha 8cd35d67205c)
  - site_page: https://libeigen.gitlab.io/eigen/docs-nightly (fetched 2026-08-29T12:40:54.173515+00:00, sha bfa17cd0af65)
  - site_page: https://libeigen.gitlab.io/documentation (fetched 2026-08-29T12:40:54.175506+00:00, sha 4369e17f868e)
  - site_page: https://libeigen.gitlab.io/eigen/docs-5.0 (fetched 2026-08-29T12:40:54.177103+00:00, sha 1578a5376b85)
  - site_page: https://libeigen.gitlab.io/eigen/docs-3.4 (fetched 2026-08-29T12:40:54.178721+00:00, sha eed67c822e7f)
  - site_page: https://libeigen.gitlab.io/eigen/docs-3.3 (fetched 2026-08-29T12:40:54.180235+00:00, sha 40375e27ea4f)
  - site_page: https://libeigen.gitlab.io/releases (fetched 2026-08-29T12:40:54.181702+00:00, sha e66bb29aec08)
  - site_page: https://libeigen.gitlab.io/releases/5.0 (fetched 2026-08-29T12:40:54.183249+00:00, sha fbbb9cbfb99b)
  - site_page: https://libeigen.gitlab.io/releases/3.4 (fetched 2026-08-29T12:40:54.185015+00:00, sha b3ae01182a5e)
- Data as of 2026-08-30T08:39:29.467469+00:00.