ALGLIB
ALGLIB is a cross-platform open source numerical analysis and data processing library. It can be used from several programming languages (C++, C#, VB.NET, Python, Delphi, Java).
| Original author(s) | Bochkanov Sergey Anatolyevich | 
|---|---|
| Developer(s) | ALGLIB LTD (UK) | 
| Stable release | 4.00.0
   / 22 May 2023  | 
| Operating system | Cross-platform | 
| Type | Numerical library | 
| License | Dual (commercial, GPL) | 
| Website | www | 
ALGLIB started in 1999 and has a long history of steady development with roughly 1-3 releases per year. It is used by several open-source projects, commercial libraries, and applications (e.g. TOL project, Math.NET Numerics,[1][2] SpaceClaim[3]).
Features
    
Distinctive features of the library are:
- Support for several programming languages with identical APIs (as of 2023, it supports C++, C#, FreePascal/Delphi, VB.NET, Python, and Java)
 - Self-contained code with no mandatory external dependencies and easy installation
 - Portability (it was tested under x86/x86-64/ARM, Windows and Linux)
 - Two independent backends (pure C# implementation, native C implementation) with automatically generated APIs (C++, C#, ...)
 - Same functionality of commercial and GPL versions, with enhancements for speed and parallelism provided in the commercial version
 
The most actively developed parts of ALGLIB are:
- Linear algebra, offering a comprehensive set of both dense and sparse linear solvers and factorizations
 - Interpolation, featuring standard algorithms like polynomials and 1D/2D splines, as well as several unique large-scale interpolation/fitting algorithms. These include penalized 1D/2D splines, fast thin plate splines and fast polyharmonic splines, all scalable to hundreds of thousands of points.
 - Least squares solvers, including linear/nonlinear unconstrained and constrained least squares and curve fitting solvers
 - Optimization, with LP, QP and NLP solvers, derivative-free global solvers and multiobjective optimization algorithms.
 - Data analysis, with various algorithms being implemented
 
The other functions in the library include:
- Fast Fourier transforms
 - Numerical integration
 - Ordinary differential equations
 - Special functions
 - Statistics (descriptive statistics, hypothesis testing)
 - Multiple precision versions of linear algebra, interpolation and optimization algorithms (using MPFR for floating point computations)
 
References
    
- "Math.NET Numerics". Numerics.mathdotnet.com. Retrieved 2010-07-10.
 - "Math.NET Numerics Contributors". GitHub.com. Retrieved 2013-05-07.
 - "End User License". .spaceclaim.com. Retrieved 2010-07-10.
 
External links
    
    
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