List of numerical libraries
Template:Short description This is a list of numerical libraries, which are libraries used in software development for performing numerical calculations. It is not a complete listing but is instead a list of numerical libraries with articles on Wikipedia, with few exceptions.
The choice of a typical library depends on a range of requirements such as: desired features (e.g. large dimensional linear algebra, parallel computation, partial differential equations), licensing, readability of API, portability or platform/compiler dependence (e.g. Linux, Windows, Visual C++, GCC), performance, ease-of-use, continued support from developers, standard compliance, specialized optimization in code for specific application scenarios or even the size of the code-base to be installed.
Multi-language
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C
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C++
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Delphi
- ALGLIB - an open source numerical analysis library.
.NET Framework languages C#, F#, VB.NET and PowerShell
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Fortran
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Java
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OCaml
- OCaml programming language has support for array programming in the standard library, also with an specific module named bigarrays for multi-dimensional, numerical arrays, with both C and Fortran layout options. A comprehensive support of numerical computations is provided by the library Owl Scientific Computing which provides methods for statistics, linear algebra (using OpenBLAS), differential equations, algorithmic differentiation, Fourier fast transform, or deep neural networks.[11] Other numerical libraries in OCaml are Lacaml that interfaces BLAS and LAPACK Fortran/C libraries, L-BFGS-ocaml (OCaml bindings for L-BFGS). For visualization there are libraries for plotting using PLplot, gnuplot or matplotlib.
Perl
- Perl Data Language gives standard Perl the ability to compactly store and speedily manipulate the large N-dimensional data arrays.[12] It can perform complex and matrix maths, and has interfaces for the GNU Scientific Library, LINPACK, PROJ, and plotting with PGPLOT. There are libraries on CPAN adding support for the linear algebra library LAPACK,[13] the Fourier transform library FFTW,[14] and plotting with gnuplot,[15] and PLplot.[16]
Python
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Others
- XNUMBERS – multi-precision floating-Point computing and numerical methods for Microsoft Excel.
- INTLAB – interval arithmetic library for MATLAB.[21][22][23][24]
See also
- List of computer algebra systems
- Comparison of numerical-analysis software
- List of information graphics software
- List of numerical analysis programming languages
- List of numerical-analysis software
- List of open source code libraries
- List of optimization software
- List of statistical software
References
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- ↑ Sanderson, C., & Curtin, R. (2016). Armadillo: a template-based C++ library for linear algebra. Journal of Open Source Software, 1(2), 26.
- ↑ Script error: No such module "Citation/CS1".
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- ↑ Smith, B. T., Boyle, J. M., Garbow, B. S., Ikebe, Y., Klema, V. C., & Moler, C. B. (2013). Matrix eigensystem routines-EISPACK guide (Vol. 6). Springer.
- ↑ Anderson, E., Bai, Z., Bischof, C., Blackford, S., Dongarra, J., Du Croz, J., ... & Sorensen, D. (1999). LAPACK Users' guide (Vol. 9). SIAM.
- ↑ Demmel, J. (1989, December). LAPACK: A portable linear algebra library for supercomputers. In IEEE Control Systems Society Workshop on Computer-Aided Control System Design (pp. 1-7). IEEE.
- ↑ Dongarra, J. J., Moler, C. B., Bunch, J. R., & Stewart, G. W. (1979). LINPACK users' guide. Society for Industrial and Applied Mathematics.
- ↑ Dongarra, J. J., Luszczek, P., & Petitet, A. (2003). The LINPACK benchmark: past, present and future. Concurrency and Computation: practice and experience, 15(9), 803-820.
- ↑ Dongarra, J. J. (1987, June). The LINPACK benchmark: An explanation. In International Conference on Supercomputing (pp. 456-474). Springer, Berlin, Heidelberg.
- ↑ Script error: No such module "citation/CS1".
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- ↑ Zimmermann, P., Casamayou, A., Cohen, N., Connan, G., Dumont, T., Fousse, L., ... & Bray, E. (2018). Computational Mathematics with SageMath. SIAM.
- ↑ Jones, E., Oliphant, T., & Peterson, P. (2001). SciPy: Open source scientific tools for Python.
- ↑ Bressert, E. (2012). SciPy and NumPy: an overview for developers. " O'Reilly Media, Inc.".
- ↑ Blanco-Silva, F. J. (2013). Learning SciPy for numerical and scientific computing. Packt Publishing Ltd.
- ↑ S.M. Rump: INTLAB – INTerval LABoratory. In Tibor Csendes, editor, Developments in Reliable Computing, pages 77–104. Kluwer Academic Publishers, Dordrecht, 1999.
- ↑ Moore, R. E., Kearfott, R. B., & Cloud, M. J. (2009). Introduction to Interval Analysis. Society for Industrial and Applied Mathematics.
- ↑ Rump, S. M. (2010). Verification methods: Rigorous results using floating-point arithmetic. Acta Numerica, 19, 287–449.
- ↑ Hargreaves, G. I. (2002). Interval analysis in MATLAB. Numerical Algorithms, (2009.1).
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External links
- The Math Forum - Math Libraries, an extensive list of mathematical libraries with short descriptions