ALGLIB - C++/C# numerical analysis library
Time 2022-09-24 17:28:08Web Name: ALGLIB - C++/C# numerical analysis library
WebSite: http://www.alglib.net
ID:327703
Keywords:
numerical,ALGLIB,library,analysisDescription:
FreeEdition CommercialEdition Docs FAQ Forum AboutUsAbout ALGLIB
ALGLIB is a cross-platform numerical analysis and data processing library.It supports several programming languages (C++, C#, Delphi) and several operating systems (Windows and POSIX, including Linux).ALGLIB features include:
Data analysis (classification/regression, statistics)Optimization and nonlinear solversInterpolation and linear/nonlinear least-squares fittingLinear algebra (direct algorithms, EVD/SVD), direct and iterative linear solversFast Fourier Transform and many other algorithmsALGLIB Project offers you several editions of ALGLIB:
ALGLIB Free Edition (download):+delivered for free under GPL or Personal/Academic license
+offers full set of numerical functionality
+extensive algorithmic optimizations
-single-threaded
-license agreement does not suit most commercial applications
ALGLIB Commercial Edition (more information):
+flexible commercial license without royalties or distribution fees
+extensive algorithmic optimizations
+high performance C++ version (SMP, commercial HPC kernels)
+two C# versions - managed and HPC one (native code, SMP/SIMD)
+commercial support and warranties
Why to choose ALGLIB? Because it is:
portable. It can be compiled almost anywhere with almost any compiler.easy to use. Easy integration, comes with extensive documentation.efficient. Deep algorithmic and low-level optimizations inside.trusted by leading companies. From nuclear research to aerospace.Announcements
ALGLIB NEWS (archive):
13.06.2022ALGLIB 3.19.0 is released
19.05.2022ALGLIB Project is now a UK company!
05.03.2022Sergey Bochkanov on the project status in light of RUS/UKR situation
27.10.2021ALGLIB 3.18.0 is released, with NET 5 SIMD support!
Resources and links
bugs.alglib.netIssues trackerforum.alglib.netALGLIB forumALGLIB User Guide online
Dense and sparse linear solversdense direct linear solverssparse iterative/direct linear solversMatrix operations and decompositions
dense and sparse BLAS-like functionalityLU, Cholesky, QR/LQ and SVD decompositionsmatrix inversion, norms and condition numbersgeneration of random matricesEigenvalues and eigenvectors
dense symmetric/Hermitian EVDdense nonsymmetric EVDsparse symmetric EVD
Interpolation and fitting
single-dimensional interpolation1D, 2D and 3D splinesfast scattered N-dimensional interpolationleast squares curve fitting
Linear programming
linear programmingsimplex methodinterior point methodOptimization (nonlinear and quadratic)
unconstrained nonlinear optimizationconstrained nonlinear optimization (box, linear, nonlinear constraints)constrained quadratic programmingnonsmooth optimization
FFT, convolution, correlation
FFTconvolutioncorrelation
Data analysis: classification, regression, other tasks
LDA, PCAhierarchical and k-means clusteringdecision forestsnonlinear classifiersDecision forest (regression and classification)
Randomized trees and decision forestsRegression and classificationVariable importanceTime series analysis
Filtering and smoothingPredictingStatistics: general algorithms
descriptive statisticsHypothesis testing
parametric and non-parametric tests
Other algorithms
nearest neighbor search
Special functions
Numerical integration
Nonlinear and polynomial equations
Differential equations
Other articles
DOCUMENTATION LICENSE:
1. ALGLIB User Guide is licensed for personal use only. See ALGLIB Reference Manual for a free documentation under BSD-like license
2. You may read the Guide and make unlimited copies for personal use.
3. Any other kinds of using the Guide, specifically, sales or any other commercial use,distribution on any material media, through computer networks or any other ways, are prohibited.
ALGLIB is a registered trademark of the ALGLIB Project.
Policies for this site: privacy policy, trademark policy.Select languageC++
CPython
DelphiC#
VB.NET
IronPythonHTML version of ALGLIB Reference Manual will open in same window, ~2MB. Right-click to open in new window.
TAGS:numerical ALGLIB library analysis
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