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Extreme Optimization Numerical Libraries for .NET
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The Extreme Optimization Numerical Libraries for .NET are a collection
of general-purpose mathematical and statistical classes built for the Microsoft
The Extreme Optimization Numerical Libraries for .NET provide the first
complete platform for technical and statistical computing built on and
for the Microsoft .NET platform. It combines
a math library, a vector and matrix library, and a statistics library
in one convenient package.
At a glance:
- Seamless parallelism using the Task Parallel Library.
- Basic math: Complex numbers,
'special functions' like Gamma and Bessel functions,
- Automatic differentiation: eliminate tedious and
error-prone manual derivative calculations.
- Solving equations: Solve equations in one variable,
or solve systems of linear or nonlinear equations.
- Curve fitting: Linear and nonlinear curve fitting,
cubic splines, polynomials, orthogonal polynomials.
- Optimization: State of the art algorithms for finding
the minimum or maximum of a function in one or more variables,
linear programming (LP), mixed integer programming (MIP),
quadratic programming (QP) and nonlinear programming (NLP).
- Genetic Optimization: Flexible framework for
finding good solutions to hard problems.
- Numerical integration: Compute integrals over finite
or infinite intervals. Integrate over 2D and higher dimensional regions.
Integrate systems of ordinary differential equations (ODE's).
- Fast Fourier Transforms: 1D and 2D FFT's using 100%
managed or fast native code (32 and 64 bit)
- BigInteger, BigRational, and BigFloat: Perform operations
with arbitrary precision.
- Generic arithmetic framework: Write the code once and
use it with any numerical type.
- Random numbers: Random variates from any distribution, 4 high-quality
random number generators, low discrepancy sequences, shufflers.
Vector and Matrix Library
- Real and complex vectors and matrices.
- Single, double and quadruple precision for elements.
- Structured matrix types: including triangular, symmetrical and
- Sparse matrices.
- Iterative sparse solvers and preconditioners.
- Matrix factorizations: LU decomposition, QR decomposition, singular
value decomposition, Cholesky decomposition, eigenvalue decomposition.
- Portability and performance: Calculations can be done
in 100% managed code, or in hand-optimized processor-specific native code (32 and
- Generic library: Use built-in .NET types or any of the new arbitrary
precision types to do matrix calculations.
- Row and column labels: Add labels to your data and take advantage of
automatic alignment on labels.
- Data frame: Advanced data analysis, manipulation and transformation.
- Data munging: Sort and filter data, process
missing values, remove outliers, etc. Supports .NET data binding.
- Data manipulation: Reshape data frames, database-like joins,
join to nearest, stacking and unstacking.
- Grouping and Aggregation: Efficient aggregation over
groupings by value or quantile, moving and expanding windows, partitions.
- Statistical Models: Simple, multiple, nonlinear,
logistic, Poisson regression. Generalized Linear Models. One and two-way ANOVA.
- Time Series Models: ARIMA and GARCH.
- Multivariate Statistics: K-means cluster analysis, hierarchical
cluster analysis, principal component analysis (PCA), factor analysis.
- Statistical Distributions:
39 continuous and discrete
statistical distributions, including uniform, Poisson, normal, lognormal, Weibull
and Gumbel (extreme value) distributions and various
- Hypothesis Tests:
15 hypothesis tests, including the
z-test, t-test, F-test, runs test, and more advanced tests, such as the Anderson-Darling
test for normality, one and two-sample Kolmogorov-Smirnov test, and Levene's test
for homogeneity of variances, Ljung-Box test for auto-correlation, Kruskal-Wallis test.
- Parallel computing. Take advantage of all the CPU and GPU power
in your machine. Full support for Task Parallel Library features
including cancellation. Support for CUDA based GPU calculations.
Great performance. We implemented the best algorithms available
today to provide you with a robust, fast toolset.
- Intuitive object model. The classes in the Extreme Optimization Numerical
Libraries for .NET and the relationships between them match our every-day concepts.
Ground-breaking usability for numerical software development. The math
itself is hard enough.
- Broad base of algorithms
covering a wide range of numerical techniques, including: linear algebra (BLAS and
LAPACK routines), numerical integration and differentiation, solving equations,
complex numbers, and more.
Whether you develop applications in C#, Visual Basic .NET, F#, C++/CLI, IronPython or any of
the other .NET Framework languages, the Extreme Optimization Numerical Libraries
for .NET provide the reliable foundation and the building
blocks developers need.
See what's new in the latest version.
You can see a list of what was new in earlier versions:
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