Extreme Optimization Numerical Libraries for .NET


・v6.0での新機能 (2016/3)

Universal improvements

  • There now is one setup for both 32 and 64 bit operating systems.
  • The documentation has been fully updated to the latest API.
  • New and updated QuickStart samples illustrate the new API.

New math features

  • Complex numbers are now generic over the type of the real and imaginary parts.
  • Flexible genetic optimization framework.
  • Akima splines and cubic Hermite splines.
  • New special functions, including complex error function and orthogonal polynomials.
  • Smoothing signals: Savitsky-Golay and Moving Average smoothing.
  • Vector functions for complex single and double precision arguments.

New Data Frame Library features

  • Support for LINQ queries on data frames, vectors and matrices.
  • New groupings: fixed and expanding windows, partitions, groupings on value and quantiles, 2D pivot tables, and resampling.
  • Many new aggregators; improved efficiency of many aggregations.
  • New generic Descriptives class for collecting descriptive statistics of vectors.
  • Lookup nearest and join on nearest for ordered indexes.
  • New Recurrence type lets you specify date/time patterns for use in resampling time based data.

New vector and matrix library features

  • All vector and matrix classes are now generic, including sparse matrices and complex versions.
  • New static Vector and Matrix classes remove the need to specify the element type as a generic type parameter.
  • Specify mutability: including read-only snapshot, read-only view, and writable with copy-on-write semantics.
  • Many new methods for in-place and out-of-place calculations on vectors and matrices.
  • The native libraries have been upgraded to Intel MKL version 11.3 Update 2.
  • The native libraries now support Conditional Numerical Reproducibility.
  • The CUDA libraries for 64 bit have been upgraded to CUDA version 7.5.
  • New fully managed implementation of the linear algebra library for single-precision.

New statistics features

  • Verbose output when working in an interactive environment.
  • Full integration with the DataFrame library.
  • Categorical variables are expanded into indicator variables as needed.
  • Models can be persisted in a form suitable for deployment in predictive modeling applications.
  • Several new probability distributions have been added.


・v5.1での新機能 (2014/11)

  • Data frame class supporting advanced data manipulation.
  • Support for GPU computing
  • Offload computations to the GPU.
  • Support for quadruple precision numbers with up to 34 digits, including our full vector and matrix library. Real and complex numbers are supported.
  • Smoothing cubic splines, monotonicity preserving splines.
  • GARCH models (Generalized AutoRegressive Conditional Heteroskedasticity).
  • Regularized linear regression models: Ridge regression, LASSO and elastic net.



・v5.0での新機能 (2013/3)

  • Much improved support for F# development.
  • Akima and cubic Hermite splines.
  • Orthogonal polynomials: Chebyshev, Legendre, Laguerre...
  • Symmetric indefinite decomposition
  • Generic and complex sparse vectors and matrices
  • Factor analysis
  • Improved setup experience.



・v4.2での新機能 (2011/12)

  • Automatic differentiation: symbolic computation of derivatives, gradients and Jacobians.
  • Extensible with built-in support for derivatives of methods in System.Math and most elementary and special functions in the library.
  • Backward differentiation with common sub-expression elimination generates optimal evaluation.
  • New SymbolicMath class that lets you optimize functions and solve equations specified as lambda expressions using automatic differentation.
  • Evaluation of (sequences of) classic orthogonal polynomials: Chebyshev (1st and 2nd kind), Hermite, Laguerre, Legendre and Gegenbauer.
  • Stepwise linear regression.
  • Regression fits of linearized curves: logarithmic, power, exponential, reciprocal...
  • 2x2 and RxC Contingency tables.



・v4.1での新機能 (2011/7)

  • Optimization framework. Provides a generic model for defining and solving optimization problems.
  • Quadratic Programming. Solve quadratic optimization models with linear constraints.
  • Nonlinear Programming. Optimize nonlinear functions with linear or nonlinear constraints.
  • New Decimal functions extend all the functions in System.Math to the decimal type, including sin, cos, exp.
  • Improved elementary functions. Evaluate sine, cosine and tangent accurately for huge arguments.
  • Iterative sparse solvers Efficiently solve systems with many thousands of variables, optionally using preconditioners.
  • New probability distributions LogSeries and Maxwell.



・v4.0での新機能 (2010/12)

  • .NET Framework Version 4.0 とVisual Studio 2010の並列処理サポート
  • 複数コア利用による計算スピードの向上 (.NET 4.0のみ)
  • 新しい疎線形プログラムソルバーは、100万変数の以上の問題を解くことが可能
  • ブランチとバウンドアルゴリズムを使った混合整数線形計画法
  • 新しい特殊関数: ハイパー幾何, Riemann zeta, 楕円積分, Fresnel関数, Dawsonの積分
  • FFTのウィンドウ関数の完全セット
  • 線形代数および任意精度のタイプでの6xまでのパフォーマンスの向上
  • F#での新しい50個のクィックスタートサンプル