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Skip Navigation LinksHome»Features»What's New»What's New in Version 6.0

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Latest version 8.1.20 (August 2023)

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Extreme Optimization Numerical Libraries for .NET

What's New in Version 6.0

Universal improvements

  • There now is one setup for both 32 and 64 bit operating systems.
  • Libraries can also be installed as NuGet packages, for easier upgrading.
  • The documentation has been fully updated to the latest API.
  • New and updated QuickStart samples illustrate the new API.

Math Library

  • Complex numbers are now generic over the type of the real and imaginary parts.
  • Dormand-Prince adaptive RK ODE solver
  • Akima splines and cubic Hermite splines.
  • Evaluation of orthogonal polynomials.
  • Error functions for Quad precision numbers.
  • Vector functions for complex single and double precision arguments.
  • Faddeeva function, Voigt function, complex error function.
  • Savitsky-Golay and Moving Average smoothing in SignalProcessing.

Data Analysis Library

  • Support for LINQ queries on data frames, vectors and matrices.
  • New groupings for aggregations include: fixed and expanding windows, partitions, groupings on value and quantiles, 2D pivot tables, and resampling.
  • A large set of aggregators and aggregator functions has been added with efficient implementations for specific types of groupings (e.g. moving averages).
  • New generic Descriptives class for collecting descriptive statistics of vectors.
  • Indexes on ordered types now support lookup nearest. Likewise, data frames with such indexes now support join on nearest.
  • New Recurrence type lets you specify date/time patterns for use in, for example, resampling of data frames.

Vector and Matrix Library

  • 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 argument.
  • New mutability options now let you create read-only vectors, and writable vectors with copy-on-write semantics.
  • Most operations on vectors and matrices are available in three forms: as a static method that returns a new value, as a static method that returns the value in a supplied object, and as an instance method that modifies the object in-place.
  • Operator methods are named consistently for static calls, in-place and out-of-place updates.
  • Relational operators are now supported for generic 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.
  • A fully managed implementation of the linear algebra library for single-precision floating-point numbers was added.

Statistics Library

  • Descriptions tailored to working in an interactive environment for statistical models, hypothesis tests and other objects.
  • Statistical models have been integrated with the DataFrame library.
  • The variable types (NumericalVariable, CategoricalVariable, DateTimeVariable) have been replaced with generic vectors.
  • Categorical variables are expanded into indicator variables when necessary. Several encoding schemes are available.
  • Models can be persisted in a form suitable for deployment in predictive modeling applications.
  • Models can be specified using R-style formulas.
  • Regression models are now robust against collinearity.
  • New distribution classes have been added: truncated distributions, inverse Weibull.