A small library for performing matrix math, linear algebra - now including sparse matrix solve. Most functions are static and use simple arrays (e.g double[,]) making it easy to use in other projects.

Install-Package StarMath -Version
dotnet add package StarMath --version
<PackageReference Include="StarMath" Version="" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add StarMath --version
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

  • .NETStandard 2.1

    • No dependencies.

NuGet packages (2)

Showing the top 2 NuGet packages that depend on StarMath:

Package Downloads
This dynamic library is focused on Computational Geometry functions likes the ones you would find in CGAL. As opposed to copying directly others work, we have sought to create functions from scratch that are optimized or straightforward as a C# implementation. As a .NET Standard library (and a legacy portable class library), the functions can be accessed from other managed code.
A library (.dll) of various linear, nonlinear, and stochastic numerical optimization techniques. While some of these are older than 40 years, many have yet to take advantage of an object-oriented programming model. This toolbox was originally created to aid in the automated design of various engineering artifacts. The following “class diagram” shows the main optimization methods that have currently been implemented – as well as some insight into organization of classes and objects. The best way to understand how to use OOOT, is through examples. There are two basic types of methods implemented so far: methods for continuous variables and methods for discrete variables. Approaches for mixed methods such as Branch-and-Bound are planned but not currently included. ClassDiagram1Many of the optimization methods for real valued decision variables will require that a line-search method be specified (Arithmetic Mean, Golden Section, DSC-Powell) and a search direction method (Cyclic Coordinate Search, Steepest Descent, Powell’s Method, Fletcher-Reeves, or Broyden-Fletcher-Goldfarb-Shanno). With this modular design it is possible to reconfigure these to create 80 unique algorithms. In addition to these there are also ten different convergence criteria that can be added individually or in any combination to these 80 algorithms. Read more about convergence methods here. But, one of the biggest advantages of the toolbox is the way that objective functions, equalities and inequalities can be easily added to the optimization process. Most (if not all open source approaches) optimization codes requires the problem specific details to be compiled along with the algorithm. Here, the problem formulation can be in another library or exe and can be customized at run-time instead of compile time. It is even possible to have the optimization algorithm change in response to the nature of the design variables and the number of constraints. Read more about problem formulation

GitHub repositories (1)

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Open Source Graphical Programming for Design

Version History

Version Downloads Last updated 822 2/4/2020 2,973 10/20/2017 1,290 7/25/2017 568 4/14/2017 769 5/29/2016 503 4/24/2016 562 3/12/2016 499 3/11/2016 475 2/29/2016 477 2/28/2016 467 2/20/2016 625 10/5/2015 496 10/2/2015 575 9/18/2015 481 9/14/2015 481 9/14/2015 504 9/12/2015 488 9/9/2015 481 9/4/2015 490 9/6/2015 530 9/4/2015 502 8/7/2015 458 8/7/2015 511 7/16/2015 543 7/7/2015 510 6/30/2015 725 2/18/2015 578 1/17/2015 556 12/7/2014 515 12/7/2014 8,043 11/14/2014 103 2/4/2020 811 8/26/2014 567 8/26/2014 551 8/8/2014 560 6/4/2014