Coder Social home page Coder Social logo

eldredvg / splinter Goto Github PK

View Code? Open in Web Editor NEW

This project forked from bgrimstad/splinter

0.0 1.0 0.0 5.41 MB

Library for multivariate function approximation with splines (B-spline, P-spline, and more) with interfaces to C++, C, Python and MATLAB

License: Mozilla Public License 2.0

CMake 3.10% C++ 73.24% C 3.52% MATLAB 6.46% Python 9.91% Shell 3.77%

splinter's Introduction

GitHub release license

Master branch Develop branch
Build Status Build Status

SPLINTER

SPLINTER (SPLine INTERpolation) is a library for multivariate function approximation with splines. The library can be used for function approximation, regression, data smoothing, data reduction, and much more. Spline approximations are represented by a speedy C++ implementation of the tensor product B-spline.

The B-spline consists of piecewise polynomial basis functions, offering a high flexibility and smoothness. The B-spline can be fitted to data using ordinary least squares (OLS), possibly with regularization. The library also offers construction of penalized splines (P-splines).

Illustration of a B-spline Figure: Illustration of a bicubic B-spline generated with the SPLINTER library.

Sharing

SPLINTER is the result of several years of development towards a fast and general library for multivariate function approximation. The initial intention with the library was to build splines for use in mathematical programming (nonlinear optimization). Thus, some effort has been put into functionality that supports this, e.g. Jacobian and Hessian computations for the B-spline.

By making SPLINTER publicly available we hope to help anyone looking for a multivariate function approximation library. In return, we expect nothing but your suggestions, improvements, and feature requests. If you use SPLINTER in a scientific work we kindly ask you to cite it. You can cite it as shown in the bibtex entry below (remember to update the date accessed).

@misc{SPLINTER,
  title={{SPLINTER: a library for multivariate function approximation with splines}},
  author={Bjarne Grimstad and others},
  howpublished={\url{http://github.com/bgrimstad/splinter}},
  year={2015},
  note={Accessed: 2015-05-16}
}

Contributing

Everyone is welcome to use and contribute to SPLINTER. We believe that collective effort over time is the only way to create a great library: one that makes multivariate function approximation with splines more accessible to practitioners and researchers.

The current goals with the library are:

  1. To make the library more accessible by improving the interfaces and documentation
  2. To implement new features
  3. To improve the current code via testing

The simplest way to contribute to SPLINTER is to use it and give us feedback on the experience. If you would like to contribute by coding, you can get started by picking a suitable issue from the list of issues. The issues are labeled with the type of work (Bug, Docs, Enhancement, New feature, Refactoring, Tests) and level of difficulty (Beginner, Intermediate, Advanced). Some issues are also labeled as Critical, which means that they deserve our attention and prioritization.

Requirements for use

A standards compliant C++11 compiler.

Guides

splinter's People

Contributors

bgrimstad avatar gablank avatar hxdnshx avatar novacrazy avatar jkhoogland avatar sdrdis avatar

Watchers

James Cloos avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.