https://github.com/iraikov/rklib

Runge-Kutta methods in Standard ML
https://github.com/iraikov/rklib

adaptive-solvers error-estimators runge-kutta runge-kutta-adaptive-step-size runge-kutta-methods standard-ml

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Runge-Kutta methods in Standard ML

• Host: GitHub
• URL: https://github.com/iraikov/rklib
• Owner: iraikov
• License: other
• Created: 2013-04-13T05:30:48.000Z (over 11 years ago)
• Default Branch: master
• Last Pushed: 2017-07-14T00:01:26.000Z (over 7 years ago)
• Last Synced: 2024-10-19T18:02:55.387Z (2 months ago)
• Topics: adaptive-solvers, error-estimators, runge-kutta, runge-kutta-adaptive-step-size, runge-kutta-methods, standard-ml
• Language: Standard ML
• Size: 52.7 KB
• Stars: 1
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
rklib

=====

Runge-Kutta methods in Standard ML.

This library is a port of the Haskell Runge-Kutta library by Uwe

Hollerbach (http://hackage.haskell.org/package/rungekutta).  It

contains a collection of explicit Runge-Kutta methods of various

orders, some with fixed-size steps (no error estimate) and some

that provid error estimate intended for adaptive stepsize.

The library provides routines that can use arbitrary coefficients

(Butcher tableau), then instantiates them with different tableaux

based on standard Runge-Kutta methods. Adaptive step-size methods add

a row of coefficients that are used to compute the error.

* non-adaptive solvers:

  rkfe, rk3, rk4a, rk4b

* adaptive solvers:

  rkhe, rkbs, rkf45, rkck, rkdp, rkf78, rkv65

* adaptive solvers with interpolation (CERK):

  cerkdp

* auxiliary non-adaptive solvers (error estimators from the adaptive ones):

  rkhe_aux, rkbs_aux, rkf45_aux, rkck_aux, rkdp_aux, rkf78_aux, rkv65_aux