GithubHelp home page GithubHelp logo

bluescarni / heyoka Goto Github PK

View Code? Open in Web Editor NEW
191.0 7.0 12.0 455.78 MB

C++ library for ODE integration via Taylor's method and LLVM

Home Page: https://bluescarni.github.io/heyoka/

License: Mozilla Public License 2.0

CMake 0.01% C++ 99.93% Shell 0.01% Jupyter Notebook 0.06% Julia 0.01%
ode ode-solver differential-equations cpp cpp17 llvm just-in-time multiprecision extended-precision astronomy

heyoka's Introduction

heyoka

Build Status Build Status

language Code Coverage

Anaconda-Server Badge


Logo

Modern Taylor's method via just-in-time compilation
Explore the docs »

Report bug · Request feature · Discuss

The heyókȟa [...] is a kind of sacred clown in the culture of the Sioux (Lakota and Dakota people) of the Great Plains of North America. The heyoka is a contrarian, jester, and satirist, who speaks, moves and reacts in an opposite fashion to the people around them.

heyoka is a C++ library for the integration of ordinary differential equations (ODEs) via Taylor's method, based on automatic differentiation techniques and aggressive just-in-time compilation via LLVM. Notable features include:

  • support for single-precision, double-precision, extended-precision (80-bit and 128-bit), and arbitrary-precision floating-point types,
  • high-precision zero-cost dense output,
  • accurate and reliable event detection,
  • builtin support for analytical mechanics - bring your own Lagrangians/Hamiltonians and let heyoka formulate and solve the equations of motion,
  • builtin support for machine learning applications via neural network models,
  • the ability to maintain machine precision accuracy over tens of billions of timesteps,
  • batch mode integration to harness the power of modern SIMD instruction sets (including AVX/AVX2/AVX-512/Neon/VSX),
  • ensemble simulations and automatic parallelisation.

If you prefer using Python rather than C++, heyoka can be used from Python via heyoka.py, its Python bindings.

If you are using heyoka as part of your research, teaching, or other activities, we would be grateful if you could star the repository and/or cite our work. For citation purposes, you can use the following BibTex entry, which refers to the heyoka paper (arXiv preprint):

@article{10.1093/mnras/stab1032,
    author = {Biscani, Francesco and Izzo, Dario},
    title = "{Revisiting high-order Taylor methods for astrodynamics and celestial mechanics}",
    journal = {Monthly Notices of the Royal Astronomical Society},
    volume = {504},
    number = {2},
    pages = {2614-2628},
    year = {2021},
    month = {04},
    issn = {0035-8711},
    doi = {10.1093/mnras/stab1032},
    url = {https://doi.org/10.1093/mnras/stab1032},
    eprint = {https://academic.oup.com/mnras/article-pdf/504/2/2614/37750349/stab1032.pdf}
}

heyoka's novel event detection system is described in the following paper (arXiv preprint):

@article{10.1093/mnras/stac1092,
    author = {Biscani, Francesco and Izzo, Dario},
    title = "{Reliable event detection for Taylor methods in astrodynamics}",
    journal = {Monthly Notices of the Royal Astronomical Society},
    volume = {513},
    number = {4},
    pages = {4833-4844},
    year = {2022},
    month = {04},
    issn = {0035-8711},
    doi = {10.1093/mnras/stac1092},
    url = {https://doi.org/10.1093/mnras/stac1092},
    eprint = {https://academic.oup.com/mnras/article-pdf/513/4/4833/43796551/stac1092.pdf}
}

Quick example

As a simple example, here's how the ODE system of the pendulum is defined and numerically integrated in heyoka:

#include <iostream>

#include <heyoka/heyoka.hpp>

using namespace heyoka;

int main()
{
    // Create the symbolic variables x and v.
    auto [x, v] = make_vars("x", "v");

    // Create the integrator object
    // in double precision.
    auto ta = taylor_adaptive<double>{// Definition of the ODE system:
                                      // x' = v
                                      // v' = -9.8 * sin(x)
                                      {prime(x) = v, prime(v) = -9.8 * sin(x)},
                                      // Initial conditions
                                      // for x and v.
                                      {0.05, 0.025}};

    // Integrate for 10 time units.
    ta.propagate_for(10.);

    // Print the state vector.
    std::cout << "x(10) = " << ta.get_state()[0] << '\n';
    std::cout << "v(10) = " << ta.get_state()[1] << '\n';
}

Output:

x(10) = 0.0487397
y(10) = 0.0429423

Documentation

The full documentation can be found here.

Authors

  • Francesco Biscani (European Space Agency)
  • Dario Izzo (European Space Agency)

License

heyoka is released under the MPL-2.0 license.

Recommend Projects

  • React photo React

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

  • Vue.js photo Vue.js

    🖖 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. 📊📈🎉

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 ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.