README.md
1heyoka.py
2=========
3
4[](https://circleci.com/gh/bluescarni/heyoka.py)
5[](https://ci.appveyor.com/project/bluescarni/heyoka-py)
6[](https://github.com/bluescarni/heyoka.py/actions?query=workflow%3A%22GitHub+CI%22)
7
8[](https://anaconda.org/conda-forge/heyoka.py)
9
10<!-- PROJECT LOGO -->
11<br />
12<p align="center">
13 <a href="https://github.com/bluescarni/heyoka.py">
14 <img src="doc/images/white_logo.png" alt="Logo" width="280">
15 </a>
16 <p align="center">
17 Modern Taylor's method via just-in-time compilation
18 <br />
19 <a href="https://bluescarni.github.io/heyoka.py/index.html"><strong>Explore the docs »</strong></a>
20 <br />
21 <br />
22 <a href="https://github.com/bluescarni/heyoka.py/issues/new/choose">Report bug</a>
23 ·
24 <a href="https://github.com/bluescarni/heyoka.py/issues/new/choose">Request feature</a>
25 ·
26 <a href="https://github.com/bluescarni/heyoka.py/discussions">Discuss</a>
27 </p>
28</p>
29
30> The [heyókȟa](https://en.wikipedia.org/wiki/Heyoka>) [...] is a kind of
31> sacred clown in the culture of the Sioux (Lakota and Dakota people)
32> of the Great Plains of North America. The heyoka is a contrarian, jester,
33> and satirist, who speaks, moves and reacts in an opposite fashion to the
34> people around them.
35
36heyoka.py is a Python library for the integration of ordinary differential equations
37(ODEs) via Taylor's method. Notable features include:
38
39* support for both double-precision and extended-precision floating-point types
40 (80-bit and 128-bit),
41* the ability to maintain machine precision accuracy over
42 tens of billions of timesteps,
43* high-precision zero-cost dense output,
44* accurate and reliable event detection,
45* batch mode integration to harness the power of modern
46 [SIMD](https://en.wikipedia.org/wiki/SIMD) instruction sets,
47* interoperability with [SymPy](https://www.sympy.org/en/index.html),
48* a high-performance implementation of Taylor's method based
49 on automatic differentiation techniques and aggressive just-in-time
50 compilation via [LLVM](https://llvm.org/).
51
52heyoka.py is based on the [heyoka C++ library](https://github.com/bluescarni/heyoka).
53
54If you are using heyoka.py as part of your research, teaching, or other activities, we would be grateful if you could star
55the repository and/or cite our work. For citation purposes, you can use the following BibTex entry, which refers
56to the heyoka.py paper ([arXiv preprint](https://arxiv.org/abs/2105.00800)):
57
58```bibtex
59@article{10.1093/mnras/stab1032,
60 author = {Biscani, Francesco and Izzo, Dario},
61 title = "{Revisiting high-order Taylor methods for astrodynamics and celestial mechanics}",
62 journal = {Monthly Notices of the Royal Astronomical Society},
63 volume = {504},
64 number = {2},
65 pages = {2614-2628},
66 year = {2021},
67 month = {04},
68 issn = {0035-8711},
69 doi = {10.1093/mnras/stab1032},
70 url = {https://doi.org/10.1093/mnras/stab1032},
71 eprint = {https://academic.oup.com/mnras/article-pdf/504/2/2614/37750349/stab1032.pdf}
72}
73```
74
75Documentation
76-------------
77
78The full documentation can be found [here](https://bluescarni.github.io/heyoka.py/).
79
80Authors
81-------
82
83* Francesco Biscani (Max Planck Institute for Astronomy)
84* Dario Izzo (European Space Agency)
85
86License
87-------
88
89heyoka.py is released under the [MPL-2.0](https://www.mozilla.org/en-US/MPL/2.0/FAQ/)
90license.
91
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