orbithunter 1.3.3
orbithunter serves as a framework for solving chaotic nonlinear partial differential equations.
Features
An object oriented approach to solutions of partial differential equations
A general-purpose framework for finding, visualizing and manipulating these solutions
High-level access to SciPy API, particularly its minimize and optimize packages.
New spatiotemporal techniques such as ‘clipping’ and ‘gluing’
Currently there is only an implementation of the Kuramoto-Sivashinsky equation (KSE).
External Links
Be sure to check out these resources for help and development!
Support
If you are having issues, please let us know. We have a mailing list located at: orbithunter@googlegroups.com
License
The project is licensed under the GNU General Public License v3 (GPLv3) license.
1 maintainer
Metadata
1 maintainer
Release files for orbithunter 1.3.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| orbithunter-1.3.3.tar.gz | 120.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| orbithunter-1.3.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 244.4 kB
Release files / orbithunter-1.3.3.tar.gz
| Download URL | orbithunter-1.3.3.tar.gz |
|---|---|
| Size | 120.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/5.1.1 CPython/3.11.7
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Release files / orbithunter-1.3.3-py3-none-any.whl
| Download URL | orbithunter-1.3.3-py3-none-any.whl |
|---|---|
| Size | 124.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.11.7
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