Simulation and visualization of strange attractors
Project description
attractors
attractors is a package for simulation and visualization of strange attractors.
Installation
The simplest way to install the module is via PyPi using pip
pip install attractors
Alternatively, the package can be installed via github as follows
git clone https://github.com/Vignesh-Desmond/attractors cd attractors python -m pip install .
To set up the package for development and debugging, it is recommended to use Poetry. Just install with poetry install and let Poetry manage the environment and dependencies.
Prerequisites
To generate video output, the package uses ffmpeg. Download and install from here according to your os and distribution and set PATH accordingly. Note that this is only required for generating video output.
Usage
See documentation on readthedocs.io
Changelog
See changelog for previous versions
Development
This package is under early stages of development it’s open to any constructive suggestions. Please send bug reports and feature requests through issue trackers and pull requests.
License
This package is licensed under the MIT License
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file attractors-1.4.1.tar.gz
.
File metadata
- Download URL: attractors-1.4.1.tar.gz
- Upload date:
- Size: 30.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.1.7 CPython/3.8.11 Linux/5.8.0-1039-azure
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0f97bb6a07aaa6f24132b1f92b75e55965d8c8ea6a789dc59ae786b900167bc8 |
|
MD5 | 815d9705c33946acd4379d3041cfe7f0 |
|
BLAKE2b-256 | 13fdf32716e07836dae77dd42b3b9a7b831589b040e15750da614e8824477d0c |
File details
Details for the file attractors-1.4.1-py3-none-any.whl
.
File metadata
- Download URL: attractors-1.4.1-py3-none-any.whl
- Upload date:
- Size: 33.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.1.7 CPython/3.8.11 Linux/5.8.0-1039-azure
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | f7345aa07cd5ee76d8849f21c390d0e947713c873d0fb8f604473e9ea0f8e421 |
|
MD5 | f39d2db3e47bd99a6277df24f8da5bb9 |
|
BLAKE2b-256 | d193d235ded8cc96e9381e08715a6789a3a3478978cdd6f5794e90cfb38bbfe1 |