Skip to main content

FURY - Free Unified Rendering in pYthon. A free and open-source software library for Scientific Visualization and 3D animations

Project description


FURY
Free Unified Rendering in Python

A software library for scientific visualization in Python.

General InformationKey FeaturesInstallationHow to useCreditsContributeCiting

FURY Networks swarming simulation shaders horse
Network Visualization Swarming/flocking simulation based on simple boids rules Easy shader effect integration.
sdf Collides simulation Physics bricks
Ray Marching and Signed Distance Functions Particle collisions Interoperability with the pyBullet library.
UI Tabs Shaders dragon skybox Picking object
Custom User Interfaces Shaders and SkyBox integration Easy picking manager

General Information

Key Features

  • Custom User Interfaces
  • Physics Engines API
  • Custom Shaders
  • Interactive local and Remote rendering in Jupyter Notebooks
  • Large amount of Tutorials and Examples

Installation

Releases

pip install fury or conda install -c conda-forge fury

Development

Installation from source

Step 1. Get the latest source by cloning this repo:

git clone https://github.com/fury-gl/fury.git

Step 2. Install requirements:

pip install -r requirements/default.txt

Step 3. Install fury

As a local project installation using:

pip install .

Or as an "editable" installation using:

pip install -e .

If you are developing fury you should go with editable installation.

Step 4: Enjoy!

For more information, see also installation page on fury.gl

Testing

After installation, you can install test suite requirements:

pip install -r requirements/test.txt

And to launch test suite:

pytest -svv fury

How to use

There are many ways to start using FURY:

Credits

Please, go to contributors page to see who have been involved in the development of FURY.

Contribute

We love contributions!

You've discovered a bug or something else you want to change - excellent! Create an issue!

Citing

If you are using FURY in your work then do cite this paper. By citing FURY, you are helping sustain the FURY ecosystem.

Eleftherios Garyfallidis, Serge Koudoro, Javier Guaje, Marc-Alexandre Côté, Soham Biswas,
David Reagan, Nasim Anousheh, Filipi Silva, Geoffrey Fox, and Fury Contributors.
"FURY: advanced scientific visualization." Journal of Open Source Software 6, no. 64 (2021): 3384.
https://doi.org/10.21105/joss.03384
    @article{Garyfallidis2021,
        doi = {10.21105/joss.03384},
        url = {https://doi.org/10.21105/joss.03384},
        year = {2021},
        publisher = {The Open Journal},
        volume = {6},
        number = {64},
        pages = {3384},
        author = {Eleftherios Garyfallidis and Serge Koudoro and Javier Guaje and Marc-Alexandre Côté and Soham Biswas and David Reagan and Nasim Anousheh and Filipi Silva and Geoffrey Fox and Fury Contributors},
        title = {FURY: advanced scientific visualization},
        journal = {Journal of Open Source Software}
    }

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

fury-0.12.0.tar.gz (69.7 MB view details)

Uploaded Source

Built Distribution

fury-0.12.0-py3-none-any.whl (596.0 kB view details)

Uploaded Python 3

File details

Details for the file fury-0.12.0.tar.gz.

File metadata

  • Download URL: fury-0.12.0.tar.gz
  • Upload date:
  • Size: 69.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.11.8

File hashes

Hashes for fury-0.12.0.tar.gz
Algorithm Hash digest
SHA256 105ff11e07974d9149f22e565c3cbb60d5d2c67ee98e66d04753e6f5a746d167
MD5 e6ef35db7bcd5a57af8ba5129b935871
BLAKE2b-256 ec2a4e89d4a3f99b8275b1f74428204c4fab721e6182fea955d03bdc94893b3d

See more details on using hashes here.

File details

Details for the file fury-0.12.0-py3-none-any.whl.

File metadata

  • Download URL: fury-0.12.0-py3-none-any.whl
  • Upload date:
  • Size: 596.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.11.8

File hashes

Hashes for fury-0.12.0-py3-none-any.whl
Algorithm Hash digest
SHA256 9e6df358d44316503d292a312184281d15cccd3d2da2c7b2e5d7ec1dfc841345
MD5 588981cf28b8fc78ab0b3dffe835a527
BLAKE2b-256 484a1a65b30905ea8ad3525d4d05a54998df6777db02e7a0649c8cacfffb06b0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page