https://github.com/glotzerlab/plato

Efficient visualization of particle data supporting several rendering engines.
https://github.com/glotzerlab/plato

2d 3d library matplotlib opengl povray python raytracing threejs visualization

Last synced: 3 months ago
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Efficient visualization of particle data supporting several rendering engines.

• Host: GitHub
• URL: https://github.com/glotzerlab/plato
• Owner: glotzerlab
• License: bsd-3-clause
• Created: 2019-02-09T12:21:29.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2021-12-10T19:11:09.000Z (about 3 years ago)
• Last Synced: 2024-10-05T04:48:15.229Z (4 months ago)
• Topics: 2d, 3d, library, matplotlib, opengl, povray, python, raytracing, threejs, visualization
• Language: Python
• Homepage: https://plato-draw.readthedocs.io/
• Size: 833 KB
• Stars: 12
• Watchers: 10
• Forks: 4
• Open Issues: 14
• Metadata Files:
  • Readme: README.md
  • Changelog: changelog.md
  • License: LICENSE.txt

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# Introduction

Plato is designed for efficient visualization of particle data:

collections of particles that may be colored or oriented

differently. It fills a similar role as matplotlib, but is less

focused on 2D plotting. It supports a variety of backends with

different capabilities and use cases, ranging from interactive

visualization in the desktop or jupyter notebooks to high-quality,

static raytraced and vector images for publication.

# Installation

Plato is available on PyPI for installation via pip:

```

$ pip install plato-draw

```

You can also install plato from source, like this:

```

$ git clone https://github.com/glotzerlab/plato.git

$ # now install

$ cd plato && python setup.py install

```

**Note**: Depending on which backends you want to use, there may be

additional steps required; see the section on interactive backends

below.

## Using Interactive Backends

Plato supports a number of backends, each with its own set of

dependencies. Getting the vispy backend working for both the desktop

and jupyter notebook can be tricky. Make sure to check the official

[vispy documentation](http://vispy.org/installation.html). We also

keep some advice

[here](https://bitbucket.org/snippets/glotzer/nMg8Gr/plato-dependency-installation-tips)

regarding particular known-good versions of dependencies for pip and

conda.

# Documentation

The documentation is available as standard sphinx documentation:

```

$ cd doc

$ pip install -r requirements.txt

$ make html

```

Automatically-built documentation is available at

https://plato-draw.readthedocs.io .

# Examples

Several usage examples are available. Many simple, but less

interesting, scenes can be found in [the test demo scene

script](https://github.com/glotzerlab/plato/blob/master/test/test_scenes.py),

available as [live examples on

mybinder.org](https://mybinder.org/v2/gh/glotzerlab/plato/master?filepath=examples). Somewhat

less transparent examples can be found in [the plato-gallery

repository](https://github.com/glotzerlab/plato-gallery).