Awesome

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. We also keep some advice here 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, available as live examples on mybinder.org. Somewhat less transparent examples can be found in the plato-gallery repository.