Metadata-Version: 2.4
Name: hiveplotlib
Version: 0.28.1
Summary: Visualize Network Data with Hive Plots
Author-email: Gary Koplik <gary.koplik@gmail.com>
License-Expression: BSD-3-Clause
Project-URL: Documentation, https://hiveplotlib.readthedocs.io/stable/
Project-URL: Source, https://gitlab.com/hiveplotlib/hiveplotlib
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Dynamic: license-file

![Hiveplotlib Logo](https://hiveplotlib.readthedocs.io/stable/_static/hiveplotlib.svg)

A plotting package for generating and visualizing static Hive Plots in Python.

![Supported Python Versions Matches PSF support](https://gitlab.com/hiveplotlib/hiveplotlib/-/raw/master/.gitlab/python_badge.svg)

[![Matplotlib Support](https://gitlab.com/hiveplotlib/hiveplotlib/-/raw/master/.gitlab/matplotlib_badge.svg)](https://matplotlib.org/)
[![Bokeh Support](https://gitlab.com/hiveplotlib/hiveplotlib/-/raw/master/.gitlab/bokeh_badge.svg)](https://docs.bokeh.org/en/latest/)
[![Holoviews Support](https://gitlab.com/hiveplotlib/hiveplotlib/-/raw/master/.gitlab/holoviews_badge.svg)](https://holoviews.org/index.html)
[![Plotly Support](https://gitlab.com/hiveplotlib/hiveplotlib/-/raw/master/.gitlab/plotly_badge.svg)](https://plotly.com/python/)
[![Datashader Support](https://gitlab.com/hiveplotlib/hiveplotlib/-/raw/master/.gitlab/datashader_badge.svg)](https://datashader.org/)
[![NetworkX Support](https://gitlab.com/hiveplotlib/hiveplotlib/-/raw/master/.gitlab/networkx_badge.svg)](https://networkx.org/)

# Installation

`hiveplotlib` can be installed via [pypi](https://pypi.org/project/hiveplotlib/):

```bash
pip install hiveplotlib
```

To uninstall, run:

```bash
pip uninstall hiveplotlib
```

By default, `hiveplotlib` supports visualization only with the [matplotlib](https://matplotlib.org/) backend, but
`hiveplotlib` also supports [bokeh](https://docs.bokeh.org/en/latest/), [holoviews](https://holoviews.org/index.html),
and [plotly](https://plotly.com/python/) visualizations, which can be installed via `pip install hiveplotlib[bokeh]`,
`pip install hiveplotlib[holoviews]`, and `pip install hiveplotlib[plotly]`, respectively.

`hiveplotlib` also supports large network visualization via the [datashader](https://datashader.org/) backend,
which can be installed as `pip install hiveplotlib[datashader]`.

Beyond the visualization backends, `hiveplotlib` integrates with [networkx](https://networkx.org/): build a hive plot
directly from a `networkx` graph and compute graph metrics on it. Install this integration with
`pip install hiveplotlib[networkx]`.

# How to Use and Examples

For more on how to use the software and examples, see the
[tutorials](https://hiveplotlib.readthedocs.io/stable/notebooks/index.html) and
[gallery examples](https://hiveplotlib.readthedocs.io/stable/gallery_examples/index.html).

We recommend starting with our
[Introduction to Hive Plots](https://hiveplotlib.readthedocs.io/stable/notebooks/introduction_to_hive_plots.html) and
[Quick Start Hive Plots](https://hiveplotlib.readthedocs.io/stable/notebooks/quick_hive_plots.html) pages.

All the example notebooks are available for download as `jupyter` notebooks in the repository under the
[examples](https://gitlab.com/hiveplotlib/hiveplotlib/-/tree/master/examples) directory.

To install this environment and associated `jupyter` kernel used to run the notebooks, clone the repository and run:

```bash
cd <path/to/repository>
bash install.sh
```

The resulting `hiveplotlib` kernel can run any of those notebooks.

# More on Hive Plots

For more on Hive Plots, see our
[Introduction to Hive Plots](https://hiveplotlib.readthedocs.io/stable/notebooks/introduction_to_hive_plots.html).

For additional resources, see:

- [https://hiveplot.com/](https://hiveplot.com/)

- Krzywinski M, Birol I, Jones S, Marra M (2011). Hive Plots — Rational Approach to
Visualizing Networks. Briefings in Bioinformatics (early access 9 December 2011,
doi: 10.1093/bib/bbr069).

# Contributing

For more on contributing to the project, see [CONTRIBUTING.md](https://gitlab.com/hiveplotlib/hiveplotlib/-/blob/master/CONTRIBUTING.md)

## Acknowledgements

We'd like to thank Rodrigo Garcia-Herrera for his work on
[`pyveplot`](https://gitlab.com/rgarcia-herrera/pyveplot), which we referenced
as a starting point for our structural design. We also translated some of his utility
methods for use in this repository.
