# contrib_colormaps: User-contributed colormaps
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## What is it?
contrib_colormaps is a collection of user-contributed colormaps
for use with Python plotting programs such as
[Bokeh](https://bokeh.org),
[Matplotlib](https://matplotlib.org),
[HoloViews](https://holoviews.org), and
[Datashader](https://datashader.org).
## Installation
contrib_colormaps supports Python 2.7, 3.5, 3.6 and 3.7 on Linux, Windows,
or Mac and can be installed with conda from the pyviz channel:
```
conda install -c pyviz contrib_colormaps
```
or with pip:
```
pip install contrib_colormaps
```
## Contributing
To add a colormap, open a pull request on this repository adding the following files:
1. comma-separated file of RGB values to the contrib_colormaps/colormaps
directory. This file should look like:
```
0, 0.20755, 0.97632
0, 0.22113, 0.96201
```
2. A Jupyter notebook in [examples/colormaps](examples/colormaps) meeting the following criteria:
1. a name that matches the name of the csv
e.g. for a new colormap called `rainforest` with a csv *rainforest.csv* there should be a corresponding *rainforest.ipynb*
2. an explanation of the colormap - what is it? and when/why would someone use it?
3. a swatch of the colormap - we recommend using our [swatch function](index.ipynb), but it's not required
4. at least one example plot using the colormap - it can be exclusively Bokeh, Matplotlib, or Holoviews
The notebook should be cleared of all outputs. To use the UI, click Cell -> All Outputs -> Clear
<img src="assets/clear_outputs.png" alt="Clear all outputs" width="50%"/>
OR clear them automatically on commit using the predefined git hook.
From within the cloned repository, run:
```bash
git config core.hooksPath .githooks
```
3. A pytest-mpl baseline image for tests. To create this image first install pytest-mpl:
```bash
pip install pytest-mpl
```
Then generate the figure **from within the tests directory** run:
```bash
pytest --mpl-generate-path=baseline
```
See [examples/colormaps](contrib_colormaps/tests) for more details.
### Sample Pull Request
You can use this sample pull request as a model: [#3](https://github.com/pyviz/contrib_colormaps/pull/3)
## About PyViz
contrib_colormaps is part of the PyViz initiative for making Python-based
visualization tools work well together. See [pyviz.org](http://pyviz.org).