.. _external_links:

==============
External links
==============

This page contain links to related projects and projects that inspired ProPlot
or are directly used by ProPlot.

Python packages
===============

* `matplotlib <https://matplotlib.org>`__ - The venerable plotting workhorse we all know
  and love.
* `xarray <http://xarray.pydata.org/en/stable/api.html>`__ - Package for working with
  annotated ND numpy arrays. If you haven't heard of it and you work with NetCDF files,
  it will change your life.
* `pandas <https://pandas.pydata.org>`__ - Package that turns spreadsheets and tables
  into annotated 2D numpy arrays. Invaluable for certain types of data.
* `seaborn <https://seaborn.pydata.org>`__ - A statistical data visualization package.
  Seaborn is based on matplotlib, but its interface is mostly separate from matplotlib.
  It is not generally suitable for geophysical data.
* `cartopy <https://scitools.org.uk/cartopy/docs/latest/>`__ - A package for
  plotting geographic and geophysical data in matplotlib. Includes a suite of
  different map projections.
* `basemap <https://github.com/matplotlib/basemap>`__ - The original cartographic
  plotting package. Basemap is less closely integrated with matplotlib than
  cartopy but still quite popular. As of 2020 it is no longer actively maintained.

Downloadable colormaps
======================

The following colormap repositories are
imported and registered by ProPlot.

* `Color Brewer <http://colorbrewer2.org/#type=sequential&scheme=BuGn&n=3>`__ - The
  O.G. perceptually uniform colormap distribution. These are included with
  matplotlib by default.
* `cmocean <https://matplotlib.org/cmocean/>`__ - Perceptually uniform colormaps
  designed for oceanography, but suitable for plenty of other applications.
* `SciVisColor <https://sciviscolor.org/>`__ - Science-focused colormaps created by the
  viz team at UT Austin. Provides tools for *concatenating* colormaps, suitable for
  complex datasets with funky distributions.
* `Fabio Crameri <http://www.fabiocrameri.ch/colourmaps.php>`__ - Perceptually uniform
  colormaps for geoscientists. These maps have unusual and interesting color
  transitions.

..
  * `Cube Helix <https://ui.adsabs.harvard.edu/abs/2011BASI...39..289G/abstract>`__ - A
    series of colormaps generated by rotating through RGB channel values. The colormaps
    were added from `Palletable <https://jiffyclub.github.io/palettable/cubehelix/>`__.

Tools for making new colormaps
==============================

Use these resources to make colormaps from scratch. Then import them into
ProPlot by :ref:`adding files to the .proplot/cmaps folder <ug_cmaps_dl>`.

* `ProPlot colormap API <https://proplot.readthedocs.io/en/latest/colormaps.html#Making-new-colormaps>`__
* `HCL Picker <http://tristen.ca/hcl-picker/#/hlc/6/1/15534C/E2E062>`__
* `Chroma.js <https://gka.github.io/palettes/>`__
* `HCL Wizard <http://hclwizard.org:64230/hclwizard/>`__
* `SciVisColor <https://sciviscolor.org/home/colormoves/>`__

Tools for making new color cycles
=================================

Use these resources to make color cycles from scratch. Then import them into
ProPlot by :ref:`adding files to the .proplot/cycles folder <ug_cycles_dl>`.

* `ProPlot color cycle API <https://proplot.readthedocs.io/en/latest/cycles.html#Making-new-color-cycles>`__
* `Color Cycle Picker <https://colorcyclepicker.mpetroff.net/>`__
* `i want hue <http://medialab.github.io/iwanthue/>`__
* `Coolors <https://coolors.co/>`__
* `Color Hunt <https://colorhunt.co/>`__
* `Color Drop <https://colordrop.io/>`__
* `Adobe Color <https://color.adobe.com/explore>`__
