chromophile 1.0.7

Color maps for continuous quantitative data

The Chromophile color maps are designed for the accurate display of quantitative data. This package contains the Chromophile color maps in both Matplotlib and Bokeh formats.

Installation

The Chromophile color maps are distributed as a Python package. To install it, open a terminal and execute:

pip install chromophile

Or, in IPython or Jupyter, use the %pip magic command:

%pip install chromophile

The chromophile package has no required dependencies. To use the Chromophile color maps with Matplotlib, the matplotlib package must be available at the time chromophile is imported.

The tools used to develop the Chromophile color maps, and the source for the online documentation, are in a separate package called chromophile-dev. Most users will not need this package.

Usage

To use the color maps, import the Chromophile package:

>>> import chromophile as cp

The Chromophile color maps are stored in two formats:

• Matplotlib Colormap objects are stored in cmap. If Matplotlib is not available, cmap will equal None. The color maps are also added to Matplotlib’s color map registry.

• Bokeh palettes are stored in palette.

Individual color maps can be accessed either as dictionary items or as attributes of these objects. For example:

>>> cp.cmap.cp_dawn
<matplotlib.colors.ListedColormap object at ...>
>>> cp.palette['cp_peacock']
('#06003c', '#06013d', '#06023e', '#07043e', ...)

The same color map is returned regardless of how it is accessed:

>>> cp.cmap.cp_lemon_lime is cp.cmap['cp_lemon_lime']
True
>>> cp.palette.cp_blue is cp.palette['cp_blue']
True

Most IDEs should support tab completion for cmap and palette.

The available color maps can be listed using the .keys() method of cmap or palette or by calling dir() on either of these objects. They are also displayed in the online documentation.