Daltonize simulates the three types of dichromatic color blindness and images and matplotlib figures. Generalizing and omitting a lot of details these types are:
- Deuteranopia: green weakness
- Protanopia: red weakness
- Tritanopia: blue weakness (extremely rare)
Daltonize can also adjust the color palette of an input image such that a color blind person can perceive the full information content. It can be used as a command line tool to convert pixel images but also as a Python module. If used as the latter, it provides an API to simulate and correct for color blindness in matplotlib figures.
This allows to create color blind friendly vector graphics suitable for publication.
$ git clone [email protected]:joergdietrich/daltonize.git
and copy daltonize.py to a location in your $PATH and/or $PYTHONPATH. Daltonize depends
- Pillow: https://python-pillow.github.io/
- numpy: http://www.numpy.org/
and
- matplotlib: http://matplotlib.org/
if it is used to work on matplotlib figure objects.
As a command line tool:
$ daltonize.py -h
usage: daltonize.py [-h] [-s | -d] [-t {d,p,t}] input_image output_image
positional arguments:
input_image
output_image
optional arguments:
-h, --help show this help message and exit
-s, --simulate create simulated image
-d, --daltonize adjust image color palette for color blindness
-t {d,p,t}, --type {d,p,t}
type of color blindness (deuteranopia, protanopia,
tritanopia), default is deuteranopia (most common)
As a Python module:
In [1]: import daltonize
[ Create a figure ]
In [10]: sim_fig = daltonize.simulate_mpl(fig, copy=True)
In [11]: daltonized_fig = daltonize.daltonize_mpl(fig, copy=True)
Based on the work and original matlab code by Onur Fidaner, Poliang Lin, Nevran Ozguven. This can be found in 'doc/'.
Based on original Python code by Oliver Siemoneit.
Further information on color blindness and daltonization is available at many web resources, including http://www.daltonize.org/
Color blind friendly color maps can be found at http://colorbrewer2.org/ All of these are included in the python matplotlib and seaborn plotting libraries.
The directory 'example_images/' contains three example Ishihara plates to test for red-green deficiency. This table describes what people with normal, red/green deficient color vision, and total color blindness see on these plates:
Plate | Normal | r/g deficiency | total color blindness |
---|---|---|---|
3 | 29 | 70 | x |
7 | 74 | 21 | x |
8 | 6 | x | x |
You can verify the r/g deficiency column by running daltonize.py with
the -s/--simulate
option and -t/--type d
or p
on these images.
This code is released und the GNU GPL version 2. See COPYING for details.