distinctipy is a lightweight python package providing functions to generate colours that are visually distinct from one another.
Commonly available qualitative colormaps provided by the likes of matplotlib generally have no more than 20 colours, but for some applications it is useful to have many more colours that are clearly different from one another. distinctipy can generate lists of colours of any length, with each new colour added to the list being as visually distinct from the pre-existing colours in the list as possible.
distinctipy is designed for Python 3 and can be installed with pip by running:
python -m pip install distinctipy
Alternatively clone the repo and install it locally:
git clone https://github.com/alan-turing-institute/distinctipy.git
cd distinctipy
python -m pip install .
Starting in version 1.2.1 distinctipy
no longer bundles matplotlib
, pandas
or dev dependencies in the default installation. If you wish to view
colours (e.g. with distinctipy.color_swatch
) or examples you will need matplotlib
and pandas
installed. To do this, either install distinctipy
with the optional flag:
python -m pip install distinctipy[extras]
⚠️ Warning ⚠️ Previous versions of distinctipy (before 1.3) used [optional]
instead of [extras]
.
Or install them separately:
python -m pip install matplotlib pandas
For developers, to install the stack needed to run tests, generate docs etc. use:
python -m pip install distinctipy[extras,tests,docs]
distinctipy can:
distinctipy.get_colors(N)
distinctipy.get_colors(N, existing_colors)
distinctipy.get_colors(N, pastel_factor=0.7)
distinctipy.get_text_color(background_color)
distinctipy.get_colormap(colors)
distinctipy.invert_colors(colors)
distinctipy.color_swatch(colors)
examples.compare_clusters()
and examples.compare_colors()
colorblind.simulate_colors(colors, colorblind_type='Deuteranomaly')
distinctipy.get_colors(N, existing_colors, colorblind_type="Deuteranomaly")
For example, to create and then display N = 36 visually distinct colours:
import distinctipy
# number of colours to generate
N = 36
# generate N visually distinct colours
colors = distinctipy.get_colors(N)
# display the colours
distinctipy.color_swatch(colors)
More detailed usage and example output can be found in the notebook examples.ipynb and examples gallery.
distinctipy was heavily influenced and inspired by several web sources and stack overflow answers. In particular:
If you would like to cite distinctipy, please refer to the upload of the package on Zenodo: https://doi.org/10.5281/zenodo.3985191