fau_colors 1.6.0

The official colors of FAU as matplotlib/seaborn colormaps

FAU - Colors

The official colors of Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) as matplotlib / seaborn colormaps and GIMP colopalette

We support the old colors based on the 2019 CI-guidelines and the brand new 2021 Brand redesign.

Download the colors

Gimp/Inkscape

If you just need the colors outside Python, you can download a GIMP colorpalette with all colors (see image below). Right click any of the links below and then select "Save Link as":

2019 colors
2021 colors

These files can be imported into GIMP or Inkscape.

Latex

We also provide a LaTeX color file for the 2021 colors. You can download it here:

2021 colors

For this to work you need to include the xcolor package in your preamble (\usepackage{xcolor}) and then you can use the colors by copying the file into your project and including it in your document (\input{fau_colors_2021.tex}).

If you need the colors in other formats, please open an issue with details about the required file format.

Installation

pip install fau-colors

Quick Guide

2021 colormaps

import seaborn as sns

from fau_colors import register_cmaps
register_cmaps()

sns.set_palette("tech")

2019 colormaps

import seaborn as sns

from fau_colors.v2019 import register_cmaps
register_cmaps()

sns.set_palette("tech")

General Usage

The 2019 and the 2021 colors are available in the separate submodules fau_colors.v2019 and fau_colors.v2021 that contain equivalent functions.

Note: For convenience, the v2021 colors can also be accessed from the top-level. In the following examples we will use this shorter notation.

The methods below show the usage with the new color scheme. For the old colors simply replace the module name.

Registering color palettes

The easiest way to use the provided color palettes is to register them as global matplotlib colormaps. This can be done by calling the register_cmaps() function from the respective submodule. All available cmaps can be seen in the images above.

2021 colors

>>> from fau_colors import register_cmaps  # v2021 colors
>>> register_cmaps()

2019 colors

>>> from fau_colors.v2019 import register_cmaps
>>> register_cmaps()

WARNING: The 2019 and 2021 cmaps have overlapping names! This means you can not register both at the same time. You need to call unregister_cmaps from the correct module first, before you can register the other colormaps. If you need colormaps from both CI-guides, use them individually, as shown below.

Getting the raw colors

All primary faculty colors are stored in a namedtuple called colors.

2021 colors

>>> from fau_colors import colors  # v2021 colors
>>> colors
FacultyColors(fau='#002F6C', tech='#779FB5', phil='#FFB81C', med='#00A3E0', nat='#43B02A', wiso='#C8102E')
>>> colors.fau
'#002F6C'

2019 colors

>>> from fau_colors.v2019 import colors
>>> colors
FacultyColors(fau='#003865', tech='#98a4ae', phil='#c99313', med='#00b1eb', nat='#009b77', wiso='#8d1429')
>>> colors.fau
'#003865'

For the 2021 color scheme also the variable colors_dark, colors_light, and colors_all are available. They contain the dark and light variants of each color, as well as regular, dark, and light colors combined, respectively.

Manually getting the colormaps

The colormaps are stored in a namedtuple called cmaps. There are colormaps for the primary colors and colormaps with varying lightness using each color as the base color. The latter colormaps contain 5 colors each with 12.5, 25, 37.5, 62.5, and 100% value of the base color. If you need more than 5 colors see below.

2021 colors

>>> from fau_colors import cmaps  # v2021 colors
>>> # Only get the names here
>>> cmaps._fields
('faculties', 'faculties_dark', 'faculties_light', 'faculties_all', 'fau', 'fau_dark', 'fau_light', 'tech', 'tech_dark', 'tech_light', 'phil', 'phil_dark', 'phil_light', 'med', 'med_dark', 'med_light', 'nat', 'nat_dark', 'nat_light', 'wiso', 'wiso_dark', 'wiso_light')
>>> cmaps.fau_dark
[(0.01568627450980392, 0.11764705882352941, 0.25882352941176473), (0.3823913879277201, 0.4463667820069205, 0.5349480968858131), (0.629434832756632, 0.6678200692041523, 0.7209688581314879), (0.7529565551710881, 0.7785467128027682, 0.8139792387543252), (0.876478277585544, 0.889273356401384, 0.9069896193771626)]
>>> import seaborn as sns
>>> sns.set_palette(cmaps.fau_dark)

2019 colors

>>> from fau_colors.v2019 import cmaps
>>> # Only get the names here
>>> cmaps._fields
('faculties', 'fau', 'tech', 'phil', 'med', 'nat', 'wiso')
>>> cmaps.fau
[(0.0, 0.2196078431372549, 0.396078431372549), (0.37254901960784315, 0.5103421760861206, 0.6210688196847366), (0.6235294117647059, 0.7062053056516724, 0.772641291810842), (0.7490196078431373, 0.8041368704344483, 0.8484275278738946), (0.8745098039215686, 0.9020684352172241, 0.9242137639369473)]
>>> import seaborn as sns
>>> sns.set_palette(cmaps.fau)

Modifying the colormaps

Sometimes five colors are not enough for a colormap. The easiest way to generate more colors is to use one of the FAU colors as base and then create custom sequential palettes from it. This can be done using sns.light_palette or sns.dark_palette, as explained here.

2021 colors

>>> from fau_colors import colors  # v2021 colors
>>> import seaborn as sns
>>> sns.light_palette(colors.med, n_colors=8)
[(0.9370639121761148, 0.9445189791516921, 0.9520035391049294), (0.8047725363394869, 0.9014173378043252, 0.9416168802970363), (0.6688064000629526, 0.8571184286417537, 0.9309417031889239), (0.5365150242263246, 0.8140167872943868, 0.9205550443810308), (0.40054888794979027, 0.7697178781318151, 0.9098798672729183), (0.2682575121131623, 0.7266162367844482, 0.8994932084650251), (0.13229137583662798, 0.6823173276218767, 0.8888180313569127), (0.0, 0.6392156862745098, 0.8784313725490196)]

2019 colors

>>> from fau_colors.v2019 import colors
>>> import seaborn as sns
>>> sns.light_palette(colors.med, n_colors=8)
[(0.9363137612705862, 0.94473936725293, 0.9520047198366567), (0.8041282890912094, 0.9093574773431737, 0.9477078597351495), (0.6682709982401831, 0.8729927571581465, 0.9432916424086003), (0.5360855260608062, 0.8376108672483904, 0.9389947823070931), (0.40022823520978, 0.8012461470633632, 0.9345785649805439), (0.2680427630304031, 0.765864257153607, 0.9302817048790367), (0.13218547217937693, 0.7294995369685797, 0.9258654875524875), (0.0, 0.6941176470588235, 0.9215686274509803)]c