The official colors of the FAU as matplotlib/seaborn colormaps

Overview

FAU - Colors

PyPI GitHub Code style: black PyPI - Downloads GitHub commit activity

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

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

Installation

pip install fau-colors

Quick Guide

2021 colormaps

2021 colors

import seaborn as sns

from fau_colors import register_cmaps
register_cmaps()

sns.set_palette("tech")

2019 colormaps

2019 colors

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 and colors_all are available. They contain the dark variant of each color, as well as light and dark 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_all', 'fau', 'fau_dark', 'tech', 'tech_dark', 'phil', 'phil_dark', 'med', 'med_dark', 'nat', 'nat_dark', 'wiso', 'wiso_dark')
>>> 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
You might also like...
:small_red_triangle: Ternary plotting library for python with matplotlib
:small_red_triangle: Ternary plotting library for python with matplotlib

python-ternary This is a plotting library for use with matplotlib to make ternary plots plots in the two dimensional simplex projected onto a two dime

Joyplots in Python with matplotlib & pandas :chart_with_upwards_trend:
Joyplots in Python with matplotlib & pandas :chart_with_upwards_trend:

JoyPy JoyPy is a one-function Python package based on matplotlib + pandas with a single purpose: drawing joyplots (a.k.a. ridgeline plots). The code f

A python package for animating plots build on matplotlib.
A python package for animating plots build on matplotlib.

animatplot A python package for making interactive as well as animated plots with matplotlib. Requires Python = 3.5 Matplotlib = 2.2 (because slider

matplotlib: plotting with Python
matplotlib: plotting with Python

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Check out our home page for more inform

Statistical data visualization using matplotlib

seaborn: statistical data visualization Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing

:small_red_triangle: Ternary plotting library for python with matplotlib
:small_red_triangle: Ternary plotting library for python with matplotlib

python-ternary This is a plotting library for use with matplotlib to make ternary plots plots in the two dimensional simplex projected onto a two dime

Joyplots in Python with matplotlib & pandas :chart_with_upwards_trend:
Joyplots in Python with matplotlib & pandas :chart_with_upwards_trend:

JoyPy JoyPy is a one-function Python package based on matplotlib + pandas with a single purpose: drawing joyplots (a.k.a. ridgeline plots). The code f

A python package for animating plots build on matplotlib.
A python package for animating plots build on matplotlib.

animatplot A python package for making interactive as well as animated plots with matplotlib. Requires Python = 3.5 Matplotlib = 2.2 (because slider

Painlessly create beautiful matplotlib plots.
Painlessly create beautiful matplotlib plots.

Announcement Thank you to everyone who has used prettyplotlib and made it what it is today! Unfortunately, I no longer have the bandwidth to maintain

Comments
Releases(v1.4.3)
Owner
Machine Learning and Data Analytics Lab FAU
Public projects of the Machine Learning and Data Analytics Lab at the Friedrich-Alexander-University Erlangen-Nürnberg
Machine Learning and Data Analytics Lab FAU
Custom Plotly Dash components based on Mantine React Components library

Dash Mantine Components Dash Mantine Components is a Dash component library based on Mantine React Components Library. It makes it easier to create go

Snehil Vijay 239 Jan 08, 2023
Simple addon for snapping active object to mesh ground

Snap to Ground Simple addon for snapping active object to mesh ground How to install: install the Python file as an addon use shortcut "D" in 3D view

Iyad Ahmed 12 Nov 07, 2022
A python package for animating plots build on matplotlib.

animatplot A python package for making interactive as well as animated plots with matplotlib. Requires Python = 3.5 Matplotlib = 2.2 (because slider

Tyler Makaro 394 Dec 18, 2022
Statistics and Visualization of acceptance rate, main keyword of CVPR 2021 accepted papers for the main Computer Vision conference (CVPR)

Statistics and Visualization of acceptance rate, main keyword of CVPR 2021 accepted papers for the main Computer Vision conference (CVPR)

Hoseong Lee 78 Aug 23, 2022
Graphical display tools, to help students debug their class implementations in the Carcassonne family of projects

carcassonne_tools Graphical display tools, to help students debug their class implementations in the Carcassonne family of projects NOTE NOTE NOTE The

1 Nov 08, 2021
Pydrawer: The Python package for visualizing curves and linear transformations in a super simple way

pydrawer 📐 The Python package for visualizing curves and linear transformations in a super simple way. ✏️ Installation Install pydrawer package with

Dylan Tintenfich 56 Dec 30, 2022
Calendar heatmaps from Pandas time series data

Note: See MarvinT/calmap for the maintained version of the project. That is also the version that gets published to PyPI and it has received several f

Martijn Vermaat 195 Dec 22, 2022
Make scripted visualizations in blender

Scripted visualizations in blender The goal of this project is to script 3D scientific visualizations using blender. To achieve this, we aim to bring

Praneeth Namburi 10 Jun 01, 2022
Plot-configurations for scientific publications, purely based on matplotlib

TUEplots Plot-configurations for scientific publications, purely based on matplotlib. Usage Please have a look at the examples in the example/ directo

Nicholas Krämer 487 Jan 08, 2023
Statistical data visualization using matplotlib

seaborn: statistical data visualization Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing

Michael Waskom 10.2k Dec 30, 2022
nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation.

nptsne nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation and HSNE modelling. For more detail s

Biomedical Visual Analytics Unit LUMC - TU Delft 29 Jul 05, 2022
This is a Web scraping project using BeautifulSoup and Python to scrape basic information of all the Test matches played till Jan 2022.

Scraping-test-matches-data This is a Web scraping project using BeautifulSoup and Python to scrape basic information of all the Test matches played ti

Souradeep Banerjee 4 Oct 10, 2022
Some examples with MatPlotLib library in Python

MatPlotLib Example Some examples with MatPlotLib library in Python Point: Run files only in project's directory About me Full name: Matin Ardestani Ag

Matin Ardestani 4 Mar 29, 2022
A Python Binder that merge 2 files with any extension by creating a new python file and compiling it to exe which runs both payloads.

Update ! ANONFILE MIGHT NOT WORK ! About A Python Binder that merge 2 files with any extension by creating a new python file and compiling it to exe w

Vesper 15 Oct 12, 2022
Sprint planner considering JIRA issues and google calendar meetings schedule.

Sprint planner Sprint planner is a Python script for planning your Jira tasks based on your calendar availability. Installation Use the package manage

Apptension 2 Dec 05, 2021
With Holoviews, your data visualizes itself.

HoloViews Stop plotting your data - annotate your data and let it visualize itself. HoloViews is an open-source Python library designed to make data a

HoloViz 2.3k Jan 02, 2023
Wikipedia WordCloud App generate Wikipedia word cloud art created using python's streamlit, matplotlib, wikipedia and wordcloud packages

Wikipedia WordCloud App Wikipedia WordCloud App generate Wikipedia word cloud art created using python's streamlit, matplotlib, wikipedia and wordclou

Siva Prakash 5 Jan 02, 2022
Productivity Tools for Plotly + Pandas

Cufflinks This library binds the power of plotly with the flexibility of pandas for easy plotting. This library is available on https://github.com/san

Jorge Santos 2.7k Dec 30, 2022
A central task in drug discovery is searching, screening, and organizing large chemical databases

A central task in drug discovery is searching, screening, and organizing large chemical databases. Here, we implement clustering on molecular similarity. We support multiple methods to provide a inte

NVIDIA Corporation 124 Jan 07, 2023
Streamlit component for Let's-Plot visualization library

streamlit-letsplot This is a work-in-progress, providing a convenience function to plot charts from the Lets-Plot visualization library. Example usage

Randy Zwitch 9 Nov 03, 2022