Add matplotlib cyclers with official RWTH colors

README.md

@@ -17,6 +17,9 @@ If you have already downloaded/cloned the package yourself you can use `python s
 ## qutil.plotting
 `cycle_plots` helps you cycling through many plots with the arrow keys (there are probably much better functions for this out there)
 `plot_2d_dataframe` helps you plot 2d data frames with numeric indices
+`get_rwth_color_cycle` and the predefined `rwth_color_cycle` are cycler instances with the official RWTH corporate design colors:
+
+![cycler example](./doc/source/_static/cycles.png)
 
 ## qutil.matlab
 In this module there are functions that are helpful for reading `.mat` files, especially those created with special measure. If you simply want to open a random `.mat` file you can use `hdf5storage.loadmat`.

qutil/plotting.py

 """This module contains some useful plotting functions"""
+from collections import OrderedDict
 from weakref import WeakValueDictionary
-from typing import Tuple
+from typing import Sequence, Tuple
 import warnings
 
+from matplotlib import cycler
 from matplotlib import pyplot as plt
 import pandas as pd
 import numpy as np
 
 
-__all__ = ["plot_2d_dataframe"]
+__all__ = ["plot_2d_dataframe", "rwth_color_cycle"]
+
+_color_names = ['blue', 'magenta', 'green', 'orange', 'teal', 'maygreen',
+                'red', 'purple', 'violet', 'bordeaux', 'petrol', 'yellow']
+_color_tuples = [
+    (0/255, 84/255, 159/255),       # blue
+    (227/255, 0/255, 102/255),      # magenta
+    (87/255, 171/255, 39/255),      # green
+    (246/255, 168/255, 0/255),      # orange
+    (0/255, 152/255, 161/255),      # teal
+    (189/255, 205/255, 0/255),      # maygreen
+    (204/255, 7/255, 30/255),       # red
+    (122/255, 111/255, 172/255),    # purple
+    (97/255, 33/255, 88/255),       # violet
+    (161/255, 16/255, 53/255),      # bordeaux
+    (0/255, 97/255, 101/255),       # petrol
+    (255/255, 237/255, 0/255),      # yellow
+]
+_RWTH_COLORS = OrderedDict(zip(_color_names, _color_tuples))
 
 
 def _to_corner_coords(index: pd.Index) -> np.ndarray:
@@ -179,3 +199,45 @@ def cycle_plots(plot_callback, *args,
     plt.draw_all()
 
     return fig, ax
+
+
+def get_rwth_color_cycle(alpha: float = 1, exclude: Sequence[str] = None):
+    """Get the default RWTH color cycle with an alpha channel.
+
+    Parameters
+    ----------
+    alpha: float
+        The alpha (transparency) value for the color cycle.
+    exclude: sequence of str
+        Exclude these colors. See _RWTH_COLORS for all available keys.
+        Yellow is a good choice to exclude.
+
+    Example
+    -------
+    >>> cycle_100 = get_rwth_color_cycle(1.)
+    >>> cycle_50 = get_rwth_color_cycle(.5)
+    >>> fig, ax = plt.subplots()
+    >>> x = np.linspace(0, 2*np.pi, 51)
+    >>> for i, (v100, v50) in enumerate(zip(cycle_100, cycle_50)):
+    >>>     ax.plot(x, np.sin(x) + i / len(cycle_100), lw=2, **v100)
+    >>>     ax.plot(x, -np.sin(x) + i / len(cycle_50), lw=2, **v50)
+
+    See Also
+    --------
+    https://matplotlib.org/3.3.3/tutorials/intermediate/color_cycle.html
+
+    https://matplotlib.org/cycler/
+    """
+    if alpha < 0 or alpha > 1:
+        raise ValueError('alpha should be in the range [0, 1].')
+
+    exclude = exclude or []
+    return cycler(color=[tup + (alpha,) for name, tup in _RWTH_COLORS.items()
+                         if name not in exclude])
+
+
+rwth_color_cycle_25 = get_rwth_color_cycle(.25)
+rwth_color_cycle_50 = get_rwth_color_cycle(.5)
+rwth_color_cycle_75 = get_rwth_color_cycle(.75)
+rwth_color_cycle_100 = get_rwth_color_cycle(1)
+rwth_color_cycle = rwth_color_cycle_100