DOC: Modernize Colorbar Tick Labelling example

StefRe · StefRe · commit ae9f76281deb · 2023-07-04T18:22:04.000+02:00
- use colorbar.set_ticks instead of colorbar.ax.set_[x|y]ticklabels whose
  usage is discouraged
- now that we don't have to handle vertical and horizontal colorbars
  differently we can instead show different ways to achieve the same
  and show additional tweaks like labelling the colorbar extensions
  (strictly speaking the old labels &gt;1 and &lt;-1 were simply wrong for
  clipped data)
- update numpy random number generation
- add admonition
diff --git a/galleries/examples/ticks/colorbar_tick_labelling_demo.py b/galleries/examples/ticks/colorbar_tick_labelling_demo.py
@@ -3,45 +3,63 @@
 Colorbar Tick Labelling
 =======================
 
-Produce custom labelling for a colorbar.
+Different ways to produce custom labelling for a colorbar.
 
-Contributed by Scott Sinclair
+Vertical colorbars have their y axis labelled, horizontal ones their x axis.
+The ``ticks`` and ``format`` parameters can be used to set ticks and format
+labels of these axes. For further adjustments, the ``yaxis`` or ``xaxis`` axes
+of the colorbar can be retrieved using its ``ax`` property.
 """
-
 import matplotlib.pyplot as plt
 import numpy as np
-from numpy.random import randn
 
-from matplotlib import cm
+import matplotlib as mpl
 
 # Fixing random state for reproducibility
-np.random.seed(19680801)
+rng = np.random.default_rng(seed=19680801)
 
 # %%
 # Make plot with vertical (default) colorbar
 
 fig, ax = plt.subplots()
 
-data = np.clip(randn(250, 250), -1, 1)
+data = rng.standard_normal((250, 250))
 
-cax = ax.imshow(data, cmap=cm.coolwarm)
+cax = ax.imshow(data, vmin=-1, vmax=1, cmap=mpl.cm.coolwarm)
 ax.set_title('Gaussian noise with vertical colorbar')
 
 # Add colorbar, make sure to specify tick locations to match desired ticklabels
-cbar = fig.colorbar(cax, ticks=[-1, 0, 1])
-cbar.ax.set_yticklabels(['< -1', '0', '> 1'])  # vertically oriented colorbar
+cbar = fig.colorbar(cax,
+                    ticks=[-1, 0, 1],
+                    format=mpl.ticker.FixedFormatter(['< -1', '0', '> 1']),
+                    extend='both'
+                    )
+labels = cbar.ax.get_yticklabels()
+labels[0].set_verticalalignment('top')
+labels[-1].set_verticalalignment('bottom')
 
 # %%
 # Make plot with horizontal colorbar
 
 fig, ax = plt.subplots()
 
-data = np.clip(randn(250, 250), -1, 1)
+data = np.clip(data, -1, 1)
 
-cax = ax.imshow(data, cmap=cm.afmhot)
+cax = ax.imshow(data, cmap=mpl.cm.afmhot)
 ax.set_title('Gaussian noise with horizontal colorbar')
 
-cbar = fig.colorbar(cax, ticks=[-1, 0, 1], orientation='horizontal')
-cbar.ax.set_xticklabels(['Low', 'Medium', 'High'])  # horizontal colorbar
+# Add colorbar and adjust ticks afterwards
+cbar = fig.colorbar(cax, orientation='horizontal')
+cbar.set_ticks(ticks=[-1, 0, 1], labels=['Low', 'Medium', 'High'])
 
 plt.show()
+
+# %%
+#
+# .. admonition:: References
+#
+#    The use of the following functions, methods, classes and modules is shown
+#    in this example:
+#
+#    - `matplotlib.colorbar.Colorbar.set_ticks`
+#    - `matplotlib.figure.Figure.colorbar` / `matplotlib.pyplot.colorbar`
