"""
=======================
Colorbar Tick Labelling
=======================

Vertical colorbars have ticks, tick labels, and labels visible on the *y* axis,
horizontal colorbars on the *x* axis. The ``ticks`` parameter can be used to
set the ticks and the ``format`` parameter can be used to format the tick labels
of the visible colorbar 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

import matplotlib.ticker as mticker

# Fixing random state for reproducibility
rng = np.random.default_rng(seed=19680801)

# %%
# Make plot with vertical (default) colorbar

fig, ax = plt.subplots()

data = rng.standard_normal((250, 250))

cax = ax.imshow(data, vmin=-1, vmax=1, cmap='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],
                    format=mticker.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(data, -1, 1)

cax = ax.imshow(data, cmap='afmhot')
ax.set_title('Gaussian noise with 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`