Agree this is broken inadvertently. We refactored some things in colorbar, but the infinite API complexity that crept in over the years is causing problems here again. I'll try to fix, but we almost need a separate colorbar for contour, rather than tests all over the place.

BTW, a workaround here is to simply call

cbar.ax.set_yscale('log')

at the end of the script.

Interesting, I shall try it out, thanks!

Bug summary

The colour bar ticks are weirdly formatted when using a logarithmic scale when using version 3.5.0 or later.

Code for reproduction

Taken from https://matplotlib.org/stable/gallery/images_contours_and_fields/contourf_log.html


import matplotlib.pyplot as plt
import numpy as np
from numpy import ma
from matplotlib import ticker, cm

N = 100
x = np.linspace(-3.0, 3.0, N)
y = np.linspace(-2.0, 2.0, N)

X, Y = np.meshgrid(x, y)

# A low hump with a spike coming out.
# Needs to have z/colour axis on a log scale so we see both hump and spike.
# linear scale only shows the spike.
Z1 = np.exp(-X**2 - Y**2)
Z2 = np.exp(-(X * 10)**2 - (Y * 10)**2)
z = Z1 + 50 * Z2

# Put in some negative values (lower left corner) to cause trouble with logs:
z[:5, :5] = -1

# The following is not strictly essential, but it will eliminate
# a warning.  Comment it out to see the warning.
z = ma.masked_where(z <= 0, z)


# Automatic selection of levels works; setting the
# log locator tells contourf to use a log scale:
fig, ax = plt.subplots()
cs = ax.contourf(X, Y, z, locator=ticker.LogLocator(), cmap=cm.PuBu_r)

cbar = fig.colorbar(cs)

plt.show()

Actual outcome

Expected outcome

Running the exact same code on 3.4.2 produces the expected behaviour

Additional information

This worked perfectly on version 3.4.2

Operating system

Windows

Matplotlib Version

3.5.0

Matplotlib Backend

No response

Python version

No response

Jupyter version

No response

Installation

pip

This issue is still happening in version 3.9.12

We don't have a 3.9.12, did you mean 3.9.1 or 3.9.2?

I can not reproduce this with 3.9.2, 3.8.4, or main

Sorry, that is my Python version, my bad. I'm using Matplotlib version 3.5.1.

This bug looks like it was fixed in mpl 3.6.3 so you will need to upgrade atleast that far to get the fix.