Bug report
Bug summary
After upgrading to Matplotlib v3.0.0, the tick marks on the colorbar are no longer placed correctly when using a matplotlib.colors.LogNorm normalization.
Code for reproduction
The code is embedded in a class defined within the NeXpy application, but uses standard Matplotlib function calls. Here are the relevant extracted lines:
from matplotlib.colors import LogNorm, Normalize, SymLogNorm
from matplotlib.ticker import AutoLocator, LogLocator, ScalarFormatter
from matplotlib.ticker import LogFormatterSciNotation as LogFormatter
self.norm = LogNorm(self.vaxis.lo, self.vaxis.hi)
self.locator = LogLocator()
self.formatter = LogFormatter()
self.image = ax.pcolormesh(x, y, self.v, cmap=self.cmap, **opts)
self.image.set_norm(self.norm)
self.colorbar = self.figure.colorbar(self.image, ax=ax, norm=self.norm)
self.colorbar.locator = self.locator
self.colorbar.formatter = self.formatter
self.colorbar.update_normal(self.image)
Actual outcome
In Matplotlib v3.0.0, I get:

Expected outcome
In Matplotlib v2.2.3, I get:

Matplotlib version
- Operating system: Mac OS 10.12.6
- Matplotlib version: 3.0.0
- Matplotlib backend: Qt5Agg
- Python version: 3.6.5
I got the same result when using conda to install v3.0.0 or pip to install the latest development version.
Bug report
Bug summary
After upgrading to Matplotlib v3.0.0, the tick marks on the colorbar are no longer placed correctly when using a matplotlib.colors.LogNorm normalization.
Code for reproduction
The code is embedded in a class defined within the NeXpy application, but uses standard Matplotlib function calls. Here are the relevant extracted lines:
Actual outcome
In Matplotlib v3.0.0, I get:

Expected outcome
In Matplotlib v2.2.3, I get:

Matplotlib version
I got the same result when using conda to install v3.0.0 or pip to install the latest development version.