Fix Logscale color normalization in contourf

xarray/plot/dataarray_plot.py

@@ -1581,11 +1581,14 @@ def newplotfunc(
         )
 
         if "contour" in plotfunc.__name__:
+            from matplotlib import ticker
+
             # extend is a keyword argument only for contour and contourf, but
             # passing it to the colorbar is sufficient for imshow and
             # pcolormesh
             kwargs["extend"] = cmap_params["extend"]
-            kwargs["levels"] = cmap_params["levels"]
+            if not (isinstance(kwargs.get("locator"), ticker.LogLocator)):
+                kwargs["levels"] = cmap_params["levels"]
             # if colors == a single color, matplotlib draws dashed negative
             # contours. we lose this feature if we pass cmap and not colors
             if isinstance(colors, str):

xarray/tests/test_plot.py

@@ -1771,6 +1771,16 @@ def test_levels(self) -> None:
         artist = self.plotmethod(levels=3)
         assert artist.extend == "neither"
 
+    def test_cbar_logscale(self) -> None:
+        _darray = self.darray.copy()
+        _darray.values = np.abs(_darray.values)
+        _darray.plot.contourf(
+            norm=mpl.colors.LogNorm(vmin=0.1, vmax=10), locator=mpl.ticker.LogLocator()
+        )
+        ax = plt.gca()
+        cbar = ax.figure.colorbar(ax.collections[0], ax=ax)
+        np.testing.assert_array_equal(cbar.get_ticks(), np.logspace(-3, 1, num=5))
+
 
 @pytest.mark.slow
 class TestContour(Common2dMixin, PlotTestCase):