Bug summary

I'm trying to produce a density plot of logarithmically spaced data. UsingNonUniformImage used to work before matplotlib version3.10, where I know exhibit a weirdly scaled axis.

Code for reproduction

importnumpyasnpimportmatplotlib.pyplotaspltfrommatplotlib.imageimportNonUniformImagex=np.linspace(0,1,2)y=np.geomspace(1e1,1e5,3)z=np.random.uniform(size=(len(x),len(y)))_, (ax1,ax2)=plt.subplots(ncols=2)# create the non-uniform imageim=NonUniformImage(ax1,extent=[0,1,1e0,1e6],origin="lower")im.set_data(x,y,z.T)ax1.add_image(im)ax1.set_yscale("log")ax1.set_ylim(1e0,1e6)# omitting this leads to very weird behaviorax1.set_title("NonUniformImage")# use pcolormesh to get reference imageax2.pcolormesh([0,0.5,1], [1e0,1e2,1e4,1e6],z.T)ax2.set_yscale("log")ax2.set_title("pcolormesh")

Actual outcome

The code above produces the following image

Expected outcome

I expect the left panel to look like the right panel, which was produced usingpcolormesh. The reason I don't want to usepcolormesh for these plots is that the quality in PDFs is often much worse (with lines showing up between patches) and the file size can easily be 10 times larger.

Additional information

I recently askeda related question on Stackoverflow, which has some additional details.

Operating system

OS/X

Matplotlib Version

3.10.0

Matplotlib Backend

module://matplotlib_inline.backend_inline

Python version

3.12.8

Jupyter version

7.3.1

Installation

conda