jiawen wang

@olivermccallion Here is a workaround, spatialdata doesn't support vmin and vmax generally: https://github.com/scverse/spatialdata-plot/issues/304

Unfortunately not. https://github.com/scverse/spatialdata-plot/issues/304#issuecomment-2227415168

@timtreis @olivermccallion I have tested the latest spatialdata-plot (v0.2.6) `vmin` and `vmax` works only in `pl.render_images`, but still don't work in `pl.render_shapes` .  As you can see, vmin and...

I think you should keep `vmin` and `vmax`. We can use these two parameters to clip/truncate the colorbar to make the figure more saturated. It's different from `norm`. We use...

> I'm surprised it even works in render_images :D Thought I had removed it. Could you try creating a matplotlib Normalise object with your desired vmin/vmax values and pass that...

@timtreis Yes, this is what I mean ! I am not familiar with matplotlib `norm` and don't know the `clip` parameter. I tested my data and found this works in...

@melonora Hi, I am trying to test it. Is this fixes released in current spatialplot version ?

@LucaMarconato I have tried the latest spatialdata_plot, now the default method is `datashader`. Here is the figure generated by `datashader`:  And this is generated by `matplotlib`:  And this...

Then I changed the region from "cell_circles" to "cell_boundaries", the figure looks clearly. Is it better to plot "cell_boundaries" instead of "cell_circles" ? ``` sdata["table"].obs["region"] = "cell_boundaries" sdata.set_table_annotates_spatialelement("table", region="cell_boundaries") sdata.pl.render_shapes("cell_boundaries",...

Another little issue: Now there are no x_axis and y_axis labels on the figures.