A useful feature in heatmap visualizations is to rasterize the heatmap itself but not the surrounding text of the plot. This is useful when saving to PDF for instance, as we want to rasterize the heatmap so that the PDF does not have to render hundreds or thousands of cells. Instead, it can just render a single image for the heatmap, while the surrounding text is maintained in vector format.
Previously, we had to rasterize the entire plot, so even the text was converted to pixels when it can easily be represented in vector format.
The API change is to add a rasterized argument to grid_archive_heatmap, cvt_archive_heatmap, and sliding_boundareis_archive_heatmap. This is similar to how Matplotlib methods like pcolormesh handle rasterization.
TODO
[x] Add rasterized arg in grid_archive_heatmap — rasterized is passed into pcolormesh, and pcm_kwargs is not allowed to contain rasterized since that would result in a duplicate kwarg to pcolormesh
[x] Add rasterized arg in cvt_archive_heatmap — rasterized is passed into PolyCollection
[x] Add rasterized arg in sliding_boundaries_archive_heatmap
Description
A useful feature in heatmap visualizations is to rasterize the heatmap itself but not the surrounding text of the plot. This is useful when saving to PDF for instance, as we want to rasterize the heatmap so that the PDF does not have to render hundreds or thousands of cells. Instead, it can just render a single image for the heatmap, while the surrounding text is maintained in vector format.
Previously, we had to rasterize the entire plot, so even the text was converted to pixels when it can easily be represented in vector format.
The API change is to add a
rasterizedargument togrid_archive_heatmap,cvt_archive_heatmap, andsliding_boundareis_archive_heatmap. This is similar to how Matplotlib methods like pcolormesh handle rasterization.TODO
Questions
Status
yapfpytestpylintHISTORY.md