8000 [ENH]: Speed up Axes.bar through the use of PatchCollection · Issue #22976 · matplotlib/matplotlib · GitHub
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[ENH]: Speed up Axes.bar through the use of PatchCollection #22976

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timhoffm opened this issue May 4, 2022 · 2 comments
Open

[ENH]: Speed up Axes.bar through the use of PatchCollection #22976

timhoffm opened this issue May 4, 2022 · 2 comments
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@timhoffm
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timhoffm commented May 4, 2022

Problem

Bar charts are relatively slow because each bar is a separate Rectangle. From a quick check, this scales really linearly with the number of bars N:

N = [30, 100, 300, 1000, 3000, 10000]
t = [29, 103, 290, 951, 2860, 9790]  # in ms for `plt.bar(x, y)`

While one should not have too many bars in a plot, possibly up to 1000 could be reasonable. The time delay is still okish herem but if e.g. I have multiple subplots, it can become noticable.

Proposed solution

One possible solution is to replace the single Rectangles by a PatchCollection (inspired by #20092).
For backward-compatibility, we'd have to intoduces this gradually similar to what has been done in hist(..., histtype=...): Add a parameter to make the created Artist configurable. The default stays on isolated bars, using a collection is opt-in. The default can be switched later.
@timhoffm timhoffm mentioned this issue May 4, 2022
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@timhoffm timhoffm changed the title [ENH]: Speed up Axes.bar through the use of Patch collection [ENH]: Speed up Axes.bar through the use of PatchCollection May 4, 2022
@anntzer anntzer mentioned this issue Jul 15, 2023
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@QuLogic
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QuLogic commented Dec 8, 2023 •
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I had a look at #20092 and copied it back to main. After fixing a larger issue, I think the main reason for the test failures is that the collection doesn't seem to do path snapping like the individual rectangles do, even though it seems like it should.

@timhoffm
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MHO it’s viable to explicitly set snapping in the tests to be able to reuse existing reference images.

We could also activate snapping when creating the collection in bar.

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