This builds off of#16688, to rebase off of main, extend as applicable to all the 3D object types, and allow for compatibility with the new 3D axlim clipping. With the test code below, I am seeing substantial speedups in draw times for some types of plots.

Closes#16659

importtimeimportnumpyasnpimportmatplotlib.pyplotaspltfig,ax=plt.subplots(subplot_kw={"projection":"3d"})x=y=np.linspace(-1,1,100)X,Y=np.meshgrid(x,y)Z=X**2+Y**2print("Timing...")start_time=time.perf_counter()#ax.plot_surface(X, Y, Z, rstride=1, cstride=1, axlim_clip=False)#ax.scatter(x, y, np.ones_like(x), axlim_clip=False)ax.plot_wireframe(X,Y,Z,axlim_clip=False)#ax.bar3d(X.ravel(), Y.ravel(), 0, 0.01, 0.01, 1, axlim_clip=False)ax.set_xlim(0,1)fig.canvas.draw()end_time=time.perf_counter()plt.close()print(f"Time taken:{end_time-start_time:.4f} seconds")

function	object	draw time main	this PR	improvement
plot_surface (400x400)	Poly3DCollection	16.55 sec	1.86 sec	8.9x
scatter (100000)	Path3DCollection	3.65 sec	3.22 sec	1.1x
plot wireframe (8000x8000)	Line3DCollection	2.72 sec	1.39 sec	2.0x
bard3d (100x100)	Patch3DCollection	7.17 sec	2.02 sec	3.5x

PR checklist

[n/a] "closes #0000" is in the body of the PR description tolink the related issue
new and changed code istested
[n/a]Plotting related features are demonstrated in anexample
[n/a]New Features andAPI Changes are noted with adirective and release note
Documentation complies withgeneral anddocstring guidelines

github-actionsbot added the topic: mplot3d label

Jan 3, 2025

scottshambaugh added the Performance label

Jan 3, 2025

scottshambaugh added this to thev3.11.0 milestone

Jan 3, 2025

scottshambaugh force-pushed themasked_array_performance branch from4527293 to2f2e65cCompare

January 3, 2025 05:07

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scottshambaugh commentedJan 5, 2025•
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Thoughts on if the 3D speedups warrant a what's new?

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timhoffm commentedJan 6, 2025

Thoughts on if the 3D speedups warrant a what's new?

Since these are substantial, I‘d say yes.

scottshambaugh changed the title~~3D masked array performance improvements~~3D plotting performance improvements

Jan 6, 2025

github-actionsbot added topic: path handling topic: transforms and scales labels

Jan 6, 2025

scottshambaugh force-pushed themasked_array_performance branch fromd51b947 to1516928Compare

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greglucas reviewed

Jan 7, 2025

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lib/mpl_toolkits/mplot3d/art3d.py OutdatedShow resolvedHide resolved

lib/mpl_toolkits/mplot3d/art3d.py

		# Some faces might contain masked vertices, so we want to ignore any
		# errors that those might cause

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greglucasJan 7, 2025

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Should these errors be handled within the_proj_transform_vectors case directly closer to where these errors would actually arise? I know there has been some work in numpy to not raise invalid/division warnings on masked elements, so is this still an issue now?

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scottshambaughJan 7, 2025•
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I removed the error ignore line and did not see any issues. The tests cover partially masked Poly3DCollections, so that case is exercised, and it looks like the improved masked handling covers any previous errors here.

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scottshambaughJan 8, 2025

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Looks like the error does crop up in the AppVeyor build, so adding the original error suppression back in. I don't want to put it in_proj_transform_vectors since it might not always be the case that we know that we have masked out the problematic vertices outside of that function.

scottshambaugh force-pushed themasked_array_performance branch from927e500 to645dfc8Compare

January 7, 2025 18:53

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Jan 7, 2025

Store vertices as (masked) arrays in Poly3DCollection#16688

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I think this is a really great performance improvement and shows how much of an impact numpy vectorization can have. Just a few minor nits that you can take or leave.