On Mon, Apr 11, 2011 at 4:16 AM, Konrad Bartkowski <
[email protected]> wrote:
> Ok, forwarding it to the matplotlib-devel list.
>
>
> Best wishes,
>
> Konrad (on behalf of our workgroup)
>
>
> -------- Original Message -------- Subject: Source of inaccuracies in the
> matplotlib library Date: Fri, 8 Apr 2011 18:12:47 +0200 From: Bartkowski,
> Konrad <[email protected]> <[email protected]> To:
> [email protected] <[email protected]> <[email protected]>, [email protected]
> <[email protected]> <[email protected]>, [email protected]
> <[email protected]> <[email protected]>, [email protected]
> <[email protected]> <[email protected]>,
> [email protected] <[email protected]> <[email protected]> CC: Bartkowski,
> Konrad <[email protected]> <[email protected]>,
> [email protected] <[email protected]> <[email protected]>, Matthias Bolten
> <[email protected]> <[email protected]>,
> Grotendorst, Johannes
> <[email protected]><[email protected]>,
> Steffen, Bernhard <[email protected]> <[email protected]>
>
> Dear Matplotlib developers,
>
> I am writing about the matplotlib library with the mpl_toolkits. First
> of all let me emphasize how great software it is. Recently, in one of
> our projects we were rendering big surfaces and encountered the
> following problem:
> http://www.mail-archive.com/[email protected]/msg06869.html
>
> It's not a bug (which all in all is a natural and unavoidable ingredient
> of the software, and especially in such a big and complex system like
> matplotlib would be fully natural), since the software does exactly the
> projection mathematics that it is expected to do, but a source of the
> inaccuracies, which is especially visible in the critical examples. For
> the profit of the Python community we are sending You a proposition of a
> modification of the surface plotting rendering system, in case You find
> it interesting enough to include in the consecutive version of the
> library. In the source code from the attachment we redesigned a little
> bit the computation process – since the computations are especially
> sensible to numerical errors, that are for example amplified while
> norming or processing the quaterions in the various stages (for example
> division over coordinate in the perspective projection). Therefore the
> computational focus can be shifted from the Polygon collection to the
> polygons itself. In the example from the above forum or the slightly
> modified one, one can observe a big difference in the numerical
> precision while the speed of the computations does not decrease (at
> least visibly). While instead of the surfaces from the forum, the
> following surfaces are rendered:
>
> u = np.linspace(0, 2 * np.pi, 100)
> v = np.linspace(0, np.pi, 100)
>
> x = 10 * np.outer(np.cos(u), np.sin(v))
> y = 10 * np.outer(np.sin(u), np.sin(v))
> z = 10 * np.outer(np.ones(np.size(u)), np.cos(v))
>
> ax.plot_surface(x, y, z, rstride=8, cstride=8, color='y', alpha=0.5)
> shiftX=28
> shiftY=28
> X,Y=np.meshgrid(range(-20+shiftX,20+shiftX),range(-20+shiftY,20+shiftY))
> Z=np.ones((X.shape[0], Y.shape[1]))
> ax.plot_surface(X, Y, Z, color='r', rstride=10, cstride=10, alpha=1.0)
>
> the issue is visible for example at the azimuth=40 , elevation=70 – with
> those parameters the mentioned case is visible on the red surface, while
> with elevation=68 not. Moreover, now also the stride is big (in the new
> approach the influence of increasing stride on the numerical precision
> grows).
> So again let me use this opportunity to thank You for empowering the
> Python community worldwide in a great, powerful scientific visualization
> tool.
>
> Best wishes,
> Konrad Bartkowski
>
>
Konrad,
Thank you for this contribution. It seems that I am currently the de facto
maintainer of the mplot3d code, but I have been focused on my PhD for the
past month. I will take a look at the code in more detail over the weekend.
Thanks!
Ben Root
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