Jerzy,
Actually, my response is still completely valid. You can only plot surfaces
that can be represented parametrically in two dimensions. Find me a single
plotting library that can do differently without having to get to this
final step. For matplotlib, it is up to the user to get the data to that
point. As you stated, he is seeking polygonization of an *implicit*
surface. Matplotlib has no means of understanding this. And this is
unlikely to happen anytime soon given the inherent 2D limitations of
Matplotlib.
I am sorry if the answer is unsatisfactory to you, but it is the correct
one to give.
Ben Root
On Sat, Nov 1, 2014 at 2:49 PM, Jerzy Karczmarczuk <
jerzy.karczmarc...@unicaen.fr> wrote:
>
> Le 01/11/2014 19:21, Benjamin Root answers the query of Peter Kerpedjiev,
> who wants to plot (with Matplotlib) the surface of an implicit surface (at
> least it was his presented example).
>
> Your comment "of course, plotting a sphere can be done in spherical
> coordinates" is actually the right thought process. Spherical coordinates
> is how you parametrize your spherical surface. Pick a coordinate system
> that is relevant to your problem at hand and use it.
>
>
> Sorry Ben, but this is not an answer. P.K. clearly states that his case is
> more complicated, and no parametrization is likely. Anyway, the spherical
> exercise as it is presented uses the 3D constraint, it is not parametric.
>
> The general solution is the *polygonization of the implicit surface*,
> which is a well established technology (although non-trivial). For example
> the *marching cubes / marching simplices* algorithms and their variants.
> These are techniques for the polygonization of a mesh.
>
> If P.K. has an analytic formula for his distributions, and is able to
> compute gradients, etc., there are some more efficient techniques, but in
> general it is the case for solving the equation F(x,y,z)=0 for {x,y,z} ;
> here Matplotlib doesn't offer (yet) any tools if I am not mistaken.
>
> Jerzy Karczmarczuk
> Caen, France.
>
>
>
>
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