[Matplotlib-users] How can I speed up a tricontourf call ?

[Ian Thomas]

Hello Francis,

Normally to help with requests of this nature we would need to see your
code to identify if you are doing anything wrong, or at least sub-optimally.

Without seeing your code, we will at least need some more information.
We'll start with:
1) How big is your triangulation, i.e. how many points and how many
triangles?
2) How much is "a huge amount of RAM"?
3) How long is a "very long time to produce"?
4) How much RAM do you have available?
5) Is the geometric triangulation static, i.e. constant in time?
6) Each time you create a matplotlib.tri.Triangulation object, do you
specify the triangles array or not (the latter meaning that a Delaunay
triangulation is calculated for you)?

Ian


On 31 August 2016 at 18:08, Francis Chabouis <fchabouis at gmail.com> wrote:

> Hello,
> I'm working on this travel times project :
>
> https://ubikiwi.com/ouhabiter?locations=[[48.85522811385678,
> 2.332191467285156]]
>
> and the contouring is done thanks to MPL tricontourf function (thanks!).
> As you can see it works pretty well and is fast enough.
>
> As I'm trying to expand the geographical coverage of the application (the
> whole country) I'm having performance issues with the contouring:
>
> - if I load the triangulation in memory at startup, it takes a huge amount
> of RAM. But the real problem is that even a very small contour in this huge
> triangulation takes a very long time to produce. For example with a small
> triangulation, a 20 minutes walk isoline is instant. The same contour on a
> country-wide triangulation takes 6sec. (It is not that long, but for a web
> application it is).
>
> - If on the other hand I compute a triangulation for each request, the
> contouring is fast but the triangulation creation is slow.
>
> Would someone have an optimisation idea ?
> Is it somehow possible to speed up the triangulation ?
> Any possible alternative ?
>
> Thanks a lot,
> Francis
>
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