Denis-B wrote: > Robert C, Robert K, folks, > > messing with the nice delaunay/testfuncs.py to time > linear_interpolate_grid nn_interpolate_grid and nn_interpolate_unstructured > in _delaunay, I see linear ~ 100 times faster than the nn_ s: > > # from: trigrid Ntri=1000 Ngrid=100 run: 21 Jul 2009 17:33 mac 10.4.11 ppc > > time: 0.027 sec trigrid: build Triangulation 1000 > time: 0.0059 sec trigrid 100 "linear" corners: 0 1 2 1 > time: 0.5 sec trigrid 100 "nn_grid" corners: 0 1 2 1 > time: 0.49 sec trigrid 100 "nn_unstruct" corners: 0 1 2 1 > > Correct me: if all 3 methods do gridpoint-to-triangle in the same way, > then the huge diff is in find-neighboring-triangles (6 on average ?), not in > gridpoint-to-triangle ? > > This is with the _delaunay.so that comes with the mac 98.5.3 egg, > however that was compiled (-O3 ?) > > > What to do ? > > 1) does it matter, how many people care ? (all who believe in telekinesis, > raise my right hand) > > 2) natgrid ? don't see it in matplotlib.sf.net > > 3) stick with fast linear, smooth the triangle planes a la 3t^2 - 2t^3 or > fancier smoothing > > In any case, add griddata( ... method = "linear" / "nn" ... ) so users have > a choice. >
Denis: I have added an 'interp' keyword to griddata (svn revision 7287) so you can choose the faster linear interpolation with interp='linear'. However, for linear interpolation the output grid is assumed to be regular with constant dx and dy (and this is *not* checked for by griddata). The natgrid toolkit is on the sf site under 'Files', then 'matplotlib-toolkits'. It is in fact slower than the Delaunay package included in matplotlib, but a little bit more robust for pathological cases. -Jeff > Can a real user or two tell us about the flow, > with some rough numbers for Ntri Ngrid Npix -- > Ntri = nr original sample points, say 1000 > Ngrid 100 x 100 > Npix 800 x 600 ? > (Ntri -> Ngrid slowly and accurately, > then Ngrid -> Npix w fast inaccurate image interpolation ? hmm.) > > cheers > -- denis > > ------------------------------------------------------------------------------ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
