> Jouni K. Sepp?nen wrote: > >> Jordan Dawe <jd...@eos.ubc.ca> writes: >> >> >>> Contourf plots that I output in vector format files have little >>> triangular glitches at the contour boundaries if the contoured array >>> is larger than about 200x200. The same files in png format are >>> perfect, even at very high dpi values. >>> >> The current svn trunk doesn't have the really jarring little triangles >> (at least in the pdf output), but there are still several very obtuse >> white triangles between the regions. Rasterization at a high dpi makes >> the output somewhat better at the cost of larger output files: >> >> c=contourf(X, Y, Z, 10) >> axis((-3, 3, -3, 3)) >> savefig('unrasterized.pdf') >> for d in c.collections: >> d.set_rasterized(True) >> savefig('rasterized.pdf',dpi=200) >> > > > At least in the trunk--and maybe in 0.99.0--the problem is caused by > path simplification. In the trunk, for the eps file, it goes away > completely if I use a matplotlibrc with > > path.simplify : False > > In the trunk, what seems to be happening is that when a contour boundary > is almost straight, but has an inflection point, the curves for the > adjacent patch boundaries are simplified slightly differently. This is > not surprising; if nothing else, the path will be traveled in a > different direction when it is an outer boundary than when it is an > inner boundary (for a set of concentric boundaries). > > Jordan, try using a local matplotlibrc with the above. Unless you are > already customizing via a local matplotlibrc, that line is all you need. > > One reason the trunk behavior differs from 0.99.0 is that contour patch > boundaries are now being turned into compound boundaries instead of > using a branch cut to connect the outside path to the inside path. I > suspect simplification is causing the artifacts in both cases, though. > > Eric > > >
Perfect, that fixed it completely. Thanks. Jordan ------------------------------------------------------------------------------ This SF.Net email is sponsored by the Verizon Developer Community Take advantage of Verizon's best-in-class app development support A streamlined, 14 day to market process makes app distribution fast and easy Join now and get one step closer to millions of Verizon customers http://p.sf.net/sfu/verizon-dev2dev _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users