Thomas, Thanks for the smaller example. I would have come up with one, but I wasn't sure what was causing it to begin with.
Is there anything to be done to prevent this? Just use another backend? Steven On 4/6/15 8:47 PM, Thomas Caswell wrote: > This is probaly due to issues with not all of the vector backends > supporting alpha gracefully. > > This can be reproduced more simply by > > x, y = np.ogrid[-5:5:.1, -5:5:.1] > dd = np.exp(-(x**2 + y**2)) > dd[dd < .1] = np.nan > > fig, ax = plt.subplots() > ax.imshow(dd, interpolation='none', cmap='gray_r') > plt.savefig('test.pdf') > > @steven In the future it is best to report bugs with minimal > copy-paste able examples. > > On Mon, Apr 6, 2015 at 5:41 PM Steven Boada <bo...@physics.tamu.edu > <mailto:bo...@physics.tamu.edu>> wrote: > > Getting some strange artifacts when I save a figure as a PDF in > matplotlib. Here are some screen shots. PDF > <http://imgur.com/oQDXkWn> and PNG <http://imgur.com/bCw3Fn4>. Any > idea why that is happening? > > Here is (most of) the source code that makes the plot. I stripped > out the data generation, because it is long and involved, and > doesn't really matter. Basically what the script is supposed to do > is make a scatter plot where the density is below some threshold, > and a 2d histogram when it is above that threshold. The code seems > to work fine, but when I save the figure (using savefig in > Ipython) it shows up funny. > > Thanks. > > import pylab as pyl > > bins = [50,50] > thresh = 3 > > xdat = #generate or load some data > ydat = #generate or load some data > > hh, locx, locy = pyl.histogram2d(xdat, ydat, > range=[[-1,4],[-26,-10]], bins=bins) > posx = pyl.digitize(xdat, locx) > posy = pyl.digitize(ydat, locy) > > # finds the bins which contain points. posx = 0 for points > outside "range" > ind = (posx > 0) & (posx <= bins[0]) & (posy > 0) & (posy <= > bins[1]) > # values of histogram with points in the bins. > hhsub = hh[posx[ind] - 1, posy[ind] - 1] > > xdat1 = xdat[ind][hhsub < thresh] # low density points > ydat1 = ydat[ind][hhsub < thresh] > hh[hh < thresh] = pyl.nan # fill the areas with low density by > NaNs > > pyl.scatter(xdat1, ydat1, s=20, c='0.8') > pyl.imshow(pyl.log10(hh.T), cmap='gray_r', > extent=pyl.array([[-1,4],[-26,-10]]).flatten(), > interpolation='none') > > pyl.show() > > -- > > Steven Boada > > Doctoral Student > Dept of Physics and Astronomy > Texas A&M University > bo...@physics.tamu.edu <mailto:bo...@physics.tamu.edu> > > > ------------------------------------------------------------------------------ > BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT > Develop your own process in accordance with the BPMN 2 standard > Learn Process modeling best practices with Bonita BPM through live > exercises > http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- > event?utm_ > > source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF_______________________________________________ > Matplotlib-users mailing list > Matplotlib-users@lists.sourceforge.net > <mailto:Matplotlib-users@lists.sourceforge.net> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > -- Steven Boada Doctoral Student Dept of Physics and Astronomy Texas A&M University bo...@physics.tamu.edu ------------------------------------------------------------------------------ BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard Learn Process modeling best practices with Bonita BPM through live exercises http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_ source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users