Menu
▾
▴
Re: [Matplotlib-users] Artifacts when saving as PDF
|
From: Steven B. <bo...@ph...> - 2015-04-07 16:18:34
|
Hi Tom,
Thanks for your help.
interpolation='nearest' doesn't produce any problems. I'm currently
using TkAgg, and I checked with a buddy of mine, using MacOSX backend.
Neither of us see any problems using interpolation='nearest'. He is
using an older version of MPL which doesn't let him use
interpolation='none'.
I will ask around to see if anyone can run a few more test cases.
Steven
On 4/7/15 10:39 AM, Thomas Caswell wrote:
> This probably should be made into an issue on github as this is
> clearly a bug.
>
> On further consideration, the fact that in my example the bad pixels
> show up only on the edge and are not symmetric makes me think that my
> original suggestion is wrong. Does `interpoltation='nearest'` work
> any better?
>
> I also am not sure that the rasterzation is happening so this may be
> an issue on the renderer end.
>
> This needs more investigation that I have time for today.
>
> Tom
>
> On Tue, Apr 7, 2015 at 11:02 AM Steven Boada <bo...@ph...
> <mailto:bo...@ph...>> wrote:
>
> 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...@ph... <mailto:bo...@ph...>
> > <mailto:bo...@ph... <mailto:bo...@ph...>>>
> 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...@ph... <mailto:bo...@ph...>
> <mailto:bo...@ph... <mailto:bo...@ph...>>
> >
> >
> ------------------------------------------------------------------------------
> > 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
> > Mat...@li...
> <mailto:Mat...@li...>
> > <mailto:Mat...@li...
> <mailto:Mat...@li...>>
> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >
>
> --
>
> Steven Boada
>
> Doctoral Student
> Dept of Physics and Astronomy
> Texas A&M University
> bo...@ph... <mailto:bo...@ph...>
>
>
> ------------------------------------------------------------------------------
> 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
> Mat...@li...
> <mailto:Mat...@li...>
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
--
Steven Boada
Doctoral Student
Dept of Physics and Astronomy
Texas A&M University
bo...@ph...
|
