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 <[email protected]
> <mailto:[email protected]>> 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
> [email protected] <mailto:[email protected]>
>
>
> ------------------------------------------------------------------------------
> 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
> [email protected]
> <mailto:[email protected]>
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
--
Steven Boada
Doctoral Student
Dept of Physics and Astronomy
Texas A&M University
[email protected]
------------------------------------------------------------------------------
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
[email protected]
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
