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From: Steven B. <bo...@ph...> - 2015-04-06 21:40:38
|
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... |
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From: Thomas C. <tca...@gm...> - 2015-04-07 01:47:35
|
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...> 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 Uni...@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...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
|
|
From: Steven B. <bo...@ph...> - 2015-04-07 15:01:35
|
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...>> 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...>
>
> ------------------------------------------------------------------------------
> 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...
|
|
From: Thomas C. <tca...@gm...> - 2015-04-07 15:39:27
|
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...> 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...>> 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...>
> >
> > ------------------------------------------------------------
> ------------------
> > 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...
>
>
> ------------------------------------------------------------
> ------------------
> 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...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
|
|
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...
|
|
From: Jouni K S. <jk...@ik...> - 2015-04-13 05:37:21
|
Thanks for the report, I turned it into a github issue: https://github.com/matplotlib/matplotlib/issues/4331 |
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