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It seems this stopped working after commit r8906 (svn) or 32f64b01c98d1e3b51be57ab49c899cf91017817: r8906 | efiring | 2011年01月11日 21:53:37 -1000 (2011年1月11日) | 2 lines Fix eps distillation bbox bug; closes 3032385 I have opened a ticket on GitHub: https://github.com/matplotlib/matplotlib/issues/85 Cheers, Tom On Friday, April 15, 2011 at 7:22 PM, Thomas Robitaille wrote: Hello, > > It seems that at some point in the last few months a change was made that means that the following code no longer works properly: > > --- > > import matplotlib as mpl > mpl.use('Agg') > import matplotlib.pyplot as plt > import numpy as np > > mpl.rc('text', usetex=True) > > fig = plt.figure() > ax = fig.add_axes([0.1,0.1,0.3,0.3]) > fig.savefig('test.eps', bbox_inches='tight') > > --- > > This produces a file that does not have the right bounding box (it's as if I wasn't specifying bbox_inches=True). Can anyone else reproduce this issue? If so, I'll open a ticket. > > Thanks, > Tom >
Hello, It seems that at some point in the last few months a change was made that means that the following code no longer works properly: --- import matplotlib as mpl mpl.use('Agg') import matplotlib.pyplot as plt import numpy as np mpl.rc('text', usetex=True) fig = plt.figure() ax = fig.add_axes([0.1,0.1,0.3,0.3]) fig.savefig('test.eps', bbox_inches='tight') --- This produces a file that does not have the right bounding box (it's as if I wasn't specifying bbox_inches=True). Can anyone else reproduce this issue? If so, I'll open a ticket. Thanks, Tom
Hello, I am having a problem with the colorbar when plotting a constant field. The small script below will generate a plot that is a solid blue image with a solid blue colorbar. However the label on the colorbar is garbage. There is no way to read the label to determine what value the image represents. Has anyone else had a similar problem? How do I fix it? I am running matplotlib version 1.0.1 installed from macports -- py26-matplotlib @1.0.1_3+tkinter Thanks. --- import matplotlib.pyplot as plt import numpy as np C = np.matrix('1 1 1; 1 1 1; 1 1 1') plt.imshow(C) plt.colorbar() plt.show()
Hi, The following code causes matplotlib to hang: --- import numpy as np import matplotlib as mpl mpl.use('Agg') import matplotlib.pyplot as plt from matplotlib.patches import Circle fig = plt.figure() ax = fig.add_subplot(1,1,1) ax.add_patch(Circle((1.e17, 1.e17), radius=1.e15)) fig.savefig('test.png') --- Am I doing something wrong? Thanks for any help, Cheers, Tom
Hi JJ, I just want to confirm that changing pswrite to ps2write fixes the issue for me. Since no-one else replied to this thread, is this something we should ask the ghostscript mailing list about? Cheers, Tom On 13 March 2011 10:01, Jae-Joon Lee <lee...@gm...> wrote: > Okay, I just confirmed that using a gs distiller greatly increases the > file size with gs 9.0. > I have no idea what's going on and I hope that someone more > knowledgeable than me steps in. > Meanwhile, using the "ps2write" device with gs seems to solve the > issue (but I'm not sure of its consequences). > So, can you test if the workaround works? > > In lib/matplotlib/backends/backend_ps.py, search for the following > line in the "gs_distill" function, > > command = '%s -dBATCH -dNOPAUSE -r%d -sDEVICE=pswrite %s -sOutputFile="%s" \ > > and replace "pswrite" with "ps2write". > > Regards, > > -JJ > > > > > On Sun, Mar 13, 2011 at 1:45 AM, Thomas Robitaille > <tho...@gm...> wrote: >> Hi Jae-Joon, >> >> Ok, that makes sense - I tried upgrading to 9.0.1 and it looks like there is still an issue: >> >> 6204 test_1.eps >> 34104 test_2.eps >> >> Cheers, >> Tom >> >> On Mar 12, 2011, at 11:38 AM, Jae-Joon Lee wrote: >> >>> Note that, even with usetex=False, you have a large ps file when >>> distiller is used . >>> When usetex=True, the distiller is always used (if distiller=None, >>> ghostscript is used). >>> Therefore, my guess is that the large file size is results of >>> distilling using the ghostscript. >>> I wonder if this is an issue of gs 9.0 version. >>> In my installation (gs 8.xx), the original ps file is about 6 M (both >>> usetex=True and False), and when they are distilled, their size is >>> reduced down to 4 M. >>> >>> I'll try to test gs 9.0 when I get a chance. >>> Meanwhile, can you try to upgrade to gs 9.01 and see if it changes anything? >>> >>> Regards, >>> >>> -JJ >>> >>> >>> >>> On Sat, Mar 12, 2011 at 2:46 AM, Thomas Robitaille >>> <tho...@gm...> wrote: >>>> Hi Jae-Joon, >>>> >>>> I tried inserting: >>>> >>>> mpl.rc('ps', usedistiller=None) >>>> >>>> after importing matplotlib, and I get: >>>> >>>> $ du -sk *.eps >>>> 6204 test_1.eps >>>> 34104 test_2.eps >>>> >>>> using 'ghostscript' I get: >>>> >>>> $ du -sk *.eps >>>> 34096 test_1.eps >>>> 34104 test_2.eps >>>> >>>> and using 'xpdf' raises an exception: >>>> >>>> File "/Users/tom/Library/Python/2.6/site-packages/matplotlib/backends/backend_ps.py", line 1091, in _print_figure >>>> xpdf_distill(tmpfile, isEPSF, ptype=papertype, bbox=bbox) >>>> File "/Users/tom/Library/Python/2.6/site-packages/matplotlib/backends/backend_ps.py", line 1421, in xpdf_distill >>>> image.\nHere is the full report generated by pdftops: \n\n' + fh.read()) >>>> RuntimeError: pdftops was not able to process your image. >>>> Here is the full report generated by pdftops: >>>> >>>> I don't have a matplotlibrc file, and I am using: >>>> >>>> Ghostscript: GPL Ghostscript 9.00 (2010年09月14日) >>>> LaTeX: Version 3.1415926-1.40.10 (TeX Live 2009) >>>> >>>> and I'm using the latest head from github for matplotlib. >>>> >>>> Cheers, >>>> Tom >>>> >>>> On Mar 8, 2011, at 7:31 AM, Jae-Joon Lee wrote: >>>> >>>>> With current master at git repo, I cannot reproduce this. >>>>> Both test_1.eps and test_2.eps are ~4M in size. >>>>> >>>>> Can you check if the file size varies significantly with rc parameters >>>>> ps.usedistiller? >>>>> I'm not sure how text setting can affect the images. >>>>> >>>>> Regards, >>>>> >>>>> -JJ >>>>> >>>>> >>>>> >>>>> On Tue, Mar 1, 2011 at 7:23 AM, Thomas Robitaille >>>>> <tho...@gm...> wrote: >>>>>> Hi, >>>>>> >>>>>> In the following example: >>>>>> >>>>>> --- >>>>>> >>>>>> import numpy as np >>>>>> >>>>>> import matplotlib as mpl >>>>>> mpl.use('Agg') >>>>>> import matplotlib.pyplot as plt >>>>>> >>>>>> fig = plt.figure() >>>>>> ax = fig.add_subplot(1, 1, 1) >>>>>> ax.imshow(np.random.random((1024, 1024)), interpolation='nearest') >>>>>> fig.savefig('test_1.eps') >>>>>> >>>>>> mpl.rc('text', usetex=True) >>>>>> >>>>>> fig = plt.figure() >>>>>> ax = fig.add_subplot(1, 1, 1) >>>>>> ax.imshow(np.random.random((1024, 1024)), interpolation='nearest') >>>>>> fig.savefig('test_2.eps') >>>>>> >>>>>> --- >>>>>> >>>>>> the file test_2.eps is almost 6 times larger than test_1.eps, and takes much longer to draw. It looks like in the first case, the image is rendered as a bitmap (the way it should be), whereas in the second case each pixel is drawn individually as a polygon. Is this a bug? >>>>>> >>>>>> I am using r8988 of matplotlib. >>>>>> >>>>>> Thanks for any help! >>>>>> >>>>>> Thomas >>>>>> ------------------------------------------------------------------------------ >>>>>> Free Software Download: Index, Search & Analyze Logs and other IT data in >>>>>> Real-Time with Splunk. Collect, index and harness all the fast moving IT data >>>>>> generated by your applications, servers and devices whether physical, virtual >>>>>> or in the cloud. Deliver compliance at lower cost and gain new business >>>>>> insights. http://p.sf.net/sfu/splunk-dev2dev >>>>>> _______________________________________________ >>>>>> Matplotlib-users mailing list >>>>>> Mat...@li... >>>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >>>>>> >>>> >>>> >> >> >
i like the module-based idea. its a bit overkill for the functionality needed, but the concise call makes it very convenient. also, installation and updating would be easy through pip/easy_install. should i start a google-code project? or does someone have a preferred way to start this? alex On Fri, 2011年04月15日 at 14:09 -0400, Tony Yu wrote: > > > On Fri, Apr 15, 2011 at 8:36 AM, Auré Gourrier > <aur...@ya...> wrote: > Good Idea ! > I'm also using mpl for other publications than ieee and it > sounds like a small mplrc data base with targeted journal > specifications would be worthwhile doing ! I would be ready to > contribute. > Cheers, > Auré > > > > > Is there any reason this needs to done with rc files? I prefer to put > document-specific configuration into modules. For example, you could > have a module that looks like: > > mplrc/ > __init__.py > aps_fullpage.py > aps_twocolumn.py > ieee.py > ... > > (`aps` could even be directory). And each module would set rc > parameters using function calls; for example, aps_twocolumn.py might > look like: > > import matplotlib.pyplot as plt > plt.rc('axes', labelsize=10) > plt.rc('text', fontsize=10) > plt.rc('legend', fontsize=10) > plt.rc('xtick', labelsize=8) > plt.rc('ytick', labelsize=8) > plt.rc('text', usetex=False) > plt.rc('figure', figsize=(3.4039, 2.1037)) > > (Alternatively, you could create a separate rc file and just have the > module load that rc file). The advantage of this module-based approach > is that you could simply import the module whenever you need it (e.g., > just add `import mplrc.aps_twocolumn` at the top of your script). If I > used an rc file instead, I'd have to copy the rc file to my working > directory each time, or somehow, manually load the rc file from a > path. > > Just a suggestion. > > -Tony >
On Fri, Apr 15, 2011 at 8:36 AM, Auré Gourrier <aur...@ya...>wrote: > Good Idea ! > I'm also using mpl for other publications than ieee and it sounds like a > small mplrc data base with targeted journal specifications would be > worthwhile doing ! I would be ready to contribute. > Cheers, > Auré > > Is there any reason this needs to done with rc files? I prefer to put document-specific configuration into modules. For example, you could have a module that looks like: mplrc/ __init__.py aps_fullpage.py aps_twocolumn.py ieee.py ... (`aps` could even be directory). And each module would set rc parameters using function calls; for example, aps_twocolumn.py might look like: import matplotlib.pyplot as plt plt.rc('axes', labelsize=10) plt.rc('text', fontsize=10) plt.rc('legend', fontsize=10) plt.rc('xtick', labelsize=8) plt.rc('ytick', labelsize=8) plt.rc('text', usetex=False) plt.rc('figure', figsize=(3.4039, 2.1037)) (Alternatively, you could create a separate rc file and just have the module load that rc file). The advantage of this module-based approach is that you could simply import the module whenever you need it (e.g., just add `import mplrc.aps_twocolumn` at the top of your script). If I used an rc file instead, I'd have to copy the rc file to my working directory each time, or somehow, manually load the rc file from a path. Just a suggestion. -Tony
It would be great to include this in matplotlib. However, I think it's not unreasonable to expect that these things would evolve faster than the release cycle of matplotlib. Perhaps a user is stuck on an older version of matplotlib because they want to use pre-built packages etc., or whatever reason. It might be better to provide this in a form that is easily updatable without updating the rest of matplotlib. Of course, small problems may arise if they use rcParams available not available in the user's version of matplotlib. (For the most part, I think the risk of that is quite small, as the rcParams that are most useful here have been stable for a long time.) We could use the existing "cbook.get_sample_data", which grabs files from the matplotlib git repo, for this. It would also be nice to generate a gallery of these settings and make it available online, linked from the documentation (again, maybe not *part* of the documentation, because it should update more frequently). Cheers, Mike On 04/15/2011 10:48 AM, alex arsenovic wrote: > this seems like the right way to do it. maybe it can be included in the > matplotlib package? > > alex > > > On Fri, 2011年04月15日 at 15:54 +0200, Adrian Hill wrote: > >> I have previously used some script from Mike DePalatis for making APS >> (PRL, PRB, etc.) suitable plots. Maybe it will be a useful starting >> point. >> >> http://mike.depalatis.net/docs/mpllatex.html >> >> >> """ >> mplparams.py >> >> M.V. DePalatis, 2010年09月01日 >> Licensed under the GNU GPL v3 >> >> matplotlib rc params and axes rects to generate figures of appropriate >> size for different types of publication. >> """ >> >> # documentclass 'article' with package 'fullpage' >> fullpage = {'params': {'axes.labelsize': 10, >> 'text.fontsize': 10, >> 'legend.fontsize': 10, >> 'xtick.labelsize': 8, >> 'ytick.labelsize': 8, >> 'text.usetex': False, >> 'font.family': 'serif', >> 'figure.figsize': (4.774, 2.950)}, >> 'axes': [0.150,0.175,0.95-0.15,0.95-0.25]} >> >> # two-column APS journal format >> aps = {'params': {'axes.labelsize': 10, >> 'text.fontsize': 10, >> 'legend.fontsize': 10, >> 'xtick.labelsize': 8, >> 'ytick.labelsize': 8, >> 'text.usetex': False, >> 'figure.figsize': (3.4039, 2.1037)}, >> 'axes': [0.125,0.2,0.95-0.125,0.95-0.2]} >> >> >> >> On 15/04/2011 14:36, Auré Gourrier wrote: >> >>> Good Idea ! >>> I'm also using mpl for other publications than ieee and it sounds >>> like a small mplrc data base with targeted journal specifications >>> would be worthwhile doing ! I would be ready to contribute. >>> Cheers, >>> Auré >>> >>> >>> >>> ____________________________________________________________________ >>> De : alex arsenovic<ai...@vi...> >>> À : mat...@li... >>> Envoyé le : Ven 15 avril 2011, 14h 06min 39s >>> Objet : [Matplotlib-users] matplotlibrc for [ieee] publications >>> >>> i was wondering if anyone had considered making a matplotlibrc which >>> generates plots suitable for ieee publications (specifically ieee >>> transactions)? >>> >>> or any other publications for that matter. like a set of matching >>> matplotlibrc's to journals (or some other way to achieve a similar >>> functionality) >>> >>> if not, i think it would be a valuable thing to make, because it >>> wouldnt >>> be very hard, and would save a lot of users time/effort. >>> specifically it >>> would specify the dimension/dpi/font type/sizes/etc. i have a >>> preliminary one for ieee we can use as a starting point, that can be >>> improved. >>> >>> >>> thanks >>> alex >>> >>> >>> >>> ------------------------------------------------------------------------------ >>> Benefiting from Server Virtualization: Beyond Initial Workload >>> Consolidation -- Increasing the use of server virtualization is a >>> top >>> priority.Virtualization can reduce costs, simplify management, and >>> improve >>> application availability and disaster protection. Learn more about >>> boosting >>> the value of server virtualization. >>> http://p.sf.net/sfu/vmware-sfdev2dev >>> _______________________________________________ >>> Matplotlib-users mailing list >>> Mat...@li... >>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >>> >>> >>> ------------------------------------------------------------------------------ >>> Benefiting from Server Virtualization: Beyond Initial Workload >>> Consolidation -- Increasing the use of server virtualization is a top >>> priority.Virtualization can reduce costs, simplify management, and improve >>> application availability and disaster protection. Learn more about boosting >>> the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev >>> >>> _______________________________________________ >>> Matplotlib-users mailing list >>> Mat...@li... >>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >>> >> ------------------------------------------------------------------------------ >> Benefiting from Server Virtualization: Beyond Initial Workload >> Consolidation -- Increasing the use of server virtualization is a top >> priority.Virtualization can reduce costs, simplify management, and improve >> application availability and disaster protection. Learn more about boosting >> the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev >> _______________________________________________ Matplotlib-users mailing list Mat...@li... https://lists.sourceforge.net/lists/listinfo/matplotlib-users >> > > > ------------------------------------------------------------------------------ > Benefiting from Server Virtualization: Beyond Initial Workload > Consolidation -- Increasing the use of server virtualization is a top > priority.Virtualization can reduce costs, simplify management, and improve > application availability and disaster protection. Learn more about boosting > the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > -- Michael Droettboom Science Software Branch Space Telescope Science Institute Baltimore, Maryland, USA
this seems like the right way to do it. maybe it can be included in the matplotlib package? alex On Fri, 2011年04月15日 at 15:54 +0200, Adrian Hill wrote: > I have previously used some script from Mike DePalatis for making APS > (PRL, PRB, etc.) suitable plots. Maybe it will be a useful starting > point. > > http://mike.depalatis.net/docs/mpllatex.html > > > """ > mplparams.py > > M.V. DePalatis, 2010年09月01日 > Licensed under the GNU GPL v3 > > matplotlib rc params and axes rects to generate figures of appropriate > size for different types of publication. > """ > > # documentclass 'article' with package 'fullpage' > fullpage = {'params': {'axes.labelsize': 10, > 'text.fontsize': 10, > 'legend.fontsize': 10, > 'xtick.labelsize': 8, > 'ytick.labelsize': 8, > 'text.usetex': False, > 'font.family': 'serif', > 'figure.figsize': (4.774, 2.950)}, > 'axes': [0.150,0.175,0.95-0.15,0.95-0.25]} > > # two-column APS journal format > aps = {'params': {'axes.labelsize': 10, > 'text.fontsize': 10, > 'legend.fontsize': 10, > 'xtick.labelsize': 8, > 'ytick.labelsize': 8, > 'text.usetex': False, > 'figure.figsize': (3.4039, 2.1037)}, > 'axes': [0.125,0.2,0.95-0.125,0.95-0.2]} > > > > On 15/04/2011 14:36, Auré Gourrier wrote: > > Good Idea ! > > I'm also using mpl for other publications than ieee and it sounds > > like a small mplrc data base with targeted journal specifications > > would be worthwhile doing ! I would be ready to contribute. > > Cheers, > > Auré > > > > > > > > ____________________________________________________________________ > > De : alex arsenovic <ai...@vi...> > > À : mat...@li... > > Envoyé le : Ven 15 avril 2011, 14h 06min 39s > > Objet : [Matplotlib-users] matplotlibrc for [ieee] publications > > > > i was wondering if anyone had considered making a matplotlibrc which > > generates plots suitable for ieee publications (specifically ieee > > transactions)? > > > > or any other publications for that matter. like a set of matching > > matplotlibrc's to journals (or some other way to achieve a similar > > functionality) > > > > if not, i think it would be a valuable thing to make, because it > > wouldnt > > be very hard, and would save a lot of users time/effort. > > specifically it > > would specify the dimension/dpi/font type/sizes/etc. i have a > > preliminary one for ieee we can use as a starting point, that can be > > improved. > > > > > > thanks > > alex > > > > > > > > ------------------------------------------------------------------------------ > > Benefiting from Server Virtualization: Beyond Initial Workload > > Consolidation -- Increasing the use of server virtualization is a > > top > > priority.Virtualization can reduce costs, simplify management, and > > improve > > application availability and disaster protection. Learn more about > > boosting > > the value of server virtualization. > > http://p.sf.net/sfu/vmware-sfdev2dev > > _______________________________________________ > > Matplotlib-users mailing list > > Mat...@li... > > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > > > > > ------------------------------------------------------------------------------ > > Benefiting from Server Virtualization: Beyond Initial Workload > > Consolidation -- Increasing the use of server virtualization is a top > > priority.Virtualization can reduce costs, simplify management, and improve > > application availability and disaster protection. Learn more about boosting > > the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev > > > > _______________________________________________ > > Matplotlib-users mailing list > > Mat...@li... > > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > ------------------------------------------------------------------------------ > Benefiting from Server Virtualization: Beyond Initial Workload > Consolidation -- Increasing the use of server virtualization is a top > priority.Virtualization can reduce costs, simplify management, and improve > application availability and disaster protection. Learn more about boosting > the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev > _______________________________________________ Matplotlib-users mailing list Mat...@li... https://lists.sourceforge.net/lists/listinfo/matplotlib-users
I have previously used some script from Mike DePalatis for making APS (PRL, PRB, etc.) suitable plots. Maybe it will be a useful starting point. http://mike.depalatis.net/docs/mpllatex.html """ mplparams.py M.V. DePalatis, 2010年09月01日 Licensed under the GNU GPL v3 matplotlib rc params and axes rects to generate figures of appropriate size for different types of publication. """ # documentclass 'article' with package 'fullpage' fullpage = {'params': {'axes.labelsize': 10, 'text.fontsize': 10, 'legend.fontsize': 10, 'xtick.labelsize': 8, 'ytick.labelsize': 8, 'text.usetex': False, 'font.family': 'serif', 'figure.figsize': (4.774, 2.950)}, 'axes': [0.150,0.175,0.95-0.15,0.95-0.25]} # two-column APS journal format aps = {'params': {'axes.labelsize': 10, 'text.fontsize': 10, 'legend.fontsize': 10, 'xtick.labelsize': 8, 'ytick.labelsize': 8, 'text.usetex': False, 'figure.figsize': (3.4039, 2.1037)}, 'axes': [0.125,0.2,0.95-0.125,0.95-0.2]} On 15/04/2011 14:36, Auré Gourrier wrote: > Good Idea ! > I'm also using mpl for other publications than ieee and it sounds like > a small mplrc data base with targeted journal specifications would be > worthwhile doing ! I would be ready to contribute. > Cheers, > Auré > > ------------------------------------------------------------------------ > *De :* alex arsenovic <ai...@vi...> > *À :* mat...@li... > *Envoyé le :* Ven 15 avril 2011, 14h 06min 39s > *Objet :* [Matplotlib-users] matplotlibrc for [ieee] publications > > i was wondering if anyone had considered making a matplotlibrc which > generates plots suitable for ieee publications (specifically ieee > transactions)? > > or any other publications for that matter. like a set of matching > matplotlibrc's to journals (or some other way to achieve a similar > functionality) > > if not, i think it would be a valuable thing to make, because it wouldnt > be very hard, and would save a lot of users time/effort. specifically it > would specify the dimension/dpi/font type/sizes/etc. i have a > preliminary one for ieee we can use as a starting point, that can be > improved. > > > thanks > alex > > > > ------------------------------------------------------------------------------ > Benefiting from Server Virtualization: Beyond Initial Workload > Consolidation -- Increasing the use of server virtualization is a top > priority.Virtualization can reduce costs, simplify management, and > improve > application availability and disaster protection. Learn more about > boosting > the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > <mailto:Mat...@li...> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > > ------------------------------------------------------------------------------ > Benefiting from Server Virtualization: Beyond Initial Workload > Consolidation -- Increasing the use of server virtualization is a top > priority.Virtualization can reduce costs, simplify management, and improve > application availability and disaster protection. Learn more about boosting > the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev > > > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Good Idea ! I'm also using mpl for other publications than ieee and it sounds like a small mplrc data base with targeted journal specifications would be worthwhile doing ! I would be ready to contribute. Cheers, Auré ________________________________ De : alex arsenovic <ai...@vi...> À : mat...@li... Envoyé le : Ven 15 avril 2011, 14h 06min 39s Objet : [Matplotlib-users] matplotlibrc for [ieee] publications i was wondering if anyone had considered making a matplotlibrc which generates plots suitable for ieee publications (specifically ieee transactions)? or any other publications for that matter. like a set of matching matplotlibrc's to journals (or some other way to achieve a similar functionality) if not, i think it would be a valuable thing to make, because it wouldnt be very hard, and would save a lot of users time/effort. specifically it would specify the dimension/dpi/font type/sizes/etc. i have a preliminary one for ieee we can use as a starting point, that can be improved. thanks alex ------------------------------------------------------------------------------ Benefiting from Server Virtualization: Beyond Initial Workload Consolidation -- Increasing the use of server virtualization is a top priority.Virtualization can reduce costs, simplify management, and improve application availability and disaster protection. Learn more about boosting the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev _______________________________________________ Matplotlib-users mailing list Mat...@li... https://lists.sourceforge.net/lists/listinfo/matplotlib-users
i was wondering if anyone had considered making a matplotlibrc which generates plots suitable for ieee publications (specifically ieee transactions)? or any other publications for that matter. like a set of matching matplotlibrc's to journals (or some other way to achieve a similar functionality) if not, i think it would be a valuable thing to make, because it wouldnt be very hard, and would save a lot of users time/effort. specifically it would specify the dimension/dpi/font type/sizes/etc. i have a preliminary one for ieee we can use as a starting point, that can be improved. thanks alex
i was wondering if anyone had considered making a matplotlibrc which generates plots suitable for ieee publications (specifically ieee transactions)? or any other publications for that matter. like a set of matching matplotlibrc's to journals. if not, i think it would be a valuable thing to make, because it wouldnt be very hard, and would save a lot of users time/effort. specifically it would specify the dimension/dpi/font sizes/etc. i have a preliminary one we can use as a starting point, that can be improved. thanks alex