matplotlib-users Mailing List for matplotlib (Page 5)

> > http://matplotlib.sourceforge.net/users/navigation_toolbar.html
Constrained zoom to x axis (hold x key + left click zoom icon) is broken 
for me with master.
Tested with TkAgg, Qt4Agg backend
features was working on mpl 1.0.0

i created the project for 'mplrc' here
https://code.google.com/p/mplrc/
let me know what you all think. if you all send me your publications'
settings i can add them, or if you want an account ill make you one. 
one thing to mention is that the params dictionary probably should set
all possible settings so that there is no ambiguity. i have yet to do
this.
here is an example of my ieee format
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
> 

Is there a way to control the distance between the axis label and the 
tick labels with mplot3d.Axes3D? For small figure sizes they overlap and 
I haven't found a way to fix that. My last resort was to remove the tick 
labels but that sucks for publication-quality plots.
Cheers,
-- 
Giovanni Luca Ciampaglia
Ph.D. Candidate
Faculty of Informatics
University of Lugano
Web: http://www.inf.usi.ch/phd/ciampaglia/
Bertastraße 36 ∙ 8003 Zürich ∙ Switzerland

Hello,
check the help ;). you can set aspect='auto' or something fixed.
Regards,
Sebastian
On Sat, 2011年04月16日 at 10:43 +0200, Paolo Zaffino wrote:
> Hi at all,
> I have a numpy matrix (an image) and I'd like to show it.
> I thought to use show function, but I have a question.
> I don't want that the pixel have dimension 1x1 unit but I want for 
> example 1X1.5 unit (I don't want a square but a rectangle).
> How can I do this?
> Thanks in advance.
> Paolo
> 
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> 

Hi at all,
I have a numpy matrix (an image) and I'd like to show it.
I thought to use show function, but I have a question.
I don't want that the pixel have dimension 1x1 unit but I want for 
example 1X1.5 unit (I don't want a square but a rectangle).
How can I do this?
Thanks in advance.
Paolo

On 04/15/2011 12:08 PM, Thomas Robitaille wrote:
> 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?
You found a bug, presumably in extension code, since Ctl-C doesn't bring 
it to a halt.
Eric
>
> Thanks for any help,
>
> Cheers,
> Tom

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
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>>>>>> _______________________________________________
>>>>>> 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 
> > 
> > 
> > 
> > ------------------------------------------------------------------------------
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> > 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.
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> > 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
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> Benefiting from Server Virtualization: Beyond Initial Workload 
> Consolidation -- Increasing the use of server virtualization is a top
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> 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 

Hi,
I've lost touch with the state of mpl and starting to use it again. Apparently some of the gallery examples in 3D aren't working, but I think I found a workaround.
However, is there a way to get 3D bar charts with semilog style (e.g. logarithmic x-axis?)
Right now, I have:
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
<snip>
prepare data
</snip>
for size, val, timepoint in zip(tdata[::2], tdata[1::2], timepoints):
 cs = ['b'] * len(size)
 ax.bar(size, val, zs = timepoint, zdir = 'y', color=cs, alpha=0.8)
as modified from one example I've found. Looks fine, except that the x-axis has to be logarithmic to make sense (data were sampled this way).
TIA,
Christian
-- 
NEU: FreePhone - kostenlos mobil telefonieren und surfen!			
Jetzt informieren: http://www.gmx.net/de/go/freephone

Hi Oğuz,
Oğuz Yarımtepe, on 2011年04月13日 23:09, wrote:
> I didn't understand why i can not see 20 dots with the below command,
> but i just see 3 dots at the graph.
> a1 = N.ndarray(shape=(10,2))*2
When you allocate an array this way - you're just allocating
space for it without initializing it to anything - there are no
guarantees about what values that array will take on - and on
most operating systems it will vary from one run to another. 
If you're trying to get a random number, changes the a1 and a2
lines to:
a1 = N.random.rand(10,2)*2
a2 = N.random.rand(10,2)+10
> P.xlim(xmin=n_x.min()*10, xmax=n_x.max()*10)
> P.ylim(ymin=n_y.min()*10, ymax=n_y.max()*10)
I don't think you want to do n_x.min()*10 - multiplying the min
and max values has a different effect on the limits depending on
the sign of those values. You probably want to find the
difference between min and max and then use that to extend and
limits, instead.
 
> Normally i have 20 different points to be plotted but because they are
> so close values it just plots three of them. Any idea how i can fix
> it?
The fact that you weren't initializing your arrays with anything
affects how many unique combinations of x and y you'll have.
len(set(zip(n_x,n_y))) will tell you how many points you should
see.
best,
-- 
Paul Ivanov
314 address only used for lists, off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7 

Dear experts,
is there a way of rotating a single subplot in a multi-faceted figure with
respect to the others?
i.e. I have a contour plot representing a 2D histogram and on the top of
it and to its left two line plots, representing the respective 1D
components. I am aware of the possibility to swap x- and y- coordinates in
analogy of one example in the gallery where they use vertical bar graphs
for the y-component and bar graphs for the x-component, so essentially I
can do what I want, but I thought that there might be an alternative way.
Thanks a lot!
cheers
ben

I didn't understand why i can not see 20 dots with the below command,
but i just see 3 dots at the graph.
import pylab as P
import numpy as N
a1 = N.ndarray(shape=(10,2))*2
x = a1[:,0]
y = a1[:,1]
a2 = N.ndarray(shape=(10,2))+10
xx = a2[:,0]
yy = a2[:,1]
n_x = N.append(x,xx)
n_y = N.append(y,yy)
P.scatter(n_x, n_y, alpha=0.5)
P.xlim(xmin=n_x.min()*10, xmax=n_x.max()*10)
P.ylim(ymin=n_y.min()*10, ymax=n_y.max()*10)
P.plot(n_x, n_y, 's', alpha=0.7, ms=3)
P.show()
Normally i have 20 different points to be plotted but because they are
so close values it just plots three of them. Any idea how i can fix
it?

Hi
Has anyone ever added this capability? I want to be able to rotate a
projection of the earth.
Thanks
Mathew

2011年4月13日 Tim Åberg <qw...@ho...>:
>
> Due to that my first question a couple of day back was a mess i thougth i
> could clear things up.
>
> Is there any way to label the lines using linecollection. In plot there is
> label, example;
> plot(x,y,label = "Hello")
>
> But are there any way to do the same thing with linecollection?
> If not, is there any eother asy way of creating labels on a line?
You can customize the legend by hand.
http://matplotlib.sourceforge.net/users/legend_guide.html
Goyo