matplotlib-devel — matplotlib developers

Re: [matplotlib-devel] Should we update sample_data in the old SVN repo?

[Fernando P. <fpe...@gm...>]

On Fri, Dec 16, 2011 at 5:11 PM, Eric Firing <ef...@ha...> wrote:
> Nope:
>
> efiring@manini:~/temp/sample_data_svn$ svn commit -m"Sync SVN repo with
> contents in current git repo"
> svn: Commit failed (details follow):
> svn: Server sent unexpected return value (403 Forbidden) in response to
> MKACTIVITY request for
> '/svnroot/matplotlib/!svn/act/9b074418-cd32-4039-88d8-06b46c4c8764'
>
> I think the repo was frozen when we moved to github.

OK, thanks for trying.  Next week we can see if John can reopen it for
this.  I think there's no danger of anyone mistakenly committing any
real work there anymore.

Cheers,

f

Re: [matplotlib-devel] Should we update sample_data in the old SVN repo?

[Eric F. <ef...@ha...>]

On 12/16/2011 02:12 PM, Fernando Perez wrote:
> wgethttp://fperez.org/tmp/sample_data_svn.tgz
> tar xzf sample_data_svn.tgz
> cd sample_data_svn
> svn commit -m"Sync SVN repo with contents in current git repo"
>

Nope:

efiring@manini:~/temp/sample_data_svn$ svn commit -m"Sync SVN repo with 
contents in current git repo"
svn: Commit failed (details follow):
svn: Server sent unexpected return value (403 Forbidden) in response to 
MKACTIVITY request for 
'/svnroot/matplotlib/!svn/act/9b074418-cd32-4039-88d8-06b46c4c8764'

I think the repo was frozen when we moved to github.

Eric

Re: [matplotlib-devel] Should we update sample_data in the old SVN repo?

[Fernando P. <fpe...@gm...>]

On Fri, Dec 16, 2011 at 3:39 PM, Fernando Perez <fpe...@gm...> wrote:
> Great, thanks.  I'll see if I can push and will report back.  If it
> doesn't work, we'll see if John can later restore write access to it.

Well, I can't seem to push.  I don't know if it's my sourceforge
credentials, or if the repos are read-only, or what.  In case anyone
else wants to give it a try, I tarred the svn directory and put it up
here:

http://fperez.org/tmp/sample_data_svn.tgz

I've already done the add steps, so all you should need to do is:


wget http://fperez.org/tmp/sample_data_svn.tgz
tar xzf sample_data_svn.tgz
cd sample_data_svn
svn commit -m"Sync SVN repo with contents in current git repo"



If one of you wants to try pasting the above four lines into a
terminal, let me know if it works for you.

Cheers,

f

Re: [matplotlib-devel] Should we update sample_data in the old SVN repo?

[Fernando P. <fpe...@gm...>]

On Fri, Dec 16, 2011 at 3:34 PM, Eric Firing <ef...@ha...> wrote:
> If you are willing and able to do it, please go ahead.  I can't think of
> any problem it would create.  (But I don't know whether the repo is
> writable.)

Great, thanks.  I'll see if I can push and will report back.  If it
doesn't work, we'll see if John can later restore write access to it.

Cheers,

f

Re: [matplotlib-devel] Should we update sample_data in the old SVN repo?

[Eric F. <ef...@ha...>]

On 12/16/2011 10:20 AM, Fernando Perez wrote:
> Hi all,
>
> I just added the stinkbug.png file to the sample_data repo so the
> Image tutorial and other examples using this image could be run by
> users making cbook.get_sample_data calls.  But while it works fine
> with a reasonably recent MPL, I tested with the system one in Ubuntu
> 11.10, and it does not find the file.  The reason is simply that this
> version of mpl still had the old SVN sample_data repo URL:
>
> baseurl = 'http://matplotlib.svn.sourceforge.net/svnroot/matplotlib/trunk/sample_data/'
>
> So the problem is that any users of 11.10 are now stuck with a 'frozen
> in time' sample_data repo.
>
> We can fix this easily by simply pushing over to sample_data an update
> with any new files in the github one.  Since that repo changes fairly
> slowly and the changes typically involve just putting new files in and
> no actual code, it should be fairly easy to do manually.
>
> What do folks think?  If you agree, I'm happy to push an update now
> (I'm assuming the SVN repo is still writable, which might not be the
> case...).

Fernando,

If you are willing and able to do it, please go ahead.  I can't think of 
any problem it would create.  (But I don't know whether the repo is 
writable.)

Eric

>
> Cheers,
>
> f
>

[matplotlib-devel] Should we update sample_data in the old SVN repo?

[Fernando P. <fpe...@gm...>]

Hi all,

I just added the stinkbug.png file to the sample_data repo so the
Image tutorial and other examples using this image could be run by
users making cbook.get_sample_data calls.  But while it works fine
with a reasonably recent MPL, I tested with the system one in Ubuntu
11.10, and it does not find the file.  The reason is simply that this
version of mpl still had the old SVN sample_data repo URL:

baseurl = 'http://matplotlib.svn.sourceforge.net/svnroot/matplotlib/trunk/sample_data/'

So the problem is that any users of 11.10 are now stuck with a 'frozen
in time' sample_data repo.

We can fix this easily by simply pushing over to sample_data an update
with any new files in the github one.  Since that repo changes fairly
slowly and the changes typically involve just putting new files in and
no actual code, it should be fairly easy to do manually.

What do folks think?  If you agree, I'm happy to push an update now
(I'm assuming the SVN repo is still writable, which might not be the
case...).

Cheers,

f

Re: [matplotlib-devel] jsxgraph or flot backend (or interactive viewer for svg backend?)

[Michael D. <md...@st...>]

On 12/15/2011 11:44 PM, Jason Grout wrote:
> On 12/15/11 8:03 PM, Michael Droettboom wrote:
>> On 12/07/2011 11:36 PM, Jason Grout wrote:
>>> On 12/7/11 10:27 PM, Chris Barker wrote:
>>>> On 12/5/11 9:49 PM, Jason Grout wrote:
>>>>> Has anyone ever worked on a backend that generates javascript code for
>>>>> one of the javascript plotters out there (like jsxgraph or flot)?
>>>>> Alternatively, I suppose we could generate an svg or html5 plot and then
>>>>> accompany it with the javascript code to trace the function, etc.
>>>> Someone has worked on a html5 back-end, It was jsut discussed a bit on
>>>> the thread "Using the Agg renderer by itself"
>>>>
>>>> Here's a cut and paste:
>>>>
>>>> On 11/27/11 12:33 PM, Ludwig Schwardt wrote:
>>>>      >
>>>>      >     Ben is referring to mplh5canvas, available at
>>>>      >     http://code.google.com/p/mplh5canvas/. The main advantage of this
>>>>      >     approach is interactive zooming of plots within the browser. If this is
>>>>      >     not important to you, it will probably be faster to generate static PNGs
>>>>      >     or SVGs.
>>>>      >
>>>>      >     The HTML5 backend should be easy to try out, as it is a pure Python
>>>>      >     package with no onerous dependencies.
>>>>      >
>>> Michael Droettboom played with this a little at the Sage Days in March,
>>> IIRC, and I seem to think he also whipped up an interactive demo using
>>> svg plots.  Michael, do you remember what your conclusions were?
>>>
>> My conclusion was basically that the current crop of browsers are plenty
>> fast and its generally feasible.  But rewriting all that Python code in
>> Javascript ain't a small project ;)
> So maybe pyjamas or pyjs might help?
>
> http://pyjs.org/
>
> http://stackoverflow.com/questions/683462/best-way-to-integrate-python-and-javascript
> gives a few other python->javascript compilers.  I don't know if any are
> currently active, though.
>
> I thought you also had some conclusion about using SVG instead of HTML5
> canvas...
>
Yes.  In the case where you want to create a bunch of graphics objects 
that may be transformed (i.e. zoomed and panned) later, SVG is much more 
efficient.  Canvas forces JavaScript to run through the entire drawing 
stack with each update, whereas SVG rendering allows a single object to 
be manipulated and only the parts of the drawing that change will be 
updated (and that all happens in the browser's renderer, not JavaScript 
so is therefore much faster).

Mike

Re: [matplotlib-devel] jsxgraph or flot backend (or interactive viewer for svg backend?)

[Jason G. <jas...@cr...>]

On 12/15/11 8:03 PM, Michael Droettboom wrote:
> On 12/07/2011 11:36 PM, Jason Grout wrote:
>> On 12/7/11 10:27 PM, Chris Barker wrote:
>>> On 12/5/11 9:49 PM, Jason Grout wrote:
>>>> Has anyone ever worked on a backend that generates javascript code for
>>>> one of the javascript plotters out there (like jsxgraph or flot)?
>>>> Alternatively, I suppose we could generate an svg or html5 plot and then
>>>> accompany it with the javascript code to trace the function, etc.
>>> Someone has worked on a html5 back-end, It was jsut discussed a bit on
>>> the thread "Using the Agg renderer by itself"
>>>
>>> Here's a cut and paste:
>>>
>>> On 11/27/11 12:33 PM, Ludwig Schwardt wrote:
>>>     >
>>>     >    Ben is referring to mplh5canvas, available at
>>>     >    http://code.google.com/p/mplh5canvas/. The main advantage of this
>>>     >    approach is interactive zooming of plots within the browser. If this is
>>>     >    not important to you, it will probably be faster to generate static PNGs
>>>     >    or SVGs.
>>>     >
>>>     >    The HTML5 backend should be easy to try out, as it is a pure Python
>>>     >    package with no onerous dependencies.
>>>     >
>> Michael Droettboom played with this a little at the Sage Days in March,
>> IIRC, and I seem to think he also whipped up an interactive demo using
>> svg plots.  Michael, do you remember what your conclusions were?
>>
> My conclusion was basically that the current crop of browsers are plenty
> fast and its generally feasible.  But rewriting all that Python code in
> Javascript ain't a small project ;)

So maybe pyjamas or pyjs might help?

http://pyjs.org/

http://stackoverflow.com/questions/683462/best-way-to-integrate-python-and-javascript 
gives a few other python->javascript compilers.  I don't know if any are 
currently active, though.

I thought you also had some conclusion about using SVG instead of HTML5 
canvas...

Jason

Re: [matplotlib-devel] jsxgraph or flot backend (or interactive viewer for svg backend?)

[Michael D. <md...@st...>]

On 12/07/2011 11:36 PM, Jason Grout wrote:
> On 12/7/11 10:27 PM, Chris Barker wrote:
>> On 12/5/11 9:49 PM, Jason Grout wrote:
>>> Has anyone ever worked on a backend that generates javascript code for
>>> one of the javascript plotters out there (like jsxgraph or flot)?
>>> Alternatively, I suppose we could generate an svg or html5 plot and then
>>> accompany it with the javascript code to trace the function, etc.
>> Someone has worked on a html5 back-end, It was jsut discussed a bit on
>> the thread "Using the Agg renderer by itself"
>>
>> Here's a cut and paste:
>>
>> On 11/27/11 12:33 PM, Ludwig Schwardt wrote:
>>    >
>>    >   Ben is referring to mplh5canvas, available at
>>    >   http://code.google.com/p/mplh5canvas/. The main advantage of this
>>    >   approach is interactive zooming of plots within the browser. If this is
>>    >   not important to you, it will probably be faster to generate static PNGs
>>    >   or SVGs.
>>    >
>>    >   The HTML5 backend should be easy to try out, as it is a pure Python
>>    >   package with no onerous dependencies.
>>    >
> Michael Droettboom played with this a little at the Sage Days in March,
> IIRC, and I seem to think he also whipped up an interactive demo using
> svg plots.  Michael, do you remember what your conclusions were?
>
My conclusion was basically that the current crop of browsers are plenty 
fast and its generally feasible.  But rewriting all that Python code in 
Javascript ain't a small project ;)

Mike

Re: [matplotlib-devel] Gtk3/GObject-introspection support in master

[Benjamin R. <ben...@ou...>]

On Wed, Dec 14, 2011 at 7:44 AM, Michael Droettboom <md...@st...> wrote:

>  Thanks to the great work of Robert Johannson, we now have Gtk3 support
> using the GObject introspection Python bindings.  To use, set your backend
> to "Gtk3Cairo" or "Gtk3Agg".
>
> It seems to be working well, but it would be great to get testing on a
> broader set of platforms etc.
>
> Unfortunately, the Gtk3Agg backend will not currently work under Python
> 3.  For the gory details, see this:
>
>  http://lists.cairographics.org/archives/cairo/2011-November/022519.html
>
> (On Fedora, you need to install the "pygobject3" package.  Can someone
> report back the package name for the Debian/Ubuntu folks?)
>
>
I have not totally confirmed this yet, but it looks like there are two
packages: one for python2.x and one for py3k.  They are python-gobject and
python3-gobject.  It also appears that in Ubuntu, it is somewhat standard
to have a separate package containing introspection data.  I don't know how
well that would apply to us.

I will update after doing some testing.

Ben Root

[matplotlib-devel] Gtk3/GObject-introspection support in master

[Michael D. <md...@st...>]

Thanks to the great work of Robert Johannson, we now have Gtk3 support 
using the GObject introspection Python bindings.  To use, set your 
backend to "Gtk3Cairo" or "Gtk3Agg".

It seems to be working well, but it would be great to get testing on a 
broader set of platforms etc.

Unfortunately, the Gtk3Agg backend will not currently work under Python 
3.  For the gory details, see this:

http://lists.cairographics.org/archives/cairo/2011-November/022519.html

(On Fedora, you need to install the "pygobject3" package.  Can someone 
report back the package name for the Debian/Ubuntu folks?)

Mike

[matplotlib-devel] bbox_inches='tight' error, is this an mpl bug or misuse on my part?

[Fernando P. <fpe...@gm...>]

Hi all,

I'm getting an error (with current mpl master) illustrated by this code:

###
from cStringIO import StringIO

import matplotlib.pyplot as plt
import matplotlib.lines as lines
fig = plt.figure()
l1 = lines.Line2D([0, 1], [0, 1], transform=fig.transFigure, figure=fig)
l2 = lines.Line2D([0, 1], [1, 0], transform=fig.transFigure, figure=fig)
fig.lines.extend([l1, l2])
fig.canvas.draw()

sio = StringIO()
fig.canvas.print_figure(sio, format='png', bbox_inches='tight')
###

Is this a bug, or am I misusing print_figure?

I don't want to open a ticket if it's not a real bug, if it is one
I'll file it on gh.

Thanks,

f

Re: [matplotlib-devel] savefig to pdf and ps don't respect mew=0 or mec

[Benjamin R. <ben...@ou...>]

On Sun, Dec 11, 2011 at 5:48 PM, Mike Kaufman <mc...@gm...> wrote:

> Attached. Also put the viewed pdf on the right side of the screen.
>
> M
>
>
> On 12/11/11 6:04 PM, Benjamin Root wrote:
>
>>
>>
>> On Sunday, December 11, 2011, Mike Kaufman <mc...@gm...
>> <mailto:mc...@gm...>> wrote:
>>  >
>>  > Both Skim 1.3.18 and Preview on OSX 10.6.8 show this. I'm using gv
>> 3.7.1 as a postscript viewer.
>>  >
>>  > M
>>  >
>>
>> Could you send the PDF and a screen capture of what you see as a png so
>> we can check?  The mac's Preview program was the one that I found to be
>> faulty.
>>
>> Ben Root
>>
>
>
Mike,

I have confirmed that the problem exists.  I have also replicated the
problem on my own machine.  Could you file a bug report for us, please?

Thanks,
Ben Root

Re: [matplotlib-devel] mplot3d tutorial, demo code needs slight fix

[Benjamin R. <ben...@ou...>]

On Sat, Dec 10, 2011 at 1:58 PM, cgraves <chr...@gm...> wrote:

>
> For the 3rd contour example at
> http://matplotlib.sourceforge.net/mpl_toolkits/mplot3d/tutorial.html , the
> code (
> http://matplotlib.sourceforge.net/mpl_examples/mplot3d/contour3d_demo3.py)
> should be changed from ax.set_xlim(-40, 40)
> to ax.set_xlim3d(-40, 40) for the code to work. Same for ylim and zlim.
> Probably the syntax was just updated since that example was made. Of course
> any other examples on that page which use xlim should also be fixed.
>
> Best,
> Chris
>

Chris,

Because the documentation is for v1.1.0, the example code is correct.
There has been significant updates to mplot3d for v1.1.0 that we really
want to move users away from previous versions (and particularly, away from
functions such as set_xlim3d()).

Thanks,
Ben Root

Re: [matplotlib-devel] savefig to pdf and ps don't respect mew=0 or mec

[Mike K. <mc...@gm...>]

Attached. Also put the viewed pdf on the right side of the screen.

M

On 12/11/11 6:04 PM, Benjamin Root wrote:
>
>
> On Sunday, December 11, 2011, Mike Kaufman <mc...@gm...
> <mailto:mc...@gm...>> wrote:
>  >
>  > Both Skim 1.3.18 and Preview on OSX 10.6.8 show this. I'm using gv
> 3.7.1 as a postscript viewer.
>  >
>  > M
>  >
>
> Could you send the PDF and a screen capture of what you see as a png so
> we can check?  The mac's Preview program was the one that I found to be
> faulty.
>
> Ben Root

Re: [matplotlib-devel] savefig to pdf and ps don't respect mew=0 or mec

[Benjamin R. <ben...@ou...>]

On Sunday, December 11, 2011, Mike Kaufman <mc...@gm...> wrote:
>
> Both Skim 1.3.18 and Preview on OSX 10.6.8 show this. I'm using gv 3.7.1
as a postscript viewer.
>
> M
>

Could you send the PDF and a screen capture of what you see as a png so we
can check?  The mac's Preview program was the one that I found to be faulty.

Ben Root

Re: [matplotlib-devel] savefig to pdf and ps don't respect mew=0 or mec

[Mike K. <mc...@gm...>]

Both Skim 1.3.18 and Preview on OSX 10.6.8 show this. I'm using gv 3.7.1 
as a postscript viewer.

M

> Mike,
>
> I was recently tracking down a somewhat similar problem a few days ago.
>   It turned out not to have been related to mpl at all, but rather a bug
> in the PDF viewer.  Which viewer are you using so that I can make sure
> that I check something different?
>
> Ben Root

Re: [matplotlib-devel] savefig to pdf and ps don't respect mew=0 or mec

[Benjamin R. <ben...@ou...>]

On Sunday, December 11, 2011, Mike Kaufman <mc...@gm...> wrote:
>
> for this code:
>
> clf()
> plot(arange(5),arange(5), 'y.', ms=30.0, mew=0, mec='r')
> draw()
> savefig('mew.pdf')
> savefig('mew.ps')
>
> The pdf and ps show a marker edge even though the gtkagg window doesn't
> (neither do the png or svg savefigures).
> The marker edge in the ps is black instead of red.
>
> I haven't done a git-bisect, but
> f1388ee3c3a5c72af00701e5a623545f0df2f426 from April 11 seems to have the
> pdf problem but the ps doesn't have a marker edge.
>
> M
>

Mike,

I was recently tracking down a somewhat similar problem a few days ago.  It
turned out not to have been related to mpl at all, but rather a bug in the
PDF viewer.  Which viewer are you using so that I can make sure that I
check something different?

Ben Root

[matplotlib-devel] savefig to pdf and ps don't respect mew=0 or mec

[Mike K. <mc...@gm...>]

for this code:

clf()
plot(arange(5),arange(5), 'y.', ms=30.0, mew=0, mec='r')
draw()
savefig('mew.pdf')
savefig('mew.ps')

The pdf and ps show a marker edge even though the gtkagg window doesn't 
(neither do the png or svg savefigures).
The marker edge in the ps is black instead of red.

I haven't done a git-bisect, but
f1388ee3c3a5c72af00701e5a623545f0df2f426 from April 11 seems to have the 
pdf problem but the ps doesn't have a marker edge.

M

[matplotlib-devel] mplot3d tutorial, demo code needs slight fix

[cgraves <chr...@gm...>]

For the 3rd contour example at
http://matplotlib.sourceforge.net/mpl_toolkits/mplot3d/tutorial.html , the
code (
http://matplotlib.sourceforge.net/mpl_examples/mplot3d/contour3d_demo3.py )
should be changed from ax.set_xlim(-40, 40)
to ax.set_xlim3d(-40, 40) for the code to work. Same for ylim and zlim.
Probably the syntax was just updated since that example was made. Of course
any other examples on that page which use xlim should also be fixed.

Best,
Chris
-- 
View this message in context: http://old.nabble.com/mplot3d-tutorial%2C-demo-code-needs-slight-fix-tp32952017p32952017.html
Sent from the matplotlib - devel mailing list archive at Nabble.com.

Re: [matplotlib-devel] imread issues

[Christoph G. <cg...@uc...>]

Pull request at <https://github.com/matplotlib/matplotlib/pull/616>

Christoph


On 12/9/2011 12:11 PM, Christoph Gohlke wrote:
> Hello,
>
> while working on the scikits-image io plugin system, I noticed some
> issues with matplotlib's imread function. I have a patch for all these
> issues and will submit a PR but wanted to check on the list first.
>
>
> 1) imread does not properly detect the file type if an open file handle
> is used.
>
>>>> lena = pylab.imread(matplotlib.cbook.get_sample_data('lena.jpg'))
> Traceback (most recent call last):
>     File "<stdin>", line 1, in<module>
>     File "X:\Python27\lib\site-packages\matplotlib\pyplot.py", line 1740,
> in imread
>       return _imread(*args, **kwargs)
>     File "X:\Python27\lib\site-packages\matplotlib\image.py", line 1207,
> in imread
>       return handler(fname)
> RuntimeError: _image_module::readpng: file not recognized as a PNG file
>
>
> 2) imread does not properly convert uint16 images to uint8 as reported
> on the scikits-image ML
> <https://groups.google.com/forum/#!topic/scikits-image/O47tNU01kLA>.
>
>
> 3) Any non-PNG image loaded with imread is displayed upside-down in imshow:
>
>>>> imshow(imread("lena.jpg")); show()
>
> A solution is to pass `origin='lower'` to imshow for non-PNG images. But
> is there a reason for this asymmetry? Any image loaded with PIL is
> explicitly flipped upside-down at
> <https://github.com/matplotlib/matplotlib/blob/master/lib/matplotlib/image.py#L1267>.
>
>
> Christoph
>
>
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>

Re: [matplotlib-devel] Code review request: minor modifications to axes.boxplot

[Paul H. <pmh...@gm...>]

Ben,

Thanks for the reply. I definitely like your idea. Seems like we could
include some logic in axes.errorbar to look at the shapes of xerr and
yerr in a similar fashion to what I propose for axes.boxplots,
allowing the user to have custom lower and upper errors for each data
point (in a time series as I would use it).

I'll try to bang that out this weekend while this is still fresh.
-p


On Fri, Dec 9, 2011 at 1:29 PM, Benjamin Root <ben...@ou...> wrote:
> On Thu, Dec 8, 2011 at 10:45 AM, Paul Hobson <pmh...@gm...> wrote:
>>
>> Matplotlib gurus:
>>
>> I took at stab at the git work flow and incorporated my personal
>> modifications to the boxplot function. Github's diff can be found
>> here:
>> https://github.com/phobson/matplotlib/compare/master...manual_boxplots
>>
>> In summary, if your data is MxN, you can manually specify medians and
>> the confidence intervals around the medians using Nx1 and Nx2 arrays,
>> respectively. Alternatively, you can use lists or tuples and use Nones
>> if you want to specify those values only for some columns in your MxN
>> data set. In other words, with an Mx5 data array, you can specify
>> conf_intervals=[(ci1a,ci2a), (ci1b,ci2b), (ci1c,ci2c), None,
>> (ci1e,ci2e)]. Within the conf_intervals "array", the CIs can be listed
>> in any order as I use np.max() and np.min() to pull the upper and
>> lower values, respectively.
>>
>> The motivation behind this is that sometimes I need the confidence
>> levels to be different than 95%, and also that I compute those
>> confidence intervals with a bootstrapping routine that is more robust
>> than mpl-compatible one I submitted some time ago.
>>
>> I hope y'all find this to be a useful contribution. I'm an avid
>> matplotlib user. It really is a wonderful tool.
>>
>> Cheers,
>> paul h
>>
>
> Paul,
>
> Interesting.  I haven't had much time to really look over your changes, but
> I have been wondering if the errorbar() and boxplot() functions could be
> treated as two different ways to display similar information.  Therefore,
> perhaps their call signatures could be made more similar to each other.
> What do you think?
>
> Ben Root
>

Re: [matplotlib-devel] Code review request: minor modifications to axes.boxplot

[Benjamin R. <ben...@ou...>]

On Thu, Dec 8, 2011 at 10:45 AM, Paul Hobson <pmh...@gm...> wrote:

> Matplotlib gurus:
>
> I took at stab at the git work flow and incorporated my personal
> modifications to the boxplot function. Github's diff can be found
> here:
> https://github.com/phobson/matplotlib/compare/master...manual_boxplots
>
> In summary, if your data is MxN, you can manually specify medians and
> the confidence intervals around the medians using Nx1 and Nx2 arrays,
> respectively. Alternatively, you can use lists or tuples and use Nones
> if you want to specify those values only for some columns in your MxN
> data set. In other words, with an Mx5 data array, you can specify
> conf_intervals=[(ci1a,ci2a), (ci1b,ci2b), (ci1c,ci2c), None,
> (ci1e,ci2e)]. Within the conf_intervals "array", the CIs can be listed
> in any order as I use np.max() and np.min() to pull the upper and
> lower values, respectively.
>
> The motivation behind this is that sometimes I need the confidence
> levels to be different than 95%, and also that I compute those
> confidence intervals with a bootstrapping routine that is more robust
> than mpl-compatible one I submitted some time ago.
>
> I hope y'all find this to be a useful contribution. I'm an avid
> matplotlib user. It really is a wonderful tool.
>
> Cheers,
> paul h
>
>
Paul,

Interesting.  I haven't had much time to really look over your changes, but
I have been wondering if the errorbar() and boxplot() functions could be
treated as two different ways to display similar information.  Therefore,
perhaps their call signatures could be made more similar to each other.
What do you think?

Ben Root

[matplotlib-devel] imread issues

[Christoph G. <cg...@uc...>]

Hello,

while working on the scikits-image io plugin system, I noticed some 
issues with matplotlib's imread function. I have a patch for all these 
issues and will submit a PR but wanted to check on the list first.


1) imread does not properly detect the file type if an open file handle 
is used.

>>> lena = pylab.imread(matplotlib.cbook.get_sample_data('lena.jpg'))
Traceback (most recent call last):
   File "<stdin>", line 1, in <module>
   File "X:\Python27\lib\site-packages\matplotlib\pyplot.py", line 1740, 
in imread
     return _imread(*args, **kwargs)
   File "X:\Python27\lib\site-packages\matplotlib\image.py", line 1207, 
in imread
     return handler(fname)
RuntimeError: _image_module::readpng: file not recognized as a PNG file


2) imread does not properly convert uint16 images to uint8 as reported 
on the scikits-image ML 
<https://groups.google.com/forum/#!topic/scikits-image/O47tNU01kLA>.


3) Any non-PNG image loaded with imread is displayed upside-down in imshow:

>>> imshow(imread("lena.jpg")); show()

A solution is to pass `origin='lower'` to imshow for non-PNG images. But 
is there a reason for this asymmetry? Any image loaded with PIL is 
explicitly flipped upside-down at 
<https://github.com/matplotlib/matplotlib/blob/master/lib/matplotlib/image.py#L1267>.


Christoph

[matplotlib-devel] Code review request: minor modifications to axes.boxplot

[Paul H. <pmh...@gm...>]

Matplotlib gurus:

I took at stab at the git work flow and incorporated my personal
modifications to the boxplot function. Github's diff can be found
here:
https://github.com/phobson/matplotlib/compare/master...manual_boxplots

In summary, if your data is MxN, you can manually specify medians and
the confidence intervals around the medians using Nx1 and Nx2 arrays,
respectively. Alternatively, you can use lists or tuples and use Nones
if you want to specify those values only for some columns in your MxN
data set. In other words, with an Mx5 data array, you can specify
conf_intervals=[(ci1a,ci2a), (ci1b,ci2b), (ci1c,ci2c), None,
(ci1e,ci2e)]. Within the conf_intervals "array", the CIs can be listed
in any order as I use np.max() and np.min() to pull the upper and
lower values, respectively.

The motivation behind this is that sometimes I need the confidence
levels to be different than 95%, and also that I compute those
confidence intervals with a bootstrapping routine that is more robust
than mpl-compatible one I submitted some time ago.

I hope y'all find this to be a useful contribution. I'm an avid
matplotlib user. It really is a wonderful tool.

Cheers,
paul h