matplotlib-users Mailing List for matplotlib (Page 5)

Could you try using faulthandler and post the traceback please? That'll
help us isolate the problem better.
Ben Root
On Wed, Feb 24, 2016 at 3:04 PM, Claude Falbriard <cl...@br...>
wrote:
> Dear colleagues,
>
> I've done a build from source of latest *Matplotlib* package and
> deployed it at our IBM z13 machine (s390x). It uses the current release
> 1.5.1.
> During the unit tests I found an issue with a test case from NOAA which
> uses a* pcolormesh* draw function with *basemap*.
>
> Example 2: Plot data from an NWW3 GRiB2 file - [ here:
> *http://polar.ncep.noaa.gov/waves/examples/usingpython.shtml*
> <http://polar.ncep.noaa.gov/waves/examples/usingpython.shtml>*]*
>
> The following line is causing a *Segmentation fault* error even when
> adding an 8GB swap memory to the process:
>
> cs = m.pcolormesh(x,y,data,shading='flat',cmap=plt.cm.jet)
>
> I also tryed to execute other, similar samples that use pcolormesh, but
> receiving the same error. Is this a known issue or might it be be related
> to the memory environment ? Any hints how to debug this error?
>
> Regards,
>
> *Claude Falbriard*
> Certified IT Specialist L2 - Middleware
> ------------------------------
> *Phone:*55-13-99662-5703 | *Mobile:*55-13-98117-3316
> *E-mail:* *cl...@br...* <cl...@br...>
>
>
>
> ------------------------------------------------------------------------------
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>
>

Dear colleagues,
 I've done a build from source of latest Matplotlib package and deployed 
it at our IBM z13 machine (s390x). It uses the current release 1.5.1. 
During the unit tests I found an issue with a test case from NOAA which 
uses a pcolormesh draw function with basemap. 
Example 2: Plot data from an NWW3 GRiB2 file - [ here: 
http://polar.ncep.noaa.gov/waves/examples/usingpython.shtml ] 
The following line is causing a Segmentation fault error even when adding 
an 8GB swap memory to the process: 
cs = m.pcolormesh(x,y,data,shading='flat',cmap=plt.cm.jet)
I also tryed to execute other, similar samples that use pcolormesh, but 
receiving the same error. Is this a known issue or might it be be related 
to the memory environment ? Any hints how to debug this error? 
Regards,
Claude Falbriard
Certified IT Specialist L2 - Middleware
Phone: 55-13-99662-5703 | Mobile: 55-13-98117-3316
E-mail: cl...@br...

Dear all,
SciPy 2016, the Fifteenth Annual Conference on Python in Science, takes
place in Austin, TX on July, 11th to 17th. The conference features two days
of tutorials by followed by three days of presentations, and concludes with
two days of developer sprints on projects of interest to attendees. .
The topics presented at SciPy are very diverse, with a focus on advanced
software engineering and original uses of Python and its scientific
libraries, either in theoretical or experimental research, from both
academia and the industry. This year we are happy to announce two
specialized tracks that run in parallel to the general conference (Data
Science , High Performance Computing) and 8 mini-symposia (Earth and Space
Science, Biology and Medicine, Engineering, Social Sciences, Special
Purpose Databases, Case Studies in Industry, Education, Reproducibility)
Submissions for talks and posters are welcome on our website (
http://scipy2016.scipy.org). In your abstract, please provide details on
what Python tools are being employed, and how. The talk and poster
submission deadline is March 25th, 2016, while the tutorial submission
deadline is March, 21st, 2016.
Important dates:
Mar 21: Tutorial Proposals Due
Mar 25: Talk and Poster Proposals Due
May 11: Plotting Contest Submissions Due
Apr 22: Tutorials Announced
Apr 22: Financial Aid Submissions Due
May 4: Talk and Posters Announced
May 11: Financial Aid Recipients Notified
May 22: Early Bird Registration Deadline
Jul 11-12: SciPy 2016 Tutorials
Jul 13-15: SciPy 2016 General Conference
Jul 16-17: SciPy 2016 Sprints
We look forward to an exciting conference and hope to see you in Austin in
July!
The Scipy 2016
http://scipy2016.scipy.org/
Conference Chairs: Aric Hagberg, Prabhu Ramachandran
Tutorial Chairs: Justin Vincent, Ben Root
Program Chair: Serge Rey, Nelle Varoquaux
Proceeding Chairs: Sebastian Benthall

Hi Matplotlib users,
We are using Matplotlib for a web service which makes PNG images on the fly
for presentation on a map (web site using the web service is here:
https://ifm-beta.fcoo.dk)
Performance and image size are two major concerns for us. We therefore save
the resulting RGBA PNG to a buffer and afterwards use Pillow (PIL) to
convert it to a P PNG (paletted PNG) to reduce the image size dramatically.
This procedure does however use a significant amount of our total
processing time per image. I would therefore be interested in extending
e.g. the AGG backend to produce paletted PNGs directly. I am of course
aware that this might not be useful for many others since one would have to
provide some extra information when rendering with this backend (possibly
output palette and quantizing method). But on the other hand it might be
useful for others doing web services using matplotlib.
My questions are:
1) Is it possible to extend the AGG backend for this and how?
2) Is it better to make a separate Pillow based backend for this (Pillow is
probably not as fast as AGG)?
Best regards,
Jesper

<html>
 <head>
 <meta http-equiv="content-type" content="text/html; charset=utf-8">
 </head>
 <body text="#000000" bgcolor="#FFFFFF">
 Hello all,<br>
 <br>
 I'm trying to use the shadedrelief() method to paint the background
 of a scatter plot, but it fails. The lines below are a minimal
 working example:<br>
 <br>
 <tt>In [1]: from mpl_toolkits.basemap import Basemap</tt><tt><br>
 </tt><tt>In [2]: world_map = Basemap(projection='cyl',
 llcrnrlat=-70., urcrnrlat=85., llcrnrlon=-180., urcrnrlon=180.,
 resolution='l')</tt><tt><br>
 </tt><tt>In [3]: world_map.shadedrelief()</tt><tt><br>
 </tt><tt>---------------------------------------------------------------------------</tt><tt><br>
 </tt><tt>IndexError                Traceback (most
 recent call last)</tt><tt><br>
 </tt><tt>&lt;ipython-input-3-2f6045a33141&gt; in &lt;module&gt;()</tt><tt><br>
 </tt><tt>----&gt; 1 world_map.shadedrelief()</tt><tt><br>
 </tt><tt><br>
 </tt><tt>/usr/local/lib/python2.7/dist-packages/mpl_toolkits/basemap/__init__.pyc
 in shadedrelief(self, ax, scale, **kwargs)</tt><tt><br>
 </tt><tt>  3997       return
 self.warpimage(image='shadedrelief',ax=ax,scale=scale,**kwargs)</tt><tt><br>
 </tt><tt>  3998     else:</tt><tt><br>
 </tt><tt>-&gt; 3999       return
 self.warpimage(image='shadedrelief',scale=scale,**kwargs)</tt><tt><br>
 </tt><tt>  4000 </tt><tt><br>
 </tt><tt>  4001   def etopo(self,ax=None,scale=None,**kwargs):</tt><tt><br>
 </tt><tt><br>
 </tt><tt>/usr/local/lib/python2.7/dist-packages/mpl_toolkits/basemap/__init__.pyc
 in warpimage(self, image, scale, **kwargs)</tt><tt><br>
 </tt><tt>  4115         # any range of longitudes may be
 plotted on a world map.</tt><tt><br>
 </tt><tt>  4116         self._bm_lons = \</tt><tt><br>
 </tt><tt>-&gt; 4117        
 np.concatenate((self._bm_lons,self._bm_lons+360),1)</tt><tt><br>
 </tt><tt>  4118         self._bm_rgba = \</tt><tt><br>
 </tt><tt>  4119        
 np.concatenate((self._bm_rgba,self._bm_rgba),1)</tt><tt><br>
 </tt><tt><br>
 </tt><tt>IndexError: axis 1 out of bounds [0, 1)</tt><br>
 <br>
 Anyone seen this error before? I'm using python 2.7.6, numpy 1.10.4,
 matplotlib 1.5.1 and basemap 1.0.7. The latter three were downloaded
 as source archives and installed using 'python setup.py install'.<br>
 <br>
 Thanks,<br>
 Sourish<br>
 <br>
 <div class="moz-signature">-- <br>
 <b>Q:</b> What if you strapped C4 to a boomerang? Could this be an
 effective weapon, or would it be as stupid as it sounds?<br>
 <b>A:</b> Aerodynamics aside, I’m curious what tactical advantage
 you’re expecting to gain by having the high explosive fly back at
 you if it misses the target.<br>
 </div>
 </body>
</html>

Thanks for your suggestion Oscar. I tried editing the ticks like this, but
this method removes both the tick marks and the labels.
I think I have found a decent solution. Unfortunately my solution required
a very particular order of operations. It is much less convenient than the
functions provided in the API like tick_params(), which don't care if you
have run plt.draw() ahead of time...
1) Run all of the setup for the plot and also the plotting commands
(ax.plot(), ax.hist()...whatever)
2) Run `plt.draw()` because this updates the tick objects contained in
your axes.
3) Grab your Tick objects: `ticks = ax.[x/y]axis.[major/minor]Ticks`
4) For each tick you want to hide do:
 `tick.tick1On = False`
 `tick.tick2On = False`
The `1` and `2` refer to the bottom, top (left, right) for the x (y) axis
respectively.
5) Run plt.show(), fig.show() or fig.savefig or whatever else you are using.
Ahhhhh, no messy ticks in the corner!
Julian
On Fri, Jan 29, 2016 at 10:49 AM, Oscar Benjamin <osc...@gm...
> wrote:
> On 28 January 2016 at 19:49, Julian Irwin <jul...@gm...> wrote:
> >
> >
> > I am looking for a way to hide tick marks (not the labels!) that
> coincide with axis lines. I think this is a problem for me because of the
> relative line thicknesses of my axis lines and tick marks, but I want to
> leave those thicknesses unchanged (I like the look of the thickness
> settings I am using now).
>
> Try this:
>
> from matplotlib import pyplot as plt
> fig = plt.figure()
> ax = fig.add_subplot(1, 1, 1)
> ax.plot([0, 1], [0, 1])
> print(ax.get_xticks())
> ax.set_xticks(ax.get_xticks()[1:-1]) # Remove first and last ticks
> print(ax.get_xticks())
>
> --
> Oscar
>

You've already done it. But we encourage you to take a crack at it. I would
suggest just first factoring it out into a new file
lib/matplotlib/hexbin.py and have the current function utilize it. When
that is done, we can look to getting it into numpy as well. We will need a
copy of it ourselves for compatibility with older releases of numpy.
Let us know if you have questions!
Ben Root
On Jan 30, 2016 8:45 PM, "Sebastian" <se...@gm...> wrote:
> Ahhhh thats too bad (that we can't recover the original ids.)
> What could one (as user) do to officially request it be fixed/factored out
> to numpy?
>
>
>
> On Fri, Jan 29, 2016 at 7:30 PM, Thomas Caswell <tca...@gm...>
> wrote:
>
>> Factor it out and give it to numpy!
>>
>> On Fri, Jan 29, 2016, 17:27 Benjamin Root <ben...@gm...> wrote:
>>
>>> Hmm, you are right, there is no way to get back the information that
>>> hexbin computed. The hexbin function is massive (in
>>> lib/matplotlib/axes/_axes.py) and is a bit tangled up with the
>>> artist-handling code, too. I think it would make sense to factor out the
>>> hexbinning component into its own hexbin.py that others might be able to
>>> use separately.
>>>
>>> Ben Root
>>>
>>>
>>> On Fri, Jan 29, 2016 at 5:15 PM, Sebastian <se...@gm...> wrote:
>>>
>>>> Is there a simple way to hexbin using "pyplot.hexbin" and to return
>>>> the ids of the set of
>>>> points in each hexbin? That is to output an array of n elements
>>>> (one for each hexbin), and each element itself an array with the point
>>>> ids? The sum
>>>> of the number of inner elements would be equal the sum of all points
>>>> (x,y).
>>>>
>>>> Is hexbin missing this simple feature?
>>>>
>>>> Or perhaps specifying C=N.arange(len(x)) then some specific
>>>> "reduced_C_function"
>>>> to return those elements. But I don't know if there is a
>>>> "reduced_C_function" available,
>>>> or perhaps one could be added?
>>>>
>>>> many thanks in advance...
>>>>
>>>> link:
>>>> http://stackoverflow
>>>> .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the-
>>>> hexbin-reduce-c-function/35088073#35088073
>>>>
>>>>
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>> Site24x7 APM Insight: Get Deep Visibility into Application Performance
>>>> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
>>>> Monitor end-to-end web transactions and take corrective actions now
>>>> Troubleshoot faster and improve end-user experience. Signup Now!
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>>>> _______________________________________________
>>>> Matplotlib-users mailing list
>>>> Mat...@li...
>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>
>>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Site24x7 APM Insight: Get Deep Visibility into Application Performance
>>> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
>>> Monitor end-to-end web transactions and take corrective actions now
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>>> _______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>
>

Ahhhh thats too bad (that we can't recover the original ids.)
What could one (as user) do to officially request it be fixed/factored out
to numpy?
On Fri, Jan 29, 2016 at 7:30 PM, Thomas Caswell <tca...@gm...> wrote:
> Factor it out and give it to numpy!
>
> On Fri, Jan 29, 2016, 17:27 Benjamin Root <ben...@gm...> wrote:
>
>> Hmm, you are right, there is no way to get back the information that
>> hexbin computed. The hexbin function is massive (in
>> lib/matplotlib/axes/_axes.py) and is a bit tangled up with the
>> artist-handling code, too. I think it would make sense to factor out the
>> hexbinning component into its own hexbin.py that others might be able to
>> use separately.
>>
>> Ben Root
>>
>>
>> On Fri, Jan 29, 2016 at 5:15 PM, Sebastian <se...@gm...> wrote:
>>
>>> Is there a simple way to hexbin using "pyplot.hexbin" and to return the
>>> ids of the set of
>>> points in each hexbin? That is to output an array of n elements
>>> (one for each hexbin), and each element itself an array with the point
>>> ids? The sum
>>> of the number of inner elements would be equal the sum of all points
>>> (x,y).
>>>
>>> Is hexbin missing this simple feature?
>>>
>>> Or perhaps specifying C=N.arange(len(x)) then some specific
>>> "reduced_C_function"
>>> to return those elements. But I don't know if there is a
>>> "reduced_C_function" available,
>>> or perhaps one could be added?
>>>
>>> many thanks in advance...
>>>
>>> link:
>>> http://stackoverflow
>>> .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the-
>>> hexbin-reduce-c-function/35088073#35088073
>>>
>>>
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Site24x7 APM Insight: Get Deep Visibility into Application Performance
>>> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
>>> Monitor end-to-end web transactions and take corrective actions now
>>> Troubleshoot faster and improve end-user experience. Signup Now!
>>> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
>>> _______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>>
>>
>> ------------------------------------------------------------------------------
>> Site24x7 APM Insight: Get Deep Visibility into Application Performance
>> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
>> Monitor end-to-end web transactions and take corrective actions now
>> Troubleshoot faster and improve end-user experience. Signup Now!
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>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>

On Fri, Jan 29, 2016 at 8:25 AM, Andreas Mueller <t3...@gm...> wrote:
> Thanks for your input Fernando.
> I thought about cross-posting to Jupyter, but I'm glad you also saw it
> here :)
> That would help, but not solve all problems.
> I guess the Figure could hold a tag for referencing, too. It would be nice
> to get a tag and caption from matplotlib.
> Maybe Benjamin's reply would help with that. But it sounds like the figure
> has a single string attached (which is more the tag).
> I guess I can do
> IPython.display.Figure(matplotlib_figure, caption="stuff", tag="tag")
> That would be acceptable, I think.
>
Yes, I'd forgotten about the label ("label" is the LaTeX name for what
you're calling "tag" here).
> But how do I reference that in a markup cell? [maybe I should move that
> question to the jupyter list, though]
>
Yup, this is the slightly trickier part. A sketch of the solution, we need
to:
- generate a local anchor element for the labeled output. That's the
easier part, it would be the job of the displayed output from this
hypothetical Figure() object.
It needs to wrap the output in `<a name=label>... </a>`.
- For markdown referencing, you simply do [link text](#label).
- The problem would be latex conversion: by default, the above is converted
to
\protect\hyperlink{label}{link text}
where as you want a \ref{label} call instead.
- You also want this to generate the
Internal cross-referencing is one of Markdown's main weaknesses for complex
more document-oriented workflows that aren't purely HTML oriented.
Markdown is really a thin wrapper around HTML, so it doesn't expose the
rich labeling/referencing semantics of rST or LaTeX.
I didn't say this was a done deal, and there might be some tricky edges to
it :)
Cheers
f
-- 
Fernando Perez (@fperez_org; http://fperez.org)
fperez.net-at-gmail: mailing lists only (I ignore this when swamped!)
fernando.perez-at-berkeley: contact me here for any direct mail

Factor it out and give it to numpy!
On Fri, Jan 29, 2016, 17:27 Benjamin Root <ben...@gm...> wrote:
> Hmm, you are right, there is no way to get back the information that
> hexbin computed. The hexbin function is massive (in
> lib/matplotlib/axes/_axes.py) and is a bit tangled up with the
> artist-handling code, too. I think it would make sense to factor out the
> hexbinning component into its own hexbin.py that others might be able to
> use separately.
>
> Ben Root
>
>
> On Fri, Jan 29, 2016 at 5:15 PM, Sebastian <se...@gm...> wrote:
>
>> Is there a simple way to hexbin using "pyplot.hexbin" and to return the
>> ids of the set of
>> points in each hexbin? That is to output an array of n elements
>> (one for each hexbin), and each element itself an array with the point
>> ids? The sum
>> of the number of inner elements would be equal the sum of all points
>> (x,y).
>>
>> Is hexbin missing this simple feature?
>>
>> Or perhaps specifying C=N.arange(len(x)) then some specific
>> "reduced_C_function"
>> to return those elements. But I don't know if there is a
>> "reduced_C_function" available,
>> or perhaps one could be added?
>>
>> many thanks in advance...
>>
>> link:
>> http://stackoverflow
>> .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the-
>> hexbin-reduce-c-function/35088073#35088073
>>
>>
>>
>>
>> ------------------------------------------------------------------------------
>> Site24x7 APM Insight: Get Deep Visibility into Application Performance
>> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
>> Monitor end-to-end web transactions and take corrective actions now
>> Troubleshoot faster and improve end-user experience. Signup Now!
>> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
> Monitor end-to-end web transactions and take corrective actions now
> Troubleshoot faster and improve end-user experience. Signup Now!
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> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hmm, you are right, there is no way to get back the information that hexbin
computed. The hexbin function is massive (in lib/matplotlib/axes/_axes.py)
and is a bit tangled up with the artist-handling code, too. I think it
would make sense to factor out the hexbinning component into its own
hexbin.py that others might be able to use separately.
Ben Root
On Fri, Jan 29, 2016 at 5:15 PM, Sebastian <se...@gm...> wrote:
> Is there a simple way to hexbin using "pyplot.hexbin" and to return the
> ids of the set of
> points in each hexbin? That is to output an array of n elements
> (one for each hexbin), and each element itself an array with the point
> ids? The sum
> of the number of inner elements would be equal the sum of all points (x,y).
>
> Is hexbin missing this simple feature?
>
> Or perhaps specifying C=N.arange(len(x)) then some specific
> "reduced_C_function"
> to return those elements. But I don't know if there is a
> "reduced_C_function" available,
> or perhaps one could be added?
>
> many thanks in advance...
>
> link:
> http://stackoverflow
> .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the-
> hexbin-reduce-c-function/35088073#35088073
>
>
>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
> Monitor end-to-end web transactions and take corrective actions now
> Troubleshoot faster and improve end-user experience. Signup Now!
> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Is there a simple way to hexbin using "pyplot.hexbin" and to return the ids
of the set of
points in each hexbin? That is to output an array of n elements
(one for each hexbin), and each element itself an array with the point ids?
The sum
of the number of inner elements would be equal the sum of all points (x,y).
Is hexbin missing this simple feature?
Or perhaps specifying C=N.arange(len(x)) then some specific
"reduced_C_function"
to return those elements. But I don't know if there is a
"reduced_C_function" available,
or perhaps one could be added?
many thanks in advance...
link:
http://stackoverflow
.com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the-
hexbin-reduce-c-function/35088073#35088073

On 28 January 2016 at 19:49, Julian Irwin <jul...@gm...> wrote:
>
>
> I am looking for a way to hide tick marks (not the labels!) that coincide with axis lines. I think this is a problem for me because of the relative line thicknesses of my axis lines and tick marks, but I want to leave those thicknesses unchanged (I like the look of the thickness settings I am using now).
Try this:
from matplotlib import pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot([0, 1], [0, 1])
print(ax.get_xticks())
ax.set_xticks(ax.get_xticks()[1:-1]) # Remove first and last ticks
print(ax.get_xticks())
--
Oscar

Thanks for your input Fernando.
I thought about cross-posting to Jupyter, but I'm glad you also saw it 
here :)
That would help, but not solve all problems.
I guess the Figure could hold a tag for referencing, too. It would be 
nice to get a tag and caption from matplotlib.
Maybe Benjamin's reply would help with that. But it sounds like the 
figure has a single string attached (which is more the tag).
I guess I can do
IPython.display.Figure(matplotlib_figure, caption="stuff", tag="tag")
That would be acceptable, I think.
But how do I reference that in a markup cell? [maybe I should move that 
question to the jupyter list, though]
On 01/28/2016 10:17 PM, Fernando Perez wrote:
> On Thu, Jan 28, 2016 at 3:23 PM, Andreas Mueller <t3...@gm... 
> <mailto:t3...@gm...>> wrote:
>
> Hi all.
>
> This is about a joint jupyter-notebook / matplotlib problem I've been
> thinking about.
> So I'm writing a book using jupyter-notebook, and all my figures are
> generated using matplotlib.
>
> In books, there is usually a figure caption with a running number and
> some description.
> From what I read, the best way to add captions is just using
> plt.text.
> However, the caption should probably be in the markup,
> not in a rendered PNG. I'm not sure if changing the backend might
> help,
> but that probably doesn't make the notebook happy?
>
> The other problem is that I want to have running numbers that I can
> refer to by a tag (as you would in latex).
> That is more of a notebook problem, though.
>
> Any feedback would be very welcome
>
>
> I've been wanting to do something about this problem for a while, but 
> haven't had the cycles to work on it... Here's my current idea, 
> perhaps I can goad you into implementing it :)
>
> I think that IPython.display should provide a Figure object, capable 
> of wrapping any input image (with nice code to automatically swallow a 
> matplotlib figure without asking the user to convert it to an image 
> first), and taking an optional caption.
>
> Figure() would then produce as output the displayed image but with a 
> bit of nice CSS to center it on the page, along with the caption.
>
> The trick is to send the entire data bundle correctly structured so 
> that, at the other end, nbconvert could recognize these figures as 
> such, and not only produce nice HTML, but more importantly, push them 
> into the LaTeX output with the correct call to \figure, including 
> \caption as well as size and placement specifiers.
>
> The signature of Figure() might be something like
>
> def Figure(fig, caption=None, width=None, height=None,
> latex_placement=None):
>
>
> I would try implementing this first as a standalone tool, and once 
> it's been tested enough in real-world usage with both HTML and LaTeX 
> output from nbconvert, it could be merged in. I suspect it's going to 
> take a few iterations to get it right.
>
> But it's not particularly hard, and someone working on a book would be 
> the perfect candidate to have enough test cases to be able to iterate 
> until happy ;)
>
> If you think you want to take a stab at this, don't hesitate to ping 
> us on the jupyter list. We can help with some of the more obscure 
> parts of getting this to work on nbconvert (and there may be things 
> I've overlooked in the sketch above).
>
> Cheers,
>
> f
>
> -- 
> Fernando Perez (@fperez_org; http://fperez.org)
> fperez.net-at-gmail: mailing lists only (I ignore this when swamped!)
> fernando.perez-at-berkeley: contact me here for any direct mail

In mpl, our figure objects get numbers assigned to them by default, but
they can also be strings. These labels are used in the figure window title
bar. Perhaps that existing data could be hijacked? Admittedly, most people
use the string name to give nice short names to their figures, so maybe
those names could be the "tag" name in latex? So, all we would need is some
way to supply the actual caption string.
Ben Root
On Thu, Jan 28, 2016 at 10:17 PM, Fernando Perez <fpe...@gm...>
wrote:
> On Thu, Jan 28, 2016 at 3:23 PM, Andreas Mueller <t3...@gm...> wrote:
>
>> Hi all.
>>
>> This is about a joint jupyter-notebook / matplotlib problem I've been
>> thinking about.
>> So I'm writing a book using jupyter-notebook, and all my figures are
>> generated using matplotlib.
>>
>> In books, there is usually a figure caption with a running number and
>> some description.
>> From what I read, the best way to add captions is just using plt.text.
>> However, the caption should probably be in the markup,
>> not in a rendered PNG. I'm not sure if changing the backend might help,
>> but that probably doesn't make the notebook happy?
>>
>> The other problem is that I want to have running numbers that I can
>> refer to by a tag (as you would in latex).
>> That is more of a notebook problem, though.
>>
>> Any feedback would be very welcome
>>
>
> I've been wanting to do something about this problem for a while, but
> haven't had the cycles to work on it... Here's my current idea, perhaps I
> can goad you into implementing it :)
>
> I think that IPython.display should provide a Figure object, capable of
> wrapping any input image (with nice code to automatically swallow a
> matplotlib figure without asking the user to convert it to an image first),
> and taking an optional caption.
>
> Figure() would then produce as output the displayed image but with a bit
> of nice CSS to center it on the page, along with the caption.
>
> The trick is to send the entire data bundle correctly structured so that,
> at the other end, nbconvert could recognize these figures as such, and not
> only produce nice HTML, but more importantly, push them into the LaTeX
> output with the correct call to \figure, including \caption as well as size
> and placement specifiers.
>
> The signature of Figure() might be something like
>
> def Figure(fig, caption=None, width=None, height=None,
> latex_placement=None):
>
>
> I would try implementing this first as a standalone tool, and once it's
> been tested enough in real-world usage with both HTML and LaTeX output from
> nbconvert, it could be merged in. I suspect it's going to take a few
> iterations to get it right.
>
> But it's not particularly hard, and someone working on a book would be the
> perfect candidate to have enough test cases to be able to iterate until
> happy ;)
>
> If you think you want to take a stab at this, don't hesitate to ping us on
> the jupyter list. We can help with some of the more obscure parts of
> getting this to work on nbconvert (and there may be things I've overlooked
> in the sketch above).
>
> Cheers,
>
> f
>
> --
> Fernando Perez (@fperez_org; http://fperez.org)
> fperez.net-at-gmail: mailing lists only (I ignore this when swamped!)
> fernando.perez-at-berkeley: contact me here for any direct mail
>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
> Monitor end-to-end web transactions and take corrective actions now
> Troubleshoot faster and improve end-user experience. Signup Now!
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> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

On Thu, Jan 28, 2016 at 3:23 PM, Andreas Mueller <t3...@gm...> wrote:
> Hi all.
>
> This is about a joint jupyter-notebook / matplotlib problem I've been
> thinking about.
> So I'm writing a book using jupyter-notebook, and all my figures are
> generated using matplotlib.
>
> In books, there is usually a figure caption with a running number and
> some description.
> From what I read, the best way to add captions is just using plt.text.
> However, the caption should probably be in the markup,
> not in a rendered PNG. I'm not sure if changing the backend might help,
> but that probably doesn't make the notebook happy?
>
> The other problem is that I want to have running numbers that I can
> refer to by a tag (as you would in latex).
> That is more of a notebook problem, though.
>
> Any feedback would be very welcome
>
I've been wanting to do something about this problem for a while, but
haven't had the cycles to work on it... Here's my current idea, perhaps I
can goad you into implementing it :)
I think that IPython.display should provide a Figure object, capable of
wrapping any input image (with nice code to automatically swallow a
matplotlib figure without asking the user to convert it to an image first),
and taking an optional caption.
Figure() would then produce as output the displayed image but with a bit of
nice CSS to center it on the page, along with the caption.
The trick is to send the entire data bundle correctly structured so that,
at the other end, nbconvert could recognize these figures as such, and not
only produce nice HTML, but more importantly, push them into the LaTeX
output with the correct call to \figure, including \caption as well as size
and placement specifiers.
The signature of Figure() might be something like
def Figure(fig, caption=None, width=None, height=None,
 latex_placement=None):
I would try implementing this first as a standalone tool, and once it's
been tested enough in real-world usage with both HTML and LaTeX output from
nbconvert, it could be merged in. I suspect it's going to take a few
iterations to get it right.
But it's not particularly hard, and someone working on a book would be the
perfect candidate to have enough test cases to be able to iterate until
happy ;)
If you think you want to take a stab at this, don't hesitate to ping us on
the jupyter list. We can help with some of the more obscure parts of
getting this to work on nbconvert (and there may be things I've overlooked
in the sketch above).
Cheers,
f
-- 
Fernando Perez (@fperez_org; http://fperez.org)
fperez.net-at-gmail: mailing lists only (I ignore this when swamped!)
fernando.perez-at-berkeley: contact me here for any direct mail

Hi all.
This is about a joint jupyter-notebook / matplotlib problem I've been 
thinking about.
So I'm writing a book using jupyter-notebook, and all my figures are 
generated using matplotlib.
In books, there is usually a figure caption with a running number and 
some description.
 From what I read, the best way to add captions is just using plt.text. 
However, the caption should probably be in the markup,
not in a rendered PNG. I'm not sure if changing the backend might help, 
but that probably doesn't make the notebook happy?
The other problem is that I want to have running numbers that I can 
refer to by a tag (as you would in latex).
That is more of a notebook problem, though.
Any feedback would be very welcome.
Cheers,
Andy

Hello,
I am looking for a way to hide tick marks (not the labels!) that coincide
with axis lines. I think this is a problem for me because of the relative
line thicknesses of my axis lines and tick marks, but I want to leave those
thicknesses unchanged (I like the look of the thickness settings I am using
now).
Here is a screenshot of what I'm talking about:
[image: Inline image 1]
I know this looks minor, but it is quite obvious on some plots and I'd
really like to get rid of it.
Thanks,
Julian Irwin

Le mercredi 27 janvier 2016, Matteo Niccoli a écrit :
> Can something like this (which by the way I can't get to work):
> http://stackoverflow.com/questions/3114925/pil-convert-rgb-image-to-a
> -specific-8-bit-palette
> 
> What I would like to do is this:
> 1) Import an RGB image, which would have its own colormap - say this
> one for example:
> https://upload.wikimedia.org/wikipedia/commons/b/b3/Jupiter_new_hubble_view_above_pole.png
> 2) convert it to intensity, display the intensity color-mapped to the
> same colours the original RGB had.
According to the PNG header, this image does not have a palette (i.e. a
list of colors). The data chunks define the image as an array of NxMx3
values (N rows, M cols, 3 channels=no alpha), each value being defined
using 8 bits. I may however badly understand what you call the "own
colormap"...
You still can convert it to a grayscale img representing the intensity
(NxM values), but you then lose some information and you cannot display
it back with the same colors as originally. Because some different RGB
tuple are converted into the same intensity level, you can then not
discriminate them using the intensity image only.
Maybe there is some trick to convert to a grayscale image where those
RGB values are converted to almost-equal-but-different intensity levels
that would enable the later reconstruction, but I am not aware of...
Fabrice

You might have better luck asking the scikit-image people, or the Pillow
people. ImageMagick might also have what you are looking for.
Cheers!
Ben Root
On Wed, Jan 27, 2016 at 11:23 PM, Matteo Niccoli <ma...@my...> wrote:
> Can something like this (which by the way I can't get to work):
>
> http://stackoverflow.com/questions/3114925/pil-convert-rgb-image-to-a-specific-8-bit-palette
>
> What I would like to do is this:
> 1) Import an RGB image, which would have its own colormap - say this one
> for example:
>
> https://upload.wikimedia.org/wikipedia/commons/b/b3/Jupiter_new_hubble_view_above_pole.png
>
> 2) convert it to intensity, display the intensity color-mapped to the same
> colours the original RGB had.
>
> Any tips, or even better code or pseudocode would be greatly appreciated.
>
> Thanks
> Matteo
>
>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
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> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Can something like this (which by the way I can't get to work):
http://stackoverflow.com/questions/3114925/pil-convert-rgb-image-to-a-specific-8-bit-palette
What I would like to do is this:
1) Import an RGB image, which would have its own colormap - say this one
for example:
https://upload.wikimedia.org/wikipedia/commons/b/b3/Jupiter_new_hubble_view_above_pole.png
2) convert it to intensity, display the intensity color-mapped to the same
colours the original RGB had.
Any tips, or even better code or pseudocode would be greatly appreciated.
Thanks
Matteo

Add "blit=False" in the instantiation for multicursor to get around the
copy_from_bbox issue.
I wonder if the use of fig.axes might be a problem?
On Jan 20, 2016 2:27 PM, "Bilheux, Jean-Christophe" <bil...@or...>
wrote:
> HI all,
>
> I wanted to help (for a change) but running the script on mac (with the
> multi cursor code commented out), I got the following error. If anyone can
> figure out why !
>
> File
> "/Users/j35/anaconda/lib/python3.4/site-packages/matplotlib/widgets.py",
> line 1046, in clear
> self.canvas.copy_from_bbox(self.canvas.figure.bbox))
> AttributeError: 'FigureCanvasMac' object has no attribute ‘copy_from_bbox'
>
> I’m using python 3.4 and matplotlib 1.4.3
>
> Thanks
>
> Jean
>
>
>
> > On Jan 20, 2016, at 1:26 PM, Michael Kaufman <kau...@or...> wrote:
> >
> > Hi Gurus:
> >
> > I'm having a serious problem with MultiCursor and autoscaling...
> >
> > If I do the code below with both MultiCursor instantiations commented
> out, then all plots are xscaled to [50,55] and yscaled to each plot's
> appropriate ylimits.
> >
> > If I uncomment the top MultiCursor instantiation, then both the xlimits
> and ylimits are screwed up: xlim=[0,60] and ylim is all over the place,
> certainly not autoscaled tight.
> >
> > If I uncomment the bottom MultiCursor instantiation, then the xlimit
> appears to be scaled correctly, [50,55], but two of the four plots (lower
> left and upper right) are not autoscaled in y.
> >
> > How to I instantiate MultiCursor to get the normal and expected
> autoscaling behavior?
> >
> > Not that it should matter, but I'm using here Tk and Python3 with MPL
> 1.5dev1 (91ca2a3724ae91d28d97)
> >
> > Thanks for any help,
> >
> > M
> >
> > =============
> >
> > from matplotlib import pyplot as pl
> > from matplotlib.widgets import MultiCursor
> > from matplotlib import gridspec
> > import numpy as np
> >
> > if __name__ == "__main__":
> >
> > fig = pl.gcf()
> > gs = gridspec.GridSpec(2,2)
> >
> > ax = None
> > for g in gs:
> > ax = pl.subplot(g, sharex=ax)
> >
> > #multi = MultiCursor(fig.canvas, tuple(fig.axes),
> > # useblit=True, horizOn=True, color='k', lw=1)
> >
> > x = np.arange(50,55,0.01)
> > y1 = np.sin(x)
> > y2 = np.cos(x) + 4
> > y3 = 0.2*np.cos(x) - 4
> > y4 = np.cos(2*x) - 1
> >
> > for ax,y in zip(fig.axes, [y1,y2,y3,y4]):
> > ax.plot(x,y)
> >
> > for ax in fig.axes:
> > ax.grid()
> >
> > #multi = MultiCursor(fig.canvas, tuple(fig.axes),
> > # useblit=True, horizOn=True, color='k', lw=1)
> >
> > pl.draw()
> > pl.show()
> >
> <multicursor_limtest.py>------------------------------------------------------------------------------
> > Site24x7 APM Insight: Get Deep Visibility into Application Performance
> > APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
> > Monitor end-to-end web transactions and take corrective actions now
> > Troubleshoot faster and improve end-user experience. Signup Now!
> >
> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140_______________________________________________
> > Matplotlib-users mailing list
> > Mat...@li...
> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
> Monitor end-to-end web transactions and take corrective actions now
> Troubleshoot faster and improve end-user experience. Signup Now!
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> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

HI all,
I wanted to help (for a change) but running the script on mac (with the multi cursor code commented out), I got the following error. If anyone can figure out why !
File "/Users/j35/anaconda/lib/python3.4/site-packages/matplotlib/widgets.py", line 1046, in clear
 self.canvas.copy_from_bbox(self.canvas.figure.bbox))
AttributeError: 'FigureCanvasMac' object has no attribute ‘copy_from_bbox'
I’m using python 3.4 and matplotlib 1.4.3
Thanks
Jean
> On Jan 20, 2016, at 1:26 PM, Michael Kaufman <kau...@or...> wrote:
> 
> Hi Gurus:
> 
> I'm having a serious problem with MultiCursor and autoscaling...
> 
> If I do the code below with both MultiCursor instantiations commented out, then all plots are xscaled to [50,55] and yscaled to each plot's appropriate ylimits.
> 
> If I uncomment the top MultiCursor instantiation, then both the xlimits and ylimits are screwed up: xlim=[0,60] and ylim is all over the place, certainly not autoscaled tight.
> 
> If I uncomment the bottom MultiCursor instantiation, then the xlimit appears to be scaled correctly, [50,55], but two of the four plots (lower left and upper right) are not autoscaled in y.
> 
> How to I instantiate MultiCursor to get the normal and expected autoscaling behavior?
> 
> Not that it should matter, but I'm using here Tk and Python3 with MPL 1.5dev1 (91ca2a3724ae91d28d97)
> 
> Thanks for any help,
> 
> M
> 
> =============
> 
> from matplotlib import pyplot as pl
> from matplotlib.widgets import MultiCursor
> from matplotlib import gridspec
> import numpy as np
> 
> if __name__ == "__main__":
> 
> fig = pl.gcf()
> gs = gridspec.GridSpec(2,2)
> 
> ax = None
> for g in gs:
> ax = pl.subplot(g, sharex=ax)
> 
> #multi = MultiCursor(fig.canvas, tuple(fig.axes),
> # useblit=True, horizOn=True, color='k', lw=1)
> 
> x = np.arange(50,55,0.01)
> y1 = np.sin(x)
> y2 = np.cos(x) + 4
> y3 = 0.2*np.cos(x) - 4
> y4 = np.cos(2*x) - 1
> 
> for ax,y in zip(fig.axes, [y1,y2,y3,y4]):
> ax.plot(x,y)
> 
> for ax in fig.axes:
> ax.grid()
> 
> #multi = MultiCursor(fig.canvas, tuple(fig.axes),
> # useblit=True, horizOn=True, color='k', lw=1)
> 
> pl.draw()
> pl.show()
> <multicursor_limtest.py>------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
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> Troubleshoot faster and improve end-user experience. Signup Now!
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> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Hi Gurus:
I'm having a serious problem with MultiCursor and autoscaling...
If I do the code below with both MultiCursor instantiations commented 
out, then all plots are xscaled to [50,55] and yscaled to each plot's 
appropriate ylimits.
If I uncomment the top MultiCursor instantiation, then both the xlimits 
and ylimits are screwed up: xlim=[0,60] and ylim is all over the place, 
certainly not autoscaled tight.
If I uncomment the bottom MultiCursor instantiation, then the xlimit 
appears to be scaled correctly, [50,55], but two of the four plots 
(lower left and upper right) are not autoscaled in y.
How to I instantiate MultiCursor to get the normal and expected 
autoscaling behavior?
Not that it should matter, but I'm using here Tk and Python3 with MPL 
1.5dev1 (91ca2a3724ae91d28d97)
Thanks for any help,
M
=============
from matplotlib import pyplot as pl
from matplotlib.widgets import MultiCursor
from matplotlib import gridspec
import numpy as np
if __name__ == "__main__":
 fig = pl.gcf()
 gs = gridspec.GridSpec(2,2)
 ax = None
 for g in gs:
 ax = pl.subplot(g, sharex=ax)
 #multi = MultiCursor(fig.canvas, tuple(fig.axes),
 # useblit=True, horizOn=True, color='k', lw=1)
 x = np.arange(50,55,0.01)
 y1 = np.sin(x)
 y2 = np.cos(x) + 4
 y3 = 0.2*np.cos(x) - 4
 y4 = np.cos(2*x) - 1
 for ax,y in zip(fig.axes, [y1,y2,y3,y4]):
 ax.plot(x,y)
 for ax in fig.axes:
 ax.grid()
 #multi = MultiCursor(fig.canvas, tuple(fig.axes),
 # useblit=True, horizOn=True, color='k', lw=1)
 pl.draw()
 pl.show()

Dear experts,
I tried to use the matplotlib function plt.xcorr for calculating cross correlation between to check its 
functionality using the data from a standard example given in R web site example.
https://onlinecourses.science.psu.edu/stat510/node/74
However when the example given above is replicated using python I get a totally different graph.
Any idea why this happens?
I tried normed=True but do not appears to have any effect. Any advice on this will be of extreme help
import urllib as web
from matplotlib import pylab as plt
f=web.urlopen('http://anson.ucdavis.edu/~shumway/soi.dat')
soi=[]
for line in f: soi.append(float(line.strip()))
f.close()
rec=[]
f=web.urlopen('http://anson.ucdavis.edu/~shumway/recruit.dat')
for line in f: rec.append(float(line.strip()))
ax=plt.figure()
anl_ccf=plt.xcorr(soi,rec,maxlags=30)
plt.show()
With best regards,
Sudheer