matplotlib-users Mailing List for matplotlib

On 2014年06月12日, 6:07 AM, M.Rule wrote:
> Hi all,
>
> I haven't been able to find a more official place to report potential
> Matplotlib bugs, so I'm going to describe the issue I'm seeing here.
> Sorry if this is the wrong forum.
This is *exactly* the right place to make a report like this. It is 
better to start with a message to a wide audience (at least, we hope it 
is a wide audience) such as this list, or maybe stack overflow, to see 
if someone else recognizes the problem. In many cases, it is not a 
matplotlib bug. If the response to an email like this does not lead to 
a solution, and the consensus is that it looks like you have hit a real 
bug, *then* file an issue on github.
>
> On my system, it takes matplotlib a very very long time to close plots.
> Sometimes, up to 20 minutes to close a simple figure. Creating new
> figures remains fast. The problem seems to occur only when I've loaded a
> large amount of data in to python ( on the order of 1GB ). I am using
> the current version of Ubuntu and running "ipython --pylab". To
> reproduce on my system, it is sufficient to load a large amount of data,
> create a plot.. any plot, and then try to close it using the little "x"
> at the top right corner of the window. The whole session will freeze for
> an extended period of time. The plot does not have to be complex: a
> hundred datapoints, a thousand, it makes no difference. Since the
> problem only occurs when a large amount of data has been loaded, my
> guess is that there is a problem with how Matplotlib/Pylab/Python is
> trying to free the memory associated with the figure?
This sounds like the problem that prompted another user to propose 
https://github.com/matplotlib/matplotlib/pull/3045, except that your 
case sounds *much* more severe.
Can you reproduce the data loading and plot generation in a script that 
does not have to be run via ipython? And if so, is it still slow?
Is the large amount of data in the form of a very large number of python 
objects? Is there something odd about the data structure--extreme 
complexity that would make garbage collection take an absurd amount of time?
Since this does sound like the problem addressed by the pull request 
("PR") noted above, please add your report (and any answers to my 
questions) as a comment on that PR.
Eric
>
> So... I just though I'd put this out there in case anyone else sees the
> same issue, or in case a developer who knows why this might be happening
> reads this. The workaround for me is... to simply wait for the figures
> to close, however long that may take, or restart the whole session.
>
> Best,
> michael.
>
>
> ------------------------------------------------------------------------------
> HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
> Find What Matters Most in Your Big Data with HPCC Systems
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>
>
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>

On 2014年06月12日, 4:14 AM, Rachana Katkam wrote:
> Hi all,
> I have an issue in upgrading my matplotlib 1.0.1 to 1.3.1
> I am using Fedora, but the command:
> Yum update python-matplotlib is not working.
> My python version is 2.7, is that an issue?
> Is there any way for upgrading matplotlib?
Updating via a linux distro generally won't bring you a new version.
Two options:
1) Install it yourself independently, typically in /usr/local/, 
compiling from source. This will involve making sure you have some 
build dependencies. Simply using "pip install matplotlib", or something 
very much like that, might work.
2) Get an entire independent python installation such as Anaconda from 
continuum.io. This provides an easy way of keeping everything up to 
date. This is what I recommend unless you really want to learn how to 
build and install software yourself, independently of installers like yum.
Eric
>
> Regards,
> Rachana K
>
>
> ------------------------------------------------------------------------------
> HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
> Find What Matters Most in Your Big Data with HPCC Systems
> Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
> Leverages Graph Analysis for Fast Processing & Easy Data Exploration
> http://p.sf.net/sfu/hpccsystems
>
>
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

On 2014年06月12日, 1:01 AM, Rachana Katkam wrote:
> Hi all,
>
> I am stuck with plotting that uses brewer2mpl.
> The following link describes my problem, please have a look at it:
>
> http://stackoverflow.com/questions/24181183/matplotlib-brewr2mpl-plotting-issue
The traceback doesn't match the code I find in mpl 1.3.1; I think you 
have hit a bug that has been fixed. I recommend upgrading. There have 
been a lot of improvements since 1.0.1.
As a workaround, you could try changing your call to "plt.grid(...)" to 
start with the positional argument True, so it would be
plt.grid(True, axis='y', color='white', linestyle='-', lw=1)
Eric
>
> Regards,
> Rachana K
>
>
>
> ------------------------------------------------------------------------------
> HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
> Find What Matters Most in Your Big Data with HPCC Systems
> Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
> Leverages Graph Analysis for Fast Processing & Easy Data Exploration
> http://p.sf.net/sfu/hpccsystems
>
>
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Well, step by step it goes.
So, I realized that for "normal" behaviour, all axeses should have same y
limit, but i need different, so there should be certain way to calculate
differente num values for aspect ratio for every axes based on ylim value.
But i hope there is more easier way to do that?
Best
On Thu, Jun 12, 2014 at 6:03 PM, Nemanja Savic <vla...@gm...> wrote:
> Hi again,
>
> I think I am very near to discover how the things work, but I need a bit
> or ur help. What I basically want is to apply the same aspect ratio to all
> Axes objects. I realized that whenevr twinx is called, a new axes is added
> in the list of axeses. So, my question is now, why when I set aspect ratio
> of 0.5 to one of the axeses, the others don't follow that?
>
> Best
>
>
> On Thu, Jun 12, 2014 at 5:44 AM, Nemanja Savic <vla...@gm...> wrote:
>
>> Hi all guys,
>>
>> I have already spent a lot of time trying to figure out how to set the
>> aspect ratio of all axeses in my plot which consists of a single subplot
>> and three y axes. Namely, i tried to set the aspect ratio of the base axes,
>> and i expect after twinx that others will inheritt that. So, what i
>> basically want is to make figure wider and thiner.
>>
>> Best regards and thanx,
>>
>> --
>> Nemanja Savić
>>
>
>
>
> --
> Nemanja Savić
>
-- 
Nemanja Savić

Hi Michael,
I don't have an answer about your bug. But the official place to report
possible bugs is github.
https://github.com/matplotlib/matplotlib/issues?state=open
Cheers,
Fra
2014年06月12日 18:07 GMT+02:00 M.Rule <mru...@gm...>:
> Hi all,
>
> I haven't been able to find a more official place to report potential
> Matplotlib bugs, so I'm going to describe the issue I'm seeing here. Sorry
> if this is the wrong forum.
>
> On my system, it takes matplotlib a very very long time to close plots.
> Sometimes, up to 20 minutes to close a simple figure. Creating new figures
> remains fast. The problem seems to occur only when I've loaded a large
> amount of data in to python ( on the order of 1GB ). I am using the current
> version of Ubuntu and running "ipython --pylab". To reproduce on my system,
> it is sufficient to load a large amount of data, create a plot.. any plot,
> and then try to close it using the little "x" at the top right corner of
> the window. The whole session will freeze for an extended period of time.
> The plot does not have to be complex: a hundred datapoints, a thousand, it
> makes no difference. Since the problem only occurs when a large amount of
> data has been loaded, my guess is that there is a problem with how
> Matplotlib/Pylab/Python is trying to free the memory associated with the
> figure?
>
> So... I just though I'd put this out there in case anyone else sees the
> same issue, or in case a developer who knows why this might be happening
> reads this. The workaround for me is... to simply wait for the figures to
> close, however long that may take, or restart the whole session.
>
> Best,
> michael.
>
>
> ------------------------------------------------------------------------------
> HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
> Find What Matters Most in Your Big Data with HPCC Systems
> Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
> Leverages Graph Analysis for Fast Processing & Easy Data Exploration
> http://p.sf.net/sfu/hpccsystems
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Hi all,
I haven't been able to find a more official place to report potential
Matplotlib bugs, so I'm going to describe the issue I'm seeing here. Sorry
if this is the wrong forum.
On my system, it takes matplotlib a very very long time to close plots.
Sometimes, up to 20 minutes to close a simple figure. Creating new figures
remains fast. The problem seems to occur only when I've loaded a large
amount of data in to python ( on the order of 1GB ). I am using the current
version of Ubuntu and running "ipython --pylab". To reproduce on my system,
it is sufficient to load a large amount of data, create a plot.. any plot,
and then try to close it using the little "x" at the top right corner of
the window. The whole session will freeze for an extended period of time.
The plot does not have to be complex: a hundred datapoints, a thousand, it
makes no difference. Since the problem only occurs when a large amount of
data has been loaded, my guess is that there is a problem with how
Matplotlib/Pylab/Python is trying to free the memory associated with the
figure?
So... I just though I'd put this out there in case anyone else sees the
same issue, or in case a developer who knows why this might be happening
reads this. The workaround for me is... to simply wait for the figures to
close, however long that may take, or restart the whole session.
Best,
michael.

Hi again,
I think I am very near to discover how the things work, but I need a bit or
ur help. What I basically want is to apply the same aspect ratio to all
Axes objects. I realized that whenevr twinx is called, a new axes is added
in the list of axeses. So, my question is now, why when I set aspect ratio
of 0.5 to one of the axeses, the others don't follow that?
Best
On Thu, Jun 12, 2014 at 5:44 AM, Nemanja Savic <vla...@gm...> wrote:
> Hi all guys,
>
> I have already spent a lot of time trying to figure out how to set the
> aspect ratio of all axeses in my plot which consists of a single subplot
> and three y axes. Namely, i tried to set the aspect ratio of the base axes,
> and i expect after twinx that others will inheritt that. So, what i
> basically want is to make figure wider and thiner.
>
> Best regards and thanx,
>
> --
> Nemanja Savić
>
-- 
Nemanja Savić

It works thanx.
On Thu, Jun 12, 2014 at 4:45 PM, Nemanja Savic <vla...@gm...> wrote:
> Thanx, I will try. By the way hiw to implement this into set_ylabel
> function? is just "text$_..." enough?
>
>
> On Thu, Jun 12, 2014 at 2:40 PM, Mike Kaufman <mc...@gm...> wrote:
>
>> use matplotlib's internal latex parsing:
>>
>> text(0.2,0.4,"text$_{\mathrm{subscript}}$")
>>
>> M
>>
>> On 6/12/14, 6:26 AM, Nemanja Savic wrote:
>> > Hi all guys,
>> >
>> > I am not able to find answer on my question: how to write subscripts
>> > using default matplotlib font?
>> >
>> > best,
>> >
>> > --
>> > Nemanja Savić
>> >
>> >
>> >
>> ------------------------------------------------------------------------------
>> > HPCC Systems Open Source Big Data Platform from LexisNexis Risk
>> Solutions
>> > Find What Matters Most in Your Big Data with HPCC Systems
>> > Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
>> > Leverages Graph Analysis for Fast Processing & Easy Data Exploration
>> > http://p.sf.net/sfu/hpccsystems
>> >
>> >
>> >
>> > _______________________________________________
>> > Matplotlib-users mailing list
>> > Mat...@li...
>> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>> >
>>
>>
>>
>> ------------------------------------------------------------------------------
>> HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
>> Find What Matters Most in Your Big Data with HPCC Systems
>> Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
>> Leverages Graph Analysis for Fast Processing & Easy Data Exploration
>> http://p.sf.net/sfu/hpccsystems
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
>
>
> --
> Nemanja Savić
>
-- 
Nemanja Savić

Thanx, I will try. By the way hiw to implement this into set_ylabel
function? is just "text$_..." enough?
On Thu, Jun 12, 2014 at 2:40 PM, Mike Kaufman <mc...@gm...> wrote:
> use matplotlib's internal latex parsing:
>
> text(0.2,0.4,"text$_{\mathrm{subscript}}$")
>
> M
>
> On 6/12/14, 6:26 AM, Nemanja Savic wrote:
> > Hi all guys,
> >
> > I am not able to find answer on my question: how to write subscripts
> > using default matplotlib font?
> >
> > best,
> >
> > --
> > Nemanja Savić
> >
> >
> >
> ------------------------------------------------------------------------------
> > HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
> > Find What Matters Most in Your Big Data with HPCC Systems
> > Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
> > Leverages Graph Analysis for Fast Processing & Easy Data Exploration
> > http://p.sf.net/sfu/hpccsystems
> >
> >
> >
> > _______________________________________________
> > Matplotlib-users mailing list
> > Mat...@li...
> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >
>
>
>
> ------------------------------------------------------------------------------
> HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
> Find What Matters Most in Your Big Data with HPCC Systems
> Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
> Leverages Graph Analysis for Fast Processing & Easy Data Exploration
> http://p.sf.net/sfu/hpccsystems
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
-- 
Nemanja Savić

Hi all,
I have an issue in upgrading my matplotlib 1.0.1 to 1.3.1
I am using Fedora, but the command:
Yum update python-matplotlib is not working.
My python version is 2.7, is that an issue?
Is there any way for upgrading matplotlib?
Regards,
Rachana K

I had just been looking into this myself.
My starting point would be this example:
http://stackoverflow.com/questions/13570287/image-overlay-in-3d-plot-using-python
but instead of the hard-coded '10' as the z values in plot_surface, put in
whatever data or function of x and y that you want. Using x+y seemed to do
what I expected. Is that what you're looking for?
On Wed, Jun 11, 2014 at 2:40 PM, Hearne, Mike <mh...@us...> wrote:
> Is it possible to drape an image over a topography dataset? One example,
> from a package called GMT, is here:
>
> http://gmt.soest.hawaii.edu/doc/5.1.1/gallery/ex32.html
>
> If so, does anyone have a sample of how this would be accomplished?
>
> Thanks,
>
> Mike
>
>
> ------------------------------------------------------------------------------
> HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
> Find What Matters Most in Your Big Data with HPCC Systems
> Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
> Leverages Graph Analysis for Fast Processing & Easy Data Exploration
> http://p.sf.net/sfu/hpccsystems
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

use matplotlib's internal latex parsing:
text(0.2,0.4,"text$_{\mathrm{subscript}}$")
M
On 6/12/14, 6:26 AM, Nemanja Savic wrote:
> Hi all guys,
>
> I am not able to find answer on my question: how to write subscripts
> using default matplotlib font?
>
> best,
>
> --
> Nemanja Savić
>
>
> ------------------------------------------------------------------------------
> HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
> Find What Matters Most in Your Big Data with HPCC Systems
> Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
> Leverages Graph Analysis for Fast Processing & Easy Data Exploration
> http://p.sf.net/sfu/hpccsystems
>
>
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hello I am using matplotlib and I have a time series plot. I need to select
one data point of the plot and I want to shift it up or down to make
correction on data. I checked matplotlib site but couldn't find it. I am
doing this for my thesis. Any help or idea will be appreciated.
Thank you
Burak

Hi all,
I am stuck with plotting that uses brewer2mpl.
The following link describes my problem, please have a look at it:
http://stackoverflow.com/questions/24181183/matplotlib-brewr2mpl-plotting-issue
Regards,
Rachana K

Hi all guys,
I am not able to find answer on my question: how to write subscripts using
default matplotlib font?
best,
-- 
Nemanja Savić

Hi all guys,
I have already spent a lot of time trying to figure out how to set the
aspect ratio of all axeses in my plot which consists of a single subplot
and three y axes. Namely, i tried to set the aspect ratio of the base axes,
and i expect after twinx that others will inheritt that. So, what i
basically want is to make figure wider and thiner.
Best regards and thanx,
-- 
Nemanja Savić