matplotlib-users Mailing List for matplotlib

Hello all,

I am trying to superimpose some annotations on a plot by transforming them
to the data coordinate space, and I am finding that the transformed
coordinates are offset from the acutal data positions I expect them to be
in.

Here is my example code:

    import matplotlib.pyplot as plt
    import matplotlib

    # A range of values
    x = list(range(0,20))

    # y = x^2
    y = [ xv*xv for xv in x ]

    fig = plt.figure()
    ax = fig.add_subplot(1,1,1)
    ax.set_xlim(0,100)
    ax.set_ylim(0,100)

    # Plot a line showing the curve
    ax.plot(x,y)

    for i in range(0,len(x)-1):
        pt = (x[i],y[i])

        # Manual transformation fo the point
        pt_tx = ax.transData.transform(pt)

        # A circle drawn automatically in the data coordinates (blue-ish)
        ax.add_artist(plt.Circle(pt, 1, color="#00ffff"))

        # A circle drawn at my manually transformed coordinates (green)
        # I expect these should end up in the same position as the blue
        ax.add_artist(plt.Circle(pt_tx, 4,
transform=matplotlib.transforms.IdentityTransform(),color="#00ff00"))

    fig.savefig("test.pdf")

What I observe when I execute this code is that the manually transformed
points are not in the same location as the ones plotted directly. They are
close, but they are offset (perhaps by the space allocated to the axes?).
Here is how it looks to me:

https://imgur.com/PiqX2o8

Thanks for any help and advice!

Simon

Well... this is a *really* late reply, but I finally got around to adding
easier navigation for the style gallery
<https://tonysyu.github.io/raw_content/matplotlib-style-gallery/gallery.html>.
I
also added an update for styles added in Matplotlib 1.5 and wrote a quick
post <https://tonysyu.github.io/matplotlib-style-gallery.html#.VvoAzxIrKV4>.

Cheers!
-Tony

On Thu, Jan 8, 2015 at 8:10 PM, Tony Yu <ts...@gm...> wrote:

> Thanks Max!
>
> I was planning to add a more interactive interface, really similar to what
> you're suggesting. I haven't gotten around to it, but hopefully, I'll have
> some time to play around with that.
>
> On Thu, Jan 8, 2015 at 4:56 PM, Maximilian Albert <
> max...@gm...> wrote:
>
>> Hi Tony,
>>
>> This is awesome. Great work!
>>
>> I was wondering, is there an easy way to cycle through all available
>> styles for a given plot? For instance, clicking on the top left plot
>> displays a maximized image of the "bmh" style. It would be great if one
>> could press arrow-down (say)  to cycle through the other styles
>> "dark_background", "fivethirtyeight", etc. for a quick comparison.
>>
>> Cheers,
>> Max
>>
>>
>> 2015-01-06 4:42 GMT+00:00 Tony Yu <ts...@gm...>:
>>
>>> I've been playing around with learning Javascript lately. As part of the
>>> process, I created a Flask app to build a gallery for matplotlib style
>>> sheets:
>>>
>>> https://github.com/tonysyu/matplotlib-style-gallery
>>>
>>> If you run that locally, you can actually input styles, either with a
>>> URL to a *.mplstyle file or with matplotlibrc commands. Here's a static
>>> version without the custom inputs:
>>>
>>>
>>> http://tonysyu.github.io/raw_content/matplotlib-style-gallery/gallery.html
>>>
>>> Ideally, I'd get this into a form that could be submitted as a PR for
>>> the matplotlib website, but I'll need a bit more spare time to learn some
>>> more web development (sessions, client storage, etc).
>>>
>>> Cheers!
>>> -Tony
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Dive into the World of Parallel Programming! The Go Parallel Website,
>>> sponsored by Intel and developed in partnership with Slashdot Media, is
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>>> hub for all things parallel software development, from weekly thought
>>> leadership blogs to news, videos, case studies, tutorials and more. Take
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>>> _______________________________________________
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>>>
>>>
>>
>

I'm terribly sorry about this second email.
The deadline for submitting talks and posters for scipy 2016 is this friday
(friday 25th), and not next friday (april fools day).

Thanks,
Nelle

On 21 March 2016 at 15:32, Nelle Varoquaux <nel...@gm...>
wrote:

> Dear all,
>
> This is a quick reminder that the deadline for submitting talks and
> posters proposal is next friday.
>
> Thanks,
> Nelle
>
> On 22 February 2016 at 10:15, Nelle Varoquaux <nel...@gm...>
> wrote:
>
>>
>> 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
>>
>>
>

Dear all,

This is a quick reminder that the deadline for submitting talks and posters
proposal is next friday.

Thanks,
Nelle

On 22 February 2016 at 10:15, Nelle Varoquaux <nel...@gm...>
wrote:

>
> 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
>
>

Dear colleagues, 

Yes, I've downloaded the latest stable image of Matplotlib source from the 
pypi repository matplotlib-1.5.1.tar.gz, running the commands: sudo python 
setup.py build and sudo python setup.py install. 

When executing larger plots, the Agg crashes with a segmentation fault 
message. My guess is that the c header files are not compiled with the 
correct platform setting (s390x).  Is there a way to rebuild 
the c prerequisites used by the embedded Agg framework? 

Thanks in advance for your advice. 

Regards,

Claude Falbriard
Certified IT Specialist L2 - Middleware


Phone: 55-13-99662-5703 | Mobile: 55-13-98117-3316
E-mail: cl...@br...




From:   Benjamin Root <ben...@gm...>
To:     Claude Falbriard/Brazil/IBM@IBMBR
Cc:     Matplotlib Users <mat...@li...>
Date:   03/03/2016 11:44
Subject:        Re: [Matplotlib-users] Matplotlib & Basemap / What is the 
Best Graphical Back-end for Raster Data Display (.png) ?



Matplotlib will not work at all without AGG. Even the AGG-less backends 
still use AGG for image handling (imshow() and such).

We can not guarantee that matplotlib would work with agg 2.5, as that is 
the GPL'ed version. We develop against a patched 2.4 branch of AGG (which 
is BSD-licensed), which is distributed with our source, and is built as 
part of our build process. Have you tried building matplotlib directly 
from our source without a system install of AGG?

Cheers
Ben Root


On Thu, Mar 3, 2016 at 6:34 AM, Claude Falbriard <cl...@br...> 
wrote:
Dear colleagues, 

I like to receive an advice about the best back-end choice for Matplotlib 
& Basemap to generate large .png images in a background processing mode. 
Having issues with the pre-compiled "Agg" package which does not work 
under my machine architecture. Also not able to recompile the Agg 2.5 
package as its build throws an error at the build script autogen.sh. 
Error:  

./configure: line 15546: syntax error near unexpected token 
`$SDL_VERSION,'
./configure: line 15546: `AM_PATH_SDL($SDL_VERSION,'

When bypassing this line it runs into another dependency which is blocking 
the make install process.
  
libtool: link: cannot find the library 
`../src/platform/X11/libaggplatformX11.la' or unhandled argument 
`../src/platform/X11/libaggplatformX11.la'
Makefile:1166: recipe for target 'aa_demo' failed
make[1]: *** [aa_demo] Error 1
make[1]: Leaving directory '/data/Downloads/agg/agg-2.5/examples'
Makefile:481: recipe for target 'install-recursive' failed
make: *** [install-recursive] Error 1

I do not plan to use any interactive access, so my guess is that excluding 
X11 libraries should work OK.  

My test showed that the  "Cairo" package is working fine, but its quality 
(vector oriented) is not as good compared to the Agg raster display. Case 
the "Agg" 
is not able to install on my machine, is there an alternate graphical 
back-end available under SuSE environments?  

Regards,

Claude Falbriard
Certified IT Specialist L2 - Middleware


Phone:55-13-99662-5703 | Mobile:55-13-98117-3316
E-mail: cl...@br...



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AGG is used for image handling, particularly for handling transforms,
scaling, interpolation and such. The AxesImage object that you get from
calling imshow() is handled through the AGG library. This is true
regardless of the backend being used because it is based in the AxesImage
class (and others). An SVG of a plot that used imshow() has raster data in
it that comes from AGG (and you can choose to rasterize other things, as
well). Cairo still needs the image buffer.

So, the distinction is the use of the AGG library, and the use of the AGG
backend. The AGG library is required, but the AGG backend is not (but
highly recommended).

I will admit that I didn't have this distinction very clear in my own head
until very recently when reviewing some PRs that reworked the image
handling architecture. I hope that clears it up for you, too.

Cheers!
Ben Root


On Thu, Mar 3, 2016 at 10:05 AM, Jerzy Karczmarczuk <
jer...@un...> wrote:

> Le 03/03/2016 15:43, Benjamin Root a écrit :
> > Matplotlib will not work at all without AGG. Even the AGG-less
> > backends still use AGG for image handling (imshow() and such).
>
> Is it so? I never found such strong statement in the docs.
>
> 1. SVG backend produces vector graphics, no rasterisation in principle,
> so why AGG?
> 2. Cairo uses its own engine. Why AGG?
> 3. Image (PNG) "production" from curves, etc. uses AntiGrain, but if
> imshow() shows an image which is just a pixel array, there is no
> manipulation needing AGG, an element (triple RGB) becomes a pixel, and
> that's it.
>
> Jerzy Karczmarczuk
>
>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just $35/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
>

Le 03/03/2016 15:43, Benjamin Root a écrit :
> Matplotlib will not work at all without AGG. Even the AGG-less 
> backends still use AGG for image handling (imshow() and such).

Is it so? I never found such strong statement in the docs.

1. SVG backend produces vector graphics, no rasterisation in principle, 
so why AGG?
2. Cairo uses its own engine. Why AGG?
3. Image (PNG) "production" from curves, etc. uses AntiGrain, but if 
imshow() shows an image which is just a pixel array, there is no 
manipulation needing AGG, an element (triple RGB) becomes a pixel, and 
that's it.

Jerzy Karczmarczuk

Matplotlib will not work at all without AGG. Even the AGG-less backends
still use AGG for image handling (imshow() and such).

We can not guarantee that matplotlib would work with agg 2.5, as that is
the GPL'ed version. We develop against a patched 2.4 branch of AGG (which
is BSD-licensed), which is distributed with our source, and is built as
part of our build process. Have you tried building matplotlib directly from
our source without a system install of AGG?

Cheers
Ben Root


On Thu, Mar 3, 2016 at 6:34 AM, Claude Falbriard <cl...@br...> wrote:

> Dear colleagues,
>
> I like to receive an advice about the best back-end choice for Matplotlib
> & Basemap to generate large .png images in a background processing mode.
> Having issues with the pre-compiled "Agg" package which does not work
> under my machine architecture. Also not able to recompile the Agg 2.5
> package as its build throws an error at the build script autogen.sh.
> Error:
>
> ./configure: line 15546: syntax error near unexpected token `$SDL_VERSION,'
> ./configure: line 15546: `AM_PATH_SDL($SDL_VERSION,'
>
> When bypassing this line it runs into another dependency which is blocking
> the make install process.
>
> libtool: link: cannot find the library
> `../src/platform/X11/libaggplatformX11.la' or unhandled argument
> `../src/platform/X11/libaggplatformX11.la'
> Makefile:1166: recipe for target 'aa_demo' failed
> make[1]: *** [aa_demo] Error 1
> make[1]: Leaving directory '/data/Downloads/agg/agg-2.5/examples'
> Makefile:481: recipe for target 'install-recursive' failed
> make: *** [install-recursive] Error 1
>
> I do not plan to use any interactive access, so my guess is that excluding
> X11 libraries should work OK.
>
> My test showed that the  "Cairo" package is working fine, but its quality
> (vector oriented) is not as good compared to the Agg raster display. Case
> the "Agg"
> is not able to install on my machine, is there an alternate graphical
> back-end available under SuSE environments?
>
> Regards,
>
> *Claude Falbriard*
> Certified IT Specialist L2 - Middleware
> ------------------------------
> *Phone:*55-13-99662-5703 | *Mobile:*55-13-98117-3316
> *E-mail:* *cl...@br...* <cl...@br...>
>
>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just $35/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=272487151&iu=/4140
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Dear colleagues, 

I like to receive an advice about the best back-end choice for Matplotlib 
& Basemap to generate large .png images in a background processing mode. 
Having issues with the pre-compiled "Agg" package which does not work 
under my machine architecture. Also not able to recompile the Agg 2.5 
package as its build throws an error at the build script autogen.sh. 
Error: 

./configure: line 15546: syntax error near unexpected token 
`$SDL_VERSION,'
./configure: line 15546: `AM_PATH_SDL($SDL_VERSION,'

When bypassing this line it runs into another dependency which is blocking 
the make install process.
 
libtool: link: cannot find the library 
`../src/platform/X11/libaggplatformX11.la' or unhandled argument 
`../src/platform/X11/libaggplatformX11.la'
Makefile:1166: recipe for target 'aa_demo' failed
make[1]: *** [aa_demo] Error 1
make[1]: Leaving directory '/data/Downloads/agg/agg-2.5/examples'
Makefile:481: recipe for target 'install-recursive' failed
make: *** [install-recursive] Error 1

I do not plan to use any interactive access, so my guess is that excluding 
X11 libraries should work OK. 

My test showed that the  "Cairo" package is working fine, but its quality 
(vector oriented) is not as good compared to the Agg raster display. Case 
the "Agg" 
is not able to install on my machine, is there an alternate graphical 
back-end available under SuSE environments? 


Regards,

Claude Falbriard
Certified IT Specialist L2 - Middleware


Phone: 55-13-99662-5703 | Mobile: 55-13-98117-3316
E-mail: cl...@br...

Dear matplotlib users and developers,

I'm using `plt.draw()` to force the rendering of all artists and then,
based on their newly calculated positions, place a text label on the figure
window in figure coordinates.

The goal is to add a text label near the conventional y-axis, at the top,
right-aligned. Example code that demonstrates the problem:

```
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
print(mpl.__version__)

x = np.linspace(0, 50)
y = 4*np.sin(x) + 5

fig = plt.figure(figsize=(18,9.8))
ax = fig.add_axes((0.1, 0.1, 0.8, 0.8),
    frameon=True,
    aspect='equal',
    adjustable='box',
    xlim=(x.min(), x.max()),
    ylim=(0, 10),
    xticks=[x.min(), x.max()],
    yticks=[0, 10],
    xlabel='dimension (unit)')
ax.plot(x, y)
plt.draw()  # force redraw

ylabel_pos =
fig.transFigure.inverted().transform_point(ax.transAxes.transform_point((0,1)))
label1 = fig.text(ylabel_pos[0], ylabel_pos[1], "label1", ha="right",
va="bottom")
plt.savefig('/tmp/test_pre_mpl_v_{}.png'.format(mpl.__version__))
ylabel_pos =
fig.transFigure.inverted().transform_point(ax.transAxes.transform_point((0,1)))
label2 = fig.text(ylabel_pos[0], ylabel_pos[1], "label2", ha="right",
va="bottom")
plt.savefig('/tmp/test_post_mpl_v_{}.png'.format(mpl.__version__))
```

The code shows that in mpl 1.4.3 both label1 and label2 end up at the same
(desired) position. However, mpl 1.5.0 and 1.5.1 (just installed to check)
show that label1 is at a height of 0.9 in the figure coordinates. After the
first call to `savefig`, the figure is rendered with the axes getting a new
height and width (due to the call to `aspect='equal', adjustable='box'`)
and so the subsequent call to `savefig` renders label2 in the correct
position.

Using `ax.text(x=0, y=1, s='label', transform=ax.transAxes, ha="right",
va="bottom")` gets the job done alright (both in 1.4.3, as well as 1.5.0),
but the call to `fig.text` using the subsequent transforms should have
worked, I believe.

Kind regards,

Oliver