matplotlib-users Mailing List for matplotlib (Page 2)

Hello,

I want to dynamically update a plot of the rate at which a neural network is
learning a function. Ideally, my python program would open up a window and
update the plot inside of it after every training epoch.

I have written the following code to do so:

	pyplot.title('Learning Curve')
	pyplot.xlabel('Epoch #')
	pyplot.ylabel('Success rate (%)')

	pyplot.plot(range(1, len(rates)+1), rates, 'r-')

	pyplot.draw()

Note that I am also calling pyplot.ion() at the start of the program.

This *mostly* works. However, I run into a strange issue. If the figure
window is minimized/hidden, when I open it up, nothing shows up in it (the
content is only grey). The plot will appear only if the window is
maximized/visible when the plotting occurs. If I again minimize the window
after the plot was drawn, it goes back to being gray.
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On Mon, Sep 28, 2009 at 9:06 AM, Nicolas Rougier
<Nic...@lo...>wrote:

>
> Hi all,
>
> glumpy is a fast OpenGL visualization tool for numpy arrays coded on
> top of pyglet (http://www.pyglet.org/). The package contains many
> demos showing basic usage as well as integration with matplotlib. As a
> reference, the animation script available from matplotlib distribution
> runs at around 500 fps using glumpy instead of 30 fps on my machine.
>
> Package/screenshots/explanations at:
> http://www.loria.fr/~rougier/coding/glumpy.html<http://www.loria.fr/%7Erougier/coding/glumpy.html>
> (it does not require installation so you can run demos from within the
> glumpy directory).
>
>
> Nicolas
> _______________________________________________
> NumPy-Discussion mailing list
> Num...@sc...
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>

Hi Nicolas,

This is technically called OpenGL backend, isn't it? It is nice that
integrates with matplotlib, however 300 hundred lines of code indeed a lot
of lines for an ordinary user. Do you think this could be further integrated
into matplotlib with a wrapper to simplify its usage?


-- 
Gökhan

Hi all,

glumpy is a fast OpenGL visualization tool for numpy arrays coded on  
top of pyglet (http://www.pyglet.org/). The package contains many  
demos showing basic usage as well as integration with matplotlib. As a  
reference, the animation script available from matplotlib distribution  
runs at around 500 fps using glumpy instead of 30 fps on my machine.

Package/screenshots/explanations at: http://www.loria.fr/~rougier/coding/glumpy.html
(it does not require installation so you can run demos from within the  
glumpy directory).


Nicolas

Is it possible to specify a path object that will use different
transforms for different vertices?

This is again related to plotting a box whose height is specified by
data coords, but whose width is a constant in axes coords regardless
of scale (so linear and log x-scales would produce a box of the same
width).

Ideally, I would draw a path like this:
1. the center of the box would be located at x and bottom and top
would be y1, y2, all in data coords
2. I would move to (x,y1) at the bottom-center of the box.
3. The x value would now need to be converted to Axes coords, possibly
by applying transData + transAxes.inverted
4. I would want to draw a line to (x-0.1, y1) where x is now in axes
coords and y is still in data coords.  Then up, then right, then down,
and then close the polygon.

How do I implement this?

As I mentioned before, a blended transform would allow me to make the
moves i am interested in.  However, a change of scale would change the
correspondence between data and axes coords, so the axes transform
part of the blended axes would have to be recomputed everytime the
scale changes based on where the (x,y1) point lands in the axes.  Is
this correct?

Any suggestions are welcome...thanks!

Uri


-- 
Uri Laserson
PhD Candidate, Biomedical Engineering
Harvard Medical School (Genetics)
Massachusetts Institute of Technology (Mathematics)
phone +1 917 742 8019
las...@mi...

Hi,

I'm having trouble building matplotlib 0.99.1.1 (transcript below). 

I'm using copies of Python (2.5.1) and Tcl/Tk (8.5.5) that I have
built myself, and that are apparently working fine. Previously, I was
using this exact procedure to build 0.91.4 without any problems.

Any suggestions would be greatly appreciated - thanks!

Chris

$ cd matplotlib-0.99.1.1
$ env PREFIX=/a/b/ LD_LIBRARY_PATH=/a/b/lib  /a/b/bin/python setup.py build
============================================================================
BUILDING MATPLOTLIB
            matplotlib: 0.99.1.1
                python: 2.5.1 (r251:54863, Feb  5 2009, 13:11:08)  [GCC
                        4.1.2 20071124 (Red Hat 4.1.2-42)]
              platform: linux2

REQUIRED DEPENDENCIES
                 numpy: 1.2.1
             freetype2: 9.10.3

OPTIONAL BACKEND DEPENDENCIES
                libpng: 1.2.10
               Tkinter: Tkinter: 50704, Tk: 8.5, Tcl: 8.5
                  Gtk+: no
                        * Building for Gtk+ requires pygtk; you must be able
                        * to "import gtk" in your build/install environment
       Mac OS X native: no
                    Qt: no
                   Qt4: no
                 Cairo: no

OPTIONAL DATE/TIMEZONE DEPENDENCIES
              datetime: present, version unknown
              dateutil: matplotlib will provide
                  pytz: matplotlib will provide
adding pytz

OPTIONAL USETEX DEPENDENCIES
                dvipng: 1.5
           ghostscript: 8.15.2
                 latex: 3.141592
               pdftops: 3.00

[Edit setup.cfg to suppress the above messages]
============================================================================
pymods ['pylab']
packages ['matplotlib', 'matplotlib.backends', 'matplotlib.projections',
'mpl_toolkits', 'mpl_toolkits.mplot3d', 'mpl_too\
lkits.axes_grid', 'matplotlib.sphinxext', 'matplotlib.numerix',
'matplotlib.numerix.mlab', 'matplotlib.numerix.ma', 'matp\
lotlib.numerix.linear_algebra', 'matplotlib.numerix.random_array',
'matplotlib.numerix.fft', 'matplotlib.delaunay', 'pytz\
', 'dateutil', 'dateutil/zoneinfo']
running build
running build_py
copying lib/matplotlib/mpl-data/matplotlibrc ->
build/lib.linux-i686-2.5/matplotlib/mpl-data
copying lib/matplotlib/mpl-data/matplotlib.conf ->
build/lib.linux-i686-2.5/matplotlib/mpl-data
running build_ext
building 'matplotlib.backends._tkagg' extension
g++ -pthread -shared build/temp.linux-i686-2.5/src/agg_py_transforms.o
build/temp.linux-i686-2.5/src/_tkagg.o build/temp.\
linux-i686-2.5/CXX/cxx_extensions.o build/temp.linux-i686-2.5/CXX/cxxsupport.o
build/temp.linux-i686-2.5/CXX/IndirectPyth\
onInterface.o build/temp.linux-i686-2.5/CXX/cxxextensions.o -L/usr/lib
-L/usr/lib -L/usr/local/lib -L/usr/lib -L/usr/lib6\
4 -L/usr/local/lib -L/usr/lib -L/usr/lib64 -ltk8.5 -ltcl8.5 -lstdc++ -lm
-lfreetype -lz -lstdc++ -lm -o build/lib.linux-i\
686-2.5/matplotlib/backends/_tkagg.so
/usr/bin/ld: cannot find -ltk8.5
collect2: ld returned 1 exit status
error: command 'g++' failed with exit status 1
make: *** [matplotlib] Error 1

$ ls /a/b/lib/*tk*
lib/libtk8.5.so  lib/libtkstub8.5.a  lib/tkConfig.sh
...

Hi,
is there a way to update a contour plot? I need to display a series of
contour plots from a directory with data files and want to view them
consecutively, preferrably without building a gui for it. Is there an 
easy way out?

Cheers, Ralph

Hi,
is there a way to update a contour plot? I need to display a series of
contour plots from a directory with data files and want to view them
consecutively, preferrably without building a gui for it. Is there an 
easy way out?

Cheers, Ralph

Hello. My problem is as follows:
(ipython --pylab)

from pylab import *
pp=plot([0,0],[1,1])
text(xlim()[0],1,'    Need padding   ',horizontalalignment='left')
text(xlim()[1],1,'    Need padding   ',horizontalalignment='right')


The second case does not do what I want, which is to pad the text on the
right. Text strings are stripped on the right, but no on the left. How can I
elegantly create a character of space?

Thanks!
c
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On Sun, Sep 27, 2009 at 3:45 PM, Peter Butterworth <bu...@gm...> wrote:
> On Sun, Sep 27, 2009 at 9:31 PM, Jae-Joon Lee <lee...@gm...> wrote:
>>> Some feedback: If plotting a line2D as discrete points rather than a
>>> continuous line, you must use numpoints=2 for the legend picking to actually
>>> occur on the points. The alpha blending doesn't work on the legend symbols
>>> however.
>>>
>>
>> I tried numpoints=1,2,3 but all worked for me. Can someone else confirm this?
>
> I'm using windows and mpl 0.99.0:

Most of the enhancements to support legend picking happened after 99.0
-- you probably need to be on svn trunk (I don't think 99.1 would work
either).  The example is working fine for me on svn HEAD (regardless
of ncol) with one exception: if I use a marker instead of a line, the
alpha is not respected (the line markers are simply turned off).
Apparently we need to fix Line2D to respect the alpha setting for
markers in this use case.

JDH

>
>
>
>> The alpha for legend symbols does not work since, inside legend, the
>> lines and symbols are drawn by different artists.
>>
>> Try something like below.
>>
>>
>>        legline.set_alpha(1.0)
>>        try:
>>            legline._legmarker.set_alpha(1.0)
>>        except AttributeError:
>>            pass
>>
>>
>>
>>> Is there any other way, I can show in the legend whether the points of the
>>> series are visible or not ?
>>>
>>> I thought of changing the labels, but failed to get them to redraw.
>>>
>>
>> Legend.get_texts() method returns the list of Text instances.
>>
>> http://matplotlib.sourceforge.net/api/artist_api.html?highlight=legend#matplotlib.legend.Legend.get_texts
>>
>> You may modify the returned Text instances.
>>
>> -JJ
>>
>
> works great.
>
>
>
>>
>>> # plots:
>>> ax.plot(t, y1, 'ro', picker=5, label='lab1')
>>> ax.plot(t, y2, 'bo', picker=5, label='lab2')
>>>
>>> # legend
>>> leg = ax.legend(loc='upper left', numpoints=2, fancybox=True, shadow=True)
>>> lines, labels = ax.get_legend_handles_labels()
>>>
>>> # Enable picking on the legend lines
>>> leglines=leg.get_lines()
>>> for legline in leglines: legline.set_picker(5)
>
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>

On Sun, Sep 27, 2009 at 4:18 PM, Gökhan Sever <gok...@gm...> wrote:
> When I run this as it is, and zoom once the top x-axis ticklabels disappear:
> http://img2.imageshack.us/img2/5493/zoom1.png
>
> After commenting these three lines:
>
> #locator    = MinuteLocator(interval=1)
> #locator    = SecondLocator(interval=30)
> #par2.xaxis.set_major_locator(locator)
>
> and running I get somewhat nice view after zooms:
> http://img340.imageshack.us/img340/6632/zoom2.png
>
> with a minute discrepancy; resulting with shifts on the top x-labels.
>
> Any last thoughts?
>

I believe that this is due to wrong tick locations. As you easily
guess, the default tick locators are not suitable for datetime ticks
and this is why we have separate locators. Please take a look at
documentations.

http://matplotlib.sourceforge.net/api/dates_api.html

If you want to have locator that works for several zoom levels, you
may try AutoDateLocator.


from matplotlib.dates import DateFormatter, MinuteLocator,
SecondLocator, AutoDateLocator, AutoDateFormatter
locator    = AutoDateLocator()
par2.xaxis.set_major_locator(locator)
formatter=AutoDateFormatter(locator)
par2.xaxis.set_major_formatter(formatter)

par2.axis["top"].major_ticklabels.set(rotation=30,
                                      ha="left",
                                      va="bottom")


While the AutoLocator seems to give too may ticks in my opinion, I
think this is as far as I can help.

Regards,

-JJ


> On Sun, Sep 27, 2009 at 2:12 PM, Jae-Joon Lee <lee...@gm...> wrote:
>>
>> Here it is.
>>
>> -JJ
>>
>> On Sun, Sep 27, 2009 at 3:09 PM, Gökhan Sever <gok...@gm...>
>> wrote:
>> > JJ,
>> >
>> > Could you please re-attach the code? Apparently, it has been forgotten
>> > on
>> > your reply.
>> >
>> > Thanks.
>> >
>> > On Sun, Sep 27, 2009 at 1:50 PM, Jae-Joon Lee <lee...@gm...>
>> > wrote:
>> >>
>> >> Here is the modified version of your code that works for me.
>> >>
>> >> 1) If you change trans_aux, you also need to plot your data in an
>> >> appropriate coordinate. Your original code did not work because you
>> >> scaled the xaxis of the second axes (par) but you were still plotting
>> >> the original data, i.e., "time" need to be scaled if you want to plot
>> >> it on "par". The code below takes slightly different approach.
>> >>
>> >> 2) I fount that I was wrong with the factor of 3600. It needs to be
>> >> 86400, i.e., a day in seconds. Also, The unit must be larger than 1.
>> >> Again, please take a look how datetime unit works.
>> >>
>> >> Regards,
>> >>
>> >> -JJ
>> >>
>> >>
>> >> import numpy as np
>> >> import matplotlib.pyplot as plt
>> >> import matplotlib.transforms as mtransforms
>> >> from mpl_toolkits.axes_grid.parasite_axes import SubplotHost
>> >>
>> >>
>> >> # Prepare some random data and time for seconds-from-midnight (sfm)
>> >> representation
>> >> ydata1 = np.random.random(100) * 1000
>> >> ydata2 = np.ones(100) / 2.
>> >> time = np.arange(3550, 3650)
>> >>
>> >>
>> >> fig = plt.figure()
>> >> host = SubplotHost(fig, 111)
>> >> fig.add_subplot(host)
>> >>
>> >> # This is the heart of the example. We have to scale the axes
>> >> correctly.
>> >> aux_trans = mtransforms.Affine2D().translate(0., 0.).scale(3600,
>> >> ydata1.max())
>> >> par = host.twin(aux_trans)
>> >>
>> >> host.set_xlabel("Time [sfm]")
>> >> host.set_ylabel("Random Data 1")
>> >> par.set_ylabel("Random Data 2")
>> >> par.axis["right"].label.set_visible(True)
>> >>
>> >> p1, = host.plot(time, ydata1)
>> >> p2, = par.plot(time, ydata2)
>> >>
>> >> host.axis["left"].label.set_color(p1.get_color())
>> >> par.axis["right"].label.set_color(p2.get_color())
>> >>
>> >> host.axis["bottom"].label.set_size(16)
>> >> host.axis["left"].label.set_size(16)
>> >> par.axis["right"].label.set_size(16)
>> >>
>> >> # Move the title little upwards so it won't overlap with the ticklabels
>> >> title = plt.title("Double time: SFM and HH:MM:SS", fontsize=18)
>> >> title.set_position((0.5, 1.05))
>> >>
>> >> plt.show()
>> >>
>> >>
>> >> On Sun, Sep 27, 2009 at 12:32 PM, Gökhan Sever <gok...@gm...>
>> >> wrote:
>> >> > Hello,
>> >> >
>> >> > As was suggested by Jae-Joon, I have simplified the code for easier
>> >> > investigation and run. The aim of the script is to have time
>> >> > represented
>> >> > on
>> >> > both bottom and top x-axes, on the bottom in seconds-from-midnight
>> >> > (SFM),
>> >> > and the top should show as HH:MM:SS, while there is two different
>> >> > data
>> >> > source being used for y-axes. The code could be seen here or from
>> >> > http://code.google.com/p/ccnworks/source/browse/trunk/double_time.py
>> >> >
>> >> > Currently something wrong with the scaling, since the right y-axis
>> >> > data
>> >> > is
>> >> > missing on the plotting area. Also, sfm hasn't been converted to
>> >> > HH:MM:SS.
>> >> > adding this: par.xaxis.set_major_formatter(DateFormatter('%H:%M:%S'))
>> >> > doesn't remedy the situation as of yet.
>> >> >
>> >> > All comments are welcome.
>> >> >
>> >> > ### BEGIN CODE ###
>> >> > #!/usr/bin/env python
>> >> >
>> >> > """
>> >> >
>> >> > Double time representation. Bottom x-axis shows time in
>> >> > seconds-from-midnight
>> >> > (sfm) fashion, whereas the top x-axis uses HH:MM:SS representation.
>> >> >
>> >> > Initially written by Gokhan Sever with helps from Jae-Joon Lee.
>> >> >
>> >> > Written: 2009-09-27
>> >> >
>> >> > """
>> >> >
>> >> > import numpy as np
>> >> > import matplotlib.pyplot as plt
>> >> > import matplotlib.transforms as mtransforms
>> >> > from mpl_toolkits.axes_grid.parasite_axes import SubplotHost
>> >> >
>> >> >
>> >> > # Prepare some random data and time for seconds-from-midnight (sfm)
>> >> > representation
>> >> > ydata1 = np.random.random(100) * 1000
>> >> > ydata2 = np.ones(100) / 2.
>> >> > time = np.arange(3550, 3650)
>> >> >
>> >> >
>> >> > fig = plt.figure()
>> >> > host = SubplotHost(fig, 111)
>> >> > fig.add_subplot(host)
>> >> >
>> >> > # This is the heart of the example. We have to scale the axes
>> >> > correctly.
>> >> > aux_trans = mtransforms.Affine2D().translate(0., 0.).scale(3600,
>> >> > ydata1.max())
>> >> > par = host.twin(aux_trans)
>> >> >
>> >> > host.set_xlabel("Time [sfm]")
>> >> > host.set_ylabel("Random Data 1")
>> >> > par.set_ylabel("Random Data 2")
>> >> > par.axis["right"].label.set_visible(True)
>> >> >
>> >> > p1, = host.plot(time, ydata1)
>> >> > p2, = par.plot(time, ydata2)
>> >> >
>> >> > host.axis["left"].label.set_color(p1.get_color())
>> >> > par.axis["right"].label.set_color(p2.get_color())
>> >> >
>> >> > host.axis["bottom"].label.set_size(16)
>> >> > host.axis["left"].label.set_size(16)
>> >> > par.axis["right"].label.set_size(16)
>> >> >
>> >> > # Move the title little upwards so it won't overlap with the
>> >> > ticklabels
>> >> > title = plt.title("Double time: SFM and HH:MM:SS", fontsize=18)
>> >> > title.set_position((0.5, 1.05))
>> >> >
>> >> > plt.show()
>> >> > ### END CODE ###
>> >> >
>> >> >
>> >> > --
>> >> > Gökhan
>> >> >
>> >> >
>> >> >
>> >> > ------------------------------------------------------------------------------
>> >> > Come build with us! The BlackBerry&reg; Developer Conference in SF,
>> >> > CA
>> >> > is the only developer event you need to attend this year. Jumpstart
>> >> > your
>> >> > developing skills, take BlackBerry mobile applications to market and
>> >> > stay
>> >> > ahead of the curve. Join us from November 9&#45;12, 2009. Register
>> >> > now&#33;
>> >> > http://p.sf.net/sfu/devconf
>> >> > _______________________________________________
>> >> > Matplotlib-users mailing list
>> >> > Mat...@li...
>> >> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>> >> >
>> >> >
>> >
>> >
>> >
>> > --
>> > Gökhan
>> >
>
>
>
> --
> Gökhan
>