matplotlib-users — Discussion related to using matplotlib

[Matplotlib-users] Adding axis labels and toolbar to embedding_in_tk.py

[Delbert D. F. <iq...@so...>]

I have been making good progress in creating a simple plotting
package for time series read from files.  I would now like
to embed this into TK.  Using some extrapolation and even
a bit of guess work I have cut and pasted material from 
.../examples/embedding_in_tk.py and have a nice window
popping up with a quit button and part of what I want. 

The axis labels are missing and so is the toolbar-items
that need to be present.  How does one add labels for 
the x and y axes as well as get the toolbar to appear
in the example: embedding_in_tk.py?  They both appear 
when the non-embedded script is run.

I have searched the examples and tried sever val options
but nothing works.  Why the toolbar appears in one
case but not the other is currently unclear to me. 

Quite impressed with matplotlib but the learning 
curve is steep and I am feeling my way 
along a tortuous cave in dim light!!

Delbert Franz

Re[2]: [Matplotlib-users] 0.65 installation no-go

[Alan G I. <ai...@am...>]

On Sat, 18 Dec 2004, John Hunter apparently wrote:
> Can we get some positive confirmation from other
> win32 users that 0.65 is working for them?

No problems yet on Win2000 Pro or Win XP.
(I have only run a few scripts since my upgrade,
but they all worked.)

Alan Isaac

Re: [Matplotlib-users] 0.65 installation no-go

[John H. <jdh...@ac...>]

>>>>> "Gary" == Gary  <pa...@in...> writes:
    Gary> I changed axes.py to remove 'min' from the 'from numerix
    Gary> import ...' line.

    Gary> Now it chokes on the very next line, from numerix import max
    Gary> as nxmax

Let's be systematic.  From the python shell, what happens when you do

  >>> import Numeric, MLab
  >>> Numeric.__version__
  >>> from MLab import min, max
  >>> import matplotlib
  >>> matplotlib.__version__
  >>> from matplotlib.numerix import min, max

This will help narrow down whether it's a matplotlib or Numeric
problem. Check the reported version numbers to make sure the numeric
upgrade went as expected.

Do you have only one python installed on your system?

    Gary> Am I the only one suffereing from this?  Isn't this impossible?

My win32 setup appears to be working fine.  It's clearly not
impossible <wink>.  Can we get some positive confirmation from other
win32 users that 0.65 is working for them?

JDH

Re: [Matplotlib-users] Error: This application has requested the Runtime to terminate it in an unusual way

[John H. <jdh...@ac...>]

>>>>> "Axel" == Axel Kowald <A.K...@gm...> writes:

    Axel> Hello, I have the following small problem when terminating a
    Axel> matplotlib script.  Basically I do the following
    Axel> (interactive set to False): from pylab import *
    Axel> plot([1,2,3]) savefig('bla.ps')

    Axel> Now, this script does produce the PS file but then
    Axel> terminates with the error message:

    >> Fatal Python error: PyEval_RestoreThread: NULL tstate This
    >> application has requested the Runtime to terminate it in an
    Axel> unusual way.
    >> Please contact the application's support team for more
    >> information.

This error has cropped up before in other contexts, always on win32,
and I think a common cause is when you import the tk backend but do
not start the tk mainloop (which is what show does), which is what I
suspect you are doing since this is the default backend on win32.  My
guess is the bug will go away if you call "show" at the end of the
script, but then you'll get the GUI window in addition to the ps file.

I'm not sure if there is a fix for this.  Basically, you want to
create postscript output using the tk backend without having the tk
window popup.  Perhaps Todd has some ideas about what to do with tk
internals to avoid this problem, but I don't know offhand.  I'll try
and take a look next week when I have access to a win32 box.  Does the
minimal script, which does nothing but "import pylab" replicate the
problem?

Do you know that you can run the script with -dPS from the shell to
switch the backend?  Then you'll get the PS, no GUI popup, no error,
and you won't have to alter your script.  You can also place an rc
file in the directory where the script resides and make PS the default
backend.  When you want to switch to GUI mode, you can replace the
backend parameter with TkAgg again.  But you'll need the show in that
case.

If you get any additional information from some of the tests suggested
above, let me know, because as I said this PyEval_RestoreThread has
popped up in many contexts, including multiple calls to show or not
calling it at all.  I would like to fix these problems if possible so
that it "just works".

See related threads

http://sourceforge.net/mailarchive/message.php?msg_id=10271482
http://sourceforge.net/mailarchive/message.php?msg_id=10114470

JDH

[Matplotlib-users] Error: This application has requested the Runtime to terminate it in an unusual way

[Axel K. <A.K...@gm...>]

Hello,

I have the following small problem when terminating a matplotlib script.
Basically I do the following (interactive set to False):
from pylab import *
plot([1,2,3])
savefig('bla.ps')

Now, this script does produce the PS file but then terminates with the 
error message:

 >Fatal Python error: PyEval_RestoreThread: NULL tstate
 >This application has requested the Runtime to terminate it in an 
unusual way.
 >Please contact the application's support team for more information.

I know that I could use the PS backend which avoids this problem, but I 
want to be flexible and either generate a PS file or some screen output 
and so I keep the default backend.
Since the script actually does what it should do the question is 
somewhat aesthetical:

How can I avoid this error message ?

Many thanks,

               Axel Kowald

Re: [Matplotlib-users] 0.65 installation no-go

[Gary <pa...@in...>]

John Hunter wrote:

>>>>>>"Gary" == Gary  <pa...@in...> writes:
>>>>>>            
>>>>>>
>
>    Gary> ---------------------------------------------------------------------
>    Gary> C:\Python23\Lib\site-packages\matplotlib\examples>python
>    Gary> Python 2.3.4 (#53, May 25 2004, 21:17:02) [MSC v.1200 32 bit
>    Gary> (Intel)] on win32 Type "help", "copyright", "credits" or
>    Gary> "license" for more information.
>    >>>> from matplotlib.numerix import min
>    Gary> Traceback (most recent call last): File "<stdin>", line 1,
>    Gary> in ?  ImportError: cannot import name min
>    Gary> ----------------------------------------------------------------
>
>It looks like your Numeric install is screwed up.  Remove
>site-packages Numeric to be on the safe side and grab the latest
>release for your python version at 
>
>  http://sourceforge.net/projects/numpy
>
>reinstall and see if that fixes your problem.  Let me know...
>
>JDH
>
>  
>
I'm sorry to report no change.  I uninstalled Numeric and matplotlib, 
and reinstalled both, and nothing has changed.  Am I the only one 
suffereing from this?  Isn't this impossible?

I tried this several times.  I uninstalled using the Control Panel Add 
and Remove feature, and then trashed the remaining directory.  I 
searched the registry for lurking remnants (there was a mention of an 
uninstaller and .matplotlibrc.  that's all.  I left those entries 
alone.) I checked .matplotlibrc... nothing obviously unusual, just 
numerix:Numeric.  A week ago I did a virus scan on the whole system, and 
ran spybot.  (I'll probably run those again tonight for good measure.)  
The version of Numeric that I installed is 23.6, the latest.  I'm using 
python 2.3.4

I changed axes.py to remove 'min' from the 'from numerix import ...' line.

Now it chokes on the very next line,
from numerix import max as nxmax

... and happy holidays.

-gary

Re: [Matplotlib-users] dynamic plots

[Arnd B. <arn...@we...>]

Dear John,

thank you very much for your helpful answer!

On Thu, 16 Dec 2004, John Hunter wrote:

> >>>>> "imaginee1" == imaginee1  <ima...@gm...> writes:

[... snip frame rates ...]

> 1000 frames per second??  A typical top of the line monitor refreshes
> at 75-100 FPS.  How can you get 1000 frames per second?  I'll humbly
> suggest that you're not accurately measuring the true refresh rate of
> xplt, while graciously acknowledging that xplt is much faster than
> matplotlib.
>
> Also, what refresh rate do you really need?  DVD refreshes at 30FPS
> and monitors typically around 75FPS.  I suspect Andrew can tell us the
> limits of the human visual system in terms of the maximal refresh rate
> that is perceptible.  I'm assuming you want to display these
> animations to humans and not flies, which of course would be a
> different story :-)

That would be an interesting research project, but
makes grant applications more complicated due to animal experiments ;-).

The FPS numbers give us an estimate on the speed of
the drawing process (see also below).

> I certainly agree that there are things matplotlib can, should and
> will do to make this process faster.  The first problem is that the
> entire figure is updated with every frame.  It would be much more
> efficient in animated mode to designate certain elements only for
> update.  These elements could store the background image of their
> bounding box, and on each update erase themselves (restore the
> background) and redraw themselves with the new data.  By limiting
> redraws to only sections of the canvas, and only certain plot
> elements, we should be able to get at least a 2x speedup, I'm
> guessing.

We have a question here concerning the example you gave: is
the whole screen updated with every `draw()`,
including the axes and labels?
If so there might be another (simpler) possibility
by just updating the white plot-area.
A problem might be the inward pointing tics.
((For the PlottingCanvas we solved this by having
ticks pointing outward and using a separate frame
for the inside of the plot)).

>     imaginee1> More generally, our impression is that with matplotlib
>     imaginee1> the code tends to be more complicated (timers, classes
>     imaginee1> etc.)  than the scipy.xplt version. Maybe there are
>     imaginee1> better ways to achieve what we want (but we haven't
>     imaginee1> found them yet ;-).
>
> All this complication arises in attempting to deal with the mainloop.
> You should be able to skip all this cruft, as you did for your tkagg
> example, by running in interactive mode
>
>     import matplotlib
>     matplotlib.use('GTKAgg')
>     matplotlib.interactive(True)
>     from matplotlib.matlab import *
>     import time
>
>     x = arange(0,2*pi,0.01)           # x-array
>     axis([0.0,2*pi,-1.0,1.0])         # setup axis
>     tstart = time.time()
>
>     line, = plot(x,sin(x))
>     for i in arange(1,200):
>         line.set_ydata(sin(x+i/10.0))
>         draw()
>
>     print 'FPS:' , 200/(time.time()-tstart)


This is indeed very nice and works (basically) the same for all backends.
For this particular example we get:

          Double buffered           Resizable
xplt        no                        no
tkagg       yes                       yes
gtk         yes  (but: frameshift)    no
gtkagg      no                        no
wx          no                        no
wxagg       no                        no

Interestingly, in this dynamics example
tkagg and gtk seem to have double buffering,
i.e. at the end of the dynamics a damaged area gets repainted.
With tkagg one can even resize the window at the end of the
dynamics.
(Actually, in the examples we posted double-buffering and resizing
worked).

Just a remark: For the gtk backend the double-buffer for
the repaint is one frame behind.


> Basically what matplotlib needs is a method like
>
>     for i in arange(1,200):
>         line.set_ydata(sin(x+i/10.0))
>         fig.update(line)
>
> in place of the call to draw which redraws the entire figure.

That could indeed give an substantial speed-up.

>     imaginee1> We also have a wx version, but the code is really
>     imaginee1> complicated (any pointers on how to code our example
>     imaginee1> most simply with the wx backend
>     imaginee1> would be also very much appreciated).
>
> Well, you'd have to post your code, but the interactive trick above
> works for WX and WXAgg as well.   But I doubt you'll beat GTK/GTKAgg
> performance wise with WX*.

We will either need Tk or WX for our Windows using students.
For Linux GTKAgg should do the job.

> With the example above, I get
>
>   TkAgg     20 FPS
>   GTK       50 FPS
>   GTKAgg    36 FPS
>   GTKCairo  15 FPS
>   WX        11 FPS
>   WXAgg     27 FPS
>
> The performance problem with Tk animation is well known and w/o
> resorting to platform dependent extension code, we don't have a good
> way to solve it.

I re-ran the tests on my laptop (PIII, 1.2 GHz)

            John     laptop
  xplt               196
  TkAgg     20 FPS     9
  GTK       50 FPS    25
  GTKAgg    36 FPS    18
  WX        11 FPS     8
  WXAgg     27 FPS    11

(Unfortunately, some of the students have even slower machines ;-(.


To provide even more data (now a PIV, 2.8 GHz, debian sarge,
but a different X driver, factor 3 slower for xplt!)

            1000 pts    10000 pts    100000 pts
xplt         330 FPS      159 FPS        43 FPS
tkagg         23 FPS       16 FPS         4 FPS
gtk           40 FPS       19 FPS         5 FPS
gtkagg        31 FPS       24 FPS         4 FPS
wx            12 FPS        3 FPS         0 FPS
wxagg         24 FPS       16 FPS         4 FPS


This shows the FPS when the number of points being plotted
is increased.
To answer your question from above:
Something like 40 FPS for plotting 10000 points
would be optimal. On slower machines (like
my laptop) this might not be realizable.

> Note in matplotlib's defense, the fact that I can run the same
> animated code across platforms and 4 GUIs (FLTK not profiled here) w/o
> changing a single line of code says something about why it's slower
> that xplt, which targets a single windowing system and thus can make
> low level calls.

There is really no need to defend matplotlib
(and we better don't post matplotlib's feature list here
to emphasize the points we like!).

Best,

Nikolai and Arnd

Re: [Matplotlib-users] dynamic plots

[Steve C. <ste...@ya...>]

On Thu, 2004-12-16 at 20:21 +0300, Alexey Shamrin wrote:
> Why is GTKAgg is slower than GTK, but WXAgg is faster than WX?
Were you thinking that GTKAgg should be as fast or faster than GTK? 

In the past I think GTKAgg and GTK would do dynamic plots at about the
same speed. GTK used to allocate a new gtk.gdk.Pixmap and a new
RendererGTK for every figure draw operation, which was inefficient. I
updated the code so GTK now creates just one RendererGTK and just one
Pixmap (as long as its size does not increase). This should have made
GTK dynamic plotting faster (I didn't benchmark the changes so I don't
know for sure).

Its possible that similar changes for GTKAgg (or TkAgg or WX) would
speed up their dynamic plotting.

Steve

Re: [Matplotlib-users] 0.65 installation no-go

[John H. <jdh...@ac...>]

>>>>> "Gary" == Gary  <pa...@in...> writes:

    Gary> ---------------------------------------------------------------------
    Gary> C:\Python23\Lib\site-packages\matplotlib\examples>python
    Gary> Python 2.3.4 (#53, May 25 2004, 21:17:02) [MSC v.1200 32 bit
    Gary> (Intel)] on win32 Type "help", "copyright", "credits" or
    Gary> "license" for more information.
    >>>> from matplotlib.numerix import min
    Gary> Traceback (most recent call last): File "<stdin>", line 1,
    Gary> in ?  ImportError: cannot import name min
    Gary> ----------------------------------------------------------------

It looks like your Numeric install is screwed up.  Remove
site-packages Numeric to be on the safe side and grab the latest
release for your python version at 

  http://sourceforge.net/projects/numpy

reinstall and see if that fixes your problem.  Let me know...

JDH

Re: [Matplotlib-users] 0.65 installation no-go

[Gary <pa...@in...>]

John Hunter wrote:

>[...]
>
>So removing "min" from the numerix import in axes.py should fix your
>problem, but\ I'm surprised that you are unable to import min from the
>numerix module.  So before you fix it could you run a test script with
>
>  > python myscript.py --verbose-helpful
>
>and report the output, particularly the numerix version information.
>  
>
---------------------------------------------------------------------
C:\Python23\Lib\site-packages\matplotlib\examples>python simple_plot.py 
--verbose-helpful
matplotlib data path C:\Python23\share\matplotlib
loaded rc file C:\Python23\share\matplotlib\.matplotlibrc
matplotlib version 0.65
verbose.level helpful
interactive is False
platform is win32
numerix Numeric 23.0
Traceback (most recent call last):
  File "simple_plot.py", line 3, in ?
    from pylab import *
  File "C:\Python23\Lib\site-packages\pylab.py", line 1, in ?
    from matplotlib.pylab import *
  File "C:\Python23\Lib\site-packages\matplotlib\pylab.py", line 184, in ?
    from axes import Axes, PolarAxes
  File "C:\Python23\Lib\site-packages\matplotlib\axes.py", line 6, in ?
    from numerix import MLab, absolute, arange, array, asarray, ones, 
transpose,
 \
ImportError: cannot import name min
-----------------------------------------------------------------------------------

>Perhaps Todd or I can then offer some insight into why the MLab.min
>function is not in the numerix namespace.  I can do
>
> >>> from matplotlib.numerix import min
>
>  
>
correct:
---------------------------------------------------------------------
C:\Python23\Lib\site-packages\matplotlib\examples>python
Python 2.3.4 (#53, May 25 2004, 21:17:02) [MSC v.1200 32 bit (Intel)] on 
win32
Type "help", "copyright", "credits" or "license" for more information.
 >>> from matplotlib.numerix import min
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
ImportError: cannot import name min
----------------------------------------------------------------

>with both Numeric and numarrary (latest release or CVS of both).  My
>guess is that you cannot, and I'd like to know why.
>
>You appear cursed in your ability to get a working matplotlib win32
>upgrade!  Maybe next time....
>  
>
Off topic comment:   I have a number or little annoyances with various 
packages.  Enough that I decided that I would try migrating to Linux.    
My Thinkpad has only a modest HD, so I didn't want to partition it.  I 
could buy a bigger drive.  But my Thinkpad can boot from an external USB 
device, so I started wondering if I could set up a Linux entirely on the 
external drive, and not touch my internal drive.  If it worked, I'd have 
a portable Linux (portable, at least, to any machine that can boot from 
USB). 

I searched the web, and found mixed reviews concening the viability of 
this idea.

So I bought a USB enclosure ($10 on eBay) and a 20 GB drive ($33 on 
eBay, but read on) and went to town.  After about three months of 
back-burner late-night tinkering, I got it working!  A week later, my 
external HD crashed.   I'm waiting for some extra time to appear before 
trying again.

If anyone is interested, I can provide some pointers.  (once I'm 
finished, I'll post my experinces on a web site somewhere)  Two initial 
comments:  1.) be very careful about buying a "Travelstar" HD on eBay.   
Apparantly manufacturing problems resulted in a large number of faulty 
units getting into circulation.  2.)  I was *not* successful using 
Mandrake or Mepis.  I was successful using Fedora FC2.

Re: [Matplotlib-users] dynamic plots

[Chris B. <Chr...@no...>]

Alexey Shamrin wrote:
> Why is GTKAgg is slower than GTK, but WXAgg is faster than WX?

My question exactly. It's unlikely that that Wx has to be slower than 
WxAgg. In theory, at least, wx can take advantage of hardware 
accelerated drawing. On the other hand, wx does not know about NumPy 
arrays of either flavor, so if the Agg wrappers do, they could have an 
advantage there. Also, wx is known to be much slower with numarray 
arrays than Numeric arrays. I'd would certainly recommend  that wx users 
stick with Numeric if they don't have a compelling reason to use numarray.

Another issue is font caching. Is the wx back-end doing font caching? 
this made a huge difference in the wxPyPlot code.

By the way, timing drawing on X is difficult, because the drawing calls 
return after the app has told X what to draw, not when it has been 
drawn. I suspect this might have something to do with the 1000 fps that 
was measured.

I hope I'll get a chance to do some work on the wx backend someday....

-Chris




-- 
Christopher Barker, Ph.D.
Oceanographer
                                     		
NOAA/OR&R/HAZMAT         (206) 526-6959   voice
7600 Sand Point Way NE   (206) 526-6329   fax
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Chr...@no...

Re: [Matplotlib-users] dynamic plots

[Alexey S. <sh...@gm...>]

Hello!

Why is GTKAgg is slower than GTK, but WXAgg is faster than WX?

Alexey

On Thu, 16 Dec 2004 10:23:26 -0600, John Hunter
<jdh...@ac...> wrote:
>     import matplotlib
>     matplotlib.use('GTKAgg')
>     matplotlib.interactive(True)
>     from matplotlib.matlab import *
>     import time
> 
>     x = arange(0,2*pi,0.01)           # x-array
>     axis([0.0,2*pi,-1.0,1.0])         # setup axis
>     tstart = time.time()
> 
>     line, = plot(x,sin(x))
>     for i in arange(1,200):
>         line.set_ydata(sin(x+i/10.0))
>         draw()
> 
>     print 'FPS:' , 200/(time.time()-tstart)
> 
>   TkAgg     20 FPS
>   GTK       50 FPS
>   GTKAgg    36 FPS
>   GTKCairo  15 FPS
>   WX        11 FPS
>   WXAgg     27 FPS

Re: [Matplotlib-users] dynamic plots

[John H. <jdh...@ac...>]

>>>>> "imaginee1" == imaginee1  <ima...@gm...> writes:

    imaginee1> Hi, we are trying to change from scipy.xplt to
    imaginee1> matplotlib and need advice on dynamic plots.  With the
    imaginee1> examples at the end of this e-mail we get the following
    imaginee1> frame rates (PIV, 2.8 GHz, debian sarge, python 2.3,
    imaginee1> matplotlib 0.64)

    imaginee1>           FPS xplt 1000 (mov_sin_xplt.py) TkAgg 20
    imaginee1> (mov_sin_mpl_tkagg.py) TkAgg2 5 (mov_sin_mpl_tkagg2.py)
    imaginee1> gtk 60 (mov_sin_mpl_gtk.py) gtkAgg 37
    imaginee1> (mov_sin_mpl_gtk.py)

1000 frames per second??  A typical top of the line monitor refreshes
at 75-100 FPS.  How can you get 1000 frames per second?  I'll humbly
suggest that you're not accurately measuring the true refresh rate of
xplt, while graciously acknowledging that xplt is much faster than
matplotlib.

Also, what refresh rate do you really need?  DVD refreshes at 30FPS
and monitors typically around 75FPS.  I suspect Andrew can tell us the
limits of the human visual system in terms of the maximal refresh rate
that is perceptible.  I'm assuming you want to display these
animations to humans and not flies, which of course would be a
different story :-)

I certainly agree that there are things matplotlib can, should and
will do to make this process faster.  The first problem is that the
entire figure is updated with every frame.  It would be much more
efficient in animated mode to designate certain elements only for
update.  These elements could store the background image of their
bounding box, and on each update erase themselves (restore the
background) and redraw themselves with the new data.  By limiting
redraws to only sections of the canvas, and only certain plot
elements, we should be able to get at least a 2x speedup, I'm
guessing.

    imaginee1> More generally, our impression is that with matplotlib
    imaginee1> the code tends to be more complicated (timers, classes
    imaginee1> etc.)  than the scipy.xplt version. Maybe there are
    imaginee1> better ways to achieve what we want (but we haven't
    imaginee1> found them yet ;-).

All this complication arises in attempting to deal with the mainloop.
You should be able to skip all this cruft, as you did for your tkagg
example, by running in interactive mode

    import matplotlib
    matplotlib.use('GTKAgg')
    matplotlib.interactive(True)
    from matplotlib.matlab import *
    import time

    x = arange(0,2*pi,0.01)           # x-array
    axis([0.0,2*pi,-1.0,1.0])         # setup axis
    tstart = time.time()

    line, = plot(x,sin(x))
    for i in arange(1,200):
        line.set_ydata(sin(x+i/10.0))
        draw()

    print 'FPS:' , 200/(time.time()-tstart)

Basically what matplotlib needs is a method like

    for i in arange(1,200):
        line.set_ydata(sin(x+i/10.0))
        fig.update(line)

in place of the call to draw which redraws the entire figure.

    imaginee1> We also have a wx version, but the code is really
    imaginee1> complicated (any pointers on how to code our example
    imaginee1> most simply with the wx backend
    imaginee1> would be also very much appreciated).

Well, you'd have to post your code, but the interactive trick above
works for WX and WXAgg as well.  But I doubt you'll beat GTK/GTKAgg
performance wise with WX*.  With the example above, I get

  TkAgg     20 FPS
  GTK       50 FPS
  GTKAgg    36 FPS
  GTKCairo  15 FPS
  WX        11 FPS
  WXAgg     27 FPS

The performance problem with Tk animation is well known and w/o
resorting to platform dependent extension code, we don't have a good
way to solve it. 

Note in matplotlib's defense, the fact that I can run the same
animated code across platforms and 4 GUIs (FLTK not profiled here) w/o
changing a single line of code says something about why it's slower
that xplt, which targets a single windowing system and thus can make
low level calls.


JDH

Re: [Matplotlib-users] 0.65 installation no-go

[John H. <jdh...@ac...>]

>>>>> "Gary" == Gary  <pa...@in...> writes:

    from numerix import MLab, absolute, arange, array,
    ImportError: cannot import name

This looks like a bug.  Right before the release I cleaned up axes.py
because the numerix min should not be mixed with the builtin min.

Hence I did

    # do not import numerix max!  we are using python max.  
    from numerix import MLab, absolute, arange, array, asarray, ones, transpose, \
       log, log10, Float, ravel, zeros, Int32, Float64, ceil, min, indices, \
       shape, which
    from numerix import max as nxmax
    from numerix import min as nxmin

I should have also remove min from the numerix import (oversight),
which I already caught and fixed in CVS thanks to pychecker.

So removing "min" from the numerix import in axes.py should fix your
problem, but\ I'm surprised that you are unable to import min from the
numerix module.  So before you fix it could you run a test script with

  > python myscript.py --verbose-helpful

and report the output, particularly the numerix version information.
Perhaps Todd or I can then offer some insight into why the MLab.min
function is not in the numerix namespace.  I can do

 >>> from matplotlib.numerix import min

with both Numeric and numarrary (latest release or CVS of both).  My
guess is that you cannot, and I'd like to know why.

You appear cursed in your ability to get a working matplotlib win32
upgrade!  Maybe next time....

JDH

[Matplotlib-users] dynamic plots

[<ima...@gm...>]

Hi,

we are trying to change from scipy.xplt to matplotlib and
need advice on dynamic plots.
With the examples at the end of this e-mail we get the following
frame rates (PIV, 2.8 GHz, debian sarge, python 2.3, matplotlib 0.64)

          FPS
xplt     1000     (mov_sin_xplt.py)
TkAgg      20     (mov_sin_mpl_tkagg.py)
TkAgg2      5     (mov_sin_mpl_tkagg2.py)
gtk        60     (mov_sin_mpl_gtk.py)
gtkAgg     37     (mov_sin_mpl_gtk.py)

We also have a wx version, but the code is really complicated
(any pointers on how to code our example most simply with the wx backend
would be also very much appreciated).

Obviously, our matplotlib implementations run much
slower than scipy.xplt. Do you have any suggestions
on how we could improve the speed of the code?

More generally, our impression is that with matplotlib
the code tends to be more complicated (timers, classes etc.)
than the scipy.xplt version. Maybe there are
better ways to achieve what we want (but we haven't found them yet ;-).

Personally we don't mind too much about using classes, timers and events,
but
we want to replace scipy.xplt in a course on computational physics.
Most of the students have not been exposed to these concepts before,
so we have to avoid that completely.
Our experiences with scipy.xplt were very positive
as it allows a `linear programming style', which is very suitable
for beginners.

Best,

Lars and Arnd

###############################################
## mov_sin_xplt.py

from scipy.xplt import *
import time

x = arange(0,2*pi,0.01)           # x-array

window(wait=1)                    # wait for plotting
animate(1)                        # use blitting

tstart = time.time()

for i in arange(10000):
    plg(sin(x+i/100.0),x,marks=0) # plot the function
    fma()                         # blit the offscreen pixmap

print 'FPS:' , 10000/(time.time()-tstart)

###############################################
## mov_sin_mpl_tkagg.py

import matplotlib
matplotlib.use('TkAgg')
matplotlib.interactive(True)
from matplotlib.matlab import *
from Numeric import *
import time

x = arange(0,2*pi,0.01)           # x-array

lines = plot(x,sin(x))            # plot the function
axis([0.0,2*pi,-1.0,1.0])         # setup axis

tstart = time.time()

for i in arange(200):
    lines[0].set_ydata(sin(x+i/10.0)) # change y-data
    draw()                            # force redraw

print 'FPS:' , 200/(time.time()-tstart)

###############################################
## mov_sin_mpl_tkagg2.py

import matplotlib
matplotlib.use('TkAgg')
matplotlib.interactive(True)
from matplotlib.matlab import *
from Numeric import *
import time

x = arange(0,2*pi,0.01)           # x-array

axis([0.0,2*pi,-1.0,1.0])         # setup axis

tstart = time.time()

or i in arange(200):
    clf()
    plot(x,sin(x+i/10.0))

print 'FPS:' , 200/(time.time()-tstart)

###############################################
## mov_sin_mpl_gtk.py

import matplotlib
matplotlib.use('GTKAgg')  # matplotlib.use('GTK')
from matplotlib.matlab import *
from Numeric import *
import gtk
import time

x = arange(0,2*pi,0.01)           # x-array

lines = plot(x,sin(x))
axis([0.0,2*pi,-1.0,1.0])
manager = get_current_fig_manager()

tstart = time.time()

def updatefig(*args):
    updatefig.count += 1
    lines[0].set_ydata(sin(x+updatefig.count/10.0))
    manager.canvas.draw()
    if updatefig.count>1000:
        print 'FPS:' , 1000/(time.time()-tstart)
        return gtk.FALSE

    return gtk.TRUE

updatefig.count=-1

gtk.idle_add(updatefig)
show()

-- 
GMX ProMail mit bestem Virenschutz http://www.gmx.net/de/go/mail
+++ Empfehlung der Redaktion +++ Internet Professionell 10/04 +++

Re: [Matplotlib-users] 0.65 installation no-go

[Alan G I. <ai...@am...>]

On Wed, 15 Dec 2004, Gary apparently wrote:
> from pylab import *

Either first import everything from matplotlib
or do instead
from matplotlib.pylab import *

hth,
Alan Isaac

[Matplotlib-users] 0.65 installation no-go

[Gary <pa...@in...>]

As is becoming usual, my attempt to upgrade has run into a problem.

WinXP,
deleted previous ...\matplotlib  before installing.

None of the examples (from the new zip file) seem to run.  They 
generally seem to start with

from pylab import *

but this fails, even from the command line.  Bug, feature, or pilot 
error?   :)

-gary

----------------------------------------------------------

C:\Python23\Lib\site-packages\matplotlib\examples>python
Python 2.3.4 (#53, May 25 2004, 21:17:02) [MSC v.1200 32 bit (Intel)] on 
win32
Type "help", "copyright", "credits" or "license" for more information.
 >>> from pylab import *
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
  File "C:\Python23\Lib\site-packages\pylab.py", line 1, in ?
    from matplotlib.pylab import *
  File "C:\Python23\Lib\site-packages\matplotlib\pylab.py", line 184, in ?
    from axes import Axes, PolarAxes
  File "C:\Python23\Lib\site-packages\matplotlib\axes.py", line 6, in ?
    from numerix import MLab, absolute, arange, array, asarray, ones, 
transpose,
 \
ImportError: cannot import name min

Re: [Matplotlib-users] Set Figure's position

[Todd M. <jm...@st...>]

On Wed, 2004-12-15 at 16:49 -0600, John Hunter wrote:
> >>>>> "Eli" == Eli Glaser <eg...@se...> writes:
> 
>     Eli> Hello, Is there an easy way to set the initial position of a
>     Eli> Figure?  I'm using Windows XP and new figures seem to pop up
>     Eli> in the typical Windows fashion where subsequent figures
>     Eli> appear about 20 pixels down and 20 pixels to the right of
>     Eli> previous figures.  How can I tell each figure where to pop up
>     Eli> on screen?
> 
> matplotlib doesn't provide explicit support for this, but it is
> possible.  What backend are you using.  The matplotlib Figure is
> embedded in a FigureCanvas which is typically a GUI widget embedded in
> a GUI Window.  In the pylab interface, the canvas is managed by a
> FigureManager, which has a window attribute on most of the backends.
> 
> Eg for the GTK backend, for example, you could do
> 
>     from pylab import *
> 
>     import gtk
> 
>     figure(1)
>     plot([1,2,3])
>     manager = get_current_fig_manager()
> 
>     # see gtk.Window class docs at
>     # http://www.pygtk.org/pygtk2reference/class-gtkwindow.html
>     manager.window.set_position(gtk.WIN_POS_CENTER)
> 
>     figure(2)
>     plot([1,2,3])
>     manager = get_current_fig_manager()
> 
>     # see gtk.Window class docs at
>     # http://www.pygtk.org/pygtk2reference/class-gtkwindow.html
>     manager.window.set_position(gtk.WIN_POS_NONE)
> 
>     show()
> 
> For the WX* backend, manager.window is a wxFrame -
> http://www.lpthe.jussieu.fr/~zeitlin/wxWindows/docs/wxwin_wxframe.html#wxframe
> 
> For the TkAgg backend, manager.window is a Tkinter.Tk instance -
> http://starship.python.net/crew/fredrik/tkclass/ClassToplevel.html
>
> Off the top of my head I don't know the right incantation for each
> backend, but hopefully the classdocs I referenced above will help.
> Perhaps Todd or Matthew can chime in with more Tk and WX information.

In TkAgg it works like this:

get_current_fig_manager().window.wm_geometry("+200+300")

To set the window position to X=200, Y=300.

Todd

Re: [Matplotlib-users] Set Figure's position

[Eli G. <eg...@se...>]

Thanks, John!  That's exactly what I was looking for

I'm using the WX backend and I was able to do:

    figure(1)
    plot([1,2,3])
    manager = get_current_fig_manager()

    manager.window.SetPosition((100,100))

#or

    manager.window.Centre()

Eli




> Eg for the GTK backend, for example, you could do
>
>     from pylab import *
>
>     import gtk
>
>     figure(1)
>     plot([1,2,3])
>     manager = get_current_fig_manager()
>
>     # see gtk.Window class docs at
>     # http://www.pygtk.org/pygtk2reference/class-gtkwindow.html
>     manager.window.set_position(gtk.WIN_POS_CENTER)
>
>     figure(2)
>     plot([1,2,3])
>     manager = get_current_fig_manager()
>
>     # see gtk.Window class docs at
>     # http://www.pygtk.org/pygtk2reference/class-gtkwindow.html
>     manager.window.set_position(gtk.WIN_POS_NONE)
>
>     show()
>
> For the WX* backend, manager.window is a wxFrame -
>
http://www.lpthe.jussieu.fr/~zeitlin/wxWindows/docs/wxwin_wxframe.html#wxframe
>
> For the TkAgg backend, manager.window is a Tkinter.Tk instance -
> http://starship.python.net/crew/fredrik/tkclass/ClassToplevel.html
>
> Off the top of my head I don't know the right incantation for each
> backend, but hopefully the classdocs I referenced above will help.
> Perhaps Todd or Matthew can chime in with more Tk and WX information.
>
> While this arrangement may be suboptimal, we are resisting the urge to
> become a GUI library.  The temptations to abstract GUI functions for
> use in matplotlib are many, and we are trying to keep this to a
> manageable core (some event handling, some basic window management,
> etc.).  It's been on my list of things to do to investigate anygui,
> however - http://anygui.sourceforge.net - which would appear to solve
> our problems but might require a substantial refactoring of the
> matplotlib backends.
>
> If you want full GUI control, you can embed matplotlib in your own GUI
> application, following one of the many embedding_in_*.py examples in
> the examples subdirectory of the matplotlib src distribution.
>
> If you come up with example code for your backend, please post it to
> the list.
>
> JDH
>
>
> -------------------------------------------------------
> SF email is sponsored by - The IT Product Guide
> Read honest & candid reviews on hundreds of IT Products from real users.
> Discover which products truly live up to the hype. Start reading now.
> http://productguide.itmanagersjournal.com/
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Re: [Matplotlib-users] Set Figure's position

[John H. <jdh...@ac...>]

>>>>> "Eli" == Eli Glaser <eg...@se...> writes:

    Eli> Hello, Is there an easy way to set the initial position of a
    Eli> Figure?  I'm using Windows XP and new figures seem to pop up
    Eli> in the typical Windows fashion where subsequent figures
    Eli> appear about 20 pixels down and 20 pixels to the right of
    Eli> previous figures.  How can I tell each figure where to pop up
    Eli> on screen?

matplotlib doesn't provide explicit support for this, but it is
possible.  What backend are you using.  The matplotlib Figure is
embedded in a FigureCanvas which is typically a GUI widget embedded in
a GUI Window.  In the pylab interface, the canvas is managed by a
FigureManager, which has a window attribute on most of the backends.

Eg for the GTK backend, for example, you could do

    from pylab import *

    import gtk

    figure(1)
    plot([1,2,3])
    manager = get_current_fig_manager()

    # see gtk.Window class docs at
    # http://www.pygtk.org/pygtk2reference/class-gtkwindow.html
    manager.window.set_position(gtk.WIN_POS_CENTER)

    figure(2)
    plot([1,2,3])
    manager = get_current_fig_manager()

    # see gtk.Window class docs at
    # http://www.pygtk.org/pygtk2reference/class-gtkwindow.html
    manager.window.set_position(gtk.WIN_POS_NONE)

    show()

For the WX* backend, manager.window is a wxFrame -
http://www.lpthe.jussieu.fr/~zeitlin/wxWindows/docs/wxwin_wxframe.html#wxframe

For the TkAgg backend, manager.window is a Tkinter.Tk instance -
http://starship.python.net/crew/fredrik/tkclass/ClassToplevel.html

Off the top of my head I don't know the right incantation for each
backend, but hopefully the classdocs I referenced above will help.
Perhaps Todd or Matthew can chime in with more Tk and WX information.

While this arrangement may be suboptimal, we are resisting the urge to
become a GUI library.  The temptations to abstract GUI functions for
use in matplotlib are many, and we are trying to keep this to a
manageable core (some event handling, some basic window management,
etc.).  It's been on my list of things to do to investigate anygui,
however - http://anygui.sourceforge.net - which would appear to solve
our problems but might require a substantial refactoring of the
matplotlib backends.

If you want full GUI control, you can embed matplotlib in your own GUI
application, following one of the many embedding_in_*.py examples in
the examples subdirectory of the matplotlib src distribution.

If you come up with example code for your backend, please post it to
the list.

JDH

[Matplotlib-users] Set Figure's position

[Eli G. <eg...@se...>]

Hello,

Is there an easy way to set the initial position of a Figure?  I'm using
Windows XP and new
figures seem to pop up in the typical Windows fashion where subsequent
figures appear about
20 pixels down and 20 pixels to the right of previous figures.  How can I
tell each figure where to
pop up on screen?

Thanks,

Eli

[Matplotlib-users] runtime error on Solaris

[Nadia D. <den...@st...>]

This is a warning to Solaris users - matplotlib 0.65 fails at runtime
with fatal relocation error. The problem was fixed in setupext.py in 
CVS,
(attached also to this message).

Nadia Dencheva

[Matplotlib-users] Has anyone done a matplotlib install on Solaris9?

[Mike R. <Rig...@UT...>]

Hey Folks, 

We are having a bear of a time installing matplotlib into Python2.3 on 
Solaris9-sparc.

The issues arises from "fatal: relocation error"s coming up when attempting 
to run matplotlib demos...but instead of getting into the details of this 
error, I want to simply ask.

Has anyone successfully installed and run matplotlib on Solaris 9 (or any 
other version) sparc?

If so, how did you build and install it?  What version of gcc (or CC if 
that's the case), what switches, ETC?

With thanks in advance!
Mike

Re: [Matplotlib-users] How to get axes limits of subplot ?

[John H. <jdh...@ac...>]

>>>>> "Axel" == Axel Kowald <ko...@mo...> writes:

    Axel> Hi, I'm new to matplotlib and I have a question regarding
    Axel> axes.  Once I created some axes (either with the axes()
    Axel> command or with subplot() ), how can I later find out the
    Axel> limits (left bottom, width, height) of the axes ?  Maybe

    7 >>> ax = subplot(111)

    8 >>> ax.get_position()
    Out[8]: [0.125, 0.10999999999999999, 0.77500000000000002, 0.79000000000000004]

You can change these values with ax.set_position.  This works whether
ax is an Axes or Subplot instance.

    Axel> some trick with get() ?  Btw. is there somewhere a list of
    Axel> properties that I can get/set with get() or set() ?

A timely question.  This feature was just added in the last release,
0.65

  >>> set(ax)  # lists all settable properties
  >>> get(ax)  # lists all properties and their values

Works for any matplotlib artist or sequence of artists; see
http://matplotlib.sf.net/examples/set_and_get.py

This is still a work in progress - the introspection works in part by
examining doc strings and I have finished porting all the artist
docstrings to the new format.  set(artist) should return a list of all
properties and their legal settable values.  If the settable values is
listed as unknown, it means I haven't done that docstring yet.

Also, I'm working on implementing Perry's suggestion of returning
silent lists where appropriate, which will help in pretty printing the
output, eg, of get(ax).

But it's mostly functional, as is.

JDH

[Matplotlib-users] ANN: matplotlib-0.65

[John H. <jdh...@ac...>]

These notes, with links, can be read at
http://matplotlib.sf.net/whats_new.html.

 - matlab namespace renamed pylab - see
   http://matplotlib.sf.net/matplotlib_to_pylab.py for details on
   conversion.  ipython pylab users should grab version 0.6.6.  You
   can import the matlab interface (now known as pylab interface) with

   from pylab import blah              # OK
   from matplotlib.pylab import blah   # OK
   from matplotlib.matlab import blah  # Deprecated

 - contouring with the contour function!!  Thanks to Nadia Dencheva.
   See examples/contour_demo.py

 - matlab compatible set and get introspection to determine settable
   properties and their values.  See examples/set_and_get.py.  Sample
   usage

   >>> lines = plot([1,2,3])  
   >>> set(lines)
       alpha: float
       antialiased or aa: [True | False]
       ...snip lots more...
   >>> get(lines)
       alpha = 1.0
       antialiased or aa = True
       ...snip lots more...

 - Added many new matlab compatible colormaps - autumn bone cool
   copper flag gray hot hsv jet pink prism spring summer winter -
   Thanks Perry!

 - zorder to artists to control drawing order of lines, patches and
   text in axes.  See examples/zorder_demo.py 

 - mathtext in cairo backend.  Also, printing now works to file
   object.  Thanks Steve Chaplin.


 - printing in WX - Matthew Newville contributed a print button and
   preview for the wx backends.  He also, who graciously volunteered
   to be the new wx backend maintainer.

 - matlab interface functions connect and disconnect replace
   mpl_connect and mpl_disconnect for event handling

 - Pass hold=True|False to any plotting command to override the
   current hold setting.  The original hold setting will be restored
   at the end of the plot function

 - all text instances now have a bbox property which is a dict of
   Rectangle properties.  If set, the text instance will display in a
   rectanglular bounding box.  Example usage
    
    title('hi mom', bbox={'facecolor':'r', 'alpha':0.5})

 - legend properties now exposed as kwargs.  See help(legend)

 - ishold to inspect the hold state

 - new plotting functions spy, spy2 for matrix sparsity visualization

 - pylab interface functions rgrids and thetagrids for customizing
   the grid locations and labels for polar plots - see
   examples/polar_demo.py.

 - add ion, ioff and isinteractive to pylab interface for control of
   interactive mode.  See updated discussion at
   http://matplotlib.sf.net/interactive.html

Bugs fixed - 

  - Fixed colorbar bug with scatter - JDH

  - SVG clipping problem - Thanks Norm Peterson

  - numerous small legend bugs fixed

  - zoom to rect works with reversed axis limits - thanks Gregory

  - fontsizing problem fixes, ps plots correctly sized, landscape
    support for ps output

  - smaller, leaner, meaner PS output - Thanks Jochen

  - make the Gtk backends build without an X-server connection -
    Thanks Jochen

 
Downloads at http://matplotlib.sf.net

JDH