matplotlib-users Mailing List for matplotlib

>>>>> "Lionel" == Lionel Roubeyrie <lro...@li...> writes:
 Lionel> Arg, I hoped that you would not say that :-) Le Mardi 19
It's not too bad, actually:
from pylab import figure, show, nx, cm
from matplotlib.transforms import blend_xy_sep_transform
fig = figure()
ax = fig.add_subplot(111)
X = 100*nx.mlab.randn(256,256)
im = ax.imshow(X, cmap=cm.jet)
cax = fig.colorbar(im)
labels = (100., 'peak1'), (-100, 'peak2')
trans = blend_xy_sep_transform(cax.transAxes, cax.transData)
for y, label in labels:
 cax.text(-0.05, y, label, ha='right', va='center', transform=trans)
show()

Arg, I hoped that you would not say that :-)
Le Mardi 19 D=E9cembre 2006 16:39, Jeff Whitaker a =E9crit=A0:
> Lionel Roubeyrie wrote:
> > Hi all,
> > I don't find any doc on this point, then I post my question here: is it
> > possible to set texts with a colorbar, like a legend?
> > You can have a look of what I want here:
> > http://www.limair.asso.fr/previsions2/index.php (just click "OK")
> > thanks
>
> Lionel: I don't think there is any automatic way to do this, but you
> can do it manually with pylab.text
> (http://matplotlib.sourceforge.net/matplotlib.pylab.html#-text).
>
> -Jeff
=2D-=20
Lionel Roubeyrie - lro...@li...
LIMAIR
http://www.limair.asso.fr

Sorry for the previsou post. Tweaking a bit I found that probably the 
problem is not in the visualisation but in cleaning memory.
I use a function to make four plot calling two subfunction.
the plot are called plotrisp and plotlev in everyone of them any tome i 
use a figure I also close it. But if I only use one fuction it do the 
plot. WhenI try to use them to plot no way it stuck in the end.
So I had the same problem while calling multiple plots with multiple 
function
Any help would be appreciated and sorry for the dup post
 nstep=30
Giorgio

Lionel Roubeyrie wrote:
> Hi all,
> I don't find any doc on this point, then I post my question here: is it 
> possible to set texts with a colorbar, like a legend?
> You can have a look of what I want here:
> http://www.limair.asso.fr/previsions2/index.php (just click "OK")
> thanks
>
> 
Lionel: I don't think there is any automatic way to do this, but you 
can do it manually with pylab.text 
(http://matplotlib.sourceforge.net/matplotlib.pylab.html#-text).
-Jeff
-- 
Jeffrey S. Whitaker Phone : (303)497-6313
Meteorologist FAX : (303)497-6449
NOAA/OAR/PSD R/PSD1 Email : Jef...@no...
325 Broadway Office : Skaggs Research Cntr 1D-124
Boulder, CO, USA 80303-3328 Web : http://tinyurl.com/5telg

Hi all,
I don't find any doc on this point, then I post my question here: is it 
possible to set texts with a colorbar, like a legend?
You can have a look of what I want here:
http://www.limair.asso.fr/previsions2/index.php (just click "OK")
thanks
-- 
Lionel Roubeyrie - lro...@li...
LIMAIR
http://www.limair.asso.fr

I've retried reloading the matrices after restaring everything twice and 
it seems to plot. Probably the problem is that the memory is "occupied" 
from previous plots. I noticed also that the possibility to command come 
back to the console only after the last plot is close manually ..any hints
Is there a way to "clean" the memory for a new start.. the command close 
doesn't seem to work ?
Here's the module that make the only previous plot before trying to do 
the meshcountour

>>>>> "David" == David Cournapeau <da...@ar...> writes:
 David> In make_image, most of the time is taken into to_rgba:
 David> almost half of it is taken in by the take call in the
 David> Colormap.__call__. Almost 200 ms to get colors from the
 David> indexes seems quite a lot (this means 280 cycles / pixel on
 David> average !). I can reproduce this number by using a small
 David> numpy test.
 David> On my laptop (pentium M, 1.2 Ghz), make_image takes almost
 David> 85 % of the time, which seems to imply that this is where
 David> one should focus if one wants to improve the speed,
This may have been lost in the longer thread above, but what
interpolation are you using? You may see a good performance boost by
using interpolation='nearest'. Also, with your clip changes and with
Eric's changes is it still painfully slow for you -- how much have
these changes helped? Of time time spent in make image, how much is
_image.fromarray, ScalarMappable.to_rgba and _image.resize?

>>>>> "Olivier" == Olivier ATTEIA <Oli...@eg...> writes:
 Olivier> Hello, sorry to bother you but I did not find a reply
 Olivier> elsewhere, I am using matplotlib with python 2.4 and
 Olivier> windows XP and it is a really nice tool. It is inside a
 Olivier> wxapplication. I have a problem because the user can
 Olivier> change the graph settings as he wants and draws several
 Olivier> times contours from 50 by 200 matrices. After some time
 Olivier> the program slows down and the memory is increasing
 Olivier> regularly. I don't understand because I use a command
 Olivier> similar as in matplotlib clear command : collections=[]
 Olivier> between each drawing. I tried in a simpler way : just
 Olivier> start matplotlib(even in tk mode), make a plot(x,y) with
 Olivier> x=randn(100,100). First it takes a lot of memory (more
 Olivier> than 50 Mb). And when you clear hte figure the meory
 Olivier> remains high, or when you set holds(False) and make a
 Olivier> simple plot the first plot disappears but the memory is
 Olivier> still high. Do you have any idea Thanks a lot Sincerely
 Olivier> O. Atteia
Hey Olivier, questions should go to the matplotlib-users mailing
list. I'm forwarding this on. You can subscribe at 
http://sourceforge.net/mailarchive/forum.php?forum_id=33405
JDH

Hello to all,
I'm finishing to convert a module for linear regression that I used in 
Matlab. It takes an experimental matrix, and a response matrix perform a 
regression and a bit of plot and then give me 3 matrices that I need to 
plot response surface and leverage surface. For plotting leverage and 
response I need to create a kind of grid of point with another program. 
and at this point everything work fine (checked also in comparison with 
matlab). The problems come when I tri to plot it. For a step of 2 (not 
really a grid) it works with 30 steps everything crashes :(
so nste=2 work nstep=30 not
I attach the file that give no problems it's a module with included the 
matrix to be plotted with nstep=2 and also the problematic one. a 
function with the same name of the plot and the matrices that give the 
problems.
Every help would be greatly appreciated because if I fix it I can get 
rid of the regression program in matlab that i generally use really a 
lot in my everyday job
Giorgio

Christopher Barker wrote:
> yardbird wrote:
> =20
>> On Saturday 16 December 2006 19:42, Xavier Gnata wrote:
>> =20
>
> =20
>>> Each time I'm working on C++ codes using vector or valarray, I would
>>> like to be able to plot them.
>>> =20
>
> =20
>> you should really check out the Boost::Python libraries. They allow yo=
u, among=20
>> other things, to expose your C++ container classes as python objects. =
I'm=20
>> using them heavily in my project and I'm very satisfied.
>> =20
>
> What this means is that you'd be using python to drive your C++ code,=20
> rather than using C++ code to drive a python/mpl code. In addition to=20
> Boost::Python, there are some other options to consider:
>
> pyrex, Cxx, SWIG.
>
> The other option is to use your C++ code to drive Python. This can be=20
> done by embedding a python interpreter in your C++ app. See the=20
> odfficial pyhton docs, and lots of other stuff online.
>
> You also might want to check out Elmer:
>
> http://elmer.sourceforge.net/
>
> I've never used it, but it looks pretty cool. It's a tool that provides=
=20
> the infrastructure for calling python from C/C++.
>
> Honestly, though, I'd go with the first approach -- drive your C++ code=
=20
> from Python -- I think that in addition to making it easy to plot=20
> results, etc, you'll be able to write unit tests, etc in python, and=20
> even get a full scripting engine, which could turn out to be very usefu=
l..
>
> -Chris
> =20
Hi,
I do agree that driving C++ from python looks easier thant driving
python from C++.
However, I really would like to inclue python code into my C++ code and
not the opposite (I have special needs so I really have to do that).
I'm going to have a look at embedding python.
Has anyone experience with that?
=20
Xavier
--=20
############################################
Xavier Gnata
CRAL - Observatoire de Lyon
9, avenue Charles Andr=E9
69561 Saint Genis Laval cedex
Phone: +33 4 78 86 85 28
Fax: +33 4 78 86 83 86
E-mail: gn...@ob...
############################################=20

Hi guys,
I'm trying to run the pcolor demo on my own data. I have an image and I 
need to draw the hot colormap on it. Can you advise on how I can do it? 
Sorry I'm not from the computer field so please try to be clear.
Thanks so much in advance,
Regards,
_________________________________________________________________
Think you're a film buff? Play the Movie Mogul quiz and win fantastic 
prizes! http://www.msnmoviemogul.com

David Cournapeau wrote:
> Eric Firing wrote:
>> There is a clip function in all three numeric packages, so a native 
>> clip is being used.
>>
>> If numpy.clip is actually slower than your version, that sounds like a 
>> problem with the implementation in numpy. By all logic a single clip 
>> function should either be the same (if it is implemented like yours) 
>> or faster (if it is a single loop in C-code, as I would expect). This 
>> warrants a little more investigation before changing the mpl code. 
>> The best thing would be if you could make a simple standalone numpy 
>> test case profiling both versions and post the results as a question 
>> to the numpy-discussion list. Many such questions in the past have 
>> resulted in big speedups in numpy.
> I am much more familiar with internal numpy code than matplotlib's, so 
> this is much easier for me, too :)
>> One more thought: it is possible that the difference is because myclip 
>> operates on the array in place while clip generates a new array. If 
>> this is the cause of the difference then changing your last line to 
>> "return a.copy()" probably would slow it down to the numpy clip speed 
>> or slower.
> It would be scary if a copy of a 8008x256 array of double took 100 ms... 
> Fortunately, it does not, this does not seem to be the problem.
>
> cheers,
>
> David
Ok, so now, with my clip function, still for a 8000x256 double array: we 
have show() after imshow which takes around 760 ms. 3/5 are in 
make_image, 2/5 in the function blop, which is just an alias I put to 
measure the difference between axes.py:1043(draw) and image.py:173(draw) 
in the function Axis.draw (file axes.py):
 def blop(dsu):
 for zorder, i, a in dsu:
 a.draw(renderer)
 blop(dsu)
In make_image, most of the time is taken into to_rgba: almost half of it 
is taken in by the take call in the Colormap.__call__. Almost 200 ms to 
get colors from the indexes seems quite a lot (this means 280 cycles / 
pixel on average !). I can reproduce this number by using a small numpy 
test.
On my laptop (pentium M, 1.2 Ghz), make_image takes almost 85 % of the 
time, which seems to imply that this is where one should focus if one 
wants to improve the speed,
cheers,
David