matplotlib-users Mailing List for matplotlib (Page 5)

Eric Emsellem <ems...@ob...> writes:

> sorry to interfere here, but it seems that I cannot see any post on
> the forum after the 05/05/2006, including the ones that I am sending. 

FWIW, I saw your post just fine on Gmane
http://news.gmane.org/gmane.comp.python.matplotlib.general
so probably this is a problem with the Sourceforge forum thing.

-- 
Jouni

Hi
sorry to interfere here, but it seems that I cannot see any post on the 
forum after the 05/05/2006, including the ones that I am sending. Going 
to the forum on the web page I don't see them.
( http://sourceforge.net/mailarchive/forum.php?forum=matplotlib-users)

I only received a single digest on 16/05 in the last 2 weeks, but even 
these posts are not on the web. So it seems I am "disconnected" from the 
forum. Is there anything wrong with forum? or with my subscription?

Thanks for any help here and sorry for the inconvenience.

Eric

Matlab 's contour function returns the contour data as x- and y- =
coordinates in a contour matrix C:

[C,H] =3D CONTOUR(...)

pylab.contour(...) returns a ContourSet object that only seems to =
contain contour heights.  How do I get the actual contour data?  I need =
the (x,y) coordinates as given by matlab.  In fact even the binary =
contour image that is displayed by contour() will be usefull.

albert

Hi,

I would like to be able to make a scatter plot using a new symbol which 
I would draw using whatever drawing software (so a sketched star, or a 
saturn like symbol...) and export in some proper format to be used by 
matplotlib.
Is there a way to do this?

thanks for any help here!

Cheers
Eric

>>>>> "Christopher" == Christopher Barker <Chr...@no...> writes:

    Christopher> That I don't know. The Agg renderer certainly can do
    Christopher> a nice job with gradients, but I don't know if MPL
    Christopher> support that.

You can emulate gradients using matplotlib images -- either with colormaps or
defining your own rgba endpoints for the gradients.  Here's an example
of an axes background gradient

    from pylab import figure, show, nx, cm

    fig = figure()

    xmin, xmax = xlim = 0,2
    ymin, ymax = ylim = -1,1
    ax = fig.add_subplot(111, xlim=xlim, ylim=ylim,
    autoscale_on=False)
    X = [[.6, .6],[.7,.7]]

    ax.imshow(X, interpolation='bicubic', cmap=cm.Blues,
              extent=(xmin, xmax, ymin, ymax), alpha=1)
    t = nx.arange(xmin, xmax,0.01)
    ax.plot(t, nx.sin(2*nx.pi*t), lw=2, color='black')
    show()


Likewise, you can make your own gradient bars charts:

    from pylab import figure, show, nx, cm

    def gbar(ax, x, y, width=0.5, bottom=0):
        X = [[.6, .6],[.7,.7]]
        for left,top in zip(x, y):
            right = left+width
            ax.imshow(X, interpolation='bicubic', cmap=cm.Blues,
                      extent=(left, right, bottom, top), alpha=1)

    fig = figure()

    xmin, xmax = xlim = 0,10
    ymin, ymax = ylim = 0,1
    ax = fig.add_subplot(111, xlim=xlim, ylim=ylim,
                         autoscale_on=False)
    X = [[.6, .6],[.7,.7]]

    ax.imshow(X, interpolation='bicubic', cmap=cm.copper,
              extent=(xmin, xmax, ymin, ymax), alpha=1)

    N = 10
    x = nx.arange(N)+0.25
    y = nx.mlab.rand(N)
    gbar(ax, x, y, width=0.7)
    ax.set_aspect('normal')
    show()

Viewer discretion is advised.

If you want to get clever, you can define patterns and fills this way
too.  We should add an interface to expose this functionality more
readily...

JDH

Bryan wrote:
> Hi all, I am working on a UI design, and I just found out about 
> matplotlib. I would like to learn if some of the following graphs are 
> possible using matplotlib with wxPython

If you want to use MPL with wxPython like that, be sure to check out wxmpl.

> http://www.geocities.com/belred1/image1.jpg
> 
> Does anyone know if matplotlib has rich charting functionality with 
> gradients and shading that could provide the same experience as the 
> performance charts on the right.

I don't think it has the nifty shading. Other than that, it can do it all.

> How difficult would this be to implement?

That I don't know. The Agg renderer certainly can do a nice job with 
gradients, but I don't know if MPL support that.

-Chris

-- 
Christopher Barker, Ph.D.
Oceanographer
                                     		
NOAA/OR&R/HAZMAT         (206) 526-6959   voice
7600 Sand Point Way NE   (206) 526-6329   fax
Seattle, WA  98115       (206) 526-6317   main reception

Chr...@no...

http://www.scipy.org/Cookbook/Matplotlib/Animations

You can get pretty good framerates using the blitting technique
described in the link above.

On 5/14/06, Allan Noriel Estrella <all...@gm...> wrote:
> Can I implement realtime plotting in matplotlib? The data will be coming
> from the serial port. The plotting will be similar to an oscilloscope. Ca=
n
> you suggest matplotlib modules I can use for this particular application.
> Thanks
>

>>>>> "clovis" == clovis  <cl...@pe...> writes:

    clovis> All, I followed up the 'memory leak' discussion in the
    clovis> sourceforge list and I know the Matplotlib-FAQ entry about
    clovis> this subject. I've also seen John Hunter's post about the
    clovis> need of matching figure/close pairs.  Anyway, I still feel
    clovis> that there are problems in this subject, which can be
    clovis> exposed by the following script (for Windows, but can
    clovis> easily be adapted to Unix).

    clovis> As can be seen by the results (also given below), there is
    clovis> a steady increase in memory usage which is not recovered!

If I recall correctly, there is a known leak in tkagg when you create
multiple canvases, and this is in Tk and not matplotlib proper.  Todd
may have something to add here.  

JDH

Hi happy matplolib users,

   Very, very nice feature, this zooming functionality is perfect.
Thanks again to the matplotlib team for the great work.

I simply have one question:
   How can I use this zooming key in my app. which is embedding matplotlib
in GTK ?

David

2006/5/16, sophana <so...@zi...>:
>
>  I made a patch on the sourceforge site that does what you need.
> you can select which layer(s) you interact with (move/pan)
>
> Daniel McQuillen wrote:
>
>
> Hi everybody. Question about multiple Y axes...
>
>
> I've seen a few posts regarding using the trick of laying one axes over
> top of the other to simulate a second Y axis -- as demonstrated in the
> matplotlib example file two_scales.py.
>
> However, in the application I'm building, the user should be able to
> select points ("outliers") for either axis. With the current approach, th=
e
> user can't select the bottom graph's points (or pan or zoom it).
>
>
> Is there a way to bring the bottom graph into "focus"?
>
> Thanks in advance for any tips.
>
>
>  =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> Daniel McQuillen
> Oakland, CA
>
>
>

I made a patch on the sourceforge site that does what you need.
you can select which layer(s) you interact with (move/pan)

Daniel McQuillen wrote:

>
> Hi everybody. Question about multiple Y axes...
>
> I've seen a few posts regarding using the trick of laying one axes 
> over top of the other to simulate a second Y axis -- as demonstrated 
> in the matplotlib example file two_scales.py.
>
> However, in the application I'm building, the user should be able to 
> select points ("outliers") for either axis. With the current approach, 
> the user can't select the bottom graph's points (or pan or zoom it).
>
> Is there a way to bring the bottom graph into "focus"?
>
> Thanks in advance for any tips.
>
>
> =====================================
> Daniel McQuillen
> Oakland, CA
>

Hello Clovis.
(Also, hello list; I <heart> matplotlib, thank you developers!)

On Sun, May 14, 2006 at 09:04:27AM -0300, cl...@pe... wrote:

> I followed up the 'memory leak' discussion in the sourceforge list
> and I know the Matplotlib-FAQ entry about this subject. I've also
> seen John Hunter's post about the need of matching figure/close pairs.
> Anyway, I still feel that there are problems in this subject, which
> can be exposed by the following script (for Windows, but can easily
> be adapted to Unix).
> As can be seen by the results (also given below), there is a steady
> increase in memory usage which is not recovered!
> Any clues????

Could some of your difficulties could be related to Python's ill memory
management? It keeps a death grip on certain types of allocated memory, 
never freeing it to the OS.  Evan Jones made a patch which 
helped that problem a bit.   His patch has been incorporated into 
Python 2.5:

http://evanjones.ca/python-memory.html

Joseph Sheedy
Technical Specialist, 3TIER Environmental Forecast Group
jo...@3t... | (206)325-1573 x116

hello,

I try to have my hist bars inside grids, some bars creep into others..
I create my hist thus:
 bins = nx.arange(1-(0.9/2),max(values))
 n, bins, patches = hist(values, width=0.9)

example:
http://ark42.free.fr/graph.png

and I have display problems for axis names, I use : 
xticks(arange(len(names)), names)


if any idea.. thanks :)

Can I implement realtime plotting in matplotlib? The data will be coming
from the serial port. The plotting will be similar to an oscilloscope. Can
you suggest matplotlib modules I can use for this particular application.
Thanks

All,

I followed up the 'memory leak' discussion in the sourceforge list
and I know the Matplotlib-FAQ entry about this subject. I've also
seen John Hunter's post about the need of matching figure/close pairs.
Anyway, I still feel that there are problems in this subject, which
can be exposed by the following script (for Windows, but can easily
be adapted to Unix).

As can be seen by the results (also given below), there is a steady
increase in memory usage which is not recovered!

Any clues????
Clovis

######################################################################
#Begin of script
######################################################################
import pylab
import os
import time
N =3D 10              # number of loops to execute
SAVEFIG =3D True      # SAVEFIG execution flag
SHOWFIG =3D True      # SHOWFIG execution flag

pylab.matplotlib.use('TkAgg')
#pylab.matplotlib.use('Agg')
#pylab.matplotlib.use('PS')

fid =3D file('memory_report.txt','wt')
fid.write('%s\n' % time.asctime())
fid.write('OS version          =3D %s\n' % os.sys.version)
fid.write('Matplotlib version  =3D %s\n' % pylab.matplotlib.__version__)
fid.write('Matplotlib revision =3D %s\n' % pylab.matplotlib.__revision__)
fid.write('Matplotlit backend  =3D %s\n' % pylab.matplotlib.get_backend()=
)
fid.write('Column #0 =3D figure index\n')
fid.write('Column #1 =3D memory usage before figure\n')
fid.write('Column #2 =3D memory usage after  figure\n')
fid.write('Column #3 =3D (after-before) memory\n')

pylab.ion()
a=3Dpylab.arange(0,10)

def report_memory():
    ### Attention: the path to the pslist utility should be adjusted
according to installation!
    ### pslist.exe is a small utility that does the same as ps in Unix!
    ### It can be found at www.sysinternals.com/Utilities/PsList.html

    if os.sys.platform =3D=3D 'win32':
        ps_exe_filename =3D os.path.join(os.getcwd(),'pslist.exe')    #Bu=
ild
ps filename
        a =3D os.popen('%s -m python' % ps_exe_filename).readlines()  #Bu=
ild
and execute command
        b =3D a[8]
        c =3D b.split()
        return int(c[3])
    else:
        print 'Sorry, you have to adapt the command for your OS!'
        return 0

def figureloop(N):
    for i in range(0,N):
        memory_usage_before =3D report_memory()
        fid.write('Memory usage before/after figure[%2d] =3D %8d' % (i,
memory_usage_before))
        pylab.figure(i)
        pylab.plot(a,2*a)
        figurename =3D 'fig%02d.eps' % i
        if SAVEFIG:
            pylab.savefig(figurename)
        if SHOWFIG:
            pylab.show()
        pylab.close(i)
        time.sleep(1.0)                 # wait 1.0 second before
inspecting memory usage
        if os.path.isfile(figurename):  # remove figure ...
            os.remove(figurename)
        memory_usage_after =3D report_memory()
        delta_memory =3D memory_usage_after - memory_usage_before
        fid.write('  %8d  %8d\n' % (memory_usage_after, delta_memory))
        print '%2d %6d %6d %6d' % (i, memory_usage_before,
memory_usage_after, delta_memory)


print 'Column #0 =3D figure index'
print 'Column #1 =3D memory usage before figure'
print 'Column #2 =3D memory usage after  figure'
print 'Column #3 =3D (after-before) memory'
print 'There is a sleep time of 1s between each figure!'
print 'Close Figure[0] to continue execution!'

SAVEFIG =3D True      # SAVEFIG execution flag
SHOWFIG =3D False     # SHOWFIG execution flag
print('\nConfiguration SHOWFIG=3D%s  SAVEFIG=3D%s' % (SHOWFIG, SAVEFIG))
fid.write('\nConfiguration SHOWFIG=3D%s  SAVEFIG=3D%s\n' % (SHOWFIG, SAVE=
FIG))
figureloop(N)

SAVEFIG =3D False     # SAVEFIG execution flag
SHOWFIG =3D True      # SHOWFIG execution flag
print('\nConfiguration SHOWFIG=3D%s  SAVEFIG=3D%s' % (SHOWFIG, SAVEFIG))
fid.write('\nConfiguration SHOWFIG=3D%s  SAVEFIG=3D%s\n' % (SHOWFIG, SAVE=
FIG))
figureloop(N)

SAVEFIG =3D True      # SAVEFIG execution flag
SHOWFIG =3D True      # SHOWFIG execution flag
print('\nConfiguration SHOWFIG=3D%s  SAVEFIG=3D%s' % (SHOWFIG, SAVEFIG))
fid.write('\nConfiguration SHOWFIG=3D%s  SAVEFIG=3D%s\n' % (SHOWFIG, SAVE=
FIG))
figureloop(N)
######################################################################
#End of script
######################################################################


######################################################################
#The results obtained
######################################################################

Sun May 14 08:35:09 2006
OS version          =3D 2.4.2 (#67, Oct 30 2005, 16:11:18) [MSC v.1310 32
bit (Intel)]
Matplotlib version  =3D 0.86.2
Matplotlib revision =3D $Revision: 1.104 $
Matplotlit backend  =3D TkAgg
Column #0 =3D figure index
Column #1 =3D memory usage before figure
Column #2 =3D memory usage after  figure
Column #3 =3D (after-before) memory

Configuration SHOWFIG=3DFalse  SAVEFIG=3DTrue
Memory usage before/after figure[ 0] =3D    15632     20168      4536
Memory usage before/after figure[ 1] =3D    20172     22532      2360
Memory usage before/after figure[ 2] =3D    22532     24912      2380
Memory usage before/after figure[ 3] =3D    24912     27256      2344
Memory usage before/after figure[ 4] =3D    27256     29700      2444
Memory usage before/after figure[ 5] =3D    29700     31980      2280
Memory usage before/after figure[ 6] =3D    31980     34328      2348
Memory usage before/after figure[ 7] =3D    34328     36696      2368
Memory usage before/after figure[ 8] =3D    36696     39052      2356
Memory usage before/after figure[ 9] =3D    39052     43160      4108

Configuration SHOWFIG=3DTrue  SAVEFIG=3DFalse
Memory usage before/after figure[ 0] =3D    43160     43796       636
Memory usage before/after figure[ 1] =3D    43796     46080      2284
Memory usage before/after figure[ 2] =3D    46080     48392      2312
Memory usage before/after figure[ 3] =3D    48392     50736      2344
Memory usage before/after figure[ 4] =3D    50736     53020      2284
Memory usage before/after figure[ 5] =3D    53020     55420      2400
Memory usage before/after figure[ 6] =3D    55420     57672      2252
Memory usage before/after figure[ 7] =3D    57672     59984      2312
Memory usage before/after figure[ 8] =3D    59984     62312      2328
Memory usage before/after figure[ 9] =3D    62312     64620      2308

Configuration SHOWFIG=3DTrue  SAVEFIG=3DTrue
Memory usage before/after figure[ 0] =3D    64620     68460      3840
Memory usage before/after figure[ 1] =3D    68460     70564      2104
Memory usage before/after figure[ 2] =3D    70564     71992      1428
Memory usage before/after figure[ 3] =3D    71992     75752      3760
Memory usage before/after figure[ 4] =3D    75752     77612      1860
Memory usage before/after figure[ 5] =3D    77612     79952      2340
Memory usage before/after figure[ 6] =3D    79952     82824      2872
Memory usage before/after figure[ 7] =3D    82824     84656      1832
Memory usage before/after figure[ 8] =3D    84656     86784      2128
Memory usage before/after figure[ 9] =3D    86784     89312      2528

Daniel McQuillen wrote:

>
> I've seen a few posts regarding using the trick of laying one axes 
> over top of the other to simulate a second Y axis -- as demonstrated 
> in the matplotlib example file two_scales.py...
>
> Is there a way to bring the bottom graph into "focus"?

I see that zooming the graph made by two_scales.py zooms the points and 
the right hand y axis but not the left hand one.  Is this what you mean?

Hi all, I am working on a UI design, and I just found out about matplotlib. I 
would like to learn if some of the following graphs are possible using 
matplotlib with wxPython (to see if anyone has done something similar).  Here is 
a mockup with some graphs we'd like to have.

http://www.geocities.com/belred1/image1.jpg

Does anyone know if matplotlib has rich charting functionality with gradients 
and shading that could provide the same experience as the performance charts on 
the right. How difficult would this be to implement?

Also, do you know if there are any commercial or popular open source projects 
that are using matplotlib that i can look at?

Thanks,

Bryan

I would like to propose expanding the inputs of pcolor to take  
vectors.  Often, you have x and y independent (seperable), and you  
don't want to go on constructing an x array of redundant values.   
Actually, in NumPy it is not straightforward to do this with resize  
if your variable is in the first dimension like time (well, there is  
meshgrid, but you would only use it for plotting, and with two  
vectors -- see below).  Since NumPy makes such heavy use of array  
broadcasting, it is not necessary.

I think MPL should follow the spirit of array broadcasting, and make  
it such that:

x = arange(10)
y = arange(30)
z = rand(30,10)
pcolor (x, y, z)

will work as expected.  Perhaps, we could require a NewAxis in the  
right places, but it would also make sense without. You should also  
be able to send in just one vector.  Consider

x,y = meshgrid(arange(10), arange(30))
y = y + random.normal(size=y.shape)
z = random.random(y.shape)
pcolor (x, y, z)
% but x is still essentially just arange(10)
pcolor(arange(10), y, z)

What do you all think?

-Rob.


-----
Rob Hetland, Assistant Professor
Dept of Oceanography, Texas A&M University
p: 979-458-0096, f: 979-845-6331
e: he...@ta..., w: http://pong.tamu.edu

are there any commercial or popular open source projects using matplotlib?

thanks,

bryan

Hi all, I am working on a UI design, and I just found out about matplotlib. I 
would like to learn if some of the following graphs are possible using 
matplotlib with wxPython (to see if anyone has done something similar).  Here is 
a mockup with some graphs we'd like to have.

http://www.geocities.com/belred1/image1.jpg

Does anyone know if matplotlib has rich charting functionality with gradients 
and shading that could provide the same experience as the performance charts on 
the right. How difficult would this be to implement?

Thanks,

Bryan

Hi everybody. Question about multiple Y axes...

I've seen a few posts regarding using the trick of laying one axes over top of the other to simulate a second Y axis -- as demonstrated in the matplotlib example file two_scales.py.

However, in the application I'm building, the user should be able to select points ("outliers") for either axis. With the current approach, the user can't select the bottom graph's points (or pan or zoom it).

Is there a way to bring the bottom graph into "focus"?

Thanks in advance for any tips.



=====================================
Daniel McQuillen 
Oakland, CA

The egg was compiled with numpy 0.9.6, which is what needs to be used.
 The Matrix error looks familiar.  Try searching the list archive.

- Charlie

On 5/10/06, Stephen Walton <ste...@cs...> wrote:
> I just tried, really just from curiousity, to install the 0.87.2 egg on
> my Kubutu 5.10 laptop, with numarray 1.5.1, numpy latest SVN, ipython
> latest SVN.  Setting numerix to numpy in matplotlibrc results in a
> segmentation fault when doing "ipython -pylab".  Setting numerix to
> numarray results in a long traceback the end of which reads:
>
>   File
> "/usr/lib/python2.4/site-packages/matplotlib-0.87.2-py2.4-linux-i686.egg/=
matplotlib/artist.py",
> line 4, in ?
>     from transforms import identity_transform
>   File
> "/usr/lib/python2.4/site-packages/matplotlib-0.87.2-py2.4-linux-i686.egg/=
matplotlib/transforms.py",
> line 189, in ?
>     from _transforms import Value, Point, Interval, Bbox, Affine
>   File
> "/usr/lib/python2.4/site-packages/matplotlib-0.87.2-py2.4-linux-i686.egg/=
matplotlib/_transforms.py",
> line 1, in ?
>     import sys, numerix
>   File
> "/usr/lib/python2.4/site-packages/matplotlib-0.87.2-py2.4-linux-i686.egg/=
matplotlib/numerix/__init__.py",
> line 62, in ?
>     from Matrix import Matrix
> ImportError: No module named Matrix
>
> If I download the tarball and build it from source, all is well.
>
>
>
> -------------------------------------------------------
> Using Tomcat but need to do more? Need to support web services, security?
> Get stuff done quickly with pre-integrated technology to make your job ea=
sier
> Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronim=
o
> http://sel.as-us.falkag.net/sel?cmd=3Dlnk&kid=3D120709&bid=3D263057&dat=
=3D121642
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

I just tried, really just from curiousity, to install the 0.87.2 egg on 
my Kubutu 5.10 laptop, with numarray 1.5.1, numpy latest SVN, ipython 
latest SVN.  Setting numerix to numpy in matplotlibrc results in a 
segmentation fault when doing "ipython -pylab".  Setting numerix to 
numarray results in a long traceback the end of which reads:

  File 
"/usr/lib/python2.4/site-packages/matplotlib-0.87.2-py2.4-linux-i686.egg/matplotlib/artist.py", 
line 4, in ?
    from transforms import identity_transform
  File 
"/usr/lib/python2.4/site-packages/matplotlib-0.87.2-py2.4-linux-i686.egg/matplotlib/transforms.py", 
line 189, in ?
    from _transforms import Value, Point, Interval, Bbox, Affine
  File 
"/usr/lib/python2.4/site-packages/matplotlib-0.87.2-py2.4-linux-i686.egg/matplotlib/_transforms.py", 
line 1, in ?
    import sys, numerix
  File 
"/usr/lib/python2.4/site-packages/matplotlib-0.87.2-py2.4-linux-i686.egg/matplotlib/numerix/__init__.py", 
line 62, in ?
    from Matrix import Matrix
ImportError: No module named Matrix

If I download the tarball and build it from source, all is well.

>>>>> "seberino" == seberino  <seb...@sp...> writes:

    seberino> I'd like to reinstall Matplotlib.  I installed from
    seberino> source......is this home grown install ALL under one
    seberino> directory in site-packages?

almost.

In addition to site-packages/matplotlib, we'll also install

site-packages/pylab.py
site-packages/pytz       # iff it doesn't already exist
site-packages/dateutil   # iff it doesn't already exist
site-packages/subprocess # iff it doesn't already exist

JDH

I'd like to reinstall Matplotlib.

I installed from source......is this home grown install
ALL under one directory in site-packages?

chris

>>>>> "manouchk" == manouchk  <man...@gm...> writes:

    manouchk> Hi, I've seen nothing about installing pytz, dateutil
    manouchk> that are usefull for matplotlib-users. In mandriva I

They are required for date plotting ....

    manouchk> think that this 2 packages are not yet in any
    manouchk> package. What is the common way to include them? (any
    manouchk> one can point me for example to a fedora rpm spec file
    manouchk> that does the work??)

    manouchk> I have a directory named
    manouchk> /usr/lib/python2.4/site-packages/pytz/zoneinfo that is
    manouchk> included in python-matplotlib package but no module pytz
    manouchk> so that date_demo*.py examples don't work.

They ship with the matplotlib src distribution.  You may have a
partial install, which may be preventing a full instal since
matplotlib checks for their existence before overriding an existing
install.

Get a copy of the matplotlib src distribution, and

  > sudo rm -rf /usr/lib/python2.4/site-packages/pytz
  > sudo rm -rf /usr/lib/python2.4/site-packages/dateutil

and then reinstall matplotlib to see if you get a proper install.

JDH