matplotlib-users Mailing List for matplotlib

>>>>> "Eugene" == Eugene A Suchkov <Cit...@in...> writes:

    Eugene> 1) I can't make 2 plots using WX-backend sequentially

Do you need to use matplotlib interactively from the prompt, or do you
simply need to make 2 figures?

The latter is easy

    import matplotlib
    matplotlib.use('WX')
    from matplotlib.matlab import *
    figure(1)
    plot([1,2,3,4])
    figure(2)
    plot([1,4,9,16])
    show()

For interactive mode, as suggested earlier, we're still ironing out
the bugs regarding interactivity and WX.

Thanks!
John Hunter

>>>>> "Eugene" == Eugene A Suchkov <Cit...@in...> writes:

    Eugene> When I'm performing smth like:

    Eugene> tl=get_xticklabels(...)  for l in tl: print get_text(l)

    Eugene> I'm wondering why tl is a correct list, but with empty
    Eugene> text :(

This is related to the first problem you are having.  When you are not
running matplotlib in interactive mode, nothing on the plotting side
is done until you call 'show()'.  The reason for this is that the
backend doesn't have access to the gtk primitives until the window is
realized.

If you start your script with

  >>> import matplotlib
  >>> from matplotlib.matlab import *
  >>> from matplotlib.backends.backend_gtk import ShowOn
  >>> ShowOn().set(1)  # turning on interactive mode

and turn on interactive mode, then you can, for example, print the
labels before calling show, as in the script below.

Note however, whether or not you are in interactive mode, you will be
able to control the text properties, as in 

  ax = subplot(111)
  ax.plot([1,2,3])
  tl = ax.get_ticklabels()
  set(tl, 'color', 'r')

You aren't the first one to be confused about interactive mode
vis-a-vis the various backends.  It's not a trivial issue since both
the GTK and WX backend have event loops that they go into, but it's a
high priority since it's causing trouble for several people.
Hopefully by the next minor release we'll have it worked out.....

import matplotlib
from matplotlib.matlab import *
from matplotlib.backends.backend_gtk import ShowOn
ShowOn().set(1)  # turning on interactive mode

t = arange(0.0, 3.0, 0.01)
s = sin(2*pi*t)
ax = subplot(111)
ax.plot(t,s)
tl = ax.get_xticklabels()
for l in tl:
    print l.get_text()

show()

>>>>> "Todd" == Todd G Gardner <pi...@ea...> writes:

    Todd> Hello all, Please pardon my ignorance as I am fairly new to
    Todd> matplotlib.

    Todd> I have 1000 sets of (x,y) data.  I would like to cycle
    Todd> through this data by graphing set 1 then 2 then ... 1000.

    Todd> How can I refresh a plot without closing and reopening that
    Todd> plot?

Pekko Piirola <pek...@he...> sent me an example some time
ago that cycles through a data set.  Currently this example only works
in the GTK backend, but we're actively working on getting a unified
GUI interface to allow for this kind of thing.  You may also want to
take a look at examples/system_monitor.py and examples/dynamic_demo.py
which show how to dynamically update a plot.

#!/usr/bin/env python2.3

import matplotlib.matlab
import gtk
import Numeric

fig = matplotlib.matlab.figure(1)
ind = Numeric.arange(60)
x_tmp=[]
for i in range(100):
    x_tmp.append(Numeric.sin((ind+i)*Numeric.pi/15.0))

X=Numeric.array(x_tmp)
lines = matplotlib.matlab.plot(X[:,0],'o')

def updatefig(*args):
    updatefig.count += 1
    if updatefig.count>59: updatefig.count=0
    lines[0].set_data(ind,X[:,updatefig.count])
    fig.draw()
    return gtk.TRUE

updatefig.count=-1

gtk.timeout_add(200,updatefig)
matplotlib.matlab.show()

Hello all,

Please pardon my ignorance as I am fairly new to matplotlib.

I have 1000 sets of (x,y) data.  I would like to cycle through this data by
graphing set 1 then 2 then ... 1000.

How can I refresh a plot without closing and reopening that plot?

Any pointer would be greatly appreciated.

Todd

Hi Eugene,

On Sunday 28 December 2003 7:34 am, you wrote:
>
> I's really useful feature, e.g.:
>
> I have a WX program. It has some buttons, checkboxes, radiobuttons, to
> combine the options (detrending, plotting autocorrelation etc), and I
> can perform this options for any file with data. Now the user should
> quit this program to plot anothe graph... I's really tiring :(

Looking at this description, I wonder if it might be better for you to embed a 
figure in your application. You will then be able to build up the figure as 
you want it and hit the 'save' button, then maybe continue with changes, or 
clear the data in the chart.

The example 'embedding_in_wx.py' shows how to embed a Matplotlib chart in a 
wxFrame (and it works just as well if the PlotFigure class is derived from 
wxPanel, which is what you would probably do in a larger program than the 
short example).

The plotted data itself is stored in a FigureWx instance. This needs to be 
associated with a FigureManager and Toolbar instance if you want to be able 
to pan, zoom and save plot images.

In the example, the plotting is done in a single function, plot_data(). 
However, it is easy to add event handling functions which act on the Figure, 
e.g., if data is held in self.data_x and self.data_y, and the axis instance 
is self.axis:

(in __init__() for PlotFigure):
    EVT_BUTTON(self, ID_REGRESSION, self.onRegressionButton)

...

and new function:
def onRegressionButton(self, evt):
    reg_x, reg_y = PerformRegression(self.data_x, self.data_y)
    self.axis.plot(reg_x, reg_y)
    self.toolbar.update()
    self.fig.draw() 

Hope this helps. I'll make the changes for show() anyway - it is important to 
John and I that all backends are as close to identical as possible, and you 
have clearly identified the bug for me. Good luck, and thanks for the 
feedback.

Regards

Jeremy

Hi Eugene,

I've had a quick look into the problem for you, and I can't give an immediate 
solution, but I'll try to get a fix in the next few days.

I can say that in the original design, the intention was that show() would be 
the last line of any script. I know that John (author of virtually everything 
in Matplotlib except backend_wx) has recently made some changes to allow 
show() to be called more than once.

Unfortunately, the code needed to do thisis quite specific to each GUI 
library, and I cannot simply port what has been done for GTK (I've just tried 
something very close to the GTK implementation, and it doesn't work).

A few questions for John Hunter: 
I think I need to do something like the following:
- show() must now instantiate any figures already defined and enter the the 
main event loop. ShowOn needs to keep track of this.
- I need to keep track of the number of figures instantiated. I assume that 
Gcf.destroy() does this.
- I need to ensure that I do not exit when the last figure is destroyed, and 
therefore need to manage that I may need to create a new figure manager if 
there is none.

Have I missed anything?

Regards

Jeremy

Eugene A. Suchkov writes:
>
> Hi all!
> 
> There are some bug's I've found in two days I got started with echotag.
> 
> 1) I can't make 2 plots using WX-backend sequentially
> 
> For example:
> 
> ---CODE---
> 
> import matplotlib
> matplotlib.use('WX')
> from matplotlib.matlab import *
> plot([1,2,3,4])
> show()
> plot([1,4,9,16])
> show()
> 
> --END CODE--
> 
> Well, everything is OK, while building 1st graph, but then an error
> occurs:
> 
> --OUTPUT--
> 
> Traceback (most recent call last):
>   File "plot.py", line 7, in ?
>     plot([1,4,9,16])
>   File "/usr/lib/python2.2/site-packages/matplotlib/matlab.py", line
> 723, in plot    draw_if_interactive()
>   File
> "/usr/lib/python2.2/site-packages/matplotlib/backends/backend_wx.py",
> line 986, in draw_if_interactive    current_fig =
> Gcf().get_current_figwin().figure AttributeError: 'Gcf' object has no
> attribute 'get_current_figwin'
> 
> --END OUTPUT--
> It was tested on Linux and Windows. Versions 0.40 and 0.32
> 
> When I'm using GTK everything is OK with both graphs, but using WX is
> critical :(

Hi all!

There are some bug's I've found in two days I got started with echotag.

1) I can't make 2 plots using WX-backend sequentially

For example:

---CODE---

import matplotlib
matplotlib.use('WX')
from matplotlib.matlab import *
plot([1,2,3,4])
show()
plot([1,4,9,16])
show()

--END CODE--

Well, everything is OK, while building 1st graph, but then an error
occurs:

--OUTPUT--

Traceback (most recent call last):
  File "plot.py", line 7, in ?
    plot([1,4,9,16])
  File "/usr/lib/python2.2/site-packages/matplotlib/matlab.py", line
723, in plot    draw_if_interactive()
  File
"/usr/lib/python2.2/site-packages/matplotlib/backends/backend_wx.py",
line 986, in draw_if_interactive    current_fig =
Gcf().get_current_figwin().figure AttributeError: 'Gcf' object has no
attribute 'get_current_figwin'

--END OUTPUT--
It was tested on Linux and Windows. Versions 0.40 and 0.32

When I'm using GTK everything is OK with both graphs, but using WX is
critical :(

2) matplotlib-0.40:

When I'm performing smth like: 

tl=get_xticklabels(...)
for l in tl:
	print get_text(l)

I'm wondering why tl is a correct list, but with empty text :(

Version 0.32 is OK

P.S. 

Sorry for my bad english
-- 
Best regards
Eugene A. Suchkov
***************************
*      ICQ:177787156      *
* JID: cit...@ja... *
***************************
 

JH> 2) The http://www.forkosh.com/mimetex.html license is GPL, which in
JH>    my understanding is not really compatible with the PSF license.

You can always write them and ask for another license.
	-crt

>>>>> "Flavio" == Flavio C Coelho <fcc...@fi...> writes:

    Flavio> Hi John, I know that you are probably already overwhelmed
    Flavio> by maintenance and developmente of this great package, but
    Flavio> I came across a post on the mod_python list in which a
    Flavio> person was inquiring about the existance of a plotting
    Flavio> package for mod_python since mod_PHP and mod_Perl have
    Flavio> theirs.  I thought that this could be a great thing to add
    Flavio> to matplotlib: a mod_python backend. It would be awesome
    Flavio> if we could have scientific python applets that could
    Flavio> generate full graphical output on the web.

    Flavio> It shouldn't be too hard to do since it could use any of
    Flavio> the existing backends and just export the resulting figure
    Flavio> to mod_python to embed in a web page...

    Flavio> what do you think?

I am currently using matplotlib as a plotting backend for a web
server.  I'm working with a PHP developer who is writing the html, and
he calls an XML-RPC python server with the parameters for the plot.
The XML-RPC server does some number crunching, generates a plot with
matplotlib, saves it in a tmp dir, and passes the image filename back
to the PHP client.  I'm using the GTK backend running in an Xvfb.

I don't know much about apache, or what is involved in making
something for mod_python.  You wouldn't really need a 'mod_python
backend' would you?  My guess is that you would just need to import
matplotlib into your mod_python python code, for example using the GD
backend, and plot away.  Or is there something more to it?  

Do you know if you can use mod_python and mod_php together?  Can
functions written in one mod_* language communicate with functions
written in another.  My guess is not....  It would be great if I could
use mod_python and my front end person uses mod_php, and we could
communicate within apache w/o going through the XML-RPC server.

John Hunter 

>>>>> "Flavio" == Flavio C Coelho <fcc...@fi...> writes:

    Flavio> Hi John, I followed a discussion on the list a while ago,
    Flavio> where some suggestions were made as to how math
    Flavio> typesetting could be added to th plots. I don't know if
    Flavio> you have already made up your mind about how this should
    Flavio> be done in matplotlib, but I recently came across a good
    Flavio> and very light solution for typesetting equations from
    Flavio> latex code without having to use tex/latex in any way.

    Flavio> Its a small ansi C program called mimetex that generates a
    Flavio> bitmap directly from latex code. I have been using it as a
    Flavio> cgi for typesetting equations from latex code embedded in
    Flavio> html, and I am very happy with it. Take a look at its
    Flavio> website: http://www.forkosh.com/mimetex.html

Hi Flavio,

Thanks for the pointer - I'll definitely keep it in mind.  I have two
reservations

 1) bitmap output might be hard to support across the various
    backends, eg, postscript.  This limitation is probably not fatal,
    though, since postscript can instead use native TeX output.  I've
    been meaning to take a closer look at pyx -
    http://pyx.sourceforge.net - which has very nice postscript / TeX
    integration, to see how they pull it off.  Even if TeX / LaTeX
    were only supported in one matplotlib backend that would be better
    than none.

 2) The http://www.forkosh.com/mimetex.html license is GPL, which in
    my understanding is not really compatible with the PSF license.
    Ie, the python license (like the BSD, MIT and related licenses)
    permits more or less *any* non-warranted use of the code,
    including proprietary / closed source.  matplotlib is released
    under the PSF license.  GPL requires that code that uses it to
    also be open source / free software.  I have not thought about
    this deeply, or consulted a lawyer, so this is really just my
    impression after a somewhat cursory investigation, but it's a
    consideration.  Licensing gurus please weigh in here....

But these considerations aside, it's a very good suggestion.  At the
least, it would be nice to have it as a backend dependent optional
addon.  I've wanted to have the ability to plot an image in an axes
for some time (something like matlab's imshow).  If this functionality
existed, it would be relatively easy to plug the mimetex bitmaps into
it.  

JDH

Is it possible to use the wx backend interactively with a wx based shell?
And If so, is there any documentation on how to do so?

Thnx,
-Mike

Whenever I run a program that imports matplotlib, it requests pythonw 
rather than python. Here's the message:

This program needs access to the screen. Please run with
'pythonw', not 'python', and only when you are logged in on the main 
display
of your Mac.

Is there any way of getting around this? In particular, when I am 
running python remotely on the terminal, it will not let me use 
matplotlib since access to the screen is required. However, I would 
like to be able to generate plots to file (remotely) without ever 
showing them on the screen. Is there something I need to set in order 
to satisfy this?

Thanks,
--
Christopher J. Fonnesbeck ( c h r i s @ f o n n e s b e c k . o r g )
Georgia Cooperative Fish & Wildlife Research Unit, University of Georgia

>>>>> "Flavio" == Flavio C Coelho <fcc...@fi...> writes:

    Flavio> John, is there a way, in matplotlib, to emulate the
    Flavio> behavior of the matlab "hold" comand to plot multiple
    Flavio> datasets on a single figure?

The default behavior in matplotlib is 'hold on'.

Eg, 

  plot(x1, y1)
  plot(x2, y2)

Both plot to the same figure.

This is one way in which matplotlib differs from matlab.

Thanks for your quick reply.

On 2003.12.16, at 20:47 Japan, John Hunter wrote:

> Is this what you mean?

More precisely, what I mean is like the top-left plot in 
http://www.slac.stanford.edu/grp/ek/hippodraw/canvaswindow.png

If I understand bar() (then hist()) functionalities correctly, it may 
be unable to create such a plot currently without using plot().

from matplotlib.matlab import *
bins = [0, 1, 2, 3]
vals = [3, 4, 5]
x = [bins[0]]
y = [0]
vals.append(0)
for i in range(len(bins) - 1):
    x.append(bins[i])
    y.append(vals[i])
    x.append(bins[i + 1])
    y.append(vals[i])
    x.append(bins[i + 1])
    y.append(vals[i + 1])
plot(x, y)
show()

>>>>> "K" == K KISHIMOTO <ko...@us...> writes:

    K> If possible, I think it is nice for matplotlib to be able to
    K> plot histograms by not only bars but also lines.  My meaning of
    K> "bar histogram plotting" is like the bottom-left plot in
    K> http://jas.freehep.org/images/screenshots/gui2.gif and "line
    K> histogram plotting" is like the others.  There are two reasons.

If I understand you correctly, and from looking at the images you
linked to, all you need to do is set the edge and face properties of
the bars to the same color.  The default edge color is black and the
default face color is blue, so if you want a solid histogram do

    from matplotlib.matlab import *

    mu, sigma = 100, 15
    x = mu + sigma*randn(10000)

    n, bins, patches = hist(x, 200, normed=1)
    set(patches, 'edgecolor', 'b')
    show()

Is this what you mean?

    K> Off course, the bar histogram plotting is more smart in one
    K> case, but in another case the line is better.  In addition, the
    K> support of both bar and line histogram plotting will matplotlib
    K> to be able to have more plotting features that the colors of
    K> line and filled area can be specified separately by the user.

The axes function 'vlines' plots vertical lines.  See the
example/vline_demo.py

Cheers,
John Hunter

Hi,

On 2003.12.15, at 23:09 Japan, John Hunter wrote:

> OK, I'll give it some thought.  Sounds reasonable enough.  It doesn't
> break backwards compatibility, adds useful features, and is more
> consistent with bar.

Thank you so much!

If possible, I think it is nice for matplotlib to be able to plot 
histograms by not only bars but also lines.
My meaning of "bar histogram plotting" is like the bottom-left plot in 
http://jas.freehep.org/images/screenshots/gui2.gif and "line histogram 
plotting" is like the others.
There are two reasons.
(1) Because one bin width becomes a few pixcels, it is hard to see when 
the number of bins is about a few thousand in the bar histogram 
plotting mode.
(2) The color of all of the data filled area become the same by using 
bar and one can specify the line color separately. This brings smart 
view when multiple histograms are plotted like in 
http://root.cern.ch/root/html/examples/gif/hsum.gif

Off course, the bar histogram plotting is more smart in one case, but 
in another case the line is better.
In addition, the support of both bar and line histogram plotting will 
matplotlib to be able to have more plotting features that the colors of 
line and filled area can be specified separately by the user.

It seems that it is relatively not difficult to implement the feature 
by connecting points of [(x0, 0), (x0, y0), (x1, y0), (x1, y1), (x2, 
y1), (x2, y2), ...(and so on)] and will also not break backwards 
compatibility.

If possible, please give a consideration to this.


>>>>>> "K" == K KISHIMOTO <ko...@us...> writes:
>
>     K> I am sorry that my last explanation was insufficient.  The
>     K> point is that I think it is inefficient to execute the
>     K> following two lines in matplotlib.mlab.hist when I know the
>     K> result of "n" already.
>
> Good point ...
>
>     K> Another point is hist() does not support error bar plot (but
>     K> bar() called from hist() does support.)
>
> Another good point....
>
>     K> So, I propose again def hist(x, bins=10, noplot=0, normed=0,
>     K> weights=None, errors=None , **kwargs): in matplotlib.matplab.
>     K> I think if matplotlib supports this by default, it is very
>     K> smart and usefull to many users when making histogram plots
>     K> with matplotlib than letting hist() be mainly for the purpose
>     K> of "calculating" histograms.
>
> OK, I'll give it some thought.  Sounds reasonable enough.  It doesn't
> break backwards compatibility, adds useful features, and is more
> consistent with bar.
>
> JDH
>

>>>>> "Christopher" == Christopher Fonnesbeck <ch...@fo...> writes:

    Christopher> ... I'm not sure why I'd want to use gtk instead of
    Christopher> wx anyhow, given the choice.

One more option.  If all you want is the batch generation of figures
offline with no display, you can use either the PS or GD backends.  PS
only requires Numeric.  gd, however, takes some energy to build.

But it works: I just built all the prereqs on OSX from source and it
worked perfectly.

You need

libjpeg - http://freshmeat.net/redir/libjpeg/5665/url_tgz/jpegsrc.v6b.tar.gz

    ./configure
    sudo make
    sudo cp libjpeg.a /usr/local/lib/
    sudo cp *.h /usr/local/include/

libpng - http://umn.dl.sourceforge.net/sourceforge/libpng/libpng-1.2.5.tar.gz

    cp scripts/makefile.macosx Makefile
    sudo make install


You then need to follow the build instructions for gd, gdmodule and
dependencies at

http://matplotlib.sourceforge.net/backends.html#GD

Here's an example script ....

import matplotlib
matplotlib.use('GD')
from matplotlib.matlab import *

t = arange(0.0, 3.0, 0.01)
for i in range(1,10):
    figure(1)
    s = sin(2*pi*i*t)
    plot(t,s)
    savefig('plot%02d' % i)
    close(1)

I put all this here mainly for archival purposes in case someone wants
to use matplotlib / OSX / gdmodule.  We'll get the wx thing figured
out too ....

JDH

>>>>> "Christopher" == Christopher Fonnesbeck <ch...@fo...> writes:

    Christopher> ... I'm not sure why I'd want to use gtk instead of
    Christopher> wx anyhow, given the choice.

No compelling reason.  The GTK backend was the first and probably the
most stable for that reason.  This is the first release with the wx
backend, so there are likely some bugs lurking that will have to be
found and stamped out.

    Christopher> I'm trying to keep my plotting in a separate module
    Christopher> from everything else, so that I don't have to make
    Christopher> changes all over the place when I change my plotting
    Christopher> code. For example, plot_histogram() can be called
    Christopher> from any other module without knowing how the plot is
    Christopher> implemented. If I have to call show() from each
    Christopher> module that uses the plotting module, it will start
    Christopher> to get messy. Outside of the Plot module, the rest of
    Christopher> my code shouldn't have to know anything about
    Christopher> matplotlib. So, I'd like to be able to gererate and
    Christopher> save a plot, then move on to the next piece of
    Christopher> code. I'm trying to use your package in place of
    Christopher> scipy, which is what I have been using to generate
    Christopher> plots up until now; hopefully I can make it work.

Would you like this to run 'offline' so that no windows pop up as you
create the figures, or is it enough simply that you can create them
one at a time in batch mode with the plot functionality encapsulated?

I just installed wxpython and matplotlib on OS X, so I'll have a
chance to delve into this issue a bit....

John Hunter

On Dec 15, 2003, at 3:29 PM, John Hunter wrote:
>
>
>     Christopher> I'm trying to use matplotlib on OSX (so with WX
>     Christopher> rather than gtk) in conjunction with my own code that
>
> Not necessarily.  pygtk, gtk-2, etc... have been packaged for fink.
> I'm going to try and install them on my powerbook when I get a few
> minutes.

I like to avoid fink unless I absolutely have to use it -- it ends up 
installing a whole bunch of packages that I already have elsewhere on 
my machine, thereby creating the need to maintain multiple 
installations of the same package.

... I'm not sure why I'd want to use gtk instead of wx anyhow, given 
the choice.

>
> show must be the last line of your script.  Is it possible to do all
> the figures in the loop and then call show?  If your number of figures
> is very large, you could run into memory problems this way.  There is
> a work-around, but if you can do it all in memory that is the easiest
> solution
>
> for i in range(1,10):
>     figure(i)
>     # do plot i
>     savefig('plot%d'%i)
> show()
>
> This is an area that I am actively working on (in fact I was working
> on it when you emailed!) so if this isn't a viable solution for you
> let me know.  I'm implementing some features to make it easier to use
> matplotlib in with xvfb (virtual x) so you can produce plots in wx or
> gtk without launching the GUI windows.
>
>

I'm trying to keep my plotting in a separate module from everything 
else, so that I don't have to make changes all over the place when I 
change my plotting code. For example, plot_histogram() can be  called 
from any other module without knowing how the plot is implemented. If I 
have to call show() from each module that uses the plotting module, it 
will start to get messy. Outside of the Plot module, the rest of my 
code shouldn't have to know anything about matplotlib. So, I'd like to 
be able to gererate and save a plot, then move on to the next piece of 
code. I'm trying to use your package in place of scipy, which is what I 
have been using to generate plots up until now; hopefully I can make it 
work.


--
Christopher J. Fonnesbeck ( c h r i s @ f o n n e s b e c k . o r g )
Georgia Cooperative Fish & Wildlife Research Unit, University of Georgia

>>>>> "Christopher" == Christopher Fonnesbeck <ch...@fo...> writes:

    Christopher> code for some reason, but instead hangs. When I try
    Christopher> and close the plot manually, it terminates the python
    Christopher> code. How can I get matplotlib to produce a new plot
    Christopher> each time it is called, moving on after each plot is
    Christopher> produced, displayed and saved to file. Here is a
    Christopher> sample function from my code:

For the GTK backend, there is another solution.  The call to 
ShowOn().set(1) tells matplotlib to execute the commands as they are
issued, which was originally designed for people using matplotlib
from the python shell but also applies to your case, where you want to
generate a bunch of figures one at a time


import matplotlib
matplotlib.use('GTK')
from matplotlib.matlab import *
from matplotlib.backends.backend_gtk import ShowOn
ShowOn().set(1)  

t = arange(0.0, 3.0, 0.01)
for i in range(1,10):
    figure(1)
    s = sin(2*pi*i*t)
    plot(t,s)
    savefig('plot%02d' % i)
    close(1)


*Note there is no call to show at the end*

The same trick *does not* currently work with the WX backend, though
perhaps Jeremy can take a look at it and determine why not.  Somehow
the call the ShowOn().set(1) seems to screw it up.

We'll look into it...

JDH

>>>>> "Christopher" == Christopher Fonnesbeck <ch...@fo...> writes:

    Christopher> First off, I want to congratulate the authors of
    Christopher> matplotlib for making a great package. This is the
    Christopher> python plotting library I've been waiting for.

Thanks!

    Christopher> I'm trying to use matplotlib on OSX (so with WX
    Christopher> rather than gtk) in conjunction with my own code that

Not necessarily.  pygtk, gtk-2, etc... have been packaged for fink.
I'm going to try and install them on my powerbook when I get a few
minutes.

    Christopher> produces Markov chain Monte Carlo simulations. At the
    Christopher> end of the simulation, I try to plot traces and
    Christopher> histograms of all of the sampled values. However,
    Christopher> matplotlib gets stuck on the first plot. After
    Christopher> calling show(), it does not move to the next line of
    Christopher> code for some reason, but instead hangs. When I try
    Christopher> and close the plot manually, it terminates the python
    Christopher> code. How can I get matplotlib to produce a new plot
    Christopher> each time it is called, moving on after each plot is
    Christopher> produced, displayed and saved to file. Here is a
    Christopher> sample function from my code:

show must be the last line of your script.  Is it possible to do all
the figures in the loop and then call show?  If your number of figures
is very large, you could run into memory problems this way.  There is
a work-around, but if you can do it all in memory that is the easiest
solution

for i in range(1,10):
    figure(i)
    # do plot i
    savefig('plot%d'%i)
show()

This is an area that I am actively working on (in fact I was working
on it when you emailed!) so if this isn't a viable solution for you
let me know.  I'm implementing some features to make it easier to use
matplotlib in with xvfb (virtual x) so you can produce plots in wx or
gtk without launching the GUI windows.

JDH

First off, I want to congratulate the authors of matplotlib for making  
a great package. This is the python plotting library I've been waiting  
for.

I'm trying to use matplotlib on OSX (so with WX rather than gtk) in  
conjunction with my own code that produces Markov chain Monte Carlo  
simulations. At the end of the simulation, I try to plot traces and  
histograms of all of the sampled values. However, matplotlib gets stuck  
on the first plot. After calling show(), it does not move to the next  
line of code for some reason, but instead hangs. When I try and close  
the plot manually, it terminates the python code. How can I  get  
matplotlib to produce a new plot each time it is called, moving on  
after each plot is produced, displayed and saved to file. Here is a  
sample function from my code:


def  
plot_histogram(data,name,nbins=None,xlab='Value',ylab='Frequency',suffix 
=''):
	'Internal histogram specification for handling nested arrays'
	
	'If there is only one data array, go ahead and plot it ... '
	if len(shape(data))==1:
		print 'Generating histogram of',name
		try:
			figure(1)
			nbins = min(nbins or 10,len(unique(data)))
			'Generate histogram'
			hist(data,nbins)
			'Plot options'
			xlabel(name)
			ylabel("Frequency")
			show()
			'Save to file'
			savefig("%s%s.png" % (name,suffix))
			close(1)
		except OverflowError:
			print '... cannot generate histogram'
	else:
		'... otherwise, plot recursively'
		tdata = swapaxes(data,0,1)
		for i in range(len(tdata)):

Thanks for any advice,
C.

--
Christopher J. Fonnesbeck ( c h r i s @ f o n n e s b e c k . o r g )
Georgia Cooperative Fish & Wildlife Research Unit, University of Georgia

matplotlib is a pure python 2D plotting library with a matlab syntax
which produces publication quality figures using in a variety of
hardcopy formats (PNG, JPG, TIFF, PS) and interactive GUI environments
(WX, GTK) across platforms.  matplotlib can be used in python scripts,
interactively from the python shell (ala matlab or mathematica), in
web application servers generating dynamic charts, or embedded in GTK
or WX applications.

  http://matplotlib.sourceforge.net

What's new

WX python backend

  Jeremy O'Donoghue has done an amazing job implementing the backend
  for wxpython, with all the features such as interactive navigation
  that are supported in the GTk backend.  matplotlib should not be
  available with a GUI anywhere wxpython, Numeric and python work,
  including linux and friends, win32, and Mac OS X.  See
  http://matplotlib.sourceforge.net/matplotlib.backends.backend_wx.html
  for a summary of known issues.

Pseudo color plots

  The pcolor command generates pseudo color plots.  See
  http://matplotlib.sourceforge.net/screenshots.html#pcolor_demo and
  http://matplotlib.sourceforge.net/screenshots.html#mri_with_eeg for
  screenshots and example code

New time-series plotting functions
  
  * psd - plots the power spectral density of a time series
  * csd - plots the cross spectral density of two time series
  * cohere - plots the coherence

  See the examples dir in the src distro: psd_demo.py and csd_demo.py

Substantially improved layout

  The transform architecture was refactored, allowing much more
  precise layout.  Lines, patches, text, etc... can now be placed and
  scaled in arbitrary units, relative axes units, or physical size.
  Applicaiton programmers who want to create lines, patches and text
  directly using the API should read the transform module docs for
  more info.  See the text help for an example of how to specify text
  locations in axes coords (0,0 is lower left and 1,1 is upper right)

Expanded legend capabilities

  The legend class is improved, with a more sophisticated layout
  engine and the ability to accept lines and rectangle patches as an
  optional first argument to specify which lines/patches make up the
  legend.  There are also additional legend placement locations, like
  'upper center'.  See
  http://matplotlib.sourceforge.net/screenshots.html#legend_demo

Expanded errorbar capabilities

  Gary Ruben contributed some code to support x and y errorbars,
  either symmetrix or asymettric, in one enhanced function 'errorbar'.
  See the errorbar_demo.py for examples of all the wild and wonderful
  errorbar styles.  Bar charts can now also display errorbars; see
  http://matplotlib.sourceforge.net/screenshots.html#barchart_demo

Figure size and DPI controllable from matlab interface

  The figure command now takes optional args figsize and dpi to set
  the figure size and DPI in the matlab interface.  This change
  involved some changes in the way default sizes and resolutions were
  handled among the various backends, with the effect that figures
  generated by existing scripts may appear different, eg, in the
  relative size of text to the figure elements.  The advantage is that
  the current implementation does a better job of computing true sizes
  with increased fidelity between backends.  Apologies for any
  inconveniences!

API changes

  There have been some minor changes to the API for those using
  matplotlib embedded in GTK applications.  

  * If you instantiate an Axes of Subplot intace, the first arg to
    __init__ must be the figure that contains it.

  * If you instantiate any artists, eg, Line2D, Rectangle, or
    AxisTextGTk, you must initialize them with their dpi, bbox, and
    transforms.  See the help for the transforms modules and the
    examples logo.py and mri_with_eeg.py, where the objects are
    explicity created using the new API.

  * The only change to the matlab interface is in the signature of the
    errorbar func, which breaks matlab compatibility for the enhanced
    ability to do x and y errorbars.

  * See matplotlib.axes.py for a complete list of API changes


John Hunter

>>>>> "K" == K KISHIMOTO <ko...@us...> writes:

    K> I am sorry that my last explanation was insufficient.  The
    K> point is that I think it is inefficient to execute the
    K> following two lines in matplotlib.mlab.hist when I know the
    K> result of "n" already.

Good point ...

    K> Another point is hist() does not support error bar plot (but
    K> bar() called from hist() does support.)

Another good point....

    K> So, I propose again def hist(x, bins=10, noplot=0, normed=0,
    K> weights=None, errors=None , **kwargs): in matplotlib.matplab.
    K> I think if matplotlib supports this by default, it is very
    K> smart and usefull to many users when making histogram plots
    K> with matplotlib than letting hist() be mainly for the purpose
    K> of "calculating" histograms.

OK, I'll give it some thought.  Sounds reasonable enough.  It doesn't
break backwards compatibility, adds useful features, and is more
consistent with bar.

JDH

Thank you for your reply.

> def func1(x=None):
>     if x is None: x = []
>     #blah blah

The indication is right.
I should have done so. Thank you.

> This seems like the kind of thing that would best be done in your user
> library.  Eg, if you make a module mymatplotlib.py, you can defined
> your own hist.  In that file, just import matplotlib.matlab and call
> matplotlib.matlab.hist within it.  In fact, matplotlib.matlab.hist
> calls matplotlib.mlab.hist.

I am sorry that my last explanation was insufficient.
The point is that I think it is inefficient to execute the following 
two lines in matplotlib.mlab.hist when I know the result of "n" already.
 >> n = searchsorted(sort(y), bins)
 >> n = diff(concatenate([n, [len(y)]]))

For the moment, I must insert extra code
 >> y = [1.0] * 1000
(and hist(y, [0.0, 2.0]) calculates n = [1000], then plot the data.)
This is very expensive.

Another point is hist() does not support error bar plot (but bar() 
called from hist() does support.)

So, I propose again
def hist(x, bins=10, noplot=0, normed=0, weights=None, errors=None , 
**kwargs):
in matplotlib.matplab.
I think if matplotlib supports this by default, it is very smart and 
usefull to many users when making histogram plots with matplotlib than 
letting hist() be mainly for the purpose of "calculating" histograms.

Example rough code.
------
def hist(x, bins=10, noplot=0, normed=0, weights=None, xerr=None, 
yerr=None, **kwargs):
    if noplot:
       if weights == None:
          return mlab.hist(x, bins, normed)
       else:
          return (weights, bins)
    else:
       try:
          if weights == None:
             ret = gca().hist(x, bins, normed)
          else:
             ret = gca().bar(bins, weights, xerr=xerr, yerr=yerr, 
**kwargs)
       except ValueError, msg:
          msg = raise_msg_to_str(msg)
          error_msg(msg)
          raise RuntimeError, msg
    draw_if_interactive()
    return ret