matplotlib-users — Discussion related to using matplotlib

[Matplotlib-users] color

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

Two questions and a comment:

Q1. For 'figure' I'm not seeing any effect
of edgecolor (on screen).  Isn't this the
color of the border between the face (or
frame) and the figure (as determined by axes)?

Q2. Can line colors be set to arbitrary rgb colors using
matlab.plot?  If so, what is the syntax?
If not, can this be a feature request?

Minor comment:
is the 'y' yellow needed for a Matlab match?
If not, it needs adjustment IMHO.

fwiw,
Alan Isaac

Re[2]: [Matplotlib-users] xzeroaxis

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

On Thu, 09 Sep 2004, John Hunter apparently wrote:
>     # set the locations of the xticks
>     xticks( arange(6) )

>     # set the locations and labels of the xticks
>     xticks( arange(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue') )

Just for context, there is much I can do with Matplotlib
that I cannot do in gnuplot, and vice versa.  Naturally I
want the best of both worlds ...

In gnuplot, I can
set xtics axis 
to put the tics (both the tics themselves and the
accompanying labels) along the zeroaxis (If the zeroaxis is
very close to the border, the axis option will move the tic
labels to outside the border.)

Now that you have given us axhline as a generalization of
gnuplot's
set xzeroaxis
please consider letting xticks take an optional "loc"
argument, which could either be "border" or a number to be
interpreted as a 'y' value.

So, e.g.,
axhline()
xticks(arange(5),loc=0)
would draw an xzeroaxis and
put the xtics along it.

Am I overlooking an obvious way to do this (in the
matlab module)?

fwiw,
Alan

Re: [Matplotlib-users] turn off antialiasing

[Peter G. <pgr...@ge...>]

Eli Glaser wrote:

>You can also use ImageMagick.  I believe the command is:
>
>convert -delay 20 c:/myimages/img*.png c:/myvideo/imgs.mpg
>  
>
might also note that to use this you will need to have mpeg2encode 
installed... ImageMagic does not depend on this directly so you will 
have to do the install yourself...

i initially used 'convert' for my purposes, but it is much more limited 
than mencoder (ex. frame rates)...

peter

Re: [Matplotlib-users] turn off antialiasing

[Darren D. <dd...@co...>]

On Monday 20 September 2004 09:56 pm, you wrote:
>
> ..you can play with lots of settings in the line above... for example
> the dimensions of your images will probably be different... the codec
> you use might also vary.. i wanted something that would be usable by
> many windows users.. (note that with wmv2 some still have to get codec
> updates)..  note that this command will use all the images in the
> current working directory..
>

OOOH, I have been avoiding figuring out how to do this sort of work to create 
movies for my thesis defense. I guess that means I have to graduate.

-- 

Darren Dale

Re: [Matplotlib-users] turn off antialiasing

[Peter G. <pgr...@ge...>]

John Hunter wrote:

>>>>>> "Peter" == Peter Groszkowski <pgr...@ge...> writes:
>>>>>
>
> Peter> use mplayer to put the png images together.. results are
> Peter> quite nice...
>
> Can you post the command you use to play the pngs? Can mplayer output
> an avi or mpg, or does it just animate the images.
>
i use something like this:

mencoder mf://*.png -mf type=png:w=600:h=500:fps=10 -ovc lavc -lavcopts 
vcodec=wmv2 -oac copy -o animation.avi

it creates an avi file as you can probably guess... initially i started 
to play with animated images (gifs) but they would be waaaay too large 
for my purposes...

..you can play with lots of settings in the line above... for example 
the dimensions of your images will probably be different... the codec 
you use might also vary.. i wanted something that would be usable by 
many windows users.. (note that with wmv2 some still have to get codec 
updates)..  note that this command will use all the images in the 
current working directory..

finally, mencoder comes with mplayer.. .the easiest is to do:

apt-get install mplayer

this will work for debian users, and redhat/fedora (althought you would 
have to get apt-get first - try here: http://apt.freshrpms.net/ )...

-- 
Peter Groszkowski         Gemini Observatory
Tel: +1 808 974-2509      670 N. A'ohoku Place
Fax: +1 808 935-9235      Hilo, Hawai'i 96720, USA

Re: [Matplotlib-users] turn off antialiasing

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

You can also use ImageMagick.  I believe the command is:

convert -delay 20 c:/myimages/img*.png c:/myvideo/imgs.mpg

Eli

----- Original Message ----- 
From: "John Hunter" <jdh...@ni...>
To: "Peter Groszkowski" <pgr...@ge...>
Cc: "Christian Kristukat" <ge...@ho...>;
<mat...@li...>
Sent: Monday, September 20, 2004 4:50 PM
Subject: Re: [Matplotlib-users] turn off antialiasing


> >>>>> "Peter" == Peter Groszkowski <pgr...@ge...> writes:
>
>     Peter> use mplayer to put the png images together.. results are
>     Peter> quite nice...
>
> Can you post the command you use to play the pngs?  Can mplayer output
> an avi or mpg, or does it just animate the images.
>
> I saw from the man pages that something like
>
>  mplayer mf=type=png:fps=25 mf:/filemask
>
> is required, but I don't know how to set the filemask of if this is
> the right approach.  I'd like to add some instructions to the FAQ.
>
> Thanks,
> JDH
>
>
> -------------------------------------------------------
> This SF.Net email is sponsored by: YOU BE THE JUDGE. Be one of 170
> Project Admins to receive an Apple iPod Mini FREE for your judgement on
> who ports your project to Linux PPC the best. Sponsored by IBM.
> Deadline: Sept. 24. Go here: http://sf.net/ppc_contest.php
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Re: [Matplotlib-users] turn off antialiasing

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

>>>>> "Peter" == Peter Groszkowski <pgr...@ge...> writes:

    Peter> use mplayer to put the png images together.. results are
    Peter> quite nice...

Can you post the command you use to play the pngs?  Can mplayer output
an avi or mpg, or does it just animate the images.

I saw from the man pages that something like

 mplayer mf=type=png:fps=25 mf:/filemask

is required, but I don't know how to set the filemask of if this is
the right approach.  I'd like to add some instructions to the FAQ.

Thanks,
JDH

Re: [Matplotlib-users] turn off antialiasing

[Peter G. <pgr...@ge...>]

>>
>> An alternative approach is to save a series of PNGs and use one of
>> many programs on the web to turn a series of images into a mpeg or
>> AVI.  Perhaps then powerpoint won't try and be so helpful :-)
>
>
> Yes, that could be an idea.

I do this all the time... infact create daily movies of the forces 
exerted on our primary mirrors during nightly observing..

use mplayer to put the png images together.. results are quite nice...

-- 
Peter Groszkowski         Gemini Observatory
Tel: +1 808 974-2509      670 N. A'ohoku Place
Fax: +1 808 935-9235      Hilo, Hawai'i 96720, USA

Re[2]: [Matplotlib-users] compresson ratio

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

Hi John,

Since I read your previous message so poorly, I really
appreciate your willingness to communicate again.

At the moment I'm overcaffeinated and underslept, so
I may do as badly again.

I just do not quite "get it" yet.  I think I do
not fully understand xlim and ylim.

What I have been doing up to now to get what I need
is to use figsize and 'axes' to determine the aspect
ratio of the viewport (AR(V), the screen area where the
data will be displayed) and then (after the plot)
'axis' to determine the aspect ratio of the viewing window
(AR(W), the relative lengths of the axes in data units).

OK, I see all these same steps, with the only thing
new that instead of having to plug the right numbers
into 'axis', I get a keyword instead.  (That "only"
is comparative, not disparaging, of course.)

So here is what I think you are offering: a keyword
that will set the same "width" of data to be displayed
on each axis, so that the AR(W)=1.  This means that
I can determine the compression ration CR=AR(W)/AR(V)
from AR(V) alone.  And in particular, if I use figsize
and 'axes' to give me AR(V)=1, then axis('equal') will
produce a compression ratio of unity as well.

Do I have that right?

If so:
i. this seems useful
ii. this seems somewhat related to the behavior of
axis('square') in Matlab, if I read the documentation right
http://www.mathworks.com/access/helpdesk/help/techdoc/ref/axis.html
iii. This does *not* seem to be like the behavior of
Matlab's axis('equal')

I'm not a Matlab user, but (relying on the documentation)
here is an example of the kind of thing I think you get
from axis('equal') in Matlab:

#define function to graph
def f(x): return 2*x**3-5*x
#choose points in domain for plotting
d=(arange(401)-200.0)/100
#set figure size for plot
figure(1,figsize=(2,5))
#determine AR(V) = AR(W) = 5/2
axes([0.1, 0.1, 0.8, 0.8])
plot(d,f(d))
#determine AR(W) = 5/2
axis([-2,2,-5,5])
show()

Conceptually this works a little backwards, of course.
What you really know first is the AR(W) that you want,
and you choose the AR(V) to yield a compression ratio
of unity (so that the units match along each axis).

So if I have understood correctly, you have indeed offered
something that can be useful, but it should have a different
name.  Or this may be overcaffeinated babble.  Gotta run...

fwiw,
Alan

Re: [Matplotlib-users] compresson ratio

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

>>>>> "Alan" == Alan G Isaac <ai...@am...> writes:


    Alan> OK, this does not work for me.  Test case:
    Alan> d=arange(201)*pi/100 plot(cos(d),sin(d)) square() show()
    Alan> This should look like a circle.  It looks like an oval.

    Alan> Problems: 1. fig.set_figsize_inches is ignored.  It has no

Right, I noted this in my original post - if you continue that
post where I posted this code:

    It's the right idea, but it doesn't work currently if you are
    using a GUI backend.  The reason it fails is has to do with the
    pipeline order in which figure managers, figures etc are created
    by default, and the fact that configure events and resize events
    change the figure width and height (so you can for example, resize
    your figure window).  It *does* work if you specify the figure
    size

    figure(figsize=(8,8))

This is a bug, as I mentioned before, but will require some thought
about how to get this right across backends.

    Alan> 2. axis('equal') should not be desirable, if it is matlab
    Alan> compatible
    Alan> http://www.mathworks.com/access/helpdesk/help/techdoc/ref/axis.html
    Alan> That is, square() should set an axis aspect ratio of unity,
    Alan> but axis('equal') should equate the *unit length* along each
    Alan> axis.  (For my example circle this is not a problem, but in
    Alan> generaly this is completely wrong.)

With the amended axes code I'm attaching below, does this example work
as you hope

    from matplotlib.matlab import *
    figure(figsize=(8,8))
    ax = axes([0.1, 0.1, 0.8, 0.8])
    d=arange(201)*pi/100
    plot(10+cos(d),sin(d))
    axis('equal')
    show()

Perhaps more typing than you want for an interactive demo, but does
make everything clear and should work, at least up to the dpix/dpiy
error we discussed earlier.

If it works fine, I'll make it a FAQ.  I still have to handle the case
where the axis lim are decreasing...

JDH

def axis(*v):
    """
    axis() returns the current axis as a length a length 4 vector

    axis(v) where v= [xmin xmax ymin ymax] sets the min and max of the
    x and y axis limits

    axis('off') turns off the axis lines and labels

    axis('equal') sets the xlim width and ylim height to be to be
    identical.  The longer of the two intervals is chosen
    """
    
    if len(v)==1 and is_string_like(v[0]):
        s = v[0]
        if s.lower()=='on': gca().set_axis_on()
        elif s.lower()=='off': gca().set_axis_off()
        elif s.lower()=='equal':
            ax = gca()
            xmin, xmax = ax.get_xlim()
            ymin, ymax = ax.get_ylim()            
            width = xmax-xmin
            height = ymax-ymin
            # TODO: handle decreasing lim
            
            interval = max([width, height])
            ax.set_xlim((xmin, xmin+interval))
            ax.set_ylim((ymin, ymin+interval))            
            draw_if_interactive()
            
        else:
            error_msg('Unrecognized string %s to axis; try on or off' % s)
        return
    
    try: v[0]
    except IndexError:
        xlim = gca().get_xlim()
        ylim = gca().get_ylim()
        return [xlim[0], xlim[1], ylim[0], ylim[1]]
    
    v = v[0]
    if len(v) != 4:
        error_msg('v must contain [xmin xmax ymin ymax]')
        return 
    gca().set_xlim([v[0], v[1]])
    gca().set_ylim([v[2], v[3]])
    draw_if_interactive()

Re[2]: [Matplotlib-users] compresson ratio

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

On Tue, 14 Sep 2004, John Hunter apparently wrote:
>     def square():
>         fig = gcf()
>         ax = gca()
>         figw, figh = fig.get_size_inches()
>         l,b,axw,axh = ax.get_position()

>         side = min([figw, figh])
>         frac = min([axw, axh])

>         fig.set_figsize_inches(side, side)
>         ax.set_position([l,b,frac,frac])
>         axis('equal')
>         draw()


OK, this does not work for me.
Test case:
d=arange(201)*pi/100
plot(cos(d),sin(d))
square()
show()
This should look like a circle.
It looks like an oval.

Problems:
1. fig.set_figsize_inches is ignored.
It has no effect on figure size.
(It changes the size the figure reports,
as checked by printing it, but not the
size that is drawn---a missing argument
to draw?)
2. axis('equal') should not be desirable,
if it is matlab compatible
 http://www.mathworks.com/access/helpdesk/help/techdoc/ref/axis.html 
That is, square() should set an axis aspect ratio of unity,
but axis('equal') should equate the *unit length* along each
axis.  (For my example circle this is not a problem, but in
generaly this is completely wrong.)

Hope that's useful,
Alan Isaac

RE: [Matplotlib-users] date proposal / dropping python2.2 support

[Shin, D. <sd...@em...>]

> I am concerned about the performance and memory hit of using, for
> example, a list of a list of datetime objects rather than a numeric
> array of floats.  In the float representation, you can efficiently
> create a large date range array with, for example, the drange code I
> posted.

Yes. For intensive operations on time series, a list of datetime objects
will
slow overall performance down significantly.
Sometimes, I dream a sort of time array in numarray like string array, or
object array.
It can be implemented by holding a datetime object indicating an epoch
and an array of floating points indicating intervals from the epoch.

Daehyok Shin

Re: [Matplotlib-users] figure border and mapping window to data coordinates

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

>>>>> "Wayne" == Wayne Christopher <wa...@4r...> writes:

    Wayne> I have been using matplotlib with TkInter (TkAgg backend)
    Wayne> and it's really nice once I got the hang of it...  I have
    Wayne> two questions though, which I couldn't find in the manual.

    Wayne> 1. The figure window has a pretty large border around it,
    Wayne> that seems to expand as I enlarge the window.  Is there a
    Wayne> way to set this to, say, N pixels?

You cannot set it by pixel, but you can control it with the axes
command.  The syntax is axes([left, bottom, width, height]) where all
values are fractions of the figure.  Eg, left and width are fractions
of the figure width, and bottom, top are fractions of the figure
height.  With a little arithmetic, you can figure out what fractions
to use for a given pixel value, since the figure width in pixels is
width in inches * dpi.  See
http://matplotlib.sf.net/matplotlib.matlab.html#-axes.

    Wayne> 2. I have some x, y window coordinates I got via Tk event
    Wayne> bindings.  How can I translate these into data coordinates?

You can plot in any coordinate system you want by setting the
appropriate transform.  If you want to plot in pixels, just specify
your data in pixels and use the identity_transform, as in this example

    from matplotlib.matlab import *
    from matplotlib.transforms import identity_transform
    # left, bottom, width, height as fractions of figure size
    axes([0.05, 0.05, .9, 0.9])

    # plot in pixel coords with the identity transform
    plot([100,400], [200,300], transform=identity_transform())
    axis('off')  # turn off tick labeling
    show()

See http://matplotlib.sf.net/matplotlib.transforms.html for more
information on transforms.

For some backends, you may want to subtract the y pixel coordinate
from the figure height.  You can get the pixel width and height of the
current figure with

  w, h =  gcf().get_width_height()

See http://matplotlib.sf.net/matplotlib.figure.html for help with
figure methods.

Good luck - when I get the users guide finished, some of these details
will be more accessible.

JDH

    Wayne> Thanks,

    Wayne> 	Wayne



    Wayne> -------------------------------------------------------
    Wayne> This SF.Net email is sponsored by: YOU BE THE JUDGE. Be one
    Wayne> of 170 Project Admins to receive an Apple iPod Mini FREE
    Wayne> for your judgement on who ports your project to Linux PPC
    Wayne> the best. Sponsored by IBM.  Deadline: Sept. 24. Go here:
    Wayne> http://sf.net/ppc_contest.php
    Wayne> _______________________________________________
    Wayne> Matplotlib-users mailing list
    Wayne> Mat...@li...
    Wayne> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

[Matplotlib-users] figure border and mapping window to data coordinates

[Wayne C. <wa...@4r...>]

I have been using matplotlib with TkInter (TkAgg backend) and it's really nice 
once I got the hang of it...  I have two questions though, which I couldn't find 
in the manual.

1. The figure window has a pretty large border around it, that seems to expand 
as I enlarge the window.  Is there a way to set this to, say, N pixels?

2. I have some x, y window coordinates I got via Tk event bindings.  How can I 
translate these into data coordinates?

Thanks,

	Wayne

Re: [Matplotlib-users] matplotlib for interactive simulation visualisation

[Andre M. <a....@hc...>]

Hi Chris

Thanks for your reply. I will take a look at your FloatCanvas to see
whether it is useful for my purpose. The way you describe it might very
well.

The Agg library is awesome and making it fully available in Python would
be more than nice. The whole Python community would benefit from this.

Unfortunately, I do not have the knowledge nor the time to do the job. I
need good graphics for the simulations that I already develop on top of
the work I am paid for... The Tkinter Canvas is looking awful and
unprofessional and the API is horrible.

My feeling is that there is already a lot available*, but it needs to be
combined in the right way. Maybe it is just getting the right developers
together to give it a push. I don't know.

hope this will really move in the right direction
kind regards
Andre


* http://matplotlib.sourceforge.net/backends.html


On Fri, 2004-09-17 at 17:23, Chris Barker wrote:
> AP Meyer wrote:
> > My problem is to visualise the process of a simulation, thus vector 
> > graphics objects controlled by a simulation program. At the moment I use 
> > a Tkinter Canvas, but it is very limiting. Look at the attached image 
> > for an example: cars driving on roads and trying to avoid crashing 
> > (Windows version). Imagine the cars driving around, of course!
> 
> Did you post a similar message to comp.lang.python? Anyway, I tried to 
> reply to that, but maybe you didn't see it.

No.

> 
> I would suggest my wxPython FloatCanvas package:
> 
> http://home.comcast.net/~chrishbarker/FloatCanvas/
> 
> (it's also included with recent versions of wxPython)
> 
> Sorry I don't have a really nifty page describing it, but it does come 
> with a fairly comprehensive demo. I'd describe it's core mission as such:
> 
> * It is designed to display data, which are likely to be in arbitrary 
> coordinates, rather than a picture, but is not a plotting tool (axes and 
> all that)
> 
> * It is object based, and thus separates you from most of the need to 
> understand drawing with wx (DCs and all), and lets you create and 
> maintain objects.
> 
> * It is designed to be high performance enough for simple animation
> 
> > What I need is something similar to the Java2D API or JGraph. I need 
> 
> With a quick glance at the Java2D page, I can say that it has a slightly 
> different mission, but the biggest issues are:
> 
> - No OpenGL (but I'd love to see that!)
> 
> - No printing (though I was given a patch that I have not had a chance 
> to integrate yet. It shouldn't be too hard)
> 
> - Not as mature or Robust (maybe a half a dozen people are using it for 
> real)
> 
> As for your requirements:
> 
> > - interactive (by application, not user) creation and modification of  
> > graphics primitives, such as:
>   circles - yes
> text -  yes
> rects - yes
> arcs - no, but it wouldn't be hard to add
> arrows - yes, but not in the released version--hopefully I'll get anew 
> one out soon, otherwise, I can send it to you directly.
> 
> > splines, etc. -- no, but same as arcs.
> 
> > - transparency (alpha blending) - No (this is NOT well supported by wx yet, :-( )
> > - anti-aliasing -- I think text is covered, but 
> 
> These two could be supported by AGG, which is used by matplotlib. There 
> was some talk a while back about creating a wxAggDC, which I could then 
> use for FloatCanvas, but no one has stepped up to do it yet! Would you 
> like to?
> 
> > - rotation, skewing, scaling, etc. -- some,a nd it wouldn't be hard to add more.
> > - SVG output -- nope
> 
> wxArt2d (A C++ library for wx) has a lot of this. It would be great to 
> see it wrapped for Python, unfortunately, not a trivial job, as I 
> understand it.
> 
> Question: do you need it to be user-interactive, i.e. events responding 
> to clicking on objects? FloatCanvas does have that.
> 
> > I have already looked at Tkinter and wxPython/OGL, but neither seems  to 
> > do what I want.
> 
> I'm afraid you're going to have to adapt anything that exists for 
> Python, the libraries just aren't as comprehensive as to for JAVA, at 
> least for this kind of thing. One reason is that there are quite a few 
> GUI toolkits, so development is kind of spread thin.
> 
> If you really need the alpha blending and anti-aliasing, and matplotlib 
> can't do what you want out of the box, I'd highly encourage you to work 
> on a general purpose Agg module. It would be a real contribution to the 
> community, and I'd integrate it into FloatCanvas, so you could get the 
> rest of what you need from that. Another option would be to look at 
> wrapping wxArt2d.
> 
> -Chris

Re: [Matplotlib-users] matplotlib for interactive simulation visualisation

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

AP Meyer wrote:
> My problem is to visualise the process of a simulation, thus vector 
> graphics objects controlled by a simulation program. At the moment I use 
> a Tkinter Canvas, but it is very limiting. Look at the attached image 
> for an example: cars driving on roads and trying to avoid crashing 
> (Windows version). Imagine the cars driving around, of course!

Did you post a similar message to comp.lang.python? Anyway, I tried to 
reply to that, but maybe you didn't see it.

I would suggest my wxPython FloatCanvas package:

http://home.comcast.net/~chrishbarker/FloatCanvas/

(it's also included with recent versions of wxPython)

Sorry I don't have a really nifty page describing it, but it does come 
with a fairly comprehensive demo. I'd describe it's core mission as such:

* It is designed to display data, which are likely to be in arbitrary 
coordinates, rather than a picture, but is not a plotting tool (axes and 
all that)

* It is object based, and thus separates you from most of the need to 
understand drawing with wx (DCs and all), and lets you create and 
maintain objects.

* It is designed to be high performance enough for simple animation

> What I need is something similar to the Java2D API or JGraph. I need 

With a quick glance at the Java2D page, I can say that it has a slightly 
different mission, but the biggest issues are:

- No OpenGL (but I'd love to see that!)

- No printing (though I was given a patch that I have not had a chance 
to integrate yet. It shouldn't be too hard)

- Not as mature or Robust (maybe a half a dozen people are using it for 
real)

As for your requirements:

> - interactive (by application, not user) creation and modification of  
> graphics primitives, such as:
  circles - yes
text -  yes
rects - yes
arcs - no, but it wouldn't be hard to add
arrows - yes, but not in the released version--hopefully I'll get anew 
one out soon, otherwise, I can send it to you directly.

> splines, etc. -- no, but same as arcs.

> - transparency (alpha blending) - No (this is NOT well supported by wx yet, :-( )
> - anti-aliasing -- I think text is covered, but 

These two could be supported by AGG, which is used by matplotlib. There 
was some talk a while back about creating a wxAggDC, which I could then 
use for FloatCanvas, but no one has stepped up to do it yet! Would you 
like to?

> - rotation, skewing, scaling, etc. -- some,a nd it wouldn't be hard to add more.
> - SVG output -- nope

wxArt2d (A C++ library for wx) has a lot of this. It would be great to 
see it wrapped for Python, unfortunately, not a trivial job, as I 
understand it.

Question: do you need it to be user-interactive, i.e. events responding 
to clicking on objects? FloatCanvas does have that.

> I have already looked at Tkinter and wxPython/OGL, but neither seems  to 
> do what I want.

I'm afraid you're going to have to adapt anything that exists for 
Python, the libraries just aren't as comprehensive as to for JAVA, at 
least for this kind of thing. One reason is that there are quite a few 
GUI toolkits, so development is kind of spread thin.

If you really need the alpha blending and anti-aliasing, and matplotlib 
can't do what you want out of the box, I'd highly encourage you to work 
on a general purpose Agg module. It would be a real contribution to the 
community, and I'd integrate it into FloatCanvas, so you could get the 
rest of what you need from that. Another option would be to look at 
wrapping wxArt2d.

-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...

[Matplotlib-users] matplotlib for interactive simulation visualisation

[AP M. <a.p...@fe...>]

Dear matplotlib users

On my search for a good drawing API for Python I discovered matplotlib. 
It has most of the features that I would like to see in a  Python vector 
drawing API.

My problem is to visualise the process of a simulation, thus vector 
graphics objects controlled by a simulation program. At the moment I use 
a Tkinter Canvas, but it is very limiting. Look at the attached image 
for an example: cars driving on roads and trying to avoid crashing 
(Windows version). Imagine the cars driving around, of course!

What I need is something similar to the Java2D API or JGraph. I need 
the  following features:

- interactive (by application, not user) creation and modification of  
graphics primitives, such as circles, text, rects, arcs, arrows,  
splines, etc.
- transparency (alpha blending)
- anti-aliasing
- rotation, skewing, scaling, etc.
- SVG output ?

Can matplotlib be used for visualising simulations? I do not need the 
axes and the various diagrams, but the rest is already there, it seems.

I have already looked at Tkinter and wxPython/OGL, but neither seems  to 
do what I want.

Thanks for your help.
Andre


Java2D
http://java.sun.com/products/java-media/2D/index.jsp
http://java.sun.com/docs/books/tutorial/2d/display/strokeandfill.html
http://java.sun.com/j2se/1.4.2/docs/guide/2d/spec/j2d-awt.html#wp64995

JGraph
http://www.jgraph.com/showcase.html

-- 
Dr. Andre P. Meyer                        http://home.hccnet.nl/a.meyer/
TNO FEL Command & Control and Simulation, http://www.fel.tno.nl/div2/
Delft Cooperation on Intelligent Systems, http://www.decis.nl/


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Re: [Matplotlib-users] imshow?

[Stephen W. <ste...@cs...>]

On Thu, 2004-09-16 at 13:41, John Hunter wrote:
> >>>>> "Stephen" == Stephen Walton <ste...@cs...> writes:
> 
>     Stephen> Attempts to do an imshow() result in an error message
>     Stephen> that "pygtk was not compiled with Numeric Python
>     Stephen> support."
> 
> My guess is you are using a precompiled pygtk (eg the one that ships
> with FC1).

Yup.  I changed .matplotlibrc to force the GTKAgg backend and all is
more or less well.  I say this because (1) I'm using "ipython -pylab" on
both FC1 and FC2; (2) I'm using the precompiled pygtk2 on both; (3)
imshow works fine on FC2 with no .matplotlibrc file; and (4) the default
colormap on FC1 seems to be grayscale, but on FC2 it is colorful.

All systems have IPython 0.6.3 installed from Fernando's RPM and
matplotlib 0.62.4 built locally with no changes to the defaults.

Steve

Re: [Matplotlib-users] imshow?

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

>>>>> "Stephen" == Stephen Walton <ste...@cs...> writes:

    Stephen> I'm doing something wrong, obviously, but am not sure
    Stephen> what.  I have Numeric 23.1 (and numarray 1.1) installed
    Stephen> under Python 2.2 on Fedora Core 1, and matplotlib 0.62.4.
    Stephen> Attempts to do an imshow() result in an error message
    Stephen> that "pygtk was not compiled with Numeric Python
    Stephen> support."

My guess is you are using a precompiled pygtk (eg the one that ships
with FC1).  You'll probably need to compile pygtk from src, with
threads and numpy support

  > ./configure --enable-thread --enable-numpy
  > sudo make install

Alternatively, you could simply use the gtkagg backend, in which case
you won't need gtk with numpy support.

JDH

Re: [Matplotlib-users] imshow?

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

On Thu, 2004-09-16 at 16:12, Stephen Walton wrote:
> I'm doing something wrong, obviously, but am not sure what.  I have
> Numeric 23.1 (and numarray 1.1) installed under Python 2.2 on Fedora
> Core 1, and matplotlib 0.62.4.  Attempts to do an imshow() result in an
> error message that "pygtk was not compiled with Numeric Python support"

I looked into this a little and the message is coming from pygtk itself,
not surprisingly.  Is there any chance you installed Numeric after
pygtk?  If so,  you might want to try reconfiguring and re-installing
pygtk.

Hope this helps,
Todd

[Matplotlib-users] imshow?

[Stephen W. <ste...@cs...>]

I'm doing something wrong, obviously, but am not sure what.  I have
Numeric 23.1 (and numarray 1.1) installed under Python 2.2 on Fedora
Core 1, and matplotlib 0.62.4.  Attempts to do an imshow() result in an
error message that "pygtk was not compiled with Numeric Python support."

--=20
Stephen Walton <ste...@cs...>
Dept. of Physics & Astronomy, Cal State Northridge

Re: [Matplotlib-users] date proposal / dropping python2.2 support

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

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

    Chris> I think you should generally not blindly apply the MATLAB
    Chris> approach. Python is a more powerful language than MATLAB,
    Chris> and support for more than just doubles is one it's
    Chris> features!

Agreed.  That's why we're here, after all.

    Chris> How does the datetime module store the values in a datetime
    Chris> object? My first inclination would be to follow it's
    Chris> approach, but it may not be suited to arrays ( :-( )

From the header of datetime.h

/* Fields are packed into successive bytes, each viewed as unsigned and
 * big-endian, unless otherwise noted:
 *
 * byte offset
 *  0 		year     2 bytes, 1-9999
 *  2		month    1 byte, 1-12
 *  3 		day      1 byte, 1-31
 *  4		hour     1 byte, 0-23
 *  5 		minute   1 byte, 0-59
 *  6 		second   1 byte, 0-59
 *  7 		usecond  3 bytes, 0-999999
 * 10
 */

I am concerned about the performance and memory hit of using, for
example, a list of a list of datetime objects rather than a numeric
array of floats.  In the float representation, you can efficiently
create a large date range array with, for example, the drange code I
posted.  Another concern is implementation: I would have to special
case setting the tick limits and locations, eg calls to set_xlim and
set_xticks, to check for datetime instances.  I'm not totally wed to
the float array approach however, and it is possible to handle
datetime conversions as special cases in the axis functions if the
consensus is that this would be better.

    Chris> A couple projects you might want to make use of:
    Chris> http://pytz.sourceforge.net/
    Chris> and:
    Chris> https://moin.conectiva.com.br/DateUtil

These look very nice and their is a good likelihood I'll use both.
DateUtil can extend and improve the date tickers considerably, and the
pytz classes should keep users happy around the world!

Thanks,
JDH

Re: [Matplotlib-users] date proposal / dropping python2.2 support

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

>>I think the
>>cleanest approach is to require python2.3 and datetime.  Ie, I would
>>jettison support for epoch times and mx datetimes, as well as the
>>converter stuff.

+1 on this.

>>    def plot_date(self, d, y, fmt='bo', **kwargs):
>>
>>where d would be an array of floats (no converter) and the floats
>>would be the number of days since 1,1,1 (Gregorian calendar).  The
>>supported date range would be datetime.min to datetime.max (years 0001
>>- 9999).
> 
> Actually, MATLAB adopts the same approach using floats for date and time.

I think you should generally not blindly apply the MATLAB approach. 
Python is a more powerful language than MATLAB, and support for more 
than just doubles is one it's features!

How does the datetime module store the values in a datetime object? My 
first inclination would be to follow it's approach, but it may not be 
suited to arrays ( :-( )

A couple projects you might want to make use of:

http://pytz.sourceforge.net/

and:

https://moin.conectiva.com.br/DateUtil

-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...

RE: [Matplotlib-users] date proposal / dropping python2.2 support

[Shin, D. <sd...@em...>]

> I would like to rewrite the dates module, and the ticker functions for
> dates, to use the python datetime module.  Getting dates, timezones,
> and daylight savings time right is non-trivial, and I think the
> cleanest approach is to require python2.3 and datetime.  Ie, I would
> jettison support for epoch times and mx datetimes, as well as the
> converter stuff.

I agree that datetime is the cleanest approach.
Always, better to choose standard libraries than 3rd party ones.

>
> The new plot_date signature would be
>
>     def plot_date(self, d, y, fmt='bo', **kwargs):
>
> where d would be an array of floats (no converter) and the floats
> would be the number of days since 1,1,1 (Gregorian calendar).  The
> supported date range would be datetime.min to datetime.max (years 0001
> - 9999).

Actually, MATLAB adopts the same approach using floats for date and time.
There, the epoch is 0000/00/00. The datenum and datestr functions provide
the conversion
between floats and strings.

>
> The dates module would provide some helper functions so that you could
> use to build date arrays from datetime and timedelta instances.  It
> not be too hard to add some helper functions to convert existing
> epoch, mx, or datetime arrays to the required array of days floats.
>
> timezones, including timezones other than the local one, would be
> supported.  Ie, if you are a financial guru in California, you could
> work with Eastern time zone stock quotes or Central time zone pork
> belly quotes.  daylight savings time, etc, would be handled by the
> datetime module.

I have developed similar functions to convert an array of date or datetime
to array of numbers. To avoid imprecision of floating points, I used seconds
since 1900/1/1
without considering time zone. For my own domain, hydrologic modeling, I am
rarely concerned about time zone.
Based on my experience, I noticed the following things.

The function names to_ordinalf and from_ordinalf are difficult to remember.
How about just time2num and num2time?
In addition, how about modifying the functions to handle an array of numbers
or datetimes directly using map function?
And the from_ordinalf function will produce an error message if date object,
not datetime object, is tossed.

I also recommend to provide strftime and isoformat functions to handle array
of floating points directly.
Thanks for your effort.

Daehyok Shin

[Matplotlib-users] date proposal / dropping python2.2 support

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

First, a general note about python2.2.  It is becoming difficult to
maintain adequate support for python2.2.  The pyparsing module, on
which mathtext relies, currently requires 2.3.  Handling dates
properly requires the datetime module (or mx.datetime but I'm not
inclined to impose an external dependency).  I am inclined to gently
drop support for 2.2.  By gently, I mean that some features will no
longer work (mathtext and dates) but the core should, at least for the
near future.  How many people would this adversely affect?

The dates module, aside from a bug that I patched yesterday in
response to a post by Jim Boyle, has two fundamental problems: no
timezone support and the date range supported by the built-in time
functions (the 1972 epoch) is too narrow.  Both of these limitations
are imposed by trying to support python2.2.

I would like to rewrite the dates module, and the ticker functions for
dates, to use the python datetime module.  Getting dates, timezones,
and daylight savings time right is non-trivial, and I think the
cleanest approach is to require python2.3 and datetime.  Ie, I would
jettison support for epoch times and mx datetimes, as well as the
converter stuff.  

The new plot_date signature would be

    def plot_date(self, d, y, fmt='bo', **kwargs):

where d would be an array of floats (no converter) and the floats
would be the number of days since 1,1,1 (Gregorian calendar).  The
supported date range would be datetime.min to datetime.max (years 0001
- 9999).

The dates module would provide some helper functions so that you could
use to build date arrays from datetime and timedelta instances.  It
not be too hard to add some helper functions to convert existing
epoch, mx, or datetime arrays to the required array of days floats.

timezones, including timezones other than the local one, would be
supported.  Ie, if you are a financial guru in California, you could
work with Eastern time zone stock quotes or Central time zone pork
belly quotes.  daylight savings time, etc, would be handled by the
datetime module.

The datetime module has functions toordinal and fromordinal to convert
to integer number of days since the start of the Gregorian calendar,
but not floating point.  Ie, hours minutes, seconds, etc are lost.  My
guess is that it is done this way to avoid imprecisions in floating
point, but am not sure.  I have implemented to_ordinalf and
from_ordinalf to do these conversions preserving the hours, etc.  They
seem to work.  I occasionally get rounding error on the order of a
couple microseconds, which I think should be tolerable for the vast
majority of cases.  If you need microsecond precision, you can
use plot and not plot_date in any case.

Below, I'm including some prototype code which does these conversions
- if you have interest or experience with dates and timezones, please
look over it to see if I'm making any fundamental or conceptual
errors.

There is also a function drange, which can be used to construct the
floating point days arrays plot_date would require.

Any other suggestions for improvement or changes to date handling
welcome.  Speak now, or forever hold your peace!

JDH

import sys, datetime
from matplotlib.numerix import arange
from matplotlib.dates import Central, Pacific, Eastern, UTC

HOURS_PER_DAY = 24.
MINUTES_PER_DAY  = 60.*HOURS_PER_DAY
SECONDS_PER_DAY =  60.*MINUTES_PER_DAY
MUSECONDS_PER_DAY = 1e6*SECONDS_PER_DAY

#tz = None
tz = Pacific
#tz = UTC

def close_to_dt(d1, d2, epsilon=5):
   'assert that datetimes d1 and d2 are within epsilon microseconds'
   delta = d2-d1
   mus = abs(delta.days*MUSECONDS_PER_DAY + delta.seconds*1e6 + delta.microseconds)
   assert(mus<epsilon)

def close_to_ordinalf(o1, o2, epsilon=5):
   'assert that float ordinals o1 and o2 are within epsilon microseconds'
   delta = abs((o2-o1)*MUSECONDS_PER_DAY)
   assert(delta<epsilon)
   
   
def to_ordinalf(dt):
    """
    convert datetime to the Gregorian date as UTC float days,
    preserving hours, minutes, seconds and microseconds.  return value
    is a float
    """

    if dt.tzinfo is not None:
        delta = dt.tzinfo.utcoffset(dt)
        if delta is not None:
            dt -= delta
    
    base =  dt.toordinal()
    return (base + dt.hour/HOURS_PER_DAY + dt.minute/MINUTES_PER_DAY +
            dt.second/SECONDS_PER_DAY + dt.microsecond/MUSECONDS_PER_DAY
            )

def from_ordinalf(x, tz=None):
    """
    convert Gregorian float of the date, preserving hours, minutes,
    seconds and microseconds.  return value is a datetime
    """
    ix = int(x)
    dt = datetime.datetime.fromordinal(ix)
    remainder = x - ix
    hour, remainder = divmod(24*remainder, 1)
    minute, remainder = divmod(60*remainder, 1)
    second, remainder = divmod(60*remainder, 1)
    microsecond = int(1e6*remainder)
    dt = datetime.datetime(dt.year, dt.month, dt.day, int(hour), int(minute), int(second), microsecond, tzinfo=UTC())


    if tz is not None:
        return dt.astimezone(tz)
    else: return dt
    
def drange(dstart, dend, delta):
    """
    Return a date range as float gregorian ordinals.  dstart and dend
    are datetime instances.  delta is a datetime.timedelta instance
    """
    step = delta.days + delta.seconds/SECONDS_PER_DAY + delta.microseconds/MUSECONDS_PER_DAY
    f1 = to_ordinalf(dstart)
    f2 = to_ordinalf(dend)
    return arange(f1, f2, step)
    
    
dt = datetime.datetime(1011, 10, 9, 13, 44, 22, 101010, tzinfo=tz)

x = to_ordinalf(dt)
newdt = from_ordinalf(x, tz)
close_to_dt(dt, newdt)

date1 = datetime.datetime( 2000, 3, 2, tzinfo=tz)
date2 = datetime.datetime( 2000, 3, 5, tzinfo=tz)
delta = datetime.timedelta(hours=8)
print drange(date1, date2, delta)


d1  = datetime.datetime( 2000, 3, 2, 4,  tzinfo=tz)
d2 =  datetime.datetime( 2000, 3, 2, 12, tzinfo=UTC())
o1 =  to_ordinalf(d1)
o2 =  to_ordinalf(d2)
close_to_ordinalf(o1, o2)

print 'all tests passed'