matplotlib-users Mailing List for matplotlib

A little roll reversal today.  Rather than you asking me how to use
matplotlib interactively on win32, I'll ask you...

The reason: a former adviser of mine is teaching a biomath course, and
is using python with Numeric and matplotlib for the computational
part.  Almost all of his students are windows XP users, and are
struggling a little bit with the impoverished command shell.  I've
recommended ipython to them, and sent a zip file with all the prereqs,
but even this may be a bit much for some typical windows users who
came of age in the post DOS era -- for one thing they still need a
code editor.

Is anyone using matplotlib robustly a GUI IDE in win32?  By robustly,
I mean, generating plots from the command shell and files, editing the
files with an integrated editor, running them from there,
interactively opening and closing windows, switching between command
line interaction and file mode, without crashes and freezes?

If so, please advise, with info about your configuration and
suggestions.

idle was my first inclination, despite the fact that it is rather
impoverished GUI, but with all the recent matplotlib changes in
tkagg's PYTHONINSPECT setting with or w/o idle -n I am not sure how
robust it is currently.

Thanks!
JDH

>>>>> "Teemu" == Teemu Rinne <Tee...@he...> writes:


    Teemu> How to do this?  Do I have to combine the RGB values of the
    Teemu> two images 'manually'?

Basically what you are talking about is adding an alpha channel to the
color map, and setting it to be transparent for image values less than
a certain value.  Perry Greenfield is the colormap implementer and
resident expert.

Perry -- how hard would it be to either subclass or extend the current
framework to include an alpha channel?  I think it could be done in
just a few lines of code actually.  Eg, something like

   self._alpha_lut  = makeMappingArray(self.N,
                     self._segmentdata.get('blue', [1.0, 1.0]) 

and then modifying

    def __call__(self, X, alpha=1.0):

to deal with it.  

Perry do you have time to take a crack at this?  I think this would be
very useful.

Thanks,
JDH

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

    Chris> I'd vote for Agg. Postscript is not the native format on
    Chris> OS-X that it is on other unices.

    Chris> Is there a way to make the default back-end system
    Chris> dependent on install?

For a src distribution, you could write a postinstall script that does
try/except on various GUIs and writes an rc file based on what it
finds.  This is basically what setup.py does in trying to figure out
which backend to build, but doesn't transmit that information to rc --
perhaps it should.  Although this would be fairly easy in a src
distro, it would be fairly hard in the binary installer which you are
trying to build.

Alternatively, the backend importer could be a little smarter, and
first try the default rc param and then loop over available backends
trying to find a match, and issue a verbose report saying "dear
newbie, I cannot import your default backend, please see http://blah."
but still go ahead and launch something.  I have mixed feelings about
this -- the more magic we do the more complex it is to debug
problems.  Also, you have to be careful not to swallow tracebacks, eg
pygtk import can fail even if pygtk has been installed on the system,
and the user needs to know about this.  But I am not totally opposed
to it.

In fact, I would definitely include it if it was an rc option.  Eg,
binary package makers like yourself could turn it on since you don't
know the user configuration, and src distributors like me could turn
it off, assuming people who build their own code can configure it like
they like it.

Power users want as little magic going on as possible -- new users
usually want maximal magic.


The function to look at is __init__.py in the main matplotlib tree.
Currently we do


def get_backend():
    return rcParams['backend']


you would want to add an rc param, something like

backend     : ['TkAgg']
# try these if default fails
backend.try = ['GTKAgg, 'WXAgg', 'Agg', 'PS]

and then modify get_backend to iterate over these backends, trying to
import something to test if it is available, issuing reports if the
default backend fails.  

In the src distro, I always have the option of making backend.try the
empty list, which would be the same as the current behavior.

and 
JDH

Hi,

Looking at the Matplotlib Mailing list, I wonder if you=20
already started working in this direction?

Nicolas


Le Jeudi 19 Ao=FBt 2004 13:58, John Hunter a =E9crit=A0:
> >>>>> "Sigve" =3D=3D Sigve Tjora <pu...@tj...> writes:
>
>     Sigve> Hi everyone, Is there any planned support for
> a Qt-backend? Sigve> We are using Qt in our project, and
> I would like to use Sigve> Matplot lib for plotting.
>
>     Sigve> If there is not any support for Qt how hard
> would it be to Sigve> make it myself? Would it be best to
> base it on the Agg Sigve> backend, or should I make a
> native Qt backend? What is the Sigve> least work? Is it
> possible to write the whole backend in Sigve> Python or
> should I use C++ in addition?
>
> Currently there is no QT backend, or one in the works,
> but it would be nice.  It is definitely much easier to
> base it on the agg backend and is in fact *strongly
> encouraged* as that minimizes the amount of maintenance
> required.
>
> Using C/C++ is an optional step.  TkAgg and GTKAgg use it
> to get the optimal transfer speed from the agg image to
> the GUI canvas.  WXAgg and FLTKAgg do not use it, and
> Gregory reports great performance for FLTKAgg.  WXAgg
> uses string methods to transfer the image and FLTKAgg
> uses a python buffer object.  I encourage you to try and
> use a python buffer object (or string method) as opposed
> to extension code in the beginning since it's easier to
> write and maintain, it will introduce no extra compile
> time dependencies, and in the event that you find it too
> slow and want to write an extension to speed things up,
> you'll have the pure python method to fall back on for
> users who can't get the extension compiled.
>
> matplotlib.backends.backend_template contains the basic
> documentation for backend writers.  But this code does a
> lot more than you need, since agg will be doing the
> drawing; ie you don't need to implement a renderer or
> graphics context.  I recommend you give it a read
> through, and then follow the lead of backend_fltkagg.  I
> also advise you not to implement the classic navigation
> toolbar (at least not until later) because the new
> toolbar design is not only better (in my opinion), it's
> currently the default and most importantly, is much
> easier to implement since all the work is done for you in
> backend bases.  You basically need to load up some images
> into a toolbar and get the signal connections right.
>
> In the event you need a different pixel format to
> transfer the agg image to the qt canvas, that will be no
> problem.  I will be glad to add it for you or you can add
> it yourself to backend_agg.
>
> The only thing I ask of submitters is that if you want
> your backend to be included with the matplotlib
> distribution, please be responsible for testing it across
> the major platforms the GUI should run on (eg linux,
> win32, and OSX), provide some install instructions,
> version dependencies, etc, for the documentation, and
> monitor the mailing lists to handle questions about your
> backend.  In a nutshell, I need you to maintain it.  If
> you don't have the time to maintain it but want to write
> one anyway for your own work, I would be happy to provide
> a link to it with a disclaimer that users are on their
> own.
>
> Good luck if you decide to do it, and let me know if I
> can help.
>
> JDH
>
>
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