I don't think we are actually disagreeing with one another. I have
written the kind of library you are talking about and used the same
library from ipython and in a wxpython app. All of my plotting
functions expect a fig instance as an input. When calling the library
from ipython, I pass in a fig=pylab.figure(), when using the data
analysis library with wxpython, my fig comes from the get_figure
method of a wxmpl PlotPanel instance. wxmpl handles all canvas issues
for me.
So, in my libraries, I have inputs that are fig instances. Creating a
fig with pylab.figure() is how I use my library from ipython.
I actually have this code in one of my data analysis library functions
def plotting_function(x, y, other inputs, fig=None):
if fig is None:
from pylab import figure
fig = figure(fignum)
and the code works beautifully as a library and plays well with
ipython and wxpython.
Ryan
On 6/21/07, Roman Bertle <[EMAIL PROTECTED]> wrote:
> Hello,
>
> thank you very much for you answer. The oddness clears if you consider
> that the generating of the figure might be done in an external library.
> Imagine a data analyze package with functions with can also generate one
> or more plots. As a library I think here the OO interface is most
> appropriate. A user of such a library might want to plot figure objects
> returned by the library function at her discretion. And of course the
> user in her interactive session uses an pylab session in ipython.
>
> In your example the figure object was already generated from within the
> ipython session using fig=figure(1). But this already pops up a canvas
> which is not appropriate for a library. In my example I generated the
> plot strictly OO with "fig = matplotlib.figure.Figure()". And as I wrote
> below, this object cannot be plotted or saved easily, because its not
> connected to a canvas, a canvas the library generating the figure knows
> nothing about, because it knows nothing about the environment of the
> user. In order to save the figure, you have to do the involved:
> > >canvas = get_current_fig_manager().canvas
> > >canvas.figure = fig
> > >canvas.print_figure('myplot.png')
> and canvas.show() does not work at all. Much better would methods like:
> fig.print_figure() and fig.show(), but this does not work.
>
> Best Regards, Roman
>
> * Ryan Krauss <[EMAIL PROTECTED]> [070621 20:40]:
> > [...]
> > But to answer your question, I think using the OO interface from an
> > ipython session is slightly odd in that your are kind of operating in
> > two different paradigms. I had no problem showing and saving a figure
> > doing the following (from an "ipython -pylab -p scipy" prompt):
> >
> > fig=figure(1)
> > t=arange(0,1,0.01)
> > y=sin(2*pi*t)
> > ax=fig.add_subplot(111)
> > ax.plot(t,y)
> > show()
> > ax.set_ylabel('$y(t)$')
> > ax.set_xlabel('Time (sec)')
> > show()
> > savefig('test.png')
> >
> > FWIW,
> >
> > Ryan
> >
> > On 6/13/07, Roman Bertle <[EMAIL PROTECTED]> wrote:
> > >Hello,
> > >
> > >why don't you reply on the mailing list? Nevermind, the problem is not
> > >that I don't know the OO API or that I don't know python well. The
> > >problem is that there is missing something in the OO API. If you
> > >generate a figure as I have done below:
> > >
> > >fig = matplotlib.figure.Figure()
> > >ax = fig.add_subplot(111)
> > >ax.plot(x)
> > >
> > >Then its not so easy to actually save or display the figure in a ipython
> > >-pylab session. fig has a method savefig(), but it fails because it
> > >cannot find a canvas. The only way is to generate a canvas and assign
> > >fig to it:
> > >
> > >canvas = get_current_fig_manager().canvas
> > >canvas.figure = fig
> > >canvas.print_figure('myplot.png')
> > >
> > >and you cannot do canvas.draw() or canvas.show(), it raises an
> > >Exception. Much better would be a working fig.print_figure() and
> > >fig.show(), creating a canvas on the fly, and maybe using an optional
> > >keyword argument to providing a canvas object.
> > >
> > >Regards, Roman
> > >
> > >
> > >* Ryan Krauss <[EMAIL PROTECTED]> [070612 08:17]:
> > >> Just my $0.02 as a personal testimony about the truth of what John is
> > >> saying. I started out using from pylab import * or from pylab import
> > >> figure, cla, clf, plot, semilogx, ... in all my code and didn't bother
> > >> learning the OO API. This worked great for the first year or two.
> > >> Then I wanted to use some of my data processing libraries with a
> > >> wxPython gui and they all started out importing Pylab. This created
> > >> quite a bit of pain for me. I was rightly advised to make sure I
> > >> never used Pylab in a utility module I might some day want to use with
> > >> any gui program and had to significantly edit all my module files.
> > >>
> > >> So, if you are serious about learning Python, then I think it is worth
> > >> a little pain now to save yourself a lot of pain later and learn to
> > >> use the OO API whenever you aren't just doing something interactively
> > >> at the IPython prompt.
> > >>
> > >> I have found that
> > >> fig = Figure()
> > >> ax = fig.add_subplot(111) #(or 212 or whatever)
> > >> and then using IPython's tab completion with fig.<tab> and ax.<tab> is
> > >> usually sufficient to learn the API commands corresponding to the
> > >> pylab commands I used for so long. Don't forget to take advantage of
> > >> this beautiful IPython feature to find commands:
> > >> In [4]: ax.*xlabel*?
> > >> ax.set_xlabel
> > >>
> > >> (finding the correct API commands to replace pylab.xlabel and
> > >> pylab.ylabel tripped my up for a little bit).
> > >>
> > >>
> > >> But, I am also a teacher making my students use Python and I will
> > >> mention none of this to them and just encourage them to use from pylab
> > >> import * to keep the entry barrier as low as possible.
> > >>
> > >> FWIW,
> > >>
> > >> Ryan
> > >>
> > >> On 6/11/07, Roman Bertle <[EMAIL PROTECTED]> wrote:
> > >> >* John Hunter <[EMAIL PROTECTED]> [070611 16:20]:
> > >> >> So the answer of which is better is a question of skill level and
> > >> >> context, but my simple advice is to use the pylab syntax from the
> > >> >> interactive python shell (and "ipython -pylab" is ideal for this) and
> > >> >> the API everywhere else. Most of my scripts are variants of this:
> > >> >>
> > >> >> import numpy as npy
> > >> >> from pylab import figure, close, show
> > >> >> fig = figure()
> > >> >> ax = fig.add_subplot(111)
> > >> >> x = npy.arange(0,10.)
> > >> >> ax.plot(x)
> > >> >> show()
> > >> >
> > >> >Hello,
> > >> >
> > >> >is there also a (possible object oriented) way to show/print a given
> > >> >figure? Like fig.show() or fig.print_figure(). I need it because I have
> > >> >a script generating (returning) several plots, and the user should be
> > >> >able to print/show the plots he likes. At the moment I use:
> > >> >
> > >> >ipython -pylab
> > >> > from myscript import plotgenerator
> > >> > fig = plotgenerator()
> > >> > canvas = get_current_fig_manager().canvas
> > >> > canvas.figure = fig
> > >> > canvas.print_figure('myplot.png')
> > >> >
> > >> >Here plotgenerator does something like:
> > >> > from matplotlib.figure import Figure
> > >> > fig = Figure()
> > >> > ax = myplot.add_subplot(111)
> > >> > ax.plot(x)
> > >> >
> > >> >But its cumbersome, and canvas.show() doesn not work (it gives an
> > >> >exception). Best would be if fig.show() (popping up a new canvas) and
> > >> >fig.print_figure() worked.
> > >> >
> > >> >Best Regards, Roman
>
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