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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