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On Thursday 21 June 2007 17:15:01 Eric Firing wrote:
> trans = blend_xy_sep_transform( self.transData, self.transAxes )
>
> where "self" in this case is the axes instance, so you would use "ax" or
> whatever. Then, since the collection is an artist, you can use its
> inherited set_transform(trans) method, 
John, Eric,
That works like a charm ! Thanks a lot !

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 <be...@sm...> 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 <rya...@gm...> [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 <be...@sm...> 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 <rya...@gm...> [070612 08:17]:
> > >> Just my 0ドル.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 <be...@sm...> wrote:
> > >> >* John Hunter <jd...@gm...> [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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I'd like to make a text instance italic, but this doesn't seem to be working:
t = text(15.e3, -70, "25 kHz")
t.set_color('r')
t.set_style('italic')
Stephen

On 6/21/07, Miquel Poch <miq...@gm...> wrote:
> And here is my problem. I can put one toolbar for each graph, but when I
> make a zoom I want all the graphs change in the same way. That's possible?
> I've been thinking in make zoom in one graph, and then create a function
> that receive the data of new axes and resize the other graphs.
If the axes are in the same figure, you can use the sharex and sharey
properties of the Axes to synchronize the pan/zoom
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212, sharex=ax1) # share x axis zoom only
but this won't work across figures. I just made some changes to svn
to support this, with new axes methods "sharex_foreign" and
"sharey_foregin" to synchronize x or y views of Axes across different
figures. This example now lives in svn as
examples/shared_axis_across_figures.py
Note I changed the little used and somewhat broken custom Axes
callback handling -- if any of you are using that see the API_CHANGES
notes in svn.
"""
connect the data limits on the axes in one figure with the axes in
another. This is not the right way to do this for two axes in the
same figure -- use the sharex and sharey property in that case
"""
import numpy
from pylab import figure, show
fig1 = figure()
fig2 = figure()
ax1 = fig1.add_subplot(111)
ax2 = fig2.add_subplot(111)
ax1.plot(numpy.random.rand(100), 'o')
ax2.plot(numpy.random.rand(100), 'o')
ax1.sharex_foreign(ax2)
ax2.sharex_foreign(ax1)
ax1.sharey_foreign(ax2)
ax2.sharey_foreign(ax1)
show()

and a quick sample (not suptitle, but using subplots_adjust):
import pylab as p
p.figtext(0.5,0.9,'Big Old Title', ha='center')
p.subplots_adjust(top=0.8)
p.subplot(1,2,1)
p.title('Lefthand')
p.plot([4,3,2,1])
p.subplot(1,2,2)
p.title('Righthand')
p.plot([3,3,1,3])
On Jun 21, 2007, at 21 Jun,2:14 PM, Philip Austin wrote:
> st...@th... writes:
>> I didn't see this in the examples. Can I have a figure title and 
>> titles
>> for subplots too? Can someone post a quick sample? Thanks.
>
> here's a short answer:
> http://thread.gmane.org/gmane.comp.python.matplotlib.devel/1071/ 
> focus=1117
>
> -- Phil
>
>
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Pierre GM wrote:
> All,
> I need to plot stripes of different widths at different locations along the x 
> axis, but spanning the whole range of y data. Using axvspan in a loop works 
> quite fine. However, I was wondering whether it wouldn't be more efficient to 
> build a PatchCollection. 
> BrokenBarHCollection could be a candidate, but I have trouble figuring how to 
> force the bars to span the whole range of y: is it possible to force the 
> ordinates to axes coordinates ?
> Thanks a lot in advance for any idea/comment
I haven't tried it, but I think you can use the same trick that axvspan 
uses:
 trans = blend_xy_sep_transform( self.transData, self.transAxes )
where "self" in this case is the axes instance, so you would use "ax" or 
whatever. Then, since the collection is an artist, you can use its 
inherited set_transform(trans) method, and specify your x coordinates in 
data units and your y as 0 and 1 to span the whole vertical extent. 
This is assuming you want the width of your bars to be in data 
coordinates, not just the x-positions of their centers.
Eric
> P.
> 
> -------------------------------------------------------------------------
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> Download DB2 Express C - the FREE version of DB2 express and take
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st...@th... writes:
 > I didn't see this in the examples. Can I have a figure title and titles
 > for subplots too? Can someone post a quick sample? Thanks.
here's a short answer:
http://thread.gmane.org/gmane.comp.python.matplotlib.devel/1071/focus=1117
-- Phil

On 6/21/07, Pierre GM <pgm...@gm...> wrote:
> All,
> I need to plot stripes of different widths at different locations along the x
> axis, but spanning the whole range of y data. Using axvspan in a loop works
> quite fine. However, I was wondering whether it wouldn't be more efficient to
> build a PatchCollection.
> BrokenBarHCollection could be a candidate, but I have trouble figuring how to
> force the bars to span the whole range of y: is it possible to force the
> ordinates to axes coordinates ?
> Thanks a lot in advance for any idea/comment
You could use this if you pass in a custom blended transform -- see
the src for axhspan and axvspan to see how it creates the blended
transform (blend of xaxis and yaxis transform) and just pass this off
to the bar collection.
Let me know if you need any help.
JDH

I didn't see this in the examples. Can I have a figure title and titles
for subplots too? Can someone post a quick sample? Thanks.
Stephen

All,
I need to plot stripes of different widths at different locations along the x 
axis, but spanning the whole range of y data. Using axvspan in a loop works 
quite fine. However, I was wondering whether it wouldn't be more efficient to 
build a PatchCollection. 
BrokenBarHCollection could be a candidate, but I have trouble figuring how to 
force the bars to span the whole range of y: is it possible to force the 
ordinates to axes coordinates ?
Thanks a lot in advance for any idea/comment
P.

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 <rya...@gm...> [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 <be...@sm...> 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 <rya...@gm...> [070612 08:17]:
> >> Just my 0ドル.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 <be...@sm...> wrote:
> >> >* John Hunter <jd...@gm...> [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

Hi!
I'm trying to embed Matplotlib in wxPython and I find myself in some
troubles. I'm sure someone here could help me.
I need an application where plot some functions, three or four graphics at
the same time. I've done a frame, and with matplotlib I've plot two graphs
in it. I've introduced a toolbar, NavigationToolbar2Wx.
And here is my problem. I can put one toolbar for each graph, but when I
make a zoom I want all the graphs change in the same way. That's possible?
I've been thinking in make zoom in one graph, and then create a function
that receive the data of new axes and resize the other graphs.
Thanks in advance, all suggestions gratefully received!
Miquel

It would be VERY nice if all characteristics of a point , e.g., alpha,
marker, label, etc., were individually configurable via a sequence in
the scatter command just as color and size are now.
Does anyone have a patch for this?
Jon