matplotlib-users Mailing List for matplotlib

On 6/30/2012 11:45 AM, Youbao Zhang wrote:
> Dear all,
>
> I successfully installed Python 3.2.3 + Numpy 1.6.2 + Matplotlib 1.2.x
> (Git version). I tried the following command sequence line by line:
>
> huskier@SqueezeVM0:~/Programming/Python/Python-3.2.3$ python3.2
> Python 3.2.3 (default, Jun 30 2012, 07:14:35)
> [GCC 4.4.5] on linux2
> Type "help", "copyright", "credits" or "license" for more information.
> *>>> import matplotlib.pyplot as plt*
> *>>> plt.plot(range(10), range(10))*
> [<matplotlib.lines.Line2D object at 0x3c6f1d0>]
> *>>> plt.show()*
>>>>
>
> However, nothing happens when I typed plt.show(). There should be a
> figure window which I can get using python 2.6.
>
> I do not know what's wrong with my installation. OR matplotlib cannot be
> used with python 3? Any ideas?
>
> Best regards,
>
> Simon
>
Did you create a `setup.cfg` file and enable `backend = TkAgg` before 
building matplotlib? Otherwise add a `import 
matplotlib;matplotlib.use("TkAgg")` statement at the top of the script.
Christoph

On Saturday, June 30, 2012, Youbao Zhang wrote:
> Dear all,
>
> I successfully installed Python 3.2.3 + Numpy 1.6.2 + Matplotlib 1.2.x
> (Git version). I tried the following command sequence line by line:
>
> huskier@SqueezeVM0:~/Programming/Python/Python-3.2.3$ python3.2
> Python 3.2.3 (default, Jun 30 2012, 07:14:35)
> [GCC 4.4.5] on linux2
> Type "help", "copyright", "credits" or "license" for more information.
> *>>> import matplotlib.pyplot as plt*
> *>>> plt.plot(range(10), range(10))*
> [<matplotlib.lines.Line2D object at 0x3c6f1d0>]
> *>>> plt.show()*
> >>>
>
> However, nothing happens when I typed plt.show(). There should be a figure
> window which I can get using python 2.6.
>
> I do not know what's wrong with my installation. OR matplotlib cannot be
> used with python 3? Any ideas?
>
> Best regards,
>
> Simon
>
> Most likely, you didn't have the Dec packages for any of the toolkits
available. Check your build log.
Ben Root

Dear all,
I successfully installed Python 3.2.3 + Numpy 1.6.2 + Matplotlib 1.2.x (Git
version). I tried the following command sequence line by line:
huskier@SqueezeVM0:~/Programming/Python/Python-3.2.3$ python3.2
Python 3.2.3 (default, Jun 30 2012, 07:14:35)
[GCC 4.4.5] on linux2
Type "help", "copyright", "credits" or "license" for more information.
*>>> import matplotlib.pyplot as plt*
*>>> plt.plot(range(10), range(10))*
[<matplotlib.lines.Line2D object at 0x3c6f1d0>]
*>>> plt.show()*
>>>
However, nothing happens when I typed plt.show(). There should be a figure
window which I can get using python 2.6.
I do not know what's wrong with my installation. OR matplotlib cannot be
used with python 3? Any ideas?
Best regards,
Simon

Hi, everyone:
 I have get a example from the documentation(
http://matplotlib.sourceforge.net/examples/user_interfaces/embedding_in_wx2.html
).
 I want to add a annotation to the figure, so I modified the code.
 I encounter a problem, I add the annotation to the figure, but it
didn't work,it cann't be dragged.What can I do for this problem?
 Thanks.
This is my code:
#!/usr/bin/env python
"""
An example of how to use wx or wxagg in an application with the new
toolbar - comment out the setA_toolbar line for no toolbar
"""
# Used to guarantee to use at least Wx2.8
import wxversion
wxversion.ensureMinimal('2.8')
from numpy import arange, sin, pi
import matplotlib
# uncomment the following to use wx rather than wxagg
#matplotlib.use('WX')
#from matplotlib.backends.backend_wx import FigureCanvasWx as FigureCanvas
# comment out the following to use wx rather than wxagg
matplotlib.use('WXAgg')
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as
FigureCanvas
from matplotlib.backends.backend_wx import NavigationToolbar2Wx
from matplotlib.figure import Figure
import matplotlib.pyplot as plt
import wx
class CanvasFrame(wx.Frame):
 def __init__(self):
 wx.Frame.__init__(self,None,-1,
 'CanvasFrame',size=(550,350))
 self.SetBackgroundColour(wx.NamedColor("WHITE"))
 self.figure = plt.figure()
 self.axes = self.figure.add_subplot(111)
 bbox_args = dict(boxstyle="round", fc="0.8")
 #this is the annotation
 self.an1 = self.axes.annotate('Drag me 1', xy=(.5, .7), #
xycoords='data',
 #xytext=(.5, .7), textcoords='data',
 ha="center", va="center",
 bbox=bbox_args,
 #arrowprops=arrow_args
 )
 self.an1.draggable(True)
 t = arange(0.0,3.0,0.01)
 s = sin(2*pi*t)
 self.axes.plot(t,s)
 self.canvas = FigureCanvas(self, -1, self.figure)
 self.sizer = wx.BoxSizer(wx.VERTICAL)
 self.sizer.Add(self.canvas, 1, wx.LEFT | wx.TOP | wx.GROW)
 self.SetSizer(self.sizer)
 self.Fit()
 self.add_toolbar() # comment this out for no toolbar
 def add_toolbar(self):
 self.toolbar = NavigationToolbar2Wx(self.canvas)
 self.toolbar.Realize()
 if wx.Platform == '__WXMAC__':
 # Mac platform (OSX 10.3, MacPython) does not seem to cope with
 # having a toolbar in a sizer. This work-around gets the buttons
 # back, but at the expense of having the toolbar at the top
 self.SetToolBar(self.toolbar)
 else:
 # On Windows platform, default window size is incorrect, so set
 # toolbar width to figure width.
 tw, th = self.toolbar.GetSizeTuple()
 fw, fh = self.canvas.GetSizeTuple()
 # By adding toolbar in sizer, we are able to put it at the
bottom
 # of the frame - so appearance is closer to GTK version.
 # As noted above, doesn't work for Mac.
 self.toolbar.SetSize(wx.Size(fw, th))
 self.sizer.Add(self.toolbar, 0, wx.LEFT | wx.EXPAND)
 # update the axes menu on the toolbar
 self.toolbar.update()
 def OnPaint(self, event):
 self.canvas.draw()
class App(wx.App):
 def OnInit(self):
 'Create the main window and insert the custom frame'
 frame = CanvasFrame()
 frame.Show(True)
 return True
app = App(0)
app.MainLoop()
-- 
leejeal
Email:lee...@gm...

Hi all,
on behalf of the IPython development team, and just in time for the
imminent Debian freeze and SciPy 2012, I'm thrilled to announce, after
an intense 6 months of work, the official release of IPython 0.13.
This version contains several major new features, as well as a large
amount of bug and regression fixes. The previous version (0.12) was
released on December 19 2011, so in this development cycle we had:
- ~6 months of work.
- 373 pull requests merged.
- 742 issues closed (non-pull requests).
- contributions from 62 authors.
- 1760 commits.
- a diff of 114226 lines.
This means that we closed a total of 1115 issues over 6 months, for a
rate of almost 200 issues closed per month and almost 300 commits per
month. We are very grateful to all of you who have contributed so
enthusiastically to the project and have had the patience of pushing
your contributions through our often lengthy review process.
We've also welcomed several new members to the core IPython
development group: Jörgen Stenarson (@jstenar - this really was an
omission as Jörgen has been our Windows expert for a long time) and
Matthias Bussonier (@Carreau), who has been very active on all fronts
of the project.
*Highlights*
There is too much new work to write up here, so we refer you to our
full What's New document
(http://ipython.org/ipython-doc/rel-0.13/whatsnew/version0.13.html)
for the full details. But the main highlights of this release are:
* Brand new UI for the notebook, with major usability improvements
(real menus, toolbar, and much more)
* Manage all your parallel cluster configurations from the notebook
with push-button simplicity (cluster start/stop with one button).
* Cell magics: commands prefixed with %% apply to an entire cell. We
ship with many cell magics by default, including timing, profiling,
running cells under bash, Perl and Ruby as well as magics to interface
seamlessly with Cython, R and Octave.
* The IPython.parallel tools have received many fixes, optimizations,
and a number of API improvements to make writing, profiling and
debugging parallel codes with IPython much easier.
* We have unified our interactive kernels (the basic ipython object
you know and love) with the engines running in parallel, so that you
can now use all IPython special tricks in parallel too. And you can
connect a console or qtconsole to any parallel engine for direct,
interactive execution, plotting and debugging in a cluster.
*Downloads*
Download links and instructions are at: http://ipython.org/download.html
And IPython is also on PyPI: http://pypi.python.org/pypi/ipython
Those contain a built version of the HTML docs; if you want pure
source downloads with no docs, those are available on github:
Tarball: https://github.com/ipython/ipython/tarball/rel-0.13
Zipball: https://github.com/ipython/ipython/zipball/rel-0.13
Please see our release notes for the full details on everything about
this release:
http://ipython.org/ipython-doc/rel-0.13/whatsnew/version0.13.html
As usual, if you find any other problem, please file a ticket --or
even better, a pull request fixing it-- on our github issues site
(https://github.com/ipython/ipython/issues).
Many thanks to all who contributed!
Fernando, on behalf of the IPython development team.
http://ipython.org