[Matplotlib-users] embedding in wx segfault

[Flavio C. C. <fcc...@fi...>]

Hi I have a variant of the embedding_in_wx script that worked fine on my
previous version of matplotlib. Now, with version 0.51 it's seg
faulting. I updated the script to reflect the changes in the library but
still... Can anyone see what may be going wrong?

thanks

here is my script:

-----------------------------------------------------------------------------
# Name:        PlotFigure.py
# Purpose:     Plotting frame that contains the plots generated by Model
Buider
#
# Author:      Flavio C. Coelho
#
# Created:     2004/09/01
# RCS-ID:      $Id: PlotFigure.py,v 1.1 2004/01/13 10:51:43 fccoelho Exp
$
# Copyright:   (c) 2003
# Licence:     GPL
# Obs:   This code was based on Jeremy Donoghue's embedding_in_wx.py
included with 
#       matplotlib.
#-----------------------------------------------------------------------------
#Boa:Frame:PlotFigure

import matplotlib
matplotlib.use('WX')

from matplotlib.backends.backend_wx import Toolbar, FigureCanvasWx,
FigureManager
from matplotlib.figure import Figure
from matplotlib.axes import Subplot
import matplotlib.numerix as numpy
from RandomArray import *

from wxPython.wx import *

def create(parent):
    return PlotFigure(parent)

[wxID_PLOTFIGURE] = map(lambda _init_ctrls: wxNewId(), range(1))

class PlotFigure(wxFrame):
    def _init_ctrls(self, prnt):
        # generated method, don't edit
        wxFrame.__init__(self, id=wxID_PLOTFIGURE, name='Output',
parent=prnt,
              pos=wxPoint(480, 335), size=wxSize(640, 480),
              style=wxDEFAULT_FRAME_STYLE, title='Results')
        self.SetClientSize(wxSize(1280, 893))

    def __init__(self, parent):
        self._init_ctrls(parent)
        self.fig = Figure((10,8), 75)
        self.canvas = FigureCanvasWx(self,-1, self.fig)
        self.toolbar = Toolbar(self.canvas)
        self.toolbar.Realize()

		# On Windows, default frame size behaviour is incorrect
        # you don't need this under Linux
        tw, th = self.toolbar.GetSizeTuple()
        fw, fh = self.canvas.GetSizeTuple()
        self.toolbar.SetSize(wxSize(fw, th))
        
        # Create a figure manager to manage things
        self.figmgr = FigureManager(self.canvas, 1, self)
        
        # Now put all into a sizer
        sizer = wxBoxSizer(wxVERTICAL)
		# This way of adding to sizer prevents resizing
        #sizer.Add(self.fig, 0, wxLEFT|wxTOP)
		
		# This way of adding to sizer allows resizing
        sizer.Add(self.fig, 1, wxLEFT|wxTOP|wxGROW)
		
		# Best to allow the toolbar to resize!
        sizer.Add(self.toolbar, 0, wxGROW)
        self.SetSizer(sizer)
        self.Fit()
        
    def plot_data(self, x,y):
        """
        This function will plot the time series as output by odeint.
        """
        # Use this line if using a toolbar
        a = self.figmgr.add_subplot(111)
        
        # Or this one if there is no toolbar
        #a = Subplot(self.fig, 111)
        
        nvar = min(y[0].shape)
        
        for i in range(nvar):
            a.plot (x,y[0][:,i])
        #plot (x,timeseries[1])
        a.set_xlabel('Time')
        a.set_ylabel('Y[i]')
        a.set_title('Time series')
#---generating tuple of
legends-------------------------------------------------
        b = range(nvar)
        leg = tuple(['y['+str(i)+']' for i in b])
#-------------------------------------------------------------------------------
        a.legend(leg)
        
        self.toolbar.update()
    def plotStats(self,x, ts):
        """
        This function will plot prior an posteriors for the model
variables and parameters.
        """
        # Use this line if using a toolbar
        a = self.figmgr.add_subplot(111)
        
        # Or this one if there is no toolbar
        #a = Subplot(self.fig, 111)
        
        
        a.plot(x,ts[0], 'r-o',x,ts[1],'b-.', x,ts[2],'b-.')
        
        
    def plotDist(data,vname):
        """
        Plots histograms ofthe prior and posterior distributions of the
model components
        meldOut is the output of the Melding.SIR function:
(w,qtiltheta,qtilphi,q1est)
        """
        # Use this line if using a toolbar
        a = self.figmgr.add_subplot(111)
        
        # Or this one if there is no toolbar
        #a = Subplot(self.fig, 111)
        
        nb, bins, patches = a.hist(data, normed=1)
        a.set_title('Prior Distribution')
        a.set_xtitle(vname)
        
        nvp = len(priors) # Get number of variable + parameters in the
model)
        nlik = len (liks) # Get number of likelihood functions
        
        for i in range(nvp):
            nb, bins, patches = a.hist(priors[i], normed=1)
            if i > 0:
                a.figure(i+1)
            a.set_title('Prior Distribution')
     
            
        
        

    def GetToolBar(self):
        # You will need to override GetToolBar if you are using an 
        # unmanaged toolbar in your frame
        return self.toolbar
        
if __name__ == '__main__':
    app = wxPySimpleApp()
    frame = create(None)
    x = normal(0,1,50)
    y = normal(0,1,(5,50))
    frame.plot_data(x,y)
    frame.Show()
    app.MainLoop()