# -*- coding:latin-1 -*- #----------------------------------------------------------------------------- # 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('WXAgg') from matplotlib.backends.backend_wx import NavigationToolbar2Wx, FigureManager from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas from matplotlib.figure import Figure from matplotlib.axes import Subplot import matplotlib.numerix as numpy #from RandomArray import * #from numpy.random.old import * from pylab import * from numpy.random import * from numpy import * import wxversion wxversion.select('2.8') import wx def create(parent): return PlotFigure(parent) [wxID_PLOTFIGURE] = [wx.NewId() for _init_ctrls in range(1)] class PlotFigure(wx.Frame): def _init_ctrls(self, prnt): # generated method, don't edit wx.Frame.__init__(self, id=wxID_PLOTFIGURE, name='Output', parent=prnt, pos=wx.Point(311, 209), size=wx.Size(1280, 893), style=wx.DEFAULT_FRAME_STYLE, title='Results') self.SetClientSize(wx.Size(1280, 893)) def __init__(self, parent): self._init_ctrls(parent) self.fig = Figure((10,8), 75) self.canvas = FigureCanvas(self,-1, self.fig) self.toolbar = NavigationToolbar2Wx(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(wx.Size(fw, th)) # Create a figure manager to manage things self.figmgr = FigureManager(self.canvas, 1, self) # Now put all into a sizer sizer = wx.BoxSizer(wx.VERTICAL) # 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.canvas, 1, wx.LEFT|wx.TOP|wx.GROW) # Best to allow the toolbar to resize! sizer.Add(self.toolbar, 0, wx.GROW) self.SetSizer(sizer) self.Fit() def plot(self,x,y,leg=[]): """ This function will plot one or more lines. y is a list of sequances or a single vector. x is a vector. """ # Use this line if using a toolbar a = self.fig.add_subplot(111) # Or this one if there is no toolbar #a = Subplot(self.fig, 111) if str(type(y)) == "": nlin = len(y) for i in range(nlin): a.plot (x,y[i]) else: a.plot(x,y) a.set_xlabel('Time', fontsize=9) #---generating tuple of legends------------------------------------------------- if str(type(y)) == "": if leg ==[]: b = range(nlin) leg = tuple(['$y_{'+str(i)+'}$' for i in b]) else: pass #------------------------------------------------------------------------------- a.legend(leg) self.toolbar.update() def vectorField(self,x,y,u,v,c=0.2,xlabel='',ylabel='',trajectory=[]): """ Plot a vector field for State space visualizations """ # Use this line if using a toolbar a = self.fig.add_subplot(111) # Or this one if there is no toolbar #a = Subplot(self.fig, 111) q = a.quiver2(x,y,u,v,c,units='x') a.set_xlabel(xlabel) a.set_ylabel(ylabel) a.set_title('State Space Diagram') if trajectory: for i in range(len(trajectory))[::2]: lt = '-' if i != 0: lt = ':' a.plot(trajectory[i],trajectory[i+1],lt,linewidth=2) # Do contours for isoclines print x.shape sq = int(sqrt(len(x))) x.shape = (sq,sq) y.shape = (sq,sq) u.shape = (sq,sq) v.shape = (sq,sq) z1 = sqrt(u**2+v**2) #basic arrow lengths z2 = u #dx/dt z3 = v #dy/dt lev = (0,) cs1 = a.contour(x,y,z1,20,origin='lower')#general isoclines # im = a.imshow(z1, interpolation='bilinear',alpha=0.9, origin='lower',cmap=cm.gray) cs1l = a.contour(x,y,z1,lev,linewidths=2,colors='k',origin='lower') cs2l = a.contour(x,y,z2,lev,linewidths=2,colors='k',origin='lower') cs3l = a.contour(x,y,z3,lev,linewidths=2,colors='k',origin='lower') #doing contour labels a.clabel(cs1l,fmt = 'Nullcline %2.1f',inline=0, colors = 'r', fontsize=14) a.clabel(cs2l,fmt = 'dx/dt=%2.1f',inline=0, colors = 'r', fontsize=14) a.clabel(cs3l,fmt = 'dy/dt=%2.1f',inline=0, colors = 'r', fontsize=14) def plotSpecg(self,x, name): """ Makes a Spectrogram plot of x """ # Use this line if using a toolbar a = self.fig.add_subplot(111) # Or this one if there is no toolbar #a = Subplot(self.fig, 111) a.specgram(x) a.set_xlabel('time') a.set_ylabel('frequency') a.set_title('Spectrogram of %s'%name) def plotSpec(self,x, name): """ Makes a power spectrum plot of x """ # Use this line if using a toolbar a = self.fig.add_subplot(111) # Or this one if there is no toolbar #a = Subplot(self.fig, 111) a.psd(x) a.set_xlabel('frequency') a.set_ylabel('Power(dB)') a.set_title('Power Spectrum of %s'%name) def plot_data(self, x,y,leg=None): """ This function will plot the time series as output by odeint. """ # Use this line if using a toolbar a = self.fig.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]) a.set_xlabel('Time', fontsize=9) a.set_ylabel('$State variables$', fontsize=9) a.set_title('Time series') #---generating tuple of legends------------------------------------------------- if not leg: b = range(nvar) leg = tuple(['$y_{'+str(i)+'}$' for i in b]) #------------------------------------------------------------------------------- a.legend(leg) self.toolbar.update() def plotStats(self,x, ts,vnames=[]): """ This function will plot multiple time series ts is a list of lists: [list of median time-series, list of lower credible intervals, list of upper credible intervals] """ # 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 = len(ts[0]) print len(x), len(ts[0]) c=['r','g','b','c','m','y','k'] for i in range(nvar): a = self.fig.add_subplot(nvar*100+10+i+1) a.plot(x,ts[0][i], '%s-o'%c[i%len(c)],x,ts[1][i],'%s-.'%c[i%len(c)], x,ts[2][i],'%s-.'%c[i%len(c)]) a.set_xlabel('Time', fontsize=9) if vnames: a.set_ylabel(vnames[i], fontsize=9) else: a.set_ylabel('$y_{'+str(i)+'}$', fontsize=9) a.legend(('$median$',)) #---generating tuple of legends------------------------------------------------- ## b = range(nvar) ## leg = tuple(['$y_{'+str(i)+'}$' for i in b]) #------------------------------------------------------------------------------- self.toolbar.update() def plotDist(self,data,vname): """ Plots histograms of each line of 'data' the name of the variables are the elements of the list 'vname' """ nvar = len(data) for i in range(nvar): # Use this line if using a toolbar a = self.fig.add_subplot(nvar*100+10+i+1) nb, bins, patches = a.hist(data[i],bins=50, normed=1) a.set_ylabel(vname[i], fontsize=9) self.toolbar.update() def plotMeldout(self,meldout,vnames=[]): """ Plots histograms of the posterior distributions of the model components meldOut is the output of the Melding.SIR function: (w,qtiltheta,qtilphi,q1est) """ nvar = len(meldout[1]) data = meldout[1] for i in range(nvar): # Use this line if using a toolbar a = self.fig.add_subplot(nvar*100+10+i+1) # Or this one if there is no toolbar #a = Subplot(self.fig, 111) nb, bins, patches = a.hist(data[i],bins=50, normed=1) a.set_title('Posterior Distribution of %s$'%vnames[i], fontsize=9) self.toolbar.update() def plotEquation(self, eqlist): """ Plot list of equations typeset with mathtext on an equation box """ a = self.fig.add_subplot(111) a.plot([0,10],'w.') a.set_xlim((0,10)) a.set_ylim((0,10)) a.set_title('Model Equations') a.set_xticklabels([]) a.set_yticklabels([]) a.set_xticks([]) a.set_yticks([]) for i in range(len(eqlist)): print eqlist[i] a.text(1,9-i,eqlist[i], fontsize=15) self.toolbar.update() 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 = wx.PySimpleApp() frame = create(None) x = normal(0,1,50) y = normal(0,1,(50,5)) frame.plot_data(x,[y]) frame.Show() app.MainLoop()