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From: Alexej Bazhenov <alexej.bazhenov@gm...>  20100314 17:04:19

Hello, I can't understand how to refresh FigureCanvasWxAgg instance. Here is the example: import wx import matplotlib from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas from matplotlib.figure import Figure class MainFrame(wx.Frame): def __init__(self): wx.Frame.__init__(self, None, wx.NewId(), "Main") self.sizer = wx.BoxSizer(wx.VERTICAL) self.figure = Figure(figsize=(1,2)) self.axe = self.figure.add_subplot(111) self.figurecanvas = FigureCanvas(self, 1, self.figure) self.buttonPlot = wx.Button(self, wx.NewId(), "Plot") self.buttonClear = wx.Button(self, wx.NewId(), "Clear") self.sizer.Add(self.figurecanvas, proportion=1, border=5, flag=wx.ALL  wx.EXPAND) self.sizer.Add(self.buttonPlot, proportion=0, border=2, flag=wx.ALL) self.sizer.Add(self.buttonClear, proportion=0, border=2, flag=wx.ALL) self.SetSizer(self.sizer) self.figurecanvas.Bind(wx.EVT_LEFT_DCLICK, self.on_dclick) self.buttonPlot.Bind(wx.EVT_BUTTON, self.on_button_plot) self.buttonClear.Bind(wx.EVT_BUTTON, self.on_button_clear) self.subframe_opened = False def on_dclick(self, evt): self.subframe = SubFrame(self, self.figure) self.subframe.Show(True) self.subframe_opened = True def on_button_plot(self, evt): self.axe.plot(range(10), color='green') self.figurecanvas.draw() def on_button_clear(self, evt): if self.subframe_opened: self.subframe.Close() self.figure.set_canvas(self.figurecanvas) self.axe.clear() self.figurecanvas.draw() class SubFrame(wx.Frame): def __init__(self, parent, figure): wx.Frame.__init__(self, parent, wx.NewId(), "Sub") self.sizer = wx.BoxSizer(wx.VERTICAL) self.figurecanvas = FigureCanvas(self, 1, figure) self.sizer.Add(self.figurecanvas, proportion=1, border=5, flag=wx.ALL  wx.EXPAND) self.SetSizer(self.sizer) self.Bind(wx.EVT_CLOSE, self.on_close) def on_close(self, evt): self.GetParent().subframe_opened = False evt.Skip() class MyApp(wx.App): def OnInit(self): frame = MainFrame() frame.Show(True) self.SetTopWindow(frame) return True app = MyApp(0) app.MainLoop() I'm interested in the following sequence of operations:  run a script  resize the main frame  press Plot button  double click on plot  press Clear button Now I get a mess on main frame plot. If I resize the frame it redraws properly. My question is what should I add to my code to do that without resizing? Thanks in advance, Alex 
From: Friedrich Romstedt <friedrichromstedt@gm...>  20100314 11:37:47

2010/3/14 David Arnold <dwarnold45@...>: > All, > > I am having difficulty with a line on: http://scipy.org/LoktaVolterraTutorial > > Here are the lines: > > values = linspace(0.3, 0.9, 5) > > vcolors = p.cm.autumn_r(linspace(0.3, 1., len(values))) > > First of all, I can find no reference to autumn_r in the Matplotlib documentation. Also, using Aptana (eclipse), PyDev complains about the vcolors line with: The colormap's data is defined in matplotlib._cm.py, there a dictionary defining the names of the colormaps is defined from line no. 5814 on. The colormaps are "imported", i.e. added to the modulelocal namespace by "patching" locals() in matplolib.cm on line 43, where cmap_d also containes reversed versions of all the data defined by matplotlib._cm, indicated by an trailing "_r" in the name. Because the data isn't imported the usual way, your program (PyDev?) will not find it. > Undefined variable from import: autumn_r Lotka.py /scipy/src/pkg line 44 PyDev Problem > > Secondly, I am used to using colormaps in Matlab, but not so much in Matplotlib. In Matlab, g=grey(256) produces an 256x3 matrix and each row is indexed by the numbers 1 through 256. Thus, if you have an image and pixel has a value 124, then row 124 gives an rgb triple that is used to color the pixel. I think you can reproduce the matlab behaviour by using: >>> result = some_colormap(numpy.linspace(0.0, 1.0, 256), [bytes = True]). The optional bytes = True argument specifies to return integer \in [0, 255] colors. The return ndarray will have shape (256, 4), and an indicing result[i] returns the ndarray array([r, g, b, a]). Note than numpy and Python use zerobased indices, opposed to matlab's onebased indices. > However, in the case of vcolors = p.cm.autumn_r(linspace(0.3, 1., len(values))), I'm really not sure what is going on. The linspace(0.3,1,len(values)) produces len(values) equally spaced numbers from 0.3 to 1. Now, how is autumn_r(array([ 0.3 , 0.475, 0.65 , 0.825, 1. ])) make any sense? The first argument to some_colormap.__call__(X, alpha [= 1.0], bytes [= False]) is the interpolation axis. I embed __call__()'s __doc__ string: """ *X* is either a scalar or an array (of any dimension). If scalar, a tuple of rgba values is returned, otherwise an array with the new shape = oldshape+(4,). If the Xvalues are integers, then they are used as indices into the array. If they are floating point, then they must be in the interval (0.0, 1.0). Alpha must be a scalar. If bytes is False, the rgba values will be floats on a 01 scale; if True, they will be uint8, 0255. """ I myself just did a short dive into the matplotlib code of cm.py, _cm.py, and colors.py, so this are just my conclusions. Friedrich 
From: David Arnold <dwarnold45@su...>  20100314 03:18:08

All, I am having difficulty with a line on: http://scipy.org/LoktaVolterraTutorial Here are the lines: values = linspace(0.3, 0.9, 5) vcolors = p.cm.autumn_r(linspace(0.3, 1., len(values))) First of all, I can find no reference to autumn_r in the Matplotlib documentation. Also, using Aptana (eclipse), PyDev complains about the vcolors line with: Undefined variable from import: autumn_r Lotka.py /scipy/src/pkg line 44 PyDev Problem Secondly, I am used to using colormaps in Matlab, but not so much in Matplotlib. In Matlab, g=grey(256) produces an 256x3 matrix and each row is indexed by the numbers 1 through 256. Thus, if you have an image and pixel has a value 124, then row 124 gives an rgb triple that is used to color the pixel. However, in the case of vcolors = p.cm.autumn_r(linspace(0.3, 1., len(values))), I'm really not sure what is going on. The linspace(0.3,1,len(values)) produces len(values) equally spaced numbers from 0.3 to 1. Now, how is autumn_r(array([ 0.3 , 0.475, 0.65 , 0.825, 1. ])) make any sense? Thanks. David. 