Python Matplotlib 交互式绘图 - 几帧后冻结

Question

我在让 matplotlib 与交互式绘图一起正常工作时遇到问题……我看到的是，在显示几帧我的模拟数据后，matplotlib 挂起 - 并且不再显示。

基本上我一直在玩一些科学模拟 - 并且希望能够在制作结果时绘制我的结果 - 而不是在最后 - 使用 pylab.show()。

我从不久前发现了一个食谱示例，它似乎可以满足我的需求 - 简单来说（尽管数据不同）。食谱在这里...http://www.scipy.org/Cookbook/Matplotlib/Animations#head-2f6224cc0c133b6e35c95f4b74b1b6fc7d3edca4

我搜索了一下，我知道有些人以前遇到过这些问题 - Matplotlib animation either freezes after a few frames or just doesn't work 但当时似乎没有好的解决方案。我想知道是否有人在这里找到了一个好的解决方案。

我在 matplotlib 上尝试了一些“后端”......TkAgg 似乎适用于几个帧...... qt4agg 不显示帧。我还没有正确安装 GTK。

我正在运行最新的 pythonxy(2.7.3)。

有人有什么建议吗？

import matplotlib
matplotlib.use('TkAgg') # 'Normal' Interactive backend. - works for several frames
#matplotlib.use('qt4agg') # 'QT' Interactive backend. - doesn't seem to work at all
#matplotlib.use('GTKAgg') # 'GTK' backend - can't seem to get this to work.... -

import matplotlib.pyplot as plt
import time
import numpy as np

plt.ion()

tstart = time.time()                     # for profiling
x = np.arange(0,2*np.pi,0.01)            # x-array
line, = plt.plot(x,np.sin(x))

#plt.ioff()

for i in np.arange(1,200):

    line.set_ydata(np.sin(x+i/10.0))  # update the data
    line.axes.set_title('frame number {0}'.format(i))

    plt.draw()                         # redraw the canvas

print 'FPS:' , 200/(time.time()-tstart)

编辑：

编辑的代码 - 摆脱一些风格问题。

Answer 1

好的...所以我整理了一些可能对我有用的东西....

基本上它就像一个淡化的 gui - 但我希望它是一个我可以导入的类，并且基本上忘记了（希望如此）的细节。

我应该说 - 这是我第一次尝试在 python 中使用线程或 gui - 所以这段代码带有健康警告。

** 不过，我不会将问题标记为已回答 - 因为我确信更有经验的人会有更好的解决方案。

'''

JP

Attempt to get multiple updating of matplotlibs working.
Uses WX to create an 'almost' gui with a mpl in the middle of it.
Data can be queued to this object - or you can directly plot to it.

Probably will have some limitations atm
- only really thinking about 2d plots for now -
but presumably can work around this for other implimentations.
- the working code seems to need to be put into another thread.
Tried to put the wx mainloop into another thread,
but it seemed unhappy. :(



Classes of Interest :
    GraphData - A silly class that holds data to be plotted.
    PlotFigure - Class of wx frame type.
        Holds a mpl figure in it + queue to queue data to.
        The frame will plot the data when it refreshes it's canvas

    ThreadSimulation - This is not to do with the plotting
                        it is a test program.


Modified version of:

Copyright (C) 2003-2005 Jeremy O'Donoghue and others

License: This work is licensed under the PSF. A copy should be included
with this source code, and is also available at
http://www.python.org/psf/license.html

'''
import threading
import collections
import time

import numpy as np

import matplotlib
matplotlib.use('WXAgg')



from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg
from matplotlib.backends.backend_wx import NavigationToolbar2Wx

from matplotlib.figure import Figure

import wx







class GraphData(object):
    '''
        A silly class that holds data to be plotted.
    '''
    def __init__(self, xdatainit, ydatainit):

        self.xdata = xdatainit
        self.ydata = ydatainit

class PlotFigure(wx.Frame):

    def __init__(self ):
        '''
            Initialises the frame.
        '''
        wx.Frame.__init__(self, None, -1, "Test embedded wxFigure")

        self.timerid = wx.NewId()

        self.fig = Figure((5,4), 75)
        self.canvas = FigureCanvasWxAgg(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))

        # Now put all into a sizer
        sizer = wx.BoxSizer(wx.VERTICAL)
        # 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()
        wx.EVT_TIMER(self, self.timerid, self.onTimer)

        self.dataqueue = collections.deque()

        # Add an axes and a line to the figure.
        self.axes = self.fig.add_subplot(111)
        self.line, = self.axes.plot([],[])

    def GetToolBar(self):
        '''
            returns default toolbar.
        '''
        return self.toolbar

    def onTimer(self, evt):
        '''
            Every timer period this is called.

            Want to redraw the canvas.
        '''
        #print "onTimer"
        if len(self.dataqueue) > 0 :
            data = self.dataqueue.pop()

            x = data.xdata
            y = data.ydata

            xmax = max(x)
            xmin = min(x)

            ymin = round(min(y), 0) - 1
            ymax = round(max(y), 0) + 1

            self.axes.set_xbound(lower=xmin, upper=xmax)
            self.axes.set_ybound(lower=ymin, upper=ymax)

            self.line.set_xdata(x)
            self.line.set_ydata(y)

        # Redraws the canvas - does this even if the data isn't updated...
        self.canvas.draw()


    def onEraseBackground(self, evt):
        '''
        this is supposed to prevent redraw flicker on some X servers...
        '''
        pass


class ThreadSimulation(threading.Thread):
    '''
    Simulation Thread - produces data to be displayed in the other thread.
    '''

    def __init__(self,  nsimloops, datastep, pltframe, slowloop = 0):
        threading.Thread.__init__(self)

        self.nsimloops = nsimloops
        self.datastep = datastep
        self.pltframe = pltframe
        self.slowloop=slowloop

    def run(self):
        '''
        This is the simulation function.
        '''
        nsimloops = self.nsimloops
        datastep = self.datastep
        pltframe = self.pltframe

        print 'Sim Thread: Starting.'
        tstart = time.time()               # for profiling

        # Define Data to share between threads.
        x  = np.arange(0,2*np.pi,datastep)            # x-array
        y  = np.sin(x )

        # Queues up the data and removes previous versions.
        pltframe.dataqueue.append(GraphData(x,y))
        for i in range(len(pltframe.dataqueue)-1):
            pltframe.dataqueue.popleft()
        pltframe.dataqueue

        for i in np.arange(1, nsimloops):


            x = x + datastep
            y = np.sin(x)

            # Queues up the data and removes previous versions.
            pltframe.dataqueue.append(GraphData(x,y))
            for i in range(len(pltframe.dataqueue)-1):
                pltframe.dataqueue.popleft()
            #pltframe.dataqueue

            if self.slowloop > 0 :
                time.sleep(self.slowloop)



        tstop= time.time()
        print 'Sim Thread: Complete.'
        print 'Av Loop Time:' , (tstop-tstart)/ nsimloops

if __name__ == '__main__':


    # Create the wx application.
    app = wx.PySimpleApp()

    # Create a frame with a plot inside it.
    pltframe = PlotFigure()
    pltframe1 = PlotFigure()

    # Initialise the timer - wxPython requires this to be connected to
    # the receiving event handler

    t = wx.Timer(pltframe, pltframe.timerid)
    t.Start(100)

    pltframe.Show()
    pltframe1.Show()

    npoints = 100
    nsimloops = 20000
    datastep = 2 * np.pi/ npoints
    slowloop = .1

    #Define and start application thread
    thrd = ThreadSimulation(nsimloops, datastep, pltframe,slowloop)
    thrd.setDaemon(True)
    thrd.start()

    pltframe1.axes.plot(np.random.rand(10),np.random.rand(10))

    app.MainLoop()