#-*-coding:utf-8-*- 
import wx 
from matplotlib.figure import Figure 
import matplotlib.font_manager as font_manager 
import numpy as np 
from matplotlib.backends.backend_wxagg import \ 
 FigureCanvasWxAgg as FigureCanvas 
# wxWidgets object ID for the timer 
TIMER_ID = wx.NewId() 
# number of data points 
POINTS = 300 
 
class PlotFigure(wx.Frame): 
  """Matplotlib wxFrame with animation effect""" 
  def __init__(self): 
    wx.Frame.__init__(self, None, wx.ID_ANY, title="CPU Usage Monitor", size=(600, 400)) 
    # Matplotlib Figure 
    self.fig = Figure((6, 4), 100) 
    # bind the Figure to the backend specific canvas 
    self.canvas = FigureCanvas(self, wx.ID_ANY, self.fig) 
    # add a subplot 
    self.ax = self.fig.add_subplot(111) 
    # limit the X and Y axes dimensions 
    self.ax.set_ylim([0, 100]) 
    self.ax.set_xlim([0, POINTS]) 
     
    self.ax.set_autoscale_on(False) 
    self.ax.set_xticks([]) 
    # we want a tick every 10 point on Y (101 is to have 10 
    self.ax.set_yticks(range(0, 101, 10)) 
    # disable autoscale, since we don't want the Axes to ad 
    # draw a grid (it will be only for Y) 
    self.ax.grid(True) 
    # generates first "empty" plots 
    self.user = [None] * POINTS 
    self.l_user,=self.ax.plot(range(POINTS),self.user,label='User %') 
 
    # add the legend 
    self.ax.legend(loc='upper center', 
              ncol=4, 
              prop=font_manager.FontProperties(size=10)) 
    # force a draw on the canvas() 
    # trick to show the grid and the legend 
    self.canvas.draw() 
    # save the clean background - everything but the line 
    # is drawn and saved in the pixel buffer background 
    self.bg = self.canvas.copy_from_bbox(self.ax.bbox) 
    # bind events coming from timer with id = TIMER_ID 
    # to the onTimer callback function 
    wx.EVT_TIMER(self, TIMER_ID, self.onTimer) 
 
  def onTimer(self, evt): 
    """callback function for timer events""" 
    # restore the clean background, saved at the beginning 
    self.canvas.restore_region(self.bg) 
        # update the data 
    temp =np.random.randint(10,80) 
    self.user = self.user[1:] + [temp] 
    # update the plot 
    self.l_user.set_ydata(self.user) 
    # just draw the "animated" objects 
    self.ax.draw_artist(self.l_user)# It is used to efficiently update Axes data (axis ticks, labels, etc are not updated) 
    self.canvas.blit(self.ax.bbox) 
if __name__ == '__main__': 
  app = wx.PySimpleApp() 
  frame = PlotFigure() 
  t = wx.Timer(frame, TIMER_ID) 
  t.Start(50) 
  frame.Show() 
  app.MainLoop() 

def __del__( self ): 
  t.Stop()