content: #Created by Dmytro Konobrytskyi, 2014 (github.com/Akson)
  import numpy as np
  import matplotlib
  import matplotlib.pyplot
  from RCP3.Infrastructure import TmpFilesStorage
  
  class Backend(object):
      def __init__(self, parentNode):
          self._parentNode = parentNode
  
      def Delete(self):
          """
          This method is called when a parent node is deleted.
          """
          pass
      
      def GetParameters(self):
          """
          Returns a dictionary with object parameters, their values, 
          limits and ways to change them.
          """
          return {}
      
      def SetParameters(self, parameters):
          """
          Gets a dictionary with parameter values and
          update object parameters accordingly
          """
          pass
      
      def ProcessMessage(self, message):
          """
          This message is called when a new message comes. 
          If an incoming message should be processed by following nodes, the 
          'self._parentNode.SendMessage(message)'
          should be called with an appropriate message.
          """
          dataArray = np.asarray(message["Data"])
  
          
          fig = matplotlib.pyplot.figure(figsize=(6, 4), dpi=float(96))
          ax=fig.add_subplot(111)
          #n, bins, patches = ax.hist(dataArray, bins=50)
          ax.plot(range(len(dataArray)), dataArray)
  
          processedMessage = {"Stream":message["Stream"], "Info":message["Info"]} 
          
          filePath, link = TmpFilesStorage.NewTemporaryFile("png")
          fig.savefig(filePath,format='png')
          matplotlib.pyplot.close(fig)
          html = '<img src="http://{}" alt="Image should come here">'.format(link)
          processedMessage["Data"] = html
         
          self._parentNode.SendMessage(processedMessage)
  
  
  
          """        
          print len(message["Data"])
          import numpy as np
          import matplotlib.pyplot as plt
          
          x = np.array(message["Data"])
          
          num_bins = 50
          # the histogram of the data
          n, bins, patches = plt.hist(x, num_bins, normed=1, facecolor='green', alpha=0.5)
          plt.subplots_adjust(left=0.15)
          plt.show()
          """
          
      def AppendContextMenuItems(self, menu):
          """
          Append backend specific menu items to a context menu that user will see
          when he clicks on a node.
          """
          pass