class_docstr: The Model which hold the data. It implements the
  observable in the observer pattern and notifies the
  registered observers on change event.
class_docstr_tok: ["The","Model","which","hold","the","data",".","It","implements","the","observable","in","the","observer","pattern","and","notifies","the","registered","observers","on","change","event","."]
code: def __init__(self):
      self.observers = []
      self.surface = None
      self.data = []
      self.cls = None
      self.surface_type = 0
  
imports: from __future__ import division, print_function
  import matplotlib
  from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
  from matplotlib.backends.backend_tkagg import NavigationToolbar2TkAgg
  from matplotlib.figure import Figure
  from matplotlib.contour import ContourSet
  import Tkinter
  import sys
  import numpy
  from sklearn import svm
  from sklearn.datasets import dump_svmlight_file
  from sklearn.externals.six.moves import xrange
label_desc: Use image node_id 1 to create a new Model object from inherited base classes: object with example: obj = Model()