code: def robot_wireless(max_iters=100, kernel=None, optimize=True, plot=True):
      
      try:import pods
      except ImportError:
          print('pods unavailable, see https://github.com/sods/ods for example datasets')
          return
      data = pods.datasets.robot_wireless()
  
      # create simple GP Model
      m = GPy.models.GPRegression(data['Y'], data['X'], kernel=kernel)
  
      # optimize
      if optimize:
          m.optimize(max_iters=max_iters)
  
      Xpredict = m.predict(data['Ytest'])[0]
      if plot:
          pb.plot(data['Xtest'][:, 0], data['Xtest'][:, 1], 'r-')
          pb.plot(Xpredict[:, 0], Xpredict[:, 1], 'b-')
          pb.axis('equal')
          pb.title('WiFi Localization with Gaussian Processes')
          pb.legend(('True Location', 'Predicted Location'))
  
      sse = ((data['Xtest'] - Xpredict)**2).sum()
  
      print(('Sum of squares error on test data: ' + str(sse)))
      return m
docs: Predict the location of a robot given wirelss signal strength readings.