text: # Write a program that will iteratively update and
  # predict based on the location measurements 
  # and inferred motions shown below. 
  
  def update(mean1, var1, mean2, var2):
      new_mean = float(var2 * mean1 + var1 * mean2) / (var1 + var2)
      new_var = 1./(1./var1 + 1./var2)
      return [new_mean, new_var]
  
  def predict(mean1, var1, mean2, var2):
      new_mean = mean1 + mean2
      new_var = var1 + var2
      return [new_mean, new_var]
  
  measurements = [5., 6., 7., 9., 10.]
  motion = [1., 1., 2., 1., 1.]
  measurement_sig = 4.
  motion_sig = 2.
  mu = 0.
  sig = 10000.
  
  #Please print out ONLY the final values of the mean
  #and the variance in a list [mu, sig]. 
  
  # Insert code here
  for i in range(len(motion)):
      mu, sig = update(mu, sig, measurements[i], measurement_sig)
      mu, sig = predict(mu, sig, motion[i], motion_sig)
  print [mu, sig]
  