old_contents: import sys
  import megatableau, data_prob
  import scipy, scipy.optimize
  
  # Argument parsing
  assert len(sys.argv)==2
  tableau_file_name = sys.argv[1]
  
  # Read in data
  mt = megatableau.MegaTableau(tableau_file_name)
  w_0 = -scipy.rand(len(mt.weights))
  nonpos_reals = [(-25,0) for wt in mt.weights]
  
  def one_minus_probability(weights, tableau):
      return 1.0-data_prob.probability(weights, tableau)
  
  def negative_probability(weights, tableau):
      return -data_prob.probability(weights, tableau)
  
  learned_weights = scipy.optimize.fmin_tnc(data_prob.probability, w_0, args = (mt.tableau,), bounds=nonpos_reals, approx_grad=True)
  
  print(learned_weights)
  
  print("Probability given weights found by the original MEGT:")
  print(data_prob.probability([-2.19,-0.43], mt.tableau))
new_contents: import sys
  import megatableau, data_prob
  import scipy, scipy.optimize
  
  # Argument parsing
  assert len(sys.argv)==2
  tableau_file_name = sys.argv[1]
  
  # Read in data
  mt = megatableau.MegaTableau(tableau_file_name)
  w_0 = -scipy.rand(len(mt.weights))
  nonpos_reals = [(-25,0) for wt in mt.weights]
  
  def one_minus_probability(weights, tableau):
      return 1.0-data_prob.probability(weights, tableau)
  
  def negative_probability(weights, tableau):
      return -data_prob.probability(weights, tableau)
  
  learned_weights = scipy.optimize.fmin_tnc(data_prob.probability, w_0, args = (mt.tableau,), bounds=nonpos_reals, approx_grad=True)
  
  print(learned_weights)
  
  # print("Probability given weights found by the original MEGT:")
  # print(data_prob.probability([-2.19,-0.43], mt.tableau))
subject: Comment out lines accidentally left in the last commit. Oops.