content: import matplotlib.pyplot as plt
  
  with open("test_pen", "r") as f:
      data = f.read()
  data = data.split("\n")[:-1]
  data = [data[i].split(" ") for i in range(0, len(data))]
  pen = [float(data[i][0]) for i in range(len(data))]
  u = [float(data[i][1]) for i in range(len(data))]
  d = [float(data[i][2]) for i in range(len(data))]
  gain = [((d[i-1] - d[i])) / (u[i] - u[i - 1]) for i in range(1, len(data))]
  gain = [gain[0]] + gain
  print(u, d, gain)
  fig, ax1 = plt.subplots()
  pu, = ax1.plot(pen, u, color="r", label="Uncertainty rate")
  ax1.scatter(pen, u, color="k")
  #ax1.axhline(9000, color="r", linestyle="--")
  #ax1.set_title("Cost evolution according to the number of iterations")
  ax1.set_xlabel("Penalization coefficient")
  ax1.set_ylabel("Uncertainty rate")
  ax2 = ax1.twinx()
  pd, = ax2.plot(pen, d, color="b", linestyle="--", label="Distance")
  ax2.scatter(pen, d, color="k")
  ax2.set_ylabel("Distance")
  #ax2.axhline(0.99, color="b", linestyle="--")
  #plt.axvline(4000000, color="k",linestyle = ":")
  plt.legend(handles=[pu, pd], loc=7)
  plt.show()
  