old_contents: import os.path
  import numpy as np
  import matplotlib.pylab as plt
  import seaborn as sbn
  from mpl_toolkits.mplot3d import Axes3D
  
  if not os.path.isfile('net_results.np'):
      import net
  
  results = np.load('net_results.np')
  
  fig = plt.figure()
  ax = fig.add_subplot(111)
  
  ax.scatter(results[:,0],results[:,3],
             c=results[:,1], cmap='Spectral',
             label=np.unique(results[:,1]))
  plt.legend()
  plt.show()
  
  """
  # 3d-plot
  fig = plt.figure()
  ax = fig.add_subplot(111, projection='3d')
  u_g, i_g = np.unique(results[:,1], return_inverse=True)
  
  ax.scatter(results[:,0], i_g, results[:,3],
             zdir='z', s=20, c='b', marker='o', depthshade=True)
  
  ax.set_xlabel('Alpha')
  ax.set_ylabel('Gamma')
  ax.set_zlabel('Error rate')
  
  ax.set_yticks(np.arange(len(np.unique(results[:,1]))))
  ax.set_yticklabels(u_g)
  
  plt.show()
  """
new_contents: import os.path
  import numpy as np
  import matplotlib.pylab as plt
  import seaborn as sbn
  from mpl_toolkits.mplot3d import Axes3D
  
  if not os.path.isfile('net_results.np'):
      import net
  
  results = np.load('net_results.np')
  
  """
  fig = plt.figure()
  ax = fig.add_subplot(111)
  
  ax.scatter(results[:,0],results[:,3],
             c=results[:,1], cmap='Spectral',
             label=np.unique(results[:,1]))
  
  ax.set_xlabel('Alpha')
  ax.set_ylabel('Error rate')
  
  plt.legend()
  plt.show()
  """
  # 2D plot
  g1_indices = np.where(results[:,1] == 0.0001)
  g2_indices = np.where(results[:,1] == 0.001)
  g3_indices = np.where(results[:,1] == 0.01)
  g4_indices = np.where(results[:,1] == 0.1)
  
  colors = ['b', 'c', 'g', 'r']
  
  g1 = plt.scatter(results[:,0][g1_indices], results[:,3][g1_indices], marker='o', color=colors[0])
  g2 = plt.scatter(results[:,0][g2_indices], results[:,3][g2_indices], marker='o', color=colors[1])
  g3 = plt.scatter(results[:,0][g3_indices], results[:,3][g3_indices], marker='o', color=colors[2])
  g4 = plt.scatter(results[:,0][g4_indices], results[:,3][g4_indices], marker='o', color=colors[3])
  
  plt.legend((g1,g2,g3,g4),
             (r'$\gamma=0.0001$',r'$\gamma=0.001$',r'$\gamma=0.01$', r'$\gamma=0.1$'),
             scatterpoints=1,
             loc='upper left',
             ncol=1,
             fontsize=8)
  
  plt.xlabel('Alpha')
  plt.ylabel('Error rate')
  
  plt.show()
  
  # 3D plot
  
  ax = plt.subplot(111, projection='3d')
  
  ax.scatter(results[:,0][g1_indices], results[:,3][g1_indices], marker='o', color=colors[0],
          label=r'$\gamma=0.0001$')
  ax.scatter(results[:,0][g2_indices], results[:,3][g2_indices], marker='o', color=colors[1],
          label=r'$\gamma=0.001$')
  ax.scatter(results[:,0][g3_indices], results[:,3][g3_indices], marker='o', color=colors[2],
          label=r'$\gamma=0.01$')
  ax.scatter(results[:,0][g4_indices], results[:,3][g4_indices], marker='o', color=colors[3],
          label=r'$\gamma=0.1$')
  
  plt.legend(loc='upper left', numpoints=1, ncol=3, fontsize=8, bbox_to_anchor=(0, 0))
  
  ax.set_xlabel('Alpha')
  ax.set_zlabel('Gamma')
  ax.set_ylabel('Error rate')
  
  plt.show()
  
  """
  # 3d-plot
  fig = plt.figure()
  ax = fig.add_subplot(111, projection='3d')
  u_g, i_g = np.unique(results[:,1], return_inverse=True)
  
  ax.scatter(results[:,0], i_g, results[:,3],
             zdir='z', s=20, c='b', marker='o', depthshade=True)
  
  ax.set_xlabel('Alpha')
  ax.set_ylabel('Gamma')
  ax.set_zlabel('Error rate')
  
  ax.set_yticks(np.arange(len(np.unique(results[:,1]))))
  ax.set_yticklabels(u_g)
  
  plt.show()
  """
subject: add plots