old_contents: # Author: Brian M. Clapper, G Varoquaux
  # License: BSD
  
  import numpy as np
  
  from sklearn.utils.linear_assignment_ import _Hungarian
  
  
  def test_hungarian():
      matrices = [
          # Square
          ([[400, 150, 400],
            [400, 450, 600],
            [300, 225, 300]],
           850  # expected cost
           ),
  
          # Rectangular variant
          ([[400, 150, 400, 1],
            [400, 450, 600, 2],
            [300, 225, 300, 3]],
           452  # expected cost
           ),
  
          # Square
          ([[10, 10,  8],
            [9,  8,  1],
            [9,  7,  4]],
           18
           ),
  
          # Rectangular variant
          ([[10, 10,  8, 11],
            [9, 8, 1, 1],
            [9, 7, 4, 10]],
           15
           ),
  
          # n == 2, m == 0 matrix
          ([[], []],
           0
           ),
      ]
  
      m = _Hungarian()
      for cost_matrix, expected_total in matrices:
          print np.array(cost_matrix)
          cost_matrix = np.array(cost_matrix)
          indexes = m.compute(cost_matrix)
          total_cost = 0
          for r, c in indexes:
              x = cost_matrix[r, c]
              total_cost += x
          assert expected_total == total_cost
  
          indexes = m.compute(cost_matrix.T)
          total_cost = 0
          for c, r in indexes:
              x = cost_matrix[r, c]
              total_cost += x
          assert expected_total == total_cost
  
new_contents: # Author: Brian M. Clapper, G Varoquaux
  # License: BSD
  
  import numpy as np
  
  from sklearn.utils.linear_assignment_ import _Hungarian
  
  
  def test_hungarian():
      matrices = [
          # Square
          ([[400, 150, 400],
            [400, 450, 600],
            [300, 225, 300]],
           850  # expected cost
           ),
  
          # Rectangular variant
          ([[400, 150, 400, 1],
            [400, 450, 600, 2],
            [300, 225, 300, 3]],
           452  # expected cost
           ),
  
          # Square
          ([[10, 10,  8],
            [9,  8,  1],
            [9,  7,  4]],
           18
           ),
  
          # Rectangular variant
          ([[10, 10,  8, 11],
            [9, 8, 1, 1],
            [9, 7, 4, 10]],
           15
           ),
  
          # n == 2, m == 0 matrix
          ([[], []],
           0
           ),
      ]
  
      m = _Hungarian()
      for cost_matrix, expected_total in matrices:
          cost_matrix = np.array(cost_matrix)
          indexes = m.compute(cost_matrix)
          total_cost = 0
          for r, c in indexes:
              x = cost_matrix[r, c]
              total_cost += x
          assert expected_total == total_cost
  
          indexes = m.compute(cost_matrix.T)
          total_cost = 0
          for c, r in indexes:
              x = cost_matrix[r, c]
              total_cost += x
          assert expected_total == total_cost
  
subject: Remove print in Hungarian tests