original_docstring: Stores the data for the problem.
docstring: Stores the data for the problem.
docstring_tokens: Stores the data for the problem .
code: def create_data_model(count):
      """Stores the data for the problem."""
      # matrix_data = pd.read_csv(''.join([filepath,'site_latlong.csv']), index_col="SAP_ID")
      matrix_data = pd.read_csv('newdata.csv')
      matrix = matrix_data.values.tolist()
      data = {}
      data['distance_matrix'] = []
      for i in matrix:   
          data['distance_matrix'].append(i)
      #data['vehicle_capacities'] = [100, 100, 100, 100,100]
      data['num_vehicles'] = 10
      data['depot'] = 0
      data['demands'] = []
      for i in range (count):
          data['demands'].append(1)
      
      num = math.ceil(count/data['num_vehicles'] + 2)
      print(num)
      data['vehicle_capacities'] = []
      for i in range (data['num_vehicles']):
          data['vehicle_capacities'].append(num)
          
      #data['vehicle_capacities'] = [20,20, 20, 20,20,20,20,20,20,20]
      return data
code_tokens: def create_data_model ( count ) : matrix_data = pd . read_csv ( 'newdata.csv' ) matrix = matrix_data . values . tolist ( ) data = { } data [ 'distance_matrix' ] = [ ] for i in matrix : data [ 'distance_matrix' ] . append ( i ) data [ 'num_vehicles' ] = 10 data [ 'depot' ] = 0 data [ 'demands' ] = [ ] for i in range ( count ) : data [ 'demands' ] . append ( 1 ) num = math . ceil ( count / data [ 'num_vehicles' ] + 2 ) print ( num ) data [ 'vehicle_capacities' ] = [ ] for i in range ( data [ 'num_vehicles' ] ) : data [ 'vehicle_capacities' ] . append ( num ) return data
short_docstring: Stores the data for the problem.
short_docstring_tokens: Stores the data for the problem .
comment: """Stores the data for the problem."""$SEP$# matrix_data = pd.read_csv(''.join([filepath,'site_latlong.csv']), index_col="SAP_ID")$SEP$#data['vehicle_capacities'] = [100, 100, 100, 100,100]$SEP$#data['vehicle_capacities'] = [20,20, 20, 20,20,20,20,20,20,20]