code: def _make_index_list(num_samples, num_params, num_groups=None):
          
          if num_groups is None:
              num_groups = num_params
  
          index_list = []
          for j in range(num_samples):
              index_list.append(np.arange(num_groups + 1) + j * (num_groups + 1))
          return index_list
docs: Identify indices of input sample associated with each trajectory
  
          For each trajectory, identifies the indexes of the input sample which
          is a function of the number of factors/groups and the number of samples
  
          Arguments
          ---------
          num_samples : int
              The number of trajectories
          num_params : int
              The number of parameters
          num_groups : int
              The number of groups
  
          Returns
          -------
          list of numpy.ndarray
  
          Example
          -------
          >>> BruteForce()._make_index_list(num_samples=4, num_params=3,
              num_groups=2)
          [np.array([0, 1, 2]), np.array([3, 4, 5]), np.array([6, 7, 8]),
           np.array([9, 10, 11])]