code: def invert_order(scores, method="multiplication"):
      """Invert the order of a list of values. The smallest value becomes
      the largest in the inverted list. This is useful while combining
      multiple detectors since their score order could be different.
  
      Parameters
      ----------
      scores : list, array or numpy array with shape (n_samples,)
          The list of values to be inverted
  
      method : str, optional (default='multiplication')
          Methods used for order inversion. Valid methods are:
  
          - 'multiplication': multiply by -1
          - 'subtraction': max(scores) - scores
  
      Returns
      -------
      inverted_scores : numpy array of shape (n_samples,)
          The inverted list
  
      Examples
      --------
      >>> scores1 = [0.1, 0.3, 0.5, 0.7, 0.2, 0.1]
      >>> invert_order(scores1)
      array([-0.1, -0.3, -0.5, -0.7, -0.2, -0.1])
      >>> invert_order(scores1, method='subtraction')
      array([0.6, 0.4, 0.2, 0. , 0.5, 0.6])
      """
  
      scores = column_or_1d(scores)
  
      if method == "multiplication":
          return scores.ravel() * -1
  
      if method == "subtraction":
          return (scores.max() - scores).ravel()
  
imports: from __future__ import division
  from __future__ import print_function
  import numbers
  import numpy
  import sklearn
  from numpy import percentile
  from sklearn.metrics import precision_score
  from sklearn.preprocessing import StandardScaler
  from sklearn.utils import check_array
  from sklearn.utils import check_consistent_length
  from sklearn.utils import check_random_state
  from sklearn.utils import column_or_1d
  from sklearn.utils.random import sample_without_replacement
label_desc: Use image node_id 11 for calling a global function with example usage: invert_order(scores, method) and returns: unknown, unknown