code: def mutual_information(cooccurrence):
      """Helper method to calculate the Mutual Information of a matrix of
      co-occurrences.
  
      Mutual information is a measurement of the amount of information
      explained by the i-th j-th item column vector.
  
      Args:
          cooccurrence (numpy.ndarray): The symmetric matrix of co-occurrences of items.
  
      Returns:
          numpy.ndarray: The matrix of mutual information between any two items.
  
      """
  
      with np.errstate(invalid="ignore", divide="ignore"):
          result = np.log2(cooccurrence.shape[0] * lift(cooccurrence))
  
      return np.array(result)
  
file_path: recommenders/recommenders/utils/python_utils.py
imports: import logging
  import numpy
  from scipy import sparse
label_desc: Use image node_id 5 for calling a global function with example usage: mutual_information(cooccurrence) and returns: np