code: def get_point_mutual(
      p_pos: float,
      p_feature: float,
      p_pos_feature: float,
      total_count: int,
  ) -> float:
      """
      Returns the Point Mutual Information of a feature, an entropy measure
      which quantifies the discrepancy between the probability of their
      coincidence given their joint distribution and their individual
      distributions (assuming independence).
      https://en.wikipedia.org/wiki/Pointwise_mutual_information
  
      :param p_pos: The probability of the positive outcome in the dataset.
      :type p_pos: float
      :param p_feature: The probability of the feature in the dataset.
      :type p_feature: float
      :param p_pos_feature: The probability of the positive outcome and the
          feature in the dataset.
      :type p_pos_feature: float
      :param total_count: The total number of observations in the dataset.
      :type total_count: int
      :return: The Point Mutual Information of the feature.
      :rtype: float
      """
      dp = get_statistical_parity(
          p_pos, p_feature, p_pos_feature, total_count
      )
      return -np.inf if dp == 0 else np.log(dp)
  
imports: import itertools
  import warnings
  from typing import Callable, Dict, List, Tuple
  import numpy
  import pandas
  import scipy
  from responsibleai.databalanceanalysis.balance_measures import BalanceMeasures
  from responsibleai.databalanceanalysis.constants import Constants, Measures
label_desc: Use image node_id 2 for calling a global function with example usage: get_point_mutual(p_pos, p_feature, p_pos_feature, total_count) and returns: unknown