docstr: Computes the q which maximizes score (q_mle).
code: def qmle(self, observed_sum: float, expectations: np.array):
      """
      Computes the q which maximizes score (q_mle).
      """
      direction = self.direction
      ans = optim.bisection_q_mle(
          self, observed_sum, expectations, direction=direction
      )
      return ans
  
file_path: AIF360/aif360/detectors/mdss/ScoringFunctions/Poisson.py
imports: from aif360.detectors.mdss.ScoringFunctions.ScoringFunction import ScoringFunction
  from aif360.detectors.mdss.ScoringFunctions import optim
  import numpy
label_desc: Use image node_id 3 for calling the Poisson obj's underlying member method code with example usage: obj.qmle(observed_sum, expectations) and returns: ans