code: def getValueForX(
      self, dist, a, b, params, z_prior, x, return_cs=False
  ):
      l_1, l_2 = params
      z_0, z_1 = 1 - z_prior, z_prior
  
      pos = np.ones(len(x))
      prob_1_1 = self.prob(dist, np.c_[x, pos, pos])
      prob_m1_1 = self.prob(dist, np.c_[x, -pos, pos])
      prob_1_0 = self.prob(dist, np.c_[x, pos, np.zeros(len(x))])
      prob_m1_0 = self.prob(dist, np.c_[x, -pos, np.zeros(len(x))])
  
      total = prob_1_1 + prob_1_0 + prob_m1_0 + prob_m1_1
      # if total == 0:
      #     return 0
  
      prob_y_1 = (prob_1_1 + prob_1_0) / total
      prob_z_0 = (prob_m1_0 + prob_1_0) / total
      prob_z_1 = (prob_m1_1 + prob_1_1) / total
  
      c_0 = prob_y_1 - 0.5
      c_1 = prob_z_0 / z_0
      c_2 = prob_z_1 / z_1
  
      t = c_0 + c_1 * l_1 + c_2 * l_2
      if return_cs:
          return t, c_1, c_2
      else:
          return t
  
file_path: AIF360/aif360/algorithms/inprocessing/celisMeta/StatisticalRate.py
imports: import numpy
  from aif360.algorithms.inprocessing.celisMeta.General import General
label_desc: Use image node_id 2 for calling the StatisticalRate obj's underlying member method code with example usage: obj.getValueForX(dist, a, b, params, z_prior, x, return_cs) and returns: t,  c_1,  c_2, t