code: def getExpectedGrad(self, dist, a, b, params, samples, mu, z_prior):
      t, probc_m1_0, probc_m1_1, prob_z_0, prob_z_1 = self.getValueForX(
          dist, a, b, params, z_prior, samples, return_probs=True
      )
      res = np.vstack(
          [
              probc_m1_0 - a * prob_z_0,
              probc_m1_1 - a * prob_z_1,
              -probc_m1_0 + b * prob_z_0,
              -probc_m1_1 + b * prob_z_1,
          ]
      )
      res *= t / np.sqrt(t**2 + mu**2)
      return np.mean(res, axis=1)
  
file_path: AIF360/aif360/algorithms/inprocessing/celisMeta/FalseDiscovery.py
imports: import numpy
  from aif360.algorithms.inprocessing.celisMeta.General import General
label_desc: Use image node_id 1 for calling the FalseDiscovery obj's underlying member method code with example usage: obj.getExpectedGrad(dist, a, b, params, samples, mu, z_prior) and returns: np