code: def update_rwalk(self, blob):
          
  
          self.scale = blob['scale']
          accept, reject = blob['accept'], blob['reject']
          facc = (1. * accept) / (accept + reject)
          norm = max(self.facc, 1. - self.facc) * self.npdim
          self.scale *= math.exp((facc - self.facc) / norm)
          self.scale = min(self.scale, math.sqrt(self.npdim))
docs: Update the random walk proposal scale based on the current
          number of accepted/rejected steps.