docs: def resample(self,N,**kwargs):
          """Random resampling of the doublegauss distribution
          """
          lovals = self.mu - np.absolute(rand.normal(size=N)*self.siglo)
          hivals = self.mu + np.absolute(rand.normal(size=N)*self.sighi)
  
          u = rand.random(size=N)
          hi = (u < float(self.sighi)/(self.sighi + self.siglo))
          lo = (u >= float(self.sighi)/(self.sighi + self.siglo))
  
          vals = np.zeros(N)
          vals[hi] = hivals[hi]
          vals[lo] = lovals[lo]
          return vals