code: def Kdiag(self, X, target):
          
          ly=1/self.lengthscaleY
          lu=np.sqrt(3)/self.lengthscaleU
          #ly=self.lengthscaleY
          #lu=self.lengthscaleU
          
          k1 = (2*lu+ly)/(lu+ly)**2
          k2 = (ly-2*lu + 2*lu-ly ) / (ly-lu)**2 
          k3 = 1/(lu+ly) + (lu)/(lu+ly)**2 
  
          np.add(self.varianceU*self.varianceY*(k1+k2+k3), target, target)
docs: Compute the diagonal of the covariance matrix associated to X.