def Gram_matrix(self):
        La = np.column_stack((self.a[0]*np.ones((self.n_basis,1)), self.a[1]*self.basis_omega, self.a[2]*self.basis_omega**2, self.a[3]*self.basis_omega**3))
        Lo = np.column_stack((self.basis_omega, self.basis_omega, self.basis_omega, self.basis_omega))
        Lp = np.column_stack((self.basis_phi, self.basis_phi+np.pi/2, self.basis_phi+np.pi, self.basis_phi+np.pi*3/2))
        r,omega,phi =  self._cos_factorization(La,Lo,Lp)
        Gint = self._int_computation( r,omega,phi, r,omega,phi)

        Flower = np.array(self._cos(self.basis_alpha,self.basis_omega,self.basis_phi)(self.lower))[:,None]
        F1lower = np.array(self._cos(self.basis_alpha*self.basis_omega,self.basis_omega,self.basis_phi+np.pi/2)(self.lower))[:,None]
        F2lower = np.array(self._cos(self.basis_alpha*self.basis_omega**2,self.basis_omega,self.basis_phi+np.pi)(self.lower))[:,None]
        lower_terms = self.b[0]*np.dot(Flower,Flower.T) + self.b[1]*np.dot(F2lower,F2lower.T) + self.b[2]*np.dot(F1lower,F1lower.T) + self.b[3]*np.dot(F2lower,Flower.T) + self.b[4]*np.dot(Flower,F2lower.T)
        return(3*self.lengthscale**5/(400*np.sqrt(5)*self.variance) * Gint + 1./self.variance*lower_terms)
dataset/ETHPy150Open SheffieldML/GPy/GPy/kern/src/periodic.py/PeriodicMatern52.Gram_matrix/original