MaternKernel.py 文件源码

def kernel(self, X, Y=None):

        GenericTests.check_type(X,'X',np.ndarray,2)
        # if X=Y, use more efficient pdist call which exploits symmetry
        if Y is None:
            dists = squareform(pdist(X, 'euclidean'))
        else:
            GenericTests.check_type(Y,'Y',np.ndarray,2)
            assert(shape(X)[1]==shape(Y)[1])
            dists = cdist(X, Y, 'euclidean')
        if self.nu==0.5:
            #for nu=1/2, Matern class corresponds to Ornstein-Uhlenbeck Process
            K = (self.sigma**2.) * exp( -dists / self.width )                 
        elif self.nu==1.5:
            K = (self.sigma**2.) * (1+ sqrt(3.)*dists / self.width) * exp( -sqrt(3.)*dists / self.width )
        elif self.nu==2.5:
            K = (self.sigma**2.) * (1+ sqrt(5.)*dists / self.width + 5.0*(dists**2.) / (3.0*self.width**2.) ) * exp( -sqrt(5.)*dists / self.width )
        else:
            raise NotImplementedError()
        return K