features.py 文件源码

def gradient(self, x, D=None):
        """
        Return gradient
        """
        dx = np.array([np.subtract.outer(x[:,d],x[:,d]) for d in range(x.shape[1])])

        D  = calc_distances(x) if D is None else D
        D  = D**(-0.5*self.n-1)
        D  = squareform(D)

        g = - self.n * dx * D

        return g.sum(-1).T