code.py 文件源码

def get_eigen_vector(self):
        # w,v = np.linalg.eig(self.M)
        # print(max(w),w)
        # max_ind = np.where(w==max(w))[0][0]
        # print(max_ind) 
        # self.w_inf = v[:,max_ind]
        # rearrangedEvalsVecs = sorted(zip(evals,evecs.T),\
        #                             key=lambda x: x[0].real, reverse=True)
        self.w_inf = eigs(self.M.T,1)[1].flatten()
        #make sum 1:
        # print(self.w_inf[:5])
        self.w_inf = self.w_inf / np.sum(self.w_inf)
        print(self.w_inf[:5])
        # print(self.w_inf.shape)