在Matlab中以相同的方式（顺序）计算python中的特征值 [英] Calculate eigen value in python as same way(order) in Matlab

问题描述

这是在V中返回特征向量和在D中返回特征值的Matlab代码。考虑C是9 * 9矩阵，则V是9 * 9矩阵，D是9 * 9对角线。矩阵。

This is the Matlab code which is returning eigenvector in V and eigenvalue in D. Consider C is 9*9 matrix then V is 9*9 matrix and D is 9*9 diagonal. matrix.

[V,D] = eig(C);

我希望Python中的内容与Matlab的顺序相同。我正在使用此代码：

I want the same thing in Python and in the same order as Matlab. I am using this code:

[V1, D] = np.linalg.eig(C)    
V = np.zeros((9,9))

for i in range(9):
    V[i][i] = V1[i]

（考虑V在for循环中）

(consider V to be in the for loop)

此代码给出我在V1中的特征值和D中的特征向量。我将V1改为V以获得对角9 * 9矩阵。

This code is giving me eigenvalue in V1 and eigenvector in D. I changed V1 to V to get a diagonal 9*9 matrix.

但问题是我想要特征值和向量与Matlab相同的顺序，我没有在python中获得。请帮我按照与Matlab相同的顺序获取值。

But the problem is that I want the eigenvalue and vector in the same order as Matlab which I am not getting in the python. Please help me in getting the values in the same order as Matlab.

请参阅下面的链接，了解Matlab和python之间的值差异。
https://drive.google.com/drive/folders/1zjhbKH0q_XXbBziZhfpL1- qS3B5oDuMb

See the link below for the difference in values between Matlab and python. https://drive.google.com/drive/folders/1zjhbKH0q_XXbBziZhfpL1-qS3B5oDuMb

推荐答案

Matlab将按升序将特征值输出到D矩阵的对角元素（即最低特征值）是D（1,1），最大的是D（9,9）。

Matlab will output the eigenvalues to the diagonal elements of the D matrix in ascending order (i.e. lowest eigenvalue is D(1,1) and the largest one is D(9,9)).

Python不遵循这个约定和输出（特征值和特征向量）必须用类似的东西排序;

Python doesn't follow this convention and the outputs (eigenvalues and eigenvectors) must be sorted with something like;

ind = np.argsort(V1);
V1 = V1[ind];
D = D[:,ind];

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