• 用矩阵乘法的形式增加行向量
  $$\begin{array}{c}A=\left[\begin{array}{ccc}1& 2& 3\\ & & \\ 4& 5& 6\\ & & \\ 7& 8& 9\end{array}\right];v=\left[\begin{array}{ccc}888& 444& 666\end{array}\right]\to E=\left[\begin{array}{ccc}1& 2& 3\\ & & \\ 4& 5& 6\\ & & \\ 7& 8& 9\\ & & \\ 888& 444& 666\end{array}\right];\end{array}$$
• 代码：

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# @FileName  :MatrixAdd.py
# @Time      :2024/10/31 20:07
# @Author    :Jason Zhang
import numpy as np

np.set_printoptions(suppress=True, precision=3)


class MatrixAddVector(object):
    def __init__(self, in_matrix, in_vector):
        self.in_matrix = in_matrix
        self.row, self.column = np.shape(self.in_matrix)
        self.in_vector = in_vector
        self.result = np.zeros((self.row + 1, self.column))

    def add_vector(self):
        my_vector = self.in_vector
        my_matrix = self.in_matrix
        my_row_1 = self.row + 1
        my_column = self.column
        left_ones = np.ones(my_row_1)
        left_ones_diag = np.diag(left_ones)
        left_matrix = left_ones_diag[:, :-1]
        left_matrix_1 = left_matrix @ self.in_matrix
        zeros_vector = np.zeros(my_row_1)
        zeros_vector[-1] = 1
        add_matrix = np.outer(zeros_vector, self.in_vector)
        result = add_matrix + left_matrix_1
        print(f"matrix=\n{self.in_matrix}")
        print(f"vector={self.in_vector}")
        print(f"result=\n{result}")


if __name__ == "__main__":
    run_code = 0
    new_matrix = np.arange(9).reshape(3, 3)+1
    new_vector = np.array([888, 444, 666])
    new_test = MatrixAddVector(new_matrix, new_vector)
    new_test.add_vector()

• 结果：

matrix=
[[1 2 3]
 [4 5 6]
 [7 8 9]]
vector=[888 444 666]
result=
[[  1.   2.   3.]
 [  4.   5.   6.]
 [  7.   8.   9.]
 [888. 444. 666.]]