将非对称矩阵转换为方阵

import numpy as np

# 假设有一个非对称矩阵
non_symmetric_matrix = np.array([[1, 2, 3], [4, 5, 6]])

# 获取矩阵的形状
rows, cols = non_symmetric_matrix.shape

# 计算需要填充的大小
max_dim = max(rows, cols)

# 创建一个新的方阵，并用零填充
square_matrix = np.zeros((max_dim, max_dim))
square_matrix[:rows, :cols] = non_symmetric_matrix

print(square_matrix)

import numpy as np

# 假设有一个非对称矩阵
non_symmetric_matrix = np.array([[1, 2, 3], [4, 5, 6]])

# 获取矩阵的形状
rows, cols = non_symmetric_matrix.shape

# 计算需要填充的大小
max_dim = max(rows, cols)

# 创建一个新的方阵，并用镜像填充
square_matrix = np.zeros((max_dim, max_dim))
square_matrix[:rows, :cols] = non_symmetric_matrix

# 镜像填充
for i in range(max_dim - rows):
    square_matrix[rows + i, :cols] = non_symmetric_matrix[i % rows, :]
for j in range(max_dim - cols):
    square_matrix[:, cols + j] = square_matrix[:, j % cols]

print(square_matrix)

import numpy as np

# 假设有一个非对称矩阵
non_symmetric_matrix = np.array([[1, 2, 3], [4, 5, 6]])

# 获取矩阵的形状
rows, cols = non_symmetric_matrix.shape

# 计算需要填充的大小
max_dim = max(rows, cols)

# 创建一个新的方阵，并用重构填充
square_matrix = np.zeros((max_dim, max_dim))
square_matrix[:rows, :cols] = non_symmetric_matrix

# 重构矩阵的示例：重复元素
for i in range(max_dim):
    for j in range(max_dim):
        if i >= rows or j >= cols:
            square_matrix[i, j] = non_symmetric_matrix[i % rows, j % cols]

print(square_matrix)