以每行为基础的矩阵中的组合

import numpy as np

# 示例矩阵
matrix = np.array([
    [1, 2, 3],
    [4, 5],
    [6, 7, 8, 9]
])

# 统一维度
max_length = max(len(row) for row in matrix)
padded_matrix = np.array([row + [0] * (max_length - len(row)) for row in matrix])

# 进行组合
combined = padded_matrix.sum(axis=0)
print(combined)

import numpy as np

# 示例矩阵
matrix = np.array([
    [1, 2, 3],
    [1, 2, 3],
    [4, 5, 6]
])

# 去重
unique_combinations = np.unique(matrix, axis=0)
print(unique_combinations)

import numpy as np

# 示例大规模矩阵
matrix = np.random.rand(10000, 100)

# 使用高效的组合方法
combined = np.apply_along_axis(lambda x: x.sum(), axis=0, arr=matrix)
print(combined)