在没有NumPy的Python语言中计算矩阵的(摩尔-彭罗斯)伪逆

import math
import itertools

def pseudoinverse(matrix):
    # Step 1: Singular Value Decomposition (SVD)
    U, S, V = svd(matrix)
    
    # Step 2: Construct the diagonal matrix S+
    S_plus = [[1/s if s != 0 else 0 for s in row] for row in S]
    
    # Step 3: Calculate the pseudoinverse
    P = matrix_multiply(matrix_multiply(V, S_plus), transpose(U))
    
    return P

# Helper function: Singular Value Decomposition (SVD)
def svd(matrix):
    # Implementation of SVD (omitted for simplicity)
    pass

# Helper function: Matrix multiplication
def matrix_multiply(matrix1, matrix2):
    # Implementation of matrix multiplication (omitted for simplicity)
    pass

# Helper function: Transpose of a matrix
def transpose(matrix):
    # Implementation of matrix transpose (omitted for simplicity)
    pass

# Example usage
matrix = [[1, 2, 3], [4, 5, 6]]
pseudoinverse_matrix = pseudoinverse(matrix)
print(pseudoinverse_matrix)