用动态规划实现矩阵连乘问题的代码

动态规划是解决矩阵连乘问题的常用方法。下面是一个用动态规划实现矩阵连乘问题的代码示例：

def matrix_chain_order(p):
    n = len(p) - 1
    m = [[0] * (n+1) for _ in range(n+1)]
    s = [[0] * (n+1) for _ in range(n+1)]

    for l in range(2, n+1):
        for i in range(1, n-l+2):
            j = i + l - 1
            m[i][j] = float('inf')
            for k in range(i, j):
                q = m[i][k] + m[k+1][j] + p[i-1]*p[k]*p[j]
                if q < m[i][j]:
                    m[i][j] = q
                    s[i][j] = k

    return m, s

def print_optimal_parens(s, i, j):
    if i == j:
        print("A" + str(i), end="")
    else:
        print("(", end="")
        print_optimal_parens(s, i, s[i][j])
        print_optimal_parens(s, s[i][j]+1, j)
        print(")", end="")

# 示例用法
p = [30, 35, 15, 5, 10, 20, 25]
m, s = matrix_chain_order(p)
print_optimal_parens(s, 1, len(p)-1)

这段代码中，`matrix_chain_order`函数用于计算最优的矩阵连乘顺序，并返回最优值矩阵`m`和最优断点矩阵`s`。`print_optimal_parens`函数用于打印最优的矩阵连乘顺序。