废话不多说，直接上代码！
一、导入邻接矩阵

import xlrd
import sys

def matrix(address):                           #读取excel生成邻接矩阵
    wb = xlrd.open_workbook(address)
    sheet1 = wb.sheet_by_name('邻接矩阵_距离')
    L = []
    for i in range(1,13):
        a = sheet1.row_values(i)
        a.remove(a[0])
        L.append([int(x) for x in a])
    # print(L)
    return L

二、实现Floyd算法

from pylab import *
import matrix


def floyd(d):
    D=d
    lengthD = len(D)                    #邻接矩阵大小
    p = list(range(lengthD))
    P = []
    for i in range(lengthD):
        P.append(p)
    P = array(P)
    for k in range(lengthD):
        for i in range(lengthD):
            for j in range(lengthD):
                if(D[i][j] >D[i][k]+D[j][k]):         #两个顶点直接较小的间接路径替换较大的直接路径
                    P[i][j] = P[i][k]                 #记录新路径的前驱
                    D[i][j] = D[i][k]+D[j][k]
    print('各个顶点的最短路径:')
    for i in range(lengthD):
        for j in range(i+1,lengthD):
            print('v%d' % (i+1) + '--' + 'v%d' % (j+1) + '\t' + 'dist_min:' + '\t' + str(D[i][j]) + '\t' + 'path:'+'v%d'%(i+1),end='' )
            temp=P[i][j]
            while (temp!=j):
                print('--'+'v%d'%(temp+1),end='')
                temp=P[temp][j]
            print('--'+'v%d'%(j+1))
    print('P矩阵:')
    print(P)
    print('D矩阵:')
    for i in D:
        print(i)
    return D


if __name__ == '__main__':
    chararray = ['A','B','C','D','E','F','G','H','I','J','K','L']
    L=[]
    for i in range(1,len(chararray)+1):
        L.append('v%d'%i)
    Dict=dict(zip(L,chararray))
    print('各点对应关系：')
    print(Dict)
    address = 'E:/py/math_b/b题数据和代码/b题基础数据.xlsx'
    data=matrix.matrix(address)
    d=matrix.tran_m(data)
    floyd(d)

三、仿真结果