习题6.6

import numpy as np  matches = np.array([  [0, 1, 0, 1, 1, 1],  # 1队  [0, 0, 0, 1, 1, 1],  # 2队  [1, 1, 0, 1, 0, 0],  # 3队  [0, 0, 0, 0, 1, 1],  # 4队  [0, 0, 1, 0, 0, 1],  # 5队  [0, 0, 1, 0, 0, 0]   # 6队  
], dtype=int)  n = matches.shape[0]  
closure = matches.copy()  
for k in range(n):  for i in range(n):  for j in range(n):  closure[i, j] = closure[i, j] or (closure[i, k] and closure[k, j])  strength = closure.sum(axis=1)  ranking = np.argsort(-strength) for i, rank in enumerate(ranking):  print(f"{chr(65 + rank)}队 排名 {i + 1}")import numpy as np  
from scipy.sparse import csr_matrix  edges = [  (0, 1), (0, 3), (0, 4), (0, 5),  # 1队胜  (1, 3), (1, 4), (1, 5),          # 2队胜  (2, 0), (2, 1), (2, 3),          # 3队胜  (3, 4), (3, 5),                  # 4队胜  (4, 2), (4, 5),                  # 5队胜  (5, 2)                           # 6队胜  
]  num_teams = 6  row_ind = []  
col_ind = []  
data = []  
for u, v in edges:  row_ind.append(u)  col_ind.append(v)  data.append(1)  
adj_matrix = csr_matrix((data, (row_ind, col_ind)), shape=(num_teams, num_teams))  adj_matrix_T = adj_matrix.T  d = 0.85  
out_degree = np.array(adj_matrix_T.sum(axis=1)).flatten()  
out_degree[out_degree == 0] = 1  
M = adj_matrix_T.multiply(1.0 / out_degree).tocsr()  
M = M + (1 - d) / num_teams * csr_matrix(np.ones((num_teams, num_teams)))  R = np.ones(num_teams) / num_teams  num_iterations = 100  
for _ in range(num_iterations):  R = R.dot(M.toarray())  pagerank_ranking = np.argsort(-R) for i, rank in enumerate(pagerank_ranking):  print(f"{chr(65 + rank)}队 PageRank排名 {i + 1}")print("学号：3008")

结果如下图所示