| from collections import defaultdict |
| from data.graph import Graph |
| import numpy as np |
| import scipy.sparse as sp |
|
|
|
|
| class Relation(Graph): |
| def __init__(self, conf, relation, user): |
| super().__init__() |
| self.config = conf |
| self.social_user = {} |
| self.relation = relation |
| self.followees = defaultdict(dict) |
| self.followers = defaultdict(dict) |
| self.user = user |
| self.__initialize() |
|
|
| def __initialize(self): |
| idx = [] |
| for n, pair in enumerate(self.relation): |
| if pair[0] not in self.user or pair[1] not in self.user: |
| idx.append(n) |
| for item in reversed(idx): |
| del self.relation[item] |
| for line in self.relation: |
| user1, user2, weight = line |
| |
| self.followees[user1][user2] = weight |
| self.followers[user2][user1] = weight |
|
|
| def get_social_mat(self): |
| row, col, entries = [], [], [] |
| for pair in self.relation: |
| row += [self.user[pair[0]]] |
| col += [self.user[pair[1]]] |
| entries += [1.0] |
| social_mat = sp.csr_matrix((entries, (row, col)), shape=(len(self.user), len(self.user)), dtype=np.float32) |
| return social_mat |
|
|
| def get_birectional_social_mat(self): |
| social_mat = self.get_social_mat() |
| bi_social_mat = social_mat.multiply(social_mat) |
| return bi_social_mat |
|
|
| def convert_to_laplacian_mat(self, adj_mat): |
| adj_shape = adj_mat.get_shape() |
| (row_np_keep, col_np_keep) = adj_mat.nonzero() |
| ratings_keep = adj_mat.data |
| tmp_adj = sp.csr_matrix((ratings_keep, (row_np_keep, col_np_keep)), shape=adj_shape, dtype=np.float32) |
| return self.normalize_graph_mat(tmp_adj) |
|
|
| def weight(self, u1, u2): |
| if u1 in self.followees and u2 in self.followees[u1]: |
| return self.followees[u1][u2] |
| else: |
| return 0 |
|
|
| def get_followers(self, u): |
| if u in self.followers: |
| return self.followers[u] |
| else: |
| return {} |
|
|
| def get_followees(self, u): |
| if u in self.followees: |
| return self.followees[u] |
| else: |
| return {} |
|
|
| def has_followee(self, u1, u2): |
| if u1 in self.followees: |
| if u2 in self.followees[u1]: |
| return True |
| else: |
| return False |
| return False |
|
|
| def has_follower(self, u1, u2): |
| if u1 in self.followers: |
| if u2 in self.followers[u1]: |
| return True |
| else: |
| return False |
| return False |
|
|
| def size(self): |
| return len(self.followers), len(self.relation) |
|
|
