2022腾讯犀牛鸟开源培训计划—张宇飞

def create_context_graph(self, max_num_layers, workers=1, verbose=0,): pair_distances = self._compute_structural_distance( max_num_layers, workers, verbose,) layers_adj, layers_distances = self._get_layer_rep(pair_distances) pd.to_pickle(layers_adj, self.temp_path + 'layers_adj.pkl')

layers_accept, layers_alias = self._get_transition_probs( layers_adj, layers_distances) pd.to_pickle(layers_alias, self.temp_path + 'layers_alias.pkl') pd.to_pickle(layers_accept, self.temp_path + 'layers_accept.pkl')

def prepare_biased_walk(self,): sum_weights = {} sum_edges = {} average_weight = {} gamma = {} layer = 0 while (os.path.exists(self.temp_path+'norm_weights_distance-layer-' + str(layer)+'.pkl')): probs = pd.read_pickle( self.temp_path+'norm_weights_distance-layer-' + str(layer)+'.pkl') for v, list_weights in probs.items(): sum_weights.setdefault(layer, 0) sum_edges.setdefault(layer, 0) sum_weights[layer] +=