def process()

in seal_link_pred.py [0:0]

• 29 lines of code
• 6 McCabe index (conditional complexity)

    def process(self):
        pos_edge, neg_edge = get_pos_neg_edges(self.split, self.split_edge, 
                                               self.data.edge_index, 
                                               self.data.num_nodes, 
                                               self.percent)

        if self.use_coalesce:  # compress mutli-edge into edge with weight
            self.data.edge_index, self.data.edge_weight = coalesce(
                self.data.edge_index, self.data.edge_weight, 
                self.data.num_nodes, self.data.num_nodes)

        if 'edge_weight' in self.data:
            edge_weight = self.data.edge_weight.view(-1)
        else:
            edge_weight = torch.ones(self.data.edge_index.size(1), dtype=int)
        A = ssp.csr_matrix(
            (edge_weight, (self.data.edge_index[0], self.data.edge_index[1])), 
            shape=(self.data.num_nodes, self.data.num_nodes)
        )

        if self.directed:
            A_csc = A.tocsc()
        else:
            A_csc = None
        
        # Extract enclosing subgraphs for pos and neg edges
        pos_list = extract_enclosing_subgraphs(
            pos_edge, A, self.data.x, 1, self.num_hops, self.node_label, 
            self.ratio_per_hop, self.max_nodes_per_hop, self.directed, A_csc)
        neg_list = extract_enclosing_subgraphs(
            neg_edge, A, self.data.x, 0, self.num_hops, self.node_label, 
            self.ratio_per_hop, self.max_nodes_per_hop, self.directed, A_csc)

        torch.save(self.collate(pos_list + neg_list), self.processed_paths[0])
        del pos_list, neg_list