(self)
| 639 | ) |
| 640 | |
| 641 | def process(self): |
| 642 | if self.seed is not None: |
| 643 | np.random.seed(self.seed) |
| 644 | |
| 645 | g = nx.balanced_tree(r=2, h=self.tree_height) |
| 646 | edges = list(g.edges()) |
| 647 | src, dst = map(list, zip(*edges)) |
| 648 | n = nx.number_of_nodes(g) |
| 649 | |
| 650 | # Nodes in the base tree graph belong to class 0 |
| 651 | node_labels = [0] * n |
| 652 | # The motifs will be evenly attached to the nodes in the base graph. |
| 653 | spacing = math.floor(n / self.num_motifs) |
| 654 | |
| 655 | # Construct an n-by-n grid |
| 656 | motif_g = nx.grid_graph([self.grid_size, self.grid_size]) |
| 657 | grid_size = nx.number_of_nodes(motif_g) |
| 658 | motif_g = nx.convert_node_labels_to_integers(motif_g, first_label=0) |
| 659 | motif_edges = list(motif_g.edges()) |
| 660 | motif_src, motif_dst = map(list, zip(*motif_edges)) |
| 661 | motif_src, motif_dst = np.array(motif_src), np.array(motif_dst) |
| 662 | |
| 663 | for motif_id in range(self.num_motifs): |
| 664 | src.extend((motif_src + n).tolist()) |
| 665 | dst.extend((motif_dst + n).tolist()) |
| 666 | |
| 667 | # Nodes in grids belong to class 1 |
| 668 | node_labels.extend([1] * grid_size) |
| 669 | |
| 670 | # Attach the motif to the base tree graph |
| 671 | src.append(n) |
| 672 | dst.append(int(motif_id * spacing)) |
| 673 | |
| 674 | n += grid_size |
| 675 | |
| 676 | g = graph((src, dst), num_nodes=n) |
| 677 | |
| 678 | # Perturb the graph by adding non-self-loop random edges |
| 679 | num_real_edges = g.num_edges() |
| 680 | max_ratio = (n * (n - 1) - num_real_edges) / num_real_edges |
| 681 | assert ( |
| 682 | self.perturb_ratio <= max_ratio |
| 683 | ), "perturb_ratio cannot exceed {:.4f}".format(max_ratio) |
| 684 | num_random_edges = int(num_real_edges * self.perturb_ratio) |
| 685 | |
| 686 | for _ in range(num_random_edges): |
| 687 | while True: |
| 688 | u = np.random.randint(0, n) |
| 689 | v = np.random.randint(0, n) |
| 690 | if (not g.has_edges_between(u, v)) and (u != v): |
| 691 | break |
| 692 | g.add_edges(u, v) |
| 693 | |
| 694 | g.ndata["label"] = F.tensor(node_labels, F.int64) |
| 695 | g.ndata["feat"] = F.ones((n, 1), F.float32, F.cpu()) |
| 696 | self._graph = reorder_graph( |
| 697 | g, |
| 698 | node_permute_algo="rcmk", |
nothing calls this directly
no test coverage detected