chore: import upstream snapshot with attribution

2026-07-13 13:35:51 +08:00
commit c36a561cd8
2172 changed files with 455595 additions and 0 deletions
@@ -0,0 +1,86 @@
+import dgl
+import numpy as np
+from ged import graph_edit_distance
+
+src1 = [0, 1, 2, 3, 4, 5]
+dst1 = [1, 2, 3, 4, 5, 6]
+
+src2 = [0, 1, 3, 4, 5]
+dst2 = [1, 2, 4, 5, 6]
+
+
+G1 = dgl.DGLGraph((src1, dst1))
+G2 = dgl.DGLGraph((src2, dst2))
+
+
+# Exact edit distance with astar search
+distance, node_mapping, edge_mapping = graph_edit_distance(
+    G1, G1, algorithm="astar"
+)
+print(distance)  # 0.0
+distance, node_mapping, edge_mapping = graph_edit_distance(
+    G1, G2, algorithm="astar"
+)
+print(distance)  # 1.0
+
+# With user-input cost matrices
+node_substitution_cost = np.empty((G1.num_nodes(), G2.num_nodes()))
+G1_node_deletion_cost = np.empty(G1.num_nodes())
+G2_node_insertion_cost = np.empty(G2.num_nodes())
+
+edge_substitution_cost = np.empty((G1.num_edges(), G2.num_edges()))
+G1_edge_deletion_cost = np.empty(G1.num_edges())
+G2_edge_insertion_cost = np.empty(G2.num_edges())
+
+# Node substitution cost of 0 when node-ids are same, else 1
+node_substitution_cost.fill(1.0)
+for i in range(G1.num_nodes()):
+    for j in range(G2.num_nodes()):
+        node_substitution_cost[i, j] = 0.0
+
+# Node insertion/deletion cost of 1
+G1_node_deletion_cost.fill(1.0)
+G2_node_insertion_cost.fill(1.0)
+
+# Edge substitution cost of 0
+edge_substitution_cost.fill(0.0)
+
+# Edge insertion/deletion cost of 0.5
+G1_edge_deletion_cost.fill(0.5)
+G2_edge_insertion_cost.fill(0.5)
+
+distance, node_mapping, edge_mapping = graph_edit_distance(
+    G1,
+    G2,
+    node_substitution_cost,
+    edge_substitution_cost,
+    G1_node_deletion_cost,
+    G2_node_insertion_cost,
+    G1_edge_deletion_cost,
+    G2_edge_insertion_cost,
+    algorithm="astar",
+)
+
+print(distance)  # 0.5
+
+
+# Approximate edit distance with beam search, it is more than or equal to the exact edit distance
+distance, node_mapping, edge_mapping = graph_edit_distance(
+    G1, G2, algorithm="beam", max_beam_size=2
+)
+print(distance)  # 3.0
+
+# Approximate edit distance with bipartite heuristic, it is more than or equal to the exact edit distance
+distance, node_mapping, edge_mapping = graph_edit_distance(
+    G1, G2, algorithm="bipartite"
+)
+print(
+    distance
+)  # 9.0, can be different as multiple solutions possible for the intermediate LAP used in this approximation
+
+
+# Approximate edit distance with hausdorff heuristic, it is less than or equal to the exact edit distance
+distance, node_mapping, edge_mapping = graph_edit_distance(
+    G1, G2, algorithm="hausdorff"
+)
+print(distance)  # 0.0