import random from typing import Any, List from graphgen.bases import BaseGraphStorage, BasePartitioner from graphgen.bases.datatypes import Community NODE_UNIT: str = "n" EDGE_UNIT: str = "e" class DFSPartitioner(BasePartitioner): """ DFS partitioner that partitions the graph into communities of a fixed size. 1. Randomly choose a unit. 2. Random walk using DFS until the community reaches the max unit size. (In GraphGen, a unit is defined as a node or an edge.) """ async def partition( self, g: BaseGraphStorage, max_units_per_community: int = 1, **kwargs: Any, ) -> List[Community]: nodes = g.get_all_nodes() edges = g.get_all_edges() adj, _ = self._build_adjacency_list(nodes, edges) used_n: set[str] = set() used_e: set[frozenset[str]] = set() communities: List[Community] = [] units = [(NODE_UNIT, n[0]) for n in nodes] + [ (EDGE_UNIT, frozenset((u, v))) for u, v, _ in edges ] random.shuffle(units) for kind, seed in units: if (kind == NODE_UNIT and seed in used_n) or ( kind == EDGE_UNIT and seed in used_e ): continue comm_n, comm_e = [], [] stack = [(kind, seed)] cnt = 0 while stack and cnt < max_units_per_community: k, it = stack.pop() if k == NODE_UNIT: if it in used_n: continue used_n.add(it) comm_n.append(it) cnt += 1 for nei in adj[it]: e_key = frozenset((it, nei)) if e_key not in used_e: stack.append((EDGE_UNIT, e_key)) break else: if it in used_e: continue used_e.add(it) comm_e.append(tuple(it)) cnt += 1 # push neighboring nodes for n in it: if n not in used_n: stack.append((NODE_UNIT, n)) if comm_n or comm_e: communities.append( Community(id=len(communities), nodes=comm_n, edges=comm_e) ) return communities