4.7. 图算法范例

提示

范例源代码下载地址： PathFindingExamplesTest.java

计算正连个节点之间的最短路径（最少数目的关系）：

Node startNode = graphDb.createNode();
Node middleNode1 = graphDb.createNode();
Node middleNode2 = graphDb.createNode();
Node middleNode3 = graphDb.createNode();
Node endNode = graphDb.createNode();
createRelationshipsBetween( startNode, middleNode1, endNode );
createRelationshipsBetween( startNode, middleNode2, middleNode3, endNode );

// Will find the shortest path between startNode and endNode via
// "MY_TYPE" relationships (in OUTGOING direction), like f.ex:
//
// (startNode)-->(middleNode1)-->(endNode)
//
PathFinder<Path> finder = GraphAlgoFactory.shortestPath(
    Traversal.expanderForTypes( ExampleTypes.MY_TYPE, Direction.OUTGOING ), 15 );
Iterable<Path> paths = finder.findAllPaths( startNode, endNode );

使用 迪科斯彻（Dijkstra） 算法解决有向图中任意两个顶点之间的最短路径问题。

PathFinder<WeightedPath> finder = GraphAlgoFactory.dijkstra(
Traversal.expanderForTypes( ExampleTypes.MY_TYPE, Direction.BOTH ), "cost" );

WeightedPath path = finder.findSinglePath( nodeA, nodeB );

// Get the weight for the found path
path.weight();

使用 A* 算法是解决静态路网中求解最短路最有效的方法。

这儿是我们的范例图：