图02--[图边删除&&图顶点删除&&图遍历BFS&&DFS]

1.图顶点和边删除

1.1删除边

@Override
    public void removeEdge(V from, V to) {
        Vertex<V, E> fromVertex = vertices.get(from);
        if (fromVertex == null) return;
        
        Vertex<V, E> toVertex = vertices.get(to);
        if (toVertex == null) return;
        
        Edge<V, E> edge = new Edge<>(fromVertex, toVertex);
        if (fromVertex.outEdges.remove(edge)) {
            toVertex.inEdges.remove(edge);
            edges.remove(edge);
        }
    }

1.2删除点

@Override
    public void removeVertex(V v) {
        Vertex<V, E> vertex = vertices.remove(v);
        if (vertex == null) return;

        for (Iterator<Edge<V, E>> iterator = vertex.outEdges.iterator(); iterator.hasNext();) {
            Edge<V, E> edge = iterator.next();
            edge.to.inEdges.remove(edge);
            // 将当前遍历到的元素edge从集合vertex.outEdges中删掉
            iterator.remove(); 
            edges.remove(edge);
        }

        for (Iterator<Edge<V, E>> iterator = vertex.inEdges.iterator(); iterator.hasNext();) {
            Edge<V, E> edge = iterator.next();
            edge.from.outEdges.remove(edge);
            // 将当前遍历到的元素edge从集合vertex.inEdges中删掉
            iterator.remove(); 
            edges.remove(edge);
        }
    }

2.图的遍历

2.1常见方式

 2.2广度优先搜索(Breadth First Search)

 

 2.3广度优先搜索--思路

 2.4广度优先搜索-实现

@Override
    public void bfs(V begin, VertexVisitor<V> visitor) {
        if (visitor == null) return;
        Vertex<V, E> beginVertex = vertices.get(begin);
        if (beginVertex == null) return;
        
        Set<Vertex<V, E>> visitedVertices = new HashSet<>();
        Queue<Vertex<V, E>> queue = new LinkedList<>();
        queue.offer(beginVertex);
        visitedVertices.add(beginVertex);
        
        while (!queue.isEmpty()) {
            Vertex<V, E> vertex = queue.poll();
            if (visitor.visit(vertex.value)) return;
            
            for (Edge<V, E> edge : vertex.outEdges) {
                if (visitedVertices.contains(edge.to)) continue;
                queue.offer(edge.to);
                visitedVertices.add(edge.to);
            }
        }
    }

2.5深度优先搜索(Depth First Search)

 

 2.6深度优先递归实现

@Override
    public void dfs(V begin, VertexVisitor<V> visitor) {
        if (visitor == null) return;
        Vertex<V, E> beginVertex = vertices.get(begin);
        if (beginVertex == null) return;

        Set<Vertex<V, E>> visitedVertices = new HashSet<>();
        Stack<Vertex<V, E>> stack = new Stack<>();
        
        // 先访问起点
        stack.push(beginVertex);
        visitedVertices.add(beginVertex);
        if (visitor.visit(begin)) return;
        
        while (!stack.isEmpty()) {
            Vertex<V, E> vertex = stack.pop();
            
            for (Edge<V, E> edge : vertex.outEdges) {
                if (visitedVertices.contains(edge.to)) continue;
                
                stack.push(edge.from);
                stack.push(edge.to);
                visitedVertices.add(edge.to);
                if (visitor.visit(edge.to.value)) return;
                
                break;
            }
        }
    }

 2.7 深度优先搜索--非递归版本

@Override
    public void dfs(V begin, VertexVisitor<V> visitor) {
        if (visitor == null) return;
        Vertex<V, E> beginVertex = vertices.get(begin);
        if (beginVertex == null) return;

        Set<Vertex<V, E>> visitedVertices = new HashSet<>();
        Stack<Vertex<V, E>> stack = new Stack<>();
        
        // 先访问起点
        stack.push(beginVertex);
        visitedVertices.add(beginVertex);
        if (visitor.visit(begin)) return;
        
        while (!stack.isEmpty()) {
            Vertex<V, E> vertex = stack.pop();
            
            for (Edge<V, E> edge : vertex.outEdges) {
                if (visitedVertices.contains(edge.to)) continue;
                
                stack.push(edge.from);
                stack.push(edge.to);
                visitedVertices.add(edge.to);
                if (visitor.visit(edge.to.value)) return;
                
                break;
            }
        }
    }