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Javascriptの完全グラフクラス


このコードでコメント化されている関数。それらに切り替えることもできます。また、importステートメントまたはrequire呼び出しを使用してインポートできる、さまざまなモジュールのQueue、Stack、およびPriorityQueueクラスを移動しました。これがGraphクラスの完全な実装です-

const Queue = require("./Queue");
const Stack = require("./Stack");
const PriorityQueue = require("./PriorityQueue");

class Graph {
   constructor() {
      this.edges = {};
      this.nodes = [];
   }

   addNode(node) {
      this.nodes.push(node);
      this.edges[node] = [];
   }

   addEdge(node1, node2, weight = 1) {
      this.edges[node1].push({ node: node2, weight: weight });
      this.edges[node2].push({ node: node1, weight: weight });
   }

   addDirectedEdge(node1, node2, weight = 1) {
      this.edges[node1].push({ node: node2, weight: weight });
   }

   // addEdge(node1, node2) {
      // this.edges[node1].push(node2);
      // this.edges[node2].push(node1);
   // }

   // addDirectedEdge(node1, node2) {
      // this.edges[node1].push(node2);
   // }

   display() {
      let graph = "";
      this.nodes.forEach(node => {
         graph += node + "->" + this.edges[node].map(n => n.node).join(", ") + "\n";
      });
      console.log(graph);
   }

   BFS(node) {
      let q = new Queue(this.nodes.length);
      let explored = new Set();
      q.enqueue(node);
      explored.add(node);
      while (!q.isEmpty()) {
         let t = q.dequeue();
         console.log(t);
         this.edges[t].filter(n => !explored.has(n)).forEach(n => {
            explored.add(n);
            q.enqueue(n);
         });
      }
   }

   DFS(node) {
      // Create a Stack and add our initial node in it
      let s = new Stack(this.nodes.length);
      let explored = new Set();
      s.push(node);

      // Mark the first node as explored
      explored.add(node);

      // We'll continue till our Stack gets empty
      while (!s.isEmpty()) {
         let t = s.pop();

         // Log every element that comes out of the Stack
         console.log(t);

         // 1. In the edges object, we search for nodes this node is
         // directly connected to.
         // 2. We filter out the nodes that have already been explored.
         // 3. Then we mark each unexplored node as explored and push it
         // to the Stack.
         this.edges[t].filter(n => !explored.has(n)).forEach(n => {
            explored.add(n);
            s.push(n);
         });
      }
   }

   topologicalSortHelper(node, explored, s) {
      explored.add(node);
      this.edges[node].forEach(n => {
         if (!explored.has(n)) {
            this.topologicalSortHelper(n, explored, s);
         }
      });
      s.push(node);
   }

   topologicalSort() {
      // Create a Stack and add our initial node in it
      let s = new Stack(this.nodes.length);
      let explored = new Set();
      this.nodes.forEach(node => {
         if (!explored.has(node)) {
            this.topologicalSortHelper(node, explored, s);
         }
      });
      while (!s.isEmpty()) {
         console.log(s.pop());
      }
   }

   BFSShortestPath(n1, n2) {
      let q = new Queue(this.nodes.length);
      let explored = new Set();
      let distances = { n1: 0 };

      q.enqueue(n1);
      explored.add(n1);

      while (!q.isEmpty()) {
         let t = q.dequeue();
         this.edges[t].filter(n => !explored.has(n)).forEach(n => {
            explored.add(n);
            distances[n] = distances[t] == undefined ? 1 : distances[t] + 1;
            q.enqueue(n);
         });
      }
      return distances[n2];
   }

   primsMST() {
      // Initialize graph that'll contain the MST
      const MST = new Graph();
      if (this.nodes.length === 0) {
         return MST;
      }

      // Select first node as starting node
      let s = this.nodes[0];

      // Create a Priority Queue and explored set
      let edgeQueue = new PriorityQueue(this.nodes.length * this.nodes.length);
      let explored = new Set();

      explored.add(s);
      MST.addNode(s);

      // Add all edges from this starting node to the PQ taking weights as priority
      this.edges[s].forEach(edge => {
         edgeQueue.enqueue([s, edge.node], edge.weight);
      });

      // Take the smallest edge and add that to the new graph
      let currentMinEdge = edgeQueue.dequeue();
      while (!edgeQueue.isEmpty()) {
         // COntinue removing edges till we get an edge with an unexplored node
         while (!edgeQueue.isEmpty() && explored.has(currentMinEdge.data[1])) {
            currentMinEdge = edgeQueue.dequeue();
         }
         let nextNode = currentMinEdge.data[1];

         // Check again as queue might get empty without giving back unexplored element
         if (!explored.has(nextNode)) {
            MST.addNode(nextNode);
            MST.addEdge(currentMinEdge.data[0], nextNode, currentMinEdge.priority);
            // Again add all edges to the PQ
            this.edges[nextNode].forEach(edge => {
               edgeQueue.enqueue([nextNode, edge.node], edge.weight);
            });

            // Mark this node as explored explored.add(nextNode);
            s = nextNode;
         }
      }
      return MST;
   }

   kruskalsMST() {
      // Initialize graph that'll contain the MST
      const MST = new Graph();
      this.nodes.forEach(node => MST.addNode(node));
      if (this.nodes.length === 0) {
         return MST;
      }

      // Create a Priority Queue
      let edgeQueue = new PriorityQueue(this.nodes.length * this.nodes.length);

      // Add all edges to the Queue:
      for (let node in this.edges) {
         this.edges[node].forEach(edge => {
            edgeQueue.enqueue([node, edge.node], edge.weight);
         });
      }

      let uf = new UnionFind(this.nodes);
      // Loop until either we explore all nodes or queue is empty
      while (!edgeQueue.isEmpty()) {
         // Get the edge data using destructuring
         let nextEdge = edgeQueue.dequeue();
         let nodes = nextEdge.data;
         let weight = nextEdge.priority;
         if (!uf.connected(nodes[0], nodes[1])) {
            MST.addEdge(nodes[0], nodes[1], weight);
            uf.union(nodes[0], nodes[1]);
         }
      }
      return MST;
   }

   djikstraAlgorithm(startNode) {
      let distances = {};
      // Stores the reference to previous nodes
      let prev = {};
      let pq = new PriorityQueue(this.nodes.length * this.nodes.length);

      // Set distances to all nodes to be infinite except startNode
      distances[startNode] = 0;
      pq.enqueue(startNode, 0);
      this.nodes.forEach(node => {
         if (node !== startNode) distances[node] = Infinity;
         prev[node] = null;
      });

      while (!pq.isEmpty()) {
         let minNode = pq.dequeue();
         let currNode = minNode.data;
         let weight = minNode.priority;

         this.edges[currNode].forEach(neighbor => {
            let alt = distances[currNode] + neighbor.weight;
            if (alt < distances[neighbor.node]) {
               distances[neighbor.node] = alt;
               prev[neighbor.node] = currNode;
               pq.enqueue(neighbor.node, distances[neighbor.node]);
            }
         });
      }
      return distances;
   }

   floydWarshallAlgorithm() {
      let dist = {};
      for (let i = 0; i < this.nodes.length; i++) {
         dist[this.nodes[i]] = {};
         // For existing edges assign the dist to be same as weight
         this.edges[this.nodes[i]].forEach(
            e => (dist[this.nodes[i]][e.node] = e.weight)
         );

         this.nodes.forEach(n => {
            // For all other nodes assign it to infinity
            if (dist[this.nodes[i]][n] == undefined)
            dist[this.nodes[i]][n] = Infinity;
            // For self edge assign dist to be 0
            if (this.nodes[i] === n) dist[this.nodes[i]][n] = 0;
         });
      }

      this.nodes.forEach(i => {
         this.nodes.forEach(j => {
            this.nodes.forEach(k => {
               // Check if going from i to k then from k to j is better
               // than directly going from i to j. If yes then update
               // i to j value to the new value
               if (dist[i][k] + dist[k][j] < dist[i][j])
                  dist[i][j] = dist[i][k] + dist[k][j];
            });
         });
      });
      return dist;
   }
}

class UnionFind {
   constructor(elements) {
      // Number of disconnected components
      this.count = elements.length;

      // Keep Track of connected components
      this.parent = {};

      // Initialize the data structure such that all
      // elements have themselves as parents
      elements.forEach(e => (this.parent[e] = e));
   }

   union(a, b) {
      let rootA = this.find(a);
      let rootB = this.find(b);

      // Roots are same so these are already connected.
      if (rootA === rootB) return;

      // Always make the element with smaller root the parent.
      if (rootA < rootB) {
         if (this.parent[b] != b) this.union(this.parent[b], a);
         this.parent[b] = this.parent[a];
      } else {
         if (this.parent[a] != a) this.union(this.parent[a], b);
         this.parent[a] = this.parent[b];
      }
   }

   // Returns final parent of a node
   find(a) {
      while (this.parent[a] !== a) {
         a = this.parent[a];
      }
      return a;
   }

   // Checks connectivity of the 2 nodes
   connected(a, b) {
      return this.find(a) === this.find(b);
   }
}

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