基本数据结构和查找算法

本文包括简单的数据结构和查找算法，属于个人整理。
初学编程可以用这里的东西联系一下，看一看也挺有意思
博主个人不认为js中算法数据结构不重要，毕竟这是程序开发的基本功。
本文还会根据博主学习进展和时间安排不定期更新

数据结构部分

列表

function List(){
  this.listSize = 0;
  this.pos = 0;
  this.dataStore = [];

  //查找
  this.find = function(element){
    return dataStore.indexOf(element);
  };

  //追加元素
  this.append = function(element){
    this.dataStore[this.listSize++] = element;
  };

  //删除元素
  this.remove = function(element){
    var foundAt = this.find(element);
    if(foundAt > -1){
      this.dataStore.splice(foundAt, 1);
      --this.listSize;
      return true;
    }
    return false;
  };

  //得到长度
  this.getLength = function(){
    return this.listSize;
  };

  //插入元素
  this.insert = function(element, after){
    var insertPos = this.find(after);
    if(insertPos > -1){
      this.dataStore.splice(insertPos+1, 0, element);
      ++this.listSize;
      return true;
    }
    return false;
  };

  //清空列表
  this.clear = function(){
    delete this.dataStore;
    this.dataStore.length = 0;
    this.listSize = this.pos = 0;
  };

  //判断是否包含某元素
  this.contains = function(element){
    return this.find(element) !== -1;
  };

  //转换为字符串
  this.toString = function(){
    return this.dataStore.join(",");
  };

  //把指针移到最前
  this.front = function(){
    this.pos = 0;
  };

  //把指针移到最后
  this.end = function(){
    this.pos = this.listSize - 1;
  };

  //前移指针
  this.prev = function(){
    if(this.pos > 0)
      --this.pos;
  };

  //后移指针
  this.next = function(){
    if(this.pos < this.listSize - 1)
      ++this.pos;
  };

  //得到指针当前位置
  this.currPos = function(){
    return this.pos;
  };

  //把指针移到posi
  this.moveTo = function(posi){
    if(posi < this.listSize && posi >= 0){
        this.pos = position;
        return true;
    }
    return false;
  };

  //得到当前指针位置元素
  this.getElement = function(){
    return this.dataStore[this.pos];
  };
}

队列

function queue(){
  this.dataStore = [];

  this.enqueue = function(element){    //入队
    this.dataStore.push(element);
  };
  this.dequeue = function(){    //出对
    return this.dataStore.shift();
  };
  this.front(){   //查看队首
    return this.dataStore[0];
  };
  this.back(){   //查看队尾
    return this.dataStore[this.dataStore.length - 1];
  };
  this.empty = function(){   //清空队列
    return this.dataStore.length === 0;
  };
  this.getLength = function(){   //得到队列长度
    return this.dataStore.length;
  };
}

栈

function Stack(){
  this.dataStore = [];

  this.push = function(element){   //入栈
    this.dataStore.push(element);
  };
  this.peek = function(){    //查看栈顶
    if(this.dataStore.length > 0)
      return this.dataStore[this.dataStore.length - 1];
    return undefined;
  };

  this.clear = function(){   //清空
    this.dataStore.length = 0;
  };

  this.pop = function(){    //出栈
    return this.dataStore.pop();
  };

  this.getLength = function(){   //得到长度
    return this.dataStore.length;
  };
}

链表

function Node(element){      //链表节点
  this.element = element;
  this.next = null;
}
function LList(){
  this.head = new Node("head");

  this.find = function(item){   //查找
    var currNode = this.head;
    while(currNode && currNode.element != item){
      currNode = currNode.next;
    };
    return currNode;
  };

  this.insert = function(newElement, item){    //在item之后插入
    var newNode = new Node(newElement);
    var current = this.find(item);
    if(current === null) {
      this.append(newElement);
      return false;
    }
    newNode.next = current.next;
    current.next = newNode;
    return true;
  };

  this.display = function(){   //输出列表
    var currNode = this.head;
    while(currNode.next !== null){
      console.log(currNode.next.element);
      currNode = currNode.next;
    }
  };

  this.remove = function(element){
    var currNode = this.head;
    while(1){
      if(currNode.next === null) return false;
      if(currNode.next.element === element) break;
      currNode = currNode.next;
    }
    currNode.next = currNode.next.next;
  };
}

环形链表

function Node(element){      //链表节点
  this.element = element;
  this.next = null;
}
function LList(){
  this.head = new Node("head");
  this.head.next = this.head;  //成环

  this.find = function(item){  //查找
    var currNode = this.head;
    while(currNode.element != item){
      if(currNode.next === this.head) return null;
      currNode = currNode.next;
    };
    return currNode;
  };

  this.insert = function(newElement, item){   //在item之后插入
    var newNode = new Node(newElement);
    var current = this.find(item);
    newNode.next = current.next;
    current.next = newNode;
  };

  this.display = function(){   //输出列表
    var currNode = this.head;
    while(currNode.next !== this.head){
      console.log(currNode.next.element);
      currNode = currNode.next;
    }
  };

  this.remove = function(element){    //删除
    var currNode = this.head;
    while(1){
      if(currNode.next == this.head) return false;
      if(currNode.next.element == element) break;
      currNode = currNode.next;
    }
    currNode.next = currNode.next.next;
  };
}

双向链表

function Node(element){
  this.element = element;
  this.next = null;
  this.previous = null;
}
function LList(){
  this.head = new Node("head");
  this.tail = this.head;

  this.find = function(item){   //查找
    var currNode = this.head;
    while(currNode.element != item){
      if(currNode.next === null) return null;
      currNode = currNode.next;
    };
    return currNode;
  };

  this.insert = function(newElement, item){   //在item之后插入
    var newNode = new Node(newElement);
    var current = this.find(item);
    newNode.next = current.next;
    current.next = newNode;
    current.next.previous = newNode;
    newNode.previous = current;
  };

  this.display = function(){   //输出列表
    var currNode = this.head;
    while(currNode.next !== null){
      console.log(currNode.next.element);
      currNode = currNode.next;
    }
  };

  this.remove = function(item){   //删除
    var currNode = this.find(item);
    if(currNode){
      currNode.previous.next = currNode.next;
      currNode.next.previous = currNode.previous;
      currNode.next = null;
      currNode.previous = null;
      return true;
    }
    return false;
  };

  this.dispReverse = function(){   //反向输出
    var currNode = this.tail;
    while(currNode.previous !== null){
      console.log(currNode.element);
      currNode = currNode.previous;
    }
  };
}

字典

function dictionary(){
  this.dataStore = [];

  this.add = function(key, value){  //插入
    if(this.find(key)) console.log("'" + key + "' exists");
    else this.dataStore[key] = value;
  };

  this.find = function(key){   //查找
    return this.dataStore[key];
  };

  this.remove = function(key){   //删除
    delete this.dataStore[key];
  };

  this.showAll = function(){   //有序输出
    var keys = Object.keys(this.dataStore).sort();
    keys.forEach(function(key){
      console.log(key + " -> " + this.dataStore[key]);
    });
  };

  this.count = function(){   //计数
    return Object.keys(this.dataStore).length;
  };

  this.clear = function(){   //清除
    for(var k in this.dataStore){
      if(dataStore.hasOwnPorperty(k)){
        delete this.dataStore[k];
      }
    }
  };
}

集合

function Set(){
  if(arr){
    this.arr = arr.filter(function(item, index) {
      return arr.indexOf(item) === index;
    });
  } else {
    this.arr = [];
  }
}
Set.prototype.constructor = Set;

Myset.prototype.sort = function(fun){  //排序
  this.arr.sort(fun);
  return this;
};

Set.prototype.add = function(data){   //添加
  if(this.dataStore.indexOf(data) < 0){
    this.dataStore.push(data);
  }
  return this;
};

Set.prototype.show = function(){  //输出
  console.log(this.dataStore.join(","));
  return this;
};

Set.prototype.remove = function(data){   //删除
  var pos = this.dataStore.indexOf(data);
  if(pos > -1){
    this.dataStore.splice(pos, 1);
  }
  return this;
};

Set.prototype.size = function(){  //得到当前集合大小(元素数量)
  return this.dataStore.length;
};
Set.prototype.contains = function(data) {    //是否包含data
  return this.dataStore.indexOf(data) > -1;
};

Set.prototype.clone = function(){   //复制当前集合
  var tempSet = new Set();
  for(var i = 0; i < this.size(); ++i)
    tempSet.add(this.dataStore[i]);
  return tempSet;
};

Set.prototype.union = function(set){   //求并集
  var tempSet = this.clone();
  for(var i = 0; i < set.size(); ++i){
    if(!tempSet.contains(set.dataStore[i]))
      temp.dataStore.push(set.dataStore[i]);
  }
  return tempSet;
};

Set.prototype.interSect = function(set){   //求交集
  var tempSet = new Set();
  for(var i = 0; i < this.size(); ++i){
    if(set.contains(this.dataStore[i]))
      tempSet.add(this.dataStore[i]);
  }
  return tempSet;
};

Set.prototype.subSet = function(set){    //判断当前集合是否set的子集
  if(this.size() > set.size()) return false;
  else{
    for(var i = 0; i < this.size(); ++i){
      if(!set.contains(this.dataStore[i]))
        return false;
    }
  }
  return true;
};

this.difference = function(set){   //求差集 this-set
  var tempSet = new Set();
  for(var i = 0; i < this.dataStore.length; ++i){
    if(!set.contains(this.dataStore[i]))
      tempSet.add(this.dataStore[i]);
  }
  return tempSet;
};

哈希表

function HashTable(){
  this.table = [];

  //this.values = [];

  //当key是整数的时候可以简单的使用simpleHash
  this.simpleHash = function(data){   //这个函数下文不会用到
    var total = 0;
    for(var i = 0; i < data.length; ++i)
      total += data.charDodeAt(i);
    return total % this.table.length;
  };

  //simpleHash()有一个严重的问题：不同字符串可能得到相同hash码，比如"Raymond"和"Clayton"。 这叫做哈希碰撞(hashing collision)

  this.betterHash = function(string, arr){
    const H = 31;    //引入一个质数
    var total = 0;
    for(var i = 0; i < string.length; ++i)
      total += H * total + string.charCodeAt(i);
    total = total % arr.length;
    return parseInt(total);
  };


  this.showDistro = function(){
    var n = 0;
    for(var i = 0; i < this.table.length; ++i){
      // if(this.table[i] !== undefined)      //线性探针法使用这个if
      if(this.table[i][0] !== undefined)    //散列法使用这个if
        console.log(i + ": " + this.table[i]);
    }
  };

  //即使使用了betterHash，也不能保证在所有输入中不会一重复的输出，因此产生了散列法(separate chaining)和线性探针法(linear probing)
  //建立散列
  this.buildChains = function(){
    for(var i = 0; i < this.table.length; ++i)
      this.table[i] = [];
  };

  //散列法对应put函数
  this.put = function(data){
    var pos = this.betterHash(data);
    var index = 0;

    if(this.table[pos][index] === undefined)
      this.table[pos][index] = data;
    else {
      while(this.table[pos][index] !== undefined) ++index;
      this.table[pos][index] = data;
    }
  };

  //散列法对应get函数
  this.get = function(key){
    var pos = this.betterHash(key);
    var index = 0;
    if(this.table[pos][index] === key)
      return this.table[pos][index + 1];
    else {
      while(this.table[pos][index] !== key) index += 2;
      return this.table[pos][index + 1];
    }
    return undefined;
  };

  /*
  //线性探针法对应put函数
  this.put = function(key, data){
    var pos = this.betterHash(data);
    if(this.table[pos] == undefined){
      this.table[pos] = key;
      this.values[pos] = data;
    } else {
      while(this.table[pos] != undefined) ++pos;
      this.table[pos] = key;
      this.values[pos] = data;
    }
  };

  //线性探针法对应get函数
  this.get = function(key){
    var hash = -1;
    hash = this.betterHash(key);
    if(hash > -1){
      for(var i = hash; this.table[hash] != undefined; ++i){
        if(this.table[hash] == key)
          return this.values[hash];
      }
    }
  };
  */
}

树

function Node(data, left, right){   //树节点
  this.data = data;
  this.left = left;
  this.right = right;
  this.show = function(){ return this.data; };
}

//建立一个二叉查找树(Binary Search Tree)
function BST(){
  this.root = null;

  this.insert = function(data){
    var n = new Node(data, null, null);
    if(this.root === null) {
      this.root = n;
    }
    else{
      var current = this.root;
      var parent;
      while(true){
        parent = current;
        if(data < current.data){
          current = current.left;
          if(current === null){
            parent.left = n;
            break;
          }
        }
        else{
          current = current.right;
          if(current == null){
            parent.right = n;
            break;
          }
        }
      }
    }
  };

  //中序遍历
  this.inOrder = function(node){
    if(node !== null){
      inOrder(node.left);
      console.log(node.show() + " ");
      inOrder(node.right);
    }
  };

  //前序遍历
  this.preOrder = function(node){
    if(node !== null){
      console.log(node.show() + " ");
      preOrder(node.left);
      preOrder(node.right);
    }
  };

  //后序遍历
  this.postOrder = function(node){
    if(node !== null){
      postOrder(node.left);
      postOrder(node.right);
      console.log(node.show() + " ");
    }
  };

  //得最小值
  this.getMin = function(){
    var current = this.root;
    while(current.left !== null)
      current = current.left;
    return current.data;
  };

  //得最大值
  this.getMax = function(){
    var current = this.root;
    while(current.right !== null)
      current = current.right;
    return current.data;
  };

  //查找值
  function find(data){
    var current = this.root;
    while(current !== null){
      if(current.data == data) return current;
      else if(data < current.data) current = current.left;
      else if(data > current.data) current = current.right;
    }
    return null;
  };

  //删除值
  this.removeData = function(data){
    this.root = removeNode(this.root, data);
    function removeNode(node, data){
      if(node === null) return null;
      if(data === node.data){
        if(node.left == null && node.right == null) return null;
        if(node.left == null) return node.right;
        if(node.right == null) return node.left;
        var tempNode = getSmallest(node.right);
        node.data = tempNode.data;
        node.right = removeNode(node.right, tempNode.data);
        return node;
      }
      else if(data < node.data){
        node.left = removeNode(node.left, data);
        return node;
      } else{
        node.right = removeNode(node.right, data);
        return node;
      }
    }
  };
}

图

function Graph(v_num){
  this.vertices = v_num;    //定点数量
  this.edges = 0;       //边的数量
  this.adj = [];        //邻接矩阵
  this.marked = [];     //用于遍历时标记已遍历的点
  this.vertexList = []; //存放顶点
  this.edgeTo = [];     //在寻找最短路径时，存放轨迹

  for(var i = 0; i < this.vertices; ++i){    //初始化邻接矩阵
    this.adj[i] = [];
    this.adj[i] = push("");
  }

  this.addEdge = function(v, w){   //添加边,传入2个点
    this.adj[v].push(w);
    this.adj[w].push(v);
    this.edges++;
  };

  this.showGraph = function(){    //输出图
    for(var i = 0; i < this.vertices; ++i){
      console.log(i + " -> ");
      for(var j = 0; j < this.vertices; ++j){
        if(this.adj[i][j] !== undefined)
          console.log(this.adj[i][j] + " ");
      }
      console.log("\n");
    }
  };

  //深度优先遍历
  this.dfs = function(v){
    for(var i = 0; i < this.vertices; ++i)   //初始化标记矩阵
      this.mark[i] = false;
    innerDfs(v);

    function innerDfs(v){
      this.marked[v] = true;
      if(this.adj[v] !== undefined)
        console.log(v + " ");
      for(var i = 0; i < this.adj[v].length; ++i){
        var ver = this.adj[v][i];
        if(!this.marked[ver]) this.innerDfs(ver);
      }
    }
  };

  //广度优先遍历
  this.bfs = function(s){
    for(var i = 0; i < this.vertices; ++i)   //初始化标记矩阵
      this.mark[i] = false;
    var queue = [];     //存放访问过的节点
    this.marked[s] = true;
    queue.push(s);
    while(queue.length > 0){
      var v = queue.shift();
      if(v !== undefined) console.log(s + "");
      for(var i = 0; i < this.adj[v].length; ++i){
        var ver = this.adj[v][i];
        if(!this.marked[ver]){
          this.edgeTo[ver] = v;
          this.marked[ver] = true;
          queue.push(ver);
        }
      }
    }
  };

  this.hasPathTo = function(v){   //判断是否有到节点v的路径
      return this.marked[v];
  };

  this.showPath = function(){     //显示路径
    while(paths.length > 0){
      if(paths.legnth > 1) console.log(paths.pop() + '-');
      else console.log(paths.pop());
    }
  };

  this.pathTo = function(v) {    //计算path路径
    var path = [];
    var source = 0;
    if(!this.hasPathTo(v))
      return undefined;
    for(var i = v; i !== source; i = this.edgeTo[i])
      path.push(i);
    path.push(source);
    return path;

  };

  //拓扑排序
  this.topologicalSort = function(){

    var stack = [];     //栈
    var visited = [];   //记录已访问节点
    //初始化
    for(var i = 0; i < this.vertices; ++i)
      visited = false;

    for(var i = 0; i < this.vertices; ++i){
      if(!visited[i])
        this.topSortHelper(i, visited);  //排列没有访问过的节点
    }

    for(var i = 0; i < stack.length; ++i){
      if(stack[i] !== undefined && stack[i] !== false)
        console.log(this.vertexList[stack[i]]);
    }

    function topSortHelper(v, visited){
      visit[v] = true;
      for(var i = 0; i < this.adj[v].length; ++i){
        var w = this.adj[v][i];
        if(!visited[w])
          this.topSortHelper(visited[w], visited);  //递归当前节点的相邻节点
      }
      stack.push(v);
    }
  };
}

查找相关算法

顺序查找

function seqSearch(arr, data){
  for(var i = 0; i < arr.length; i++){
    if(arr[i] == data) return i;
  }
  return -1;
}

二分查找

//数组arr应该已升序排列
function binSearch(arr, data){
  var upperBound = arr.length - 1;
  var lowerBound = 0;
  while(lowerBound <= upperBound){
    var mid = Math.floor((upperBound + lowerBound) / 2);
    if(arr[mid] < data) lowerBound = mid + 1;
    if(arr[mid] > data) upperBound = mid - 1;
    if(arr[mid] == data) return mid;
  }
  return -1;
}

//利用二分查找计数
//数组arr应该已升序排列
function count(arr, data){
  var count = 0;
  var pos = binSearch(arr, data);
  if(pos > -1){
    ++count;
    for(var i = pos - 1; i > 0; --i){
      if(arr[i] == data) ++count;
      else break;
    }
    for(var i = pos + 1; i < arr.length; ++i){
      if(arr[i] == data) ++count;
      else break;
    }
  }
  return count;
}

二叉查找树

在本文数据结构部分——树的部分已经实现

哈希查找

在本文数据结构部分——哈希表部分的get()方法已经实现

插值查找

function insertionSearch(arr, value){
  return insertionSearchHelper(arr, value, 0, arr.length);

  function insertionSearchHelper(arr, value, low, high){
    var mid = low + (value - arr[low]) / (arr[high] - arr[low]) * (high - low);

    if(arr[mid] === value)
      return mid;
    if(arr[mid] > value)
      return InsertionSearchHelper(arr, value, low, mid-1);
    if(arr[mid] < value)
      return InsertionSearchHelper(arr, value, mid+1, high);
    return null;
  }
}

整理所有查找算法时间复杂度

算法	查找(最坏)	插入(最坏)	删除(最坏)	查找(最好)	插入(最好)	删除(最好)	是否要求有序
顺序结构	N	N	N	N/2	N	N/2	No
二分算法	logN	N	N	logN	N/2	N/2	Yes
二叉查找树(BST)	N	N	N	1.39logN	1.39logN	√N	Yes
2-3树	clogN	clogN	clogN	clogN	clogN	clogN	Yes
红黑树	2logN	2logN	2logN	logN	logN	logN	Yes
哈希散列查找	logN	logN	logN	3~5	3~5	3~5	No
哈希探针查找	logN	logN	logN	3~5	3~5	3~5	No

平均查找长度(ASL) = 查找表中第 i 个元素概率(Pi) * 找到第 i 个元素时已经比较的次数(Ci)