JavaScript笔记 #07# 用js写算法
算法盒子初代（为了提高学习算法的热情。。。）
效果图：
所有代码放在单个html中：
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title></title>
</head>
<body>
<textarea id="data-area" rows="25" cols="80" placeholder="paste your data here..."></textarea>
<p>Algorithm:
<select id="algorithms">
<option value="Temp" style="color: #FF0000;">*临时测试</option>
<option value="EqualElement">相等元素</option>
<option value="Permutations">排列问题</option>
<option value="BinarySearch">二分查找</option>
<option value="Quicksort">快速排序</option>
<option value="MergeSort">归并排序</option>
<option value="InsertSort">插入排序</option>
<option value="BinarySearchTree">二叉搜索树</option>
<option value="IntegerSum">整数和</option>
<option value="MaxSub">最大子段和</option>
<option value="theKnapsackProblem">0-1背包问题</option>
<option value="LCS">最长公共子序列</option>
<option value="HeapSort" selected>堆排序</option>
</select>
<button id="run">run code</button>
</p>
<script type="text/javascript">
let btn = document.querySelector("#run");
btn.addEventListener("click", handleClick);
function handleClick() {
let dataArea = document.querySelector('#data-area');
let selector = document.querySelector("#algorithms");
let data = dataArea.value;
let algorithm = algorithms[selector.value];
// console.time(selector.value);
// data = CommonUtil.handleData(data);
// for (let i = 0; i != 100; ++i) {
algorithm.run(data);
//}
// console.timeEnd(selector.value);
}
</script>
<script type="text/javascript">
class CommonUtil {
static handleData(data) {
let result = [];
let digit = /-?\d+\b/g;
let match;
while(match = digit.exec(data)) {
result.push(Number(match[0]));
}
return result;
}
// 浅拷贝，对象的属性不能是对象
static lightCopy(obj) {
let result = {}
Object.assign(result, obj); // 复制对象所有的属性
return result;
}
static deepCopy(obj) {
let result = JSON.parse(JSON.stringify(obj));
return result;
}
static zeros(x, y) {
let result = [];
for (let i = 0; i != x; ++i) {
result[i] = [];
for (let j = 0; j != y; ++j) {
result[i][j] = 0;
}
}
return result;
}
}
</script>
<script type="text/javascript">
class Temp {
static testMaxSub(data) {
let arr = CommonUtil.handleData(data);
console.time("DP");
for (let i = 0; i != 100; ++i) {
MaxSub.solve(arr, 0, arr.length);
}
console.timeEnd("DP");
console.time("brute-force");
for (let i = 0; i != 100; ++i) {
MaxSub.solve2(arr, 0, arr.length);
}
console.timeEnd("brute-force");
console.time("recursive");
for (let i = 0; i != 100; ++i) {
MaxSub.solve3(arr, 0, arr.length);
}
console.timeEnd("recursive");
}
static run(data) {
Temp.testMaxSub(data);
}
}
</script>
<script type="text/javascript">
class EqualElement {
static hasEqualElement(digitSet) {
for (let i = 0; i != digitSet.length; ++i) {
for (let j = i + 1; j != digitSet.length; ++j) {
if (digitSet[i] == digitSet[j]) return true;
}
}
return false;
}
static run(data) {
data = CommonUtil.handleData(data);
let numOFbatchs = data.shift();
for (let batch = 0; batch != numOFbatchs; ++batch) {
let numOFdigits = data.shift();
let digitSet = [];
while (numOFdigits > 0) {
digitSet.push(data.shift());
numOFdigits--;
}
if (EqualElement.hasEqualElement(digitSet)) {
console.log("yes");
} else {
console.log("no");
}
}
}
}
</script>
<script type="text/javascript">
class Permutations {
static getSequences(arr) {
if (arr.length == 2) {
return [arr, arr.slice().reverse()];
}
let result = [];
for (let i = 0; i != arr.length; ++i) {
let subArr = arr.slice(0, i).concat(arr.slice(i + 1, arr.length));
let subSequences = Permutations.getSequences(subArr);
let wrapped = subSequences.map(subSeq => [arr[i]].concat(subSeq));
result = result.concat(wrapped);
}
return result;
}
static run(data) {
data = CommonUtil.handleData(data);
console.log(data);
if (EqualElement.hasEqualElement(data)) {
console.log("Invalid data.");
} else {
let result = Permutations.getSequences(data);
console.log(result);
}
}
}
</script>
<script type="text/javascript">
class BinarySearch {
static find(x, arr, start, end) {
if (start > end) return { success: false};
let mid = Math.floor((start + end) / 2);
if (arr[mid] == x) {
return { success: true, index: mid};
} else if (arr[mid] < x) {
return BinarySearch.find(x, arr, mid + 1, end);
} else {
return BinarySearch.find(x, arr, start, mid - 1);
}
}
static run(data) {
data = CommonUtil.handleData(data);
if (data.length == 0) {
const DEFAULT_SIZE = 10;
const MAX = 100;
for (let i = 0; i != DEFAULT_SIZE; ++i) {
data.push(Math.floor(Math.random() * MAX));
}
}
Quicksort.sort(data, 0, data.length - 1);
console.log(data);
let x = Number(prompt("请输入要查找的数据："));
if (Number.isNaN(x)) {
console.log("非法输入！");
} else {
let result = BinarySearch.find(x, data, 0, data.length - 1);
if (result.success) {
console.log(`A[${result.index}]: ${x}`);
} else {
console.log(`元素 ${x} 不在数组中`);
}
}
}
}
</script>
<script type="text/javascript">
class Quicksort {
static sort(arr, start, end) {
if (start >= end) return;
let left = start;
let right = end;
let x = arr[left];
while (left < right) {
while (left < right && arr[right] > x) right--;
if (left != right) {
arr[left] = arr[right];
left++;
}
while (left < right && arr[left] < x) left++;
if (left != right) {
arr[right] = arr[left];
right--;
}
}
arr[left] = x;
Quicksort.sort(arr, start, left - 1);
Quicksort.sort(arr, left + 1, end);
}
static run(data) {
data = CommonUtil.handleData(data);
Quicksort.sort(data, 0, data.length - 1);
console.log(data);
}
}
</script>
<script type="text/javascript">
class MergeSort {
// merge two sorted sequences: arr[start:mid] and arr[mid:end]
static merge(arr, start, mid, end) {
let leftArr = arr.slice(start, mid); // arr[mid] is excluded
let rightArr = arr.slice(mid, end); // arr[end] is excluded
// put on the buttom of each pile a sentinel
// card, which contains a special value that
// we use to simplify out codes
let sentinel = Infinity;
leftArr.push(sentinel);
rightArr.push(sentinel);
let i = 0, j = 0; // index of leftArr and rightArr
for (let k = start; k < end; ++k) {
arr[k] = leftArr[i] < rightArr[j] ? leftArr[i++] : rightArr[j++];
}
}
// sort arr[start:end], arr[end] is excluded
static sort(arr, start, end) {
// calling sort(arr, 0, 1) doesn't make
// sense for there's only one element,
// so just stop dividing/recursive and merge directly.
if (start + 1 < end) {
// divide the problem into two subproblems
let mid = Math.floor((start + end) / 2);
// recursively solve subproblems
MergeSort.sort(arr, start, mid);
MergeSort.sort(arr, mid, end);
// combine the solutions to the subproblems into
// the solution for the original problem.
MergeSort.merge(arr, start, mid, end);
}
}
static run(data) {
// convert a string to a numeric array
data = CommonUtil.handleData(data);
MergeSort.sort(data, 0, data.length);
console.log(data);
}
}
</script>
<script type="text/javascript">
class InsertSort {
static sort(arr, start, end) {
for (let i = start + 1; i != end; ++i) {
let insertDate = arr[i];
let k = i - 1;
while (k >= 0 && arr[k] > insertDate) {
arr[k + 1] = arr[k];
k--;
}
arr[k + 1] = insertDate;
}
}
static run(data) {
// convert a string to a numeric array
data = CommonUtil.handleData(data);
InsertSort.sort(data, 0, data.length);
console.log(data);
}
}
</script>
<script type="text/javascript">
class Node {
constructor(data) {
this.data = data;
this.left = null;
this.right = null;
}
}
class BinarySearchTree {
constructor(firstData) {
this.root = new Node(firstData);
// force user to provide a root,
// avoid checking every time .
}
insert(data, current=this.root) {
if (data <= current.data) {
if (current.left == null) {
current.left = new Node(data);
} else {
this.insert(data, current.left);
}
} else {
if (current.right == null) {
current.right = new Node(data);
} else {
this.insert(data, current.right);
}
}
}
toList() {
this.result = [];
this.inorder(this.root);
return this.result;
}
inorder(node) {
if (node == null) return;
this.inorder(node.left);
this.result.push(node.data);
this.inorder(node.right);
}
static run(data) {
data = CommonUtil.handleData(data);
let bst = new BinarySearchTree(data[0]);
for (let x of data.slice(1)) {
bst.insert(x);
}
console.log(bst.toList());
}
}
</script>
<script type="text/javascript">
class IntegerSum {
static searchSum(arr, start, end, x) {
if (end - start <= 1) return false;
let sum = arr[start] + arr[end - 1];
if (sum < x) {
return IntegerSum.searchSum(arr, start + 1, end, x);
} else if (sum > x) {
return IntegerSum.searchSum(arr, start, end - 1, x);
} else {
console.log(arr[start], arr[end - 1]);
return true;
}
}
static run(data) {
data = CommonUtil.handleData(data); // cn
MergeSort.sort(data, 0, data.length); // cnlgn
// let x = Number(prompt("please enter the value of x :"));
let x = Math.floor(Math.random() * 40);
console.log("data=" + data);
console.log("x=" + x);
let end = -1;
while (data[++end] <= x); // cn
let result;
let max = data[end - 1] + data[end - 2];
let min = data[0] + data[1];
if (max < x || min > x) { // deal with special situations
result = false;
} else if (max == x || min == x) {
result = true;
} else {
result = IntegerSum.searchSum(data, 0, end, x); // cn
}
console.log(result);
}
}
</script>
<script type="text/javascript">
class MaxSub {
// 解法1：动态规划 -- O(n)
static solve(arr, start, end) {
let s = []; // s[n]保存arr[start:n+1]的最大子段和
let b = []; // b[n]保存由从arr[n]开始到arr[start]的逆向最大和
s[start] = {
sum: arr[start],
start: start,
end: start + 1
}; // 当数组只有一个元素的时候，最大子段和只能是这个元素
b[start] = CommonUtil.lightCopy(s[start]);
for (let i = start + 1; i != end; ++i) {
// b[i] = max(b[i-1]+arr[i], arr[i])
if (b[i - 1].sum + arr[i] > arr[i]) {
b[i] = CommonUtil.lightCopy(b[i - 1]);
b[i].sum += arr[i];
} else {
b[i] = {sum: arr[i], start: i};
}
b[i].end = i + 1;
// s[i] = max(s[i-1], b[i])
s[i] = CommonUtil.lightCopy(
s[i - 1].sum >= b[i].sum ? s[i - 1] : b[i]
);
}
// 证明：假设s[n]是截至arr[n]的最大子段和（包括arr[n]）
// 当考察s[n+1]时，相当于往原序列添加一个新元素arr[n+1]
// 结果是生成了arr[0..n+1],arr[1..n+1]等n+1个新序列
// 我们选取这些新序列中最大的,即从arr[n+1]开始的"逆向最大和",
// 与旧序列的最大子段和s[n]比较，s[n+1]取两者中更大的一个
// （其实就是在新和旧之间决策），因为考虑了所有可能的情况，
// 并且是大中选大，所以s[n+1]是截至arr[n+1]的最大子段和。
// 思路：先考虑一个元素的情况，显然最大子段和只能是那个元素
// 然后考虑2个元素的情况（在原基础上增加1个），要么仍是第
// 一个元素，要么就是逆向最大和，继续增加元素考虑，发现都是
// 反复在做同样的决策....
return s[end - 1];
}
// 解法2：暴力求解 -- O(n^2)
static solve2(arr, start, end) {
let result = {
sum: -Infinity,
start: start,
end: end
};
for (let i = start; i != end; ++i) {
let temp = {
sum: 0,
start: i
};
for (let j = i; j != end; ++j) {
temp.sum += arr[j];
temp.end = j + 1;
if (temp.sum > result.sum) {
result = CommonUtil.lightCopy(temp);
}
}
}
return result;
}
// 解法3：递归（分治） -- O(nlgn),来自算法导论
static solve3(arr, start, end) {
function findMaxCrossingSubarray(arr, start, mid, end) {
let leftSum = -Infinity;
let sum = 0;
let maxLeft; // 开始下标
for (let i = mid - 1; i >= start; --i) {
sum = sum + arr[i];
if (sum > leftSum) {
leftSum = sum;
maxLeft = i;
}
}
let rightSum = -Infinity;
sum = 0;
let maxRight; // 结束下标
for (let j = mid; j != end; ++j) {
sum = sum + arr[j];
if (sum > rightSum) {
rightSum = sum;
maxRight = j;
}
}
return {
sum: leftSum + rightSum,
start: maxLeft,
end: maxRight + 1
};
}
if (start + 1 == end) { // base case
return {
sum: arr[start],
start: start,
end: end
};
} else {
let mid = Math.floor((start + end) / 2);
let leftResult = MaxSub.solve3(arr, start, mid);
let rightResult = MaxSub.solve3(arr, mid, end);
let crossResult = findMaxCrossingSubarray(arr, start, mid, end);
let finalResult = {
sum: -Infinity,
};
if (leftResult.sum > finalResult.sum) finalResult = CommonUtil.lightCopy(leftResult);
if (rightResult.sum > finalResult.sum) finalResult = CommonUtil.lightCopy(rightResult);
if (crossResult.sum > finalResult.sum) finalResult = CommonUtil.lightCopy(crossResult);
return finalResult;
}
}
static run(data) {
let arr = CommonUtil.handleData(data);
let result = MaxSub.solve(arr, 0, arr.length);
// console.log(result);
console.log(arr.slice(result.start, result.end));
console.log(`max_sum = ${result.sum}`);
}
}
</script>
<script type="text/javascript">
class theKnapsackProblem {
static solve(wt, val, knapsackMaxWeight) {
let numOfItems = wt.length; // 物品总数
let maxValue = [];
for (let i = 0; i <= numOfItems; ++i) {
maxValue[i] = [];
for (let j = 0; j <= knapsackMaxWeight; ++j)
maxValue[i][j] = { val: 0, items: []};
} // 初始化边界，当可选物品为前0个，背包容量为0时显然最大价值只能是0
for (let i = 1; i <= numOfItems; ++i) {
let current = i - 1; // wt,val的序号是从0开始的
for (let j = 1; j <= knapsackMaxWeight; ++j) {
let notPut = maxValue[i - 1][j];
if (wt[current] <= j) {
let put = {
val: maxValue[i - 1][j - wt[current]].val + val[current],
items: maxValue[i - 1][j - wt[current]].items.concat(current)
};
maxValue[i][j] = put.val > notPut.val ? put : notPut;
} else {
maxValue[i][j] = notPut;
}
}
}
return maxValue[numOfItems][knapsackMaxWeight];
}
static run(data) {
data = CommonUtil.handleData(data);
let batchs = data.shift();
for (let i = 0; i != batchs; ++i) {
let numOfItems = data.shift();
let knapsackMaxWeight = data.shift();
let wt = [], val = [];
for (let j = 0; j != numOfItems; ++j) {
wt.push(data.shift());
}
for (let j = 0; j != numOfItems; ++j) {
val.push(data.shift());
}
let result = theKnapsackProblem.solve(wt, val, knapsackMaxWeight);
// 格式化输出结果↓
let items = [];
console.log(result.items);
for (let i = 0; i != numOfItems; ++i) {
if (result.items.indexOf(i) != -1) {
items.push(1);
} else {
items.push(0);
}
}
console.log(result.val);
console.log(items + "");
}
}
// 证明：假设maxValue[i][j]是在仅可以选择前i个物品，
// 且背包的最大容量为j时，能够组合得到的最大总价值。
// 当考察maxValue[i+1][j]时，实际上就是考察放不放第
// i+1个物品的问题，该决策取决于能不能得到最大价值，
// 放第i+1个物品产生的最大价值为maxValue[i][j-w]+v
// 不放的最大价值仍为maxValue[i][j]，放不放就是所有
// 情况，我们在所有情况里决策一个最大的就可以了。所以
// 这个迭代可以保持循环不变式。
}
</script>
<script type="text/javascript">
class LCS {
static solve(a, b) {
// 初始化表
a.unshift(undefined); // 便于处理，从a[1]开始存东西
b.unshift(undefined);
let lcs = CommonUtil.zeros(a.length, b.length);
// 填表
for (let i = 1; i != a.length; ++i) {
for (let j = 1; j != b.length; ++j) {
if (a[i] == b[j]) {
lcs[i][j] = lcs[i - 1][j - 1] + 1;
} else {
lcs[i][j] = Math.max(lcs[i - 1][j], lcs[i][j - 1]);
}
}
}
// 返回结果
return lcs[a.length - 1][b.length - 1];
}
static run(data) {
data = data.split("\n");
let a = data[0].split("");
let b = data[1].split("");
console.log(LCS.solve(a, b));
/**
* test:
* aebfc
* abc
* output=3
*/
}
}
</script>
<script type="text/javascript">
class HeapSort {
static left(i) {
return 2 * i;
}
static right(i) {
return 2 * i + 1;
}
static parent(i) {
return Math.floor(i / 2);
}
// 递归版本
static maxHeapify(arr, i) {
let l = HeapSort.left(i);
let r = HeapSort.right(i);
let largest = i;
if (l < arr.length && arr[l] > arr[largest]) {
largest = l;
}
if (r < arr.length && arr[r] > arr[largest]) {
largest = r;
}
if (largest != i) {
let temp = arr[i];
arr[i] = arr[largest];
arr[largest] = temp; // 此时arr[largest]已经被置换成更小的那个
HeapSort.maxHeapify(arr, largest);
}
}
// 非递归修正版本，heapSize表示改动范围仅限于arr[1:heapSize+1]
static maxHeapify2(arr, i, heapSize) {
let flag = true;
while (flag) {
let l = HeapSort.left(i);
let r = HeapSort.right(i);
let largest = i;
if (l <= heapSize && arr[l] > arr[largest]) {
largest = l;
}
if (r <= heapSize && arr[r] > arr[largest]) {
largest = r;
}
if (largest != i) {
let temp = arr[i];
arr[i] = arr[largest];
arr[largest] = temp; // 此时arr[largest]已经被置换成更小的那个
i = largest;
} else {
flag = false;
}
}
}
static buildMaxHeap(arr, heapSize) {
for (let i = Math.floor(heapSize / 2); i >= 1; --i) {
HeapSort.maxHeapify2(arr, i, heapSize);
}
}
static sort(arr) {
let heapSize = arr.length - 1;
HeapSort.buildMaxHeap(arr, heapSize);
for (let i = arr.length - 1; i >= 2; --i) {
let temp = arr[i];
arr[i] = arr[1];
arr[1] = temp;
HeapSort.maxHeapify2(arr, 1, --heapSize);
}
}
static run(data) {
let test1 = [undefined, 16, 4, 10, 14, 7, 9, 3, 2, 8, 1];
HeapSort.sort(test1);
console.log(test1);
}
}
</script>
<script type="text/javascript">
const algorithms = {
"Temp": Temp,
"EqualElement": EqualElement,
"Permutations": Permutations,
"BinarySearch": BinarySearch,
"Quicksort": Quicksort,
"MergeSort": MergeSort,
"InsertSort": InsertSort,
"BinarySearchTree": BinarySearchTree,
"IntegerSum": IntegerSum,
"MaxSub": MaxSub,
"theKnapsackProblem": theKnapsackProblem,
"LCS": LCS,
"HeapSort": HeapSort
};
</script>
</body>
</html>
稍微模块化：
<!DOCTYPE html> <html> <head> <meta charset="UTF-8"> <title></title> </head> <body> <textarea id="data-area" rows="25" cols="80" placeholder="paste your data here..."></textarea> <p>Algorithm: <select id="algorithms"> <option value="EqualElement">相等元素</option> <option value="Permutations">排列问题</option> <option value="BinarySearch">二分查找</option> <option value="Quicksort">快速排序</option> <option value="MergeSort">归并排序</option> <option value="InsertSort">插入排序</option> <option value="BinarySearchTree">二叉搜索树</option> <option value="IntegerSum">整数和</option> <option value="MaxSub">最大子段和</option> <option value="theKnapsackProblem">0-1背包问题</option> <option value="LCS">最长公共子序列</option> <option value="HeapSort">堆排序</option> <option value="OptimalLoading" selected="">最优装载问题</option> </select> <button id="run">run code</button> </p> <script type="text/javascript"> let btn = document.querySelector("#run"); btn.addEventListener("click", handleClick); function handleClick() { let dataArea = document.querySelector('#data-area'); let selector = document.querySelector("#algorithms"); let data = dataArea.value; let algorithm = algorithms[selector.value]; algorithm.run(data); } </script> <script src="js/CommonUtil.js"></script> <script src="js/EqualElement.js"></script> <script src="js/Permutations.js"></script> <script src="js/BinarySearch.js"></script> <script src="js/Quicksort.js"></script> <script src="js/MergeSort.js"></script> <script src="js/InsertSort.js"></script> <script src="js/BinarySearchTree.js"></script> <script src="js/IntegerSum.js"></script> <script src="js/MaxSub.js"></script> <script src="js/theKnapsackProblem.js"></script> <script src="js/LCS.js"></script> <script src="js/HeapSort.js"></script> <script src="js/OptimalLoading.js"></script> <script type="text/javascript"> const algorithms = { "EqualElement": EqualElement, "Permutations": Permutations, "BinarySearch": BinarySearch, "Quicksort": Quicksort, "MergeSort": MergeSort, "InsertSort": InsertSort, "BinarySearchTree": BinarySearchTree, "IntegerSum": IntegerSum, "MaxSub": MaxSub, "theKnapsackProblem": theKnapsackProblem, "LCS": LCS, "HeapSort": HeapSort, "OptimalLoading": OptimalLoading }; </script> </body> </html>
