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  • License MIT

Package Exports

  • algm
  • algm/dist/algm.esm.js
  • algm/dist/index.js

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (algm) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

algm

NPM version npm download ci

A fast algorithm library for JavaScript/TypeScript.

Problem

When you participate in an algorithm competition or code algorithm problems online such as leetcode, you may choose c++,java,python. Because they have the built-in library like STL that contains priority queue,order set etc.

Installation

npm install algm

Documentation

You can find the algm documentation on the website.

Why algm?

Safe

import a from 'algm';
const arr = Array(125625).fill(0);
//Maximum call stack size exceeded in nodejs
Math.max(...arr);
//safe
a.max(arr);

// the recursive version postorder traversal may result in maximum call stack error
// a.postorder internal use iteration
a.postorder(root, (node, fatherNode) => {
  console.log(node);
});

Contains many frequently used functions

import a from 'algm';
// init an array with an initial value of 0
a.initArray(4); // => [0,0,0,0]

// init a two-dimensional array with an initial value of 0
a.init2Array(3, 4); // => [[0,0,0,0],[0,0,0,0],[0,0,0,0]]

// get the max value
a.max(1, 3, 2); // => 3
a.max([1, 3, 2]); // => 3

// get the min value
a.min(1, 3, 2); // => 1
a.min([1, 3, 2]); // => 1

// compute the sum of an array
a.sum([1, 2, 3]); // => 6

// get the last element of an array
a.last([3, 2, 1]); // => 1

// return a new arr that does not contains duplicate elements.
a.unique([1, 1, 2, 2, 2, 6, 1]); //=> [1,2,6]

// sort the array in ascending order
a.sortA([3, 1, 2]); // => [1, 2, 3]
a.sortA([{ height: 3 }, { height: 2 }, { height: 1 }], x => x.height);
// => [{ height: 1 }, { height: 2 }, { height: 3 }]

a.sortD([3, 1, 2]); // => [3, 2, 1]
a.sortD([{ height: 3 }, { height: 2 }, { height: 1 }], x => x.height);
// => [{ height: 3 }, { height: 2 }, { height: 1 }]

// compute the greatest common divisor of a and b
a.gcd(4, 2); // => 2
a.gcd(9, 6); // => 3

// Randomly returns integers in [min, max)
a.random(2, 8); // => 4

// Compute the number of permutations c(n,m)=n*(n-1)*...(n-m+1)/(m!)
// the result is bigint
a.c(5, 2); // => 10n
a.c(5, 0); // => 1n

// Compute the number of permutations,
// then take the remainder of modulo 10 * * 9 + 7
a.cm(5, 2); // => 10
a.cm(5, 0); // => 1

// Compute the remainder of m mod n
// The main difference with m%n is that a.mod always return nonnegative number.
a.mod(2, 3); // => 2
a.mod(-2, 3); // => 1
-2 % 3; // => -2
a.mod(-2, 2); // => 0

data structure

  • priority queue

    max priority queue

    const input = [4, 3, 1];
    const maxP = new MaxPQ(input);
    maxP.max(); //=> 4
    maxP.insert(5);
    maxP.max(); //=> 5
    maxP.insert(8);
    maxP.max(); //=> 8
    maxP.delMax();
    maxP.max(); //=> 5

    Provide the specified key

    const input = [
      { name: 'xiao', age: 21 },
      { name: 'wang', age: 22 },
      { name: 'li', age: 25 },
    ];
    const maxP = new MaxPQ(input, v => v.age);
    const m = maxP.max(); //=> { name: 'li', age: 25 }
  • SkipList

    a probabilistic data structure

    search, insert, remove achieve O(Logn) expected performance. max,min cost O(1) time complexity

    const sl = new SkipList();
    sl.insert(3);
    sl.insert(1);
    sl.insert(5);
    sl.search(1); // => 1
    sl.remove(1);
    sl.search(1); // => null
  • randomized binary search tree

    search, insert, remove, find the k-th max value achieve O(Logn) expected performance.

    const rbst = new RBST();
    const arr = [1, 7, 3];
    arr.forEach(v => {
      rbst.insert(v);
    });
    rbst.search(3); // => 3
    rbst.findKMax(1); // => 7
    rbst.remove(3);
    rbst.search(3); // => null
    rbst.findKMax(2); // => 1
  • Segment tree

    Max segment tree

    Query the maximum value of given range and update the value in O(Logn) time.

    import { MaxArr } from 'algm';
    const maxArr = new MaxArr([2, 3, 1, 7, 9]);
    const [l, r] = [0, 2];
    // find the maximum value from [l,r]
    maxArr.query(l, r); //=> 3
    maxArr.query(0, 3); //=> 7
    maxArr.update(1, 9); // arr=[2, 9, 1, 7, 9]
    maxArr.query(0, 3); //=> 9

    Provide the specified key

    import { MaxArr } from 'algm';
    const maxArr = new MaxArr(
      [
        { name: 'li', age: 21 },
        { name: 'wang', age: 24 },
        { name: 'xx', age: 23 },
      ],
      node => node.age
    );
    maxArr.query(0, 2); //=> { name: 'wang', age: 24 }
    maxArr.update(0, { name: 'xiao', age: 25 });
    maxArr.query(0, 2); //=> { name: 'xiao', age: 25 }

    sum segment tree

    Query the sum of given range and update the value in O(Logn) time.

    import { SumArr } from 'algm';
    const sumArr = new SumArr([2, 3, 1, 7, 9]);
    sumArr.query(0, 2); //=> 6
    sumArr.update(2, 4);
    sumArr.query(0, 2); //=> 9

    value segment tree

    Given an array contains all the values,insert the value one by one,and query the number of value in [lower,upper].

    import { ValueArr } from 'algm';
    const arr = [1, 2, 3, 5, 7];
    const vArr = new ValueArr(arr);
    vArr.insert(1);
    vArr.insert(3);
    vArr.insert(5);
    assert.strictEqual(vArr.query(1, 5), 3);
    vArr.insert(1);
    assert.strictEqual(vArr.query(1, 5), 4);
  • union–find

    A data structure that stores a collection of disjoint (non-overlapping) sets. It provides operations for merging sets (union), and finding a representative member(find) of a set.

    import { UnionFind } from 'algm';
    const n = 4;
    const uf = new UnionFind(n);
    uf.union(0, 1);
    uf.union(1, 2);
    uf.isSameSet(0, 2); //=> true
    uf.isSameSet(0, 3); //=> false

algorithm

  • topsort

    topsort({
      n: 5,
      edges: [
        [1, 0],
        [1, 3],
        [3, 2],
        [3, 4],
      ],
    }); // => [1,3,4,2,0]
  • Hopcroft–Karp algorithm

    a fast bipartite matching algorithms

    hopcroftKarp(5, [
      [5, 6],
      [5, 9],
      [7, 8],
      [5, 9],
      [6, 8],
    ]);
    // => Map(10){ 0=>6,1=>9,2=>7,3=>5,4=>8,6=>0,7=>2,8=>4,9=>1 }
  • manacher a linear time algorithm to find all the palindromic substring

  import { getPalindromeArr } from 'algm';
  const  palindromeLengthArr=getPalindromeArr('aba')
  // The length of the palindrome centered on each vertex
  // => [1,3,1]