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Weird array behavior in JavaScript

I'm trying to write a tool for visualizing the bubble sort algorithm.
The array arr holding all the values, that is to be sorted, is a global variable. The user clicks the "Fill" button btnFill to fill the array with unsorted, random numbers using the fillArray function. The function returns an array of objects: {val: x, col: "y"} where x is the value and col is a color class used for CSS.
When the array is filled, if the user clicks the "sort" button btnSort, the bubbleSort function is invoked where I guess my problem is:
This function saves a copy of the array arr on every iteration of the inner loop. This is an idea that I had since I was having a lot of issues using setInterval to animate - I could just save snapshots of the array during every stage of the sorting, and then pass it to the draw function so that there wouldn't be any JavaScript weirdness combining loops and intervals.
The function finishes running and is expected (by me at least) to return an array filled with copies of the arr array from every loop iteration.
The actual behavior which I have tried to understand for hours is that the snapShot array is filled with arrays of a sorted arr. All elements are the same - sorted arrays. Doesn't make sense to me since when debugging it comes out as sorted in console.log when it enters the sorting loop for the first time.
I appreciate any help greatly, thank you!
--EDIT--
I'm aware that the snapShot array gets sent as an array of arrays and will not be drawn to the screen but the problem is somewhere before that. That part was changed for debugging reasons
const btnFill = document.querySelector("#btnFill");
const btnSort = document.querySelector("#btnSort");
const container = document.querySelector(".container");
let arr = [];
btnFill.addEventListener("click", function () {
arr = fillArray();
draw(arr);
});
btnSort.addEventListener("click", function () {
let sorted = bubbleSort();
draw(sorted);
});
function bubbleSort() {
let snapShots = [];
for (let i = 0; i < arr.length - 1; i++) {
for (let j = 0; j < arr.length - 1 - i; j++) {
if (arr[j].val > arr[j + 1].val) {
let tmp = arr[j].val;
arr[j].val = arr[j + 1].val;
arr[j + 1].val = tmp;
snapShots.push([...arr]);
}
}
}
return snapShots;
}
function fillArray() {
const tmp = [];
const len = 50;
for (let i = 0; i < len; i++) {
tmp[i] = { val: Math.floor(Math.random() * 100 + 1), col: "red" };
}
return tmp;
}
function draw(array) {
container.innerHTML = "";
for (let i = 0; i < array.length; i++) {
const tmp = document.createElement("div");
tmp.style.height = array[i].val + "%";
tmp.classList.add("bar", array[i].col);
container.appendChild(tmp);
}
}

The reason that it's not working like you want it is because you are doing shallow copies of the array, but the objects in each position are the same references.
This means that this part of the code:
let tmp = arr[j].val;
arr[j].val = arr[j + 1].val;
arr[j + 1].val = tmp;
Is changing the object that every snapshot element is pointing in the same position. And that's why you get every array sorted, because you are creating new arrays with the same references to the objects.
To get what you want you can do a deep copy instead, which also creates new references of the nested values.
function bubbleSort() {
let snapShots = [];
for (let i = 0; i < arr.length - 1; i++) {
for (let j = 0; j < arr.length - 1 - i; j++) {
if (arr[j].val > arr[j + 1].val) {
let tmp = arr[j].val;
arr[j].val = arr[j + 1].val;
arr[j + 1].val = tmp;
snapShots.push(JSON.parse(JSON.stringify(arr)));
}
}
}
return snapShots;
}
Other solution (and simpler) is to change the position of the object in the array instead of changing the property val of the object:
function bubbleSort() {
let snapShots = [];
for (let i = 0; i < arr.length - 1; i++) {
for (let j = 0; j < arr.length - 1 - i; j++) {
if (arr[j].val > arr[j + 1].val) {
let tmp = arr[j];
arr[j] = arr[j + 1];
arr[j + 1] = tmp;
snapShots.push([...arr]);
}
}
}
return snapShots;
}

find all numbers disappeared in array

Please help me to solve this leetcode problem using javascript as I am a beginner and dont know why this code is not working
Ques: Given an array of integers where 1 ≤ a[i] ≤ n (n = size of array), some elements appear twice and others appear once.
Find all the elements of [1, n] inclusive that do not appear in this array.
var findDisappearedNumbers = function (nums) {
var numLength = nums.length;
nums.sort(function (a, b) { return a - b });
for (var i = 0; i < nums.length - 1; i++) {
if (nums[i + 1] === nums[i]) {
nums.splice(i, 1);
}
}
for (var k = 0; k < nums.length; k++) {
for (var j = 1; j <= numLength; j++) {
if (nums[k] !== j) {
return j;
}
}
}
};
if there is any error in my code please let me know;
i have done the following thing
first i have sorted the array in ascending order
then i have cut all the duplicate elements
then i have created loop that will check if nums[k] !== j ;
and it will return j which is the missing number;
for example this is the testcase [4,3,2,7,8,2,3,1]
first my code will sort this in ascending order [1,2,2,3,3,4,7,8]
then it will remove all duplicate elements and it will return [1,2,3,4,,7,8]
and then it will check nums[k] is not equal to j and it will print j

I think it'd be easier to create a Set of numbers from 1 to n, then just iterate through the array and delete every found item from the set:
var findDisappearedNumbers = function(nums) {
const set = new Set();
for (let i = 0; i < nums.length; i++) {
set.add(i + 1);
}
for (const num of nums) {
set.delete(num);
}
return [...set];
};
console.log(findDisappearedNumbers([4,3,2,7,8,2,3,1]));
To fix your existing code, I'm not sure what the logic you're trying to implement in the lower section, but you can iterate from 1 to numLength (in the outer loop, not the inner loop) and check to see if the given number is anywhere in the array. Also, since you're mutating the array with splice while iterating over it in the upper loop, make sure to subtract one from i at the same time so you don't skip an element.
var findDisappearedNumbers = function(nums) {
var numLength = nums.length;
nums.sort(function(a, b) {
return a - b
});
for (var i = 0; i < nums.length - 1; i++) {
if (nums[i + 1] === nums[i]) {
nums.splice(i, 1);
i--;
}
}
const notFound = [];
outer:
for (var j = 1; j < numLength; j++) {
for (var k = 0; k < nums.length; k++) {
if (nums[k] === j) {
continue outer;
}
}
notFound.push(j);
}
return notFound;
};
console.log(findDisappearedNumbers([4, 3, 2, 7, 8, 2, 3, 1]));

#CertainPerformance certainly cracked it again using the modern Set class. Here is a slighly more conservative approach using an old fashioned object:
console.log(missingIn([4,3,2,7,8,2,3,1]));
function missingIn(arr){
const o={};
arr.forEach((n,i)=>o[i+1]=1 );
arr.forEach((n) =>delete o[n] );
return Object.keys(o).map(v=>+v);
}

My solution for the problem to find the missing element
var findDisappearedNumbers = function(nums) {
const map={};
const result=[];
for(let a=0;a<nums.length;a++){
map[nums[a]]=a;
}
for(let b=0;b<nums.length;b++){
if(map[b+1]===undefined){
result.push(b+1)
}
}
return result;
};
Example 1:
Input: nums = [4,3,2,7,8,2,3,1]
Output: [5,6]
Example 2:
Input: nums = [1,1]
Output: [2]

Two Sum Leetcode in Javascript - code looks correct but Leetcode says it's wrong

I'm working on the 'Two Sum' problem in Leetcode.
I'm sure this code is correct, I've tested it in Repl and it looks correct there, but Leetcode is giving me an error.
Here's my code:
var arr = [];
var twoSum = function(nums, target) {
for(var i = 0; i < nums.length; i++){
for(var j = i+1; j < nums.length; j++){
console.log(nums[i] + ', ' + nums[j]);
var tot = nums[i] + nums[j];
if(tot === target){
arr.push(i,j);
console.log(arr);
return arr;
}
}
}
};
//var a = [2, 7, 11, 15];
//var b = 9;
var a = [2, 3, 4];
var b = 6;
twoSum(a, b);
The error I'm getting is as follows:
Input:
[3,2,4]
6
Output:
[0,1,1,2]
Expected:
[1,2]
Why is it expecting [1, 2]? Surely it should expect [0, 1] in this case, and then why is my code adding to the arr array twice? It looks like a bug to me...
Note: I see there's many posts about this problem on Leetcode, but none address the specific issue I have run into in Javascript.

Why is it expecting [1, 2]?
Because 2 + 4 = 6
Surely it should expect [0, 1] in this case
No, because 3 + 2 = 5
and then why is my code adding to the arr array twice?
Because you declared the array outside of the function. It is being re-used for every call to the function. Move the array declaration into your twoSum function or even better: Simply return [i, j] instead of pushing into the empty array.

Here is another solution you can try...
var twoSum = function(nums, target) {
let map = {};
for (let i = 0; i < nums.length; i++) {
let compliment = target - nums[i];
if (map[compliment]) {
return [(map[compliment] - 1), i];
} else {
map[nums[i]] = i + 1;
}
}
};
twoSum([2, 3, 4],6);
Click Here to RUN

Here is an optimum solution
/**
* #param {number[]} nums
* #param {number} target
* #return {number[]}
*/
function twoSum(nums, target) {
const numsObjs = {}; // create nums obj with value as key and index as value eg: [2,7,11,15] => {2: 0, 7: 1, 11: 2, 15: 3}
for (let i = 0; i < nums.length; i++) {
const currentValue = nums[i];
if (target - currentValue in numsObjs) {
return [i, numsObjs[target - currentValue]];
}
numsObjs[nums[i]] = i;
}
return [-1, -1];
}
console.log(twoSum([2, 7, 11, 15], 9))

This is my solution, which is a brute force method that uses javascript to search for all possible pairs of numbers.
var twoSum = function(nums, target) {
let numarray = new Array(2);
for (var i = 0; i < nums.length; i++) {
for (var j = i + 1; j < nums.length; j++) {
if (nums[i] + nums[j] == target) {
numarray[0] = i;
numarray[1] = j;
}
}
}
return numarray;
};

Loop trough array and sum the length

EDITED:
Can someone help me with the problem below further. I have a class and an array inside the class. I want now use a for loop to sum the length of the previous array length, but for each iteration. If i == 1 I want sum the length of arr[0].x.length, If i == 2 I want sum the length of arr[0].x.length+arr[1].x.length, ect. It will be a lot of code to check each iteration.
Is there a simple way to do this? Instead allways use a new line like
if (i == 1) n = n + arr[i-1].x.length;
if (i == 2) n = n + arr[i-1].x.length+arr[i-2].x.length;
if (i == 3) n = n + arr[i-1].x.length+arr[i-2].x.length+arr[i-3].x.length;
function Class() {
var x = [];
}
for (var i = 0; i < 9; i++) {
arr[i] = new Class();
}
I add 4 items to each object.
arr[0].x.push(...)
arr[0].x.push(...)
...
arr[1].x.push(...)
arr[1].x.push(...)
...
var n = 0;
for (var i = 0; i < arr.length; i++) {
if (i == 1) {
n = n + arr[i-1].x.length;
} else if (i == 2) {
n = n + arr[i-1].x.length+arr[i-2].x.length;
} else if (i == 3) {
n = n + arr[i-1].x.length+arr[i-2].x.length+arr[i-3].x.length;
}
// ect.
}

You could use reduce to get a total of all the lengths of your sub-arrays. For example:
const arrs = [[1, 2, 3], [4, 5, 6]];
const sum = arrs.reduce((acc, arr) => acc += arr.length, 0);
console.log(sum);
// 6

Just nest the loop two times: go over the indexes once then go up to that index from 0 in an inner loop:
for (var i = 0; i < arr1.length; i++) {
for(var j = 0; j <= i; j++) {
n = n + arr1[j].length;
}
}

Edit: benvc's answer is what you are looking for if you want to use reduce.
var arr = [[1,2,3], [4,5,6], [7]];
var n = 0;
for (var i = 0; i < arr.length; i++){
n += arr[i].length;
}
console.log(n);

Partial sort in JavaScript

Is there any built-in JavaScript function to do a partial sort? If not, what is a good way to implement it?
Given an unsorted array of N elements, I would like to find K elements that are minimal with respect to some weighting function. K is much smaller than N, so it would be inefficient to sort the whole array and take the first K elements.
I would be happy even if there was something non-standard, browser-dependent. I could still fallback to the custom JavaScript implementation.
PS: This is my current custom implementation (without taking a weighting function into account, just sorting the elements as they are for simplicity):
function bisect(items, x, lo, hi) {
var mid;
if (typeof(lo) == 'undefined') lo = 0;
if (typeof(hi) == 'undefined') hi = items.length;
while (lo < hi) {
mid = Math.floor((lo + hi) / 2);
if (x < items[mid]) hi = mid;
else lo = mid + 1;
}
return lo;
}
function insort(items, x) {
items.splice(bisect(items, x), 0, x);
}
function partialSort(items, k) {
var smallest = [];
for (var i = 0, len = items.length; i < len; ++i) {
var item = items[i];
if (smallest.length < k || item < smallest[smallest.length - 1]) {
insort(smallest, item);
if (smallest.length > k)
smallest.splice(k, 1);
}
}
return smallest;
}
console.log(partialSort([5, 4, 3, 2, 1, 6, 7, 8, 1, 9], 3));
The algorithm walks through the given array one single time, keeping track of a sorted list of the k smallest items so far, using binary search to insert new elements.
Please post alternative solutions if you think they might be faster or more elegant. Timings are very welcome.

No. There's only the full array sort, so you will need to use your own implementation.
Little improvement on your code (I had thought of exactly the same algorithm :-)):
function partialSort(items, k) {
var smallest = items.slice(0, k).sort(),
max = smallest[k-1];
for (var i = k, len = items.length; i < len; ++i) {
var item = items[i];
if (item < max) {
insort(smallest, item);
smallest.length = k;
max = smallest[k-1];
}
}
return smallest;
}
(Even seems to be a little faster, I guess due to caching the max variable)

For relatively small k it can be worth it to implement a Max Heap (by lack of a native one in JavaScript):
Create a Max Heap of the first k values
For each remaining value:
If it is less than the root of the heap, replace the root with this value. Otherwise ignore the value. Note that the heap never changes in size.
Finally sort the heap and return it.
This is in fact an improvement on another idea using a Min Heap, but that one needs to heapify the whole array, and so will not run as fast. After heapifying the whole array, you just extract k times a value from that heap, and return those values.
I have added both solutions to Bergi's jsperf.com performance tests (copied to jsbench.me). For that particular test (5000 array values, k = 10), the Max Heap solution is faster. But this advantage will shrink as k is increased.
Here is the code for the Max Heap solution:
// A few Heap-functions that operate on an array
function maxSiftDown(arr, i=0, value=arr[i]) {
if (i >= arr.length) return;
while (true) {
var j = i*2+1;
if (j+1 < arr.length && arr[j] < arr[j+1]) j++;
if (j >= arr.length || value >= arr[j]) break;
arr[i] = arr[j];
i = j;
}
arr[i] = value;
}
function maxHeapify(arr) {
for (var i = arr.length>>1; i--; ) maxSiftDown(arr, i);
return arr;
}
// The main algorithm
function partialSortWithMaxHeap(items, k) {
var heap = maxHeapify(items.slice(0, k));
for (var i = k, len = items.length; i < len; ++i) {
var item = items[i];
if (item < heap[0]) maxSiftDown(heap, 0, item);
}
return heap.sort((a,b) => a-b);
}
// Sample data & call
var arr = Array.from({length:5000}, () => Math.floor(Math.random() * 1e5));
console.log(partialSortWithMaxHeap(arr, 10));

There's no native partial sort function. The closest thing to what you want is Array.filter.
function isSmallEnough(element, index, array) {
return (element <= 10);
}
var filtered = [12, 5, 8, 130, 44].filter(isSmallEnough);
// filtered is [5, 8]
The example was borrowed (and slightly modified) from the above link.

I made a version than works with objects, like Array.sort(f):
function partialSort(items, k,f) {
function bisect(items, x, lo, hi) {
var mid;
if (typeof(lo) == 'undefined') lo = 0;
if (typeof(hi) == 'undefined') hi = items.length;
while (lo < hi) {
mid = Math.floor((lo + hi) / 2);
if (0>f(x,items[mid])) hi = mid;
else lo = mid + 1;
}
return lo;
}
function insort(items, x) {
items.splice(bisect(items, x), 0, x);
}
var smallest = items.slice(0, k).sort(f),
max = smallest[k-1];
for (var i = k, len = items.length; i < len; ++i) {
var item = items[i];
if (0>f(item,max)) {
insort(smallest, item);
smallest.length = k;
max = smallest[k-1];
}
}
return smallest;
}
// [ { e: 1 }, { e: 1 }, { e: 2 } ]
console.log(partialSort([{e:4},{e:6},{e:1},{e:8},{e:3},{e:1},{e:6},{e:2}],3,(a,b)=>a.e-b.e))
console.log()

In the code block below, the nisetamafibo function keeps an array of the smallest items found so far. The array is sorted and truncated to length K after a certain number of new items have been added to the array, where the number is taken from the Fibonacci sequence so that it is first 1, next 1, then 2, then 3, then 5, and so on. The nisetamadouble method doubles the interval after which the array is sorted instead, so that it is first 1, then 2, then 4, and so on. (I also tried the approach that I sorted the array each time after a fixed number of new items like 10 had been added, but it was slower. And I also tried to initialize the array at the start of the function so that I took in a fixed number of the first items of the input and sorted them, but I found that initializing the array with 1 or 0 items was the fastest, so I removed the initialization step.)
The nisetamainsertion function uses insertion sort to sort the items. It's very slow at high K-values because insertion sort has quadratic time complexity, but it's fast at K-values of around 10 to 100 or lower, because insertion sort is fast for short arrays. The nisetamachoose method chooses nisetamainsertion for K-values of 100 or less but nisetamafibo otherwise. (In the Java JDK, the file DualPivotQuicksort.java uses insertion sort instead of quicksort for arrays with less than 47 items. A presentation about sorting algorithms in R said that "fastest for < 30 items is insert sort".)
I also tried to implement the quickselect algorithm with and without recursion. The version that didn't use recursion was a bit faster, but both versions were still slow compared to other methods especially in cases where N was high and K was low.
On another Stack Exchange site, someone came up with new variants of the Floyd-Rivest algorithm which were faster than the regular Floyd-Rivest algorithm in C: https://softwareengineering.stackexchange.com/questions/284767/kth-selection-routine-floyd-algorithm-489. I tried to implement the variant called select7MO3 in JavaScript, but it ended up being one of the slowest options in my benchmark.
function nisetamafibo(a,k=1){
let found=[],len=a.length,unsorted=0,biggestfound=Infinity,nextsort=1,prevsort=1,oldsort
for(let i=0;i<len;i++){
if(a[i]<biggestfound||i<k){
found.push(a[i])
if(++unsorted==nextsort){
found.sort((l,r)=>l<r?-1:l>r?1:0)
found=found.slice(0,k)
biggestfound=found[found.length-1]
oldsort=nextsort;nextsort+=prevsort;prevsort=oldsort
unsorted=0
}
}
}
found.sort((l,r)=>l<r?-1:l>r?1:0)
return found.slice(0,k)
}
function nisetamadouble(a,k=1){
let found=[],len=a.length,unsorted=0,biggestfound=Infinity,nextsort=1
for(let i=0;i<len;i++){
if(a[i]<biggestfound||i<k){
found.push(a[i])
if(++unsorted==nextsort){
found.sort((l,r)=>l<r?-1:l>r?1:0)
found=found.slice(0,k)
biggestfound=found[found.length-1]
nextsort*=2
unsorted=0
}
}
}
found.sort((l,r)=>l<r?-1:l>r?1:0)
return found.slice(0,k)
}
function nisetamainsertion(a,k=1){
let found=a.slice(0,k),l=a.length
found.sort((l,r)=>l<r?-1:l>r?1:0)
let biggestfound=found[k-1]
for(let i=0;i<l;i++){
let v=a[i]
if(v<biggestfound){
let insertat=k-1
for(let j=0;j<k-1;j++)if(v<found[j]||j==i){insertat=j;break}
for(let j=k-1;j>insertat;j--)found[j]=found[j-1]
found[insertat]=v
biggestfound=found[k-1]
}
}
return found
}
function nisetamachoose(a,k=1){
return k<=100?nisetamainsertion(a,k):nisetamafibo(a,k)
}
function quickselect(a,k,l,r){
l=l||0
r=r||a.length-1
while(true){
let pivot=a[r],pos=l
for(let i=l;i<=r;i++)if(a[i]<pivot){let temp=a[i];a[i]=a[pos];a[pos++]=temp}
let temp=a[r];a[r]=a[pos];a[pos]=temp
if(pos==k)break
pos<k?l=pos+1:r=pos-1
}
}
function quickselectrecursive(a,k,l,r){
l=l||0
r=r||a.length-1
let pivot=a[r],pos=l
for(let i=l;i<=r;i++)if(a[i]<pivot){let temp=a[i];a[i]=a[pos];a[pos++]=temp}
let temp=a[r];a[r]=a[pos];a[pos]=temp
if(pos<k)quickselectrecursive(a,pos+1,r,k)
if(pos>k)quickselectrecursive(a,l,pos-1,k)
}
function sortslice(a,k){
a.sort((l,r)=>l<r?-1:l>r?1:0)
return a.slice(0,k)
}
// https://softwareengineering.stackexchange.com/questions/284767/kth-selection-routine-floyd-algorithm-489
function select7MO3(a,k){
let l=0,i,r=a.length-1,rr=r,ll=l
while(r>l){
if(a[k]<a[l]){let t=a[l];a[l]=a[k];a[k]=t}
if(a[r]<a[l]){let t=a[l];a[l]=a[r];a[r]=t}
if(a[r]<a[k]){let t=a[k];a[k]=a[r];a[r]=t}
if((r-l)>k){
let n=r-l+1
i=k-l+1
let s=(2*n/3)
let div=i-n
let sd=(n*s*(n-s)/n)*(div<0?-1:div>0?1:0)
ll=Math.max(l,k-i*s/n+sd)
rr=Math.min(r,k+(n-i)*s/n+sd)
}
let pivot=a[k]
i=l
let j=r
let t=a[l];a[l]=a[k];a[k]=t
if(a[r]>pivot){t=a[r];a[r]=a[l];a[l]=t}
while(i<j){
let t=a[i];a[i]=a[j];a[j]=t
i++
j--
while(a[i]<pivot)i++
while(a[j]>pivot)j--
}
if(a[l]==pivot){i--;let t=a[l];a[l]=a[j];a[j]=t}
else{j++;let t=a[j];a[j]=a[r];a[r]=t}
if(j<=k)l=j+1
else if(k<=j)r=j-1
}
let out=a.slice(0,k)
out.sort((l,r)=>l<r?-1:l>r?1:0)
return out
}
// OP and Bergi
function bisect(items, x, lo, hi) {
var mid;
if (typeof(lo) == 'undefined') lo = 0;
if (typeof(hi) == 'undefined') hi = items.length;
while (lo < hi) {
mid = Math.floor((lo + hi) / 2);
if (x < items[mid]) hi = mid;
else lo = mid + 1;
}
return lo;
}
function insort(items, x) {
items.splice(bisect(items, x), 0, x);
}
function OP(items, k) {
var smallest = [];
for (var i = 0, len = items.length; i < len; ++i) {
var item = items[i];
if (smallest.length < k || item < smallest[smallest.length - 1]) {
insort(smallest, item);
if (smallest.length > k)
smallest.splice(k, 1);
}
}
return smallest;
}
function OP_Bergi(items, k) {
var smallest = items.slice(0, k).sort(),
max = smallest[k-1];
for (var i = k, len = items.length; i < len; ++i) {
var item = items[i];
if (item < max) {
insort(smallest, item);
smallest.length = k;
max = smallest[k-1];
}
}
return smallest;
}
// trincot
function maxSiftDown(arr, i=0, value=arr[i]) {
if (i >= arr.length) return;
while (true) {
var j = i*2+1;
if (j+1 < arr.length && arr[j] < arr[j+1]) j++;
if (j >= arr.length || value >= arr[j]) break;
arr[i] = arr[j];
i = j;
}
arr[i] = value;
}
function maxHeapify(arr) {
for (var i = arr.length>>1; i--; ) maxSiftDown(arr, i);
return arr;
}
function trincot_MaxHeap(items, k) {
var heap = maxHeapify(items.slice(0, k));
for (var i = k, len = items.length; i < len; ++i) {
var item = items[i];
if (item < heap[0]) maxSiftDown(heap, 0, item);
}
return heap.sort((a,b) => a-b);
}
// DiazJara
function DiazJara(items, k,f) {
function bisect(items, x, lo, hi) {
var mid;
if (typeof(lo) == 'undefined') lo = 0;
if (typeof(hi) == 'undefined') hi = items.length;
while (lo < hi) {
mid = Math.floor((lo + hi) / 2);
if (0>f(x,items[mid])) hi = mid;
else lo = mid + 1;
}
return lo;
}
function insort(items, x) {
items.splice(bisect(items, x), 0, x);
}
var smallest = items.slice(0, k).sort(f),
max = smallest[k-1];
for (var i = k, len = items.length; i < len; ++i) {
var item = items[i];
if (0>f(item,max)) {
insort(smallest, item);
smallest.length = k;
max = smallest[k-1];
}
}
return smallest;
}
// benchmark
for(let nk of'31 33 40 42 44 51 53 55 60 62 64 66 71 73 75'.split(' ')){
let n=parseInt(nk[0]),k0=parseInt(nk[1]),k=10**k0
let opt=[
'OP(a,k)',
'OP_Bergi(a,k)',
'trincot_MaxHeap(a,k)',
'DiazJara(a,k,(l,r)=>l-r)',
'DiazJara(a,k,(l,r)=>l<r?-1:l>r?1:0)',
'nisetamafibo(a,k)',
'nisetamadouble(a,k)',
// 'nisetamainsertion(a,k)', // this would've taken too long to run at K=1e6
'nisetamachoose(a,k)',
'quickselect(a,k);a=a.slice(0,k);a.sort((l,r)=>l<r?-1:l>r?1:0)',
'quickselectrecursive(a,k);a=a.slice(0,k);a.sort((l,r)=>l<r?-1:l>r?1:0)',
'select7MO3(a,k);a=a.slice(0,k);a.sort((l,r)=>l<r?-1:l>r?1:0)',
'sortslice(a,k)'
]
let ord=Array.from({length:100},()=>Array(opt.length).fill().map((_,i)=>i)).flat()
ord.sort(()=>Math.random()-.5)
for(let x of ord){
let o=opt[x]
let a=Array.from({length:10**n},()=>Math.random())
let t1=process.hrtime.bigint()
eval(o)
let t2=process.hrtime.bigint()-t1
console.log(n+' '+k0+' '+o+' '+t2)
}
}
This shows the median time of a hundred runs in ms and the average rank of each method (where for example 7/4 means that N was 1e7 and K was 1e4):
For most combinations of N and K, Bergi's modified version of the OP's code was actually slower than the OP's code, even though the OP's code was extremely slow in the case where N and K were both 1e6.
(l,r)=>l<r?-1:l>r?1:0 is faster than (l,r)=>l-r as you can see by comparing the two versions of Díaz-Jara's method above.
Here's also versions of my nisetamadouble and nisetamainsertion methods which return the indexes of the smallest items in addition to the values:
let a=Array.from({length:1e5},()=>Math.random())
let k=10
let l=a.length
let biggestfound=Infinity,foundind=[],foundval=[]
for(let i=0;i<l;i++){
let v=a[i]
if(i<k||v<biggestfound){
let insertat=k-1
for(let j=0;j<k-1;j++)if(v<foundval[j]||j==i){insertat=j;break}
for(let j=k-1;j>insertat;j--){foundind[j]=foundind[j-1];foundval[j]=foundval[j-1]}
foundind[insertat]=i
foundval[insertat]=v
biggestfound=foundval[k-1]
}
}
console.log(foundind)
console.log(foundval)
function nisetama(a,k=1){
let found=[],len=a.length,unsorted=0,biggestfound=Infinity,nextsort=1
for(let i=0;i<len;i++){
if(a[i]<biggestfound||i<k){
found.push(a[i])
if(++unsorted==nextsort){
found.sort((l,r)=>l<r?-1:l>r?1:0)
found=found.slice(0,k)
biggestfound=found[found.length-1]
nextsort*=2
unsorted=0
}
}
}
found.sort((l,r)=>l<r?-1:l>r?1:0)
return found.slice(0,k)
}
let a2=a
nisetama(a2,k)
biggestfound=a2[k-1],foundind=[]
for(let i=0;i<l;i++)if(a[i]<=biggestfound)foundind.push(i)
foundind.sort((l,r)=>a[l]<a[r]?-1:a[l]>a[r]?1:0)
foundind=foundind.slice(0,k)
console.log(foundind)
console.log(foundval)