After having a long difficult coding challenge, there was a problem that bugged me. I thought about it for an adequate time but couldn't find the way to solve it. Here, I am providing a problem and example below.
Input
v : an array of numbers.
q : 2 dimensional array with 3 elements in nested array.
Description
v is an array and q is a commands that does different thing according to its nested element.
if first element of nested array is 1 => second and third element of the nested array becomes the index and it returns sum[second:third+1] (As you can see, it is inclusive)
if first element of nested array is 2 => element of second index becomes the third. same as v[second] = third
Input example
v : [1,2,3,4,5]
q : [[1,2,4], [2,3,8], [1,2,4]]
Example
With a provided example, it goes like
command is [1,2,4] => first element is 1. it should return sum from v[2] to v[4] (inclusive) => 12.
command is [2,3,8] => first element is 2. it switches v[3] to 8. (now v is [1,2,3,8,5])
command is [1,2,4] => first element is 1. it should return sum from v[2] to v[4] (inclusive) => 16, as the third index has been changed from the previous command.
So the final answer is [12, 16]
Question.
The code below is how I solved, however, this is O(n**2) complexity. I wonder how I can reduce the time complexity in this case.
I tried making a hash object, but it didn't work. I can't think of a good way to make a cache in this case.
function solution(v, q) {
let answer = [];
for (let i = 0; i < q.length; i++) {
let [a, b, c] = q[i];
if (a === 1) {
let sum = 0;
for (let i = b; i <= c; i++) {
sum += v[i];
}
answer.push(sum);
} else if (a === 2) {
v[b] = c;
}
}
return answer;
}
This type of problem can typically be solved more efficiently with a Fenwick tree
Here is an implementation:
class BinaryIndexedTree extends Array {
constructor(length) {
super(length + 1);
this.fill(0);
}
add(i, delta) {
i++; // make index 1-based
while (i < this.length) {
this[i] += delta;
i += i & -i; // add least significant bit
}
}
sumUntil(i) {
i++; // make index 1-based
let sum = 0;
while (i) {
sum += this[i];
i -= i & -i;
}
return sum;
}
}
function solution(values, queries) {
const tree = new BinaryIndexedTree(values.length);
values.forEach((value, i) => tree.add(i, value));
const answer = [];
for (const [a, b, c] of queries) {
if (a === 1) {
answer.push(tree.sumUntil(c) - tree.sumUntil(b - 1));
} else {
tree.add(b, c - values[b]);
values[b] = c;
}
}
return answer;
}
let answer = solution([1,2,3,4,5], [[1,2,4], [2,3,8], [1,2,4]]);
console.log(answer);
Time Complexity
The time complexity of running tree.add or tree.sumUntil once is O(logπ), where π is the size of the input values (values.length). So this is also the time complexity of running one query.
The creation of the tree costs O(π), as this is the size of the tree
The initialisation of the tree with values costs O(πlogπ), as really each value in the input acts as a query that updates a value from 0 to the actual value.
Executing the queries costs O(πlogπ) where π is the number of queries (queries.length)
So in total, we have a time complexity of O(π + πlogπ + πlogπ) = O((π+π)logπ)
Further reading
For more information on Fenwick trees, see BIT: What is the intuition behind a binary indexed tree and how was it thought about?
How can I generate some unique random numbers between 1 and 100 using JavaScript?
For example: To generate 8 unique random numbers and store them to an array, you can simply do this:
var arr = [];
while(arr.length < 8){
var r = Math.floor(Math.random() * 100) + 1;
if(arr.indexOf(r) === -1) arr.push(r);
}
console.log(arr);
Populate an array with the numbers 1 through 100.
Shuffle it.
Take the first 8 elements of the resulting array.
Modern JS Solution using Set (and average case O(n))
const nums = new Set();
while(nums.size !== 8) {
nums.add(Math.floor(Math.random() * 100) + 1);
}
console.log([...nums]);
Another approach is to generate an 100 items array with ascending numbers and sort it randomly. This leads actually to a really short and (in my opinion) simple snippet.
const numbers = Array(100).fill().map((_, index) => index + 1);
numbers.sort(() => Math.random() - 0.5);
console.log(numbers.slice(0, 8));
Generate permutation of 100 numbers and then choose serially.
Use Knuth Shuffle(aka the Fisher-Yates shuffle) Algorithm.
JavaScript:
function fisherYates ( myArray,stop_count ) {
var i = myArray.length;
if ( i == 0 ) return false;
int c = 0;
while ( --i ) {
var j = Math.floor( Math.random() * ( i + 1 ) );
var tempi = myArray[i];
var tempj = myArray[j];
myArray[i] = tempj;
myArray[j] = tempi;
// Edited thanks to Frerich Raabe
c++;
if(c == stop_count)return;
}
}
CODE COPIED FROM LINK.
EDIT:
Improved code:
function fisherYates(myArray,nb_picks)
{
for (i = myArray.length-1; i > 1 ; i--)
{
var r = Math.floor(Math.random()*i);
var t = myArray[i];
myArray[i] = myArray[r];
myArray[r] = t;
}
return myArray.slice(0,nb_picks);
}
Potential problem:
Suppose we have array of 100 numbers {e.g. [1,2,3...100]} and we stop swapping after 8 swaps;
then most of the times array will look like {1,2,3,76,5,6,7,8,...numbers here will be shuffled ...10}.
Because every number will be swapped with probability 1/100 so
prob. of swapping first 8 numbers is 8/100 whereas prob. of swapping other 92 is 92/100.
But if we run algorithm for full array then we are sure (almost)every entry is swapped.
Otherwise we face a question : which 8 numbers to choose?
The above techniques are good if you want to avoid a library, but depending if you would be alright with a library, I would suggest checking out Chance for generating random stuff in JavaScript.
Specifically to solve your question, using Chance it's as easy as:
// One line!
var uniques = chance.unique(chance.natural, 8, {min: 1, max: 100});
// Print it out to the document for this snippet so we can see it in action
document.write(JSON.stringify(uniques));
<script src="http://chancejs.com/chance.min.js"></script>
Disclaimer, as the author of Chance, I am a bit biased ;)
To avoid any long and unreliable shuffles, I'd do the following...
Generate an array that contains the number between 1 and 100, in order.
Generate a random number between 1 and 100
Look up the number at this index in the array and store in your results
Remove the elemnt from the array, making it one shorter
Repeat from step 2, but use 99 as the upper limit of the random number
Repeat from step 2, but use 98 as the upper limit of the random number
Repeat from step 2, but use 97 as the upper limit of the random number
Repeat from step 2, but use 96 as the upper limit of the random number
Repeat from step 2, but use 95 as the upper limit of the random number
Repeat from step 2, but use 94 as the upper limit of the random number
Repeat from step 2, but use 93 as the upper limit of the random number
Voila - no repeated numbers.
I may post some actual code later, if anybody is interested.
Edit: It's probably the competitive streak in me but, having seen the post by #Alsciende, I couldn't resist posting the code that I promised.
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2 Final//EN">
<html>
<head>
<title>8 unique random number between 1 and 100</title>
<script type="text/javascript" language="Javascript">
function pick(n, min, max){
var values = [], i = max;
while(i >= min) values.push(i--);
var results = [];
var maxIndex = max;
for(i=1; i <= n; i++){
maxIndex--;
var index = Math.floor(maxIndex * Math.random());
results.push(values[index]);
values[index] = values[maxIndex];
}
return results;
}
function go(){
var running = true;
do{
if(!confirm(pick(8, 1, 100).sort(function(a,b){return a - b;}))){
running = false;
}
}while(running)
}
</script>
</head>
<body>
<h1>8 unique random number between 1 and 100</h1>
<p><button onclick="go()">Click me</button> to start generating numbers.</p>
<p>When the numbers appear, click OK to generate another set, or Cancel to stop.</p>
</body>
I would do this:
function randomInt(min, max) {
return Math.round(min + Math.random()*(max-min));
}
var index = {}, numbers = [];
for (var i=0; i<8; ++i) {
var number;
do {
number = randomInt(1, 100);
} while (index.hasOwnProperty("_"+number));
index["_"+number] = true;
numbers.push(number);
}
delete index;
This is a very generic function I have written to generate random unique/non-unique integers for an array. Assume the last parameter to be true in this scenario for this answer.
/* Creates an array of random integers between the range specified
len = length of the array you want to generate
min = min value you require
max = max value you require
unique = whether you want unique or not (assume 'true' for this answer)
*/
function _arrayRandom(len, min, max, unique) {
var len = (len) ? len : 10,
min = (min !== undefined) ? min : 1,
max = (max !== undefined) ? max : 100,
unique = (unique) ? unique : false,
toReturn = [], tempObj = {}, i = 0;
if(unique === true) {
for(; i < len; i++) {
var randomInt = Math.floor(Math.random() * ((max - min) + min));
if(tempObj['key_'+ randomInt] === undefined) {
tempObj['key_'+ randomInt] = randomInt;
toReturn.push(randomInt);
} else {
i--;
}
}
} else {
for(; i < len; i++) {
toReturn.push(Math.floor(Math.random() * ((max - min) + min)));
}
}
return toReturn;
}
Here the 'tempObj' is a very useful obj since every random number generated will directly check in this tempObj if that key already exists, if not, then we reduce the i by one since we need 1 extra run since the current random number already exists.
In your case, run the following
_arrayRandom(8, 1, 100, true);
That's all.
Shuffling the numbers from 1 to 100 is the right basic strategy, but if you need only 8 shuffled numbers, there's no need to shuffle all 100 numbers.
I don't know Javascript very well, but I believe it's easy to create an array of 100 nulls quickly. Then, for 8 rounds, you swap the n'th element of the array (n starting at 0) with a randomly selected element from n+1 through 99. Of course, any elements not populated yet mean that the element would really have been the original index plus 1, so that's trivial to factor in. When you're done with the 8 rounds, the first 8 elements of your array will have your 8 shuffled numbers.
var arr = []
while(arr.length < 8){
var randomnumber=Math.ceil(Math.random()*100)
if(arr.indexOf(randomnumber) === -1){arr.push(randomnumber)}
}
document.write(arr);
shorter than other answers I've seen
Implementing this as a generator makes it pretty nice to work with. Note, this implementation differs from ones that require the entire input array to be shuffled first.
This sample function works lazily, giving you 1 random item per iteration up to N items you ask for. This is nice because if you just want 3 items from a list of 1000, you don't have to touch all 1000 items first.
// sample :: Integer -> [a] -> [a]
const sample = n => function* (xs) {
let ys = xs.slice(0);
let len = xs.length;
while (n > 0 && len > 0) {
let i = (Math.random() * len) >> 0;
yield ys.splice(i,1)[0];
n--; len--;
}
}
// example inputs
let items = ['a', 'b', 'c', 'd', 'e', 'f', 'g'];
let numbers = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9];
// get 3 random items
for (let i of sample(3) (items))
console.log(i); // f g c
// partial application
const lotto = sample(3);
for (let i of lotto(numbers))
console.log(i); // 3 8 7
// shuffle an array
const shuffle = xs => Array.from(sample (Infinity) (xs))
console.log(shuffle(items)) // [b c g f d e a]
I chose to implement sample in a way that does not mutate the input array, but you could easily argue that a mutating implementation is favourable.
For example, the shuffle function might wish to mutate the original input array. Or you might wish to sample from the same input at various times, updating the input each time.
// sample :: Integer -> [a] -> [a]
const sample = n => function* (xs) {
let len = xs.length;
while (n > 0 && len > 0) {
let i = (Math.random() * len) >> 0;
yield xs.splice(i,1)[0];
n--; len--;
}
}
// deal :: [Card] -> [Card]
const deal = xs => Array.from(sample (2) (xs));
// setup a deck of cards (13 in this case)
// cards :: [Card]
let cards = 'A234567890JQK'.split('');
// deal 6 players 2 cards each
// players :: [[Card]]
let players = Array.from(Array(6), $=> deal(cards))
console.log(players);
// [K, J], [6, 0], [2, 8], [Q, 7], [5, 4], [9, A]
// `cards` has been mutated. only 1 card remains in the deck
console.log(cards);
// [3]
sample is no longer a pure function because of the array input mutation, but in certain circumstances (demonstrated above) it might make more sense.
Another reason I chose a generator instead of a function that just returns an array is because you may want to continue sampling until some specific condition.
Perhaps I want the first prime number from a list of 1,000,000 random numbers.
"How many should I sample?" β you don't have to specify
"Do I have to find all the primes first and then select a random prime?" β Nope.
Because we're working with a generator, this task is trivial
const randomPrimeNumber = listOfNumbers => {
for (let x of sample(Infinity) (listOfNumbers)) {
if (isPrime(x))
return x;
}
return NaN;
}
This will continuously sample 1 random number at a time, x, check if it's prime, then return x if it is. If the list of numbers is exhausted before a prime is found, NaN is returned.
Note:
This answer was originally shared on another question that was closed as a duplicate of this one. Because it's very different from the other solutions provided here, I've decided to share it here as well
var numbers = [];
for (let i = 0; i < 8; i++) {
let a = true,
n;
while(a) {
n = Math.floor(Math.random() * 100) + 1;
a = numbers.includes(n);
}
numbers.push(n);
}
console.log(numbers);
Same permutation algorithm as The Machine Charmer, but with a prototyped implementation. Better suited to large number of picks. Uses js 1.7 destructuring assignment if available.
// swaps elements at index i and j in array this
// swapping is easy on js 1.7 (feature detection)
Array.prototype.swap = (function () {
var i=0, j=1;
try { [i,j]=[j,i]; }
catch (e) {}
if(i) {
return function(i,j) {
[this[i],this[j]] = [this[j],this[i]];
return this;
}
} else {
return function(i,j) {
var temp = this[i];
this[i] = this[j];
this[j] = temp;
return this;
}
}
})();
// shuffles array this
Array.prototype.shuffle = function() {
for(var i=this.length; i>1; i--) {
this.swap(i-1, Math.floor(i*Math.random()));
}
return this;
}
// returns n unique random numbers between min and max
function pick(n, min, max) {
var a = [], i = max;
while(i >= min) a.push(i--);
return a.shuffle().slice(0,n);
}
pick(8,1,100);
Edit:
An other proposition, better suited to small number of picks, based on belugabob's answer. To guarantee uniqueness, we remove the picked numbers from the array.
// removes n random elements from array this
// and returns them
Array.prototype.pick = function(n) {
if(!n || !this.length) return [];
var i = Math.floor(this.length*Math.random());
return this.splice(i,1).concat(this.pick(n-1));
}
// returns n unique random numbers between min and max
function pick(n, min, max) {
var a = [], i = max;
while(i >= min) a.push(i--);
return a.pick(n);
}
pick(8,1,100);
for arrays with holes like this [,2,,4,,6,7,,]
because my problem was to fill these holes. So I modified it as per my need :)
the following modified solution worked for me :)
var arr = [,2,,4,,6,7,,]; //example
while(arr.length < 9){
var randomnumber=Math.floor(Math.random()*9+1);
var found=false;
for(var i=0;i<arr.length;i++){
if(arr[i]==randomnumber){found=true;break;}
}
if(!found)
for(k=0;k<9;k++)
{if(!arr[k]) //if it's empty !!MODIFICATION
{arr[k]=randomnumber; break;}}
}
alert(arr); //outputs on the screen
The best earlier answer is the answer by sje397. You will get as good random numbers as you can get, as quick as possible.
My solution is very similar to his solution. However, sometimes you want the random numbers in random order, and that is why I decided to post an answer. In addition, I provide a general function.
function selectKOutOfN(k, n) {
if (k>n) throw "k>n";
var selection = [];
var sorted = [];
for (var i = 0; i < k; i++) {
var rand = Math.floor(Math.random()*(n - i));
for (var j = 0; j < i; j++) {
if (sorted[j]<=rand)
rand++;
else
break;
}
selection.push(rand);
sorted.splice(j, 0, rand);
}
return selection;
}
alert(selectKOutOfN(8, 100));
Here is my ES6 version I cobbled together. I'm sure it can be a little more consolidated.
function randomArray(i, min, max) {
min = Math.ceil(min);
max = Math.floor(max);
let arr = Array.from({length: i}, () => Math.floor(Math.random()* (max - min)) + min);
return arr.sort();
}
let uniqueItems = [...new Set(randomArray(8, 0, 100))]
console.log(uniqueItems);
How about using object properties as a hash table? This way your best scenario is to only randomize 8 times. It would only be effective if you want a small part of the range of numbers. It's also much less memory intensive than Fisher-Yates because you don't have to allocate space for an array.
var ht={}, i=rands=8;
while ( i>0 || keys(ht).length<rands) ht[Math.ceil(Math.random()*100)]=i--;
alert(keys(ht));
I then found out that Object.keys(obj) is an ECMAScript 5 feature so the above is pretty much useless on the internets right now. Fear not, because I made it ECMAScript 3 compatible by adding a keys function like this.
if (typeof keys == "undefined")
{
var keys = function(obj)
{
props=[];
for (k in ht) if (ht.hasOwnProperty(k)) props.push(k);
return props;
}
}
var bombout=0;
var checkArr=[];
var arr=[];
while(arr.length < 8 && bombout<100){
bombout++;
var randomNumber=Math.ceil(Math.random()*100);
if(typeof checkArr[randomNumber] == "undefined"){
checkArr[randomNumber]=1;
arr.push(randomNumber);
}
}β
// untested - hence bombout
if you need more unique you must generate a array(1..100).
var arr=[];
function generateRandoms(){
for(var i=1;i<=100;i++) arr.push(i);
}
function extractUniqueRandom()
{
if (arr.length==0) generateRandoms();
var randIndex=Math.floor(arr.length*Math.random());
var result=arr[randIndex];
arr.splice(randIndex,1);
return result;
}
function extractUniqueRandomArray(n)
{
var resultArr=[];
for(var i=0;i<n;i++) resultArr.push(extractUniqueRandom());
return resultArr;
}
above code is faster:
extractUniqueRandomArray(50)=>
[2, 79, 38, 59, 63, 42, 52, 22, 78, 50, 39, 77, 1, 88, 40, 23, 48, 84, 91, 49, 4, 54, 93, 36, 100, 82, 62, 41, 89, 12, 24, 31, 86, 92, 64, 75, 70, 61, 67, 98, 76, 80, 56, 90, 83, 44, 43, 47, 7, 53]
Adding another better version of same code (accepted answer) with JavaScript 1.6 indexOf function. Do not need to loop thru whole array every time you are checking the duplicate.
var arr = []
while(arr.length < 8){
var randomnumber=Math.ceil(Math.random()*100)
var found=false;
if(arr.indexOf(randomnumber) > -1){found=true;}
if(!found)arr[arr.length]=randomnumber;
}
Older version of Javascript can still use the version at top
PS: Tried suggesting an update to the wiki but it was rejected. I still think it may be useful for others.
This is my personal solution :
<script>
var i, k;
var numbers = new Array();
k = Math.floor((Math.random()*8));
numbers[0]=k;
for (var j=1;j<8;j++){
k = Math.floor((Math.random()*8));
i=0;
while (i < numbers.length){
if (numbers[i] == k){
k = Math.floor((Math.random()*8));
i=0;
}else {i++;}
}
numbers[j]=k;
}
for (var j=0;j<8;j++){
alert (numbers[j]);
}
</script>
It randomly generates 8 unique array values (between 0 and 7), then displays them using an alert box.
function getUniqueRandomNos() {
var indexedArrayOfRandomNo = [];
for (var i = 0; i < 100; i++) {
var randNo = Math.random();
indexedArrayOfRandomNo.push([i, randNo]);
}
indexedArrayOfRandomNo.sort(function (arr1, arr2) {
return arr1[1] - arr2[1]
});
var uniqueRandNoArray = [];
for (i = 0; i < 8; i++) {
uniqueRandNoArray.push(indexedArrayOfRandomNo[i][0]);
}
return uniqueRandNoArray;
}
I think this method is different from methods given in most of the answers, so I thought I might add an answer here (though the question was asked 4 years ago).
We generate 100 random numbers, and tag each of them with numbers from 1 to 100. Then we sort these tagged random numbers, and the tags get shuffled randomly. Alternatively, as needed in this question, one could do away with just finding top 8 of the tagged random numbers. Finding top 8 items is cheaper than sorting the whole array.
One must note here, that the sorting algorithm influences this algorithm. If the sorting algorithm used is stable, there is slight bias in favor of smaller numbers. Ideally, we would want the sorting algorithm to be unstable and not even biased towards stability (or instability) to produce an answer with perfectly uniform probability distribution.
This can handle generating upto 20 digit UNIQUE random number
JS
var generatedNumbers = [];
function generateRandomNumber(precision) { // input --> number precision in integer
if (precision <= 20) {
var randomNum = Math.round(Math.random().toFixed(precision) * Math.pow(10, precision));
if (generatedNumbers.indexOf(randomNum) > -1) {
if (generatedNumbers.length == Math.pow(10, precision))
return "Generated all values with this precision";
return generateRandomNumber(precision);
} else {
generatedNumbers.push(randomNum);
return randomNum;
}
} else
return "Number Precision shoould not exceed 20";
}
generateRandomNumber(1);
jsFiddle
This solution uses the hash which is much more performant O(1) than checking if the resides in the array. It has extra safe checks too. Hope it helps.
function uniqueArray(minRange, maxRange, arrayLength) {
var arrayLength = (arrayLength) ? arrayLength : 10
var minRange = (minRange !== undefined) ? minRange : 1
var maxRange = (maxRange !== undefined) ? maxRange : 100
var numberOfItemsInArray = 0
var hash = {}
var array = []
if ( arrayLength > (maxRange - minRange) ) throw new Error('Cannot generate unique array: Array length too high')
while(numberOfItemsInArray < arrayLength){
// var randomNumber = Math.floor(Math.random() * (maxRange - minRange + 1) + minRange)
// following line used for performance benefits
var randomNumber = (Math.random() * (maxRange - minRange + 1) + minRange) << 0
if (!hash[randomNumber]) {
hash[randomNumber] = true
array.push(randomNumber)
numberOfItemsInArray++
}
}
return array
}
document.write(uniqueArray(1, 100, 8))
You can also do it with a one liner like this:
[...((add, set) => add(set, add))((set, add) => set.size < 8 ? add(set.add(Math.floor(Math.random()*100) + 1), add) : set, new Set())]
getRandom (min, max) {
return Math.floor(Math.random() * (max - min)) + min
}
getNRandom (min, max, n) {
const numbers = []
if (min > max) {
return new Error('Max is gt min')
}
if (min === max) {
return [min]
}
if ((max - min) >= n) {
while (numbers.length < n) {
let rand = this.getRandom(min, max + 1)
if (numbers.indexOf(rand) === -1) {
numbers.push(rand)
}
}
}
if ((max - min) < n) {
for (let i = min; i <= max; i++) {
numbers.push(i)
}
}
return numbers
}
Using a Set is your fastest option. Here is a generic function for getting a unique random that uses a callback generator. Now it's fast and reusable.
// Get a unique 'anything'
let unique = new Set()
function getUnique(generator) {
let number = generator()
while (!unique.add(number)) {
number = generator()
}
return number;
}
// The generator. Return anything, not just numbers.
const between_1_100 = () => 1 + Math.floor(Math.random() * 100)
// Test it
for (var i = 0; i < 8; i++) {
const aNumber = getUnique(between_1_100)
}
// Dump the 'stored numbers'
console.log(Array.from(unique))
This is a implementation of Fisher Yates/Durstenfeld Shuffle, but without actual creation of a array thus reducing space complexity or memory needed, when the pick size is small compared to the number of elements available.
To pick 8 numbers from 100, it is not necessary to create a array of 100 elements.
Assuming a array is created,
From the end of array(100), get random number(rnd) from 1 to 100
Swap 100 and the random number rnd
Repeat step 1 with array(99)
If a array is not created, A hashMap may be used to remember the actual swapped positions. When the second random number generated is equal to the one of the previously generated numbers, the map provides the current value in that position rather than the actual value.
const getRandom_ = (start, end) => {
return Math.floor(Math.random() * (end - start + 1)) + start;
};
const getRealValue_ = (map, rnd) => {
if (map.has(rnd)) {
return getRealValue_(map, map.get(rnd));
} else {
return rnd;
}
};
const getRandomNumbers = (n, start, end) => {
const out = new Map();
while (n--) {
const rnd = getRandom_(start, end--);
out.set(getRealValue_(out, rnd), end + 1);
}
return [...out.keys()];
};
console.info(getRandomNumbers(8, 1, 100));
console.info(getRandomNumbers(8, 1, Math.pow(10, 12)));
console.info(getRandomNumbers(800000, 1, Math.pow(10, 15)));
Here is an example of random 5 numbers taken from a range of 0 to 100 (both 0 and 100 included) with no duplication.
let finals = [];
const count = 5; // Considering 5 numbers
const max = 100;
for(let i = 0; i < max; i++){
const rand = Math.round(Math.random() * max);
!finals.includes(rand) && finals.push(rand)
}
finals = finals.slice(0, count)
I just took a coding test online and this one question really bothered me. My solution was correct but was rejected for being unoptimized. The question is as following:
Write a function combineTheGivenNumber taking two arguments:
numArray: number[]
num: a number
The function should check all the concatenation pairs that can result in making a number equal to num and return their count.
E.g. if numArray = [1, 212, 12, 12] & num = 1212 then we will have return value of 3 from combineTheGivenNumber
The pairs are as following:
numArray[0]+numArray[1]
numArray[2]+numArray[3]
numArray[3]+numArray[2]
The function I wrote for this purpose is as following:
function combineTheGivenNumber(numArray, num) {
//convert all numbers to strings for easy concatenation
numArray = numArray.map(e => e+'');
//also convert the `hay` to string for easy comparison
num = num+'';
let pairCounts = 0;
// itereate over the array to get pairs
numArray.forEach((e,i) => {
numArray.forEach((f,j) => {
if(i!==j && num === (e+f)) {
pairCounts++;
}
});
});
return pairCounts;
}
console.log('Test 1: ', combineTheGivenNumber([1,212,12,12],1212));
console.log('Test 2: ', combineTheGivenNumber([4,21,42,1],421));
From my experience, I know conversion of number to string is slow in JS, but I am not sure whether my approach is wrong/lack of knowledge or does the tester is ignorant of this fact. Can anyone suggest further optimization of the code snipped?
Elimination of string to number to string will be a significant speed boost but I am not sure how to check for concatenated numbers otherwise.
Elimination of string to number to string will be a significant speed boost
No, it won't.
Firstly, you're not converting strings to numbers anywhere, but more importantly the exercise asks for concatenation so working with strings is exactly what you should do. No idea why they're even passing numbers. You're doing fine already by doing the conversion only once for each number input, not every time your form a pair. And last but not least, avoiding the conversion will not be a significant improvement.
To get a significant improvement, you should use a better algorithm. #derpirscher is correct in his comment: "[It's] the nested loop checking every possible combination which hits the time limit. For instance for your example, when the outer loop points at 212 you don't need to do any checks, because regardless, whatever you concatenate to 212, it can never result in 1212".
So use
let pairCounts = 0;
numArray.forEach((e,i) => {
if (num.startsWith(e)) {
//^^^^^^^^^^^^^^^^^^^^^^
numArray.forEach((f,j) => {
if (i !== j && num === e+f) {
pairCounts++;
}
});
}
});
You might do the same with suffixes, but it becomes more complicated to rule out concatenation to oneself there.
Optimising further, you can even achieve a linear complexity solution by putting the strings in a lookup structure, then when finding a viable prefix just checking whether the missing part is an available suffix:
function combineTheGivenNumber(numArray, num) {
const strings = new Map();
for (const num of numArray) {
const str = String(num);
strings.set(str, 1 + (strings.get(str) ?? 0));
}
const whole = String(num);
let pairCounts = 0;
for (const [prefix, pCount] of strings) {
if (!whole.startsWith(prefix))
continue;
const suffix = whole.slice(prefix.length);
if (strings.has(suffix)) {
let sCount = strings.get(suffix);
if (suffix == prefix) sCount--; // no self-concatenation
pairCounts += pCount*sCount;
}
}
return pairCounts;
}
(the proper handling of duplicates is a bit difficile)
I like your approach of going to strings early. I can suggest a couple of simple optimizations.
You only need the numbers that are valid "first parts" and those that are valid "second parts"
You can use the javascript .startsWith and .endsWith to test for those conditions. All other strings can be thrown away.
The lengths of the strings must add up to the length of the desired answer
Suppose your target string is 8 digits long. If you have 2 valid 3-digit "first parts", then you only need to know how many valid 5-digit "second parts" you have. Suppose you have 9 of them. Those first parts can only combine with those second parts, and give you 2 * 9 = 18 valid pairs.
You don't actually need to keep the strings!
It struck me that if you know you have 2 valid 3-digit "first parts", you don't need to keep those actual strings. Knowing that they are valid 2-digit first parts is all you need to know.
So let's build an array containing:
How many valid 1-digit first parts do we have?,
How many valid 2-digit first parts do we have?,
How many valid 3-digit first parts do we have?,
etc.
And similarly an array containing the number of valid 1-digit second parts, etc.
X first parts and Y second parts can be combined in X * Y ways
Except if the parts are the same length, in which case we are reusing the same list, and so it is just X * (Y-1).
So not only do we not need to keep the strings, but we only need to do the multiplication of the appropriate elements of the arrays.
5 1-char first parts & 7 3-char second parts = 5 * 7 = 35 pairs
6 2-char first part & 4 2-char second parts = 6 * (4-1) = 18 pairs
etc
So this becomes extremely easy. One pass over the strings, tallying the "first part" and "second part" matches of each length. This can be done with an if and a ++ of the relevant array element.
Then one pass over the lengths, which will be very quick as the array of lengths will be very much shorter than the array of actual strings.
function combineTheGivenNumber(numArray, num) {
const sElements = numArray.map(e => "" + e);
const sTarget = "" + num;
const targetLength = sTarget.length
const startsByLen = (new Array(targetLength)).fill(0);
const endsByLen = (new Array(targetLength)).fill(0);
sElements.forEach(sElement => {
if (sTarget.startsWith(sElement)) {
startsByLen[sElement.length]++
}
if (sTarget.endsWith(sElement)) {
endsByLen[sElement.length]++
}
})
// We can now throw away the strings. We have two separate arrays:
// startsByLen[1] is the count of strings (without attempting to remove duplicates) which are the first character of the required answer
// startsByLen[2] similarly the count of strings which are the first 2 characters of the required answer
// etc.
// and endsByLen[1] is the count of strings which are the last character ...
// and endsByLen[2] is the count of strings which are the last 2 characters, etc.
let pairCounts = 0;
for (let firstElementLength = 1; firstElementLength < targetLength; firstElementLength++) {
const secondElementLength = targetLength - firstElementLength;
if (firstElementLength === secondElementLength) {
pairCounts += startsByLen[firstElementLength] * (endsByLen[secondElementLength] - 1)
} else {
pairCounts += startsByLen[firstElementLength] * endsByLen[secondElementLength]
}
}
return pairCounts;
}
console.log('Test 1: ', combineTheGivenNumber([1, 212, 12, 12], 1212));
console.log('Test 2: ', combineTheGivenNumber([4, 21, 42, 1], 421));
Depending on a setup, the integer slicing can be marginally faster
Although in the end it falls short
Also, when tested on higher N values, the previous answer exploded in jsfiddle. Possibly a memory error.
As far as I have tested with both random and hand-crafted values, my solution holds. It is based on an observation, that if X, Y concantenated == Z, then following must be true:
Z - Y == X * 10^(floor(log10(Y)) + 1)
an example of this:
1212 - 12 = 1200
12 * 10^(floor((log10(12)) + 1) = 12 * 10^(1+1) = 12 * 100 = 1200
Now in theory, this should be faster then manipulating strings. And in many other languages it most likely would be. However in Javascript as I just learned, the situation is a bit more complicated. Javascript does some weird things with casting that I haven't figured out yet. In short - when I tried storing the numbers(and their counts) in a map, the code got significantly slower making any possible gains from this logarithm shenanigans evaporate. Furthermore, storing them in a custom-crafted data structure isn't guaranteed to be faster since you have to build it etc. Also it would be quite a lot of work.
As it stands this log comparison is ~ 8 times faster in a case without(or with just a few) matches since the quadratic factor is yet to kick in. As long as the possible postfix count isn't too high, it will outperform the linear solution. Unfortunately it is still quadratic in nature with the breaking point depending on a total number of strings as well as their length.
So if you are searching for a needle in a haystack - for example you are looking for a few pairs in a huge heap of numbers, this can help. In the other case of searching for many matches, this won't help. Similarly, if the input array was sorted, you could use binary search to push the breaking point further up.
In the end, unless you manage to figure out how to store ints in a map(or some custom implementation of it) in a way that doesn't completely kill the performance, the linear solution of the previous answer will be faster. It can still be useful even with the performance hit if your computation is going to be memory heavy. Storing numbers takes less space then storing strings.
var log10 = Math.log(10)
function log10floored(num) {
return Math.floor(Math.log(num) / log10)
}
function combineTheGivenNumber(numArray, num) {
count = 0
for (var i=0; i!=numArray.length; i++) {
let portion = num - numArray[i]
let removedPart = Math.pow(10, log10floored(numArray[i]))
if (portion % (removedPart * 10) == 0) {
for (var j=0; j!=numArray.length; j++) {
if (j != i && portion / (removedPart * 10) == numArray[j] ) {
count += 1
}
}
}
}
return count
}
//The previous solution, that I used for timing, comparison and check purposes
function combineTheGivenNumber2(numArray, num) {
const strings = new Map();
for (const num of numArray) {
const str = String(num);
strings.set(str, 1 + (strings.get(str) ?? 0));
}
const whole = String(num);
let pairCounts = 0;
for (const [prefix, pCount] of strings) {
if (!whole.startsWith(prefix))
continue;
const suffix = whole.slice(prefix.length);
if (strings.has(suffix)) {
let sCount = strings.get(suffix);
if (suffix == prefix) sCount--; // no self-concatenation
pairCounts += pCount*sCount;
}
}
return pairCounts;
}
var myArray = []
for (let i =0; i!= 10000000; i++) {
myArray.push(Math.floor(Math.random() * 1000000))
}
var a = new Date()
t1 = a.getTime()
console.log('Test 1: ', combineTheGivenNumber(myArray,15285656));
var b = new Date()
t2 = b.getTime()
console.log('Test 2: ', combineTheGivenNumber2(myArray,15285656));
var c = new Date()
t3 = c.getTime()
console.log('Test1 time: ', t2 - t1)
console.log('test2 time: ', t3 - t2)
Small update
As long as you are willing to take a performance hit with the setup and settle for the ~2 times performance, using a simple "hashing" table can help.(Hashing tables are nice and tidy, this is a simple modulo lookup table. The principle is similar though.)
Technically this isn't linear, practicaly it is enough for the most cases - unless you are extremely unlucky and all your numbers fall in the same bucket.
function combineTheGivenNumber(numArray, num) {
count = 0
let size = 1000000
numTable = new Array(size)
for (var i=0; i!=numArray.length; i++) {
let idx = numArray[i] % size
if (numTable[idx] == undefined) {
numTable[idx] = [numArray[i]]
} else {
numTable[idx].push(numArray[i])
}
}
for (var i=0; i!=numArray.length; i++) {
let portion = num - numArray[i]
let removedPart = Math.pow(10, log10floored(numArray[i]))
if (portion % (removedPart * 10) == 0) {
if (numTable[portion / (removedPart * 10) % size] != undefined) {
let a = numTable[portion / (removedPart * 10) % size]
for (var j=0; j!=a.length; j++) {
if (j != i && portion / (removedPart * 10) == a[j] ) {
count += 1
}
}
}
}
}
return count
}
Here's a simplified, and partially optimised approach with 2 loops:
// let's optimise 'combineTheGivenNumber', where
// a=array of numbers AND n=number to match
const ctgn = (a, n) => {
// convert our given number to a string using `toString` for clarity
// this isn't entirely necessary but means we can use strict equality later
const ns = n.toString();
// reduce is an efficient mechanism to return a value based on an array, giving us
// _=[accumulator], na=[array number] and i=[index]
return a.reduce((_, na, i) => {
// convert our 'array number' to an 'array number string' for later concatenation
const nas = na.toString();
// iterate back over our array of numbers ... we're using an optimised/reverse loop
for (let ii = a.length - 1; ii >= 0; ii--) {
// skip the current array number
if (i === ii) continue;
// string + number === string, which lets us strictly compare our 'number to match'
// if there's a match we increment the accumulator
if (a[ii] + nas === ns) ++_;
}
// we're done
return _;
}, 0);
}
I'm building an app and in one of my functions I need to generate random & unique 4 digit codes. Obviously there is a finite range from 0000 to 9999 but each day the entire list will be wiped and each day I will not need more than the available amount of codes which means it's possible to have unique codes for each day. Realistically I will probably only need a few hundred codes a day.
The way I've coded it for now is the simple brute force way which would be to generate a random 4 digit number, check if the number exists in an array and if it does, generate another number while if it doesn't, return the generated number.
Since it's 4 digits, the runtime isn't anything too crazy and I'm mostly generating a few hundred codes a day so there won't be some scenario where I've generated 9999 codes and I keep randomly generating numbers to find the last remaining one.
It would also be fine to have letters in there as well instead of just numbers if it would make the problem easier.
Other than my brute force method, what would be a more efficient way of doing this?
Thank you!
Since you have a constrained number of values that will easily fit in memory, the simplest way I know of is to create a list of the possible values and select one randomly, then remove it from the list so it can't be selected again. This will never have a collision with a previously used number:
function initValues(numValues) {
const values = new Array(numValues);
// fill the array with each value
for (let i = 0; i < values.length; i++) {
values[i] = i;
}
return values;
}
function getValue(array) {
if (!array.length) {
throw new Error("array is empty, no more random values");
}
const i = Math.floor(Math.random() * array.length);
const returnVal = array[i];
array.splice(i, 1);
return returnVal;
}
// sample code to use it
const rands = initValues(10000);
console.log(getValue(rands));
console.log(getValue(rands));
console.log(getValue(rands));
console.log(getValue(rands));
This works by doing the following:
Generate an array of all possible values.
When you need a value, select one from the array with a random index.
After selecting the value, remove it from the array.
Return the selected value.
Items are never repeated because they are removed from the array when used.
There are no collisions with used values because you're always just selecting a random value from the remaining unused values.
This relies on the fact that an array of integers is pretty well optimized in Javascript so doing a .splice() on a 10,000 element array is still pretty fast (as it can probably just be memmove instructions).
FYI, this could be made more memory efficient by using a typed array since your numbers can be represented in 16-bit values (instead of the default 64 bits for doubles). But, you'd have to implement your own version of .splice() and keep track of the length yourself since typed arrays don't have these capabilities built in.
For even larger problems like this where memory usage becomes a problem, I've used a BitArray to keep track of previous usage of values.
Here's a class implementation of the same functionality:
class Randoms {
constructor(numValues) {
this.values = new Array(numValues);
for (let i = 0; i < this.values.length; i++) {
this.values[i] = i;
}
}
getRandomValue() {
if (!this.values.length) {
throw new Error("no more random values");
}
const i = Math.floor(Math.random() * this.values.length);
const returnVal = this.values[i];
this.values.splice(i, 1);
return returnVal;
}
}
const rands = new Randoms(10000);
console.log(rands.getRandomValue());
console.log(rands.getRandomValue());
console.log(rands.getRandomValue());
console.log(rands.getRandomValue());
Knuth's multiplicative method looks to work pretty well: it'll map numbers 0 to 9999 to a random-looking other number 0 to 9999, with no overlap:
const hash = i => i*2654435761 % (10000);
const s = new Set();
for (let i = 0; i < 10000; i++) {
const n = hash(i);
if (s.has(n)) { console.log(i, n); break; }
s.add(n);
}
To implement it, simply keep track of an index that gets incremented each time a new one is generated:
const hash = i => i*2654435761 % (10000);
let i = 1;
console.log(
hash(i++),
hash(i++),
hash(i++),
hash(i++),
hash(i++),
);
These results aren't actually random, but they probably do the job well enough for most purposes.
Disclaimer:
This is copy-paste from my answer to another question here. The code was in turn ported from yet another question here.
Utilities:
function isPrime(n) {
if (n <= 1) return false;
if (n <= 3) return true;
if (n % 2 == 0 || n % 3 == 0) return false;
for (let i = 5; i * i <= n; i = i + 6) {
if (n % i == 0 || n % (i + 2) == 0) return false;
}
return true;
}
function findNextPrime(n) {
if (n <= 1) return 2;
let prime = n;
while (true) {
prime++;
if (isPrime(prime)) return prime;
}
}
function getIndexGeneratorParams(spaceSize) {
const N = spaceSize;
const Q = findNextPrime(Math.floor(2 * N / (1 + Math.sqrt(5))))
const firstIndex = Math.floor(Math.random() * spaceSize);
return [firstIndex, N, Q]
}
function getNextIndex(prevIndex, N, Q) {
return (prevIndex + Q) % N
}
Usage
// Each day you bootstrap to get a tuple of these parameters and persist them throughout the day.
const [firstIndex, N, Q] = getIndexGeneratorParams(10000)
// need to keep track of previous index generated.
// itβs a seed to generate next one.
let prevIndex = firstIndex
// calling this function gives you the unique code
function getHashCode() {
prevIndex = getNextIndex(prevIndex, N, Q)
return prevIndex.toString().padStart(4, "0")
}
console.log(getHashCode());
Explanation
For simplicity letβs say you want generate non-repeat numbers from 0 to 35 in random order. We get pseudo-randomness by polling a "full cycle iterator"β . The idea is simple:
have the indexes 0..35 layout in a circle, denote upperbound as N=36
decide a step size, denoted as Q (Q=23 in this case) given by this formulaβ‘
Q = findNextPrime(Math.floor(2 * N / (1 + Math.sqrt(5))))
randomly decide a starting point, e.g. number 5
start generating seemingly random nextIndex from prevIndex, by
nextIndex = (prevIndex + Q) % N
So if we put 5 in we get (5 + 23) % 36 == 28. Put 28 in we get (28 + 23) % 36 == 15.
This process will go through every number in circle (jump back and forth among points on the circle), it will pick each number only once, without repeating. When we get back to our starting point 5, we know we've reach the end.
β : I'm not sure about this term, just quoting from this answer
β‘: This formula only gives a nice step size that will make things look more "random", the only requirement for Q is it must be coprime to N
This problem is so small I think a simple solution is best. Build an ordered array of the 10k possible values & permute it at the start of each day. Give the k'th value to the k'th request that day.
It avoids the possible problem with your solution of having multiple collisions.
I want to loop over an array whilst addding the numbers together.
Whilst looping over the array, I would like to add the current number to the next.
My array looks like
[0,1,0,4,1]
I would like to do the following;
[0,1,0,4,1] - 0+1= 1, 1+0= 1, 0+4=4, 4+1=5
which would then give me [1,1,4,5] to do the following; 1+1 = 2, 1+4=5, 4+5=9
and so on until I get 85.
Could anyone advise on the best way to go about this
This transform follows the specified method of summation, but I also get an end result of 21, so please specify how you get to 85.
var ary = [0,1,0,4,1],
transform = function (ary) {
var length = ary.length;
return ary.reduce(function (acc, val, index, ary) {
if (index + 1 !== length) acc.push(ary[index] + ary[index + 1]);
return acc;
}, []);
};
while (ary.length !== 1) ary = transform(ary);
If you do in fact want the answer to be 21 (as it seems like it should be), what you are really trying to do is closely related to the Binomial Theorem.
I am not familiar with javascript, so I will write an example in c-style pseudocode:
var array = [0,1,0,4,1]
int result = 0;
for (int i = 0; i < array.length; i++)
{
int result += array[i] * nChooseK(array.length - 1, i);
}
This will put the following numbers into result for each respective iteration:
0 += 0 * 1 --> 0
0 += 1 * 4 --> 4
4 += 0 * 6 --> 4
4 += 4 * 4 --> 20
20 += 1 * 1 --> 21
This avoids all the confusing array operations that arise when trying to iterate through creating shorter-and-shorter arrays; it will also be faster if you have a good nChooseK() implementation.
Now, finding an efficient algorithm for a nChooseK() function is a different matter, but it is a relatively common task so it shouldn't be too difficult (Googling "n choose k algorithm" should work just fine). Some languages even have combinatoric functions in standard math libraries.
The result I get is 21 not 85. This code can be optimised to only use single array. Anyway it gets the job done.
var input = [0, 1, 0, 4, 1];
function calc(input) {
if (input.length === 1) {
return input;
}
var result = [];
for (var i = 0; i < input.length - 1; i++) {
result[i] = input[i] + input[i + 1];
}
return calc(result);
}
alert(calc(input));
This is an O(n^2) algorithm.