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Javascript / JQuery - Favor Number Range In Math.random() [duplicate]

I'm trying to devise a (good) way to choose a random number from a range of possible numbers where each number in the range is given a weight. To put it simply: given the range of numbers (0,1,2) choose a number where 0 has an 80% probability of being selected, 1 has a 10% chance and 2 has a 10% chance.
It's been about 8 years since my college stats class, so you can imagine the proper formula for this escapes me at the moment.
Here's the 'cheap and dirty' method that I came up with. This solution uses ColdFusion. Yours may use whatever language you'd like. I'm a programmer, I think I can handle porting it. Ultimately my solution needs to be in Groovy - I wrote this one in ColdFusion because it's easy to quickly write/test in CF.
public function weightedRandom( Struct options ) {
var tempArr = [];
for( var o in arguments.options )
{
var weight = arguments.options[ o ] * 10;
for ( var i = 1; i<= weight; i++ )
{
arrayAppend( tempArr, o );
}
}
return tempArr[ randRange( 1, arrayLen( tempArr ) ) ];
}
// test it
opts = { 0=.8, 1=.1, 2=.1 };
for( x = 1; x<=10; x++ )
{
writeDump( weightedRandom( opts ) );
}
I'm looking for better solutions, please suggest improvements or alternatives.

Rejection sampling (such as in your solution) is the first thing that comes to mind, whereby you build a lookup table with elements populated by their weight distribution, then pick a random location in the table and return it. As an implementation choice, I would make a higher order function which takes a spec and returns a function which returns values based on the distribution in the spec, this way you avoid having to build the table for each call. The downsides are that the algorithmic performance of building the table is linear by the number of items and there could potentially be a lot of memory usage for large specs (or those with members with very small or precise weights, e.g. {0:0.99999, 1:0.00001}). The upside is that picking a value has constant time, which might be desirable if performance is critical. In JavaScript:
function weightedRand(spec) {
var i, j, table=[];
for (i in spec) {
// The constant 10 below should be computed based on the
// weights in the spec for a correct and optimal table size.
// E.g. the spec {0:0.999, 1:0.001} will break this impl.
for (j=0; j<spec[i]*10; j++) {
table.push(i);
}
}
return function() {
return table[Math.floor(Math.random() * table.length)];
}
}
var rand012 = weightedRand({0:0.8, 1:0.1, 2:0.1});
rand012(); // random in distribution...
Another strategy is to pick a random number in [0,1) and iterate over the weight specification summing the weights, if the random number is less than the sum then return the associated value. Of course, this assumes that the weights sum to one. This solution has no up-front costs but has average algorithmic performance linear by the number of entries in the spec. For example, in JavaScript:
function weightedRand2(spec) {
var i, sum=0, r=Math.random();
for (i in spec) {
sum += spec[i];
if (r <= sum) return i;
}
}
weightedRand2({0:0.8, 1:0.1, 2:0.1}); // random in distribution...

Generate a random number R between 0 and 1.
If R in [0, 0.1) -> 1
If R in [0.1, 0.2) -> 2
If R in [0.2, 1] -> 3
If you can't directly get a number between 0 and 1, generate a number in a range that will produce as much precision as you want. For example, if you have the weights for
(1, 83.7%) and (2, 16.3%), roll a number from 1 to 1000. 1-837 is a 1. 838-1000 is 2.

I use the following
function weightedRandom(min, max) {
return Math.round(max / (Math.random() * max + min));
}
This is my go-to "weighted" random, where I use an inverse function of "x" (where x is a random between min and max) to generate a weighted result, where the minimum is the most heavy element, and the maximum the lightest (least chances of getting the result)
So basically, using weightedRandom(1, 5) means the chances of getting a 1 are higher than a 2 which are higher than a 3, which are higher than a 4, which are higher than a 5.
Might not be useful for your use case but probably useful for people googling this same question.
After a 100 iterations try, it gave me:
==================
| Result | Times |
==================
| 1 | 55 |
| 2 | 28 |
| 3 | 8 |
| 4 | 7 |
| 5 | 2 |
==================

Here are 3 solutions in javascript since I'm not sure which language you want it in. Depending on your needs one of the first two might work, but the the third one is probably the easiest to implement with large sets of numbers.
function randomSimple(){
return [0,0,0,0,0,0,0,0,1,2][Math.floor(Math.random()*10)];
}
function randomCase(){
var n=Math.floor(Math.random()*100)
switch(n){
case n<80:
return 0;
case n<90:
return 1;
case n<100:
return 2;
}
}
function randomLoop(weight,num){
var n=Math.floor(Math.random()*100),amt=0;
for(var i=0;i<weight.length;i++){
//amt+=weight[i]; *alternative method
//if(n<amt){
if(n<weight[i]){
return num[i];
}
}
}
weight=[80,90,100];
//weight=[80,10,10]; *alternative method
num=[0,1,2]

8 years late but here's my solution in 4 lines.
Prepare an array of probability mass function such that
pmf[array_index] = P(X=array_index):
var pmf = [0.8, 0.1, 0.1]
Prepare an array for the corresponding cumulative distribution function such that
cdf[array_index] = F(X=array_index):
var cdf = pmf.map((sum => value => sum += value)(0))
// [0.8, 0.9, 1]
3a) Generate a random number.
3b) Get an array of elements that are more than or equal to this number.
3c) Return its length.
var r = Math.random()
cdf.filter(el => r >= el).length

This is more or less a generic-ized version of what #trinithis wrote, in Java: I did it with ints rather than floats to avoid messy rounding errors.
static class Weighting {
int value;
int weighting;
public Weighting(int v, int w) {
this.value = v;
this.weighting = w;
}
}
public static int weightedRandom(List<Weighting> weightingOptions) {
//determine sum of all weightings
int total = 0;
for (Weighting w : weightingOptions) {
total += w.weighting;
}
//select a random value between 0 and our total
int random = new Random().nextInt(total);
//loop thru our weightings until we arrive at the correct one
int current = 0;
for (Weighting w : weightingOptions) {
current += w.weighting;
if (random < current)
return w.value;
}
//shouldn't happen.
return -1;
}
public static void main(String[] args) {
List<Weighting> weightings = new ArrayList<Weighting>();
weightings.add(new Weighting(0, 8));
weightings.add(new Weighting(1, 1));
weightings.add(new Weighting(2, 1));
for (int i = 0; i < 100; i++) {
System.out.println(weightedRandom(weightings));
}
}

How about
int [ ] numbers = { 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 , 1 , 2 } ;
then you can randomly select from numbers and 0 will have an 80% chance, 1 10%, and 2 10%

This one is in Mathematica, but it's easy to copy to another language, I use it in my games and it can handle decimal weights:
weights = {0.5,1,2}; // The weights
weights = N#weights/Total#weights // Normalize weights so that the list's sum is always 1.
min = 0; // First min value should be 0
max = weights[[1]]; // First max value should be the first element of the newly created weights list. Note that in Mathematica the first element has index of 1, not 0.
random = RandomReal[]; // Generate a random float from 0 to 1;
For[i = 1, i <= Length#weights, i++,
If[random >= min && random < max,
Print["Chosen index number: " <> ToString#i]
];
min += weights[[i]];
If[i == Length#weights,
max = 1,
max += weights[[i + 1]]
]
]
(Now I'm talking with a lists first element's index equals 0) The idea behind this is that having a normalized list weights there is a chance of weights[n] to return the index n, so the distances between the min and max at step n should be weights[n]. The total distance from the minimum min (which we put it to be 0) and the maximum max is the sum of the list weights.
The good thing behind this is that you don't append to any array or nest for loops, and that increases heavily the execution time.
Here is the code in C# without needing to normalize the weights list and deleting some code:
int WeightedRandom(List<float> weights) {
float total = 0f;
foreach (float weight in weights) {
total += weight;
}
float max = weights [0],
random = Random.Range(0f, total);
for (int index = 0; index < weights.Count; index++) {
if (random < max) {
return index;
} else if (index == weights.Count - 1) {
return weights.Count-1;
}
max += weights[index+1];
}
return -1;
}

I suggest to use a continuous check of the probability and the rest of the random number.
This function sets first the return value to the last possible index and iterates until the rest of the random value is smaller than the actual probability.
The probabilities have to sum to one.
function getRandomIndexByProbability(probabilities) {
var r = Math.random(),
index = probabilities.length - 1;
probabilities.some(function (probability, i) {
if (r < probability) {
index = i;
return true;
}
r -= probability;
});
return index;
}
var i,
probabilities = [0.8, 0.1, 0.1],
count = probabilities.map(function () { return 0; });
for (i = 0; i < 1e6; i++) {
count[getRandomIndexByProbability(probabilities)]++;
}
console.log(count);
.as-console-wrapper { max-height: 100% !important; top: 0; }

Thanks all, this was a helpful thread. I encapsulated it into a convenience function (Typescript). Tests below (sinon, jest). Could definitely be a bit tighter, but hopefully it's readable.
export type WeightedOptions = {
[option: string]: number;
};
// Pass in an object like { a: 10, b: 4, c: 400 } and it'll return either "a", "b", or "c", factoring in their respective
// weight. So in this example, "c" is likely to be returned 400 times out of 414
export const getRandomWeightedValue = (options: WeightedOptions) => {
const keys = Object.keys(options);
const totalSum = keys.reduce((acc, item) => acc + options[item], 0);
let runningTotal = 0;
const cumulativeValues = keys.map((key) => {
const relativeValue = options[key]/totalSum;
const cv = {
key,
value: relativeValue + runningTotal
};
runningTotal += relativeValue;
return cv;
});
const r = Math.random();
return cumulativeValues.find(({ key, value }) => r <= value)!.key;
};
Tests:
describe('getRandomWeightedValue', () => {
// Out of 1, the relative and cumulative values for these are:
// a: 0.1666 -> 0.16666
// b: 0.3333 -> 0.5
// c: 0.5 -> 1
const values = { a: 10, b: 20, c: 30 };
it('returns appropriate values for particular random value', () => {
// any random number under 0.166666 should return "a"
const stub1 = sinon.stub(Math, 'random').returns(0);
const result1 = randomUtils.getRandomWeightedValue(values);
expect(result1).toEqual('a');
stub1.restore();
const stub2 = sinon.stub(Math, 'random').returns(0.1666);
const result2 = randomUtils.getRandomWeightedValue(values);
expect(result2).toEqual('a');
stub2.restore();
// any random number between 0.166666 and 0.5 should return "b"
const stub3 = sinon.stub(Math, 'random').returns(0.17);
const result3 = randomUtils.getRandomWeightedValue(values);
expect(result3).toEqual('b');
stub3.restore();
const stub4 = sinon.stub(Math, 'random').returns(0.3333);
const result4 = randomUtils.getRandomWeightedValue(values);
expect(result4).toEqual('b');
stub4.restore();
const stub5 = sinon.stub(Math, 'random').returns(0.5);
const result5 = randomUtils.getRandomWeightedValue(values);
expect(result5).toEqual('b');
stub5.restore();
// any random number above 0.5 should return "c"
const stub6 = sinon.stub(Math, 'random').returns(0.500001);
const result6 = randomUtils.getRandomWeightedValue(values);
expect(result6).toEqual('c');
stub6.restore();
const stub7 = sinon.stub(Math, 'random').returns(1);
const result7 = randomUtils.getRandomWeightedValue(values);
expect(result7).toEqual('c');
stub7.restore();
});
});

Shortest solution in modern JavaScript
Note: all weights need to be integers
function weightedRandom(items){
let table = Object.entries(items)
.flatMap(([item, weight]) => Array(item).fill(weight))
return table[Math.floor(Math.random() * table.length)]
}
const key = weightedRandom({
"key1": 1,
"key2": 4,
"key3": 8
}) // returns e.g. "key1"

here is the input and ratios : 0 (80%), 1(10%) , 2 (10%)
lets draw them out so its easy to visualize.
0 1 2
-------------------------------------________+++++++++
lets add up the total weight and call it TR for total ratio. so in this case 100.
lets randomly get a number from (0-TR) or (0 to 100 in this case) . 100 being your weights total. Call it RN for random number.
so now we have TR as the total weight and RN as the random number between 0 and TR.
so lets imagine we picked a random # from 0 to 100. Say 21. so thats actually 21%.
WE MUST CONVERT/MATCH THIS TO OUR INPUT NUMBERS BUT HOW ?
lets loop over each weight (80, 10, 10) and keep the sum of the weights we already visit.
the moment the sum of the weights we are looping over is greater then the random number RN (21 in this case), we stop the loop & return that element position.
double sum = 0;
int position = -1;
for(double weight : weight){
position ++;
sum = sum + weight;
if(sum > 21) //(80 > 21) so break on first pass
break;
}
//position will be 0 so we return array[0]--> 0
lets say the random number (between 0 and 100) is 83. Lets do it again:
double sum = 0;
int position = -1;
for(double weight : weight){
position ++;
sum = sum + weight;
if(sum > 83) //(90 > 83) so break
break;
}
//we did two passes in the loop so position is 1 so we return array[1]---> 1

I have a slotmachine and I used the code below to generate random numbers. In probabilitiesSlotMachine the keys are the output in the slotmachine, and the values represent the weight.
const probabilitiesSlotMachine = [{0 : 1000}, {1 : 100}, {2 : 50}, {3 : 30}, {4 : 20}, {5 : 10}, {6 : 5}, {7 : 4}, {8 : 2}, {9 : 1}]
var allSlotMachineResults = []
probabilitiesSlotMachine.forEach(function(obj, index){
for (var key in obj){
for (var loop = 0; loop < obj[key]; loop ++){
allSlotMachineResults.push(key)
}
}
});
Now to generate a random output, I use this code:
const random = allSlotMachineResults[Math.floor(Math.random() * allSlotMachineResults.length)]

Enjoy the O(1) (constant time) solution for your problem.
If the input array is small, it can be easily implemented.
const number = Math.floor(Math.random() * 99); // Generate a random number from 0 to 99
let element;
if (number >= 0 && number <= 79) {
/*
In the range of 0 to 99, every number has equal probability
of occurring. Therefore, if you gather 80 numbers (0 to 79) and
make a "sub-group" of them, then their probabilities will get added.
Hence, what you get is an 80% chance that the number will fall in this
range.
So, quite naturally, there is 80% probability that this code will run.
Now, manually choose / assign element of your array to this variable.
*/
element = 0;
}
else if (number >= 80 && number <= 89) {
// 10% chance that this code runs.
element = 1;
}
else if (number >= 90 && number <= 99) {
// 10% chance that this code runs.
element = 2;
}

Make array consecutive

i got stucked in a chalenge in codeFights.my code pass the simple test and fail in just 2 from five of hidden tests her is the chalenge instruction:
Ratiorg got statues of different sizes as a present from CodeMaster for his birthday, each statue having an non-negative integer size. Since he likes to make things perfect, he wants to arrange them from smallest to largest so that each statue will be bigger than the previous one exactly by 1. He may need some additional statues to be able to accomplish that. Help him figure out the minimum number of additional statues needed.
Example
For statues = [6, 2, 3, 8], the output should be
makeArrayConsecutive2(statues) = 3.
Ratiorg needs statues of sizes 4, 5 and 7.
Input/Output
[time limit] 4000ms (js)
[input] array.integer statues
An array of distinct non-negative integers.
Constraints:
1 ≤ statues.length ≤ 10,
0 ≤ statues[i] ≤ 20.
[output] integer
The minimal number of statues that need to be added to existing statues such that it contains every integer size from an interval [L, R] (for some L, R) and no other sizes.
and here is my code :
function makeArrayConsecutive2(statues) {
//range the table from min to max
var rang=statues.sort();
var some=0;
//if the table is one element
if(rang.length-1==0){
return 0;
}else{
//if the table contain more then one element
for(i=0;i<=rang.length-2;i++){
//add the deference of two consecutive position -1
//to find the number of missing numbers
some+=(rang[i+1]-rang[i]-1);
}
return some;
}
}

Everything is correct, except the sorting part.
You have used sort function to sort the array in increasing order
var rang = statues.sort();
But if sort function is not provided a compare function, it converts its elements in strings and then sort it in unicode order.
For eg: [2,1,11] will be sorted as [1,11,2] which will give undesired output.
Correct way is
var rang = statues.sort(function (a, b){
return (a - b)
});

SO THE LOGIC TO SOLVE THIS QUESTION IS:
Find the Smallest and Largest Element in Array.
Get the count of can say, difference of Largest and Smallest value of array in order to calculate, how many elements must be there to make it as a continuous array
. Like from 5 to 9, count of total elements must be 5 ( i.e.5,6,7,8,9) and also add 1 to the result to make count inclusive.
Find the Length of the Array
Subtract the count i.e. "difference of largest and smallest value " with the length of array
PYTHON CODE (For explanation):
def makeArrayConsecutive2(statues):
max_height = max(statues)
min_height = min(statues)
array_length = len(statues)
count_of_element = max_height - min_height + 1
# '1 ' is added to make it inclusive
return count_of_element-array_length
and Python one liner :
def makeArrayConsecutive2(statues):
return max(statues)-min(statues)-len(statues)+1

I agree with Deepak's Solution. The question is ready not about sorting but helping to figure out the minimum number of additional statues needed. You only need to get the max and min values.
int makeArrayConsecutive2(int[] statues)
{
int min=Integer.MAX_VALUE,max=-1;
for(int i=0;i<statues.length;i++)
{
if(statues[i] < min){ min = statues[i]; }
if(statues[i] > max){ max = statues[i]; }
}
return (max-min)+1 - statues.length;
}

Solution in typescript. Create a new array from the min and max from the status array using a for loop. Subtract new array length with status array length.
function makeArrayConsecutive2(statues: number[]): number {
let min = Math.min(...statues);
let max = Math.max(...statues);
let arr = [];
for (let i = min; i <= max; i++) {
arr.push(i);
}
return arr.length - statues.length;
}

function makeArrayConsecutive2(statues) {
const nums = [];
for (let i = Math.min(...statues); i <= Math.max(...statues); i++) {
if (!statues.includes(i)) {
nums.push(i);
}
}
return nums.length;
}
console.log(makeArrayConsecutive2([6, 2, 3, 8]))

Sorting (nlogn)is not required. Below is the solution in Java.
int makeArrayConsecutive2(int[] statues) {
int max = Integer.MIN_VALUE;
int min = Integer.MAX_VALUE;
for (int i = 0; i < statues.length; i++) {
max = Math.max(max, statues[i]);
min = Math.min(min, statues[i]);
}
return (max - min) + 1 - statues.length;
}

This Code works
var statues = [2, 3, 6, 8];
var newStatues = [];
Function declaration
function makeArrayConsecutive2(statues) {
statues.sort(function(a, b) { return a - b });
for(var i = statues[0]; i <= statues[statues.length-1]; i++) {
newStatues.push(i);
}
return console.log(newStatues.length - statues.length);
}
Function Calling
makeArrayConsecutive2(statues);

Best solution goes here in just O(1) complexity:
let n = statues.length;
let max = Math.max.apply(null, statues);
let min = Math.min.apply(null, statues);
return max - min - n + 1;

function makeArrayConsecutive2(statues) {
var rang = statues.sort(function (a, b){
return (a - b)
});
var some=0;
if(rang.length-1==0){
return 0;
}else{
for(i=0;i<=rang.length-2;i++){
some+=(rang[i+1]-rang[i]-1);
}
return some;
}
}

function makeArrayConsecutive2(statues) {
const n = statues.length;
const min = Math.min(...statues);
const max = Math.max(...statues);
return max - min - n + 1;
}
If we subtract the minimum from the maximum element, then we get the number of elements that should be in the final array. Now subtract the already existing number of elements from this amount and add 1, then we get the result we need - the number of missing elements

Just for fun in C#
static int makeArrayConsecutive2(int[] statues)
{
List<int> ConsecutiveNums = new List<int>();
for(int i = statues.Min(); i != statues.Max() + 1; i++)
ConsecutiveNums.Add(i);
return ConsecutiveNums.Count - statues.Length;
}

function makeArrayConsecutive2(statues) {
return Math.max(...statues) - Math.min(...statues) + 1 -(statues.length)
}
I don't think we need a Looping there, that's my solution

you can try using for loop and ternary operation by the following code
def makeArrayConsecutive2(statues):
count=0
for i in range (min(statues),max(statues)):
count=count+1 if i not in statues else count
return count

function makeArrayConsecutive2(statues) {
s = statues.sort(function(a, b){return a - b});
n = statues.length;
val = 0;
for (let i=0;i<n-1;i++) {
val += (Math.abs(s[i]-s[i+1]))-1;
}
return val;
}

sort(statues.begin(), statues.end());
int count = 0;
for(int i = 1;i<statues.size(); i++){
int diff = statues[i]-statues[i-1];
if(diff>1){
count+=diff-1;
}
}
return count;

Solution in PHP
function solution($statues) {
return max($statues) - min($statues) - count($statues) + 1;
}

PHP solution for question.
function solution($statues) {
sort($statues);
$missing = 0;
$lowest = min($statues);
$highest = max($statues);
$numbers = range($lowest, $highest);
foreach($numbers as $number){
if(!in_array($number, $statues)){
$missing++;
}
}
return $missing;
}

here is code in python
def solution(statues):
statues.sort()
c = 0
for i in range(len(statues)-1):
if statues[i+1]-statues[i] > 1:
c += statues[i+1]-statues[i] -1
return (c)

It's the weight! How to return weighted probabilities? (Javascript) [duplicate]

I'm trying to devise a (good) way to choose a random number from a range of possible numbers where each number in the range is given a weight. To put it simply: given the range of numbers (0,1,2) choose a number where 0 has an 80% probability of being selected, 1 has a 10% chance and 2 has a 10% chance.
It's been about 8 years since my college stats class, so you can imagine the proper formula for this escapes me at the moment.
Here's the 'cheap and dirty' method that I came up with. This solution uses ColdFusion. Yours may use whatever language you'd like. I'm a programmer, I think I can handle porting it. Ultimately my solution needs to be in Groovy - I wrote this one in ColdFusion because it's easy to quickly write/test in CF.
public function weightedRandom( Struct options ) {
var tempArr = [];
for( var o in arguments.options )
{
var weight = arguments.options[ o ] * 10;
for ( var i = 1; i<= weight; i++ )
{
arrayAppend( tempArr, o );
}
}
return tempArr[ randRange( 1, arrayLen( tempArr ) ) ];
}
// test it
opts = { 0=.8, 1=.1, 2=.1 };
for( x = 1; x<=10; x++ )
{
writeDump( weightedRandom( opts ) );
}
I'm looking for better solutions, please suggest improvements or alternatives.

Rejection sampling (such as in your solution) is the first thing that comes to mind, whereby you build a lookup table with elements populated by their weight distribution, then pick a random location in the table and return it. As an implementation choice, I would make a higher order function which takes a spec and returns a function which returns values based on the distribution in the spec, this way you avoid having to build the table for each call. The downsides are that the algorithmic performance of building the table is linear by the number of items and there could potentially be a lot of memory usage for large specs (or those with members with very small or precise weights, e.g. {0:0.99999, 1:0.00001}). The upside is that picking a value has constant time, which might be desirable if performance is critical. In JavaScript:
function weightedRand(spec) {
var i, j, table=[];
for (i in spec) {
// The constant 10 below should be computed based on the
// weights in the spec for a correct and optimal table size.
// E.g. the spec {0:0.999, 1:0.001} will break this impl.
for (j=0; j<spec[i]*10; j++) {
table.push(i);
}
}
return function() {
return table[Math.floor(Math.random() * table.length)];
}
}
var rand012 = weightedRand({0:0.8, 1:0.1, 2:0.1});
rand012(); // random in distribution...
Another strategy is to pick a random number in [0,1) and iterate over the weight specification summing the weights, if the random number is less than the sum then return the associated value. Of course, this assumes that the weights sum to one. This solution has no up-front costs but has average algorithmic performance linear by the number of entries in the spec. For example, in JavaScript:
function weightedRand2(spec) {
var i, sum=0, r=Math.random();
for (i in spec) {
sum += spec[i];
if (r <= sum) return i;
}
}
weightedRand2({0:0.8, 1:0.1, 2:0.1}); // random in distribution...

Generate a random number R between 0 and 1.
If R in [0, 0.1) -> 1
If R in [0.1, 0.2) -> 2
If R in [0.2, 1] -> 3
If you can't directly get a number between 0 and 1, generate a number in a range that will produce as much precision as you want. For example, if you have the weights for
(1, 83.7%) and (2, 16.3%), roll a number from 1 to 1000. 1-837 is a 1. 838-1000 is 2.

I use the following
function weightedRandom(min, max) {
return Math.round(max / (Math.random() * max + min));
}
This is my go-to "weighted" random, where I use an inverse function of "x" (where x is a random between min and max) to generate a weighted result, where the minimum is the most heavy element, and the maximum the lightest (least chances of getting the result)
So basically, using weightedRandom(1, 5) means the chances of getting a 1 are higher than a 2 which are higher than a 3, which are higher than a 4, which are higher than a 5.
Might not be useful for your use case but probably useful for people googling this same question.
After a 100 iterations try, it gave me:
==================
| Result | Times |
==================
| 1 | 55 |
| 2 | 28 |
| 3 | 8 |
| 4 | 7 |
| 5 | 2 |
==================

Here are 3 solutions in javascript since I'm not sure which language you want it in. Depending on your needs one of the first two might work, but the the third one is probably the easiest to implement with large sets of numbers.
function randomSimple(){
return [0,0,0,0,0,0,0,0,1,2][Math.floor(Math.random()*10)];
}
function randomCase(){
var n=Math.floor(Math.random()*100)
switch(n){
case n<80:
return 0;
case n<90:
return 1;
case n<100:
return 2;
}
}
function randomLoop(weight,num){
var n=Math.floor(Math.random()*100),amt=0;
for(var i=0;i<weight.length;i++){
//amt+=weight[i]; *alternative method
//if(n<amt){
if(n<weight[i]){
return num[i];
}
}
}
weight=[80,90,100];
//weight=[80,10,10]; *alternative method
num=[0,1,2]

8 years late but here's my solution in 4 lines.
Prepare an array of probability mass function such that
pmf[array_index] = P(X=array_index):
var pmf = [0.8, 0.1, 0.1]
Prepare an array for the corresponding cumulative distribution function such that
cdf[array_index] = F(X=array_index):
var cdf = pmf.map((sum => value => sum += value)(0))
// [0.8, 0.9, 1]
3a) Generate a random number.
3b) Get an array of elements that are more than or equal to this number.
3c) Return its length.
var r = Math.random()
cdf.filter(el => r >= el).length

This is more or less a generic-ized version of what #trinithis wrote, in Java: I did it with ints rather than floats to avoid messy rounding errors.
static class Weighting {
int value;
int weighting;
public Weighting(int v, int w) {
this.value = v;
this.weighting = w;
}
}
public static int weightedRandom(List<Weighting> weightingOptions) {
//determine sum of all weightings
int total = 0;
for (Weighting w : weightingOptions) {
total += w.weighting;
}
//select a random value between 0 and our total
int random = new Random().nextInt(total);
//loop thru our weightings until we arrive at the correct one
int current = 0;
for (Weighting w : weightingOptions) {
current += w.weighting;
if (random < current)
return w.value;
}
//shouldn't happen.
return -1;
}
public static void main(String[] args) {
List<Weighting> weightings = new ArrayList<Weighting>();
weightings.add(new Weighting(0, 8));
weightings.add(new Weighting(1, 1));
weightings.add(new Weighting(2, 1));
for (int i = 0; i < 100; i++) {
System.out.println(weightedRandom(weightings));
}
}

How about
int [ ] numbers = { 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 , 1 , 2 } ;
then you can randomly select from numbers and 0 will have an 80% chance, 1 10%, and 2 10%

This one is in Mathematica, but it's easy to copy to another language, I use it in my games and it can handle decimal weights:
weights = {0.5,1,2}; // The weights
weights = N#weights/Total#weights // Normalize weights so that the list's sum is always 1.
min = 0; // First min value should be 0
max = weights[[1]]; // First max value should be the first element of the newly created weights list. Note that in Mathematica the first element has index of 1, not 0.
random = RandomReal[]; // Generate a random float from 0 to 1;
For[i = 1, i <= Length#weights, i++,
If[random >= min && random < max,
Print["Chosen index number: " <> ToString#i]
];
min += weights[[i]];
If[i == Length#weights,
max = 1,
max += weights[[i + 1]]
]
]
(Now I'm talking with a lists first element's index equals 0) The idea behind this is that having a normalized list weights there is a chance of weights[n] to return the index n, so the distances between the min and max at step n should be weights[n]. The total distance from the minimum min (which we put it to be 0) and the maximum max is the sum of the list weights.
The good thing behind this is that you don't append to any array or nest for loops, and that increases heavily the execution time.
Here is the code in C# without needing to normalize the weights list and deleting some code:
int WeightedRandom(List<float> weights) {
float total = 0f;
foreach (float weight in weights) {
total += weight;
}
float max = weights [0],
random = Random.Range(0f, total);
for (int index = 0; index < weights.Count; index++) {
if (random < max) {
return index;
} else if (index == weights.Count - 1) {
return weights.Count-1;
}
max += weights[index+1];
}
return -1;
}

I suggest to use a continuous check of the probability and the rest of the random number.
This function sets first the return value to the last possible index and iterates until the rest of the random value is smaller than the actual probability.
The probabilities have to sum to one.
function getRandomIndexByProbability(probabilities) {
var r = Math.random(),
index = probabilities.length - 1;
probabilities.some(function (probability, i) {
if (r < probability) {
index = i;
return true;
}
r -= probability;
});
return index;
}
var i,
probabilities = [0.8, 0.1, 0.1],
count = probabilities.map(function () { return 0; });
for (i = 0; i < 1e6; i++) {
count[getRandomIndexByProbability(probabilities)]++;
}
console.log(count);
.as-console-wrapper { max-height: 100% !important; top: 0; }

Thanks all, this was a helpful thread. I encapsulated it into a convenience function (Typescript). Tests below (sinon, jest). Could definitely be a bit tighter, but hopefully it's readable.
export type WeightedOptions = {
[option: string]: number;
};
// Pass in an object like { a: 10, b: 4, c: 400 } and it'll return either "a", "b", or "c", factoring in their respective
// weight. So in this example, "c" is likely to be returned 400 times out of 414
export const getRandomWeightedValue = (options: WeightedOptions) => {
const keys = Object.keys(options);
const totalSum = keys.reduce((acc, item) => acc + options[item], 0);
let runningTotal = 0;
const cumulativeValues = keys.map((key) => {
const relativeValue = options[key]/totalSum;
const cv = {
key,
value: relativeValue + runningTotal
};
runningTotal += relativeValue;
return cv;
});
const r = Math.random();
return cumulativeValues.find(({ key, value }) => r <= value)!.key;
};
Tests:
describe('getRandomWeightedValue', () => {
// Out of 1, the relative and cumulative values for these are:
// a: 0.1666 -> 0.16666
// b: 0.3333 -> 0.5
// c: 0.5 -> 1
const values = { a: 10, b: 20, c: 30 };
it('returns appropriate values for particular random value', () => {
// any random number under 0.166666 should return "a"
const stub1 = sinon.stub(Math, 'random').returns(0);
const result1 = randomUtils.getRandomWeightedValue(values);
expect(result1).toEqual('a');
stub1.restore();
const stub2 = sinon.stub(Math, 'random').returns(0.1666);
const result2 = randomUtils.getRandomWeightedValue(values);
expect(result2).toEqual('a');
stub2.restore();
// any random number between 0.166666 and 0.5 should return "b"
const stub3 = sinon.stub(Math, 'random').returns(0.17);
const result3 = randomUtils.getRandomWeightedValue(values);
expect(result3).toEqual('b');
stub3.restore();
const stub4 = sinon.stub(Math, 'random').returns(0.3333);
const result4 = randomUtils.getRandomWeightedValue(values);
expect(result4).toEqual('b');
stub4.restore();
const stub5 = sinon.stub(Math, 'random').returns(0.5);
const result5 = randomUtils.getRandomWeightedValue(values);
expect(result5).toEqual('b');
stub5.restore();
// any random number above 0.5 should return "c"
const stub6 = sinon.stub(Math, 'random').returns(0.500001);
const result6 = randomUtils.getRandomWeightedValue(values);
expect(result6).toEqual('c');
stub6.restore();
const stub7 = sinon.stub(Math, 'random').returns(1);
const result7 = randomUtils.getRandomWeightedValue(values);
expect(result7).toEqual('c');
stub7.restore();
});
});

Shortest solution in modern JavaScript
Note: all weights need to be integers
function weightedRandom(items){
let table = Object.entries(items)
.flatMap(([item, weight]) => Array(item).fill(weight))
return table[Math.floor(Math.random() * table.length)]
}
const key = weightedRandom({
"key1": 1,
"key2": 4,
"key3": 8
}) // returns e.g. "key1"

here is the input and ratios : 0 (80%), 1(10%) , 2 (10%)
lets draw them out so its easy to visualize.
0 1 2
-------------------------------------________+++++++++
lets add up the total weight and call it TR for total ratio. so in this case 100.
lets randomly get a number from (0-TR) or (0 to 100 in this case) . 100 being your weights total. Call it RN for random number.
so now we have TR as the total weight and RN as the random number between 0 and TR.
so lets imagine we picked a random # from 0 to 100. Say 21. so thats actually 21%.
WE MUST CONVERT/MATCH THIS TO OUR INPUT NUMBERS BUT HOW ?
lets loop over each weight (80, 10, 10) and keep the sum of the weights we already visit.
the moment the sum of the weights we are looping over is greater then the random number RN (21 in this case), we stop the loop & return that element position.
double sum = 0;
int position = -1;
for(double weight : weight){
position ++;
sum = sum + weight;
if(sum > 21) //(80 > 21) so break on first pass
break;
}
//position will be 0 so we return array[0]--> 0
lets say the random number (between 0 and 100) is 83. Lets do it again:
double sum = 0;
int position = -1;
for(double weight : weight){
position ++;
sum = sum + weight;
if(sum > 83) //(90 > 83) so break
break;
}
//we did two passes in the loop so position is 1 so we return array[1]---> 1

I have a slotmachine and I used the code below to generate random numbers. In probabilitiesSlotMachine the keys are the output in the slotmachine, and the values represent the weight.
const probabilitiesSlotMachine = [{0 : 1000}, {1 : 100}, {2 : 50}, {3 : 30}, {4 : 20}, {5 : 10}, {6 : 5}, {7 : 4}, {8 : 2}, {9 : 1}]
var allSlotMachineResults = []
probabilitiesSlotMachine.forEach(function(obj, index){
for (var key in obj){
for (var loop = 0; loop < obj[key]; loop ++){
allSlotMachineResults.push(key)
}
}
});
Now to generate a random output, I use this code:
const random = allSlotMachineResults[Math.floor(Math.random() * allSlotMachineResults.length)]

Enjoy the O(1) (constant time) solution for your problem.
If the input array is small, it can be easily implemented.
const number = Math.floor(Math.random() * 99); // Generate a random number from 0 to 99
let element;
if (number >= 0 && number <= 79) {
/*
In the range of 0 to 99, every number has equal probability
of occurring. Therefore, if you gather 80 numbers (0 to 79) and
make a "sub-group" of them, then their probabilities will get added.
Hence, what you get is an 80% chance that the number will fall in this
range.
So, quite naturally, there is 80% probability that this code will run.
Now, manually choose / assign element of your array to this variable.
*/
element = 0;
}
else if (number >= 80 && number <= 89) {
// 10% chance that this code runs.
element = 1;
}
else if (number >= 90 && number <= 99) {
// 10% chance that this code runs.
element = 2;
}

Looping through array elements in javascript generated by random nr generator [duplicate]

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?" – you don't have to specify
"Do I have to find all the primes first and then select a random prime?" – 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);
}
}​
// 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)

How to compute the sum and average of elements in an array? [duplicate]

Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted.
This question already has answers here:
How to find the sum of an array of numbers
(59 answers)
Closed 3 months ago.
I am having problems adding all the elements of an array as well as averaging them out. How would I do this and implement it with the code I currently have? The elements are supposed to be defined as I have it below.
<script type="text/javascript">
//<![CDATA[
var i;
var elmt = new Array();
elmt[0] = "0";
elmt[1] = "1";
elmt[2] = "2";
elmt[3] = "3";
elmt[4] = "4";
elmt[5] = "7";
elmt[6] = "8";
elmt[7] = "9";
elmt[8] = "10";
elmt[9] = "11";
// Problem here
for (i = 9; i < 10; i++){
document.write("The sum of all the elements is: " + /* Problem here */ + " The average of all the elements is: " + /* Problem here */ + "<br/>");
}
//]]>
</script>

A solution I consider more elegant:
const sum = times.reduce((a, b) => a + b, 0);
const avg = (sum / times.length) || 0;
console.log(`The sum is: ${sum}. The average is: ${avg}.`);

ES6
const average = arr => arr.reduce( ( p, c ) => p + c, 0 ) / arr.length;
const result = average( [ 4, 4, 5, 6, 6 ] ); // 5
console.log(result);

var sum = 0;
for( var i = 0; i < elmt.length; i++ ){
sum += parseInt( elmt[i], 10 ); //don't forget to add the base
}
var avg = sum/elmt.length;
document.write( "The sum of all the elements is: " + sum + " The average is: " + avg );
Just iterate through the array, since your values are strings, they have to be converted to an integer first. And average is just the sum of values divided by the number of values.

Calculating average (mean) using reduce and ES6:
const average = list => list.reduce((prev, curr) => prev + curr) / list.length;
const list = [0, 10, 20, 30]
average(list) // 15

Shortest one liner for Average
const avg = arr => arr.reduce((acc,v,i,a)=>(acc+v/a.length),0);
Shortest one liner for Sum
const sum = arr => arr.reduce((a,b)=>a+b);

Let's imagine we have an array of integers like this:
var values = [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11];
The average is obtained with the following formula
A= (1/n)Σxi ( with i = 1 to n ) ... So: x1/n + x2/n + ... + xn/n
We divide the current value by the number of values and add the previous result to the returned value.
The reduce method signature is
reduce(callback[,default_previous_value])
The reduce callback function takes the following parameters:
p : Result
of the previous calculation
c : Current value (from the current index)
i : Current array element's index value
a : The current reduced Array
The second reduce's parameter is the default value ... (Used in case the array is empty ).
So the average reduce method will be:
var avg = values.reduce(function(p,c,i,a){return p + (c/a.length)},0);
If you prefer you can create a separate function
function average(p,c,i,a){return p + (c/a.length)};
function sum(p,c){return p + c)};
And then simply refer to the callback method signature
var avg = values.reduce(average,0);
var sum= values.reduce(sum,0);
Or Augment the Array prototype directly..
Array.prototype.sum = Array.prototype.sum || function (){
return this.reduce(function(p,c){return p+c},0);
};
It's possible to divide the value each time the reduce method is called..
Array.prototype.avg = Array.prototype.avg || function () {
return this.reduce(function(p,c,i,a){return p+(c/a.length)},0);
};
Or even better , using the previously defined Array.protoype.sum()
method, optimize the process my calling the division only once :)
Array.prototype.avg = Array.prototype.avg || function () {
return this.sum()/this.length;
};
Then on any Array object of the scope:
[2, 6].avg();// -> 4
[2, 6].sum();// -> 8
NB: an empty array with return a NaN wish is more correct than 0 in my point of view and can be useful in specific use cases.

generally average using one-liner reduce is like this
elements.reduce(function(sum, a,i,ar) { sum += a; return i==ar.length-1?(ar.length==0?0:sum/ar.length):sum},0);
specifically to question asked
elements.reduce(function(sum, a,i,ar) { sum += parseFloat(a); return i==ar.length-1?(ar.length==0?0:sum/ar.length):sum},0);
an efficient version is like
elements.reduce(function(sum, a) { return sum + a },0)/(elements.length||1);
Understand Javascript Array Reduce in 1 Minute
http://www.airpair.com/javascript/javascript-array-reduce
as gotofritz pointed out seems Array.reduce skips undefined values.
so here is a fix:
(function average(arr){var finalstate=arr.reduce(function(state,a) { state.sum+=a;state.count+=1; return state },{sum:0,count:0}); return finalstate.sum/finalstate.count})([2,,,6])

You can also use lodash, _.sum(array) and _.mean(array) in Math part (also have other convenient stuff).
_.sum([4, 2, 8, 6]);
// => 20
_.mean([4, 2, 8, 6]);
// => 5

Not the fastest, but the shortest and in one line is using map() & reduce():
var average = [7,14,21].map(function(x,i,arr){return x/arr.length}).reduce(function(a,b){return a + b})

I use these methods in my personal library:
Array.prototype.sum = Array.prototype.sum || function() {
return this.reduce(function(sum, a) { return sum + Number(a) }, 0);
}
Array.prototype.average = Array.prototype.average || function() {
return this.sum() / (this.length || 1);
}
EDIT:
To use them, simply ask the array for its sum or average, like:
[1,2,3].sum() // = 6
[1,2,3].average() // = 2

In ES6-ready browsers this polyfill may be helpful.
Math.sum = (...a) => Array.prototype.reduce.call(a,(a,b) => a+b)
Math.avg = (...a) => Math.sum(...a)/a.length;
You can share same call method between Math.sum,Math.avg and Math.max,such as
var maxOne = Math.max(1,2,3,4) // 4;
you can use Math.sum as
var sumNum = Math.sum(1,2,3,4) // 10
or if you have an array to sum up,you can use
var sumNum = Math.sum.apply(null,[1,2,3,4]) // 10
just like
var maxOne = Math.max.apply(null,[1,2,3,4]) // 4

One sneaky way you could do it although it does require the use of (the much hated) eval().
var sum = eval(elmt.join('+')), avg = sum / elmt.length;
document.write("The sum of all the elements is: " + sum + " The average of all the elements is: " + avg + "<br/>");
Just thought I'd post this as one of those 'outside the box' options. You never know, the slyness might grant you (or taketh away) a point.

Here is a quick addition to the “Math” object in javascript to add a “average” command to it!!
Math.average = function(input) {
this.output = 0;
for (this.i = 0; this.i < input.length; this.i++) {
this.output+=Number(input[this.i]);
}
return this.output/input.length;
}
Then i have this addition to the “Math” object for getting the sum!
Math.sum = function(input) {
this.output = 0;
for (this.i = 0; this.i < input.length; this.i++) {
this.output+=Number(input[this.i]);
}
return this.output;
}
So then all you do is
alert(Math.sum([5,5,5])); //alerts “15”
alert(Math.average([10,0,5])); //alerts “5”
And where i put the placeholder array just pass in your variable (The input if they are numbers can be a string because of it parsing to a number!)

I found Mansilla's answer to work fine with the extension of making sure that I am doing summation of floats and not concatonation of strings using parseFloat():
let sum = ourarray.reduce((a, b) => parseFloat(a) + parseFloat(b), 0);
let avg = (sum / ourarray.length) || 0;
console.log(sum); // print out sum
console.log(avg); // print out avg

set your for loop counter to 0.... you're getting element 9 and then you're done as you have it now. The other answers are basic math. Use a variable to store your sum (need to cast the strings to ints), and divide by your array length.

Start by defining all of the variables we plan on using. You'll note that for the numbers array, I'm using the literal notation of [] as opposed to the constructor method array(). Additionally, I'm using a shorter method to set multiple variables to 0.
var numbers = [], count = sum = avg = 0;
Next I'm populating my empty numbers array with the values 0 through 11. This is to get me to your original starting point. Note how I'm pushing onto the array count++. This pushing the current value of count, and then increments it for the next time around.
while ( count < 12 )
numbers.push( count++ );
Lastly, I'm performing a function "for each" of the numbers in the numbers array. This function will handle one number at a time, which I'm identifying as "n" within the function body.
numbers.forEach(function(n){
sum += n;
avg = sum / numbers.length;
});
In the end, we can output both the sum value, and the avg value to our console in order to see the result:
// Sum: 66, Avg: 5.5
console.log( 'Sum: ' + sum + ', Avg: ' + avg );
See it in action online at http://jsbin.com/unukoj/3/edit

I am just building on Abdennour TOUMI's answer. here are the reasons why:
1.) I agree with Brad, I do not think it is a good idea to extend object that we did not create.
2.) array.length is exactly reliable in javascript, I prefer Array.reduce beacuse a=[1,3];a[1000]=5; , now a.length would return 1001.
function getAverage(arry){
// check if array
if(!(Object.prototype.toString.call(arry) === '[object Array]')){
return 0;
}
var sum = 0, count = 0;
sum = arry.reduce(function(previousValue, currentValue, index, array) {
if(isFinite(currentValue)){
count++;
return previousValue+ parseFloat(currentValue);
}
return previousValue;
}, sum);
return count ? sum / count : 0;
};

Array.prototype.avg=function(fn){
fn =fn || function(e,i){return e};
return (this.map(fn).reduce(function(a,b){return parseFloat(a)+parseFloat(b)},0) / this.length ) ;
};
Then :
[ 1 , 2 , 3].avg() ; //-> OUT : 2
[{age:25},{age:26},{age:27}].avg(function(e){return e.age}); // OUT : 26

On evergreen browsers you can use arrow functions
avg = [1,2,3].reduce((a,b) => (a+b);
Running it 100,000 times, the time difference between the for loop approach and reduce is negligible.
s=Date.now();for(i=0;i<100000;i++){ n=[1,2,3]; a=n.reduce((a,b) => (a+b)) / n.length };
console.log("100k reduce took " + (Date.now()-s) + "ms.");
s=Date.now();for(i=0;i<100000;i++){n=[1,2,3]; nl=n.length; a=0; for(j=nl-1;j>0;j--){a=a+n[j];} a/nl };
console.log("100k for loop took " + (Date.now()-s) + "ms.");
s=Date.now();for(i=0;i<1000000;i++){n=[1,2,3]; nl=n.length; a=0; for(j=nl-1;j>0;j--){a=a+n[j];} a/nl };
console.log("1M for loop took " + (Date.now()-s) + "ms.");
s=Date.now();for(i=0;i<1000000;i++){ n=[1,2,3]; a=n.reduce((a,b) => (a+b)) / n.length };
console.log("1M reduce took " + (Date.now()-s) + "ms.");
/*
* RESULT on Chrome 51
* 100k reduce took 26ms.
* 100k for loop took 35ms.
* 10M for loop took 126ms.
* 10M reduce took 209ms.
*/

If you are in need of the average and can skip the requirement of calculating the sum, you can compute the average with a single call of reduce:
// Assumes an array with only values that can be parsed to a Float
var reducer = function(cumulativeAverage, currentValue, currentIndex) {
// 1. multiply average by currentIndex to find cumulative sum of previous elements
// 2. add currentValue to get cumulative sum, including current element
// 3. divide by total number of elements, including current element (zero-based index + 1)
return (cumulativeAverage * currentIndex + parseFloat(currentValue))/(currentIndex + 1)
}
console.log([1, 2, 3, 4, 5, 6, 7, 8, 9, 10].reduce(reducer, 0)); // => 5.5
console.log([].reduce(reducer, 0)); // => 0
console.log([0].reduce(reducer, 0)); // => 0
console.log([].reduce(reducer, 0)); // => 0
console.log([,,,].reduce(reducer, 0)); // => 0
console.log([].reduce(reducer, 0)); // => 0

If anyone ever needs it - Here is a recursive average.
In the context of the original question, you may want to use the recursive average if you allowed the user to insert additional values and, without incurring the cost of visiting each element again, wanted to "update" the existing average.
/**
* Computes the recursive average of an indefinite set
* #param {Iterable<number>} set iterable sequence to average
* #param {number} initAvg initial average value
* #param {number} initCount initial average count
*/
function average(set, initAvg, initCount) {
if (!set || !set[Symbol.iterator])
throw Error("must pass an iterable sequence");
let avg = initAvg || 0;
let avgCnt = initCount || 0;
for (let x of set) {
avgCnt += 1;
avg = avg * ((avgCnt - 1) / avgCnt) + x / avgCnt;
}
return avg; // or {avg: avg, count: avgCnt};
}
average([2, 4, 6]); //returns 4
average([4, 6], 2, 1); //returns 4
average([6], 3, 2); //returns 4
average({
*[Symbol.iterator]() {
yield 2; yield 4; yield 6;
}
}); //returns 4
How:
this works by maintaining the current average and element count. When a new value is to be included you increment count by 1, scale the existing average by (count-1) / count, and add newValue / count to the average.
Benefits:
you don't sum all the elements, which may result in large number that cannot be stored in a 64-bit float.
you can "update" an existing average if additional values become available.
you can perform a rolling average without knowing the sequence length.
Downsides:
incurs lots more divisions
not infinite - limited to Number.MAX_SAFE_INTEGER items unless you employ BigNumber

Having read the other choices, I will try to make a simpler version for the future viewers, elaborating on the existing code and not creating a more elegant one. First of all, you declared the numbers as strings. Apart from the .parseInt we can also do:
const numberConverter = elmt.map(Number);
So what map does is that it "returns a copy of the original array". But I convert its values to numbers. Then we can use the reduce method (It can also be simpler, but I am writing easy to read versions and I also have 2 average methods) What the reduce method does is it has an accumulator that gets bigger and bigger if you add values to it, as it iterates through the array and adds (in this case) the currentValue to it.:
var i;
const elmt = new Array();
elmt[0] = '0';
elmt[1] = '1';
elmt[2] = '2';
elmt[3] = '3';
elmt[4] = '4';
elmt[5] = '7';
elmt[6] = '8';
elmt[7] = '9';
elmt[8] = '10';
elmt[9] = '11';
console.log(elmt);
const numberConverter = elmt.map(Number);
const sum = numberConverter.reduce((accumulator, currentValue) => {
return accumulator + currentValue;
}, 0);
const average = numberConverter.reduce(
(accumulator, currentvalue, index, numArray) => {
return accumulator + currentvalue / numArray.length;
},
0
);
const average2 =
numberConverter.reduce(
(accumulator, currentValue) => accumulator + currentValue,
0
) / numberConverter.length;
for (i = 9; i < 10; i++) {
console.log(
`The sum of all the elements is: ${sum}. <br> The average of all the elements is: ${average2}`
);}

Unless I missed something, every solution up to this point uses the length of the list to calculate the average after summing the values.
There is a downside to this approach that a slightly modified, yet still simple algorithm will address without the downsides.
The downside is that you assuming that there won't be an overflow by summing all the numbers. If you have a lot of numbers that are very big, and you add them all up, they may exceed the maximum size that can fit into the data type.
A better approach is to simply calculate the average as you go, rather than summing it and then dividing with the length at the end:
function getAvg(values) {
return values.reduce((m, x, i) => m + (x - m) / (i + 1), 0)
}
Props to Knuth's "Art of Computer Programming" vol. 2.

just for fun
let avg = [81, 77, -88, 195, 6.8].reduce((a,e,i) => (a*i+e)/(i+1));
console.log(avg)

Just for kicks:
var elmt = [0, 1, 2,3, 4, 7, 8, 9, 10, 11], l = elmt.length, i = -1, sum = 0;
for (; ++i < l; sum += elmt[i])
;
document.body.appendChild(document.createTextNode('The sum of all the elements is: ' + sum + ' The average of all the elements is: ' + (sum / l)));

I think we can do like
var k=elmt.reduce(function(a,b){return parseFloat(a+parseFloat(b));})
var avg=k/elmt.length;
console.log(avg);
I am using parseFloat twice because
when
1) you add (a)9+b("1") number then result will be "91" but we want addition. so i used parseFloat
2)When addition of (a)9+parseFloat("1") happen though result will be "10" but it will be in string which we don't want so again i used parseFloat.
I hope i am clear. Suggestions are welcome

Here is my rookie way of simply finding the avg. Hope this helps somebody.
function numAvg(num){
var total = 0;
for(var i = 0;i < num.length; i++) {
total+=num[i];
}
return total/num.length;
}

here's your one liner:
var average = arr.reduce((sum,item,index,arr)=>index !== arr.length-1?sum+item:sum+item/arr.length,0)

I think this may be a direct solution to calculate the average with a for loop and function.
var elmts = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11];
function average(arr) {
var total = 0;
for (var i = 0; i < arr.length; i++) {
total += arr[i];
}
console.log(Math.round(total/arr.length));
}
average(elmts);

There seem to be an endless number of solutions for this but I found this to be concise and elegant.
const numbers = [1,2,3,4];
const count = numbers.length;
const reducer = (adder, value) => (adder + value);
const average = numbers.map(x => x/count).reduce(reducer);
console.log(average); // 2.5
Or more consisely:
const numbers = [1,2,3,4];
const average = numbers.map(x => x/numbers.length).reduce((adder, value) => (adder + value));
console.log(average); // 2.5
Depending on your browser you may need to do explicit function calls because arrow functions are not supported:
const r = function (adder, value) {
return adder + value;
};
const m = function (x) {
return x/count;
};
const average = numbers.map(m).reduce(r);
console.log(average); // 2.5
Or:
const average1 = numbers
.map(function (x) {
return x/count;
})
.reduce(function (adder, value) {
return adder + value;
});
console.log(average1);