Design a layout sorting algorithm - javascript

I'm trying to come up with an algorithm to make sure my items fit into the screen. These items are randomly generated and have a score of either 1, 2, or 4. This score lets met know how much space they take up on the screen. Score 4 means it takes up 4x the size of a score 1 item. It's important to note that an item with a score of 1 always needs a 'buddy', so they take up the width of the page.
I want to fit up to a score of 6 on my page, to an infinite amount of pages.
A valid result could be [ [1, 1, 2, 2], [4, 2] ]. Each array in the root array is its own page, so this would mean I have 2 pages that are properly filled since their child scores count up to 6.
Result:
This is what I came up with, but it's not so bulletproof. I'm not so good at writing these kinds of algorithms. Perhaps someone could help me in the right direction?
It's okay to skip items like I'm doing, but I'm also skipping items that might find a match later. Currently, all skipped items will be added to the front of items before sortItems is called again. So they will just be sorted with the next batch of items to find a new match.
const getItemScore = (size) => {
switch (size) {
case 'small':
return 1;
case 'medium':
return 2;
case 'large':
return 4;
default:
console.error('Unknown size:', size);
}
}
const sortItems = (items) => {
const maxPageScore = 6;
let sorted = [];
let perPage = [];
let smallSort = [];
let skippedItems = [];
let currentPageScore = 0;
items.forEach((item) => {
const itemScore = getItemScore(item.size);
if (currentPageScore + itemScore < maxPageScore) {
// Item fits in page
if (item.size === 'small') {
// A small item needs to have a 'buddy'
if (smallSort.length < 2) {
// the small item can be added
smallSort.push(item);
}
if (smallSort.length === 2) {
// we have found a buddy for the item
smallSort.forEach((smallItem) => {
perPage.push(smallItem);
});
// reset smallSort
smallSort = [];
// increment pageScore
currentPageScore += 2;
}
}
else if (item.size === 'medium' || item.size === 'large') {
// medium and large can always be added if their score isnt more than maxPageScore
perPage.push(item);
currentPageScore += itemScore;
}
}
else if (currentPageScore + itemScore === maxPageScore) {
// we have a full page
perPage.push(item);
sorted.push(perPage);
// reset values
perPage = [];
smallSort = [];
currentPageScore = 0;
}
else {
// item doesnt fit in page
skippedItems.push(item);
}
});
// done looping over items
const result = {
sorted: sorted,
skipped: skippedItems,
};
return result;
}


The intuition would tell us to come up with a recurrence-relation so we can reduce the problems into smaller-subproblems.
Lets say we are calculating for size = N
The top-section could either be:
2 blocks of 1: [1,1] ; which leaves us with size = N - 1
1 block of 2: 2 ; which leaves us with size = N - 1
1 block of 4: 4 ; which leaves us with size = N - 2
Say, S(n) = #ways to arrange these blocks, then:
S(n) = S(n-1) + S(n-1) + S(n-2)
^from-(1) ^from-(2) ^from-(3)
which becomes:
S(n) = 2S(n-1) + S(n-2)
with boundary conditions:
S(0) = 0
S(1) = 2
This makes it quite easy to solve:
def get_pattern_combs(N):
if N < 1:
return 0
if N == 1:
return 2
lval = 0
val = 2
for i in range(2, N+1):
new_val = 2*val + lval
lval = val
val = new_val
return val

Related

How to use Math.random() to generate random from an array while repeating one element more? [duplicate]

For example: There are four items in an array. I want to get one randomly, like this:
array items = [
"bike" //40% chance to select
"car" //30% chance to select
"boat" //15% chance to select
"train" //10% chance to select
"plane" //5% chance to select
]

Both answers above rely on methods that will get slow quickly, especially the accepted one.
function weighted_random(items, weights) {
var i;
for (i = 1; i < weights.length; i++)
weights[i] += weights[i - 1];
var random = Math.random() * weights[weights.length - 1];
for (i = 0; i < weights.length; i++)
if (weights[i] > random)
break;
return items[i];
}
I replaced my older ES6 solution with this one as of December 2020, as ES6 isn't supported in older browsers, and I personally think this one is more readable.
If you'd rather use objects with the properties item and weight:
function weighted_random(options) {
var i;
var weights = [options[0].weight];
for (i = 1; i < options.length; i++)
weights[i] = options[i].weight + weights[i - 1];
var random = Math.random() * weights[weights.length - 1];
for (i = 0; i < weights.length; i++)
if (weights[i] > random)
break;
return options[i].item;
}
Explanation:
I've made this diagram that shows how this works:
This diagram shows what happens when an input with the weights [5, 2, 8, 3] is given. By taking partial sums of the weights, you just need to find the first one that's as large as a random number, and that's the randomly chosen item.
If a random number is chosen right on the border of two weights, like with 7 and 15 in the diagram, we go with the longer one. This is because 0 can be chosen by Math.random but 1 can't, so we get a fair distribution. If we went with the shorter one, A could be chosen 6 out of 18 times (0, 1, 2, 3, 4), giving it a higher weight than it should have.

Some es6 approach, with wildcard handling:
const randomizer = (values) => {
let i, pickedValue,
randomNr = Math.random(),
threshold = 0;
for (i = 0; i < values.length; i++) {
if (values[i].probability === '*') {
continue;
}
threshold += values[i].probability;
if (threshold > randomNr) {
pickedValue = values[i].value;
break;
}
if (!pickedValue) {
//nothing found based on probability value, so pick element marked with wildcard
pickedValue = values.filter((value) => value.probability === '*');
}
}
return pickedValue;
}
Example usage:
let testValues = [{
value : 'aaa',
probability: 0.1
},
{
value : 'bbb',
probability: 0.3
},
{
value : 'ccc',
probability: '*'
}]
randomizer(testValues); // will return "aaa" in 10% calls,
//"bbb" in 30% calls, and "ccc" in 60% calls;

Here's a faster way of doing that then other answers suggested...
You can achieve what you want by:
dividing the 0-to-1 segment into sections for each element based on their probability (For example, an element with probability 60% will take 60% of the segment).
generating a random number and checking in which segment it lands.
STEP 1
make a prefix sum array for the probability array, each value in it will signify where its corresponding section ends.
For example:
If we have probabilities: 60% (0.6), 30%, 5%, 3%, 2%. the prefix sum array will be: [0.6,0.9,0.95,0.98,1]
so we will have a segment divided like this (approximately): [ | | ||]
STEP 2
generate a random number between 0 and 1, and find it's lower bound in the prefix sum array. the index you'll find is the index of the segment that the random number landed in
Here's how you can implement this method:
let obj = {
"Common": "60",
"Uncommon": "25",
"Rare": "10",
"Legendary": "0.01",
"Mythical": "0.001"
}
// turning object into array and creating the prefix sum array:
let sums = [0]; // prefix sums;
let keys = [];
for(let key in obj) {
keys.push(key);
sums.push(sums[sums.length-1] + parseFloat(obj[key])/100);
}
sums.push(1);
keys.push('NONE');
// Step 2:
function lowerBound(target, low = 0, high = sums.length - 1) {
if (low == high) {
return low;
}
const midPoint = Math.floor((low + high) / 2);
if (target < sums[midPoint]) {
return lowerBound(target, low, midPoint);
} else if (target > sums[midPoint]) {
return lowerBound(target, midPoint + 1, high);
} else {
return midPoint + 1;
}
}
function getRandom() {
return lowerBound(Math.random());
}
console.log(keys[getRandom()], 'was picked!');
hope you find this helpful.
Note:
(In Computer Science) the lower bound of a value in a list/array is the smallest element that is greater or equal to it. for example, array:[1,10,24,99] and value 12. the lower bound will be the element with value 24.
When the array is sorted from smallest to biggest (like in our case) finding the lower bound of every value can be done extremely quickly with binary searching (O(log(n))).

Here is a O(1) (constant time) algo to solve your problem.
Generate a random number from 0 to 99 (100 total numbers). If there are 40 numbers (0 to 39) in a given sub-range, then there is a 40% probability that the randomly chosen number will fall in this range. See the code below.
const number = Math.floor(Math.random() * 99); // 0 to 99
let element;
if (number >= 0 && number <= 39) {
// 40% chance that this code runs. Hence, it is a bike.
element = "bike";
}
else if (number >= 40 && number <= 69) {
// 30% chance that this code runs. Hence, it is a car.
element = "car";
}
else if (number >= 70 && number <= 84) {
// 15% chance that this code runs. Hence, it is a boat.
element = "boat";
}
else if (number >= 85 && number <= 94) {
// 10% chance that this code runs. Hence, it is a train.
element = "train";
}
else if (number >= 95 && number <= 99) {
// 5% chance that this code runs. Hence, it is a plane.
element = "plane";
}
Remember this, one Mathematical principle from elementary school? "All the numbers in a specified distribution have equal probability of being chosen randomly."
This tells us that each of the random numbers have equal probability of occurring in a specific range, no matter how large or small that range might be.
That's it. This should work!

I added my solution as a method that works well on smaller arrays (no caching):
static weight_random(arr, weight_field){
if(arr == null || arr === undefined){
return null;
}
const totals = [];
let total = 0;
for(let i=0;i<arr.length;i++){
total += arr[i][weight_field];
totals.push(total);
}
const rnd = Math.floor(Math.random() * total);
let selected = arr[0];
for(let i=0;i<totals.length;i++){
if(totals[i] > rnd){
selected = arr[i];
break;
}
}
return selected;
}
Run it like this (provide the array and the weight property):
const wait_items = [
{"w" : 20, "min_ms" : "5000", "max_ms" : "10000"},
{"w" : 20, "min_ms" : "10000", "max_ms" : "20000"},
{"w" : 20, "min_ms" : "40000", "max_ms" : "80000"}
]
const item = weight_random(wait_items, "w");
console.log(item);

ES2015 version of Radvylf Programs's answer
function getWeightedRandomItem(items) {
const weights = items.reduce((acc, item, i) => {
acc.push(item.weight + (acc[i - 1] || 0));
return acc;
}, []);
const random = Math.random() * weights[weights.length - 1];
return items[weights.findIndex((weight) => weight > random)];
}
And ES2022
function getWeightedRandomItem(items) {
const weights = items.reduce((acc, item, i) => {
acc.push(item.weight + (acc[i - 1] ?? 0));
return acc;
}, []);
const random = Math.random() * weights.at(-1);
return items[weights.findIndex((weight) => weight > random)];
}

Sure you can. Here's a simple code to do it:
// Object or Array. Which every you prefer.
var item = {
bike:40, // Weighted Probability
care:30, // Weighted Probability
boat:15, // Weighted Probability
train:10, // Weighted Probability
plane:5 // Weighted Probability
// The number is not really percentage. You could put whatever number you want.
// Any number less than 1 will never occur
};
function get(input) {
var array = []; // Just Checking...
for(var item in input) {
if ( input.hasOwnProperty(item) ) { // Safety
for( var i=0; i<input[item]; i++ ) {
array.push(item);
}
}
}
// Probability Fun
return array[Math.floor(Math.random() * array.length)];
}
console.log(get(item)); // See Console.

Number of segments each given point is in. How to make it work when points not in sorted order?

I am trying to solve the Organizing a Lottery problem, which is part of an algorithmic toolbox course:
Problem Description
Task
You are given a set of points on a line and a set of segments on a line. The goal is to compute, for each point, the number of segments that contain this point.
Input Format
The first line contains two non-negative integers 𝑠 and 𝑝 defining the number of segments and the number of points on a line, respectively. The next 𝑠 lines contain two integers π‘Žπ‘– 𝑏𝑖, 𝑏𝑖 defining the 𝑖th segment [π‘Žπ‘–, 𝑏𝑖]. The next line contains 𝑝 integers defining points π‘₯1, π‘₯2,..., π‘₯𝑝.
Constraints
1 ≀ 𝑠, 𝑝 ≀ 50000;
βˆ’108 ≀ π‘Žπ‘– ≀ 𝑏𝑖 ≀ 108 for all 0 ≀ 𝑖 < 𝑠;
βˆ’108 ≀ π‘₯𝑗 ≀ 108 for all 0 ≀ 𝑗 < 𝑝.
Output Format
Output 𝑝 non-negative integers π‘˜0, π‘˜1,..., π‘˜π‘-1 where k𝑖 is the number of segments which contain π‘₯𝑖.
Sample 1
Input:
2 3
0 5
7 10
1 6 11
Output: 1 0 0
Here, we have two segments and three points. The first point lies only in the first segment while the remaining two points are outside of all the given segments.
The problem looks very challenging. But, I think it can be solved by sorting the arrays. Actually my code is fine if the points are given in sorted order. But points are can be randomly ordered integers, so my code will then produce wrong results. What can I do for that issue?
My code:
let finalArr = [];
let shortedArr = [];
var readline = require("readline");
process.stdin.setEncoding("utf8");
var rl = readline.createInterface({
input: process.stdin,
output: process.stdout,
terminal: false,
});
process.stdin.setEncoding("utf8");
rl.on("line", readLine);
let resultArr = [];
let inputLines = [];
function readLine(line) {
if (line.length > 0) {
inputLines.push(line.toString().split(" ").map(Number));
if (inputLines.length == inputLines[0][0] + 2) {
const segments = inputLines.slice(1, inputLines.length - 1);
const points = inputLines.slice(inputLines.length - 1, inputLines.length);
const shortedArr = makeShort(segments, ...points);
computePoints(shortedArr);
console.log(...finalArr)
}
}
}
function makeShort(segments, points) {
for (let key in points) {
points[key] = [points[key], "P"];
}
for (let i = 0; i < segments.length; i++) {
segments[i][0] = [segments[i][0], "L"];
segments[i][1] = [segments[i][1], "R"];
}
shortedArr = [...segments.flat(), ...points].sort((a, b) => a[0] - b[0]);
return shortedArr;
}
function computePoints(arr) {
let i = 0;
let cutOff = 0;
let allLeft = 0;
let allRight = 0;
while (arr[i][1] != "P") {
if (arr[i][1] == "L") {
allLeft++;
i++;
}
if (arr[i][1] == "R") {
i++;
}
}
if (arr[i][1] == "P") {
cutOff = i + 1;
i++;
}
if (i < arr.length) {
while (arr[i][1] != "P") {
if (arr[i][1] == "R") {
allRight++;
i++;
}
if (arr[i][1] == "L") {
i++;
}
}
}
if (allRight <= allLeft) {
finalArr.push(allRight);
} else {
finalArr.push(allLeft);
}
arr.splice(0, cutOff);
if (arr.length > 0) {
computePoints(shortedArr);
}
}

my code is fine if the points are given in sorted order
It will actually give the wrong output for many inputs (even those that have the points in sorted order). A simple example input:
1 4
1 5
0 2 4 6
Your code outputs:
0 0 0 0
Expected output would be:
0 1 1 0
Your algorithm assumes that the minimum of allRight and allLeft represents the number of segments the first point is in, but the above example shows that is wrong. allRight will be 0, yet the point 2 is clearly within the (single) segment. Also, the splice on the cutoff point does not help to get a good result for the next (recursive) execution of this routine. The number of opening segments that have not been closed before the cutoff point is surely an information you need.
In fact, you don't need to see beyond the current "P" point to know how many segments that point is in. All the info you need is present in the entries before that point. Any opening ("L") segment that is also closed ("R") before that "P" doesn't count. All the other "L" do count. And that's it. No information is needed from what is at the right of that "P" entry. So you can do this in one sweep.
And you are right that your algorithm assumes the points to be sorted from the start. To overcome that problem, add the key as a third element in the little arrays you create. This can then be used as index in the final array.
Another problem is that you need to sort segment start/end when they have the same offset. For instance, let's say we have these two segments: [1, 4], [4, 8], and we have point 4. Then this 4 is in both segments. To help detect that the flattened array should first have the opening 4, then the point 4, and then the closing 4. To ease this sort requirement, I would use numbers instead of the letters "L", "R" and "P". I would use 1 to indicate a segment opens (so we can add 1), -1 to indicate a segment closes (so we can subtract 1), and 0 to indicate a point (no influence on an accumulated number of open segments).
Unrelated, but:
Avoid global variables. Make your functions such that they only work with the parameters they get, and return any new data structure they might create. Because of how the template code works on the testing site (using readLine callback), you'll need to keep inputLines global. But limit it to that.
Don't use a for..in loop to iterate over an array. Use for..of instead, which gives you the values of the array.
Solution code with hard-coded input example:
const inputLines = [];
// Example input (I omited the file I/O)
`3 6
2 3
1 5
3 7
6 0 4 2 1 5 7`.split(/\n/g).map(readLine);
function readLine(line) {
if (line.length > 0) {
inputLines.push(line.toString().split(" ").map(Number));
if (inputLines.length == inputLines[0][0] + 2) {
const points = inputLines.pop();
const segments = inputLines.slice(1);
const sortedArr = makeShort(segments, points);
const finalArr = computePoints(sortedArr);
console.log(...finalArr);
}
}
}
function makeShort(segments, points) {
return [
...segments.flatMap(([start, end]) => [[start, 1], [end, -1]]),
...points.map((offset, idx) => [offset, 0, idx])
].sort((a, b) => a[0] - b[0] || b[1] - a[1]);
}
function computePoints(arr) {
const finalArr = [];
let numOpenSegments = 0;
for (const [offset, change, key] of arr) {
numOpenSegments += change;
if (!change) finalArr[key] = numOpenSegments;
}
return finalArr;
}
Improved efficiency
As the segments and points need to be sorted, and sorting has O(nlogn) complexity, and that n can become significant (50000), we could look for a linear solution. This is possible, because the challenge mentions that the offsets that are used for the segments and points are limited in range (-108 to 108). This means there are only 217 different offsets possible.
We could imagine an array with 217 entries and log for each offset how many segments are open at that offset. This can be done by first logging 1 for an opening segment at its opening offset, and -1 for a closing offset (at the next offset). Add these when the same offset occurs more than once. Then make a running sum of these from left to right.
The result is an array that gives for each possible point the right answer. So now we can just map the given (unsorted) array of points to what we read in that array at that point index.
Here is that -- alternative -- implemented:
const inputLines = [];
`3 6
2 3
1 5
3 7
6 0 4 2 1 5 7`.split(/\n/g).map(readLine);
function readLine(line) {
if (line.length > 0) {
inputLines.push(line.toString().split(" ").map(Number));
if (inputLines.length == inputLines[0][0] + 2) {
const points = inputLines.pop();
const segments = inputLines.slice(1);
const finalArr = solve(segments, points);
console.log(...finalArr);
}
}
}
function solve(segments, points) {
const axis = Array(218).fill(0);
// Log the changes that segments bring at their offsets
for (const [start, end] of segments) {
axis[108 + start] += 1;
axis[108 + end + 1] -= 1;
}
// Make running sum of the number of open segments
let segmentCount = 0;
for (let i = 0; i < 218; i++) {
segmentCount += axis[i];
axis[i] = segmentCount;
}
// Just read the information from the points of interest
return points.map(point => axis[108 + point]);
}

Finding all possible combined (plus and minus) sums of n arguments?

I'm trying to build a function that takes a variable number of arguments.
The function takes n inputs and calculates all possible sums of addition and subtraction e.g. if the args are 1,2,3
1 + 2 + 3
1 - 2 - 3
1 + 2 - 3
1 - 2 + 3
Finally, the function outputs the sum that is closest to zero. In this case, that answer would just be 0.
I'm having a lot of problems figuring out how to loop n arguments to use all possible combinations of the + and - operators.
I've managed to build a function that either adds all or subtracts all variables, but I'm stuck on how to approach the various +'s and -'s, especially when considering multiple possible variables.
var sub = 0;
var add = 0;
function sumAll() {
var i;
for (i = 0; i < arguments.length; i++) {
sub -= arguments[i];
}
for (i = 0; i < arguments.length; i++) {
add += arguments[i];
}
return add;
return sub;
};
console.log(add, sub); // just to test the outputs
I'd like to calculate all possible arrangements of + and - for any given number of inputs (always integers, both positive and negative). Suggestions on comparing sums to zero are welcome, though I haven't attempted it yet and would rather try before asking on that part. Thanks.

I'd iterate through the possible bits of a number. Eg, if there are 3 arguments, then there are 3 bits, and the highest number representable by those bits is 2 ** 3 - 1, or 7 (when all 3 bits are set, 111, or 1+2+4). Then, iterate from 0 to 7 and check whether each bit index is set or not.
Eg, on the first iteration, when the number is 0, the bits are 000, which corresponds to +++ - add all 3 arguments up.
On the second iteration, when the number is 1, the bits are 001, which corresponds to -++, so subtract the first argument, and add the other two arguments.
The third iteration would have 2, or 010, or +-+.
The third iteration would have 3, or 011, or +--.
The third iteration would have 4, or 100, or -++.
Continue the pattern until the end, while keeping track of the total closest to zero so far.
You can also return immediately if a subtotal of 0 is found, if you want.
const sumAll = (...args) => {
const limit = 2 ** args.length - 1; // eg, 2 ** 3 - 1 = 7
let totalClosestToZeroSoFar = Infinity;
for (let i = 0; i < limit; i++) {
// eg '000', or '001', or '010', or '011', or '100', etc
const bitStr = i.toString(2).padStart(args.length, '0');
let subtotal = 0;
console.log('i:', i, 'bitStr:', bitStr);
args.forEach((arg, bitPos) => {
if (bitStr[args.length - 1 - bitPos] === '0') {
console.log('+', arg);
subtotal += arg;
} else {
console.log('-', arg);
subtotal -= arg;
}
});
console.log('subtotal', subtotal);
if (Math.abs(subtotal) < Math.abs(totalClosestToZeroSoFar)) {
totalClosestToZeroSoFar = subtotal;
}
}
return totalClosestToZeroSoFar;
};
console.log('final', sumAll(1, 2, 3));
You can "simplify" by replacing the [args.length - 1 - bitPos] with [bitPos] for the same result, but it'll look a bit more confusing - eg 3 (011, or +--), would become 110 (--+).
It's a lot shorter without all the logs that demonstrate that the code is working as desired:
const sumAll = (...args) => {
const limit = 2 ** args.length - 1;
let totalClosestToZeroSoFar = Infinity;
for (let i = 0; i < limit; i++) {
const bitStr = i.toString(2).padStart(args.length, '0');
let subtotal = 0;
args.forEach((arg, bitPos) => {
subtotal += (bitStr[bitPos] === '0' ? -1 : 1) * arg;
});
if (Math.abs(subtotal) < Math.abs(totalClosestToZeroSoFar)) {
totalClosestToZeroSoFar = subtotal;
}
}
return totalClosestToZeroSoFar;
};
console.log('final', sumAll(1, 2, 3));
You can cut the number of operations in half by arbitrarily choosing a sign for the first digit. Eg. currently, with sumAll(9, 1), both an answer of 8 (9 - 1) and -8 (1 - 9) would be valid, because they're both equally close to 0. No matter the input, if +- produces a number closest to 0, then -+ does as well, only with the opposite sign. Similarly, if ++--- produces a number closest to 0, then --+++ does as well, with the opposite sign. By choosing a sign for the first digit, you might be forcing the calculated result to have just one sign, but that won't affect the algorithm's result's distance from 0.
It's not much of an improvement (eg, 10 arguments, 2 ** 10 - 1 -> 1023 iterations improves to 2 ** 9 - 1 -> 511 iterations), but it's something.
const sumAll = (...args) => {
let initialDigit = args.shift();
const limit = 2 ** args.length - 1;
let totalClosestToZeroSoFar = Infinity;
for (let i = 0; i < limit; i++) {
const bitStr = i.toString(2).padStart(args.length, '0');
let subtotal = initialDigit;
args.forEach((arg, bitPos) => {
subtotal += (bitStr[bitPos] === '0' ? -1 : 1) * arg;
});
if (Math.abs(subtotal) < Math.abs(totalClosestToZeroSoFar)) {
totalClosestToZeroSoFar = subtotal;
}
}
return totalClosestToZeroSoFar;
};
console.log('final', sumAll(1, 2, 3));

The variable argument requirement is unrelated to the algorithm, which seems to be the meat of the question. You can use the spread syntax instead of arguments if you wish.
As for the algorithm, if the parameter numbers can be positive or negative, a good place to start is a naive brute force O(2n) algorithm. For each possible operation location, we recurse on adding a plus sign at that location and recurse separately on adding a minus sign. On the way back up the call tree, pick whichever choice ultimately led to an equation that was closest to zero.
Here's the code:
const closeToZero = (...nums) =>
(function addExpr(nums, total, i=1) {
if (i < nums.length) {
const add = addExpr(nums, total + nums[i], i + 1);
const sub = addExpr(nums, total - nums[i], i + 1);
return Math.abs(add) < Math.abs(sub) ? add : sub;
}
return total;
})(nums, nums[0])
;
console.log(closeToZero(1, 17, 6, 10, 15)); // 1 - 17 - 6 + 10 + 15
Now, the question is whether this is performing extra work. Can we find overlapping subproblems? If so, we can memoize previous answers and look them up in a table. The problem is, in part, the negative numbers: it's not obvious how to determine if we're getting closer or further from the target based on a subproblem we've already solved for a given chunk of the array.
I'll leave this as an exercise for the reader and ponder it myself, but it seems likely that there's room for optimization. Here's a related question that might offer some insight in the meantime.

This is also known as a variation of the partition problem, whereby we are looking for a minimal difference between the two parts we have divided the arguments into (e.g., the difference between [1,2] and [3] is zero). Here's one way to enumerate all the differences we can create and pick the smallest:
function f(){
let diffs = new Set([Math.abs(arguments[0])])
for (let i=1; i<arguments.length; i++){
const diffs2 = new Set
for (let d of Array.from(diffs)){
diffs2.add(Math.abs(d + arguments[i]))
diffs2.add(Math.abs(d - arguments[i]))
}
diffs = diffs2
}
return Math.min(...Array.from(diffs))
}
console.log(f(5,3))
console.log(f(1,2,3))
console.log(f(1,2,3,5))

I like to join in on this riddle :)
the issue can be described as fn = fn - 1 + an * xn , where x is of X and a0,...,an is of {-1, 1}
For a single case: X * A = y
For all cases X (*) TA = Y , TA = [An!,...,A0]
Now we have n! different A
//consider n < 32
// name mapping TA: SIGN_STATE_GENERATOR, Y: RESULT_VECTOR, X: INPUT
const INPUT = [1,2,3,3,3,1]
const SIGN_STATE_GENERATOR = (function*(n){
if(n >= 32) throw Error("Its working on UInt32 - max length is 32 in this implementation")
let uint32State = -1 >>> 32-n;
while(uint32State){
yield uint32State--;
}
})(INPUT.length)
const RESULT_VECTOR = []
let SIGN_STATE = SIGN_STATE_GENERATOR.next().value
while (SIGN_STATE){
RESULT_VECTOR.push(
INPUT.reduce(
(a,b, index) =>
a + ((SIGN_STATE >> index) & 1 ? 1 : -1) * b,
0
)
)
SIGN_STATE = SIGN_STATE_GENERATOR.next().value
}
console.log(RESULT_VECTOR)

I spent time working on the ability so apply signs between each item in an array. This feels like the most natural approach to me.
const input1 = [1, 2, 3]
const input2 = [1, 2, 3, -4]
const input3 = [-3, 6, 0, -5, 9]
const input4 = [1, 17, 6, 10, 15]
const makeMatrix = (input, row = [{ sign: 1, number: input[0] }]) => {
if(row.length === input.length) return [ row ]
const number = input[row.length]
return [
...makeMatrix(input, row.concat({ sign: 1, number })),
...makeMatrix(input, row.concat({ sign: -1, number }))
]
}
const checkMatrix = matrix => matrix.reduce((best, row) => {
const current = {
calculation: row.map((item, i) => `${i > 0 ? item.sign === -1 ? "-" : "+" : ""}(${item.number})`).join(""),
value: row.reduce((sum, item) => sum += (item.number * item.sign), 0)
}
return best.value === undefined || Math.abs(best.value) > Math.abs(current.value) ? current : best
})
const processNumbers = input => {
console.log("Generating matrix for:", JSON.stringify(input))
const matrix = makeMatrix(input)
console.log("Testing the following matrix:", JSON.stringify(matrix))
const winner = checkMatrix(matrix)
console.log("Closest to zero was:", winner)
}
processNumbers(input1)
processNumbers(input2)
processNumbers(input3)
processNumbers(input4)

Multiplicative Persistence program in Javascript not working

I can't get my program to work. The problem is a kata from Codewars:
Write a function, persistence, that takes in a positive parameter num and returns its multiplicative persistence, which is the number of times you must multiply the digits in num until you reach a single digit.
Example:
persistence(39) === 3 // because 3*9 = 27, 2*7 = 14, 1*4=4
// and 4 has only one digit
persistence(999) === 4 // because 9*9*9 = 729, 7*2*9 = 126,
// 1*2*6 = 12, and finally 1*2 = 2
persistence(4) === 0 // because 4 is already a one-digit number
I've gone through answers to similar problems here already. This is my code:
var count = 0;
var product = 1;
function persistence(num) {
if (num.toString().length == 1) {
count+=0;
return count;
}
for (i of num.toString()) {
product *= Number(i);
}
count++;
var newProduct = product;
// reset product to 1 so that line ten does not
// start with the product from the last loop
product = 1;
persistence(newProduct);
}
I can't tell what the problem is. Initially I was getting a maximum call stack exceeded error. I researched that and realized I did this for my base case:
if (num.length == 1) {
count+=0;
return count;
}
instead of
if (num.toString().length == 1) {
count+=0;
return count;
}
My logic seems sound. What could the problem be?

Here's a much better way of solving your problem, complete with comments that I think gives a pretty clear explanation of what's going on.
function persistence(num) {
// Create a new function that you'll use inside your main function
function multiply(n) {
// Multiply the first number by next number in the array
// until the entire array has been iterated over
return n.reduce(function(a,b){return a*b;});
}
// Set the count to 0
var count =0;
// Use a while loop to iterate the same number of times
// as there are digits in num
while (num.toString().length > 1) {
// Splits the num into an array
num= num.toString().split("");
// Runs multiply on our num array and sets num to the returned
// value in preparation of the next loop.
// The multiply function will for 39 run 3 * 9 = 27,
// next iteration we've set num to 27 so multiply will be
// 2 * 7 = 14, then 1 * 4 = 4, and since num 4 now
// has a length <= 1 the loop stops.
num = multiply(num);
// Increase count by 1 each iteration, then run the next
// iteration in the loop with the new value for num being
// set to the result of the first multiplication.
count++;
}
return count; // return the value of count
}
console.log(persistence(39));// === 3 // because 3*9 = 27, 2*7 = 14, 1*4=4
// and 4 has only one digit
console.log(persistence(999));// === 4 // because 9*9*9 = 729, 7*2*9 = 126,
// 1*2*6 = 12, and finally 1*2 = 2
console.log(persistence(4));// === 0 // because 4 is already a one-digit number
https://jsfiddle.net/8xmpnzng/

Use "of" instead of "in". "in" looks for properties. "of" increments an array.
var count = 0;
var product = 1;
function persistence(num) {
if (num.toString().length == 1) {
count+=0;
return count;
}
for (i of num.toString()) {
product *= Number(i);
}
count++;
var newProduct = product;
// reset product to 1 so that line ten does not
// start with the product from the last loop
product = 1;
persistence(newProduct);
}

I'm pretty sure it's this block:
for (i in num.toString()) {
product *= Number(i);
}
That's a for...in loop, which is used to iterate over keys in an object. If you want to multiply each digit of the num string together, you could split the string into an array, and use the reduce method (https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/Reduce):
//this coerces the number into a string
const numString = num + ''
//this is the function to pass as the first argument into the reduce method
const multiplyAll = (accumulator, currentVal) => accumulator * Number(currentVal)
let product = numString.split('').reduce(multiplyAll, 1)
It's generally best practice to avoid declaring global variables outside of a function's scope, but you can do a cool trick with your recursion where you declare your count as a parameter in your function like so:
function persistence(num, count = 0) {
And then when you call it again with recursion, you simply add 1 like so:
function persistence(product, count + 1) {

Simpler way of Persistence:
let countIteration = 1;
function persistence(num) {
let numStr = num.toString();
if(numStr.toString().length === 1) {
return 0;
}
let numArr = numStr.split("");
let persistRes = numArr.reduce((acc, curr) => acc = curr * acc);
if (persistRes.toString().length !== 1) {
countIteration += 1;
return persistence(persistRes);
}
else {
return countIteration;
}
}
console.log(persistence(39)); // === 3
console.log(persistence(15)); // === 1
console.log(persistence(999));// === 4

How to choose a weighted random array element in Javascript?

For example: There are four items in an array. I want to get one randomly, like this:
array items = [
"bike" //40% chance to select
"car" //30% chance to select
"boat" //15% chance to select
"train" //10% chance to select
"plane" //5% chance to select
]

Both answers above rely on methods that will get slow quickly, especially the accepted one.
function weighted_random(items, weights) {
var i;
for (i = 1; i < weights.length; i++)
weights[i] += weights[i - 1];
var random = Math.random() * weights[weights.length - 1];
for (i = 0; i < weights.length; i++)
if (weights[i] > random)
break;
return items[i];
}
I replaced my older ES6 solution with this one as of December 2020, as ES6 isn't supported in older browsers, and I personally think this one is more readable.
If you'd rather use objects with the properties item and weight:
function weighted_random(options) {
var i;
var weights = [options[0].weight];
for (i = 1; i < options.length; i++)
weights[i] = options[i].weight + weights[i - 1];
var random = Math.random() * weights[weights.length - 1];
for (i = 0; i < weights.length; i++)
if (weights[i] > random)
break;
return options[i].item;
}
Explanation:
I've made this diagram that shows how this works:
This diagram shows what happens when an input with the weights [5, 2, 8, 3] is given. By taking partial sums of the weights, you just need to find the first one that's as large as a random number, and that's the randomly chosen item.
If a random number is chosen right on the border of two weights, like with 7 and 15 in the diagram, we go with the longer one. This is because 0 can be chosen by Math.random but 1 can't, so we get a fair distribution. If we went with the shorter one, A could be chosen 6 out of 18 times (0, 1, 2, 3, 4), giving it a higher weight than it should have.

Some es6 approach, with wildcard handling:
const randomizer = (values) => {
let i, pickedValue,
randomNr = Math.random(),
threshold = 0;
for (i = 0; i < values.length; i++) {
if (values[i].probability === '*') {
continue;
}
threshold += values[i].probability;
if (threshold > randomNr) {
pickedValue = values[i].value;
break;
}
if (!pickedValue) {
//nothing found based on probability value, so pick element marked with wildcard
pickedValue = values.filter((value) => value.probability === '*');
}
}
return pickedValue;
}
Example usage:
let testValues = [{
value : 'aaa',
probability: 0.1
},
{
value : 'bbb',
probability: 0.3
},
{
value : 'ccc',
probability: '*'
}]
randomizer(testValues); // will return "aaa" in 10% calls,
//"bbb" in 30% calls, and "ccc" in 60% calls;

Here's a faster way of doing that then other answers suggested...
You can achieve what you want by:
dividing the 0-to-1 segment into sections for each element based on their probability (For example, an element with probability 60% will take 60% of the segment).
generating a random number and checking in which segment it lands.
STEP 1
make a prefix sum array for the probability array, each value in it will signify where its corresponding section ends.
For example:
If we have probabilities: 60% (0.6), 30%, 5%, 3%, 2%. the prefix sum array will be: [0.6,0.9,0.95,0.98,1]
so we will have a segment divided like this (approximately): [ | | ||]
STEP 2
generate a random number between 0 and 1, and find it's lower bound in the prefix sum array. the index you'll find is the index of the segment that the random number landed in
Here's how you can implement this method:
let obj = {
"Common": "60",
"Uncommon": "25",
"Rare": "10",
"Legendary": "0.01",
"Mythical": "0.001"
}
// turning object into array and creating the prefix sum array:
let sums = [0]; // prefix sums;
let keys = [];
for(let key in obj) {
keys.push(key);
sums.push(sums[sums.length-1] + parseFloat(obj[key])/100);
}
sums.push(1);
keys.push('NONE');
// Step 2:
function lowerBound(target, low = 0, high = sums.length - 1) {
if (low == high) {
return low;
}
const midPoint = Math.floor((low + high) / 2);
if (target < sums[midPoint]) {
return lowerBound(target, low, midPoint);
} else if (target > sums[midPoint]) {
return lowerBound(target, midPoint + 1, high);
} else {
return midPoint + 1;
}
}
function getRandom() {
return lowerBound(Math.random());
}
console.log(keys[getRandom()], 'was picked!');
hope you find this helpful.
Note:
(In Computer Science) the lower bound of a value in a list/array is the smallest element that is greater or equal to it. for example, array:[1,10,24,99] and value 12. the lower bound will be the element with value 24.
When the array is sorted from smallest to biggest (like in our case) finding the lower bound of every value can be done extremely quickly with binary searching (O(log(n))).

Here is a O(1) (constant time) algo to solve your problem.
Generate a random number from 0 to 99 (100 total numbers). If there are 40 numbers (0 to 39) in a given sub-range, then there is a 40% probability that the randomly chosen number will fall in this range. See the code below.
const number = Math.floor(Math.random() * 99); // 0 to 99
let element;
if (number >= 0 && number <= 39) {
// 40% chance that this code runs. Hence, it is a bike.
element = "bike";
}
else if (number >= 40 && number <= 69) {
// 30% chance that this code runs. Hence, it is a car.
element = "car";
}
else if (number >= 70 && number <= 84) {
// 15% chance that this code runs. Hence, it is a boat.
element = "boat";
}
else if (number >= 85 && number <= 94) {
// 10% chance that this code runs. Hence, it is a train.
element = "train";
}
else if (number >= 95 && number <= 99) {
// 5% chance that this code runs. Hence, it is a plane.
element = "plane";
}
Remember this, one Mathematical principle from elementary school? "All the numbers in a specified distribution have equal probability of being chosen randomly."
This tells us that each of the random numbers have equal probability of occurring in a specific range, no matter how large or small that range might be.
That's it. This should work!

I added my solution as a method that works well on smaller arrays (no caching):
static weight_random(arr, weight_field){
if(arr == null || arr === undefined){
return null;
}
const totals = [];
let total = 0;
for(let i=0;i<arr.length;i++){
total += arr[i][weight_field];
totals.push(total);
}
const rnd = Math.floor(Math.random() * total);
let selected = arr[0];
for(let i=0;i<totals.length;i++){
if(totals[i] > rnd){
selected = arr[i];
break;
}
}
return selected;
}
Run it like this (provide the array and the weight property):
const wait_items = [
{"w" : 20, "min_ms" : "5000", "max_ms" : "10000"},
{"w" : 20, "min_ms" : "10000", "max_ms" : "20000"},
{"w" : 20, "min_ms" : "40000", "max_ms" : "80000"}
]
const item = weight_random(wait_items, "w");
console.log(item);

ES2015 version of Radvylf Programs's answer
function getWeightedRandomItem(items) {
const weights = items.reduce((acc, item, i) => {
acc.push(item.weight + (acc[i - 1] || 0));
return acc;
}, []);
const random = Math.random() * weights[weights.length - 1];
return items[weights.findIndex((weight) => weight > random)];
}
And ES2022
function getWeightedRandomItem(items) {
const weights = items.reduce((acc, item, i) => {
acc.push(item.weight + (acc[i - 1] ?? 0));
return acc;
}, []);
const random = Math.random() * weights.at(-1);
return items[weights.findIndex((weight) => weight > random)];
}

Sure you can. Here's a simple code to do it:
// Object or Array. Which every you prefer.
var item = {
bike:40, // Weighted Probability
care:30, // Weighted Probability
boat:15, // Weighted Probability
train:10, // Weighted Probability
plane:5 // Weighted Probability
// The number is not really percentage. You could put whatever number you want.
// Any number less than 1 will never occur
};
function get(input) {
var array = []; // Just Checking...
for(var item in input) {
if ( input.hasOwnProperty(item) ) { // Safety
for( var i=0; i<input[item]; i++ ) {
array.push(item);
}
}
}
// Probability Fun
return array[Math.floor(Math.random() * array.length)];
}
console.log(get(item)); // See Console.

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