I've got a little app that recalculates the apportionment of seats in Congress in each state as the user changes the population hypothetically by moving counties between states. There are functionally infinite combinations, so I need to compute this on the fly.
The method is fairly straightforward: You give each state 1 seat, then assign the remaining 385 iteratively by weighting them according to population / ((seats * (seats + 1)) and assigning the seat to the top priority state.
I've got this working fine the obvious way:
function apportion(states) {
var totalReps = 435;
// assign one seat to each state
states.forEach(function(state) {
state.totalReps = 1;
totalReps -= 1;
state.priority = state.data.population / Math.sqrt(2); //Calculate default quota
});
// sort function
var topPriority = function(a, b) {
return b.priority - a.priority;
};
// assign the remaining 385
for (totalReps; totalReps > 0; totalReps -= 1) {
states.sort(topPriority);
states[0].totalReps += 1;
// recalculate the priority for this state
states[0].priority = states[0].data.population / Math.sqrt(states[0].totalReps * (states[0].totalReps + 1));
}
return states;
}
However, it drags a little when called several times a second. I'm wondering whether there's a better way to place the state that received the seat back in the sorted array other than by resorting the whole array. I don't know a ton about the Javascript sort() function and whether it will already do this with maximal efficiency without being told that all but the first element in the array is already sorted. Is there a more efficient way that I can implement by hand?
jsFiddle here: http://jsfiddle.net/raphaeljs/zoyLb9g6/1/
Using a strategy of avoiding sorts, the following keeps an array of priorities that is aligned with the states object and uses Math.max to find the highest priority value, then indexOf to find its position in the array, then updates the states object and priorities array.
As with all performance optimisations, it has very different results in different browsers (see http://jsperf.com/calc-reps), but is at least no slower (Chrome) and up to 4 times faster (Firefox).
function apportion1(states) {
var totalReps = 435;
var sqrt2 = Math.sqrt(2);
var priorities = [];
var max, idx, state, n;
// assign one seat to each state
states.forEach(function(state) {
state.totalReps = 1;
state.priority = state.data.population / sqrt2; //Calculate default quota
priorities.push(state.priority);
});
totalReps -= states.length;
while (totalReps--) {
max = Math.max.apply(Math, priorities);
idx = priorities.indexOf(max);
state = states[idx];
n = ++state.totalReps;
state.priority = state.data.population / Math.sqrt(n * ++n);
priorities[idx] = state.priority;
}
return states;
}
For testing I used an assumed states object with only 5 states, but real population data. Hopefully, with the full 50 states the benefit will be larger.
Another strategy is to sort on population since that's how the priorities are distributed, assign at least one rep to each state and calculate the priority, then run from 0 adding reps and recalculating priorities. There will be a threshold below which a state should not get any more reps.
Over to you. ;-)
Edit
Here's a really simple method that apportions based on population. If may allocation one too many or one too few. In the first case, find the state with the lowest priority and at least 2 reps (and recalc priority if you want) and take a rep away. In the second, find the state with the highest priority and add one rep (and recalc priority if required).
function simple(states) {
var totalPop = 0;
var totalReps = 435
states.forEach(function(state){totalPop += state.data.population});
var popperrep = totalPop/totalReps;
states.forEach(function(state){
state.totalReps = Math.round(state.data.population / popperrep);
state.priority = state.data.population / Math.sqrt(state.totalReps * (state.totalReps + 1));
});
return states;
}
Untested, but I'll bet it's very much faster than the others. ;-)
I've updated the test example for the simple function to adjust if the distribution results in an incorrect total number of reps. Tested across a variety of scenarios, it gives identical results to the original code even though it uses a very different algorithm. It's several hundred times faster than the original with the full 50 states.
Here's the final version of the simple function:
function simple(states) {
var count = 0;
var state, diff;
var totalPop = states.reduce(function(prev, curr){return prev + curr.data.population},0);
var totalReps = 435
var popperrep = totalPop/totalReps;
states.forEach(function(state){
state.totalReps = Math.round(state.data.population / popperrep) || 1;
state.priority = state.data.population / Math.sqrt(state.totalReps * (state.totalReps + 1));
count += state.totalReps;
});
// If too many reps distributed, trim from lowest priority with 2 or more
// If not enough reps distributed, add to highest priority
while ((diff = count - totalReps)) {
state = states[getPriority(diff < 0)];
state.totalReps += diff > 0? -1 : 1;
count += diff > 0? -1 : 1;
state.priority = state.data.population / Math.sqrt(state.totalReps * (state.totalReps + 1));
// console.log('Adjusted ' + state.data.name + ' ' + diff);
}
return states;
// Get lowest priority state with 2 or more reps,
// or highest priority state if high is true
function getPriority(high) {
var idx, p = high? 0 : +Infinity;
states.forEach(function(state, i){
if (( high && state.priority > p) || (!high && state.totalReps > 1 && state.priority < p)) {
p = state.priority;
idx = i;
}
});
return idx;
}
}
Related
I have been working to solve this problem on the HackerRank site: Fraudulent Activity Notifications.
Below is the code I have written which satisfies the three sample test cases; however, it does not satisfy the larger test cases since it seems to take longer than 10 seconds.
The 10 second constraint is taken from here: HackerRank Environment.
function activityNotifications(expenditure, d) {
let notifications = 0;
let tmp = [];
let median = 0, medianEven = 0, iOfMedian = 0;
// Begin looping thru 'expenditure'
for(let i = 0; i < expenditure.length; i++) {
// slice from 'expenditure' beginning at 'i' and ending at 'i + d' where d = number of days
// sort 'tmp' in ascending order after
tmp = expenditure.slice(i, i + d);
tmp.sort();
// edge case, make sure we do not exceed boundaries of 'expenditure'
if((i + d) < expenditure.length) {
// if length of 'tmp' is divisible by 2, then we have an even length
// compute median accordingly
if(tmp.length % 2 == 0) {
medianEven = tmp.length / 2;
median = (tmp[medianEven - 1] + tmp[medianEven]) / 2;
// test if expenditures > 2 x median
if(expenditure[i + d] >= (2 * median)) {
notifications++;
}
}
// otherwise, we have an odd length of numbers
// therefore, compute median accordingly
else {
iOfMedian = (tmp.length + 1) / 2;
// test if expenditures > 2 x median
if(expenditure[i + d] >= (2 * tmp[iOfMedian - 1])) {
notifications++;
}
}
}
}
return notifications;
}
I am familiar with O notation for computing time complexity, so initially it seems the problem is either the excessive amount of variables declared or conditional statements used. Only one for loop is being used so I don't think the loop is where I should look to optimize the code. Unless, of course, we were to include the .sort() function used on 'tmp' which would definitely add to the time it takes to compute efficiently.
Is there anything I have not realized which is causing the code to take longer than expected? Any other hints would be greatly appreciated, thanks.
I'm building an app and in one of my functions I need to generate random & unique 4 digit codes. Obviously there is a finite range from 0000 to 9999 but each day the entire list will be wiped and each day I will not need more than the available amount of codes which means it's possible to have unique codes for each day. Realistically I will probably only need a few hundred codes a day.
The way I've coded it for now is the simple brute force way which would be to generate a random 4 digit number, check if the number exists in an array and if it does, generate another number while if it doesn't, return the generated number.
Since it's 4 digits, the runtime isn't anything too crazy and I'm mostly generating a few hundred codes a day so there won't be some scenario where I've generated 9999 codes and I keep randomly generating numbers to find the last remaining one.
It would also be fine to have letters in there as well instead of just numbers if it would make the problem easier.
Other than my brute force method, what would be a more efficient way of doing this?
Thank you!
Since you have a constrained number of values that will easily fit in memory, the simplest way I know of is to create a list of the possible values and select one randomly, then remove it from the list so it can't be selected again. This will never have a collision with a previously used number:
function initValues(numValues) {
const values = new Array(numValues);
// fill the array with each value
for (let i = 0; i < values.length; i++) {
values[i] = i;
}
return values;
}
function getValue(array) {
if (!array.length) {
throw new Error("array is empty, no more random values");
}
const i = Math.floor(Math.random() * array.length);
const returnVal = array[i];
array.splice(i, 1);
return returnVal;
}
// sample code to use it
const rands = initValues(10000);
console.log(getValue(rands));
console.log(getValue(rands));
console.log(getValue(rands));
console.log(getValue(rands));
This works by doing the following:
Generate an array of all possible values.
When you need a value, select one from the array with a random index.
After selecting the value, remove it from the array.
Return the selected value.
Items are never repeated because they are removed from the array when used.
There are no collisions with used values because you're always just selecting a random value from the remaining unused values.
This relies on the fact that an array of integers is pretty well optimized in Javascript so doing a .splice() on a 10,000 element array is still pretty fast (as it can probably just be memmove instructions).
FYI, this could be made more memory efficient by using a typed array since your numbers can be represented in 16-bit values (instead of the default 64 bits for doubles). But, you'd have to implement your own version of .splice() and keep track of the length yourself since typed arrays don't have these capabilities built in.
For even larger problems like this where memory usage becomes a problem, I've used a BitArray to keep track of previous usage of values.
Here's a class implementation of the same functionality:
class Randoms {
constructor(numValues) {
this.values = new Array(numValues);
for (let i = 0; i < this.values.length; i++) {
this.values[i] = i;
}
}
getRandomValue() {
if (!this.values.length) {
throw new Error("no more random values");
}
const i = Math.floor(Math.random() * this.values.length);
const returnVal = this.values[i];
this.values.splice(i, 1);
return returnVal;
}
}
const rands = new Randoms(10000);
console.log(rands.getRandomValue());
console.log(rands.getRandomValue());
console.log(rands.getRandomValue());
console.log(rands.getRandomValue());
Knuth's multiplicative method looks to work pretty well: it'll map numbers 0 to 9999 to a random-looking other number 0 to 9999, with no overlap:
const hash = i => i*2654435761 % (10000);
const s = new Set();
for (let i = 0; i < 10000; i++) {
const n = hash(i);
if (s.has(n)) { console.log(i, n); break; }
s.add(n);
}
To implement it, simply keep track of an index that gets incremented each time a new one is generated:
const hash = i => i*2654435761 % (10000);
let i = 1;
console.log(
hash(i++),
hash(i++),
hash(i++),
hash(i++),
hash(i++),
);
These results aren't actually random, but they probably do the job well enough for most purposes.
Disclaimer:
This is copy-paste from my answer to another question here. The code was in turn ported from yet another question here.
Utilities:
function isPrime(n) {
if (n <= 1) return false;
if (n <= 3) return true;
if (n % 2 == 0 || n % 3 == 0) return false;
for (let i = 5; i * i <= n; i = i + 6) {
if (n % i == 0 || n % (i + 2) == 0) return false;
}
return true;
}
function findNextPrime(n) {
if (n <= 1) return 2;
let prime = n;
while (true) {
prime++;
if (isPrime(prime)) return prime;
}
}
function getIndexGeneratorParams(spaceSize) {
const N = spaceSize;
const Q = findNextPrime(Math.floor(2 * N / (1 + Math.sqrt(5))))
const firstIndex = Math.floor(Math.random() * spaceSize);
return [firstIndex, N, Q]
}
function getNextIndex(prevIndex, N, Q) {
return (prevIndex + Q) % N
}
Usage
// Each day you bootstrap to get a tuple of these parameters and persist them throughout the day.
const [firstIndex, N, Q] = getIndexGeneratorParams(10000)
// need to keep track of previous index generated.
// it’s a seed to generate next one.
let prevIndex = firstIndex
// calling this function gives you the unique code
function getHashCode() {
prevIndex = getNextIndex(prevIndex, N, Q)
return prevIndex.toString().padStart(4, "0")
}
console.log(getHashCode());
Explanation
For simplicity let’s say you want generate non-repeat numbers from 0 to 35 in random order. We get pseudo-randomness by polling a "full cycle iterator"†. The idea is simple:
have the indexes 0..35 layout in a circle, denote upperbound as N=36
decide a step size, denoted as Q (Q=23 in this case) given by this formula‡
Q = findNextPrime(Math.floor(2 * N / (1 + Math.sqrt(5))))
randomly decide a starting point, e.g. number 5
start generating seemingly random nextIndex from prevIndex, by
nextIndex = (prevIndex + Q) % N
So if we put 5 in we get (5 + 23) % 36 == 28. Put 28 in we get (28 + 23) % 36 == 15.
This process will go through every number in circle (jump back and forth among points on the circle), it will pick each number only once, without repeating. When we get back to our starting point 5, we know we've reach the end.
†: I'm not sure about this term, just quoting from this answer
‡: This formula only gives a nice step size that will make things look more "random", the only requirement for Q is it must be coprime to N
This problem is so small I think a simple solution is best. Build an ordered array of the 10k possible values & permute it at the start of each day. Give the k'th value to the k'th request that day.
It avoids the possible problem with your solution of having multiple collisions.
A friend of mine takes a sequence of numbers from 1 to n (where n > 0)
Within that sequence, he chooses two numbers, a and b
He says that the product of a and b should be equal to the sum of all numbers in the sequence, excluding a and b
Given a number n, could you tell me the numbers he excluded from the sequence?
Have found the solution to this Kata from Code Wars but it times out (After 12 seconds) in the editor when I run it; any ideas as too how I should further optimize the nested for loop and or remove it?
function removeNb(n) {
var nArray = [];
var sum = 0;
var answersArray = [];
for (let i = 1; i <= n; i++) {
nArray.push(n - (n - i));
sum += i;
}
var length = nArray.length;
for (let i = Math.round(n / 2); i < length; i++) {
for (let y = Math.round(n / 2); y < length; y++) {
if (i != y) {
if (i * y === sum - i - y) {
answersArray.push([i, y]);
break;
}
}
}
}
return answersArray;
}
console.log(removeNb(102));
.as-console-wrapper { max-height: 100% !important; top: 0; }
I think there is no reason for calculating the sum after you fill the array, you can do that while filling it.
function removeNb(n) {
let nArray = [];
let sum = 0;
for(let i = 1; i <= n; i++) {
nArray.push(i);
sum += i;
}
}
And since there could be only two numbers a and b as the inputs for the formula a * b = sum - a - b, there could be only one possible value for each of them. So, there's no need to continue the loop when you find them.
if(i*y === sum - i - y) {
answersArray.push([i,y]);
break;
}
I recommend looking at the problem in another way.
You are trying to find two numbers a and b using this formula a * b = sum - a - b.
Why not reduce the formula like this:
a * b + a = sum - b
a ( b + 1 ) = sum - b
a = (sum - b) / ( b + 1 )
Then you only need one for loop that produces the value of b, check if (sum - b) is divisible by ( b + 1 ) and if the division produces a number that is less than n.
for(let i = 1; i <= n; i++) {
let eq1 = sum - i;
let eq2 = i + 1;
if (eq1 % eq2 === 0) {
let a = eq1 / eq2;
if (a < n && a != i) {
return [[a, b], [b, a]];
}
}
}
You can solve this in linear time with two pointers method (page 77 in the book).
In order to gain intuition towards a solution, let's start thinking about this part of your code:
for(let i = Math.round(n/2); i < length; i++) {
for(let y = Math.round(n/2); y < length; y++) {
...
You already figured out this is the part of your code that is slow. You are trying every combination of i and y, but what if you didn't have to try every single combination?
Let's take a small example to illustrate why you don't have to try every combination.
Suppose n == 10 so we have 1 2 3 4 5 6 7 8 9 10 where sum = 55.
Suppose the first combination we tried was 1*10.
Does it make sense to try 1*9 next? Of course not, since we know that 1*10 < 55-10-1 we know we have to increase our product, not decrease it.
So let's try 2*10. Well, 20 < 55-10-2 so we still have to increase.
3*10==30 < 55-3-10==42
4*10==40 < 55-4-10==41
But then 5*10==50 > 55-5-10==40. Now we know we have to decrease our product. We could either decrease 5 or we could decrease 10, but we already know that there is no solution if we decrease 5 (since we tried that in the previous step). So the only choice is to decrease 10.
5*9==45 > 55-5-9==41. Same thing again: we have to decrease 9.
5*8==40 < 55-5-8==42. And now we have to increase again...
You can think about the above example as having 2 pointers which are initialized to the beginning and end of the sequence. At every step we either
move the left pointer towards right
or move the right pointer towards left
In the beginning the difference between pointers is n-1. At every step the difference between pointers decreases by one. We can stop when the pointers cross each other (and say that no solution can be obtained if one was not found so far). So clearly we can not do more than n computations before arriving at a solution. This is what it means to say that the solution is linear with respect to n; no matter how large n grows, we never do more than n computations. Contrast this to your original solution, where we actually end up doing n^2 computations as n grows large.
Hassan is correct, here is a full solution:
function removeNb (n) {
var a = 1;
var d = 1;
// Calculate the sum of the numbers 1-n without anything removed
var S = 0.5 * n * (2*a + (d *(n-1)));
// For each possible value of b, calculate a if it exists.
var results = [];
for (let numB = a; numB <= n; numB++) {
let eq1 = S - numB;
let eq2 = numB + 1;
if (eq1 % eq2 === 0) {
let numA = eq1 / eq2;
if (numA < n && numA != numB) {
results.push([numA, numB]);
results.push([numB, numA]);
}
}
}
return results;
}
In case it's of interest, CY Aries pointed this out:
ab + a + b = n(n + 1)/2
add 1 to both sides
ab + a + b + 1 = (n^2 + n + 2) / 2
(a + 1)(b + 1) = (n^2 + n + 2) / 2
so we're looking for factors of (n^2 + n + 2) / 2 and have some indication about the least size of the factor. This doesn't necessarily imply a great improvement in complexity for the actual search but still it's kind of cool.
This is part comment, part answer.
In engineering terms, the original function posted is using "brute force" to solve the problem, iterating every (or more than needed) possible combinations. The number of iterations is n is large - if you did all possible it would be
n * (n-1) = bazillio n
Less is More
So lets look at things that can be optimized, first some minor things, I'm a little confused about the first for loop and nArray:
// OP's code
for(let i = 1; i <= n; i++) {
nArray.push(n - (n - i));
sum += i;
}
??? You don't really use nArray for anything? Length is just n .. am I so sleep deprived I'm missing something? And while you can sum a consecutive sequence of integers 1-n by using a for loop, there is a direct and easy way that avoids a loop:
sum = ( n + 1 ) * n * 0.5 ;
THE LOOPS
// OP's loops, not optimized
for(let i = Math.round(n/2); i < length; i++) {
for(let y = Math.round(n/2); y < length; y++) {
if(i != y) {
if(i*y === sum - i - y) {
Optimization Considerations:
I see you're on the right track in a way, cutting the starting i, y values in half since the factors . But you're iterating both of them in the same direction : UP. And also, the lower numbers look like they can go a little below half of n (perhaps not because the sequence start at 1, I haven't confirmed that, but it seems the case).
Plus we want to avoid division every time we start an instantiation of the loop (i.e set the variable once, and also we're going to change it). And finally, with the IF statements, i and y will never be equal to each other the way we're going to create the loops, so that's a conditional that can vanish.
But the more important thing is the direction of transversing the loops. The smaller factor low is probably going to be close to the lowest loop value (about half of n) and the larger factor hi is probably going to be near the value of n. If we has some solid math theory that said something like "hi will never be less than 0.75n" then we could make a couple mods to take advantage of that knowledge.
The way the loops are show below, they break and iterate before the hi and low loops meet.
Moreover, it doesn't matter which loop picks the lower or higher number, so we can use this to shorten the inner loop as number pairs are tested, making the loop smaller each time. We don't want to waste time checking the same pair of numbers more than once! The lower factor's loop will start a little below half of n and go up, and the higher factor's loop will start at n and go down.
// Code Fragment, more optimized:
let nHi = n;
let low = Math.trunc( n * 0.49 );
let sum = ( n + 1 ) * n * 0.5 ;
// While Loop for the outside (incrementing) loop
while( low < nHi ) {
// FOR loop for the inside decrementing loop
for(let hi = nHi; hi > low; hi--) {
// If we're higher than the sum, we exit, decrement.
if( hi * low + hi + low > sum ) {
continue;
}
// If we're equal, then we're DONE and we write to array.
else if( hi * low + hi + low === sum) {
answersArray.push([hi, low]);
low = nHi; // Note this is if we want to end once finding one pair
break; // If you want to find ALL pairs for large numbers then replace these low = nHi; with low++;
}
// And if not, we increment the low counter and restart the hi loop from the top.
else {
low++;
break;
}
} // close for
} // close while
Tutorial:
So we set the few variables. Note that low is set slightly less than half of n, as larger numbers look like they could be a few points less. Also, we don't round, we truncate, which is essentially "always rounding down", and is slightly better for performance, (though it dosenit matter in this instance with just the single assignment).
The while loop starts at the lowest value and increments, potentially all the way up to n-1. The hi FOR loop starts at n (copied to nHi), and then decrements until the factor are found OR it intercepts at low + 1.
The conditionals:
First IF: If we're higher than the sum, we exit, decrement, and continue at a lower value for the hi factor.
ELSE IF: If we are EQUAL, then we're done, and break for lunch. We set low = nHi so that when we break out of the FOR loop, we will also exit the WHILE loop.
ELSE: If we get here it's because we're less than the sum, so we need to increment the while loop and reset the hi FOR loop to start again from n (nHi).
I'm trying to make it to where when a user does a certain thing, they get between 2 and 100 units. But for every 1,000 requests I want it to add up to 3,500 units given collectively.
Here's the code I have for adding different amounts randomly to a user:
if (Math.floor(Math.random() * 1000) + 1 === 900) {
//db call adding 100
}
else if (Math.floor(Math.random() * 100) + 1 === 90) {
//db call adding 40
}
else if (Math.floor(Math.random() * 30) + 1 === 20) {
//db call adding 10
}
else if (Math.floor(Math.random() * 5) + 1 === 4) {
//db call adding 5
}
else {
//db call adding 2
}
If my math is correct, this should average around 4,332 units per 1,000 calls. But obviously it would vary and I don't want that. I'd also like it to add random amounts instead, as the units added in my example are arbitrary.
EDIT: Guys, Gildor is right that I simply want to have 3,500 units, and give them away within 1,000 requests. It isn't even entirely necessary that it always reaches that maximum of 3,500 either (I could have specified that). The important thing is that I'm not giving users too much, while creating a chance for them to win a bigger amount.
Here's what I have set up now, and it's working well, and will work even better with some tweaking:
Outside of call:
var remaining = 150;
var count = 0;
Inside of call:
count += 1;
if (count === 100) {
remaining = 150;
count = 0;
}
if (Math.floor(Math.random() * 30) + 1 === 20) {
var addAmount = Math.floor(Math.random() * 85) + 15;
if (addAmount <= remaining) {
remaining -= addAmount;
//db call adding addAmount + 2
}
else {
//db call adding 2
}
}
else if (Math.floor(Math.random() * 5) + 1 === 4) {
var addAmount1 = Math.floor(Math.random() * 10) + 1;
if (addAmount1 <= remaining) {
remaining -= addAmount1;
//db call adding addAmount1 + 2
}
else {
//db call adding 2
}
}
else {
//db call adding 2
}
I guess I should have clarified, I want a "random" number with a high likelihood of being small. That's kind of part of the gimmick, where you have low probability of getting a larger amount.
As I've commented, 1,000 random numbers between 2 and 100 that add up to 3,500 is an average number of 3.5 which is not consistent with random choices between 2 and 100. You'd have to have nearly all 2 and 3 values in order to achieve that and, in fact couldn't have more than a couple large numbers. Nothing even close to random. So, for this to even be remotely random and feasible, you'd have to pick a total much large than 3,500. A random total of 1,000 numbers between 2 and 100 would be more like 51,000.
Furthermore, you can't dynamically generate each number in a truly random fashion and guarantee a particular total. The main way to guarantee that outcome is to pre-allocate random numbers that add up to the total that are known to achieve that and then random select each number from the pre-allocated scheme, then remove that from the choice for future selections.
You could also try to keep a running total and bias your randomness if you get skewed away form your total, but doing it that way, the last set of numbers may have to be not even close to random in order to hit your total consistently.
A scheme that could work if you reset the total to support what it should be for actual randomness (e.g. to 51,000) would be to preallocated an array of 500 random numbers between 2 and 100 and then add another 500 numbers that are the complements of those. This guarantees the 51 avg number. You can then select each number randomly from the pre-allocated array and then remove it form the array so it won't be selected again. I can add code to do this in a second.
function RandResults(low, high, qty) {
var results = new Array(qty);
var limit = qty/2;
var avg = (low + high) / 2;
for (var i = 0; i < limit; i++) {
results[i] = Math.floor((Math.random() * (high - low)) + low);
//
results[qty - i - 1] = (2 * avg) - results[i];
}
this.results = results;
}
RandResults.prototype.getRand = function() {
if (!this.results.length) {
throw new Error("getRand() called, but results are empty");
}
var randIndex = Math.floor(Math.random() * this.results.length);
var value = this.results[randIndex];
this.results.splice(randIndex, 1);
return value;
}
RandResults.prototype.getRemaining = function() {
return this.results.length;
}
var randObj = new RandResults(2, 100, 1000);
// get next single random value
if (randObj.getRemaining()) {
var randomValue = randObj.getRand();
}
Working demo for a truly random selection of numbers that add up to 51,000 (which is what 1,000 random values between 2 and 100 should add up to): http://jsfiddle.net/jfriend00/wga26n7p/
If what you want is the following: 1,000 numbers that add up to 3,500 and are selected from between the range 2 to 100 (inclusive) where most numbers will be 2 or 3, but occasionally something could be up to 100, then that's a different problem. I wouldn't really use the word random to describe it because it's a highly biased selection.
Here's a way to do that. It generates 1,000 random numbers between 2 and 100, keeping track of the total. Then, afterwards it corrects the random numbers to hit the right total by randomly selected values and decrementing them until the total is down to 3,500. You can see it work here: http://jsfiddle.net/jfriend00/m4ouonj4/
The main part of the code is this:
function RandResults(low, high, qty, total) {
var results = new Array(qty);
var runningTotal = 0, correction, index, trial;
for (var i = 0; i < qty; i++) {
runningTotal += results[i] = Math.floor((Math.random() * (high - low)) + low);
}
// now, correct to hit the total
if (runningTotal > total) {
correction = -1;
} else if (runningTotal < total) {
correction = 1;
}
// loop until we've hit the total
// randomly select a value to apply the correction to
while (runningTotal !== total) {
index = Math.floor(Math.random() * qty);
trial = results[index] + correction;
if (trial >= low && trial <= high) {
results[index] = trial;
runningTotal += correction;
}
}
this.results = results;
}
This meets an objective of a biased total of 3,500 and all numbers between 2 and 100, though the probability of a 2 in this scheme is very high and the probably of a 100 in this scheme is almost non-existent.
And, here's a weighted random generator that adds up to a precise total. This uses a cubic weighting scheme to favor the lower numbers (the probably of a number goes down with the cube of the number) and then after the random numbers are generated, a correction algorithm applies random corrections to the numbers to make the total come out exactly as specified. The code for a working demo is here: http://jsfiddle.net/jfriend00/g6mds8rr/
function RandResults(low, high, numPicks, total) {
var avg = total / numPicks;
var i, j;
// calculate probabilities for each value
// by trial and error, we found that a cubic weighting
// gives an approximately correct sub-total that can then
// be corrected to the exact total
var numBuckets = high - low + 1;
var item;
var probabilities = [];
for (i = 0; i < numBuckets; i++) {
item = low + i;
probabilities[i] = avg / (item * item * item);
}
// now using those probabilities, create a steps array
var sum = 0;
var steps = probabilities.map(function(item) {
sum += item;
return sum;
});
// now generate a random number and find what
// index it belongs to in the steps array
// and use that as our pick
var runningTotal = 0, rand;
var picks = [], pick, stepsLen = steps.length;
for (i = 0; i < numPicks; i++) {
rand = Math.random() * sum;
for (j = 0; j < stepsLen; j++) {
if (steps[j] >= rand) {
pick = j + low;
picks.push(pick);
runningTotal += pick;
break;
}
}
}
var correction;
// now run our correction algorithm to hit the total exactly
if (runningTotal > total) {
correction = -1;
} else if (runningTotal < total) {
correction = 1;
}
// loop until we've hit the total
// randomly select a value to apply the correction to
while (runningTotal !== total) {
index = Math.floor(Math.random() * numPicks);
trial = picks[index] + correction;
if (trial >= low && trial <= high) {
picks[index] = trial;
runningTotal += correction;
}
}
this.results = picks;
}
RandResults.prototype.getRand = function() {
if (!this.results.length) {
throw new Error("getRand() called, but results are empty");
}
return this.results.pop();
}
RandResults.prototype.getAllRand = function() {
if (!this.results.length) {
throw new Error("getAllRand() called, but results are empty");
}
var r = this.results;
this.results = [];
return r;
}
RandResults.prototype.getRemaining = function() {
return this.results.length;
}
As some comments pointed out... the numbers in the question does not quite make sense, but conceptually there are two approaches: calculate dynamically just in time or ahead of time.
To calculate just in time:
You can maintain a remaining variable which tracks how many of 3500 left. Each time when you randomly give some units, subtract the number from remaining until it goes to 0.
In addition, to make sure each time at least 2 units are given, you can start with remaining = 1500 and give random + 2 units each time.
To prevent cases that after 1000 gives there are still balances left, you may need to add some logic to give units more aggressively towards the last few times. However it will result in not-so-random results.
To calculate ahead of time:
Generate a random list with 1000 values in [2, 100] and sums up to 3500. Then shuffle the list. Each time you want to give some units, pick the next item in the array. After 1000 gives, generate another list in the same way. This way you get much better randomized results.
Be aware that both approaches requires some kind of shared state that needs to be handled carefully in a multi-threaded environment.
Hope the ideas help.
I ran into the challenge where I need a function that returns a random number within a given range from 0 - X. Not only that, but I require the number returned to be unique; not duplicating numbers that have already been returned on previous calls to the function.
Optionally, when this is done (e.g. the range has been 'exhausted'), just return a random number within the range.
How would one go about doing this?
This should do it:
function makeRandomRange(x) {
var used = new Array(x),
exhausted = false;
return function getRandom() {
var random = Math.floor(Math.random() * x);
if (exhausted) {
return random;
} else {
for (var i=0; i<x; i++) {
random = (random + 1) % x;
if (random in used)
continue;
used[random] = true;
return random;
}
// no free place found
exhausted = true;
used = null; // free memory
return random;
}
};
}
Usage:
var generate = makeRandomRange(20);
var x1 = generate(),
x2 = generate(),
...
Although it works, it has no good performance when the x-th random is generated - it searches the whole list for a free place. This algorithm, a step-by-step Fisher–Yates shuffle, from the question Unique (non-repeating) random numbers in O(1)?, will perform better:
function makeRandomRange(x) {
var range = new Array(x),
pointer = x;
return function getRandom() {
pointer = (pointer-1+x) % x;
var random = Math.floor(Math.random() * pointer);
var num = (random in range) ? range[random] : random;
range[random] = (pointer in range) ? range[pointer] : pointer;
return range[pointer] = num;
};
}
(Demo at jsfiddle.net)
Extended version which does only generate one "group" of unique numbers:
function makeRandomRange(x) {
var range = new Array(x),
pointer = x;
return function getRandom() {
if (range) {
pointer--;
var random = Math.floor(Math.random() * pointer);
var num = (random in range) ? range[random] : random;
range[random] = (pointer in range) ? range[pointer] : pointer;
range[pointer] = num;
if (pointer <= 0) { // first x numbers had been unique
range = null; // free memory;
}
return num;
} else {
return Math.floor(Math.random() * x);
}
};
}
(Demo)
You got some great programming answer. Here's one with a more theoretical flavor to complete your panorama :-)
Your problem is called "sampling" or "subset sampling" and there are several ways you could do this. Let N be the range you are sampling frame (i.e., N=X+1) and M be the size of your sample (the number of elements you want to pick).
if N is much larger than M, you'll want to use an algorithm such as the one suggested by Bentley and Floyd in his column "Programming Pearls: a sample of brilliance" (temporarily available without ACM's lock screen here), I really recommend this as they explicitly give code and discuss in terms of hash tables, etc.; there a few neat tricks in there
if N is within the same range as M, then you might want to use the Fisher-Yates shuffle but stop after only M steps (instead of N)
if you don't really know then the algorithm on page 647 of Devroye's book on random generation is pretty fast.
I wrote this function. It keeps its own array with a history of generated numbers, preventing initial duplicates, continuing to output a random number if all numbers in the range have been outputted once:
// Generates a unique number from a range
// keeps track of generated numbers in a history array
// if all numbers in the range have been returned once, keep outputting random numbers within the range
var UniqueRandom = { NumHistory: new Array(), generate: function(maxNum) {
var current = Math.round(Math.random()*(maxNum-1));
if (maxNum > 1 && this.NumHistory.length > 0) {
if (this.NumHistory.length != maxNum) {
while($.inArray(current, this.NumHistory) != -1) { current = Math.round(Math.random()*(maxNum-1)); }
this.NumHistory.push(current);
return current;
} else {
//unique numbers done, continue outputting random numbers, or we could reset the history array (NumHistory = [];)
return current;
}
} else {
//first time only
this.NumHistory.push(current);
return current;
}
}
};
Here's a working Fiddle
I hope this is of use to someone!
Edit: as pointed out by Pointy below, it might get slow with a large range (here is a
fiddle, going over a range from 0-1000, which seems to run fine). However; I didn't require a very large range, so perhaps this function is indeed not suited if you look to generate and keep track of an enormous range.
You may try generating the number using the current date and time value which would make it unique. To make it within the range, you may have to use some mathematical function.