Generating random results by weight in PHP? - php

I know how to generate a random number in PHP but lets say I want a random number between 1-10 but I want more 3,4,5's then 8,9,10's. How is this possible? I would post what I have tried but honestly, I don't even know where to start.

Based on #Allain's answer/link, I worked up this quick function in PHP. You will have to modify it if you want to use non-integer weighting.
/**
* getRandomWeightedElement()
* Utility function for getting random values with weighting.
* Pass in an associative array, such as array('A'=>5, 'B'=>45, 'C'=>50)
* An array like this means that "A" has a 5% chance of being selected, "B" 45%, and "C" 50%.
* The return value is the array key, A, B, or C in this case. Note that the values assigned
* do not have to be percentages. The values are simply relative to each other. If one value
* weight was 2, and the other weight of 1, the value with the weight of 2 has about a 66%
* chance of being selected. Also note that weights should be integers.
*
* #param array $weightedValues
*/
function getRandomWeightedElement(array $weightedValues) {
$rand = mt_rand(1, (int) array_sum($weightedValues));
foreach ($weightedValues as $key => $value) {
$rand -= $value;
if ($rand <= 0) {
return $key;
}
}
}

For an efficient random number skewed consistently towards one end of the scale:
Choose a continuous random number between 0..1
Raise to a power γ, to bias it. 1 is unweighted, lower gives more of the higher numbers and vice versa
Scale to desired range and round to integer
eg. in PHP (untested):
function weightedrand($min, $max, $gamma) {
$offset= $max-$min+1;
return floor($min+pow(lcg_value(), $gamma)*$offset);
}
echo(weightedrand(1, 10, 1.5));

There's a pretty good tutorial for you.
Basically:
Sum the weights of all the numbers.
Pick a random number less than that
subtract the weights in order until the result is negative and return that number if it is.

This tutorial walks you through it, in PHP, with multiple cut and paste solutions. Note that this routine is slightly modified from what you'll find on that page, as a result of the comment below.
A function taken from the post:
/**
* weighted_random_simple()
* Pick a random item based on weights.
*
* #param array $values Array of elements to choose from
* #param array $weights An array of weights. Weight must be a positive number.
* #return mixed Selected element.
*/
function weighted_random_simple($values, $weights){
$count = count($values);
$i = 0;
$n = 0;
$num = mt_rand(1, array_sum($weights));
while($i < $count){
$n += $weights[$i];
if($n >= $num){
break;
}
$i++;
}
return $values[$i];
}

/**
* #param array $weightedValues
* #return string
*/
function getRandomWeightedElement(array $weightedValues)
{
$array = array();
foreach ($weightedValues as $key => $weight) {
$array = array_merge(array_fill(0, $weight, $key), $array);
}
return $array[array_rand($array)];
}
getRandomWeightedElement(array('A'=>10, 'B'=>90));
This is very easy method. How get random weighted element. I fill array variable $key. I get $key to array $weight x. After that, use array_rand to array. And I have random value ;).

Plain and fair.
Just copy/paste and test it.
/**
* Return weighted probability
* #param (array) prob=>item
* #return key
*/
function weightedRand($stream) {
$pos = mt_rand(1,array_sum(array_keys($stream)));
$em = 0;
foreach ($stream as $k => $v) {
$em += $k;
if ($em >= $pos)
return $v;
}
}
$item['30'] = 'I have more chances than everybody :]';
$item['10'] = 'I have good chances';
$item['1'] = 'I\'m difficult to appear...';
for ($i = 1; $i <= 10; $i++) {
echo weightedRand($item).'<br />';
}
Edit: Added missing bracket at the end.

You can use weightedChoice from Non-standard PHP library. It accepts a list of pairs (item, weight) to have the possibility to work with items that can't be array keys. You can use pairs function to convert array(item => weight) to the needed format.
use function \nspl\a\pairs;
use function \nspl\rnd\weightedChoice;
$weights = pairs(array(
1 => 10,
2 => 15,
3 => 15,
4 => 15,
5 => 15,
6 => 10,
7 => 5,
8 => 5,
9 => 5,
10 => 5
));
$number = weightedChoice($weights);
In this example, 2-5 will appear 3 times more often than 7-10.

i used Brad's answar and changed it a little to fit my situation and add more flexibility
i have an array with array value
$products = [
['id'=>1,'name'=> 'product1' , 'chance'=>2] ,
['id'=>2,'name'=> 'product2' , 'chance'=>7]
]
first i shuffle the products array
shuffle($products );
then you can pass it to the function
function getRandomWeightedElement(array $products) {
$chancesSum = 0;
foreach ($products as $product){
$chancesSum += (int) $product['chance'];
}
$rand = mt_rand(1, $chancesSum);
$range = 0;
foreach ($products as $product) {
$range += (int) $product['chance'];
$compare = $rand - $range;
if ($compare <= 0){
return (int) $product['id'];
}
}}

Since I used IainMH's solution, I may as well share my PHP code:
<pre><?php
// Set total number of iterations
$total = 1716;
// Set array of random number
$arr = array(1, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 5);
$arr2 = array(0, 0, 1, 1, 2, 2, 2, 3, 3, 4, 5);
// Print out random numbers
for ($i=0; $i<$total; $i++){
// Pick random array index
$rand = array_rand($arr);
$rand2 = array_rand($arr2);
// Print array values
print $arr[$rand] . "\t" . $arr2[$rand2] . "\r\n";
}
?></pre>

I just released a class to perform weighted sorting easily.
It's based on the same algorithm mentioned in Brad's and Allain's answers, and is optimized for speed, unit-tested for uniform distribution, and supports elements of any PHP type.
Using it is simple. Instantiate it:
$picker = new Brick\Random\RandomPicker();
Then add elements as an array of weighted values (only if your elements are strings or integers):
$picker->addElements([
'foo' => 25,
'bar' => 50,
'baz' => 100
]);
Or use individual calls to addElement(). This method supports any kind of PHP values as elements (strings, numbers, objects, ...), as opposed to the array approach:
$picker->addElement($object1, $weight1);
$picker->addElement($object2, $weight2);
Then get a random element:
$element = $picker->getRandomElement();
The probability of getting one of the elements depends on its associated weight. The only restriction is that weights must be integers.

Many of the answers on this page seem to use array bloating, excessive iteration, a library, or a hard-to-read process. Of course, everyone thinks their own baby is the cutest, but I honestly think my approach is lean, simple and easy to read/modify...
Per the OP, I will create an array of values (declared as keys) from 1 to 10, with 3, 4, and 5 having double the weight of the other values (declared as values).
$values_and_weights=array(
1=>1,
2=>1,
3=>2,
4=>2,
5=>2,
6=>1,
7=>1,
8=>1,
9=>1,
10=>1
);
If you are only going to make one random selection and/or your array is relatively small* (do your own benchmarking to be sure), this is probably your best bet:
$pick=mt_rand(1,array_sum($values_and_weights));
$x=0;
foreach($values_and_weights as $val=>$wgt){
if(($x+=$wgt)>=$pick){
echo "$val";
break;
}
}
This approach involves no array modification and probably won't need to iterate the entire array (but may).
On the other hand, if you are going to make more than one random selection on the array and/or your array is sufficiently large* (do your own benchmarking to be sure), restructuring the array may be better.
The cost in memory for generating a new array will be increasingly justified as:
array size increases and
number of random selections increases.
The new array requires the replacement of "weight" with a "limit" for each value by adding the previous element's weight to the current element's weight.
Then flip the array so that the limits are the array keys and the values are the array values.
The logic is: the selected value will have the lowest limit that is >= $pick.
// Declare new array using array_walk one-liner:
array_walk($values_and_weights,function($v,$k)use(&$limits_and_values,&$x){$limits_and_values[$x+=$v]=$k;});
//Alternative declaration method - 4-liner, foreach() loop:
/*$x=0;
foreach($values_and_weights as $val=>$wgt){
$limits_and_values[$x+=$wgt]=$val;
}*/
var_export($limits_and_values);
Creates this array:
array (
1 => 1,
2 => 2,
4 => 3,
6 => 4,
8 => 5,
9 => 6,
10 => 7,
11 => 8,
12 => 9,
13 => 10,
)
Now to generate the random $pick and select the value:
// $x (from walk/loop) is the same as writing: end($limits_and_values); $x=key($limits_and_values);
$pick=mt_rand(1,$x); // pull random integer between 1 and highest limit/key
while(!isset($limits_and_values[$pick])){++$pick;} // smallest possible loop to find key
echo $limits_and_values[$pick]; // this is your random (weighted) value
This approach is brilliant because isset() is very fast and the maximum number of isset() calls in the while loop can only be as many as the largest weight (not to be confused with limit) in the array. For this case, maximum iterations = 2!
THIS APPROACH NEVER NEEDS TO ITERATE THE ENTIRE ARRAY

I used this:
mt_rand($min, mt_rand($min, $max));
it give more lower values and less higher values, since the more the value is high the more is cutted out by one of the mt_rand
The probability is linearly increasing in the lower values, forming a square diagonal (see maths lower)
PRO: easy and strightforward
CON: maybe too simple so not enough weightable or balanceable for some use case
Maths:
let i index of i-nth value from min to max,
let P(i) the probability of obtaining the i-nth value,
let N=max-min:
P(i)=(1+N-i)/sum(1,N)
Since N is equals for all terms:
P(i) is proportional to N-i
so, in facts, the probability is linearly increasing in the lower values, forming a square diagonal
Variants:
you can write variants:
mt_rand($min, mt_rand(1, mt_rand(1, $max))); //value more given in low part
mt_rand(mt_rand($min, $max), $max); //mirrored, more upper values than lower
...

function getBucketFromWeights($values) {
$total = $currentTotal = $bucket = 0;
foreach ($values as $amount) {
$total += $amount;
}
$rand = mt_rand(0, $total-1);
foreach ($values as $amount) {
$currentTotal += $amount;
if ($rand => $currentTotal) {
$bucket++;
}
else {
break;
}
}
return $bucket;
}
I ugh modified this from an answer here Picking random element by user defined weights
After I wrote this I saw someone else had an even more elegant answer. He he he he.

Related

Weighted random pick

I have a set of items. I need to randomly pick one. The problem is that they each have a weight of 1-10. A weight of 2 means that the item is twice as likely to be picked than a weight of 1. A weight of 3 is three times as likely.
I currently fill an array with each item. If the weight is 3, I put three copies of the item in the array. Then, I pick a random item.
My method is fast, but uses a lot of memory. I am trying to think of a faster method, but nothing comes to mind. Anyone have a trick for this problem?
EDIT: My Code...
Apparently, I wasn't clear. I do not want to use (or improve) my code. This is what I did.
//Given an array $a where $a[0] is an item name and $a[1] is the weight from 1 to 100.
$b = array();
foreach($a as $t)
$b = array_merge($b, array_fill(0,$t[1],$t));
$item = $b[array_rand($b)];
This required me to check every item in $a and uses max_weight/2*size of $a memory for the array. I wanted a COMPLETELY DIFFERENT algorithm.
Further, I asked this question in the middle of the night using a phone. Typing code on a phone is nearly impossible because those silly virtual keyboards simply suck. It auto-corrects everything, ruining any code I type.
An yet further, I woke up this morning with an entirely new algorithm that uses virtual no extra memory at all and does not require checking every item in the array. I posted it as an answer below.
This ones your huckleberry.
$arr = array(
array("val" => "one", "weight" => 1),
array("val" => "two", "weight" => 2),
array("val" => "three", "weight" => 3),
array("val" => "four", "weight" => 4)
);
$weight_sum = 0;
foreach($arr as $val)
{
$weight_sum += $val['weight'];
}
$r = rand(1, $weight_sum);
print "random value is $r\n";
for($i = 0; $i < count($arr); $i++)
{
if($r <= $arr[$i]['weight'])
{
print "$r <= {$arr[$i]['weight']}, this is our match\n";
print $arr[$i]['val'] . "\n";
break;
}
else
{
print "$r > {$arr[$i]['weight']}, subtracting weight\n";
$r -= $arr[$i]['weight'];
print "new \$r is $r\n";
}
}
No need to generate arrays containing an item for every weight, no need to fill an array with n elements for a weight of n. Just generate a random number between 1 and total weight, then loop through the array until you find a weight less than your random number. If it isn't less than the number, subtract that weight from the random and continue.
Sample output:
# php wr.php
random value is 8
8 > 1, subtracting weight
new $r is 7
7 > 2, subtracting weight
new $r is 5
5 > 3, subtracting weight
new $r is 2
2 <= 4, this is our match
four
This should also support fractional weights.
modified version to use array keyed by weight, rather than by item
$arr2 = array(
);
for($i = 0; $i <= 500000; $i++)
{
$weight = rand(1, 10);
$num = rand(1, 1000);
$arr2[$weight][] = $num;
}
$start = microtime(true);
$weight_sum = 0;
foreach($arr2 as $weight => $vals) {
$weight_sum += $weight * count($vals);
}
print "weighted sum is $weight_sum\n";
$r = rand(1, $weight_sum);
print "random value is $r\n";
$found = false;
$elem = null;
foreach($arr2 as $weight => $vals)
{
if($found) break;
for($j = 0; $j < count($vals); $j ++)
{
if($r < $weight)
{
$elem = $vals[$j];
$found = true;
break;
}
else
{
$r -= $weight;
}
}
}
$end = microtime(true);
print "random element is: $elem\n";
print "total time is " . ($end - $start) . "\n";
With sample output:
# php wr2.php
weighted sum is 2751550
random value is 345713
random element is: 681
total time is 0.017189025878906
measurement is hardly scientific - and fluctuates depending on where in the array the element falls (obviously) but it seems fast enough for huge datasets.
This way requires two random calculations but they should be faster and require about 1/4 of the memory but with some reduced accuracy if weights have disproportionate counts. (See Update for increased accuracy at the cost of some memory and processing)
Store a multidimensional array where each item is stored in the an array based on its weight:
$array[$weight][] = $item;
// example: Item with a weight of 5 would be $array[5][] = 'Item'
Generate a new array with the weights (1-10) appearing n times for n weight:
foreach($array as $n=>$null) {
for ($i=1;$i<=$n;$i++) {
$weights[] = $n;
}
}
The above array would be something like: [ 1, 2, 2, 3, 3, 3, 4, 4, 4, 4 ... ]
First calculation: Get a random weight from the weighted array we just created
$weight = $weights[mt_rand(0, count($weights)-1)];
Second calculation: Get a random key from that weight array
$value = $array[$weight][mt_rand(0, count($array[$weight])-1)];
Why this works: You solve the weighted issue by using the weighted array of integers we created. Then you select randomly from that weighted group.
Update: Because of the possibility of disproportionate counts of items per weight, you could add another loop and array for the counts to increase accuracy.
foreach($array as $n=>$null) {
$counts[$n] = count($array[$n]);
}
foreach($array as $n=>$null) {
// Calculate proportionate weight (number of items in this weight opposed to minimum counted weight)
$proportion = $n * ($counts[$n] / min($counts));
for ($i=1; $i<=$proportion; $i++) {
$weights[] = $n;
}
}
What this does is if you have 2000 10's and 100 1's, it'll add 200 10's (20 * 10, 20 because it has 20x the count, and 10 because it is weighted 10) instead of 10 10's to make it proportionate to how many are in there opposed the minimum weight count. So to be accurate, instead of adding one for EVERY possible key, you are just being proportionate based on the MINIMUM count of weights.
I greatly appreciate the answers above. Please consider this answer, which does not require checking every item in the original array.
// Given $a as an array of items
// where $a[0] is the item name and $a[1] is the item weight.
// It is known that weights are integers from 1 to 100.
for($i=0; $i<sizeof($a); $i++) // Safeguard described below
{
$item = $a[array_rand($a)];
if(rand(1,100)<=$item[1]) break;
}
This algorithm only requires storage for two variables ($i and $item) as $a was already created before the algorithm kicked in. It does not require a massive array of duplicate items or an array of intervals.
In a best-case scenario, this algorithm will touch one item in the original array and be done. In a worst-case scenario, it will touch n items in an array of n items (not necessarily every item in the array as some may be touched more than once).
If there was no safeguard, this could run forever. The safeguard is there to stop the algorithm if it simply never picks an item. When the safeguard is triggered, the last item touched is the one selected. However, in millions of tests using random data sets of 100,000 items with random weights of 1 to 10 (changing rand(1,100) to rand(1,10) in my code), the safeguard was never hit.
I made histograms comparing the frequency of items selected among my original algorithm, the ones from answers above, and the one in this answer. The differences in frequencies are trivial - easy to attribute to variances in the random numbers.
EDIT... It is apparent to me that my algorithm may be combined with the algorithm pala_ posted, removing the need for a safeguard.
In pala_'s algorithm, a list is required, which I call an interval list. To simplify, you begin with a random_weight that is rather high. You step down the list of items and subtract the weight of each one until your random_weight falls to zero (or less). Then, the item you ended on is your item to return. There are variations on this interval algorithm that I've tested and pala_'s is a very good one. But, I wanted to avoid making a list. I wanted to use only the given weighted list and never touch all the items. The following algorithm merges my use of random jumping with pala_'s interval list. Instead of a list, I randomly jump around the list. I am guaranteed to get to zero eventually, so no safeguard is needed.
// Given $a as the weighted array (described above)
$weight = rand(1,100); // The bigger this is, the slower the algorithm runs.
while($weight>0)
{
$item = $a[array_rand($a)];
$weight-= $item[1];
}
// $item is the random item you want.
I wish I could select both pala_ and this answer as the correct answers.
I'm not sure if this is "faster", but I think it may be more "balance"d between memory usage and speed.
The thought is to transform your current implementation (500000 items array) into an equal-length array (100000 items), with the lowest "origin" position as key, and origin index as value:
<?php
$set=[["a",3],["b",5]];
$current_implementation=["a","a","a","b","b","b","b","b"];
// 0=>0 means the lowest "position" 0
// points to 0 in the set;
// 3=>1 means the lowest "position" 3
// points to 1 in the set;
$my_implementation=[0=>0,3=>1];
And then randomly picks a number between 0 and highest "origin" position:
// 3 is the lowest position of the last element ("b")
// and 5 the weight of that last element
$my_implemention_pick=mt_rand(0,3+5-1);
Full code:
<?php
function randomPickByWeight(array $set)
{
$low=0;
$high=0;
$candidates=[];
foreach($set as $key=>$item)
{
$candidates[$high]=$key;
$high+=$item["weight"];
}
$pick=mt_rand($low,$high-1);
while(!array_key_exists($pick,$candidates))
{
$pick--;
}
return $set[$candidates[$pick]];
}
$cache=[];
for($i=0;$i<100000;$i++)
{
$cache[]=["item"=>"item {$i}","weight"=>mt_rand(1,10)];
}
$time=time();
for($i=0;$i<100;$i++)
{
print_r(randomPickByWeight($cache));
}
$time=time()-$time;
var_dump($time);
3v4l.org demo
3v4l.org have some time limitation on codes, so the demo didn't finished. On my laptop the above demo finished in 10 seconds (i7-4700 HQ)
ere is my offer in case I've understand you right. I offer you take a look and if there are some question I'll explain.
Some words in advance:
My sample is with only 3 stages of weight - to be clear
- With outer while I'm simulating your main loop - I count only to 100.
- The array must to be init with one set of initial numbers as shown in my sample.
- In every pass of main loop I get only one random value and I'm keeping the weight at all.
<?php
$array=array(
0=>array('item' => 'A', 'weight' => 1),
1=>array('item' => 'B', 'weight' => 2),
2=>array('item' => 'C', 'weight' => 3),
);
$etalon_weights=array(1,2,3);
$current_weights=array(0,0,0);
$ii=0;
while($ii<100){ // Simulates your main loop
// Randomisation cycle
if($current_weights==$etalon_weights){
$current_weights=array(0,0,0);
}
$ft=true;
while($ft){
$curindex=rand(0,(count($array)-1));
$cur=$array[$curindex];
if($current_weights[$cur['weight']-1]<$etalon_weights[$cur['weight']-1]){
echo $cur['item'];
$array[]=$cur;
$current_weights[$cur['weight']-1]++;
$ft=false;
}
}
$ii++;
}
?>
I'll use this input array for my explanation:
$values_and_weights=array(
"one"=>1,
"two"=>8,
"three"=>10,
"four"=>4,
"five"=>3,
"six"=>10
);
The simple version isn't going to work for you because your array is so large. It requires no array modification but may need to iterate the entire array, and that's a deal breaker.
/*$pick=mt_rand(1,array_sum($values_and_weights));
$x=0;
foreach($values_and_weights as $val=>$wgt){
if(($x+=$wgt)>=$pick){
echo "$val";
break;
}
}*/
For your case, re-structuring the array will offer great benefits.
The cost in memory for generating a new array will be increasingly justified as:
array size increases and
number of selections increases.
The new array requires the replacement of "weight" with a "limit" for each value by adding the previous element's weight to the current element's weight.
Then flip the array so that the limits are the array keys and the values are the array values.
The selection logic is: the selected value will have the lowest limit that is >= $pick.
// Declare new array using array_walk one-liner:
array_walk($values_and_weights,function($v,$k)use(&$limits_and_values,&$x){$limits_and_values[$x+=$v]=$k;});
//Alternative declaration method - 4-liner, foreach() loop:
/*$x=0;
foreach($values_and_weights as $val=>$wgt){
$limits_and_values[$x+=$wgt]=$val;
}*/
var_export($limits_and_values);
$limits_and_values looks like this:
array (
1 => 'one',
9 => 'two',
19 => 'three',
23 => 'four',
26 => 'five',
36 => 'six',
)
Now to generate the random $pick and select the value:
// $x (from walk/loop) is the same as writing: end($limits_and_values); $x=key($limits_and_values);
$pick=mt_rand(1,$x); // pull random integer between 1 and highest limit/key
while(!isset($limits_and_values[$pick])){++$pick;} // smallest possible loop to find key
echo $limits_and_values[$pick]; // this is your random (weighted) value
This approach is brilliant because isset() is very fast and the maximum number of isset() calls in the while loop can only be as many as the largest weight (not to be confused with limit) in the array.
FOR YOUR CASE, THIS APPROACH WILL FIND THE VALUE IN 10 ITERATIONS OR LESS!
Here is my Demo that will accept a weighted array (like $values_and_weights), then in just four lines:
Restructure the array,
Generate a random number,
Find the correct value, and
Display it.

random numbers in order + unique php

I am trying to create a random number generator which has the following features:
Each one is unique
Numbers are either 1 or 49 and all in between
Ordered from lowest to highest
This is what I have so far
$numbers = rand(1, 49)." ".rand(1, 49)." ".rand(1, 49)." ".rand(1, 49)." ".rand(1, 49)." ".rand(1, 49);
echo "Your Lucky Lotto Numbers Are: ".$numbers;
Im just not quite sure how to go about ordering them, plus the numbers being unique.
Just create an array with all the numbers from 1 to 49, and start randomly removing elements. Leave only the number of elements you need. That way, they are already in order, and are definitely unique.
Example:
$values = range(1,49);
while(count($values)>6) {
unset($values[array_rand($values)]);
}
print "Your results: ".implode(', ',$values);
$numbers = range(1, 49);
shuffle($numbers);
$numbers = array_slice($numbers, 0, 5);
sort($numbers);
foreach ($i=0; $i<6; $i++) {
echo $numbers[$i]." ";
}
Range & Shuffle.
You should use an array for this:
$numbers = range(1, 49); //generate the array
shuffle($numbers); //shuffle the array
$numbers = array_slice($numbers, 0, 6); // cut the array in the appopriate length
echo "Your Lucky Lotto Numbers Are: ";
print_r(asort($numbers)); //sort and print
Some useful literature:
Arrays in php: http://php.net/manual/en/language.types.array.php
Loop through array elements using foreach: http://php.net/manual/en/control-structures.foreach.php
Sorting in PHP: http://php.net/manual/en/array.sorting.php
Take an array with your numbers, take 6 random numbers (or shuffle array, pick first 6), sort your picked numbers. Not highly efficient, but should definitely work:
$numbers = range(1, 49);
shuffle($numbers);
$picks = array_slice($numbers, 0, 6);
sort($picks);
There are at least 3 ways how to do this:
1) generate non-existing numbers
You create array and add random numbers to it. If newly generated number already is in that array, generate another one (and so on until it is unique, check it in some while cycle), then sort it. i would recommend this
2) increment for all existing lower numbers
With each new random number, you lower the maximum by 1, then when adding this number, increment it for each lower number in you array
for example, when you have range 1-49 (inclusive) and numbers [4, 8, 6, 15], you generate number from 1-45 (inclusive), cause there are only 45 free numbers left. Lets say you generated 8, that means 8ht free number, and since 4, 8 and 6 are already there increment that three times and you got 11, however this requires your array to be sorted all the time.
3) same as #hexblot said
I would choose 1 cause its simple and you dont get much same selections if the amount of number is "lot" smaller then the number range (i.e. 5 numbers from 1-49 - 10% isnt much)
a little extensive maybe, but this will give you 6 unique sorted numbers
$arr = array();
while ( count($arr) < 6 ) {
$x = mt_rand(1,49);
if ( !in_array($x,$arr) ) {
$arr[] = $x;
asort($arr);
}
}
foreach($arr as $x){
echo $x." ";
}

array picking by percent [duplicate]

I know how to generate a random number in PHP but lets say I want a random number between 1-10 but I want more 3,4,5's then 8,9,10's. How is this possible? I would post what I have tried but honestly, I don't even know where to start.
Based on #Allain's answer/link, I worked up this quick function in PHP. You will have to modify it if you want to use non-integer weighting.
/**
* getRandomWeightedElement()
* Utility function for getting random values with weighting.
* Pass in an associative array, such as array('A'=>5, 'B'=>45, 'C'=>50)
* An array like this means that "A" has a 5% chance of being selected, "B" 45%, and "C" 50%.
* The return value is the array key, A, B, or C in this case. Note that the values assigned
* do not have to be percentages. The values are simply relative to each other. If one value
* weight was 2, and the other weight of 1, the value with the weight of 2 has about a 66%
* chance of being selected. Also note that weights should be integers.
*
* #param array $weightedValues
*/
function getRandomWeightedElement(array $weightedValues) {
$rand = mt_rand(1, (int) array_sum($weightedValues));
foreach ($weightedValues as $key => $value) {
$rand -= $value;
if ($rand <= 0) {
return $key;
}
}
}
For an efficient random number skewed consistently towards one end of the scale:
Choose a continuous random number between 0..1
Raise to a power γ, to bias it. 1 is unweighted, lower gives more of the higher numbers and vice versa
Scale to desired range and round to integer
eg. in PHP (untested):
function weightedrand($min, $max, $gamma) {
$offset= $max-$min+1;
return floor($min+pow(lcg_value(), $gamma)*$offset);
}
echo(weightedrand(1, 10, 1.5));
There's a pretty good tutorial for you.
Basically:
Sum the weights of all the numbers.
Pick a random number less than that
subtract the weights in order until the result is negative and return that number if it is.
This tutorial walks you through it, in PHP, with multiple cut and paste solutions. Note that this routine is slightly modified from what you'll find on that page, as a result of the comment below.
A function taken from the post:
/**
* weighted_random_simple()
* Pick a random item based on weights.
*
* #param array $values Array of elements to choose from
* #param array $weights An array of weights. Weight must be a positive number.
* #return mixed Selected element.
*/
function weighted_random_simple($values, $weights){
$count = count($values);
$i = 0;
$n = 0;
$num = mt_rand(1, array_sum($weights));
while($i < $count){
$n += $weights[$i];
if($n >= $num){
break;
}
$i++;
}
return $values[$i];
}
/**
* #param array $weightedValues
* #return string
*/
function getRandomWeightedElement(array $weightedValues)
{
$array = array();
foreach ($weightedValues as $key => $weight) {
$array = array_merge(array_fill(0, $weight, $key), $array);
}
return $array[array_rand($array)];
}
getRandomWeightedElement(array('A'=>10, 'B'=>90));
This is very easy method. How get random weighted element. I fill array variable $key. I get $key to array $weight x. After that, use array_rand to array. And I have random value ;).
Plain and fair.
Just copy/paste and test it.
/**
* Return weighted probability
* #param (array) prob=>item
* #return key
*/
function weightedRand($stream) {
$pos = mt_rand(1,array_sum(array_keys($stream)));
$em = 0;
foreach ($stream as $k => $v) {
$em += $k;
if ($em >= $pos)
return $v;
}
}
$item['30'] = 'I have more chances than everybody :]';
$item['10'] = 'I have good chances';
$item['1'] = 'I\'m difficult to appear...';
for ($i = 1; $i <= 10; $i++) {
echo weightedRand($item).'<br />';
}
Edit: Added missing bracket at the end.
You can use weightedChoice from Non-standard PHP library. It accepts a list of pairs (item, weight) to have the possibility to work with items that can't be array keys. You can use pairs function to convert array(item => weight) to the needed format.
use function \nspl\a\pairs;
use function \nspl\rnd\weightedChoice;
$weights = pairs(array(
1 => 10,
2 => 15,
3 => 15,
4 => 15,
5 => 15,
6 => 10,
7 => 5,
8 => 5,
9 => 5,
10 => 5
));
$number = weightedChoice($weights);
In this example, 2-5 will appear 3 times more often than 7-10.
i used Brad's answar and changed it a little to fit my situation and add more flexibility
i have an array with array value
$products = [
['id'=>1,'name'=> 'product1' , 'chance'=>2] ,
['id'=>2,'name'=> 'product2' , 'chance'=>7]
]
first i shuffle the products array
shuffle($products );
then you can pass it to the function
function getRandomWeightedElement(array $products) {
$chancesSum = 0;
foreach ($products as $product){
$chancesSum += (int) $product['chance'];
}
$rand = mt_rand(1, $chancesSum);
$range = 0;
foreach ($products as $product) {
$range += (int) $product['chance'];
$compare = $rand - $range;
if ($compare <= 0){
return (int) $product['id'];
}
}}
Since I used IainMH's solution, I may as well share my PHP code:
<pre><?php
// Set total number of iterations
$total = 1716;
// Set array of random number
$arr = array(1, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 5);
$arr2 = array(0, 0, 1, 1, 2, 2, 2, 3, 3, 4, 5);
// Print out random numbers
for ($i=0; $i<$total; $i++){
// Pick random array index
$rand = array_rand($arr);
$rand2 = array_rand($arr2);
// Print array values
print $arr[$rand] . "\t" . $arr2[$rand2] . "\r\n";
}
?></pre>
I just released a class to perform weighted sorting easily.
It's based on the same algorithm mentioned in Brad's and Allain's answers, and is optimized for speed, unit-tested for uniform distribution, and supports elements of any PHP type.
Using it is simple. Instantiate it:
$picker = new Brick\Random\RandomPicker();
Then add elements as an array of weighted values (only if your elements are strings or integers):
$picker->addElements([
'foo' => 25,
'bar' => 50,
'baz' => 100
]);
Or use individual calls to addElement(). This method supports any kind of PHP values as elements (strings, numbers, objects, ...), as opposed to the array approach:
$picker->addElement($object1, $weight1);
$picker->addElement($object2, $weight2);
Then get a random element:
$element = $picker->getRandomElement();
The probability of getting one of the elements depends on its associated weight. The only restriction is that weights must be integers.
Many of the answers on this page seem to use array bloating, excessive iteration, a library, or a hard-to-read process. Of course, everyone thinks their own baby is the cutest, but I honestly think my approach is lean, simple and easy to read/modify...
Per the OP, I will create an array of values (declared as keys) from 1 to 10, with 3, 4, and 5 having double the weight of the other values (declared as values).
$values_and_weights=array(
1=>1,
2=>1,
3=>2,
4=>2,
5=>2,
6=>1,
7=>1,
8=>1,
9=>1,
10=>1
);
If you are only going to make one random selection and/or your array is relatively small* (do your own benchmarking to be sure), this is probably your best bet:
$pick=mt_rand(1,array_sum($values_and_weights));
$x=0;
foreach($values_and_weights as $val=>$wgt){
if(($x+=$wgt)>=$pick){
echo "$val";
break;
}
}
This approach involves no array modification and probably won't need to iterate the entire array (but may).
On the other hand, if you are going to make more than one random selection on the array and/or your array is sufficiently large* (do your own benchmarking to be sure), restructuring the array may be better.
The cost in memory for generating a new array will be increasingly justified as:
array size increases and
number of random selections increases.
The new array requires the replacement of "weight" with a "limit" for each value by adding the previous element's weight to the current element's weight.
Then flip the array so that the limits are the array keys and the values are the array values.
The logic is: the selected value will have the lowest limit that is >= $pick.
// Declare new array using array_walk one-liner:
array_walk($values_and_weights,function($v,$k)use(&$limits_and_values,&$x){$limits_and_values[$x+=$v]=$k;});
//Alternative declaration method - 4-liner, foreach() loop:
/*$x=0;
foreach($values_and_weights as $val=>$wgt){
$limits_and_values[$x+=$wgt]=$val;
}*/
var_export($limits_and_values);
Creates this array:
array (
1 => 1,
2 => 2,
4 => 3,
6 => 4,
8 => 5,
9 => 6,
10 => 7,
11 => 8,
12 => 9,
13 => 10,
)
Now to generate the random $pick and select the value:
// $x (from walk/loop) is the same as writing: end($limits_and_values); $x=key($limits_and_values);
$pick=mt_rand(1,$x); // pull random integer between 1 and highest limit/key
while(!isset($limits_and_values[$pick])){++$pick;} // smallest possible loop to find key
echo $limits_and_values[$pick]; // this is your random (weighted) value
This approach is brilliant because isset() is very fast and the maximum number of isset() calls in the while loop can only be as many as the largest weight (not to be confused with limit) in the array. For this case, maximum iterations = 2!
THIS APPROACH NEVER NEEDS TO ITERATE THE ENTIRE ARRAY
I used this:
mt_rand($min, mt_rand($min, $max));
it give more lower values and less higher values, since the more the value is high the more is cutted out by one of the mt_rand
The probability is linearly increasing in the lower values, forming a square diagonal (see maths lower)
PRO: easy and strightforward
CON: maybe too simple so not enough weightable or balanceable for some use case
Maths:
let i index of i-nth value from min to max,
let P(i) the probability of obtaining the i-nth value,
let N=max-min:
P(i)=(1+N-i)/sum(1,N)
Since N is equals for all terms:
P(i) is proportional to N-i
so, in facts, the probability is linearly increasing in the lower values, forming a square diagonal
Variants:
you can write variants:
mt_rand($min, mt_rand(1, mt_rand(1, $max))); //value more given in low part
mt_rand(mt_rand($min, $max), $max); //mirrored, more upper values than lower
...
function getBucketFromWeights($values) {
$total = $currentTotal = $bucket = 0;
foreach ($values as $amount) {
$total += $amount;
}
$rand = mt_rand(0, $total-1);
foreach ($values as $amount) {
$currentTotal += $amount;
if ($rand => $currentTotal) {
$bucket++;
}
else {
break;
}
}
return $bucket;
}
I ugh modified this from an answer here Picking random element by user defined weights
After I wrote this I saw someone else had an even more elegant answer. He he he he.

Algorithm for probability when looping over a randomly ordered array

The problem is pretty straightforward, I think, by looking at the code. I have a randomized array (the array must be randomized, some code has been excluded because it doesn't pertain to the actual problem, but does require randomization). For each element in the array, there is a "probability" index (described here as the value itself, in $rules) that is suppose to hint that, if other conditions are met (that are removed here for the sake of non-relevancy), the probability that array element will be "triggered" (in this case, that the array element's score will increment by 1)
Consider the code:
<?php
// Taken from php.net/shuffle user notes
// Shuffles an array order for the sake of foreach while maintaining
// key => value associations
function shuffle_assoc(&$array) {
$keys = array_keys($array);
shuffle($keys);
foreach($keys as $key) {
$new[$key] = $array[$key];
}
return $new;
}
$i = 1000000; // How many tests to perform
// This is my rule list. Each key is a simple color
// and each value is a probability represented as a percent
$rules = array(
'black' => 20,
'white' => 10,
'red' => 40,
'green' => 5,
'blue' => 25,
);
// Initialize the scores array with all 0's
// The "outs" will be used when the probability does not
// occur in any of the rules
$scores = array('outs' => 0);
foreach($rules as $k => $v) {
$scores[$k] = 0;
}
$count = count($rules);
for($x = 0; $x < $i; $x++) {
$rules = shuffle_assoc($rules);
foreach($rules as $k => $probability) {
$rand = mt_rand(1,100);
//$probability = ??; I've tried applying many different operations here to "correct" the probability
if($rand > $probability) {
continue;
} else {
$scores[$k]++;
continue 2;
}
}
$scores['outs']++;
}
foreach($scores as $k => $v) {
echo "$k: " . (($v/$i)*100) . "% ($v/$i)\n";
}
?>
Expected output (pseudo). Note the percentages correspond with the values of $rules
outs: less than 1% (.../1000000)
black: 20% (.../1000000)
white: 10% (.../1000000)
red: 40% (.../1000000)
green: 5% (.../1000000)
blue: 25% (.../1000000)
Example output:
outs: 30.7128% (307128/1000000)
black: 13.2114% (132114/1000000)
white: 6.3381% (63381/1000000)
red: 29.5247% (295247/1000000)
green: 3.1585% (31585/1000000)
blue: 17.0545% (170545/1000000)
Things I've tried & Considerations:
As you can see, within the loop I have a commented out section of $probability = ?? which I've tried various obvious-to-me methods of calculating the actual probability to use within each element, including playing with $count (count of rules) which is why that variable exists and isn't used.
It doesn't have to be exact obviously, but preferably has stable results over a smaller set of numbers (e.x. 1,000 iterations).
It can be pretty fuzzy. A variance of +/- 5% wouldn't hurt my feelings, especially in smaller numbers of iterations, I understand big number theory comes to play here.
The number of outs isn't a big deal as long as they're less than 1%-2%. I also tried eliminating outs using various methods to see if the outs alone were skewing, and interestingly enough when I did that on one occasion, I got a 20% split all around (i.e. even).
Furthermore, on "outs", I was able to get pretty close to the proper split with very little outs by basically brute-forcing the probability "numbers" (that is, the values of $rules) starting from 100 backwards, but I was never able to find out a precise, optimal method. Each time, I would get closer to the result for one color, that would skew the other colors on a small but noticeable scale. There was no easy-for-me-to-grasp correlation in these numbers and were seemingly random although it is obvious that the results played well with probability vs big numbers.
Tell me there is a precise way to calculate this. It's driving me nuts.
Edit: I have a finalized version of my code, with the help from the two answers below, that does this without the need for knowing probability percentages before the loop begins, and no additional or nested loops (which is what I specifically needed, I guess I should of been more direct in that part) .. In the sense of, each iteration, you could be pulling the probability dynamically based on that specific iteration's properties.. All answers here were invaluable, here is my version of the final code: http://pastebin.com/eB3TVP1E
Just normalize the results, accumulate them and then you are done.
What I mean is:
sum all probabilities given for every item of the array to get the total (which is 100 in your case but it's easily generalizable)
divide every probability for the total
So for example:
$rules = array(
'black' => 20,
'white' => 10,
'red' => 40,
'green' => 5,
'blue' => 25,
);
will be normalized to:
$rules_norm = array(
'black' => 0.2,
'white' => 0.1,
'red' => 0.4,
'green' => 0.05,
'blue' => 0.25,
);
now accumulate the result so that for every element in $rules_norm you calculate the sum of all previous elements plus the current one.
So:
$rules_norm = array(
'black' => 0.2,
'white' => 0.3,
'red' => 0.7,
'green' => 0.75,
'blue' => 1.0,
);
Now with this you can just extract a random float number in range [0,1) and choose which elements are increased according to the result: to increment the score of one element just start from the first one in the array and increment the one such that $rand > $rules_norm[k]
Jack's idea implemented in your code (if the sum of probabilities is >100 this won't work):
php fiddle
<?php
// Taken from php.net/shuffle user notes
// Shuffles an array order for the sake of foreach while maintaining
// key => value associations
function shuffle_assoc(&$array) {
$keys = array_keys($array);
shuffle($keys);
foreach($keys as $key) {
$new[$key] = $array[$key];
}
return $new;
}
$i = 1000000; // How many tests to perform
// This is my rule list. Each key is a simple color
// and each value is a probability represented as a percent
$rules = array(
'black' => 20,
'white' => 10,
'red' => 40,
'green' => 5,
'blue' => 25,
);
// Initialize the scores array with all 0's
// The "outs" will be used when the probability does not
// occur in any of the rules
$scores = array('outs' => 0);
foreach($rules as $k => $v) {
$scores[$k] = 0;
}
$count = count($rules);
//$limits is what Jack called $rules_norm
$limits=array();
$limit=0;
foreach($rules as $k=>$v)
{
$limit+=$v;
$limits[$k]=$limit;
}
for($x = 0; $x < $i; $x++) {
$rand = mt_rand(1,100);
foreach($limits as $k=>$v)
{
if($v>=$rand)
{
$scores[$k]++;
continue(2);
}
}
$scores['outs']++;
}
foreach($scores as $k => $v) {
echo "$k: " . (($v/$i)*100) . "% ($v/$i)\n";
}
?>

Fixed Proportionate Selection

I have a set of elements and i need to choose any one element out of it. Each element is associated with a percentage chance. The percentages add to 100.
I need to choose one out of those element so that the chances of an element being chosen is equal to the percent value. So if a element has 25% chance, it is supposed to have 25% chances of getting chosen. In other words, if we choose elements 1 mil times, that element should be chosen near 250k times.
What you describe is a multinomial process.
http://en.wikipedia.org/wiki/Multinomial_distribution#Sampling_from_a_multinomial_distribution
They way to generate such random process is like this:
( I'll use pseudo code but it should be easy to make it in to real code. )
Sort the 'boxes' in reverse order of their probability:
(not needed. it's just an optimization)
so that you have for example values=[0.45,0.3,0.15,0.1]
then create the 'cumulative' distribution, which is the sum of all elements with index <=i.
pseudocode:
cumulant=[0,0,0,0] // initiate it
s=0
for j=0 to size()-1 {
s=s+values[i] ;
cumulant[i]=s
}
in our case cumulant=[0.45,0.70,0.85 ,1 ]
make a uniform random number x between 0 and 1.
For php: http://php.net/manual/en/function.rand.php
the resulting random box index i is
the highest i for which cumulant[i]< x
pseudocode:
for j=0 to size()-1 {
if !(cumulant[i]<){
print "your index is ",i
break;
}
that is it. Get another random index i by going back to point 3.
if you sort like suggested above, that means that the final search will be faster. For example, if you have this vector of probabilities: 0.001 0.001 0.001 0.001 0.996 then, when you sort it, you will almost always only have to look only at index i=0, since the random number x will almost always be lower than 0.996. If the sort pays off or not depends on if you repeatedly use the same 'boxes'. So, yes with 250k tries it will help a lot. Just remember that the box index i you get is for the sorted vector.
I guess it was faster for me to write it than it was for you to show us what you did so far.
Probably not the best solution, but as it stands, it looks like it's the only one you've got.
Here you go:
$elements = array(
'This' => 25,
'is' => 15,
'a' => 15,
'crappy' => 20,
'list' => 25
);
asort($elements);
$elements = array_reverse($elements);
// Precalc cumulative value
$cumulant = 0;
foreach ($elements as $key => &$value) {
$cumulant += $value;
$value = $cumulant;
}
function pickAnElement($elements) {
$random = rand(1, 100);
foreach ($elements as $key => $value) {
if ($random <= $value) {
return $key;
}
}
}
$picks = array();
for ($i = 0; $i < 10000; $i++) {
$element = pickAnElement($elements);
if (!array_key_exists($element, $picks)) {
$picks[$element] = 0;
}
$picks[$element]++;
}
var_dump($picks);
Inspired by Johans answer, I added a loop to sort and pre-calculate the cumulant.

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