randy

Random utilities based on WELL-1024a PRNG.

npm install randy
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Randy.js

NPM

Randy is a utility module inspired by Python's very handy standard module "random". It contains a PRNG and useful randomness functions.

All functions are based on a JavaScript implementation of WELL-1024a, with up to 53-bit precision. The reason for this is that the built-in Math.random() function is implementation-dependent and therefore of very limited usefulness, as you risk running into crappy implementations. Even the V8 engine (used by Node.js) only provides 32-bit entropy, and is based on the platform-dependent C++ rand() function.

Quick Examples

var a = randy.randInt(100);
// a == 42
var d = randy.shuffle(["J spades", "K hearts", "10 hearts"]);
// d == [ "K hearts", "J spades", "10 hearts" ]
var c = randy.choice(["heads", "tails"]);
// c == "heads"

Download

For Node.js, use npm:

npm install randy

In the Browser

Download and include as a <script>. The module will be available as the global object randy.

Development: randy.js - 12Kb Uncompressed

Production: randy.min.js - 3.4Kb Minified

Example

<img id="computerHandImg">
<script src="randy.min.js"></script>
<script>
    var h = document.getElementById("computerHandImg");
    h.src = randy.choice([
        "/img/rock",
        "/img/paper",
        "/img/kitten"
    ]);
</script>

Documentation

Randomness Functions

State Functions

High-Precision Functions

All the above randomness functions use 32-bit precision if possible, but will use 53-bit precision if they need to go outside the 32-bit range.

The randomness functions are also available in always-53-bit-precision versions, under the good namespace. If you're working with values over 65536 or so, imbalances of 0.01% will start to creep in, and a higher precision will reduce this problem.

These functions take about 35% longer to run than the ones available directly under randy.

Example

// Generate example salary between 1,000,000 and 5,000,000
// with values clustering around 2,000,000.
var salary = randy.good.triangular(1000000, 5000000, 2000000);

Maximally Uniform Functions

The randomness functions are also available in maximally uniform versions, under the best namespace.

Random integer calculations in the randy and randy.good functions are done via a modulo of a large random unsigned integer. This will slightly favour lower numbers, but it is fast, and good enough for most use cases. However, if you wish to avoid this imbalance, you can use these functions.

These functions take on average 110% longer to run than the ones available directly under randy.

Example

var numbers = [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
                13, 14, 15, 16, 17, 18, 19, 20, 21, 22 ];
var lottery = randy.best.sample(numbers, 7);

Randomness Functions

randInt (min, max, step)

randInt (min, max)

randInt (max)

randInt ()

Returns a random integer i such that min <= i < max, and (i - min) % step = 0.

Return value is based on a random 32-bit integer.

If max >= 2^32, will call good.getInt(), which goes up to 2^53.

Arguments

  • min - default=0. Returned integer will be min or greater.
  • max - default=2^32. Returned integer will be less than max.
  • step - default=1. Returned integer will be a multiple of this, counting from min.

Example

console.log("Rolling the dice:");
var d1 = randy.randInt(1, 7);
var d2 = randy.randInt(1, 7);
console.log(d1 + " + " + d2 + " = " + (d1 + d2));
if (d1 + d2 == 2)
    console.log("Snake eyes!");

choice (arr)

Returns a randomly chosen element from the array arr.

Throws an exception if arr is empty.

Arguments

  • arr - Array of elements of any type. Length > 0. Return value will be an element of arr.

Example

var breakfast = randy.choice(["whisky", "bacon", "panic"]);
console.log("Good morning!  Enjoy some " + breakfast + "!");
// Set direction vector for a ghost from Pac-Man.
ghost.currentDirection = randy.choice([
    {x:0, y:-1}, {x:1, y:0}, {x:0, y:1}, {x:-1, y:0}
]);

shuffle (arr)

Returns a shuffled copy of arr. Returned array contains the exact same elements as arr, and equally many elements, but in a new order.

Uses the Fisher-Yates algorithm, aka the Knuth Shuffle.

Arguments

  • arr - Array of elements of any type.

Example

var runners = ["Andy", "Bob", "Clarence", "David"];
var startingOrder = randy.shuffle(runners);

shuffleInplace (arr)

Shuffles the array arr. A more memory-efficient version of shuffle.

Uses the Fisher-Yates algorithm, aka the Knuth Shuffle.

Arguments

  • arr - Array of elements of any type. Will be modified.

Example

// Reorder elements at random until they happen to be sorted.
function bogosort (arr) {
    while (true) {
        randy.shuffleInplace(arr);

        var sorted = true;
        for (var i=0; i<arr.length-1; i++)
            sorted = sorted && (arr[i] < arr[i+1]);
        if (sorted)
            return;
    }
}
// Create new draw deck from card discard pile.
if (deck.length == 0) {
    deck = discardPile.splice(0);
    randy.shuffleInplace(deck);
}

sample (population, count)

Returns an array of length count, containing unique elements chosen from the array population. Like a raffle draw.

Mathematically equivalent to shuffle(population).slice(0, count), but more efficient. Catches fire if count > population.length.

Arguments

  • population - Array of elements of any type.
  • count - How many elements to pick from array population.

Example

// Raffle draw for 3 bottles of wine.  Cindy has bought 2 tickets.
var raffleTickets = ["Alice", "Beatrice", "Cindy", "Cindy", "Donna"];

var winners = randy.sample(raffleTickets, 3);

console.log("The winners are: " + winners.join(", "));

random ()

Returns a floating point number n, such that 0.0 <= n < 1.0.

Exactly as uniform(), but provided for familiarity.


uniform (min, max)

uniform (max)

uniform ()

Returns a floating point number n, such that min <= n < max.

Arguments

  • min - Default=0.0. Returned value will be equal to or larger than this.
  • max - Default=1.0. Returned value will be less than this.

Example

// Torpedo guidance system.
var heading = randy.uniform(360.0);
// Random event repeating every 1-5 minutes.
function flashLightning () {
    flash();
    var delayNext = randy.uniform(1.0 * 60000, 5.0 * 60000);
    setTimeout(flashLightning, delayNext);
}

triangular (min, max, mode)

triangular (min, max)

triangular (max)

triangular ()

The triangular distribution is typically used as a subjective description of a population for which there is only limited sample data, and especially in cases where the relationship between variables is known but data is scarce (possibly because of the high cost of collection). It is based on a knowledge of the minimum and maximum and an "inspired guess" as to the modal value.

Wikipedia article

Arguments

  • min - Default=0.0. Returned value will be equal to or larger than this.
  • max - Default=1.0. Returned value will be less than this.
  • mode - Default is average of min and max. Returned values are likely to be close to this value.

Example

// Generate customer test data.  Customers are aged 18 to 40, but
// most of them are in their twenties.  Their income is between
// 40000-150000 Hyrulean Rupees per year, but typically around
// 60000.
for (i=0; i<1000; i++) {
    db.insertCustomer({
        name: "Bruce",
        birthYear: Math.floor( randy.triangular(1972, 1990, 1983) ),
        income: randy.triangular(40000, 150000, 60000)
    });
}

getRandBits (n)

Returns a random integer of bit width n, where n <= 53.

Arguments

  • n - Number of random bits in return value.

Example

// A perfect distribution function, which rejects overflow values
// instead of squeezing them into the desired range by use of modulo.
function perfectInt (max) {
    if (max == 0)
        return 0;
    var log2 = 0;
    var mult = 1;
    while (mult < max) {
        log2 += 1;
        mult *= 2;
    }
    while (false == false) {
        var r = randy.getRandBits(log2);
        if (r < max)
            return r;
    }
}

State Functions

getState ()

Returns a JavaScript object representing the current state of the generator.

This object can be used as a parameter to setState().

setState (state)

Sets the generator to a specific state, allowing for replay of random values.

Arguments

  • state - Must be object retrieved from an earlier call to getState().

Example

This will roll a pair of dice, reset the generator state, and roll the dice again with the exact same output.

var state = randy.getState();
console.log("Rolling the dice:");
var d1 = randy.randInt(1, 7);
var d2 = randy.randInt(1, 7);
console.log(d1 + " + " + d2 + " = " + (d1 + d2));

console.log("Instant replay:");
randy.setState(state);
d1 = randy.randInt(1, 7);
d2 = randy.randInt(1, 7);
console.log(d1 + " + " + d2 + " = " + (d1 + d2));

instance ()

instance (state)

Creates a separate randy instance, for those use cases where a global object is a bad fit. The instance has the same functions as the global object.

If no state parameter is given, the new instance will be initialized randomly.

Calling this will not affect the generator state.

Arguments

  • state - Must be object retrieved from an earlier call to getState().

Example

Create two instances, one a copy of the global object. Sync the copies to the original randy state.

var origState = randy.getState();
var r1 = randy.instance(origState);
var r2 = randy.instance();
console.log(randy.randInt(50), r1.randInt(50), r2.randInt(50)); // 34 34 17
console.log(randy.randInt(50), r1.randInt(50), r2.randInt(50)); // 12 12 4
r1.setState(origState);
r2.setState(origState);
console.log(randy.randInt(50), r1.randInt(50), r2.randInt(50)); // 15 34 34
console.log(randy.randInt(50), r1.randInt(50), r2.randInt(50)); // 36 12 12

Notes

No functions rely on this, so it's safe to e.g. assign randy.good.randInt to a variable or pass it around as a parameter.

Due to floating point rounding, functions returning floating point values may extremely rarely tangent the upper bound.

Maximum integer range is 2^53 = 9007199254740992. This is the maximum integer available in JavaScript without losing precision. Any calls requiring a larger range than this, explicitly or implicitly, will not yield correct results.

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