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@hyperfrontend/random-generator-utils

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@hyperfrontend/random-generator-utils - npm Package Compare versions

Comparing version
0.0.4
 to
0.0.5
+6
_dependencies/@hyp...-utils/built-in-copy/error/index.cjs.js
'use strict';
const _Error = globalThis.Error;
const _Reflect = globalThis.Reflect;
const createError = (message, options) => _Reflect.construct(_Error, [message, options]);
exports.createError = createError;
+5
_dependencies/@hyp...-utils/built-in-copy/error/index.esm.js
const _Error = globalThis.Error;
const _Reflect = globalThis.Reflect;
const createError = (message, options) => _Reflect.construct(_Error, [message, options]);
export { createError };
+17
_dependencies/@hyp...i-utils/built-in-copy/math/index.cjs.js
'use strict';
const _Math = globalThis.Math;
const floor = _Math.floor;
const pow = _Math.pow;
const sqrt = _Math.sqrt;
const exp = _Math.exp;
const log = _Math.log;
const sin = _Math.sin;
const random = _Math.random;
exports.exp = exp;
exports.floor = floor;
exports.log = log;
exports.pow = pow;
exports.random = random;
exports.sin = sin;
exports.sqrt = sqrt;
+10
_dependencies/@hyp...i-utils/built-in-copy/math/index.esm.js
const _Math = globalThis.Math;
const floor = _Math.floor;
const pow = _Math.pow;
const sqrt = _Math.sqrt;
const exp = _Math.exp;
const log = _Math.log;
const sin = _Math.sin;
const random = _Math.random;
export { exp, floor, log, pow, random, sin, sqrt };
+110
-18
bundle/index.iife.js

@@ -12,3 +12,2 @@ var HyperfrontendRandomGenerator = (function (exports) {

*/
// Capture references at module initialization time
const _Math = globalThis.Math;

@@ -19,5 +18,2 @@ /**

const floor = _Math.floor;
// ============================================================================
// Powers and Roots
// ============================================================================
/**

@@ -35,5 +31,2 @@ * (Safe copy) Returns the base to the exponent power.

const exp = _Math.exp;
// ============================================================================
// Logarithms
// ============================================================================
/**

@@ -43,5 +36,2 @@ * (Safe copy) Returns the natural logarithm of a number.

const log = _Math.log;
// ============================================================================
// Trigonometry
// ============================================================================
/**

@@ -51,5 +41,2 @@ * (Safe copy) Returns the sine of a number.

const sin = _Math.sin;
// ============================================================================
// Random
// ============================================================================
/**

@@ -67,2 +54,11 @@ * (Safe copy) Returns a pseudo-random number between 0 and 1.

* @returns A random number from the exponential distribution
*
* @example Modeling time between events (e.g., customer arrivals)
* ```typescript
* // Higher lambda = shorter average wait time
* const averageWaitMinutes = 5
* const lambda = 1 / averageWaitMinutes
* const waitTime = randomExponential(lambda)
* // => 3.7 (varies each call, most values clustered near 0-10)
* ```
*/

@@ -85,3 +81,2 @@ function randomExponential(lambda) {

*/
// Capture references at module initialization time
const _Error = globalThis.Error;

@@ -96,2 +91,9 @@ const _Reflect = globalThis.Reflect;

* @returns A new Error instance.
*
* @example Creating Error instances
* ```typescript
* const error = createError('Operation failed')
* // With cause for error chaining
* const wrapped = createError('Request failed', { cause: originalError })
* ```
*/

@@ -106,2 +108,14 @@ const createError = (message, options) => _Reflect.construct(_Error, [message, options]);

* @returns A random number from the Gaussian distribution bounded by min and max
*
* @example Simulating human heights in centimeters
* ```typescript
* const heightCm = randomGaussian(150, 200)
* // => 174.3 (most values cluster around the midpoint 175)
* ```
*
* @example Generating test scores with realistic distribution
* ```typescript
* const testScore = randomGaussian(0, 100)
* // => 52.8 (bell curve centered at 50, rarely hits extremes)
* ```
*/

@@ -136,2 +150,13 @@ function randomGaussian(min, max) {

* @returns A random number from the logarithmic distribution
*
* @example Generating values with exponential growth characteristics
* ```typescript
* // scale=1 produces values from 1 to e (~2.718)
* const smallScale = randomLogarithmic(1)
* // => 1.8 (values between 1 and ~2.7)
*
* // scale=5 produces values from 1 to e^5 (~148)
* const largeScale = randomLogarithmic(5)
* // => 42.3 (wider range, skewed toward lower values)
* ```
*/

@@ -150,2 +175,15 @@ function randomLogarithmic(scale) {

* @returns A random number from the power law distribution bounded by min and max
*
* @example Simulating social network follower counts (few have many, many have few)
* ```typescript
* // alpha > 2 creates "long tail" - most values near min
* const followerCount = randomPowerLaw(2.5, 1, 1000000)
* // => 127 (typically low, occasionally very large)
* ```
*
* @example Modeling file sizes in a system
* ```typescript
* const fileSizeKb = randomPowerLaw(2.0, 1, 10000)
* // => 45 (many small files, rare large files)
* ```
*/

@@ -163,2 +201,15 @@ function randomPowerLaw(alpha, min, max) {

* @returns A pseudo-random number between 0 and 1.
*
* @example Reproducible random values for testing
* ```typescript
* // Same seed always yields the same result
* randomPseudo(42)
* // => 0.6853... (deterministic)
*
* randomPseudo(42)
* // => 0.6853... (identical)
*
* randomPseudo(43)
* // => 0.1762... (different seed, different result)
* ```
*/

@@ -175,2 +226,12 @@ function randomPseudo(seed) {

* @returns The pseudo-random variation as a number.
*
* @example Reproducible randomness for a specific timestamp
* ```typescript
* const releaseDate = new Date('2024-03-15T10:30:00Z')
*
* // Same date always produces the same result
* const value1 = randomPseudoTimeBased(releaseDate)
* const value2 = randomPseudoTimeBased(releaseDate)
* // value1 === value2 (deterministic)
* ```
*/

@@ -187,2 +248,15 @@ function randomPseudoTimeBased(seedTime) {

* @returns A random number between min (inclusive) and max (exclusive)
*
* @example Generating a random price within a budget range
* ```typescript
* const priceUsd = randomUniform(10, 50)
* // => 27.34 (any value equally likely within range)
* ```
*
* @example Random coordinates for game object placement
* ```typescript
* const xPosition = randomUniform(0, 800)
* const yPosition = randomUniform(0, 600)
* // => x: 342.7, y: 198.2
* ```
*/

@@ -197,10 +271,16 @@ function randomUniform(min, max) {

* @returns a version 4 UUID.
*
* @example Creating unique identifiers for entities
* ```typescript
* const userId = uuidV4()
* // => 'a1b2c3d4-e5f6-4a7b-8c9d-0e1f2a3b4c5d'
*
* const sessionId = uuidV4()
* // => '9f8e7d6c-5b4a-4321-8765-4321fedcba98'
* ```
*/
function uuidV4() {
return 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, (char) => {
// Generate a random hexadecimal digit, 0 - 15
const randomHex = (random() * 16) | 0;
// Use the randomHex for 'x' and a specific subset for 'y'
const finalHex = char === 'x' ? randomHex : (randomHex & 0x3) | 0x8;
// Convert the final hexadecimal digit to a string
return finalHex.toString(16);

@@ -214,2 +294,15 @@ });

* @returns true if the string is a version 4 UUID, otherwise false.
*
* @example Validating user input as UUID
* ```typescript
* isUuidV4('a1b2c3d4-e5f6-4a7b-8c9d-0e1f2a3b4c5d')
* // => true
*
* isUuidV4('not-a-uuid')
* // => false
*
* // Version 1 UUID (has '1' in third segment, not '4')
* isUuidV4('550e8400-e29b-11d4-a716-446655440000')
* // => false
* ```
*/

@@ -234,2 +327,1 @@ function isUuidV4(str) {

})({});
//# sourceMappingURL=index.iife.js.map
+0
-1
bundle/index.iife.min.js
var HyperfrontendRandomGenerator=function(n){"use strict";const o=globalThis.Math,r=o.floor,t=o.pow,e=o.sqrt,x=o.exp,a=o.log,u=o.sin,i=o.random;const s=globalThis.Error,c=globalThis.Reflect;function f(n){const o=1e4*u(n);return o-r(o)}return n.isUuidV4=function(n){return/^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-4[0-9a-fA-F]{3}-[89aAbB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}$/.test(n)},n.randomExponential=function(n){const o=i();return-a(1-o)/n},n.randomGaussian=function n(o,r){if(o>r)throw t="Min value should be less than or equal to max value.",c.construct(s,[t,x]);var t,x;let u,f,l;do{u=2*i()-1,f=2*i()-1,l=u*u+f*f}while(l>=1||0===l);const d=(o+r)/2+u*e(-2*a(l)/l)*((r-o)/6);return d>=o&&d<=r?d:n(o,r)},n.randomLogarithmic=function(n){const o=i();return x(n*o)},n.randomPowerLaw=function(n,o,r){const e=i(),x=(t(r,n-1)-t(o,n-1))*e+t(o,n-1);return t(x,1/(n-1))},n.randomPseudo=f,n.randomPseudoTimeBased=function(n){return f(n.getTime())},n.randomUniform=function(n,o){return i()*(o-n)+n},n.uuidV4=function(){return"xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx".replace(/[xy]/g,n=>{const o=16*i()|0;return("x"===n?o:3&o|8).toString(16)})},n}({});
//# sourceMappingURL=index.iife.min.js.map
+110
-18
bundle/index.umd.js

@@ -15,3 +15,2 @@ (function (global, factory) {

*/
// Capture references at module initialization time
const _Math = globalThis.Math;

@@ -22,5 +21,2 @@ /**

const floor = _Math.floor;
// ============================================================================
// Powers and Roots
// ============================================================================
/**

@@ -38,5 +34,2 @@ * (Safe copy) Returns the base to the exponent power.

const exp = _Math.exp;
// ============================================================================
// Logarithms
// ============================================================================
/**

@@ -46,5 +39,2 @@ * (Safe copy) Returns the natural logarithm of a number.

const log = _Math.log;
// ============================================================================
// Trigonometry
// ============================================================================
/**

@@ -54,5 +44,2 @@ * (Safe copy) Returns the sine of a number.

const sin = _Math.sin;
// ============================================================================
// Random
// ============================================================================
/**

@@ -70,2 +57,11 @@ * (Safe copy) Returns a pseudo-random number between 0 and 1.

* @returns A random number from the exponential distribution
*
* @example Modeling time between events (e.g., customer arrivals)
* ```typescript
* // Higher lambda = shorter average wait time
* const averageWaitMinutes = 5
* const lambda = 1 / averageWaitMinutes
* const waitTime = randomExponential(lambda)
* // => 3.7 (varies each call, most values clustered near 0-10)
* ```
*/

@@ -88,3 +84,2 @@ function randomExponential(lambda) {

*/
// Capture references at module initialization time
const _Error = globalThis.Error;

@@ -99,2 +94,9 @@ const _Reflect = globalThis.Reflect;

* @returns A new Error instance.
*
* @example Creating Error instances
* ```typescript
* const error = createError('Operation failed')
* // With cause for error chaining
* const wrapped = createError('Request failed', { cause: originalError })
* ```
*/

@@ -109,2 +111,14 @@ const createError = (message, options) => _Reflect.construct(_Error, [message, options]);

* @returns A random number from the Gaussian distribution bounded by min and max
*
* @example Simulating human heights in centimeters
* ```typescript
* const heightCm = randomGaussian(150, 200)
* // => 174.3 (most values cluster around the midpoint 175)
* ```
*
* @example Generating test scores with realistic distribution
* ```typescript
* const testScore = randomGaussian(0, 100)
* // => 52.8 (bell curve centered at 50, rarely hits extremes)
* ```
*/

@@ -139,2 +153,13 @@ function randomGaussian(min, max) {

* @returns A random number from the logarithmic distribution
*
* @example Generating values with exponential growth characteristics
* ```typescript
* // scale=1 produces values from 1 to e (~2.718)
* const smallScale = randomLogarithmic(1)
* // => 1.8 (values between 1 and ~2.7)
*
* // scale=5 produces values from 1 to e^5 (~148)
* const largeScale = randomLogarithmic(5)
* // => 42.3 (wider range, skewed toward lower values)
* ```
*/

@@ -153,2 +178,15 @@ function randomLogarithmic(scale) {

* @returns A random number from the power law distribution bounded by min and max
*
* @example Simulating social network follower counts (few have many, many have few)
* ```typescript
* // alpha > 2 creates "long tail" - most values near min
* const followerCount = randomPowerLaw(2.5, 1, 1000000)
* // => 127 (typically low, occasionally very large)
* ```
*
* @example Modeling file sizes in a system
* ```typescript
* const fileSizeKb = randomPowerLaw(2.0, 1, 10000)
* // => 45 (many small files, rare large files)
* ```
*/

@@ -166,2 +204,15 @@ function randomPowerLaw(alpha, min, max) {

* @returns A pseudo-random number between 0 and 1.
*
* @example Reproducible random values for testing
* ```typescript
* // Same seed always yields the same result
* randomPseudo(42)
* // => 0.6853... (deterministic)
*
* randomPseudo(42)
* // => 0.6853... (identical)
*
* randomPseudo(43)
* // => 0.1762... (different seed, different result)
* ```
*/

@@ -178,2 +229,12 @@ function randomPseudo(seed) {

* @returns The pseudo-random variation as a number.
*
* @example Reproducible randomness for a specific timestamp
* ```typescript
* const releaseDate = new Date('2024-03-15T10:30:00Z')
*
* // Same date always produces the same result
* const value1 = randomPseudoTimeBased(releaseDate)
* const value2 = randomPseudoTimeBased(releaseDate)
* // value1 === value2 (deterministic)
* ```
*/

@@ -190,2 +251,15 @@ function randomPseudoTimeBased(seedTime) {

* @returns A random number between min (inclusive) and max (exclusive)
*
* @example Generating a random price within a budget range
* ```typescript
* const priceUsd = randomUniform(10, 50)
* // => 27.34 (any value equally likely within range)
* ```
*
* @example Random coordinates for game object placement
* ```typescript
* const xPosition = randomUniform(0, 800)
* const yPosition = randomUniform(0, 600)
* // => x: 342.7, y: 198.2
* ```
*/

@@ -200,10 +274,16 @@ function randomUniform(min, max) {

* @returns a version 4 UUID.
*
* @example Creating unique identifiers for entities
* ```typescript
* const userId = uuidV4()
* // => 'a1b2c3d4-e5f6-4a7b-8c9d-0e1f2a3b4c5d'
*
* const sessionId = uuidV4()
* // => '9f8e7d6c-5b4a-4321-8765-4321fedcba98'
* ```
*/
function uuidV4() {
return 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, (char) => {
// Generate a random hexadecimal digit, 0 - 15
const randomHex = (random() * 16) | 0;
// Use the randomHex for 'x' and a specific subset for 'y'
const finalHex = char === 'x' ? randomHex : (randomHex & 0x3) | 0x8;
// Convert the final hexadecimal digit to a string
return finalHex.toString(16);

@@ -217,2 +297,15 @@ });

* @returns true if the string is a version 4 UUID, otherwise false.
*
* @example Validating user input as UUID
* ```typescript
* isUuidV4('a1b2c3d4-e5f6-4a7b-8c9d-0e1f2a3b4c5d')
* // => true
*
* isUuidV4('not-a-uuid')
* // => false
*
* // Version 1 UUID (has '1' in third segment, not '4')
* isUuidV4('550e8400-e29b-11d4-a716-446655440000')
* // => false
* ```
*/

@@ -235,2 +328,1 @@ function isUuidV4(str) {

}));
//# sourceMappingURL=index.umd.js.map
+0
-1
bundle/index.umd.min.js
!function(n,o){"object"==typeof exports&&"undefined"!=typeof module?o(exports):"function"==typeof define&&define.amd?define(["exports"],o):o((n="undefined"!=typeof globalThis?globalThis:n||self).HyperfrontendRandomGenerator={})}(this,function(n){"use strict";const o=globalThis.Math,t=o.floor,e=o.pow,r=o.sqrt,i=o.exp,x=o.log,u=o.sin,a=o.random;const s=globalThis.Error,f=globalThis.Reflect;function c(n){const o=1e4*u(n);return o-t(o)}n.isUuidV4=function(n){return/^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-4[0-9a-fA-F]{3}-[89aAbB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}$/.test(n)},n.randomExponential=function(n){const o=a();return-x(1-o)/n},n.randomGaussian=function n(o,t){if(o>t)throw e="Min value should be less than or equal to max value.",f.construct(s,[e,i]);var e,i;let u,c,d;do{u=2*a()-1,c=2*a()-1,d=u*u+c*c}while(d>=1||0===d);const l=(o+t)/2+u*r(-2*x(d)/d)*((t-o)/6);return l>=o&&l<=t?l:n(o,t)},n.randomLogarithmic=function(n){const o=a();return i(n*o)},n.randomPowerLaw=function(n,o,t){const r=a(),i=(e(t,n-1)-e(o,n-1))*r+e(o,n-1);return e(i,1/(n-1))},n.randomPseudo=c,n.randomPseudoTimeBased=function(n){return c(n.getTime())},n.randomUniform=function(n,o){return a()*(o-n)+n},n.uuidV4=function(){return"xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx".replace(/[xy]/g,n=>{const o=16*a()|0;return("x"===n?o:3&o|8).toString(16)})}});
//# sourceMappingURL=index.umd.min.js.map
+14
-8
CHANGELOG.md
# Changelog
This file was generated using [@jscutlery/semver](https://github.com/jscutlery/semver).
All notable changes to this project will be documented in this file.
## [0.0.4](https://github.com/AndrewRedican/hyperfrontend/compare/lib-random-generator-utils@0.0.3...lib-random-generator-utils@0.0.4) (2026-03-08)
## [0.0.5](https://github.com/AndrewRedican/hyperfrontend/compare/c8db08be8b183addd26caf81fdd17fb3693f296f...466c0388c4cd516b9c704214140b4df1004098e6) - 2026-06-23
### Other
- **@hyperfrontend/workspace:** remove lib-builder and tool-package as implicit dependencies for all lib projects
## [0.0.4](https://github.com/AndrewRedican/hyperfrontend/compare/lib-random-generator-utils@0.0.3...lib-random-generator-utils@0.0.4) - 2026-03-08
### Bug Fixes
* **lib-random-generator-utils:** correct package exports ([0feacc4](https://github.com/AndrewRedican/hyperfrontend/commit/0feacc4295e2f687e6c9f4df118db59aa10d1c69))
- **lib-random-generator-utils:** correct package exports ([0feacc4](https://github.com/AndrewRedican/hyperfrontend/commit/0feacc4295e2f687e6c9f4df118db59aa10d1c69))
## [0.0.3](https://github.com/AndrewRedican/hyperfrontend/compare/lib-random-generator-utils@0.0.2...lib-random-generator-utils@0.0.3) (2026-03-02)
## [0.0.3](https://github.com/AndrewRedican/hyperfrontend/compare/lib-random-generator-utils@0.0.2...lib-random-generator-utils@0.0.3) - 2026-03-02
### Bug Fixes
* **lib-random-generator-utils:** correct package exports ([0feacc4](https://github.com/AndrewRedican/hyperfrontend/commit/0feacc4295e2f687e6c9f4df118db59aa10d1c69))
- **lib-random-generator-utils:** correct package exports ([0feacc4](https://github.com/AndrewRedican/hyperfrontend/commit/0feacc4295e2f687e6c9f4df118db59aa10d1c69))
## [0.0.2](https://github.com/AndrewRedican/hyperfrontend/compare/lib-random-generator-utils@0.0.1...lib-random-generator-utils@0.0.2) (2026-02-26)
## [0.0.2](https://github.com/AndrewRedican/hyperfrontend/compare/lib-random-generator-utils@0.0.1...lib-random-generator-utils@0.0.2) - 2026-02-26
## 0.0.1 (2026-02-15)
## 0.0.1 - 2026-02-15
+120
-95
index.cjs.js
'use strict';
/**
* Safe copies of Math built-in methods.
*
* These references are captured at module initialization time to protect against
* prototype pollution attacks. Import only what you need for tree-shaking.
*
* @module @hyperfrontend/immutable-api-utils/built-in-copy/math
*/
// Capture references at module initialization time
const _Math = globalThis.Math;
/**
* (Safe copy) Returns the largest integer less than or equal to a number.
*/
const floor = _Math.floor;
// ============================================================================
// Powers and Roots
// ============================================================================
/**
* (Safe copy) Returns the base to the exponent power.
*/
const pow = _Math.pow;
/**
* (Safe copy) Returns the square root of a number.
*/
const sqrt = _Math.sqrt;
/**
* (Safe copy) Returns e raised to the power of a number.
*/
const exp = _Math.exp;
// ============================================================================
// Logarithms
// ============================================================================
/**
* (Safe copy) Returns the natural logarithm of a number.
*/
const log = _Math.log;
// ============================================================================
// Trigonometry
// ============================================================================
/**
* (Safe copy) Returns the sine of a number.
*/
const sin = _Math.sin;
// ============================================================================
// Random
// ============================================================================
/**
* (Safe copy) Returns a pseudo-random number between 0 and 1.
* Note: This is NOT cryptographically secure. For secure random values,
* use crypto.getRandomValues().
*/
const random = _Math.random;
const index_cjs_js = require('./_dependencies/@hyperfrontend/immutable-api-utils/built-in-copy/math/index.cjs.js');
const index_cjs_js$1 = require('./_dependencies/@hyperfrontend/immutable-api-utils/built-in-copy/error/index.cjs.js');

@@ -61,33 +11,18 @@ /**

* @returns A random number from the exponential distribution
*
* @example Modeling time between events (e.g., customer arrivals)
* ```typescript
* // Higher lambda = shorter average wait time
* const averageWaitMinutes = 5
* const lambda = 1 / averageWaitMinutes
* const waitTime = randomExponential(lambda)
* // => 3.7 (varies each call, most values clustered near 0-10)
* ```
*/
function randomExponential(lambda) {
const u = random();
return -log(1 - u) / lambda;
const u = index_cjs_js.random();
return -index_cjs_js.log(1 - u) / lambda;
}
/**
* Safe copies of Error built-ins via factory functions.
*
* Since constructors cannot be safely captured via Object.assign, this module
* provides factory functions that use Reflect.construct internally.
*
* These references are captured at module initialization time to protect against
* prototype pollution attacks. Import only what you need for tree-shaking.
*
* @module @hyperfrontend/immutable-api-utils/built-in-copy/error
*/
// Capture references at module initialization time
const _Error = globalThis.Error;
const _Reflect = globalThis.Reflect;
/**
* (Safe copy) Creates a new Error using the captured Error constructor.
* Use this instead of `new Error()`.
*
* @param message - Optional error message.
* @param options - Optional error options.
* @returns A new Error instance.
*/
const createError = (message, options) => _Reflect.construct(_Error, [message, options]);
/**
* Generates a random number following a Gaussian (normal) distribution within a specified range.

@@ -98,14 +33,26 @@ *

* @returns A random number from the Gaussian distribution bounded by min and max
*
* @example Simulating human heights in centimeters
* ```typescript
* const heightCm = randomGaussian(150, 200)
* // => 174.3 (most values cluster around the midpoint 175)
* ```
*
* @example Generating test scores with realistic distribution
* ```typescript
* const testScore = randomGaussian(0, 100)
* // => 52.8 (bell curve centered at 50, rarely hits extremes)
* ```
*/
function randomGaussian(min, max) {
if (min > max) {
throw createError('Min value should be less than or equal to max value.');
throw index_cjs_js$1.createError('Min value should be less than or equal to max value.');
}
let u, v, s;
do {
u = random() * 2 - 1;
v = random() * 2 - 1;
u = index_cjs_js.random() * 2 - 1;
v = index_cjs_js.random() * 2 - 1;
s = u * u + v * v;
} while (s >= 1 || s === 0);
const std_dev = sqrt((-2 * log(s)) / s);
const std_dev = index_cjs_js.sqrt((-2 * index_cjs_js.log(s)) / s);
const z0 = u * std_dev;

@@ -128,6 +75,17 @@ const mu = (min + max) / 2;

* @returns A random number from the logarithmic distribution
*
* @example Generating values with exponential growth characteristics
* ```typescript
* // scale=1 produces values from 1 to e (~2.718)
* const smallScale = randomLogarithmic(1)
* // => 1.8 (values between 1 and ~2.7)
*
* // scale=5 produces values from 1 to e^5 (~148)
* const largeScale = randomLogarithmic(5)
* // => 42.3 (wider range, skewed toward lower values)
* ```
*/
function randomLogarithmic(scale) {
const u = random();
return exp(scale * u);
const u = index_cjs_js.random();
return index_cjs_js.exp(scale * u);
}

@@ -142,7 +100,20 @@

* @returns A random number from the power law distribution bounded by min and max
*
* @example Simulating social network follower counts (few have many, many have few)
* ```typescript
* // alpha > 2 creates "long tail" - most values near min
* const followerCount = randomPowerLaw(2.5, 1, 1000000)
* // => 127 (typically low, occasionally very large)
* ```
*
* @example Modeling file sizes in a system
* ```typescript
* const fileSizeKb = randomPowerLaw(2.0, 1, 10000)
* // => 45 (many small files, rare large files)
* ```
*/
function randomPowerLaw(alpha, min, max) {
const u = random();
const factor = (pow(max, alpha - 1) - pow(min, alpha - 1)) * u + pow(min, alpha - 1);
return pow(factor, 1 / (alpha - 1));
const u = index_cjs_js.random();
const factor = (index_cjs_js.pow(max, alpha - 1) - index_cjs_js.pow(min, alpha - 1)) * u + index_cjs_js.pow(min, alpha - 1);
return index_cjs_js.pow(factor, 1 / (alpha - 1));
}

@@ -155,6 +126,19 @@

* @returns A pseudo-random number between 0 and 1.
*
* @example Reproducible random values for testing
* ```typescript
* // Same seed always yields the same result
* randomPseudo(42)
* // => 0.6853... (deterministic)
*
* randomPseudo(42)
* // => 0.6853... (identical)
*
* randomPseudo(43)
* // => 0.1762... (different seed, different result)
* ```
*/
function randomPseudo(seed) {
const x = sin(seed) * 10000;
return x - floor(x);
const x = index_cjs_js.sin(seed) * 10000;
return x - index_cjs_js.floor(x);
}

@@ -167,2 +151,12 @@

* @returns The pseudo-random variation as a number.
*
* @example Reproducible randomness for a specific timestamp
* ```typescript
* const releaseDate = new Date('2024-03-15T10:30:00Z')
*
* // Same date always produces the same result
* const value1 = randomPseudoTimeBased(releaseDate)
* const value2 = randomPseudoTimeBased(releaseDate)
* // value1 === value2 (deterministic)
* ```
*/

@@ -179,5 +173,18 @@ function randomPseudoTimeBased(seedTime) {

* @returns A random number between min (inclusive) and max (exclusive)
*
* @example Generating a random price within a budget range
* ```typescript
* const priceUsd = randomUniform(10, 50)
* // => 27.34 (any value equally likely within range)
* ```
*
* @example Random coordinates for game object placement
* ```typescript
* const xPosition = randomUniform(0, 800)
* const yPosition = randomUniform(0, 600)
* // => x: 342.7, y: 198.2
* ```
*/
function randomUniform(min, max) {
return random() * (max - min) + min;
return index_cjs_js.random() * (max - min) + min;
}

@@ -189,10 +196,16 @@

* @returns a version 4 UUID.
*
* @example Creating unique identifiers for entities
* ```typescript
* const userId = uuidV4()
* // => 'a1b2c3d4-e5f6-4a7b-8c9d-0e1f2a3b4c5d'
*
* const sessionId = uuidV4()
* // => '9f8e7d6c-5b4a-4321-8765-4321fedcba98'
* ```
*/
function uuidV4() {
return 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, (char) => {
// Generate a random hexadecimal digit, 0 - 15
const randomHex = (random() * 16) | 0;
// Use the randomHex for 'x' and a specific subset for 'y'
const randomHex = (index_cjs_js.random() * 16) | 0;
const finalHex = char === 'x' ? randomHex : (randomHex & 0x3) | 0x8;
// Convert the final hexadecimal digit to a string
return finalHex.toString(16);

@@ -206,2 +219,15 @@ });

* @returns true if the string is a version 4 UUID, otherwise false.
*
* @example Validating user input as UUID
* ```typescript
* isUuidV4('a1b2c3d4-e5f6-4a7b-8c9d-0e1f2a3b4c5d')
* // => true
*
* isUuidV4('not-a-uuid')
* // => false
*
* // Version 1 UUID (has '1' in third segment, not '4')
* isUuidV4('550e8400-e29b-11d4-a716-446655440000')
* // => false
* ```
*/

@@ -222,2 +248,1 @@ function isUuidV4(str) {

exports.uuidV4 = uuidV4;
//# sourceMappingURL=index.cjs.js.map
+178
-9
index.d.ts

@@ -1,9 +0,178 @@

export * from './random-exponential';
export * from './random-gaussian';
export * from './random-logarithmic';
export * from './random-power-law';
export * from './random-pseudo';
export * from './random-pseudo-time-based';
export * from './random-uniform';
export * from './uuid-v4';
//# sourceMappingURL=index.d.ts.map
/**
* Generates a random number following an exponential distribution.
*
* @param lambda - The rate parameter (λ) controlling the distribution shape
* @returns A random number from the exponential distribution
*
* @example Modeling time between events (e.g., customer arrivals)
* ```typescript
* // Higher lambda = shorter average wait time
* const averageWaitMinutes = 5
* const lambda = 1 / averageWaitMinutes
* const waitTime = randomExponential(lambda)
* // => 3.7 (varies each call, most values clustered near 0-10)
* ```
*/
declare function randomExponential(lambda: number): number;
/**
* Generates a random number following a Gaussian (normal) distribution within a specified range.
*
* @param min - The minimum value of the range
* @param max - The maximum value of the range
* @returns A random number from the Gaussian distribution bounded by min and max
*
* @example Simulating human heights in centimeters
* ```typescript
* const heightCm = randomGaussian(150, 200)
* // => 174.3 (most values cluster around the midpoint 175)
* ```
*
* @example Generating test scores with realistic distribution
* ```typescript
* const testScore = randomGaussian(0, 100)
* // => 52.8 (bell curve centered at 50, rarely hits extremes)
* ```
*/
declare function randomGaussian(min: number, max: number): number;
/**
* Generates a random number following a logarithmic distribution.
*
* @param scale - The scale parameter controlling the distribution spread
* @returns A random number from the logarithmic distribution
*
* @example Generating values with exponential growth characteristics
* ```typescript
* // scale=1 produces values from 1 to e (~2.718)
* const smallScale = randomLogarithmic(1)
* // => 1.8 (values between 1 and ~2.7)
*
* // scale=5 produces values from 1 to e^5 (~148)
* const largeScale = randomLogarithmic(5)
* // => 42.3 (wider range, skewed toward lower values)
* ```
*/
declare function randomLogarithmic(scale: number): number;
/**
* Generates a random number following a power law distribution within a specified range.
*
* @param alpha - The power law exponent controlling the distribution
* @param min - The minimum value of the range
* @param max - The maximum value of the range
* @returns A random number from the power law distribution bounded by min and max
*
* @example Simulating social network follower counts (few have many, many have few)
* ```typescript
* // alpha > 2 creates "long tail" - most values near min
* const followerCount = randomPowerLaw(2.5, 1, 1000000)
* // => 127 (typically low, occasionally very large)
* ```
*
* @example Modeling file sizes in a system
* ```typescript
* const fileSizeKb = randomPowerLaw(2.0, 1, 10000)
* // => 45 (many small files, rare large files)
* ```
*/
declare function randomPowerLaw(alpha: number, min: number, max: number): number;
/**
* A simple pseudo-random number generator.
*
* @param seed - The seed for the generator.
* @returns A pseudo-random number between 0 and 1.
*
* @example Reproducible random values for testing
* ```typescript
* // Same seed always yields the same result
* randomPseudo(42)
* // => 0.6853... (deterministic)
*
* randomPseudo(42)
* // => 0.6853... (identical)
*
* randomPseudo(43)
* // => 0.1762... (different seed, different result)
* ```
*/
declare function randomPseudo(seed: number): number;
/**
* Generates a deterministic pseudo-random variation based solely on the seed time.
*
* @param seedTime - The seed time for the variation.
* @returns The pseudo-random variation as a number.
*
* @example Reproducible randomness for a specific timestamp
* ```typescript
* const releaseDate = new Date('2024-03-15T10:30:00Z')
*
* // Same date always produces the same result
* const value1 = randomPseudoTimeBased(releaseDate)
* const value2 = randomPseudoTimeBased(releaseDate)
* // value1 === value2 (deterministic)
* ```
*/
declare function randomPseudoTimeBased(seedTime: Date): number;
/**
* Generates a random number uniformly distributed within a specified range.
*
* @param min - The minimum value of the range (inclusive)
* @param max - The maximum value of the range (exclusive)
* @returns A random number between min (inclusive) and max (exclusive)
*
* @example Generating a random price within a budget range
* ```typescript
* const priceUsd = randomUniform(10, 50)
* // => 27.34 (any value equally likely within range)
* ```
*
* @example Random coordinates for game object placement
* ```typescript
* const xPosition = randomUniform(0, 800)
* const yPosition = randomUniform(0, 600)
* // => x: 342.7, y: 198.2
* ```
*/
declare function randomUniform(min: number, max: number): number;
/**
* Generates a version 4 UUID.
*
* @returns a version 4 UUID.
*
* @example Creating unique identifiers for entities
* ```typescript
* const userId = uuidV4()
* // => 'a1b2c3d4-e5f6-4a7b-8c9d-0e1f2a3b4c5d'
*
* const sessionId = uuidV4()
* // => '9f8e7d6c-5b4a-4321-8765-4321fedcba98'
* ```
*/
declare function uuidV4(): string;
/**
* Validate if a string is a version 4 UUID.
*
* @param str the string to be validated.
* @returns true if the string is a version 4 UUID, otherwise false.
*
* @example Validating user input as UUID
* ```typescript
* isUuidV4('a1b2c3d4-e5f6-4a7b-8c9d-0e1f2a3b4c5d')
* // => true
*
* isUuidV4('not-a-uuid')
* // => false
*
* // Version 1 UUID (has '1' in third segment, not '4')
* isUuidV4('550e8400-e29b-11d4-a716-446655440000')
* // => false
* ```
*/
declare function isUuidV4(str: string): boolean;
export { isUuidV4, randomExponential, randomGaussian, randomLogarithmic, randomPowerLaw, randomPseudo, randomPseudoTimeBased, randomUniform, uuidV4 };
+1
-1
index.d.ts.map

@@ -1,1 +0,1 @@

{"version":3,"file":"index.d.ts","sourceRoot":"","sources":["../../../../../../../../libs/utils/random-generator/src/index.ts"],"names":[],"mappings":"AAAA,cAAc,sBAAsB,CAAA;AACpC,cAAc,mBAAmB,CAAA;AACjC,cAAc,sBAAsB,CAAA;AACpC,cAAc,oBAAoB,CAAA;AAClC,cAAc,iBAAiB,CAAA;AAC/B,cAAc,4BAA4B,CAAA;AAC1C,cAAc,kBAAkB,CAAA;AAChC,cAAc,WAAW,CAAA"}
{"version":3,"file":"index.d.ts","sourceRoot":"","sources":["../../../../../../../../libs/utils/random-generator/src/index.ts"],"names":[],"mappings":"AAAA;;;;GAIG;AACH,OAAO,EAAE,iBAAiB,EAAE,MAAM,sBAAsB,CAAA;AACxD,OAAO,EAAE,cAAc,EAAE,MAAM,mBAAmB,CAAA;AAClD,OAAO,EAAE,iBAAiB,EAAE,MAAM,sBAAsB,CAAA;AACxD,OAAO,EAAE,cAAc,EAAE,MAAM,oBAAoB,CAAA;AACnD,OAAO,EAAE,YAAY,EAAE,MAAM,iBAAiB,CAAA;AAC9C,OAAO,EAAE,qBAAqB,EAAE,MAAM,4BAA4B,CAAA;AAClE,OAAO,EAAE,aAAa,EAAE,MAAM,kBAAkB,CAAA;AAChD,OAAO,EAAE,MAAM,EAAE,QAAQ,EAAE,MAAM,WAAW,CAAA"}
+105
-80
index.esm.js

@@ -1,53 +0,3 @@

/**
* Safe copies of Math built-in methods.
*
* These references are captured at module initialization time to protect against
* prototype pollution attacks. Import only what you need for tree-shaking.
*
* @module @hyperfrontend/immutable-api-utils/built-in-copy/math
*/
// Capture references at module initialization time
const _Math = globalThis.Math;
/**
* (Safe copy) Returns the largest integer less than or equal to a number.
*/
const floor = _Math.floor;
// ============================================================================
// Powers and Roots
// ============================================================================
/**
* (Safe copy) Returns the base to the exponent power.
*/
const pow = _Math.pow;
/**
* (Safe copy) Returns the square root of a number.
*/
const sqrt = _Math.sqrt;
/**
* (Safe copy) Returns e raised to the power of a number.
*/
const exp = _Math.exp;
// ============================================================================
// Logarithms
// ============================================================================
/**
* (Safe copy) Returns the natural logarithm of a number.
*/
const log = _Math.log;
// ============================================================================
// Trigonometry
// ============================================================================
/**
* (Safe copy) Returns the sine of a number.
*/
const sin = _Math.sin;
// ============================================================================
// Random
// ============================================================================
/**
* (Safe copy) Returns a pseudo-random number between 0 and 1.
* Note: This is NOT cryptographically secure. For secure random values,
* use crypto.getRandomValues().
*/
const random = _Math.random;
import { random, log, sqrt, exp, pow, sin, floor } from './_dependencies/@hyperfrontend/immutable-api-utils/built-in-copy/math/index.esm.js';
import { createError } from './_dependencies/@hyperfrontend/immutable-api-utils/built-in-copy/error/index.esm.js';

@@ -59,2 +9,11 @@ /**

* @returns A random number from the exponential distribution
*
* @example Modeling time between events (e.g., customer arrivals)
* ```typescript
* // Higher lambda = shorter average wait time
* const averageWaitMinutes = 5
* const lambda = 1 / averageWaitMinutes
* const waitTime = randomExponential(lambda)
* // => 3.7 (varies each call, most values clustered near 0-10)
* ```
*/

@@ -67,26 +26,2 @@ function randomExponential(lambda) {

/**
* Safe copies of Error built-ins via factory functions.
*
* Since constructors cannot be safely captured via Object.assign, this module
* provides factory functions that use Reflect.construct internally.
*
* These references are captured at module initialization time to protect against
* prototype pollution attacks. Import only what you need for tree-shaking.
*
* @module @hyperfrontend/immutable-api-utils/built-in-copy/error
*/
// Capture references at module initialization time
const _Error = globalThis.Error;
const _Reflect = globalThis.Reflect;
/**
* (Safe copy) Creates a new Error using the captured Error constructor.
* Use this instead of `new Error()`.
*
* @param message - Optional error message.
* @param options - Optional error options.
* @returns A new Error instance.
*/
const createError = (message, options) => _Reflect.construct(_Error, [message, options]);
/**
* Generates a random number following a Gaussian (normal) distribution within a specified range.

@@ -97,2 +32,14 @@ *

* @returns A random number from the Gaussian distribution bounded by min and max
*
* @example Simulating human heights in centimeters
* ```typescript
* const heightCm = randomGaussian(150, 200)
* // => 174.3 (most values cluster around the midpoint 175)
* ```
*
* @example Generating test scores with realistic distribution
* ```typescript
* const testScore = randomGaussian(0, 100)
* // => 52.8 (bell curve centered at 50, rarely hits extremes)
* ```
*/

@@ -127,2 +74,13 @@ function randomGaussian(min, max) {

* @returns A random number from the logarithmic distribution
*
* @example Generating values with exponential growth characteristics
* ```typescript
* // scale=1 produces values from 1 to e (~2.718)
* const smallScale = randomLogarithmic(1)
* // => 1.8 (values between 1 and ~2.7)
*
* // scale=5 produces values from 1 to e^5 (~148)
* const largeScale = randomLogarithmic(5)
* // => 42.3 (wider range, skewed toward lower values)
* ```
*/

@@ -141,2 +99,15 @@ function randomLogarithmic(scale) {

* @returns A random number from the power law distribution bounded by min and max
*
* @example Simulating social network follower counts (few have many, many have few)
* ```typescript
* // alpha > 2 creates "long tail" - most values near min
* const followerCount = randomPowerLaw(2.5, 1, 1000000)
* // => 127 (typically low, occasionally very large)
* ```
*
* @example Modeling file sizes in a system
* ```typescript
* const fileSizeKb = randomPowerLaw(2.0, 1, 10000)
* // => 45 (many small files, rare large files)
* ```
*/

@@ -154,2 +125,15 @@ function randomPowerLaw(alpha, min, max) {

* @returns A pseudo-random number between 0 and 1.
*
* @example Reproducible random values for testing
* ```typescript
* // Same seed always yields the same result
* randomPseudo(42)
* // => 0.6853... (deterministic)
*
* randomPseudo(42)
* // => 0.6853... (identical)
*
* randomPseudo(43)
* // => 0.1762... (different seed, different result)
* ```
*/

@@ -166,2 +150,12 @@ function randomPseudo(seed) {

* @returns The pseudo-random variation as a number.
*
* @example Reproducible randomness for a specific timestamp
* ```typescript
* const releaseDate = new Date('2024-03-15T10:30:00Z')
*
* // Same date always produces the same result
* const value1 = randomPseudoTimeBased(releaseDate)
* const value2 = randomPseudoTimeBased(releaseDate)
* // value1 === value2 (deterministic)
* ```
*/

@@ -178,2 +172,15 @@ function randomPseudoTimeBased(seedTime) {

* @returns A random number between min (inclusive) and max (exclusive)
*
* @example Generating a random price within a budget range
* ```typescript
* const priceUsd = randomUniform(10, 50)
* // => 27.34 (any value equally likely within range)
* ```
*
* @example Random coordinates for game object placement
* ```typescript
* const xPosition = randomUniform(0, 800)
* const yPosition = randomUniform(0, 600)
* // => x: 342.7, y: 198.2
* ```
*/

@@ -188,10 +195,16 @@ function randomUniform(min, max) {

* @returns a version 4 UUID.
*
* @example Creating unique identifiers for entities
* ```typescript
* const userId = uuidV4()
* // => 'a1b2c3d4-e5f6-4a7b-8c9d-0e1f2a3b4c5d'
*
* const sessionId = uuidV4()
* // => '9f8e7d6c-5b4a-4321-8765-4321fedcba98'
* ```
*/
function uuidV4() {
return 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, (char) => {
// Generate a random hexadecimal digit, 0 - 15
const randomHex = (random() * 16) | 0;
// Use the randomHex for 'x' and a specific subset for 'y'
const finalHex = char === 'x' ? randomHex : (randomHex & 0x3) | 0x8;
// Convert the final hexadecimal digit to a string
return finalHex.toString(16);

@@ -205,2 +218,15 @@ });

* @returns true if the string is a version 4 UUID, otherwise false.
*
* @example Validating user input as UUID
* ```typescript
* isUuidV4('a1b2c3d4-e5f6-4a7b-8c9d-0e1f2a3b4c5d')
* // => true
*
* isUuidV4('not-a-uuid')
* // => false
*
* // Version 1 UUID (has '1' in third segment, not '4')
* isUuidV4('550e8400-e29b-11d4-a716-446655440000')
* // => false
* ```
*/

@@ -213,2 +239,1 @@ function isUuidV4(str) {

export { isUuidV4, randomExponential, randomGaussian, randomLogarithmic, randomPowerLaw, randomPseudo, randomPseudoTimeBased, randomUniform, uuidV4 };
//# sourceMappingURL=index.esm.js.map
+13
-7
package.json
{
"name": "@hyperfrontend/random-generator-utils",
"version": "0.0.4",
"version": "0.0.5",
"description": "Statistical random distributions and UUID generation for simulations, testing, and procedural content.",

@@ -34,6 +34,2 @@ "license": "MIT",

"require": "./index.cjs.js"
},
"./bundle": {
"import": "./bundle/index.iife.min.js",
"require": "./bundle/index.iife.min.js"
}

@@ -61,3 +57,13 @@ },

"unpkg": "./bundle/index.umd.min.js",
"jsdelivr": "./bundle/index.umd.min.js"
}
"jsdelivr": "./bundle/index.umd.min.js",
"files": [
"**/index.*",
"**/index.d.ts",
"CHANGELOG.md",
"FUNDING.md",
"LICENSE.md",
"README.md",
"SECURITY.md",
"!**/*.js.map"
]
}
+3
-1
README.md

@@ -38,2 +38,4 @@ # @hyperfrontend/random-generator-utils

• 👉 See [**documentation**](https://www.hyperfrontend.dev/docs/libraries/utils/random-generator/)
## What is @hyperfrontend/random-generator-utils?

@@ -221,2 +223,2 @@

MIT
[MIT](https://github.com/AndrewRedican/hyperfrontend/blob/main/LICENSE.md)
-1
bundle/index.iife.js.map
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index.esm.js.map
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-8
random-exponential.d.ts
/**
* Generates a random number following an exponential distribution.
*
* @param lambda - The rate parameter (λ) controlling the distribution shape
* @returns A random number from the exponential distribution
*/
export declare function randomExponential(lambda: number): number;
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random-exponential.d.ts.map
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-10
random-gaussian.d.ts
/**
* Generates a random number following a Gaussian (normal) distribution within a specified range.
*
* @param min - The minimum value of the range
* @param max - The maximum value of the range
* @returns A random number from the Gaussian distribution bounded by min and max
*/
export declare function randomGaussian(min: number, max: number): number;
export default randomGaussian;
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random-gaussian.d.ts.map
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-8
random-logarithmic.d.ts
/**
* Generates a random number following a logarithmic distribution.
*
* @param scale - The scale parameter controlling the distribution spread
* @returns A random number from the logarithmic distribution
*/
export declare function randomLogarithmic(scale: number): number;
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random-logarithmic.d.ts.map
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-10
random-power-law.d.ts
/**
* Generates a random number following a power law distribution within a specified range.
*
* @param alpha - The power law exponent controlling the distribution
* @param min - The minimum value of the range
* @param max - The maximum value of the range
* @returns A random number from the power law distribution bounded by min and max
*/
export declare function randomPowerLaw(alpha: number, min: number, max: number): number;
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-1
random-power-law.d.ts.map
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-8
random-pseudo-time-based.d.ts
/**
* Generates a deterministic pseudo-random variation based solely on the seed time.
*
* @param seedTime - The seed time for the variation.
* @returns The pseudo-random variation as a number.
*/
export declare function randomPseudoTimeBased(seedTime: Date): number;
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-1
random-pseudo-time-based.d.ts.map
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-8
random-pseudo.d.ts
/**
* A simple pseudo-random number generator.
*
* @param seed - The seed for the generator.
* @returns A pseudo-random number between 0 and 1.
*/
export declare function randomPseudo(seed: number): number;
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random-pseudo.d.ts.map
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-9
random-uniform.d.ts
/**
* Generates a random number uniformly distributed within a specified range.
*
* @param min - The minimum value of the range (inclusive)
* @param max - The maximum value of the range (exclusive)
* @returns A random number between min (inclusive) and max (exclusive)
*/
export declare function randomUniform(min: number, max: number): number;
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random-uniform.d.ts.map
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-14
uuid-v4.d.ts
/**
* Generates a version 4 UUID.
*
* @returns a version 4 UUID.
*/
export declare function uuidV4(): string;
/**
* Validate if a string is a version 4 UUID.
*
* @param str the string to be validated.
* @returns true if the string is a version 4 UUID, otherwise false.
*/
export declare function isUuidV4(str: string): boolean;
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uuid-v4.d.ts.map
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