Pick a random outcome given probabilities.
Port of TweetNaCl cryptographic library to JavaScript
A Node.js module for efficient sampling from a discrete probability distribution using the alias method.
Generate random numbers from various distributions.
TypeScript definitions for d3-random
Fastest random ID and random string generation for Node.js
URL and cookie safe UIDs
Use the random function in CSS
An alias package for `crypto.randomBytes` in Node.js and/or browsers
Generate a cryptographically strong random string
Random utility functions for ethers.
A Pulumi package to safely use randomness in Pulumi programs.
The Serverless Framework's new infrastructure provisioning technology — Build, compose, & deploy serverless apps in seconds...
A small implementation of `crypto.getRandomValues` for React Native. This is useful to polyfill for libraries like [uuid](https://www.npmjs.com/package/uuid) that depend on it.
Generate a random integer
Statistical routines and probability distributions.
Provides functions for detecting if the host environment supports the WebCrypto API
Library for sampling of random values from a discrete probability distribution, using the Walker-Vose alias method.
math-random is an isomorphic, drop-in replacement for `Math.random` that uses cryptographically secure random number generation, where available
Generate random numbers with a seed, useful for reproducible tests
GRC's UHE PRNG in node (Ultra-High Entropy Pseudo-Random Number Generator by Gibson Research Corporation)
Temporary file and directory creator
Qlik supported browsers
Generates an id useable in json rpc payloads.
Useful or gaming.
If a categorical distribution has k distinct values, traditional approaches will require O(k) work to pick an outcome with the correct probabilities. This algorithm uses conditional probability to construct a table which will yield outcomes with the correct probabilities. Table generation requires O(k) time, but subsequent generation is done in O(1) time.
'Copyright (c) <2016> <Daniel Rainey> Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.']
Fork of aliastable by Paul J Sanchez. If a categorical distribution has k distinct values, traditional approaches will require O(k) work to pick an outcome with the correct probabilities. This algorithm uses conditional probability to construct a table which will yield outcomes with the correct probabilities, but in O(1) time.