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mathjs

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Math.js is an extensive math library for JavaScript and Node.js. It features a flexible expression parser with support for symbolic computation, comes with a large set of built-in functions and constants, and offers an integrated solution to work with dif

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import { factory } from '../../utils/factory'; import { isNumber } from '../../utils/is'; import { createRng } from './util/seededRNG'; import { flatten } from '../../utils/array'; var name = 'pickRandom'; var dependencies = ['typed', 'config', '?on']; export var createPickRandom = /* #__PURE__ */factory(name, dependencies, function (_ref) { var typed = _ref.typed, config = _ref.config, on = _ref.on; // seeded pseudo random number generator var rng = createRng(config.randomSeed); if (on) { on('config', function (curr, prev) { if (curr.randomSeed !== prev.randomSeed) { rng = createRng(curr.randomSeed); } }); } /** * Random pick one or more values from a one dimensional array. * Array elements are picked using a random function with uniform or weighted distribution. * * Syntax: * * math.pickRandom(array) * math.pickRandom(array, number) * math.pickRandom(array, weights) * math.pickRandom(array, number, weights) * math.pickRandom(array, weights, number) * * Examples: * * math.pickRandom([3, 6, 12, 2]) // returns one of the values in the array * math.pickRandom([3, 6, 12, 2], 2) // returns an array of two of the values in the array * math.pickRandom([3, 6, 12, 2], [1, 3, 2, 1]) // returns one of the values in the array with weighted distribution * math.pickRandom([3, 6, 12, 2], 2, [1, 3, 2, 1]) // returns an array of two of the values in the array with weighted distribution * math.pickRandom([3, 6, 12, 2], [1, 3, 2, 1], 2) // returns an array of two of the values in the array with weighted distribution * * See also: * * random, randomInt * * @param {Array | Matrix} array A one dimensional array * @param {Int} number An int or float * @param {Array | Matrix} weights An array of ints or floats * @return {number | Array} Returns a single random value from array when number is 1 or undefined. * Returns an array with the configured number of elements when number is > 1. */ return typed({ 'Array | Matrix': function ArrayMatrix(possibles) { return _pickRandom(possibles); }, 'Array | Matrix, number': function ArrayMatrixNumber(possibles, number) { return _pickRandom(possibles, number, undefined); }, 'Array | Matrix, Array': function ArrayMatrixArray(possibles, weights) { return _pickRandom(possibles, undefined, weights); }, 'Array | Matrix, Array | Matrix, number': function ArrayMatrixArrayMatrixNumber(possibles, weights, number) { return _pickRandom(possibles, number, weights); }, 'Array | Matrix, number, Array | Matrix': function ArrayMatrixNumberArrayMatrix(possibles, number, weights) { return _pickRandom(possibles, number, weights); } }); function _pickRandom(possibles, number, weights) { var single = typeof number === 'undefined'; if (single) { number = 1; } possibles = flatten(possibles.valueOf()).valueOf(); // get Array if (weights) { weights = weights.valueOf(); // get Array } var totalWeights = 0; if (typeof weights !== 'undefined') { if (weights.length !== possibles.length) { throw new Error('Weights must have the same length as possibles'); } for (var i = 0, len = weights.length; i < len; i++) { if (!isNumber(weights[i]) || weights[i] < 0) { throw new Error('Weights must be an array of positive numbers'); } totalWeights += weights[i]; } } var length = possibles.length; if (length === 0) { return []; } else if (number >= length) { return number > 1 ? possibles : possibles[0]; } var result = []; var pick; while (result.length < number) { if (typeof weights === 'undefined') { pick = possibles[Math.floor(rng() * length)]; } else { var randKey = rng() * totalWeights; for (var _i = 0, _len = possibles.length; _i < _len; _i++) { randKey -= weights[_i]; if (randKey < 0) { pick = possibles[_i]; break; } } } if (result.indexOf(pick) === -1) { result.push(pick); } } return single ? result[0] : result; // TODO: return matrix when input was a matrix // TODO: add support for multi dimensional matrices } });