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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' const name = 'kldivergence' const dependencies = ['typed', 'matrix', 'divide', 'sum', 'multiply', 'dotDivide', 'log', 'isNumeric'] export const createKldivergence = /* #__PURE__ */ factory(name, dependencies, ({ typed, matrix, divide, sum, multiply, dotDivide, log, isNumeric }) => { /** * Calculate the Kullback-Leibler (KL) divergence between two distributions * * Syntax: * * math.kldivergence(x, y) * * Examples: * * math.kldivergence([0.7,0.5,0.4], [0.2,0.9,0.5]) //returns 0.24376698773121153 * * * @param {Array | Matrix} q First vector * @param {Array | Matrix} p Second vector * @return {number} Returns distance between q and p */ return typed(name, { 'Array, Array': function (q, p) { return _kldiv(matrix(q), matrix(p)) }, 'Matrix, Array': function (q, p) { return _kldiv(q, matrix(p)) }, 'Array, Matrix': function (q, p) { return _kldiv(matrix(q), p) }, 'Matrix, Matrix': function (q, p) { return _kldiv(q, p) } }) function _kldiv (q, p) { const plength = p.size().length const qlength = q.size().length if (plength > 1) { throw new Error('first object must be one dimensional') } if (qlength > 1) { throw new Error('second object must be one dimensional') } if (plength !== qlength) { throw new Error('Length of two vectors must be equal') } // Before calculation, apply normalization const sumq = sum(q) if (sumq === 0) { throw new Error('Sum of elements in first object must be non zero') } const sump = sum(p) if (sump === 0) { throw new Error('Sum of elements in second object must be non zero') } const qnorm = divide(q, sum(q)) const pnorm = divide(p, sum(p)) const result = sum(multiply(qnorm, log(dotDivide(qnorm, pnorm)))) if (isNumeric(result)) { return result } else { return Number.NaN } } })