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