webppl/src/dists/ispNormal.js

Probabilistic programming for the web

'use strict';
var ad = require('../ad');
var base = require('./base');
var types = require('../types');
var gaussian = require('./gaussian');
var Gaussian = gaussian.Gaussian;
var IspNormal = base.makeDistributionType({
    name: 'IspNormal',
    nodoc: true,
    desc: 'A distribution over positive reals obtained by mapping a Gaussian ' + 'distributed variable through the softplus function.',
    params: [
        {
            name: 'mu',
            desc: 'location',
            type: types.unboundedReal
        },
        {
            name: 'sigma',
            desc: 'scale',
            type: types.positiveReal
        }
    ],
    mixins: [base.continuousSupport],
    sample: function () {
        var mu = ad.value(this.params.mu);
        var sigma = ad.value(this.params.sigma);
        return Math.log(Math.exp(gaussian.sample(mu, sigma)) + 1);
    },
    score: function (val) {
        var mu = this.params.mu;
        var sigma = this.params.sigma;
        var x = ad.scalar.log(ad.scalar.sub(ad.scalar.exp(val), 1));
        return ad.scalar.sub(ad.scalar.add(gaussian.score(mu, sigma, x), val), x);
    },
    base: function () {
        return new Gaussian({
            mu: 0,
            sigma: 1
        });
    },
    transform: function (x) {
        var mu = this.params.mu;
        var sigma = this.params.sigma;
        return ad.scalar.log(ad.scalar.add(ad.scalar.exp(ad.scalar.add(ad.scalar.mul(x, sigma), mu)), 1));
    },
    support: function () {
        return {
            lower: 0,
            upper: Infinity
        };
    }
});
module.exports = { IspNormal: IspNormal };