// <copyright file="MetropolisSampler.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://numerics.mathdotnet.com
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// http://github.com/mathnet/mathnet-numerics
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//
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// Copyright (c) 2009-2010 Math.NET
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//
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
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// Software is furnished to do so, subject to the following
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// conditions:
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// </copyright>
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using System;
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using IStation.Numerics.Distributions;
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namespace IStation.Numerics.Statistics.Mcmc
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{
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/// <summary>
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/// Metropolis sampling produces samples from distribution P by sampling from a proposal distribution Q
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/// and accepting/rejecting based on the density of P. Metropolis sampling requires that the proposal
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/// distribution Q is symmetric. All densities are required to be in log space.
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///
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/// The Metropolis sampler is a stateful sampler. It keeps track of where it currently is in the domain
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/// of the distribution P.
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/// </summary>
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/// <typeparam name="T">The type of samples this sampler produces.</typeparam>
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public class MetropolisSampler<T> : McmcSampler<T>
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{
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/// <summary>
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/// Evaluates the log density function of the sampling distribution.
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/// </summary>
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private readonly DensityLn<T> _pdfLnP;
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/// <summary>
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/// A function which samples from a proposal distribution.
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/// </summary>
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private readonly LocalProposalSampler<T> _proposal;
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/// <summary>
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/// The current location of the sampler.
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/// </summary>
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private T _current;
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/// <summary>
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/// The log density at the current location.
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/// </summary>
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private double _currentDensityLn;
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/// <summary>
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/// The number of burn iterations between two samples.
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/// </summary>
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private int _burnInterval;
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/// <summary>
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/// Constructs a new Metropolis sampler using the default <see cref="System.Random"/> random number generator.
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/// </summary>
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/// <param name="x0">The initial sample.</param>
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/// <param name="pdfLnP">The log density of the distribution we want to sample from.</param>
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/// <param name="proposal">A method that samples from the symmetric proposal distribution.</param>
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/// <param name="burnInterval">The number of iterations in between returning samples.</param>
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/// <exception cref="ArgumentOutOfRangeException">When the number of burnInterval iteration is negative.</exception>
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public MetropolisSampler(T x0, DensityLn<T> pdfLnP, LocalProposalSampler<T> proposal, int burnInterval = 0)
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{
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_current = x0;
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_currentDensityLn = pdfLnP(x0);
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_pdfLnP = pdfLnP;
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_proposal = proposal;
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BurnInterval = burnInterval;
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Burn(BurnInterval);
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}
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/// <summary>
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/// Gets or sets the number of iterations in between returning samples.
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/// </summary>
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/// <exception cref="ArgumentOutOfRangeException">When burn interval is negative.</exception>
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public int BurnInterval
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{
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get => _burnInterval;
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set
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{
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if (value < 0)
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{
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throw new ArgumentException("Value must not be negative (zero is ok).");
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}
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_burnInterval = value;
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}
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}
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/// <summary>
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/// This method runs the sampler for a number of iterations without returning a sample
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/// </summary>
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private void Burn(int n)
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{
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for (int i = 0; i < n; i++)
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{
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// Get a sample from the proposal.
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T next = _proposal(_current);
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// Evaluate the density at the next sample.
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double p = _pdfLnP(next);
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Samples++;
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double acc = Math.Min(0.0, p - _currentDensityLn);
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if (acc == 0.0)
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{
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_current = next;
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_currentDensityLn = p;
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Accepts++;
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}
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else if (Bernoulli.Sample(RandomSource, Math.Exp(acc)) == 1)
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{
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_current = next;
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_currentDensityLn = p;
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Accepts++;
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}
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}
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}
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/// <summary>
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/// Returns a sample from the distribution P.
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/// </summary>
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public override T Sample()
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{
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Burn(BurnInterval + 1);
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return _current;
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}
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}
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}
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