//
// Math.NET Numerics, part of the Math.NET Project
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// http://github.com/mathnet/mathnet-numerics
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using System;
using System.Linq;
using IStation.Numerics.Distributions;
using IStation.Numerics.Random;
namespace IStation.Numerics.Statistics.Mcmc
{
///
/// A hybrid Monte Carlo sampler for multivariate distributions.
///
public class HybridMC : HybridMCGeneric
{
///
/// Number of parameters in the density function.
///
private readonly int _length;
///
/// Distribution to sample momentum from.
///
private Normal _pDistribution;
///
/// Standard deviations used in the sampling of different components of the
/// momentum.
///
private double[] _mpSdv;
///
/// Gets or sets the standard deviations used in the sampling of different components of the
/// momentum.
///
/// When the length of pSdv is not the same as Length.
public double[] MomentumStdDev
{
get => (double[])_mpSdv.Clone();
set
{
CheckVariance(value);
_mpSdv = (double[])value.Clone();
}
}
///
/// Constructs a new Hybrid Monte Carlo sampler for a multivariate probability distribution.
/// The components of the momentum will be sampled from a normal distribution with standard deviation
/// 1 using the default random
/// number generator. A three point estimation will be used for differentiation.
/// This constructor will set the burn interval.
///
/// The initial sample.
/// The log density of the distribution we want to sample from.
/// Number frog leap simulation steps.
/// Size of the frog leap simulation steps.
/// The number of iterations in between returning samples.
/// When the number of burnInterval iteration is negative.
public HybridMC(double[] x0, DensityLn pdfLnP, int frogLeapSteps, double stepSize, int burnInterval = 0)
: this(x0, pdfLnP, frogLeapSteps, stepSize, burnInterval, new double[x0.Length], SystemRandomSource.Default, Grad)
{
for (int i = 0; i < _length; i++)
{
_mpSdv[i] = 1;
}
}
///
/// Constructs a new Hybrid Monte Carlo sampler for a multivariate probability distribution.
/// The components of the momentum will be sampled from a normal distribution with standard deviation
/// specified by pSdv using the default random
/// number generator. A three point estimation will be used for differentiation.
/// This constructor will set the burn interval.
///
/// The initial sample.
/// The log density of the distribution we want to sample from.
/// Number frog leap simulation steps.
/// Size of the frog leap simulation steps.
/// The number of iterations in between returning samples.
/// The standard deviations of the normal distributions that are used to sample
/// the components of the momentum.
/// When the number of burnInterval iteration is negative.
public HybridMC(double[] x0, DensityLn pdfLnP, int frogLeapSteps, double stepSize, int burnInterval, double[] pSdv)
: this(x0, pdfLnP, frogLeapSteps, stepSize, burnInterval, pSdv, SystemRandomSource.Default)
{
}
///
/// Constructs a new Hybrid Monte Carlo sampler for a multivariate probability distribution.
/// The components of the momentum will be sampled from a normal distribution with standard deviation
/// specified by pSdv using the a random number generator provided by the user.
/// A three point estimation will be used for differentiation.
/// This constructor will set the burn interval.
///
/// The initial sample.
/// The log density of the distribution we want to sample from.
/// Number frog leap simulation steps.
/// Size of the frog leap simulation steps.
/// The number of iterations in between returning samples.
/// The standard deviations of the normal distributions that are used to sample
/// the components of the momentum.
/// Random number generator used for sampling the momentum.
/// When the number of burnInterval iteration is negative.
public HybridMC(double[] x0, DensityLn pdfLnP, int frogLeapSteps, double stepSize, int burnInterval, double[] pSdv, System.Random randomSource)
: this(x0, pdfLnP, frogLeapSteps, stepSize, burnInterval, pSdv, randomSource, Grad)
{
}
///
/// Constructs a new Hybrid Monte Carlo sampler for a multivariate probability distribution.
/// The components of the momentum will be sampled from a normal distribution with standard deviations
/// given by pSdv. This constructor will set the burn interval, the method used for
/// numerical differentiation and the random number generator.
///
/// The initial sample.
/// The log density of the distribution we want to sample from.
/// Number frog leap simulation steps.
/// Size of the frog leap simulation steps.
/// The number of iterations in between returning samples.
/// The standard deviations of the normal distributions that are used to sample
/// the components of the momentum.
/// Random number generator used for sampling the momentum.
/// The method used for numerical differentiation.
/// When the number of burnInterval iteration is negative.
/// When the length of pSdv is not the same as x0.
public HybridMC(double[] x0, DensityLn pdfLnP, int frogLeapSteps, double stepSize, int burnInterval, double[] pSdv, System.Random randomSource, DiffMethod diff)
: base(x0, pdfLnP, frogLeapSteps, stepSize, burnInterval, randomSource, diff)
{
_length = x0.Length;
MomentumStdDev = pSdv;
Initialize(x0);
Burn(BurnInterval);
}
///
/// Initialize parameters.
///
/// The current location of the sampler.
private void Initialize(double[] x0)
{
Current = (double[])x0.Clone();
_pDistribution = new Normal(0.0, 1.0, RandomSource);
}
///
/// Checking that the location and the momentum are of the same dimension and that each component is positive.
///
/// The standard deviations used for sampling the momentum.
/// When the length of pSdv is not the same as Length or if any
/// component is negative.
/// When pSdv is null.
private void CheckVariance(double[] pSdv)
{
if (pSdv == null)
{
throw new ArgumentNullException(nameof(pSdv), "Standard deviation cannot be null.");
}
if (pSdv.Length != _length)
{
throw new ArgumentOutOfRangeException(nameof(pSdv), "Standard deviation of momentum must have same length as sample.");
}
if (pSdv.Any(sdv => sdv < 0))
{
throw new ArgumentOutOfRangeException(nameof(pSdv), "Standard deviation must be positive.");
}
}
///
/// Use for copying objects in the Burn method.
///
/// The source of copying.
/// A copy of the source object.
protected override double[] Copy(double[] source)
{
var destination = new double[_length];
Array.Copy(source, 0, destination, 0, _length);
return destination;
}
///
/// Use for creating temporary objects in the Burn method.
///
/// An object of type T.
protected override double[] Create()
{
return new double[_length];
}
///
protected override void DoAdd(ref double[] first, double factor, double[] second)
{
for (int i = 0; i < _length; i++)
{
first[i] += factor * second[i];
}
}
///
protected override void DoSubtract(ref double[] first, double factor, double[] second)
{
for (int i = 0; i < _length; i++)
{
first[i] -= factor * second[i];
}
}
///
protected override double DoProduct(double[] first, double[] second)
{
double prod = 0;
for (int i = 0; i < _length; i++)
{
prod += first[i] * second[i];
}
return prod;
}
///
/// Samples the momentum from a normal distribution.
///
/// The momentum to be randomized.
protected override void RandomizeMomentum(ref double[] p)
{
for (int j = 0; j < _length; j++)
{
p[j] = _mpSdv[j] * _pDistribution.Sample();
}
}
///
/// The default method used for computing the gradient. Uses a simple three point estimation.
///
/// Function which the gradient is to be evaluated.
/// The location where the gradient is to be evaluated.
/// The gradient of the function at the point x.
static double[] Grad(DensityLn function, double[] x)
{
int length = x.Length;
var returnValue = new double[length];
var increment = new double[length];
var decrement = new double[length];
Array.Copy(x, 0, increment, 0, length);
Array.Copy(x, 0, decrement, 0, length);
for (int i = 0; i < length; i++)
{
double y = x[i];
double h = Math.Max(10e-4, (10e-7) * y);
increment[i] += h;
decrement[i] -= h;
returnValue[i] = (function(increment) - function(decrement)) / (2 * h);
increment[i] = y;
decrement[i] = y;
}
return returnValue;
}
}
}