public T Generate()
{
for (int i = 0; i < _maxLoops; i++)
{
var sample = _sampler.Generate();
if (_accepter(sample))
{
return(sample);
}
}
throw new TimeoutException("The Monte Carlo sampler failed to pick a value within the prescribed number of iterations.");
}
public static IEnumerable <T> Generate <T>(this IDistribution <T> distribution, int count)
{
for (int i = 0; i < count; i++)
{
yield return(distribution.Generate());
}
}
public IParticleBehavior MakeBehavior()
{
double xScale = _xScale.Generate();
double yScale = _yScale?.Generate() ?? xScale;
return(new ScaleBehavior(xScale, yScale));
}
/// <summary>
/// y = phi_x * w + noise, noise ~ x
/// </summary>
public static double Generate(int nBasis, IEnumerable <double> w, IDistribution <double> noise, double x)
{
if (w.Count() != nBasis)
{
throw new ArgumentException();
}
// 1 * nBasis
var phiX = Core.Utils.PolynomialBasisLinearModelUtility.GetDesignMatrix(nBasis, x);
// nBasis * 1
var wm = new Matrix(w, false);
return((phiX * wm)[0, 0] + noise.Generate());
}
public IntVector Generate() => new IntVector(_first.Generate(), _second.Generate());
public static IDistribution <TOut> Transform <TIn, TOut>(this IDistribution <TIn> distribution, Func <TIn, TOut> transformer) => new FuncDistribution <TOut>(() => transformer(distribution.Generate()));