public TruncatedDistribution(ITruncatableDistribution <double> distribution, double lowerBound, double upperBound)
{
if (lowerBound > upperBound)
{
throw new ArgumentOutOfRangeException($"lowerBound ({lowerBound}) > upperBound ({upperBound})");
}
this.Distribution = distribution;
this.LowerBound = lowerBound;
this.UpperBound = upperBound;
this.TotalProbability = distribution.GetProbBetween(lowerBound, upperBound);
this.LowerProbability = distribution.GetProbLessThan(lowerBound);
}
/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="IntegralOp"]/message_doc[@name="UpperBoundAverageConditional(Gaussian, Gaussian, Func{double,double}, ITruncatableDistribution{double})"]/*'/>
public static Gaussian UpperBoundAverageConditional(Gaussian integral, [RequiredArgument] Gaussian upperBound, Func <double, double> func, ITruncatableDistribution <double> distribution)
{
if (upperBound.IsPointMass)
{
return(UpperBoundAverageConditional(integral, upperBound.Point, func, distribution));
}
else
{
throw new NotSupportedException();
}
}
/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="IntegralOp"]/message_doc[@name="UpperBoundAverageConditional(Gaussian, double, Func{double,double}, ITruncatableDistribution{double})"]/*'/>
public static Gaussian UpperBoundAverageConditional(Gaussian integral, double upperBound, Func <double, double> func, ITruncatableDistribution <double> distribution)
{
CanGetLogProb <double> canGetLogProb = (CanGetLogProb <double>)distribution;
double dlogf = integral.MeanTimesPrecision * func(upperBound) * Math.Exp(canGetLogProb.GetLogProb(upperBound));
double ddlogf = 0; // approximation ignoring integral.Precision
return(Gaussian.FromDerivatives(upperBound, dlogf, ddlogf, false));
}
/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="IntegralOp"]/message_doc[@name="IntegralAverageConditional(Gaussian, Gaussian, Func{double,double}, ITruncatableDistribution{double})"]/*'/>
public static Gaussian IntegralAverageConditional([RequiredArgument] Gaussian lowerBound, [RequiredArgument] Gaussian upperBound, Func <double, double> func, ITruncatableDistribution <double> distribution)
{
if (lowerBound.IsPointMass && upperBound.IsPointMass)
{
return(Gaussian.PointMass(Factor.Integral(lowerBound.Point, upperBound.Point, func, distribution)));
}
else
{
throw new NotSupportedException();
}
}
/// <summary>
/// Returns the integral from lowerBound to upperBound of func(x) times p(x).
/// </summary>
public static double Integral(double lowerBound, double upperBound, Func <double, double> func, ITruncatableDistribution <double> distribution)
{
var dist = new TruncatedDistribution(distribution, lowerBound, upperBound);
// To approximate the average, we divide the region into intervals of equal probability.
// We compute the function at the midpoint of each interval, and take an unweighted average.
// The quantile ranks of the midpoints are 0.5/count, 1.5/count, ..., (count-0.5)/count
const int count = 100;
double increment = 1.0 / count;
double start = increment / 2;
double sum = 0;
for (int i = 0; i < count; i++)
{
double quantileRank = start + i * increment;
double input = dist.GetQuantile(quantileRank);
sum += func(input);
}
return(sum * increment * distribution.GetProbBetween(lowerBound, upperBound));
}
