/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="BetaOp"]/message_doc[@name="MeanAverageLogarithm(Beta, Beta, Gamma, Beta)"]/*'/>
public static Beta MeanAverageLogarithm([Proper] Beta prob, Beta mean, [Proper] Gamma totalCount, Beta to_mean)
{
// Calculate gradient using method for DirichletOp
double ELogP, ELogOneMinusP;
prob.GetMeanLogs(out ELogP, out ELogOneMinusP);
Vector gradS = DirichletOp.CalculateGradientForMean(
Vector.FromArray(new double[] { mean.TrueCount, mean.FalseCount }),
totalCount,
Vector.FromArray(new double[] { ELogP, ELogOneMinusP }));
// Project onto a Beta distribution
Matrix A = new Matrix(2, 2);
double c = MMath.Trigamma(mean.TotalCount);
A[0, 0] = MMath.Trigamma(mean.TrueCount) - c;
A[1, 0] = A[0, 1] = -c;
A[1, 1] = MMath.Trigamma(mean.FalseCount) - c;
Vector theta = GammaFromShapeAndRateOp.twoByTwoInverse(A) * gradS;
Beta approximateFactor = new Beta(theta[0] + 1, theta[1] + 1);
if (damping == 0.0)
{
return(approximateFactor);
}
else
{
return((approximateFactor ^ (1 - damping)) * (to_mean ^ damping));
}
}
/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="BetaFromMeanAndTotalCountOp"]/message_doc[@name="TotalCountAverageLogarithm(Beta, Gamma, Beta, Gamma)"]/*'/>
public static Gamma TotalCountAverageLogarithm([Proper] Beta mean, Gamma totalCount, [SkipIfUniform] Beta prob, Gamma to_totalCount)
{
prob.GetMeanLogs(out double ELogP, out double ELogOneMinusP);
Gamma approximateFactor = DirichletOp.TotalCountAverageLogarithmHelper(
Vector.FromArray(new double[] { mean.TrueCount, mean.FalseCount }),
totalCount,
Vector.FromArray(new double[] { ELogP, ELogOneMinusP }));
if (damping == 0.0)
{
return(approximateFactor);
}
else
{
return((approximateFactor ^ (1 - damping)) * (to_totalCount ^ damping));
}
}
public void DirichletOpQuadratureTest()
{
var matlabResults
= new double[]
{
0.625872049875551,
0.866057568760984,
-0.266065360660541,
-1.227320719860393,
1.280900246404125
};
var matlabResults2
= new double[]
{
0.843302107208523,
0.610546297106219,
-2.182481855300747,
-0.254011377373013,
-0.217430057568389
};
double am = 2;
double bm = 1;
double at = 3;
double bt = 1;
Dirichlet meanQ = new Dirichlet(new double[] { am, bm });
Gamma totalCountQ = new Gamma(at, 1 / bt);
double[] EELogGamma;
double[] EELogMLogGamma;
double[] EELogOneMinusMLogGamma;
double[] EELogSLogGamma;
double[] EEMSDigamma;
DirichletOp.MeanMessageExpectations(
meanQ.PseudoCount,
totalCountQ,
out EELogGamma,
out EELogMLogGamma,
out EELogOneMinusMLogGamma);
Console.WriteLine(System.Math.Abs(EELogGamma[0] - matlabResults[0]));
Console.WriteLine(System.Math.Abs(EELogMLogGamma[0] - matlabResults[2]));
Console.WriteLine(System.Math.Abs(EELogOneMinusMLogGamma[0] - matlabResults[3]));
Console.WriteLine(System.Math.Abs(EELogGamma[1] - matlabResults2[0]));
Console.WriteLine(System.Math.Abs(EELogMLogGamma[1] - matlabResults2[2]));
Console.WriteLine(System.Math.Abs(EELogOneMinusMLogGamma[1] - matlabResults2[3]));
DirichletOp.TotalCountMessageExpectations(
meanQ.PseudoCount,
totalCountQ,
out EELogGamma,
out EELogSLogGamma,
out EEMSDigamma);
Console.WriteLine(System.Math.Abs(EELogGamma[0] - matlabResults[0]));
Console.WriteLine(System.Math.Abs(EELogSLogGamma[0] - matlabResults[1]));
Console.WriteLine(System.Math.Abs(EEMSDigamma[0] - matlabResults[4]));
Console.WriteLine(System.Math.Abs(EELogGamma[1] - matlabResults2[0]));
Console.WriteLine(System.Math.Abs(EELogSLogGamma[1] - matlabResults2[1]));
Console.WriteLine(System.Math.Abs(EEMSDigamma[1] - matlabResults2[4]));
}
