private ExpectationResult Expectation(
Corpus corpus,
LLNAModel llnaModel,
LLNASufficientStatistics llnaSufficientStatistics,
Matrix <double> corpusLambda,
Matrix <double> corpusNu,
Matrix <double> corpusPhiSum,
bool resetVar)
{
double avgNIter = 0, avgConverged = 0;
double total = 0;
for (int i = 0; i < corpus.NbDocuments; i++)
{
Debug.WriteLine($"Document {i}");
var doc = corpus.GetDocument(i);
var varInference = new VariationalInferenceParameter(doc.NbTerms, llnaModel.K);
if (resetVar)
{
varInference.Init(llnaModel);
}
else
{
varInference.Lambda = corpusLambda.Row(i);
varInference.Nu = corpusNu.Row(i);
varInference.OptimizeZeta(llnaModel);
varInference.OptimizePhi(llnaModel, doc);
varInference.NIter = 0;
}
var lHood = Inference(varInference, doc, llnaModel);
llnaSufficientStatistics.Update(varInference, doc);
total += lHood;
avgNIter += varInference.NIter;
if (varInference.Converged)
{
avgConverged++;
}
corpusLambda.SetRow(i, varInference.Lambda);
corpusNu.SetRow(i, varInference.Nu);
var phiSum = varInference.Phi.ColumnSum();
corpusPhiSum.SetRow(i, phiSum);
}
avgNIter = avgNIter / corpus.NbDocuments;
avgConverged = avgConverged / corpus.NbDocuments;
return(new ExpectationResult(avgNIter, avgConverged, total));
}
