static public QmrrPartialModel GetInstance(ModelLikelihoodFactories modelLikelihoodFactories,
string peptide,
Dictionary <string, double> patientToAnyReaction,
Set <Hla> knownHlaSet,
Dictionary <string, Set <Hla> > patientList,
OptimizationParameterList qmrrParamsStart
)
{
QmrrPartialModel aQmrrPartialModel = new QmrrPartialModel();
aQmrrPartialModel.QmrrParamsStart = qmrrParamsStart;
aQmrrPartialModel.Peptide = peptide;
aQmrrPartialModel.PatientToAnyReaction = patientToAnyReaction;
aQmrrPartialModel.PatientList = patientList;
aQmrrPartialModel.KnownHlaSet = knownHlaSet;
aQmrrPartialModel.CreateHlaList();
aQmrrPartialModel.CreateSwitchableHlasWithRespondingPatients();
aQmrrPartialModel.ModelLikelihoodFactories = modelLikelihoodFactories;
if (modelLikelihoodFactories != null)
{
aQmrrPartialModel.LogLikelihoodOfCompleteModelConditionedOnKnownHlas = modelLikelihoodFactories.PartialModelDelegateFactory(aQmrrPartialModel);
}
else
{
aQmrrPartialModel.LogLikelihoodOfCompleteModelConditionedOnKnownHlas = null;
}
return(aQmrrPartialModel);
}
private void ReportPerHla(OptimizationParameterList qmrrParams, Dictionary <string, BestSoFar <double, TrueCollection> > peptideToBestHlaAssignmentSoFar,
string directory, string name)
{
string fileName = string.Format(@"{0}\NoisyOr.PeptideHlaProbability.{1}.new.txt", directory, name);
using (StreamWriter output = File.CreateText(fileName))
{
output.WriteLine(SpecialFunctions.CreateTabString("Peptide", "HLA", "LogOdds", "Probability"));
foreach (QmrrPartialModel qmrrPartialModel in QmrrPartialModelCollection)
{
QmrrModelMissingAssignment aQmrrModelMissingAssignment = QmrrModelMissingAssignment.GetInstance(ModelLikelihoodFactories, qmrrPartialModel, qmrrParams);
BestSoFar <double, TrueCollection> bestHlaAssignment = peptideToBestHlaAssignmentSoFar[qmrrPartialModel.Peptide];
Set <Hla> trueCollectionFullAsSet = new Set <Hla>(bestHlaAssignment.Champ);
double loglikelihoodFull = bestHlaAssignment.ChampsScore;
foreach (Hla hla in trueCollectionFullAsSet)
{
bool known = qmrrPartialModel.KnownHlaSet.Contains(hla);
if (!known)
{
Set <Hla> allLessOne = trueCollectionFullAsSet.SubtractElement(hla);
TrueCollection trueCollectionWithout = TrueCollection.GetInstance(allLessOne);
double loglikelihoodWithout = aQmrrModelMissingAssignment.LogLikelihoodOfCompleteModelConditionedOnKnownHlas(trueCollectionWithout);
double logOdds = loglikelihoodFull - loglikelihoodWithout;
double probabilityFull = Math.Exp(loglikelihoodFull);
double probabilityWithout = Math.Exp(loglikelihoodWithout);
double probability = probabilityFull / (probabilityFull + probabilityWithout);
Debug.Assert(logOdds >= 0); // real assert
output.WriteLine(SpecialFunctions.CreateTabString(qmrrPartialModel.Peptide, hla, logOdds, probability));
}
}
}
}
}
internal OptimizationParameterList FindBestParams(OptimizationParameterList qmrrParamsStart, out double logLikelihood)
{
OptimizationParameterList qmrrParamsEnd = qmrrParamsStart.Clone();
logLikelihood = GridSearch.Optimize(ScoreParameterList, qmrrParamsEnd, 10, 10);
return(qmrrParamsEnd);
}
public static ModelLikelihoodFactories GetInstanceCoverage(OptimizationParameterList qmrrParamsStart, string dataset)
{
SpecialFunctions.CheckCondition(qmrrParamsStart.Count == 1);
SpecialFunctions.CheckCondition(qmrrParamsStart.ContainsKey("useKnownList"));
SpecialFunctions.CheckCondition(!qmrrParamsStart["useKnownList"].DoSearch);
SpecialFunctions.CheckCondition(qmrrParamsStart["useKnownList"].Value == 0.0 || qmrrParamsStart["useKnownList"].Value == 1.0);
Coverage aCoverage = new Coverage();
return(aCoverage);
}
public double ScoreParameterList(OptimizationParameterList parameterList)
{
double sum = 0.0;
foreach (QmrrlModelMissingParameters qmrrlModelMissingParameters in Collection)
{
double loglikelihood = qmrrlModelMissingParameters.LogLikelihoodOfCompleteModelConditionedOnKnownHlas(parameterList);
sum += loglikelihood;
}
return(sum);
}
internal void FindBestQmrrParams(QmrrPartialModelCollection qmrrPartialModelCollection)
{
SpecialFunctions.CheckCondition(false, "Regression test this to be sure that switch to new optimization method didn't change anything important - cmk 5/1/2006");
QmrrlModelMissingParametersCollection aQmrrlModelMissingParametersCollection =
QmrrlModelMissingParametersCollection.GetInstance(ModelLikelihoodFactories, qmrrPartialModelCollection, PeptideToBestHlaAssignmentSoFar);
double score;
OptimizationParameterList qmrrParamsEnd = aQmrrlModelMissingParametersCollection.FindBestParams(BestParamsSoFar.Champ, out score);
BestParamsSoFar.Compare(score, qmrrParamsEnd);
}
static public ModelLikelihoodFactories GetInstanceThreeParamSlow(OptimizationParameterList qmrrParams)
{
SpecialFunctions.CheckCondition(qmrrParams.Count == 4);
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey("causePrior"));
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey("link"));
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey("leakProbability"));
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey("useKnownList"));
SpecialFunctions.CheckCondition(!qmrrParams["useKnownList"].DoSearch);
SpecialFunctions.CheckCondition(qmrrParams["useKnownList"].Value == 0.0 || qmrrParams["useKnownList"].Value == 1.0);
ThreeParamSlow aThreeParamSlow = new ThreeParamSlow();
return(aThreeParamSlow);
}
static public ModelLikelihoodFactories GetInstanceTwoCausePriors(OptimizationParameterList qmrrParams, string dataset)
{
SpecialFunctions.CheckCondition(qmrrParams.Count == 5);
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey("causePrior"));
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey("fitFactor"));
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey("link"));
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey("leakProbability"));
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey("useKnownList"));
SpecialFunctions.CheckCondition(!qmrrParams["useKnownList"].DoSearch);
SpecialFunctions.CheckCondition(qmrrParams["useKnownList"].Value == 0.0 || qmrrParams["useKnownList"].Value == 1.0);
TwoCausePriors aTwoCausePriors = new TwoCausePriors();
aTwoCausePriors.SetPeptideToFitUniverse(dataset);
return(aTwoCausePriors);
}
static public double Optimize(FunctionToOptimizeDelegate functionToOptimize,
ref List <double> point, List <double> low, List <double> high,
OptimizationParameterList qmrrParamsStart, int numberOfIterationsOverParameters, double precision, int gridLineCount)
{
double eps = 1e-9;
//Debug.WriteLine(qmrrParamsStart.ToStringHeader());
double oldScore = double.NaN;
//Debug.WriteLine(SpecialFunctions.CreateTabString("iterationOverParameters", "iParameter", "Probability", "LogOdds", "Score"));
for (int iterationOverParameters = 0; iterationOverParameters < numberOfIterationsOverParameters; ++iterationOverParameters)
{
double newScore = double.NaN;
int doSearchParameterCount = 0;
for (int iParameter = 0; iParameter < point.Count; ++iParameter)
{
if (qmrrParamsStart.DoSearch(iParameter))
{
++doSearchParameterCount;
List <double> pointClone = new List <double>(point);
BestSoFar <double, double> bestParamSoFar =
OneDOptimization(
delegate(double parameter) { pointClone[iParameter] = parameter; return(functionToOptimize(pointClone)); },
low[iParameter], high[iParameter], precision, gridLineCount);
point[iParameter] = bestParamSoFar.Champ;
//Debug.WriteLine(SpecialFunctions.CreateTabString(iterationOverParameters, iParameter, SpecialFunctions.Probability(bestParamSoFar.Champ), bestParamSoFar.Champ, bestParamSoFar.ChampsScore));
newScore = bestParamSoFar.ChampsScore;
//Debug.WriteLine("END ITER:" + SpecialFunctions.CreateTabString2(point) + SpecialFunctions.CreateTabString("", newScore));
}
}
if ((!double.IsNaN(oldScore) && Math.Abs(oldScore - newScore) < eps) ||
doSearchParameterCount < 2) //If only 0 or 1 searchable params, then one pass is enough
{
oldScore = newScore;
break;
}
oldScore = newScore;
}
return(oldScore);
}
public bool Close(OptimizationParameterList other, double eps)
{
if (other == null)
{
return(false);
}
SpecialFunctions.CheckCondition(other.Count == Count);
for (int iParam = 0; iParam < Count; ++iParam)
{
if (!Close(AsParameterArray[iParam], other.AsParameterArray[iParam], eps))
{
return(false);
}
}
return(true);
}
internal static ModelLikelihoodFactories GetInstanceLinkPerHla(OptimizationParameterList qmrrParams, Set <Hla> candidateHlaSet)
{
SpecialFunctions.CheckCondition(qmrrParams.Count == 3 + candidateHlaSet.Count);
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey("causePrior"));
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey("leakProbability"));
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey("useKnownList"));
SpecialFunctions.CheckCondition(!qmrrParams["useKnownList"].DoSearch);
SpecialFunctions.CheckCondition(qmrrParams["useKnownList"].Value == 1.0);
foreach (Hla hla in candidateHlaSet)
{
string paramName = "link" + hla.ToString();
SpecialFunctions.CheckCondition(qmrrParams.ContainsKey(paramName));
}
LinkPerHla aLinkPerHla = new LinkPerHla();
return(aLinkPerHla);
}
public static OptimizationParameterList GetInstance2(IEnumerable <OptimizationParameter> parameterCollection)
{
OptimizationParameterList aQmrrParams = new OptimizationParameterList();
aQmrrParams.AsSortedDictionary = new SortedDictionary <string, OptimizationParameter>();
foreach (OptimizationParameter parameter in parameterCollection)
{
aQmrrParams.AsSortedDictionary.Add(parameter.Name, parameter);
}
//Must do this after because the parameters may get re-ordered.
aQmrrParams.AsParameterArray = new OptimizationParameter[aQmrrParams.AsSortedDictionary.Count];
int iParam = -1;
foreach (OptimizationParameter parameter in aQmrrParams.AsSortedDictionary.Values)
{
++iParam;
aQmrrParams.AsParameterArray[iParam] = parameter;
}
return(aQmrrParams);
}
public static QmrrPartialModelCollection GetInstance(string peptide,
ModelLikelihoodFactories modelLikelihoodFactories,
OptimizationParameterList qmrrParamsStart,
Dictionary <string, Set <Hla> > patientList,
Dictionary <string, Dictionary <string, double> > reactTable,
Dictionary <string, Set <Hla> > knownTable,
string hlaFactoryName
)
{
QmrrPartialModelCollection aQmrrPartialModelCollection = new QmrrPartialModelCollection();
aQmrrPartialModelCollection.HlaFactory = Qmrr.HlaFactory.GetFactory(hlaFactoryName);
aQmrrPartialModelCollection.OptimizationParameterList = qmrrParamsStart;
aQmrrPartialModelCollection.SetFileNamesToNull();
aQmrrPartialModelCollection.PeptideList = new List <string>(new string[] { peptide });
aQmrrPartialModelCollection.PatientList = patientList;
aQmrrPartialModelCollection.ReactTable = reactTable;
aQmrrPartialModelCollection._knownTable = knownTable;
aQmrrPartialModelCollection.ModelLikelihoodFactories = modelLikelihoodFactories;
aQmrrPartialModelCollection.CreateList();
return(aQmrrPartialModelCollection);
}
private void SearchForBestParamsAndHlaAssignments(QmrrPartialModelCollection qmrrPartialModelCollection, double depth)
{
int cStep = 100;
double eps = 1e-7;
OptimizationParameterList oldQmrrParams = null;
Debug.WriteLine(SpecialFunctions.CreateTabString("depth", "dataset", QmrrParamsStart.ToStringHeader(), "Step", "After", QmrrParamsStart.ToStringHeader(), "Score"));
for (int iStep = 0; iStep < cStep && !(BestParamsSoFar.Champ.IsClose(oldQmrrParams, eps)); ++iStep)
{
oldQmrrParams = BestParamsSoFar.Champ.Clone();
double hlaAssignmentSumScore = FindBestHlaAssignmentSet(qmrrPartialModelCollection, depth);
Debug.WriteLine(SpecialFunctions.CreateTabString(depth, qmrrPartialModelCollection.DatasetName,
QmrrParamsStart, iStep + 1, "AfterHla", BestParamsSoFar.Champ,
hlaAssignmentSumScore));
FindBestQmrrParams(qmrrPartialModelCollection);
Debug.WriteLine(SpecialFunctions.CreateTabString(depth, qmrrPartialModelCollection.DatasetName,
QmrrParamsStart, iStep + 1, "AfterParam", BestParamsSoFar.Champ, BestParamsSoFar.ChampsScore));
}
}
protected QmmrModelOnePeptide QmmrModelOnePeptideGetInstance(QmrrPartialModel qmrrPartialModel, OptimizationParameterList qmrrParams, double depth)
{
QmmrModelOnePeptide aQmmrModelOnePeptide = new QmmrModelOnePeptide();
aQmmrModelOnePeptide.QmrrModelMissingAssignment = QmrrModelMissingAssignment.GetInstance(ModelLikelihoodFactories, qmrrPartialModel, qmrrParams);
aQmmrModelOnePeptide.CreateNoSwitchablesHlaAssignment();
if (depth == 0)
{
// do nothing
}
else if (depth == Math.Floor(depth))
{
SpecialFunctions.CheckCondition(depth > 0);
aQmmrModelOnePeptide.SetForDepthSearch((int)Math.Floor(depth));
}
else
{
SpecialFunctions.CheckCondition(depth == 1.5);
aQmmrModelOnePeptide.SetForBitFlipsAnd1Replacement();
}
return(aQmmrModelOnePeptide);
}
override protected double LogLikelihoodOfEffects(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection, OptimizationParameterList qmrrParams)
{
Set <Hla> trueCollectionAsSet = trueCollection.CreateHlaAssignmentAsSet();
double logOneLessLeakProbability = Math.Log(1.0 - qmrrParams["leakProbability"].Value);
Dictionary <Hla, double> hlaToLogOneLessLink = new Dictionary <Hla, double>();
foreach (Hla hla in trueCollectionAsSet)
{
double logOneLessLink = Math.Log(1.0 - qmrrParams["link" + hla].Value);
hlaToLogOneLessLink.Add(hla, logOneLessLink);
}
double logLikelihood = 0.0;
foreach (KeyValuePair <string, Set <Hla> > patientAndHlaList in qmrrPartialModel.PatientList)
{
double logLikelihoodNoReactionInThisPatient = logOneLessLeakProbability;
foreach (Hla hla in patientAndHlaList.Value)
{
if (trueCollectionAsSet.Contains(hla))
{
double logOneLessLink = hlaToLogOneLessLink[hla];
logLikelihoodNoReactionInThisPatient += logOneLessLink;
}
}
bool didReact = qmrrPartialModel.PatientToAnyReaction.ContainsKey(patientAndHlaList.Key);
logLikelihood += LogLikelihoodOfThisPatient(logLikelihoodNoReactionInThisPatient, didReact);
}
return(logLikelihood);
}
virtual protected double LogLikelihoodOfEffects(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection, OptimizationParameterList qmrrParams)
{
double logOneLessLink = Math.Log(1.0 - qmrrParams["link"].Value);
double logOneLessLeakProbability = Math.Log(1.0 - qmrrParams["leakProbability"].Value);
double logLikelihood = 0.0;
Set <Hla> trueCollectionAsSet = trueCollection.CreateHlaAssignmentAsSet();
foreach (KeyValuePair <string, Set <Hla> > patientAndHlaList in qmrrPartialModel.PatientList)
{
double logLikelihoodNoReactionInThisPatient =
logOneLessLeakProbability
+ NumberOfPositiveHlas(patientAndHlaList.Value, trueCollectionAsSet) * logOneLessLink;
bool didReact = qmrrPartialModel.PatientToAnyReaction.ContainsKey(patientAndHlaList.Key);
logLikelihood += LogLikelihoodOfThisPatient(logLikelihoodNoReactionInThisPatient, didReact);
}
return(logLikelihood);
}
virtual protected double LogLikelihoodOfCausesConditionedOnKnownHlas(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection, OptimizationParameterList qmrrParams)
{
double logCausePrior = Math.Log(qmrrParams["causePrior"].Value);
double logOneLessCausePrior = Math.Log(1.0 - qmrrParams["causePrior"].Value);
int trueCountLessKnown = trueCollection.Count - qmrrPartialModel.KnownHlaSet.Count;
Debug.Assert(trueCountLessKnown >= 0); // real assert
int falseCount = qmrrPartialModel.HlaList.Count - trueCollection.Count;
double logLikelihood =
(double)trueCountLessKnown * logCausePrior
+ (double)falseCount * logOneLessCausePrior;
return(logLikelihood);
}
virtual protected double LogLikelihoodOfCompleteModelConditionedOnKnownHlas(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection, OptimizationParameterList qmrrParams)
{
double logLikelihood =
LogLikelihoodOfCausesConditionedOnKnownHlas(qmrrPartialModel, trueCollection, qmrrParams)
+ LogLikelihoodOfEffects(qmrrPartialModel, trueCollection, qmrrParams);
return(logLikelihood);
}
public static QmrrModelAllPeptides GetInstance(ModelLikelihoodFactories modelLikelihoodFactories, string datasetName, OptimizationParameterList qmrrParamsStart, double depth, string hlaFactoryName)
{
QmrrModelAllPeptides aQmrrModelAllPeptides = new QmrrModelAllPeptides();
aQmrrModelAllPeptides.QmrrPartialModelCollection = QmrrPartialModelCollection.GetInstance(modelLikelihoodFactories, datasetName, qmrrParamsStart, hlaFactoryName);
aQmrrModelAllPeptides.BestParamsAndHlaAssignments = BestParamsAndHlaAssignments.GetInstance(modelLikelihoodFactories, qmrrParamsStart, aQmrrModelAllPeptides.QmrrPartialModelCollection, depth);
aQmrrModelAllPeptides.ModelLikelihoodFactories = modelLikelihoodFactories;
return(aQmrrModelAllPeptides);
}
protected override double LogLikelihoodOfCausesConditionedOnKnownHlas(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection, OptimizationParameterList qmrrParams)
{
//!!!This could be calculated during the construction of qmrrPartialModel
Set <Hla> fitUniverse = SpecialFunctions.GetValueOrDefault(PeptideToFitUniverse, qmrrPartialModel.Peptide);
//Compute with priors
double unfitCausePrior = qmrrParams["causePrior"].Value;
double fitFactor = qmrrParams["fitFactor"].Value;
double fitCausePrior = unfitCausePrior * fitFactor;
double logUnfitCausePrior = Math.Log(unfitCausePrior);
double logOneLessUnfitCausePrior = Math.Log(1.0 - unfitCausePrior);
double logFitCausePrior = Math.Log(fitCausePrior);
double logOneLessFitCausePrior = Math.Log(1.0 - fitCausePrior);
//Tabulate counts
int unfitTotalCount = qmrrPartialModel.HlaList.Count - fitUniverse.Count;
int trueCountLessKnown = trueCollection.Count - qmrrPartialModel.KnownHlaSet.Count;
int falseCount = qmrrPartialModel.HlaList.Count - trueCollection.Count;
int knownFitCount = KnownFitCount(fitUniverse, qmrrPartialModel.KnownHlaSet); //!!!could be pretabulated
int knownUnfitCount = qmrrPartialModel.KnownHlaSet.Count - knownFitCount;
int fitTrueCountLessKnown = FitTrueCount(fitUniverse, trueCollection) - knownFitCount;
int unfitTrueCountLessKnown = trueCountLessKnown - fitTrueCountLessKnown;
int fitFalseCount = fitUniverse.Count - fitTrueCountLessKnown - knownFitCount;
int unfitFalseCount = unfitTotalCount - unfitTrueCountLessKnown - knownUnfitCount;
//Compute logLikelihood
double logLikelihood =
(double)unfitTrueCountLessKnown * logUnfitCausePrior
+ (double)unfitFalseCount * logOneLessUnfitCausePrior
+ (double)fitTrueCountLessKnown * logFitCausePrior
+ (double)fitFalseCount * logOneLessFitCausePrior;
return(logLikelihood);
}
//private BestParamsAndHlaAssignments(OptimizationParameterList qmrrParamsStart)
//{
// QmrrParamsStart = qmrrParamsStart;
// CreateBestParamsSoFar();
// PeptideToBestHlaAssignmentSoFar = null;
//}
public static BestParamsAndHlaAssignments GetInstance(ModelLikelihoodFactories modelLikelihoodFactories, OptimizationParameterList qmrrParamsStart, QmrrPartialModelCollection qmrrPartialModelCollection, double depth)
{
BestParamsAndHlaAssignments aBestParamsAndHlaAssignments = new BestParamsAndHlaAssignments();
aBestParamsAndHlaAssignments.QmrrParamsStart = qmrrParamsStart;
aBestParamsAndHlaAssignments.CreateBestParamsSoFar();
aBestParamsAndHlaAssignments.ModelLikelihoodFactories = modelLikelihoodFactories;
aBestParamsAndHlaAssignments.SearchForBestParamsAndHlaAssignments(qmrrPartialModelCollection, depth);
return(aBestParamsAndHlaAssignments);
}
public static QmrrModelMissingAssignment GetInstance(ModelLikelihoodFactories modelLikelihoodFactories, QmrrPartialModel qmrrPartialModel, OptimizationParameterList qmrrParams)
{
QmrrModelMissingAssignment aQmrrModelMissingAssignment = new QmrrModelMissingAssignment();
aQmrrModelMissingAssignment.QmrrPartialModel = qmrrPartialModel;
aQmrrModelMissingAssignment.OptimizationParameterList = qmrrParams;
aQmrrModelMissingAssignment.KnownHlaSet = qmrrPartialModel.KnownHlaSet;
aQmrrModelMissingAssignment.SwitchableHlasOfRespondingPatients = qmrrPartialModel.SwitchableHlasOfRespondingPatients;
aQmrrModelMissingAssignment.ModelLikelihoodFactories = modelLikelihoodFactories;
aQmrrModelMissingAssignment.LogLikelihoodOfCompleteModelConditionedOnKnownHlas = modelLikelihoodFactories.MissingAssignmentDelegateFactory(qmrrPartialModel, qmrrParams);
return(aQmrrModelMissingAssignment);
//SetOfAllHlasCount = qmrrPartialModel.HlaList.Count;
}
virtual public MissingAssignmentDelegate MissingAssignmentDelegateFactory(QmrrPartialModel qmrrPartialModel, OptimizationParameterList qmrrParams)
{
PartialModelDelegate LogLikelihoodOfCompleteModelConditionedOnKnownHlas = PartialModelDelegateFactory(qmrrPartialModel);
return(delegate(TrueCollection trueCollection)
{
return LogLikelihoodOfCompleteModelConditionedOnKnownHlas(trueCollection, qmrrParams);
});
}
private double LogLikelihoodOfCompleteModelConditionedOnKnownHlas(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection, OptimizationParameterList qmrrParams)
{
Set <Hla> trueHlaSet = trueCollection.CreateHlaAssignmentAsSet();
int reactionsCoveredCount = CountReactionsCovered(qmrrPartialModel, trueHlaSet);
SpecialFunctions.CheckCondition(reactionsCoveredCount < 1000);
int trueCount = trueCollection.Count;
SpecialFunctions.CheckCondition(trueCount < 1000);
int falseCount = qmrrPartialModel.HlaList.Count - trueCollection.Count;
SpecialFunctions.CheckCondition(falseCount < 1000);
string llAsString = string.Format("{0:000}.{1:000}{2:000}", reactionsCoveredCount, falseCount, trueCount);
double logLikelihood = double.Parse(llAsString);
return(logLikelihood);
}
static public QmrrPartialModelCollection GetInstance(ModelLikelihoodFactories modelLikelihoodFactories, string datasetName, OptimizationParameterList qmrrParams, string hlaFactoryName)
{
QmrrPartialModelCollection aQmrrPartialModelCollection = new QmrrPartialModelCollection();
aQmrrPartialModelCollection.HlaFactory = Qmrr.HlaFactory.GetFactory(hlaFactoryName);
aQmrrPartialModelCollection.OptimizationParameterList = qmrrParams;
aQmrrPartialModelCollection.SetFileNames(datasetName);
aQmrrPartialModelCollection.ReadTables();
aQmrrPartialModelCollection.ModelLikelihoodFactories = modelLikelihoodFactories;
aQmrrPartialModelCollection.CreateList();
return(aQmrrPartialModelCollection);
}