private BestSoFar <double, double> OneDOptimizationInternal(Converter <double, double> oneDRealFunction,
double logOddsLow, double logOddsHigh, double logOddsPrecision)
{
int gridLineCount = 10;
double logOddsRangeIncrement = (logOddsHigh - logOddsLow) / (double)gridLineCount;
BestSoFar <double, double> bestParameterSoFar = BestSoFar <double, double> .GetInstance(SpecialFunctions.DoubleGreaterThan);
Debug.WriteLine(SpecialFunctions.CreateTabString("parameter", "parameterLogOdds", "score"));
for (int gridLine = 0; gridLine <= gridLineCount; ++gridLine)
{
double parameterLogOdds = logOddsLow + gridLine * logOddsRangeIncrement;
double parameter = SpecialFunctions.Probability(parameterLogOdds);
double score = oneDRealFunction(parameter);
Debug.WriteLine(SpecialFunctions.CreateTabString(parameter, parameterLogOdds, score));
bestParameterSoFar.Compare(score, parameterLogOdds);
}
Debug.WriteLine("");
if (logOddsHigh - logOddsLow < logOddsPrecision)
{
return(bestParameterSoFar);
}
return(OneDOptimizationInternal(oneDRealFunction, bestParameterSoFar.Champ - logOddsRangeIncrement, bestParameterSoFar.Champ + logOddsRangeIncrement, logOddsPrecision));
}
//private BestSoFar<double, double> OneDOptimizationInternal(oneDRealFunctionDelegate oneDRealFunction,
// double start, double increment, int gridStart, int gridLines)
//{
// BestSoFar<double, double> bestParameterSoFar = BestSoFar<double, double>.GetInstance(delegate(double champScore, double challengerScore) { return challengerScore > champScore; });
// for(int gridLine = gridStart; gridLine < gridLines; ++gridLine)
// {
// double parameter = start + gridLine * increment;
// double score = oneDRealFunction(parameter);
// bestParameterSoFar.Compare(score, parameter);
// }
// if (Math.Abs(bestParameterSoFar.Champ - increment) < increment * .1)
// {
// return OneDOptimizationInternal(oneDRealFunction, 0.0, increment * .1, 1, 9);
// }
// else if (Math.Abs((1.0 - bestParameterSoFar.Champ) - increment) < increment * .1)
// {
// return OneDOptimizationInternal(oneDRealFunction, bestParameterSoFar.Champ, increment * .1, 1, 9);
// }
// else
// {
// return bestParameterSoFar;
// }
//}
static public BestSoFar <double, double> OneDOptimization(Converter <double, double> oneDRealFunction,
double low, double high, double precision, int gridLineCount)
{
double rangeIncrement = (high - low) / (double)gridLineCount;
BestSoFar <double, double> bestParameterSoFar = BestSoFar <double, double> .GetInstance(SpecialFunctions.DoubleGreaterThan);
//Debug.WriteLine(SpecialFunctions.CreateTabString("parameter", "score"));
//Debug.WriteLine(SpecialFunctions.CreateTabString(low, high, rangeIncrement));
for (int gridLine = 0; gridLine <= gridLineCount; ++gridLine)
{
double parameter = low + gridLine * rangeIncrement;
//double parameter = SpecialFunctions.Probability(parameterLogOdds);
double score = oneDRealFunction(parameter);
//Debug.WriteLine(SpecialFunctions.CreateTabString(parameter, score));
bestParameterSoFar.Compare(score, parameter);
}
//Debug.WriteLine("");
if (high - low < precision)
{
return(bestParameterSoFar);
}
return(OneDOptimization(oneDRealFunction, bestParameterSoFar.Champ - rangeIncrement, bestParameterSoFar.Champ + rangeIncrement,
precision, gridLineCount));
}
//public void FindBestHlaAssignment()
//{
// while (true)
// {
// int previousChangeCount = BestHlaAssignmentSoFar.ChangeCount;
// foreach(HlaAssignmentsToConsiderDelegate hlaAssignmentsToConsider in HlaAssignmentsToConsiderCollection)
// {
// RepeatUntilToImprovement(hlaAssignmentsToConsider);
// }
// if (previousChangeCount == BestHlaAssignmentSoFar.ChangeCount)
// {
// break;
// }
// }
//}
//private void RepeatUntilToImprovement(HlaAssignmentsToConsiderDelegate hlaAssignmentsToConsider)
//{
// while (true)
// {
// int previousChangeCount = BestHlaAssignmentSoFar.ChangeCount;
// ScoreAssignments(hlaAssignmentsToConsider);
// if (previousChangeCount == BestHlaAssignmentSoFar.ChangeCount)
// {
// break;
// }
// }
//}
private void ScoreAssignments(HlaAssignmentsToConsider hlaAssignmentsToConsider)
{
foreach (TrueCollection hlaAssignment in hlaAssignmentsToConsider.Collection())
{
double score = QmrrModelMissingAssignment.LogLikelihoodOfCompleteModelConditionedOnKnownHlas(hlaAssignment);
BestHlaAssignmentSoFar.Compare(score, hlaAssignment);
}
}
internal void CreateNoSwitchablesHlaAssignment()
{
BestHlaAssignmentSoFar = BestSoFar <double, TrueCollection> .GetInstance(SpecialFunctions.DoubleGreaterThan);
TrueCollection trueCollection = TrueCollection.GetInstance(QmrrModelMissingAssignment.KnownHlaSet);
double scoreOnNoSwitchables = QmrrModelMissingAssignment.LogLikelihoodOfCompleteModelConditionedOnKnownHlas(trueCollection);
BestHlaAssignmentSoFar.Compare(scoreOnNoSwitchables, trueCollection);
}
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);
}
internal override Dictionary <Hla, PValueDetails> CreateHlaToPValueDetails(int nullIndex, string peptide, Dictionary <string, Set <Hla> > pidToHlaSetAll, Set <Hla> setOfHlasToConsiderAdding, TextWriter writer)
{
Dictionary <Hla, PValueDetails> hlaToPValueDetails = new Dictionary <Hla, PValueDetails>();
if (setOfHlasToConsiderAdding.Count == 0)
{
return(hlaToPValueDetails);
}
Dictionary <string, double> pidToReactValue = ReactTableUnfiltered[peptide];
Set <Hla> knownHlaSet = KnownTable(peptide);
SpecialFunctions.CheckCondition(setOfHlasToConsiderAdding.Intersection(knownHlaSet).Count == 0);
Set <Hla> bestHlaSetSoFar = Set <Hla> .GetInstance();
while (setOfHlasToConsiderAdding.Count > 0)
{
BestSoFar <PValueDetails, Hla> bestHlaToAddSoFar = BestSoFar <PValueDetails, Hla> .GetInstance(delegate(PValueDetails pValueDetails1, PValueDetails pValueDetails2) { return(pValueDetails1.Diff.CompareTo(pValueDetails2.Diff)); });
foreach (Hla hla in setOfHlasToConsiderAdding) //!!!only look at hla's of patients with reactivity to this peptide (how effects nulls?)
{
PValueDetails pValueDetails = CreateAPValueDetail(nullIndex, peptide, pidToHlaSetAll, knownHlaSet, bestHlaSetSoFar, hla);
bestHlaToAddSoFar.Compare(pValueDetails, hla);
}
//Debug.WriteLine("");
PValueDetails bestPValueDetails = bestHlaToAddSoFar.ChampsScore; //!!!weird that PValue details is the score and the object
if (bestPValueDetails.PValue() > PValueCutOff)
{
break;
}
Hla hlaToAdd = bestHlaToAddSoFar.Champ;
setOfHlasToConsiderAdding.Remove(hlaToAdd);
bestHlaSetSoFar = bestHlaSetSoFar.Union(hlaToAdd);
hlaToPValueDetails.Add(hlaToAdd, bestPValueDetails);
writer.WriteLine(bestPValueDetails);
//Debug.WriteLine(bestPValueDetails);
writer.Flush();
}
return(hlaToPValueDetails);
}
protected OptimizationParameterList FindBestParams(string peptide,
Set <Hla> candidateHlaSet,
Set <Hla> hlaWithLinkZero,
Dictionary <string, Set <Hla> > patientList,
//Dictionary<string, Dictionary<string,double>> reactTable,
out double score)
{
//SpecialFunctions.CheckCondition(false, "Regression test this to be sure that switch to new optimization method didn't change anything important - cmk 5/1/2006");
Set <Hla> knownHlaSet = KnownTable(peptide);
TrueCollection trueCollection = TrueCollection.GetInstance(candidateHlaSet, knownHlaSet);
OptimizationParameterList qmrrParamsThisPeptide = CreateQmrrParamsStartForTheseCandidateHlas(trueCollection.CreateHlaAssignmentAsSet(), hlaWithLinkZero);
//OptimizationParameterList qmrrParamsThisPeptide = CreateQmrrParamsX(causePrior, leakProbability, trueCollection.CreateHlaAssignmentAsSet());
ModelLikelihoodFactories modelLikelihoodFactories = ModelLikelihoodFactories.GetInstanceLinkPerHla(qmrrParamsThisPeptide, trueCollection.CreateHlaAssignmentAsSet());
QmrrPartialModelCollection singletonQmrrPartialModelCollection =
QmrrPartialModelCollection.GetInstance(
peptide,
modelLikelihoodFactories,
qmrrParamsThisPeptide,
patientList,
ReactTableUnfiltered,
_knownTable,
HlaFactory.Name //!!!would it be better to pass the actual factory???
);
BestSoFar <double, TrueCollection> bestSoFar = BestSoFar <double, TrueCollection> .GetInstance(SpecialFunctions.DoubleGreaterThan);
bestSoFar.Compare(double.NegativeInfinity, trueCollection);
Dictionary <string, BestSoFar <double, TrueCollection> > peptideToBestHlaAssignmentSoFar = new Dictionary <string, BestSoFar <double, TrueCollection> >();
peptideToBestHlaAssignmentSoFar.Add(peptide, bestSoFar);
QmrrlModelMissingParametersCollection aQmrrlModelMissingParametersCollection
= QmrrlModelMissingParametersCollection.GetInstance(modelLikelihoodFactories, singletonQmrrPartialModelCollection, peptideToBestHlaAssignmentSoFar);
OptimizationParameterList qmrrParamsEnd = aQmrrlModelMissingParametersCollection.FindBestParams(qmrrParamsThisPeptide, out score);
return(qmrrParamsEnd);
}
override public double Run(Converter <OptimizationParameter, double> oneDRealFunction,
OptimizationParameter param)
{
double low = param.LowForSearch;
double high = param.HighForSearch;
Converter <double, double> oneDRealFunctionInDoubleSpace = delegate(double d)
{
param.ValueForSearch = d;
return(oneDRealFunction(param));
};
double initParamValue = param.ValueForSearch;
BestSoFar <double, double> bestFound = OneDOptimizationX(oneDRealFunctionInDoubleSpace, low, high, GridLineCount, Tolerance);
bestFound.Compare(oneDRealFunctionInDoubleSpace(initParamValue), initParamValue); // make sure we didn't get any worse
//bestInput = bestFound.Champ;
param.ValueForSearch = bestFound.Champ;
return(bestFound.ChampsScore);
}
private void CreateBestParamsSoFar()
{
BestParamsSoFar = BestSoFar <double, OptimizationParameterList> .GetInstance(SpecialFunctions.DoubleGreaterThan);
BestParamsSoFar.Compare(double.NegativeInfinity, QmrrParamsStart);
}
