private TableFormula createTableFormulaFrom(TableFormulaParameter <IDistributedParameter> parameter, IReadOnlyList <ParameterDistributionMetaData> allDistributionsWithAgeStrictBiggerThanOriginData)
{
if (allDistributionsWithAgeStrictBiggerThanOriginData.Count == 0)
{
return(null);
}
var tableFormula = _formulaFactory.CreateDistributedTableFormula();
updateTableFormulaFrom(tableFormula, parameter.Parameter);
tableFormula.Percentile = parameter.Percentile;
if (parameter.PercentileIsInvalid)
{
throw new PKSimException(PKSimConstants.Error.CannotCreateAgingSimulationWithInvalidPercentile(_fullPathDisplayResolver.FullPathFor(parameter.Parameter), parameter.Percentile));
}
//0 because of the offset with age
tableFormula.AddPoint(0, parameter.Value, DistributionMetaData.From(parameter.Parameter));
foreach (var scaledDistribution in scaleDistributions(parameter, allDistributionsWithAgeStrictBiggerThanOriginData))
{
var age = ageWithOffsetInMin(scaledDistribution.Age, parameter.OriginData.Age.Value);
var value = valueFrom(scaledDistribution, parameter.Percentile);
tableFormula.AddPoint(age, value, DistributionMetaData.From(scaledDistribution));
}
return(tableFormula);
}
private TableFormula createTableFormulaFrom(IDistributedParameter individualParameter, IReadOnlyList <ParameterDistributionMetaData> allDistributionsWithAgeStrictBiggerThanOriginData)
{
var parameter = new TableFormulaParameter <IDistributedParameter>
{
OriginData = _baseOriginData,
Parameter = individualParameter,
Value = individualParameter.Value,
Percentile = individualParameter.Percentile
};
return(createTableFormulaFrom(parameter, allDistributionsWithAgeStrictBiggerThanOriginData));
}
private IEnumerable <ParameterDistributionMetaData> scaleDistributions(TableFormulaParameter <IDistributedParameter> parameter, IEnumerable <ParameterDistributionMetaData> distributionsToScale)
{
//Retrieve the mean height parameter for the given origin data
var originData = parameter.OriginData;
var individualParameter = parameter.Parameter;
bool needHeightScaling = needScaling(originData, individualParameter);
if (!needHeightScaling)
{
return(distributionsToScale);
}
//retrieve the height distribution for the original individual
var heightDistributions = allDistributionsFor(_allHeightDistributionMaleParameters, _allHeightDistributionFemaleParameters, originData).ToList();
var heightDistributionParameters = distributionParametersFor(heightDistributions, originData);
double meanHeight = heightDistributionParameters.Item1;
double deviation = heightDistributionParameters.Item2;
var heigthDistributionFormula = distributionFrom(DistributionTypes.Normal, meanHeight, deviation);
double currentHeight = originData.Height.GetValueOrDefault(meanHeight);
//same height, not need to scale
if (ValueComparer.AreValuesEqual(meanHeight, currentHeight))
{
return(distributionsToScale);
}
//is used in order to retrieve the percentile
double currentPercentile = heigthDistributionFormula.CalculatePercentileForValue(currentHeight);
double alpha = individualParameter.ParentContainer.Parameter(CoreConstants.Parameter.ALLOMETRIC_SCALE_FACTOR).Value;
var currentOriginData = originData.Clone();
var scaledParameterDistributionMetaData = new List <ParameterDistributionMetaData>();
foreach (var originDistributionMetaData in distributionsToScale)
{
var distributionMetaData = ParameterDistributionMetaData.From(originDistributionMetaData);
currentOriginData.Age = originDistributionMetaData.Age;
double hrelForAge = calculateRelativeHeightForAge(heightDistributions, currentOriginData, currentPercentile);
scaleDistributionMetaData(distributionMetaData, hrelForAge, alpha);
scaledParameterDistributionMetaData.Add(distributionMetaData);
}
return(scaledParameterDistributionMetaData);
}
private void addAgingDataToPopulationSimulation <TParameter>(
PopulationSimulation populationSimulation,
string parameterPath,
TParameter parameter,
Func <TableFormulaParameter <TParameter>, TableFormula> tableFormulaRetriever) where TParameter : IParameter
{
if (populationSimulation == null || !_createAgingDataInPopulationSimulation)
{
return;
}
var originData = _baseOriginData.Clone();
var allAges = populationSimulation.AllOrganismValuesFor(CoreConstants.Parameters.AGE, _entityPathResolver);
var allGAs = populationSimulation.AllOrganismValuesFor(Constants.Parameters.GESTATIONAL_AGE, _entityPathResolver);
var allHeights = populationSimulation.AllOrganismValuesFor(CoreConstants.Parameters.HEIGHT, _entityPathResolver);
var allGender = populationSimulation.AllGenders(_genderRepository).ToList();
var allValues = populationSimulation.AllValuesFor(parameterPath).ToList();
var allPercentiles = populationSimulation.AllPercentilesFor(parameterPath)
.Select(x => x.CorrectedPercentileValue()).ToList();
var tableFormulaParameter = new TableFormulaParameter <TParameter> {
OriginData = originData, Parameter = parameter
};
for (int individualIndex = 0; individualIndex < populationSimulation.NumberOfItems; individualIndex++)
{
//create origin data for individual i
originData.Age.Value = allAges[individualIndex];
originData.GestationalAge.Value = allGAs[individualIndex];
originData.Height.Value = allHeights[individualIndex];
originData.Gender = allGender[individualIndex];
tableFormulaParameter.Value = allValues[individualIndex];
tableFormulaParameter.Percentile = allPercentiles[individualIndex];
var tableFormula = tableFormulaRetriever(tableFormulaParameter);
if (tableFormula == null)
{
continue;
}
populationSimulation.AddAgingTableFormula(parameterPath, individualIndex, tableFormula);
}
}
private void createPopulationHeightTableParameter(
string heightParameterPath,
IDistributedParameter meanHeightParameter,
PopulationSimulation populationSimulation
)
{
if (populationSimulation == null || !_createAgingDataInPopulationSimulation)
{
return;
}
var originData = _baseOriginData.Clone();
var allAges = populationSimulation.AllOrganismValuesFor(CoreConstants.Parameters.AGE, _entityPathResolver);
var allGAs = populationSimulation.AllOrganismValuesFor(Constants.Parameters.GESTATIONAL_AGE, _entityPathResolver);
var allHeights = populationSimulation.AllOrganismValuesFor(CoreConstants.Parameters.HEIGHT, _entityPathResolver);
var allGender = populationSimulation.AllGenders(_genderRepository).ToList();
var tableFormulaParameter = new TableFormulaParameter <IDistributedParameter> {
OriginData = originData, Parameter = meanHeightParameter
};
for (int individualIndex = 0; individualIndex < populationSimulation.NumberOfItems; individualIndex++)
{
//create origin data for individual i
originData.Age.Value = allAges[individualIndex];
originData.GestationalAge.Value = allGAs[individualIndex];
originData.Height.Value = allHeights[individualIndex];
originData.Gender = allGender[individualIndex];
tableFormulaParameter.Value = originData.Height.Value;
var heightDistributions = heightDistributionsFor(originData);
tableFormulaParameter.Percentile = heightDistributions.currentPercentile;
var distributions = allDistributionsWithAgeStrictBiggerThanOriginData(_allHeightDistributionMaleParameters, _allHeightDistributionFemaleParameters, tableFormulaParameter.OriginData);
var tableFormula = createTableFormulaFrom(tableFormulaParameter, distributions);
if (tableFormula == null)
{
continue;
}
populationSimulation.AddAgingTableFormula(heightParameterPath, individualIndex, tableFormula);
}
}
private IReadOnlyList <ParameterDistributionMetaData> scaleDistributions(TableFormulaParameter <IDistributedParameter> parameter, IReadOnlyList <ParameterDistributionMetaData> distributionsToScale)
{
//Retrieve the mean height parameter for the given origin data
var originData = parameter.OriginData;
var individualParameter = parameter.Parameter;
bool needHeightScaling = needScaling(originData, individualParameter);
if (!needHeightScaling)
{
return(distributionsToScale);
}
var(meanHeight, currentHeight, currentPercentile, heightDistributionSamples) = heightDistributionsFor(originData);
//same height, not need to scale
if (ValueComparer.AreValuesEqual(meanHeight, currentHeight))
{
return(distributionsToScale);
}
//is used in order to retrieve the percentile
double alpha = individualParameter.ParentContainer.Parameter(CoreConstants.Parameters.ALLOMETRIC_SCALE_FACTOR).Value;
var currentOriginData = originData.Clone();
var scaledParameterDistributionMetaData = new List <ParameterDistributionMetaData>();
foreach (var originDistributionMetaData in distributionsToScale)
{
var distributionMetaData = ParameterDistributionMetaData.From(originDistributionMetaData);
currentOriginData.Age.Value = originDistributionMetaData.Age;
var(mean, deviation) = heightDistributionSamples(currentOriginData);
double heightAtPercentile = valueFrom(DistributionTypes.Normal, mean, deviation, currentPercentile);
double hrelForAge = heightAtPercentile / mean;
scaleDistributionMetaData(distributionMetaData, hrelForAge, alpha);
scaledParameterDistributionMetaData.Add(distributionMetaData);
}
return(scaledParameterDistributionMetaData);
}