public ParameterValue[] CreateIndividual(OriginData matlabOriginData, IEnumerable <MoleculeOntogeny> moleculeOntogenies)
{
var originData = originDataFrom(matlabOriginData);
var individual = _individualFactory.CreateAndOptimizeFor(originData);
var individualProperties = _individualValuesMapper.MapFrom(individual);
var allIndividualParameters = individualProperties.ParameterValues.ToList();
allIndividualParameters.AddRange(_ontogenyFactorsRetriever.FactorsFor(originData, moleculeOntogenies));
return(allIndividualParameters.ToArray());
}
public CreateIndividualResults CreateIndividual(IndividualCharacteristics individualCharacteristics)
{
var originData = originDataFrom(individualCharacteristics);
var moleculeOntogenies = individualCharacteristics.MoleculeOntogenies;
var individual = _individualFactory.CreateAndOptimizeFor(originData, individualCharacteristics.Seed);
var individualProperties = _individualValuesMapper.MapFrom(individual);
var allIndividualParameters = individualProperties.ParameterValues;
var ontogenyParameters = _ontogenyFactorsRetriever.FactorsFor(originData, moleculeOntogenies).Select(x => new ParameterValueWithUnit(x));
var allDistributedParameterCache = _containerTask.CacheAllChildren <IDistributedParameter>(individual);
var allIndividualParametersCache = _containerTask.CacheAllChildren <IParameter>(individual);
var distributedParameters = new Cache <string, ParameterValueWithUnit>(x => x.ParameterPath);
var derivedParameters = new List <ParameterValueWithUnit>();
//Add Age and Height parameter that is not distributed at the moment
if (originData.Population.IsAgeDependent)
{
distributedParameters.Add(parameterValueFrom(individual.Organism.Parameter(CoreConstants.Parameters.AGE)));
distributedParameters.Add(parameterValueFrom(individual.Organism.Parameter(Constants.Parameters.GESTATIONAL_AGE)));
}
if (originData.Population.IsHeightDependent)
{
distributedParameters.Add(parameterValueFrom(individual.Organism.Parameter(CoreConstants.Parameters.HEIGHT)));
}
distributedParameters.Add(parameterValueFrom(individual.Organism.Parameter(CoreConstants.Parameters.ONTOGENY_FACTOR_AGP)));
distributedParameters.Add(parameterValueFrom(individual.Organism.Parameter(CoreConstants.Parameters.ONTOGENY_FACTOR_ALBUMIN)));
foreach (var individualParameter in allIndividualParameters)
{
var parameter = allIndividualParametersCache[individualParameter.ParameterPath];
if (parameter == null)
{
continue;
}
var parameterValue = new ParameterValueWithUnit(individualParameter, parameter?.BaseUnitName());
if (allDistributedParameterCache.Contains(individualParameter.ParameterPath))
{
distributedParameters.Add(parameterValue);
}
//Do not add parameters that were added specifically
else if (!distributedParameters.Contains(individualParameter.ParameterPath))
{
derivedParameters.Add(parameterValue);
}
}
//add Ontogeny parameters
distributedParameters.AddRange(ontogenyParameters);
return(new CreateIndividualResults(distributedParameters.ToArray(), derivedParameters.ToArray(), individual.Seed));
}
public Task <RandomPopulation> CreateFor(RandomPopulationSettings populationSettings, CancellationToken cancellationToken, int?seed = null, bool addMoleculeParametersVariability = true)
{
return(Task.Run(() =>
{
using (var progressUpdater = _progressManager.Create())
{
var randomPopulation = createPopulationFor(populationSettings, seed);
fllUpGenderQueueBasedOn(populationSettings);
progressUpdater.Initialize(populationSettings.NumberOfIndividuals, PKSimConstants.UI.CreatingPopulation);
//the base individual is used to retrieve the default values.
var baseIndividual = populationSettings.BaseIndividual;
//current individual defined as a clone of the based individual. The current individual will be the one varying
var currentIndividual = _cloner.Clone(populationSettings.BaseIndividual);
//cache containing all parameters changed by the create individual from the current individual. This will be used just as reference to the current parameters
var allChangedByCreatedIndividualParameters = getAllCreateIndividualParametersFrom(currentIndividual);
//all distributed parameters. This will be used to update the distribution for the current individual
var allDistributedParameters = getAllDistributedParametersFrom(currentIndividual);
var allBaseDistributedParameters = getAllDistributedParametersFrom(baseIndividual);
//all individual parameters. Just an optimization to avoid call GetAllChildren for each individual
var allIndividualParameters = currentIndividual.GetAllChildren <IParameter>().ToList();
int maxTotalIterations = populationSettings.NumberOfIndividuals * _maxIterations;
uint numberOfTry = 0;
var currentGender = _genderQueue.Dequeue();
do
{
cancellationToken.ThrowIfCancellationRequested();
numberOfTry++;
//could not create one item in max Iteration try=>exit
if (numberOfTry > _maxIterations && randomPopulation.NumberOfItems == 0)
{
throw new CannotCreatePopulationWithConstraintsException(_reportGenerator.StringReportFor(populationSettings));
}
//create a new individual based on population settings defined by the user
updateCurrentIndividualFromSettings(populationSettings, currentIndividual, allDistributedParameters, allBaseDistributedParameters, currentGender, randomPopulation.RandomGenerator);
bool success = tryRandomize(currentIndividual, populationSettings, allIndividualParameters, randomPopulation.RandomGenerator);
if (!success)
{
continue;
}
randomPopulation.AddIndividualValues(_individualValuesMapper.MapFrom(currentIndividual, allChangedByCreatedIndividualParameters));
currentGender = _genderQueue.Dequeue();
progressUpdater.IncrementProgress(PKSimConstants.UI.CreatingIndividualInPopulation(randomPopulation.NumberOfItems, populationSettings.NumberOfIndividuals));
} while (randomPopulation.NumberOfItems < populationSettings.NumberOfIndividuals && numberOfTry < maxTotalIterations);
if (numberOfTry >= maxTotalIterations)
{
throw new CannotCreatePopulationWithConstraintsException(_reportGenerator.StringReportFor(populationSettings));
}
if (addMoleculeParametersVariability)
{
_moleculeParameterVariabilityCreator.AddVariabilityTo(randomPopulation);
}
_moleculeOntogenyVariabilityUpdater.UpdateAllOntogenies(randomPopulation);
randomPopulation.IsLoaded = true;
return randomPopulation;
}
}, cancellationToken));
}
