public ConstraintBasedStructureLearner(IList <RandomVariable> randomVariables, DualKeyDictionary <RandomVariable, ICollection <ISet <RandomVariable> > > independencies)
{
_randomVariables = randomVariables;
_independencies = independencies;
_dag = DagPattern <RandomVariable> .InitCompleteDag(randomVariables);
_collectedConditions = new DualKeyDictionary <RandomVariable, ISet <RandomVariable> >();
foreach (var x in _dag.Nodes)
{
foreach (var y in _dag.Nodes.Where(y => x != y))
{
_collectedConditions[x, y] = new HashSet <RandomVariable>();
}
}
}
/// <summary>
/// Identifies as many conditional independencies in the model as possible.
/// </summary>
public DualKeyDictionary <RandomVariable, ICollection <ISet <RandomVariable> > > FindIndependencies(IList <FaultRandomVariable> faults, ICollection <McsRandomVariable> minimalCriticalSets, IList <BooleanRandomVariable> states, BooleanRandomVariable hazard)
{
_hazard = hazard;
_faults = faults;
_minimalCriticalSets = new HashSet <McsRandomVariable>(minimalCriticalSets);
_states = states;
_conditionalIndependencies = new DualKeyDictionary <RandomVariable, ICollection <ISet <RandomVariable> > >();
var variablesForCalculation = GetVariablesForCalculation();
CalculatePairIndependencies(variablesForCalculation);
if (_config.UseDccaResultsForLearning && _minimalCriticalSets.Count > 0)
{
GenerateDccaIndependencies();
CalculateFurtherDccaIndependencies();
}
return(_conditionalIndependencies);
}