public static void Message_Tranfer_Poliarbol(BayesianGraph poliarbol, KeyValuePair <BayesianNode, int>[] evidence = null)
{
foreach (var item in poliarbol)
{
item.Inicialize();
}
//fijar la evidencia
evidence = evidence ?? new KeyValuePair <BayesianNode, int> [0];
poliarbol.AbsorbeEvidence(evidence);
if (poliarbol.Count > ParalellStartNumber)
{
#region PararellAlgorithm
poliarbol.Debug = true;
var taskarr = new Task[poliarbol.Count];
for (int i = 0; i < poliarbol.Count; i++)
{
taskarr[i] = new Task(o =>
{
var node = o as BayesianNode;
if (node != null)
{
lock (node)
{
do
{
poliarbol.Work(node);
} while (!node.Finished);
}
}
}, poliarbol[i]);
taskarr[i].Start();
}
for (int i = 0; i < poliarbol.Count * 8; i++)
{
System.Threading.Thread.Sleep(300);
Increment();
}
Task.WaitAll(taskarr);
poliarbol.Debug = false;
#endregion
}
else
#region DeterministicAlgorithm
{
while (!poliarbol.All(x => x.Finished))
{
for (int i = 0; i < poliarbol.Count; i++)
{
poliarbol.Work(poliarbol[i]);
}
Increment();
}
}
#endregion
}
public MarkovNet(BayesianGraph bayesianNet)
{
this.BayesianNet = bayesianNet;
TreeCluster = new TreeCluster();
FirstTreeCluster();
TransformTreeCluster();
CheckSubConj();
foreach (var clique in TreeCluster)
{
clique.Inicialize(TreeCluster.AdjCount(clique));
}
}
static void Generic(Evidence evidence, BayesianGraph poliarbol, MarkovNet arboldeunion)
{
//tamanno del grafo sea poliarbol o de racimos
var count = poliarbol == null
? arboldeunion.Count
: poliarbol.Count;
double realization_probalility = 1.0;
var nodesConditionalProbabilities = new double[count][];
var bayesianGraph = poliarbol ?? arboldeunion.BayesianNet;
bool traspasoEnPoliarbol = poliarbol != null;
if (evidence == null)
{
return;
}
var deterministicEvidence = new KeyValuePair <BayesianNode, int> [evidence.EvidenceValues.Length];
//absorber evidencia
//no hay evidencia
for (int i = 0; i < count; i++)
{
deterministicEvidence[i] = new KeyValuePair <BayesianNode, int>(bayesianGraph[i], -1);
}
for (int j = 0; j < count; j++)
{
nodesConditionalProbabilities[j] = new double[bayesianGraph[j].ConditionalProbability.Length];
}
bool stocasticrealizations = false;
foreach (var item in EvidenceRealization(evidence, deterministicEvidence, 0))
{
stocasticrealizations = true;
if (traspasoEnPoliarbol)
{
Message_Tranfer_Poliarbol(poliarbol, item.Item1);
}
else
{
Message_Tranfer_Arbol_Union(arboldeunion, item.Item1);
}
realization_probalility = item.Item2;
for (int i = 0; i < nodesConditionalProbabilities.Length; i++)
{
for (int j = 0; j < nodesConditionalProbabilities[i].Length; j++)
{
nodesConditionalProbabilities[i][j] += bayesianGraph[i].ConditionalProbability[j] * realization_probalility;
}
}
}
//si no hubo evidencia estocastica es que se esta solicitando el traspaso de
//msges sin evidencia
if (stocasticrealizations)
{
for (int i = 0; i < nodesConditionalProbabilities.Length; i++)
{
for (int j = 0; j < nodesConditionalProbabilities[i].Length; j++)
{
bayesianGraph[i].ConditionalProbability[j] = nodesConditionalProbabilities[i][j];
}
}
}
else
{
if (traspasoEnPoliarbol)
{
Message_Tranfer_Poliarbol(poliarbol, deterministicEvidence);
}
else
{
Message_Tranfer_Arbol_Union(arboldeunion, deterministicEvidence);
}
}
}
/// <summary>
/// Metodo que calcula, mediante el traspaso de mensajes en un poliarbol,
/// las probabilidades condicionales de un nodo dada la evidencia.
/// </summary>
/// <typeparam name="T"></typeparam>
/// <param name="poliarbol"></param>
/// <param name="evidence">Tiene tantos elementos como nodos el poliarbol.
/// En la posicion i-esima guarda el valor del estado de la variable i si esta forma parte de la evidencia;
/// -1 en otro caso.
/// </param>
public static void Message_Tranfer_Poliarbol(BayesianGraph poliarbol, Evidence evidence)
{
Generic(evidence, poliarbol, null);
}
