public static void Message_Tranfer_Arbol_Union(MarkovNet arboldeunion, Evidence evidence)
{
Generic(evidence, null, arboldeunion);
}
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);
}
}
}
public static void Message_Tranfer_Arbol_Union(MarkovNet arboldeunion, KeyValuePair <BayesianNode, int>[] evidence = null)
{
//absorber evidence
if (evidence != null && evidence.Length > 0)
{
arboldeunion.BayesianNet.Evidence = evidence.Select(x => x.Value).ToArray();
}
if (arboldeunion.Count() > ParalellStartNumber)
{
#region ParalellAlgorithm
arboldeunion.Debug = true;
var taskarr = new Task[arboldeunion.Count];
for (int i = 0; i < arboldeunion.Count; i++)
{
taskarr[i] = new Task(o =>
{
var node = o as BayesianNode;
if (node != null)
{
lock (node)
{
do
{
arboldeunion.Work(node);
} while (!node.Finished);
}
}
}, arboldeunion[i]);
taskarr[i].Start();
}
for (int i = 0; i < arboldeunion.Count * 8; i++)
{
System.Threading.Thread.Sleep(300);
Increment();
}
Task.WaitAll(taskarr);
arboldeunion.Debug = false;
#endregion
}
else
#region DeterministicAlgorithm
{
while (!arboldeunion.AllConditionalProbabilitiesComputed())
{
foreach (var item in arboldeunion)
{
arboldeunion.Work(item);
}
Increment();
}
}
#endregion
foreach (var node in arboldeunion.BayesianNet)
{
arboldeunion.Marginalize_X(node);
}
}
