/// <summary>
/// Computes a spanning tree
/// </summary>
/// <param name="g"></param>
/// <param name="s"></param>
/// <returns></returns>
public static IGraph PrimsAlgorithm(IGraph g, int s)
{
int i1 = g.NumberOfVertices;
Entry[] entrys = new Entry[i1];
for (int j1 = 0; j1 < i1; j1++)
{
entrys[j1] = new Entry(false, int.MaxValue, int.MaxValue);
}
entrys[s].distance = 0;
IPriorityQueue priorityQueue = new BinaryHeap(g.NumberOfEdges);
priorityQueue.Enqueue(new Association(0, g.GetVertex(s)));
while (!priorityQueue.IsEmpty)
{
IVertex vertex1 = (IVertex)((Association)priorityQueue.DequeueMin()).Value;
if (entrys[vertex1.Number].known)
{
continue;
}
entrys[vertex1.Number].known = true;
IEnumerator iEnumerator = vertex1.EmanatingEdges.GetEnumerator();
try
{
while (iEnumerator.MoveNext())
{
IEdge edge = (IEdge)iEnumerator.Current;
IVertex vertex2 = edge.MateOf(vertex1);
int k = (edge.Weight == null? 0 :(int)edge.Weight);
if (!entrys[vertex2.Number].known && entrys[vertex2.Number].distance > k)
{
entrys[vertex2.Number].distance = k;
entrys[vertex2.Number].predecessor = vertex1.Number;
priorityQueue.Enqueue(new Association(k, vertex2));
}
}
}
finally
{
IDisposable iDisposable = iEnumerator as IDisposable;
if (iDisposable != null)
{
iDisposable.Dispose();
}
}
}
IGraph graph1 = new GraphAsLists(i1);
for (int i2 = 0; i2 < i1; i2++)
{
graph1.AddVertex(i2);
}
for (int j2 = 0; j2 < i1; j2++)
{
if (j2 != s)
{
graph1.AddConnection(j2, entrys[j2].predecessor);
}
}
return(graph1);
}
/// <summary>
/// Kruskal's algorithm is an algorithm that finds a minimum spanning tree for a connected weighted graph.
/// This means it finds a subset of the edges that forms a tree that includes every vertex,
/// where the total weight of all the edges in the tree is minimized.
/// If the graph is not connected, then it finds a minimum spanning forest (a minimum spanning tree for each connected component).
/// </summary>
/// <param name="g"></param>
/// <returns></returns>
public static IGraph KruskalsAlgorithm(IGraph g)
{
Console.WriteLine("Starting...");
int i1 = g.NumberOfVertices;
IGraph graph1 = new GraphAsLists(i1);
for (int j1 = 0; j1 < i1; j1++)
{
graph1.AddVertex(j1);
}
IPriorityQueue priorityQueue = new BinaryHeap(g.NumberOfEdges);
IEnumerator iEnumerator = g.Edges.GetEnumerator();
Console.WriteLine("got the edge enumerator...");
try
{
while (iEnumerator.MoveNext())
{
IEdge edge1 = (IEdge)iEnumerator.Current;
int k;
//the casting depends on the datatype of the weight, here you are on your own
//we'll assume that an int will do as an example
if (edge1.Weight == null)
{
k = 0;
}
else
{
try
{
k = (int)edge1.Weight;
}
catch
{
k = 0;
}
}
priorityQueue.Enqueue(new Association(k, edge1));
}
}
finally
{
IDisposable iDisposable = iEnumerator as IDisposable;
if (iDisposable != null)
{
iDisposable.Dispose();
}
}
Console.WriteLine("after the edge enumerator...");
Console.WriteLine(priorityQueue.ToString());
IPartition partition = new PartitionAsForest(i1);
Console.WriteLine("The partition: " + partition.Count);
while (!priorityQueue.IsEmpty && (partition.Count > 1))
{
IEdge edge2 = (IEdge)((Association)priorityQueue.DequeueMin()).Value;
Console.WriteLine(edge2.ToString());
int i2 = edge2.V0.Number;
int j2 = edge2.V1.Number;
Console.WriteLine("got vertices (" + i2 + "," + j2 + ")");
ISet set1 = partition.Find(i2);
ISet set2 = partition.Find(j2);
if (set1 != set2)
{
partition.Join(set1, set2);
graph1.AddConnection(i2, j2);
}
}
return(graph1);
}
internal Enumerator(BinaryHeap heap)
{
position = 0;
this.heap = heap;
}