public MST primGenerateMST()
{
// populates list of distances
List<primState> cost_table = new List<primState>();
for (int i = 0; i < Cities.Length; i++)
{
for (int j = 0; j < Cities.Length; j++)
{
primState state = new primState(Cities[i], Cities[j]);
if (i == j)
{
state.setCost(double.PositiveInfinity);
}
cost_table.Add(state);
}
}
// sort list: O(n^2), worst case. Average case likely O(nlogn), assuming LINQ implements quicksort under-the-hood
cost_table = cost_table.OrderBy(State => State.cost).ToList();
// FIND MST
// initialize mst to contain the smallest edge
MST mst = new MST();
Random random = new Random();
//mst.root = new MSTNode(cost_table.ElementAt(0).startCity);
int index = random.Next(0, cost_table.Count);
mst.root = new MSTNode(cost_table.ElementAt(index).startCity);
mst.root.addChild(new MSTNode(cost_table.ElementAt(index).endCity));
MSTNode curNode = null;
cost_table.RemoveAt(0);
// create container of cities in the tree for convenience later on
ArrayList citiesInMst = new ArrayList();
citiesInMst.Add(mst.root.getCity());
citiesInMst.Add(mst.root.getChildren().ElementAt(0).getCity()); // root only has one child
while (citiesInMst.Count < Cities.Length) // grow mst one city at a time until it connects each city (until its size is Cities.length)
{
foreach (primState curEdge in cost_table) // iterate across remaining (unused) edges from shortest to longest
{
curNode = mst.findNode(curEdge.startCity);
if (curNode != null) // if the start of current edge is already in the tree (expand the current tree, no parallel tree growth for this algorithm)...
{
// only if the end of current edge is NOT in the tree (no cycles allowed)...
if(!citiesInMst.Contains(curEdge.endCity))
{
curNode.addChild(new MSTNode(curEdge.endCity));
citiesInMst.Add(curEdge.endCity);
cost_table.Remove(curEdge); // O(n) complexity
break;
}
}
}
}
return mst;
}
