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Maximum Weight Spanning tree (Undirected)

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Maximum Weight Spanning tree (Undirected)

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12 Mar 2009 (Updated )

Chu-Liu-Edmonds Algorithm for learning "Undirected Maximum Weight Spanning tree" is proposed here.

UndirectedMaximumSpanningTree (CostMatrix)
function [ Tree,Cost ] =  UndirectedMaximumSpanningTree (CostMatrix)
% The function takes CostMatrix as input and returns the maximum spanning tree T
% Uses Kruskal's Algorithm
% Extract the edge weights from the cost matrix
% Sort the edges in a non decreasing order of weights 
% This algorithm is revised by Lowell Guangdi at 2009/06/11.

n = size (CostMatrix,1); %Number of vertices
EdgeWeights = 0;         %Edges and corresponding weights
EdgeWeightsCounter = 0;
for i = 1:n
    for j = (i+1):n
        if ((CostMatrix(i,j))~=0)
            EdgeWeightsCounter = EdgeWeightsCounter + 1;
            EdgeWeights(EdgeWeightsCounter,1) = CostMatrix(i,j);
            EdgeWeights(EdgeWeightsCounter,2) = i;
            EdgeWeights(EdgeWeightsCounter,3) = j;
        end
    end
end

SortedEdgeWeights = 0;
SortedEdgeWeights = sortrows(EdgeWeights);
% First column of SortedEdgeWeights are the weights
% Second and third column are the vertices that the edges connect
m = size(SortedEdgeWeights,1); % number of edges 

% We use the Disjoint sets data structures to detect cycle while adding new
% edges. Union by Rank with path compression is implemented here.

% Assign parent pointers to each vertex. Initially each vertex points to 
% itself. Now we have a conceptual forest of n trees representing n disjoint 
% sets 
global ParentPointer ;
ParentPointer = 0;
ParentPointer(1:n) = 1:n;

% Assign a rank to each vertex (root of each tree). Initially all vertices 
% have the rank zero.
TreeRank = 0;
TreeRank(1:n) = 0;

% Visit each edge in the sorted edges array
% If the two end vertices of the edge are in different sets (no cycle), add
% the edge to the set of edges in maximum spanning tree
MSTreeEdges = 0;
MSTreeEdgesCounter = 0; i = m;
while ((MSTreeEdgesCounter < (n-1)) && (i>=1))
%Find the roots of the trees that the selected edge's two vertices
%belong to. Also perform path compression.
    root1=0; root2=0; temproot=0;
    temproot = SortedEdgeWeights(i,2);
    root1 = FIND_PathCompression(temproot);
  
    temproot = SortedEdgeWeights(i,3);
    root2 = FIND_PathCompression(temproot);
    
    if (root1 ~= root2)
        MSTreeEdgesCounter = MSTreeEdgesCounter + 1;
        MSTreeEdges(MSTreeEdgesCounter,1:3) = SortedEdgeWeights(i,:);
        if (TreeRank(root1)>TreeRank(root2))
            ParentPointer(root2)=root1;
        else
            if (TreeRank(root1)==TreeRank(root2))
               TreeRank(root2)=TreeRank(root2) + 1;
            end
            ParentPointer(root1)=root2;
        end
    end
    i = i - 1;
end

MSTreeEdgesCounter = 0;
Tree = 0;
Tree(1:n,1:n)=0;
while (MSTreeEdgesCounter < (n-1))
    MSTreeEdgesCounter = MSTreeEdgesCounter + 1;
    Tree(MSTreeEdges(MSTreeEdgesCounter,2),MSTreeEdges(MSTreeEdgesCounter,3))=1;
    Tree(MSTreeEdges(MSTreeEdgesCounter,3),MSTreeEdges(MSTreeEdgesCounter,2))=1;
end
%T

Cost = 0;
for p = 1:n
    for q = p+1:n
       if Tree( p,q ) == 1 
          Cost = Cost + CostMatrix( p,q );
       end
    end
end

end

function [parent] = FIND_PathCompression(temproot)

global ParentPointer;
ParentPointer(temproot);
if (ParentPointer(temproot)~=temproot)
    ParentPointer(temproot) = FIND_PathCompression(ParentPointer(temproot));
end
parent = ParentPointer(temproot);
end

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