self organizing maps- matlab

%                        Neural Netowrks Project
%                          srinivas muddana
%                             9561 - 2909
%                         self organizing maps


function [initMap, map, elapsedTime, winNeurons] = testsomap(mapSize,ipData,epoochs)

initTime = clock;

mapDim = mapSize ; %array of  two variables indicating the length and width of map
etaInit=0.1;


if (size(mapSize,1)~=1)
    error 'The map size must be a vector'
end %end if for checking map is a two dim

ipDim = size(ipData,2);
ipLength = size(ipData,1);
%initializing the nodes assuming the map size is two D
totalNodes = mapSize(1) * mapSize(2);
rndWgts = rand(totalNodes,ipDim);
nodeCell = cell(mapSize(1),mapSize(2));
perm = randperm(ipLength);
for i=1:mapSize(1)
    for j=1:mapSize(2)
        nodeCell{i,j}=ipData(perm((i-1)*mapSize(2)+j),:);
        %nodeCell{i,j}=rndWgts((i-1)*mapSize(2)+j,:);
        %nodeCell{i,j}=somNode(i,j,rndWgts((i-1)*mapSize(2)+j,:));
    end
end
initMap = nodeCell;
sigmaInit = max(mapSize(1),mapSize(2))/2;

winNeurons = []; 
%traigning start
for numEpooch=1:epoochs  %number of iterations...numEpooch is the n term
    perm = randperm(ipLength);
    numEpooch
    for nIp=1:ipLength
        minVal=inf;
        %minPos; % showing x and y of the node .. like [2 4] 2nd row and 4th column
        tempIp=ipData(perm(nIp),:);
        %[minVal, minPos] = compete(obj,tempIp,minVal);

        for i=1:mapDim(1)
            for j=1:mapDim(2)
                tempNode = nodeCell{i,j};
                tempMinVal = norm(tempNode);
                %tempMinVal = tempNode.FindArgMin(tempIp);
                if(tempMinVal<minVal)
                    minVal = tempMinVal;
                    minPos=[i j];
                end
            end  %end for scaning the columns in nodeCell
        end  %end for scaning the rows in nodeCell
        
        var = find(winNeurons==(mapDim(1)-1)*minPos(1)+minPos(2));
        if(size(var,1)>0)
            
        else
            winNeurons(size(winNeurons,1)+1) = (mapDim(1)-1)*minPos(1)+minPos(2);
        end 

        testh=[];
        %minPos
        %co-operative process stats
        for i=1:mapDim(1)
            for j=1:mapDim(2)
                tempWgts = nodeCell{i,j};
                %tempNode.updateWgts(tempIp,minPos(1),minPos(2),numEpooch,sigmaInit,etaInit);
             
                eucDisSq = sqrt(sum(([i j]-[minPos(1) minPos(2)]).^2));
                t1=1000/log(sigmaInit);
                sigma = sigmaInit * exp((-1*numEpooch)/t1);
                if(sigma >= eucDisSq)
                h=exp((-1*eucDisSq)/(2*sigma*sigma));
                
                testh(size(testh,2)+1) = h;
                t2=1000;
                eta = etaInit * exp((-1*numEpooch)/t2); 
                if eta < 0.01
                    eta = 0.01;
                end
                delWgts = (tempIp-tempWgts).*eta * h;
                nodeCell{i,j} = nodeCell{i,j} + delWgts;
                else
                    minPos
                end
             
            end  %end for scaning the columns in nodeCell
        end  %end for scaning the rows in nodeCell
        %end of co-opertaive process
    end  %end for input order
end %end for
map = nodeCell;
 

finalTime = clock;
elapsedTime = etime(finalTime, initTime);