how to extract the value from voronoi diagram in matlab?

I need to know how to extract the value from the "voronoi" diagram in matlab. Please reply to me as soon as possible.

I'm plotting this graph by using this command "voronoi". And now I want to extract the value of each "node" in each "cluster".

[Geoff Hayes]

Arul - are you doing more than just calling voronoi to get the above plot? What are the lines of code that you are calling to produce the above? The cluster heads are presumably the coordinates for the points passed into the voronoi function, but where do the other ones come from?

[Matlab111]

see below my code's are available...

Answer 1

[Geoff Hayes]

Arul - if you want to get the vertices for each Voronoi cell, then use voronoin. For example, from this link, [V,C] = voronoin(X) returns Voronoi vertices V and the Voronoi cells C of the Voronoi diagram of X.

[Matlab111]

No actually my problem is this http://www.mathworks.in/matlabcentral/answers/153084-how-to-extract-the-neighborhood-node-value-from-this-graph just look at this than try to tell the solution plz.

[Geoff Hayes]

The above link is invalid. Can you post the code that you have used to produce the above plot?

[Matlab111]

 close all;
clear all;
%Field Dimensions - x and y maximum (in meters)
xm=100;
ym=100;
sink.x=0.5*xm;
sink.y=0.5*ym;
n=100;
p=0.1;
Eo=0.1;
ETX=50*0.000000001;
ERX=50*0.000000001;
Efs=10*0.000000000001;
Emp=0.0013*0.000000000001;
EDA=5*0.000000001;
m=0.1;
x=0.2;
a=1;
b=0.5;
rmax=5;
Ave_CH=0;
    sum=0;
count_ch=0;
Throughput=0;
Packet=40;
do=sqrt(Efs/Emp); 
figure(1);
for i=1:1:n
    S(i).xd=rand(1,1)*xm;
    XR(i)=S(i).xd
    S(i).yd=rand(1,1)*ym;
    YR(i)=S(i).yd
    S(i).G=0;
    S(i).E=0;
    S(i).type='N'
   keep(i)=i;
    temp_rnd0=i;
    if (temp_rnd0>=(x+m)*n+1) 
        S(i).E=Eo;
        S(i).ENERGY=0;
     plot(S(i).xd,S(i).yd,'o');
        hold on;
    end
end
S(n+1).xd=sink.x;
S(n+1).yd=sink.y;
figure(1);
countCHs=0;
rcountCHs=0;
cluster=1;
countCHs;
rcountCHs=rcountCHs+countCHs;
flag_first_dead=0;
flag_first_Hdead=0;
flag_last_dead=0;
c=1;
for r=0:1:rmax
   for i=1:1:n
        if(S(i).E>0)
            holder(i)=S(i).E;
            id(i)=keep(i);
            node= struct('energy', holder, 'id',id);
            [energy,index] = sort([node.energy],'descend');  
    end     
    end
     total=0;
for k=1:length(node.energy)
        energy_level=sort(node.energy, 'descend');
        total=total + node.energy(k);
        end
        average=total/length(node.energy);        
TEnergy(r+1)=total; 
AveEnergy(r+1)=average;
    r
  %Election Probability for Normal Nodes
  pnrm=( p/ (1+a*m+b*x) );
  if(mod(r, round(1/pnrm) )==0)
    for i=1:1:n
        S(i).G=0;
        S(i).cl=0;
    end
  end
  end
 Hdead=0;
dead=0;
packets_TO_BS=0;
packets_TO_CH=0;
PACKETS_TO_CH(r+1)=0;
PACKETS_TO_BS(r+1)=0;
figure(1);
for i=1:1:n
    if (S(i).E<=(Eo/2)) && (S(i).E>0)
        plot(S(i).xd,S(i).yd,'yellow .');
        Hdead=Hdead+1;
        if(S(i).ENERGY==1)
            Hdead_a=Hdead_a+1;
        end
        hold on; 
    end   
   if (S(i).E<=Eo)||(S(i).E>Eo)
      if(S(i).ENERGY==0)
          RnEnergy(r+1)=S(i).E;
      end
    end
    if (S(i).E<=0)
        plot(S(i).xd,S(i).yd,'red .');
        dead=dead+1;
        if(S(i).ENERGY==1)
            dead_a=dead_a+1;
        end
        hold on;    
    end
    if S(i).E>0
        S(i).type='N'
        if (S(i).ENERGY==0)  
        plot(S(i).xd,S(i).yd,'o');
        end
        hold on;
    end
end
plot(S(n+1).xd,S(n+1).yd,'x');
HSTATISTICS(r+1).DEAD=Hdead;
HDEAD(r+1)=Hdead;
if (Hdead==1)
    if(flag_first_Hdead==0)
        first_Hdead=r;
        flag_first_Hdead=1;
    end
end
STATISTICS(r+1).DEAD=dead;
DEAD(r+1)=dead;
if (dead==1)
    if(flag_first_dead==0)
        first_dead=r;
        flag_first_dead=1;
    end
end
alive=0;
for i=1:1:n
    if (S(i).E>0)
        alive=alive+1;
        if(S(i).ENERGY==1)
            alive_a=alive_a+1;
        end
        hold on;    
    end
if (S(i).E>0)
    nodes_status=1;
end
if (S(i).E<0)
    nodes_status=0;
end          
    ASTATISTICS(r+1).Live=alive;
Live(r+1)=alive;
end
countCHs=0;
cluster=1;
for i=1:1:n
   if(S(i).E>0)
   temp_rand=rand;     
   if ( (S(i).G)<=0)
 if( ( S(i).ENERGY==0 && ( temp_rand <= ( pnrm / ( 1 - pnrm * mod(r,round(1/pnrm)) )) ) )  )
            countCHs=countCHs+1;
            packets_TO_BS=packets_TO_BS+1;
            PACKETS_TO_BS(r+1)=packets_TO_BS;
            S(i).type='C'
            S(i).G=100;
            C(cluster).xd=S(i).xd
            C(cluster).yd=S(i).yd
            plot(S(i).xd,S(i).yd,'red+');
            distance=sqrt( (S(i).xd-(S(n+1).xd) )^2 + (S(i).yd-(S(n+1).yd) )^2 );
            C(cluster).distance=distance
            C(cluster).id=i
            X(cluster)=S(i).xd
            Y(cluster)=S(i).yd
            cluster=cluster+1;
            distance;
            if (distance>do)
 S(i).E=S(i).E-((ETX+EDA)*(Packet)+Emp*Packet*( distance*distance*distance*distance )); 
    Energy_CH_N=(ETX+EDA)*(Packet) + Emp*Packet*( distance*distance*distance*distance );
            end
            if (distance<=do)
                S(i).E=S(i).E- ( (ETX+EDA)*(Packet) + Efs*Packet*( distance * distance )); 
                Energy_CH_N=(ETX+EDA)*(Packet) + Emp*Packet*( distance*distance);
            end
        end        
    end
  end 
end
warning('OFF');
[vx,vy]=voronoi(X,Y);
voronoi(X,Y);
axis([0 xm 0 ym]);

[Matlab111]

ya this is my code above....

[Geoff Hayes]

Okay - if I run the above code, there always seems to be 101 nodes and a varying number of cells/clusters. If you want to find which nodes belong to which clusters, then just calculate the distance from each node to each cluster "centre" and that distance which is the shortest is the cluster that the node belongs to. Something like

 % pre-allocate memory to the node~cluster array
 clusterData = cell(size(X,2),1);

 % iterate over each node
 for k=1:size(S,2)

    x       = S(k).xd;
    y       = S(k).yd;
    minDist = Inf;
    at      = 0;

    % iterate over each cluster
    for u=1:size(X,2)
        dist = sqrt((x-X(u))^2+(y-Y(u))^2);
        if dist<minDist
            % distance is shorter, so the node is closer to this cluster
            minDist = dist;
            at      = u;
        end
    end

    % add the node to the array of clusters
    if at>0
        clusterData{at} = [clusterData{at} ; S(k)];
    end

end

The above code will group each node into the cluster that it belongs. So if there are 12 clusters/cells, then the size of clusterData is 12 with each element having zero or more nodes.

[Matlab111]

K sir. From this code(your code) how to get cluster head position and their member node's position separately ? I need to display cluster head position separately and cluster head member position separately...

[Geoff Hayes]

Arul - you will need to describe (to me) what the cluster head position is. What in your code represents the cluster head? Are the cluster heads different from the input to the call to voronoi at

 [vx,vy]=voronoi(X,Y);

[Matlab111]

1.'X' and 'Y' represents the cluster head positions.

2. X(cluster)=S(i).xd 
   Y(cluster)=S(i).yd

3."Are the cluster heads different from the input to the call to voronoi at [vx,vy]=voronoi(X,Y);" -No,the Cluster head is same.

[Geoff Hayes]

So, change the above code to the following to get the positions of each cluster head and the positions of each node within that cluster

 clusterData = cell(size(X,2),1);

 for k=1:size(clusterData)
    clusterData{k}.clusterHead   = [X(k) Y(k)];
    clusterData{k}.clusterNodes = [];
 end

 for k=1:size(S,2)

    x       = S(k).xd;
    y       = S(k).yd;
    minDist = Inf;
    at      = 0;

    for u=1:size(X,2)
        dist = sqrt((x-X(u))^2+(y-Y(u))^2);
        if dist<minDist
            minDist = dist;
            at      = u;
        end
    end

    if at>0
        clusterData{at}.clusterNodes = ...
           [clusterData{at}.clusterNodes ; [x y] ];
    end
 end

Now clusterData will be a cell array of structs where each struct has two fields: the clusterHead which is the (x,y) coordinate of the cluster head, and an array of cluster node positions. For example,

 clusterData{1}

 ans = 
     clusterHead: [92.0332039836564 5.26769976807926]
    clusterNodes: [5x2 double]

and

 clusterData{1}.clusterNodes

 ans =
           72.122749858174          10.6761861607241
          68.1971904149063          4.24311375007417
          82.5313795402046           8.3469814858914
           80.336439160244          6.04711791698936
          92.0332039836564          5.26769976807926

[Matlab111]

ya sir i'm getting, now i want to do multihop communication. which means, like this

in this diagram that read color line represent's finding the nearer cluster head by communicating through the neighborhood node. so now i want to find nearer cluster head through the nodes.Display which cluster head is nearer and display other cluster head and display through which node it's finding.

[Geoff Hayes]

Arul - please create a new question as what you are requesting (in your above comment) has nothing to do with the original question that began this thread.

[Matlab111]

k thanks

[Matlab111]

http://www.mathworks.in/matlabcentral/answers/153186#comment_235285 sir from your code i can get an cluster head and cluster head member. But i want to get their residual energy also ('energy'(S.E in my code)).For every node i want.(i need both cluster head and cluster member energy).

[Mark Neoglobal]

hello. i am using this code and need to display the number of packets received and sent by each cluster head. how is it possible. any help?