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  1. # Single linkage hirerarichal Algorithm
  2.  
  3. %Cluster reads data from a file called data.dat.  It will arbitrarily
  4. %choose one point to be a hub and cluster all the points around this hub.
  5. %It then finds the point farthest away from the hub and makes this point a
  6. %new hub. Next it clusters the data around the hub it is nearest. This
  7. %process is repeated  until the distance from every point to its hub is
  8. %less than half the average distance between all pairs of hubs.
  9.  
  10. load data.dat;
  11. graph_data;            %Plots original points
  12. [clusters,dist,hubs] = setup(data);  %Clusters all points around first point
  13.  
  14. counter =1;             %Keeps track of number of the present number of hubs
  15. continue = 1;   % 1=true 0=false indicates whether to continue forming new
  16.                 %hubs
  17.  
  18.     while continue
  19.         counter = counter + 1;    % adding new hub
  20.         [m,i]=max(dist);        %m= maximum value in the distance array
  21.                                %i is the location of the maximum value in the
  22.                                 % array
  23.         hubs(counter)=i;        %assigns index to new hub
  24.  
  25.         [dist,clusters] = recluster(data,dist,clusters,i);  %Clusters points
  26.                                                            %to nearest hub
  27.         pause
  28.         redraw                  %Draws new clusters
  29.         maxdist=max(dist);      %returns distance of point farthest from its hub
  30.         continue = farout(counter,hubs,data,maxdist); %Checks the stop condition
  31.  
  32.     end
  33.  
  34. %Set up function.
  35.  
  36.     function [clusters,dist,hubs]=setup(data)
  37.  
  38. %SETUP  [clusters,dist,hubs]=setup(data)
  39. %       This function  assigns to the cluster array all ones, (telling that
  40. %       all points belong to Hub 1), assigns to the hub array a one in
  41. %       position 1 (telling that the first hub is point 1) and zeros in all
  42. %       other locations. The distance array contains the square of the
  43. %       distance from each point to hub one.
  44.  
  45. n=size(data,1);
  46. clusters=ones(n,1);
  47. hubs=zeros(n,1);
  48. hubs(1,1)=1;
  49.  
  50. dist = distance(data,clusters);
  51.  
  52. end
  53.  
  54. %distance function.
  55.  
  56. function dist=distance(d,c)
  57.  
  58. %DIST   Distance from hub  dist=distance(d,c)
  59. %       This finds the square of the distance between each point and its hub
  60. %       d = data coordinates of points; c = cluster array contains index of
  61. %       hub to which point is assigned; c(i)=j point i belongs to the cluster
  62. %       whose hub is point j
  63.  
  64. n = size(d,1);
  65.  
  66.   for i = 1:n
  67.  
  68.       dif(i,:)= d(c(i),:) - d(i,:);
  69.  
  70.   end
  71.  
  72. dist =( sum((dif.*dif)'))';     %sums the squares of the row elements
  73.  
  74. end
  75.  
  76. %Far out function
  77.  
  78. function continue = farout(counter,hubs,data,maxdist)
  79.  
  80. %FAROUT continue = farout(counter,hubs,data,maxdist)
  81. %       Calculates stop condition.  Stops if the point farthest from its
  82. %       hub is within the average distance value.
  83.  
  84. index = 0;
  85.  
  86.  
  87.     for i = 1:(counter-1)
  88.         for j = i+1 : counter
  89.             index = index + 1;
  90.             dif(index,:)=data(hubs(i),:) - data(hubs(j),:);
  91.         end
  92.     end
  93.  
  94. dist=sqrt((sum((dif.*dif)'))');
  95. average_dist = sum(dist)/(2*index);
  96.   if sqrt(maxdist) < average_dist
  97.         continue = 0;
  98.         else continue =1;
  99.   end
  100. end                             % end for farout
  101.  
  102. %Graph_data plots the points and draws the axes
  103.  
  104. x = data(:,1);
  105. y = data(:,2);
  106. minx = min(x);
  107. maxx = max(x);
  108. miny = min(y);
  109. maxy = max(y);
  110. plot(x,y,'*')
  111. axis([minx-1, maxx+1, miny - 1, maxy + 1]);
  112.  
  113.  
  114. % Redraw draws the points so that each cluster is a different color.
  115. % The hubs are represented by a + and the members are represented by a *.
  116.  
  117. n = size(data,1);
  118. pointer = zeros(n, 1);
  119. for i=1:counter
  120.    pointer(hubs(i))=i;   % Pointer's indices are the data point indices
  121.                          % Pointer's cells are the hub numbers for the points
  122. end;
  123. hold off;
  124.  
  125. % Color code the points based on the cluster number
  126.  
  127. for i = 1:n
  128.    x = data(i,1);
  129.    y = data(i,2);
  130.    if pointer(clusters(i)) == 1
  131.       if clusters(i) == i
  132.          plot(x, y, 'y+');
  133.       else
  134.          plot(x, y, 'y*');
  135.       end
  136.       hold on;
  137.    elseif pointer(clusters(i)) == 2
  138.       if clusters(i) == i
  139.          plot(x, y, 'm+');
  140.       else
  141.          plot(x, y, 'm*');
  142.       end
  143.       hold on;
  144.  
  145.    elseif pointer(clusters(i)) == 3
  146.       if clusters(i) == i
  147.          plot(x, y, 'c+');
  148.       else
  149.          plot(x, y, 'c*');
  150.       end
  151.       hold on
  152.    elseif pointer(clusters(i)) == 4
  153.       if clusters(i) == i
  154.          plot(x, y, 'r+');
  155.      else
  156.          plot(x, y, 'r*');
  157.       end
  158.       hold on
  159.    elseif pointer(clusters(i)) == 5
  160.       if clusters(i) == i
  161.          plot(x, y, 'g+');
  162.       else
  163.          plot(x, y, 'g*');
  164.       end
  165.       hold on
  166.    elseif pointer(clusters(i)) == 6
  167.       if clusters(i) == i
  168.          plot(x, y, 'b+');
  169.       else
  170.          plot(x, y, 'b*');
  171.       end
  172.       hold on
  173.    else
  174.       if clusters(i) == i
  175.          plot(x, y, 'w+');
  176.       else
  177.          plot(x, y, 'w*');
  178.       end
  179.       hold on
  180.    end
  181. end
  182.  
  183. % Sets up the axes
  184.  
  185. x = data(:,1);
  186. y = data(:,2);
  187. minx = min(x);
  188. maxx = max(x);
  189. miny = min(y);
  190. maxy = max(y);
  191. axis([minx-1, maxx+1, miny - 1, maxy + 1]);
  192.  
Success #stdin #stdout #stderr 0.17s 65048KB
comments (?)
stdin 
Standard input is empty
stdout 
Standard output is empty
stderr 
error: load: unable to find file data.dat
https://ideone.com/LKN23E
language:
Octave (octave 4.4.1)
created:
10 years ago
visibility:
public

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