function [c]=showclus(data,typevec,spflg);
[npts,nvar]=size(data);close all;
if spflg==1 % sphere data if flag set
    data=(data-ones(npts,1)*mean(data))./(ones(npts,1)*std(data));end;
% plot covariance plot

figure;gplotmatrix(data,data,typevec)
title('true definitions');

% cluster using Hierarchical clustering
distmetric='Euclidean';
linkmethod='average';
%distmetric,
c=1;
[z,t]=hierclus(data,distmetric,linkmethod);


figure;gplotmatrix(data,data,t)
title('Hierarchical Euclidean Average');

% cluster using single clustering
distmetric='Euclidean';
linkmethod='single';
%distmetric,
c=1;
[z,t]=hierclus(data,distmetric,linkmethod);


figure;gplotmatrix(data,data,t)
title('Hierarchical Euclidean Single Linkage');
% cluster using Hierarchical clustering, complete
distmetric='Euclidean';
linkmethod='complete';
%distmetric,
c=1;
[z,t]=hierclus(data,distmetric,linkmethod);


figure;gplotmatrix(data,data,t)
title('Hierarchical Euclidean Complete Linkage');

% cluster using Hierarchical clustering, different linkage method
distmetric='Euclidean';
linkmethod='ward';
%distmetric,
c=1;
[z,t]=hierclus(data,distmetric,linkmethod);


figure;gplotmatrix(data,data,t)
title('Hierarchical Euclidean ward');