Sequential Clustering Algorithm (BSCA)

I am currently trying to apply Sequential Clustering Algorithm (BSCA) to wine data. And for some reason I am unable to generate any clusters.

Below is my code where the data has first been reduced via PCA. and than BSCA is applied.

Does anyone see anything wrong with the code ?

%Reading in Data

Data = dlmread('wine.csv');

%Extracting data only

X = Data(2:179, 2:14);

%Calculating Eigenvalues and Eigenvectors

[EIGVEC, EIGVAL] = eig(cov(X));

%Reducing the data to 2D

XT = [];

for i=1: length(X)

XT(i,1) = X(i,:) * EIGVEC(:,13);

XT(i,2) = X(i,:) * EIGVEC(:,12);

end

%Prompt for alpha

%prompt2 = 'What is the value for alpha? ';

%alpha = input(prompt2);

function res = BSAS(XT,alpha,q)

N = size(XT,1);

nFeatures = size(XT,2);

labels = zeros(1,N); % zero value indicates unclustered point

m=1;

labels(1)=1;

q=3;

alpha=0.2;

function [d_x_i_C_k, k] = closestcluster(i, labels, XT)

ulab = unique(labels);

if( ulab(1)==0 )

ulab = ulab(2:end);%removes zero value as points are clustered

end

assignclust = [];

for lab = ulab

indv = find(labels==lab);

rep = mean(XT(indv,:), 1)';

d = sqrt(( XT(i,:)' - rep )' * ( XT(i,:)' - rep ) );

assignclust = [assignclust, d];

end

[d_x_i_C_k,mind] = min(assignclust);

k = ulab(mind);%closest cluster

end

for i = 2:N

%find C_k : d(x_i,C_k) = min_{1 <= j <= m} d(x_i,C_j)

[d_x_i_C_k, k] = closestcluster(i, labels, XT );

if((d_x_i_C_k > alpha) & (m < q))

m = m+1;

end

labels(i)=m;

end

res=labels

end