code_for_project.m

% This code is supplementary material for the project of the course
% "Clustering algorithms"
function [X,cl_label] = code_for_project()
%     clear
%     format compact
%     close all

    load Salinas_Data

    [p,n,l]=size(Salinas_Image); % Size of the Salinas cube

    % Depicting the bands of the Salinas cube
    % for i=1:l
    %     figure(1); imagesc(Salinas_Image(:,:,i))
    %     pause(0.1)
    % end

    % Making a two dimensional array whose rows correspond to the pixels and
    % the columns to the bands, containing only the pixels with nonzero label.
    X_total=reshape(Salinas_Image, p*n,l);
    L=reshape(Salinas_Labels,p*n,1);
    existed_L=(L>0);   %This contains 1 in the positions corresponding to pixels with known class label
    X=X_total(existed_L,:);
    [px,nx]=size(X); % px= no. of rows (pixels) and nx=no. of columns (bands)

    cl_label = L(existed_L);
    %...---> cl_label
    

    % The following code can be used after the execution of an algorithm 
    % Let "cl_label" be the px-dimensional vector, whose i-th element is the label
    % of the class where the i-th vector in X has been assigned
    % The code below, helps in depicting the results as an image again

%     cl_label_tot=zeros(p*n,1);
%     cl_label_tot(existed_L)=cl_label;
%     im_cl_label=reshape(cl_label_tot,p,n);
%     figure(10), imagesc(im_cl_label), axis equal
%     figure(11), imagesc(Salinas_Labels), axis equal
end