function [data,vars,classes] = load_iris(do_preprocessing, do_column_ordering, do_zscore)
% LOAD_IRIS - Loads the iris dataset and applys some preprocessing if desired  
% 
% Written by:
% -- 
% John L. Weatherwax                2005-08-14
% 
% email: wax@alum.mit.edu
% 
% Please send comments and especially bug reports to the
% above email address.
% 
%-----

addpath( '../../Code/eda_data' );

load iris
data = [setosa; versicolor; virginica];
classes = [ 0*ones(size(setosa,1),1); 1*ones(size(versicolor,1),1); 2*ones(size(virginica,1),1) ]; 
vars = ['Sepal Length';
        'Sepal Width ';
        'Petal Length';
        'Petal Width '];

% n=number of samples=number of patients=72; 
% p=number of features=number of gene expressions=50
%
[n,p] = size(data);

if( do_preprocessing )
  % this data comes from a natural process ... might be gaussian ... apply the zscore transformation  
  f_mu = mean( data ); 
  f_sd = std( data ); 

  % lets sort the columns in decending order by the magnitude of the variance/standard deviation: 
  if( do_column_ordering ) 
    [f_sd_s,indx] = sort( f_sd ); f_sd_s = fliplr(f_sd_s); indx = fliplr(indx); 
  
    data = data(:,indx); 
    f_mu = f_mu(indx); 
    f_st = f_sd(indx); 
  end
    
  % compute the z-score of this data: 
  if( do_zscore )
    data_t = ( data - repmat( f_mu, [n,1] ) ) ./ repmat( f_sd, [n,1] ); 
    data = data_t; 
  end
  
end