Predicting Mortality of ICU Patients: The PhysioNet/Computing in Cardiology Challenge 2012 1.0.0

function plot_means(MEAN_DATA_ALL,DATA,IHD,ALL_CATEGORIES)

    num_params=size(MEAN_DATA_ALL,2);

    for param_idx=1:num_params
        mean_all=MEAN_DATA_ALL(:,param_idx);
        mean_1=MEAN_DATA_ALL(IHD==1,param_idx);
        mean_0=MEAN_DATA_ALL(IHD==0,param_idx);
        
        
        isnan1=sum(~isnan(MEAN_DATA_ALL(IHD==1,param_idx)))/(sum(IHD==1));
        isnan0=sum(~isnan(MEAN_DATA_ALL(IHD==0,param_idx)))/(sum(IHD==0));
        
        M1 = mode(mean_1);
        M0 = mode(mean_0);
        
%         figure(param_idx)
%         
%         subplot(1,3,1)
%         hist(mean_all)
%         title([ALL_CATEGORIES{param_idx} ' all'])
%         
%         
%         subplot(1,3,2)
%         hist(mean_1)   
%         title([ALL_CATEGORIES{param_idx} ' 1'])
%        
%         
%         subplot(1,3,3)
%         hist(mean_0)    
%         title([ALL_CATEGORIES{param_idx} ' 0'])
        
%         figure(param_idx+num_params+5)
%         hist(mean_1,20)
%         h = findobj(gca,'Type','patch');
%         set(h,'FaceColor','r','EdgeColor','w','facealpha',0.75)
%         hold on;
%         hist(mean_0,20)
%         h1 = findobj(gca,'Type','patch');
%         set(h1,'facealpha',0.75);
%         title([ALL_CATEGORIES{param_idx} ' mode0=' num2str(M0) '. '  ' mode1=' num2str(M1)]);
% 
%      
        
        figure(param_idx+num_params+5)
         title([ALL_CATEGORIES{param_idx} ' mode0=' num2str(M0) '. '  ' mode1= ' num2str(M1) '. isnan0= ' num2str(isnan0)  '. isnan1= ' num2str(isnan1)]);

        subplot(1,2,1)
        [N, X] =  hist(mean_1,25);
        bar(X, N./sum(N), 1);
        h = findobj(gca,'Type','patch');
        set(h,'FaceColor','r','EdgeColor','w','facealpha',0.75)
        hold on;
        [N, X] =  hist(mean_0, X);
        bar(X, N./sum(N), 1);
        h1 = findobj(gca,'Type','patch');
        set(h1,'facealpha',0.75);
        title([ALL_CATEGORIES{param_idx} ' mode0=' num2str(M0) '. '  ' mode1= ' num2str(M1) '. isnan0= ' num2str(isnan0)  '. isnan1= ' num2str(isnan1)]);

        
        subplot(1,2,2)
        
        scatter(mean_1,ones(size(mean_1)),'xr')
        mean1=mean(mean_1(~isnan(mean_1)));
       % vari=var(mean_1(~isnan(mean_1)));
        medi=median(mean_1(~isnan(mean_1)));
        line([mean1 mean1],[1 0.5],'Color','r')
        
        line([medi medi],[1 0.5],'Color','r','LineStyle','--')
        
        hold on
        scatter(mean_0,zeros(size(mean_0)),'ob')
        mean0=mean(mean_0(~isnan(mean_0)));
        %vari=var(mean_0(~isnan(mean_0)));
         medi=median(mean_0(~isnan(mean_0)));
        line([mean0 mean0],[0 0.5],'Color','b')
        line([medi medi],[0 0.5],'Color','r','LineStyle','--')
        title([ALL_CATEGORIES{param_idx} ' mode0=' num2str(M0) '. '  ' mode1= ' num2str(M1) '. isnan0= ' num2str(isnan0)  '. isnan1= ' num2str(isnan1)]);

        
        

        
     
        
        
        
        
        
%         data = rand(1, 100);
% [N, X] = hist(data, 0:0.1:1);
% 
% subplot(2, 1, 1);
% hist(data, 0:0.1:1);
% 
% subplot(2, 1, 2);
% bar(X, N./sum(N), 1);
        
    end




end