function pca3d( x, y, z )
% computes covariance matrix from the triples x, y, z
% diagonalizes covariance matrix, i.e. performs pca on [ x, y, z ]
% x, y and z are column vectors

    % covariance matrix:
    cv = cov( [ x y z ] );

    % eigen values:
    [ v , d] = eig( cv )

    % plots:
    subplot( 1, 2, 1 );
    hold on;

    % scatter plot:
    view( 3 );
scatter3( x, y, z ); % , 1.0, 'b', 'filled' ); %, 'MarkerEdgeColor', 'blue' );
    xlabel( 'x' );
    ylabel( 'y' );
    zlabel( 'z' );
    grid on;
    
    % plot eigenvectors:
    quiver3( ones( 1, 3 ).*mean( x ), ones( 1, 3 )*mean(y), ones( 1, 3 )*mean(z), v(1,:).*sqrt(diag(d))', v(2,:).*sqrt(diag(d))', v(3,:).*sqrt(diag(d))', 'r' ); %, 'LineWidth', 3, 'AutoScale', 'off', 'AutoScaleFactor', 1.0, 'MaxHeadSize', 0.7 )
    
    %axis( 'equal' );
    hold off;

    % 2D scatter plots:
    subplot( 2, 6, 4 );
    scatter( x, y, 'b', 'filled' ); %, 'MarkerEdgeColor', 'white' );
    xlabel( 'x' )
    ylabel( 'y' )
    subplot( 2, 6, 5 );
    scatter( x, z, 'b', 'filled' ); %, 'MarkerEdgeColor', 'white' );
    xlabel( 'x' )
    ylabel( 'z' )
    subplot( 2, 6, 6 );
    scatter( y, z, 'b', 'filled' ); %, 'MarkerEdgeColor', 'white' );
    xlabel( 'y' )
    ylabel( 'z' )

    % sort the eigenvalues:
    [d,inx] = sort( diag(d), 'descend' );
    
    subplot( 2, 2, 4 );
    hold on;
    % subtract means:
    x = x - mean( x );
    y = y - mean( y );
    % project onto eigenvectors:
    nx = [ x y z ] * v(:,inx);
    scatter( nx(:,1), nx(:,2), 'b', 'filled' ); %, 'MarkerEdgeColor', 'white' );
    xlabel( 'ex' )
    ylabel( 'ey' )
    axis( 'equal' );
    hold off;

end