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    Metadata details:
    filename: calcdistancevector.m
    path of file: ./repos/mdtoolbox/mdtoolbox
    
    the code of the file until where you have to start completion: function distanceVector = calcdistancevector(trj)

    
function distanceVector = calcdistancevector(trj)
%% calcdistancevector
% calculate distance-matrix-based state-space vectors from trajectory
%
%% Syntax
%# distanceVector = calcdistancevector(trj)
% 
%% Description
% This code creates state-space vectors from trajectory. 
% The state-space vector is caculated from the distance matrix. 
% This code is often used with a subsequent dimensional reduction analysis
% (e.g., principal component analysis). 
%
% * trj            - trajectory
%                    [nframe x 3natom]
% * distanceVector - distance matrix vector
%                    [nframe x natom(natom-1)/2]
%
%% Example
%# trj = readdcd('bln.dcd');
%# distanceVector = calcdistancevector(trj);
%#
%# [Principal Component Analysis]
%# [pmode, p, variances, t] = princomp(distanceVector);
%# scatter(p(:,1), p(:,2), 10, 'filled'); xlabel('PC1', 'FontSize', 45); ylabel('PC2', 'FontSize', 45);
%#
%# [K-means Clustering]
%# indexOfCluster = kmeans(distanceVector, 3, 'distance', 'sqEuclidean', 'Replicates', 5);
%# scatter(p(:, 1), p(:, 2), 10, indexOfCluster, 'filled'); xlabel('PC1', 'FontSize', 45); ylabel('PC2', 'FontSize', 45);
%# colorbar % check color-cluster correspondence
%# crd = zeros(3, size(trj, 2));
%# for i = 1:3
%#   crd(i, :) = meanstructure(trj(indexOfCluster == i, :));
%# end