Clustering rows and columns

For the purposes of visualizing the data matrix, it is often desirable to have the rows and columns reordered to put similar rows adjacent to one another, and similarly to place similar columns adjacent to one another. This reordering can be done using hierarchical linkage clustering, by the function TS_cluster:

distanceMetricRow = 'euclidean'; % time-series feature distance
linkageMethodRow = 'average'; % linkage method
distanceMetricCol = 'corr_fast'; % a (poor) approximation of correlations with NaNs
linkageMethodCol = 'average'; % linkage method
​
TS_cluster(distanceMetricRow, linkageMethodRow, distanceMetricCol, linkageMethodCol);

This function reads in the data from HCTSA_N.mat, and stores the re-ordering of rows and columns back into HCTSA_N.mat in the ts_clust and op_clust (and, if the size is manageable, also the pairwise distance information). Visualization functions (such as TS_plot_DataMatrix and TS_SimSearch) can then take advantage of this information, using the general input label 'cl'.