Global running parameter file added along with setup function

SS_Clustering_main.m

@@ -1,16 +1,15 @@
 % If your code hangs in SS_NormaliseAndFilter remove '-append' from save 
 % command on line 150 in TS_local_clear_remove 
 
-% Load your data matrix then normalise and filter it
-SS_NormaliseAndFilter('HCTSA_Empirical1000_Aug2015');
+% Set up default run info file
+SS_SetupRunInfo;
 
-% % If you have filtered normalised data already
-% load('HCTSA_Empirical1000_Aug2015_N_filtered.mat');
-% save('HCTSA_N.mat');
+% Load your data matrix then normalise and filter it
+SS_NormaliseAndFilter;
 
 % Enter values of K you want to calculate 
 % NB: The largest value of K will automatically be used for the linkage clustering etc
-SS_ClusterKMedoids([3,5,10,20]);
+SS_ClusterKMedoids;
 
 % Calculates residual variance for above clusters 
 SS_ResidVariance;
@@ -25,7 +24,7 @@
 SS_CorrOpsWithClusters;
 
 % Output final clusters to a text file
-SS_OutputBestOpsTxtFile('cluster_info.txt');
+SS_OutputBestOpsTxtFile;
 
 % Cluster the time series in the reduced operation space to visualise
 % effectiveness of selected operations 

SS_SetupRunInfo.m

@@ -0,0 +1,37 @@
+function SS_SetupRunInfo( ks , kToUse , op_km_repeats , ts_km_repeats , ...
+    inMatFileName , outTxtFileName , corr_dist_threshold)
+
+if nargin < 1
+    ks = [5,7,10,20:20:100,200,500,1000];
+end
+if nargin < 2
+    kToUse = 40;
+end
+if nargin < 3
+    op_km_repeats = 50;
+end
+if nargin < 4
+    ts_km_repeats = 500;
+end
+if nargin < 5
+    inMatFileName = 'HCTSA_new_data';
+end
+if nargin < 6
+    outTxtFileName = 'cluster_info.txt';
+end
+if nargin < 7
+    corr_dist_threshold = 0.2;
+end
+
+kIdx = find(ks == kToUse);
+if isempty(kIdx)
+    fprintf('Could not find K = %i in ks - setting kToUse to %i',...
+        kToUse , ks(length(ks)));
+    kIdx = length(ks); 
+end
+
+save('run_options.mat','ks','kIdx','op_km_repeats','ts_km_repeats',...
+    'inMatFileName','outTxtFileName','corr_dist_threshold');
+
+end
+