package ca.pfv.spmf.test; import java.io.IOException; import java.io.UnsupportedEncodingException; import java.net.URL; import java.util.Arrays; import java.util.List; import ca.pfv.spmf.algorithms.clustering.dbscan.AlgoDBSCAN; import ca.pfv.spmf.algorithms.clustering.optics.AlgoOPTICS; import ca.pfv.spmf.algorithms.clustering.optics.DoubleArrayOPTICS; import ca.pfv.spmf.patterns.cluster.Cluster; import ca.pfv.spmf.patterns.cluster.DoubleArray; /** * Example of how to use the OPTICS algorithm from the source code to obtain the OPTICS cluster * ordering of points and keep the result in memory. */ public class MainTestOPTICS_extractClusterOrdering_saveToMemory { public static void main(String []args) throws NumberFormatException, IOException{ String input = fileToPath("inputDBScan.txt"); // we set the parameters of DBScan: int minPts=2; double epsilon = 20d; // We specify that in the input file, double values on each line are separated by spaces String separator = " "; // Apply the algorithm to compute a cluster ordering AlgoOPTICS algo = new AlgoOPTICS(); List<DoubleArrayOPTICS> clusterOrdering = algo.computerClusterOrdering(input, minPts, epsilon, separator); // Print the cluster-ordering of points to the console (for debugging) System.out.println("THE CLUSTER ORDERING:"); System.out.println(" [data point] - reachability distance"); for(DoubleArrayOPTICS arrayOP : clusterOrdering) { System.out.println(" " + Arrays.toString(arrayOP.data) + " - " + arrayOP.reachabilityDistance); } algo.printStatistics(); } public static String fileToPath(String filename) throws UnsupportedEncodingException{ URL url = MainTestOPTICS_extractClusterOrdering_saveToMemory.class.getResource(filename); return java.net.URLDecoder.decode(url.getPath(),"UTF-8"); } }