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");
}
}