DBSCAN.rar_DBSCAN_DBSCAN in java_DBScan java_dbscan java_dbscan

package xmu.hll.Models.Clustering.CDBased.Algorithms.DBSCAN; import java.util.ArrayList; import java.util.Collections; import java.util.Vector; import com.prudsys.pdm.Core.MiningException; import com.prudsys.pdm.Input.MiningVector; import com.prudsys.pdm.Models.Clustering.Cluster; import com.prudsys.pdm.Models.Clustering.CDBased.CDBasedClusteringAlgorithm; import xmu.hll.Models.Clustering.CDBased.Algorithms.DBSCAN.DataPoint; public class DBSCAN extends CDBasedClusteringAlgorithm { //初始时获得的数据--------------------------------------------------------------- private int eps; //半径 private int minPoints; //最少的点的数目 private int numAtt; //属性的个数 private int m_Core_Num; //核心点的数目 private int m_MinPts; //最少的点的数目 private int m_Cluster_Num; //簇的数目 private double m_eps; //半径 public ArrayList m_cluster; public ArrayList temp = new ArrayList(128);//临时存放同一簇点的ArrayList public ArrayList dataPoints = new ArrayList(128); //初始数据的ArrayList private ArrayList dp2dp; public DBSCAN() {} //添加数据点到簇 // public void AddDataPoint(DataPoint dp) { // dataPoints.add(dp); // m_Core_Num = 0; // m_MinPts = 0; // m_eps = 0; // } //移除簇中的数据点 public void RemoveAllDataPoints() { dataPoints.clear(); m_Core_Num = 0; m_MinPts = 0; m_eps = 0; } //重置所有的数据点的状态 public void ResetAllDataPointsState() { DataPoint dp; for(int i = 0; i < dataPoints.size(); i++) { dp = (DataPoint) dataPoints.get(i); dp.class_id = 0; //簇的id dp.core_tag = false; //是否是核心点 dp.used_tag = false; //是否已经使用 } } @SuppressWarnings("unchecked") public void PrepareDBSCAN_Table() { int dp_count = dataPoints.size(); //数据的数目 //初始化dp2dp，并向dp2dp中加入一个长度为数据数目的ArrayList dp2dp = new ArrayList(dp_count); for(int i=0;i<dp_count;i++) { dp2dp.add(new ArrayList(dp_count)); } ArrayList tempList; //临时的ArrayList，用于保存一次比较距离的排序结果 for(int i = 0; i < dp_count; i++) { tempList = (ArrayList) dp2dp.get(i); DataPoint dp1 = (DataPoint) dataPoints.get(i); for(int j = 0; j < dp_count; j++) { DataPoint dp2 = (DataPoint) dataPoints.get(j); dp2.Distance(dp1); //改变dp2的distance属性的值 tempList.add(dataPoints.get(j)); } Collections.sort(tempList,new DBSCANSort()); dp2dp.set(i,tempList); } //------------------------测试dp2dp // for(int a = 0; a < dp2dp.size(); a++) { // ArrayList list = (ArrayList) dp2dp.get(a); // String s = ""; // // for(int b = 0; b < list.size(); b++) { // DataPoint d = (DataPoint) list.get(b); // s += d.d1+","+d.d2+" "; // } // JOptionPane.showMessageDialog(null, s); // } } //建立核心点 public int BuildCorePoint(double eps, int minPts) { ResetAllDataPointsState(); //重置所有点的状态 int core_num = 0; //核心点的数目 DataPoint src_dp, des_dp; for(int i = 0; i < dataPoints.size(); i++) { ArrayList tempList =(ArrayList) dp2dp.get(i); des_dp = (DataPoint) tempList.get(minPts); src_dp = (DataPoint) dataPoints.get(i); if(src_dp.Distance(des_dp) <= eps) { src_dp.core_tag = true; core_num++; } } if(core_num > 0) { m_Core_Num = core_num; m_MinPts = minPts; m_eps = eps; } return core_num; } @SuppressWarnings("unchecked") public void DBSCAN_Cluster() { DataPoint dp; int current_class_id = 0; m_cluster = new ArrayList(128); for(int i = 0; i < 128; i++) { m_cluster.add(new ArrayList(128)); } for(int i = 0; i < dataPoints.size(); i++) { dp=(DataPoint)dataPoints.get(i); if(dp.core_tag == true && dp.used_tag == false) { dp.class_id = current_class_id + 1; dp.used_tag = true; CorePointCluster(i, current_class_id + 1); temp.add(dp); m_cluster.set(current_class_id, temp); current_class_id++; } } m_Cluster_Num = current_class_id; for(int i = 0; i < dataPoints.size(); i++){ dp = (DataPoint) dataPoints.get(i); if(dp.class_id == 0){ ArrayList temp1 = new ArrayList(); temp1.add(dp); m_cluster.set(m_Cluster_Num, temp1); m_Cluster_Num++; } } } @SuppressWarnings("unchecked") private void CorePointCluster(int dp_pos, int core_class_id) { DataPoint src_dp, des_dp; ArrayList sl=(ArrayList) dp2dp.get(dp_pos); src_dp=(DataPoint)sl.get(0); int i=1; des_dp=(DataPoint)sl.get(i); while(src_dp.Distance(des_dp) <= m_eps) { if(des_dp.used_tag == false) { des_dp.class_id = core_class_id; des_dp.used_tag = true; temp.add(des_dp); if(des_dp.core_tag == true) { CorePointCluster(dataPoints.indexOf(des_dp),core_class_id); } } i++; try { des_dp=(DataPoint)sl.get(i); } catch( IndexOutOfBoundsException e ) { // To avoid eps is too large that out of index return; } } } @SuppressWarnings("unchecked") @Override protected void runAlgorithm() throws MiningException { //获取所有的属性 numAtt = metaData.getAttributesNumber(); ResetAllDataPointsState(); RemoveAllDataPoints(); //获取所有的数据点，并添加到dataPoints while (miningInputStream.next()) { DataPoint dp = new DataPoint(miningInputStream.readAttributeValue(1), miningInputStream.readAttributeValue(2)); dataPoints.add(dp); } PrepareDBSCAN_Table(); BuildCorePoint(getEps(), getMinPoints()); DBSCAN_Cluster(); //实例化clusters，并设置每一簇的名字 clusters = new Cluster[m_Cluster_Num]; for(int i = 0; i < m_Cluster_Num; i++) { clusters[i] = new Cluster(); clusters[i].setName("clust" + i); } //设置核心点--------------------------------------------------------------------- for(int a = 0; a < m_Cluster_Num; a++) { ArrayList list = (ArrayList) m_cluster.get(a); double value[] = new double[numAtt]; MiningVector centerVec = new MiningVector(value); centerVec.setMetaData(metaData); if(list.size()>1) { for(int b = 0; b < list.size(); b++) { DataPoint d = (DataPoint) list.get(b); if(d.core_tag) { centerVec.setValue(1, d.d1); centerVec.setValue(2, d.d2); } } } else { DataPoint d = (DataPoint) list.get(0); centerVec.setValue(1, d.d1); centerVec.setValue(2, d.d2); } clusters[a].setCenterVec(centerVec); } //设置每一簇的点--------------------------------------------------------------------- Vector allContainedVectors[] = new Vector[m_Cluster_Num]; for(int i = 0; i < m_Cluster_Num; i++) { allContainedVectors[i] = new Vector(); } for(int a = 0; a < m_Cluster_Num; a++) { ArrayList list = (ArrayList) m_cluster.get(a); for(int b = 0; b < list.size(); b++) { double value[] = new double[numAtt]; MiningVector centerVec = new MiningVector(value); centerVec.setMetaData(metaData); DataPoint d = (DataPoint) list.get(b); centerVec.setValue(1, d.d1); centerVec.setValue(2, d.d2); allContainedVectors[a].add(b, centerVec); } } for(int i = 0; i < m_Cluster_Num; i++) { clusters[i].setContainedVectors(allContainedVectors[i]); } } public int getEps() { return eps; } public void setEps(int eps) { this.eps = eps; } public int getMinPoints() { return minPoints; } public void setMinPoints(int minPoints) { this.minPoints = minPoints; } }