changed file name

.classpath

@@ -0,0 +1,27 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<classpath>
+	<classpathentry kind="src" path="src/dev/java"/>
+	<classpathentry kind="src" path="src/main/java"/>
+	<classpathentry kind="lib" path="libs/colloquial.jar"/>
+	<classpathentry kind="lib" path="libs/commons-math3-3.0.jar"/>
+	<classpathentry kind="lib" path="libs/gs-algo-1.3.jar"/>
+	<classpathentry kind="lib" path="libs/gs-core-1.3.jar"/>
+	<classpathentry kind="lib" path="libs/gs-ui-1.3.jar"/>
+	<classpathentry kind="lib" path="libs/guava-18.0.jar"/>
+	<classpathentry kind="lib" path="libs/htsjdk-1.126.jar"/>
+	<classpathentry kind="lib" path="libs/jaligner.jar"/>
+	<classpathentry kind="lib" path="libs/javax.json-1.0.4.jar"/>
+	<classpathentry kind="lib" path="libs/javax.json-api-1.0.jar"/>
+	<classpathentry kind="lib" path="libs/jcommon-1.0.23.jar"/>
+	<classpathentry kind="lib" path="libs/jfreechart-1.0.19.jar"/>
+	<classpathentry kind="lib" path="libs/jfxrt.jar"/>
+	<classpathentry kind="lib" path="libs/jhdf5.jar"/>
+	<classpathentry kind="lib" path="libs/jhdfobj.jar"/>
+	<classpathentry kind="lib" path="libs/JRI.jar"/>
+	<classpathentry kind="lib" path="libs/JRIEngine.jar"/>
+	<classpathentry kind="lib" path="libs/REngine.jar"/>
+	<classpathentry kind="lib" path="libs/slf4j-api-1.7.25.jar"/>
+	<classpathentry kind="lib" path="libs/slf4j-simple-1.7.25.jar"/>
+	<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER"/>
+	<classpathentry kind="output" path="bin"/>
+</classpath>

.project

@@ -0,0 +1,17 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<projectDescription>
+	<name>japsa</name>
+	<comment></comment>
+	<projects>
+	</projects>
+	<buildSpec>
+		<buildCommand>
+			<name>org.eclipse.jdt.core.javabuilder</name>
+			<arguments>
+			</arguments>
+		</buildCommand>
+	</buildSpec>
+	<natures>
+		<nature>org.eclipse.jdt.core.javanature</nature>
+	</natures>
+</projectDescription>

bin/.gitignore

@@ -0,0 +1,2 @@
+/japsa/
+/japsadev/

src/dev/java/japsadev/bio/hts/clustering/KmeanClustering.java

@@ -15,7 +15,7 @@
 public class KmeanClustering {	
 	
 	public static void Clustering() throws Exception{
-		FileInputStream file1 = new FileInputStream("TRfile.fasta");
+		FileInputStream file1 = new FileInputStream("TRfiletemp.fasta");
 		BufferedReader br = new BufferedReader(new InputStreamReader(file1));
 		String line = null;
 		while((line = br.readLine())!=null){

src/dev/java/japsadev/bio/hts/clustering/KmeanClustering1.java

@@ -1,300 +0,0 @@
-package japsadev.bio.hts.clustering;
-
-import java.util.ArrayList;
-import java.io.*;
-
-import japsa.seq.SequenceOutputStream;
-import japsadev.bio.hts.clustering.PairDistance;
-import japsadev.bio.hts.clustering.GettingTreadsFromFasta;
-
-/**
- * @author buvan.suji
- *
- */
-
-public class KmeanClustering1 {	
-	
-	public static void Clustering() throws Exception{
-		FileInputStream file1 = new FileInputStream("TRfile1.fasta");
-		BufferedReader br = new BufferedReader(new InputStreamReader(file1));
-		String line = null;
-		while((line = br.readLine())!=null){
-			ArrayList<String> descript = new ArrayList<String>();
-			ArrayList<String> reads = new ArrayList<String>();
-			//ArrayList<Integer> MaxReadLn = new ArrayList<Integer>();
-			int MaxReadLn = 0;
-			int Nreads;
-			String FileName;
-			int NumberElements;
-			int ClustElements;
-			int n;	
-			int d[];
-			int k[][];
-			final int p =2;//number of clusters
-			int tempk[][];
-			int m[];
-			int Nclusters = 0;
-				
-			double max = 0;
-			double temp1 = 0;
-			int index1=0;
-			int index2=0;	
-			int count1=0,count2=0;
-			long startTime = System.nanoTime();
-			
-			
-			GettingTreadsFromFasta.DestReads(line);
-			//GettingTreadsFromFasta.DestReads();
-			descript = GettingTreadsFromFasta.GetRname();
-			reads = GettingTreadsFromFasta.GetTReads();
-			Nreads = GettingTreadsFromFasta.NumberReads();
-			FileName = GettingTreadsFromFasta.GetFileName();
-			NumberElements = GettingTreadsFromFasta.SeqLength();
-			ClustElements = GettingTreadsFromFasta.NelementsClustering();			
-			
-			double[][] table = new double[Nreads][Nreads];	
-			
-			for (int i=0; i<Nreads; ++i){
-				for(int j=0;j<Nreads;++j){
-					table[i][j]=0;
-				}
-			}
-
-			for (int i = 0; i < reads.size(); i++) {
-				int temp = 0;
-				for (int j = i + 1; j < reads.size(); j++) {				
-					String x = reads.get(i);
-					String y = reads.get(j);				
-					PairDistance.EditDistanceResult result = PairDistance.compute(x, y);
-					double normdist = ((double) result.getDistance())
-							/ Math.max(x.length(), y.length());				
-					table[i][j]=normdist; 
-					temp = x.length();
-				}
-				MaxReadLn = Math.max(MaxReadLn, temp);
-				
-			}
-			
-			n=Nreads;
-			d=new int[n];
-			
-			 //name of the reads		
-			for(int i=0;i<n;++i){
-				d[i]=i;
-			}	
-			
-			 //Initialising arrays 
-			k=new int[p][n];
-			tempk=new int[p][n];		
-			m=new int [p];
-				
-			
-			for (int i = 0; i < n; i++) {
-				for (int j = i + 1; j < n; j++) {
-					temp1 = table[i][j];
-					if(max < temp1){
-						max = temp1;
-						index1=i;
-						index2=j;
-					}
-				}
-			}			
-			
-			 //Initializing m 
-			m[0] = index1;
-			m[1] = index2;		
-			
-			int temp=0;
-			int flag=0;
-			
-			do{
-				for(int i=0;i<p;++i){
-					for(int j=0;j<n;++j){
-						k[i][j]=-1;					
-					}
-				}
-				
-				for(int i=0;i<n;++i){
-					temp=NewCluster(d[i], table, m);					
-					if(temp==0){
-						k[temp][count1++]=d[i];					
-					}
-					else if(temp==1){
-						k[temp][count2++]=d[i];					
-					}					 
-				}
-				
-				NewMean(table, m, n, k); // call to method which will calculate mean at this step.
-				flag = VerifyEqual(n, k, tempk); // check if terminating condition is satisfied.
-				if(flag!=1){
-					/*Take backup of k in tempk so that you can check for equivalence in next step*/
-					for(int i=0;i<p;++i){
-						for(int j=0;j<n;++j){
-							tempk[i][j]=k[i][j];
-						}
-					}				
-				}
-				
-				System.out.println("\nClusters Results:");
-				for(int i=0;i<p;++i){
-					System.out.print("C"+(i+1)+"{ ");
-					for(int j=0;k[i][j]!=-1 && j<n-1;++j)
-					System.out.print(k[i][j]+" ");
-					System.out.println("}");
-				}
-				//end of for loop
-				
-				System.out.println("\nCentroid of the clusters are: ");
-				for(int i=0;i<p;++i){
-					System.out.print("m"+(i+1)+"="+m[i]+"  ");
-				}
-				
-				
-				count1=0;count2=0;
-				Nclusters += 1;
-			}
-			while(flag==0);
-			long t = System.nanoTime()-startTime;
-			double estimateTime = (double)t/1000000000.0;
-			File file = new File("ClusterResult_"+FileName);
-			FileWriter fw = new FileWriter(file.getAbsoluteFile());
-			BufferedWriter bw = new BufferedWriter(fw);
-			
-			bw.write("Number of Reads: "+ Nreads);
-			bw.newLine();
-			bw.write("Maximum Read Length: "+ MaxReadLn);
-			bw.newLine();
-			bw.write("Number of Iterations: "+ Nclusters);		
-			bw.newLine();		
-			bw.write("Estimated Time: "+estimateTime+" s");
-			bw.newLine();			
-			bw.write("Two clusters elements are: ");
-			bw.newLine();
-			for(int i=0;i<p;++i){
-				String s = "C"+(i+1)+"{ ";
-				bw.write(s);
-				for(int j=0;k[i][j]!=-1 && j<n-1;++j){
-					bw.write(descript.get(k[i][j]));
-					bw.newLine();
-				}
-				bw.write("}");
-				bw.newLine();
-			}
-			bw.close();
-		}
-		br.close();
-		
-				
-	}
-	
-
-	
-	public static int NewCluster(int a, double list[][], int m[] ){ 		
-		
-		double diff[] = new double[2];
-			
-		for(int i=0;i<2;++i){
-			if(a<m[i]){
-				diff[i] = list[a][m[i]];
-			}
-			else if(a>m[i]){
-				diff[i] = list[m[i]][a];
-			}
-			else{
-				diff[i]=0;
-			}			
-		}
-		
-		int val=0;
-		double temp=diff[0];
-		for(int i=0;i<2;++i){
-			if(diff[i]<temp){
-				temp=diff[i];
-				val=i;
-			}
-			
-		}//end of for loop
-		
-		return val;
-	}
-	
-	static void NewMean(double list [][], int m[], int n, int k[][]){
-		ArrayList<Integer> t = new ArrayList<Integer>() ;
-		
-		for(int i=0;i<2;++i){
-			m[i]=0; // initializing means to 0			
-		}
-		
-		//int cnt=0;
-		for(int i=0;i<2;++i){			
-			
-			for(int j=0;j<n-1;++j){								
-				if(k[i][j]!=-1){
-					t.add(k[i][j]);
-				}
-			}
-				
-			ArrayList<Double> s = new ArrayList<Double>();				
-				
-			for(int x1 = 0; x1<t.size();++x1){
-				double sum = 0;					
-				for(int x2=0;x2<t.size();++x2){
-					if(t.get(x1)<t.get(x2)){
-						sum = sum+(list[t.get(x1)][t.get(x2)]*list[t.get(x1)][t.get(x2)]);
-					}
-					else if(t.get(x1)>t.get(x2)){
-						sum = sum+(list[t.get(x2)][t.get(x1)]*list[t.get(x2)][t.get(x1)]);
-					}
-					else{
-						sum = sum+0;
-					}	
-				}
-					//System.out.println(sum);					
-					s.add(sum/t.size());					
-			}
-			//System.out.println(s.size());
-			double min=s.get(0);	
-			int d2 = 0;
-			for(int x3=1;x3<s.size();++x3){					
-				if(min>s.get(x3)){
-					min = s.get(x3);
-					d2  = x3;
-				}					
-			}	
-				
-			
-			m[i]=t.get(d2);
-			s.clear();
-			t.clear();
-			
-		}
-	}
-
-//This checks if previous k ie. tempk and current k are same.Used as terminating case.
-	static int VerifyEqual(int n, int k[][], int tempk[][]){	
-		for(int i=0;i<2;++i){
-			for(int j=0;j<n;++j){
-				if(tempk[i][j]!=k[i][j]){
-					return 0;
-				}
-			}				
-		}		
-		return 1;
-	}	
-
-	public static void main(String[] args) throws Exception {
-		
-		// TODO Auto-generated method stub
-		Clustering();
-		// C:\Users\buvan.suji\workspace\Distance\SampleData\results\TR_Fasta\OutputReads\chr11119005_1121390.fasta
-		// C:\Users\buvan.suji\workspace\Distance\SampleData\results\TR_Fasta\OutputReads\chr1842862036_42864557.fasta
-		//C:/Users/Subashchandran/Marseclipse/workspace/Data/TrResults/Finished Cluster/chr11119005_1121390.fasta
-		//C:/Users/Subashchandran/Marseclipse/workspace/Data/TrResults/chr2440992_444078.fasta
-		//C:/Users/Subashchandran/Marseclipse/workspace/Data/TrResults/chr68826819_8829365.fasta
-		//C:/Users/Subashchandran/Marseclipse/workspace/Data/TrResults/FinishedCluster/chr11119005_1121390.fasta
-		//C:\Users\Subashchandran\Marseclipse\workspace\OldData\TrResults\Finished Cluster\chr11119005_1121390.fasta
-	}
-
-
-
-}