diff src/samer/mds/CovarianceTask.java @ 0:bf79fb79ee13

Initial Mercurial check in.
author samer
date Tue, 17 Jan 2012 17:50:20 +0000
parents
children
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/src/samer/mds/CovarianceTask.java	Tue Jan 17 17:50:20 2012 +0000
@@ -0,0 +1,44 @@
+package samer.mds;
+
+// import samer.core.*;
+import samer.maths.*;
+import samer.tools.*;
+
+/**
+	Transfer covariance matrix to MDS distances
+	Assumes that elements are not normalised to unit variance
+  */
+public class CovarianceTask extends AnonymousTask
+{
+	int		N;
+	double [] d;				// linear array of distances
+	double [][] _C;			// matrix of covariances
+	double [] var;			// array of variances
+		
+	/** link each object to all the others using distances in matrix, returns a task
+		that can be used to refresh distances from original matrix */
+	public CovarianceTask(MDSBase mds, Matrix C) {
+		N = C.getRowDimension();
+		
+		d=new double[N*(N - 1)/2];
+		var=new double[N];
+		_C=C.getArray();
+		
+		mds.clearLinks(d);
+		for (int k=0, i=0; i<N; i++) 
+			for (int j=0; j<i; j++) mds.setLink(k++,i,j);
+		
+		run();
+	}
+
+	public Vec getDistances() { return new Vec.ForArray(d); }
+	public void run() {
+		for (int i=0; i<N; i++) var[i]=_C[i][i];
+		for (int k=0, i=0; i<N; i++) {
+			double [] Ci=_C[i];
+			double vari=var[i];
+			for (int j=0; j<i; j++)
+				d[k++]=Math.sqrt(0.5*Math.log(vari*var[j]/(Ci[j]*Ci[j])));
+		}
+	}
+}