Mercurial > hg > jslab
diff src/samer/mds/CovarianceTask.java @ 0:bf79fb79ee13
Initial Mercurial check in.
author | samer |
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date | Tue, 17 Jan 2012 17:50:20 +0000 |
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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]))); + } + } +}