Framework works properly now, but whitening still has a kink which is that the covariance matrix gets re-sorted automatically by the eigendecomposition, so somehow the association between eigenvalue and dimension (e.g. association track) needs to be maintained throughout.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@5530 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
parent
4c04c5a47a
commit
f3e4c24f63
|
|
@ -136,10 +136,12 @@ public class RegionalAssociationRecalibrator extends RodWalker<RegionalAssociati
|
|||
Arrays.sort(normRanks);
|
||||
for ( LocHashingPair lhp : normByLoc ) {
|
||||
int rank = Arrays.binarySearch(normRanks,lhp.second);
|
||||
// note - equal values will always be assigned the same rank -- however
|
||||
// it is proper, no need for random assignment.
|
||||
double prob = ((double) rank)/((double)normRanks.length);
|
||||
int qual = AssociationTestRunner.pToQ(prob);
|
||||
out.printf("%s\t%d\t%d\t%d\t%.2e\t%d",lhp.getFirst().getContig(),lhp.getFirst().getStart(),lhp.getFirst().getStop(),
|
||||
qual,prob,rank);
|
||||
out.printf("%s\t%d\t%d\t%d\t%.2e\t%d\t%.2e%n",lhp.getFirst().getContig(),lhp.getFirst().getStart(),lhp.getFirst().getStop(),
|
||||
qual,prob,rank,lhp.getSecond());
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue