MnCovarianceSqueeze.cxx

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// @(#)root/minuit2:$Id: MnCovarianceSqueeze.cxx 20880 2007-11-19 11:23:41Z rdm $
// Authors: M. Winkler, F. James, L. Moneta, A. Zsenei   2003-2005  

/**********************************************************************
 *                                                                    *
 * Copyright (c) 2005 LCG ROOT Math team,  CERN/PH-SFT                *
 *                                                                    *
 **********************************************************************/

#include "Minuit2/MnCovarianceSqueeze.h"
#include "Minuit2/MnUserCovariance.h"
#include "Minuit2/MinimumError.h"

#if defined(DEBUG) || defined(WARNINGMSG)
#include "Minuit2/MnPrint.h" 
#endif


namespace ROOT {

   namespace Minuit2 {


MnUserCovariance MnCovarianceSqueeze::operator()(const MnUserCovariance& cov, unsigned int n) const {
   // squeeze MnUserCovariance class 
   // MnUserCovariance contasins the error matrix. Need to invert first to get the hessian, then 
   // after having squuezed the hessian, need to invert again to get the new error matrix
   assert(cov.Nrow() > 0);
   assert(n < cov.Nrow());
   
   MnAlgebraicSymMatrix hess(cov.Nrow());
   for(unsigned int i = 0; i < cov.Nrow(); i++) {
      for(unsigned int j = i; j < cov.Nrow(); j++) {
         hess(i,j) = cov(i,j);
      }
   }
   
   int ifail = Invert(hess);
   
   if(ifail != 0) {
#ifdef WARNINGMSG
      MN_INFO_MSG("MnUserCovariance inversion failed; return diagonal matrix;");
#endif
      MnUserCovariance result(cov.Nrow() - 1);
      for(unsigned int i = 0, j =0; i < cov.Nrow(); i++) {
         if(i == n) continue;
         result(j,j) = cov(i,i);
         j++;
      }
      return result;
   }
   
   MnAlgebraicSymMatrix squeezed = (*this)(hess, n);
   
   ifail = Invert(squeezed);
   if(ifail != 0) {
#ifdef WARNINGMSG
      MN_INFO_MSG("MnUserCovariance back-inversion failed; return diagonal matrix;");
#endif
      MnUserCovariance result(squeezed.Nrow());
      for(unsigned int i = 0; i < squeezed.Nrow(); i++) {
         result(i,i) = 1./squeezed(i,i);
      }
      return result;
   }
   
   return MnUserCovariance(std::vector<double>(squeezed.Data(), squeezed.Data() + squeezed.size()), squeezed.Nrow());
}

MinimumError MnCovarianceSqueeze::operator()(const MinimumError& err, unsigned int n) const {
   // squueze the minimum error class
   // Remove index-row on the Hessian matrix and the get the new correct error matrix 
   // (inverse of new Hessian)
   MnAlgebraicSymMatrix hess = err.Hessian();
   MnAlgebraicSymMatrix squeezed = (*this)(hess, n);
   int ifail = Invert(squeezed);
   if(ifail != 0) {
#ifdef WARNINGMSG
      MN_INFO_MSG("MnCovarianceSqueeze: MinimumError inversion fails; return diagonal matrix.");
#endif
      MnAlgebraicSymMatrix tmp(squeezed.Nrow());
      for(unsigned int i = 0; i < squeezed.Nrow(); i++) {
         tmp(i,i) = 1./squeezed(i,i);
      }
      return MinimumError(tmp, MinimumError::MnInvertFailed());
   }
   
   return MinimumError(squeezed, err.Dcovar());
}

MnAlgebraicSymMatrix MnCovarianceSqueeze::operator()(const MnAlgebraicSymMatrix& hess, unsigned int n) const {
   // squueze a symmetrix matrix (remove entire row and column n)
   assert(hess.Nrow() > 0);
   assert(n < hess.Nrow());
   
   MnAlgebraicSymMatrix hs(hess.Nrow() - 1);
   for(unsigned int i = 0, j = 0; i < hess.Nrow(); i++) {
      if(i == n) continue;
      for(unsigned int k = i, l = j; k < hess.Nrow(); k++) {
         if(k == n) continue;
         hs(j,l) = hess(i,k);
         l++;
      }
      j++;
   }
   
   return hs;
}

   }  // namespace Minuit2

}  // namespace ROOT

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