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Replace the qr factorization from (c)minpack (qrfac) by Eigen's own stuff.

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Results as checked by unit tests are very slightly worse, but not much.
This commit is contained in:
Thomas Capricelli
2010-01-25 07:22:28 +01:00
parent 1cb0be05b0
commit ee0e39284c
5 changed files with 71 additions and 134 deletions
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30
unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
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@@ -218,7 +218,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(
const int mode
)
{
int i, j, l, iwa[1];
int i, j, l;
jeval = true;
/* calculate the jacobian matrix. */
@@ -249,7 +249,13 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(
}
/* compute the qr factorization of the jacobian. */
ei_qrfac<Scalar>(n, n, fjac.data(), fjac.rows(), false, iwa, wa1.data());
wa2 = fjac.colwise().blueNorm();
HouseholderQR<JacobianType> qrfac(fjac); // no pivoting:
fjac = qrfac.matrixQR();
wa1 = fjac.diagonal();
fjac.diagonal() = qrfac.hCoeffs();
// TODO : avoid this:
for(int ii=0; ii< fjac.cols(); ii++) fjac.col(ii).segment(ii+1, fjac.rows()-ii-1) *= fjac(ii,ii); // rescale vectors
/* form (q transpose)*fvec and store in qtf. */
@@ -280,6 +286,11 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(
/* accumulate the orthogonal factor in fjac. */
ei_qform<Scalar>(n, n, fjac.data(), fjac.rows(), wa1.data());
#if 0
std::cout << "ei_qform<Scalar>: " << fjac << std::endl;
fjac = qrfac.matrixQ();
std::cout << "qrfac.matrixQ():" << fjac << std::endl;
#endif
/* rescale if necessary. */
@@ -530,7 +541,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(
const int mode
)
{
int i, j, l, iwa[1];
int i, j, l;
jeval = true;
if (parameters.nb_of_subdiagonals<0) parameters.nb_of_subdiagonals= n-1;
if (parameters.nb_of_superdiagonals<0) parameters.nb_of_superdiagonals= n-1;
@@ -563,7 +574,13 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(
}
/* compute the qr factorization of the jacobian. */
ei_qrfac<Scalar>(n, n, fjac.data(), fjac.rows(), false, iwa, wa1.data());
wa2 = fjac.colwise().blueNorm();
HouseholderQR<JacobianType> qrfac(fjac); // no pivoting:
fjac = qrfac.matrixQR();
wa1 = fjac.diagonal();
fjac.diagonal() = qrfac.hCoeffs();
// TODO : avoid this:
for(int ii=0; ii< fjac.cols(); ii++) fjac.col(ii).segment(ii+1, fjac.rows()-ii-1) *= fjac(ii,ii); // rescale vectors
/* form (q transpose)*fvec and store in qtf. */
@@ -594,6 +611,11 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(
/* accumulate the orthogonal factor in fjac. */
ei_qform<Scalar>(n, n, fjac.data(), fjac.rows(), wa1.data());
#if 0
std::cout << "ei_qform<Scalar>: " << fjac << std::endl;
fjac = qrfac.matrixQ();
std::cout << "qrfac.matrixQ():" << fjac << std::endl;
#endif
/* rescale if necessary. */