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just a stub for the householder stuff we did with keir yesterday...

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Benoit Jacob 2009-01-12 16:56:11 +00:00
parent 24fd14dab6
commit 38d916d50f
1 changed files with 32 additions and 0 deletions
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disabled/Householder.h Normal file
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#include<Eigen/Core>
using namespace Eigen;
/** From Golub & van Loan Algorithm 5.1.1 page 210
*/
template<typename InputVector, typename OutputVector>
void ei_compute_householder(const InputVector& x, OutputVector *v, typename OutputVector::RealScalar *beta)
{
EIGEN_STATIC_ASSERT(ei_is_same_type<typename InputVector::Scalar, typename OutputVector::Scalar>::ret,
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
EIGEN_STATIC_ASSERT((InputVector::SizeAtCompileTime == OutputVector::SizeAtCompileTime+1)
|| InputVector::SizeAtCompileTime == Dynamic
|| OutputVector::SizeAtCompileTime == Dynamic)
typedef typename OutputVector::RealScalar RealScalar;
ei_assert(x.size() == v->size()+1);
int n = x.size();
RealScalar sigma = x.end(n-1).squaredNorm();
*v = x.end(n-1);
// the big assumption in this code is that ei_abs2(x->coeff(0)) is not much smaller than sigma.
if(ei_isMuchSmallerThan(sigma, ei_abs2(x.coeff(0))))
{
// in this case x is approx colinear to (1,0,....,0)
// fixme, implement this trivial case
}
else
{
RealScalar mu = ei_sqrt(ei_abs2(x.coeff(0)) + sigma);
RealScalar kappa = -sigma/(x.coeff(0)+mu);
*beta =
}
}