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massive documentation update

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This commit is contained in:
Johann Dreo 2012-07-19 17:23:41 +02:00
commit 7fed1ebf51
33 changed files with 399 additions and 181 deletions
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27
edo/src/edoEstimatorNormalAdaptive.h
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@ -40,17 +40,20 @@ Authors:
/** An estimator that works on adaptive normal distributions, basically the heart of the CMA-ES algorithm.
*
* @ingroup Estimators
* @ingroup CMAES
* @ingroup Adaptivenormal
*/
template< typename EOT, typename EOD = edoNormalAdaptive<EOT> >
class edoEstimatorNormalAdaptive : public edoEstimatorAdaptive< EOD >
template< typename EOT, typename D = edoNormalAdaptive<EOT> >
class edoEstimatorNormalAdaptive : public edoEstimatorAdaptive< D >
{
public:
typedef typename EOT::AtomType AtomType;
typedef typename EOD::Vector Vector; // column vectors @see edoNormalAdaptive
typedef typename EOD::Matrix Matrix;
typedef typename D::Vector Vector; // column vectors @see edoNormalAdaptive
typedef typename D::Matrix Matrix;
edoEstimatorNormalAdaptive( EOD& distrib ) :
edoEstimatorAdaptive<EOD>( distrib ),
edoEstimatorNormalAdaptive( D& distrib ) :
edoEstimatorAdaptive<D>( distrib ),
_calls(0),
_eigeneval(0)
{}
@ -133,7 +136,7 @@ public:
// shortcut to the referenced distribution
EOD& d = this->distribution();
D& d = this->distribution();
// C^-1/2
Matrix invsqrtC =
@ -226,12 +229,12 @@ public:
Eigen::SelfAdjointEigenSolver<Matrix> eigensolver( d.covar() ); // FIXME use JacobiSVD?
d.coord_sys( eigensolver.eigenvectors() );
Matrix D = eigensolver.eigenvalues().asDiagonal();
assert( D.innerSize() == N && D.outerSize() == N );
Matrix mD = eigensolver.eigenvalues().asDiagonal();
assert( mD.innerSize() == N && mD.outerSize() == N );
// from variance to standard deviations
D.cwiseSqrt();
d.scaling( D.diagonal() );
mD.cwiseSqrt();
d.scaling( mD.diagonal() );
}
return d;
@ -243,7 +246,7 @@ protected:
unsigned int _eigeneval;
// EOD & distribution() inherited from edoEstimatorAdaptive
// D & distribution() inherited from edoEstimatorAdaptive
};
#endif // WITH_EIGEN