12 #ifndef LSST_IP_DIFFIM_KERNELSOLUTION_H 13 #define LSST_IP_DIFFIM_KERNELSOLUTION_H 51 bool fitForBackground);
57 virtual void solve(Eigen::MatrixXd
const& mMat,
58 Eigen::VectorXd
const& bVec);
63 inline Eigen::MatrixXd
const&
getM() {
return _mMat;}
64 inline Eigen::VectorXd
const&
getB() {
return _bVec;}
81 template <
typename InputT>
87 bool fitForBackground);
99 virtual double getBackground();
100 virtual double getKsum();
113 void _setKernelUncertainty();
117 template <
typename InputT>
123 bool fitForBackground);
128 const &varianceEstimate,
134 const &varianceEstimate,
140 const &varianceEstimate,
141 lsst::afw::geom::Box2I maskBox);
146 template <
typename InputT>
152 bool fitForBackground,
153 Eigen::MatrixXd
const& hMat,
159 double estimateRisk(
double maxCond);
162 Eigen::MatrixXd
getM(
bool includeHmat =
true);
165 Eigen::MatrixXd
const _hMat;
186 void addConstraint(
float xCenter,
float yCenter,
187 Eigen::MatrixXd
const& qMat,
188 Eigen::VectorXd
const& wVec);
197 bool _constantFirstTerm;
210 void _setKernelUncertainty();
std::shared_ptr< SpatialKernelSolution > Ptr
std::shared_ptr< RegularizedKernelSolution< InputT > > Ptr
Eigen::MatrixXd _cMat
K_i x R.
Eigen::VectorXd _bVec
Derived least squares B vector.
virtual ~SpatialKernelSolution()
KernelSolvedBy _solvedBy
Type of algorithm used to make solution.
double _background
Derived differential background estimate.
Eigen::VectorXd _iVec
Vectorized I.
lsst::afw::math::Kernel::Pixel PixelT
Eigen::VectorXd _ivVec
Inverse variance.
virtual ~RegularizedKernelSolution()
Eigen::VectorXd const & getB()
std::shared_ptr< StaticKernelSolution< InputT > > Ptr
static int _SolutionId
Unique identifier for solution.
bool _fitForBackground
Background terms included in fit.
lsst::afw::image::Image< lsst::afw::math::Kernel::Pixel > ImageT
virtual double getConditionNumber(ConditionNumberType conditionType)
int _id
Unique ID for object.
KernelSolvedBy getSolvedBy()
std::shared_ptr< KernelSolution > Ptr
Eigen::MatrixXd _mMat
Derived least squares M matrix.
double _kSum
Derived kernel sum.
virtual ~StaticKernelSolution()
Eigen::MatrixXd const & getM()
Eigen::VectorXd _aVec
Derived least squares solution matrix.
std::shared_ptr< lsst::afw::math::Kernel > _kernel
Derived single-object convolution kernel.
std::shared_ptr< MaskedKernelSolution< InputT > > Ptr
virtual ~KernelSolution()
virtual ~MaskedKernelSolution()