File KernelSolution.h¶
Declaration of classes to store the solution for convolution kernels.
- Author
Andrew Becker, University of Washington
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namespace
lsst Class for a simple mapping implementing a generic AstrometryTransform.
Remove all non-astronomical counts from the Chunk Exposure’s pixels.
Forward declarations for lsst::utils::Cache
For details on the Cache class, see the Cache.h file.
It uses a template rather than a pointer so that the derived classes can use the specifics of the transform. The class simplePolyMapping overloads a few routines.
A base class for image defects
Numeric constants used by the Integrate.h integrator routines.
Compute Image Statistics
- Note
Gauss-Kronrod-Patterson quadrature coefficients for use in quadpack routine qng. These coefficients were calculated with 101 decimal digit arithmetic by L. W. Fullerton, Bell Labs, Nov 1981.
- Note
The Statistics class itself can only handle lsst::afw::image::MaskedImage() types. The philosophy has been to handle other types by making them look like lsst::afw::image::MaskedImage() and reusing that code. Users should have no need to instantiate a Statistics object directly, but should use the overloaded makeStatistics() factory functions.
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namespace
ip -
namespace
diffim -
class
KernelSolution Subclassed by lsst::ip::diffim::SpatialKernelSolution, lsst::ip::diffim::StaticKernelSolution< InputT >
Public Types
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enum
KernelSolvedBy¶ Values:
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NONE= 0¶
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CHOLESKY_LDLT= 1¶
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CHOLESKY_LLT= 2¶
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LU= 3¶
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EIGENVECTOR= 4¶
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typedef std::shared_ptr<KernelSolution>
Ptr
Public Functions
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KernelSolution(Eigen::MatrixXd mMat, Eigen::VectorXd bVec, bool fitForBackground)
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KernelSolution(bool fitForBackground)
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KernelSolution()
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virtual
~KernelSolution()
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virtual void
solve()
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virtual void
solve(Eigen::MatrixXd const &mMat, Eigen::VectorXd const &bVec)
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KernelSolvedBy
getSolvedBy()
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virtual double
getConditionNumber(ConditionNumberType conditionType)
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virtual double
getConditionNumber(Eigen::MatrixXd const &mMat, ConditionNumberType conditionType)
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Eigen::MatrixXd const &
getM()
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Eigen::VectorXd const &
getB()
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void
printM()
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void
printB()
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void
printA()
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int
getId() const
Protected Attributes
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int
_id Unique ID for object.
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Eigen::MatrixXd
_mMat Derived least squares M matrix.
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Eigen::VectorXd
_bVec Derived least squares B vector.
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Eigen::VectorXd
_aVec Derived least squares solution matrix.
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KernelSolvedBy
_solvedBy Type of algorithm used to make solution.
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bool
_fitForBackground Background terms included in fit.
Protected Static Attributes
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int
_SolutionId Unique identifier for solution.
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enum
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template<typename
InputT>
classMaskedKernelSolution: public lsst::ip::diffim::StaticKernelSolution<InputT> Public Types
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typedef std::shared_ptr<MaskedKernelSolution<InputT>>
Ptr
Public Functions
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MaskedKernelSolution(lsst::afw::math::KernelList const &basisList, bool fitForBackground)
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virtual
~MaskedKernelSolution()
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virtual void
buildOrig(lsst::afw::image::Image<InputT> const &templateImage, lsst::afw::image::Image<InputT> const &scienceImage, lsst::afw::image::Image<lsst::afw::image::VariancePixel> const &varianceEstimate, lsst::afw::image::Mask<lsst::afw::image::MaskPixel> pixelMask)
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typedef std::shared_ptr<MaskedKernelSolution<InputT>>
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template<typename
InputT>
classRegularizedKernelSolution: public lsst::ip::diffim::StaticKernelSolution<InputT> Public Types
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typedef std::shared_ptr<RegularizedKernelSolution<InputT>>
Ptr
Public Functions
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RegularizedKernelSolution(lsst::afw::math::KernelList const &basisList, bool fitForBackground, Eigen::MatrixXd const &hMat, lsst::daf::base::PropertySet const &ps)
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virtual
~RegularizedKernelSolution()
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void
solve()
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double
getLambda()
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double
estimateRisk(double maxCond)
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Eigen::MatrixXd
getM(bool includeHmat = true)
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typedef std::shared_ptr<RegularizedKernelSolution<InputT>>
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class
SpatialKernelSolution: public lsst::ip::diffim::KernelSolution Public Types
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typedef std::shared_ptr<SpatialKernelSolution>
Ptr
Public Functions
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SpatialKernelSolution(lsst::afw::math::KernelList const &basisList, lsst::afw::math::Kernel::SpatialFunctionPtr spatialKernelFunction, lsst::afw::math::Kernel::SpatialFunctionPtr background, lsst::daf::base::PropertySet const &ps)
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virtual
~SpatialKernelSolution()
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void
addConstraint(float xCenter, float yCenter, Eigen::MatrixXd const &qMat, Eigen::VectorXd const &wVec)
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void
solve()
Private Functions
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void
_setKernel()¶ Set kernel after solution.
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void
_setKernelUncertainty()¶ Not implemented.
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typedef std::shared_ptr<SpatialKernelSolution>
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template<typename
InputT>
classStaticKernelSolution: public lsst::ip::diffim::KernelSolution Subclassed by lsst::ip::diffim::MaskedKernelSolution< InputT >, lsst::ip::diffim::RegularizedKernelSolution< InputT >
Public Types
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typedef std::shared_ptr<StaticKernelSolution<InputT>>
Ptr
Public Functions
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StaticKernelSolution(lsst::afw::math::KernelList const &basisList, bool fitForBackground)
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virtual
~StaticKernelSolution()
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void
solve()
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virtual void
build(lsst::afw::image::Image<InputT> const &templateImage, lsst::afw::image::Image<InputT> const &scienceImage, lsst::afw::image::Image<lsst::afw::image::VariancePixel> const &varianceEstimate)
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virtual double
getBackground()
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virtual double
getKsum()
Protected Functions
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void
_setKernel() Set kernel after solution.
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void
_setKernelUncertainty() Not implemented.
Protected Attributes
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Eigen::MatrixXd
_cMat K_i x R.
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Eigen::VectorXd
_iVec Vectorized I.
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Eigen::VectorXd
_ivVec Inverse variance.
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double
_background Derived differential background estimate.
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double
_kSum Derived kernel sum.
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typedef std::shared_ptr<StaticKernelSolution<InputT>>
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class
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namespace