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LSST Data Management Base Package
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Namespaces | |
namespace | cmodel |
namespace | common |
namespace | detail |
namespace | optimizer |
namespace | pixelFitRegion |
namespace | priors |
namespace | psf |
namespace | version |
Classes | |
class | AdaptiveImportanceSampler |
Sampler class that performs Monte Carlo sampling, while iteratively updating the analytic distribution from which points are drawn. More... | |
class | CModelAlgorithm |
Main public interface class for CModel algorithm. More... | |
struct | CModelControl |
The main control object for CModel, containing parameters for the final linear fit and aggregating the other control objects. More... | |
struct | CModelResult |
Master result object for CModel, containing results for the final linear fit and three nested CModelStageResult objects for the results of the previous stages. More... | |
struct | CModelStageControl |
Nested control object for CModel that configures one of the three ("initial", "exp", "dev") nonlinear fitting stages. More... | |
struct | CModelStageResult |
Result object for a single nonlinear fitting stage of the CModel algorithm. More... | |
class | DoubleShapeletPsfApproxAlgorithm |
An algorithm that fits a 2-component shapelet approximation to the PSF model. More... | |
class | DoubleShapeletPsfApproxControl |
Control object used to configure a 2-shapelet fit to a PSF model; see DoubleShapeletPsfApproxAlgorithm. More... | |
class | EpochFootprint |
An image at one epoch of a galaxy, plus associated info. More... | |
class | GeneralPsfFitter |
Class for fitting multishapelet models to PSF images. More... | |
class | GeneralPsfFitterAlgorithm |
class | GeneralPsfFitterComponentControl |
Control object used to define one piece of multishapelet fit to a PSF model; see GeneralPsfFitterControl. More... | |
class | GeneralPsfFitterControl |
Control object used to configure a multishapelet fit to a PSF model; see GeneralPsfFitter. More... | |
class | ImportanceSamplerControl |
Control object for one iteration of adaptive importance sampling. More... | |
class | Likelihood |
Base class for optimizer/sampler likelihood functions that compute likelihood at a point. More... | |
struct | LocalUnitTransform |
A local mapping between two UnitSystems. More... | |
class | Mixture |
class | MixtureComponent |
A weighted Student's T or Gaussian distribution used as a component in a Mixture. More... | |
class | MixturePrior |
A prior that's flat in amplitude parameters, and uses a Mixture for nonlinear parameters. More... | |
class | MixtureUpdateRestriction |
Helper class used to define restrictions to the form of the component parameters in Mixture::updateEM. More... | |
class | Model |
Abstract base class and concrete factories that define multi-shapelet galaxy models. More... | |
class | MultiModel |
A concrete Model class that simply concatenates several other Models. More... | |
class | MultiShapeletPsfLikelihood |
Likelihood object used to fit multishapelet models to PSF model images; mostly for internal use by GeneralPsfFitter. More... | |
class | Optimizer |
A numerical optimizer customized for least-squares problems with Bayesian priors. More... | |
class | OptimizerControl |
Configuration object for Optimizer. More... | |
class | OptimizerHistoryRecorder |
class | OptimizerObjective |
Base class for objective functions for Optimizer. More... | |
class | PixelFitRegion |
struct | PixelFitRegionControl |
class | Prior |
Base class for Bayesian priors. More... | |
class | Sampler |
class | SamplingObjective |
class | SemiEmpiricalPrior |
A piecewise prior motivated by both real distributions and practical considerations. More... | |
struct | SemiEmpiricalPriorControl |
class | SoftenedLinearPrior |
A prior that's linear in radius and flat in ellipticity, with a cubic roll-off at the edges. More... | |
struct | SoftenedLinearPriorControl |
class | TruncatedGaussian |
Represents a multidimensional Gaussian function truncated at zero. More... | |
class | TruncatedGaussianEvaluator |
Helper class for evaluating the -log of a TruncatedGaussian. More... | |
class | TruncatedGaussianLogEvaluator |
Helper class for evaluating the -log of a TruncatedGaussian. More... | |
class | TruncatedGaussianSampler |
Helper class for drawing samples from a TruncatedGaussian. More... | |
struct | UnitSystem |
A simple struct that combines a Wcs and a PhotoCalib. More... | |
class | UnitTransformedLikelihood |
A concrete Likelihood class that does not require its parameters and data to be in the same UnitSystem. More... | |
class | UnitTransformedLikelihoodControl |
Control object used to initialize a UnitTransformedLikelihood. More... | |
typedef Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic> lsst::meas::modelfit::Matrix |
typedef float lsst::meas::modelfit::Pixel |
Definition at line 42 of file adaptiveImportanceSampler.cc.
using lsst::meas::modelfit::PyEpochFootprint = py::class_<EpochFootprint, std::shared_ptr<EpochFootprint>> |
Definition at line 43 of file unitTransformedLikelihood.cc.
Definition at line 40 of file adaptiveImportanceSampler.cc.
using lsst::meas::modelfit::PyLikelihood = py::class_<Likelihood, std::shared_ptr<Likelihood>> |
Definition at line 38 of file likelihood.cc.
using lsst::meas::modelfit::PyLocalUnitTransform = py::class_<LocalUnitTransform, std::shared_ptr<LocalUnitTransform>> |
Definition at line 37 of file unitSystem.cc.
using lsst::meas::modelfit::PyModel = py::class_<Model, std::shared_ptr<Model>> |
using lsst::meas::modelfit::PyMultiModel = py::class_<MultiModel, std::shared_ptr<MultiModel>, Model> |
Definition at line 37 of file multiModel.cc.
using lsst::meas::modelfit::PyPixelFitRegion = py::class_<PixelFitRegion, std::shared_ptr<PixelFitRegion>> |
Definition at line 40 of file pixelFitRegion.cc.
using lsst::meas::modelfit::PyPixelFitRegionControl = py::class_<PixelFitRegionControl, std::shared_ptr<PixelFitRegionControl>> |
Definition at line 39 of file pixelFitRegion.cc.
using lsst::meas::modelfit::PySampler = py::class_<Sampler, std::shared_ptr<Sampler>> |
Definition at line 42 of file sampler.cc.
using lsst::meas::modelfit::PySamplingObjective = py::class_<SamplingObjective, std::shared_ptr<SamplingObjective>> |
Definition at line 41 of file sampler.cc.
using lsst::meas::modelfit::PyUnitSystem = py::class_<UnitSystem, std::shared_ptr<UnitSystem>> |
Definition at line 36 of file unitSystem.cc.
Definition at line 45 of file unitTransformedLikelihood.cc.
Definition at line 40 of file unitTransformedLikelihood.cc.
typedef double lsst::meas::modelfit::Scalar |
typedef Eigen::Matrix<Scalar,Eigen::Dynamic,1> lsst::meas::modelfit::Vector |
lsst::meas::modelfit::PYBIND11_MODULE | ( | _modelfitLib | , |
mod | ) |
Definition at line 51 of file _modelfitLib.cc.
void lsst::meas::modelfit::solveTrustRegion | ( | ndarray::Array< Scalar, 1, 1 > const & | x, |
ndarray::Array< Scalar const, 2, 1 > const & | F, | ||
ndarray::Array< Scalar const, 1, 1 > const & | g, | ||
double | r, | ||
double | tolerance ) |
Solve a symmetric quadratic matrix equation with a ball constraint.
This computes a near-exact solution to the "trust region subproblem" necessary in trust-region-based nonlinear optimizers:
\[ \min_x{\quad g^T x + \frac{1}{2}x^T F x}\quad\quad\quad \text{s.t.} ||x|| \le r \]
The tolerance parameter sets how close to \(r\) we require the norm of the solution to be when it lies on the constraint, as a fraction of \(r\) itself.
This implementation is based on the algorithm described in Section 4.3 of "Nonlinear Optimization" by Nocedal and Wright.
void lsst::meas::modelfit::wrapAdaptiveImportanceSampler | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 45 of file adaptiveImportanceSampler.cc.
void lsst::meas::modelfit::wrapCmodel | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 205 of file cmodel.cc.
void lsst::meas::modelfit::wrapIntegrals | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 36 of file integrals.cc.
void lsst::meas::modelfit::wrapLikelihood | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 40 of file likelihood.cc.
void lsst::meas::modelfit::wrapMixture | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 143 of file mixture.cc.
void lsst::meas::modelfit::wrapModel | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 43 of file model.cc.
void lsst::meas::modelfit::wrapMultiModel | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 39 of file multiModel.cc.
void lsst::meas::modelfit::wrapOptimizer | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 172 of file optimizer.cc.
void lsst::meas::modelfit::wrapPixelFitRegion | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 42 of file pixelFitRegion.cc.
void lsst::meas::modelfit::wrapPriors | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
void lsst::meas::modelfit::wrapPsf | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
void lsst::meas::modelfit::wrapSampler | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 44 of file sampler.cc.
void lsst::meas::modelfit::wrapTruncatedGaussian | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 121 of file truncatedGaussian.cc.
void lsst::meas::modelfit::wrapUnitSystem | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 39 of file unitSystem.cc.
void lsst::meas::modelfit::wrapUnitTransformedLikelihood | ( | lsst::cpputils::python::WrapperCollection & | wrappers | ) |
Definition at line 48 of file unitTransformedLikelihood.cc.