lsst.meas.modelfit  22.0.1-3-g849a1b8+02e96ff2fe
Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
[detail level 1234567]
 Nlsst
 Nmeas
 Nmodelfit
 Ncmodel
 NcmodelContinued
 CCModelSingleFrameConfig
 CCModelSingleFramePlugin
 CCModelForcedConfig
 CCModelForcedPlugin
 Ndetail
 CVandermondeClass that computes rows of the Vandermonde matrix and related matrices; the dot product of these row vectors with the polynomial coefficient vectors evaluates the polynomial (or computes a derivative)
 Ndisplay
 NdensityPlot
 CHistogramLayer
 CScatterLayer
 CSurfaceLayer
 CCrossPointsLayer
 CDensityPlot
 CLayerDict
 CExampleData
 Ninteractive
 CInteractive
 NmodelFitAdapters
 CModelFitDataAdapter
 CSamplingDataAdapter
 COptimizerTrackLayer
 COptimizerDataAdapter
 NoptimizerDisplay
 COptimizerIterationDisplay
 COptimizerDisplay
 COptimizerDisplayFigure
 Noptimizer
 NoptimizerContinued
 COptimizerControl
 COptimizer
 Npriors
 NpriorsContinued
 CSemiEmpiricalPrior
 CSoftenedLinearPrior
 Npsf
 NpsfContinued
 CGeneralShapeletPsfApproxConfig
 CGeneralShapeletPsfApproxMixin
 CGeneralShapeletPsfApproxSingleFrameConfig
 CGeneralShapeletPsfApproxSingleFramePlugin
 CGeneralShapeletPsfApproxForcedConfig
 CGeneralShapeletPsfApproxForcedPlugin
 CImportanceSamplerControlControl object for one iteration of adaptive importance sampling
 CAdaptiveImportanceSamplerSampler class that performs Monte Carlo sampling, while iteratively updating the analytic distribution from which points are drawn
 CCModelStageControlNested control object for CModel that configures one of the three ("initial", "exp", "dev") nonlinear fitting stages
 CCModelControlThe main control object for CModel, containing parameters for the final linear fit and aggregating the other control objects
 CCModelStageResultResult object for a single nonlinear fitting stage of the CModel algorithm
 CCModelResultMaster result object for CModel, containing results for the final linear fit and three nested CModelStageResult objects for the results of the previous stages
 CCModelAlgorithmMain public interface class for CModel algorithm
 CDoubleShapeletPsfApproxControlControl object used to configure a 2-shapelet fit to a PSF model; see DoubleShapeletPsfApproxAlgorithm
 CDoubleShapeletPsfApproxAlgorithmAn algorithm that fits a 2-component shapelet approximation to the PSF model
 CGeneralPsfFitterComponentControlControl object used to define one piece of multishapelet fit to a PSF model; see GeneralPsfFitterControl
 CGeneralPsfFitterControlControl object used to configure a multishapelet fit to a PSF model; see GeneralPsfFitter
 CGeneralPsfFitterClass for fitting multishapelet models to PSF images
 CGeneralPsfFitterAlgorithm
 CMultiShapeletPsfLikelihoodLikelihood object used to fit multishapelet models to PSF model images; mostly for internal use by GeneralPsfFitter
 CLikelihoodBase class for optimizer/sampler likelihood functions that compute likelihood at a point
 CMixtureComponentA weighted Student's T or Gaussian distribution used as a component in a Mixture
 CMixtureUpdateRestrictionHelper class used to define restrictions to the form of the component parameters in Mixture::updateEM
 CMixture
 CMixturePriorA prior that's flat in amplitude parameters, and uses a Mixture for nonlinear parameters
 CModelAbstract base class and concrete factories that define multi-shapelet galaxy models
 CMultiModelA concrete Model class that simply concatenates several other Models
 COptimizerObjectiveBase class for objective functions for Optimizer
 COptimizerControlConfiguration object for Optimizer
 COptimizerHistoryRecorder
 COptimizerA numerical optimizer customized for least-squares problems with Bayesian priors
 CPixelFitRegionControl
 CPixelFitRegion
 CPriorBase class for Bayesian priors
 CSamplingObjective
 CSampler
 CSemiEmpiricalPriorControl
 CSemiEmpiricalPriorA piecewise prior motivated by both real distributions and practical considerations
 CSoftenedLinearPriorControl
 CSoftenedLinearPriorA prior that's linear in radius and flat in ellipticity, with a cubic roll-off at the edges
 CTruncatedGaussianRepresents a multidimensional Gaussian function truncated at zero
 CTruncatedGaussianLogEvaluatorHelper class for evaluating the -log of a TruncatedGaussian
 CTruncatedGaussianEvaluatorHelper class for evaluating the -log of a TruncatedGaussian
 CTruncatedGaussianSamplerHelper class for drawing samples from a TruncatedGaussian
 CUnitSystemA simple struct that combines a Wcs and a PhotoCalib
 CLocalUnitTransformA local mapping between two UnitSystems
 CUnitTransformedLikelihoodControlControl object used to initialize a UnitTransformedLikelihood
 CEpochFootprintAn image at one epoch of a galaxy, plus associated info
 CUnitTransformedLikelihoodA concrete Likelihood class that does not require its parameters and data to be in the same UnitSystem