LSST Applications 27.0.0,g0265f82a02+469cd937ee,g02d81e74bb+21ad69e7e1,g1470d8bcf6+cbe83ee85a,g2079a07aa2+e67c6346a6,g212a7c68fe+04a9158687,g2305ad1205+94392ce272,g295015adf3+81dd352a9d,g2bbee38e9b+469cd937ee,g337abbeb29+469cd937ee,g3939d97d7f+72a9f7b576,g487adcacf7+71499e7cba,g50ff169b8f+5929b3527e,g52b1c1532d+a6fc98d2e7,g591dd9f2cf+df404f777f,g5a732f18d5+be83d3ecdb,g64a986408d+21ad69e7e1,g858d7b2824+21ad69e7e1,g8a8a8dda67+a6fc98d2e7,g99cad8db69+f62e5b0af5,g9ddcbc5298+d4bad12328,ga1e77700b3+9c366c4306,ga8c6da7877+71e4819109,gb0e22166c9+25ba2f69a1,gb6a65358fc+469cd937ee,gbb8dafda3b+69d3c0e320,gc07e1c2157+a98bf949bb,gc120e1dc64+615ec43309,gc28159a63d+469cd937ee,gcf0d15dbbd+72a9f7b576,gdaeeff99f8+a38ce5ea23,ge6526c86ff+3a7c1ac5f1,ge79ae78c31+469cd937ee,gee10cc3b42+a6fc98d2e7,gf1cff7945b+21ad69e7e1,gfbcc870c63+9a11dc8c8f
LSST Data Management Base Package
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A concrete Likelihood class that does not require its parameters and data to be in the same UnitSystem. More...
#include <UnitTransformedLikelihood.h>
Public Member Functions | |
void | computeModelMatrix (ndarray::Array< Pixel, 2,-1 > const &modelMatrix, ndarray::Array< Scalar const, 1, 1 > const &nonlinear, bool doApplyWeights=true) const override |
Evaluate the model for the given vector of nonlinear parameters. | |
UnitTransformedLikelihood (std::shared_ptr< Model > model, ndarray::Array< Scalar const, 1, 1 > const &fixed, UnitSystem const &fitSys, geom::SpherePoint const &position, std::vector< std::shared_ptr< EpochFootprint > > const &epochFootprintList, UnitTransformedLikelihoodControl const &ctrl) | |
Initialize a UnitTransformedLikelihood with data from multiple exposures. | |
UnitTransformedLikelihood (std::shared_ptr< Model > model, ndarray::Array< Scalar const, 1, 1 > const &fixed, UnitSystem const &fitSys, geom::SpherePoint const &position, afw::image::Exposure< Pixel > const &exposure, afw::detection::Footprint const &footprint, shapelet::MultiShapeletFunction const &psf, UnitTransformedLikelihoodControl const &ctrl) | |
Initialize a UnitTransformedLikelihood with data from multiple exposures. | |
virtual | ~UnitTransformedLikelihood () |
int | getDataDim () const |
Return the number of data points. | |
int | getAmplitudeDim () const |
Return the number of linear parameters (columns of the model matrix) | |
int | getNonlinearDim () const |
Return the number of nonlinear parameters (which parameterize the model matrix) | |
int | getFixedDim () const |
Return the number of fixed nonlinear parameters (set on Likelihood construction) | |
ndarray::Array< Scalar const, 1, 1 > | getFixed () const |
Return the vector of fixed nonlinear parameters. | |
ndarray::Array< Pixel const, 1, 1 > | getData () const |
Return the vector of weighted, scaled data points \(z\). | |
ndarray::Array< Pixel const, 1, 1 > | getUnweightedData () const |
Return the vector of unweighted data points \(y\). | |
ndarray::Array< Pixel const, 1, 1 > | getWeights () const |
Return the vector of weights \(w\) applied to data points and model matrix rows. | |
ndarray::Array< Pixel const, 1, 1 > | getVariance () const |
Return the vector of per-data-point variances. | |
std::shared_ptr< Model > | getModel () const |
Return an object that defines the model and its parameters. | |
Protected Attributes | |
std::shared_ptr< Model > | _model |
ndarray::Array< Scalar const, 1, 1 > | _fixed |
ndarray::Array< Pixel, 1, 1 > | _data |
ndarray::Array< Pixel, 1, 1 > | _unweightedData |
ndarray::Array< Pixel, 1, 1 > | _variance |
ndarray::Array< Pixel, 1, 1 > | _weights |
A concrete Likelihood class that does not require its parameters and data to be in the same UnitSystem.
This is the main concrete Likelihood class using when fitting sources, even in the case where the measurement UnitSystem is the same as that of the data; we always prefer to fit in a special UnitSystem (see Units and Coordinate Systems), using this class to transform the model realization when comparing to the data. This makes forced photometry and modelfit measurements just as easy as single-frame measurements (aside from data access); one can simply initialize a UnitTransformedLikelihood with multiple exposures instead of a single exposure to fit simultaneously to multiple exposures.
Definition at line 102 of file UnitTransformedLikelihood.h.
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explicit |
Initialize a UnitTransformedLikelihood with data from multiple exposures.
[in] | model | Object that defines the model to fit and its parameters. |
[in] | fixed | Model parameters that are held fixed. |
[in] | fitSys | Geometric and photometric system to fit in |
[in] | position | ICRS sky position of object being fit |
[in] | epochFootprintList | List of shared pointers to EpochFootprint |
[in] | ctrl | Control object with various options |
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explicit |
Initialize a UnitTransformedLikelihood with data from multiple exposures.
[in] | model | Object that defines the model to fit and its parameters. |
[in] | fixed | Model parameters that are held fixed. |
[in] | fitSys | Geometric and photometric system to fit in |
[in] | position | ICRS sky position of object being fit |
[in] | exposure | Exposure containing the data to fit |
[in] | footprint | Footprint that defines the pixels to include in the fit |
[in] | psf | Shapelet approximation to the PSF |
[in] | ctrl | Control object with various options |
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virtual |
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overridevirtual |
Evaluate the model for the given vector of nonlinear parameters.
[out] | modelMatrix | The dataDim x amplitudeDim matrix \(B\) that expresses the model projected in such a way that it can be compared to the data when multiplied by an amplitude vector \(\alpha\). It should be weighted if the data vector is. The caller is responsible for guaranteeing that the shape of the matrix correct, but implementations should not assume anything about the initial values of the matrix elements. |
[in] | nonlinear | Vector of nonlinear parameters at which to evaluate the model. |
[in] | doApplyWeights | If False, do not apply the weights to the modelMatrix. |
Implements lsst::meas::modelfit::Likelihood.
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inlineinherited |
Return the number of linear parameters (columns of the model matrix)
Definition at line 77 of file Likelihood.h.
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inlineinherited |
Return the vector of weighted, scaled data points \(z\).
Definition at line 89 of file Likelihood.h.
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inlineinherited |
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inlineinherited |
Return the vector of fixed nonlinear parameters.
Definition at line 86 of file Likelihood.h.
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inlineinherited |
Return the number of fixed nonlinear parameters (set on Likelihood construction)
Definition at line 83 of file Likelihood.h.
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inlineinherited |
Return an object that defines the model and its parameters.
Definition at line 105 of file Likelihood.h.
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inlineinherited |
Return the number of nonlinear parameters (which parameterize the model matrix)
Definition at line 80 of file Likelihood.h.
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inlineinherited |
Return the vector of unweighted data points \(y\).
Definition at line 92 of file Likelihood.h.
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inlineinherited |
Return the vector of per-data-point variances.
Definition at line 102 of file Likelihood.h.
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inlineinherited |
Return the vector of weights \(w\) applied to data points and model matrix rows.
Will be an empty array if no weights are applied.
Definition at line 99 of file Likelihood.h.
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protectedinherited |
Definition at line 149 of file Likelihood.h.
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protectedinherited |
Definition at line 148 of file Likelihood.h.
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protectedinherited |
Definition at line 147 of file Likelihood.h.
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protectedinherited |
Definition at line 150 of file Likelihood.h.
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protectedinherited |
Definition at line 151 of file Likelihood.h.
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protectedinherited |
Definition at line 152 of file Likelihood.h.