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LSST Data Management Base Package
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Implementation of an axisymmetric 2D Gaussian convolved with a line – a model for a fast-moving, trailed-source (Veres et al. More...
#include <VeresModel.h>
Public Types | |
using | ImageF = afw::image::Image< float > |
using | ExposureF = afw::image::Exposure< float > |
Public Member Functions | |
VeresModel (ExposureF const &data) | |
Constructor for VeresModel. More... | |
VeresModel (VeresModel const &)=default | |
VeresModel (VeresModel &&)=default | |
VeresModel & | operator= (VeresModel const &)=default |
VeresModel & | operator= (VeresModel &&)=default |
~VeresModel ()=default | |
double | operator() (std::vector< double > const ¶ms) const |
Compute chi-squared of the model given the data. More... | |
std::vector< double > | gradient (std::vector< double > const ¶ms) const |
Compute the gradient of chi-squared of the model given the data. More... | |
std::tuple< double, std::vector< double > > | computeFluxWithGradient (std::vector< double > const ¶ms) const |
Computes the flux and the gradient with respect to the other model parameters. More... | |
std::shared_ptr< ImageF > | computeModelImage (std::vector< double > const ¶ms) const |
Compute an image for a trail generated from the Veres model. More... | |
double | getSigma () const noexcept |
Return the PSF sigma. More... | |
Implementation of an axisymmetric 2D Gaussian convolved with a line – a model for a fast-moving, trailed-source (Veres et al.
2012).
VeresModel is designed to compute the chi-squared of the model given an lsst::afw::image::Exposure.
Definition at line 47 of file VeresModel.h.
Definition at line 50 of file VeresModel.h.
Definition at line 49 of file VeresModel.h.
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Constructor for VeresModel.
data | Exposure passed from the measurement task. |
Definition at line 39 of file VeresModel.cc.
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std::tuple< double, std::vector< double > > lsst::meas::extensions::trailedSources::VeresModel::computeFluxWithGradient | ( | std::vector< double > const & | params | ) | const |
Computes the flux and the gradient with respect to the other model parameters.
We estimate the flux by solving the linear least-squares problem for the Veres et al. 2012 model. By keeping the length, angle, and centroid coordinates fixed, we analytically solve for the flux.
params | Model parameters. |
Definition at line 95 of file VeresModel.cc.
std::shared_ptr< ImageF > lsst::meas::extensions::trailedSources::VeresModel::computeModelImage | ( | std::vector< double > const & | params | ) | const |
Compute an image for a trail generated from the Veres model.
Definition at line 132 of file VeresModel.cc.
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std::vector< double > lsst::meas::extensions::trailedSources::VeresModel::gradient | ( | std::vector< double > const & | params | ) | const |
Compute the gradient of chi-squared of the model given the data.
params | Model parameters. |
Definition at line 70 of file VeresModel.cc.
double lsst::meas::extensions::trailedSources::VeresModel::operator() | ( | std::vector< double > const & | params | ) | const |
Compute chi-squared of the model given the data.
params | Model parameters. |
Definition at line 46 of file VeresModel.cc.
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