LSST Applications  21.0.0-172-gfb10e10a+18fedfabac,22.0.0+297cba6710,22.0.0+80564b0ff1,22.0.0+8d77f4f51a,22.0.0+a28f4c53b1,22.0.0+dcf3732eb2,22.0.1-1-g7d6de66+2a20fdde0d,22.0.1-1-g8e32f31+297cba6710,22.0.1-1-geca5380+7fa3b7d9b6,22.0.1-12-g44dc1dc+2a20fdde0d,22.0.1-15-g6a90155+515f58c32b,22.0.1-16-g9282f48+790f5f2caa,22.0.1-2-g92698f7+dcf3732eb2,22.0.1-2-ga9b0f51+7fa3b7d9b6,22.0.1-2-gd1925c9+bf4f0e694f,22.0.1-24-g1ad7a390+a9625a72a8,22.0.1-25-g5bf6245+3ad8ecd50b,22.0.1-25-gb120d7b+8b5510f75f,22.0.1-27-g97737f7+2a20fdde0d,22.0.1-32-gf62ce7b1+aa4237961e,22.0.1-4-g0b3f228+2a20fdde0d,22.0.1-4-g243d05b+871c1b8305,22.0.1-4-g3a563be+32dcf1063f,22.0.1-4-g44f2e3d+9e4ab0f4fa,22.0.1-42-gca6935d93+ba5e5ca3eb,22.0.1-5-g15c806e+85460ae5f3,22.0.1-5-g58711c4+611d128589,22.0.1-5-g75bb458+99c117b92f,22.0.1-6-g1c63a23+7fa3b7d9b6,22.0.1-6-g50866e6+84ff5a128b,22.0.1-6-g8d3140d+720564cf76,22.0.1-6-gd805d02+cc5644f571,22.0.1-8-ge5750ce+85460ae5f3,master-g6e05de7fdc+babf819c66,master-g99da0e417a+8d77f4f51a,w.2021.48
LSST Data Management Base Package
KernelCandidate.h
Go to the documentation of this file.
1 // -*- lsst-c++ -*-
12 #ifndef LSST_IP_DIFFIM_KERNELCANDIDATE_H
13 #define LSST_IP_DIFFIM_KERNELCANDIDATE_H
14 
15 #include <memory>
16 #include "Eigen/Core"
17 
18 #include "lsst/afw/math.h"
19 #include "lsst/afw/image.h"
21 #include "lsst/afw/table/Source.h"
22 #include "lsst/daf/base.h"
23 
24 namespace lsst {
25 namespace ip {
26 namespace diffim {
27 
28 
38  template <typename _PixelT>
40  public:
42  typedef _PixelT PixelT; // _after_ afw::math::Kernel::Pixel
43  public:
48 
50  ORIG = 0,
51  PCA = 1,
52  RECENT = 2
53  };
54 
64  KernelCandidate(float const xCenter,
65  float const yCenter,
66  MaskedImagePtr const& templateMaskedImage,
67  MaskedImagePtr const& scienceMaskedImage,
68  daf::base::PropertySet const& ps);
69 
80  MaskedImagePtr const& templateMaskedImage,
81  MaskedImagePtr const& scienceMaskedImage,
82  daf::base::PropertySet const& ps);
84  virtual ~KernelCandidate() {};
85 
91  double getCandidateRating() const { return _coreFlux; }
95  SourcePtr getSource() const { return _source; }
99  MaskedImagePtr getTemplateMaskedImage() {return _templateMaskedImage;}
100  MaskedImagePtr getScienceMaskedImage() {return _scienceMaskedImage;}
101 
107  double getBackground(CandidateSwitch cand) const;
108  double getKsum(CandidateSwitch cand) const;
110  std::shared_ptr<ImageT const> getImage() const; // For SpatialCellImageCandidate
112 
117 
125  double background
126  );
127 
128  bool isInitialized() const {return _isInitialized;}
129 
130 
165  /*
166  * @note This method uses an estimate of the variance which is the
167  * straight difference of the 2 images. If requested in the PropertySet
168  * ("iterateSingleKernel"), the kernel will be rebuilt using the
169  * variance of the difference image resulting from this first
170  * approximate step. This is particularly useful when convolving a
171  * single-depth science image; the variance (and thus resulting kernel)
172  * generally converges after 1 iteration. If
173  * "constantVarianceWeighting" is requested in the PropertySet, no iterations
174  * will be performed even if requested.
175  */
176 
177  void build(
178  afw::math::KernelList const& basisList
179  );
180  void build(
181  afw::math::KernelList const& basisList,
182  Eigen::MatrixXd const& hMat
183  );
184 
185  private:
186  MaskedImagePtr _templateMaskedImage;
187  MaskedImagePtr _scienceMaskedImage;
188  VariancePtr _varianceEstimate;
190  SourcePtr _source;
191  double _coreFlux;
192  bool _isInitialized;
193  bool _useRegularization;
194  bool _fitForBackground;
195 
196  /* best single raw kernel */
197  std::shared_ptr<StaticKernelSolution<PixelT> > _kernelSolutionOrig;
198 
199  /* with Pca basis */
200  std::shared_ptr<StaticKernelSolution<PixelT> > _kernelSolutionPca;
201 
202  void _buildKernelSolution(afw::math::KernelList const& basisList,
203  Eigen::MatrixXd const& hMat);
204  };
205 
206 
218  template <typename PixelT>
220  makeKernelCandidate(float const xCenter,
221  float const yCenter,
222  std::shared_ptr<afw::image::MaskedImage<PixelT> > const& templateMaskedImage,
223  std::shared_ptr<afw::image::MaskedImage<PixelT> > const& scienceMaskedImage,
224  daf::base::PropertySet const& ps){
225 
227  templateMaskedImage,
228  scienceMaskedImage,
229  ps));
230  }
231 
243  template <typename PixelT>
246  std::shared_ptr<afw::image::MaskedImage<PixelT> > const& templateMaskedImage,
247  std::shared_ptr<afw::image::MaskedImage<PixelT> > const& scienceMaskedImage,
248  daf::base::PropertySet const& ps){
249 
251  templateMaskedImage,
252  scienceMaskedImage,
253  ps));
254  }
255 
256 
257 }}} // end of namespace lsst::ip::diffim
258 
259 #endif
Declaration of classes to store the solution for convolution kernels.
A class to represent a 2-dimensional array of pixels.
Definition: Image.h:51
A class to manipulate images, masks, and variance as a single object.
Definition: MaskedImage.h:73
Base class for candidate objects in a SpatialCell that are able to return an Image of some sort (e....
Definition: SpatialCell.h:124
Class for storing generic metadata.
Definition: PropertySet.h:66
Class stored in SpatialCells for spatial Kernel fitting.
std::shared_ptr< ImageT const > getImage() const
std::shared_ptr< afw::image::MaskedImage< PixelT > > MaskedImagePtr
std::shared_ptr< afw::image::Image< afw::image::VariancePixel > > VariancePtr
virtual ~KernelCandidate()
Destructor.
afw::image::Image< afw::math::Kernel::Pixel > ImageT
afw::image::MaskedImage< PixelT > getDifferenceImage(CandidateSwitch cand)
Calculate associated difference image using internal solutions.
double getCandidateRating() const
Return Candidate rating.
std::shared_ptr< KernelCandidate > Ptr
MaskedImagePtr getTemplateMaskedImage()
Return pointers to the image pixels used in kernel determination.
double getBackground(CandidateSwitch cand) const
double getKsum(CandidateSwitch cand) const
std::shared_ptr< afw::table::SourceRecord > SourcePtr
std::shared_ptr< StaticKernelSolution< PixelT > > getKernelSolution(CandidateSwitch cand) const
std::shared_ptr< afw::math::Kernel > getKernel(CandidateSwitch cand) const
Return results of kernel solution.
KernelCandidate(float const xCenter, float const yCenter, MaskedImagePtr const &templateMaskedImage, MaskedImagePtr const &scienceMaskedImage, daf::base::PropertySet const &ps)
Constructor.
SourcePtr getSource() const
Return the original source.
std::shared_ptr< ImageT > getKernelImage(CandidateSwitch cand) const
void build(afw::math::KernelList const &basisList)
Core functionality of KernelCandidate, to build and fill a KernelSolution.
const char * source()
Source function that allows astChannel to source from a Stream.
Definition: Stream.h:224
std::shared_ptr< KernelCandidate< PixelT > > makeKernelCandidate(float const xCenter, float const yCenter, std::shared_ptr< afw::image::MaskedImage< PixelT > > const &templateMaskedImage, std::shared_ptr< afw::image::MaskedImage< PixelT > > const &scienceMaskedImage, daf::base::PropertySet const &ps)
Return a KernelCandidate pointer of the right sort.
A base class for image defects.