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LSST Applications 28.0.0,g1653933729+a8ce1bb630,g1a997c3884+a8ce1bb630,g28da252d5a+5bd70b7e6d,g2bbee38e9b+638fca75ac,g2bc492864f+638fca75ac,g3156d2b45e+07302053f8,g347aa1857d+638fca75ac,g35bb328faa+a8ce1bb630,g3a166c0a6a+638fca75ac,g3e281a1b8c+7bbb0b2507,g4005a62e65+17cd334064,g414038480c+5b5cd4fff3,g41af890bb2+4ffae9de63,g4e1a3235cc+0f1912dca3,g6249c6f860+3c3976f90c,g80478fca09+46aba80bd6,g82479be7b0+77990446f6,g858d7b2824+78ba4d1ce1,g89c8672015+f667a5183b,g9125e01d80+a8ce1bb630,ga5288a1d22+2a6264e9ca,gae0086650b+a8ce1bb630,gb58c049af0+d64f4d3760,gc22bb204ba+78ba4d1ce1,gc28159a63d+638fca75ac,gcf0d15dbbd+32ddb6096f,gd6b7c0dfd1+3e339405e9,gda3e153d99+78ba4d1ce1,gda6a2b7d83+32ddb6096f,gdaeeff99f8+1711a396fd,gdd5a9049c5+b18c39e5e3,ge2409df99d+a5e4577cdc,ge33fd446bb+78ba4d1ce1,ge79ae78c31+638fca75ac,gf0baf85859+64e8883e75,gf5289d68f6+e1b046a8d7,gfa443fc69c+91d9ed1ecf,gfda6b12a05+8419469a56
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KernelPca.h
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1// -*- lsst-c++ -*-
12#ifndef LSST_IP_DIFFIM_KERNELPCA_H
13#define LSST_IP_DIFFIM_KERNELPCA_H
14
15#include "lsst/afw/image.h"
16#include "lsst/afw/math.h"
17
18namespace lsst {
19namespace ip {
20namespace diffim {
21namespace detail {
22
23 template <typename ImageT>
24 class KernelPca : public lsst::afw::image::ImagePca<ImageT> {
26 public:
31
33 explicit KernelPca(bool constantWeight=true) : Super(constantWeight) {}
34
36 virtual void analyze();
37 };
38
39 template<typename PixelT>
56
57 template<typename PixelT>
62
63}}}} // end of namespace lsst::ip::diffim::detail
64
65#endif
A class to represent a 2-dimensional array of pixels.
Definition Statistics.h:40
void addImage(std::shared_ptr< ImageT > img, double flux=0.0)
Add an image to the set to be analyzed.
Definition ImagePca.cc:64
ImageList const & getEigenImages() const
Return Eigen images.
Definition ImagePca.h:100
std::vector< double > const & getEigenValues() const
Return Eigen values.
Definition ImagePca.h:98
Base class for candidate objects in a SpatialCell.
Definition SpatialCell.h:70
Overrides the analyze method of base class afwImage::ImagePca.
Definition KernelPca.h:24
KernelPca(bool constantWeight=true)
Ctor.
Definition KernelPca.h:33
virtual void analyze()
Generate eigenimages that are normalised.
Definition KernelPca.cc:163
std::shared_ptr< KernelPca< ImageT > > Ptr
Definition KernelPca.h:27
A class to run a PCA on all candidate kernels (represented as Images).
Definition KernelPca.h:40
std::shared_ptr< KernelPcaVisitor< PixelT > > Ptr
Definition KernelPca.h:43
void processCandidate(lsst::afw::math::SpatialCellCandidate *candidate)
Definition KernelPca.cc:89
std::shared_ptr< ImageT > returnMean()
Definition KernelPca.h:51
lsst::afw::math::KernelList getEigenKernels()
Definition KernelPca.cc:65
KernelPcaVisitor(std::shared_ptr< KernelPca< ImageT > > imagePca)
Definition KernelPca.cc:56
lsst::afw::image::Image< lsst::afw::math::Kernel::Pixel > ImageT
Definition KernelPca.h:42
std::shared_ptr< KernelPcaVisitor< PixelT > > makeKernelPcaVisitor(std::shared_ptr< KernelPca< typename KernelPcaVisitor< PixelT >::ImageT > > imagePca)
Definition KernelPca.h:59