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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KernelPca.h
Go to the documentation of this file.
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 Image.h:51
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