lsst.ip.diffim  20.0.0-9-g4aef684+c1174c9ddd
KernelPca.cc
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1 // -*- lsst-c++ -*-
12 #include "lsst/afw/math.h"
13 #include "lsst/afw/image.h"
14 #include "lsst/log/Log.h"
16 
19 
20 namespace afwMath = lsst::afw::math;
21 namespace afwImage = lsst::afw::image;
23 
24 namespace lsst {
25 namespace ip {
26 namespace diffim {
27 namespace detail {
28 
55  template<typename PixelT>
58  ) :
59  afwMath::CandidateVisitor(),
60  _imagePca(imagePca),
61  _mean()
62  {};
63 
64  template<typename PixelT>
66  afwMath::KernelList kernelList;
67 
68  std::vector<std::shared_ptr<ImageT>> eigenImages = _imagePca->getEigenImages();
69  int ncomp = eigenImages.size();
70 
71  if (_mean) {
75  (*_mean, true))));
76  }
77  for (int i = 0; i < ncomp; i++) {
79  afwImage::Image<afwMath::Kernel::Pixel>(*eigenImages[i], true);
81  new afwMath::FixedKernel(img)
82  ));
83  }
84 
85  return kernelList;
86  }
87 
88  template<typename PixelT>
90 
91  KernelCandidate<PixelT> *kCandidate = dynamic_cast<KernelCandidate<PixelT> *>(candidate);
92  if (kCandidate == NULL) {
94  "Failed to cast SpatialCellCandidate to KernelCandidate");
95  }
96  LOGL_DEBUG("TRACE5.ip.diffim.SetPcaImageVisitor.processCandidate",
97  "Processing candidate %d", kCandidate->getId());
98 
99  try {
100  /* Normalize to unit sum */
101  PTR(ImageT) kImage = kCandidate->getKernelSolution(
102  KernelCandidate<PixelT>::ORIG)->makeKernelImage();
103  *kImage /= kCandidate->getKernelSolution(
104  KernelCandidate<PixelT>::ORIG)->getKsum();
105  /* Tell imagePca they have the same weighting in the Pca */
106  _imagePca->addImage(kImage, 1.0);
107  } catch(pexExcept::Exception &e) {
108  return;
109  }
110  }
111 
112  template<typename PixelT>
114  /*
115  If we don't subtract off the mean before we do the Pca, the
116  subsequent terms carry less of the power than if you do subtract
117  off the mean. Explicit example:
118 
119  With mean subtraction:
120  DEBUG: Eigenvalue 0 : 0.010953 (0.373870 %)
121  DEBUG: Eigenvalue 1 : 0.007927 (0.270604 %)
122  DEBUG: Eigenvalue 2 : 0.001393 (0.047542 %)
123  DEBUG: Eigenvalue 3 : 0.001092 (0.037261 %)
124  DEBUG: Eigenvalue 4 : 0.000829 (0.028283 %)
125 
126  Without mean subtraction:
127  DEBUG: Eigenvalue 0 : 0.168627 (0.876046 %)
128  DEBUG: Eigenvalue 1 : 0.007935 (0.041223 %)
129  DEBUG: Eigenvalue 2 : 0.006049 (0.031424 %)
130  DEBUG: Eigenvalue 3 : 0.001188 (0.006173 %)
131  DEBUG: Eigenvalue 4 : 0.001050 (0.005452 %)
132 
133  After the first term above, which basically represents the mean,
134  the remaining terms carry less of the power than if you do
135  subtract off the mean. (0.041223/(1-0.876046) < 0.373870).
136  */
137  LOGL_DEBUG("TRACE5.ip.diffim.KernelPcaVisitor.subtractMean",
138  "Subtracting mean feature before Pca");
139 
140  _mean = _imagePca->getMean();
141  KernelPca<ImageT>::ImageList imageList = _imagePca->getImageList();
142  for (typename KernelPca<ImageT>::ImageList::const_iterator ptr = imageList.begin(),
143  end = imageList.end(); ptr != end; ++ptr) {
144  **ptr -= *_mean;
145  }
146  }
147 
162  template <typename ImageT>
164  {
165  Super::analyze();
166 
167  typename Super::ImageList const &eImageList = this->getEigenImages();
168  typename Super::ImageList::const_iterator iter = eImageList.begin(), end = eImageList.end();
169  for (size_t i = 0; iter != end; ++i, ++iter) {
170  PTR(ImageT) eImage = *iter;
171 
172  /*
173  * Normalise eigenImages to have a maximum of 1.0. For n > 0 they
174  * (should) have mean == 0, so we can't use that to normalize
175  */
176  afwMath::Statistics stats = afwMath::makeStatistics(*eImage, (afwMath::MIN | afwMath::MAX));
177  double const min = stats.getValue(afwMath::MIN);
178  double const max = stats.getValue(afwMath::MAX);
179 
180  double const extreme = (fabs(min) > max) ? min :max;
181  if (extreme != 0.0) {
182  *eImage /= extreme;
183  }
184  }
185  }
186 
187 
188  typedef float PixelT;
189  template class KernelPcaVisitor<PixelT>;
191 
192 }}}} // end of namespace lsst::ip::diffim::detail
lsst::afw::image
lsst::afw::math::SpatialCellCandidate
std::shared_ptr
STL class.
lsst::ip::diffim::detail::KernelPca
Overrides the analyze method of base class afwImage::ImagePca.
Definition: KernelPca.h:24
std::vector
STL class.
std::vector::size
T size(T... args)
lsst::ip::diffim::KernelCandidate
Class stored in SpatialCells for spatial Kernel fitting.
Definition: KernelCandidate.h:39
lsst::ip::diffim::detail::KernelPca::analyze
virtual void analyze()
Generate eigenimages that are normalised.
Definition: KernelPca.cc:163
lsst::afw::math::FixedKernel
lsst::ip::diffim::detail::PixelT
float PixelT
Definition: AssessSpatialKernelVisitor.cc:208
Runtime.h
lsst::ip::diffim::detail::KernelPcaVisitor::processCandidate
void processCandidate(lsst::afw::math::SpatialCellCandidate *candidate)
Definition: KernelPca.cc:89
lsst::afw::math::Statistics::getValue
double getValue(Property const prop=NOTHING) const
iter
def iter(self)
end
int end
LOGL_DEBUG
#define LOGL_DEBUG(logger, message...)
std::vector::push_back
T push_back(T... args)
lsst::ip::diffim::detail::KernelPcaVisitor
A class to run a PCA on all candidate kernels (represented as Images).
Definition: KernelPca.h:40
image.h
lsst::ip::diffim::detail::KernelPcaVisitor::KernelPcaVisitor
KernelPcaVisitor(std::shared_ptr< KernelPca< ImageT > > imagePca)
Definition: KernelPca.cc:56
PTR
#define PTR(...)
lsst::pex::exceptions::LogicError
lsst::ip::diffim::detail::KernelPcaVisitor::getEigenKernels
lsst::afw::math::KernelList getEigenKernels()
Definition: KernelPca.cc:65
math.h
lsst::afw::math::SpatialCellImageCandidate::getId
int getId() const
max
int max
lsst
LSST_EXCEPT
#define LSST_EXCEPT(type,...)
Log.h
lsst::ip::diffim::KernelCandidate::getKernelSolution
std::shared_ptr< StaticKernelSolution< PixelT > > getKernelSolution(CandidateSwitch cand) const
Definition: KernelCandidate.cc:322
KernelPca.h
Declaration of KernelPca and KernelPcaVisitor.
lsst::ip::diffim::detail::KernelPcaVisitor::subtractMean
void subtractMean()
Definition: KernelPca.cc:113
std::vector::begin
T begin(T... args)
min
int min
lsst::afw::math
KernelCandidate.h
Class used by SpatialModelCell for spatial Kernel fitting.
lsst::afw::math::Statistics
lsst::pex::exceptions
lsst::pex::exceptions::Exception
std::vector::end
T end(T... args)
lsst::afw::image::Image