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
KernelSumVisitor.cc
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1 // -*- lsst-c++ -*-
11 #include <limits>
12 
13 #include "lsst/afw/math.h"
14 #include "lsst/log/Log.h"
17 
20 
21 namespace afwMath = lsst::afw::math;
22 namespace dafBase = lsst::daf::base;
24 
25 namespace lsst {
26 namespace ip {
27 namespace diffim {
28 namespace detail {
29 
64  template<typename PixelT>
67  ) :
68  afwMath::CandidateVisitor(),
69  _mode(AGGREGATE),
70  _kSums(std::vector<double>()),
71  _kSumMean(0.),
72  _kSumStd(0.),
73  _dkSumMax(0.),
74  _kSumNpts(0),
75  _nRejected(0),
76  _ps(ps.deepCopy())
77  {};
78 
79  template<typename PixelT>
81  _kSums.clear();
82  _kSumMean = 0.;
83  _kSumStd = 0.;
84  _dkSumMax = 0.;
85  _kSumNpts = 0;
86  _nRejected = 0;
87  }
88 
89  template<typename PixelT>
91  *candidate) {
92 
93  KernelCandidate<PixelT> *kCandidate = dynamic_cast<KernelCandidate<PixelT> *>(candidate);
94  if (kCandidate == NULL) {
96  "Failed to cast SpatialCellCandidate to KernelCandidate");
97  }
98  LOGL_DEBUG("TRACE5.ip.diffim.KernelSumVisitor.processCandidate",
99  "Processing candidate %d, mode %d", kCandidate->getId(), _mode);
100 
101  /* Grab all kernel sums and look for outliers */
102  if (_mode == AGGREGATE) {
103  _kSums.push_back(kCandidate->getKernelSolution(KernelCandidate<PixelT>::ORIG)->getKsum());
104  }
105  else if (_mode == REJECT) {
106  if (_ps->getAsBool("kernelSumClipping")) {
107  double kSum =
108  kCandidate->getKernelSolution(KernelCandidate<PixelT>::ORIG)->getKsum();
109 
110  if (fabs(kSum - _kSumMean) > _dkSumMax) {
112  LOGL_DEBUG("TRACE3.ip.diffim.KernelSumVisitor.processCandidate",
113  "Rejecting candidate %d; bad source kernel sum : (%.2f)",
114  kCandidate->getId(),
115  kSum);
116  _nRejected += 1;
117  }
118  }
119  else {
120  LOGL_DEBUG("TRACE5.ip.diffim.KernelSumVisitor.processCandidate",
121  "Sigma clipping not enabled");
122  }
123  }
124  }
125 
126  template<typename PixelT>
128  if (_kSums.size() == 0) {
130  "Unable to determine kernel sum; 0 candidates");
131  }
132  else if (_kSums.size() == 1) {
133  LOGL_DEBUG("TRACE1.ip.diffim.KernelSumVisitor.processKsumDistribution",
134  "WARNING: only 1 kernel candidate");
135 
136  _kSumMean = _kSums[0];
137  _kSumStd = 0.0;
138  _kSumNpts = 1;
139  }
140  else {
141  try {
146  _kSumMean = stats.getValue(afwMath::MEANCLIP);
147  _kSumStd = stats.getValue(afwMath::STDEVCLIP);
148  _kSumNpts = static_cast<int>(stats.getValue(afwMath::NPOINT));
149  } catch (pexExcept::Exception &e) {
150  LSST_EXCEPT_ADD(e, "Unable to calculate kernel sum statistics");
151  throw e;
152  }
153  if (std::isnan(_kSumMean)) {
155  str(boost::format("Mean kernel sum returns NaN (%d points)")
156  % _kSumNpts));
157  }
158  if (std::isnan(_kSumStd)) {
160  str(boost::format("Kernel sum stdev returns NaN (%d points)")
161  % _kSumNpts));
162  }
163  }
164  _dkSumMax = _ps->getAsDouble("maxKsumSigma") * _kSumStd;
165  LOGL_DEBUG("TRACE1.ip.diffim.KernelSumVisitor.processCandidate",
166  "Kernel Sum Distribution : %.3f +/- %.3f (%d points)",
167  _kSumMean, _kSumStd, _kSumNpts);
168  }
169 
170  typedef float PixelT;
171 
172  template class KernelSumVisitor<PixelT>;
173 
176 
177 }}}} // end of namespace lsst::ip::diffim::detail
#define LSST_EXCEPT_ADD(e, m)
Add the current location and a message to an existing exception before rethrowing it.
Definition: Exception.h:54
#define LSST_EXCEPT(type,...)
Create an exception with a given type.
Definition: Exception.h:48
Class used by SpatialModelCell for spatial Kernel fitting.
Declaration of KernelSumVisitor.
LSST DM logging module built on log4cxx.
#define LOGL_DEBUG(logger, message...)
Log a debug-level message using a varargs/printf style interface.
Definition: Log.h:515
Base class for candidate objects in a SpatialCell.
Definition: SpatialCell.h:70
int getId() const
Return the candidate's unique ID.
Definition: SpatialCell.h:102
void setStatus(Status status)
Set the candidate's status.
Definition: SpatialCell.cc:53
A class to evaluate image statistics.
Definition: Statistics.h:220
double getValue(Property const prop=NOTHING) const
Return the value of the desired property (if specified in the constructor)
Definition: Statistics.cc:1047
Class for storing generic metadata.
Definition: PropertySet.h:66
Class stored in SpatialCells for spatial Kernel fitting.
std::shared_ptr< StaticKernelSolution< PixelT > > getKernelSolution(CandidateSwitch cand) const
A class to accumulate kernel sums across SpatialCells.
KernelSumVisitor(lsst::daf::base::PropertySet const &ps)
void processCandidate(lsst::afw::math::SpatialCellCandidate *candidate)
Provides consistent interface for LSST exceptions.
Definition: Exception.h:107
Reports errors in the logical structure of the program.
Definition: Runtime.h:46
T isnan(T... args)
Statistics makeStatistics(lsst::afw::image::Image< Pixel > const &img, lsst::afw::image::Mask< image::MaskPixel > const &msk, int const flags, StatisticsControl const &sctrl=StatisticsControl())
Handle a watered-down front-end to the constructor (no variance)
Definition: Statistics.h:359
@ STDEVCLIP
estimate sample N-sigma clipped stdev (N set in StatisticsControl, default=3)
Definition: Statistics.h:72
@ MEANCLIP
estimate sample N-sigma clipped mean (N set in StatisticsControl, default=3)
Definition: Statistics.h:71
@ NPOINT
number of sample points
Definition: Statistics.h:65
template std::shared_ptr< KernelSumVisitor< PixelT > > makeKernelSumVisitor< PixelT >(lsst::daf::base::PropertySet const &)
def format(config, name=None, writeSourceLine=True, prefix="", verbose=False)
Definition: history.py:174
A base class for image defects.
STL namespace.