lsst.meas.algorithms
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src
ImagePca.cc
Go to the documentation of this file.
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// -*- LSST-C++ -*-
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/*
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* LSST Data Management System
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* Copyright 2008, 2009, 2010 LSST Corporation.
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*
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* This product includes software developed by the
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* LSST Project (http://www.lsst.org/).
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*
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* This program is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the LSST License Statement and
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* the GNU General Public License along with this program. If not,
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* see <http://www.lsstcorp.org/LegalNotices/>.
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*/
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#include "
lsst/afw.h
"
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#include "
lsst/meas/algorithms/ImagePca.h
"
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namespace
lsst
{
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namespace
meas
{
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namespace
algorithms
{
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template
<
typename
ImageT>
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void
PsfImagePca<ImageT>::analyze
() {
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Super::analyze
();
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typename
Super::ImageList
const
&eImageList = this->
getEigenImages
();
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typename
Super::ImageList::const_iterator iter = eImageList.
begin
(), end = eImageList.
end
();
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for
(
size_t
i = 0; iter != end; ++i, ++iter) {
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std::shared_ptr<ImageT>
eImage = *iter;
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/*
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* Normalise eigenImages to have a maximum of 1.0. For n > 0 they
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* (should) have mean == 0, so we can't use that to normalize
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*/
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afw::math::Statistics
stats =
afw::math::makeStatistics
(*eImage, (
afw::math::MIN
|
afw::math::MAX
));
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double
const
min = stats.
getValue
(
afw::math::MIN
);
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double
const
max = stats.
getValue
(
afw::math::MAX
);
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double
const
extreme = (fabs(min) > max) ? min : max;
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if
(extreme != 0.0) {
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*eImage /= extreme;
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}
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/*
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* Estimate and subtract the mean background level from the i > 0
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* eigen images; if we don't do that then PSF variation can get mixed
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* with subtle variations in the background and potentially amplify
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* them disasterously.
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*
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* It is not at all clear that doing this is a good idea; it'd be
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* better to get the sky level right in the first place.
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*/
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if
(i > 0 && _border > 0) {
/* not the zeroth KL component */
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int
const
height = eImage->getHeight();
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int
const
width = eImage->getWidth();
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double
background;
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if
(2 * _border >=
std::min
(height, width)) {
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// _Border consumes the entire image
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background =
afw::math::makeStatistics
(*
afw::image::GetImage<ImageT>::getImage
(eImage),
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afw::math::MEDIAN
)
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.
getValue
();
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}
else
{
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// Use the median of the edge pixels
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// If ImageT is a MaskedImage, unpack the Image
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std::shared_ptr<typename afw::image::GetImage<ImageT>::type
> eImageIm =
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afw::image::GetImage<ImageT>::getImage
(eImage);
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int
const
nEdge = width * height - (width - 2 * _border) * (height - 2 * _border);
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std::vector<double>
edgePixels(nEdge);
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std::vector<double>::iterator bi = edgePixels.
begin
();
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typedef
typename
afw::image::GetImage<ImageT>::type::x_iterator
imIter;
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int
y = 0;
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for
(; y != _border; ++y) {
// Bottom border of eImage
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for
(imIter ptr = eImageIm->row_begin(y), end = eImageIm->row_end(y); ptr != end;
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++ptr, ++bi) {
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*bi = *ptr;
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}
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}
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for
(; y != height - _border; ++y) {
// Left and right borders of eImage
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for
(imIter ptr = eImageIm->row_begin(y), end = eImageIm->x_at(_border, y); ptr != end;
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++ptr, ++bi) {
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*bi = *ptr;
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}
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for
(imIter ptr = eImageIm->x_at(width - _border, y), end = eImageIm->row_end(y);
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ptr != end; ++ptr, ++bi) {
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*bi = *ptr;
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}
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}
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for
(; y != height; ++y) {
// Top border of eImage
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for
(imIter ptr = eImageIm->row_begin(y), end = eImageIm->row_end(y); ptr != end;
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++ptr, ++bi) {
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*bi = *ptr;
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}
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}
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assert(
std::distance
(edgePixels.
begin
(), bi) == nEdge);
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background =
afw::math::makeStatistics
(edgePixels,
afw::math::MEDIAN
).
getValue
();
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}
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*eImage -= background;
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}
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}
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}
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#define INSTANTIATE_IMAGE(IMAGE) template class PsfImagePca<IMAGE>;
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#define INSTANTIATE(TYPE) \
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INSTANTIATE_IMAGE(afw::image::Image<TYPE>); \
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INSTANTIATE_IMAGE(afw::image::MaskedImage<TYPE>);
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INSTANTIATE
(
float
);
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}
// namespace algorithms
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}
// namespace meas
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}
// namespace lsst
INSTANTIATE
#define INSTANTIATE(TYPE)
Definition
ImagePca.cc:127
ImagePca.h
Class for doing PCA on PSF stars.
afw.h
std::vector::begin
T begin(T... args)
lsst::afw::image::ImagePca< ImageT >::getEigenImages
ImageList const & getEigenImages() const
lsst::afw::image::ImagePca< ImageT >::ImageList
std::vector< std::shared_ptr< ImageT > > ImageList
lsst::afw::image::ImagePca< ImageT >::analyze
virtual void analyze()
lsst::afw::math::Statistics
lsst::afw::math::Statistics::getValue
double getValue(Property const prop=NOTHING) const
lsst::meas::algorithms::PsfImagePca::analyze
virtual void analyze()
Generate eigenimages that are normalised and background-subtracted.
Definition
ImagePca.cc:41
std::distance
T distance(T... args)
std::vector::end
T end(T... args)
std::min
T min(T... args)
lsst::afw::math::makeStatistics
Statistics makeStatistics(lsst::afw::image::Image< Pixel > const &img, lsst::afw::image::Mask< image::MaskPixel > const &msk, int const flags, StatisticsControl const &sctrl=StatisticsControl())
lsst::afw::math::MIN
MIN
lsst::afw::math::MEDIAN
MEDIAN
lsst::afw::math::MAX
MAX
lsst::meas::algorithms
Definition
mainpage.dox:13
lsst::meas
lsst
std::shared_ptr
lsst::afw::image::GetImage
std::vector
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