CR.cc

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// -*- LSST-C++ -*-
 
/*
 * LSST Data Management System
 * Copyright 2008-2016 AURA/LSST.
 *
 * This product includes software developed by the
 * LSST Project (http://www.lsst.org/).
 *
 * This program is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the LSST License Statement and
 * the GNU General Public License along with this program.  If not,
 * see <https://www.lsstcorp.org/LegalNotices/>.
 */

#include <stdexcept>
#include <algorithm>
#include <cassert>
#include <string>
#include <typeinfo>
 
#include <iostream>
 
#include "boost/format.hpp"
 
#include "lsst/pex/exceptions.h"
#include "lsst/log/Log.h"
#include "lsst/pex/exceptions.h"
#include "lsst/afw/detection/Footprint.h"
#include "lsst/afw/geom.h"
#include "lsst/afw/detection/Psf.h"
#include "lsst/afw/image/MaskedImage.h"
#include "lsst/afw/math/Random.h"
#include "lsst/meas/algorithms/CR.h"
#include "lsst/meas/algorithms/Interp.h"
 
/*
 * TODO: These should go into afw --- actually, there're already there, but
 * in an anon namespace (DM-35750).
 */
namespace lsst {
namespace afw {
namespace detection {
class IdSpan {
public:
    typedef std::shared_ptr<IdSpan> Ptr;
    typedef std::shared_ptr<const IdSpan> ConstPtr;
 
    explicit IdSpan(int id, int y, int x0, int x1) : id(id), y(y), x0(x0), x1(x1) {}
    int id;     /* ID for object */
    int y;      /* Row wherein IdSpan dwells */
    int x0, x1; /* inclusive range of columns */
};

  struct IdSpanCompar {
    bool operator()(const IdSpan::ConstPtr a, const IdSpan::ConstPtr b) {
        if (a->id < b->id) {
            return true;
        } else if (a->id > b->id) {
            return false;
        } else {
            if (a->y < b->y) {
                return true;
            } else if (a->y > b->y) {
                return false;
            } else {
                return (a->x0 < b->x0) ? true : false;
            }
        }
    }
};

int resolve_alias(const std::vector<int> &aliases, /* list of aliases */
                  int id) {                        /* alias to look up */
    int resolved = id;                             /* resolved alias */
 
    while (id != aliases[id]) {
        resolved = id = aliases[id];
    }
 
    return (resolved);
}
}  // namespace detection
}  // namespace afw
}  // namespace lsst
 
namespace lsst {
namespace meas {
namespace algorithms {
 
namespace {
 
template <typename ImageT, typename MaskT>
void removeCR(afw::image::MaskedImage<ImageT, MaskT> &mi,
              std::vector<std::shared_ptr<afw::detection::Footprint>> &CRs, double const bkgd, MaskT const,
              MaskT const saturBit, MaskT const badMask, bool const debias, bool const grow);
 
template <typename ImageT>
bool condition_3(ImageT *estimate, double const peak, double const mean_ns, double const mean_we,
                 double const mean_swne, double const mean_nwse, double const dpeak, double const dmean_ns,
                 double const dmean_we, double const dmean_swne, double const dmean_nwse, double const thresH,
                 double const thresV, double const thresD, double const cond3Fac);
 
/************************************************************************************************************/
//
// A class to hold a detected pixel
template <typename ImageT>
struct CRPixel {
    typedef typename std::shared_ptr<CRPixel> Ptr;
 
    CRPixel(int _col, int _row, ImageT _val, int _id = -1) : id(_id), col(_col), row(_row), val(_val) {
        _i = ++i;
    }
    ~CRPixel() {}
 
    bool operator<(const CRPixel &a) const { return _i < a._i; }
 
    int get_i() const { return _i; }
 
    int id;      // Unique ID for cosmic ray (not cosmic ray pixel)
    int col;     // position
    int row;     //    of pixel
    ImageT val;  // initial value of pixel
private:
    static int i;    // current value of running index
    int mutable _i;  // running index
};
 
template <typename ImageT>
int CRPixel<ImageT>::i = 0;
 
template <typename ImageT>
struct Sort_CRPixel_by_id {
    bool operator()(CRPixel<ImageT> const &a, CRPixel<ImageT> const &b) const { return a.id < b.id; }
};
 
/*****************************************************************************/
/*
 * This is the code to see if a given pixel is bad
 *
 * Note that the pixel in question is at index 0, so its value is pt_0[0]
 */
template <typename MaskedImageT>
bool is_cr_pixel(typename MaskedImageT::Image::Pixel *corr,  // corrected value
                 typename MaskedImageT::xy_locator loc,      // locator for this pixel
                 double const minSigma,                      // minSigma, or -threshold if negative
                 double const thresH, double const thresV, double const thresD,  // for condition #3
                 double const bkgd,     // unsubtracted background level
                 double const cond3Fac  // fiddle factor for condition #3
) {
    typedef typename MaskedImageT::Image::Pixel ImagePixel;
    //
    // Unpack some values
    //
    ImagePixel const v_00 = loc.image(0, 0);
 
    if (v_00 < 0) {
        return false;
    }
    /*
     * condition #1 is not applied on a pixel-by-pixel basis
     */
    ;
    /*
     * condition #2
     */
    ImagePixel const mean_we = (loc.image(-1, 0) + loc.image(1, 0)) / 2;  // avgs of surrounding 8 pixels
    ImagePixel const mean_ns = (loc.image(0, 1) + loc.image(0, -1)) / 2;
    ImagePixel const mean_swne = (loc.image(-1, -1) + loc.image(1, 1)) / 2;
    ImagePixel const mean_nwse = (loc.image(-1, 1) + loc.image(1, -1)) / 2;
 
    if (minSigma < 0) { /* |thres_sky_sigma| is threshold */
        if (v_00 < -minSigma) {
            return false;
        }
    } else {
        double const thres_sky_sigma = minSigma * sqrt(loc.variance(0, 0));
 
        if (v_00 < mean_ns + thres_sky_sigma && v_00 < mean_we + thres_sky_sigma &&
            v_00 < mean_swne + thres_sky_sigma && v_00 < mean_nwse + thres_sky_sigma) {
            return false;
        }
    }
    /*
     * condition #3
     *
     * Note that this uses mean_ns etc. even if minSigma is negative
     */
    double const dv_00 = sqrt(loc.variance(0, 0));
    // standard deviation of means of surrounding pixels
    double const dmean_we = sqrt(loc.variance(-1, 0) + loc.variance(1, 0)) / 2;
    double const dmean_ns = sqrt(loc.variance(0, 1) + loc.variance(0, -1)) / 2;
    double const dmean_swne = sqrt(loc.variance(-1, -1) + loc.variance(1, 1)) / 2;
    double const dmean_nwse = sqrt(loc.variance(-1, 1) + loc.variance(1, -1)) / 2;
 
    if (!condition_3(corr, v_00 - bkgd, mean_ns - bkgd, mean_we - bkgd, mean_swne - bkgd, mean_nwse - bkgd,
                     dv_00, dmean_ns, dmean_we, dmean_swne, dmean_nwse, thresH, thresV, thresD, cond3Fac)) {
        return false;
    }
    /*
     * OK, it's a contaminated pixel
     */
    *corr += static_cast<ImagePixel>(bkgd);
 
    return true;
}
 
/************************************************************************************************************/
//
// Worker routine to process the pixels adjacent to a span (including the points just
// to the left and just to the right)
//
template <typename MaskedImageT>
void checkSpanForCRs(afw::detection::Footprint *extras,  // Extra spans get added to this Footprint
                     std::vector<CRPixel<typename MaskedImageT::Image::Pixel>> &crpixels,
                     // a list of pixels containing CRs
                     int const y,                 // the row to process
                     int const x0, int const x1,  // range of pixels in the span (inclusive)
                     MaskedImageT &image,         
                     double const minSigma,       // minSigma
                     double const thresH, double const thresV, double const thresD,  // for cond. #3
                     double const bkgd,      // unsubtracted background level
                     double const cond3Fac,  // fiddle factor for condition #3
                     bool const keep         // if true, don't remove the CRs
) {
    typedef typename MaskedImageT::Image::Pixel MImagePixel;
    typename MaskedImageT::xy_locator loc = image.xy_at(x0 - 1, y);  // locator for data
 
    int const imageX0 = image.getX0();
    int const imageY0 = image.getY0();
 
    for (int x = x0 - 1; x <= x1 + 1; ++x) {
        MImagePixel corr = 0;  // new value for pixel
        if (is_cr_pixel<MaskedImageT>(&corr, loc, minSigma, thresH, thresV, thresD, bkgd, cond3Fac)) {
            if (keep) {
                crpixels.push_back(CRPixel<MImagePixel>(x + imageX0, y + imageY0, loc.image()));
            }
            loc.image() = corr;
 
            std::vector<afw::geom::Span> spanList(extras->getSpans()->begin(), extras->getSpans()->end());
            spanList.push_back(afw::geom::Span(y + imageY0, x + imageX0, x + imageX0));
            extras->setSpans(std::make_shared<afw::geom::SpanSet>(std::move(spanList)));
        }
        ++loc.x();
    }
}
 
/************************************************************************************************************/
/*
 * Find the sum of the pixels in a Footprint
 */
template <typename ImageT>
class CountsInCR {
public:
    CountsInCR(double const bkgd) : _bkgd(bkgd), _sum(0.0) {}
 
    void operator()(geom::Point2I const &point, ImageT const &val) { _sum += val - _bkgd; }
 
    virtual void reset(afw::detection::Footprint const &) {}
    virtual void reset() { _sum = 0.0; }
 
    double getCounts() const { return _sum; }
 
private:
    double const _bkgd;  // the Image's background level
    ImageT _sum;         // the sum of all DN in the Footprint, corrected for bkgd
};
}  // namespace
 
/*
 * Restore all the pixels in crpixels to their pristine state
 */
template <typename ImageT>
static void reinstateCrPixels(
        ImageT *image,                                                // the image in question
        std::vector<CRPixel<typename ImageT::Pixel>> const &crpixels  // a list of pixels with CRs
) {
    if (crpixels.empty()) return;
 
    typedef typename std::vector<CRPixel<typename ImageT::Pixel>>::const_iterator crpixel_iter;
    for (crpixel_iter crp = crpixels.begin(), end = crpixels.end(); crp < end - 1; ++crp) {
        *image->at(crp->col - image->getX0(), crp->row - image->getY0()) = crp->val;
    }
}

template <typename MaskedImageT>
std::vector<std::shared_ptr<afw::detection::Footprint>> findCosmicRays(
        MaskedImageT &mimage,               
        afw::detection::Psf const &psf,     
        double const bkgd,                  
        daf::base::PropertySet const &ps,   
        bool const keep                     
) {
    typedef typename MaskedImageT::Image ImageT;
    typedef typename ImageT::Pixel ImagePixel;
    typedef typename MaskedImageT::Mask::Pixel MaskPixel;
 
    // Parse the PropertySet
    double const minSigma = ps.getAsDouble("minSigma");       // min sigma over sky in pixel for CR candidate
    double const minDn = ps.getAsDouble("min_DN");            // min number of DN in an CRs
    double const cond3Fac = ps.getAsDouble("cond3_fac");      // fiddle factor for condition #3
    double const cond3Fac2 = ps.getAsDouble("cond3_fac2");    // 2nd fiddle factor for condition #3
    int const niteration = ps.getAsInt("niteration");         // Number of times to look for contaminated
                                                              // pixels near CRs
    int const nCrPixelMax = ps.getAsInt("nCrPixelMax");       // maximum number of contaminated pixels
                                                              /*
                                                               * thresholds for 3rd condition
                                                               *
                                                               * Realise PSF at center of image
                                                               */
    std::shared_ptr<afw::math::Kernel const> kernel = psf.getLocalKernel(psf.getAveragePosition());
    if (!kernel) {
        throw LSST_EXCEPT(pexExcept::NotFoundError, "Psf is unable to return a kernel");
    }
    afw::detection::Psf::Image psfImage =
            afw::detection::Psf::Image(geom::ExtentI(kernel->getWidth(), kernel->getHeight()));
    kernel->computeImage(psfImage, true);
 
    int const xc = kernel->getCtr().getX();  // center of PSF
    int const yc = kernel->getCtr().getY();
 
    double const I0 = psfImage(xc, yc);
    double const thresH =
            cond3Fac2 * (0.5 * (psfImage(xc - 1, yc) + psfImage(xc + 1, yc))) / I0;  // horizontal
    double const thresV = cond3Fac2 * (0.5 * (psfImage(xc, yc - 1) + psfImage(xc, yc + 1))) / I0;  // vertical
    double const thresD = cond3Fac2 *
                          (0.25 * (psfImage(xc - 1, yc - 1) + psfImage(xc + 1, yc + 1) +
                                   psfImage(xc - 1, yc + 1) + psfImage(xc + 1, yc - 1))) /
                          I0;                                                  // diag
                                                                               /*
                                                                                * Setup desired mask planes
                                                                                */
    MaskPixel const badBit = mimage.getMask()->getPlaneBitMask("BAD");         // Generic bad pixels
    MaskPixel const crBit = mimage.getMask()->getPlaneBitMask("CR");           // CR-contaminated pixels
    MaskPixel const interpBit = mimage.getMask()->getPlaneBitMask("INTRP");    // Interpolated pixels
    MaskPixel const saturBit = mimage.getMask()->getPlaneBitMask("SAT");       // Saturated pixels
    MaskPixel const nodataBit = mimage.getMask()->getPlaneBitMask("NO_DATA");  // Non data pixels
 
    MaskPixel const badMask = (badBit | interpBit | saturBit | nodataBit);  // naughty pixels
                                                                            /*
                                                                             * Go through the frame looking at each pixel (except the edge ones which we ignore)
                                                                             */
    int const ncol = mimage.getWidth();
    int const nrow = mimage.getHeight();
 
    std::vector<CRPixel<ImagePixel>> crpixels;  // storage for detected CR-contaminated pixels
    typedef typename std::vector<CRPixel<ImagePixel>>::iterator crpixel_iter;
    typedef typename std::vector<CRPixel<ImagePixel>>::reverse_iterator crpixel_riter;
 
    for (int j = 1; j < nrow - 1; ++j) {
        typename MaskedImageT::xy_locator loc = mimage.xy_at(1, j);  // locator for data
 
        for (int i = 1; i < ncol - 1; ++i, ++loc.x()) {
            ImagePixel corr = 0;
            if (!is_cr_pixel<MaskedImageT>(&corr, loc, minSigma, thresH, thresV, thresD, bkgd, cond3Fac)) {
                continue;
            }
            /*
             * condition #4
             */
            if (loc.mask() & badMask) {
                continue;
            }
            if ((loc.mask(-1, 1) | loc.mask(0, 1) | loc.mask(1, 1) | loc.mask(-1, 0) | loc.mask(1, 0) |
                 loc.mask(-1, -1) | loc.mask(0, -1) | loc.mask(1, -1)) &
                interpBit) {
                continue;
            }
            /*
             * OK, it's a CR
             *
             * replace CR-contaminated pixels with reasonable values as we go through
             * image, which increases the detection rate
             */
            crpixels.push_back(CRPixel<ImagePixel>(i + mimage.getX0(), j + mimage.getY0(), loc.image()));
            loc.image() = corr; /* just a preliminary estimate */
 
            if (static_cast<int>(crpixels.size()) > nCrPixelMax) {
                reinstateCrPixels(mimage.getImage().get(), crpixels);
 
                throw LSST_EXCEPT(pex::exceptions::LengthError,
                                  (boost::format("Too many CR pixels (max %d)") % nCrPixelMax).str());
            }
        }
    }
    /*
     * We've found them on a pixel-by-pixel basis, now merge those pixels
     * into cosmic rays
     */
    std::vector<int> aliases;                  // aliases for initially disjoint parts of CRs
    aliases.reserve(1 + crpixels.size() / 2);  // initial size of aliases
 
    std::vector<afw::detection::IdSpan::Ptr> spans;  // y:x0,x1 for objects
    spans.reserve(aliases.capacity());               // initial size of spans
 
    aliases.push_back(0);  // 0 --> 0

 
    int ncr = 0;  // number of detected cosmic rays
    if (!crpixels.empty()) {
        int id;                        // id number for a CR
        int x0 = -1, x1 = -1, y = -1;  // the beginning and end column, and row of this span in a CR
 
        // I am dummy
        CRPixel<ImagePixel> dummy(0, -1, 0, -1);
        crpixels.push_back(dummy);
        // printf("Created dummy CR: i %i, id %i, col %i, row %i, val %g\n", dummy.get_i(), dummy.id,
        // dummy.col, dummy.row, (double)dummy.val);
        for (crpixel_iter crp = crpixels.begin(); crp < crpixels.end() - 1; ++crp) {
            // printf("Looking at CR: i %i, id %i, col %i, row %i, val %g\n", crp->get_i(), crp->id, crp->col,
            // crp->row, (double)crp->val);
 
            if (crp->id < 0) {    // not already assigned
                crp->id = ++ncr;  // a new CR
                aliases.push_back(crp->id);
                y = crp->row;
                x0 = x1 = crp->col;
                // printf("  Assigned ID %i; looking at row %i, start col %i\n", crp->id, crp->row, crp->col);
            }
            id = crp->id;
            // printf("  Next CRpix has i=%i, id=%i, row %i, col %i\n", crp[1].get_i(), crp[1].id, crp[1].row,
            // crp[1].col);
 
            if (crp[1].row == crp[0].row && crp[1].col == crp[0].col + 1) {
                // printf("  Adjoining!  Set next CRpix id = %i; x1=%i\n", crp[1].id, x1);
                crp[1].id = id;
                ++x1;
            } else {
                assert(y >= 0 && x0 >= 0 && x1 >= 0);
                spans.push_back(afw::detection::IdSpan::Ptr(new afw::detection::IdSpan(id, y, x0, x1)));
                // printf("  Not adjoining; adding span id=%i, y=%i, x = [%i, %i]\n", id, y, x0, x1);
            }
        }
    }
 
    /*
     * See if spans touch each other
     */
    for (std::vector<afw::detection::IdSpan::Ptr>::iterator sp = spans.begin(), end = spans.end(); sp != end;
         ++sp) {
        int const y = (*sp)->y;
        int const x0 = (*sp)->x0;
        int const x1 = (*sp)->x1;
 
        // this loop will probably run for only a few steps
        for (std::vector<afw::detection::IdSpan::Ptr>::iterator sp2 = sp + 1; sp2 != end; ++sp2) {
            if ((*sp2)->y == y) {
                // on this row (but not adjoining columns, since it would have been merged into this span);
                // keep looking.
                continue;
            } else if ((*sp2)->y != (y + 1)) {
                // sp2 is more than one row below; can't be connected.
                break;
            } else if ((*sp2)->x0 > (x1 + 1)) {
                // sp2 is more than one column away to the right; can't be connected
                break;
            } else if ((*sp2)->x1 >= (x0 - 1)) {
                // touches
                int r1 = afw::detection::resolve_alias(aliases, (*sp)->id);
                int r2 = afw::detection::resolve_alias(aliases, (*sp2)->id);
                aliases[r1] = r2;
            }
        }
    }
 
    /*
     * Resolve aliases; first alias chains, then the IDs in the spans
     */
    for (unsigned int i = 0; i != spans.size(); ++i) {
        spans[i]->id = afw::detection::resolve_alias(aliases, spans[i]->id);
    }
 
    /*
     * Sort spans by ID, so we can sweep through them once
     */
    if (spans.size() > 0) {
        std::sort(spans.begin(), spans.end(), afw::detection::IdSpanCompar());
    }
 
    /*
     * Build Footprints from spans
     */
    std::vector<std::shared_ptr<afw::detection::Footprint>> CRs;  // our cosmic rays
 
    if (spans.size() > 0) {
        int id = spans[0]->id;
        unsigned int i0 = 0;                                 // initial value of i
        for (unsigned int i = i0; i <= spans.size(); ++i) {  // <= size to catch the last object
            if (i == spans.size() || spans[i]->id != id) {
                std::shared_ptr<afw::detection::Footprint> cr(new afw::detection::Footprint());
 
                std::vector<afw::geom::Span> spanList;
                spanList.reserve(i - i0);
                for (; i0 < i; ++i0) {
                    spanList.push_back(afw::geom::Span(spans[i0]->y, spans[i0]->x0, spans[i0]->x1));
                }
                cr->setSpans(std::make_shared<afw::geom::SpanSet>(std::move(spanList)));
                CRs.push_back(cr);
            }
 
            if (i < spans.size()) {
                id = spans[i]->id;
            }
        }
    }
 
    reinstateCrPixels(mimage.getImage().get(), crpixels);
    /*
     * apply condition #1
     */
    CountsInCR<typename ImageT::Pixel> CountDN(bkgd);
    for (std::vector<std::shared_ptr<afw::detection::Footprint>>::iterator cr = CRs.begin(), end = CRs.end();
         cr != end; ++cr) {
        // find the sum of pixel values within the CR
        (*cr)->getSpans()->applyFunctor(CountDN, *mimage.getImage());
 
        LOGL_DEBUG("TRACE4.lsst.algorithms.CR", "CR at (%d, %d) has %g DN", (*cr)->getBBox().getMinX(),
                   (*cr)->getBBox().getMinY(), CountDN.getCounts());
        if (CountDN.getCounts() < minDn) { /* not bright enough */
            LOGL_DEBUG("TRACE5.lsst.algorithms.CR", "Erasing CR");
 
            cr = CRs.erase(cr);
            --cr;  // back up to previous CR (we're going to increment it)
            --end;
        }
        CountDN.reset();
    }
    ncr = CRs.size(); /* some may have been too faint */
                      /*
                       * We've found them all, time to kill them all
                       */
    bool const debias_values = true;
    bool grow = false;
    LOGL_DEBUG("TRACE2.lsst.algorithms.CR", "Removing initial list of CRs");
    removeCR(mimage, CRs, bkgd, crBit, saturBit, badMask, debias_values, grow);
#if 0  // Useful to see phase 2 in display; debugging only
    (void)setMaskFromFootprintList(mimage.getMask().get(), CRs,
                                   mimage.getMask()->getPlaneBitMask("DETECTED"));
#endif
    /*
     * Now that we've removed them, go through image again, examining area around
     * each CR for extra bad pixels. Note that we set cond3Fac = 0 for this pass
     *
     * We iterate niteration times;  niter==1 was sufficient for SDSS data, but megacam
     * CCDs are different -- who knows for other devices?
     */
    bool too_many_crs = false;  // we've seen too many CR pixels
    int nextra = 0;             // number of pixels added to list of CRs
    for (int i = 0; i != niteration && !too_many_crs; ++i) {
        LOGL_DEBUG("TRACE1.lsst.algorithms.CR", "Starting iteration %d", i);
        for (std::vector<std::shared_ptr<afw::detection::Footprint>>::iterator fiter = CRs.begin();
             fiter != CRs.end(); fiter++) {
            std::shared_ptr<afw::detection::Footprint> cr = *fiter;
            /*
             * Are all those `CR' pixels interpolated?  If so, don't grow it
             */
            {
                // this work should be taken on in DM-9538
                // std::shared_ptr<afw::detection::Footprint> om = footprintAndMask(cr, mimage.getMask(),
                // interpBit);
                // Placeholder until DM-9538 then remove empty footprint
                auto om = std::make_shared<afw::detection::Footprint>();
                int const npix = (om) ? om->getArea() : 0;
 
                if (static_cast<std::size_t>(npix) == cr->getArea()) {
                    continue;
                }
            }
            /*
             * No; some of the suspect pixels aren't interpolated
             */
            afw::detection::Footprint extra;  // extra pixels added to cr
            for (auto siter = cr->getSpans()->begin(); siter != cr->getSpans()->end(); siter++) {
                auto const span = siter;
 
                /*
                 * Check the lines above and below the span.  We're going to check a 3x3 region around
                 * the pixels, so we need a buffer around the edge.  We check the pixels just to the
                 * left/right of the span, so the buffer needs to be 2 pixels (not just 1) in the
                 * column direction, but only 1 in the row direction.
                 */
                int const y = span->getY() - mimage.getY0();
                if (y < 2 || y >= nrow - 2) {
                    continue;
                }
                int x0 = span->getX0() - mimage.getX0();
                int x1 = span->getX1() - mimage.getX0();
                x0 = (x0 < 2) ? 2 : (x0 > ncol - 3) ? ncol - 3 : x0;
                x1 = (x1 < 2) ? 2 : (x1 > ncol - 3) ? ncol - 3 : x1;
 
                checkSpanForCRs(&extra, crpixels, y - 1, x0, x1, mimage, minSigma / 2, thresH, thresV, thresD,
                                bkgd, 0, keep);
                checkSpanForCRs(&extra, crpixels, y, x0, x1, mimage, minSigma / 2, thresH, thresV, thresD,
                                bkgd, 0, keep);
                checkSpanForCRs(&extra, crpixels, y + 1, x0, x1, mimage, minSigma / 2, thresH, thresV, thresD,
                                bkgd, 0, keep);
            }
 
            if (extra.getSpans()->size() > 0) {  // we added some pixels
                if (nextra + static_cast<int>(crpixels.size()) > nCrPixelMax) {
                    too_many_crs = true;
                    break;
                }
 
                nextra += extra.getArea();
 
                std::vector<afw::geom::Span> tmpSpanList(cr->getSpans()->begin(), cr->getSpans()->end());
                for (auto const &spn : (*extra.getSpans())) {
                    tmpSpanList.push_back(spn);
                }
                cr->setSpans(std::make_shared<afw::geom::SpanSet>(std::move(tmpSpanList)));
            }
        }
 
        if (nextra == 0) {
            break;
        }
    }
    /*
     * mark those pixels as CRs
     */
    if (!too_many_crs) {
        for (auto const &foot : CRs) {
            foot->getSpans()->setMask(*mimage.getMask().get(), crBit);
        }
    }
    /*
     * Maybe reinstate initial values; n.b. the same pixel may appear twice, so we want the
     * first value stored (hence the uses of rbegin/rend)
     *
     * We have to do this if we decide _not_ to remove certain CRs,
     * for example those which lie next to saturated pixels
     */
    if (keep || too_many_crs) {
        if (crpixels.size() > 0) {
            int const imageX0 = mimage.getX0();
            int const imageY0 = mimage.getY0();
 
            std::sort(crpixels.begin(), crpixels.end());  // sort into birth order
 
            crpixel_riter rend = crpixels.rend();
            for (crpixel_riter crp = crpixels.rbegin(); crp != rend; ++crp) {
                if (crp->row == -1)
                    // dummy; skip it.
                    continue;
                mimage.at(crp->col - imageX0, crp->row - imageY0).image() = crp->val;
            }
        }
    } else {
        if (true || nextra > 0) {
            grow = true;
            LOGL_DEBUG("TRACE2.lsst.algorithms.CR", "Removing final list of CRs, grow = %d", grow);
            removeCR(mimage, CRs, bkgd, crBit, saturBit, badMask, debias_values, grow);
        }
        /*
         * we interpolated over all CR pixels, so set the interp bits too
         */
        for (auto const &foot : CRs) {
            foot->getSpans()->setMask(*mimage.getMask().get(), static_cast<MaskPixel>(crBit | interpBit));
        }
    }
 
    if (too_many_crs) {  // we've cleaned up, so we can throw the exception
        throw LSST_EXCEPT(pex::exceptions::LengthError,
                          (boost::format("Too many CR pixels (max %d)") % nCrPixelMax).str());
    }
 
    return CRs;
}
 
/*****************************************************************************/
namespace {
/*
 * Is condition 3 true?
 */
template <typename ImageT>
bool condition_3(ImageT *estimate,         // estimate of true value of pixel
                 double const peak,        // counts in central pixel (no sky)
                 double const mean_ns,     // mean in NS direction (no sky)
                 double const mean_we,     //  "   "  WE    "  "     "   "
                 double const mean_swne,   //  "   "  SW-NE "  "     "   "
                 double const mean_nwse,   //  "   "  NW-SE "  "     "   "
                 double const dpeak,       // standard deviation of peak value
                 double const dmean_ns,    //   s.d. of mean in NS direction
                 double const dmean_we,    //    "   "   "   "  WE    "  "
                 double const dmean_swne,  //  "   "   "   "  SW-NE "  "
                 double const dmean_nwse,  //  "   "   "   "  NW-SE "  "
                 double const thresH,      // horizontal threshold
                 double const thresV,      // vertical threshold
                 double const thresD,      // diagonal threshold
                 double const cond3Fac     // fiddle factor for noise
) {
    if (thresV * (peak - cond3Fac * dpeak) > mean_ns + cond3Fac * dmean_ns) {
        *estimate = (ImageT)mean_ns;
        return true;
    }
 
    if (thresH * (peak - cond3Fac * dpeak) > mean_we + cond3Fac * dmean_we) {
        *estimate = mean_we;
        return true;
    }
 
    if (thresD * (peak - cond3Fac * dpeak) > mean_swne + cond3Fac * dmean_swne) {
        *estimate = mean_swne;
        return true;
    }
 
    if (thresD * (peak - cond3Fac * dpeak) > mean_nwse + cond3Fac * dmean_nwse) {
        *estimate = mean_nwse;
        return true;
    }
 
    return false;
}
 
/************************************************************************************************************/
/*
 * Interpolate over a CR's pixels
 */
template <typename MaskedImageT>
class RemoveCR {
public:
    RemoveCR(MaskedImageT const &mimage, double const bkgd, typename MaskedImageT::Mask::Pixel badMask,
             bool const debias, afw::math::Random &rand)
            : _image(mimage),
              _bkgd(bkgd),
              _ncol(mimage.getWidth()),
              _nrow(mimage.getHeight()),
              _badMask(badMask),
              _debias(debias),
              _rand(rand) {}
 
    void operator()(geom::Point2I const &point, int) {
        int const &x = point.getX();
        int const &y = point.getY();
        typename MaskedImageT::xy_locator loc = _image.xy_at(x - _image.getX0(), y - _image.getY0());
        typedef typename MaskedImageT::Image::Pixel MImagePixel;
        MImagePixel min = std::numeric_limits<MImagePixel>::max();
        int ngood = 0;  // number of good values on min
 
        MImagePixel const minval =
                _bkgd - 2 * sqrt(loc.variance());  // min. acceptable pixel value after interp
                                                   /*
                                                    * W-E row
                                                    */
        if (x - 2 >= 0 && x + 2 < _ncol) {
            if ((loc.mask(-2, 0) | _badMask) || (loc.mask(-1, 0) | _badMask) || (loc.mask(1, 0) | _badMask) ||
                (loc.mask(2, 0) | _badMask)) {
                ;  // estimate is contaminated
            } else {
                MImagePixel const v_m2 = loc.image(-2, 0);
                MImagePixel const v_m1 = loc.image(-1, 0);
                MImagePixel const v_p1 = loc.image(1, 0);
                MImagePixel const v_p2 = loc.image(2, 0);
 
                MImagePixel const tmp = interp::lpc_1_c1 * (v_m1 + v_p1) + interp::lpc_1_c2 * (v_m2 + v_p2);
 
                if (tmp > minval && tmp < min) {
                    min = tmp;
                    ngood++;
                }
            }
        }
        /*
         * N-S column
         */
        if (y - 2 >= 0 && y + 2 < _nrow) {
            if ((loc.mask(0, -2) | _badMask) || (loc.mask(0, -1) | _badMask) || (loc.mask(0, 1) | _badMask) ||
                (loc.mask(0, 2) | _badMask)) {
                ; /* estimate is contaminated */
            } else {
                MImagePixel const v_m2 = loc.image(0, -2);
                MImagePixel const v_m1 = loc.image(0, -1);
                MImagePixel const v_p1 = loc.image(0, 1);
                MImagePixel const v_p2 = loc.image(0, 2);
 
                MImagePixel const tmp = interp::lpc_1_c1 * (v_m1 + v_p1) + interp::lpc_1_c2 * (v_m2 + v_p2);
 
                if (tmp > minval && tmp < min) {
                    min = tmp;
                    ngood++;
                }
            }
        }
        /*
         * SW--NE diagonal
         */
        if (x - 2 >= 0 && x + 2 < _ncol && y - 2 >= 0 && y + 2 < _nrow) {
            if ((loc.mask(-2, -2) | _badMask) || (loc.mask(-1, -1) | _badMask) ||
                (loc.mask(1, 1) | _badMask) || (loc.mask(2, 2) | _badMask)) {
                ; /* estimate is contaminated */
            } else {
                MImagePixel const v_m2 = loc.image(-2, -2);
                MImagePixel const v_m1 = loc.image(-1, -1);
                MImagePixel const v_p1 = loc.image(1, 1);
                MImagePixel const v_p2 = loc.image(2, 2);
 
                MImagePixel const tmp =
                        interp::lpc_1s2_c1 * (v_m1 + v_p1) + interp::lpc_1s2_c2 * (v_m2 + v_p2);
 
                if (tmp > minval && tmp < min) {
                    min = tmp;
                    ngood++;
                }
            }
        }
        /*
         * SE--NW diagonal
         */
        if (x - 2 >= 0 && x + 2 < _ncol && y - 2 >= 0 && y + 2 < _nrow) {
            if ((loc.mask(2, -2) | _badMask) || (loc.mask(1, -1) | _badMask) ||
                (loc.mask(-1, 1) | _badMask) || (loc.mask(-2, 2) | _badMask)) {
                ; /* estimate is contaminated */
            } else {
                MImagePixel const v_m2 = loc.image(2, -2);
                MImagePixel const v_m1 = loc.image(1, -1);
                MImagePixel const v_p1 = loc.image(-1, 1);
                MImagePixel const v_p2 = loc.image(-2, 2);
 
                MImagePixel const tmp =
                        interp::lpc_1s2_c1 * (v_m1 + v_p1) + interp::lpc_1s2_c2 * (v_m2 + v_p2);
 
                if (tmp > minval && tmp < min) {
                    min = tmp;
                    ngood++;
                }
            }
        }
        /*
         * Have we altogether failed to find an acceptable value? If so interpolate
         * using the full-up interpolation code both vertically and horizontally
         * and take the average. This can fail for large enough defects (e.g. CRs
         * lying in bad columns), in which case the interpolator returns -1. If
         * both directions fail, use the background value.
         */
        if (ngood == 0) {
            std::pair<bool, MImagePixel const> val_h = interp::singlePixel(x, y, _image, true, minval);
            std::pair<bool, MImagePixel const> val_v = interp::singlePixel(x, y, _image, false, minval);
 
            if (!val_h.first) {
                if (!val_v.first) {  // Still no good value. Guess wildly
                    min = _bkgd + sqrt(loc.variance()) * _rand.gaussian();
                } else {
                    min = val_v.second;
                }
            } else {
                if (val_v.first) {
                    min = val_h.second;
                } else {
                    min = (val_v.second + val_h.second) / 2;
                }
            }
        }
        /*
         * debias the minimum; If more than one uncontaminated estimate was
         * available, estimate the bias to be simply that due to choosing the
         * minimum of two Gaussians. In fact, even some of the "good" pixels
         * may have some extra charge, so even if ngood > 2, still use this
         * estimate
         */
        if (ngood > 0) {
            LOGL_DEBUG("TRACE3.lsst.algorithms.CR", "Adopted min==%g at (%d, %d) (ngood=%d)",
                       static_cast<double>(min), x, y, ngood);
        }
 
        if (_debias && ngood > 1) {
            min -= interp::min2GaussianBias * sqrt(loc.variance()) * _rand.gaussian();
        }
 
        loc.image() = min;
    }
 
private:
    MaskedImageT const &_image;
    double _bkgd;
    int _ncol, _nrow;
    typename MaskedImageT::Mask::Pixel _badMask;
    bool _debias;
    afw::math::Random &_rand;
};
 
/************************************************************************************************************/
/*
 * actually remove CRs from the frame
 */
template <typename ImageT, typename MaskT>
void removeCR(afw::image::MaskedImage<ImageT, MaskT> &mi,                    // image to search
              std::vector<std::shared_ptr<afw::detection::Footprint>> &CRs,  // list of cosmic rays
              double const bkgd,                                             // non-subtracted background
              MaskT const,                                                   // Bit value used to label CRs
              MaskT const saturBit,  // Bit value used to label saturated pixels
              MaskT const badMask,   // Bit mask for bad pixels
              bool const debias,     // statistically debias values?
              bool const grow        // Grow CRs?
) {
    afw::math::Random rand;  // a random number generator
    /*
     * replace the values of cosmic-ray contaminated pixels with 1-dim 2nd-order weighted means Cosmic-ray
     * contaminated pixels have already been given a mask value, crBit
     *
     * If there are no good options (i.e. all estimates are contaminated), try using just pixels that are not
     * CRs; failing that, interpolate in the row- or column direction over as large a distance as is required
     *
     * XXX SDSS (and we) go through this list backwards; why?
     */
 
    // a functor to remove a CR
    RemoveCR<afw::image::MaskedImage<ImageT, MaskT>> removeCR(mi, bkgd, badMask, debias, rand);
 
    for (std::vector<std::shared_ptr<afw::detection::Footprint>>::reverse_iterator fiter = CRs.rbegin();
         fiter != CRs.rend(); ++fiter) {
        std::shared_ptr<afw::detection::Footprint> cr = *fiter;
        /*
         * If I grow this CR does it touch saturated pixels?  If so, don't
         * interpolate and add CR pixels to saturated mask
         */
        /* This is commented out pending work from DM-9538
                if (grow && cr->getArea() < 100) {
                    try {
                        bool const isotropic = false; // use a slow isotropic grow?
                        auto gcr = std::make_shared<afw::detection::Footprint>(cr->getSpans()->dilate(1),
           cr.getRegion()); std::shared_ptr<afw::detection::Footprint> const saturPixels =
           footprintAndMask(gcr, mi.getMask(), saturBit); auto const saturPixels = footprintAndMask(gcr,
           mi.getMask(), saturBit);
 
                     if (saturPixels->getArea() > 0) { // pixel is adjacent to a saturation trail
                         setMaskFromFootprint(mi.getMask().get(), *saturPixels, saturBit);
 
                            continue;
                        }
                    } catch(pex::exceptions::LengthError &) {
                        continue;
                    }
                }
                */
        /*
         * OK, fix it
         */
        // applyFunctor must have an argument other than the functor, however in this case
        // additional arguments are unneeded, so pass a constant 1 to be iterated over
        // and ignore
        cr->getSpans()->applyFunctor(removeCR, 1);
    }
}
}  // namespace
 
/************************************************************************************************************/
//
// Explicit instantiations
// \cond
#define INSTANTIATE(TYPE)                                                                            \
    template std::vector<std::shared_ptr<afw::detection::Footprint>> findCosmicRays(                 \
            afw::image::MaskedImage<TYPE> &image, afw::detection::Psf const &psf, double const bkgd, \
            daf::base::PropertySet const &ps, bool const keep)
 
INSTANTIATE(float);
INSTANTIATE(double);  // Why do we need double images?
// \endcond
}  // namespace algorithms
}  // namespace meas
}  // namespace lsst