LSSTApplications  10.0+286,10.0+36,10.0+46,10.0-2-g4f67435,10.1+152,10.1+37,11.0,11.0+1,11.0-1-g47edd16,11.0-1-g60db491,11.0-1-g7418c06,11.0-2-g04d2804,11.0-2-g68503cd,11.0-2-g818369d,11.0-2-gb8b8ce7
LSSTDataManagementBasePackage
Todo List
File ConvolveImage.h
Consider adding a flag to convolve indicating which specialized version of basicConvolve was used. This would only be used for unit testing and trace messages suffice (barely), so not a high priority.
File Coord.h
add FK4 ... as needed
File KernelFunctions.h
Namespace lsst
These should go into afw — actually, there're already there, but in an anon namespace
Class lsst::afw::cameraGeom::Detector
: this would probably be a bit more robust if it used a ConstAmpInfoCatalog (a catalog with const records) but I don't think const catalogs really work yet; for instance it is not possible to construct one from a non-const catalog, so I don't know how to construct one.
Member lsst::afw::cameraGeom::rotateBBoxBy90.rotateBBoxBy90
document dimensions better; what does it specify?
Member lsst::afw::coord::angleToDmsString (lsst::afw::geom::Angle const deg)
allow a user specified format
Member lsst::afw::detection::FootprintSet::FootprintSet (FootprintSet const &footprints1, FootprintSet const &footprints2, bool const includePeaks)
Implement this. There's RHL Pan-STARRS code to do it, but it isn't yet converted to LSST C++
Member lsst::afw::formatters::ExposureFormatter< ImagePixelT, MaskPixelT, VariancePixelT >::read (lsst::daf::persistence::Storage::Ptr storage, lsst::daf::base::PropertySet::Ptr additionalData)

Should really have FITS be a separate Storage.

Need to implement overwriting of FITS metadata PropertySet

Member lsst::afw::formatters::ExposureFormatter< ImagePixelT, MaskPixelT, VariancePixelT >::update (lsst::daf::base::Persistable *persistable, lsst::daf::persistence::Storage::Ptr storage, lsst::daf::base::PropertySet::Ptr additionalData)
Implement update from FitsStorage, keeping DB-provided headers.
Member lsst::afw::formatters::ExposureFormatter< ImagePixelT, MaskPixelT, VariancePixelT >::write (lsst::daf::base::Persistable const *persistable, lsst::daf::persistence::Storage::Ptr storage, lsst::daf::base::PropertySet::Ptr additionalData)
Check that rawCCDExposureId == scienceCCDExposureId – KTL – 2008-01-25
Class lsst::afw::image::pixel::BinaryExpr< ExprT1, double, ImageBinOp, MaskBinOp, VarianceBinOp >
Could use a traits class to handle all scalar types
Class lsst::afw::math::BilinearWarpingKernel
: make a new class WarpingKernel and make this a subclass.
Class lsst::afw::math::LanczosWarpingKernel
: make a new class WarpingKernel and make this a subclass.
Class lsst::afw::math::NearestWarpingKernel
: make a new class WarpingKernel and make this a subclass.
Member lsst::afw::math::SpatialCell::visitAllCandidates (CandidateVisitor *visitor, bool const ignoreExceptions=false, bool const reset=true) const
This is currently implemented via a const_cast (arghhh). The problem is that SpatialCell::begin() const isn't yet implemented
Member lsst::afw::math::SpatialCell::visitCandidates (CandidateVisitor *visitor, int const nMaxPerCell=-1, bool const ignoreExceptions=false, bool const reset=true) const
This is currently implemented via a const_cast (arghhh). The problem is that SpatialCell::begin() const isn't yet implemented
Member lsst::afw::math::Statistics::getResult (Property const prop=NOTHING) const
uncertainties on MEANCLIP,STDEVCLIP are sketchy. _n != _nClip
Member lsst::afw::math::warpImage (DestImageT &destImage, lsst::afw::image::Wcs const &destWcs, SrcImageT const &srcImage, lsst::afw::image::Wcs const &srcWcs, WarpingControl const &control, typename DestImageT::SinglePixel padValue=lsst::afw::math::edgePixel< DestImageT >(typename lsst::afw::image::detail::image_traits< DestImageT >::image_category()))

Should support an additional color-based position correction in the remapping (differential chromatic refraction). This can be done either object-by-object or pixel-by-pixel.

Need to deal with oversampling and/or weight maps. If done we can use faster kernels than sinc.

Need to deal with oversampling and/or weight maps. If done we can use faster kernels than sinc.

Class ndarray::EigenView< T, N, C, XprKind_, Rows_, Cols_ >
Add reference-counted share and transpose operations that return EigenViews.