File PeakLikelihoodFlux.h

namespace lsst

Class for a simple mapping implementing a generic AstrometryTransform.

Remove all non-astronomical counts from the Chunk Exposure’s pixels.

Forward declarations for lsst::utils::Cache

For details on the Cache class, see the Cache.h file.

It uses a template rather than a pointer so that the derived classes can use the specifics of the transform. The class simplePolyMapping overloads a few routines.

A base class for image defects

Numeric constants used by the Integrate.h integrator routines.

Compute Image Statistics

Note

Gauss-Kronrod-Patterson quadrature coefficients for use in quadpack routine qng. These coefficients were calculated with 101 decimal digit arithmetic by L. W. Fullerton, Bell Labs, Nov 1981.

Note

The Statistics class itself can only handle lsst::afw::image::MaskedImage() types. The philosophy has been to handle other types by making them look like lsst::afw::image::MaskedImage() and reusing that code. Users should have no need to instantiate a Statistics object directly, but should use the overloaded makeStatistics() factory functions.

namespace meas

namespace base

class PeakLikelihoodFluxAlgorithm : public lsst::meas::base::SimpleAlgorithm

#include <PeakLikelihoodFlux.h>

A measurement algorithm that estimates the peak instrument flux, using a filtered image which has been convolved with its own PSF.

Public Types

typedef PeakLikelihoodFluxControl Control

A typedef to the Control object for this algorithm, defined above. The control object contains the configuration parameters for this algorithm.

Public Functions

PeakLikelihoodFluxAlgorithm(Control const &ctrl, std::string const &name, afw::table::Schema &schema)

virtual void measure(afw::table::SourceRecord &measRecord, afw::image::Exposure<float> const &exposure) const

Called to measure a single child source in an image.

Before this method is called, all neighbors will be replaced with noise, using the outputs of the deblender. Outputs should be saved in the given SourceRecord, which can also be used to obtain centroid (see SafeCentroidExtractor) and shape (see SafeShapeExtractor) information.

virtual void fail(afw::table::SourceRecord &measRecord, MeasurementError *error = nullptr) const

Handle an exception thrown by the current algorithm by setting flags in the given record.

fail() is called by the measurement framework when an exception is allowed to propagate out of one the algorithm’s measure() methods. It should generally set both a general failure flag for the algorithm as well as a specific flag indicating the error condition, if possible. To aid in this, if the exception was an instance of MeasurementError, it will be passed in, carrying information about what flag to set.

An algorithm can also to chose to set flags within its own measure() methods, and then just return, rather than throw an exception. However, fail() should be implemented even when all known failure modes do not throw exceptions, to ensure that unexpected exceptions thrown in lower-level code are properly handled.

Public Static Functions

static FlagDefinitionList const &getFlagDefinitions()

Public Static Attributes

FlagDefinition const FAILURE

Private Members

Control _ctrl

FluxResultKey _instFluxResultKey

FlagHandler _flagHandler

SafeCentroidExtractor _centroidExtractor

class PeakLikelihoodFluxControl

#include <PeakLikelihoodFlux.h>

C++ control object for peak likelihood instrument flux.

Peak likelihood flux requires an image that has been filtered by convolving with its own PSF (or an approximate model). It is equivalent to a PSF instrument flux (e.g. as computed by PsfFluxAlgorithm) computed on a non-preconvolved image.

The PSF must be provided in the exposure, as it is used to compute a weighting factor.

Flux and error are computed as follows:

• instFlux = sum(unfiltered image * PSF) / sum(PSF^2) = value of peak of filtered source / sum(PSF^2)

• err = sqrt(sum(unfiltered variance * PSF^2) / sum(PSF^2)^2) = sqrt(value of filtered variance at peak / sum(PSF^2)^2)

• The pixels in the image are samples of a band-limited function, and by using a sinc interpolation (via a warping kernel) we can evaluate this function at any point. We use this technique to compute the peak of the function, which is assumed to be at the centroid of the filtered source.

Public Functions

LSST_CONTROL_FIELD(warpingKernelName, std::string)

PeakLikelihoodFluxControl()

class PeakLikelihoodFluxTransform : public lsst::meas::base::FluxTransform

Public Types

typedef PeakLikelihoodFluxControl Control

Public Functions

PeakLikelihoodFluxTransform(Control const &ctrl, std::string const &name, afw::table::SchemaMapper &mapper)