DipoleFitPlugin

class lsst.ip.diffim.DipoleFitPlugin(config, name, schema, metadata, logName=None)

Bases: SingleFramePlugin

A single frame measurement plugin that fits dipoles to all merged (two-peak) diaSources.

This measurement plugin accepts up to three input images in its measure method. If these are provided, it includes data from the pre-subtraction posImage (science image) and optionally negImage (template image) to constrain the fit. The meat of the fitting routines are in the class DipoleFitAlgorithm.

Notes

The motivation behind this plugin and the necessity for including more than one exposure are documented in DMTN-007 (http://dmtn-007.lsst.io).

This class is named ip_diffim_DipoleFit so that it may be used alongside the existing ip_diffim_DipoleMeasurement classes until such a time as those are deemed to be replaceable by this.

Attributes Summary

FAILURE_EDGE
FAILURE_FIT
FAILURE_NOT_DIPOLE
FAILURE_TOO_LARGE

Methods Summary

doClassify(measRecord, chi2val)	Classify a source as a dipole.
fail(measRecord[, error])	Catch failures and set the correct flags.
getExecutionOrder()	This algorithm simultaneously fits the centroid and flux, and does not require any previous centroid fit.
measureDipoles(measRecord, exposure[, ...])	Perform the non-linear least squares minimization on the putative dipole source.

Attributes Documentation

FAILURE_EDGE = 1

FAILURE_FIT = 2

FAILURE_NOT_DIPOLE = 4

FAILURE_TOO_LARGE = 8

Methods Documentation

doClassify(measRecord, chi2val)

Classify a source as a dipole.

Parameters

measRecordTODO: DM-17458

TODO: DM-17458

chi2valTODO: DM-17458

TODO: DM-17458

Notes

Sources are classified as dipoles, or not, according to three criteria:

1. Does the total signal-to-noise surpass the minSn?

2. Are the pos/neg fluxes greater than 1.0 and no more than 0.65 (maxFluxRatio) of the total flux? By default this will never happen since posFlux == negFlux.

3. Is it a good fit (chi2dof < 1)? (Currently not used.)

fail(measRecord, error=None)

Catch failures and set the correct flags.

Fallback on the current slot centroid positions, but set the dipole failure flag, since we attempted to fit the source.

classmethod getExecutionOrder()

This algorithm simultaneously fits the centroid and flux, and does not require any previous centroid fit.

measureDipoles(measRecord, exposure, posExp=None, negExp=None)

Perform the non-linear least squares minimization on the putative dipole source.

Parameters

measRecordlsst.afw.table.SourceRecord

diaSources that will be measured using dipole measurement

exposurelsst.afw.image.Exposure

Difference exposure on which the diaSources were detected; exposure = posExp-negExp If both posExp and negExp are None, will attempt to fit the dipole to just the exposure with no constraint.

posExplsst.afw.image.Exposure, optional

“Positive” exposure, typically a science exposure, or None if unavailable When posExp is None, will compute posImage = exposure + negExp.

negExplsst.afw.image.Exposure, optional

“Negative” exposure, typically a template exposure, or None if unavailable When negExp is None, will compute negImage = posExp - exposure.

Notes

The main functionality of this routine was placed outside of this plugin (into DipoleFitAlgorithm.fitDipole()) so that DipoleFitAlgorithm.fitDipole() can be called separately for testing (@see tests/testDipoleFitter.py)