DipoleFitPlugin

class lsst.ip.diffim.DipoleFitPlugin(config, name, schema, metadata)

Bases: lsst.meas.base.sfm.SingleFramePlugin

!Subclass of SingleFramePlugin which fits dipoles to all merged (two-peak) diaSources

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.

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

Methods Summary

doClassify(measRecord, chi2val) !Determine if source is classified as dipole via three criteria: - does the total signal-to-noise surpass the minSn? - are the pos/neg fluxes greater than 1.0 and no more than 0.65 (param maxFluxRatio) of the total flux? By default this will never happen since posFlux == negFlux.
fail(measRecord[, error]) !Catch failures and set the correct flags.
getExecutionOrder() !Set execution order to FLUX_ORDER.
measure(measRecord, exposure[, posExp, negExp]) !Perform the non-linear least squares minimization on the putative dipole source.

Attributes Documentation

FAILURE_EDGE = 1
FAILURE_FIT = 2
FAILURE_NOT_DIPOLE = 4

Methods Documentation

doClassify(measRecord, chi2val)

!Determine if source is classified as dipole via three criteria: - does the total signal-to-noise surpass the minSn? - are the pos/neg fluxes greater than 1.0 and no more than 0.65 (param maxFluxRatio)

of the total flux? By default this will never happen since posFlux == negFlux.
  • is it a good fit (chi2dof < 1)? (Currently not used.)
fail(measRecord, error=None)

!Catch failures and set the correct flags.

classmethod getExecutionOrder()

!Set execution order to FLUX_ORDER.

This includes algorithms that require both getShape() and getCentroid(), in addition to a Footprint and its Peaks.

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

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

@param measRecord diaSources that will be measured using dipole measurement @param exposure Difference exposure on which the diaSources were detected; exposure = posExp-negExp @param posExp “Positive” exposure, typically a science exposure, or None if unavailable @param negExp “Negative” exposure, typically a template exposure, or None if unavailable

@note When posExp is None, will compute posImage = exposure + negExp. Likewise, when negExp is None, will compute negImage = posExp - exposure. If both posExp and negExp are None, will attempt to fit the dipole to just the exposure with no constraint.

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)