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

`APCORR_ORDER`	Order for algorithms which require shape, centroid and flux (`float`).
`CENTROID_ORDER`	Order for algorithms which require only Footprint and Peaks (`float`).
`DEFAULT_CATALOGCALCULATION`	Order for catalog calculation plugins.
`FAILURE_EDGE`
`FAILURE_FIT`
`FAILURE_NOT_DIPOLE`
`FAILURE_TOO_LARGE`
`FLUX_ORDER`	Order for algorithms which require a shape and a centroid (`float`).
`SHAPE_ORDER`	Order for algorithms which require a centroid (`float`).
`registry`	Registry of subclasses of `SingleFramePlugin` (`PluginRegistry`).

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.
`getLogName`()
`getTransformClass`()	Get the measurement transformation appropriate to this plugin.
`measure`(measRecord, exposure)	Measure the properties of a source on a single image.
`measureDipoles`(measRecord, exposure[, ...])	Perform the non-linear least squares minimization on the putative dipole source.
`measureN`(measCat, exposure)	Measure the properties of blended sources on a single image.

Attributes Documentation

APCORR_ORDER = 3.0¶

Order for algorithms which require shape, centroid and flux (float).

Notes

These algorithms may assume that getCentroid and getShape will return good values, that flux has been measured, and that and that a Footprint and its Peaks are available.

CENTROID_ORDER = 0.0¶

Order for algorithms which require only Footprint and Peaks (float).

Notes

Algorithms with this execution order include centroids.

DEFAULT_CATALOGCALCULATION = 4.0¶

Order for catalog calculation plugins.

Notes

These plugins only operate on catalogs; they may not access pixel values.

FAILURE_EDGE = 1¶

FAILURE_FIT = 2¶

FAILURE_NOT_DIPOLE = 4¶

FAILURE_TOO_LARGE = 8¶

FLUX_ORDER = 2.0¶

Order for algorithms which require a shape and a centroid (float).

Notes

These algorithms may assume that both getCentroid and getShape will return good values, and that a Footprint and its Peaks are available.

SHAPE_ORDER = 1.0¶

Order for algorithms which require a centroid (float).

Notes

These algorithms may refer assume that getCentroid will return a good centroid, and that a Footprint and its Peaks are available.

registry = <lsst.meas.base.pluginRegistry.PluginRegistry object>¶: Registry of subclasses of SingleFramePlugin (PluginRegistry).

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:

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

getLogName()¶

static getTransformClass()¶

Get the measurement transformation appropriate to this plugin.

This returns a subclass of transforms.MeasurementTransform, which may be instantiated with details of the algorithm configuration and then called with information about calibration and WCS to convert from raw measurement quantities to calibrated units. Calibrated data is then provided in a separate output table.

Notes

By default, we copy everything from the input to the output without transformation.

measure(measRecord, exposure)¶

Measure the properties of a source on a single image.

The image may be from a single epoch, or it may be a coadd.

Parameters:

measRecordlsst.afw.table.SourceRecord: Record describing the object being measured. Previously-measured quantities may be retrieved from here, and it will be updated in-place tih the outputs of this plugin.
exposurelsst.afw.image.ExposureF: The pixel data to be measured, together with the associated PSF, WCS, etc. All other sources in the image should have been replaced by noise according to deblender outputs.

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)

measureN(measCat, exposure)¶

Measure the properties of blended sources on a single image.

This operates on all members of a blend family at once. The image may be from a single epoch, or it may be a coadd.

Parameters:

measCatlsst.afw.table.SourceCatalog: Catalog describing the objects (and only those objects) being measured. Previously-measured quantities will be retrieved from here, and it will be updated in-place with the outputs of this plugin.
exposurelsst.afw.image.ExposureF: The pixel data to be measured, together with the associated PSF, WCS, etc. All other sources in the image should have been replaced by noise according to deblender outputs.

Notes

Derived classes that do not implement measureN should just inherit this disabled version. Derived classes that do implement measureN should additionally add a bool doMeasureN config field to their config class to signal that measureN-mode is available.

Navigation

DipoleFitPlugin¶