lsst.meas.extensions.scarlet

lsst.meas.extensions.scarlet contains the pipeline task used to execute the scarlet deblending algorithm (Melchior et. al 2018).

Using lsst.meas.extensions.scarlet

• Deblending in the Science Pipelines
• Deblending a Catalog
• Working with scarlet-lite Models

Contributing

lsst.meas.extensions.scarlet is developed at https://github.com/lsst/meas_extensions_scarlet. You can find Jira issues for this module under the meas_extensions_scarlet component.

Python API reference

lsst.meas.extensions.scarlet Package

Functions

deblend(context, footprint, config[, ...])	Deblend a parent footprint
setDeblenderMetrics(blend)	Set metrics that can be used to evalute the deblender accuracy

Classes

DeblenderMetrics(maxOverlap, fluxOverlap, ...)	Metrics and measurements made on single sources.
DeconvolveExposureConfig(*args, **kw)	Configuration for DeconvolveExposureTask
DeconvolveExposureConnections(*[, config])	Connections for DeconvolveExposureTask
DeconvolveExposureTask([initInputs])	Deconvolve an Exposure using scarlet lite.
ScarletDeblendConfig(*args, **kw)	MultibandDeblendConfig
ScarletDeblendContext(*, monotonicity, ...)	Context with parameters and config options for deblending
ScarletDeblendTask(schema[, peakSchema])	Split blended sources into individual sources.