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

Python API reference

lsst.meas.extensions.scarlet Package


boundedDataToBox(nBands, boundedData) Convert bounds from the data storage format to a scarlet.bbox.Box
dataToScarlet(blendData[, nBands, …]) Convert the storage data model into a scarlet lite blend
deblend(mExposure, footprint, config, …) Deblend a parent footprint
modelToHeavy(source, mExposure, blend[, …]) Convert a scarlet model to a MultibandFootprint.
scarletLiteToData(blend, psfCenter, xy0) Convert a scarlet lite blend into a persistable data object
scarletToData(blend, psfCenter, xy0) Convert a scarlet blend into a persistable data object
updateBlendRecords(blendData, catalog, …) Create footprints and update band-dependent columns in the catalog


ComponentCube(model, center, bbox, model_bbox) Dummy component for scarlet main sources.
ScarletBlendData(xy0, extent, sources, psfCenter) Data for an entire blend.
ScarletComponentData(xy0, extent, center, model) Data for a component expressed as a 3D data cube
ScarletDeblendConfig MultibandDeblendConfig
ScarletDeblendTask(schema[, peakSchema]) Split blended sources into individual sources.
ScarletFactorizedComponentData(xy0, extent, …) Data for a factorized component
ScarletModelData(filters, psf[, blends]) A container that propagates scarlet models for an entire SourceCatalog
ScarletSourceData(components, …) Data for a scarlet source