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¶
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¶
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 |
deblend_lite(mExposure, modelPsf, footprint, …) |
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 |
Classes¶
ComponentCube(model, center, bbox, model_bbox) |
Dummy component for scarlet main sources. |
DummyObservation(psfs, model_psf, bbox, dtype) |
An observation that does not have any image data |
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(bands, psf[, blends]) |
A container that propagates scarlet models for an entire SourceCatalog |
ScarletSourceData(components, …) |
Data for a scarlet source |