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¶
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 | Calculate the fraction of pixels with no data in a Footprint Parameters ---------- footprint :  | 
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 | Deblend a parent footprint | 
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 | Convert the storage data model into a scarlet lite blend | 
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 | Convert a scarlet.lite blend into a persistable data object | 
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 | Convert a scarlet_lite model to a  | 
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 | Set metrics that can be used to evalute the deblender accuracy | 
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 | Create footprints and update band-dependent columns in the catalog | 
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 | Use the scarlet models to set HeavyFootprints for modeled sources | 
Classes¶
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 | A single blend. | 
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 | Bounding Box for an object | 
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 | A base component in scarlet lite. | 
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 | Metrics and measurements made on single sources. | 
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 | Configuration for DeconvolveExposureTask | 
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 | Connections for DeconvolveExposureTask | 
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 | Deconvolve an Exposure using scarlet lite. | 
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 | A component that can be factorized into spectrum and morphology parameters. | 
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 | A parameter that is not updated | 
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 | A numpy array with an origin and (optional) bands | 
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 | MultibandDeblendConfig | 
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 | Split blended sources into individual sources. | 
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 | A container for components associated with the same astrophysical object | 
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 | alias of  |