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def | outputDataset (self) |
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def | inputDataset (self) |
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def | ConfigClass (self) |
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def | __init__ (self, *args, **kwargs) |
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def | runQuantum (self, butlerQC, inputRefs, outputRefs) |
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def | run (self, parq, funcs=None, dataId=None, band=None) |
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def | getFunctors (self) |
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def | getAnalysis (self, parq, funcs=None, band=None) |
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def | transform (self, band, parq, funcs, dataId) |
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def | write (self, df, parqRef) |
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def | writeMetadata (self, dataRef) |
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Base class for transforming/standardizing a catalog
by applying functors that convert units and apply calibrations.
The purpose of this task is to perform a set of computations on
an input `ParquetTable` dataset (such as `deepCoadd_obj`) and write the
results to a new dataset (which needs to be declared in an `outputDataset`
attribute).
The calculations to be performed are defined in a YAML file that specifies
a set of functors to be computed, provided as
a `--functorFile` config parameter. An example of such a YAML file
is the following:
funcs:
psfMag:
functor: Mag
args:
- base_PsfFlux
filt: HSC-G
dataset: meas
cmodel_magDiff:
functor: MagDiff
args:
- modelfit_CModel
- base_PsfFlux
filt: HSC-G
gauss_magDiff:
functor: MagDiff
args:
- base_GaussianFlux
- base_PsfFlux
filt: HSC-G
count:
functor: Column
args:
- base_InputCount_value
filt: HSC-G
deconvolved_moments:
functor: DeconvolvedMoments
filt: HSC-G
dataset: forced_src
refFlags:
- calib_psfUsed
- merge_measurement_i
- merge_measurement_r
- merge_measurement_z
- merge_measurement_y
- merge_measurement_g
- base_PixelFlags_flag_inexact_psfCenter
- detect_isPrimary
The names for each entry under "func" will become the names of columns in
the output dataset. All the functors referenced are defined in
`lsst.pipe.tasks.functors`. Positional arguments to be passed to each
functor are in the `args` list, and any additional entries for each column
other than "functor" or "args" (e.g., `'filt'`, `'dataset'`) are treated as
keyword arguments to be passed to the functor initialization.
The "flags" entry is the default shortcut for `Column` functors.
All columns listed under "flags" will be copied to the output table
untransformed. They can be of any datatype.
In the special case of transforming a multi-level oject table with
band and dataset indices (deepCoadd_obj), these will be taked from the
`meas` dataset and exploded out per band.
There are two special shortcuts that only apply when transforming
multi-level Object (deepCoadd_obj) tables:
- The "refFlags" entry is shortcut for `Column` functor
taken from the `'ref'` dataset if transforming an ObjectTable.
- The "forcedFlags" entry is shortcut for `Column` functors.
taken from the ``forced_src`` dataset if transforming an ObjectTable.
These are expanded out per band.
This task uses the `lsst.pipe.tasks.postprocess.PostprocessAnalysis` object
to organize and excecute the calculations.
Definition at line 849 of file postprocess.py.