|
def | run (self, parq, funcs=None, dataId=None, band=None) |
|
def | outputDataset (self) |
|
def | inputDataset (self) |
|
def | ConfigClass (self) |
|
def | runQuantum (self, butlerQC, inputRefs, outputRefs) |
|
def | runDataRef (self, dataRef) |
|
def | getFunctors (self) |
|
def | getAnalysis (self, parq, funcs=None, band=None) |
|
def | transform (self, band, parq, funcs, dataId) |
|
def | write (self, df, parqRef) |
|
def | writeMetadata (self, dataRef) |
|
Produce a flattened Object Table to match the format specified in
sdm_schemas.
Do the same set of postprocessing calculations on all bands
This is identical to `TransformCatalogBaseTask`, except for that it does the
specified functor calculations for all filters present in the
input `deepCoadd_obj` table. Any specific `"filt"` keywords specified
by the YAML file will be superceded.
Definition at line 691 of file postprocess.py.
def lsst.pipe.tasks.postprocess.TransformObjectCatalogTask.run |
( |
|
self, |
|
|
|
parq, |
|
|
|
funcs = None , |
|
|
|
dataId = None , |
|
|
|
band = None |
|
) |
| |
Do postprocessing calculations
Takes a `ParquetTable` object and dataId,
returns a dataframe with results of postprocessing calculations.
Parameters
----------
parq : `lsst.pipe.tasks.parquetTable.ParquetTable`
ParquetTable from which calculations are done.
funcs : `lsst.pipe.tasks.functors.Functors`
Functors to apply to the table's columns
dataId : dict, optional
Used to add a `patchId` column to the output dataframe.
band : `str`, optional
Filter band that is being processed.
Returns
------
`pandas.DataFrame`
Reimplemented from lsst.pipe.tasks.postprocess.TransformCatalogBaseTask.
Definition at line 716 of file postprocess.py.