TransformCatalogBaseTask¶
- class lsst.pipe.tasks.postprocess.TransformCatalogBaseTask(*args, **kwargs)¶
Bases:
PipelineTask
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
DeferredDatasetHandle
orInMemoryDatasetHandle
that holds aDataFrame
dataset (such asdeepCoadd_obj
), and write the results to a new dataset (which needs to be declared in anoutputDataset
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:
- sourceId:
functor: Index
- x:
functor: Column args: slot_Centroid_x
- y:
functor: Column args: slot_Centroid_y
- psfFlux:
functor: LocalNanojansky args:
slot_PsfFlux_instFlux
slot_PsfFlux_instFluxErr
base_LocalPhotoCalib
base_LocalPhotoCalibErr
- psfFluxErr:
functor: LocalNanojanskyErr args:
slot_PsfFlux_instFlux
slot_PsfFlux_instFluxErr
base_LocalPhotoCalib
base_LocalPhotoCalibErr
- flags:
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
functors
. Positional arguments to be passed to each functor are in theargs
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 themeas
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 theforced_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.Attributes Summary
Methods Summary
Empty (clear) the metadata for this Task and all sub-Tasks.
getAnalysis
(handles[, funcs, band])Get metadata for all tasks.
Get the task name as a hierarchical name including parent task names.
getName
()Get the name of the task.
Get a dictionary of all tasks as a shallow copy.
makeField
(doc)Make a
lsst.pex.config.ConfigurableField
for this task.makeSubtask
(name, **keyArgs)Create a subtask as a new instance as the
name
attribute of this task.run
(handle[, funcs, dataId, band])Do postprocessing calculations
runQuantum
(butlerQC, inputRefs, outputRefs)Do butler IO and transform to provide in memory objects for tasks
run
method.timer
(name[, logLevel])Context manager to log performance data for an arbitrary block of code.
transform
(band, handles, funcs, dataId)Attributes Documentation
- ConfigClass: ClassVar[type[PipelineTaskConfig]]¶
- inputDataset¶
- outputDataset¶
Methods Documentation
- getAnalysis(handles, funcs=None, band=None)¶
- getFullMetadata() TaskMetadata ¶
Get metadata for all tasks.
- Returns:
- metadata
TaskMetadata
The keys are the full task name. Values are metadata for the top-level task and all subtasks, sub-subtasks, etc.
- metadata
Notes
The returned metadata includes timing information (if
@timer.timeMethod
is used) and any metadata set by the task. The name of each item consists of the full task name with.
replaced by:
, followed by.
and the name of the item, e.g.:topLevelTaskName:subtaskName:subsubtaskName.itemName
using
:
in the full task name disambiguates the rare situation that a task has a subtask and a metadata item with the same name.
- getFullName() str ¶
Get the task name as a hierarchical name including parent task names.
- Returns:
- fullName
str
The full name consists of the name of the parent task and each subtask separated by periods. For example:
The full name of top-level task “top” is simply “top”.
The full name of subtask “sub” of top-level task “top” is “top.sub”.
The full name of subtask “sub2” of subtask “sub” of top-level task “top” is “top.sub.sub2”.
- fullName
- getFunctors()¶
- getName() str ¶
Get the name of the task.
- Returns:
- taskName
str
Name of the task.
- taskName
See also
getFullName
Get the full name of the task.
- getTaskDict() dict[str, weakref.ReferenceType[lsst.pipe.base.task.Task]] ¶
Get a dictionary of all tasks as a shallow copy.
- Returns:
- taskDict
dict
Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc.
- taskDict
- classmethod makeField(doc: str) ConfigurableField ¶
Make a
lsst.pex.config.ConfigurableField
for this task.- Parameters:
- doc
str
Help text for the field.
- doc
- Returns:
- configurableField
lsst.pex.config.ConfigurableField
A
ConfigurableField
for this task.
- configurableField
Examples
Provides a convenient way to specify this task is a subtask of another task.
Here is an example of use:
class OtherTaskConfig(lsst.pex.config.Config): aSubtask = ATaskClass.makeField("brief description of task")
- makeSubtask(name: str, **keyArgs: Any) None ¶
Create a subtask as a new instance as the
name
attribute of this task.- Parameters:
- name
str
Brief name of the subtask.
- **keyArgs
Extra keyword arguments used to construct the task. The following arguments are automatically provided and cannot be overridden:
config
.parentTask
.
- name
Notes
The subtask must be defined by
Task.config.name
, an instance ofConfigurableField
orRegistryField
.
- run(handle, funcs=None, dataId=None, band=None)¶
Do postprocessing calculations
Takes a
DeferredDatasetHandle
orInMemoryDatasetHandle
orDataFrame
object and dataId, returns a dataframe with results of postprocessing calculations.- Parameters:
- handles
DeferredDatasetHandle
or InMemoryDatasetHandle
orDataFrame
, or list of these.DataFrames from which calculations are done.
- funcs
Functor
Functors to apply to the table’s columns
- dataIddict, optional
Used to add a
patchId
column to the output dataframe.- band
str
, optional Filter band that is being processed.
- handles
- Returns:
- runQuantum(butlerQC, inputRefs, outputRefs)¶
Do butler IO and transform to provide in memory objects for tasks
run
method.- Parameters:
- butlerQC
QuantumContext
A butler which is specialized to operate in the context of a
lsst.daf.butler.Quantum
.- inputRefs
InputQuantizedConnection
Datastructure whose attribute names are the names that identify connections defined in corresponding
PipelineTaskConnections
class. The values of these attributes are thelsst.daf.butler.DatasetRef
objects associated with the defined input/prerequisite connections.- outputRefs
OutputQuantizedConnection
Datastructure whose attribute names are the names that identify connections defined in corresponding
PipelineTaskConnections
class. The values of these attributes are thelsst.daf.butler.DatasetRef
objects associated with the defined output connections.
- butlerQC
- timer(name: str, logLevel: int = 10) Iterator[None] ¶
Context manager to log performance data for an arbitrary block of code.
- Parameters:
See also
lsst.utils.timer.logInfo
Implementation function.
Examples
Creating a timer context:
with self.timer("someCodeToTime"): pass # code to time
- transform(band, handles, funcs, dataId)¶