TransformDiaSourceCatalogTask¶
- class lsst.ap.association.TransformDiaSourceCatalogTask(initInputs, **kwargs)¶
Bases:
TransformCatalogBaseTask
Apply Science DataModel-ification on the DiaSource afw table.
This task calibrates and renames columns in the DiaSource catalog to ready the catalog for insertion into the Apdb.
This is a Gen3 Butler only task. It will not run in Gen2.
Attributes Summary
Methods Summary
Add Column functor for each of the flags
bitPackFlags
(df)Pack requested flag columns in inputRecord into single columns in outputRecord.
computeBBoxSizes
(inputCatalog)Compute the size of a square bbox that fully contains the detection footprint.
Empty (clear) the metadata for this Task and all sub-Tasks.
Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
getAnalysis
(parq[, 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.
Return resource configuration for this task.
Get the schemas generated by this 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
(diaSourceCat, diffIm, band, ccdVisitId)Convert input catalog to ParquetTable/Pandas and run functors.
runQuantum
(butlerQC, inputRefs, outputRefs)Method to do butler IO and or transforms 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, parq, funcs, dataId)write
(df, parqRef)writeMetadata
(dataRef)No metadata to write.
Attributes Documentation
- inputDataset = 'deepDiff_diaSrc'¶
- outputDataset = 'deepDiff_diaSrcTable'¶
Methods Documentation
- addUnpackedFlagFunctors()¶
Add Column functor for each of the flags
to the internal functor dictionary
- bitPackFlags(df)¶
Pack requested flag columns in inputRecord into single columns in outputRecord.
- Parameters:
- df
pandas.DataFrame
DataFrame to read bits from and pack them into.
- df
- computeBBoxSizes(inputCatalog)¶
Compute the size of a square bbox that fully contains the detection footprint.
- Parameters:
- inputCatalog
lsst.afw.table.SourceCatalog
Catalog containing detected footprints.
- inputCatalog
- Returns:
- getAllSchemaCatalogs() Dict[str, Any] ¶
Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
- Returns:
- schemacatalogs
dict
Keys are butler dataset type, values are a empty catalog (an instance of the appropriate
lsst.afw.table
Catalog type) for all tasks in the hierarchy, from the top-level task down through all subtasks.
- schemacatalogs
Notes
This method may be called on any task in the hierarchy; it will return the same answer, regardless.
The default implementation should always suffice. If your subtask uses schemas the override
Task.getSchemaCatalogs
, not this method.
- getAnalysis(parq, 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()¶
- getResourceConfig() ResourceConfig | None ¶
Return resource configuration for this task.
- Returns:
- Object of type
ResourceConfig
orNone
if resource - configuration is not defined for this task.
- Object of type
- getSchemaCatalogs() Dict[str, Any] ¶
Get the schemas generated by this task.
- Returns:
- schemaCatalogs
dict
Keys are butler dataset type, values are an empty catalog (an instance of the appropriate
lsst.afw.table
Catalog type) for this task.
- schemaCatalogs
See also
Task.getAllSchemaCatalogs
Notes
Warning
Subclasses that use schemas must override this method. The default implementation returns an empty dict.
This method may be called at any time after the Task is constructed, which means that all task schemas should be computed at construction time, not when data is actually processed. This reflects the philosophy that the schema should not depend on the data.
Returning catalogs rather than just schemas allows us to save e.g. slots for SourceCatalog as well.
- getTaskDict() Dict[str, ReferenceType[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(diaSourceCat, diffIm, band, ccdVisitId, funcs=None)¶
Convert input catalog to ParquetTable/Pandas and run functors.
Additionally, add new columns for stripping information from the exposure and into the DiaSource catalog.
- Parameters:
- Returns:
- results
lsst.pipe.base.Struct
Results struct with components.
diaSourceTable
: Catalog of DiaSources with calibrated values and renamed columns. (lsst.pipe.tasks.ParquetTable
orpandas.DataFrame
)
- results
- runQuantum(butlerQC, inputRefs, outputRefs)¶
Method to do butler IO and or transforms to provide in memory objects for tasks run method
- Parameters:
- butlerQC
ButlerQuantumContext
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
timer.logInfo
Examples
Creating a timer context:
with self.timer("someCodeToTime"): pass # code to time
- transform(band, parq, funcs, dataId)¶
- write(df, parqRef)¶
- writeMetadata(dataRef)¶
No metadata to write.