FinalizeCharacterizationTask¶
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class
lsst.pipe.tasks.finalizeCharacterization.
FinalizeCharacterizationTask
(initInputs=None, **kwargs)¶ Bases:
lsst.pipe.base.PipelineTask
Run final characterization on exposures.
Attributes Summary
canMultiprocess
Methods Summary
compute_psf_and_ap_corr_map
(visit, detector, …)Compute psf model and aperture correction map for a single exposure. concat_isolated_star_cats
(band, …)Concatenate isolated star catalogs and make reserve selection. emptyMetadata
()Empty (clear) the metadata for this Task and all sub-Tasks. getAllSchemaCatalogs
()Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict. getFullMetadata
()Get metadata for all tasks. getFullName
()Get the task name as a hierarchical name including parent task names. getName
()Get the name of the task. getResourceConfig
()Return resource configuration for this task. getSchemaCatalogs
()Get the schemas generated by this task. getTaskDict
()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
(visit, band, isolated_star_cat_dict, …)Run the FinalizeCharacterizationTask. 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. Attributes Documentation
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canMultiprocess
= True¶
Methods Documentation
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compute_psf_and_ap_corr_map
(visit, detector, exposure, src, isolated_source_table)¶ Compute psf model and aperture correction map for a single exposure.
Parameters: - visit :
int
Visit number (for logging).
- detector :
int
Detector number (for logging).
- exposure :
lsst.afw.image.ExposureF
- src :
lsst.afw.table.SourceCatalog
- isolated_source_table :
np.ndarray
Returns: - psf :
lsst.meas.algorithms.ImagePsf
PSF Model
- ap_corr_map :
lsst.afw.image.ApCorrMap
Aperture correction map.
- measured_src :
lsst.afw.table.SourceCatalog
Updated source catalog with measurements, flags and aperture corrections.
- visit :
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concat_isolated_star_cats
(band, isolated_star_cat_dict, isolated_star_source_dict)¶ Concatenate isolated star catalogs and make reserve selection.
Parameters: Returns: - isolated_table :
np.ndarray
(N,) Table of isolated stars, with indexes to isolated sources.
- isolated_source_table :
np.ndarray
(M,) Table of isolated sources, with indexes to isolated stars.
- isolated_table :
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emptyMetadata
() → None¶ Empty (clear) the metadata for this Task and all sub-Tasks.
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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.
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.- schemacatalogs :
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getFullMetadata
() → lsst.pipe.base._task_metadata.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.
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.- metadata :
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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 :
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getResourceConfig
() → Optional[ResourceConfig]¶ 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.
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.
- schemaCatalogs :
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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 :
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classmethod
makeField
(doc: str) → lsst.pex.config.configurableField.ConfigurableField¶ Make a
lsst.pex.config.ConfigurableField
for this task.Parameters: - doc :
str
Help text for the field.
Returns: - configurableField :
lsst.pex.config.ConfigurableField
A
ConfigurableField
for this task.
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")
- doc :
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makeSubtask
(name: str, **keyArgs) → 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”.
Notes
The subtask must be defined by
Task.config.name
, an instance ofConfigurableField
orRegistryField
.- name :
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run
(visit, band, isolated_star_cat_dict, isolated_star_source_dict, src_dict, calexp_dict)¶ Run the FinalizeCharacterizationTask.
Parameters: - visit :
int
Visit number. Used in the output catalogs.
- band :
str
Band name. Used to select reserved stars.
- isolated_star_cat_dict :
dict
Per-tract dict of isolated star catalog handles.
- isolated_star_source_dict :
dict
Per-tract dict of isolated star source catalog handles.
- src_dict :
dict
Per-detector dict of src catalog handles.
- calexp_dict :
dict
Per-detector dict of calibrated exposure handles.
Returns: - struct :
lsst.pipe.base.struct
Struct with outputs for persistence.
- visit :
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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 :
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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
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