ImageReducer

class lsst.ip.diffim.ImageReducer(config: Optional[Config] = None, name: Optional[str] = None, parentTask: Optional[Task] = None, log: Optional[Union[logging.Logger, lsst.utils.logging.LsstLogAdapter]] = None)

Bases: Task

Base class for any ‘reduce’ task that is to be used as ImageMapReduceConfig.reducer.

Basic reduce operations are provided by the run method of this class, to be selected by its config.

Methods Summary

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.

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(mapperResults, exposure, **kwargs)

Reduce a list of items produced by ImageMapper.

timer(name[, logLevel])

Context manager to log performance data for an arbitrary block of code.

Methods Documentation

emptyMetadata() → None

Empty (clear) the metadata for this Task and all sub-Tasks.

getAllSchemaCatalogs() → Dict[str, Any]

Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.

Returns:
schemacatalogsdict

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.

getFullMetadata() → TaskMetadata

Get metadata for all tasks.

Returns:
metadataTaskMetadata

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.

getFullName() → str

Get the task name as a hierarchical name including parent task names.

Returns:
fullNamestr

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”.

getName() → str

Get the name of the task.

Returns:
taskNamestr

Name of the task.

See also

getFullName
getSchemaCatalogs() → Dict[str, Any]

Get the schemas generated by this task.

Returns:
schemaCatalogsdict

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.

getTaskDict() → Dict[str, ReferenceType[Task]]

Get a dictionary of all tasks as a shallow copy.

Returns:
taskDictdict

Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc.

classmethod makeField(doc: str) → ConfigurableField

Make a lsst.pex.config.ConfigurableField for this task.

Parameters:
docstr

Help text for the field.

Returns:
configurableFieldlsst.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")
makeSubtask(name: str, **keyArgs: Any) → None

Create a subtask as a new instance as the name attribute of this task.

Parameters:
namestr

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 of ConfigurableField or RegistryField.

run(mapperResults, exposure, **kwargs)

Reduce a list of items produced by ImageMapper.

Either stitch the passed mapperResults list together into a new Exposure (default) or pass it through (if self.config.reduceOperation is ‘none’).

If self.config.reduceOperation is not ‘none’, then expect that the pipeBase.Struct`s in the `mapperResults list contain sub-exposures named ‘subExposure’, to be stitched back into a single Exposure with the same dimensions, PSF, and mask as the input exposure. Otherwise, the mapperResults list is simply returned directly.

Parameters:
mapperResultslist

list of lsst.pipe.base.Struct returned by ImageMapper.run.

exposurelsst.afw.image.Exposure

the original exposure which is cloned to use as the basis for the resulting exposure (if self.config.mapper.reduceOperation is not ‘None’)

kwargs

additional keyword arguments propagated from ImageMapReduceTask.run.

Returns:
A lsst.pipe.base.Struct containing either an lsst.afw.image.Exposure
(named ‘exposure’) or a list (named ‘result’),
depending on config.reduceOperation.

Notes

  1. This currently correctly handles overlapping sub-exposures. For overlapping sub-exposures, use config.reduceOperation='average'.

  2. This correctly handles varying PSFs, constructing the resulting exposure’s PSF via CoaddPsf (DM-9629).

Known issues

  1. To be done: correct handling of masks (nearly there)

  2. This logic currently makes two copies of the original exposure (one here and one in mapper.run()). Possibly of concern for large images on memory-constrained systems.

timer(name: str, logLevel: int = 10) → Iterator[None]

Context manager to log performance data for an arbitrary block of code.

Parameters:
namestr

Name of code being timed; data will be logged using item name: Start and End.

logLevel

A logging level constant.

See also

timer.logInfo

Examples

Creating a timer context:

with self.timer("someCodeToTime"):
    pass  # code to time