ImageMapReduceTask

class lsst.ip.diffim.ImageMapReduceTask(*args, **kwargs)

Bases: Task

Split an Exposure into subExposures (optionally on a grid) and perform the same operation on each.

Perform ‘simple’ operations on a gridded set of subExposures of a larger Exposure, and then (by default) have those subExposures stitched back together into a new, full-sized image.

Contrary to the expectation given by its name, this task does not perform these operations in parallel, although it could be updatd to provide such functionality.

The actual operations are performed by two subTasks passed to the config. The exposure passed to this task’s run method will be divided, and those subExposures will be passed to the subTasks, along with the original exposure. The reducing operation is performed by the second subtask.

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.

plotBoxes(fullBBox[, skip])

Plot both grids of boxes using matplotlib.

run(exposure, **kwargs)

Perform a map-reduce operation on the given exposure.

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.

plotBoxes(fullBBox, skip=3)

Plot both grids of boxes using matplotlib.

Will compute the grid via _generateGrid if self.boxes0 and self.boxes1 have not already been set.

Parameters:
exposurelsst.afw.image.Exposure

Exposure whose bounding box is gridded by this task.

skipint

Plot every skip-ped box (help make plots less confusing)

run(exposure, **kwargs)

Perform a map-reduce operation on the given exposure.

Split the exposure into sub-expposures on a grid (parameters given by ImageMapReduceConfig) and perform config.mapper.run() on each. Reduce the resulting sub-exposures by running config.reducer.run().

Parameters:
exposurelsst.afw.image.Exposure

the full exposure to process

kwargs

additional keyword arguments to be passed to subtask run methods

Returns:
output of reducer.run()
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