ImageMapReduceTask¶
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class
lsst.ip.diffim.
ImageMapReduceTask
(*args, **kwargs)¶ Bases:
lsst.pipe.base.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
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emptyMetadata
()¶ Empty (clear) the metadata for this Task and all sub-Tasks.
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getAllSchemaCatalogs
()¶ 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
()¶ Get metadata for all tasks.
Returns: - metadata :
lsst.daf.base.PropertySet
The
PropertySet
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
()¶ 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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getSchemaCatalogs
()¶ 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
()¶ 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)¶ 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, **keyArgs)¶ 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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plotBoxes
(fullBBox, skip=3)¶ Plot both grids of boxes using matplotlib.
Will compute the grid via
_generateGrid
ifself.boxes0
andself.boxes1
have not already been set.Parameters: - exposure :
lsst.afw.image.Exposure
Exposure whose bounding box is gridded by this task.
- skip :
int
Plot every skip-ped box (help make plots less confusing)
- exposure :
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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 performconfig.mapper.run()
on each. Reduce the resulting sub-exposures by runningconfig.reducer.run()
.Parameters: - exposure :
lsst.afw.image.Exposure
the full exposure to process
- kwargs :
additional keyword arguments to be passed to subtask
run
methods
Returns: - output of `reducer.run()`
- exposure :
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timer
(name, logLevel=10)¶ 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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