ReserveSourcesTask¶
-
class
lsst.meas.algorithms.ReserveSourcesTask(columnName=None, schema=None, doc=None, **kwargs)¶ Bases:
lsst.pipe.base.TaskReserve sources from analysis
We randomly select a fraction of sources that will be reserved from analysis. This allows evaluation of the quality of model fits using sources that were not involved in the fitting process.
Parameters: - columnName :
str, required Name of flag column to add; we will suffix this with “_reserved”.
- schema :
lsst.afw.table.Schema, required Catalog schema.
- doc :
str Documentation for column to add.
- config :
ReserveSourcesConfig Configuration.
Methods Summary
applySelectionPrior(prior, selection)Apply selection to full catalog 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.ConfigurableFieldfor this task.makeSubtask(name, **keyArgs)Create a subtask as a new instance as the nameattribute of this task.markSources(sources, selection)Mark sources in a list or catalog run(sources[, prior, expId])Select sources to be reserved select(numSources[, expId])Randomly select some sources timer(name, logLevel)Context manager to log performance data for an arbitrary block of code. Methods Documentation
-
applySelectionPrior(prior, selection)¶ Apply selection to full catalog
The
selectmethod makes a random selection of sources. If those sources don’t represent the full population (because a sub-selection has already been made), then we need to generate a selection covering the entire population.Parameters: - prior :
numpy.ndarrayof typebool Prior selection of sources, identifying the subset from which the random selection has been made.
- selection :
numpy.ndarrayof typebool Selection of sources in subset identified by
prior.
Returns: - full :
numpy.ndarrayof typebool Selection applied to full population.
- prior :
-
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: - schemacatalogs :
dict Keys are butler dataset type, values are a empty catalog (an instance of the appropriate
lsst.afw.tableCatalog 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 :
-
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.timeMethodis 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 :
-
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 :
-
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.tableCatalog 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 :
-
getTaskDict() → Dict[str, weakref]¶ 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) → lsst.pex.config.configurableField.ConfigurableField¶ Make a
lsst.pex.config.ConfigurableFieldfor this task.Parameters: - doc :
str Help text for the field.
Returns: - configurableField :
lsst.pex.config.ConfigurableField A
ConfigurableFieldfor 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 :
-
makeSubtask(name: str, **keyArgs) → None¶ Create a subtask as a new instance as the
nameattribute 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 ofConfigurableFieldorRegistryField.- name :
-
markSources(sources, selection)¶ Mark sources in a list or catalog
This requires iterating through the list and setting the flag in each source individually. Even if the
sourcesis aCatalogwith contiguous records, it’s not currently possible to set a boolean column (DM-6981) so we need to iterate.Parameters: - catalog :
lsst.afw.table.Catalogorlistoflsst.afw.table.Record Catalog in which to flag selected sources.
- selection :
numpy.ndarrayof typebool Selection of sources to mark.
- catalog :
-
run(sources, prior=None, expId=0)¶ Select sources to be reserved
Reserved sources will be flagged in the catalog, and we will return boolean arrays that identify the sources to be reserved from and used in the analysis. Typically you’ll want to use the sources from the
usearray in your fitting, and use the sources from thereservedarray as an independent test of your fitting.Parameters: - sources :
lsst.afw.table.Catalogorlistoflsst.afw.table.Record Sources from which to select some to be reserved.
- prior :
numpy.ndarrayof typebool, optional Prior selection of sources. Should have the same length as
sources. If set, we will only consider for reservation sources that are flaggedTruein this array.- expId :
int Exposure identifier; used for seeding the random number generator.
Returns: - results :
lsst.pipe.base.Struct The results in a
Struct:reservedSources to be reserved are flagged
Truein this array. (numpy.ndarrayof typebool)useSources the user should use in analysis are flagged
True. (numpy.ndarrayof typebool)
- sources :
-
select(numSources, expId=0)¶ Randomly select some sources
We return a boolean array with a random selection. The fraction of sources selected is specified by the config parameter
fraction.Parameters: Returns: - selection :
numpy.ndarrayof typebool Selected sources are flagged
Truein this array.
- selection :
-
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
- columnName :