DipoleMeasurementTask¶
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class
lsst.ip.diffim.DipoleMeasurementTask(schema, algMetadata=None, **kwds)¶ Bases:
lsst.meas.base.SingleFrameMeasurementTaskMeasurement of Sources, specifically ones from difference images, for characterization as dipoles
Parameters: Notes
The list of badFlags will be used to make a list of keys to check for measurement flags on. By default the centroid keys are added to this list
Description
This class provides a default configuration for running Source measurement on image differences.
class DipoleMeasurementConfig(SingleFrameMeasurementConfig): "Measurement of detected diaSources as dipoles" def setDefaults(self): SingleFrameMeasurementConfig.setDefaults(self) self.plugins = ["base_CircularApertureFlux", "base_PixelFlags", "base_SkyCoord", "base_PsfFlux", "ip_diffim_NaiveDipoleCentroid", "ip_diffim_NaiveDipoleFlux", "ip_diffim_PsfDipoleFlux", "ip_diffim_ClassificationDipole", ] self.slots.calibFlux = None self.slots.modelFlux = None self.slots.instFlux = None self.slots.shape = None self.slots.centroid = "ip_diffim_NaiveDipoleCentroid" self.doReplaceWithNoise = False
These plugins enabled by default allow the user to test the hypothesis that the Source is a dipole. This includes a set of measurements derived from intermediate base classes DipoleCentroidAlgorithm and DipoleFluxAlgorithm. Their respective algorithm control classes are defined in DipoleCentroidControl and DipoleFluxControl. Each centroid and flux measurement will have _neg (negative) and _pos (positive lobe) fields.
The first set of measurements uses a “naive” alrogithm for centroid and flux measurements, implemented in NaiveDipoleCentroidControl and NaiveDipoleFluxControl. The algorithm uses a naive 3x3 weighted moment around the nominal centroids of each peak in the Source Footprint. These algorithms fill the table fields ip_diffim_NaiveDipoleCentroid* and ip_diffim_NaiveDipoleFlux*
The second set of measurements undertakes a joint-Psf model on the negative and positive lobe simultaneously. This fit simultaneously solves for the negative and positive lobe centroids and fluxes using non-linear least squares minimization. The fields are stored in table elements ip_diffim_PsfDipoleFlux*.
Because this Task is just a config for SingleFrameMeasurementTask, the same result may be acheived by manually editing the config and running SingleFrameMeasurementTask. For example:
config = SingleFrameMeasurementConfig() config.plugins.names = ["base_PsfFlux", "ip_diffim_PsfDipoleFlux", "ip_diffim_NaiveDipoleFlux", "ip_diffim_NaiveDipoleCentroid", "ip_diffim_ClassificationDipole", "base_CircularApertureFlux", "base_SkyCoord"] config.slots.calibFlux = None config.slots.modelFlux = None config.slots.instFlux = None config.slots.shape = None config.slots.centroid = "ip_diffim_NaiveDipoleCentroid" config.doReplaceWithNoise = False schema = afwTable.SourceTable.makeMinimalSchema() task = SingleFrameMeasurementTask(schema, config=config)-
Debug variables
The
lsst.pipe.base.cmdLineTask.CmdLineTaskcommand line task interface supports a flag-d/–debug to import debug.py from your PYTHONPATH. The relevant contents of debug.py for this Task include:import sys import lsstDebug def DebugInfo(name): di = lsstDebug.getInfo(name) if name == "lsst.ip.diffim.dipoleMeasurement": di.display = True # enable debug output di.maskTransparency = 90 # display mask transparency di.displayDiaSources = True # show exposure with dipole results return di lsstDebug.Info = DebugInfo lsstDebug.frame = 1 config.slots.calibFlux = None config.slots.modelFlux = None config.slots.gaussianFlux = None config.slots.shape = None config.slots.centroid = "ip_diffim_NaiveDipoleCentroid" config.doReplaceWithNoise = False
This code is dipoleMeasTask.py in the examples directory, and can be run as e.g.
examples/dipoleMeasTask.py examples/dipoleMeasTask.py --debug examples/dipoleMeasTask.py --debug --image /path/to/image.fits
Start the processing by parsing the command line, where the user has the option of enabling debugging output and/or sending their own image for demonstration (in case they have not downloaded the afwdata package).
if __name__ == "__main__": import argparse parser = argparse.ArgumentParser( description="Demonstrate the use of SourceDetectionTask and DipoleMeasurementTask") parser.add_argument('--debug', '-d', action="store_true", help="Load debug.py?", default=False) parser.add_argument("--image", "-i", help="User defined image", default=None) args = parser.parse_args() if args.debug: try: import debug debug.lsstDebug.frame = 2 except ImportError as e: print(e, file=sys.stderr) run(args)
The processing occurs in the run function. We first extract an exposure from disk or afwdata, displaying it if requested:
def run(args): exposure = loadData(args.image) if args.debug: afwDisplay.Display(frame=1).mtv(exposure)
Create a default source schema that we will append fields to as we add more algorithms:
schema = afwTable.SourceTable.makeMinimalSchema()
Create the detection and measurement Tasks, with some minor tweaking of their configs:
# Create the detection task config = SourceDetectionTask.ConfigClass() config.thresholdPolarity = "both" config.background.isNanSafe = True config.thresholdValue = 3 detectionTask = SourceDetectionTask(config=config, schema=schema) # And the measurement Task config = DipoleMeasurementTask.ConfigClass() config.plugins.names.remove('base_SkyCoord') algMetadata = dafBase.PropertyList() measureTask = DipoleMeasurementTask(schema, algMetadata, config=config)
Having fully initialied the schema, we create a Source table from it:
# Create the output table tab = afwTable.SourceTable.make(schema)
Run detection:
# Process the data results = detectionTask.run(tab, exposure)
Because we are looking for dipoles, we need to merge the positive and negative detections:
# Merge the positve and negative sources fpSet = results.fpSets.positive growFootprint = 2 fpSet.merge(results.fpSets.negative, growFootprint, growFootprint, False) diaSources = afwTable.SourceCatalog(tab) fpSet.makeSources(diaSources) print("Merged %s Sources into %d diaSources (from %d +ve, %d -ve)" % (len(results.sources), len(diaSources), results.fpSets.numPos, results.fpSets.numNeg))
Finally, perform measurement (both standard and dipole-specialized) on the merged sources:
measureTask.run(diaSources, exposure)
Optionally display debugging information:
# Display dipoles if debug enabled if args.debug: dpa = DipoleAnalysis() dpa.displayDipoles(exposure, diaSources)
Attributes Summary
NOISE_EXPOSURE_IDNOISE_OFFSETNOISE_SEED_MULTIPLIERNOISE_SOURCEalgMetadatapluginsMethods Summary
callMeasure(measRecord, *args, **kwds)Call measureon all plugins and consistently handle exceptions.callMeasureN(measCat, *args, **kwds)Call measureNon all plugins and consistently handle exceptions.doMeasurement(plugin, measRecord, *args, **kwds)Call measureon the specified plugin.doMeasurementN(plugin, measCat, *args, **kwds)Call measureNon the specified plugin.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. getPluginLogName(pluginName)getSchemaCatalogs()Get the schemas generated by this task. getTaskDict()Get a dictionary of all tasks as a shallow copy. initializePlugins(**kwds)Initialize plugins (and slots) according to configuration. 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.measure(measCat, exposure)Backwards-compatibility alias for run.run(measCat, exposure[, noiseImage, …])Run single frame measurement over an exposure and source catalog. runPlugins(noiseReplacer, measCat, exposure)Call the configured measument plugins on an image. timer(name[, logLevel])Context manager to log performance data for an arbitrary block of code. Attributes Documentation
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NOISE_EXPOSURE_ID= 'NOISE_EXPOSURE_ID'¶
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NOISE_OFFSET= 'NOISE_OFFSET'¶
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NOISE_SEED_MULTIPLIER= 'NOISE_SEED_MULTIPLIER'¶
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NOISE_SOURCE= 'NOISE_SOURCE'¶
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algMetadata= None¶
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plugins= None¶
Methods Documentation
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callMeasure(measRecord, *args, **kwds)¶ Call
measureon all plugins and consistently handle exceptions.Parameters: - measRecord :
lsst.afw.table.SourceRecord The record corresponding to the object being measured. Will be updated in-place with the results of measurement.
- *args
Positional arguments forwarded to
plugin.measure- **kwds
Keyword arguments. Two are handled locally:
- beginOrder :
int Beginning execution order (inclusive). Measurements with
executionOrder<beginOrderare not executed.Nonefor no limit.- endOrder :
int Ending execution order (exclusive). Measurements with
executionOrder>=endOrderare not executed.Nonefor no limit.
Others are forwarded to
plugin.measure().- beginOrder :
Notes
This method can be used with plugins that have different signatures; the only requirement is that
measRecordbe the first argument. Subsequent positional arguments and keyword arguments are forwarded directly to the plugin.This method should be considered “protected”: it is intended for use by derived classes, not users.
- measRecord :
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callMeasureN(measCat, *args, **kwds)¶ Call
measureNon all plugins and consistently handle exceptions.Parameters: - measCat :
lsst.afw.table.SourceCatalog Catalog containing only the records for the source family to be measured, and where outputs should be written.
- *args
Positional arguments forwarded to
plugin.measure()- **kwds
Keyword arguments. Two are handled locally:
- beginOrder:
Beginning execution order (inclusive): Measurements with
executionOrder<beginOrderare not executed.Nonefor no limit.- endOrder:
Ending execution order (exclusive): measurements with
executionOrder>=endOrderare not executed.Nonefor nolimit.
Others are are forwarded to
plugin.measure().
Notes
This method can be used with plugins that have different signatures; the only requirement is that
measRecordbe the first argument. Subsequent positional arguments and keyword arguments are forwarded directly to the plugin.This method should be considered “protected”: it is intended for use by derived classes, not users.
- measCat :
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doMeasurement(plugin, measRecord, *args, **kwds)¶ Call
measureon the specified plugin.Exceptions are handled in a consistent way.
Parameters: - plugin : subclass of
BasePlugin Plugin that will be executed.
- measRecord :
lsst.afw.table.SourceRecord The record corresponding to the object being measured. Will be updated in-place with the results of measurement.
- *args
Positional arguments forwarded to
plugin.measure().- **kwds
Keyword arguments forwarded to
plugin.measure().
Notes
This method can be used with plugins that have different signatures; the only requirement is that
pluginandmeasRecordbe the first two arguments. Subsequent positional arguments and keyword arguments are forwarded directly to the plugin.This method should be considered “protected”: it is intended for use by derived classes, not users.
- plugin : subclass of
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doMeasurementN(plugin, measCat, *args, **kwds)¶ Call
measureNon the specified plugin.Exceptions are handled in a consistent way.
Parameters: - plugin : subclass of
BasePlugin Plugin that will be executed.
- measCat :
lsst.afw.table.SourceCatalog Catalog containing only the records for the source family to be measured, and where outputs should be written.
- *args
Positional arguments forwarded to
plugin.measureN().- **kwds
Keyword arguments forwarded to
plugin.measureN().
Notes
This method can be used with plugins that have different signatures; the only requirement is that the
pluginandmeasCatbe the first two arguments. Subsequent positional arguments and keyword arguments are forwarded directly to the plugin.This method should be considered “protected”: it is intended for use by derived classes, not users.
- plugin : subclass of
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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.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 :
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getFullMetadata()¶ Get metadata for all tasks.
Returns: - metadata :
lsst.daf.base.PropertySet The
PropertySetkeys 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 :
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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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getPluginLogName(pluginName)¶
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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.tableCatalog type) for this task.
See also
Task.getAllSchemaCatalogsNotes
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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initializePlugins(**kwds)¶ Initialize plugins (and slots) according to configuration.
Parameters: - **kwds
Keyword arguments forwarded directly to plugin constructors.
Notes
Derived class constructors should call this method to fill the
pluginsattribute and add corresponding output fields and slot aliases to the output schema.In addition to the attributes added by
BaseMeasurementTask.__init__, aschema`attribute holding the output schema must be present before this method is called.Keyword arguments are forwarded directly to plugin constructors, allowing derived classes to use plugins with different signatures.
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classmethod
makeField(doc)¶ 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 :
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makeSubtask(name, **keyArgs)¶ 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 :
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run(measCat, exposure, noiseImage=None, exposureId=None, beginOrder=None, endOrder=None)¶ Run single frame measurement over an exposure and source catalog.
Parameters: - measCat :
lsst.afw.table.SourceCatalog Catalog to be filled with the results of measurement. Must contain all the
lsst.afw.table.SourceRecords to be measured (withlsst.afw.detection.Footprints attached), and have a schema that is a superset ofself.schema.- exposure :
lsst.afw.image.ExposureF Image containing the pixel data to be measured together with associated PSF, WCS, etc.
- noiseImage :
lsst.afw.image.ImageF, optional Can be used to specify the a predictable noise replacement field for testing purposes.
- exposureId :
int, optional Unique exposure identifier used to calculate the random number generator seed during noise replacement.
- beginOrder :
float, optional Start execution order (inclusive): measurements with
executionOrder < beginOrderare not executed.Nonefor no limit.- endOrder :
float, optional Final execution order (exclusive): measurements with
executionOrder >= endOrderare not executed.Nonefor no limit.
- measCat :
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runPlugins(noiseReplacer, measCat, exposure, beginOrder=None, endOrder=None)¶ Call the configured measument plugins on an image.
Parameters: - noiseReplacer :
NoiseReplacer Used to fill sources not being measured with noise.
- measCat :
lsst.afw.table.SourceCatalog Catalog to be filled with the results of measurement. Must contain all the
lsst.afw.table.SourceRecords to be measured (withlsst.afw.detection.Footprints attached), and have a schema that is a superset ofself.schema.- exposure :
lsst.afw.image.ExposureF Image containing the pixel data to be measured together with associated PSF, WCS, etc.
- beginOrder :
float, optional Start execution order (inclusive): measurements with
executionOrder < beginOrderare not executed.Nonefor no limit.- endOrder :
float, optional Final execution order (exclusive): measurements with
executionOrder >= endOrderare not executed.Nonefor no limit.
- noiseReplacer :
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timer(name, logLevel=10000)¶ Context manager to log performance data for an arbitrary block of code.
Parameters: - name :
str Name of code being timed; data will be logged using item name:
StartandEnd.- logLevel
A
lsst.loglevel constant.
See also
timer.logInfoExamples
Creating a timer context:
with self.timer("someCodeToTime"): pass # code to time
- name :
-