DipoleMeasurementTask¶

class lsst.ip.diffim.DipoleMeasurementTask(schema, algMetadata=None, **kwds)¶

Bases: lsst.meas.base.SingleFrameMeasurementTask

Measurement of Sources, specifically ones from difference images, for characterization as dipoles

Parameters:	sources : ‘lsst.afw.table.SourceCatalog’ Sources that will be measured badFlags : `list` of `dict` A list of flags that will be used to determine if there was a measurement problem

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 pipetask command line interface supports a flag –debug to import @b 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

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_ID`
`NOISE_OFFSET`
`NOISE_SEED_MULTIPLIER`
`NOISE_SOURCE`
`algMetadata`
`plugins`

Methods Summary

`callMeasure`(measRecord, args, *kwds)	Call `measure` on all plugins and consistently handle exceptions.
`callMeasureN`(measCat, args, *kwds)	Call `measureN` on all plugins and consistently handle exceptions.
`doMeasurement`(plugin, measRecord, args, *kwds)	Call `measure` on the specified plugin.
`doMeasurementN`(plugin, measCat, args, *kwds)	Call `measureN` on the specified plugin.
`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`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.
`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.ConfigurableField` for this task.
`makeSubtask`(name, **keyArgs)	Create a subtask as a new instance as the `name` attribute 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

NOISE_EXPOSURE_ID = 'NOISE_EXPOSURE_ID'¶

NOISE_OFFSET = 'NOISE_OFFSET'¶

NOISE_SEED_MULTIPLIER = 'NOISE_SEED_MULTIPLIER'¶

NOISE_SOURCE = 'NOISE_SOURCE'¶

algMetadata = None¶

plugins = None¶

Methods Documentation

callMeasure(measRecord, *args, **kwds)¶

Call measure on 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 < beginOrder are not executed. None for no limit.
endOrder : int: Ending execution order (exclusive). Measurements with executionOrder >= endOrder are not executed. None for no limit.

Others are forwarded to plugin.measure().

Notes

This method can be used with plugins that have different signatures; the only requirement is that measRecord be 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.

callMeasureN(measCat, *args, **kwds)¶

Call measureN on 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 < beginOrder are not executed. None for no limit.
endOrder:: Ending execution order (exclusive): measurements with executionOrder >= endOrder are not executed. None for no limit.

Others are are forwarded to plugin.measure().

Notes

This method can be used with plugins that have different signatures; the only requirement is that measRecord be 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.

doMeasurement(plugin, measRecord, *args, **kwds)¶

Call measure on 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 plugin and measRecord be 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.

doMeasurementN(plugin, measCat, *args, **kwds)¶

Call measureN on 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 plugin and measCat be 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.

emptyMetadata() → None¶: Empty (clear) the metadata for this Task and all sub-Tasks.

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.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:	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”.

getName() → str¶

Get the name of the task.

Returns:	taskName : `str` Name of the task.

See also

getFullName

getTaskDict() → Dict[str, weakref.ReferenceType[lsst.pipe.base.task.Task]]¶

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.

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 plugins attribute and add corresponding output fields and slot aliases to the output schema.

In addition to the attributes added by BaseMeasurementTask.__init__, a schema` 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.

classmethod makeField(doc: str) → lsst.pex.config.configurableField.ConfigurableField¶

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")

makeSubtask(name: str, **keyArgs) → None¶

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 of ConfigurableField or RegistryField.

measure(measCat, exposure)¶: Backwards-compatibility alias for run.

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 (with lsst.afw.detection.Footprints attached), and have a schema that is a superset of self.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 < beginOrder are not executed. None for no limit.
endOrder : float, optional: Final execution order (exclusive): measurements with executionOrder >= endOrder are not executed. None for no limit.

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 (with lsst.afw.detection.Footprints attached), and have a schema that is a superset of self.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 < beginOrder are not executed. None for no limit.
endOrder : float, optional: Final execution order (exclusive): measurements with executionOrder >= endOrder are not executed. None for no limit.

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

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: `Start` and `End`. logLevel A `logging` level constant.

Navigation

DipoleMeasurementTask¶