lsst.meas.algorithms.measureApCorr.MeasureApCorrTask Class Reference

Inheritance diagram for lsst.meas.algorithms.measureApCorr.MeasureApCorrTask:

Public Member Functions
def	__init__ (self, schema, **kwds)
def	run (self, exposure, catalog)
def	emptyMetadata (self)
def	getSchemaCatalogs (self)
def	getAllSchemaCatalogs (self)
def	getFullMetadata (self)
def	getFullName (self)
def	getName (self)
def	getTaskDict (self)
def	makeSubtask (self, name, **keyArgs)
def	timer (self, name, logLevel=Log.DEBUG)
def	makeField (cls, doc)
def	__reduce__ (self)

Public Attributes
	refFluxKeys
	toCorrect
	metadata
	log
	config

Static Public Attributes
	ConfigClass = MeasureApCorrConfig

Detailed Description

Task to measure aperture correction

Definition at line 110 of file measureApCorr.py.

Constructor & Destructor Documentation

__init__()

def lsst.meas.algorithms.measureApCorr.MeasureApCorrTask.__init__	(		self,
			schema,
		**	kwds
	)

Construct a MeasureApCorrTask

For every name in lsst.meas.base.getApCorrNameSet():
- If the corresponding flux fields exist in the schema:
    - Add a new field apcorr_{name}_used
    - Add an entry to the self.toCorrect dict
- Otherwise silently skip the name

Definition at line 116 of file measureApCorr.py.

    def __init__(self, schema, **kwds):
        """Construct a MeasureApCorrTask
 
        For every name in lsst.meas.base.getApCorrNameSet():
        - If the corresponding flux fields exist in the schema:
            - Add a new field apcorr_{name}_used
            - Add an entry to the self.toCorrect dict
        - Otherwise silently skip the name
        """
        Task.__init__(self, **kwds)
        self.refFluxKeys = FluxKeys(self.config.refFluxName, schema)
        self.toCorrect = {}  # dict of flux field name prefix: FluxKeys instance
        for name in sorted(getApCorrNameSet()):
            try:
                self.toCorrect[name] = FluxKeys(name, schema)
            except KeyError:
                # if a field in the registry is missing, just ignore it.
                pass
        self.makeSubtask("sourceSelector")
 

Member Function Documentation

__reduce__()

def lsst.pipe.base.task.Task.__reduce__ (   self )

inherited

Pickler.

Reimplemented in lsst.pipe.drivers.multiBandDriver.MultiBandDriverTask, and lsst.pipe.drivers.coaddDriver.CoaddDriverTask.

Definition at line 432 of file task.py.

    def __reduce__(self):
        """Pickler.
        """
        return self._unpickle_via_factory, (self.__class__, [], self._reduce_kwargs())

emptyMetadata()

def lsst.pipe.base.task.Task.emptyMetadata (   self )

inherited

Empty (clear) the metadata for this Task and all sub-Tasks.

Definition at line 166 of file task.py.

    def emptyMetadata(self):
        """Empty (clear) the metadata for this Task and all sub-Tasks.
        """
        for subtask in self._taskDict.values():
            subtask.metadata = dafBase.PropertyList()
 

getAllSchemaCatalogs()

def lsst.pipe.base.task.Task.getAllSchemaCatalogs (   self )

inherited

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.

Definition at line 204 of file task.py.

    def getAllSchemaCatalogs(self):
        """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.
        """
        schemaDict = self.getSchemaCatalogs()
        for subtask in self._taskDict.values():
            schemaDict.update(subtask.getSchemaCatalogs())
        return schemaDict
 

getFullMetadata()

def lsst.pipe.base.task.Task.getFullMetadata (   self )

inherited

Get metadata for all tasks.

Returns
-------
metadata : `lsst.daf.base.PropertySet`
    The `~lsst.daf.base.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.

Definition at line 229 of file task.py.

    def getFullMetadata(self):
        """Get metadata for all tasks.
 
        Returns
        -------
        metadata : `lsst.daf.base.PropertySet`
            The `~lsst.daf.base.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.
        """
        fullMetadata = dafBase.PropertySet()
        for fullName, task in self.getTaskDict().items():
            fullMetadata.set(fullName.replace(".", ":"), task.metadata)
        return fullMetadata
 

getFullName()

def lsst.pipe.base.task.Task.getFullName (   self )

inherited

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".

Definition at line 256 of file task.py.

    def getFullName(self):
        """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".
        """
        return self._fullName
 

getName()

def lsst.pipe.base.task.Task.getName (   self )

inherited

Get the name of the task.

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

See also
--------
getFullName

Definition at line 274 of file task.py.

    def getName(self):
        """Get the name of the task.
 
        Returns
        -------
        taskName : `str`
            Name of the task.
 
        See also
        --------
        getFullName
        """
        return self._name
 

getSchemaCatalogs()

def lsst.pipe.base.task.Task.getSchemaCatalogs (   self )

inherited

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.

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.

See also
--------
Task.getAllSchemaCatalogs

Definition at line 172 of file task.py.

    def getSchemaCatalogs(self):
        """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.
 
        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.
 
        See also
        --------
        Task.getAllSchemaCatalogs
        """
        return {}
 

getTaskDict()

def lsst.pipe.base.task.Task.getTaskDict (   self )

inherited

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.

Definition at line 288 of file task.py.

    def getTaskDict(self):
        """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.
        """
        return self._taskDict.copy()
 

makeField()

def lsst.pipe.base.task.Task.makeField (   cls,   doc  )

inherited

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:

.. code-block:: python

    class OtherTaskConfig(lsst.pex.config.Config):
        aSubtask = ATaskClass.makeField("brief description of task")

Definition at line 359 of file task.py.

    def makeField(cls, 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:
 
        .. code-block:: python
 
            class OtherTaskConfig(lsst.pex.config.Config):
                aSubtask = ATaskClass.makeField("brief description of task")
        """
        return ConfigurableField(doc=doc, target=cls)
 

makeSubtask()

def lsst.pipe.base.task.Task.makeSubtask (   self,   name, **  keyArgs  )

inherited

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
`~lsst.pex.config.ConfigurableField` or
`~lsst.pex.config.RegistryField`.

Definition at line 299 of file task.py.

    def makeSubtask(self, 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 of
        `~lsst.pex.config.ConfigurableField` or
        `~lsst.pex.config.RegistryField`.
        """
        taskField = getattr(self.config, name, None)
        if taskField is None:
            raise KeyError(f"{self.getFullName()}'s config does not have field {name!r}")
        subtask = taskField.apply(name=name, parentTask=self, **keyArgs)
        setattr(self, name, subtask)
 

run()

def lsst.meas.algorithms.measureApCorr.MeasureApCorrTask.run	(		self,
			exposure,
			catalog
	)

Measure aperture correction

Parameters
----------
exposure : `lsst.afw.image.Exposure`
    Exposure aperture corrections are being measured on. The
    bounding box is retrieved from it, and it is passed to the
    sourceSelector. The output aperture correction map is *not*
    added to the exposure; this is left to the caller.
catalog : `lsst.afw.table.SourceCatalog`
    SourceCatalog containing measurements to be used to
    compute aperture corrections.

Returns
-------
Struct : `lsst.pipe.base.Struct`
    Contains the following:

    ``apCorrMap``
        aperture correction map (`lsst.afw.image.ApCorrMap`)
        that contains two entries for each flux field:
        - flux field (e.g. base_PsfFlux_instFlux): 2d model
        - flux sigma field (e.g. base_PsfFlux_instFluxErr): 2d model of error

Definition at line 136 of file measureApCorr.py.

    def run(self, exposure, catalog):
        """Measure aperture correction
 
        Parameters
        ----------
        exposure : `lsst.afw.image.Exposure`
            Exposure aperture corrections are being measured on. The
            bounding box is retrieved from it, and it is passed to the
            sourceSelector. The output aperture correction map is *not*
            added to the exposure; this is left to the caller.
        catalog : `lsst.afw.table.SourceCatalog`
            SourceCatalog containing measurements to be used to
            compute aperture corrections.
 
        Returns
        -------
        Struct : `lsst.pipe.base.Struct`
            Contains the following:
 
            ``apCorrMap``
                aperture correction map (`lsst.afw.image.ApCorrMap`)
                that contains two entries for each flux field:
                - flux field (e.g. base_PsfFlux_instFlux): 2d model
                - flux sigma field (e.g. base_PsfFlux_instFluxErr): 2d model of error
        """
        bbox = exposure.getBBox()
        import lsstDebug
        display = lsstDebug.Info(__name__).display
        doPause = lsstDebug.Info(__name__).doPause
 
        self.log.info("Measuring aperture corrections for %d flux fields" % (len(self.toCorrect),))
        # First, create a subset of the catalog that contains only selected stars
        # with non-flagged reference fluxes.
        subset1 = [record for record in self.sourceSelector.run(catalog, exposure=exposure).sourceCat
                   if (not record.get(self.refFluxKeys.flag)
                       and numpy.isfinite(record.get(self.refFluxKeys.flux)))]
 
        apCorrMap = ApCorrMap()
 
        # Outer loop over the fields we want to correct
        for name, keys in self.toCorrect.items():
            fluxName = name + "_instFlux"
            fluxErrName = name + "_instFluxErr"
 
            # Create a more restricted subset with only the objects where the to-be-correct flux
            # is not flagged.
            fluxes = numpy.fromiter((record.get(keys.flux) for record in subset1), float)
            with numpy.errstate(invalid="ignore"):  # suppress NAN warnings
                isGood = numpy.logical_and.reduce([
                    numpy.fromiter((not record.get(keys.flag) for record in subset1), bool),
                    numpy.isfinite(fluxes),
                    fluxes > 0.0,
                ])
            subset2 = [record for record, good in zip(subset1, isGood) if good]
 
            # Check that we have enough data points that we have at least the minimum of degrees of
            # freedom specified in the config.
            if len(subset2) - 1 < self.config.minDegreesOfFreedom:
                if name in self.config.allowFailure:
                    self.log.warn("Unable to measure aperture correction for '%s': "
                                  "only %d sources, but require at least %d." %
                                  (name, len(subset2), self.config.minDegreesOfFreedom+1))
                    continue
                raise RuntimeError("Unable to measure aperture correction for required algorithm '%s': "
                                   "only %d sources, but require at least %d." %
                                   (name, len(subset2), self.config.minDegreesOfFreedom+1))
 
            # If we don't have enough data points to constrain the fit, reduce the order until we do
            ctrl = self.config.fitConfig.makeControl()
            while len(subset2) - ctrl.computeSize() < self.config.minDegreesOfFreedom:
                if ctrl.orderX > 0:
                    ctrl.orderX -= 1
                if ctrl.orderY > 0:
                    ctrl.orderY -= 1
 
            # Fill numpy arrays with positions and the ratio of the reference flux to the to-correct flux
            x = numpy.zeros(len(subset2), dtype=float)
            y = numpy.zeros(len(subset2), dtype=float)
            apCorrData = numpy.zeros(len(subset2), dtype=float)
            indices = numpy.arange(len(subset2), dtype=int)
            for n, record in enumerate(subset2):
                x[n] = record.getX()
                y[n] = record.getY()
                apCorrData[n] = record.get(self.refFluxKeys.flux)/record.get(keys.flux)
 
            for _i in range(self.config.numIter):
 
                # Do the fit, save it in the output map
                apCorrField = ChebyshevBoundedField.fit(bbox, x, y, apCorrData, ctrl)
 
                if display:
                    plotApCorr(bbox, x, y, apCorrData, apCorrField, "%s, iteration %d" % (name, _i), doPause)
 
                # Compute errors empirically, using the RMS difference between the true reference flux and the
                # corrected to-be-corrected flux.
                apCorrDiffs = apCorrField.evaluate(x, y)
                apCorrDiffs -= apCorrData
                apCorrErr = numpy.mean(apCorrDiffs**2)**0.5
 
                # Clip bad data points
                apCorrDiffLim = self.config.numSigmaClip * apCorrErr
                with numpy.errstate(invalid="ignore"):  # suppress NAN warning
                    keep = numpy.fabs(apCorrDiffs) <= apCorrDiffLim
                x = x[keep]
                y = y[keep]
                apCorrData = apCorrData[keep]
                indices = indices[keep]
 
            # Final fit after clipping
            apCorrField = ChebyshevBoundedField.fit(bbox, x, y, apCorrData, ctrl)
 
            self.log.info("Aperture correction for %s: RMS %f from %d" %
                          (name, numpy.mean((apCorrField.evaluate(x, y) - apCorrData)**2)**0.5, len(indices)))
 
            if display:
                plotApCorr(bbox, x, y, apCorrData, apCorrField, "%s, final" % (name,), doPause)
 
            # Save the result in the output map
            # The error is constant spatially (we could imagine being
            # more clever, but we're not yet sure if it's worth the effort).
            # We save the errors as a 0th-order ChebyshevBoundedField
            apCorrMap[fluxName] = apCorrField
            apCorrErrCoefficients = numpy.array([[apCorrErr]], dtype=float)
            apCorrMap[fluxErrName] = ChebyshevBoundedField(bbox, apCorrErrCoefficients)
 
            # Record which sources were used
            for i in indices:
                subset2[i].set(keys.used, True)
 
        return Struct(
            apCorrMap=apCorrMap,
        )
 
 

timer()

def lsst.pipe.base.task.Task.timer (   self,   name,   logLevel = Log.DEBUG  )

inherited

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 `lsst.log` level constant.

Examples
--------
Creating a timer context:

.. code-block:: python

    with self.timer("someCodeToTime"):
        pass  # code to time

See also
--------
timer.logInfo

Definition at line 327 of file task.py.

    def timer(self, name, logLevel=Log.DEBUG):
        """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 `lsst.log` level constant.
 
        Examples
        --------
        Creating a timer context:
 
        .. code-block:: python
 
            with self.timer("someCodeToTime"):
                pass  # code to time
 
        See also
        --------
        timer.logInfo
        """
        logInfo(obj=self, prefix=name + "Start", logLevel=logLevel)
        try:
            yield
        finally:
            logInfo(obj=self, prefix=name + "End", logLevel=logLevel)
 

Member Data Documentation

config

lsst.pipe.base.task.Task.config

inherited

Definition at line 162 of file task.py.

ConfigClass

lsst.meas.algorithms.measureApCorr.MeasureApCorrTask.ConfigClass = MeasureApCorrConfig

static

Definition at line 113 of file measureApCorr.py.

log

lsst.pipe.base.task.Task.log

inherited

Definition at line 161 of file task.py.

metadata

lsst.pipe.base.task.Task.metadata

inherited

Definition at line 134 of file task.py.

refFluxKeys

lsst.meas.algorithms.measureApCorr.MeasureApCorrTask.refFluxKeys

Definition at line 126 of file measureApCorr.py.

toCorrect

lsst.meas.algorithms.measureApCorr.MeasureApCorrTask.toCorrect

Definition at line 127 of file measureApCorr.py.

---

The documentation for this class was generated from the following file:

• /j/snowflake/release/lsstsw/stack/0.4.3/Linux64/meas_algorithms/21.0.0-19-g4cded4ca+71a93a33c0/python/lsst/meas/algorithms/measureApCorr.py