lsst.meas.algorithms.debugger.MeasurementDebuggerTask Class Reference

Inheritance diagram for lsst.meas.algorithms.debugger.MeasurementDebuggerTask:

Public Member Functions
def	__init__ (self, schema=None, kwargs)
def	runDataRef (self, dataRef, image, catalog)
def	readImage (self, image)
def	readSources (self, catalog)
def	mapSchemas (self, sources)
def	subsetSources (self, sources)
def	writeSources (self, sources)
def	writeConfig (self, args, kwargs)
def	writeMetadata (self, args, kwargs)
def	writeSchemas (self, args, kwargs)
def	applyOverrides (cls, config)
def	parseAndRun (cls, args=None, config=None, log=None, doReturnResults=False)
def	writeConfig (self, butler, clobber=False, doBackup=True)
def	writeSchemas (self, butler, clobber=False, doBackup=True)
def	writeMetadata (self, dataRef)
def	writePackageVersions (self, butler, clobber=False, doBackup=True, dataset="packages")
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
	schema
	metadata
	log
	config

Static Public Attributes
	ConfigClass = MeasurementDebuggerConfig
	RunnerClass = MeasurementDebuggerRunner
bool	canMultiprocess = True

Detailed Description

Definition at line 96 of file debugger.py.

Constructor & Destructor Documentation

__init__()

def lsst.meas.algorithms.debugger.MeasurementDebuggerTask.__init__	(		self,
			schema = None,
			kwargs
	)

Definition at line 101 of file debugger.py.

    def __init__(self, schema=None, **kwargs):
        super(MeasurementDebuggerTask, self).__init__(**kwargs)
        if schema is None:
            schema = afwTable.SourceTable.makeMinimalSchema()
        self.schema = schema
        self.makeSubtask("measurement", schema=schema)

Member Function Documentation

__reduce__()

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

inherited

Pickler.

Definition at line 373 of file task.py.

    def __reduce__(self):
        """Pickler.
        """
        return self.__class__, (self.config, self._name, self._parentTask, None)

applyOverrides()

def lsst.pipe.base.cmdLineTask.CmdLineTask.applyOverrides (   cls,   config  )

inherited

A hook to allow a task to change the values of its config *after* the camera-specific
overrides are loaded but before any command-line overrides are applied.

Parameters
----------
config : instance of task's ``ConfigClass``
    Task configuration.

Notes
-----
This is necessary in some cases because the camera-specific overrides may retarget subtasks,
wiping out changes made in ConfigClass.setDefaults. See LSST Trac ticket #2282 for more discussion.

.. warning::

   This is called by CmdLineTask.parseAndRun; other ways of constructing a config will not apply
   these overrides.

Definition at line 527 of file cmdLineTask.py.

    def applyOverrides(cls, config):
        """A hook to allow a task to change the values of its config *after* the camera-specific
        overrides are loaded but before any command-line overrides are applied.

        Parameters
        ----------
        config : instance of task's ``ConfigClass``
            Task configuration.

        Notes
        -----
        This is necessary in some cases because the camera-specific overrides may retarget subtasks,
        wiping out changes made in ConfigClass.setDefaults. See LSST Trac ticket #2282 for more discussion.

        .. warning::

           This is called by CmdLineTask.parseAndRun; other ways of constructing a config will not apply
           these overrides.
        """
        pass

emptyMetadata()

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

inherited

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

Definition at line 153 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 188 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 210 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 235 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 250 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 implemenation 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 159 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 implemenation 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 264 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::

    class OtherTaskConfig(lsst.pex.config.Config)
aSubtask = ATaskClass.makeField("a brief description of what this task does")

Definition at line 329 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::

            class OtherTaskConfig(lsst.pex.config.Config)
                aSubtask = ATaskClass.makeField("a brief description of what this task does")
        """
        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 pex_config ConfigurableField
or RegistryField.

Definition at line 275 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 pex_config ConfigurableField
        or RegistryField.
        """
        taskField = getattr(self.config, name, None)
        if taskField is None:
            raise KeyError("%s's config does not have field %r" % (self.getFullName(), name))
        subtask = taskField.apply(name=name, parentTask=self, **keyArgs)
        setattr(self, name, subtask)

mapSchemas()

def lsst.meas.algorithms.debugger.MeasurementDebuggerTask.mapSchemas	(		self,
			sources
	)

Definition at line 131 of file debugger.py.

    def mapSchemas(self, sources):
        catalog = afwTable.SourceCatalog(self.schema)
        for ss in sources:
            new = catalog.addNew()
            new.setFootprint(ss.getFootprint())
            for name in self.schema.getNames():
                if name in ss.schema:
                    new.set(name, ss.get(name))
        return catalog

parseAndRun()

def lsst.pipe.base.cmdLineTask.CmdLineTask.parseAndRun (   cls,   args = None,   config = None,   log = None,   doReturnResults = False  )

inherited

Parse an argument list and run the command.

Parameters
----------
args : `list`, optional
    List of command-line arguments; if `None` use `sys.argv`.
config : `lsst.pex.config.Config`-type, optional
    Config for task. If `None` use `Task.ConfigClass`.
log : `lsst.log.Log`-type, optional
    Log. If `None` use the default log.
doReturnResults : `bool`, optional
    If `True`, return the results of this task. Default is `False`. This is only intended for
    unit tests and similar use. It can easily exhaust memory (if the task returns enough data and you
    call it enough times) and it will fail when using multiprocessing if the returned data cannot be
    pickled.

Returns
-------
struct : `lsst.pipe.base.Struct`
    Fields are:

    - ``argumentParser``: the argument parser.
    - ``parsedCmd``: the parsed command returned by the argument parser's
      `lsst.pipe.base.ArgumentParser.parse_args` method.
    - ``taskRunner``: the task runner used to run the task (an instance of `Task.RunnerClass`).
    - ``resultList``: results returned by the task runner's ``run`` method, one entry per invocation.
This will typically be a list of `None` unless ``doReturnResults`` is `True`;
see `Task.RunnerClass` (`TaskRunner` by default) for more information.

Notes
-----
Calling this method with no arguments specified is the standard way to run a command-line task
from the command-line. For an example see ``pipe_tasks`` ``bin/makeSkyMap.py`` or almost any other
file in that directory.

If one or more of the dataIds fails then this routine will exit (with a status giving the
number of failed dataIds) rather than returning this struct;  this behaviour can be
overridden by specifying the ``--noExit`` command-line option.

Definition at line 549 of file cmdLineTask.py.

    def parseAndRun(cls, args=None, config=None, log=None, doReturnResults=False):
        """Parse an argument list and run the command.

        Parameters
        ----------
        args : `list`, optional
            List of command-line arguments; if `None` use `sys.argv`.
        config : `lsst.pex.config.Config`-type, optional
            Config for task. If `None` use `Task.ConfigClass`.
        log : `lsst.log.Log`-type, optional
            Log. If `None` use the default log.
        doReturnResults : `bool`, optional
            If `True`, return the results of this task. Default is `False`. This is only intended for
            unit tests and similar use. It can easily exhaust memory (if the task returns enough data and you
            call it enough times) and it will fail when using multiprocessing if the returned data cannot be
            pickled.

        Returns
        -------
        struct : `lsst.pipe.base.Struct`
            Fields are:

            - ``argumentParser``: the argument parser.
            - ``parsedCmd``: the parsed command returned by the argument parser's
              `lsst.pipe.base.ArgumentParser.parse_args` method.
            - ``taskRunner``: the task runner used to run the task (an instance of `Task.RunnerClass`).
            - ``resultList``: results returned by the task runner's ``run`` method, one entry per invocation.
                This will typically be a list of `None` unless ``doReturnResults`` is `True`;
                see `Task.RunnerClass` (`TaskRunner` by default) for more information.

        Notes
        -----
        Calling this method with no arguments specified is the standard way to run a command-line task
        from the command-line. For an example see ``pipe_tasks`` ``bin/makeSkyMap.py`` or almost any other
        file in that directory.

        If one or more of the dataIds fails then this routine will exit (with a status giving the
        number of failed dataIds) rather than returning this struct;  this behaviour can be
        overridden by specifying the ``--noExit`` command-line option.
        """
        if args is None:
            commandAsStr = " ".join(sys.argv)
            args = sys.argv[1:]
        else:
            commandAsStr = "{}{}".format(lsst.utils.get_caller_name(skip=1), tuple(args))

        argumentParser = cls._makeArgumentParser()
        if config is None:
            config = cls.ConfigClass()
        parsedCmd = argumentParser.parse_args(config=config, args=args, log=log, override=cls.applyOverrides)
        # print this message after parsing the command so the log is fully configured
        parsedCmd.log.info("Running: %s", commandAsStr)

        taskRunner = cls.RunnerClass(TaskClass=cls, parsedCmd=parsedCmd, doReturnResults=doReturnResults)
        resultList = taskRunner.run(parsedCmd)

        try:
            nFailed = sum(((res.exitStatus != 0) for res in resultList))
        except (TypeError, AttributeError) as e:
            # NOTE: TypeError if resultList is None, AttributeError if it doesn't have exitStatus.
            parsedCmd.log.warn("Unable to retrieve exit status (%s); assuming success", e)
            nFailed = 0

        if nFailed > 0:
            if parsedCmd.noExit:
                parsedCmd.log.error("%d dataRefs failed; not exiting as --noExit was set", nFailed)
            else:
                sys.exit(nFailed)

        return Struct(
            argumentParser=argumentParser,
            parsedCmd=parsedCmd,
            taskRunner=taskRunner,
            resultList=resultList,
        )

readImage()

def lsst.meas.algorithms.debugger.MeasurementDebuggerTask.readImage	(		self,
			image
	)

Definition at line 121 of file debugger.py.

    def readImage(self, image):
        exp = afwImage.ExposureF(image)
        self.log.info("Read %dx%d image", exp.getWidth(), exp.getHeight())
        return exp

readSources()

def lsst.meas.algorithms.debugger.MeasurementDebuggerTask.readSources	(		self,
			catalog
	)

Definition at line 126 of file debugger.py.

    def readSources(self, catalog):
        sources = afwTable.SourceCatalog.readFits(catalog)
        self.log.info("Read %d sources", len(sources))
        return sources

runDataRef()

def lsst.meas.algorithms.debugger.MeasurementDebuggerTask.runDataRef	(		self,
			dataRef,
			image,
			catalog
	)

Definition at line 112 of file debugger.py.

    def runDataRef(self, dataRef, image, catalog):
        exp = self.readImage(image)
        sources = self.readSources(catalog)
        sources = self.subsetSources(sources)
        sources = self.mapSchemas(sources)
        self.measurement.measure(exp, sources)
        self.writeSources(sources)
        return Struct(exp=exp, sources=sources)

subsetSources()

def lsst.meas.algorithms.debugger.MeasurementDebuggerTask.subsetSources	(		self,
			sources
	)

Return a subset of the input catalog

The full catalog is used if the 'sourceId' list is empty.

Parent sources (in the deblending sense) are also added to the
subset so that they can be removed (via replaceWithNoise).

Definition at line 141 of file debugger.py.

    def subsetSources(self, sources):
        """Return a subset of the input catalog

        The full catalog is used if the 'sourceId' list is empty.

        Parent sources (in the deblending sense) are also added to the
        subset so that they can be removed (via replaceWithNoise).
        """
        if not self.config.sourceId:
            return sources

        identifiers = set(self.config.sourceId)
        subset = afwTable.SourceCatalog(sources.table)
        while len(identifiers) > 0:
            ident = identifiers.pop()
            ss = sources.find(ident)
            if ss is None:
                raise RuntimeError("Unable to find id=%d in catalog" % ident)
            subset.append(ss)
            parent = ss.getParent()
            if parent:
                identifiers.add(parent)
        self.log.info("Subset to %d sources", len(subset))
        return subset

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::

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

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

Definition at line 301 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::

            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)

writeConfig() [1/2]

def lsst.meas.algorithms.debugger.MeasurementDebuggerTask.writeConfig	(		self,
			args,
			kwargs
	)

Definition at line 170 of file debugger.py.

    def writeConfig(self, *args, **kwargs):
        pass

writeConfig() [2/2]

def lsst.pipe.base.cmdLineTask.CmdLineTask.writeConfig (   self,   butler,   clobber = False,   doBackup = True  )

inherited

Write the configuration used for processing the data, or check that an existing
one is equal to the new one if present.

Parameters
----------
butler : `lsst.daf.persistence.Butler`
    Data butler used to write the config. The config is written to dataset type
    `CmdLineTask._getConfigName`.
clobber : `bool`, optional
    A boolean flag that controls what happens if a config already has been saved:
    - `True`: overwrite or rename the existing config, depending on ``doBackup``.
    - `False`: raise `TaskError` if this config does not match the existing config.
doBackup : bool, optional
    Set to `True` to backup the config files if clobbering.

Definition at line 649 of file cmdLineTask.py.

    def writeConfig(self, butler, clobber=False, doBackup=True):
        """Write the configuration used for processing the data, or check that an existing
        one is equal to the new one if present.

        Parameters
        ----------
        butler : `lsst.daf.persistence.Butler`
            Data butler used to write the config. The config is written to dataset type
            `CmdLineTask._getConfigName`.
        clobber : `bool`, optional
            A boolean flag that controls what happens if a config already has been saved:
            - `True`: overwrite or rename the existing config, depending on ``doBackup``.
            - `False`: raise `TaskError` if this config does not match the existing config.
        doBackup : bool, optional
            Set to `True` to backup the config files if clobbering.
        """
        configName = self._getConfigName()
        if configName is None:
            return
        if clobber:
            butler.put(self.config, configName, doBackup=doBackup)
        elif butler.datasetExists(configName, write=True):
            # this may be subject to a race condition; see #2789
            try:
                oldConfig = butler.get(configName, immediate=True)
            except Exception as exc:
                raise type(exc)("Unable to read stored config file %s (%s); consider using --clobber-config" %
                                (configName, exc))

            def logConfigMismatch(msg):
                self.log.fatal("Comparing configuration: %s", msg)

            if not self.config.compare(oldConfig, shortcut=False, output=logConfigMismatch):
                raise TaskError(
                    ("Config does not match existing task config %r on disk; tasks configurations " +
                     "must be consistent within the same output repo (override with --clobber-config)") %
                    (configName,))
        else:
            butler.put(self.config, configName)

writeMetadata() [1/2]

def lsst.meas.algorithms.debugger.MeasurementDebuggerTask.writeMetadata	(		self,
			args,
			kwargs
	)

Definition at line 173 of file debugger.py.

    def writeMetadata(self, *args, **kwargs):
        pass

writeMetadata() [2/2]

def lsst.pipe.base.cmdLineTask.CmdLineTask.writeMetadata (   self,   dataRef  )

inherited

Write the metadata produced from processing the data.

Parameters
----------
dataRef
    Butler data reference used to write the metadata.
    The metadata is written to dataset type `CmdLineTask._getMetadataName`.

Definition at line 724 of file cmdLineTask.py.

    def writeMetadata(self, dataRef):
        """Write the metadata produced from processing the data.

        Parameters
        ----------
        dataRef
            Butler data reference used to write the metadata.
            The metadata is written to dataset type `CmdLineTask._getMetadataName`.
        """
        try:
            metadataName = self._getMetadataName()
            if metadataName is not None:
                dataRef.put(self.getFullMetadata(), metadataName)
        except Exception as e:
            self.log.warn("Could not persist metadata for dataId=%s: %s", dataRef.dataId, e)

writePackageVersions()

def lsst.pipe.base.cmdLineTask.CmdLineTask.writePackageVersions (   self,   butler,   clobber = False,   doBackup = True,   dataset = "packages"  )

inherited

Compare and write package versions.

Parameters
----------
butler : `lsst.daf.persistence.Butler`
    Data butler used to read/write the package versions.
clobber : `bool`, optional
    A boolean flag that controls what happens if versions already have been saved:
    - `True`: overwrite or rename the existing version info, depending on ``doBackup``.
    - `False`: raise `TaskError` if this version info does not match the existing.
doBackup : `bool`, optional
    If `True` and clobbering, old package version files are backed up.
dataset : `str`, optional
    Name of dataset to read/write.

Raises
------
TaskError
    Raised if there is a version mismatch with current and persisted lists of package versions.

Notes
-----
Note that this operation is subject to a race condition.

Definition at line 740 of file cmdLineTask.py.

    def writePackageVersions(self, butler, clobber=False, doBackup=True, dataset="packages"):
        """Compare and write package versions.

        Parameters
        ----------
        butler : `lsst.daf.persistence.Butler`
            Data butler used to read/write the package versions.
        clobber : `bool`, optional
            A boolean flag that controls what happens if versions already have been saved:
            - `True`: overwrite or rename the existing version info, depending on ``doBackup``.
            - `False`: raise `TaskError` if this version info does not match the existing.
        doBackup : `bool`, optional
            If `True` and clobbering, old package version files are backed up.
        dataset : `str`, optional
            Name of dataset to read/write.

        Raises
        ------
        TaskError
            Raised if there is a version mismatch with current and persisted lists of package versions.

        Notes
        -----
        Note that this operation is subject to a race condition.
        """
        packages = Packages.fromSystem()

        if clobber:
            return butler.put(packages, dataset, doBackup=doBackup)
        if not butler.datasetExists(dataset, write=True):
            return butler.put(packages, dataset)

        try:
            old = butler.get(dataset, immediate=True)
        except Exception as exc:
            raise type(exc)("Unable to read stored version dataset %s (%s); "
                            "consider using --clobber-versions or --no-versions" %
                            (dataset, exc))
        # Note that because we can only detect python modules that have been imported, the stored
        # list of products may be more or less complete than what we have now.  What's important is
        # that the products that are in common have the same version.
        diff = packages.difference(old)
        if diff:
            raise TaskError(
                "Version mismatch (" +
                "; ".join("%s: %s vs %s" % (pkg, diff[pkg][1], diff[pkg][0]) for pkg in diff) +
                "); consider using --clobber-versions or --no-versions")
        # Update the old set of packages in case we have more packages that haven't been persisted.
        extra = packages.extra(old)
        if extra:
            old.update(packages)
            butler.put(old, dataset, doBackup=doBackup)

writeSchemas() [1/2]

def lsst.meas.algorithms.debugger.MeasurementDebuggerTask.writeSchemas	(		self,
			args,
			kwargs
	)

Definition at line 176 of file debugger.py.

    def writeSchemas(self, *args, **kwargs):
        pass

writeSchemas() [2/2]

def lsst.pipe.base.cmdLineTask.CmdLineTask.writeSchemas (   self,   butler,   clobber = False,   doBackup = True  )

inherited

Write the schemas returned by `lsst.pipe.base.Task.getAllSchemaCatalogs`.

Parameters
----------
butler : `lsst.daf.persistence.Butler`
    Data butler used to write the schema. Each schema is written to the dataset type specified as the
    key in the dict returned by `~lsst.pipe.base.Task.getAllSchemaCatalogs`.
clobber : `bool`, optional
    A boolean flag that controls what happens if a schema already has been saved:
    - `True`: overwrite or rename the existing schema, depending on ``doBackup``.
    - `False`: raise `TaskError` if this schema does not match the existing schema.
doBackup : `bool`, optional
    Set to `True` to backup the schema files if clobbering.

Notes
-----
If ``clobber`` is `False` and an existing schema does not match a current schema,
then some schemas may have been saved successfully and others may not, and there is no easy way to
tell which is which.

Definition at line 689 of file cmdLineTask.py.

    def writeSchemas(self, butler, clobber=False, doBackup=True):
        """Write the schemas returned by `lsst.pipe.base.Task.getAllSchemaCatalogs`.

        Parameters
        ----------
        butler : `lsst.daf.persistence.Butler`
            Data butler used to write the schema. Each schema is written to the dataset type specified as the
            key in the dict returned by `~lsst.pipe.base.Task.getAllSchemaCatalogs`.
        clobber : `bool`, optional
            A boolean flag that controls what happens if a schema already has been saved:
            - `True`: overwrite or rename the existing schema, depending on ``doBackup``.
            - `False`: raise `TaskError` if this schema does not match the existing schema.
        doBackup : `bool`, optional
            Set to `True` to backup the schema files if clobbering.

        Notes
        -----
        If ``clobber`` is `False` and an existing schema does not match a current schema,
        then some schemas may have been saved successfully and others may not, and there is no easy way to
        tell which is which.
        """
        for dataset, catalog in self.getAllSchemaCatalogs().items():
            schemaDataset = dataset + "_schema"
            if clobber:
                butler.put(catalog, schemaDataset, doBackup=doBackup)
            elif butler.datasetExists(schemaDataset, write=True):
                oldSchema = butler.get(schemaDataset, immediate=True).getSchema()
                if not oldSchema.compare(catalog.getSchema(), afwTable.Schema.IDENTICAL):
                    raise TaskError(
                        ("New schema does not match schema %r on disk; schemas must be " +
                         " consistent within the same output repo (override with --clobber-config)") %
                        (dataset,))
            else:
                butler.put(catalog, schemaDataset)

writeSources()

def lsst.meas.algorithms.debugger.MeasurementDebuggerTask.writeSources	(		self,
			sources
	)

Definition at line 166 of file debugger.py.

    def writeSources(self, sources):
        sources.writeFits(self.config.outputName)
        self.log.info("Wrote %s", self.config.outputName)

Member Data Documentation

canMultiprocess

bool lsst.pipe.base.cmdLineTask.CmdLineTask.canMultiprocess = True

staticinherited

Definition at line 524 of file cmdLineTask.py.

config

lsst.pipe.base.task.Task.config

inherited

Definition at line 149 of file task.py.

ConfigClass

lsst.meas.algorithms.debugger.MeasurementDebuggerTask.ConfigClass = MeasurementDebuggerConfig

static

Definition at line 98 of file debugger.py.

log

lsst.pipe.base.task.Task.log

inherited

Definition at line 148 of file task.py.

metadata

lsst.pipe.base.task.Task.metadata

inherited

Definition at line 121 of file task.py.

RunnerClass

lsst.meas.algorithms.debugger.MeasurementDebuggerTask.RunnerClass = MeasurementDebuggerRunner

static

Definition at line 99 of file debugger.py.

schema

lsst.meas.algorithms.debugger.MeasurementDebuggerTask.schema

Definition at line 105 of file debugger.py.

---

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

• /j/snowflake/release/lsstsw/stack/Linux64/meas_algorithms/17.0.1-4-ga7077188/python/lsst/meas/algorithms/debugger.py

---

Generated on Thu Apr 4 2019 08:10:37 for LSSTApplications by   1.8.13