forcedPhotImage.py

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# This file is part of meas_base.
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"""Base command-line driver task for forced measurement.
 
Must be inherited to specialize for a specific dataset to be used (see
`ForcedPhotCcdTask`, `ForcedPhotCoaddTask`).
"""
 
import lsst.afw.table
import lsst.pex.config
import lsst.daf.base
import lsst.pipe.base
import lsst.pex.config
 
from lsst.pipe.base import PipelineTaskConnections, PipelineTaskConfig
import lsst.pipe.base.connectionTypes as cT
 
from .references import MultiBandReferencesTask
from .forcedMeasurement import ForcedMeasurementTask
from .applyApCorr import ApplyApCorrTask
from .catalogCalculation import CatalogCalculationTask
 
__all__ = ("ForcedPhotImageConfig", "ForcedPhotImageTask", "ForcedPhotImageConnections")
 
 
class ForcedPhotImageConnections(PipelineTaskConnections,
                                 dimensions=("band", "skymap", "tract", "patch"),
                                 defaultTemplates={"inputCoaddName": "deep",
                                                   "outputCoaddName": "deep"}):
    inputSchema = cT.InitInput(
        doc="Schema for the input measurement catalogs.",
        name="{inputCoaddName}Coadd_ref_schema",
        storageClass="SourceCatalog",
    )
    outputSchema = cT.InitOutput(
        doc="Schema for the output forced measurement catalogs.",
        name="{outputCoaddName}Coadd_forced_src_schema",
        storageClass="SourceCatalog",
    )
    exposure = cT.Input(
        doc="Input exposure to perform photometry on.",
        name="{inputCoaddName}Coadd",
        storageClass="ExposureF",
        dimensions=["band", "skymap", "tract", "patch"],
    )
    refCat = cT.Input(
        doc="Catalog of shapes and positions at which to force photometry.",
        name="{inputCoaddName}Coadd_ref",
        storageClass="SourceCatalog",
        dimensions=["skymap", "tract", "patch"],
    )
    refWcs = cT.Input(
        doc="Reference world coordinate system.",
        name="{inputCoaddName}Coadd.wcs",
        storageClass="Wcs",
        dimensions=["band", "skymap", "tract", "patch"],
    )
    measCat = cT.Output(
        doc="Output forced photometry catalog.",
        name="{outputCoaddName}Coadd_forced_src",
        storageClass="SourceCatalog",
        dimensions=["band", "skymap", "tract", "patch"],
    )
 
 
class ForcedPhotImageConfig(PipelineTaskConfig, pipelineConnections=ForcedPhotImageConnections):
    """Config class for forced measurement driver task."""
    # ForcedPhotImage options
    references = lsst.pex.config.ConfigurableField(
        target=MultiBandReferencesTask,
        doc="subtask to retrieve reference source catalog"
    )
    measurement = lsst.pex.config.ConfigurableField(
        target=ForcedMeasurementTask,
        doc="subtask to do forced measurement"
    )
    coaddName = lsst.pex.config.Field(
        doc="coadd name: typically one of deep or goodSeeing",
        dtype=str,
        default="deep",
    )
    doApCorr = lsst.pex.config.Field(
        dtype=bool,
        default=True,
        doc="Run subtask to apply aperture corrections"
    )
    applyApCorr = lsst.pex.config.ConfigurableField(
        target=ApplyApCorrTask,
        doc="Subtask to apply aperture corrections"
    )
    catalogCalculation = lsst.pex.config.ConfigurableField(
        target=CatalogCalculationTask,
        doc="Subtask to run catalogCalculation plugins on catalog"
    )
 
    def setDefaults(self):
        # Docstring inherited.
        # Make catalogCalculation a no-op by default as no modelFlux is setup by default in
        # ForcedMeasurementTask
        super().setDefaults()
 
        self.catalogCalculation.plugins.names = []
 
 
class ForcedPhotImageTask(lsst.pipe.base.PipelineTask, lsst.pipe.base.CmdLineTask):
    """A base class for command-line forced measurement drivers.
 
    Parameters
    ----------
    butler : `lsst.daf.persistence.butler.Butler`, optional
        A Butler which will be passed to the references subtask to allow it to
        load its schema from disk. Optional, but must be specified if
        ``refSchema`` is not; if both are specified, ``refSchema`` takes
        precedence.
    refSchema : `lsst.afw.table.Schema`, optional
        The schema of the reference catalog, passed to the constructor of the
        references subtask. Optional, but must be specified if ``butler`` is
        not; if both are specified, ``refSchema`` takes precedence.
    **kwds
        Keyword arguments are passed to the supertask constructor.
 
    Notes
    -----
    This is a an abstract class, which is the common ancestor for
    `ForcedPhotCcdTask` and `ForcedPhotCoaddTask`. It provides the
    `runDataRef` method that does most of the work, while delegating a few
    customization tasks to other methods that are overridden by subclasses.
 
    This task is not directly usable as a command line task. Subclasses must:
 
    - Set the `_DefaultName` class attribute;
    - Implement `makeIdFactory`;
    - Implement `fetchReferences`;
    - Optionally, implement `attachFootprints`.
    """
 
    ConfigClass = ForcedPhotImageConfig
    _DefaultName = "processImageForcedTask"
 
    def __init__(self, butler=None, refSchema=None, initInputs=None, **kwds):
        super().__init__(**kwds)
 
        if initInputs is not None:
            refSchema = initInputs['inputSchema'].schema
 
        self.makeSubtask("references", butler=butler, schema=refSchema)
        if refSchema is None:
            refSchema = self.references.schema
        self.makeSubtask("measurement", refSchema=refSchema)
        # It is necessary to get the schema internal to the forced measurement task until such a time
        # that the schema is not owned by the measurement task, but is passed in by an external caller
        if self.config.doApCorr:
            self.makeSubtask("applyApCorr", schema=self.measurement.schema)
        self.makeSubtask('catalogCalculation', schema=self.measurement.schema)
        self.outputSchema = lsst.afw.table.SourceCatalog(self.measurement.schema)
 
    def runQuantum(self, butlerQC, inputRefs, outputRefs):
        inputs = butlerQC.get(inputRefs)
        inputs['measCat'] = self.generateMeasCat(inputRefs.exposure.dataId,
                                                 inputs['exposure'],
                                                 inputs['refCat'], inputs['refWcs'],
                                                 "tract_patch")
        outputs = self.run(**inputs)
        butlerQC.put(outputs, outputRefs)
 
    def generateMeasCat(self, exposureDataId, exposure, refCat, refWcs, idPackerName):
        """Generate a measurement catalog for Gen3.
 
        Parameters
        ----------
        exposureDataId : `DataId`
            Butler dataId for this exposure.
        exposure : `lsst.afw.image.exposure.Exposure`
            Exposure to generate the catalog for.
        refCat : `lsst.afw.table.SourceCatalog`
            Catalog of shapes and positions at which to force photometry.
        refWcs : `lsst.afw.image.SkyWcs`
            Reference world coordinate system.
        idPackerName : `str`
            Name of DimensionPacker to use to generate the packed version
            of the data ID to mangle into source IDs.
 
        Returns
        -------
        measCat : `lsst.afw.table.SourceCatalog`
            Catalog of forced sources to measure.
        """
        expId, expBits = exposureDataId.pack(idPackerName, returnMaxBits=True)
        idFactory = lsst.afw.table.IdFactory.makeSource(expId, 64 - expBits)
 
        measCat = self.measurement.generateMeasCat(exposure, refCat, refWcs,
                                                   idFactory=idFactory)
        return measCat
 
    def runDataRef(self, dataRef, psfCache=None):
        """Perform forced measurement on a single exposure.
 
        Parameters
        ----------
        dataRef : `lsst.daf.persistence.ButlerDataRef`
            Passed to the ``references`` subtask to obtain the reference WCS,
            the ``getExposure`` method (implemented by derived classes) to
            read the measurment image, and the ``fetchReferences`` method to
            get the exposure and load the reference catalog (see
            :lsst-task`lsst.meas.base.references.CoaddSrcReferencesTask`).
            Refer to derived class documentation for details of the datasets
            and data ID keys which are used.
        psfCache : `int`, optional
            Size of PSF cache, or `None`. The size of the PSF cache can have
            a significant effect upon the runtime for complicated PSF models.
 
        Notes
        -----
        Sources are generated with ``generateMeasCat`` in the ``measurement``
        subtask. These are passed to ``measurement``'s ``run`` method, which
        fills the source catalog with the forced measurement results. The
        sources are then passed to the ``writeOutputs`` method (implemented by
        derived classes) which writes the outputs.
        """
        refWcs = self.references.getWcs(dataRef)
        exposure = self.getExposure(dataRef)
        if psfCache is not None:
            exposure.getPsf().setCacheSize(psfCache)
        refCat = self.fetchReferences(dataRef, exposure)
 
        measCat = self.measurement.generateMeasCat(exposure, refCat, refWcs,
                                                   idFactory=self.makeIdFactory(dataRef))
        self.log.info("Performing forced measurement on %s" % (dataRef.dataId,))
        self.attachFootprints(measCat, refCat, exposure, refWcs, dataRef)
 
        exposureId = self.getExposureId(dataRef)
 
        forcedPhotResult = self.run(measCat, exposure, refCat, refWcs, exposureId=exposureId)
 
        self.writeOutput(dataRef, forcedPhotResult.measCat)
 
    def run(self, measCat, exposure, refCat, refWcs, exposureId=None):
        """Perform forced measurement on a single exposure.
 
        Parameters
        ----------
        measCat : `lsst.afw.table.SourceCatalog`
            The measurement catalog, based on the sources listed in the
            reference catalog.
        exposure : `lsst.afw.image.Exposure`
            The measurement image upon which to perform forced detection.
        refCat : `lsst.afw.table.SourceCatalog`
            The reference catalog of sources to measure.
        refWcs : `lsst.afw.image.SkyWcs`
            The WCS for the references.
        exposureId : `int`
            Optional unique exposureId used for random seed in measurement
            task.
 
        Returns
        -------
        result : `lsst.pipe.base.Struct`
            Structure with fields:
 
            ``measCat``
                Catalog of forced measurement results
                (`lsst.afw.table.SourceCatalog`).
        """
        self.measurement.run(measCat, exposure, refCat, refWcs, exposureId=exposureId)
        if self.config.doApCorr:
            self.applyApCorr.run(
                catalog=measCat,
                apCorrMap=exposure.getInfo().getApCorrMap()
            )
        self.catalogCalculation.run(measCat)
 
        return lsst.pipe.base.Struct(measCat=measCat)
 
    def makeIdFactory(self, dataRef):
        """Hook for derived classes to make an ID factory for forced sources.
 
        Notes
        -----
        That this applies to forced *source* IDs, not object IDs, which are
        usually handled by the ``measurement.copyColumns`` config option.
 
        """
        raise NotImplementedError()
 
    def getExposureId(self, dataRef):
        raise NotImplementedError()
 
    def fetchReferences(self, dataRef, exposure):
        """Hook for derived classes to define how to get reference objects.
 
        Notes
        -----
        Derived classes should call one of the ``fetch*`` methods on the
        ``references`` subtask, but which one they call depends on whether the
        region to get references for is a easy to describe in patches (as it
        would be when doing forced measurements on a coadd), or is just an
        arbitrary box (as it would be for CCD forced measurements).
        """
        raise NotImplementedError()
 
    def attachFootprints(self, sources, refCat, exposure, refWcs, dataRef):
        r"""Attach footprints to blank sources prior to measurements.
 
        Notes
        -----
        `~lsst.afw.detection.Footprint`\ s for forced photometry must be in the
        pixel coordinate system of the image being measured, while the actual
        detections may start out in a different coordinate system.
 
        Subclasses of this class must implement this method to define how
        those `~lsst.afw.detection.Footprint`\ s should be generated.
 
        This default implementation transforms the
        `~lsst.afw.detection.Footprint`\ s from the reference catalog from the
        reference WCS to the exposure's WcS, which downgrades
        `lsst.afw.detection.heavyFootprint.HeavyFootprint`\ s into regular
        `~lsst.afw.detection.Footprint`\ s, destroying deblend information.
        """
        return self.measurement.attachTransformedFootprints(sources, refCat, exposure, refWcs)
 
    def getExposure(self, dataRef):
        """Read input exposure on which measurement will be performed.
 
        Parameters
        ----------
        dataRef : `lsst.daf.persistence.ButlerDataRef`
            Butler data reference.
        """
        return dataRef.get(self.dataPrefix + "calexp", immediate=True)
 
    def writeOutput(self, dataRef, sources):
        """Write forced source table
 
        Parameters
        ----------
        dataRef : `lsst.daf.persistence.ButlerDataRef`
            Butler data reference. The forced_src dataset (with
            self.dataPrefix prepended) is all that will be modified.
        sources : `lsst.afw.table.SourceCatalog`
            Catalog of sources to save.
        """
        dataRef.put(sources, self.dataPrefix + "forced_src", flags=lsst.afw.table.SOURCE_IO_NO_FOOTPRINTS)
 
    def getSchemaCatalogs(self):
        """The schema catalogs that will be used by this task.
 
        Returns
        -------
        schemaCatalogs : `dict`
            Dictionary mapping dataset type to schema catalog.
 
        Notes
        -----
        There is only one schema for each type of forced measurement. The
        dataset type for this measurement is defined in the mapper.
        """
        catalog = lsst.afw.table.SourceCatalog(self.measurement.schema)
        catalog.getTable().setMetadata(self.measurement.algMetadata)
        datasetType = self.dataPrefix + "forced_src"
        return {datasetType: catalog}
 
    def _getConfigName(self):
        # Documented in superclass
        return self.dataPrefix + "forced_config"
 
    def _getMetadataName(self):
        # Documented in superclass
        return self.dataPrefix + "forced_metadata"