CalibrateImageConfig#

class lsst.pipe.tasks.calibrateImage.CalibrateImageConfig(*args, **kw)#

Bases: PipelineTaskConfig

Attributes Summary

`astrometry`	Task to perform astrometric calibration to fit a WCS.
`astrometry_ref_loader`	Configuration of reference object loader for astrometric fit.
`background_stats_flux_column`	Column used to generate post-subtracted background stats.
`background_stats_ignored_pixel_masks`	Pixel mask flags to ignore when calculating post-sky-subtraction background statistics.
`compute_summary_stats`	Task to to compute summary statistics on the calibrated exposure.
`connections`	Field which refers to a dynamically added configuration class which is based on a PipelineTaskConnections class.
`diffractionSpikeMask`	Task to identify and mask the diffraction spikes of bright stars.
`doMaskDiffractionSpikes`	If True, load the photometric reference catalog again but select only bright stars.
`do_adaptive_threshold_detection`	Implement the adaptive detection thresholding approach? (`bool`, default `True`)
`do_calibrate_pixels`	If True, apply the photometric calibration to the image pixels and background model, and attach an identity PhotoCalib to the output image to reflect this.
`do_downsample_footprints`	Downsample footprints prior to deblending to optimize speed? (`bool`, default `False`)
`do_illumination_correction`	If True, apply the illumination correction.
`do_include_astrometric_errors`	If True, include astrometric errors in the output catalog.
`downsample_max_footprints`	Maximum number of non-sky-source footprints to use if do_downsample_footprints is True, (`int`, default `1000`)
`id_generator`	Configuration for how to generate catalog IDs from data IDs.
`install_simple_psf`	Task to install a simple PSF model into the input exposure to use when detecting bright sources for PSF estimation.
`measure_aperture_correction`	Task to compute the aperture correction from the bright stars.
`optional_outputs`	Which optional outputs to save (as their connection name)? (`List`, default `['psf_stars', 'psf_stars_footprints', 'astrometry_matches', 'photometry_matches', 'mask']`)
`photometry`	Task to perform photometric calibration to fit a PhotoCalib.
`photometry_ref_loader`	Configuration of reference object loader for photometric fit.
`psf_adaptive_threshold_detection`	Task to adaptively detect sources for PSF determination.
`psf_detection`	Task to detect sources for PSF determination.
`psf_measure_psf`	Task to measure the psf on bright sources.
`psf_normalized_calibration_flux`	Task to normalize the calibration flux (e.g. compensated tophats) for the bright stars used for psf estimation.
`psf_repair`	Task to repair cosmic rays on the exposure before PSF determination.
`psf_source_measurement`	Task to measure sources to be used for psf estimation.
`psf_subtract_background`	Task to perform initial background subtraction, before first detection pass.
`run_sattle`	If True, the sattle service will populate a cache for later use in ip_diffim.detectAndMeasure alert verification.
`sattle_historical`	If re-running a pipeline that requires sattle, this should be set to True.
`saveLogOutput`	Flag to enable/disable saving of log output for a task, enabled by default.
`snap_combine`	Task to combine two snaps to make one exposure.
`star_apply_aperture_correction`	Task to apply aperture corrections to the selected stars.
`star_background`	Task to perform final background subtraction, just before photoCal.
`star_background_min_footprints`	Minimum number of footprints in the detection mask for star_background measurement.
`star_background_peak_fraction`	The minimum number of footprints in the detection mask for star_background measurement.
`star_catalog_calculation`	Task to compute extendedness values on the star catalog, for the star selector to remove extended sources.
`star_deblend`	Split blended sources into their components.
`star_detection`	Task to detect stars to return in the output catalog.
`star_measurement`	Task to measure stars to return in the output catalog.
`star_normalized_calibration_flux`	Task to apply the normalization for calibration fluxes (e.g. compensated tophats) for the final output star catalog.
`star_selector`	Task to select reliable stars to use for calibration.
`star_set_primary_flags`	Task to add isPrimary to the catalog.
`star_sky_sources`	Task to generate sky sources ('empty' regions where there are no detections).
`useButlerCamera`	If True, use a camera distortion model generated elsewhere in the pipeline combined with the telescope boresight as a starting point for fitting the WCS, instead of using the WCS attached to the exposure, which is generated from the boresight and the camera model from the obs_* package.

Methods Summary

`setDefaults`()	Subclass hook for computing defaults.
`validate`()	Validate the Config, raising an exception if invalid.

Attributes Documentation

astrometry#: Task to perform astrometric calibration to fit a WCS. (ConfigurableInstance, default <class 'lsst.meas.astrom.astrometry.AstrometryConfig'>)

astrometry_ref_loader#: Configuration of reference object loader for astrometric fit. (LoadReferenceObjectsConfig, default <class 'lsst.meas.algorithms.loadReferenceObjects.LoadReferenceObjectsConfig'>)

background_stats_flux_column#: Column used to generate post-subtracted background stats. (str, default 'base_CircularApertureFlux_12_0_flux')

background_stats_ignored_pixel_masks#: Pixel mask flags to ignore when calculating post-sky-subtraction background statistics. These are added to those ignored by the meas.algorithms.SubtractBackgroundConfig algorithm. (List, default ['SAT', 'SUSPECT', 'SPIKE'])

compute_summary_stats#: Task to to compute summary statistics on the calibrated exposure. (ConfigurableInstance, default <class 'lsst.pipe.tasks.computeExposureSummaryStats.ComputeExposureSummaryStatsConfig'>)

connections: pexConfig.ConfigField#: Field which refers to a dynamically added configuration class which is based on a PipelineTaskConnections class.

diffractionSpikeMask#: Task to identify and mask the diffraction spikes of bright stars. (ConfigurableInstance, default <class 'lsst.pipe.tasks.diffractionSpikeMask.DiffractionSpikeMaskConfig'>)

doMaskDiffractionSpikes#: If True, load the photometric reference catalog again but select only bright stars. Use the bright star catalog to set the SPIKE mask for regions likely contaminated by diffraction spikes. (bool, default False)

do_adaptive_threshold_detection#: Implement the adaptive detection thresholding approach? (bool, default True)

do_calibrate_pixels#: If True, apply the photometric calibration to the image pixels and background model, and attach an identity PhotoCalib to the output image to reflect this. If False`, leave the image and background uncalibrated and attach the PhotoCalib that maps them to physical units. (bool, default True)

do_downsample_footprints#: Downsample footprints prior to deblending to optimize speed? (bool, default False)

do_illumination_correction#: If True, apply the illumination correction. This assumes that the input image has already been flat-fielded such that it is suitable for background subtraction. (bool, default False)

do_include_astrometric_errors#: If True, include astrometric errors in the output catalog. (bool, default True)

downsample_max_footprints#: Maximum number of non-sky-source footprints to use if do_downsample_footprints is True, (int, default 1000)

id_generator#: Configuration for how to generate catalog IDs from data IDs. (DetectorVisitIdGeneratorConfig, default <class 'lsst.meas.base._id_generator.DetectorVisitIdGeneratorConfig'>)

install_simple_psf#: Task to install a simple PSF model into the input exposure to use when detecting bright sources for PSF estimation. (ConfigurableInstance, default <class 'lsst.meas.algorithms.installGaussianPsf.InstallGaussianPsfConfig'>)

measure_aperture_correction#: Task to compute the aperture correction from the bright stars. (ConfigurableInstance, default <class 'lsst.meas.algorithms.measureApCorr.MeasureApCorrConfig'>)

optional_outputs#: Which optional outputs to save (as their connection name)? (List, default ['psf_stars', 'psf_stars_footprints', 'astrometry_matches', 'photometry_matches', 'mask'])

photometry#: Task to perform photometric calibration to fit a PhotoCalib. (ConfigurableInstance, default <class 'lsst.pipe.tasks.photoCal.PhotoCalConfig'>)

photometry_ref_loader#: Configuration of reference object loader for photometric fit. (LoadReferenceObjectsConfig, default <class 'lsst.meas.algorithms.loadReferenceObjects.LoadReferenceObjectsConfig'>)

psf_adaptive_threshold_detection#: Task to adaptively detect sources for PSF determination. (ConfigurableInstance, default <class 'lsst.meas.algorithms.adaptive_thresholds.AdaptiveThresholdDetectionConfig'>)

psf_detection#: Task to detect sources for PSF determination. (ConfigurableInstance, default <class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)

psf_measure_psf#: Task to measure the psf on bright sources. (ConfigurableInstance, default <class 'lsst.pipe.tasks.measurePsf.MeasurePsfConfig'>)

psf_normalized_calibration_flux#: Task to normalize the calibration flux (e.g. compensated tophats) for the bright stars used for psf estimation. (ConfigurableInstance, default <class 'lsst.meas.algorithms.normalizedCalibrationFlux.NormalizedCalibrationFluxConfig'>)

psf_repair#: Task to repair cosmic rays on the exposure before PSF determination. (ConfigurableInstance, default <class 'lsst.pipe.tasks.repair.RepairConfig'>)

psf_source_measurement#: Task to measure sources to be used for psf estimation. (ConfigurableInstance, default <class 'lsst.meas.base.sfm.SingleFrameMeasurementConfig'>)

psf_subtract_background#: Task to perform initial background subtraction, before first detection pass. (ConfigurableInstance, default <class 'lsst.meas.algorithms.subtractBackground.SubtractBackgroundConfig'>)

run_sattle#: If True, the sattle service will populate a cache for later use in ip_diffim.detectAndMeasure alert verification. (bool, default False)

sattle_historical#: If re-running a pipeline that requires sattle, this should be set to True. This will populate sattle’s cache with the historic data closest in time to the exposure. (bool, default False)

saveLogOutput#: Flag to enable/disable saving of log output for a task, enabled by default. (bool, default True)

snap_combine#: Task to combine two snaps to make one exposure. (ConfigurableInstance, default <class 'lsst.pipe.tasks.snapCombine.SnapCombineConfig'>)

star_apply_aperture_correction#: Task to apply aperture corrections to the selected stars. (ConfigurableInstance, default <class 'lsst.meas.base.applyApCorr.ApplyApCorrConfig'>)

star_background#: Task to perform final background subtraction, just before photoCal. (ConfigurableInstance, default <class 'lsst.meas.algorithms.subtractBackground.SubtractBackgroundConfig'>)

star_background_min_footprints#: Minimum number of footprints in the detection mask for star_background measurement. This number will get adjusted to the fraction config.star_background_peak_fraction of the detected peaks if that number is larger. If the number of footprints is less than the minimum, the detection threshold is iteratively increased until the threshold is met. (int, default 3)

star_background_peak_fraction#: The minimum number of footprints in the detection mask for star_background measurement. gets set to the maximum of this fraction of the detected peaks and the value set in config.star_background_min_footprints. If the number of footprints is less than the current minimum set, the detection threshold is iteratively increased until the threshold is met. (float, default 0.01)

star_catalog_calculation#: Task to compute extendedness values on the star catalog, for the star selector to remove extended sources. (ConfigurableInstance, default <class 'lsst.meas.base.catalogCalculation.CatalogCalculationConfig'>)

star_deblend#: Split blended sources into their components. (ConfigurableInstance, default <class 'lsst.meas.deblender.sourceDeblendTask.SourceDeblendConfig'>)

star_detection#: Task to detect stars to return in the output catalog. (ConfigurableInstance, default <class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)

star_measurement#: Task to measure stars to return in the output catalog. (ConfigurableInstance, default <class 'lsst.meas.base.sfm.SingleFrameMeasurementConfig'>)

star_normalized_calibration_flux#: Task to apply the normalization for calibration fluxes (e.g. compensated tophats) for the final output star catalog. (ConfigurableInstance, default <class 'lsst.meas.algorithms.normalizedCalibrationFlux.NormalizedCalibrationFluxConfig'>)

star_selector#: Task to select reliable stars to use for calibration. (RegistryInstanceDict, default 'science')

star_set_primary_flags#: Task to add isPrimary to the catalog. (ConfigurableInstance, default <class 'lsst.meas.algorithms.setPrimaryFlags.SetPrimaryFlagsConfig'>)

star_sky_sources#: Task to generate sky sources (‘empty’ regions where there are no detections). (ConfigurableInstance, default <class 'lsst.meas.algorithms.skyObjects.SkyObjectsConfig'>)

useButlerCamera#: If True, use a camera distortion model generated elsewhere in the pipeline combined with the telescope boresight as a starting point for fitting the WCS, instead of using the WCS attached to the exposure, which is generated from the boresight and the camera model from the obs_* package. (bool, default False)

Methods Documentation

setDefaults()#: Subclass hook for computing defaults.

Notes#

Derived Config classes that must compute defaults rather than using the Field instances’s defaults should do so here. To correctly use inherited defaults, implementations of setDefaults must call their base class’s setDefaults.

validate()#

Validate the Config, raising an exception if invalid.

Raises#

lsst.pex.config.FieldValidationError: Raised if verification fails.

Notes#

The base class implementation performs type checks on all fields by calling their validate methods.

Complex single-field validation can be defined by deriving new Field types. For convenience, some derived lsst.pex.config.Field-types (ConfigField and ConfigChoiceField) are defined in lsst.pex.config that handle recursing into subconfigs.

Inter-field relationships should only be checked in derived Config classes after calling this method, and base validation is complete.