MultiProFitPsfTask¶

class lsst.meas.extensions.multiprofit.fit_coadd_psf.MultiProFitPsfTask(**kwargs)¶

Bases: CatalogPsfFitter, CoaddPsfFitSubTask

Fit a Gaussian mixture PSF model at cataloged locations.

This task uses MultiProFit to fit a PSF model to the coadd PSF, evaluated at the centroid of each source in the corresponding catalog.

Parameters:

**kwargs: Keyword arguments to pass to CoaddPsfFitSubTask.__init__.

Methods Summary

`check_source`(source, config)	Check whether a source can have its PSF model fit.
`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`fit`(catexp[, config_data, logger])	Fit PSF models for a catalog with MultiProFit.
`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.
`initialize_model`(model, config_data[, ...])	Initialize a ModelD for a single source row.
`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.
`run`(catexp, **kwargs)	Run the MultiProFit PSF task on a catalog-exposure pair.
`timer`(name[, logLevel])	Context manager to log performance data for an arbitrary block of code.

Methods Documentation

check_source(source, config)¶

Check whether a source can have its PSF model fit.

Parameters:

source: The source row to check.
config: The fitter config.

Notes

Derived classes may use the source row as they deem fit. For example, if the source has poor quality flags, a fitter may choose not to fit the PSF model if it will not end up being used anyway.

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

fit(catexp: CatalogExposurePsfABC, config_data: CatalogPsfFitterConfigData | None = None, logger: Logger | None = None, **kwargs: Any) → Table¶

Fit PSF models for a catalog with MultiProFit.

Each source has its PSF fit with a configureable Gaussian mixture PSF model, given a pixellated PSF image from the CatalogExposure.

Parameters:

catexp: An exposure to fit a model PSF at the position of all sources in the corresponding catalog.
config_data: Configuration settings for fitting and output.
logger: The logger. Defaults to calling _getlogger.
**kwargs: Additional keyword arguments to pass to self.modeller.

Returns:

catalog: A table with fit parameters for the PSF model at the location of each source.

getFullMetadata() → TaskMetadata¶

Get metadata for all tasks.

Returns:

metadataTaskMetadata: 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:

fullNamestr

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:

taskNamestr: Name of the task.

See also

getFullName: Get the full name of the task.

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

Get a dictionary of all tasks as a shallow copy.

Returns:

taskDictdict: Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc.

initialize_model(model: ModelD, config_data: CatalogPsfFitterConfigData, limits_x: LimitsD = None, limits_y: LimitsD = None) → None¶

Initialize a ModelD for a single source row.

Parameters:

model: The model object to initialize.
config_data: The fitter config with cached data.
limits_x: Hard limits for the source’s x centroid.
limits_y: Hard limits for the source’s y centroid.

classmethod makeField(doc: str) → ConfigurableField¶

Make a lsst.pex.config.ConfigurableField for this task.

Parameters:

docstr: Help text for the field.

Returns:

configurableFieldlsst.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: Any) → None¶

Create a subtask as a new instance as the name attribute of this task.

Parameters:

namestr

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.

run(catexp: CatalogExposurePsf, **kwargs) → Struct¶

Run the MultiProFit PSF task on a catalog-exposure pair.

Parameters:

catexp: An exposure to fit a model PSF at the position of all sources in the corresponding catalog.
**kwargs: Additional keyword arguments to pass to self.fit.

Returns:

catalog: A table with fit parameters for the PSF model at the location of each source.

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

Context manager to log performance data for an arbitrary block of code.

Parameters:

namestr: Name of code being timed; data will be logged using item name: Start and End.
logLevelint: A logging level constant.

Navigation

MultiProFitPsfTask¶