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.

See also

lsst.utils.timer.logInfo

Implementation function.

Examples

Creating a timer context:

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