SkyMeasurementTask

class lsst.pipe.tasks.background.SkyMeasurementTask(config: Optional[Config] = None, name: Optional[str] = None, parentTask: Optional[Task] = None, log: Optional[Union[logging.Logger, lsst.utils.logging.LsstLogAdapter]] = None)

Bases: lsst.pipe.base.Task

Task for creating, persisting and using sky frames

A sky frame is like a fringe frame (the sum of many exposures of the night sky, combined with rejection to remove astrophysical objects) except the structure is on larger scales, and hence we bin the images and represent them as a background model (a lsst.afw.math.BackgroundMI). The sky frame represents the dominant response of the camera to the sky background.

Methods Summary

averageBackgrounds(bgList) Average multiple background models
backgroundToExposure(statsImage, bbox) Convert a background model to an exposure
emptyMetadata() Empty (clear) the metadata for this Task and all sub-Tasks.
exposureToBackground(bgExp) Convert an exposure to background model
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.
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.
measureBackground(image) Measure a background model for image
measureScale(image, skyBackground) Measure scale of background model in image
solveScales(scales) Solve multiple scales for a single scale factor
subtractSkyFrame(image, skyBackground, scale) Subtract sky frame from science image
timer(name, logLevel) Context manager to log performance data for an arbitrary block of code.

Methods Documentation

averageBackgrounds(bgList)

Average multiple background models

The input background models should be a BackgroundList consisting of a single BackgroundMI.

Parameters:
bgList : list of lsst.afw.math.BackgroundList

Background models to average.

Returns:
bgExp : lsst.afw.image.Exposure

Background model in Exposure format.

backgroundToExposure(statsImage, bbox)

Convert a background model to an exposure

Calibs need to be persisted as an Exposure, so we need to convert the background model to an Exposure.

Parameters:
statsImage : lsst.afw.image.MaskedImageF

Background model’s statistics image.

bbox : lsst.geom.Box2I

Bounding box for image.

Returns:
exp : lsst.afw.image.Exposure

Background model in Exposure format.

emptyMetadata() → None

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

static exposureToBackground(bgExp)

Convert an exposure to background model

Calibs need to be persisted as an Exposure, so we need to convert the persisted Exposure to a background model.

Parameters:
bgExp : lsst.afw.image.Exposure

Background model in Exposure format.

Returns:
bg : lsst.afw.math.BackgroundList

Background model

getFullMetadata() → lsst.pipe.base._task_metadata.TaskMetadata

Get metadata for all tasks.

Returns:
metadata : TaskMetadata

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:
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”.
getName() → str

Get the name of the task.

Returns:
taskName : str

Name of the task.

See also

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

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.

classmethod makeField(doc: str) → lsst.pex.config.configurableField.ConfigurableField

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("brief description of task")
makeSubtask(name: str, **keyArgs) → None

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 ConfigurableField or RegistryField.

measureBackground(image)

Measure a background model for image

This doesn’t use a full-featured background model (e.g., no Chebyshev approximation) because we just want the binning behaviour. This will allow us to average the bins later (averageBackgrounds).

The BackgroundMI is wrapped in a BackgroundList so it can be pickled and persisted.

Parameters:
image : lsst.afw.image.MaskedImage

Image for which to measure background.

Returns:
bgModel : lsst.afw.math.BackgroundList

Background model.

measureScale(image, skyBackground)

Measure scale of background model in image

We treat the sky frame much as we would a fringe frame (except the length scale of the variations is different): we measure samples on the input image and the sky frame, which we will use to determine the scaling factor in the ‘solveScales` method.

Parameters:
image : lsst.afw.image.Exposure or lsst.afw.image.MaskedImage

Science image for which to measure scale.

skyBackground : lsst.afw.math.BackgroundList

Sky background model.

Returns:
imageSamples : numpy.ndarray

Sample measurements on image.

skySamples : numpy.ndarray

Sample measurements on sky frame.

solveScales(scales)

Solve multiple scales for a single scale factor

Having measured samples from the image and sky frame, we fit for the scaling factor.

Parameters:
scales : list of a tuple of two numpy.ndarray arrays

A list of the results from measureScale method.

Returns:
scale : float

Scale factor.

subtractSkyFrame(image, skyBackground, scale, bgList=None)

Subtract sky frame from science image

Parameters:
image : lsst.afw.image.Exposure or lsst.afw.image.MaskedImage

Science image.

skyBackground : lsst.afw.math.BackgroundList

Sky background model.

scale : float

Scale to apply to background model.

bgList : lsst.afw.math.BackgroundList

List of backgrounds applied to image

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

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 logging level constant.

See also

timer.logInfo

Examples

Creating a timer context:

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