ScaleVarianceTask

class lsst.pipe.tasks.scaleVariance.ScaleVarianceTask(*args, **kwargs)

Bases: lsst.pipe.base.Task

Scale the variance in a MaskedImage

The variance plane in a convolved or warped image (or a coadd derived from warped images) does not accurately reflect the noise properties of the image because variance has been lost to covariance. This Task attempts to correct for this by scaling the variance plane to match the observed variance in the image. This is not perfect (because we’re not tracking the covariance) but it’s simple and is often good enough.

Methods Summary

emptyMetadata() Empty (clear) the metadata for this Task and all sub-Tasks.
getAllSchemaCatalogs() Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
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.
getSchemaCatalogs() Get the schemas generated by this task.
getTaskDict() Get a dictionary of all tasks as a shallow copy.
imageBased(maskedImage) Determine the variance rescaling factor from image statistics
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.
pixelBased(maskedImage) Determine the variance rescaling factor from pixel statistics
run(maskedImage) Rescale the variance in a maskedImage
subtractedBackground(maskedImage) Context manager for subtracting the background
timer(name[, logLevel]) Context manager to log performance data for an arbitrary block of code.

Methods Documentation

emptyMetadata()

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

getAllSchemaCatalogs()

Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.

Returns:
schemacatalogs : dict

Keys are butler dataset type, values are a empty catalog (an instance of the appropriate lsst.afw.table Catalog type) for all tasks in the hierarchy, from the top-level task down through all subtasks.

Notes

This method may be called on any task in the hierarchy; it will return the same answer, regardless.

The default implementation should always suffice. If your subtask uses schemas the override Task.getSchemaCatalogs, not this method.

getFullMetadata()

Get metadata for all tasks.

Returns:
metadata : lsst.daf.base.PropertySet

The PropertySet 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()

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()

Get the name of the task.

Returns:
taskName : str

Name of the task.

See also

getFullName

getSchemaCatalogs()

Get the schemas generated by this task.

Returns:
schemaCatalogs : dict

Keys are butler dataset type, values are an empty catalog (an instance of the appropriate lsst.afw.table Catalog type) for this task.

See also

Task.getAllSchemaCatalogs

Notes

Warning

Subclasses that use schemas must override this method. The default implementation returns an empty dict.

This method may be called at any time after the Task is constructed, which means that all task schemas should be computed at construction time, not when data is actually processed. This reflects the philosophy that the schema should not depend on the data.

Returning catalogs rather than just schemas allows us to save e.g. slots for SourceCatalog as well.

getTaskDict()

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.

imageBased(maskedImage)

Determine the variance rescaling factor from image statistics

We calculate average(SNR) = stdev(image)/median(variance), and the value should be unity. The variance rescaling factor is the factor that brings this value to unity.

This may not work well if the pixels from which we measure the standard deviation of the image are not effectively the same pixels from which we measure the median of the variance. In that case, use an alternate method.

Parameters:
maskedImage : lsst.afw.image.MaskedImage

Image for which to determine the variance rescaling factor.

Returns:
factor : float

Variance rescaling factor.

classmethod makeField(doc)

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, **keyArgs)

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.

pixelBased(maskedImage)

Determine the variance rescaling factor from pixel statistics

We calculate SNR = image/sqrt(variance), and the distribution for most of the background-subtracted image should have a standard deviation of unity. The variance rescaling factor is the factor that brings that distribution to have unit standard deviation.

This may not work well if the image has a lot of structure in it, as the assumptions are violated. In that case, use an alternate method.

Parameters:
maskedImage : lsst.afw.image.MaskedImage

Image for which to determine the variance rescaling factor.

Returns:
factor : float

Variance rescaling factor.

run(maskedImage)

Rescale the variance in a maskedImage

Parameters:
maskedImage : lsst.afw.image.MaskedImage

Image for which to determine the variance rescaling factor.

Returns:
factor : float

Variance rescaling factor.

Raises:
RuntimeError

If the estimated variance rescaling factor exceeds the configured limit.

subtractedBackground(maskedImage)

Context manager for subtracting the background

We need to subtract the background so that the entire image (apart from objects, which should be clipped) will have the image/sqrt(variance) distributed about zero.

This context manager subtracts the background, and ensures it is restored on exit.

Parameters:
maskedImage : lsst.afw.image.MaskedImage

Image+mask+variance to have background subtracted and restored.

Returns:
context : context manager

Context manager that ensure the background is restored.

timer(name, logLevel=10000)

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 lsst.log level constant.

See also

timer.logInfo

Examples

Creating a timer context:

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