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

Task.getAllSchemaCatalogs

Notes

Warning

Subclasses that use schemas must override this method. The default implemenation 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("a brief description of what this task does")

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 pex_config 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.

Navigation

ScaleVarianceTask¶