MaskStreaksTask¶

class lsst.pipe.tasks.maskStreaks.MaskStreaksTask(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

Find streaks or other straight lines in image data.

Nearby objects passing through the field of view of the telescope leave a bright trail in images. This class uses the Kernel Hough Transform (KHT) (Fernandes and Oliveira, 2007), implemented in lsst.houghtransform. The procedure works by taking a binary image, either provided as put or produced from the input data image, using a Canny filter to make an image of the edges in the original image, then running the KHT on the edge image. The KHT identifies clusters of non-zero points, breaks those clusters of points into straight lines, keeps clusters with a size greater than the user-set threshold, then performs a voting procedure to find the best-fit coordinates of any straight lines. Given the results of the KHT algorithm, clusters of lines are identified and grouped (generally these correspond to the two edges of a strea) and a profile is fit to the streak in the original (non-binary) image.

Methods Summary

`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`find`(maskedImage)	Find streaks in a masked image.
`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.
`run`(maskedImage)	Find and mask streaks in a masked image.
`timer`(name, logLevel)	Context manager to log performance data for an arbitrary block of code.

Methods Documentation

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

find(maskedImage)¶

Find streaks in a masked image.

Parameters:	maskedImage : `lsst.afw.image.maskedImage` The image in which to search for streaks.
Returns:	result : `lsst.pipe.base.Struct` Results as a struct with attributes: `originalLines` Lines identified by kernel hough transform. `lineClusters` Lines grouped into clusters in rho-theta space. `lines` Final result for lines after line-profile fit. `mask` 2-d boolean mask where detected lines are True.

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.

run(maskedImage)¶

Find and mask streaks in a masked image.

Finds streaks in the image and modifies maskedImage in place by adding a mask plane with any identified streaks.

Parameters:	maskedImage : `lsst.afw.image.maskedImage` The image in which to search for streaks. The mask detection plane corresponding to `config.detectedMaskPlane` must be set with the detected pixels.
Returns:	result : `lsst.pipe.base.Struct` Results as a struct with attributes: `originalLines` Lines identified by kernel hough transform. `lineClusters` Lines grouped into clusters in rho-theta space. `lines` Final result for lines after line-profile fit.

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.

Navigation

MaskStreaksTask¶