MeasureDefectsCombinedTask¶
- class lsst.cp.pipe.MeasureDefectsCombinedTask(*, config: PipelineTaskConfig | None = None, log: logging.Logger | LsstLogAdapter | None = None, initInputs: dict[str, Any] | None = None, **kwargs: Any)¶
Bases:
MeasureDefectsTask
Task to measure defects in combined images.
Attributes Summary
Methods Summary
debugHistogram
(stepname, ampImage, ...)Make a histogram of the distribution of pixel values for each amp.
debugView
(stepname, ampImage, defects, detector)Plot the defects found by the task.
Empty (clear) the metadata for this Task and all sub-Tasks.
Get metadata for all tasks.
Get the task name as a hierarchical name including parent task names.
getName
()Get the name of the task.
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.Mask blocks in a column if there are on-and-off bad pixels
run
(inputExp, camera)Measure one exposure for defects.
runQuantum
(butlerQC, inputRefs, outputRefs)Do butler IO and transform to provide in memory objects for tasks
run
method.timer
(name[, logLevel])Context manager to log performance data for an arbitrary block of code.
Attributes Documentation
Methods Documentation
- debugHistogram(stepname, ampImage, nSigmaUsed, exp)¶
Make a histogram of the distribution of pixel values for each amp.
The main image data histogram is plotted in blue. Edge pixels, if masked, are in red. Note that masked edge pixels do not contribute to the underflow and overflow numbers.
Note that this currently only supports the 16-amp LSST detectors.
- debugView(stepname, ampImage, defects, detector)¶
Plot the defects found by the task.
- Parameters:
- stepname
str
Debug frame to request.
- ampImage
lsst.afw.image.MaskedImage
Amplifier image to display.
- defects
lsst.ip.isr.Defects
The defects to plot.
- detector
lsst.afw.cameraGeom.Detector
Detector holding camera geometry.
- stepname
- getFullMetadata() 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.
- metadata
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”.
- fullName
- getName() str ¶
Get the name of the task.
- Returns:
- taskName
str
Name of the task.
- taskName
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:
- taskDict
dict
Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc.
- taskDict
- classmethod makeField(doc: str) ConfigurableField ¶
Make a
lsst.pex.config.ConfigurableField
for this task.- Parameters:
- doc
str
Help text for the field.
- doc
- Returns:
- configurableField
lsst.pex.config.ConfigurableField
A
ConfigurableField
for this task.
- configurableField
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:
- 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
.
- name
Notes
The subtask must be defined by
Task.config.name
, an instance ofConfigurableField
orRegistryField
.
- maskBlocksIfIntermitentBadPixelsInColumn(defects)¶
Mask blocks in a column if there are on-and-off bad pixels
If there’s a column with on and off bad pixels, mask all the pixels in between, except if there is a large enough gap of consecutive good pixels between two bad pixels in the column.
- Parameters:
- defects
lsst.ip.isr.Defects
The defects found in the image so far
- defects
- Returns:
- defects
lsst.ip.isr.Defects
If the number of bad pixels in a column is not larger or equal than self.config.badPixelColumnThreshold, the input list is returned. Otherwise, the defects list returned will include boxes that mask blocks of on-and-of pixels.
- badColumnCount
int
Number of bad columns masked.
- defects
- run(inputExp, camera)¶
Measure one exposure for defects.
- Parameters:
- inputExp
lsst.afw.image.Exposure
Exposure to examine.
- camera
lsst.afw.cameraGeom.Camera
Camera to use for metadata.
- inputExp
- Returns:
- results
lsst.pipe.base.Struct
Results struct containing:
outputDefects
The defects measured from this exposure (
lsst.ip.isr.Defects
).
- results
- runQuantum(butlerQC: QuantumContext, inputRefs: InputQuantizedConnection, outputRefs: OutputQuantizedConnection) None ¶
Do butler IO and transform to provide in memory objects for tasks
run
method.- Parameters:
- butlerQC
QuantumContext
A butler which is specialized to operate in the context of a
lsst.daf.butler.Quantum
.- inputRefs
InputQuantizedConnection
Datastructure whose attribute names are the names that identify connections defined in corresponding
PipelineTaskConnections
class. The values of these attributes are thelsst.daf.butler.DatasetRef
objects associated with the defined input/prerequisite connections.- outputRefs
OutputQuantizedConnection
Datastructure whose attribute names are the names that identify connections defined in corresponding
PipelineTaskConnections
class. The values of these attributes are thelsst.daf.butler.DatasetRef
objects associated with the defined output connections.
- butlerQC