DecorrelateALKernelSpatialTask¶
- class lsst.ip.diffim.DecorrelateALKernelSpatialTask(*args, **kwargs)¶
Bases:
TaskDecorrelate the effect of convolution by Alard-Lupton matching kernel in image difference
Methods Summary
computeVarianceMean(exposure)Compute the mean of the variance plane of
exposure.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.ConfigurableFieldfor this task.makeSubtask(name, **keyArgs)Create a subtask as a new instance as the
nameattribute of this task.run(scienceExposure, templateExposure, ...)Perform decorrelation of an image difference exposure.
timer(name[, logLevel])Context manager to log performance data for an arbitrary block of code.
Methods Documentation
- computeVarianceMean(exposure)¶
Compute the mean of the variance plane of
exposure.
- 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.timeMethodis 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
- getTaskDict() Dict[str, ReferenceType[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.ConfigurableFieldfor this task.- Parameters:
- doc
str Help text for the field.
- doc
- Returns:
- configurableField
lsst.pex.config.ConfigurableField A
ConfigurableFieldfor 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
nameattribute 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 ofConfigurableFieldorRegistryField.
- run(scienceExposure, templateExposure, subtractedExposure, psfMatchingKernel, spatiallyVarying=True, preConvKernel=None, templateMatched=True, preConvMode=False)¶
Perform decorrelation of an image difference exposure.
Decorrelates the diffim due to the convolution of the templateExposure with the A&L psfMatchingKernel. If
spatiallyVaryingis True, it utilizes the spatially varying matching kernel via theimageMapReduceframework to perform spatially-varying decorrelation on a grid of subExposures.- Parameters:
- scienceExposure
lsst.afw.image.Exposure the science Exposure used for PSF matching
- templateExposure
lsst.afw.image.Exposure the template Exposure used for PSF matching
- subtractedExposure
lsst.afw.image.Exposure the subtracted Exposure produced by
ip_diffim.ImagePsfMatchTask.subtractExposures()- psfMatchingKernelan (optionally spatially-varying) PSF matching kernel produced
by
ip_diffim.ImagePsfMatchTask.subtractExposures()- spatiallyVarying
bool if True, perform the spatially-varying operation
- preConvKernel
lsst.meas.algorithms.Psf if not none, the scienceExposure has been pre-filtered with this kernel. (Currently this option is experimental.)
- templateMatched
bool, optional If True, the template exposure was matched (convolved) to the science exposure.
- preConvMode
bool, optional If True,
subtractedExposureis assumed to be a likelihood difference image and will be noise corrected as a likelihood image.
- scienceExposure
- Returns:
- results
lsst.pipe.base.Struct a structure containing: -
correctedExposure: the decorrelated diffim
- results