MakeKernelTask¶
- class lsst.ip.diffim.MakeKernelTask(*args, **kwargs)¶
Bases:
PsfMatchTask
Construct a kernel for PSF matching two exposures.
Methods Summary
Empty (clear) the metadata for this Task and all sub-Tasks.
Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
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 the schemas generated by this task.
getSelectSources
(exposure[, sigma, ...])Get sources to use for Psf-matching.
Get a dictionary of all tasks as a shallow copy.
makeCandidateList
(templateExposure, ...[, ...])Make a list of acceptable KernelCandidates.
makeField
(doc)Make a
lsst.pex.config.ConfigurableField
for this task.makeKernelBasisList
([targetFwhmPix, ...])Wrapper to set log messages for
lsst.ip.diffim.makeKernelBasisList
.makeSubtask
(name, **keyArgs)Create a subtask as a new instance as the
name
attribute of this task.run
(template, science, kernelSources[, ...])Solve for the kernel and background model that best match two Exposures evaluated at the given source locations.
selectKernelSources
(template, science[, ...])Select sources from a list of candidates, and extract footprints.
timer
(name[, logLevel])Context manager to log performance data for an arbitrary block of code.
Methods Documentation
- getAllSchemaCatalogs() Dict[str, Any] ¶
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.
- schemacatalogs
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() 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
- getSchemaCatalogs() Dict[str, Any] ¶
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.
- schemaCatalogs
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.
- getSelectSources(exposure, sigma=None, doSmooth=True, idFactory=None)¶
Get sources to use for Psf-matching.
This method runs detection and measurement on an exposure. The returned set of sources will be used as candidates for Psf-matching.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure on which to run detection/measurement
- sigma
float
, optional PSF sigma, in pixels, used for smoothing the image for detection. If
None
, the PSF width will be used.- doSmooth
bool
Whether or not to smooth the Exposure with Psf before detection
- idFactory
lsst.afw.table.IdFactory
Factory for the generation of Source ids
- exposure
- Returns:
- selectSources
source catalog containing candidates for the Psf-matching
- 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
- makeCandidateList(templateExposure, scienceExposure, kernelSize, candidateList=None, preconvolved=False)¶
Make a list of acceptable KernelCandidates.
Accept or generate a list of candidate sources for Psf-matching, and examine the Mask planes in both of the images for indications of bad pixels
- Parameters:
- templateExposure
lsst.afw.image.Exposure
Exposure that will be convolved
- scienceExposure
lsst.afw.image.Exposure
Exposure that will be matched-to
- kernelSize
float
Dimensions of the Psf-matching Kernel, used to grow detection footprints
- candidateList
list
, optional List of Sources to examine. Elements must be of type afw.table.Source or a type that wraps a Source and has a getSource() method, such as meas.algorithms.PsfCandidateF.
- preconvolved
bool
, optional Was the science exposure already convolved with its PSF?
- templateExposure
- Returns:
- Raises:
- RuntimeError
If
candidateList
is empty or contains incompatible types.
- 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")
- makeKernelBasisList(targetFwhmPix=None, referenceFwhmPix=None, basisDegGauss=None, basisSigmaGauss=None, metadata=None)¶
Wrapper to set log messages for
lsst.ip.diffim.makeKernelBasisList
.- Parameters:
- targetFwhmPix
float
, optional Passed on to
lsst.ip.diffim.generateAlardLuptonBasisList
. Not used for delta function basis sets.- referenceFwhmPix
float
, optional Passed on to
lsst.ip.diffim.generateAlardLuptonBasisList
. Not used for delta function basis sets.- basisDegGauss
list
ofint
, optional Passed on to
lsst.ip.diffim.generateAlardLuptonBasisList
. Not used for delta function basis sets.- basisSigmaGauss
list
ofint
, optional Passed on to
lsst.ip.diffim.generateAlardLuptonBasisList
. Not used for delta function basis sets.- metadata
lsst.daf.base.PropertySet
, optional Passed on to
lsst.ip.diffim.generateAlardLuptonBasisList
. Not used for delta function basis sets.
- targetFwhmPix
- Returns:
- basisList:
list
oflsst.afw.math.kernel.FixedKernel
List of basis kernels.
- basisList:
- 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
.
- run(template, science, kernelSources, preconvolved=False)¶
Solve for the kernel and background model that best match two Exposures evaluated at the given source locations.
- Parameters:
- template
lsst.afw.image.Exposure
Exposure that will be convolved.
- science
lsst.afw.image.Exposure
The exposure that will be matched.
- kernelSources
list
ofdict
A list of dicts having a “source” and “footprint” field for the Sources deemed to be appropriate for Psf matching. Can be the output from
selectKernelSources
.- preconvolved
bool
, optional Was the science image convolved with its own PSF?
- template
- Returns:
- results
lsst.pipe.base.Struct
psfMatchingKernel
lsst.afw.math.LinearCombinationKernel
Spatially varying Psf-matching kernel.
backgroundModel
lsst.afw.math.Function2D
Spatially varying background-matching function.
- results
- selectKernelSources(template, science, candidateList=None, preconvolved=False)¶
Select sources from a list of candidates, and extract footprints.
- Parameters:
- template
lsst.afw.image.Exposure
Exposure that will be convolved.
- science
lsst.afw.image.Exposure
The exposure that will be matched.
- candidateList
list
, optional List of Sources to examine. Elements must be of type afw.table.Source or a type that wraps a Source and has a getSource() method, such as meas.algorithms.PsfCandidateF.
- preconvolved
bool
, optional Was the science image convolved with its own PSF?
- template
- Returns: