InsertFakesTask¶
- class lsst.pipe.tasks.insertFakes.InsertFakesTask(*, config: PipelineTaskConfig | None = None, log: logging.Logger | LsstLogAdapter | None = None, initInputs: dict[str, Any] | None = None, **kwargs: Any)¶
Bases:
PipelineTask
Insert fake objects into images.
Add fake stars and galaxies to the given image, read in through the dataRef. Galaxy parameters are read in from the specified file and then modelled using galsim.
InsertFakesTask
has five functions that make images of the fake sources and then add them to the image.addPixCoords
Use the WCS information to add the pixel coordinates of each source.
mkFakeGalsimGalaxies
Use Galsim to make fake double sersic galaxies for each set of galaxy parameters in the input file.
mkFakeStars
Use the PSF information from the image to make a fake star using the magnitude information from the input file.
cleanCat
Remove rows of the input fake catalog which have half light radius, of either the bulge or the disk, that are 0. Also removes rows that have Sersic index outside of galsim’s allowed paramters. If the config option sourceSelectionColName is set then this function limits the catalog of input fakes to only those which are True in this column.
addFakeSources
Add the fake sources to the image.
Attributes Summary
Methods Summary
addFakeSources
(image, fakeImages, sourceType)Add the fake sources to the given image
addPixCoords
(fakeCat, image)Add pixel coordinates to the catalog of fakes.
cleanCat
(fakeCat, starCheckVal)Remove rows from the fakes catalog which have HLR = 0 for either the buldge or disk component,
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.mkFakeGalsimGalaxies
(fakeCat, band, ...)Make images of fake galaxies using GalSim.
mkFakeStars
(fakeCat, band, photoCalib, psf, ...)Make fake stars based off the properties in the fakeCat.
processImagesForInsertion
(fakeCat, wcs, psf, ...)Process images from files into the format needed for insertion.
run
(fakeCat, image, wcs, photoCalib)Add fake sources to an image.
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.
trimFakeCat
(fakeCat, image)Trim the fake cat to the size of the input image plus trimBuffer padding.
Attributes Documentation
Methods Documentation
- addFakeSources(image, fakeImages, sourceType)¶
Add the fake sources to the given image
- Parameters:
- image
lsst.afw.image.exposure.exposure.ExposureF
The image into which the fake sources should be added
- fakeImages
typing.Iterator
[tuple
[‘lsst.afw.image.ImageF`,lsst.geom.Point2d
]] An iterator of tuples that contains (or generates) images of fake sources, and the locations they are to be inserted at.
- sourceType
str
The type (star/galaxy) of fake sources input
- image
- Returns:
- image
lsst.afw.image.exposure.exposure.ExposureF
- image
Notes
Uses the x, y information in the
fakeCat
to position an image of the fake interpolated onto the pixel grid of the image. Sets theFAKE
mask plane for the pixels added with the fake source.
- addPixCoords(fakeCat, image)¶
Add pixel coordinates to the catalog of fakes.
- Parameters:
- fakeCat
pandas.core.frame.DataFrame
The catalog of fake sources to be input
- image
lsst.afw.image.exposure.exposure.ExposureF
The image into which the fake sources should be added
- fakeCat
- Returns:
- fakeCat
pandas.core.frame.DataFrame
- fakeCat
- cleanCat(fakeCat, starCheckVal)¶
- Remove rows from the fakes catalog which have HLR = 0 for either the buldge or disk component,
also remove galaxies that have Sersic index outside the galsim min and max allowed (0.3 <= n <= 6.2).
- Parameters:
- fakeCat
pandas.core.frame.DataFrame
The catalog of fake sources to be input
- starCheckVal
str
,bytes
orint
The value that is set in the sourceType column to specifiy an object is a star.
- fakeCat
- Returns:
- fakeCat
pandas.core.frame.DataFrame
The input catalog of fake sources but with the bad objects removed
- fakeCat
- 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
.
- mkFakeGalsimGalaxies(fakeCat, band, photoCalib, pixelScale, psf, image)¶
Make images of fake galaxies using GalSim.
- Parameters:
- band
str
- pixelScale
float
- psf
lsst.meas.extensions.psfex.psfexPsf.PsfexPsf
The PSF information to use to make the PSF images
- fakeCat
pandas.core.frame.DataFrame
The catalog of fake sources to be input
- photoCalib
lsst.afw.image.photoCalib.PhotoCalib
Photometric calibration to be used to calibrate the fake sources
- band
- Yields:
- galImages
generator
A generator of tuples of
lsst.afw.image.exposure.exposure.ExposureF
andlsst.geom.Point2D
of their locations.
- galImages
Notes
Fake galaxies are made by combining two sersic profiles, one for the bulge and one for the disk. Each component has an individual sersic index (n), a, b and position angle (PA). The combined profile is then convolved with the PSF at the specified x, y position on the image.
The names of the columns in the
fakeCat
are configurable and are the column names from the University of Washington simulations database as default. For more information see the doc strings attached to the config options.See mkFakeStars doc string for an explanation of calibration to instrumental flux.
- mkFakeStars(fakeCat, band, photoCalib, psf, image)¶
Make fake stars based off the properties in the fakeCat.
- Parameters:
- band
str
- psf
lsst.meas.extensions.psfex.psfexPsf.PsfexPsf
The PSF information to use to make the PSF images
- fakeCat
pandas.core.frame.DataFrame
The catalog of fake sources to be input
- image
lsst.afw.image.exposure.exposure.ExposureF
The image into which the fake sources should be added
- photoCalib
lsst.afw.image.photoCalib.PhotoCalib
Photometric calibration to be used to calibrate the fake sources
- band
- Yields:
- starImages
generator
A generator of tuples of
lsst.afw.image.ImageF
of fake stars andlsst.geom.Point2D
of their locations.
- starImages
Notes
To take a given magnitude and translate to the number of counts in the image we use photoCalib.magnitudeToInstFlux, which returns the instrumental flux for the given calibration radius used in the photometric calibration step. Thus
calibFluxRadius
should be set to this same radius so that we can normalize the PSF model to the correct instrumental flux within calibFluxRadius.
- processImagesForInsertion(fakeCat, wcs, psf, photoCalib, band, pixelScale)¶
Process images from files into the format needed for insertion.
- Parameters:
- fakeCat
pandas.core.frame.DataFrame
The catalog of fake sources to be input
- wcs
lsst.afw.geom.skyWcs.skyWcs.SkyWc
WCS to use to add fake sources
- psf
lsst.meas.algorithms.coaddPsf.coaddPsf.CoaddPsf
or lsst.meas.extensions.psfex.psfexPsf.PsfexPsf
The PSF information to use to make the PSF images
- photoCalib
lsst.afw.image.photoCalib.PhotoCalib
Photometric calibration to be used to calibrate the fake sources
- band
str
The filter band that the observation was taken in.
- pixelScale
float
The pixel scale of the image the sources are to be added to.
- fakeCat
- Returns:
- galImages
list
A list of tuples of
lsst.afw.image.exposure.exposure.ExposureF
andlsst.geom.Point2D
of their locations. For sources labelled as galaxy.- starImages
list
A list of tuples of
lsst.afw.image.exposure.exposure.ExposureF
andlsst.geom.Point2D
of their locations. For sources labelled as star.
- galImages
Notes
The input fakes catalog needs to contain the absolute path to the image in the band that is being used to add images to. It also needs to have the R.A. and declination of the fake source in radians and the sourceType of the object.
- run(fakeCat, image, wcs, photoCalib)¶
Add fake sources to an image.
- Parameters:
- fakeCat
pandas.core.frame.DataFrame
The catalog of fake sources to be input
- image
lsst.afw.image.exposure.exposure.ExposureF
The image into which the fake sources should be added
- wcs
lsst.afw.geom.SkyWcs
WCS to use to add fake sources
- photoCalib
lsst.afw.image.photoCalib.PhotoCalib
Photometric calibration to be used to calibrate the fake sources
- fakeCat
- Returns:
- resultStruct
lsst.pipe.base.struct.Struct
contains : image :
lsst.afw.image.exposure.exposure.ExposureF
- resultStruct
Notes
Adds pixel coordinates for each source to the fakeCat and removes objects with bulge or disk half light radius = 0 (if
config.doCleanCat = True
).Adds the
Fake
mask plane to the image which is then set byaddFakeSources
to mark where fake sources have been added. Uses the information in thefakeCat
to make fake galaxies (using galsim) and fake stars, using the PSF models from the PSF information for the image. These are then added to the image and the image with fakes included returned.The galsim galaxies are made using a double sersic profile, one for the bulge and one for the disk, this is then convolved with the PSF at that point.
- runQuantum(butlerQC, inputRefs, outputRefs)¶
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
- timer(name: str, logLevel: int = 10) Iterator[None] ¶
Context manager to log performance data for an arbitrary block of code.
- Parameters:
See also
lsst.utils.timer.logInfo
Implementation function.
Examples
Creating a timer context:
with self.timer("someCodeToTime"): pass # code to time
- trimFakeCat(fakeCat, image)¶
Trim the fake cat to the size of the input image plus trimBuffer padding.
fakeCat
must be processed with addPixCoords before using this method.- Parameters:
- fakeCat
pandas.core.frame.DataFrame
The catalog of fake sources to be input
- image
lsst.afw.image.exposure.exposure.ExposureF
The image into which the fake sources should be added
- fakeCat
- Returns:
- fakeCat
pandas.core.frame.DataFrame
The original fakeCat trimmed to the area of the image
- fakeCat