lsst.ip.diffim  17.0.1-12-g112a4bc
Public Member Functions | Static Public Member Functions | Public Attributes | Static Public Attributes | List of all members
lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelMapper Class Reference
Inheritance diagram for lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelMapper:
lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelTask lsst.ip.diffim.imageMapReduce.ImageMapper

Public Member Functions

def __init__ (self, args, kwargs)
 
def run (self, subExposure, expandedSubExposure, fullBBox, template, science, alTaskResult=None, psfMatchingKernel=None, preConvKernel=None, kwargs)
 
def computeVarianceMean (self, exposure)
 
def run (self, subExposure, expandedSubExposure, fullBBox, kwargs)
 

Static Public Member Functions

def computeCorrectedDiffimPsf (kappa, psf, svar=0.04, tvar=0.04)
 

Public Attributes

 statsControl
 

Static Public Attributes

 ConfigClass = DecorrelateALKernelConfig
 

Detailed Description

Task to be used as an ImageMapper for performing
A&L decorrelation on subimages on a grid across a A&L difference image.

This task subclasses DecorrelateALKernelTask in order to implement
all of that task's configuration parameters, as well as its `run` method.

Definition at line 429 of file imageDecorrelation.py.

Constructor & Destructor Documentation

◆ __init__()

def lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelMapper.__init__ (   self,
  args,
  kwargs 
)

Definition at line 440 of file imageDecorrelation.py.

Member Function Documentation

◆ computeCorrectedDiffimPsf()

def lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelTask.computeCorrectedDiffimPsf (   kappa,
  psf,
  svar = 0.04,
  tvar = 0.04 
)
staticinherited
Compute the (decorrelated) difference image's new PSF.
new_psf = psf(k) * sqrt((svar + tvar) / (svar + tvar * kappa_ft(k)**2))

Parameters
----------
kappa : `numpy.ndarray`
    A matching kernel array derived from Alard & Lupton PSF matching
psf : `numpy.ndarray`
    The uncorrected psf array of the science image (and also of the diffim)
svar : `float`, optional
    Average variance of science image used for PSF matching
tvar : `float`, optional
    Average variance of template image used for PSF matching

Returns
-------
pcf : `numpy.ndarray`
    a 2-d numpy.array containing the new PSF

Definition at line 293 of file imageDecorrelation.py.

◆ computeVarianceMean()

def lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelTask.computeVarianceMean (   self,
  exposure 
)
inherited

Definition at line 103 of file imageDecorrelation.py.

◆ run() [1/2]

def lsst.ip.diffim.imageMapReduce.ImageMapper.run (   self,
  subExposure,
  expandedSubExposure,
  fullBBox,
  kwargs 
)
inherited
Perform operation on `subExposure`.

To be implemented by subclasses. See class docstring for more
details. This method is given the `subExposure` which
is to be operated upon, and an `expandedSubExposure` which
will contain `subExposure` with additional surrounding
pixels. This allows for, for example, convolutions (which
should be performed on `expandedSubExposure`), to prevent the
returned sub-exposure from containing invalid pixels.

This method may return a new, processed sub-exposure which can
be be "stitched" back into a new resulting larger exposure
(depending on the paired, configured `ImageReducer`);
otherwise if it does not return an lsst.afw.image.Exposure, then the
`ImageReducer.config.mapper.reduceOperation`
should be set to 'none' and the result will be propagated
as-is.

Parameters
----------
subExposure : `lsst.afw.image.Exposure`
    the sub-exposure upon which to operate
expandedSubExposure : `lsst.afw.image.Exposure`
    the expanded sub-exposure upon which to operate
fullBBox : `lsst.afw.geom.BoundingBox`
    the bounding box of the original exposure
kwargs :
    additional keyword arguments propagated from
    `ImageMapReduceTask.run`.

Returns
-------
result : `lsst.pipe.base.Struct`
    A structure containing the result of the `subExposure` processing,
    which may itself be of any type. See above for details. If it is an
    `lsst.afw.image.Exposure` (processed sub-exposure), then the name in
    the Struct should be 'subExposure'. This is implemented here as a
    pass-through example only.

Definition at line 109 of file imageMapReduce.py.

◆ run() [2/2]

def lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelMapper.run (   self,
  subExposure,
  expandedSubExposure,
  fullBBox,
  template,
  science,
  alTaskResult = None,
  psfMatchingKernel = None,
  preConvKernel = None,
  kwargs 
)
Perform decorrelation operation on `subExposure`, using
`expandedSubExposure` to allow for invalid edge pixels arising from
convolutions.

This method performs A&L decorrelation on `subExposure` using
local measures for image variances and PSF. `subExposure` is a
sub-exposure of the non-decorrelated A&L diffim. It also
requires the corresponding sub-exposures of the template
(`template`) and science (`science`) exposures.

Parameters
----------
subExposure : `lsst.afw.image.Exposure`
    the sub-exposure of the diffim
expandedSubExposure : `lsst.afw.image.Exposure`
    the expanded sub-exposure upon which to operate
fullBBox : `lsst.afw.geom.BoundingBox`
    the bounding box of the original exposure
template : `lsst.afw.image.Exposure`
    the corresponding sub-exposure of the template exposure
science : `lsst.afw.image.Exposure`
    the corresponding sub-exposure of the science exposure
alTaskResult : `lsst.pipe.base.Struct`
    the result of A&L image differencing on `science` and
    `template`, importantly containing the resulting
    `psfMatchingKernel`. Can be `None`, only if
    `psfMatchingKernel` is not `None`.
psfMatchingKernel : Alternative parameter for passing the
    A&L `psfMatchingKernel` directly.
preConvKernel : If not None, then pre-filtering was applied
    to science exposure, and this is the pre-convolution
    kernel.
kwargs :
    additional keyword arguments propagated from
    `ImageMapReduceTask.run`.

Returns
-------
A `pipeBase.Struct` containing:

    - ``subExposure`` : the result of the `subExposure` processing.
    - ``decorrelationKernel`` : the decorrelation kernel, currently
not used.

Notes
-----
This `run` method accepts parameters identical to those of
`ImageMapper.run`, since it is called from the
`ImageMapperTask`. See that class for more information.

Definition at line 445 of file imageDecorrelation.py.

Member Data Documentation

◆ ConfigClass

lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelMapper.ConfigClass = DecorrelateALKernelConfig
static

Definition at line 437 of file imageDecorrelation.py.

◆ statsControl

lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelTask.statsControl
inherited

Definition at line 98 of file imageDecorrelation.py.


The documentation for this class was generated from the following file: