lsst.ip.diffim  15.0-5-g0db841d+1
Classes | Functions
lsst.ip.diffim.diffimTools Namespace Reference

Classes

class  NbasisEvaluator
 

Functions

def makeFlatNoiseImage (mi, seedStat=afwMath.MAX)
 Add noise. More...
 
def makePoissonNoiseImage (im)
 
def fakeCoeffs ()
 Make fake images for testing; one is a delta function (or narrow gaussian) and the other is a convolution of this with a spatially varying kernel. More...
 
def makeFakeKernelSet (sizeCell=128, nCell=3, deltaFunctionCounts=1.e4, tGaussianWidth=1.0, addNoise=True, bgValue=100., display=False)
 
def backgroundSubtract (config, maskedImages)
 Background subtraction for ip_diffim. More...
 
def writeKernelCellSet (kernelCellSet, psfMatchingKernel, backgroundModel, outdir)
 More coarse debugging. More...
 
def sourceToFootprintList (candidateInList, templateExposure, scienceExposure, kernelSize, config, log)
 Converting types. More...
 
def sourceTableToCandidateList (sourceTable, templateExposure, scienceExposure, kConfig, dConfig, log, basisList, doBuild=False)
 

Function Documentation

◆ backgroundSubtract()

def lsst.ip.diffim.diffimTools.backgroundSubtract (   config,
  maskedImages 
)

Background subtraction for ip_diffim.

Definition at line 231 of file diffimTools.py.

◆ fakeCoeffs()

def lsst.ip.diffim.diffimTools.fakeCoeffs ( )

Make fake images for testing; one is a delta function (or narrow gaussian) and the other is a convolution of this with a spatially varying kernel.

Definition at line 90 of file diffimTools.py.

◆ makeFakeKernelSet()

def lsst.ip.diffim.diffimTools.makeFakeKernelSet (   sizeCell = 128,
  nCell = 3,
  deltaFunctionCounts = 1.e4,
  tGaussianWidth = 1.0,
  addNoise = True,
  bgValue = 100.,
  display = False 
)

Definition at line 102 of file diffimTools.py.

◆ makeFlatNoiseImage()

def lsst.ip.diffim.diffimTools.makeFlatNoiseImage (   mi,
  seedStat = afwMath.MAX 
)

Add noise.

Definition at line 52 of file diffimTools.py.

◆ makePoissonNoiseImage()

def lsst.ip.diffim.diffimTools.makePoissonNoiseImage (   im)
Return a Poisson noise image based on im

Uses numpy.random; you may wish to call numpy.random.seed first.

@warning This uses an undocumented numpy API (the documented API
uses a single float expectation value instead of an array).

@param[in] im image; the output image has the same dimensions and shape
    and its expectation value is the value of im at each pixel

Definition at line 61 of file diffimTools.py.

◆ sourceTableToCandidateList()

def lsst.ip.diffim.diffimTools.sourceTableToCandidateList (   sourceTable,
  templateExposure,
  scienceExposure,
  kConfig,
  dConfig,
  log,
  basisList,
  doBuild = False 
)
Takes an input list of Sources, and turns them into
KernelCandidates for fitting of the Psf-matching kernel.

Definition at line 367 of file diffimTools.py.

◆ sourceToFootprintList()

def lsst.ip.diffim.diffimTools.sourceToFootprintList (   candidateInList,
  templateExposure,
  scienceExposure,
  kernelSize,
  config,
  log 
)

Converting types.

Takes an input list of Sources that were selected to constrain
the Psf-matching Kernel and turns them into a List of Footprints,
which are used to seed a set of KernelCandidates.  The function
checks both the template and science image for masked pixels,
rejecting the Source if certain Mask bits (defined in config) are
set within the Footprint.

@param candidateInList: Input list of Sources
@param templateExposure: Template image, to be checked for Mask bits in Source Footprint
@param scienceExposure: Science image, to be checked for Mask bits in Source Footprint
@param config: Config that defines the Mask planes that indicate an invalid Source and Bbox grow radius
@param log: Log for output

@return a list of dicts having a "source" and "footprint" field, to be used for Psf-matching

Definition at line 287 of file diffimTools.py.

◆ writeKernelCellSet()

def lsst.ip.diffim.diffimTools.writeKernelCellSet (   kernelCellSet,
  psfMatchingKernel,
  backgroundModel,
  outdir 
)

More coarse debugging.

Definition at line 259 of file diffimTools.py.