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.

Subtract the background from masked images.

Parameters
----------
config : TODO: DM-17458
    TODO: DM-17458
maskedImages : `list` of `lsst.afw.image.MaskedImage`
    TODO: DM-17458

Returns
-------
TODO: DM-17458
    TODO: DM-17458

Definition at line 263 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 99 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`
	)

TODO: DM-17458

Parameters
----------
sizeCell : `int`, optional
    TODO: DM-17458
nCell : `int`, optional
    TODO: DM-17458
deltaFunctionCounts : `float`, optional
    TODO: DM-17458
tGaussianWidth : `float`, optional
    TODO: DM-17458
addNoise : `bool`, optional
    TODO: DM-17458
bgValue : `float`, optional
    TODO: DM-17458
display : `bool`, optional
    TODO: DM-17458

Returns
-------
TODO: DM-17458
    TODO: DM-17458

Definition at line 111 of file diffimTools.py.

◆ makeFlatNoiseImage()

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

Add noise.

Definition at line 51 of file diffimTools.py.

◆ makePoissonNoiseImage()

def lsst.ip.diffim.diffimTools.makePoissonNoiseImage ( im )

Return a Poisson noise image based on im

Parameters
----------
im : `lsst.afw.image.Image`
    image; the output image has the same dimensions and shape
    and its expectation value is the value of ``im`` at each pixel

Returns
-------
noiseIm : `lsst.afw.image.Image`
    TODO: DM-17458

Notes
-----
- Warning: This uses an undocumented numpy API (the documented API
    uses a single float expectation value instead of an array).

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

Definition at line 60 of file diffimTools.py.

◆ sourceTableToCandidateList()

def lsst.ip.diffim.diffimTools.sourceTableToCandidateList	(	sourceTable,
		templateExposure,
		scienceExposure,
		kConfig,
		dConfig,
		log,
		basisList,
		doBuild = `False`
	)

Convert a list of Sources into KernelCandidates.

The KernelCandidates are used for fitting the Psf-matching kernel.

Parameters
----------
sourceTable : TODO: DM-17458
    TODO: DM-17458
templateExposure : TODO: DM-17458
    TODO: DM-17458
scienceExposure : TODO: DM-17458
    TODO: DM-17458
kConfig : TODO: DM-17458
    TODO: DM-17458
dConfig : TODO: DM-17458
    TODO: DM-17458
log : TODO: DM-17458
    TODO: DM-17458
basisList : TODO: DM-17458
    TODO: DM-17458
doBuild : `bool`, optional
    TODO: DM-17458

Returns
-------
TODO: DM-17458
    TODO: DM-17458

Definition at line 447 of file diffimTools.py.

◆ sourceToFootprintList()

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

Converting types.

Convert a list of sources for the PSF-matching Kernel to Footprints.

Parameters
----------
candidateInList : TODO: DM-17458
    Input list of Sources
templateExposure : TODO: DM-17458
    Template image, to be checked for Mask bits in Source Footprint
scienceExposure : TODO: DM-17458
    Science image, to be checked for Mask bits in Source Footprint
kernelSize : TODO: DM-17458
    TODO: DM-17458
config : TODO: DM-17458
    Config that defines the Mask planes that indicate an invalid Source and Bbox grow radius
log : TODO: DM-17458
    Log for output

Returns
-------
candidateOutList : `list`
    a list of dicts having a "source" and "footprint" field, to be used for Psf-matching

Raises
------
RuntimeError
    TODO: DM-17458

Notes
-----
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.

Definition at line 346 of file diffimTools.py.

◆ writeKernelCellSet()

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

More coarse debugging.

TODO: DM-17458

Parameters
----------
kernelCellSet : TODO: DM-17458
    TODO: DM-17458
psfMatchingKernel : TODO: DM-17458
    TODO: DM-17458
backgroundModel : TODO: DM-17458
    TODO: DM-17458
outdir : TODO: DM-17458
    TODO: DM-17458

Definition at line 305 of file diffimTools.py.

Classes

Functions