IsrMock

class lsst.ip.isr.IsrMock(**kwargs)

Bases: Task

Class to generate consistent mock images for ISR testing.

ISR testing currently relies on one-off fake images that do not accurately mimic the full set of detector effects. This class uses the test camera/detector/amplifier structure defined in lsst.afw.cameraGeom.testUtils to avoid making the test data dependent on any of the actual obs package formats.

Methods Summary

amplifierAddFringe(amp, ampData, scale[, x0, y0])	Add a fringe-like ripple pattern to an amplifier's image data.
amplifierAddNoise(ampData, mean, sigma[, rng])	Add Gaussian noise to an amplifier's image data.
amplifierAddSource(ampData, scale, x0, y0)	Add a single Gaussian source to an amplifier.
amplifierAddYGradient(ampData, start, end)	Add a y-axis linear gradient to an amplifier's image data.
amplifierMultiplyFlat(amp, ampData, fracDrop)	Multiply an amplifier's image data by a flat-like pattern.
getCamera([isForAssembly])	Construct a test camera object.
getExposure([isTrimmed])	Construct a test exposure.
getWcs()	Construct a dummy WCS object.
localCoordToExpCoord(ampData, x, y)	Convert between a local amplifier coordinate and the full exposure coordinate.
makeBfKernel()	Generate a simple Gaussian brighter-fatter kernel.
makeCrosstalkCoeff()	Generate the simulated crosstalk coefficients.
makeData()	Generate simulated ISR data.
makeDefectList()	Generate a simple single-entry defect list.
makeDeferredChargeCalib()	Generate a CTI calibration.
makeElectrostaticBf()	Generate a simple Gaussian brighter-fatter kernel.
makeImage()	Generate a simulated ISR image.
makeLinearity()	Generate a linearity dataset.
makeTransmissionCurve()	Generate a simulated flat transmission curve.
run()	Generate a mock ISR product, and return it.

Methods Documentation

amplifierAddFringe(amp, ampData, scale, x0=100, y0=0)

Add a fringe-like ripple pattern to an amplifier’s image data.

Parameters

ampAmpInfoRecord

Amplifier to operate on. Needed for amp<->exp coordinate transforms.

ampDatalsst.afw.image.ImageF

Amplifier image to operate on.

scalenumpy.array or float

Peak intensity scaling for the ripple.

x0numpy.array or float, optional

Fringe center

y0numpy.array or float, optional

Fringe center

Notes

This uses an offset sinc function to generate a ripple pattern. True fringes have much finer structure, but this pattern should be visually identifiable. The (x, y) coordinates are in the frame of the amplifier, and (u, v) in the frame of the full trimmed image.

amplifierAddNoise(ampData, mean, sigma, rng=None)

Add Gaussian noise to an amplifier’s image data.

This method operates in the amplifier coordinate frame.

Parameters

ampDatalsst.afw.image.ImageF

Amplifier image to operate on.

meanfloat

Mean value of the Gaussian noise.

sigmafloat

Sigma of the Gaussian noise.

rngnp.random.RandomState, optional

Random state to use instead of self.rng.

amplifierAddSource(ampData, scale, x0, y0)

Add a single Gaussian source to an amplifier.

This method operates in the amplifier coordinate frame.

Parameters

ampDatalsst.afw.image.ImageF

Amplifier image to operate on.

scalefloat

Peak flux of the source to add.

x0float

X-coordinate of the source peak.

y0float

Y-coordinate of the source peak.

amplifierAddYGradient(ampData, start, end)

Add a y-axis linear gradient to an amplifier’s image data.

This method operates in the amplifier coordinate frame.

Parameters

ampDatalsst.afw.image.ImageF

Amplifier image to operate on.

startfloat

Start value of the gradient (at y=0).

endfloat

End value of the gradient (at y=ymax).

amplifierMultiplyFlat(amp, ampData, fracDrop, u0=100.0, v0=100.0)

Multiply an amplifier’s image data by a flat-like pattern.

Parameters

amplsst.afw.ampInfo.AmpInfoRecord

Amplifier to operate on. Needed for amp<->exp coordinate transforms.

ampDatalsst.afw.image.ImageF

Amplifier image to operate on.

fracDropfloat

Fractional drop from center to edge of detector along x-axis.

u0float

Peak location in detector coordinates.

v0float

Peak location in detector coordinates.

Notes

This uses a 2-d Gaussian to simulate an illumination pattern that falls off towards the edge of the detector. The (x, y) coordinates are in the frame of the amplifier, and (u, v) in the frame of the full trimmed image.

getCamera(isForAssembly=False)

Construct a test camera object.

Parameters

isForAssemblybool

If True, construct a camera with “super raw” orientation (all amplifiers have LL readout corner but still contains the necessary flip and offset info needed for assembly. This is needed if isLsstLike is True. If False, return a camera with bboxes flipped and offset to the correct orientation given the readout corner.

Returns

cameralsst.afw.cameraGeom.camera

Test camera.

getExposure(isTrimmed=None)

Construct a test exposure.

The test exposure has a simple WCS set, as well as a list of unlikely header keywords that can be removed during ISR processing to exercise that code.

Parameters

isTrimmedbool or None, optional

Override the configuration isTrimmed?

Returns

exposurelsst.afw.exposure.Exposure

Construct exposure containing masked image of the appropriate size.

getWcs()

Construct a dummy WCS object.

Taken from the deprecated ip_isr/examples/exampleUtils.py.

This is not guaranteed, given the distortion and pixel scale listed in the afwTestUtils camera definition.

Returns

wcslsst.afw.geom.SkyWcs

Test WCS transform.

localCoordToExpCoord(ampData, x, y)

Convert between a local amplifier coordinate and the full exposure coordinate.

Parameters

ampDatalsst.afw.image.ImageF

Amplifier image to use for conversions.

xint

X-coordinate of the point to transform.

yint

Y-coordinate of the point to transform.

Returns

uint

Transformed x-coordinate.

vint

Transformed y-coordinate.

Notes

The output is transposed intentionally here, to match the internal transpose between numpy and afw.image coordinates.

makeBfKernel()

Generate a simple Gaussian brighter-fatter kernel.

Returns

kernelnumpy.ndarray

Simulated brighter-fatter kernel.

makeCrosstalkCoeff()

Generate the simulated crosstalk coefficients.

Returns

coeffsnumpy.ndarray

Simulated crosstalk coefficients.

makeData()

Generate simulated ISR data.

Currently, only the class defined crosstalk coefficient matrix, brighter-fatter kernel, a constant unity transmission curve, or a simple single-entry defect list can be generated.

Returns

dataProduct :

Simulated ISR data product.

makeDefectList()

Generate a simple single-entry defect list.

Returns

defectListlsst.meas.algorithms.Defects

Simulated defect list

makeDeferredChargeCalib()

Generate a CTI calibration.

makeElectrostaticBf()

Generate a simple Gaussian brighter-fatter kernel.

Returns

kernelnumpy.ndarray

Simulated brighter-fatter kernel.

makeImage()

Generate a simulated ISR image.

Returns

exposurelsst.afw.image.Exposure or dict

Simulated ISR image data.

Notes

This method currently constructs a “raw” data image by:

• Generating a simulated sky with noise

• Adding a single Gaussian “star”

• Adding the fringe signal

• Multiplying the frame by the simulated flat

• Adding dark current (and noise)

• Adding a bias offset (and noise)

• Adding an overscan gradient parallel to the pixel y-axis

• Simulating crosstalk by adding a scaled version of each amplifier to each other amplifier.

The exposure with image data constructed this way is in one of three formats.

• A single image, with overscan and prescan regions retained

• A single image, with overscan and prescan regions trimmed

• A dict, containing the amplifer data indexed by the amplifier name.

The nonlinearity, CTE, and brighter fatter are currently not implemented.

Note that this method generates an image in the reverse direction as the ISR processing, as the output image here has had a series of instrument effects added to an idealized exposure.

makeLinearity()

Generate a linearity dataset.

Returns

linearizer : lsst.ip.isr.Linearizer

makeTransmissionCurve()

Generate a simulated flat transmission curve.

Returns

transmissionlsst.afw.image.TransmissionCurve

Simulated transmission curve.

run()

Generate a mock ISR product, and return it.

Returns

imagelsst.afw.image.Exposure

Simulated ISR image with signals added.

dataProduct :

Simulated ISR data products.

None :

Returned if no valid configuration was found.

Raises

RuntimeError

Raised if both doGenerateImage and doGenerateData are specified.