CrosstalkCalib

class lsst.ip.isr.CrosstalkCalib(detector=None, nAmp=0, **kwargs)

Bases: IsrCalib

Calibration of amp-to-amp crosstalk coefficients.

Parameters:

detectorlsst.afw.cameraGeom.Detector, optional

Detector to use to pull coefficients from.

nAmpint, optional

Number of amplifiers to initialize.

loglogging.Logger, optional

Log to write messages to.

**kwargs

Parameters to pass to parent constructor.

Notes

The crosstalk attributes stored are:

hasCrosstalkbool

Whether there is crosstalk defined for this detector.

nAmpint

Number of amplifiers in this detector.

crosstalkShapetuple [int, int]

A tuple containing the shape of the coeffs matrix. This should be equivalent to (nAmp, nAmp).

coeffsnumpy.ndarray

A matrix containing the crosstalk coefficients. coeff[i][j] contains the coefficients to calculate the contribution amplifier_j has on amplifier_i (each row[i] contains the corrections for detector_i).

coeffErrnumpy.ndarray, optional

A matrix (as defined by coeffs) containing the standard distribution of the crosstalk measurements.

coeffNumnumpy.ndarray, optional

A matrix containing the number of pixel pairs used to measure the coeffs and coeffErr.

coeffValidnumpy.ndarray, optional

A matrix of Boolean values indicating if the coefficient is valid, defined as abs(coeff) > coeffErr / sqrt(coeffNum).

coeffsSqrnumpy.ndarray, optional

A matrix containing potential quadratic crosstalk coefficients (see e.g., Snyder+21, 2001.03223). coeffsSqr[i][j] contains the coefficients to calculate the contribution amplifier_j has on amplifier_i (each row[i] contains the corrections for detector_i).

coeffErrSqrnumpy.ndarray, optional

A matrix (as defined by coeffsSqr) containing the standard distribution of the quadratic term of the crosstalk measurements.

interChipdict [numpy.ndarray]

A dictionary keyed by detectorName containing coeffs matrices used to correct for inter-chip crosstalk with a source on the detector indicated.

Version 1.1 adds quadratic coefficients, a matrix with the ratios of amplifiers gains per detector, and a field to indicate the units of the numerator and denominator of the source and target signals, with “adu” meaning “ADU / ADU” and “electron” meaning “e- / e-“.

Version 1.2 adds the original gains used in the crosstalk fit.

Attributes Summary

metadata
requiredAttributes

Methods Summary

apply(target)	Method to apply the calibration to the target object.
calculateBackground(mi[, badPixels])	Estimate median background in image.
calibInfoFromDict(dictionary)	Handle common keywords.
determineCalibClass(metadata, message)	Attempt to find calibration class in metadata.
extractAmp(image, amp, ampTarget[, ...])	Extract the image data from an amp, flipped to match ampTarget.
fromDetector(detector[, coeffVector, ...])	Set calibration parameters from the detector.
fromDict(dictionary)	Construct a calibration from a dictionary of properties.
fromTable(tableList)	Construct calibration from a list of tables.
getMetadata()	Retrieve metadata associated with this calibration.
readFits(filename, **kwargs)	Read calibration data from a FITS file.
readText(filename, **kwargs)	Read calibration representation from a yaml/ecsv file.
setMetadata(metadata)	Store a copy of the supplied metadata with this calibration.
subtractCrosstalk(thisExposure[, ...])	Subtract the crosstalk from thisExposure, optionally using a different source.
toDict()	Return a dictionary containing the calibration properties.
toTable()	Construct a list of tables containing the information in this calibration.
updateMetadata([setDate])	Update calibration metadata.
updateMetadataFromExposures(exposures)	Extract and unify metadata information.
validate([other])	Validate that this calibration is defined and can be used.
writeFits(filename)	Write calibration data to a FITS file.
writeText(filename[, format])	Write the calibration data to a text file.

Attributes Documentation

metadata

requiredAttributes

Methods Documentation

apply(target)

Method to apply the calibration to the target object.

Parameters:

targetobject

Thing to validate against.

Returns:

validbool

Returns true if the calibration was applied correctly.

Raises:

NotImplementedError

Raised if not implemented.

static calculateBackground(mi, badPixels=['BAD'])

Estimate median background in image.

Getting a great background model isn’t important for crosstalk correction, since the crosstalk is at a low level. The median should be sufficient.

Parameters:

milsst.afw.image.MaskedImage

MaskedImage for which to measure background.

badPixelslist of str

Mask planes to ignore.

Returns

——-

bgfloat

Median background level.

calibInfoFromDict(dictionary)

Handle common keywords.

This isn’t an ideal solution, but until all calibrations expect to find everything in the metadata, they still need to search through dictionaries.

Parameters:

dictionarydict or lsst.daf.base.PropertyList

Source for the common keywords.

Raises:

RuntimeError

Raised if the dictionary does not match the expected OBSTYPE.

classmethod determineCalibClass(metadata, message)

Attempt to find calibration class in metadata.

Parameters:

metadatadict or lsst.daf.base.PropertyList

Metadata possibly containing a calibration class entry.

messagestr

Message to include in any errors.

Returns:

calibClassobject

The class to use to read the file contents. Should be an lsst.ip.isr.IsrCalib subclass.

Raises:

ValueError

Raised if the resulting calibClass is the base lsst.ip.isr.IsrClass (which does not implement the content methods).

static extractAmp(image, amp, ampTarget, isTrimmed=False, fullAmplifier=False, parallelOverscan=False)

Extract the image data from an amp, flipped to match ampTarget.

Parameters:

imagelsst.afw.image.Image or lsst.afw.image.MaskedImage

Image containing the amplifier of interest.

amplsst.afw.cameraGeom.Amplifier

Amplifier on image to extract.

ampTargetlsst.afw.cameraGeom.Amplifier

Target amplifier that the extracted image will be flipped to match.

isTrimmedbool, optional

The image is already trimmed. TODO : DM-15409 will resolve this.

fullAmplifierbool, optional

Use full amplifier and not just imaging region.

parallelOverscanbool, optional

Extract parallel overscan region instead of imaging region. Cannot be used if isTrimmed or fullAmplifier True.

Returns:

outputlsst.afw.image.Image

Image of the amplifier in the desired configuration.

fromDetector(detector, coeffVector=None, coeffSqrVector=None)

Set calibration parameters from the detector.

Parameters:

detectorlsst.afw.cameraGeom.Detector

Detector to use to set parameters from.

coeffVectornumpy.array, optional

Use the detector geometry (bounding boxes and flip information), but use coeffVector instead of the output of detector.getCrosstalk().

coeffSqrVectornumpy.array, optional

Quadratic crosstalk coefficients.

Returns:

caliblsst.ip.isr.CrosstalkCalib

The calibration constructed from the detector.

classmethod fromDict(dictionary)

Construct a calibration from a dictionary of properties.

Must be implemented by the specific calibration subclasses.

Parameters:

dictionarydict

Dictionary of properties.

Returns:

caliblsst.ip.isr.CalibType

Constructed calibration.

Raises:

RuntimeError

Raised if the supplied dictionary is for a different calibration.

classmethod fromTable(tableList)

Construct calibration from a list of tables.

This method uses the fromDict method to create the calibration, after constructing an appropriate dictionary from the input tables.

Parameters:

tableListlist [lsst.afw.table.Table]

List of tables to use to construct the crosstalk calibration.

Returns:

caliblsst.ip.isr.CrosstalkCalib

The calibration defined in the tables.

getMetadata()

Retrieve metadata associated with this calibration.

Returns:

metalsst.daf.base.PropertyList

Metadata. The returned PropertyList can be modified by the caller and the changes will be written to external files.

classmethod readFits(filename, **kwargs)

Read calibration data from a FITS file.

Parameters:

filenamestr

Filename to read data from.

kwargsdict or collections.abc.Mapping`, optional

Set of key=value pairs to pass to the fromTable method.

Returns:

caliblsst.ip.isr.IsrCalib

Calibration contained within the file.

classmethod readText(filename, **kwargs)

Read calibration representation from a yaml/ecsv file.

Parameters:

filenamestr

Name of the file containing the calibration definition.

kwargsdict or collections.abc.Mapping`, optional

Set of key=value pairs to pass to the fromDict or fromTable methods.

Returns:

calibIsrCalibType

Calibration class.

Raises:

RuntimeError

Raised if the filename does not end in “.ecsv” or “.yaml”.

setMetadata(metadata)

Store a copy of the supplied metadata with this calibration.

Parameters:

metadatalsst.daf.base.PropertyList

Metadata to associate with the calibration. Will be copied and overwrite existing metadata.

subtractCrosstalk(thisExposure, sourceExposure=None, crosstalkCoeffs=None, crosstalkCoeffsSqr=None, crosstalkCoeffsValid=None, badPixels=['BAD'], minPixelToMask=45000, doSubtrahendMasking=False, crosstalkStr='CROSSTALK', isTrimmed=False, backgroundMethod='None', doSqrCrosstalk=False, fullAmplifier=False, parallelOverscan=False, detectorConfig=None, badAmpDict=None)

Subtract the crosstalk from thisExposure, optionally using a different source.

We set the mask plane indicated by crosstalkStr in a target amplifier for pixels in a source amplifier that exceed minPixelToMask. Note that the correction is applied to all pixels in the amplifier, but only those that have a substantial crosstalk are masked with crosstalkStr.

The uncorrected image is used as a template for correction. This is good enough if the crosstalk is small (e.g., coefficients < ~ 1e-3), but if it’s larger you may want to iterate.

Parameters:

thisExposurelsst.afw.image.Exposure

Exposure for which to subtract crosstalk.

sourceExposurelsst.afw.image.Exposure, optional

Exposure to use as the source of the crosstalk. If not set, thisExposure is used as the source (intra-detector crosstalk).

crosstalkCoeffsnumpy.ndarray, optional.

Coefficients to use to correct crosstalk.

crosstalkCoeffsSqrnumpy.ndarray, optional.

Quadratic coefficients to use to correct crosstalk.

crosstalkCoeffsValidnumpy.ndarray, optional

Boolean array that is True where coefficients are valid.

badPixelslist of str, optional

Mask planes to ignore.

minPixelToMaskfloat, optional

Minimum pixel value (relative to the background level) in source amplifier for which to set crosstalkStr mask plane in target amplifier.

crosstalkStrstr, optional

Mask plane name for pixels greatly modified by crosstalk (above minPixelToMask).

isTrimmedbool, optional

The image is already trimmed. This should no longer be needed once DM-15409 is resolved.

backgroundMethodstr, optional

Method used to subtract the background. “AMP” uses amplifier-by-amplifier background levels, “DETECTOR” uses full exposure/maskedImage levels. Any other value results in no background subtraction.

doSqrCrosstalk: `bool`, optional

Should the quadratic crosstalk coefficients be used for the crosstalk correction?

fullAmplifierbool, optional

Use full amplifier and not just imaging region.

parallelOverscanbool, optional

Only correct the parallel overscan region.

detectorConfiglsst.ip.isr.overscanDetectorConfig, optional

Per-amplifier configs to use if parallelOverscan is True.

badAmpDictdict [str, bool], optional

Dictionary to identify bad amplifiers that should not be source or target for crosstalk correction.

Notes

For a given image I, we want to find the crosstalk subtrahend image CT, such that

I_corrected = I - CT

The subtrahend image is the sum of all crosstalk contributions that appear in I, so we can build it up by amplifier. Each amplifier A in image I sees the contributions from all other amplifiers B_v != A. For the current linear model, we set sImage equal to the segment of the subtrahend image CT corresponding to amplifier A, and then build it up as: simage_linear = sum_v coeffsA_v * (B_v - bkg_v) where coeffsA_v is the vector of crosstalk coefficients for sources that cause images in amplifier A. The bkg_v term in this equation is identically 0.0 for all cameras except obs_subaru (and is only non-zero there for historical reasons). To include the non-linear term, we can again add to the subtrahend image using the same loop, as:

simage_nonlinear = sum_v (coeffsA_v * B_v) + (NLcoeffsA_v * B_v * B_v)

= sum_v linear_term_v + nonlinear_term_v

where coeffsA_v is the linear term, and NLcoeffsA_v are the quadratic component. For LSSTCam, it has been observed that the linear_term_v >> nonlinear_term_v.

toDict()

Return a dictionary containing the calibration properties.

The dictionary should be able to be round-tripped through fromDict.

Returns:

dictionarydict

Dictionary of properties.

toTable()

Construct a list of tables containing the information in this calibration.

The list of tables should create an identical calibration after being passed to this class’s fromTable method.

Returns:

tableListlist [lsst.afw.table.Table]

List of tables containing the crosstalk calibration information.

updateMetadata(setDate=False, **kwargs)

Update calibration metadata.

This calls the base class’s method after ensuring the required calibration keywords will be saved.

Parameters:

setDatebool, optional

Update the CALIBDATE fields in the metadata to the current time. Defaults to False.

kwargs

Other keyword parameters to set in the metadata.

updateMetadataFromExposures(exposures)

Extract and unify metadata information.

Parameters:

exposureslist

Exposures or other calibrations to scan.

validate(other=None)

Validate that this calibration is defined and can be used.

Parameters:

otherobject, optional

Thing to validate against.

Returns:

validbool

Returns true if the calibration is valid and appropriate.

writeFits(filename)

Write calibration data to a FITS file.

Parameters:

filenamestr

Filename to write data to.

Returns:

usedstr

The name of the file used to write the data.

writeText(filename, format='auto')

Write the calibration data to a text file.

Parameters:

filenamestr

Name of the file to write.

formatstr

Format to write the file as. Supported values are:

"auto" : Determine filetype from filename. "yaml" : Write as yaml. "ecsv" : Write as ecsv.

Returns:

usedstr

The name of the file used to write the data. This may differ from the input if the format is explicitly chosen.

Raises:

RuntimeError

Raised if filename does not end in a known extension, or if all information cannot be written.

Notes

The file is written to YAML/ECSV format and will include any associated metadata.