CrosstalkCalib¶
- class lsst.ip.isr.CrosstalkCalib(detector=None, nAmp=0, **kwargs)¶
Bases:
IsrCalib
Calibration of amp-to-amp crosstalk coefficients.
- Parameters:
- detector
lsst.afw.cameraGeom.Detector
, optional Detector to use to pull coefficients from.
- nAmp
int
, optional Number of amplifiers to initialize.
- log
logging.Logger
, optional Log to write messages to.
- **kwargs
Parameters to pass to parent constructor.
- detector
Notes
The crosstalk attributes stored are:
- hasCrosstalk
bool
Whether there is crosstalk defined for this detector.
- nAmp
int
Number of amplifiers in this detector.
- crosstalkShape
tuple
[int
,int
] A tuple containing the shape of the
coeffs
matrix. This should be equivalent to (nAmp
,nAmp
).- coeffs
numpy.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).
- coeffErr
numpy.ndarray
, optional A matrix (as defined by
coeffs
) containing the standard distribution of the crosstalk measurements.- coeffNum
numpy.ndarray
, optional A matrix containing the number of pixel pairs used to measure the
coeffs
andcoeffErr
.- coeffValid
numpy.ndarray
, optional A matrix of Boolean values indicating if the coefficient is valid, defined as abs(coeff) > coeffErr / sqrt(coeffNum).
- coeffsSqr
numpy.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).
- coeffErrSqr
numpy.ndarray
, optional A matrix (as defined by
coeffsSqr
) containing the standard distribution of the quadratic term of the crosstalk measurements.- interChip
dict
[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
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.
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.
- 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.
- 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:
- dictionary
dict
orlsst.daf.base.PropertyList
Source for the common keywords.
- dictionary
- Raises:
- RuntimeError
Raised if the dictionary does not match the expected OBSTYPE.
- classmethod determineCalibClass(metadata, message)¶
Attempt to find calibration class in metadata.
- Parameters:
- Returns:
- calibClass
object
The class to use to read the file contents. Should be an
lsst.ip.isr.IsrCalib
subclass.
- calibClass
- 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:
- image
lsst.afw.image.Image
orlsst.afw.image.MaskedImage
Image containing the amplifier of interest.
- amp
lsst.afw.cameraGeom.Amplifier
Amplifier on image to extract.
- ampTarget
lsst.afw.cameraGeom.Amplifier
Target amplifier that the extracted image will be flipped to match.
- isTrimmed
bool
, optional The image is already trimmed. TODO : DM-15409 will resolve this.
- fullAmplifier
bool
, optional Use full amplifier and not just imaging region.
- parallelOverscan
bool
, optional Extract parallel overscan region instead of imaging region. Cannot be used if isTrimmed or fullAmplifier True.
- image
- Returns:
- output
lsst.afw.image.Image
Image of the amplifier in the desired configuration.
- output
- fromDetector(detector, coeffVector=None, coeffSqrVector=None)¶
Set calibration parameters from the detector.
- Parameters:
- detector
lsst.afw.cameraGeom.Detector
Detector to use to set parameters from.
- coeffVector
numpy.array
, optional Use the detector geometry (bounding boxes and flip information), but use
coeffVector
instead of the output ofdetector.getCrosstalk()
.- coeffSqrVector
numpy.array
, optional Quadratic crosstalk coefficients.
- detector
- Returns:
- calib
lsst.ip.isr.CrosstalkCalib
The calibration constructed from the detector.
- calib
- classmethod fromDict(dictionary)¶
Construct a calibration from a dictionary of properties.
Must be implemented by the specific calibration subclasses.
- Parameters:
- dictionary
dict
Dictionary of properties.
- dictionary
- Returns:
- calib
lsst.ip.isr.CalibType
Constructed calibration.
- calib
- 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:
- tableList
list
[lsst.afw.table.Table
] List of tables to use to construct the crosstalk calibration.
- tableList
- Returns:
- calib
lsst.ip.isr.CrosstalkCalib
The calibration defined in the tables.
- calib
- getMetadata()¶
Retrieve metadata associated with this calibration.
- Returns:
- meta
lsst.daf.base.PropertyList
Metadata. The returned
PropertyList
can be modified by the caller and the changes will be written to external files.
- meta
- classmethod readFits(filename, **kwargs)¶
Read calibration data from a FITS file.
- Parameters:
- Returns:
- calib
lsst.ip.isr.IsrCalib
Calibration contained within the file.
- calib
- classmethod readText(filename, **kwargs)¶
Read calibration representation from a yaml/ecsv file.
- Parameters:
- Returns:
- calib
IsrCalibType
Calibration class.
- calib
- 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:
- metadata
lsst.daf.base.PropertyList
Metadata to associate with the calibration. Will be copied and overwrite existing metadata.
- 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 exceedminPixelToMask
, ifdoSubtrahendMasking
is False. With that enabled, the mask is only set if the absolute value of the correction applied exceedsminPixelToMask
. Note that the correction is applied to all pixels in the amplifier, but only those that have a substantial crosstalk are masked withcrosstalkStr
.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:
- thisExposure
lsst.afw.image.Exposure
Exposure for which to subtract crosstalk.
- sourceExposure
lsst.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).
- crosstalkCoeffs
numpy.ndarray
, optional. Coefficients to use to correct crosstalk.
- crosstalkCoeffsSqr
numpy.ndarray
, optional. Quadratic coefficients to use to correct crosstalk.
- crosstalkCoeffsValid
numpy.ndarray
, optional Boolean array that is True where coefficients are valid.
- badPixels
list
ofstr
, optional Mask planes to ignore.
- minPixelToMask
float
, optional Minimum pixel value to set the
crosstalkStr
mask plane. If doSubtrahendMasking is True, this is calculated from the absolute magnitude of the subtrahend image. Otherwise, this sets the minimum source value to use to set that mask.- doSubtrahendMasking
bool
, optional If true, the mask is calculated from the properties of the subtrahend image, not from the brightness of the source pixel.
- crosstalkStr
str
, optional Mask plane name for pixels greatly modified by crosstalk (above minPixelToMask).
- isTrimmed
bool
, optional The image is already trimmed. This should no longer be needed once DM-15409 is resolved.
- backgroundMethod
str
, 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?
- fullAmplifier
bool
, optional Use full amplifier and not just imaging region.
- parallelOverscan
bool
, optional Only correct the parallel overscan region.
- detectorConfig
lsst.ip.isr.overscanDetectorConfig
, optional Per-amplifier configs to use if parallelOverscan is True.
- badAmpDict
dict
[str
,bool
], optional Dictionary to identify bad amplifiers that should not be source or target for crosstalk correction.
- thisExposure
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:
- dictionary
dict
Dictionary of properties.
- dictionary
- 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:
- tableList
list
[lsst.afw.table.Table
] List of tables containing the crosstalk calibration information.
- tableList
- updateMetadata(setDate=False, **kwargs)¶
Update calibration metadata.
This calls the base class’s method after ensuring the required calibration keywords will be saved.
- Parameters:
- setDate
bool
, optional Update the CALIBDATE fields in the metadata to the current time. Defaults to False.
- kwargs
Other keyword parameters to set in the metadata.
- setDate
- updateMetadataFromExposures(exposures)¶
Extract and unify metadata information.
- Parameters:
- exposures
list
Exposures or other calibrations to scan.
- exposures
- validate(other=None)¶
Validate that this calibration is defined and can be used.
- writeFits(filename)¶
Write calibration data to a FITS file.
- writeText(filename, format='auto')¶
Write the calibration data to a text file.
- Parameters:
- Returns:
- used
str
The name of the file used to write the data. This may differ from the input if the format is explicitly chosen.
- used
- 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.