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Overscan refactor cleanup.
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@czwa
czwa committed Aug 5, 2022
1 parent 50e57b6 commit 3fae353
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112 changes: 11 additions & 101 deletions python/lsst/ip/isr/isrTask.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,7 @@
from contextlib import contextmanager
from lsstDebug import getDebugFrame

from lsst.afw.cameraGeom import NullLinearityType, ReadoutCorner
from lsst.afw.cameraGeom import NullLinearityType
from lsst.afw.display import getDisplay
from lsst.meas.algorithms.detection import SourceDetectionTask
from lsst.utils.timer import timeMethod
Expand Down Expand Up @@ -462,85 +462,6 @@ class IsrTaskConfig(pipeBase.PipelineTaskConfig,
target=OverscanCorrectionTask,
doc="Overscan subtraction task for image segments.",
)
overscanFitType = pexConfig.ChoiceField(
dtype=str,
doc="The method for fitting the overscan bias level.",
default='MEDIAN',
allowed={
"POLY": "Fit ordinary polynomial to the longest axis of the overscan region",
"CHEB": "Fit Chebyshev polynomial to the longest axis of the overscan region",
"LEG": "Fit Legendre polynomial to the longest axis of the overscan region",
"NATURAL_SPLINE": "Fit natural spline to the longest axis of the overscan region",
"CUBIC_SPLINE": "Fit cubic spline to the longest axis of the overscan region",
"AKIMA_SPLINE": "Fit Akima spline to the longest axis of the overscan region",
"MEAN": "Correct using the mean of the overscan region",
"MEANCLIP": "Correct using a clipped mean of the overscan region",
"MEDIAN": "Correct using the median of the overscan region",
"MEDIAN_PER_ROW": "Correct using the median per row of the overscan region",
},
deprecated=("Please configure overscan via the OverscanCorrectionConfig interface."
" This option will no longer be used, and will be removed after v20.")
)
overscanOrder = pexConfig.Field(
dtype=int,
doc=("Order of polynomial or to fit if overscan fit type is a polynomial, "
"or number of spline knots if overscan fit type is a spline."),
default=1,
deprecated=("Please configure overscan via the OverscanCorrectionConfig interface."
" This option will no longer be used, and will be removed after v20.")
)
overscanNumSigmaClip = pexConfig.Field(
dtype=float,
doc="Rejection threshold (sigma) for collapsing overscan before fit",
default=3.0,
deprecated=("Please configure overscan via the OverscanCorrectionConfig interface."
" This option will no longer be used, and will be removed after v20.")
)
overscanIsInt = pexConfig.Field(
dtype=bool,
doc="Treat overscan as an integer image for purposes of overscan.FitType=MEDIAN"
" and overscan.FitType=MEDIAN_PER_ROW.",
default=True,
deprecated=("Please configure overscan via the OverscanCorrectionConfig interface."
" This option will no longer be used, and will be removed after v20.")
)
# These options do not get deprecated, as they define how we slice up the
# image data.
overscanNumLeadingColumnsToSkip = pexConfig.Field(
dtype=int,
doc="Number of columns to skip in overscan, i.e. those closest to amplifier",
default=0,
)
overscanNumTrailingColumnsToSkip = pexConfig.Field(
dtype=int,
doc="Number of columns to skip in overscan, i.e. those farthest from amplifier",
default=0,
)
overscanMaxDev = pexConfig.Field(
dtype=float,
doc="Maximum deviation from the median for overscan",
default=1000.0, check=lambda x: x > 0
)
overscanBiasJump = pexConfig.Field(
dtype=bool,
doc="Fit the overscan in a piecewise-fashion to correct for bias jumps?",
default=False,
)
overscanBiasJumpKeyword = pexConfig.Field(
dtype=str,
doc="Header keyword containing information about devices.",
default="NO_SUCH_KEY",
)
overscanBiasJumpDevices = pexConfig.ListField(
dtype=str,
doc="List of devices that need piecewise overscan correction.",
default=(),
)
overscanBiasJumpLocation = pexConfig.Field(
dtype=int,
doc="Location of bias jump along y-axis.",
default=0,
)

# Amplifier to CCD assembly configuration
doAssembleCcd = pexConfig.Field(
Expand Down Expand Up @@ -1326,30 +1247,18 @@ def run(self, ccdExposure, *, camera=None, bias=None, linearizer=None,
self.log.debug("Corrected overscan for amplifier %s.", amp.getName())
if overscanResults is not None and \
self.config.qa is not None and self.config.qa.saveStats is True:
if isinstance(overscanResults.overscanFit, float):
qaMedian = overscanResults.overscanFit
qaStdev = float("NaN")
else:
qaStats = afwMath.makeStatistics(overscanResults.overscanFit,
afwMath.MEDIAN | afwMath.STDEVCLIP)
qaMedian = qaStats.getValue(afwMath.MEDIAN)
qaStdev = qaStats.getValue(afwMath.STDEVCLIP)

self.metadata[f"FIT MEDIAN {amp.getName()}"] = qaMedian
self.metadata[f"FIT STDEV {amp.getName()}"] = qaStdev
self.metadata[f"FIT MEDIAN {amp.getName()}"] = overscanResults.overscanMean
self.metadata[f"FIT STDEV {amp.getName()}"] = overscanResults.overscanSigma
self.log.debug(" Overscan stats for amplifer %s: %f +/- %f",
amp.getName(), qaMedian, qaStdev)

# Residuals after overscan correction
qaStatsAfter = afwMath.makeStatistics(overscanResults.overscanImage,
afwMath.MEDIAN | afwMath.STDEVCLIP)
qaMedianAfter = qaStatsAfter.getValue(afwMath.MEDIAN)
qaStdevAfter = qaStatsAfter.getValue(afwMath.STDEVCLIP)
amp.getName(), overscanResults.overscanMean,
overscanResults.overscanSigma)

self.metadata[f"RESIDUAL MEDIAN {amp.getName()}"] = qaMedianAfter
self.metadata[f"RESIDUAL STDEV {amp.getName()}"] = qaStdevAfter
self.metadata[f"RESIDUAL MEDIAN {amp.getName()}"] = overscanResults.residualMean
self.metadata[f"RESIDUAL STDEV {amp.getName()}"] = overscanResults.residualSigma
self.log.debug(" Overscan stats for amplifer %s after correction: %f +/- %f",
amp.getName(), qaMedianAfter, qaStdevAfter)
amp.getName(), overscanResults.residualMean,
overscanResults.residualSigma)

ccdExposure.getMetadata().set('OVERSCAN', "Overscan corrected")
else:
Expand Down Expand Up @@ -1923,7 +1832,8 @@ def updateVariance(self, ampExposure, amp, overscanImage=None, ptcDataset=None):
if self.config.doEmpiricalReadNoise and overscanImage is not None:
stats = afwMath.StatisticsControl()
stats.setAndMask(overscanImage.mask.getPlaneBitMask(maskPlanes))
readNoise = afwMath.makeStatistics(overscanImage, afwMath.STDEVCLIP, stats).getValue()
readNoise = afwMath.makeStatistics(overscanImage.getImage(),
afwMath.STDEVCLIP, stats).getValue()
self.log.info("Calculated empirical read noise for amp %s: %f.",
amp.getName(), readNoise)
elif self.config.usePtcReadNoise:
Expand Down
22 changes: 0 additions & 22 deletions python/lsst/ip/isr/overscan.py
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Original file line number Diff line number Diff line change
Expand Up @@ -453,7 +453,6 @@ def measureConstantOverscan(self, image):
overscanValue = afwMath.makeStatistics(calcImage, fitType, self.statControl).getValue()

return pipeBase.Struct(overscanValue=overscanValue,
maskArray=None,
isTransposed=False)

# Vector correction utilities
Expand All @@ -476,27 +475,6 @@ def getImageArray(self, image):
calcImage = image.getArray()
return calcImage

@staticmethod
def transpose(imageArray):
"""Transpose input numpy array if necessary.
Parameters
----------
imageArray : `numpy.ndarray`
Image data to transpose.
Returns
-------
imageArray : `numpy.ndarray`
Transposed image data.
isTransposed : `bool`
Indicates whether the input data was transposed.
"""
if np.argmin(imageArray.shape) == 0:
return np.transpose(imageArray), True
else:
return imageArray, False

def maskOutliers(self, imageArray):
"""Mask outliers in a row of overscan data from a robust sigma
clipping procedure.
Expand Down

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