Inheritance diagram for lsst.ip.isr.overscan.OverscanCorrectionTaskBase:

Public Member Functions
	__init__ (self, statControl=None, **kwargs)

	run (self, exposure, amp, isTransposed=False)

	correctOverscan (self, exposure, amp, imageBBox, overscanBBox, isTransposed=True, leadingToSkip=0, trailingToSkip=0, overscanFraction=1.0, imageThreshold=np.inf, maskedRowColumnGrowSize=0, medianSmoothingKernel=0, medianSmoothingOutlierThreshold=np.inf)

	broadcastFitToImage (self, overscanValue, imageArray, transpose=False)

	trimOverscan (self, exposure, amp, bbox, skipLeading, skipTrailing, transpose=False)

	fitOverscan (self, overscanImage, isTransposed=False)

	maskParallelOverscan (self, exposure, detector)

	measureConstantOverscan (self, image)

	getImageArray (self, image)

	maskOutliers (self, imageArray)

	fillMaskedPixels (self, overscanVector)

	collapseArray (self, maskedArray, fillMasked=True)

	splineFit (self, indices, collapsed, numBins)

	measureVectorOverscan (self, image, isTransposed=False)

	debugView (self, image, model, amp=None, isTransposed=True)

Static Public Member Functions
	splineEval (indices, interp)

	maskExtrapolated (collapsed)

Public Attributes
bool	allowDebug = True

	statControl = statControl

Static Public Attributes
	ConfigClass = OverscanCorrectionTaskConfigBase

Static Protected Member Functions
	_maskRowsOrColumns (exposure, overscanBBox, overscanMaskedImage, overscanMask, maxDeviation, maskedRowColumnGrowSize, medianSmoothingKernel, medianSmoothingOutlierThreshold, doAbsoluteMaxDeviation, isTransposed)

Static Protected Attributes
str	_DefaultName = "overscanBase"

Detailed Description

Base Correction task for overscan.

This class contains a number of utilities that are easier to
understand and use when they are not embedded in nested if/else
loops.

Parameters
----------
statControl : `lsst.afw.math.StatisticsControl`, optional
    Statistics control object.

Definition at line 137 of file overscan.py.

Constructor & Destructor Documentation

◆ init()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.__init__	(		self,
			statControl = None,
		**	kwargs )

Definition at line 152 of file overscan.py.

Member Function Documentation

◆ _maskRowsOrColumns()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase._maskRowsOrColumns	(	exposure,
		overscanBBox,
		overscanMaskedImage,
		overscanMask,
		maxDeviation,
		maskedRowColumnGrowSize,
		medianSmoothingKernel,
		medianSmoothingOutlierThreshold,
		doAbsoluteMaxDeviation,
		isTransposed )

staticprotected

Mask overscan rows (~serial) or columns (~parallel).

Parameters
----------
exposure : `lsst.afw.image.Exposure`
    Exposure containing the data.
overscanBBox: `lsst.geom.Box2I`
    Bounding box for the overscan data.
overscanMaskedImage : `lsst.afw.image.MaskedImage`
    Masked image containing the overscan data.
overscanMask : `np.ndarray`
    Numpy array of the mask bits, anded with appropriate
    mask planes.
maxDeviation : `float`
    Maximum deviation from median (overscan units) to mask in overscan
    correction. For parallel overscan this is a one-sided (positive
    only) cut.
maskedRowColumnGrowSize : `int`
    If a column (parallel overscan) or row (serial overscan) is
    completely masked, then grow the mask by this radius. If the
    value is <=0 then this will not be checked.
medianSmoothingKernel : `int`
    Kernel (pixels) to smooth rows/columns. If <=0, median smoothing
    is skipped. Otherwise must be odd.
medianSmoothingOutlierThreshold : `float`
    Outlier threshold after median smoothing (overscan units). This
    is applied only to positive outliers.
doAbsoluteMaxDeviation : `bool`
    If true, deviation comparisons will use the absolute value;
    otherwise it will cut positive outliers only.
isTransposed : `bool`
    If true, then the data will be transposed before fitting
    the overscan.

Returns
-------
badRowsOrColumns : `np.ndarray`
    Array of bad rows (serial) or columns (parallel) that were
    found, prior to dilation by maskedRowColumnGrowSize.

Definition at line 167 of file overscan.py.

◆ broadcastFitToImage()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.broadcastFitToImage	(	self,
		overscanValue,
		imageArray,
		transpose = False )

Broadcast 0 or 1 dimension fit to appropriate shape.

Parameters
----------
overscanValue : `numpy.ndarray`, (Nrows, ) or scalar
    Overscan fit to broadcast.
imageArray : `numpy.ndarray`, (Nrows, Ncols)
    Image array that we want to match.
transpose : `bool`, optional
    Switch order to broadcast along the other axis.

Returns
-------
overscanModel : `numpy.ndarray`, (Nrows, Ncols) or scalar
    Expanded overscan fit.

Raises
------
RuntimeError
    Raised if no axis has the appropriate dimension.

Definition at line 485 of file overscan.py.

◆ collapseArray()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.collapseArray	(	self,
		maskedArray,
		fillMasked = True )

Collapse overscan array (and mask) to a 1-D vector of values.

Parameters
----------
maskedArray : `numpy.ma.masked_array`
    Masked array of input overscan data.
fillMasked : `bool`, optional
    If true, fill any pixels that are masked with a median of
    neighbors.

Returns
-------
collapsed : `numpy.ma.masked_array`
    Single dimensional overscan data, combined with the mean.

Definition at line 763 of file overscan.py.

◆ correctOverscan()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.correctOverscan	(	self,
		exposure,
		amp,
		imageBBox,
		overscanBBox,
		isTransposed = True,
		leadingToSkip = 0,
		trailingToSkip = 0,
		overscanFraction = 1.0,
		imageThreshold = np.inf,
		maskedRowColumnGrowSize = 0,
		medianSmoothingKernel = 0,
		medianSmoothingOutlierThreshold = np.inf )

Trim the exposure, fit the overscan, subtract the fit, and
calculate statistics.

Parameters
----------
exposure : `lsst.afw.image.Exposure`
    Exposure containing the data.
amp : `lsst.afw.cameraGeom.Amplifier`
    The amplifier that is to be corrected.
imageBBox: `lsst.geom.Box2I`
    Bounding box of the image data that will have the overscan
    subtracted.  If parallel overscan will be performed, that
    area is added to the image bounding box during serial
    overscan correction.
overscanBBox: `lsst.geom.Box2I`
    Bounding box for the overscan data.
isTransposed: `bool`
    If true, then the data will be transposed before fitting
    the overscan.
leadingToSkip : `int`, optional
    Leading rows/columns to skip.
trailingToSkip : `int`, optional
    Leading rows/columns to skip.
overscanFraction : `float`, optional
    If the overscan region median is greater than overscanFraction
    and the imaging region median is greater than imageThreshold
    then overscan correction will be skipped.
maxLevel : `float`, optional
    If the overscan region median is greater than overscanFraction
    and the imaging region median is greater than imageThreshold
    then overscan correction will be skipped.
maskedRowColumnGrowSize : `int`, optional
    If a column (parallel overscan) or row (serial overscan) is
    completely masked, then grow the mask by this radius. If the
    value is <=0 then this will not be checked.
medianSmoothingKernel : `int`, optional
    Kernel (pixels) to use to smooth rows/columns for row/column
    outlier rejection. Must be odd if positive; if <=0 median
    smoothing will not be used to find outliers.
medianSmoothingOutlierThreshold : `float`, optional
    Threshold to look for outliers after median smoothing (adu).

Returns
-------
results : `lsst.pipe.base.Struct`
    ``ampOverscanModel``
        Overscan model broadcast to the full image size.
        (`lsst.afw.image.Exposure`)
    ``overscanOverscanModel``
        Overscan model broadcast to the full overscan image
        size. (`lsst.afw.image.Exposure`)
    ``overscanImage``
        Overscan image with the overscan fit subtracted.
        (`lsst.afw.image.Exposure`)
    ``overscanValue``
        Overscan model. (`float` or `np.array`)
    ``overscanMean``
        Mean value of the overscan fit. (`float`)
    ``overscanMedian``
        Median value of the overscan fit. (`float`)
    ``overscanSigma``
        Standard deviation of the overscan fit. (`float`)
    ``overscanMeanResidual``
        Mean value of the overscan region after overscan
        subtraction. (`float`)
    ``overscanMedianResidual``
        Median value of the overscan region after overscan
        subtraction. (`float`)
    ``overscanSigmaResidual``
        Standard deviation of the overscan region after
        overscan subtraction. (`float`)

Definition at line 297 of file overscan.py.

◆ debugView()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.debugView	(	self,
		image,
		model,
		amp = None,
		isTransposed = True )

Debug display for the final overscan solution.

Parameters
----------
image : `lsst.afw.image.Image`
    Input image the overscan solution was determined from.
model : `numpy.ndarray` or `float`
    Overscan model determined for the image.
amp : `lsst.afw.cameraGeom.Amplifier`, optional
    Amplifier to extract diagnostic information.
isTransposed : `bool`, optional
    Does the data need to be transposed before display?

Definition at line 967 of file overscan.py.

◆ fillMaskedPixels()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.fillMaskedPixels	(		self,
			overscanVector )

Fill masked/NaN pixels in the overscan.

Parameters
----------
overscanVector : `np.array` or `np.ma.masked_array`
    Overscan vector to fill.

Returns
-------
overscanVector : `np.ma.masked_array`
    Filled vector.

Notes
-----
Each maskSlice is a section of overscan with contiguous masks.
Ideally this adds 5 pixels from the left and right of that
mask slice, and takes the median of those values to fill the
slice.  If this isn't possible, the median of all non-masked
values is used.  The mask is removed for the pixels filled.

Definition at line 722 of file overscan.py.

◆ fitOverscan()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.fitOverscan	(	self,
		overscanImage,
		isTransposed = False )

Definition at line 582 of file overscan.py.

◆ getImageArray()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.getImageArray	(		self,
			image )

Extract the numpy array from the input image.

Parameters
----------
image : `lsst.afw.image.Image` or `lsst.afw.image.MaskedImage`
    Image data to pull array from.

calcImage : `numpy.ndarray`
    Image data array for numpy operating.

Definition at line 671 of file overscan.py.

◆ maskExtrapolated()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.maskExtrapolated ( collapsed )

static

Create mask if edges are extrapolated.

Parameters
----------
collapsed : `numpy.ma.masked_array`
    Masked array to check the edges of.

Returns
-------
maskArray : `numpy.ndarray`
    Boolean numpy array of pixels to mask.

Definition at line 852 of file overscan.py.

◆ maskOutliers()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.maskOutliers	(		self,
			imageArray )

Mask  outliers in  a  row  of overscan  data  from  a robust  sigma
clipping procedure.

Parameters
----------
imageArray : `numpy.ndarray`
    Image to filter along numpy axis=1.

Returns
-------
maskedArray : `numpy.ma.masked_array`
    Masked image marking outliers.

Definition at line 690 of file overscan.py.

◆ maskParallelOverscan()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.maskParallelOverscan	(	self,
		exposure,
		detector )

Mask the union of high values on all amplifiers in the parallel
overscan.

This operates on the image in-place.

Parameters
----------
exposure : `lsst.afw.image.Exposure`
    An untrimmed raw exposure.
detector : `lsst.afw.cameraGeom.Detector`
    The detetor to use for amplifier geometry.

Definition at line 612 of file overscan.py.

◆ measureConstantOverscan()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.measureConstantOverscan	(		self,
			image )

Measure a constant overscan value.

Parameters
----------
image : `lsst.afw.image.Image` or `lsst.afw.image.MaskedImage`
    Image data to measure the overscan from.

Returns
-------
results : `lsst.pipe.base.Struct`
    Overscan result with entries:
    - ``overscanValue``: Overscan value to subtract (`float`)
    - ``isTransposed``: Orientation of the overscan (`bool`)

Definition at line 649 of file overscan.py.

◆ measureVectorOverscan()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.measureVectorOverscan	(	self,
		image,
		isTransposed = False )

Calculate the 1-d vector overscan from the input overscan image.

Parameters
----------
image : `lsst.afw.image.MaskedImage`
    Image containing the overscan data.
isTransposed : `bool`
    If true, the image has been transposed.

Returns
-------
results : `lsst.pipe.base.Struct`
    Overscan result with entries:

    ``overscanValue``
        Overscan value to subtract (`float`)
    ``maskArray``
        List of rows that should be masked as ``SUSPECT`` when the
        overscan solution is applied. (`list` [ `bool` ])
    ``isTransposed``
       Indicates if the overscan data was transposed during
       calcuation, noting along which axis the overscan should be
       subtracted. (`bool`)

Definition at line 880 of file overscan.py.

◆ run()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.run	(	self,
		exposure,
		amp,
		isTransposed = False )

Reimplemented in lsst.ip.isr.overscan.OverscanCorrectionTask, lsst.ip.isr.overscan.ParallelOverscanCorrectionTask, and lsst.ip.isr.overscan.SerialOverscanCorrectionTask.

Definition at line 163 of file overscan.py.

◆ splineEval()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.splineEval	(		indices,
			interp )

static

Wrapper function to match spline evaluation API to polynomial fit
API.

Parameters
----------
indices : `numpy.ndarray`
    Locations to evaluate the spline.
interp : `lsst.afw.math.interpolate`
    Interpolation object to use.

Returns
-------
values : `numpy.ndarray`
    Evaluated spline values at each index.

Definition at line 832 of file overscan.py.

◆ splineFit()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.splineFit	(	self,
		indices,
		collapsed,
		numBins )

Wrapper function to match spline fit API to polynomial fit API.

Parameters
----------
indices : `numpy.ndarray`
    Locations to evaluate the spline.
collapsed : `numpy.ndarray`
    Collapsed overscan values corresponding to the spline
    evaluation points.
numBins : `int`
    Number of bins to use in constructing the spline.

Returns
-------
interp : `lsst.afw.math.Interpolate`
    Interpolation object for later evaluation.

Definition at line 786 of file overscan.py.

◆ trimOverscan()

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.trimOverscan	(	self,
		exposure,
		amp,
		bbox,
		skipLeading,
		skipTrailing,
		transpose = False )

Trim overscan region to remove edges.

Parameters
----------
exposure : `lsst.afw.image.Exposure`
    Exposure containing data.
amp : `lsst.afw.cameraGeom.Amplifier`
    Amplifier containing geometry information.
bbox : `lsst.geom.Box2I`
    Bounding box of the overscan region.
skipLeading : `int`
    Number of leading (towards data region) rows/columns to skip.
skipTrailing : `int`
    Number of trailing (away from data region) rows/columns to skip.
transpose : `bool`, optional
    Operate on the transposed array.

Returns
-------
overscanArray : `numpy.array`, (N, M)
    Data array to fit.
overscanMask : `numpy.array`, (N, M)
    Data mask.

Definition at line 535 of file overscan.py.

Member Data Documentation

◆ _DefaultName

str lsst.ip.isr.overscan.OverscanCorrectionTaskBase._DefaultName = "overscanBase"

staticprotected

Definition at line 150 of file overscan.py.

◆ allowDebug

bool lsst.ip.isr.overscan.OverscanCorrectionTaskBase.allowDebug = True

Definition at line 154 of file overscan.py.

◆ ConfigClass

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.ConfigClass = OverscanCorrectionTaskConfigBase

static

Definition at line 149 of file overscan.py.

◆ statControl

lsst.ip.isr.overscan.OverscanCorrectionTaskBase.statControl = statControl

Definition at line 157 of file overscan.py.

The documentation for this class was generated from the following file:

python/lsst/ip/isr/overscan.py

Public Member Functions

Static Public Member Functions

Public Attributes

Static Public Attributes

Static Protected Member Functions

Static Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ __init__()

Member Function Documentation

◆ _maskRowsOrColumns()

◆ broadcastFitToImage()

◆ collapseArray()

◆ correctOverscan()

◆ debugView()

◆ fillMaskedPixels()

◆ fitOverscan()

◆ getImageArray()

◆ maskExtrapolated()

◆ maskOutliers()

◆ maskParallelOverscan()

◆ measureConstantOverscan()

◆ measureVectorOverscan()

◆ run()

◆ splineEval()

◆ splineFit()

◆ trimOverscan()

Member Data Documentation

◆ _DefaultName

◆ allowDebug

◆ ConfigClass

◆ statControl

◆ init()