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def | run (self, inputExp, camera) |
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def | findHotAndColdPixels (self, exp, nSigma) |
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def | maskBlocksIfIntermitentBadPixelsInColumn (self, defects) |
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def | debugView (self, stepname, ampImage, defects, detector) |
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def | debugHistogram (self, stepname, ampImage, nSigmaUsed, exp) |
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Measure the defects from one exposure.
Definition at line 126 of file defects.py.
◆ debugHistogram()
def lsst.cp.pipe.defects.MeasureDefectsTask.debugHistogram |
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self, |
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stepname, |
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ampImage, |
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nSigmaUsed, |
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exp |
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Make a histogram of the distribution of pixel values for each amp.
The main image data histogram is plotted in blue. Edge pixels,
if masked, are in red. Note that masked edge pixels do not contribute
to the underflow and overflow numbers.
Note that this currently only supports the 16-amp LSST detectors.
Parameters
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dataRef : `lsst.daf.persistence.ButlerDataRef`
dataRef for the detector.
exp : `lsst.afw.image.exposure.Exposure`
The exposure in which the defects were found.
visit : `int`
The visit number.
nSigmaUsed : `float`
The number of sigma used for detection
Definition at line 439 of file defects.py.
◆ debugView()
def lsst.cp.pipe.defects.MeasureDefectsTask.debugView |
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self, |
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stepname, |
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ampImage, |
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defects, |
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detector |
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Plot the defects found by the task.
Parameters
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exp : `lsst.afw.image.exposure.Exposure`
The exposure in which the defects were found.
visit : `int`
The visit number.
defects : `lsst.ip.isr.Defect`
The defects to plot.
imageType : `str`
The type of image, either 'dark' or 'flat'.
Definition at line 399 of file defects.py.
◆ findHotAndColdPixels()
def lsst.cp.pipe.defects.MeasureDefectsTask.findHotAndColdPixels |
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self, |
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exp, |
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nSigma |
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Find hot and cold pixels in an image.
Using config-defined thresholds on a per-amp basis, mask
pixels that are nSigma above threshold in dark frames (hot
pixels), or nSigma away from the clipped mean in flats (hot &
cold pixels).
Parameters
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exp : `lsst.afw.image.exposure.Exposure`
The exposure in which to find defects.
nSigma : `list [ `float` ]
Detection threshold to use. Positive for DETECTED pixels,
negative for DETECTED_NEGATIVE pixels.
Returns
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defects : `lsst.ip.isr.Defect`
The defects found in the image.
Definition at line 190 of file defects.py.
◆ maskBlocksIfIntermitentBadPixelsInColumn()
def lsst.cp.pipe.defects.MeasureDefectsTask.maskBlocksIfIntermitentBadPixelsInColumn |
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self, |
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defects |
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Mask blocks in a column if there are on-and-off bad pixels
If there's a column with on and off bad pixels, mask all the
pixels in between, except if there is a large enough gap of
consecutive good pixels between two bad pixels in the column.
Parameters
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defects: `lsst.ip.isr.Defect`
The defects found in the image so far
Returns
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defects: `lsst.ip.isr.Defect`
If the number of bad pixels in a column is not larger or
equal than self.config.badPixelColumnThreshold, the iput
list is returned. Otherwise, the defects list returned
will include boxes that mask blocks of on-and-of pixels.
Definition at line 298 of file defects.py.
◆ run()
def lsst.cp.pipe.defects.MeasureDefectsTask.run |
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self, |
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inputExp, |
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camera |
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Measure one exposure for defects.
Parameters
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inputExp : `lsst.afw.image.Exposure`
Exposure to examine.
camera : `lsst.afw.cameraGeom.Camera`
Camera to use for metadata.
Returns
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results : `lsst.pipe.base.Struct`
Results struct containing:
- ``outputDefects` : `lsst.ip.isr.Defects`
The defects measured from this exposure.
Definition at line 132 of file defects.py.
◆ ConfigClass
The documentation for this class was generated from the following file: