DonutQuickMeasurementTaskConfig#

class lsst.ts.wep.task.DonutQuickMeasurementTaskConfig(*args, **kw)#

Bases: QuickFrameMeasurementTaskConfig

Attributes Summary

`centroidPixelPercentile`	The image's percentile value which the centroid must be greater than to pass the final peak check.
`doCheckCentroidPixelValue`	Check that the centroid found is actually in the centroidPixelPercentile percentile of the image? Set to False for donut images.
`doExtendednessCut`	Apply the extendeness cut, as definted by maxExtendedness (`bool`, default `False`)
`doPreConvolution`	Perform a preconvolution of the image with a donut model? (The default is True.) (`bool`, default `True`)
`donutDiameter`	The expected diameter of donuts in a donut image, in pixels.
`initialCutoutPadding`	Additional padding in pixels on each side of initial `donutDiameter` guess for template postage stamp size and for bounding boxes used for estimating centroids.
`initialPsfWidth`	Guess at the initial PSF FWHM in pixels.
`installPsf`	Task for installing an initial PSF (`ConfigurableInstance`, default `<class 'lsst.meas.algorithms.installGaussianPsf.InstallGaussianPsfConfig'>`)
`maxExtendedness`	Max absolute value of xx and yy above which to cut, in order to exclude large/things (`float`, default `100`)
`maxNonRoundness`	Ratio of xx to yy (or vice versa) above which to cut, in order to exclude spectra (`float`, default `5.0`)
`nPixMinDetection`	Minimum number of pixels in a detected source.
`nSigmaDetection`	Number of sigma for the detection limit.

Attributes Documentation

centroidPixelPercentile#: The image’s percentile value which the centroid must be greater than to pass the final peak check. Ignored if doCheckCentroidPixelValue is False (float, default 90)

doCheckCentroidPixelValue#: Check that the centroid found is actually in the centroidPixelPercentile percentile of the image? Set to False for donut images. (bool, default True)

doExtendednessCut#: Apply the extendeness cut, as definted by maxExtendedness (bool, default False)

doPreConvolution: Field#: Perform a preconvolution of the image with a donut model? (The default is True.) (bool, default True)

donutDiameter#: The expected diameter of donuts in a donut image, in pixels. (int, default 400)

initialCutoutPadding: Field#: Additional padding in pixels on each side of initial donutDiameter guess for template postage stamp size and for bounding boxes used for estimating centroids. (int, default 5)

initialPsfWidth#: Guess at the initial PSF FWHM in pixels. (float, default 10)

installPsf#: Task for installing an initial PSF (ConfigurableInstance, default <class 'lsst.meas.algorithms.installGaussianPsf.InstallGaussianPsfConfig'>)

maxExtendedness#: Max absolute value of xx and yy above which to cut, in order to exclude large/things (float, default 100)

maxNonRoundness#: Ratio of xx to yy (or vice versa) above which to cut, in order to exclude spectra (float, default 5.0)

nPixMinDetection#: Minimum number of pixels in a detected source. (int, default 10)

nSigmaDetection#: Number of sigma for the detection limit. (float, default 20)