ChooseReferenceVisitConfig

class lsst.pipe.tasks.matchBackgrounds.ChooseReferenceVisitConfig(*args, **kw)

Bases: Config

Attributes Summary

bestRefWeightChi2	Mean background goodness of fit statistic weight when calculating the best reference exposure.
bestRefWeightGlobalCoverage	Global coverage weight (total number of valid pixels) when calculating the best reference exposure.
bestRefWeightVariance	Image variance weight when calculating the best reference exposure.
gridStatistic	Type of statistic to estimate pixel value for the grid points (str, default 'MEANCLIP')
interpStyle	Algorithm to interpolate the background values; ignored if usePolynomial=True.Maps to an enum; see afw.math.Background for more information.
numIter	Number of iterations of outlier rejection.
numSigmaClip	Sigma for outlier rejection.
tractBgModel	Background model for the entire tract (TractBackgroundConfig, default <class 'lsst.pipe.tasks.tractBackground.TractBackgroundConfig'>)
undersampleStyle	Behavior if there are too few points in the grid for requested interpolation style (str, default 'REDUCE_INTERP_ORDER')

Attributes Documentation

bestRefWeightChi2

Mean background goodness of fit statistic weight when calculating the best reference exposure. Higher weights prefer exposures with flatter backgrounds. Ignored when ref visit supplied. (float, default 0.3)

Valid Range = [0.0,1.0)

bestRefWeightGlobalCoverage

Global coverage weight (total number of valid pixels) when calculating the best reference exposure. Higher weights prefer exposures with high coverage. Ignored when ref visit supplied. (float, default 0.4)

Valid Range = [0.0,1.0)

bestRefWeightVariance

Image variance weight when calculating the best reference exposure. Higher weights prefers exposures with low image variances. Ignored when ref visit supplied. (float, default 0.3)

Valid Range = [0.0,1.0)

gridStatistic

Type of statistic to estimate pixel value for the grid points (str, default 'MEANCLIP')

Allowed values:

'MEAN'

mean

'MEDIAN'

median

'MEANCLIP'

clipped mean

'None'

Field is optional

interpStyle

Algorithm to interpolate the background values; ignored if usePolynomial=True.Maps to an enum; see afw.math.Background for more information. (str, default 'AKIMA_SPLINE')

Allowed values:

'CONSTANT'

Use a single constant value.

'LINEAR'

Use linear interpolation.

'NATURAL_SPLINE'

A cubic spline with zero second derivative at endpoints.

'AKIMA_SPLINE'

A higher-level non-linear spline that is more robust to outliers.

'NONE'

No background estimation is to be attempted.

'None'

Field is optional

numIter

Number of iterations of outlier rejection. Ignored if gridStatistic != 'MEANCLIP'. (int, default 3)

numSigmaClip

Sigma for outlier rejection. Ignored if gridStatistic != 'MEANCLIP'. (int, default 3)

tractBgModel

Background model for the entire tract (TractBackgroundConfig, default <class 'lsst.pipe.tasks.tractBackground.TractBackgroundConfig'>)

undersampleStyle

Behavior if there are too few points in the grid for requested interpolation style (str, default 'REDUCE_INTERP_ORDER')

Allowed values:

'THROW_EXCEPTION'

throw an exception if there are too few points.

'REDUCE_INTERP_ORDER'

use an interpolation style with a lower order.

'None'

Field is optional