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def | showSourceSet (sSet, xy0=(0, 0), frame=0, ctype=afwDisplay.GREEN, symb="+", size=2) |
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def | showKernelSpatialCells (maskedIm, kernelCellSet, showChi2=False, symb="o", ctype=None, ctypeUnused=None, ctypeBad=None, size=3, frame=None, title="Spatial Cells") |
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def | showDiaSources (sources, exposure, isFlagged, isDipole, frame=None) |
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def | showKernelCandidates (kernelCellSet, kernel, background, frame=None, showBadCandidates=True, resids=False, kernels=False) |
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def | showKernelBasis (kernel, frame=None) |
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def | plotKernelSpatialModel (kernel, kernelCellSet, showBadCandidates=True, numSample=128, keepPlots=True, maxCoeff=10) |
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def | plotKernelCoefficients (spatialKernel, kernelCellSet, showBadCandidates=False, keepPlots=True) |
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def | showKernelMosaic (bbox, kernel, nx=7, ny=None, frame=None, title=None, showCenter=True, showEllipticity=True) |
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def | plotPixelResiduals (exposure, warpedTemplateExposure, diffExposure, kernelCellSet, kernel, background, testSources, config, origVariance=False, nptsFull=1e6, keepPlots=True, titleFs=14) |
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def | calcCentroid (arr) |
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def | calcWidth (arr, centx, centy) |
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def | printSkyDiffs (sources, wcs) |
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def | makeRegions (sources, outfilename, wcs=None) |
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def | showSourceSetSky (sSet, wcs, xy0, frame=0, ctype=afwDisplay.GREEN, symb="+", size=2) |
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def | plotWhisker (results, newWcs) |
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def | getPsfFwhm (psf) |
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def lsst.ip.diffim.utils.plotKernelCoefficients |
( |
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spatialKernel, |
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kernelCellSet, |
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showBadCandidates = False , |
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keepPlots = True |
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) |
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Plot the individual kernel candidate and the spatial kernel solution coefficients.
Parameters
----------
spatialKernel : `lsst.afw.math.LinearCombinationKernel`
The spatial spatialKernel solution model which is a spatially varying linear combination
of the spatialKernel basis functions.
Typically returned by `lsst.ip.diffim.SpatialKernelSolution.getSolutionPair()`.
kernelCellSet : `lsst.afw.math.SpatialCellSet`
The spatial cells that was used for solution for the spatialKernel. They contain the
local solutions of the AL kernel for the selected sources.
showBadCandidates : `bool`, optional
If True, plot the coefficient values for kernel candidates where the solution was marked
bad by the numerical algorithm. Defaults to False.
keepPlots: `bool`, optional
If True, sets ``plt.show()`` to be called before the task terminates, so that the plots
can be explored interactively. Defaults to True.
Notes
-----
This function produces 3 figures per image subtraction operation.
* A grid plot of the local solutions. Each grid cell corresponds to a proportional area in
the image. In each cell, local kernel solution coefficients are plotted of kernel candidates (color)
that fall into this area as a function of the kernel basis function number.
* A grid plot of the spatial solution. Each grid cell corresponds to a proportional area in
the image. In each cell, the spatial solution coefficients are evaluated for the center of the cell.
* Histogram of the local solution coefficients. Red line marks the spatial solution value at
center of the image.
This function is called if ``lsst.ip.diffim.psfMatch.plotKernelCoefficients==True`` in lsstDebug. This
function was implemented as part of DM-17825.
Definition at line 428 of file utils.py.