lsst.ip.diffim g07994bdeae+30b05a742e
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Classes | |
class | DipoleTestImage |
Variables | |
bool | keptPlots = False |
_LOG = getLogger(__name__) | |
Support utilities for Measuring sources
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protected |
lsst.ip.diffim.utils.calcCentroid | ( | arr | ) |
lsst.ip.diffim.utils.calcWidth | ( | arr, | |
centx, | |||
centy | |||
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afwImage.ImageD lsst.ip.diffim.utils.computeAveragePsf | ( | afwImage.Exposure | exposure, |
float | psfExposureBuffer, | ||
int | psfExposureGrid | ||
) |
Get the average PSF by evaluating it on a grid within an exposure. Parameters ---------- exposure : `~lsst.afw.image.Exposure` The exposure for which the average PSF is to be computed. The exposure must contain a `psf` attribute. psfExposureBuffer : `float` Fractional buffer margin to be left out of all sides of the image during the construction of the grid to compute average PSF in an exposure. psfExposureGrid : `int` Grid size to compute the average PSF in an exposure. Returns ------- psfImage : `~lsst.afw.image.Image` The average PSF across the exposure. Raises ------ ValueError Raised if the PSF cannot be computed at any of the grid points. See Also -------- `evaluateMeanPsfFwhm`
lsst.ip.diffim.utils.computePSFNoiseEquivalentArea | ( | psf | ) |
lsst.ip.diffim.utils.computeRobustStatistics | ( | image, | |
mask, | |||
statsCtrl, | |||
statistic = afwMath.MEANCLIP |
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Calculate a robust mean of the variance plane of an exposure. Parameters ---------- image : `lsst.afw.image.Image` Image or variance plane of an exposure to evaluate. mask : `lsst.afw.image.Mask` Mask plane to use for excluding pixels. statsCtrl : `lsst.afw.math.StatisticsControl` Statistics control object for configuring the calculation. statistic : `lsst.afw.math.Property`, optional The type of statistic to compute. Typical values are ``afwMath.MEANCLIP`` or ``afwMath.STDEVCLIP``. Returns ------- value : `float` The result of the statistic calculated from the unflagged pixels.
lsst.ip.diffim.utils.detectTestSources | ( | exposure | ) |
Minimal source detection wrapper suitable for unit tests. Parameters ---------- exposure : `lsst.afw.image.Exposure` Exposure on which to run detection/measurement The exposure is modified in place to set the 'DETECTED' mask plane. Returns ------- selectSources : Source catalog containing candidates
float lsst.ip.diffim.utils.evaluateMeanPsfFwhm | ( | afwImage.Exposure | exposure, |
float | fwhmExposureBuffer, | ||
int | fwhmExposureGrid | ||
) |
Get the mean PSF FWHM by evaluating it on a grid within an exposure. Parameters ---------- exposure : `~lsst.afw.image.Exposure` The exposure for which the mean FWHM of the PSF is to be computed. The exposure must contain a `psf` attribute. fwhmExposureBuffer : `float` Fractional buffer margin to be left out of all sides of the image during the construction of the grid to compute mean PSF FWHM in an exposure. fwhmExposureGrid : `int` Grid size to compute the mean FWHM in an exposure. Returns ------- meanFwhm : `float` The mean PSF FWHM on the exposure. Raises ------ ValueError Raised if the PSF cannot be computed at any of the grid points. See Also -------- `getPsfFwhm` `computeAveragePsf`
lsst.ip.diffim.utils.getPsfFwhm | ( | psf, | |
average = True , |
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position = None |
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Directly calculate the horizontal and vertical widths of a PSF at half its maximum value. Parameters ---------- psf : `~lsst.afw.detection.Psf` Point spread function (PSF) to evaluate. average : `bool`, optional Set to return the average width over Y and X axes. position : `~lsst.geom.Point2D`, optional The position at which to evaluate the PSF. If `None`, then the average position is used. Returns ------- psfSize : `float` | `tuple` [`float`] The FWHM of the PSF computed at its average position. Returns the widths along the Y and X axes, or the average of the two if `average` is set. See Also -------- evaluateMeanPsfFwhm
lsst.ip.diffim.utils.makeFakeWcs | ( | ) |
lsst.ip.diffim.utils.makeRegions | ( | sources, | |
outfilename, | |||
wcs = None |
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lsst.ip.diffim.utils.makeStats | ( | badMaskPlanes = None | ) |
Create a statistics control for configuring calculations on images. Parameters ---------- badMaskPlanes : `list` of `str`, optional List of mask planes to exclude from calculations. Returns ------- statsControl : ` lsst.afw.math.StatisticsControl` Statistics control object for configuring calculations on images.
lsst.ip.diffim.utils.makeTestImage | ( | seed = 5 , |
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nSrc = 20 , |
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psfSize = 2. , |
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noiseLevel = 5. , |
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noiseSeed = 6 , |
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fluxLevel = 500. , |
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fluxRange = 2. , |
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kernelSize = 32 , |
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templateBorderSize = 0 , |
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background = None , |
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xSize = 256 , |
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ySize = 256 , |
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x0 = 12345 , |
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y0 = 67890 , |
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calibration = 1. , |
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doApplyCalibration = False , |
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xLoc = None , |
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yLoc = None , |
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flux = None , |
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clearEdgeMask = False |
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Make a reproduceable PSF-convolved exposure for testing. Parameters ---------- seed : `int`, optional Seed value to initialize the random number generator for sources. nSrc : `int`, optional Number of sources to simulate. psfSize : `float`, optional Width of the PSF of the simulated sources, in pixels. noiseLevel : `float`, optional Standard deviation of the noise to add to each pixel. noiseSeed : `int`, optional Seed value to initialize the random number generator for noise. fluxLevel : `float`, optional Reference flux of the simulated sources. fluxRange : `float`, optional Range in flux amplitude of the simulated sources. kernelSize : `int`, optional Size in pixels of the kernel for simulating sources. templateBorderSize : `int`, optional Size in pixels of the image border used to pad the image. background : `lsst.afw.math.Chebyshev1Function2D`, optional Optional background to add to the output image. xSize, ySize : `int`, optional Size in pixels of the simulated image. x0, y0 : `int`, optional Origin of the image. calibration : `float`, optional Conversion factor between instFlux and nJy. doApplyCalibration : `bool`, optional Apply the photometric calibration and return the image in nJy? xLoc, yLoc : `list` of `float`, optional User-specified coordinates of the simulated sources. If specified, must have length equal to ``nSrc`` flux : `list` of `float`, optional User-specified fluxes of the simulated sources. If specified, must have length equal to ``nSrc`` clearEdgeMask : `bool`, optional Clear the "EDGE" mask plane after source detection. Returns ------- modelExposure : `lsst.afw.image.Exposure` The model image, with the mask and variance planes. sourceCat : `lsst.afw.table.SourceCatalog` Catalog of sources detected on the model image. Raises ------ ValueError If `xloc`, `yloc`, or `flux` are supplied with inconsistant lengths.
lsst.ip.diffim.utils.plotKernelCoefficients | ( | spatialKernel, | |
kernelCellSet, | |||
showBadCandidates = False , |
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keepPlots = True |
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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.
lsst.ip.diffim.utils.plotKernelSpatialModel | ( | kernel, | |
kernelCellSet, | |||
showBadCandidates = True , |
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numSample = 128 , |
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keepPlots = True , |
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maxCoeff = 10 |
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) |
lsst.ip.diffim.utils.plotWhisker | ( | results, | |
newWcs | |||
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lsst.ip.diffim.utils.printSkyDiffs | ( | sources, | |
wcs | |||
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lsst.ip.diffim.utils.showDiaSources | ( | sources, | |
exposure, | |||
isFlagged, | |||
isDipole, | |||
frame = None |
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lsst.ip.diffim.utils.showKernelBasis | ( | kernel, | |
frame = None |
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lsst.ip.diffim.utils.showSourceSet | ( | sSet, | |
xy0 = (0, 0) , |
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frame = 0 , |
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ctype = afwDisplay.GREEN , |
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symb = "+" , |
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size = 2 |
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lsst.ip.diffim.utils.showSourceSetSky | ( | sSet, | |
wcs, | |||
xy0, | |||
frame = 0 , |
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ctype = afwDisplay.GREEN , |
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symb = "+" , |
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size = 2 |
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) |