LSST Applications
21.0.0-147-g0e635eb1+1acddb5be5,22.0.0+052faf71bd,22.0.0+1ea9a8b2b2,22.0.0+6312710a6c,22.0.0+729191ecac,22.0.0+7589c3a021,22.0.0+9f079a9461,22.0.1-1-g7d6de66+b8044ec9de,22.0.1-1-g87000a6+536b1ee016,22.0.1-1-g8e32f31+6312710a6c,22.0.1-10-gd060f87+016f7cdc03,22.0.1-12-g9c3108e+df145f6f68,22.0.1-16-g314fa6d+c825727ab8,22.0.1-19-g93a5c75+d23f2fb6d8,22.0.1-19-gb93eaa13+aab3ef7709,22.0.1-2-g8ef0a89+b8044ec9de,22.0.1-2-g92698f7+9f079a9461,22.0.1-2-ga9b0f51+052faf71bd,22.0.1-2-gac51dbf+052faf71bd,22.0.1-2-gb66926d+6312710a6c,22.0.1-2-gcb770ba+09e3807989,22.0.1-20-g32debb5+b8044ec9de,22.0.1-23-gc2439a9a+fb0756638e,22.0.1-3-g496fd5d+09117f784f,22.0.1-3-g59f966b+1e6ba2c031,22.0.1-3-g849a1b8+f8b568069f,22.0.1-3-gaaec9c0+c5c846a8b1,22.0.1-32-g5ddfab5d3+60ce4897b0,22.0.1-4-g037fbe1+64e601228d,22.0.1-4-g8623105+b8044ec9de,22.0.1-5-g096abc9+d18c45d440,22.0.1-5-g15c806e+57f5c03693,22.0.1-7-gba73697+57f5c03693,master-g6e05de7fdc+c1283a92b8,master-g72cdda8301+729191ecac,w.2021.39
LSST Data Management Base Package
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Functions | |
def | plantSources (bbox, kwid, sky, coordList, addPoissonNoise=True) |
def | makeRandomTransmissionCurve (rng, minWavelength=4000.0, maxWavelength=7000.0, nWavelengths=200, maxRadius=80.0, nRadii=30, perturb=0.05) |
def | makeDefectList () |
def lsst.meas.algorithms.testUtils.makeDefectList | ( | ) |
Create a list of defects that can be used for testing. Returns ------- defectList = `list` [`lsst.meas.algorithms.Defect`] The list of defects.
Definition at line 142 of file testUtils.py.
def lsst.meas.algorithms.testUtils.makeRandomTransmissionCurve | ( | rng, | |
minWavelength = 4000.0 , |
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maxWavelength = 7000.0 , |
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nWavelengths = 200 , |
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maxRadius = 80.0 , |
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nRadii = 30 , |
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perturb = 0.05 |
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) |
Create a random TransmissionCurve with nontrivial spatial and wavelength variation. Parameters ---------- rng : numpy.random.RandomState Random number generator. minWavelength : float Average minimum wavelength for generated TransmissionCurves (will be randomly perturbed). maxWavelength : float Average maximum wavelength for generated TransmissionCurves (will be randomly perturbed). nWavelengths : int Number of samples in the wavelength dimension. maxRadius : float Average maximum radius for spatial variation (will be perturbed). nRadii : int Number of samples in the radial dimension. perturb: float Fraction by which wavelength and radius bounds should be randomly perturbed.
Definition at line 98 of file testUtils.py.
def lsst.meas.algorithms.testUtils.plantSources | ( | bbox, | |
kwid, | |||
sky, | |||
coordList, | |||
addPoissonNoise = True |
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) |
Make an exposure with stars (modelled as Gaussians) Parameters ---------- bbox : `lsst.geom.Box2I` Parent bbox of exposure kwid : `int` Kernal width (and height; kernal is square) sky : `float` Amount of sky background (counts) coordList : `list [tuple]` A list of [x, y, counts, sigma] where: * x,y are relative to exposure origin * counts is the integrated counts for the star * sigma is the Gaussian sigma in pixels addPoissonNoise : `bool` If True: add Poisson noise to the exposure
Definition at line 34 of file testUtils.py.