Coverage for python/lsst/meas/algorithms/testUtils.py : 14%

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1#
2# LSST Data Management System
3#
4# Copyright 2008-2017 AURA/LSST.
5#
6# This product includes software developed by the
7# LSST Project (http://www.lsst.org/).
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the LSST License Statement and
20# the GNU General Public License along with this program. If not,
21# see <https://www.lsstcorp.org/LegalNotices/>.
22#
24import numpy as np
26import lsst.geom
27import lsst.afw.image as afwImage
28from . import SingleGaussianPsf
29from . import Defect
32def plantSources(bbox, kwid, sky, coordList, addPoissonNoise=True):
33 """Make an exposure with stars (modelled as Gaussians)
35 @param bbox: parent bbox of exposure
36 @param kwid: kernel width (and height; kernel is square)
37 @param sky: amount of sky background (counts)
38 @param coordList: a list of [x, y, counts, sigma], where:
39 * x,y are relative to exposure origin
40 * counts is the integrated counts for the star
41 * sigma is the Gaussian sigma in pixels
42 @param addPoissonNoise: add Poisson noise to the exposure?
43 """
44 # make an image with sources
45 img = afwImage.ImageD(bbox)
46 meanSigma = 0.0
47 for coord in coordList:
48 x, y, counts, sigma = coord
49 meanSigma += sigma
51 # make a single gaussian psf
52 psf = SingleGaussianPsf(kwid, kwid, sigma)
54 # make an image of it and scale to the desired number of counts
55 thisPsfImg = psf.computeImage(lsst.geom.PointD(x, y))
56 thisPsfImg *= counts
58 # bbox a window in our image and add the fake star image
59 psfBox = thisPsfImg.getBBox()
60 psfBox.clip(bbox)
61 if psfBox != thisPsfImg.getBBox():
62 thisPsfImg = thisPsfImg[psfBox, afwImage.PARENT]
63 imgSeg = img[psfBox, afwImage.PARENT]
64 imgSeg += thisPsfImg
65 meanSigma /= len(coordList)
67 img += sky
69 # add Poisson noise
70 if (addPoissonNoise):
71 np.random.seed(seed=1) # make results reproducible
72 imgArr = img.getArray()
73 imgArr[:] = np.random.poisson(imgArr)
75 # bundle into a maskedimage and an exposure
76 mask = afwImage.Mask(bbox)
77 var = img.convertFloat()
78 img -= sky
79 mimg = afwImage.MaskedImageF(img.convertFloat(), mask, var)
80 exposure = afwImage.makeExposure(mimg)
82 # insert an approximate psf
83 psf = SingleGaussianPsf(kwid, kwid, meanSigma)
84 exposure.setPsf(psf)
86 return exposure
89def makeRandomTransmissionCurve(rng, minWavelength=4000.0, maxWavelength=7000.0, nWavelengths=200,
90 maxRadius=80.0, nRadii=30, perturb=0.05):
91 """Create a random TransmissionCurve with nontrivial spatial and
92 wavelength variation.
94 Parameters
95 ----------
96 rng : numpy.random.RandomState
97 Random number generator.
98 minWavelength : float
99 Average minimum wavelength for generated TransmissionCurves (will be
100 randomly perturbed).
101 maxWavelength : float
102 Average maximum wavelength for generated TransmissionCurves (will be
103 randomly perturbed).
104 nWavelengths : int
105 Number of samples in the wavelength dimension.
106 maxRadius : float
107 Average maximum radius for spatial variation (will be perturbed).
108 nRadii : int
109 Number of samples in the radial dimension.
110 perturb: float
111 Fraction by which wavelength and radius bounds should be randomly
112 perturbed.
113 """
114 dWavelength = maxWavelength - minWavelength
116 def perturbed(x, s=perturb*dWavelength):
117 return x + 2.0*s*(rng.rand() - 0.5)
119 wavelengths = np.linspace(perturbed(minWavelength), perturbed(maxWavelength), nWavelengths)
120 radii = np.linspace(0.0, perturbed(maxRadius, perturb*maxRadius), nRadii)
121 throughput = np.zeros(wavelengths.shape + radii.shape, dtype=float)
122 # throughput will be a rectangle in wavelength, shifting to higher wavelengths and shrinking
123 # in height with radius, going to zero at all bounds.
124 peak0 = perturbed(0.9, 0.05)
125 start0 = perturbed(minWavelength + 0.25*dWavelength)
126 stop0 = perturbed(minWavelength + 0.75*dWavelength)
127 for i, r in enumerate(radii):
128 mask = np.logical_and(wavelengths >= start0 + r, wavelengths <= stop0 + r)
129 throughput[mask, i] = peak0*(1.0 - r/1000.0)
130 return afwImage.TransmissionCurve.makeRadial(throughput, wavelengths, radii)
133def makeDefectList():
134 """Create a list of defects that can be used for testing.
136 Returns
137 -------
138 defectList = `list` [`lsst.meas.algorithms.Defect`]
139 The list of defects.
140 """
141 defectList = [Defect(lsst.geom.Box2I(lsst.geom.Point2I(962, 0),
142 lsst.geom.Extent2I(2, 4611))),
143 Defect(lsst.geom.Box2I(lsst.geom.Point2I(1316, 0),
144 lsst.geom.Extent2I(2, 4611))),
145 Defect(lsst.geom.Box2I(lsst.geom.Point2I(1576, 0),
146 lsst.geom.Extent2I(4, 4611))),
147 Defect(lsst.geom.Box2I(lsst.geom.Point2I(1626, 0),
148 lsst.geom.Extent2I(2, 4611))),
149 Defect(lsst.geom.Box2I(lsst.geom.Point2I(1994, 252),
150 lsst.geom.Extent2I(2, 4359))),
151 Defect(lsst.geom.Box2I(lsst.geom.Point2I(1426, 702),
152 lsst.geom.Extent2I(2, 3909))),
153 Defect(lsst.geom.Box2I(lsst.geom.Point2I(1526, 1140),
154 lsst.geom.Extent2I(2, 3471))),
155 Defect(lsst.geom.Box2I(lsst.geom.Point2I(856, 2300),
156 lsst.geom.Extent2I(2, 2311))),
157 Defect(lsst.geom.Box2I(lsst.geom.Point2I(858, 2328),
158 lsst.geom.Extent2I(2, 65))),
159 Defect(lsst.geom.Box2I(lsst.geom.Point2I(859, 2328),
160 lsst.geom.Extent2I(1, 56))),
161 Defect(lsst.geom.Box2I(lsst.geom.Point2I(844, 2796),
162 lsst.geom.Extent2I(4, 1814))),
163 Defect(lsst.geom.Box2I(lsst.geom.Point2I(1366, 2804),
164 lsst.geom.Extent2I(2, 1806))),
165 Defect(lsst.geom.Box2I(lsst.geom.Point2I(1766, 3844),
166 lsst.geom.Extent2I(2, 766))),
167 Defect(lsst.geom.Box2I(lsst.geom.Point2I(1872, 4228),
168 lsst.geom.Extent2I(2, 382))),
169 ]
171 return defectList