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# 

# LSST Data Management System 

# 

# Copyright 2008-2016 AURA/LSST. 

# 

# This product includes software developed by the 

# LSST Project (http://www.lsst.org/). 

# 

# This program is free software: you can redistribute it and/or modify 

# it under the terms of the GNU General Public License as published by 

# the Free Software Foundation, either version 3 of the License, or 

# (at your option) any later version. 

# 

# This program is distributed in the hope that it will be useful, 

# but WITHOUT ANY WARRANTY; without even the implied warranty of 

# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

# GNU General Public License for more details. 

# 

# You should have received a copy of the LSST License Statement and 

# the GNU General Public License along with this program. If not, 

# see <https://www.lsstcorp.org/LegalNotices/>. 

# 

import math 

import numpy as np 

import unittest 

 

import lsst.utils.tests 

import lsst.afw.image as afwImage 

import lsst.afw.detection as afwDetection 

import lsst.afw.geom as afwGeom 

import lsst.afw.math as afwMath 

import lsst.afw.table as afwTable 

import lsst.afw.display.ds9 as ds9 

import lsst.daf.base as dafBase 

import lsst.meas.algorithms as measAlg 

# register the PSF determiner 

import lsst.meas.extensions.psfex.psfexPsfDeterminer 

assert lsst.meas.extensions.psfex.psfexPsfDeterminer # make pyflakes happy 

from lsst.meas.base import SingleFrameMeasurementTask 

 

try: 

type(verbose) 

except NameError: 

verbose = 0 

display = False 

 

#-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- 

 

 

def psfVal(ix, iy, x, y, sigma1, sigma2, b): 

"""Return the value at (ix, iy) of a double Gaussian 

(N(0, sigma1^2) + b*N(0, sigma2^2))/(1 + b) 

centered at (x, y) 

""" 

dx, dy = x - ix, y - iy 

theta = np.radians(30) 

ab = 1.0/0.75 # axis ratio 

c, s = np.cos(theta), np.sin(theta) 

u, v = c*dx - s*dy, s*dx + c*dy 

 

return (math.exp(-0.5*(u**2 + (v*ab)**2)/sigma1**2) + 

b*math.exp(-0.5*(u**2 + (v*ab)**2)/sigma2**2))/(1 + b) 

 

 

class SpatialModelPsfTestCase(unittest.TestCase): 

"""A test case for SpatialModelPsf""" 

 

def measure(self, footprintSet, exposure): 

"""Measure a set of Footprints, returning a SourceCatalog""" 

catalog = afwTable.SourceCatalog(self.schema) 

71 ↛ 72line 71 didn't jump to line 72, because the condition on line 71 was never true if display: 

ds9.mtv(exposure, title="Original", frame=0) 

 

footprintSet.makeSources(catalog) 

 

self.measureSources.run(catalog, exposure) 

return catalog 

 

def setUp(self): 

config = SingleFrameMeasurementTask.ConfigClass() 

config.slots.apFlux = 'base_CircularApertureFlux_12_0' 

self.schema = afwTable.SourceTable.makeMinimalSchema() 

 

self.measureSources = SingleFrameMeasurementTask(self.schema, config=config) 

 

width, height = 110, 301 

 

self.mi = afwImage.MaskedImageF(afwGeom.ExtentI(width, height)) 

self.mi.set(0) 

sd = 3 # standard deviation of image 

self.mi.getVariance().set(sd*sd) 

self.mi.getMask().addMaskPlane("DETECTED") 

 

self.ksize = 31 # size of desired kernel 

 

sigma1 = 1.75 

sigma2 = 2*sigma1 

 

self.exposure = afwImage.makeExposure(self.mi) 

self.exposure.setPsf(measAlg.DoubleGaussianPsf(self.ksize, self.ksize, 

1.5*sigma1, 1, 0.1)) 

cdMatrix = np.array([1.0, 0.0, 0.0, 1.0]) 

cdMatrix.shape = (2, 2) 

wcs = afwGeom.makeSkyWcs(crpix=afwGeom.PointD(0, 0), 

crval=afwGeom.SpherePoint(0.0, 0.0, afwGeom.degrees), 

cdMatrix=cdMatrix) 

self.exposure.setWcs(wcs) 

 

# 

# Make a kernel with the exactly correct basis functions. Useful for debugging 

# 

basisKernelList = [] 

for sigma in (sigma1, sigma2): 

basisKernel = afwMath.AnalyticKernel(self.ksize, self.ksize, 

afwMath.GaussianFunction2D(sigma, sigma)) 

basisImage = afwImage.ImageD(basisKernel.getDimensions()) 

basisKernel.computeImage(basisImage, True) 

basisImage /= np.sum(basisImage.getArray()) 

 

if sigma == sigma1: 

basisImage0 = basisImage 

else: 

basisImage -= basisImage0 

 

basisKernelList.append(afwMath.FixedKernel(basisImage)) 

 

order = 1 # 1 => up to linear 

spFunc = afwMath.PolynomialFunction2D(order) 

 

exactKernel = afwMath.LinearCombinationKernel(basisKernelList, spFunc) 

exactKernel.setSpatialParameters([[1.0, 0, 0], 

[0.0, 0.5*1e-2, 0.2e-2]]) 

 

rand = afwMath.Random() # make these tests repeatable by setting seed 

 

addNoise = True 

 

138 ↛ 144line 138 didn't jump to line 144, because the condition on line 138 was never false if addNoise: 

im = self.mi.getImage() 

afwMath.randomGaussianImage(im, rand) # N(0, 1) 

im *= sd # N(0, sd^2) 

del im 

 

xarr, yarr = [], [] 

 

for x, y in [(20, 20), (60, 20), 

(30, 35), 

(50, 50), 

(20, 90), (70, 160), (25, 265), (75, 275), (85, 30), 

(50, 120), (70, 80), 

(60, 210), (20, 210), 

]: 

xarr.append(x) 

yarr.append(y) 

 

for x, y in zip(xarr, yarr): 

dx = rand.uniform() - 0.5 # random (centered) offsets 

dy = rand.uniform() - 0.5 

 

k = exactKernel.getSpatialFunction(1)(x, y) # functional variation of Kernel ... 

b = (k*sigma1**2/((1 - k)*sigma2**2)) # ... converted double Gaussian's "b" 

 

#flux = 80000 - 20*x - 10*(y/float(height))**2 

flux = 80000*(1 + 0.1*(rand.uniform() - 0.5)) 

I0 = flux*(1 + b)/(2*np.pi*(sigma1**2 + b*sigma2**2)) 

for iy in range(y - self.ksize//2, y + self.ksize//2 + 1): 

167 ↛ 168line 167 didn't jump to line 168, because the condition on line 167 was never true if iy < 0 or iy >= self.mi.getHeight(): 

continue 

 

for ix in range(x - self.ksize//2, x + self.ksize//2 + 1): 

171 ↛ 172line 171 didn't jump to line 172, because the condition on line 171 was never true if ix < 0 or ix >= self.mi.getWidth(): 

continue 

 

I = I0*psfVal(ix, iy, x + dx, y + dy, sigma1, sigma2, b) 

Isample = rand.poisson(I) if addNoise else I 

self.mi.getImage().set(ix, iy, self.mi.getImage().get(ix, iy) + Isample) 

self.mi.getVariance().set(ix, iy, self.mi.getVariance().get(ix, iy) + I) 

 

bbox = afwGeom.BoxI(afwGeom.PointI(0, 0), afwGeom.ExtentI(width, height)) 

self.cellSet = afwMath.SpatialCellSet(bbox, 100) 

 

self.footprintSet = afwDetection.FootprintSet(self.mi, afwDetection.Threshold(100), "DETECTED") 

 

self.catalog = self.measure(self.footprintSet, self.exposure) 

 

for source in self.catalog: 

try: 

cand = measAlg.makePsfCandidate(source, self.exposure) 

self.cellSet.insertCandidate(cand) 

 

except Exception as e: 

print(e) 

continue 

 

def tearDown(self): 

del self.cellSet 

del self.exposure 

del self.mi 

del self.footprintSet 

del self.catalog 

del self.schema 

del self.measureSources 

 

def setupDeterminer(self, exposure): 

"""Setup the starSelector and psfDeterminer""" 

starSelectorClass = measAlg.sourceSelectorRegistry["objectSize"] 

starSelectorConfig = starSelectorClass.ConfigClass() 

starSelectorConfig.sourceFluxField = "base_GaussianFlux_flux" 

starSelectorConfig.badFlags = ["base_PixelFlags_flag_edge", 

"base_PixelFlags_flag_interpolatedCenter", 

"base_PixelFlags_flag_saturatedCenter", 

"base_PixelFlags_flag_crCenter", 

] 

starSelectorConfig.widthStdAllowed = 0.5 # Set to match when the tolerance of the test was set 

 

self.starSelector = starSelectorClass(config=starSelectorConfig) 

 

self.makePsfCandidates = measAlg.MakePsfCandidatesTask() 

 

psfDeterminerClass = measAlg.psfDeterminerRegistry["psfex"] 

psfDeterminerConfig = psfDeterminerClass.ConfigClass() 

width, height = exposure.getMaskedImage().getDimensions() 

psfDeterminerConfig.sizeCellX = width 

psfDeterminerConfig.sizeCellY = height//3 

psfDeterminerConfig.spatialOrder = 1 

 

self.psfDeterminer = psfDeterminerClass(psfDeterminerConfig) 

 

def subtractStars(self, exposure, catalog, chi_lim=-1): 

"""Subtract the exposure's PSF from all the sources in catalog""" 

mi, psf = exposure.getMaskedImage(), exposure.getPsf() 

 

subtracted = mi.Factory(mi, True) 

for s in catalog: 

xc, yc = s.getX(), s.getY() 

bbox = subtracted.getBBox(afwImage.PARENT) 

237 ↛ 234line 237 didn't jump to line 234, because the condition on line 237 was never false if bbox.contains(afwGeom.PointI(int(xc), int(yc))): 

try: 

measAlg.subtractPsf(psf, subtracted, xc, yc) 

except: 

pass 

chi = subtracted.Factory(subtracted, True) 

var = subtracted.getVariance() 

np.sqrt(var.getArray(), var.getArray()) # inplace sqrt 

chi /= var 

 

247 ↛ 248line 247 didn't jump to line 248, because the condition on line 247 was never true if display: 

ds9.mtv(subtracted, title="Subtracted", frame=1) 

ds9.mtv(chi, title="Chi", frame=2) 

xc, yc = exposure.getWidth()//2, exposure.getHeight()//2 

ds9.mtv(psf.computeImage(afwGeom.Point2D(xc, yc)), title="Psf %.1f,%.1f" % (xc, yc), frame=3) 

 

chi_min, chi_max = np.min(chi.getImage().getArray()), np.max(chi.getImage().getArray()) 

if False: 

print(chi_min, chi_max) 

 

257 ↛ exitline 257 didn't return from function 'subtractStars', because the condition on line 257 was never false if chi_lim > 0: 

self.assertGreater(chi_min, -chi_lim) 

self.assertLess(chi_max, chi_lim) 

 

def testPsfexDeterminer(self): 

"""Test the (Psfex) psfDeterminer on subImages""" 

 

self.setupDeterminer(self.exposure) 

metadata = dafBase.PropertyList() 

 

stars = self.starSelector.run(self.catalog, exposure=self.exposure) 

psfCandidateList = self.makePsfCandidates.run(stars.sourceCat, exposure=self.exposure).psfCandidates 

psf, cellSet = self.psfDeterminer.determinePsf(self.exposure, psfCandidateList, metadata) 

self.exposure.setPsf(psf) 

 

# Test how well we can subtract the PSF model 

self.subtractStars(self.exposure, self.catalog, chi_lim=5.6) 

 

# Test PsfexPsf.computeBBox 

self.assertEqual(psf.computeBBox(), psf.computeKernelImage().getBBox()) 

self.assertEqual(psf.computeBBox(), psf.getKernel().getBBox()) 

 

#-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- 

 

 

class TestMemory(lsst.utils.tests.MemoryTestCase): 

pass 

 

 

def setup_module(module): 

lsst.utils.tests.init() 

 

289 ↛ 290line 289 didn't jump to line 290, because the condition on line 289 was never trueif __name__ == "__main__": 

lsst.utils.tests.init() 

unittest.main()