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from builtins import range 

# 

# 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 unittest 

import os 

import glob 

import numpy 

 

import lsst.utils.tests 

import lsst.shapelet 

import lsst.afw.geom.ellipses 

import lsst.log 

import lsst.log.utils 

import lsst.meas.modelfit 

import lsst.meas.base 

 

numpy.random.seed(500) 

 

# Set trace to 0-5 to view debug messages. Level 5 enables all traces. 

lsst.log.utils.traceSetAt("meas.modelfit.optimizer.Optimizer", -1) 

lsst.log.utils.traceSetAt("meas.modelfit.optimizer.solveTrustRegion", -1) 

 

ELLIPSE_PARAMETER_NAMES = ["eta1", "eta2", "logR", "x", "y"] 

DATA_DIR = os.path.join(os.environ["MEAS_MODELFIT_DIR"], "tests", "data") 

 

 

def computeMoments(image): 

"""Helper function to compute moments of a postage stamp about its origin.""" 

maskedImage = lsst.afw.image.MaskedImageD(image) 

result = lsst.meas.base.SdssShapeAlgorithm.computeAdaptiveMoments( 

maskedImage, 

lsst.afw.geom.Point2D(0.0, 0.0) 

) 

return result.getShape() 

 

 

class GeneralPsfFitterTestCase(lsst.utils.tests.TestCase): 

 

def setUp(self): 

self.configs = {} 

self.configs['fixed'] = lsst.meas.modelfit.GeneralPsfFitterConfig() 

self.configs['fixed'].primary.ellipticityPriorSigma = 0.0 

self.configs['fixed'].primary.radiusPriorSigma = 0.0 

self.configs['fixed'].primary.positionPriorSigma = 0.0 

self.configs['fixed'].wings.ellipticityPriorSigma = 0.0 

self.configs['fixed'].wings.radiusPriorSigma = 0.0 

self.configs['fixed'].wings.positionPriorSigma = 0.0 

self.configs['ellipse'] = lsst.meas.modelfit.GeneralPsfFitterConfig() 

self.configs['ellipse'].primary.positionPriorSigma = 0.0 

self.configs['ellipse'].wings.positionPriorSigma = 0.0 

self.configs['full'] = lsst.meas.modelfit.GeneralPsfFitterConfig() 

self.configs['full'].inner.order = 0 

self.configs['full'].primary.order = 4 

self.configs['full'].wings.order = 4 

self.configs['full'].outer.order = 0 

self.configs['full'].inner.ellipticityPriorSigma = 0.3 

self.configs['full'].inner.radiusPriorSigma = 0.5 

self.configs['full'].inner.positionPriorSigma = 0.1 

self.configs['full'].primary.ellipticityPriorSigma = 0.3 

self.configs['full'].primary.radiusPriorSigma = 0.5 

self.configs['full'].primary.positionPriorSigma = 0.1 

self.configs['full'].wings.ellipticityPriorSigma = 0.3 

self.configs['full'].wings.radiusPriorSigma = 0.5 

self.configs['full'].wings.positionPriorSigma = 0.1 

self.configs['full'].outer.ellipticityPriorSigma = 0.3 

self.configs['full'].outer.radiusPriorSigma = 0.5 

self.configs['full'].outer.positionPriorSigma = 0.1 

 

def tearDown(self): 

del self.configs 

 

def testFixedModel(self): 

fitter = lsst.meas.modelfit.GeneralPsfFitter(self.configs['fixed'].makeControl()) 

model = fitter.getModel() 

 

# check that we have the right numbers and names for parameters 

self.assertEqual(model.getNonlinearDim(), 0) 

self.assertEqual(model.getFixedDim(), 10) 

self.assertEqual(model.getAmplitudeDim(), 2) 

self.assertEqual(model.getBasisCount(), 2) 

self.assertEqual(list(model.getNonlinearNames()), []) 

self.assertEqual(list(model.getAmplitudeNames()), ["primary.alpha[0,0]", "wings.alpha[0,0]"]) 

self.assertEqual(list(model.getFixedNames()), 

["primary.fiducial.%s" % s for s in ELLIPSE_PARAMETER_NAMES] + 

["wings.fiducial.%s" % s for s in ELLIPSE_PARAMETER_NAMES]) 

 

# test that we can round-trip ellipses through the model, and that this agrees 

# with makeShapeletFunction 

ellipseParameters = numpy.array([[0.01, -0.01, 1.1, 0.03, -0.04], 

[0.02, -0.02, 0.9, 0.05, -0.06]]) 

ellipses1 = model.makeEllipseVector() 

for i in range(len(ellipses1)): 

ellipses1[i].setParameterVector(ellipseParameters[i]) 

nonlinear = numpy.zeros(model.getNonlinearDim(), dtype=lsst.meas.modelfit.Scalar) 

fixed = numpy.zeros(model.getFixedDim(), dtype=lsst.meas.modelfit.Scalar) 

amplitudes = numpy.array([1.0, 0.1], dtype=lsst.meas.modelfit.Scalar) 

model.readEllipses(ellipses1, nonlinear, fixed) 

self.assertFloatsAlmostEqual(fixed, ellipseParameters.ravel()) 

ellipses2 = model.writeEllipses(nonlinear, fixed) 

msf = model.makeShapeletFunction(nonlinear, amplitudes, fixed) 

self.assertFloatsAlmostEqual(len(msf.getComponents()), len(ellipses1)) 

ellipses3 = model.makeEllipseVector() 

for i in range(len(ellipses2)): 

self.assertFloatsAlmostEqual(ellipses1[i].getParameterVector(), ellipses2[i].getParameterVector()) 

# need to convert ellipse parametrization 

ellipses3[i].setCore(msf.getComponents()[i].getEllipse().getCore()) 

ellipses3[i].setCenter(msf.getComponents()[i].getEllipse().getCenter()) 

self.assertFloatsAlmostEqual(ellipses1[i].getParameterVector(), ellipses3[i].getParameterVector()) 

self.assertFloatsAlmostEqual(amplitudes[i:i+1], msf.getComponents()[i].getCoefficients()) 

 

def testEllipseModel(self): 

fitter = lsst.meas.modelfit.GeneralPsfFitter(self.configs['ellipse'].makeControl()) 

model = fitter.getModel() 

 

# check that we have the right numbers and names for parameters 

self.assertEqual(model.getNonlinearDim(), 6) 

self.assertEqual(model.getFixedDim(), 10) 

self.assertEqual(model.getAmplitudeDim(), 2) 

self.assertEqual(model.getBasisCount(), 2) 

self.assertEqual(list(model.getNonlinearNames()), 

["primary.%s" % s for s in ELLIPSE_PARAMETER_NAMES[:3]] + 

["wings.%s" % s for s in ELLIPSE_PARAMETER_NAMES[:3]] 

) 

self.assertEqual(list(model.getAmplitudeNames()), ["primary.alpha[0,0]", "wings.alpha[0,0]"]) 

self.assertEqual(list(model.getFixedNames()), 

["primary.fiducial.%s" % s for s in ELLIPSE_PARAMETER_NAMES] + 

["wings.fiducial.%s" % s for s in ELLIPSE_PARAMETER_NAMES]) 

 

# test that we can round-trip ellipses through the model, and that this agrees 

# with makeShapeletFunction 

ellipseParameters = numpy.array([[0.01, -0.01, 1.1, 0.03, -0.04], 

[0.02, -0.02, 0.9, 0.05, -0.06]]) 

ellipses1 = model.makeEllipseVector() 

for i in range(len(ellipses1)): 

ellipses1[i].setParameterVector(ellipseParameters[i]) 

nonlinear = numpy.zeros(model.getNonlinearDim(), dtype=lsst.meas.modelfit.Scalar) 

fixed = numpy.zeros(model.getFixedDim(), dtype=lsst.meas.modelfit.Scalar) 

amplitudes = numpy.array([1.0, 0.1], dtype=lsst.meas.modelfit.Scalar) 

model.readEllipses(ellipses1, nonlinear, fixed) 

self.assertFloatsAlmostEqual(nonlinear, numpy.zeros(model.getNonlinearDim(), 

dtype=lsst.meas.modelfit.Scalar)) 

self.assertFloatsAlmostEqual(fixed, ellipseParameters.ravel()) 

ellipses2 = model.writeEllipses(nonlinear, fixed) 

msf = model.makeShapeletFunction(nonlinear, amplitudes, fixed) 

self.assertEqual(len(msf.getComponents()), len(ellipses1)) 

ellipses3 = model.makeEllipseVector() 

for i in range(len(ellipses2)): 

self.assertFloatsAlmostEqual(ellipses1[i].getParameterVector(), ellipses2[i].getParameterVector(), 

rtol=1E-8) 

# need to convert ellipse parametrization 

ellipses3[i].setCore(msf.getComponents()[i].getEllipse().getCore()) 

ellipses3[i].setCenter(msf.getComponents()[i].getEllipse().getCenter()) 

self.assertFloatsAlmostEqual(ellipses1[i].getParameterVector(), ellipses3[i].getParameterVector(), 

rtol=1E-8) 

self.assertFloatsAlmostEqual(amplitudes[i:i+1], msf.getComponents()[i].getCoefficients(), 

rtol=1E-8) 

 

# test the ellipse round-tripping again, this time starting with nonzero nonlinear parameters: 

# this will be read back in by adding to the fixed parameters and zeroing the nonlinear parameters. 

nonlinear[:] = 0.5*ellipseParameters[:, :3].ravel() 

ellipses4 = model.writeEllipses(nonlinear, fixed) 

model.readEllipses(ellipses4, nonlinear, fixed) 

self.assertFloatsAlmostEqual(nonlinear, numpy.zeros(model.getNonlinearDim(), 

dtype=lsst.meas.modelfit.Scalar), 

rtol=1E-8) 

self.assertFloatsAlmostEqual(fixed.reshape(2, 5)[:, :3], 1.5*ellipseParameters[:, :3], rtol=1E-8) 

self.assertFloatsAlmostEqual(fixed.reshape(2, 5)[:, 3:], ellipseParameters[:, 3:], rtol=1E-8) 

 

def testFullModel(self): 

fitter = lsst.meas.modelfit.GeneralPsfFitter(self.configs['full'].makeControl()) 

model = fitter.getModel() 

 

# check that we have the right numbers and names for parameters 

self.assertEqual(model.getNonlinearDim(), 20) 

self.assertEqual(model.getFixedDim(), 20) 

self.assertEqual(model.getAmplitudeDim(), 2*(1 + lsst.shapelet.computeSize(4))) 

self.assertEqual(model.getBasisCount(), 4) 

self.assertEqual(list(model.getNonlinearNames()), 

["inner.%s" % s for s in ELLIPSE_PARAMETER_NAMES] + 

["primary.%s" % s for s in ELLIPSE_PARAMETER_NAMES] + 

["wings.%s" % s for s in ELLIPSE_PARAMETER_NAMES] + 

["outer.%s" % s for s in ELLIPSE_PARAMETER_NAMES] 

) 

self.assertEqual(list(model.getAmplitudeNames()), 

["inner.alpha[0,0]"] + 

["primary.alpha[%d,%d]" % (x, y) 

for n, x, y in lsst.shapelet.HermiteIndexGenerator(4)] + 

["wings.alpha[%d,%d]" % (x, y) 

for n, x, y in lsst.shapelet.HermiteIndexGenerator(4)] + 

["outer.alpha[0,0]"]) 

self.assertEqual(list(model.getFixedNames()), 

["inner.fiducial.%s" % s for s in ELLIPSE_PARAMETER_NAMES] + 

["primary.fiducial.%s" % s for s in ELLIPSE_PARAMETER_NAMES] + 

["wings.fiducial.%s" % s for s in ELLIPSE_PARAMETER_NAMES] + 

["outer.fiducial.%s" % s for s in ELLIPSE_PARAMETER_NAMES] 

) 

 

# test that we can round-trip ellipses through the model, and that this agrees 

# with makeShapeletFunction 

ellipseParameters = numpy.array([[0.01, -0.01, 1.1, 0.03, -0.04], 

[0.015, -0.015, 1.0, 0.04, -0.05], 

[0.02, -0.02, 0.9, 0.05, -0.06], 

[0.025, -0.025, 0.8, 0.06, -0.07], 

]) 

ellipses1 = model.makeEllipseVector() 

for i in range(len(ellipses1)): 

ellipses1[i].setParameterVector(ellipseParameters[i]) 

nonlinear = numpy.zeros(model.getNonlinearDim(), dtype=lsst.meas.modelfit.Scalar) 

fixed = numpy.zeros(model.getFixedDim(), dtype=lsst.meas.modelfit.Scalar) 

amplitudes = numpy.random.randn(model.getAmplitudeDim()) 

model.readEllipses(ellipses1, nonlinear, fixed) 

self.assertFloatsAlmostEqual(nonlinear, numpy.zeros(model.getNonlinearDim(), 

dtype=lsst.meas.modelfit.Scalar)) 

self.assertFloatsAlmostEqual(fixed, ellipseParameters.ravel()) 

ellipses2 = model.writeEllipses(nonlinear, fixed) 

msf = model.makeShapeletFunction(nonlinear, amplitudes, fixed) 

self.assertFloatsAlmostEqual(len(msf.getComponents()), len(ellipses1)) 

ellipses3 = model.makeEllipseVector() 

amplitudeOffset = 0 

for i in range(len(ellipses2)): 

self.assertFloatsAlmostEqual(ellipses1[i].getParameterVector(), ellipses2[i].getParameterVector(), 

rtol=1E-8) 

# need to convert ellipse parametrization 

ellipses3[i].setCore(msf.getComponents()[i].getEllipse().getCore()) 

ellipses3[i].setCenter(msf.getComponents()[i].getEllipse().getCenter()) 

amplitudeCount = len(msf.getComponents()[i].getCoefficients()) 

self.assertFloatsAlmostEqual(ellipses1[i].getParameterVector(), ellipses3[i].getParameterVector(), 

rtol=1E-8) 

self.assertFloatsAlmostEqual(amplitudes[amplitudeOffset:amplitudeOffset+amplitudeCount], 

msf.getComponents()[i].getCoefficients(), rtol=1E-8) 

amplitudeOffset += amplitudeCount 

 

# test the ellipse round-tripping again, this time starting with nonzero nonlinear parameters: 

# this will be read back in by adding to the fixed parameters and zeroing the nonlinear parameters. 

nonlinear[:] = 0.5*ellipseParameters.ravel() 

ellipses4 = model.writeEllipses(nonlinear, fixed) 

model.readEllipses(ellipses4, nonlinear, fixed) 

self.assertFloatsAlmostEqual(nonlinear, numpy.zeros(model.getNonlinearDim(), 

dtype=lsst.meas.modelfit.Scalar)) 

self.assertFloatsAlmostEqual(fixed, 1.5*ellipseParameters.ravel()) 

 

def testApply(self): 

tolerances = {"full": 3E-4, "ellipse": 8E-3, "fixed": 1E-2} 

for filename in glob.glob(os.path.join(DATA_DIR, "psfs", "great3*.fits")): 

kernelImage = lsst.afw.image.ImageD(filename) 

shape = computeMoments(kernelImage) 

for configKey in ["full", "ellipse", "fixed"]: 

fitter = lsst.meas.modelfit.GeneralPsfFitter(self.configs[configKey].makeControl()) 

multiShapeletFit = fitter.apply(kernelImage, shape, 0.01) 

modelImage = lsst.afw.image.ImageD(kernelImage.getBBox(lsst.afw.image.PARENT)) 

multiShapeletFit.evaluate().addToImage(modelImage) 

self.assertFloatsAlmostEqual(kernelImage.getArray(), modelImage.getArray(), 

atol=tolerances[configKey], 

plotOnFailure=True) 

 

 

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

pass 

 

 

def setup_module(module): 

lsst.utils.tests.init() 

 

 

285 ↛ 286line 285 didn't jump to line 286, because the condition on line 285 was never trueif __name__ == "__main__": 

lsst.utils.tests.init() 

unittest.main()