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# 

# LSST Data Management System 

# Copyright 2008-2016 LSST Corporation. 

# 

# 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 <http://www.lsstcorp.org/LegalNotices/>. 

# 

import unittest 

 

 

import lsst.utils.tests 

import lsst.afw.image as afwImage 

import lsst.afw.math as afwMath 

import lsst.geom as geom 

import lsst.ip.diffim as ipDiffim 

import lsst.log.utils as logUtils 

import lsst.pex.config as pexConfig 

import numpy as num 

 

verbosity = 0 

logUtils.traceSetAt("ip.diffim", verbosity) 

 

 

class DiffimTestCases(unittest.TestCase): 

 

def setUp(self): 

self.config = ipDiffim.ImagePsfMatchTask.ConfigClass() 

self.subconfig = self.config.kernel["DF"] 

self.ps = pexConfig.makePropertySet(self.subconfig) 

 

def tearDown(self): 

del self.ps 

 

def testImageStatisticsNan(self, core=3): 

numArray = num.zeros((20, 20)) 

mi = afwImage.MaskedImageF(geom.Extent2I(20, 20)) 

for j in range(mi.getHeight()): 

for i in range(mi.getWidth()): 

mi[i, j, afwImage.LOCAL] = (numArray[j][i], 0x0, 0) 

 

# inverse variance weight of 0 is NaN 

imstat = ipDiffim.ImageStatisticsF(self.ps) 

imstat.apply(mi) 

self.assertEqual(imstat.getNpix(), 0) 

 

imstat = ipDiffim.ImageStatisticsF(self.ps) 

imstat.apply(mi, core) 

self.assertEqual(imstat.getNpix(), 0) 

 

def testImageStatisticsZero(self): 

numArray = num.zeros((20, 20)) 

mi = afwImage.MaskedImageF(geom.Extent2I(20, 20)) 

for j in range(mi.getHeight()): 

for i in range(mi.getWidth()): 

mi[i, j, afwImage.LOCAL] = (numArray[j][i], 0x0, 1) 

 

imstat = ipDiffim.ImageStatisticsF(self.ps) 

imstat.apply(mi) 

 

self.assertEqual(imstat.getMean(), 0) 

self.assertEqual(imstat.getRms(), 0) 

self.assertEqual(imstat.getNpix(), 20*20) 

 

def testImageStatisticsOne(self): 

numArray = num.ones((20, 20)) 

mi = afwImage.MaskedImageF(geom.Extent2I(20, 20)) 

for j in range(mi.getHeight()): 

for i in range(mi.getWidth()): 

mi[i, j, afwImage.LOCAL] = (numArray[j][i], 0x0, 1) 

 

imstat = ipDiffim.ImageStatisticsF(self.ps) 

imstat.apply(mi) 

 

self.assertEqual(imstat.getMean(), 1) 

self.assertEqual(imstat.getRms(), 0) 

self.assertEqual(imstat.getNpix(), 20*20) 

 

def testImageStatisticsCore(self, core=3): 

numArray = num.ones((20, 20)) 

mi = afwImage.MaskedImageF(geom.Extent2I(20, 20)) 

for j in range(mi.getHeight()): 

for i in range(mi.getWidth()): 

mi[i, j, afwImage.LOCAL] = (numArray[j][i], 0x0, 1) 

 

imstat = ipDiffim.ImageStatisticsF(self.ps) 

imstat.apply(mi, core) 

 

self.assertEqual(imstat.getMean(), 1) 

self.assertEqual(imstat.getRms(), 0) 

self.assertEqual(imstat.getNpix(), (2*core+1)**2) 

 

def testImageStatisticsGeneral(self): 

numArray = num.ones((20, 20)) 

mi = afwImage.MaskedImageF(geom.Extent2I(20, 20)) 

for j in range(mi.getHeight()): 

for i in range(mi.getWidth()): 

val = i + 2.3 * j 

mi[i, j, afwImage.LOCAL] = (val, 0x0, 1) 

numArray[j][i] = val 

 

imstat = ipDiffim.ImageStatisticsF(self.ps) 

imstat.apply(mi) 

 

self.assertAlmostEqual(imstat.getMean(), numArray.mean()) 

# note that these don't agree exactly... 

self.assertAlmostEqual(imstat.getRms(), numArray.std(), 1) 

self.assertEqual(imstat.getNpix(), 20 * 20) 

 

afwStat = afwMath.makeStatistics(mi.getImage(), afwMath.MEAN | afwMath.STDEV) 

self.assertAlmostEqual(imstat.getMean(), afwStat.getValue(afwMath.MEAN)) 

# even though these do 

self.assertAlmostEqual(imstat.getRms(), afwStat.getValue(afwMath.STDEV)) 

 

def testImageStatisticsMask1(self): 

# Mask value that gets ignored 

maskPlane = self.ps.getArray("badMaskPlanes")[0] 

maskVal = afwImage.Mask.getPlaneBitMask(maskPlane) 

numArray = num.ones((20, 19)) 

mi = afwImage.MaskedImageF(geom.Extent2I(20, 20)) 

for j in range(mi.getHeight()): 

for i in range(mi.getWidth()): 

val = i + 2.3 * j 

 

if i == 19: 

mi[i, j, afwImage.LOCAL] = (val, maskVal, 1) 

else: 

mi[i, j, afwImage.LOCAL] = (val, 0x0, 1) 

numArray[j][i] = val 

 

imstat = ipDiffim.ImageStatisticsF(self.ps) 

imstat.apply(mi) 

 

self.assertAlmostEqual(imstat.getMean(), numArray.mean()) 

# note that these don't agree exactly... 

self.assertAlmostEqual(imstat.getRms(), numArray.std(), 1) 

self.assertEqual(imstat.getNpix(), 20 * (20 - 1)) 

 

def testImageStatisticsMask2(self): 

# Mask value that does not get ignored 

maskPlanes = self.ps.getArray("badMaskPlanes") 

for maskPlane in ("BAD", "EDGE", "CR", "SAT", "INTRP"): 

if maskPlane not in maskPlanes: 

maskVal = afwImage.Mask.getPlaneBitMask(maskPlane) 

break 

self.assertGreater(maskVal, 0) 

 

numArray = num.ones((20, 20)) 

mi = afwImage.MaskedImageF(geom.Extent2I(20, 20)) 

for j in range(mi.getHeight()): 

for i in range(mi.getWidth()): 

val = i + 2.3 * j 

 

if i == 19: 

mi[i, j, afwImage.LOCAL] = (val, maskVal, 1) 

numArray[j][i] = val 

else: 

mi[i, j, afwImage.LOCAL] = (val, 0x0, 1) 

numArray[j][i] = val 

 

imstat = ipDiffim.ImageStatisticsF(self.ps) 

imstat.apply(mi) 

 

self.assertAlmostEqual(imstat.getMean(), numArray.mean()) 

# note that these don't agree exactly... 

self.assertAlmostEqual(imstat.getRms(), numArray.std(), 1) 

self.assertEqual(imstat.getNpix(), 20 * 20) 

 

 

##### 

 

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

pass 

 

 

def setup_module(module): 

lsst.utils.tests.init() 

 

 

193 ↛ 194line 193 didn't jump to line 194, because the condition on line 193 was never trueif __name__ == "__main__": 

lsst.utils.tests.init() 

unittest.main()