def testGalaxyPhotometricIndices(self):
baselineCatName = os.path.join(
getPackageDir('sims_catUtils'), 'tests', 'scratchSpace',
'testPhotMix_testGalIndices_galaxyBaselineCatalog.txt')
if os.path.exists(baselineCatName):
os.unlink(baselineCatName)
baselineDtype = np.dtype([('galid', int), ('raObserved', float),
('decObserved', float), ('ctotal_u', float),
('ctotal_g', float), ('ctotal_r', float),
('ctotal_i', float), ('ctotal_z', float)])
obs_metadata_pointed = ObservationMetaData(mjd=50000.0,
boundType='circle',
pointingRA=0.0,
pointingDec=0.0,
boundLength=10.0)
baseline_cat = cartoonGalaxies(self.galaxy,
obs_metadata=obs_metadata_pointed)
baseline_cat.write_catalog(baselineCatName)
baselineData = np.genfromtxt(baselineCatName,
dtype=baselineDtype,
delimiter=',')
self.assertGreater(len(baselineData), 0)
testCatName = os.path.join(
getPackageDir('sims_catUtils'), 'tests', 'scratchSpace',
'testPhotMix_testGalIndices_galaxyTestCatalog.txt')
if os.path.exists(testCatName):
os.unlink(testCatName)
testDtype = np.dtype([('galid', int), ('raObserved', float),
('decObserved', float), ('ctotal_i', float),
('ctotal_g', float)])
test_cat = cartoonGalaxiesIG(self.galaxy,
obs_metadata=obs_metadata_pointed)
test_cat.write_catalog(testCatName)
testData = np.genfromtxt(testCatName, dtype=testDtype, delimiter=',')
self.assertGreater(len(testData), 0)
for b, t in zip(baselineData, testData):
self.assertAlmostEqual(b['ctotal_i'], t['ctotal_i'], 10)
self.assertAlmostEqual(b['ctotal_g'], t['ctotal_g'], 10)
if os.path.exists(baselineCatName):
os.unlink(baselineCatName)
if os.path.exists(testCatName):
os.unlink(testCatName)
def testAlternateBandpassesGalaxies(self):
"""
the same as testAlternateBandpassesStars, but for galaxies
"""
obs_metadata_pointed=ObservationMetaData(mjd=50000.0,
boundType='circle',unrefractedRA=0.0,unrefractedDec=0.0,
boundLength=10.0)
test_cat=cartoonGalaxies(self.galaxy,obs_metadata=obs_metadata_pointed)
test_cat.write_catalog("testGalaxiesCartoon.txt")
cartoonDir = os.getenv('SIMS_PHOTUTILS_DIR')+'/tests/cartoonSedTestData/'
testBandPasses = {}
keys = ['u','g','r','i','z']
bplist = []
for kk in keys:
testBandPasses[kk] = Bandpass()
testBandPasses[kk].readThroughput(os.path.join(cartoonDir,"test_bandpass_%s.dat" % kk))
bplist.append(testBandPasses[kk])
sedObj = Sed()
phiArray, waveLenStep = sedObj.setupPhiArray(bplist)
components = ['Bulge', 'Disk', 'Agn']
ct = 0
for cc in components:
i = 0
for ss in test_cat.sedMasterDict[cc]:
if ss.wavelen != None:
ss.resampleSED(wavelen_match = bplist[0].wavelen)
ss.flambdaTofnu()
mags = -2.5*numpy.log10(numpy.sum(phiArray*ss.fnu, axis=1)*waveLenStep) - ss.zp
for j in range(len(mags)):
ct += 1
self.assertAlmostEqual(mags[j],test_cat.magnitudeMasterDict[cc][i][j],10)
i += 1
self.assertTrue(ct>0)
os.unlink("testGalaxiesCartoon.txt")
def testGalaxyPhotometricIndices(self):
baselineCatName = 'galaxyBaselineCatalog.txt'
baselineDtype = numpy.dtype([('galid', int),
('raObserved', float),
('decObserved', float),
('ctotal_u', float),
('ctotal_g', float),
('ctotal_r', float),
('ctotal_i', float),
('ctotal_z', float)])
obs_metadata_pointed=ObservationMetaData(mjd=50000.0,
boundType='circle',unrefractedRA=0.0,unrefractedDec=0.0,
boundLength=10.0)
baseline_cat=cartoonGalaxies(self.galaxy,obs_metadata=obs_metadata_pointed)
baseline_cat.write_catalog(baselineCatName)
baselineData = numpy.genfromtxt(baselineCatName, dtype=baselineDtype, delimiter=',')
testCatName = 'galaxyTestCatalog.txt'
testDtype = numpy.dtype([('galid', int),
('raObserved', float),
('decObserved', float),
('ctotal_i', float),
('ctotal_g', float)])
test_cat = cartoonGalaxiesIG(self.galaxy, obs_metadata=obs_metadata_pointed)
test_cat.write_catalog(testCatName)
testData = numpy.genfromtxt(testCatName, dtype=testDtype, delimiter=',')
ct = 0
for b,t in zip(baselineData, testData):
self.assertAlmostEqual(b['ctotal_i'], t['ctotal_i'], 10)
self.assertAlmostEqual(b['ctotal_g'], t['ctotal_g'], 10)
ct += 1
self.assertTrue(ct>0)
if os.path.exists(baselineCatName):
os.unlink(baselineCatName)
if os.path.exists(testCatName):
os.unlink(testCatName)
def testGalaxyPhotometricIndices(self):
baselineDtype = np.dtype([('galid', int), ('raObserved', float),
('decObserved', float), ('ctotal_u', float),
('ctotal_g', float), ('ctotal_r', float),
('ctotal_i', float), ('ctotal_z', float)])
obs_metadata_pointed = ObservationMetaData(mjd=50000.0,
boundType='circle',
pointingRA=0.0,
pointingDec=0.0,
boundLength=10.0)
baseline_cat = cartoonGalaxies(self.galaxy,
obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as baselineCatName:
baseline_cat.write_catalog(baselineCatName)
baselineData = np.genfromtxt(baselineCatName,
dtype=baselineDtype,
delimiter=',')
self.assertGreater(len(baselineData), 0)
testDtype = np.dtype([('galid', int), ('raObserved', float),
('decObserved', float), ('ctotal_i', float),
('ctotal_g', float)])
test_cat = cartoonGalaxiesIG(self.galaxy,
obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as testCatName:
test_cat.write_catalog(testCatName)
testData = np.genfromtxt(testCatName,
dtype=testDtype,
delimiter=',')
self.assertGreater(len(testData), 0)
for b, t in zip(baselineData, testData):
self.assertAlmostEqual(b['ctotal_i'], t['ctotal_i'], 10)
self.assertAlmostEqual(b['ctotal_g'], t['ctotal_g'], 10)
def testGalaxyPhotometricIndices(self):
baselineDtype = np.dtype([('galid', int),
('raObserved', float),
('decObserved', float),
('ctotal_u', float),
('ctotal_g', float),
('ctotal_r', float),
('ctotal_i', float),
('ctotal_z', float)])
obs_metadata_pointed = ObservationMetaData(mjd=50000.0,
boundType='circle',
pointingRA=0.0, pointingDec=0.0,
boundLength=10.0)
baseline_cat = cartoonGalaxies(self.galaxy, obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as baselineCatName:
baseline_cat.write_catalog(baselineCatName)
baselineData = np.genfromtxt(baselineCatName, dtype=baselineDtype, delimiter=',')
self.assertGreater(len(baselineData), 0)
testDtype = np.dtype([('galid', int),
('raObserved', float),
('decObserved', float),
('ctotal_i', float),
('ctotal_g', float)])
test_cat = cartoonGalaxiesIG(self.galaxy, obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as testCatName:
test_cat.write_catalog(testCatName)
testData = np.genfromtxt(testCatName, dtype=testDtype, delimiter=',')
self.assertGreater(len(testData), 0)
for b, t in zip(baselineData, testData):
self.assertAlmostEqual(b['ctotal_i'], t['ctotal_i'], 10)
self.assertAlmostEqual(b['ctotal_g'], t['ctotal_g'], 10)
def testAlternateBandpassesGalaxies(self):
"""
the same as testAlternateBandpassesStars, but for galaxies
"""
obs_metadata_pointed = ObservationMetaData(mjd=50000.0,
boundType='circle',
pointingRA=0.0, pointingDec=0.0,
boundLength=10.0)
dtype = np.dtype([('galid', np.int),
('ra', np.float),
('dec', np.float),
('uTotal', np.float),
('gTotal', np.float),
('rTotal', np.float),
('iTotal', np.float),
('zTotal', np.float),
('uBulge', np.float),
('gBulge', np.float),
('rBulge', np.float),
('iBulge', np.float),
('zBulge', np.float),
('uDisk', np.float),
('gDisk', np.float),
('rDisk', np.float),
('iDisk', np.float),
('zDisk', np.float),
('uAgn', np.float),
('gAgn', np.float),
('rAgn', np.float),
('iAgn', np.float),
('zAgn', np.float),
('bulgeName', str, 200),
('bulgeNorm', np.float),
('bulgeAv', np.float),
('diskName', str, 200),
('diskNorm', np.float),
('diskAv', np.float),
('agnName', str, 200),
('agnNorm', np.float),
('redshift', np.float)])
test_cat = cartoonGalaxies(self.galaxy, obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as catName:
test_cat.write_catalog(catName)
catData = np.genfromtxt(catName, dtype=dtype, delimiter=', ')
self.assertGreater(len(catData), 0)
cartoonDir = getPackageDir('sims_photUtils')
cartoonDir = os.path.join(cartoonDir, 'tests', 'cartoonSedTestData')
sedDir = getPackageDir('sims_sed_library')
testBandpasses = {}
keys = ['u', 'g', 'r', 'i', 'z']
for kk in keys:
testBandpasses[kk] = Bandpass()
testBandpasses[kk].readThroughput(os.path.join(cartoonDir, "test_bandpass_%s.dat" % kk))
imsimBand = Bandpass()
imsimBand.imsimBandpass()
specMap = defaultSpecMap
ct = 0
for line in catData:
bulgeMagList = []
diskMagList = []
agnMagList = []
if line['bulgeName'] == 'None':
for bp in keys:
np.testing.assert_equal(line['%sBulge' % bp], np.NaN)
bulgeMagList.append(np.NaN)
else:
ct += 1
dummySed = Sed()
dummySed.readSED_flambda(os.path.join(sedDir, specMap[line['bulgeName']]))
fnorm = dummySed.calcFluxNorm(line['bulgeNorm'], imsimBand)
dummySed.multiplyFluxNorm(fnorm)
a_int, b_int = dummySed.setupCCM_ab()
dummySed.addDust(a_int, b_int, A_v=line['bulgeAv'])
dummySed.redshiftSED(line['redshift'], dimming=True)
dummySed.resampleSED(wavelen_match=testBandpasses['u'].wavelen)
for bpName in keys:
mag = dummySed.calcMag(testBandpasses[bpName])
self.assertAlmostEqual(mag, line['%sBulge' % bpName], 10)
bulgeMagList.append(mag)
if line['diskName'] == 'None':
for bp in keys:
np.assert_equal(line['%sDisk' % bp], np.NaN)
diskMagList.append(np.NaN)
else:
ct += 1
dummySed = Sed()
dummySed.readSED_flambda(os.path.join(sedDir, specMap[line['diskName']]))
fnorm = dummySed.calcFluxNorm(line['diskNorm'], imsimBand)
dummySed.multiplyFluxNorm(fnorm)
a_int, b_int = dummySed.setupCCM_ab()
dummySed.addDust(a_int, b_int, A_v=line['diskAv'])
dummySed.redshiftSED(line['redshift'], dimming=True)
dummySed.resampleSED(wavelen_match=testBandpasses['u'].wavelen)
for bpName in keys:
mag = dummySed.calcMag(testBandpasses[bpName])
self.assertAlmostEqual(mag, line['%sDisk' % bpName], 10)
diskMagList.append(mag)
if line['agnName'] == 'None':
for bp in keys:
np.testing.assert_true(line['%sAgn' % bp], np.NaN)
agnMagList.append(np.NaN)
else:
ct += 1
dummySed = Sed()
dummySed.readSED_flambda(os.path.join(sedDir, specMap[line['agnName']]))
fnorm = dummySed.calcFluxNorm(line['agnNorm'], imsimBand)
dummySed.multiplyFluxNorm(fnorm)
dummySed.redshiftSED(line['redshift'], dimming=True)
dummySed.resampleSED(wavelen_match=testBandpasses['u'].wavelen)
for bpName in keys:
mag = dummySed.calcMag(testBandpasses[bpName])
self.assertAlmostEqual(mag, line['%sAgn' % bpName], 10)
agnMagList.append(mag)
totalMags = PhotometryGalaxies().sum_magnitudes(bulge=np.array(bulgeMagList),
disk=np.array(diskMagList),
agn=np.array(agnMagList))
for testMag, bpName in zip(totalMags, keys):
if np.isnan(line['%sTotal' % bpName]):
np.testing.assert_equal(testMag, np.NaN)
else:
self.assertAlmostEqual(testMag, line['%sTotal' % bpName], 10)
self.assertGreater(ct, 0)
def testAlternateBandpassesGalaxies(self):
"""
the same as testAlternateBandpassesStars, but for galaxies
"""
obs_metadata_pointed = ObservationMetaData(mjd=50000.0,
boundType='circle',
pointingRA=0.0,
pointingDec=0.0,
boundLength=10.0)
dtype = np.dtype([('galid', np.int), ('ra', np.float),
('dec', np.float), ('uTotal', np.float),
('gTotal', np.float), ('rTotal', np.float),
('iTotal', np.float), ('zTotal', np.float),
('uBulge', np.float), ('gBulge', np.float),
('rBulge', np.float), ('iBulge', np.float),
('zBulge', np.float), ('uDisk', np.float),
('gDisk', np.float), ('rDisk', np.float),
('iDisk', np.float), ('zDisk', np.float),
('uAgn', np.float), ('gAgn', np.float),
('rAgn', np.float), ('iAgn', np.float),
('zAgn', np.float), ('bulgeName', str, 200),
('bulgeNorm', np.float), ('bulgeAv', np.float),
('diskName', str, 200), ('diskNorm', np.float),
('diskAv', np.float), ('agnName', str, 200),
('agnNorm', np.float), ('redshift', np.float)])
test_cat = cartoonGalaxies(self.galaxy,
obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as catName:
test_cat.write_catalog(catName)
catData = np.genfromtxt(catName, dtype=dtype, delimiter=', ')
self.assertGreater(len(catData), 0)
cartoonDir = getPackageDir('sims_photUtils')
cartoonDir = os.path.join(cartoonDir, 'tests', 'cartoonSedTestData')
sedDir = getPackageDir('sims_sed_library')
testBandpasses = {}
keys = ['u', 'g', 'r', 'i', 'z']
for kk in keys:
testBandpasses[kk] = Bandpass()
testBandpasses[kk].readThroughput(
os.path.join(cartoonDir, "test_bandpass_%s.dat" % kk))
imsimBand = Bandpass()
imsimBand.imsimBandpass()
specMap = defaultSpecMap
ct = 0
for line in catData:
bulgeMagList = []
diskMagList = []
agnMagList = []
if line['bulgeName'] == 'None':
for bp in keys:
np.testing.assert_equal(line['%sBulge' % bp], np.NaN)
bulgeMagList.append(np.NaN)
else:
ct += 1
dummySed = Sed()
dummySed.readSED_flambda(
os.path.join(sedDir, specMap[line['bulgeName']]))
fnorm = dummySed.calcFluxNorm(line['bulgeNorm'], imsimBand)
dummySed.multiplyFluxNorm(fnorm)
a_int, b_int = dummySed.setupCCM_ab()
dummySed.addDust(a_int, b_int, A_v=line['bulgeAv'])
dummySed.redshiftSED(line['redshift'], dimming=True)
dummySed.resampleSED(wavelen_match=testBandpasses['u'].wavelen)
for bpName in keys:
mag = dummySed.calcMag(testBandpasses[bpName])
self.assertAlmostEqual(mag, line['%sBulge' % bpName], 10)
bulgeMagList.append(mag)
if line['diskName'] == 'None':
for bp in keys:
np.assert_equal(line['%sDisk' % bp], np.NaN)
diskMagList.append(np.NaN)
else:
ct += 1
dummySed = Sed()
dummySed.readSED_flambda(
os.path.join(sedDir, specMap[line['diskName']]))
fnorm = dummySed.calcFluxNorm(line['diskNorm'], imsimBand)
dummySed.multiplyFluxNorm(fnorm)
a_int, b_int = dummySed.setupCCM_ab()
dummySed.addDust(a_int, b_int, A_v=line['diskAv'])
dummySed.redshiftSED(line['redshift'], dimming=True)
dummySed.resampleSED(wavelen_match=testBandpasses['u'].wavelen)
for bpName in keys:
mag = dummySed.calcMag(testBandpasses[bpName])
self.assertAlmostEqual(mag, line['%sDisk' % bpName], 10)
diskMagList.append(mag)
if line['agnName'] == 'None':
for bp in keys:
np.testing.assert_true(line['%sAgn' % bp], np.NaN)
agnMagList.append(np.NaN)
else:
ct += 1
dummySed = Sed()
dummySed.readSED_flambda(
os.path.join(sedDir, specMap[line['agnName']]))
fnorm = dummySed.calcFluxNorm(line['agnNorm'], imsimBand)
dummySed.multiplyFluxNorm(fnorm)
dummySed.redshiftSED(line['redshift'], dimming=True)
dummySed.resampleSED(wavelen_match=testBandpasses['u'].wavelen)
for bpName in keys:
mag = dummySed.calcMag(testBandpasses[bpName])
self.assertAlmostEqual(mag, line['%sAgn' % bpName], 10)
agnMagList.append(mag)
totalMags = PhotometryGalaxies().sum_magnitudes(
bulge=np.array(bulgeMagList),
disk=np.array(diskMagList),
agn=np.array(agnMagList))
for testMag, bpName in zip(totalMags, keys):
if np.isnan(line['%sTotal' % bpName]):
np.testing.assert_equal(testMag, np.NaN)
else:
self.assertAlmostEqual(testMag, line['%sTotal' % bpName],
10)
self.assertGreater(ct, 0)
