def calcBasicColors(self, sedList, bandpassDict, makeCopy = False):
"""
This will calculate a set of colors from a list of SED objects when there is no need to redshift
the SEDs.
@param [in] sedList is the set of spectral objects from the models SEDs provided by loaders in
rgStar or rgGalaxy. NOTE: Since this uses photometryBase.manyMagCalc_list the SED objects
will be changed.
@param [in] bandpassDict is a BandpassDict class instance with the Bandpasses set to those
for the magnitudes given for the catalog object
@param [in] makeCopy indicates whether or not to operate on copies of the SED objects in sedList
since this method will change the wavelength grid.
@param [out] modelColors is the set of colors in the Bandpasses provided for the given sedList.
"""
modelColors = []
for specObj in sedList:
if makeCopy==True:
fileSED = Sed()
fileSED.setSED(wavelen = specObj.wavelen, flambda = specObj.flambda)
sEDMags = bandpassDict.magListForSed(fileSED)
else:
sEDMags = bandpassDict.magListForSed(specObj)
colorInfo = []
for filtNum in range(0, len(bandpassDict)-1):
colorInfo.append(sEDMags[filtNum] - sEDMags[filtNum+1])
modelColors.append(colorInfo)
return modelColors
def __init__(self,
catsim_cat,
om10_cat='twinkles_tdc_rung4.fits',
density_param=1.):
"""
Input:
catsim_cat:
The results array from an instance catalog.
density_param:
A float between 0. and 1.0 that determines the fraction of eligible agn objects that become lensed.
Output:
updated_catalog:
A new results array with lens systems added.
"""
self.catalog = catsim_cat
# ****** THIS ASSUMES THAT THE ENVIRONMENT VARIABLE OM10_DIR IS SET *******
lensdb = om10.DB(catalog=om10_cat)
self.lenscat = lensdb.lenses.copy()
self.density_param = density_param
self.bandpassDict = BandpassDict.loadTotalBandpassesFromFiles(
bandpassNames=['i'])
specFileStart = 'Burst'
for key, val in sorted(iteritems(SpecMap.subdir_map)):
if re.match(key, specFileStart):
galSpecDir = str(val)
galDir = str(
getPackageDir('sims_sed_library') + '/' + galSpecDir + '/')
self.LRG_name = 'Burst.25E09.1Z.spec'
self.LRG = Sed()
self.LRG.readSED_flambda(str(galDir + self.LRG_name))
def calcBasicColors(self, sedList, bandpassDict, makeCopy=False):
"""
This will calculate a set of colors from a list of SED objects when there is no need to redshift
the SEDs.
@param [in] sedList is the set of spectral objects from the models SEDs provided by loaders in
rgStar or rgGalaxy. NOTE: Since this uses photometryBase.manyMagCalc_list the SED objects
will be changed.
@param [in] bandpassDict is a BandpassDict class instance with the Bandpasses set to those
for the magnitudes given for the catalog object
@param [in] makeCopy indicates whether or not to operate on copies of the SED objects in sedList
since this method will change the wavelength grid.
@param [out] modelColors is the set of colors in the Bandpasses provided for the given sedList.
"""
modelColors = []
for specObj in sedList:
if makeCopy == True:
fileSED = Sed()
fileSED.setSED(wavelen=specObj.wavelen,
flambda=specObj.flambda)
sEDMags = bandpassDict.magListForSed(fileSED)
else:
sEDMags = bandpassDict.magListForSed(specObj)
colorInfo = []
for filtNum in range(0, len(bandpassDict) - 1):
colorInfo.append(sEDMags[filtNum] - sEDMags[filtNum + 1])
modelColors.append(colorInfo)
return modelColors
def testAlternateBandpassesStars(self):
"""
This will test our ability to do photometry using non-LSST bandpasses.
It will first calculate the magnitudes using the getters in cartoonPhotometryStars.
It will then load the alternate bandpass files 'by hand' and re-calculate the magnitudes
and make sure that the magnitude values agree. This is guarding against the possibility
that some default value did not change and the code actually ended up loading the
LSST bandpasses.
"""
obs_metadata_pointed = ObservationMetaData(mjd=2013.23,
boundType='circle',
pointingRA=200.0,
pointingDec=-30.0,
boundLength=1.0)
test_cat = cartoonStars(self.star, obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as catName:
test_cat.write_catalog(catName)
with open(catName, 'r') as input_file:
lines = input_file.readlines()
self.assertGreater(len(lines), 1)
cartoonDir = os.path.join(getPackageDir('sims_photUtils'), '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)
i = 0
# since all of the SEDs in the cartoon database are the same, just test on the first
# if we ever include more SEDs, this can be something like
# for ss in test_cata.sedMasterList:
ss = test_cat.sedMasterList[0]
ss.resampleSED(wavelen_match=bplist[0].wavelen)
ss.flambdaTofnu()
mags = -2.5 * np.log10(
np.sum(phiArray * ss.fnu, axis=1) * waveLenStep) - ss.zp
self.assertEqual(len(mags), len(test_cat.cartoonBandpassDict))
self.assertGreater(len(mags), 0)
for j in range(len(mags)):
self.assertAlmostEqual(mags[j], test_cat.magnitudeMasterList[i][j],
4)
def testAlternateBandpassesStars(self):
"""
This will test our ability to do photometry using non-LSST bandpasses.
It will first calculate the magnitudes using the getters in cartoonPhotometryStars.
It will then load the alternate bandpass files 'by hand' and re-calculate the magnitudes
and make sure that the magnitude values agree. This is guarding against the possibility
that some default value did not change and the code actually ended up loading the
LSST bandpasses.
"""
obs_metadata_pointed = ObservationMetaData(mjd=2013.23,
boundType='circle',
pointingRA=200.0, pointingDec=-30.0,
boundLength=1.0)
test_cat = cartoonStars(self.star, obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as catName:
test_cat.write_catalog(catName)
with open(catName, 'r') as input_file:
lines = input_file.readlines()
self.assertGreater(len(lines), 1)
cartoonDir = os.path.join(getPackageDir('sims_photUtils'), '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)
i = 0
# since all of the SEDs in the cartoon database are the same, just test on the first
# if we ever include more SEDs, this can be something like
# for ss in test_cata.sedMasterList:
ss = test_cat.sedMasterList[0]
ss.resampleSED(wavelen_match = bplist[0].wavelen)
ss.flambdaTofnu()
mags = -2.5*np.log10(np.sum(phiArray*ss.fnu, axis=1)*waveLenStep) - ss.zp
self.assertEqual(len(mags), len(test_cat.cartoonBandpassDict))
self.assertGreater(len(mags), 0)
for j in range(len(mags)):
self.assertAlmostEqual(mags[j], test_cat.magnitudeMasterList[i][j], 4)
def testSystematicUncertainty(self):
"""
Test that systematic uncertainty is added correctly.
"""
sigmaSys = 0.002
m5 = [23.5, 24.3, 22.1, 20.0, 19.5, 21.7]
photParams = PhotometricParameters(sigmaSys=sigmaSys)
bandpassDict = BandpassDict.loadTotalBandpassesFromFiles()
obs_metadata = ObservationMetaData(unrefractedRA=23.0,
unrefractedDec=45.0,
m5=m5,
bandpassName=self.bandpasses)
magnitudes = bandpassDict.magListForSed(self.starSED)
skySeds = []
for i in range(len(self.bandpasses)):
skyDummy = Sed()
skyDummy.readSED_flambda(
os.path.join(lsst.utils.getPackageDir('throughputs'),
'baseline', 'darksky.dat'))
normalizedSkyDummy = setM5(obs_metadata.m5[self.bandpasses[i]],
skyDummy,
self.totalBandpasses[i],
self.hardwareBandpasses[i],
seeing=LSSTdefaults().seeing(
self.bandpasses[i]),
photParams=PhotometricParameters())
skySeds.append(normalizedSkyDummy)
for i in range(len(self.bandpasses)):
snr = calcSNR_sed(self.starSED,
self.totalBandpasses[i],
skySeds[i],
self.hardwareBandpasses[i],
seeing=LSSTdefaults().seeing(self.bandpasses[i]),
photParams=PhotometricParameters())
testSNR, gamma = calcSNR_m5(
numpy.array([magnitudes[i]]), [self.totalBandpasses[i]],
numpy.array([m5[i]]),
photParams=PhotometricParameters(sigmaSys=0.0))
self.assertAlmostEqual(snr, testSNR[0], 10, msg = 'failed on calcSNR_m5 test %e != %e ' \
% (snr, testSNR[0]))
control = numpy.sqrt(
numpy.power(magErrorFromSNR(testSNR), 2) +
numpy.power(sigmaSys, 2))
def testAlternateBandpassesStars(self):
"""
This will test our ability to do photometry using non-LSST bandpasses.
It will first calculate the magnitudes using the getters in cartoonPhotometryStars.
It will then load the alternate bandpass files 'by hand' and re-calculate the magnitudes
and make sure that the magnitude values agree. This is guarding against the possibility
that some default value did not change and the code actually ended up loading the
LSST bandpasses.
"""
obs_metadata_pointed=ObservationMetaData(mjd=2013.23,
boundType='circle',unrefractedRA=200.0,unrefractedDec=-30.0,
boundLength=1.0)
test_cat=cartoonStars(self.star,obs_metadata=obs_metadata_pointed)
test_cat.write_catalog("testStarsCartoon.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)
i = 0
#since all of the SEDs in the cartoon database are the same, just test on the first
#if we ever include more SEDs, this can be something like
#for ss in test_cata.sedMasterList:
#
ss=test_cat.sedMasterList[0]
ss.resampleSED(wavelen_match = bplist[0].wavelen)
ss.flambdaTofnu()
mags = -2.5*numpy.log10(numpy.sum(phiArray*ss.fnu, axis=1)*waveLenStep) - ss.zp
self.assertTrue(len(mags)==len(test_cat.bandpassDict))
self.assertTrue(len(mags)>0)
for j in range(len(mags)):
self.assertAlmostEqual(mags[j],test_cat.magnitudeMasterList[i][j],10)
i += 1
os.unlink("testStarsCartoon.txt")
def loadKuruczSEDs(self, subset=None):
"""
By default will load all seds in kurucz directory. The user can also define a subset of
what's in the directory and load only those SEDs instead. Will skip over extraneous
files in sed folder.
@param [in] subset is the list of the subset of files wanted if one doesn't want all files
in the kurucz directory.
@param [out] sedList is the set of model SED spectra objects to be passed onto the matching
routines.
"""
files = []
if subset is None:
for fileName in os.listdir(self.kuruczDir):
files.append(fileName)
else:
for fileName in subset:
files.append(fileName)
numFiles = len(files)
numOn = 0
sedList = []
for fileName in files:
if numOn % 100 == 0:
print 'Loading %i of %i: Kurucz SEDs' % (numOn, numFiles)
try:
spec = Sed()
spec.readSED_flambda(str(self.kuruczDir + '/' + fileName))
logZTimesTen, temp, gravity, fineTemp = [
x.split(".")[0] for x in fileName.split("_")
]
if logZTimesTen[1] == 'm':
spec.logZ = -1.0 * float(logZTimesTen[2:]) * 0.1
else:
spec.logZ = float(logZTimesTen[2:]) * 0.1
spec.logg = float(gravity[1:]) * 0.1
spec.temp = float(fineTemp)
spec.name = fileName
except:
continue
sedList.append(spec)
numOn += 1
return sedList
def loadwdSEDs(self, subset = None):
"""
By default will load all seds in wd directory. The user can also define a subset of
what's in the directory and load only those SEDs instead. Will skip over extraneous
files in sed folder.
@param [in] subset is the list of the subset of files wanted if one doesn't want all files
in the kurucz directory.
@param [out] sedListH is the set of model SED spectra objects for Hydrogen WDs to be passed onto
the matching routines.
@param [out] sedListHE is the set of model SED spectra objects for Helium WDs to be passed onto
the matching routines.
"""
files = []
if subset is None:
for fileName in os.listdir(self.wdDir):
files.append(fileName)
else:
for fileName in subset:
files.append(fileName)
numFiles = len(files)
numOn = 0
sedListH = []
sedListHE = []
for fileName in files:
if numOn % 100 == 0:
print 'Loading %i of %i: WD SEDs' % (numOn, numFiles)
try:
spec = Sed()
spec.readSED_flambda(str(self.wdDir + '/' + fileName))
spec.name = fileName
if fileName.split("_")[1] == 'He':
sedListHE.append(spec)
else:
sedListH.append(spec)
except:
continue
numOn += 1
return sedListH, sedListHE
def testApplyIGM(self):
"""Test application of IGM from Lookup Tables to SED objects"""
#Test that a warning comes up if input redshift is out of range and that no changes occurs to SED
testSed = Sed()
testSed.readSED_flambda(os.environ['SIMS_SED_LIBRARY_DIR'] +
'/galaxySED/Inst.80E09.25Z.spec.gz')
testFlambda = []
for fVal in testSed.flambda:
testFlambda.append(fVal)
testIGM = ApplyIGM()
testIGM.initializeIGM()
with warnings.catch_warnings(record=True) as wa:
testIGM.applyIGM(1.1, testSed)
self.assertEqual(len(wa), 1)
self.assertTrue('IGM Lookup tables' in str(wa[-1].message))
np.testing.assert_equal(testFlambda, testSed.flambda)
#Test that lookup table is read in correctly
testTable15 = np.genfromtxt(
str(os.environ['SIMS_SED_LIBRARY_DIR'] + '/igm/' +
'MeanLookupTable_zSource1.5.tbl'))
np.testing.assert_equal(testTable15, testIGM.meanLookups['1.5'])
#Test output by making sure that an incoming sed with flambda = 1.0 everywhere will return the
#transmission values of the lookup table as its flambda output
testSed.setSED(testSed.wavelen, flambda=np.ones(len(testSed.wavelen)))
testIGM.applyIGM(1.5, testSed)
testTable15Above300 = testTable15[np.where(testTable15[:, 0] >= 300.0)]
testSed.resampleSED(wavelen_match=testTable15Above300[:, 0])
np.testing.assert_allclose(testTable15Above300[:, 1], testSed.flambda,
1e-4)
def loadwdSEDs(self, subset=None):
"""
By default will load all seds in wd directory. The user can also define a subset of
what's in the directory and load only those SEDs instead. Will skip over extraneous
files in sed folder.
@param [in] subset is the list of the subset of files wanted if one doesn't want all files
in the kurucz directory.
@param [out] sedListH is the set of model SED spectra objects for Hydrogen WDs to be passed onto
the matching routines.
@param [out] sedListHE is the set of model SED spectra objects for Helium WDs to be passed onto
the matching routines.
"""
files = []
if subset is None:
for fileName in os.listdir(self.wdDir):
files.append(fileName)
else:
for fileName in subset:
files.append(fileName)
numFiles = len(files)
numOn = 0
sedListH = []
sedListHE = []
for fileName in files:
if numOn % 100 == 0:
print 'Loading %i of %i: WD SEDs' % (numOn, numFiles)
try:
spec = Sed()
spec.readSED_flambda(str(self.wdDir + '/' + fileName))
spec.name = fileName
if fileName.split("_")[1] == 'He':
sedListHE.append(spec)
else:
sedListH.append(spec)
except:
continue
numOn += 1
return sedListH, sedListHE
def testSystematicUncertainty(self):
"""
Test that systematic uncertainty is added correctly.
"""
sigmaSys = 0.002
m5 = [23.5, 24.3, 22.1, 20.0, 19.5, 21.7]
photParams = PhotometricParameters(sigmaSys=sigmaSys)
bandpassDict = BandpassDict.loadTotalBandpassesFromFiles()
obs_metadata = ObservationMetaData(unrefractedRA=23.0, unrefractedDec=45.0, m5=m5, bandpassName=self.bandpasses)
magnitudes = bandpassDict.magListForSed(self.starSED)
skySeds = []
for i in range(len(self.bandpasses)):
skyDummy = Sed()
skyDummy.readSED_flambda(os.path.join(lsst.utils.getPackageDir("throughputs"), "baseline", "darksky.dat"))
normalizedSkyDummy = setM5(
obs_metadata.m5[self.bandpasses[i]],
skyDummy,
self.totalBandpasses[i],
self.hardwareBandpasses[i],
seeing=LSSTdefaults().seeing(self.bandpasses[i]),
photParams=PhotometricParameters(),
)
skySeds.append(normalizedSkyDummy)
for i in range(len(self.bandpasses)):
snr = calcSNR_sed(
self.starSED,
self.totalBandpasses[i],
skySeds[i],
self.hardwareBandpasses[i],
seeing=LSSTdefaults().seeing(self.bandpasses[i]),
photParams=PhotometricParameters(),
)
testSNR, gamma = calcSNR_m5(
numpy.array([magnitudes[i]]),
[self.totalBandpasses[i]],
numpy.array([m5[i]]),
photParams=PhotometricParameters(sigmaSys=0.0),
)
self.assertAlmostEqual(snr, testSNR[0], 10, msg="failed on calcSNR_m5 test %e != %e " % (snr, testSNR[0]))
control = numpy.sqrt(numpy.power(magErrorFromSNR(testSNR), 2) + numpy.power(sigmaSys, 2))
def __init__(self, catsim_cat, om10_cat='twinkles_lenses_v2.fits',
density_param=1.):
"""
Parameters
----------
catsim_cat: catsim catalog
The results array from an instance catalog.
om10_cat: optional, defaults to 'twinkles_tdc_rung4.fits
fits file with OM10 catalog
density_param: `np.float`, optioanl, defaults to 1.0
the fraction of eligible agn objects that become lensed and should
be between 0.0 and 1.0.
Returns
-------
updated_catalog:
A new results array with lens systems added.
"""
twinklesDir = getPackageDir('Twinkles')
om10_cat = os.path.join(twinklesDir, 'data', om10_cat)
self.catalog = catsim_cat
# ****** THIS ASSUMES THAT THE ENVIRONMENT VARIABLE OM10_DIR IS SET *******
lensdb = om10.DB(catalog=om10_cat)
self.lenscat = lensdb.lenses.copy()
self.density_param = density_param
self.bandpassDict = BandpassDict.loadTotalBandpassesFromFiles(bandpassNames=['i'])
specFileStart = 'Burst'
for key, val in sorted(iteritems(SpecMap.subdir_map)):
if re.match(key, specFileStart):
galSpecDir = str(val)
galDir = str(getPackageDir('sims_sed_library') + '/' + galSpecDir + '/')
self.LRG_name = 'Burst.25E09.1Z.spec'
self.LRG = Sed()
self.LRG.readSED_flambda(str(galDir + self.LRG_name))
#return
#Calculate imsimband magnitudes of source galaxies for matching
agn_sed = Sed()
agn_fname = str(getPackageDir('sims_sed_library') + '/agnSED/agn.spec.gz')
agn_sed.readSED_flambda(agn_fname)
src_iband = self.lenscat['MAGI_IN']
self.src_mag_norm = []
for src in src_iband:
self.src_mag_norm.append(matchBase().calcMagNorm([src],
agn_sed,
self.bandpassDict))
def testSignalToNoise(self):
"""
Test that calcSNR_m5 and calcSNR_sed give similar results
"""
defaults = LSSTdefaults()
photParams = PhotometricParameters()
totalDict, hardwareDict = BandpassDict.loadBandpassesFromFiles()
skySED = Sed()
skySED.readSED_flambda(os.path.join(lsst.utils.getPackageDir("throughputs"), "baseline", "darksky.dat"))
m5 = []
for filt in totalDict:
m5.append(calcM5(skySED, totalDict[filt], hardwareDict[filt], photParams, seeing=defaults.seeing(filt)))
sedDir = lsst.utils.getPackageDir("sims_sed_library")
sedDir = os.path.join(sedDir, "starSED", "kurucz")
fileNameList = os.listdir(sedDir)
numpy.random.seed(42)
offset = numpy.random.random_sample(len(fileNameList)) * 2.0
for ix, name in enumerate(fileNameList):
if ix > 100:
break
spectrum = Sed()
spectrum.readSED_flambda(os.path.join(sedDir, name))
ff = spectrum.calcFluxNorm(m5[2] - offset[ix], totalDict.values()[2])
spectrum.multiplyFluxNorm(ff)
magList = []
controlList = []
magList = []
for filt in totalDict:
controlList.append(
calcSNR_sed(
spectrum, totalDict[filt], skySED, hardwareDict[filt], photParams, defaults.seeing(filt)
)
)
magList.append(spectrum.calcMag(totalDict[filt]))
testList, gammaList = calcSNR_m5(
numpy.array(magList), numpy.array(totalDict.values()), numpy.array(m5), photParams
)
for tt, cc in zip(controlList, testList):
msg = "%e != %e " % (tt, cc)
self.assertTrue(numpy.abs(tt / cc - 1.0) < 0.001, msg=msg)
def __init__(self, catsim_cat, om10_cat='twinkles_tdc_rung4.fits', density_param = 1.):
"""
Input:
catsim_cat:
The results array from an instance catalog.
density_param:
A float between 0. and 1.0 that determines the fraction of eligible agn objects that become lensed.
Output:
updated_catalog:
A new results array with lens systems added.
"""
self.catalog = catsim_cat
# ****** THIS ASSUMES THAT THE ENVIRONMENT VARIABLE OM10_DIR IS SET *******
lensdb = om10.DB(catalog=om10_cat)
self.lenscat = lensdb.lenses.copy()
self.density_param = density_param
self.bandpassDict = BandpassDict.loadTotalBandpassesFromFiles(bandpassNames=['i'])
specFileStart = 'Burst'
for key, val in sorted(iteritems(SpecMap.subdir_map)):
if re.match(key, specFileStart):
galSpecDir = str(val)
galDir = str(getPackageDir('sims_sed_library') + '/' + galSpecDir + '/')
self.LRG_name = 'Burst.25E09.1Z.spec'
self.LRG = Sed()
self.LRG.readSED_flambda(str(galDir + self.LRG_name))
def setUp(self):
starName = os.path.join(lsst.utils.getPackageDir('sims_sed_library'),defaultSpecMap['km20_5750.fits_g40_5790'])
self.starSED = Sed()
self.starSED.readSED_flambda(starName)
imsimband = Bandpass()
imsimband.imsimBandpass()
fNorm = self.starSED.calcFluxNorm(22.0, imsimband)
self.starSED.multiplyFluxNorm(fNorm)
self.totalBandpasses = []
self.hardwareBandpasses = []
componentList = ['detector.dat', 'm1.dat', 'm2.dat', 'm3.dat',
'lens1.dat', 'lens2.dat', 'lens3.dat']
hardwareComponents = []
for c in componentList:
hardwareComponents.append(os.path.join(lsst.utils.getPackageDir('throughputs'),'baseline',c))
self.bandpasses = ['u', 'g', 'r', 'i', 'z', 'y']
for b in self.bandpasses:
filterName = os.path.join(lsst.utils.getPackageDir('throughputs'),'baseline','filter_%s.dat' % b)
components = hardwareComponents + [filterName]
bandpassDummy = Bandpass()
bandpassDummy.readThroughputList(components)
self.hardwareBandpasses.append(bandpassDummy)
components = components + [os.path.join(lsst.utils.getPackageDir('throughputs'),'baseline','atmos.dat')]
bandpassDummy = Bandpass()
bandpassDummy.readThroughputList(components)
self.totalBandpasses.append(bandpassDummy)
def setUp(self):
starName = os.path.join(lsst.utils.getPackageDir("sims_sed_library"), defaultSpecMap["km20_5750.fits_g40_5790"])
self.starSED = Sed()
self.starSED.readSED_flambda(starName)
imsimband = Bandpass()
imsimband.imsimBandpass()
fNorm = self.starSED.calcFluxNorm(22.0, imsimband)
self.starSED.multiplyFluxNorm(fNorm)
self.totalBandpasses = []
self.hardwareBandpasses = []
componentList = ["detector.dat", "m1.dat", "m2.dat", "m3.dat", "lens1.dat", "lens2.dat", "lens3.dat"]
hardwareComponents = []
for c in componentList:
hardwareComponents.append(os.path.join(lsst.utils.getPackageDir("throughputs"), "baseline", c))
self.bandpasses = ["u", "g", "r", "i", "z", "y"]
for b in self.bandpasses:
filterName = os.path.join(lsst.utils.getPackageDir("throughputs"), "baseline", "filter_%s.dat" % b)
components = hardwareComponents + [filterName]
bandpassDummy = Bandpass()
bandpassDummy.readThroughputList(components)
self.hardwareBandpasses.append(bandpassDummy)
components = components + [os.path.join(lsst.utils.getPackageDir("throughputs"), "baseline", "atmos.dat")]
bandpassDummy = Bandpass()
bandpassDummy.readThroughputList(components)
self.totalBandpasses.append(bandpassDummy)
def loadmltSEDs(self, subset = None):
"""
By default will load all seds in mlt directory. The user can also define a subset of
what's in the directory and load only those SEDs instead. Will skip over extraneous
files in sed folder.
@param [in] subset is the list of the subset of files wanted if one doesn't want all files
in the mlt directory.
@param [out] sedList is the set of model SED spectra objects to be passed onto the matching
routines.
"""
files = []
if subset is None:
for fileName in os.listdir(self.mltDir):
files.append(fileName)
else:
for fileName in subset:
files.append(fileName)
numFiles = len(files)
numOn = 0
sedList = []
for fileName in files:
if numOn % 100 == 0:
print 'Loading %i of %i: MLT SEDs' % (numOn, numFiles)
try:
spec = Sed()
spec.readSED_flambda(str(self.mltDir + '/' + fileName))
spec.name = fileName
except:
continue
sedList.append(spec)
numOn += 1
return sedList
def testApplyIGM(self):
"""Test application of IGM from Lookup Tables to SED objects"""
#Test that a warning comes up if input redshift is out of range and that no changes occurs to SED
testSed = Sed()
testSed.readSED_flambda(os.environ['SIMS_SED_LIBRARY_DIR'] + '/galaxySED/Inst.80E09.25Z.spec.gz')
testFlambda = []
for fVal in testSed.flambda:
testFlambda.append(fVal)
testIGM = ApplyIGM()
testIGM.initializeIGM()
with warnings.catch_warnings(record=True) as wa:
testIGM.applyIGM(1.1, testSed)
self.assertEqual(len(wa), 1)
self.assertTrue('IGM Lookup tables' in str(wa[-1].message))
np.testing.assert_equal(testFlambda, testSed.flambda)
#Test that lookup table is read in correctly
testTable15 = np.genfromtxt(str(os.environ['SIMS_SED_LIBRARY_DIR'] + '/igm/' +
'MeanLookupTable_zSource1.5.tbl'))
np.testing.assert_equal(testTable15, testIGM.meanLookups['1.5'])
#Test output by making sure that an incoming sed with flambda = 1.0 everywhere will return the
#transmission values of the lookup table as its flambda output
testSed.setSED(testSed.wavelen, flambda = np.ones(len(testSed.wavelen)))
testIGM.applyIGM(1.5, testSed)
testTable15Above300 = testTable15[np.where(testTable15[:,0] >= 300.0)]
testSed.resampleSED(wavelen_match = testTable15Above300[:,0])
np.testing.assert_allclose(testTable15Above300[:,1], testSed.flambda, 1e-4)
def testInitializeIGM(self):
"Test Initialization Method"
#Make sure that if we initialize IGM with new inputs that it is initializing with them
testIGM = ApplyIGM()
testSed = Sed()
testSed.readSED_flambda(os.environ['SIMS_SED_LIBRARY_DIR'] + '/galaxySED/Inst.80E09.25Z.spec.gz')
testIGM.applyIGM(1.8, testSed)
testZmin = 1.8
testZmax = 2.2
#Want new values for testing,
#so make sure we are not just putting in the same values as are already there
self.assertNotEqual(testZmin, testIGM.zMin)
self.assertNotEqual(testZmax, testIGM.zMax)
testIGM.initializeIGM(zMin = testZmin, zMax = testZmax)
self.assertEqual(testZmin, testIGM.zMin)
self.assertEqual(testZmax, testIGM.zMax)
def testCalcBasicColors(self):
"""Tests the calculation of the colors of an SED in given bandpasses."""
testUtils = matchBase()
testSED = Sed()
bandpassDir = os.path.join(lsst.utils.getPackageDir('throughputs'),
'sdss')
testPhot = BandpassDict.loadTotalBandpassesFromFiles(
self.filterList, bandpassDir=bandpassDir, bandpassRoot='sdss_')
testSED.readSED_flambda(str(self.galDir + os.listdir(self.galDir)[0]))
testMags = testPhot.magListForSed(testSED)
testColors = []
for filtNum in range(0, len(self.filterList) - 1):
testColors.append(testMags[filtNum] - testMags[filtNum + 1])
testOutput = testUtils.calcBasicColors([testSED], testPhot)
np.testing.assert_equal([testColors], testOutput)
def testCalcBasicColors(self):
"""Tests the calculation of the colors of an SED in given bandpasses."""
testUtils = matchBase()
testSED = Sed()
testPhot = BandpassDict.loadTotalBandpassesFromFiles(self.filterList,
bandpassDir = os.path.join(lsst.utils.getPackageDir('throughputs'),'sdss'),
bandpassRoot = 'sdss_')
testSED.readSED_flambda(str(self.galDir + os.listdir(self.galDir)[0]))
testMags = testPhot.magListForSed(testSED)
testColors = []
for filtNum in range(0, len(self.filterList)-1):
testColors.append(testMags[filtNum] - testMags[filtNum+1])
testOutput = testUtils.calcBasicColors([testSED], testPhot)
np.testing.assert_equal([testColors], testOutput)
def testPhotometricIndicesRaw(self):
"""
Use manMagCalc_list with specified indices on an Sed. Make sure
that the appropriate magnitudes are or are not Nan
"""
starName = os.path.join(getPackageDir('sims_sed_library'), defaultSpecMap['km20_5750.fits_g40_5790'])
starPhot = BandpassDict.loadTotalBandpassesFromFiles()
testSed = Sed()
testSed.readSED_flambda(starName)
indices = [1, 3]
mags = starPhot.magListForSed(testSed, indices=indices)
np.testing.assert_equal(mags[0], np.NaN)
self.assertFalse(np.isnan(mags[1]), msg='mags[1] is NaN; should not be')
np.testing.assert_equal(mags[2], np.NaN)
self.assertFalse(np.isnan(mags[3]), msg='mags[3] is NaN; should not be')
np.testing.assert_equal(mags[4], np.NaN)
np.testing.assert_equal(mags[5], np.NaN)
self.assertEqual(len(mags), 6)
def loadmltSEDs(self, subset=None):
"""
By default will load all seds in mlt directory. The user can also define a subset of
what's in the directory and load only those SEDs instead. Will skip over extraneous
files in sed folder.
@param [in] subset is the list of the subset of files wanted if one doesn't want all files
in the mlt directory.
@param [out] sedList is the set of model SED spectra objects to be passed onto the matching
routines.
"""
files = []
if subset is None:
for fileName in os.listdir(self.mltDir):
files.append(fileName)
else:
for fileName in subset:
files.append(fileName)
numFiles = len(files)
numOn = 0
sedList = []
for fileName in files:
if numOn % 100 == 0:
print 'Loading %i of %i: MLT SEDs' % (numOn, numFiles)
try:
spec = Sed()
spec.readSED_flambda(str(self.mltDir + '/' + fileName))
spec.name = fileName
except:
continue
sedList.append(spec)
numOn += 1
return sedList
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 testPhotometricIndicesRaw(self):
"""
Use manMagCalc_list with specified indices on an Sed. Make sure
that the appropriate magnitudes are or are not Nan
"""
starName = os.path.join(lsst.utils.getPackageDir('sims_sed_library'),defaultSpecMap['km20_5750.fits_g40_5790'])
starPhot = PhotometryStars()
starPhot.loadTotalBandpassesFromFiles()
testSed = Sed()
testSed.readSED_flambda(starName)
indices = [1,3]
mags = starPhot.manyMagCalc_list(testSed, indices=indices)
self.assertTrue(numpy.isnan(mags[0]))
self.assertFalse(numpy.isnan(mags[1]))
self.assertTrue(numpy.isnan(mags[2]))
self.assertFalse(numpy.isnan(mags[3]))
self.assertTrue(numpy.isnan(mags[4]))
self.assertTrue(numpy.isnan(mags[5]))
self.assertTrue(len(mags)==6)
def testInitializeIGM(self):
"Test Initialization Method"
#Make sure that if we initialize IGM with new inputs that it is initializing with them
testIGM = ApplyIGM()
testSed = Sed()
testSed.readSED_flambda(os.environ['SIMS_SED_LIBRARY_DIR'] +
'/galaxySED/Inst.80E09.25Z.spec.gz')
testIGM.applyIGM(1.8, testSed)
testZmin = 1.8
testZmax = 2.2
#Want new values for testing,
#so make sure we are not just putting in the same values as are already there
self.assertNotEqual(testZmin, testIGM.zMin)
self.assertNotEqual(testZmax, testIGM.zMax)
testIGM.initializeIGM(zMin=testZmin, zMax=testZmax)
self.assertEqual(testZmin, testIGM.zMin)
self.assertEqual(testZmax, testIGM.zMax)
def loadKuruczSEDs(self, subset = None):
"""
By default will load all seds in kurucz directory. The user can also define a subset of
what's in the directory and load only those SEDs instead. Will skip over extraneous
files in sed folder.
@param [in] subset is the list of the subset of files wanted if one doesn't want all files
in the kurucz directory.
@param [out] sedList is the set of model SED spectra objects to be passed onto the matching
routines.
"""
files = []
if subset is None:
for fileName in os.listdir(self.kuruczDir):
files.append(fileName)
else:
for fileName in subset:
files.append(fileName)
numFiles = len(files)
numOn = 0
sedList = []
for fileName in files:
if numOn % 100 == 0:
print 'Loading %i of %i: Kurucz SEDs' % (numOn, numFiles)
try:
spec = Sed()
spec.readSED_flambda(str(self.kuruczDir + '/' + fileName))
logZTimesTen, temp, gravity, fineTemp = [x.split(".")[0] for x in fileName.split("_")]
if logZTimesTen[1] == 'm':
spec.logZ = -1.0 * float(logZTimesTen[2:]) * 0.1
else:
spec.logZ = float(logZTimesTen[2:]) * 0.1
spec.logg = float(gravity[1:]) * 0.1
spec.temp = float(fineTemp)
spec.name = fileName
except:
continue
sedList.append(spec)
numOn += 1
return sedList
def testMatchToRestFrame(self):
"""Test that Galaxies with no effects added into catalog mags are matched correctly."""
rng = np.random.RandomState(42)
galPhot = BandpassDict.loadTotalBandpassesFromFiles()
imSimBand = Bandpass()
imSimBand.imsimBandpass()
testMatching = selectGalaxySED(galDir=self.testSpecDir)
testSEDList = testMatching.loadBC03()
testSEDNames = []
testMags = []
testMagNormList = []
magNormStep = 1
for testSED in testSEDList:
getSEDMags = Sed()
testSEDNames.append(testSED.name)
getSEDMags.setSED(wavelen=testSED.wavelen, flambda=testSED.flambda)
testMagNorm = np.round(rng.uniform(20.0, 22.0), magNormStep)
testMagNormList.append(testMagNorm)
fluxNorm = getSEDMags.calcFluxNorm(testMagNorm, imSimBand)
getSEDMags.multiplyFluxNorm(fluxNorm)
testMags.append(galPhot.magListForSed(getSEDMags))
# Also testing to make sure passing in non-default bandpasses works
# Substitute in nan values to simulate incomplete data.
testMags[0][1] = np.nan
testMags[0][2] = np.nan
testMags[0][4] = np.nan
testMags[1][1] = np.nan
testMatchingResults = testMatching.matchToRestFrame(
testSEDList, testMags, bandpassDict=galPhot)
self.assertEqual(None, testMatchingResults[0][0])
self.assertEqual(testSEDNames[1:], testMatchingResults[0][1:])
self.assertEqual(None, testMatchingResults[1][0])
np.testing.assert_almost_equal(testMagNormList[1:],
testMatchingResults[1][1:],
decimal=magNormStep)
# Test Match Errors
errMags = np.array(
(testMags[2], testMags[2], testMags[2], testMags[2]))
errMags[1, 1] += 1. # Total MSE will be 2/(5 colors) = 0.4
errMags[2, 0:2] = np.nan
errMags[2, 3] += 1. # Total MSE will be 2/(3 colors) = 0.667
errMags[3, :] = None
errSED = testSEDList[2]
testMatchingResultsErrors = testMatching.matchToRestFrame(
[errSED], errMags, bandpassDict=galPhot)
np.testing.assert_almost_equal(np.array((0.0, 0.4, 2. / 3.)),
testMatchingResultsErrors[2][0:3],
decimal=3)
self.assertEqual(None, testMatchingResultsErrors[2][3])
def testPhotometricIndicesRaw(self):
"""
Use manMagCalc_list with specified indices on an Sed. Make sure
that the appropriate magnitudes are or are not Nan
"""
starName = os.path.join(getPackageDir('sims_sed_library'),
defaultSpecMap['km20_5750.fits_g40_5790'])
starPhot = BandpassDict.loadTotalBandpassesFromFiles()
testSed = Sed()
testSed.readSED_flambda(starName)
indices = [1, 3]
mags = starPhot.magListForSed(testSed, indices=indices)
np.testing.assert_equal(mags[0], np.NaN)
self.assertFalse(np.isnan(mags[1]),
msg='mags[1] is NaN; should not be')
np.testing.assert_equal(mags[2], np.NaN)
self.assertFalse(np.isnan(mags[3]),
msg='mags[3] is NaN; should not be')
np.testing.assert_equal(mags[4], np.NaN)
np.testing.assert_equal(mags[5], np.NaN)
self.assertEqual(len(mags), 6)
def loadBC03(self, subset=None):
"""
This loads the Bruzual and Charlot SEDs that are currently in the SIMS_SED_LIBRARY.
If the user wants to use different SEDs another loading method can be created and used in place
of this.
@param [in] subset is the list of the subset of files in the galDir that the user
can specify if using all the SEDs in the directory is not desired.
@param [out] sedList is the set of model SED spectra objects to be passed onto the matching routines.
"""
files = []
if subset is None:
for fileName in os.listdir(self.galDir):
files.append(fileName)
else:
for fileName in subset:
files.append(fileName)
numFiles = len(files)
numOn = 0
sedList = []
for fileName in files:
if numOn % 100 == 0:
print 'Loading %i of %i: BC Galaxy SEDs' % (numOn, numFiles)
try:
spec = Sed()
spec.readSED_flambda(str(self.galDir + '/' + fileName))
spec.name = fileName
fileNameAsList = fileName.split('.')
spec.type = fileNameAsList[0]
spec.age = float(fileNameAsList[1])
metallicity = fileNameAsList[2].split('Z')[0]
#Final form is z/zSun
spec.metallicity = float(metallicity) * (10**(
(len(metallicity) - 1) * -1))
except:
continue
sedList.append(spec)
numOn += 1
return sedList
def testInitializeIGM(self):
"Test Initialization Method"
# Make sure that if we initialize IGM with new inputs that it
# is initializing with them
testIGM = ApplyIGM()
testSed = Sed()
sedName = os.path.join(getPackageDir('sims_sed_library'), 'galaxySED')
testSed.readSED_flambda(os.path.join(sedName,
'Burst.10E08.002Z.spec.gz'))
testIGM.applyIGM(1.8, testSed)
testZmin = 1.8
testZmax = 2.2
# Want new values for testing,
# so make sure we are not just putting in the same values
# as are already there
self.assertNotEqual(testZmin, testIGM.zMin)
self.assertNotEqual(testZmax, testIGM.zMax)
testIGM.initializeIGM(zMin = testZmin, zMax = testZmax)
self.assertEqual(testZmin, testIGM.zMin)
self.assertEqual(testZmax, testIGM.zMax)
def testInitializeIGM(self):
"Test Initialization Method"
# Make sure that if we initialize IGM with new inputs that it
# is initializing with them
testIGM = ApplyIGM()
testSed = Sed()
sedName = os.path.join(getPackageDir('sims_sed_library'), 'galaxySED')
testSed.readSED_flambda(
os.path.join(sedName, 'Burst.10E08.002Z.spec.gz'))
testIGM.applyIGM(1.8, testSed)
testZmin = 1.8
testZmax = 2.2
# Want new values for testing,
# so make sure we are not just putting in the same values
# as are already there
self.assertNotEqual(testZmin, testIGM.zMin)
self.assertNotEqual(testZmax, testIGM.zMax)
testIGM.initializeIGM(zMin=testZmin, zMax=testZmax)
self.assertEqual(testZmin, testIGM.zMin)
self.assertEqual(testZmax, testIGM.zMax)
class UncertaintyMixinTest(unittest.TestCase):
def setUp(self):
starName = os.path.join(getPackageDir('sims_sed_library'),
defaultSpecMap['km20_5750.fits_g40_5790'])
self.starSED = Sed()
self.starSED.readSED_flambda(starName)
imsimband = Bandpass()
imsimband.imsimBandpass()
fNorm = self.starSED.calcFluxNorm(22.0, imsimband)
self.starSED.multiplyFluxNorm(fNorm)
self.totalBandpasses = []
self.hardwareBandpasses = []
componentList = [
'detector.dat', 'm1.dat', 'm2.dat', 'm3.dat', 'lens1.dat',
'lens2.dat', 'lens3.dat'
]
hardwareComponents = []
for c in componentList:
hardwareComponents.append(
os.path.join(getPackageDir('throughputs'), 'baseline', c))
self.bandpasses = ['u', 'g', 'r', 'i', 'z', 'y']
for b in self.bandpasses:
filterName = os.path.join(getPackageDir('throughputs'), 'baseline',
'filter_%s.dat' % b)
components = hardwareComponents + [filterName]
bandpassDummy = Bandpass()
bandpassDummy.readThroughputList(components)
self.hardwareBandpasses.append(bandpassDummy)
components = components + [
os.path.join(getPackageDir('throughputs'), 'baseline',
'atmos.dat')
]
bandpassDummy = Bandpass()
bandpassDummy.readThroughputList(components)
self.totalBandpasses.append(bandpassDummy)
def loadBC03(self, subset = None):
"""
This loads the Bruzual and Charlot SEDs that are currently in the SIMS_SED_LIBRARY.
If the user wants to use different SEDs another loading method can be created and used in place
of this.
@param [in] subset is the list of the subset of files in the galDir that the user
can specify if using all the SEDs in the directory is not desired.
@param [out] sedList is the set of model SED spectra objects to be passed onto the matching routines.
"""
files = []
if subset is None:
for fileName in os.listdir(self.galDir):
files.append(fileName)
else:
for fileName in subset:
files.append(fileName)
numFiles = len(files)
numOn = 0
sedList = []
for fileName in files:
if numOn % 100 == 0:
print 'Loading %i of %i: BC Galaxy SEDs' % (numOn, numFiles)
try:
spec = Sed()
spec.readSED_flambda(str(self.galDir + '/' + fileName))
spec.name = fileName
fileNameAsList = fileName.split('.')
spec.type = fileNameAsList[0]
spec.age = float(fileNameAsList[1])
metallicity = fileNameAsList[2].split('Z')[0]
#Final form is z/zSun
spec.metallicity = float(metallicity) * (10 ** ((len(metallicity)-1)*-1))
except:
continue
sedList.append(spec)
numOn += 1
return sedList
def testMatchToRestFrame(self):
"""Test that Galaxies with no effects added into catalog mags are matched correctly."""
np.random.seed(42)
galPhot = BandpassDict.loadTotalBandpassesFromFiles()
imSimBand = Bandpass()
imSimBand.imsimBandpass()
testMatching = selectGalaxySED(galDir = self.testSpecDir)
testSEDList = testMatching.loadBC03()
testSEDNames = []
testMags = []
testMagNormList = []
magNormStep = 1
for testSED in testSEDList:
getSEDMags = Sed()
testSEDNames.append(testSED.name)
getSEDMags.setSED(wavelen = testSED.wavelen, flambda = testSED.flambda)
testMagNorm = np.round(np.random.uniform(20.0,22.0),magNormStep)
testMagNormList.append(testMagNorm)
fluxNorm = getSEDMags.calcFluxNorm(testMagNorm, imSimBand)
getSEDMags.multiplyFluxNorm(fluxNorm)
testMags.append(galPhot.magListForSed(getSEDMags))
#Also testing to make sure passing in non-default bandpasses works
#Substitute in nan values to simulate incomplete data.
testMags[0][1] = np.nan
testMags[0][2] = np.nan
testMags[0][4] = np.nan
testMags[1][1] = np.nan
testMatchingResults = testMatching.matchToRestFrame(testSEDList, testMags,
bandpassDict = galPhot)
self.assertEqual(None, testMatchingResults[0][0])
self.assertEqual(testSEDNames[1:], testMatchingResults[0][1:])
self.assertEqual(None, testMatchingResults[1][0])
np.testing.assert_almost_equal(testMagNormList[1:], testMatchingResults[1][1:], decimal = magNormStep)
#Test Match Errors
errMags = np.array((testMags[2], testMags[2], testMags[2], testMags[2]))
errMags[1,1] += 1. #Total MSE will be 2/(5 colors) = 0.4
errMags[2, 0:2] = np.nan
errMags[2, 3] += 1. #Total MSE will be 2/(3 colors) = 0.667
errMags[3, :] = None
errSED = testSEDList[2]
testMatchingResultsErrors = testMatching.matchToRestFrame([errSED], errMags,
bandpassDict = galPhot)
np.testing.assert_almost_equal(np.array((0.0, 0.4, 2./3.)), testMatchingResultsErrors[2][0:3],
decimal = 3)
self.assertEqual(None, testMatchingResultsErrors[2][3])
def testSEDCopyBasicColors(self):
"""Tests that when makeCopy=True in calcBasicColors the SED object is unchanged after calling
and that colors are still accurately calculated"""
testUtils = matchBase()
testSED = Sed()
copyTest = Sed()
testPhot = BandpassDict.loadTotalBandpassesFromFiles(self.filterList,
bandpassDir = os.path.join(lsst.utils.getPackageDir('throughputs'),'sdss'),
bandpassRoot = 'sdss_')
testSED.readSED_flambda(str(self.galDir + os.listdir(self.galDir)[0]))
copyTest.setSED(wavelen = testSED.wavelen, flambda = testSED.flambda)
testLambda = copyTest.wavelen[0]
testMags = testPhot.magListForSed(testSED)
testColors = []
for filtNum in range(0, len(self.filterList)-1):
testColors.append(testMags[filtNum] - testMags[filtNum+1])
testOutput = testUtils.calcBasicColors([copyTest], testPhot, makeCopy=True)
self.assertEqual(testLambda, copyTest.wavelen[0])
np.testing.assert_equal([testColors], testOutput)
def testApplyIGM(self):
"""Test application of IGM from Lookup Tables to SED objects"""
# Test that a warning comes up if input redshift is out
# of range and that no changes occurs to SED
testSed = Sed()
sedName = os.path.join(getPackageDir('sims_photUtils'),
'tests/cartoonSedTestData/galaxySed/')
testSed.readSED_flambda(os.path.join(sedName,
'Burst.10E08.002Z.spec.gz'))
testFlambda = []
for fVal in testSed.flambda:
testFlambda.append(fVal)
testIGM = ApplyIGM()
testIGM.initializeIGM()
with warnings.catch_warnings(record=True) as wa:
testIGM.applyIGM(1.1, testSed)
self.assertEqual(len(wa), 1)
self.assertIn('IGM Lookup tables', str(wa[-1].message))
np.testing.assert_equal(testFlambda, testSed.flambda)
# Test that lookup table is read in correctly
testTable15 = np.genfromtxt(str(getPackageDir('sims_photUtils') +
'/python/lsst/sims/photUtils/igm_tables/' +
'MeanLookupTable_zSource1.5.tbl.gz'))
np.testing.assert_equal(testTable15, testIGM.meanLookups['1.5'])
# Test output by making sure that an incoming sed
# with flambda = 1.0 everywhere will return the
# transmission values of the lookup table as its
# flambda output
testSed.setSED(testSed.wavelen, flambda=np.ones(len(testSed.wavelen)))
testIGM.applyIGM(1.5, testSed)
testTable15Above300 = testTable15[np.where(testTable15[:, 0] >= 300.0)]
testSed.resampleSED(wavelen_match = testTable15Above300[:, 0])
np.testing.assert_allclose(testTable15Above300[:, 1],
testSed.flambda, 1e-4)
def testApplyIGM(self):
"""Test application of IGM from Lookup Tables to SED objects"""
# Test that a warning comes up if input redshift is out
# of range and that no changes occurs to SED
testSed = Sed()
sedName = os.path.join(getPackageDir('sims_sed_library'), 'galaxySED')
testSed.readSED_flambda(os.path.join(sedName,
'Burst.10E08.002Z.spec.gz'))
testFlambda = []
for fVal in testSed.flambda:
testFlambda.append(fVal)
testIGM = ApplyIGM()
testIGM.initializeIGM()
with warnings.catch_warnings(record=True) as wa:
testIGM.applyIGM(1.1, testSed)
self.assertEqual(len(wa), 1)
self.assertIn('IGM Lookup tables', str(wa[-1].message))
np.testing.assert_equal(testFlambda, testSed.flambda)
# Test that lookup table is read in correctly
testTable15 = np.genfromtxt(str(getPackageDir('sims_catUtils') +
'/python/lsst/sims/catUtils/IGM/igm_tables/' +
'MeanLookupTable_zSource1.5.tbl.gz'))
np.testing.assert_equal(testTable15, testIGM.meanLookups['1.5'])
# Test output by making sure that an incoming sed
# with flambda = 1.0 everywhere will return the
# transmission values of the lookup table as its
# flambda output
testSed.setSED(testSed.wavelen, flambda=np.ones(len(testSed.wavelen)))
testIGM.applyIGM(1.5, testSed)
testTable15Above300 = testTable15[np.where(testTable15[:, 0] >= 300.0)]
testSed.resampleSED(wavelen_match = testTable15Above300[:, 0])
np.testing.assert_allclose(testTable15Above300[:, 1],
testSed.flambda, 1e-4)
def testSEDCopyBasicColors(self):
"""Tests that when makeCopy=True in calcBasicColors the SED object is unchanged after calling
and that colors are still accurately calculated"""
testUtils = matchBase()
testSED = Sed()
copyTest = Sed()
testPhot = BandpassDict.loadTotalBandpassesFromFiles(self.filterList,
bandpassDir = os.path.join(lsst.utils.getPackageDir('throughputs'),'sdss'),
bandpassRoot = 'sdss_')
testSED.readSED_flambda(str(self.galDir + os.listdir(self.galDir)[0]))
copyTest.setSED(wavelen = testSED.wavelen, flambda = testSED.flambda)
testLambda = copyTest.wavelen[0]
testMags = testPhot.magListForSed(testSED)
testColors = []
for filtNum in range(0, len(self.filterList)-1):
testColors.append(testMags[filtNum] - testMags[filtNum+1])
testOutput = testUtils.calcBasicColors([copyTest], testPhot, makeCopy=True)
self.assertEqual(testLambda, copyTest.wavelen[0])
np.testing.assert_equal([testColors], testOutput)
def calcMagNorm(self, objectMags, sedObj, bandpassDict, mag_error = None,
redshift = None, filtRange = None):
"""
This will find the magNorm value that gives the closest match to the magnitudes of the object
using the matched SED. Uses scipy.optimize.leastsq to find the values of fluxNorm that minimizes
the function: ((flux_obs - (fluxNorm*flux_model))/flux_error)**2.
@param [in] objectMags are the magnitude values for the object with extinction matching that of
the SED object. In the normal case using the selectSED routines above it will be dereddened mags.
@param [in] sedObj is an Sed class instance that is set with the wavelength and flux of the
matched SED
@param [in] bandpassDict is a BandpassDict class instance with the Bandpasses set to those
for the magnitudes given for the catalog object
@param [in] mag_error are provided error values for magnitudes in objectMags. If none provided
then this defaults to 1.0. This should be an array of the same length as objectMags.
@param [in] redshift is the redshift of the object if the magnitude is observed
@param [in] filtRange is a selected range of filters specified by their indices in the bandpassList
to match up against. Used when missing data in some magnitude bands.
@param [out] bestMagNorm is the magnitude normalization for the given magnitudes and SED
"""
import scipy.optimize as opt
sedTest = Sed()
sedTest.setSED(sedObj.wavelen, flambda = sedObj.flambda)
if redshift is not None:
sedTest.redshiftSED(redshift)
imSimBand = Bandpass()
imSimBand.imsimBandpass()
zp = -2.5*np.log10(3631) #Note using default AB zeropoint
flux_obs = np.power(10,(objectMags + zp)/(-2.5))
sedTest.resampleSED(wavelen_match=bandpassDict.values()[0].wavelen)
sedTest.flambdaTofnu()
flux_model = sedTest.manyFluxCalc(bandpassDict.phiArray, bandpassDict.wavelenStep)
if filtRange is not None:
flux_obs = flux_obs[filtRange]
flux_model = flux_model[filtRange]
if mag_error is None:
flux_error = np.ones(len(flux_obs))
else:
flux_error = np.abs(flux_obs*(np.log(10)/(-2.5))*mag_error)
bestFluxNorm = opt.leastsq(lambda x: ((flux_obs - (x*flux_model))/flux_error), 1.0)[0][0]
sedTest.multiplyFluxNorm(bestFluxNorm)
bestMagNorm = sedTest.calcMag(imSimBand)
return bestMagNorm
def read_asteroids_reflectance(dataDir='.'):
# Read the sun's spectrum.
sun = Sed()
sun.readSED_flambda('kurucz_sun')
# Read the asteroid reflectance spectra.
allfiles = os.listdir(dataDir)
asteroidDtype = numpy.dtype([
('wavelength', numpy.float),
('A', numpy.float),
('A_sig', numpy.float),
('B', numpy.float),
('B_sig', numpy.float),
('C', numpy.float),
('C_sig', numpy.float),
('Cb', numpy.float),
('Cb_sig', numpy.float),
('Cg', numpy.float),
('Cg_sig', numpy.float),
('Cgh', numpy.float),
('Cgh_sig', numpy.float),
('Ch', numpy.float),
('Ch_sig', numpy.float),
('D', numpy.float),
('D_sig', numpy.float),
('K', numpy.float),
('K_sig', numpy.float),
('L', numpy.float),
('L_sig', numpy.float),
('O', numpy.float),
('O_sig', numpy.float),
('Q', numpy.float),
('Q_sig', numpy.float),
('R', numpy.float),
('R_sig', numpy.float),
('S', numpy.float),
('S_sig', numpy.float),
('Sa', numpy.float),
('Sa_sig', numpy.float),
('Sq', numpy.float),
('Sq_sig', numpy.float),
('Sr', numpy.float),
('Sr_sig', numpy.float),
('Sv', numpy.float),
('Sv_sig', numpy.float),
('T', numpy.float),
('T_sig', numpy.float),
('V', numpy.float),
('V_sig', numpy.float),
('X', numpy.float),
('X_sig', numpy.float),
('Xc', numpy.float),
('Xc_sig', numpy.float),
('Xe', numpy.float),
('Xe_sig', numpy.float),
('Xk', numpy.float),
('Xk_sig', numpy.float),
])
data = numpy.loadtxt(os.path.join(dataDir, 'meanspectra.tab'),
dtype=asteroidDtype)
data['wavelength'] *= 1000.0 #because spectra are in microns
wavelen_step = min(
numpy.diff(data['wavelength']).min(),
numpy.diff(sun.wavelen).min())
wavelen = numpy.arange(sun.wavelen[0], data['wavelength'][-1],
wavelen_step)
ast_reflect = {}
for a in data.dtype.names:
if a == 'wavelength' or a[-3:] == 'sig':
continue
# Read the basic reflectance data
ast_reflect[a] = Sed(wavelen=data['wavelength'], flambda=data[a])
# And now add an extrapolation to the blue end.
# Binzel cuts off at 450nm.
condition = ((ast_reflect[a].wavelen >= 450) &
(ast_reflect[a].wavelen < 700))
x = ast_reflect[a].wavelen[condition]
y = ast_reflect[a].flambda[condition]
p = numpy.polyfit(x, y, deg=2)
condition = (wavelen < 450)
flambda = numpy.zeros(len(wavelen), 'float')
interpolated = numpy.polyval(p, wavelen[condition])
flambda[condition] = [ii if ii > 0.0 else 0.0 for ii in interpolated]
condition = (wavelen >= 450)
flambda[condition] = numpy.interp(wavelen[condition],
ast_reflect[a].wavelen,
ast_reflect[a].flambda)
ast_reflect[a] = Sed(wavelen, flambda)
ast = {}
for a in ast_reflect:
ast[a] = sun.multiplySED(ast_reflect[a], wavelen_step=wavelen_step)
for a in ast:
name = a + '.dat'
normalizedSed = Sed(wavelen=ast[a].wavelen, flambda=ast[a].flambda)
norm = numpy.interp(500.0, normalizedSed.wavelen,
normalizedSed.flambda)
normalizedSed.multiplyFluxNorm(1.0 / norm)
normalizedSed.writeSED(
name,
print_header='21 April 2015; normalized to flambda=1 at 500nm')
return ast_reflect, sun, ast
def matchToObserved(self, sedList, catMags, catRedshifts, catRA = None, catDec = None,
mag_error = None, bandpassDict = None, dzAcc = 2, reddening = True,
extCoeffs = (4.239, 3.303, 2.285, 1.698, 1.263)):
"""
This will find the closest match to the magnitudes of a galaxy catalog if those magnitudes are in
the observed frame and can correct for reddening from within the milky way as well if needed.
In order to make things faster it first calculates colors for all model SEDs at redshifts between
the minimum and maximum redshifts of the catalog objects provided with a grid spacing in redshift
defined by the parameter dzAcc. Objects without magnitudes in at least two adjacent bandpasses will
return as none and print out a message.
@param [in] sedList is the set of spectral objects from the models SEDs provided by loadBC03
or other custom loader routine.
@param [in] catMags is an array of the magnitudes of catalog objects to be matched with a model SED.
It should be organized so that there is one object's magnitudes along each row.
@param [in] catRedshifts is an array of the redshifts of each catalog object.
@param [in] catRA is an array of the RA positions for each catalog object.
@param [in] catDec is an array of the Dec position for each catalog object.
@param [in] mag_error are provided error values for magnitudes in objectMags. If none provided
then this defaults to 1.0. This should be an array of the same size as catMags.
@param [in] bandpassDict is a BandpassDict with which to calculate magnitudes.
If left equal to None it will by default load the SDSS [u,g,r,i,z] bandpasses and therefore agree with
default extCoeffs.
@param [in] dzAcc is the number of decimal places you want to use when building the redshift grid.
For example, dzAcc = 2 will create a grid between the minimum and maximum redshifts with colors
calculated at every 0.01 change in redshift.
@param [in] reddening is a boolean that determines whether to correct catalog magnitudes for
dust in the milky way. By default, it is True.
If true, this uses calculateEBV from EBV.py to find an EBV value for the object's
ra and dec coordinates and then uses the coefficients provided by extCoeffs which should come
from Schlafly and Finkbeiner (2011) for the correct filters and in the same order as provided
in bandpassDict.
If false, this means it will not run the dereddening procedure.
@param [in] extCoeffs are the Schlafly and Finkbeiner (2011) (ApJ, 737, 103) coefficients for the
given filters from bandpassDict and need to be in the same order as bandpassDict. The default given
are the SDSS [u,g,r,i,z] values.
@param [out] sedMatches is a list with the name of a model SED that matches most closely to each
object in the catalog.
@param [out] magNormMatches are the magnitude normalizations for the given magnitudes and
matched SED.
@param [out] matchErrors contains the Mean Squared Error between the colors of each object and
the colors of the matched SED.
"""
#Set up photometry to calculate model Mags
if bandpassDict is None:
galPhot = BandpassDict.loadTotalBandpassesFromFiles(['u','g','r','i','z'],
bandpassDir = os.path.join(lsst.utils.getPackageDir('throughputs'),'sdss'),
bandpassRoot = 'sdss_')
else:
galPhot = bandpassDict
#Calculate ebv from ra, dec coordinates if needed
if reddening == True:
#Check that catRA and catDec are included
if catRA is None or catDec is None:
raise RuntimeError("Reddening is True, but catRA and catDec are not included.")
calcEBV = ebv()
raDec = np.array((catRA,catDec))
#If only matching one object need to reshape for calculateEbv
if len(raDec.shape) == 1:
raDec = raDec.reshape((2,1))
ebvVals = calcEBV.calculateEbv(equatorialCoordinates = raDec)
objMags = self.deReddenMags(ebvVals, catMags, extCoeffs)
else:
objMags = catMags
minRedshift = np.round(np.min(catRedshifts), dzAcc)
maxRedshift = np.round(np.max(catRedshifts), dzAcc)
dz = np.power(10., (-1*dzAcc))
redshiftRange = np.round(np.arange(minRedshift - dz, maxRedshift + (2*dz), dz), dzAcc)
numRedshifted = 0
sedMatches = [None] * len(catRedshifts)
magNormMatches = [None] * len(catRedshifts)
matchErrors = [None] * len(catRedshifts)
redshiftIndex = np.argsort(catRedshifts)
numOn = 0
notMatched = 0
lastRedshift = -100
print 'Starting Matching. Arranged by redshift value.'
for redshift in redshiftRange:
if numRedshifted % 10 == 0:
print '%i out of %i redshifts gone through' % (numRedshifted, len(redshiftRange))
numRedshifted += 1
colorSet = []
for galSpec in sedList:
sedColors = []
fileSED = Sed()
fileSED.setSED(wavelen = galSpec.wavelen, flambda = galSpec.flambda)
fileSED.redshiftSED(redshift)
sedColors = self.calcBasicColors([fileSED], galPhot, makeCopy = True)
colorSet.append(sedColors)
colorSet = np.transpose(colorSet)
for currentIndex in redshiftIndex[numOn:]:
matchMags = objMags[currentIndex]
if lastRedshift < np.round(catRedshifts[currentIndex],dzAcc) <= redshift:
colorRange = np.arange(0, len(galPhot)-1)
matchColors = []
for colorNum in colorRange:
matchColors.append(matchMags[colorNum] - matchMags[colorNum+1])
#This is done to handle objects with incomplete magnitude data
filtNums = np.arange(0, len(galPhot))
if np.isnan(np.amin(matchColors))==True:
colorRange = np.where(np.isnan(matchColors)==False)[0]
filtNums = np.unique([colorRange, colorRange+1]) #Pick right filters in calcMagNorm
if len(colorRange) == 0:
print 'Could not match object #%i. No magnitudes for two adjacent bandpasses.' \
% (currentIndex)
notMatched += 1
#Don't need to assign 'None' here in result array, b/c 'None' is default value
else:
distanceArray = [np.zeros(len(sedList))]
for colorNum in colorRange:
distanceArray += np.power((colorSet[colorNum] - matchColors[colorNum]),2)
matchedSEDNum = np.nanargmin(distanceArray)
sedMatches[currentIndex] = sedList[matchedSEDNum].name
magNormVal = self.calcMagNorm(np.array(matchMags), sedList[matchedSEDNum],
galPhot, mag_error = mag_error,
redshift = catRedshifts[currentIndex],
filtRange = filtNums)
magNormMatches[currentIndex] = magNormVal
matchErrors[currentIndex] = (distanceArray[0,matchedSEDNum]/len(colorRange))
numOn += 1
else:
break
lastRedshift = redshift
print 'Done Matching. Matched %i of %i catalog objects to SEDs' % (len(catMags)-notMatched,
len(catMags))
if notMatched > 0:
print '%i objects did not get matched.' % (notMatched)
return sedMatches, magNormMatches, matchErrors
def loadGalfast(self, filenameList, outFileList, sEDPath = None, kuruczPath = None,
mltPath = None, wdPath = None, kuruczSubset = None,
mltSubset = None, wdSubset = None, chunkSize = 10000):
"""
This is customized for the outputs we currently need for the purposes of consistent output
It will read in a galfast output file and output desired values for database input into a file
@param [in] filenameList is a list of the galfast output files that will be loaded and processed.
Can process fits, gzipped, or txt output from galfast.
@param [in] outFileList is a list of the names of the output files that will be created. If gzipped
output is desired simply write the filenames with .gz at the end.
@param [in] kuruczPath is a place to specify a path to kurucz SED files
@param [in] mltPath is the same as kuruczPath except that it specifies a directory for the
mlt SEDs
@param [in] wdPath is the same as the previous two except that it specifies a path to a
white dwarf SED directory.
@param [in] kuruczSubset is a list which provides a subset of the kurucz files within the
kurucz folder that one wants to use
@param [in] mltSubset is a list which provides a subset of the mlt files within the
mlt folder that one wants to use
@param [in] wdSubset is a list which provides a subset of the wd files within the
wd folder that one wants to use
@param [in] chunkSize is the size of chunks of lines to be read from the catalog at one time.
"""
for filename in filenameList:
#Make sure input file exists and is readable format before doing anything else
if os.path.isfile(filename) == False:
raise RuntimeError('*** File does not exist')
#Process various possible galfast outputs
if filename.endswith(('.txt', '.gz', '.fits')):
continue
else:
raise RuntimeError(str('*** Unsupported File Format in file: ' + str(filename)))
#If all files exist and are in proper formats then load seds
selectStarSED0 = selectStarSED(kuruczDir=kuruczPath,
mltDir=mltPath,
wdDir=wdPath)
if kuruczSubset is None:
kuruczList = selectStarSED0.loadKuruczSEDs()
else:
kuruczList = selectStarSED0.loadKuruczSEDs(subset = kuruczSubset)
#Only need one dictionary since none of the names overlap
positionDict = {}
for kNum, kuruczSED in enumerate(kuruczList):
positionDict[kuruczSED.name] = kNum
if mltSubset is None:
mltList = selectStarSED0.loadmltSEDs()
else:
mltList = selectStarSED0.loadmltSEDs(subset = mltSubset)
for mltNum, mltSED in enumerate(mltList):
positionDict[mltSED.name] = mltNum
if wdSubset is None:
wdListH, wdListHE = selectStarSED0.loadwdSEDs()
else:
wdListH, wdListHE = selectStarSED0.loadwdSEDs(subset = wdSubset)
for hNum, hSED in enumerate(wdListH):
positionDict[hSED.name] = hNum
for heNum, heSED in enumerate(wdListHE):
positionDict[heSED.name] = heNum
#For adding/subtracting extinction when calculating colors
#Numbers below come from Schlafly and Finkbeiner (2011) (ApJ, 737, 103)
#normalized by SDSS r mag value
sdssExtCoeffs = [1.8551, 1.4455, 1.0, 0.7431, 0.5527]
lsstExtCoeffs = [1.8140, 1.4166, 0.9947, 0.7370, 0.5790, 0.4761]
sdssPhot = BandpassDict.loadTotalBandpassesFromFiles(['u','g','r','i','z'],
bandpassDir = os.path.join(lsst.utils.getPackageDir('throughputs'),
'sdss'),
bandpassRoot = 'sdss_')
#Load Bandpasses for LSST colors to get colors from matched SEDs
lsstFilterList = ('u', 'g', 'r', 'i', 'z', 'y')
lsstPhot = BandpassDict.loadTotalBandpassesFromFiles(lsstFilterList)
imSimBand = Bandpass()
imSimBand.imsimBandpass()
#Calculate colors and add them to the SED objects
kuruczColors = selectStarSED0.calcBasicColors(kuruczList, sdssPhot)
mltColors = selectStarSED0.calcBasicColors(mltList, sdssPhot)
hColors = selectStarSED0.calcBasicColors(wdListH, sdssPhot)
heColors = selectStarSED0.calcBasicColors(wdListHE, sdssPhot)
listDict = {'kurucz':kuruczList, 'mlt':mltList, 'H':wdListH, 'HE':wdListHE}
colorDict = {'kurucz':kuruczColors, 'mlt':mltColors, 'H':hColors, 'HE':heColors}
for filename, outFile in zip(filenameList, outFileList):
if filename.endswith('.txt'):
galfastIn = open(filename, 'rt')
inFits = False
gzFile = False
num_lines = sum(1 for line in open(filename))
elif filename.endswith('.gz'):
galfastIn = gzip.open(filename, 'rt')
inFits = False
gzFile = True
num_lines = sum(1 for line in gzip.open(filename))
elif filename.endswith('fits'):
hdulist = fits.open(filename)
galfastIn = hdulist[1].data
num_lines = len(galfastIn)
gzFile = False
inFits = True
if outFile.endswith('.txt'):
fOut = open(outFile, 'wt')
elif outFile.endswith('.gz'):
fOut = gzip.open(outFile, 'wt')
fOut.write('#oID, ra, dec, gall, galb, coordX, coordY, coordZ, sEDName, magNorm, ' +\
'LSSTugrizy, SDSSugriz, absSDSSr, pmRA, pmDec, vRad, pml, pmb, vRadlb, ' +\
'vR, vPhi, vZ, FeH, pop, distKpc, ebv, ebvInf\n')
header_length = 0
numChunks = 0
if inFits == False:
galfastDict = self.parseGalfast(galfastIn.readline())
header_length += 1
header_status = True
while header_status == True:
newLine = galfastIn.readline()
if newLine[0] != '#':
header_status = False
else:
header_length += 1
print('Total objects = %i' % (num_lines - header_length))
numChunks = ((num_lines-header_length)//chunkSize) + 1
for chunk in range(0,numChunks):
if chunk == numChunks-1:
lastChunkSize = (num_lines - header_length) % chunkSize
readSize = lastChunkSize
else:
readSize = chunkSize
oID = np.arange(readSize*chunk, readSize*(chunk+1))
if inFits:
starData = galfastIn[readSize*chunk:(readSize*chunk + readSize)]
sDSS = starData.field('SDSSugriz')
gall, galb = np.transpose(starData.field('lb'))
ra, dec = np.transpose(starData.field('radec'))
coordX, coordY, coordZ = np.transpose(starData.field('XYZ'))
DM = starData.field('DM')
absSDSSr = starData.field('absSDSSr')
pop = starData.field('comp')
FeH = starData.field('FeH')
vR, vPhi, vZ = np.transpose(starData.field('vcyl'))
pml, pmb, vRadlb = np.transpose(starData.field('pmlb'))
pmRA, pmDec, vRad = np.transpose(starData.field('pmradec'))
am = starData.field('Am')
amInf = starData.field('AmInf')
sdssPhotoFlags = starData.field('SDSSugrizPhotoFlags')
else:
if gzFile == False:
with open(filename) as t_in:
starData = np.loadtxt(itertools.islice(t_in,((readSize*chunk)+header_length),
((readSize*(chunk+1))+header_length)))
else:
with gzip.open(filename) as t_in:
starData = np.loadtxt(itertools.islice(t_in,((readSize*chunk)+header_length),
((readSize*(chunk+1))+header_length)))
starData = np.transpose(starData)
gall = starData[galfastDict['l']]
galb = starData[galfastDict['b']]
ra = starData[galfastDict['ra']]
dec = starData[galfastDict['dec']]
coordX = starData[galfastDict['X']]
coordY = starData[galfastDict['Y']]
coordZ = starData[galfastDict['Z']]
DM = starData[galfastDict['DM']]
absSDSSr = starData[galfastDict['absSDSSr']]
pop = starData[galfastDict['comp']]
FeH = starData[galfastDict['FeH']]
vR = starData[galfastDict['Vr']]
vPhi = starData[galfastDict['Vphi']]
vZ = starData[galfastDict['Vz']]
pml = starData[galfastDict['pml']]
pmb = starData[galfastDict['pmb']]
vRadlb = starData[galfastDict['vRadlb']]
pmRA = starData[galfastDict['pmra']]
pmDec = starData[galfastDict['pmdec']]
vRad = starData[galfastDict['vRad']]
am = starData[galfastDict['Am']]
amInf = starData[galfastDict['AmInf']]
sDSS = np.transpose(starData[galfastDict['SDSSu']:galfastDict['SDSSz']+1])
sDSSPhotoFlags = starData[galfastDict['SDSSPhotoFlags']]
#End of input, now onto processing and output
sDSSunred = selectStarSED0.deReddenMags(am, sDSS, sdssExtCoeffs)
if readSize == 1:
ra = np.array([ra])
dec = np.array([dec])
"""
Info about the following population cuts:
From Zeljko: "This color corresponds to the temperature (roughly spectral type M0) where
Kurucz models become increasingly bad, and thus we switch to empirical SEDs (the problem
is that for M and later stars, the effective surface temperature is low enough for
molecules to form, and their opacity is too complex to easily model, especially TiO)."
"""
mIn = np.where(((pop < 10) | (pop >= 20)) & (sDSSunred[:,2] - sDSSunred[:,3] > 0.59))
kIn = np.where(((pop < 10) | (pop >= 20)) & (sDSSunred[:,2] - sDSSunred[:,3] <= 0.59))
hIn = np.where((pop >= 10) & (pop < 15))
heIn = np.where((pop >= 15) & (pop < 20))
sEDNameK, magNormK, matchErrorK = selectStarSED0.findSED(listDict['kurucz'],
sDSSunred[kIn], ra[kIn], dec[kIn],
reddening = False,
colors = colorDict['kurucz'])
sEDNameM, magNormM, matchErrorM = selectStarSED0.findSED(listDict['mlt'],
sDSSunred[mIn], ra[mIn], dec[mIn],
reddening = False,
colors = colorDict['mlt'])
sEDNameH, magNormH, matchErrorH = selectStarSED0.findSED(listDict['H'],
sDSSunred[hIn], ra[hIn], dec[hIn],
reddening = False,
colors = colorDict['H'])
sEDNameHE, magNormHE, matchErrorHE = selectStarSED0.findSED(listDict['HE'],
sDSSunred[heIn],
ra[heIn], dec[heIn],
reddening = False,
colors = colorDict['HE'])
chunkNames = np.empty(readSize, dtype = 'S32')
chunkTypes = np.empty(readSize, dtype = 'S8')
chunkMagNorms = np.zeros(readSize)
chunkMatchErrors = np.zeros(readSize)
chunkNames[kIn] = sEDNameK
chunkTypes[kIn] = 'kurucz'
chunkMagNorms[kIn] = magNormK
chunkMatchErrors[kIn] = matchErrorK
chunkNames[mIn] = sEDNameM
chunkTypes[mIn] = 'mlt'
chunkMagNorms[mIn] = magNormM
chunkMatchErrors[mIn] = matchErrorM
chunkNames[hIn] = sEDNameH
chunkTypes[hIn] = 'H'
chunkMagNorms[hIn] = magNormH
chunkMatchErrors[hIn] = matchErrorH
chunkNames[heIn] = sEDNameHE
chunkTypes[heIn] = 'HE'
chunkMagNorms[heIn] = magNormHE
chunkMatchErrors[heIn] = matchErrorHE
lsstMagsUnred = []
for sedName, sedType, magNorm, matchError in zip(chunkNames.astype(str),
chunkTypes.astype(str),
chunkMagNorms,
chunkMatchErrors):
testSED = Sed()
testSED.setSED(listDict[sedType][positionDict[sedName]].wavelen,
flambda = listDict[sedType][positionDict[sedName]].flambda)
fluxNorm = testSED.calcFluxNorm(magNorm, imSimBand)
testSED.multiplyFluxNorm(fluxNorm)
lsstMagsUnred.append(lsstPhot.magListForSed(testSED))
#If the extinction value is negative then it will add the reddening back in
lsstMags = selectStarSED0.deReddenMags((-1.0*am), lsstMagsUnred,
lsstExtCoeffs)
distKpc = self.convDMtoKpc(DM)
ebv = am / 2.285 #From Schlafly and Finkbeiner 2011, (ApJ, 737, 103) for sdssr
ebvInf = amInf / 2.285
for line in range(0, readSize):
outFmt = '%i,%3.7f,%3.7f,%3.7f,%3.7f,%3.7f,' +\
'%3.7f,%3.7f,%s,' +\
'%3.7f,%3.7f,' +\
'%3.7f,%3.7f,%3.7f,' +\
'%3.7f,%3.7f,%3.7f,' +\
'%3.7f,%3.7f,%3.7f,%3.7f,' +\
'%3.7f,%3.7f,%3.7f,%3.7f,%3.7f,' +\
'%3.7f,%3.7f,%3.7f,%3.7f,%3.7f,%3.7f,' +\
'%3.7f,%i,%3.7f,%3.7f,%3.7f\n'
if readSize == 1:
if inFits == True:
sDSS = sDSS[0]
outDat = (oID, ra[line], dec[line], gall, galb, coordX,
coordY, coordZ, chunkNames,
chunkMagNorms, chunkMatchErrors,
lsstMags[line][0], lsstMags[line][1], lsstMags[line][2],
lsstMags[line][3], lsstMags[line][4], lsstMags[line][5],
sDSS[0], sDSS[1], sDSS[2], sDSS[3],
sDSS[4], absSDSSr, pmRA, pmDec, vRad,
pml, pmb, vRadlb, vR, vPhi, vZ,
FeH, pop, distKpc, ebv, ebvInf)
else:
outDat = (oID[line], ra[line], dec[line], gall[line], galb[line], coordX[line],
coordY[line], coordZ[line], chunkNames[line],
chunkMagNorms[line], chunkMatchErrors[line],
lsstMags[line][0], lsstMags[line][1], lsstMags[line][2],
lsstMags[line][3], lsstMags[line][4], lsstMags[line][5],
sDSS[line][0], sDSS[line][1], sDSS[line][2], sDSS[line][3],
sDSS[line][4], absSDSSr[line], pmRA[line], pmDec[line], vRad[line],
pml[line], pmb[line], vRadlb[line], vR[line], vPhi[line], vZ[line],
FeH[line], pop[line], distKpc[line], ebv[line], ebvInf[line])
fOut.write(outFmt % outDat)
print('Chunk Num Done = %i out of %i' % (chunk+1, numChunks))
def testCalcMagNorm(self):
"""Tests the calculation of magnitude normalization for an SED with the given magnitudes
in the given bandpasses."""
testUtils = matchBase()
bandpassDir = os.path.join(lsst.utils.getPackageDir('throughputs'), 'sdss')
testPhot = BandpassDict.loadTotalBandpassesFromFiles(self.filterList,
bandpassDir = bandpassDir,
bandpassRoot = 'sdss_')
unChangedSED = Sed()
unChangedSED.readSED_flambda(str(self.galDir + os.listdir(self.galDir)[0]))
imSimBand = Bandpass()
imSimBand.imsimBandpass()
testSED = Sed()
testSED.setSED(unChangedSED.wavelen, flambda = unChangedSED.flambda)
magNorm = 20.0
redVal = 0.1
testSED.redshiftSED(redVal)
fluxNorm = testSED.calcFluxNorm(magNorm, imSimBand)
testSED.multiplyFluxNorm(fluxNorm)
sedMags = testPhot.magListForSed(testSED)
stepSize = 0.001
testMagNorm = testUtils.calcMagNorm(sedMags, unChangedSED, testPhot, redshift = redVal)
# Test adding in mag_errors. If an array of np.ones is passed in we should get same result
testMagNormWithErr = testUtils.calcMagNorm(sedMags, unChangedSED, testPhot,
mag_error = np.ones(len(sedMags)), redshift = redVal)
# Also need to add in test for filtRange
sedMagsIncomp = sedMags
sedMagsIncomp[1] = None
filtRangeTest = [0, 2, 3, 4]
testMagNormFiltRange = testUtils.calcMagNorm(sedMagsIncomp, unChangedSED, testPhot,
redshift = redVal, filtRange = filtRangeTest)
self.assertAlmostEqual(magNorm, testMagNorm, delta = stepSize)
self.assertAlmostEqual(magNorm, testMagNormWithErr, delta = stepSize)
self.assertAlmostEqual(magNorm, testMagNormFiltRange, delta = stepSize)
def testAlternateBandpassesStars(self):
"""
This will test our ability to do photometry using non-LSST bandpasses.
It will first calculate the magnitudes using the getters in cartoonPhotometryStars.
It will then load the alternate bandpass files 'by hand' and re-calculate the magnitudes
and make sure that the magnitude values agree. This is guarding against the possibility
that some default value did not change and the code actually ended up loading the
LSST bandpasses.
"""
bandpassDir = os.path.join(lsst.utils.getPackageDir('sims_photUtils'), 'tests', 'cartoonSedTestData')
cartoon_dict = BandpassDict.loadTotalBandpassesFromFiles(['u', 'g', 'r', 'i', 'z'],
bandpassDir=bandpassDir,
bandpassRoot='test_bandpass_')
testBandPasses = {}
keys = ['u', 'g', 'r', 'i', 'z']
bplist = []
for kk in keys:
testBandPasses[kk] = Bandpass()
testBandPasses[kk].readThroughput(os.path.join(bandpassDir, "test_bandpass_%s.dat" % kk))
bplist.append(testBandPasses[kk])
sedObj = Sed()
phiArray, waveLenStep = sedObj.setupPhiArray(bplist)
sedFileName = os.path.join(lsst.utils.getPackageDir('sims_photUtils'),
'tests/cartoonSedTestData/starSed/')
sedFileName = os.path.join(sedFileName, 'kurucz', 'km20_5750.fits_g40_5790.gz')
ss = Sed()
ss.readSED_flambda(sedFileName)
controlBandpass = Bandpass()
controlBandpass.imsimBandpass()
ff = ss.calcFluxNorm(22.0, controlBandpass)
ss.multiplyFluxNorm(ff)
testMags = cartoon_dict.magListForSed(ss)
ss.resampleSED(wavelen_match = bplist[0].wavelen)
ss.flambdaTofnu()
mags = -2.5*np.log10(np.sum(phiArray*ss.fnu, axis=1)*waveLenStep) - ss.zp
self.assertEqual(len(mags), len(testMags))
self.assertGreater(len(mags), 0)
for j in range(len(mags)):
self.assertAlmostEqual(mags[j], testMags[j], 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 SNObjectSED(self, time, wavelen=None, bandpass=None,
applyExtinction=True):
'''
return a `lsst.sims.photUtils.sed` object from the SN model at the
requested time and wavelengths with or without extinction from MW
according to the SED extinction methods. The wavelengths may be
obtained from a `lsst.sims.Bandpass` object or a `lsst.sims.BandpassDict`
object instead. (Currently, these have the same wavelengths). See notes
for details on handling of exceptions.
If the sed is requested at times outside the validity range of the
model, the flux density is returned as 0. If the time is within the
range of validity of the model, but the wavelength range requested
is outside the range, then the returned fluxes are np.nan outside
the range, and the model fluxes inside
Parameters
----------
time: float
time of observation
wavelen: `np.ndarray` of floats, optional, defaults to None
array containing wavelengths in nm
bandpass: `lsst.sims.photUtils.Bandpass` object or
`lsst.sims.photUtils.BandpassDict`, optional, defaults to `None`.
Using the dict assumes that the wavelength sampling and range
is the same for all elements of the dict.
if provided, overrides wavelen input and the SED is
obtained at the wavelength values native to bandpass
object.
Returns
-------
`sims_photutils.sed` object containing the wavelengths and SED
values from the SN at time time in units of ergs/cm^2/sec/nm
.. note: If both wavelen and bandpassobject are `None` then exception,
will be raised.
Examples
--------
>>> sed = SN.SNObjectSED(time=0., wavelen=wavenm)
'''
if wavelen is None and bandpass is None:
raise ValueError('A non None input to either wavelen or\
bandpassobject must be provided')
# if bandpassobject present, it overrides wavelen
if bandpass is not None:
if isinstance(bandpass, BandpassDict):
firstfilter = bandpass.keys()[0]
bp = bandpass[firstfilter]
else:
bp = bandpass
# remember this is in nm
wavelen = bp.wavelen
flambda = np.zeros(len(wavelen))
# self.mintime() and self.maxtime() are properties describing
# the ranges of SNCosmo.Model in time. Behavior beyond this is
# determined by self.modelOutSideTemporalRange
if (time >= self.mintime()) and (time <= self.maxtime()):
# If SNCosmo is requested a SED value beyond the wavelength range
# of model it will crash. Try to prevent that by returning np.nan for
# such wavelengths. This will still not help band flux calculations
# but helps us get past this stage.
flambda = flambda * np.nan
# Convert to Ang
wave = wavelen * 10.0
mask1 = wave >= self.minwave()
mask2 = wave <= self.maxwave()
mask = mask1 & mask2
wave = wave[mask]
# flux density dE/dlambda returned from SNCosmo in
# ergs/cm^2/sec/Ang, convert to ergs/cm^2/sec/nm
flambda[mask] = self.flux(time=time, wave=wave)
flambda[mask] = flambda[mask] * 10.0
else:
# use prescription for modelOutSideTemporalRange
if self.modelOutSideTemporalRange != 'zero':
raise NotImplementedError('Model not implemented, change to zero\n')
# Else Do nothing as flambda is already 0.
# This takes precedence over being outside wavelength range
if self.rectifySED:
# Note that this converts nans into 0.
flambda = np.where(flambda > 0., flambda, 0.)
SEDfromSNcosmo = Sed(wavelen=wavelen, flambda=flambda)
if not applyExtinction:
return SEDfromSNcosmo
# Apply LSST extinction
global _sn_ax_cache
global _sn_bx_cache
global _sn_ax_bx_wavelen
if _sn_ax_bx_wavelen is None \
or len(wavelen)!=len(_sn_ax_bx_wavelen) \
or (wavelen!=_sn_ax_bx_wavelen).any():
ax, bx = SEDfromSNcosmo.setupCCM_ab()
_sn_ax_cache = ax
_sn_bx_cache = bx
_sn_ax_bx_wavelen = np.copy(wavelen)
else:
ax = _sn_ax_cache
bx = _sn_bx_cache
if self.ebvofMW is None:
raise ValueError('ebvofMW attribute cannot be None Type and must'
' be set by hand using set_MWebv before this'
'stage, or by using setcoords followed by'
'mwEBVfromMaps\n')
SEDfromSNcosmo.addDust(a_x=ax, b_x=bx, ebv=self.ebvofMW)
return SEDfromSNcosmo
def calcMagNorm(self,
objectMags,
sedObj,
bandpassDict,
mag_error=None,
redshift=None,
filtRange=None):
"""
This will find the magNorm value that gives the closest match to the magnitudes of the object
using the matched SED. Uses scipy.optimize.leastsq to find the values of fluxNorm that minimizes
the function: ((flux_obs - (fluxNorm*flux_model))/flux_error)**2.
@param [in] objectMags are the magnitude values for the object with extinction matching that of
the SED object. In the normal case using the selectSED routines above it will be dereddened mags.
@param [in] sedObj is an Sed class instance that is set with the wavelength and flux of the
matched SED
@param [in] bandpassDict is a BandpassDict class instance with the Bandpasses set to those
for the magnitudes given for the catalog object
@param [in] mag_error are provided error values for magnitudes in objectMags. If none provided
then this defaults to 1.0. This should be an array of the same length as objectMags.
@param [in] redshift is the redshift of the object if the magnitude is observed
@param [in] filtRange is a selected range of filters specified by their indices in the bandpassList
to match up against. Used when missing data in some magnitude bands.
@param [out] bestMagNorm is the magnitude normalization for the given magnitudes and SED
"""
import scipy.optimize as opt
sedTest = Sed()
sedTest.setSED(sedObj.wavelen, flambda=sedObj.flambda)
if redshift is not None:
sedTest.redshiftSED(redshift)
imSimBand = Bandpass()
imSimBand.imsimBandpass()
zp = -2.5 * np.log10(3631) #Note using default AB zeropoint
flux_obs = np.power(10, (objectMags + zp) / (-2.5))
sedTest.resampleSED(wavelen_match=bandpassDict.values()[0].wavelen)
sedTest.flambdaTofnu()
flux_model = sedTest.manyFluxCalc(bandpassDict.phiArray,
bandpassDict.wavelenStep)
if filtRange is not None:
flux_obs = flux_obs[filtRange]
flux_model = flux_model[filtRange]
if mag_error is None:
flux_error = np.ones(len(flux_obs))
else:
flux_error = np.abs(flux_obs * (np.log(10) / (-2.5)) * mag_error)
bestFluxNorm = opt.leastsq(
lambda x: ((flux_obs - (x * flux_model)) / flux_error), 1.0)[0][0]
sedTest.multiplyFluxNorm(bestFluxNorm)
bestMagNorm = sedTest.calcMag(imSimBand)
return bestMagNorm
def matchToObserved(self,
sedList,
catMags,
catRedshifts,
catRA=None,
catDec=None,
mag_error=None,
bandpassDict=None,
dzAcc=2,
reddening=True,
extCoeffs=(4.239, 3.303, 2.285, 1.698, 1.263)):
"""
This will find the closest match to the magnitudes of a galaxy catalog if those magnitudes are in
the observed frame and can correct for reddening from within the milky way as well if needed.
In order to make things faster it first calculates colors for all model SEDs at redshifts between
the minimum and maximum redshifts of the catalog objects provided with a grid spacing in redshift
defined by the parameter dzAcc. Objects without magnitudes in at least two adjacent bandpasses will
return as none and print out a message.
@param [in] sedList is the set of spectral objects from the models SEDs provided by loadBC03
or other custom loader routine.
@param [in] catMags is an array of the magnitudes of catalog objects to be matched with a model SED.
It should be organized so that there is one object's magnitudes along each row.
@param [in] catRedshifts is an array of the redshifts of each catalog object.
@param [in] catRA is an array of the RA positions for each catalog object.
@param [in] catDec is an array of the Dec position for each catalog object.
@param [in] mag_error are provided error values for magnitudes in objectMags. If none provided
then this defaults to 1.0. This should be an array of the same size as catMags.
@param [in] bandpassDict is a BandpassDict with which to calculate magnitudes.
If left equal to None it will by default load the SDSS [u,g,r,i,z] bandpasses and therefore agree with
default extCoeffs.
@param [in] dzAcc is the number of decimal places you want to use when building the redshift grid.
For example, dzAcc = 2 will create a grid between the minimum and maximum redshifts with colors
calculated at every 0.01 change in redshift.
@param [in] reddening is a boolean that determines whether to correct catalog magnitudes for
dust in the milky way. By default, it is True.
If true, this uses calculateEBV from EBV.py to find an EBV value for the object's
ra and dec coordinates and then uses the coefficients provided by extCoeffs which should come
from Schlafly and Finkbeiner (2011) for the correct filters and in the same order as provided
in bandpassDict.
If false, this means it will not run the dereddening procedure.
@param [in] extCoeffs are the Schlafly and Finkbeiner (2011) (ApJ, 737, 103) coefficients for the
given filters from bandpassDict and need to be in the same order as bandpassDict. The default given
are the SDSS [u,g,r,i,z] values.
@param [out] sedMatches is a list with the name of a model SED that matches most closely to each
object in the catalog.
@param [out] magNormMatches are the magnitude normalizations for the given magnitudes and
matched SED.
@param [out] matchErrors contains the Mean Squared Error between the colors of each object and
the colors of the matched SED.
"""
#Set up photometry to calculate model Mags
if bandpassDict is None:
galPhot = BandpassDict.loadTotalBandpassesFromFiles(
['u', 'g', 'r', 'i', 'z'],
bandpassDir=os.path.join(
lsst.utils.getPackageDir('throughputs'), 'sdss'),
bandpassRoot='sdss_')
else:
galPhot = bandpassDict
#Calculate ebv from ra, dec coordinates if needed
if reddening == True:
#Check that catRA and catDec are included
if catRA is None or catDec is None:
raise RuntimeError(
"Reddening is True, but catRA and catDec are not included."
)
calcEBV = ebv()
raDec = np.array((catRA, catDec))
#If only matching one object need to reshape for calculateEbv
if len(raDec.shape) == 1:
raDec = raDec.reshape((2, 1))
ebvVals = calcEBV.calculateEbv(equatorialCoordinates=raDec)
objMags = self.deReddenMags(ebvVals, catMags, extCoeffs)
else:
objMags = catMags
minRedshift = np.round(np.min(catRedshifts), dzAcc)
maxRedshift = np.round(np.max(catRedshifts), dzAcc)
dz = np.power(10., (-1 * dzAcc))
redshiftRange = np.round(
np.arange(minRedshift - dz, maxRedshift + (2 * dz), dz), dzAcc)
numRedshifted = 0
sedMatches = [None] * len(catRedshifts)
magNormMatches = [None] * len(catRedshifts)
matchErrors = [None] * len(catRedshifts)
redshiftIndex = np.argsort(catRedshifts)
numOn = 0
notMatched = 0
lastRedshift = -100
print 'Starting Matching. Arranged by redshift value.'
for redshift in redshiftRange:
if numRedshifted % 10 == 0:
print '%i out of %i redshifts gone through' % (
numRedshifted, len(redshiftRange))
numRedshifted += 1
colorSet = []
for galSpec in sedList:
sedColors = []
fileSED = Sed()
fileSED.setSED(wavelen=galSpec.wavelen,
flambda=galSpec.flambda)
fileSED.redshiftSED(redshift)
sedColors = self.calcBasicColors([fileSED],
galPhot,
makeCopy=True)
colorSet.append(sedColors)
colorSet = np.transpose(colorSet)
for currentIndex in redshiftIndex[numOn:]:
matchMags = objMags[currentIndex]
if lastRedshift < np.round(catRedshifts[currentIndex],
dzAcc) <= redshift:
colorRange = np.arange(0, len(galPhot) - 1)
matchColors = []
for colorNum in colorRange:
matchColors.append(matchMags[colorNum] -
matchMags[colorNum + 1])
#This is done to handle objects with incomplete magnitude data
filtNums = np.arange(0, len(galPhot))
if np.isnan(np.amin(matchColors)) == True:
colorRange = np.where(
np.isnan(matchColors) == False)[0]
filtNums = np.unique([
colorRange, colorRange + 1
]) #Pick right filters in calcMagNorm
if len(colorRange) == 0:
print 'Could not match object #%i. No magnitudes for two adjacent bandpasses.' \
% (currentIndex)
notMatched += 1
#Don't need to assign 'None' here in result array, b/c 'None' is default value
else:
distanceArray = [np.zeros(len(sedList))]
for colorNum in colorRange:
distanceArray += np.power(
(colorSet[colorNum] - matchColors[colorNum]),
2)
matchedSEDNum = np.nanargmin(distanceArray)
sedMatches[currentIndex] = sedList[matchedSEDNum].name
magNormVal = self.calcMagNorm(
np.array(matchMags),
sedList[matchedSEDNum],
galPhot,
mag_error=mag_error,
redshift=catRedshifts[currentIndex],
filtRange=filtNums)
magNormMatches[currentIndex] = magNormVal
matchErrors[currentIndex] = (
distanceArray[0, matchedSEDNum] / len(colorRange))
numOn += 1
else:
break
lastRedshift = redshift
print 'Done Matching. Matched %i of %i catalog objects to SEDs' % (
len(catMags) - notMatched, len(catMags))
if notMatched > 0:
print '%i objects did not get matched.' % (notMatched)
return sedMatches, magNormMatches, matchErrors
def testMatchToObserved(self):
"""Test that Galaxy SEDs with extinction or redshift are matched correctly"""
rng = np.random.RandomState(42)
galPhot = BandpassDict.loadTotalBandpassesFromFiles()
imSimBand = Bandpass()
imSimBand.imsimBandpass()
testMatching = selectGalaxySED(galDir = self.testSpecDir)
testSEDList = testMatching.loadBC03()
testSEDNames = []
testRA = []
testDec = []
testRedshifts = []
testMagNormList = []
magNormStep = 1
extCoeffs = [1.8140, 1.4166, 0.9947, 0.7370, 0.5790, 0.4761]
testMags = []
testMagsRedshift = []
testMagsExt = []
for testSED in testSEDList:
# As a check make sure that it matches when no extinction and no redshift are present
getSEDMags = Sed()
testSEDNames.append(testSED.name)
getSEDMags.setSED(wavelen = testSED.wavelen, flambda = testSED.flambda)
testMags.append(galPhot.magListForSed(getSEDMags))
# Check Extinction corrections
sedRA = rng.uniform(10, 170)
sedDec = rng.uniform(10, 80)
testRA.append(sedRA)
testDec.append(sedDec)
raDec = np.array((sedRA, sedDec)).reshape((2, 1))
ebvVal = ebv().calculateEbv(equatorialCoordinates = raDec)
extVal = ebvVal*extCoeffs
testMagsExt.append(galPhot.magListForSed(getSEDMags) + extVal)
# Setup magnitudes for testing matching to redshifted values
getRedshiftMags = Sed()
testZ = np.round(rng.uniform(1.1, 1.3), 3)
testRedshifts.append(testZ)
testMagNorm = np.round(rng.uniform(20.0, 22.0), magNormStep)
testMagNormList.append(testMagNorm)
getRedshiftMags.setSED(wavelen = testSED.wavelen, flambda = testSED.flambda)
getRedshiftMags.redshiftSED(testZ)
fluxNorm = getRedshiftMags.calcFluxNorm(testMagNorm, imSimBand)
getRedshiftMags.multiplyFluxNorm(fluxNorm)
testMagsRedshift.append(galPhot.magListForSed(getRedshiftMags))
# Will also test in passing of non-default bandpass
testNoExtNoRedshift = testMatching.matchToObserved(testSEDList, testMags, np.zeros(8),
reddening = False,
bandpassDict = galPhot)
testMatchingEbvVals = testMatching.matchToObserved(testSEDList, testMagsExt, np.zeros(8),
catRA = testRA, catDec = testDec,
reddening = True, extCoeffs = extCoeffs,
bandpassDict = galPhot)
# Substitute in nan values to simulate incomplete data and make sure magnorm works too.
testMagsRedshift[0][1] = np.nan
testMagsRedshift[0][3] = np.nan
testMagsRedshift[0][4] = np.nan
testMagsRedshift[1][1] = np.nan
testMatchingRedshift = testMatching.matchToObserved(testSEDList, testMagsRedshift, testRedshifts,
dzAcc = 3, reddening = False,
bandpassDict = galPhot)
self.assertEqual(testSEDNames, testNoExtNoRedshift[0])
self.assertEqual(testSEDNames, testMatchingEbvVals[0])
self.assertEqual(None, testMatchingRedshift[0][0])
self.assertEqual(testSEDNames[1:], testMatchingRedshift[0][1:])
self.assertEqual(None, testMatchingRedshift[1][0])
np.testing.assert_almost_equal(testMagNormList[1:], testMatchingRedshift[1][1:],
decimal = magNormStep)
# Test Match Errors
errMag = testMagsRedshift[2]
errRedshift = testRedshifts[2]
errMags = np.array((errMag, errMag, errMag, errMag))
errRedshifts = np.array((errRedshift, errRedshift, errRedshift, errRedshift))
errMags[1, 1] += 1. # Total MSE will be 2/(5 colors) = 0.4
errMags[2, 0:2] = np.nan
errMags[2, 3] += 1. # Total MSE will be 2/(3 colors) = 0.667
errMags[3, :] = None
errSED = testSEDList[2]
testMatchingResultsErrors = testMatching.matchToObserved([errSED], errMags, errRedshifts,
reddening = False,
bandpassDict = galPhot,
dzAcc = 3)
np.testing.assert_almost_equal(np.array((0.0, 0.4, 2./3.)), testMatchingResultsErrors[2][0:3],
decimal = 2) # Give a little more leeway due to redshifting effects
self.assertEqual(None, testMatchingResultsErrors[2][3])
def testSignalToNoise(self):
"""
Test that calcSNR_m5 and calcSNR_sed give similar results
"""
defaults = LSSTdefaults()
photParams = PhotometricParameters()
totalDict, hardwareDict = BandpassDict.loadBandpassesFromFiles()
skySED = Sed()
skySED.readSED_flambda(
os.path.join(lsst.utils.getPackageDir('throughputs'), 'baseline',
'darksky.dat'))
m5 = []
for filt in totalDict:
m5.append(
calcM5(skySED,
totalDict[filt],
hardwareDict[filt],
photParams,
seeing=defaults.seeing(filt)))
sedDir = lsst.utils.getPackageDir('sims_sed_library')
sedDir = os.path.join(sedDir, 'starSED', 'kurucz')
fileNameList = os.listdir(sedDir)
numpy.random.seed(42)
offset = numpy.random.random_sample(len(fileNameList)) * 2.0
for ix, name in enumerate(fileNameList):
if ix > 100:
break
spectrum = Sed()
spectrum.readSED_flambda(os.path.join(sedDir, name))
ff = spectrum.calcFluxNorm(m5[2] - offset[ix],
totalDict.values()[2])
spectrum.multiplyFluxNorm(ff)
magList = []
controlList = []
magList = []
for filt in totalDict:
controlList.append(
calcSNR_sed(spectrum, totalDict[filt], skySED,
hardwareDict[filt], photParams,
defaults.seeing(filt)))
magList.append(spectrum.calcMag(totalDict[filt]))
testList, gammaList = calcSNR_m5(numpy.array(magList),
numpy.array(totalDict.values()),
numpy.array(m5), photParams)
for tt, cc in zip(controlList, testList):
msg = '%e != %e ' % (tt, cc)
self.assertTrue(numpy.abs(tt / cc - 1.0) < 0.001, msg=msg)
def testFindSED(self):
"""Pull SEDs from each type and make sure that each SED gets matched to itself.
Includes testing with extinction and passing in only colors."""
rng = np.random.RandomState(42)
bandpassDir = os.path.join(lsst.utils.getPackageDir('throughputs'), 'sdss')
starPhot = BandpassDict.loadTotalBandpassesFromFiles(('u', 'g', 'r', 'i', 'z'),
bandpassDir = bandpassDir,
bandpassRoot = 'sdss_')
imSimBand = Bandpass()
imSimBand.imsimBandpass()
testMatching = selectStarSED(kuruczDir=self.testKDir,
mltDir=self.testMLTDir,
wdDir=self.testWDDir)
testSEDList = []
testSEDList.append(testMatching.loadKuruczSEDs())
testSEDList.append(testMatching.loadmltSEDs())
testSEDListH, testSEDListHE = testMatching.loadwdSEDs()
testSEDList.append(testSEDListH)
testSEDList.append(testSEDListHE)
testSEDNames = []
testMags = []
testMagNormList = []
magNormStep = 1
for typeList in testSEDList:
if len(typeList) != 0:
typeSEDNames = []
typeMags = []
typeMagNorms = []
for testSED in typeList:
getSEDMags = Sed()
typeSEDNames.append(testSED.name)
getSEDMags.setSED(wavelen = testSED.wavelen, flambda = testSED.flambda)
testMagNorm = np.round(rng.uniform(20.0, 22.0), magNormStep)
typeMagNorms.append(testMagNorm)
fluxNorm = getSEDMags.calcFluxNorm(testMagNorm, imSimBand)
getSEDMags.multiplyFluxNorm(fluxNorm)
typeMags.append(starPhot.magListForSed(getSEDMags))
testSEDNames.append(typeSEDNames)
testMags.append(typeMags)
testMagNormList.append(typeMagNorms)
# Since default bandpassDict should be SDSS ugrizy shouldn't need to specify it
# Substitute in nan values to simulate incomplete data.
for typeList, names, mags, magNorms in zip(testSEDList, testSEDNames, testMags, testMagNormList):
if len(typeList) > 2:
nanMags = np.array(mags)
nanMags[0][0] = np.nan
nanMags[0][2] = np.nan
nanMags[0][3] = np.nan
nanMags[1][1] = np.nan
testMatchingResults = testMatching.findSED(typeList, nanMags, reddening = False)
self.assertEqual(None, testMatchingResults[0][0])
self.assertEqual(names[1:], testMatchingResults[0][1:])
self.assertEqual(None, testMatchingResults[1][0])
np.testing.assert_almost_equal(magNorms[1:], testMatchingResults[1][1:],
decimal = magNormStep)
else:
testMatchingResults = testMatching.findSED(typeList, mags, reddening = False)
self.assertEqual(names, testMatchingResults[0])
np.testing.assert_almost_equal(magNorms, testMatchingResults[1], decimal = magNormStep)
# Test Null Values option
nullMags = np.array(testMags[0])
nullMags[0][0] = -99.
nullMags[0][4] = -99.
nullMags[1][0] = -99.
nullMags[1][1] = -99.
testMatchingResultsNull = testMatching.findSED(testSEDList[0], nullMags,
nullValues = -99., reddening = False)
self.assertEqual(testSEDNames[0], testMatchingResultsNull[0])
np.testing.assert_almost_equal(testMagNormList[0], testMatchingResultsNull[1],
decimal = magNormStep)
# Test Error Output
errMags = np.array((testMags[0][0], testMags[0][0], testMags[0][0], testMags[0][0]))
errMags[1, 1] += 1. # Total MSE will be 2/(4 colors) = 0.5
errMags[2, 0:2] = np.nan
errMags[2, 3] += 1. # Total MSE will be 2/(2 colors) = 1.0
errMags[3, :] = None
errSED = testSEDList[0][0]
testMatchingResultsErrors = testMatching.findSED([errSED], errMags, reddening = False)
np.testing.assert_almost_equal(np.array((0.0, 0.5, 1.0)), testMatchingResultsErrors[2][0:3],
decimal = 3)
self.assertEqual(None, testMatchingResultsErrors[2][3])
# Now test what happens if we pass in a bandpassDict
testMatchingResultsNoDefault = testMatching.findSED(testSEDList[0], testMags[0],
bandpassDict = starPhot,
reddening = False)
self.assertEqual(testSEDNames[0], testMatchingResultsNoDefault[0])
np.testing.assert_almost_equal(testMagNormList[0], testMatchingResultsNoDefault[1],
decimal = magNormStep)
# Test Reddening
testRA = rng.uniform(10, 170, len(testSEDList[0]))
testDec = rng.uniform(10, 80, len(testSEDList[0]))
extFactor = .5
raDec = np.array((testRA, testDec))
ebvVals = ebv().calculateEbv(equatorialCoordinates = raDec)
extVals = ebvVals*extFactor
testRedMags = []
for extVal, testMagSet in zip(extVals, testMags[0]):
testRedMags.append(testMagSet + extVal)
testMatchingResultsRed = testMatching.findSED(testSEDList[0], testRedMags, catRA = testRA,
catDec = testDec, reddening = True,
extCoeffs = np.ones(5)*extFactor)
self.assertEqual(testSEDNames[0], testMatchingResultsRed[0])
np.testing.assert_almost_equal(testMagNormList[0], testMatchingResultsRed[1],
decimal = magNormStep)
# Finally, test color input
testColors = []
for testMagSet in testMags[0]:
testColorSet = []
for filtNum in range(0, len(starPhot)-1):
testColorSet.append(testMagSet[filtNum] - testMagSet[filtNum+1])
testColors.append(testColorSet)
testMatchingColorsInput = testMatching.findSED(testSEDList[0], testMags[0],
reddening = False, colors = testColors)
self.assertEqual(testSEDNames[0], testMatchingColorsInput[0])
np.testing.assert_almost_equal(testMagNormList[0], testMatchingColorsInput[1],
decimal = magNormStep)
def applyIGM(self, redshift, sedobj):
"""
Apply IGM extinction to already redshifted sed with redshift
between zMin and zMax defined by range of lookup tables
@param [in] redshift is the redshift of the incoming SED object
@param [in] sedobj is the SED object to which IGM extinction will be applied. This object
will be modified as a result of this.
"""
if self.IGMisInitialized == False:
self.initializeIGM()
#First make sure redshift is in range of lookup tables.
if (redshift < self.zMin) or (redshift > self.zMax):
warnings.warn(
str("IGM Lookup tables only applicable for " + str(self.zMin) +
" < z < " + str(self.zMax) + ". No action taken"))
return
#Now read in closest two lookup tables for given redshift
lowerSed = Sed()
upperSed = Sed()
for lower, upper in zip(self.zRange[:-1], self.zRange[1:]):
if lower <= redshift <= upper:
lowerSed.setSED(self.meanLookups[str(lower)][:, 0],
flambda=self.meanLookups[str(lower)][:, 1])
upperSed.setSED(self.meanLookups[str(upper)][:, 0],
flambda=self.meanLookups[str(upper)][:, 1])
break
#Redshift lookup tables to redshift of source, i.e. if source redshift is 1.78 shift lookup
#table for 1.7 and lookup table for 1.8 to up and down to 1.78, respectively
zLowerShift = ((1.0 + redshift) / (1.0 + lower)) - 1.0
zUpperShift = ((1.0 + redshift) / (1.0 + upper)) - 1.0
lowerSed.redshiftSED(zLowerShift)
upperSed.redshiftSED(zUpperShift)
#Resample lower and upper transmission data onto same wavelength grid.
minWavelen = 300. #All lookup tables are usable above 300nm
maxWavelen = np.amin([lowerSed.wavelen[-1], upperSed.wavelen[-1]
]) - 0.01
lowerSed.resampleSED(wavelen_min=minWavelen,
wavelen_max=maxWavelen,
wavelen_step=0.01)
upperSed.resampleSED(wavelen_match=lowerSed.wavelen)
#Now insert this into a transmission array of 1.0 beyond the limits of current application
#So that we can get an sed back that extends to the longest wavelengths of the incoming sed
finalWavelen = np.arange(300., sedobj.wavelen[-1] + 0.01, 0.01)
finalFlambdaExtended = np.ones(len(finalWavelen))
#Weighted Average of Transmission from each lookup table to get final transmission
#table at desired redshift
dzGrid = self.zDelta #Step in redshift between transmission lookup table files
finalSed = Sed()
finalFlambda = (lowerSed.flambda * (1.0 -
((redshift - lower) / dzGrid)) +
upperSed.flambda * (1.0 -
((upper - redshift) / dzGrid)))
finalFlambdaExtended[0:len(finalFlambda)] = finalFlambda
finalSed.setSED(wavelen=finalWavelen, flambda=finalFlambdaExtended)
#Resample incoming sed to new grid so that we don't get warnings from multiplySED
#about matching wavelength grids
sedobj.resampleSED(wavelen_match=finalSed.wavelen)
#Now multiply transmission curve by input SED to get final result and make it the new flambda
#data in the original sed which also is now on a new grid starting at 300 nm
test = sedobj.multiplySED(finalSed)
sedobj.flambda = test.flambda
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 loadGalfast(self,
filenameList,
outFileList,
sEDPath=None,
kuruczPath=None,
mltPath=None,
wdPath=None,
kuruczSubset=None,
mltSubset=None,
wdSubset=None,
chunkSize=10000):
"""
This is customized for the outputs we currently need for the purposes of consistent output
It will read in a galfast output file and output desired values for database input into a file
@param [in] filenameList is a list of the galfast output files that will be loaded and processed.
Can process fits, gzipped, or txt output from galfast.
@param [in] outFileList is a list of the names of the output files that will be created. If gzipped
output is desired simply write the filenames with .gz at the end.
@param [in] kuruczPath is a place to specify a path to kurucz SED files
@param [in] mltPath is the same as kuruczPath except that it specifies a directory for the
mlt SEDs
@param [in] wdPath is the same as the previous two except that it specifies a path to a
white dwarf SED directory.
@param [in] kuruczSubset is a list which provides a subset of the kurucz files within the
kurucz folder that one wants to use
@param [in] mltSubset is a list which provides a subset of the mlt files within the
mlt folder that one wants to use
@param [in] wdSubset is a list which provides a subset of the wd files within the
wd folder that one wants to use
@param [in] chunkSize is the size of chunks of lines to be read from the catalog at one time.
"""
for filename in filenameList:
#Make sure input file exists and is readable format before doing anything else
if os.path.isfile(filename) == False:
raise RuntimeError('*** File does not exist')
#Process various possible galfast outputs
if filename.endswith(('.txt', '.gz', '.fits')):
continue
else:
raise RuntimeError(
str('*** Unsupported File Format in file: ' +
str(filename)))
#If all files exist and are in proper formats then load seds
selectStarSED0 = selectStarSED(kuruczDir=kuruczPath,
mltDir=mltPath,
wdDir=wdPath)
if kuruczSubset is None:
kuruczList = selectStarSED0.loadKuruczSEDs()
else:
kuruczList = selectStarSED0.loadKuruczSEDs(subset=kuruczSubset)
#Only need one dictionary since none of the names overlap
positionDict = {}
for kNum, kuruczSED in enumerate(kuruczList):
positionDict[kuruczSED.name] = kNum
if mltSubset is None:
mltList = selectStarSED0.loadmltSEDs()
else:
mltList = selectStarSED0.loadmltSEDs(subset=mltSubset)
for mltNum, mltSED in enumerate(mltList):
positionDict[mltSED.name] = mltNum
if wdSubset is None:
wdListH, wdListHE = selectStarSED0.loadwdSEDs()
else:
wdListH, wdListHE = selectStarSED0.loadwdSEDs(subset=wdSubset)
for hNum, hSED in enumerate(wdListH):
positionDict[hSED.name] = hNum
for heNum, heSED in enumerate(wdListHE):
positionDict[heSED.name] = heNum
#For adding/subtracting extinction when calculating colors
#Numbers below come from Schlafly and Finkbeiner (2011) (ApJ, 737, 103)
#normalized by SDSS r mag value
sdssExtCoeffs = [1.8551, 1.4455, 1.0, 0.7431, 0.5527]
lsstExtCoeffs = [1.8140, 1.4166, 0.9947, 0.7370, 0.5790, 0.4761]
sdssPhot = BandpassDict.loadTotalBandpassesFromFiles(
['u', 'g', 'r', 'i', 'z'],
bandpassDir=os.path.join(lsst.utils.getPackageDir('throughputs'),
'sdss'),
bandpassRoot='sdss_')
#Load Bandpasses for LSST colors to get colors from matched SEDs
lsstFilterList = ('u', 'g', 'r', 'i', 'z', 'y')
lsstPhot = BandpassDict.loadTotalBandpassesFromFiles(lsstFilterList)
imSimBand = Bandpass()
imSimBand.imsimBandpass()
#Calculate colors and add them to the SED objects
kuruczColors = selectStarSED0.calcBasicColors(kuruczList, sdssPhot)
mltColors = selectStarSED0.calcBasicColors(mltList, sdssPhot)
hColors = selectStarSED0.calcBasicColors(wdListH, sdssPhot)
heColors = selectStarSED0.calcBasicColors(wdListHE, sdssPhot)
listDict = {
'kurucz': kuruczList,
'mlt': mltList,
'H': wdListH,
'HE': wdListHE
}
colorDict = {
'kurucz': kuruczColors,
'mlt': mltColors,
'H': hColors,
'HE': heColors
}
for filename, outFile in zip(filenameList, outFileList):
if filename.endswith('.txt'):
galfastIn = open(filename, 'rt')
inFits = False
gzFile = False
num_lines = sum(1 for line in open(filename))
elif filename.endswith('.gz'):
galfastIn = gzip.open(filename, 'rt')
inFits = False
gzFile = True
num_lines = sum(1 for line in gzip.open(filename))
elif filename.endswith('fits'):
hdulist = fits.open(filename)
galfastIn = hdulist[1].data
num_lines = len(galfastIn)
gzFile = False
inFits = True
if outFile.endswith('.txt'):
fOut = open(outFile, 'wt')
elif outFile.endswith('.gz'):
fOut = gzip.open(outFile, 'wt')
fOut.write('#oID, ra, dec, gall, galb, coordX, coordY, coordZ, sEDName, magNorm, ' +\
'LSSTugrizy, SDSSugriz, absSDSSr, pmRA, pmDec, vRad, pml, pmb, vRadlb, ' +\
'vR, vPhi, vZ, FeH, pop, distKpc, ebv, ebvInf\n')
header_length = 0
numChunks = 0
if inFits == False:
galfastDict = self.parseGalfast(galfastIn.readline())
header_length += 1
header_status = True
while header_status == True:
newLine = galfastIn.readline()
if newLine[0] != '#':
header_status = False
else:
header_length += 1
print('Total objects = %i' % (num_lines - header_length))
numChunks = ((num_lines - header_length) // chunkSize) + 1
for chunk in range(0, numChunks):
if chunk == numChunks - 1:
lastChunkSize = (num_lines - header_length) % chunkSize
readSize = lastChunkSize
else:
readSize = chunkSize
oID = np.arange(readSize * chunk, readSize * (chunk + 1))
if inFits:
starData = galfastIn[readSize * chunk:(readSize * chunk +
readSize)]
sDSS = starData.field('SDSSugriz')
gall, galb = np.transpose(starData.field('lb'))
ra, dec = np.transpose(starData.field('radec'))
coordX, coordY, coordZ = np.transpose(
starData.field('XYZ'))
DM = starData.field('DM')
absSDSSr = starData.field('absSDSSr')
pop = starData.field('comp')
FeH = starData.field('FeH')
vR, vPhi, vZ = np.transpose(starData.field('vcyl'))
pml, pmb, vRadlb = np.transpose(starData.field('pmlb'))
pmRA, pmDec, vRad = np.transpose(starData.field('pmradec'))
am = starData.field('Am')
amInf = starData.field('AmInf')
sdssPhotoFlags = starData.field('SDSSugrizPhotoFlags')
else:
if gzFile == False:
with open(filename) as t_in:
starData = np.loadtxt(
itertools.islice(
t_in, ((readSize * chunk) + header_length),
((readSize *
(chunk + 1)) + header_length)))
else:
with gzip.open(filename) as t_in:
starData = np.loadtxt(
itertools.islice(
t_in, ((readSize * chunk) + header_length),
((readSize *
(chunk + 1)) + header_length)))
starData = np.transpose(starData)
gall = starData[galfastDict['l']]
galb = starData[galfastDict['b']]
ra = starData[galfastDict['ra']]
dec = starData[galfastDict['dec']]
coordX = starData[galfastDict['X']]
coordY = starData[galfastDict['Y']]
coordZ = starData[galfastDict['Z']]
DM = starData[galfastDict['DM']]
absSDSSr = starData[galfastDict['absSDSSr']]
pop = starData[galfastDict['comp']]
FeH = starData[galfastDict['FeH']]
vR = starData[galfastDict['Vr']]
vPhi = starData[galfastDict['Vphi']]
vZ = starData[galfastDict['Vz']]
pml = starData[galfastDict['pml']]
pmb = starData[galfastDict['pmb']]
vRadlb = starData[galfastDict['vRadlb']]
pmRA = starData[galfastDict['pmra']]
pmDec = starData[galfastDict['pmdec']]
vRad = starData[galfastDict['vRad']]
am = starData[galfastDict['Am']]
amInf = starData[galfastDict['AmInf']]
sDSS = np.transpose(
starData[galfastDict['SDSSu']:galfastDict['SDSSz'] +
1])
sDSSPhotoFlags = starData[galfastDict['SDSSPhotoFlags']]
#End of input, now onto processing and output
sDSSunred = selectStarSED0.deReddenMags(
am, sDSS, sdssExtCoeffs)
if readSize == 1:
ra = np.array([ra])
dec = np.array([dec])
"""
Info about the following population cuts:
From Zeljko: "This color corresponds to the temperature (roughly spectral type M0) where
Kurucz models become increasingly bad, and thus we switch to empirical SEDs (the problem
is that for M and later stars, the effective surface temperature is low enough for
molecules to form, and their opacity is too complex to easily model, especially TiO)."
"""
mIn = np.where(((pop < 10) | (pop >= 20))
& (sDSSunred[:, 2] - sDSSunred[:, 3] > 0.59))
kIn = np.where(((pop < 10) | (pop >= 20))
& (sDSSunred[:, 2] - sDSSunred[:, 3] <= 0.59))
hIn = np.where((pop >= 10) & (pop < 15))
heIn = np.where((pop >= 15) & (pop < 20))
sEDNameK, magNormK, matchErrorK = selectStarSED0.findSED(
listDict['kurucz'],
sDSSunred[kIn],
ra[kIn],
dec[kIn],
reddening=False,
colors=colorDict['kurucz'])
sEDNameM, magNormM, matchErrorM = selectStarSED0.findSED(
listDict['mlt'],
sDSSunred[mIn],
ra[mIn],
dec[mIn],
reddening=False,
colors=colorDict['mlt'])
sEDNameH, magNormH, matchErrorH = selectStarSED0.findSED(
listDict['H'],
sDSSunred[hIn],
ra[hIn],
dec[hIn],
reddening=False,
colors=colorDict['H'])
sEDNameHE, magNormHE, matchErrorHE = selectStarSED0.findSED(
listDict['HE'],
sDSSunred[heIn],
ra[heIn],
dec[heIn],
reddening=False,
colors=colorDict['HE'])
chunkNames = np.empty(readSize, dtype='S32')
chunkTypes = np.empty(readSize, dtype='S8')
chunkMagNorms = np.zeros(readSize)
chunkMatchErrors = np.zeros(readSize)
chunkNames[kIn] = sEDNameK
chunkTypes[kIn] = 'kurucz'
chunkMagNorms[kIn] = magNormK
chunkMatchErrors[kIn] = matchErrorK
chunkNames[mIn] = sEDNameM
chunkTypes[mIn] = 'mlt'
chunkMagNorms[mIn] = magNormM
chunkMatchErrors[mIn] = matchErrorM
chunkNames[hIn] = sEDNameH
chunkTypes[hIn] = 'H'
chunkMagNorms[hIn] = magNormH
chunkMatchErrors[hIn] = matchErrorH
chunkNames[heIn] = sEDNameHE
chunkTypes[heIn] = 'HE'
chunkMagNorms[heIn] = magNormHE
chunkMatchErrors[heIn] = matchErrorHE
lsstMagsUnred = []
for sedName, sedType, magNorm, matchError in zip(
chunkNames.astype(str), chunkTypes.astype(str),
chunkMagNorms, chunkMatchErrors):
testSED = Sed()
testSED.setSED(
listDict[sedType][positionDict[sedName]].wavelen,
flambda=listDict[sedType][
positionDict[sedName]].flambda)
fluxNorm = testSED.calcFluxNorm(magNorm, imSimBand)
testSED.multiplyFluxNorm(fluxNorm)
lsstMagsUnred.append(lsstPhot.magListForSed(testSED))
#If the extinction value is negative then it will add the reddening back in
lsstMags = selectStarSED0.deReddenMags(
(-1.0 * am), lsstMagsUnred, lsstExtCoeffs)
distKpc = self.convDMtoKpc(DM)
ebv = am / 2.285 #From Schlafly and Finkbeiner 2011, (ApJ, 737, 103) for sdssr
ebvInf = amInf / 2.285
for line in range(0, readSize):
outFmt = '%i,%3.7f,%3.7f,%3.7f,%3.7f,%3.7f,' +\
'%3.7f,%3.7f,%s,' +\
'%3.7f,%3.7f,' +\
'%3.7f,%3.7f,%3.7f,' +\
'%3.7f,%3.7f,%3.7f,' +\
'%3.7f,%3.7f,%3.7f,%3.7f,' +\
'%3.7f,%3.7f,%3.7f,%3.7f,%3.7f,' +\
'%3.7f,%3.7f,%3.7f,%3.7f,%3.7f,%3.7f,' +\
'%3.7f,%i,%3.7f,%3.7f,%3.7f\n'
if readSize == 1:
if inFits == True:
sDSS = sDSS[0]
outDat = (oID, ra[line], dec[line], gall, galb, coordX,
coordY, coordZ, chunkNames, chunkMagNorms,
chunkMatchErrors, lsstMags[line][0],
lsstMags[line][1], lsstMags[line][2],
lsstMags[line][3], lsstMags[line][4],
lsstMags[line][5], sDSS[0], sDSS[1], sDSS[2],
sDSS[3], sDSS[4], absSDSSr, pmRA, pmDec,
vRad, pml, pmb, vRadlb, vR, vPhi, vZ, FeH,
pop, distKpc, ebv, ebvInf)
else:
outDat = (oID[line], ra[line], dec[line], gall[line],
galb[line], coordX[line], coordY[line],
coordZ[line], chunkNames[line],
chunkMagNorms[line], chunkMatchErrors[line],
lsstMags[line][0], lsstMags[line][1],
lsstMags[line][2], lsstMags[line][3],
lsstMags[line][4], lsstMags[line][5],
sDSS[line][0], sDSS[line][1], sDSS[line][2],
sDSS[line][3], sDSS[line][4], absSDSSr[line],
pmRA[line], pmDec[line], vRad[line],
pml[line], pmb[line], vRadlb[line], vR[line],
vPhi[line], vZ[line], FeH[line], pop[line],
distKpc[line], ebv[line], ebvInf[line])
fOut.write(outFmt % outDat)
print('Chunk Num Done = %i out of %i' % (chunk + 1, numChunks))
def testMatchToObserved(self):
"""Test that Galaxy SEDs with extinction or redshift are matched correctly"""
np.random.seed(42)
galPhot = BandpassDict.loadTotalBandpassesFromFiles()
imSimBand = Bandpass()
imSimBand.imsimBandpass()
testMatching = selectGalaxySED(galDir = self.testSpecDir)
testSEDList = testMatching.loadBC03()
testSEDNames = []
testRA = []
testDec = []
testRedshifts = []
testMagNormList = []
magNormStep = 1
extCoeffs = [1.8140, 1.4166, 0.9947, 0.7370, 0.5790, 0.4761]
testMags = []
testMagsRedshift = []
testMagsExt = []
for testSED in testSEDList:
#As a check make sure that it matches when no extinction and no redshift are present
getSEDMags = Sed()
testSEDNames.append(testSED.name)
getSEDMags.setSED(wavelen = testSED.wavelen, flambda = testSED.flambda)
testMags.append(galPhot.magListForSed(getSEDMags))
#Check Extinction corrections
sedRA = np.random.uniform(10,170)
sedDec = np.random.uniform(10,80)
testRA.append(sedRA)
testDec.append(sedDec)
raDec = np.array((sedRA, sedDec)).reshape((2,1))
ebvVal = ebv().calculateEbv(equatorialCoordinates = raDec)
extVal = ebvVal*extCoeffs
testMagsExt.append(galPhot.magListForSed(getSEDMags) + extVal)
#Setup magnitudes for testing matching to redshifted values
getRedshiftMags = Sed()
testZ = np.round(np.random.uniform(1.1,1.3),3)
testRedshifts.append(testZ)
testMagNorm = np.round(np.random.uniform(20.0,22.0),magNormStep)
testMagNormList.append(testMagNorm)
getRedshiftMags.setSED(wavelen = testSED.wavelen, flambda = testSED.flambda)
getRedshiftMags.redshiftSED(testZ)
fluxNorm = getRedshiftMags.calcFluxNorm(testMagNorm, imSimBand)
getRedshiftMags.multiplyFluxNorm(fluxNorm)
testMagsRedshift.append(galPhot.magListForSed(getRedshiftMags))
#Will also test in passing of non-default bandpass
testNoExtNoRedshift = testMatching.matchToObserved(testSEDList, testMags, np.zeros(20),
reddening = False,
bandpassDict = galPhot)
testMatchingEbvVals = testMatching.matchToObserved(testSEDList, testMagsExt, np.zeros(20),
catRA = testRA, catDec = testDec,
reddening = True, extCoeffs = extCoeffs,
bandpassDict = galPhot)
#Substitute in nan values to simulate incomplete data and make sure magnorm works too.
testMagsRedshift[0][1] = np.nan
testMagsRedshift[0][3] = np.nan
testMagsRedshift[0][4] = np.nan
testMagsRedshift[1][1] = np.nan
testMatchingRedshift = testMatching.matchToObserved(testSEDList, testMagsRedshift, testRedshifts,
dzAcc = 3, reddening = False,
bandpassDict = galPhot)
self.assertEqual(testSEDNames, testNoExtNoRedshift[0])
self.assertEqual(testSEDNames, testMatchingEbvVals[0])
self.assertEqual(None, testMatchingRedshift[0][0])
self.assertEqual(testSEDNames[1:], testMatchingRedshift[0][1:])
self.assertEqual(None, testMatchingRedshift[1][0])
np.testing.assert_almost_equal(testMagNormList[1:], testMatchingRedshift[1][1:],
decimal = magNormStep)
#Test Match Errors
errMag = testMagsRedshift[2]
errRedshift = testRedshifts[2]
errMags = np.array((errMag, errMag, errMag, errMag))
errRedshifts = np.array((errRedshift, errRedshift, errRedshift, errRedshift))
errMags[1,1] += 1. #Total MSE will be 2/(5 colors) = 0.4
errMags[2, 0:2] = np.nan
errMags[2, 3] += 1. #Total MSE will be 2/(3 colors) = 0.667
errMags[3, :] = None
errSED = testSEDList[2]
testMatchingResultsErrors = testMatching.matchToObserved([errSED], errMags, errRedshifts,
reddening = False,
bandpassDict = galPhot,
dzAcc = 3)
np.testing.assert_almost_equal(np.array((0.0, 0.4, 2./3.)), testMatchingResultsErrors[2][0:3],
decimal = 2) #Give a little more leeway due to redshifting effects
self.assertEqual(None, testMatchingResultsErrors[2][3])
def SNObjectSourceSED(self, time, wavelen=None):
"""
Return the rest Frame SED of SNObject at the phase corresponding to
time, at rest frame wavelengths wavelen. If wavelen is None,
then the SED is sampled at the rest frame wavelengths native to the
SALT model being used.
Parameters
----------
time : float, mandatory,
observer frame time at which the SED has been requested in units
of days.
wavelen : `np.ndarray`, optional, defaults to native SALT wavelengths
array of wavelengths in the rest frame of the supernova in units
of nm. If None, this defaults to the wavelengths at which the
SALT model is sampled natively.
Returns
-------
`numpy.ndarray` of dtype float.
.. note: The result should usually match the SALT source spectrum.
However, it may be different for the following reasons:
1. If the time of observation is outside the model range, the values
have to be inserted using additional models. Here only one model
is currently implemented, where outside the model range the value
is set to 0.
2. If the wavelengths are beyond the range of the SALT model, the SED
flambda values are set to `np.nan` and these are actually set to 0.
if `self.rectifySED = True`
3. If the `flambda` values of the SALT model are negative which happens
in the less sampled phases of the model, these values are set to 0,
if `self.rectifySED` = True. (Note: if `self.rectifySED` = True, then
care will be taken to make sure that the flux at 500nm is not exactly
zero, since that will cause PhoSim normalization of the SED to be
NaN).
"""
phase = (time - self.get('t0')) / (1. + self.get('z'))
source = self.source
# Set the default value of wavelength input
if wavelen is None:
# use native SALT grid in Ang
wavelen = source._wave
else:
#input wavelen in nm, convert to Ang
wavelen = wavelen.copy()
wavelen *= 10.0
flambda = np.zeros(len(wavelen))
# self.mintime() and self.maxtime() are properties describing
# the ranges of SNCosmo.Model in time. Behavior beyond this is
# determined by self.modelOutSideTemporalRange
insidephaseRange = (phase <= source.maxphase())and(phase >= source.minphase())
if insidephaseRange:
# If SNCosmo is requested a SED value beyond the wavelength range
# of model it will crash. Try to prevent that by returning np.nan for
# such wavelengths. This will still not help band flux calculations
# but helps us get past this stage.
flambda = flambda * np.nan
mask1 = wavelen >= source.minwave()
mask2 = wavelen <= source.maxwave()
mask = mask1 & mask2
# Where we have to calculate fluxes because it is not `np.nan`
wave = wavelen[mask]
flambda[mask] = source.flux(phase, wave)
else:
if self.modelOutSideTemporalRange == 'zero':
# flambda was initialized as np.zeros before start of
# conditional
pass
else:
raise NotImplementedError('Only modelOutSideTemporalRange=="zero" implemented')
# rectify the flux
if self.rectifySED:
flux = np.where(flambda>0., flambda, 0.)
else:
flux = flambda
# convert per Ang to per nm
flux *= 10.0
# convert ang to nm
wavelen = wavelen / 10.
# If there is zero flux at 500nm, set
# the flux in the slot closest to 500nm
# equal to 0.01*minimum_non_zero_flux
# (this is so SEDs used in PhoSim can have
# finite normalization)
if self.rectifySED:
closest_to_500nm = np.argmin(np.abs(wavelen-500.0))
if flux[closest_to_500nm] == 0.0:
non_zero_flux = np.where(flux>0.0)
if len(non_zero_flux[0])>0:
min_non_zero = np.min(flux[non_zero_flux])
flux[closest_to_500nm] = 0.01*min_non_zero
sed = Sed(wavelen=wavelen, flambda=flux)
# This has the cosmology built in.
return sed
def testFindSED(self):
"""Pull SEDs from each type and make sure that each SED gets matched to itself.
Includes testing with extinction and passing in only colors."""
np.random.seed(42)
starPhot = BandpassDict.loadTotalBandpassesFromFiles(('u','g','r','i','z'),
bandpassDir = os.path.join(lsst.utils.getPackageDir('throughputs'),'sdss'),
bandpassRoot = 'sdss_')
imSimBand = Bandpass()
imSimBand.imsimBandpass()
testMatching = selectStarSED(sEDDir = self.testSpecDir, kuruczDir = self.testKDir,
mltDir = self.testMLTDir, wdDir = self.testWDDir)
testSEDList = []
testSEDList.append(testMatching.loadKuruczSEDs())
testSEDList.append(testMatching.loadmltSEDs())
testSEDListH, testSEDListHE = testMatching.loadwdSEDs()
testSEDList.append(testSEDListH)
testSEDList.append(testSEDListHE)
testSEDNames = []
testMags = []
testMagNormList = []
magNormStep = 1
for typeList in testSEDList:
if len(typeList) != 0:
typeSEDNames = []
typeMags = []
typeMagNorms = []
for testSED in typeList:
getSEDMags = Sed()
typeSEDNames.append(testSED.name)
getSEDMags.setSED(wavelen = testSED.wavelen, flambda = testSED.flambda)
testMagNorm = np.round(np.random.uniform(20.0,22.0),magNormStep)
typeMagNorms.append(testMagNorm)
fluxNorm = getSEDMags.calcFluxNorm(testMagNorm, imSimBand)
getSEDMags.multiplyFluxNorm(fluxNorm)
typeMags.append(starPhot.magListForSed(getSEDMags))
testSEDNames.append(typeSEDNames)
testMags.append(typeMags)
testMagNormList.append(typeMagNorms)
fakeRA = np.ones(len(testSEDList[0]))
fakeDec = np.ones(len(testSEDList[0]))
#Since default bandpassDict should be SDSS ugrizy shouldn't need to specify it
#Substitute in nan values to simulate incomplete data.
for typeList, names, mags, magNorms in zip(testSEDList, testSEDNames, testMags, testMagNormList):
if len(typeList) > 2:
nanMags = np.array(mags)
nanMags[0][0] = np.nan
nanMags[0][2] = np.nan
nanMags[0][3] = np.nan
nanMags[1][1] = np.nan
testMatchingResults = testMatching.findSED(typeList, nanMags, reddening = False)
self.assertEqual(None, testMatchingResults[0][0])
self.assertEqual(names[1:], testMatchingResults[0][1:])
self.assertEqual(None, testMatchingResults[1][0])
np.testing.assert_almost_equal(magNorms[1:], testMatchingResults[1][1:],
decimal = magNormStep)
else:
testMatchingResults = testMatching.findSED(typeList, mags, reddening = False)
self.assertEqual(names, testMatchingResults[0])
np.testing.assert_almost_equal(magNorms, testMatchingResults[1], decimal = magNormStep)
#Test Null Values option
nullMags = np.array(testMags[0])
nullMags[0][0] = -99.
nullMags[0][4] = -99.
nullMags[1][0] = -99.
nullMags[1][1] = -99.
testMatchingResultsNull = testMatching.findSED(testSEDList[0], nullMags,
nullValues = -99., reddening = False)
self.assertEqual(testSEDNames[0], testMatchingResultsNull[0])
np.testing.assert_almost_equal(testMagNormList[0], testMatchingResultsNull[1],
decimal = magNormStep)
#Test Error Output
errMags = np.array((testMags[0][0], testMags[0][0], testMags[0][0], testMags[0][0]))
errMags[1,1] += 1. #Total MSE will be 2/(4 colors) = 0.5
errMags[2, 0:2] = np.nan
errMags[2, 3] += 1. #Total MSE will be 2/(2 colors) = 1.0
errMags[3, :] = None
errSED = testSEDList[0][0]
testMatchingResultsErrors = testMatching.findSED([errSED], errMags, reddening = False)
np.testing.assert_almost_equal(np.array((0.0, 0.5, 1.0)), testMatchingResultsErrors[2][0:3],
decimal = 3)
self.assertEqual(None, testMatchingResultsErrors[2][3])
#Now test what happens if we pass in a bandpassDict
testMatchingResultsNoDefault = testMatching.findSED(testSEDList[0], testMags[0],
bandpassDict = starPhot,
reddening = False)
self.assertEqual(testSEDNames[0], testMatchingResultsNoDefault[0])
np.testing.assert_almost_equal(testMagNormList[0], testMatchingResultsNoDefault[1],
decimal = magNormStep)
#Test Reddening
testRA = np.random.uniform(10,170,len(testSEDList[0]))
testDec = np.random.uniform(10,80,len(testSEDList[0]))
extFactor = .5
raDec = np.array((testRA, testDec))
ebvVals = ebv().calculateEbv(equatorialCoordinates = raDec)
extVals = ebvVals*extFactor
testRedMags = []
for extVal, testMagSet in zip(extVals, testMags[0]):
testRedMags.append(testMagSet + extVal)
testMatchingResultsRed = testMatching.findSED(testSEDList[0], testRedMags, catRA = testRA,
catDec = testDec, reddening = True,
extCoeffs = np.ones(5)*extFactor)
self.assertEqual(testSEDNames[0], testMatchingResultsRed[0])
np.testing.assert_almost_equal(testMagNormList[0], testMatchingResultsRed[1],
decimal = magNormStep)
#Finally, test color input
testColors = []
for testMagSet in testMags[0]:
testColorSet = []
for filtNum in range(0, len(starPhot)-1):
testColorSet.append(testMagSet[filtNum] - testMagSet[filtNum+1])
testColors.append(testColorSet)
testMatchingColorsInput = testMatching.findSED(testSEDList[0], testMags[0],
reddening = False, colors = testColors)
self.assertEqual(testSEDNames[0], testMatchingColorsInput[0])
np.testing.assert_almost_equal(testMagNormList[0], testMatchingColorsInput[1],
decimal = magNormStep)
