def findSED(self,
sedList,
catMags,
catRA=None,
catDec=None,
mag_error=None,
reddening=True,
bandpassDict=None,
colors=None,
extCoeffs=(4.239, 3.303, 2.285, 1.698, 1.263),
makeCopy=False):
"""
This will find the SEDs that are the closest match to the magnitudes of a star catalog.
It can also correct for reddening from within the milky way. 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 loaders in rgStar
in rgUtils.py 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] 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 length as objectMags.
@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] 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] colors is None if you are just providing a list of SED objects to match, but is the
array holding the colors of those SED models (each row should be the colors for one model in the
same order as sedList) if you have already calculated the colors.
@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 [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] 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.
"""
if bandpassDict is None:
starPhot = BandpassDict.loadTotalBandpassesFromFiles(
['u', 'g', 'r', 'i', 'z'],
bandpassDir=os.path.join(
lsst.utils.getPackageDir('throughputs'), 'sdss'),
bandpassRoot='sdss_')
else:
starPhot = bandpassDict
if colors is None:
modelColors = self.calcBasicColors(sedList,
starPhot,
makeCopy=makeCopy)
else:
modelColors = colors
#Transpose so that all values for one color are in one row as needed for the matching loop below
modelColors = np.transpose(modelColors)
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
objMags = np.array(objMags)
matchColors = []
for filtNum in range(0, len(starPhot) - 1):
matchColors.append(
np.transpose(objMags)[filtNum] -
np.transpose(objMags)[filtNum + 1])
matchColors = np.transpose(matchColors)
numCatMags = len(catMags)
numOn = 0
sedMatches = []
magNormMatches = []
notMatched = 0
matchErrors = []
for catObject in matchColors:
#This is done to handle objects with incomplete magnitude data
colorRange = np.arange(0, len(starPhot) - 1)
filtNums = np.arange(0, len(starPhot))
if np.isnan(np.amin(catObject)) == True:
colorRange = np.where(np.isnan(catObject) == 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.' % (
numOn)
notMatched += 1
sedMatches.append(None)
magNormMatches.append(None)
matchErrors.append(None)
else:
distanceArray = np.zeros(len(sedList))
for colorNum in colorRange:
distanceArray += np.power(
(modelColors[colorNum] - catObject[colorNum]), 2)
matchedSEDNum = np.nanargmin(distanceArray)
sedMatches.append(sedList[matchedSEDNum].name)
magNorm = self.calcMagNorm(objMags[numOn],
sedList[matchedSEDNum],
starPhot,
filtRange=filtNums)
magNormMatches.append(magNorm)
matchErrors.append(distanceArray[matchedSEDNum] /
len(colorRange)) #Mean Squared Error
numOn += 1
if numOn % 10000 == 0:
print 'Matched %i of %i catalog objects to SEDs' % (
numOn - notMatched, numCatMags)
if numCatMags > 1:
print 'Done Matching. Matched %i of %i catalog objects to SEDs' % (
numCatMags - notMatched, numCatMags)
if notMatched > 0:
print '%i objects did not get matched' % (notMatched)
return sedMatches, magNormMatches, matchErrors
def findSED(
self,
sedList,
catMags,
catRA=None,
catDec=None,
mag_error=None,
reddening=True,
bandpassDict=None,
colors=None,
extCoeffs=(4.239, 3.303, 2.285, 1.698, 1.263),
makeCopy=False,
):
"""
This will find the SEDs that are the closest match to the magnitudes of a star catalog.
It can also correct for reddening from within the milky way. 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 loaders in rgStar
in rgUtils.py 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] 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 length as objectMags.
@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] 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] colors is None if you are just providing a list of SED objects to match, but is the
array holding the colors of those SED models (each row should be the colors for one model in the
same order as sedList) if you have already calculated the colors.
@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 [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] 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.
"""
if bandpassDict is None:
starPhot = BandpassDict.loadTotalBandpassesFromFiles(
["u", "g", "r", "i", "z"],
bandpassDir=os.path.join(lsst.utils.getPackageDir("throughputs"), "sdss"),
bandpassRoot="sdss_",
)
else:
starPhot = bandpassDict
if colors is None:
modelColors = self.calcBasicColors(sedList, starPhot, makeCopy=makeCopy)
else:
modelColors = colors
# Transpose so that all values for one color are in one row as needed for the matching loop below
modelColors = np.transpose(modelColors)
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
objMags = np.array(objMags)
matchColors = []
for filtNum in range(0, len(starPhot) - 1):
matchColors.append(np.transpose(objMags)[filtNum] - np.transpose(objMags)[filtNum + 1])
matchColors = np.transpose(matchColors)
numCatMags = len(catMags)
numOn = 0
sedMatches = []
magNormMatches = []
notMatched = 0
matchErrors = []
for catObject in matchColors:
# This is done to handle objects with incomplete magnitude data
colorRange = np.arange(0, len(starPhot) - 1)
filtNums = np.arange(0, len(starPhot))
if np.isnan(np.amin(catObject)) == True:
colorRange = np.where(np.isnan(catObject) == 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." % (numOn)
notMatched += 1
sedMatches.append(None)
magNormMatches.append(None)
matchErrors.append(None)
else:
distanceArray = np.zeros(len(sedList))
for colorNum in colorRange:
distanceArray += np.power((modelColors[colorNum] - catObject[colorNum]), 2)
matchedSEDNum = np.nanargmin(distanceArray)
sedMatches.append(sedList[matchedSEDNum].name)
magNorm = self.calcMagNorm(objMags[numOn], sedList[matchedSEDNum], starPhot, filtRange=filtNums)
magNormMatches.append(magNorm)
matchErrors.append(distanceArray[matchedSEDNum] / len(colorRange)) # Mean Squared Error
numOn += 1
if numOn % 10000 == 0:
print "Matched %i of %i catalog objects to SEDs" % (numOn - notMatched, numCatMags)
if numCatMags > 1:
print "Done Matching. Matched %i of %i catalog objects to SEDs" % (numCatMags - notMatched, numCatMags)
if notMatched > 0:
print "%i objects did not get matched" % (notMatched)
return sedMatches, magNormMatches, matchErrors
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 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 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 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)
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 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
