def compileSpectra(p):
"""
@brief compile the various auto/cross spectra
"""
patchDir = "patches"
labels = p['labels']
taper = p['taper']
gaussApod = p['gaussianApodization']
applyMask = p['applyMask']
nPatches = 0
l = os.listdir(patchDir)
for il in l:
if 'patch_%s_00'%labels[0] in il and '_season' in il[-7:]:
nPatches += 1
print "Found %d season patch(es) ..."%nPatches
if taper['apply'] and gaussApod['apply']:
raise ValueError, "Both taper and Gaussian Apodization cannot be applied."+\
"Use one or the other"
trimAtL = p['trimAtL']
specDir = 'spectra/'
try:
os.makedirs(specDir)
except:
pass
lU,lL,lCen = fftTools.readBinningFile(p['binningFile'])
ii = numpy.where(lU<p['trimAtL'])
#beam transfer ()
binnedBeamWindow = []
for label in labels:
Bb = speckMisc.getBinnedBeamTransfer(p['beamFile_%s'%label],p['binningFile'],trimAtL)
binnedBeamWindow += [Bb]
hpfDict = p['highPassCosSqFilter']
filter = 1.0
if hpfDict['apply']:
print "Will take off the cos^2 high pass filter"
filter = speckMisc.getBinnedInvCosSqFilter(hpfDict['lMin'],hpfDict['lMax'],p['binningFile'],trimAtL)
for iPatch in xrange(nPatches):
mbb = pickle.load(open('mcm/'+p['mcmFileRoot']+'_%03d.pkl'%iPatch,mode="r"))
mbbInv = scipy.linalg.inv(mbb)
if applyMask:
mask = liteMap.liteMapFromFits("%s/mask%03d"%(patchDir,iPatch))
else:
mask = None
pixW = None
if p['applyPixelWeights']:
pixW = (liteMap.liteMapFromFits("%s/totalWeightMap_%03d"%(patchDir,iPatch)))
binWeightMap = pickle.load(open('noiseAndWeights/weightMap%03d.pkl'%iPatch,mode="r"))
# Get the auto spectra first
ilabel = 0
for label in labels:
print "In patch: %03d, computing %sx%s season spectrum "%(iPatch,label,label)
m0 = liteMap.liteMapFromFits("%s/patch_%s_%03d_season" %(patchDir,label,iPatch))
area = m0.Nx*m0.Ny*m0.pixScaleX*m0.pixScaleY
p2d = get2DSpectrum(m0,m0,taper,gaussApod,mask=mask,pixelWeight=pixW)
lL,lU,lbin,clbin,binCount = weightedBinInAnnuli(p2d,\
binWeightMap.powerMap,\
p['binningFile'],p['trimAtL'],\
p['powerOfL'])
clbinDecoup = numpy.dot(mbbInv,clbin)*area*filter**2
# There is an additional correction for the autos as MCM had a transfer
# function B_l_AR1*B_l_AR_2
clbinDecoup *= binnedBeamWindow[ilabel-1]/binnedBeamWindow[ilabel]
inds = numpy.where(clbinDecoup < 0.0)[0]
clbinDecoup[inds] = 0.0
fName = "%s/clBinAutoSeason_%sX%s_%03d.dat"%(specDir,label,label,iPatch)
speckMisc.writeBinnedSpectrum(lbin,clbinDecoup,binCount,fName)
ilabel += 1
# Now do the cross- spectra
m0 = liteMap.liteMapFromFits("%s/patch_%s_%03d_season"\
%(patchDir,labels[0],iPatch))
area = m0.Nx*m0.Ny*m0.pixScaleX*m0.pixScaleY
m1 = liteMap.liteMapFromFits("%s/patch_%s_%03d_season"\
%(patchDir,labels[1],iPatch))
print "In patch: %03d, computing %sx%s season spectrum "%(iPatch,labels[0],labels[-1])
p2d = get2DSpectrum(m0,m1,taper,gaussApod,mask=mask,pixelWeight=pixW)
lL,lU,lbin,clbin,binCount = weightedBinInAnnuli(p2d,\
binWeightMap.powerMap,\
p['binningFile'],p['trimAtL'],\
p['powerOfL'])
clbinDecoup = numpy.dot(mbbInv,clbin)*area*filter**2
fName = "%s/clBinCrossSeason_%sX%s_%03d.dat"%(specDir,labels[0],labels[-1],iPatch)
speckMisc.writeBinnedSpectrum(lbin,clbinDecoup,binCount,fName)
return 0 #success
seasonPairs = []
for i in xrange(len(seasons)):
for j in xrange(len(seasons)):
if arrays[0] == arrays[-1] and i > j: continue
seasonPairs += [[seasons[i], seasons[j]]]
print arraysPair
print seasonPairs
binnedBeamDict = {}
for seas in seasons:
binnedBeamWindow = []
for ar in arraysPair:
Bb = speckMisc.getBinnedBeamTransfer(p['beam_%s_%s' % (ar, seas)],
p['binningFile'], trimAtL)
binnedBeamWindow += [Bb]
binnedBeamDict[seas] = binnedBeamWindow
mbbInvArray = {}
for sps in seasonPairs:
spTag = '%sx%s' % (sps[0], sps[1])
arrayTag = '%sx%s' % (arraysPair[0], arraysPair[1])
mbb = numpy.loadtxt('mcm/' + p['mcmFileRoot'] + '_%s_%s.dat' %
(arrayTag, spTag))
mbb_cos1 = numpy.loadtxt('mcm/' + p['mcmFileRoot'] +
'_cos1_%s_%s.dat' % (arrayTag, spTag))
mbb_sin1 = numpy.loadtxt('mcm/' + p['mcmFileRoot'] +
'_sin1_%s_%s.dat' % (arrayTag, spTag))
seasonPairs = []
for i in xrange(len(seasons)):
for j in xrange(len(seasons)):
if arrays[0] == arrays[-1] and i>j: continue
seasonPairs += [[seasons[i],seasons[j]]]
print arraysPair
print seasonPairs
binnedBeamDict = {}
for seas in seasons:
binnedBeamWindow = []
for ar in arraysPair:
Bb = speckMisc.getBinnedBeamTransfer(p['beam_%s_%s'%(ar,seas)],p['binningFile'],trimAtL)
binnedBeamWindow += [Bb]
binnedBeamDict[seas] = binnedBeamWindow
mbbInvArray={}
for sps in seasonPairs:
spTag = '%sx%s'%(sps[0],sps[1])
arrayTag = '%sx%s'%(arraysPair[0],arraysPair[1])
mbb = numpy.loadtxt('mcm/'+p['mcmFileRoot']+'_%s_%s.dat'%(arrayTag,spTag))
mbb_cos1 = numpy.loadtxt('mcm/'+p['mcmFileRoot']+'_cos1_%s_%s.dat'%(arrayTag,spTag))
mbb_sin1 = numpy.loadtxt('mcm/'+p['mcmFileRoot']+'_sin1_%s_%s.dat'%(arrayTag,spTag))
mbb_cos2 =numpy.loadtxt('mcm/'+p['mcmFileRoot']+'_cos2_%s_%s.dat'%(arrayTag,spTag))
mbb_sin2 = numpy.loadtxt('mcm/'+p['mcmFileRoot']+'_sin2_%s_%s.dat'%(arrayTag,spTag))
mbb_sincos = numpy.loadtxt('mcm/'+p['mcmFileRoot']+'_sincos_%s_%s.dat'%(arrayTag,spTag))
