def allpowersTEB(mapT, mapE, mapB, binFile = None):
fT = fftTools.fftFromLiteMap(mapT)
fE = fftTools.fftFromLiteMap(mapE)
fB = fftTools.fftFromLiteMap(mapB)
#for now no cross spectra in this routine, can be addded if necessary.
TT_power,TE_power,ET_power,TB_power,BT_power,EE_power,EB_power,BE_power,BB_power=fftPol.fourierTEBtoPowerTEB(fT,fE,fB,fT.copy(),fE.copy(), fB.copy())
l_Lo,l_Up,lbin,cl_TT,j,k = statsTools.aveBinInAnnuli(TT_power, binFile)#, './binningTest')
l_Lo,l_Up,lbin,cl_TE,j,k = statsTools.aveBinInAnnuli(TE_power, binFile)#, './binningTest')
l_Lo,l_Up,lbin,cl_TB,j,k = statsTools.aveBinInAnnuli(TB_power, binFile)#, './binningTest')
l_Lo,l_Up,lbin,cl_EE,j,k = statsTools.aveBinInAnnuli(EE_power, binFile)#, './binningTest')
l_Lo,l_Up,lbin,cl_EB,j,k = statsTools.aveBinInAnnuli(EB_power, binFile)#, './binningTest')
l_Lo,l_Up,lbin,cl_BB,j,k = statsTools.aveBinInAnnuli(BB_power, binFile)#, './binningTest')
#this will be what we leave in after the unblinding......
print 'got here e'
output = {'lbin':lbin, \
'cl_TT':cl_TT, \
'cl_TE':cl_TE, \
'cl_EE':cl_EE, \
'cl_EB':cl_EB, \
'cl_BB':cl_BB}
return output
def quickPower(inmap,
inmap2=None,
window=None,
useFlipperRoutine=False,
applySlepianTaper=False,
nanToNum=True,
binFile=None):
if binFile == None:
binFileToUse = 'binningTest'
else:
binFileToUse = binFile
temp = inmap.copy()
if inmap2 == None:
temp2 = inmap.copy()
else:
temp2 = inmap2.copy()
if window != None:
temp.data *= window.data / sqrt(numpy.mean(window.data**2))
temp2.data *= window.data / sqrt(numpy.mean(window.data**2))
# print "correcting for window"
if nanToNum:
temp.data = numpy.nan_to_num(temp.data)
temp2.data = numpy.nan_to_num(temp2.data)
power2D = fftTools.powerFromLiteMap(temp,
liteMap2=temp2,
applySlepianTaper=applySlepianTaper)
if useFlipperRoutine:
llower, lupper, lbin, clbin_0, clbin_N, binweight = power2D.binInAnnuli(
binFileToUse, nearestIntegerBinning=True)
else:
llower, lupper, lbin, clbin_0, clbin_N, binweight = statsTools.aveBinInAnnuli(
power2D, binFileToUse)
output = {
'lbin': lbin,
'clbin': clbin_0,
'dlbin': lbin * (lbin + 1) * clbin_0 / 2 / numpy.pi
}
# return (lbin, clbin_0)
return output
def allpowers(T_map, Q_map, U_map, T_map2 = None, Q_map2 = None, U_map2 = None , \
window = None, beamFile = None, flipQ = False, \
method = 'pure', binFile = None) :
T_map_local = T_map.copy()
Q_map_local = Q_map.copy()
U_map_local = U_map.copy()
T_map_local.data = numpy.nan_to_num(T_map_local.data)
Q_map_local.data = numpy.nan_to_num(Q_map_local.data)
U_map_local.data = numpy.nan_to_num(U_map_local.data)
if T_map2 != None:
T_map2_local = T_map2.copy()
Q_map2_local = Q_map2.copy()
U_map2_local = U_map2.copy()
else:
T_map2_local = T_map.copy()
Q_map2_local = Q_map.copy()
U_map2_local = U_map.copy()
T_map2_local.data = numpy.nan_to_num(T_map2_local.data)
Q_map2_local.data = numpy.nan_to_num(Q_map2_local.data)
U_map2_local.data = numpy.nan_to_num(U_map2_local.data)
print 'got here'
if flipQ:
print 'note: flipping sign of Q map'
Q_map_local.data *= -1.
if window != None:
T_map_local.data *= window.data / sqrt(numpy.mean(window.data**2))
Q_map_local.data *= 1 / sqrt(numpy.mean(window.data**2))
U_map_local.data *= 1 / sqrt(numpy.mean(window.data**2))
T_map2_local.data *= window.data / sqrt(numpy.mean(window.data**2))
Q_map2_local.data *= 1 / sqrt(numpy.mean(window.data**2))
U_map2_local.data *= 1 / sqrt(numpy.mean(window.data**2))
else:
window = T_map.copy()
window.data[:] = 1.
modLMap, angLMap = fftPol.makeEllandAngCoordinate(T_map_local,
bufferFactor=1)
print 'got here a'
fT, fE, fB = fftPol.TQUtoPureTEB(T_map_local,
Q_map_local,
U_map_local,
window,
modLMap,
angLMap,
method=method)
print 'got here b'
fT2, fE2, fB2 = fftPol.TQUtoPureTEB(T_map2_local,
Q_map2_local,
U_map2_local,
window,
modLMap,
angLMap,
method=method)
if beamFile != None:
beamdata = numpy.loadtxt(beamFile)
ell, f_ell = numpy.transpose(beamdata)[0:2, :]
t = mapTools.makeTemplate(ell, f_ell, fT)
fT.kMap /= t
fE.kMap /= t
fB.kMap /= t
fT2.kMap /= t
fE2.kMap /= t
fB2.kMap /= t
# print 'got here'
# pdb.set_trace()
print 'got here c'
TT_power, TE_power, ET_power, TB_power, BT_power, EE_power, EB_power, BE_power, BB_power = fftPol.fourierTEBtoPowerTEB(
fT, fE, fB, fT2, fE2, fB2)
print 'got here d'
l_Lo, l_Up, lbin, cl_TT, j, k = statsTools.aveBinInAnnuli(
TT_power, binFile) #, './binningTest')
l_Lo, l_Up, lbin, cl_TE, j, k = statsTools.aveBinInAnnuli(
TE_power, binFile) #, './binningTest')
l_Lo, l_Up, lbin, cl_TB, j, k = statsTools.aveBinInAnnuli(
TB_power, binFile) #, './binningTest')
l_Lo, l_Up, lbin, cl_EE, j, k = statsTools.aveBinInAnnuli(
EE_power, binFile) #, './binningTest')
l_Lo, l_Up, lbin, cl_EB, j, k = statsTools.aveBinInAnnuli(
EB_power, binFile) #, './binningTest')
l_Lo, l_Up, lbin, cl_BB, j, k = statsTools.aveBinInAnnuli(
BB_power, binFile) #, './binningTest')
#this will be what we leave in after the unblinding......
print 'got here e'
output = {'lbin':lbin, \
'cl_TT':cl_TT, \
'cl_TE':cl_TE, \
'cl_EE':cl_EE, \
'cl_EB':cl_EB, \
'cl_BB':cl_BB}
# output = {'lbin':lbin, \
# 'cl_TT':cl_TT, \
# 'cl_TE':cl_TE, \
# 'cl_EE':cl_EE}
return output