def rewrite_mask_files(pskys=[40,60,70,80],
mask_sources=True,
apodization=2,
smask_name='HFI_Mask_PointSrc_2048_R2.00.fits'):
for psky in pskys:
maskfile = pf.PLANCK_DATA_PATH + 'mask_psky{}_apo{}.fits'.format(psky,apodization)
mask = pf.get_planck_mask(psky=psky,
mask_sources=mask_sources,
apodization=apodization,
smask_name=smask_name)
hp.write_map(maskfile, mask)
def rewrite_mask_files(pskys=[40, 60, 70, 80],
mask_sources=True,
apodization=2,
smask_name='HFI_Mask_PointSrc_2048_R2.00.fits'):
for psky in pskys:
maskfile = pf.PLANCK_DATA_PATH + 'mask_psky{}_apo{}.fits'.format(
psky, apodization)
mask = pf.get_planck_mask(psky=psky,
mask_sources=mask_sources,
apodization=apodization,
smask_name=smask_name)
hp.write_map(maskfile, mask)
def b_cov_T353_E143_B143(cl_file=pf.PLANCK_DATA_PATH+'bf_base_cmbonly_plikHMv18_TT_lowTEB_lmax4000.minimum.theory_cl',lmax=100):
Imap = hp.read_map(pf.PLANCK_DATA_PATH + 'HFI_SkyMap_353_2048_R2.02_full.fits')
Tlm = hp.map2alm(Imap,lmax=lmax)
cltt = hp.alm2cl(Tlm,lmax=lmax)
mask = pf.get_planck_mask(psky=70)
Qmap, Umap = hp.read_map(pf.PLANCK_DATA_PATH + 'HFI_SkyMap_143_2048_R2.02_full.fits',field=(1,2))
Elm, Blm = hp.map2alm_spin( (Qmap*mask,Umap*mask), 2, lmax=lmax )
clee = hp.alm2cl(Elm,lmax=lmax)
clbb = hp.alm2cl(Blm,lmax=lmax)
cov = calc_b_cov_TEB(cltt, clee, clbb)
return cov
def b_cov_TEB(lmax=100,frequency=353):
"""this one is map-based"""
Imap,Qmap, Umap = hp.read_map(pf.PLANCK_DATA_PATH + 'HFI_SkyMap_{}_2048_R2.02_full.fits'.format(frequency),field=(0,1,2))
mask = pf.get_planck_mask()
Tlm = hp.map2alm(Imap*mask,lmax=lmax)
cltt = hp.alm2cl(Tlm,lmax=lmax)
Elm, Blm = hp.map2alm_spin( (Qmap*mask,Umap*mask), 2, lmax=lmax )
clee = hp.alm2cl(Elm,lmax=lmax)
clbb = hp.alm2cl(Blm,lmax=lmax)
#hs = get_hs(lmax=100)
cov = calc_b_cov_TEB(cltt, clee, clbb)#/hs
return cov
from process_fullsky import simulate_observed_map, calc_alm, get_planck_mask
frequencies = [353] #[100,143,353,217]
filebase = sys.argv[1]
smear = True
mask_sources = True
nside = 2048
psky = 70
apodization = 2
lmax = 2000
lmax_bispectrum = 200
mask = get_planck_mask(psky=psky,
mask_sources=mask_sources,
apodization=apodization,
smask_name='HFI_Mask_PointSrc_2048_R2.00.fits')
#get the raw alms:
filename_cmb = FGS_SIM_PATH + 'alms/' + '{}_cmb_alm_lmax{}.npz'.format(
filebase, lmax)
filename_fg = FGS_SIM_PATH + 'alms/' + '{}_fg_alm_lmax{}.npz'.format(
filebase, lmax)
d = np.load(filename_cmb)
Tlm_cmb = d['Tlm']
Elm_cmb = d['Elm']
Blm_cmb = d['Blm']
alms_cmb = np.array([Tlm_cmb, Elm_cmb, Blm_cmb])
d = np.load(filename_fg)
from process_fullsky import PLANCK_DATA_PATH,calc_alm,get_planck_mask
import healpy as hp
frequencies = [353]#[100,143,353,217]
smear = True
mask_sources = True
nside=2048
psky = 70
apodization = 2
lmax_bispectrum = 199
mask = get_planck_mask(psky=psky,
mask_sources=mask_sources,
apodization=apodization,
smask_name='HFI_Mask_PointSrc_2048_R2.00.fits')
for f in frequencies:
outfilename = PLANCK_DATA_PATH + 'bispectrum_alms/' + 'data_planck_{}GHz_lmax{}'.format(f,lmax_bispectrum)
mapname = PLANCK_DATA_PATH + 'HFI_SkyMap_{}_2048_R2.02_full.fits'.format(f)
print 'reading map from file: {} ...'.format(mapname)
I,Q,U = hp.read_map(mapname, field=(0,1,2))
Tlm,Elm,Blm = calc_alm(I, Q, U, mask=mask,
lmax=lmax_bispectrum,add_beam=None,div_beam=None,
healpy_format=False)
np.save(outfilename + '_Tlm.npy', Tlm)
np.save(outfilename + '_Elm.npy', Elm)
np.save(outfilename + '_Blm.npy', Blm)
def calibrate_fsky(mode,
nsim=1,
smear=True,
apo=2,
psky=70,
f=353,
nside=2048,
lmax=1000,
visual_check=False,
beam_file=pf.PLANCK_DATA_PATH +
'HFI_RIMO_Beams-100pc_R2.00.fits',
mask_sources=True,
put_mask=True):
"""No noise treatment here"""
fsky_correction = []
TTm = np.zeros(lmax + 1)
EEm = np.zeros(lmax + 1)
BBm = np.zeros(lmax + 1)
if put_mask:
print 'reading mask...'
mask = pf.get_planck_mask(psky=psky,
mask_sources=mask_sources,
apodization=apo)
else:
mask = None
print 'reading beams...'
hdulist = pf.fits.open(beam_file)
beam = hdulist[pf.BEAM_INDEX['{}'.format(f)]].data.NOMINAL[0][:lmax + 1]
beamP = hdulist[pf.BEAM_INDEX['{}P'.format(f)]].data.NOMINAL[0][:lmax + 1]
beam = beam[:lmax + 1]
beamP = beamP[:lmax + 1]
if mode == 'fg':
ls, cls_theory = get_theory_fg(f=f, lmax=lmax, psky=psky, apo=apo)
if mode == 'cmb':
ls, cls_theor = pf.get_theory_cmb(lmax=lmax, mode='cl')
factor = ls * (1 + ls)
for i in np.arange(nsim):
print 'sim #{}...'.format(i + 1)
I, Q, U = pf.simulate_cmb_map(nside=nside,
lmax=lmax,
frequency=f,
smear=smear,
cls_theory=cls_theory,
beam=beam,
beamP=beamP,
save=False,
beam_file=None)
print 'Cl #{}...'.format(i + 1)
Tlm, Elm, Blm = pf.calc_alm(I,
Q,
U,
mask=mask,
lmax=lmax,
add_beam=None,
add_beamP=None,
div_beam=beam,
div_beamP=beamP,
healpy_format=True)
TT = hp.alm2cl(Tlm)
EE = hp.alm2cl(Elm)
BB = hp.alm2cl(Blm)
#ls, TT, EE, BB, TE, TB, EB = measure_dlcl(mask=mask, Imap=I, Qmap=Q, Umap=U,
# beam=beam, beamP=beamP,
# mode='cl',frequency=f,
# lmax=lmax,lmin=0,
# put_mask=put_mask,
# psky=psky,
# mask_sources=mask_sources,
# apodization=apo)
TTm += TT / nsim
EEm += EE / nsim
BBm += BB / nsim
if visual_check:
hp.mollview(I)
hp.mollview(Q)
hp.mollview(U)
fsky_correction.append(cls_theory[0] / TTm)
fsky_correction.append(cls_theory[1] / EEm)
fsky_correction.append(cls_theory[2] / BBm)
fsky_correction = np.array(fsky_correction)
fsky_correction[np.isnan(fsky_correction)] = 0.
fsky_correction[fsky_correction == np.inf] = 0.
return ls, fsky_correction, TTm, EEm, BBm, cls_theory
def measure_dlcl(mode='dl',
frequency=353,
mask=None,
lmax=600,
lmin=40,
put_mask=True,
psky=70,
mask_sources=True,
apodization=2,
beam=None,
beamP=None,
Imap=None,
Qmap=None,
Umap=None,
Imap2=None,
Qmap2=None,
Umap2=None,
fsky_correction=True):
"""
If mode=='dl', returns D quantity = Cl *ls*(ls+1)/2./np.pi*1e12 [units: uK_CMB^2]
"""
if put_mask:
if mask is None:
print 'reading masks...'
mask = pf.get_planck_mask(psky=psky,
mask_sources=mask_sources,
apodization=apodization)
else:
mask = map.copy() * 0. + 1.
if (beam is None) or (beamP is None):
print 'reading beams...'
beam_file = pf.PLANCK_DATA_PATH + 'HFI_RIMO_Beams-100pc_R2.00.fits'
hdulist = pf.fits.open(beam_file)
beam = hdulist[pf.BEAM_INDEX['{}'.format(
frequency)]].data.NOMINAL[0][:lmax + 1]
beamP = hdulist[pf.BEAM_INDEX['{}P'.format(
frequency)]].data.NOMINAL[0][:lmax + 1]
beam = beam[lmin:lmax + 1]
beamP = beamP[lmin:lmax + 1]
fsky = mask.sum() / len(mask)
ls = np.arange(lmin, lmax + 1)
if mode == 'dl':
factor = ls * (ls + 1) / (2. * np.pi) * 1e12 / fsky
if mode == 'cl':
factor = 1. / fsky
if fsky_correction:
fcfilename = pf.FGS_RESULTS_PATH + 'fskycorr_fg_psky{}_apo{}_lmax1000_TT_EE_BB.npy'.format(
psky, apodization)
if os.path.exists(fcfilename):
fcorr = np.load(fcfilename)
fcorr_TT = fcorr[0][lmin:lmax + 1]
fcorr_EE = fcorr[1][lmin:lmax + 1]
fcorr_BB = fcorr[2][lmin:lmax + 1]
else:
fcorr = None
else:
fcorr = None
if (Imap is None) or (Qmap is None) or (Umap is None):
print 'reading maps...'
mapname1 = pf.PLANCK_DATA_PATH + 'HFI_SkyMap_{}_2048_R2.02_halfmission-1.fits'.format(
frequency)
mapname2 = pf.PLANCK_DATA_PATH + 'HFI_SkyMap_{}_2048_R2.02_halfmission-2.fits'.format(
frequency)
Imap = hp.read_map(mapname1, field=0)
Imap2 = hp.read_map(mapname2, field=0)
Qmap, Umap = hp.read_map(mapname1, field=(1, 2))
Qmap2, Umap2 = hp.read_map(mapname2, field=(1, 2))
Tlm1 = hp.map2alm(Imap * mask, lmax=lmax)
Elm1, Blm1 = hp.map2alm_spin((Qmap * mask, Umap * mask), 2, lmax=lmax)
if (Imap2 is None) or (Qmap2 is None) or (Umap2 is None):
Tlm2 = Tlm1
Elm2 = Elm1
Blm2 = Blm1
else:
Tlm2 = hp.map2alm(Imap2 * mask, lmax=lmax)
Elm2, Blm2 = hp.map2alm_spin((Qmap2 * mask, Umap2 * mask),
2,
lmax=lmax)
TT = hp.alm2cl(Tlm1, Tlm2)
EE = hp.alm2cl(Elm1, Elm2)
BB = hp.alm2cl(Blm1, Blm2)
EE = EE[lmin:] * factor / beamP**2
TT = TT[lmin:] * factor / beam**2
BB = BB[lmin:] * factor / beamP**2
TE = hp.alm2cl(Tlm1, Elm2)
EB = hp.alm2cl(Blm1, Elm2)
TB = hp.alm2cl(Blm1, Tlm2)
TE = TE[lmin:] * factor / beam / beamP
TB = TB[lmin:] * factor / beam / beamP
EB = EB[lmin:] * factor / beamP**2
if fcorr is not None:
TT *= fcorr_TT
EE *= fcorr_EE
BB *= fcorr_BB
return ls, TT, EE, BB, TE, TB, EB
def calibrate_fsky(mode, nsim=1,
smear=True,apo=2,
psky=70, f=353,
nside=2048,lmax=1000,
visual_check=False,
beam_file=pf.PLANCK_DATA_PATH+'HFI_RIMO_Beams-100pc_R2.00.fits',
mask_sources=True, put_mask=True):
"""No noise treatment here"""
fsky_correction = []
TTm = np.zeros(lmax + 1)
EEm = np.zeros(lmax + 1)
BBm = np.zeros(lmax + 1)
if put_mask:
print 'reading mask...'
mask = pf.get_planck_mask(psky=psky,
mask_sources=mask_sources,
apodization=apo)
else:
mask = None
print 'reading beams...'
hdulist = pf.fits.open(beam_file)
beam = hdulist[pf.BEAM_INDEX['{}'.format(f)]].data.NOMINAL[0][:lmax+1]
beamP = hdulist[pf.BEAM_INDEX['{}P'.format(f)]].data.NOMINAL[0][:lmax+1]
beam = beam[:lmax+1]
beamP = beamP[:lmax+1]
if mode == 'fg':
ls, cls_theory = get_theory_fg(f=f, lmax=lmax, psky=psky, apo=apo)
if mode == 'cmb':
ls, cls_theor = pf.get_theory_cmb(lmax=lmax, mode='cl')
factor = ls*(1+ls)
for i in np.arange(nsim):
print 'sim #{}...'.format(i+1)
I, Q, U = pf.simulate_cmb_map(nside=nside, lmax=lmax,
frequency=f,smear=smear,
cls_theory=cls_theory,
beam=beam, beamP=beamP,
save=False,
beam_file=None)
print 'Cl #{}...'.format(i+1)
Tlm, Elm, Blm = pf.calc_alm(I, Q, U, mask=mask,
lmax=lmax,
add_beam=None,add_beamP=None,
div_beam=beam,div_beamP=beamP,
healpy_format=True)
TT = hp.alm2cl(Tlm)
EE = hp.alm2cl(Elm)
BB = hp.alm2cl(Blm)
#ls, TT, EE, BB, TE, TB, EB = measure_dlcl(mask=mask, Imap=I, Qmap=Q, Umap=U,
# beam=beam, beamP=beamP,
# mode='cl',frequency=f,
# lmax=lmax,lmin=0,
# put_mask=put_mask,
# psky=psky,
# mask_sources=mask_sources,
# apodization=apo)
TTm += TT/nsim; EEm += EE/nsim; BBm += BB/nsim
if visual_check:
hp.mollview(I)
hp.mollview(Q)
hp.mollview(U)
fsky_correction.append(cls_theory[0] / TTm)
fsky_correction.append(cls_theory[1] / EEm)
fsky_correction.append(cls_theory[2] / BBm)
fsky_correction = np.array(fsky_correction)
fsky_correction[np.isnan(fsky_correction)] = 0.
fsky_correction[fsky_correction==np.inf] = 0.
return ls, fsky_correction, TTm, EEm, BBm, cls_theory
def measure_dlcl(mode='dl',frequency=353,
mask=None,
lmax=600,lmin=40,
put_mask=True,
psky=70,
mask_sources=True,
apodization=2,
beam=None,beamP=None,
Imap=None,Qmap=None,Umap=None,
Imap2=None,Qmap2=None,Umap2=None,
fsky_correction=True):
"""
If mode=='dl', returns D quantity = Cl *ls*(ls+1)/2./np.pi*1e12 [units: uK_CMB^2]
"""
if put_mask:
if mask is None:
print 'reading masks...'
mask = pf.get_planck_mask(psky=psky,
mask_sources=mask_sources,
apodization=apodization)
else:
mask = map.copy()*0. + 1.
if (beam is None) or (beamP is None):
print 'reading beams...'
beam_file = pf.PLANCK_DATA_PATH+'HFI_RIMO_Beams-100pc_R2.00.fits'
hdulist = pf.fits.open(beam_file)
beam = hdulist[pf.BEAM_INDEX['{}'.format(frequency)]].data.NOMINAL[0][:lmax+1]
beamP = hdulist[pf.BEAM_INDEX['{}P'.format(frequency)]].data.NOMINAL[0][:lmax+1]
beam = beam[lmin:lmax+1]
beamP = beamP[lmin:lmax+1]
fsky = mask.sum() / len(mask)
ls = np.arange(lmin, lmax+1)
if mode == 'dl':
factor = ls * (ls+1) / (2.*np.pi) * 1e12 / fsky
if mode == 'cl':
factor = 1. / fsky
if fsky_correction:
fcfilename = pf.FGS_RESULTS_PATH + 'fskycorr_fg_psky{}_apo{}_lmax1000_TT_EE_BB.npy'.format(psky,apodization)
if os.path.exists(fcfilename):
fcorr = np.load(fcfilename)
fcorr_TT = fcorr[0][lmin:lmax+1]
fcorr_EE = fcorr[1][lmin:lmax+1]
fcorr_BB = fcorr[2][lmin:lmax+1]
else:
fcorr = None
else:
fcorr = None
if (Imap is None) or (Qmap is None) or (Umap is None):
print 'reading maps...'
mapname1 = pf.PLANCK_DATA_PATH + 'HFI_SkyMap_{}_2048_R2.02_halfmission-1.fits'.format(frequency)
mapname2 = pf.PLANCK_DATA_PATH + 'HFI_SkyMap_{}_2048_R2.02_halfmission-2.fits'.format(frequency)
Imap = hp.read_map(mapname1,field=0)
Imap2 = hp.read_map(mapname2,field=0)
Qmap, Umap = hp.read_map(mapname1,field=(1,2))
Qmap2, Umap2 = hp.read_map(mapname2,field=(1,2))
Tlm1 = hp.map2alm(Imap*mask, lmax=lmax)
Elm1, Blm1 = hp.map2alm_spin( (Qmap*mask, Umap*mask), 2, lmax=lmax )
if (Imap2 is None) or (Qmap2 is None) or (Umap2 is None):
Tlm2 = Tlm1
Elm2 = Elm1
Blm2 = Blm1
else:
Tlm2 = hp.map2alm(Imap2*mask, lmax=lmax)
Elm2, Blm2 = hp.map2alm_spin( (Qmap2*mask,Umap2*mask), 2, lmax=lmax )
TT = hp.alm2cl(Tlm1, Tlm2)
EE = hp.alm2cl(Elm1, Elm2)
BB = hp.alm2cl(Blm1, Blm2)
EE = EE[lmin:] * factor / beamP**2
TT = TT[lmin:] * factor / beam**2
BB = BB[lmin:] * factor / beamP**2
TE = hp.alm2cl(Tlm1, Elm2)
EB = hp.alm2cl(Blm1, Elm2)
TB = hp.alm2cl(Blm1, Tlm2)
TE = TE[lmin:] * factor / beam / beamP
TB = TB[lmin:] * factor / beam / beamP
EB = EB[lmin:] * factor / beamP**2
if fcorr is not None:
TT *= fcorr_TT
EE *= fcorr_EE
BB *= fcorr_BB
return ls, TT, EE, BB, TE, TB, EB
