def quad_filter(fcinv, fdiag, lmax, lcl, **kwargs):
# CMB filtering
fl = prjlib.loadocl(fcinv['o'], **kwargs)
ol = prjlib.loadocl(fdiag['o'], **kwargs)
xl = prjlib.loadocl(fcinv['x'], **kwargs)
alp = np.zeros((3, lmax + 1))
ocl = np.zeros((4, lmax + 1))
ifl = np.zeros((3, lmax + 1))
alp[1:3, 2:] = xl[1:3, 2:] / lcl[1:3, 2:]
ocl[0, :] = ol[0, :]
ocl[1:3, 2:] = fl[1:3, 2:] / alp[1:3, 2:]**2
ocl[3, :] = ol[3, :]
ifl[0, :] = lcl[0, :]
ifl[1:3, 2:] = fl[1:3, 2:] / alp[1:3, 2:]
return ocl, ifl
np.concatenate((pquad.eL[None, :], np.mean(cl[1:, :, :], axis=0),
np.std(cl[1:, :, :], axis=0))).T)
p, f, r = prjlib.init()
ps, fs, _ = prjlib.init(stype='lcmb', dodust='False')
#//// Reconstruction ////#
ow = False
#ow = True
snmax = p.snmax
if p.stype not in ['lcmb', 'dust']: snmax = 100
if p.stype in ['absrot', 'relrot', 'dust']:
rdn0 = False
ocl = prjlib.loadocl(fs.scl)
quad_func.quad.diagcinv(ps.quad, ocl)
quad_func.quad.diagcinv(p.quad, ocl)
quad_func.quad.qrec(ps.quad,
p.snmin,
snmax,
f.alm,
r.lcl,
qout=p.quad,
overwrite=ow)
if p.stype == 'dust':
rdn0 = True
quad_func.quad.rdn0(ps.quad,
p.snmin,
p.snmax,
f.alm,
import prjlib
import quad_func
import binning as bins
p, f, r = prjlib.init(loadw=False)
p0, f0 = prjlib.filename_init(PSA='s14&15_deep56',
doreal='True',
dearot='True')
p1, f1 = prjlib.filename_init(PSA='s14&15_boss', doreal='True')
px, fx = prjlib.filename_init(PSA='s14&15_cross', doreal='True')
__, __, w1, __ = prjlib.window(f0)
__, __, w2, __ = prjlib.window(f1)
r.w4 = np.sqrt(w1 * w2)
#//// bias terms ////#
oc0 = prjlib.loadocl(f0.scl)
oc1 = prjlib.loadocl(f1.scl)
quad_func.quad.diagcinv(p0.quad, oc0)
quad_func.quad.diagcinv(p1.quad, oc1)
#quad_func.n0x(px.quad,p0.quad,p1.quad,f0.alm,f1.alm,r.w4,r.lcl)
#quad_func.rdn0x(px.quad,p0.quad,p1.quad,0,1,f0.alm,f1.alm,r.w4,r.lcl)
#//// Power spectrum ////#
oLmax = p.quad.oLmax
bn = p.quad.bn
binspc = p.quad.binspc
for q in p.quad.qlist:
cl = np.zeros((p.snmax - p.snmin + 1, 1, oLmax + 1))
def interface(freqs,kwargs_ov={},kwargs_cmb={},run=['map2alm','combfreq','wiener_iso','wiener_diag']):
telescope = kwargs_cmb['t']
snmin = kwargs_cmb['snmin']
snmax = kwargs_cmb['snmax']
ntype = kwargs_cmb['ntype']
if 'hitmap' in run:
output_hitmap(**kwargs_ov)
if 'simmap' in run:
if telescope in ['la','sa']:
for freq in freqs:
# signal sim
sobj = sim_map(telescope=telescope,freq=freq,snmin=snmin,snmax=snmax,ntype='',**kwargs_ov)
sim_map.SOsim(sobj)
# noise sim
sobj = sim_map(telescope=telescope,freq=freq,snmin=snmin,snmax=snmax,ntype=ntype,**kwargs_ov)
sim_map.SOsim(sobj)
if 'calcalm' in run: # map -> alm for each freq (and com) and telescope
if '_iso' in ntype:
# compute alms for isotropic noise
# need pre-computed frequency-coadded spectrum
if kwargs_cmb['fltr'] != 'none':
sys.exit('isotropic noise calculation is only valid for none-filtered case')
if telescope in ['la','co']:
# for isotropic noise spectrum and diagonal wiener filtering
pc = prjlib.analysis_init(t=telescope,freq='com',snmin=snmin,snmax=snmax,ntype=ntype.replace('_iso',''))
ncl = prjlib.loadocl(pc.fcmb.scl['n'],lTmin=pc.lTmin,lTmax=pc.lTmax)
# setup filenames for input and output
inp = prjlib.analysis_init(t='id',ntype='cv',snmin=snmin,snmax=snmax) # to use fullsky signal
out = prjlib.analysis_init(t=telescope,freq='com',fltr='none',snmin=snmin,snmax=snmax,ntype=ntype)
# alm and aps
iso_noise(pc.rlz,pc.roll,pc.lmax,inp.fcmb.alms['o'],out.fcmb.alms['o'],ncl[0:3,:],**kwargs_ov)
aps(pc.rlz,pc.lmax,out.fcmb,1.,stype=['o'],**kwargs_ov)
else:
if kwargs_cmb['fltr'] == 'none':
if telescope == 'co':
sys.exit('does not support none filter case for LA+SA')
if telescope == 'id': # map -> alm for fullsky case
stype = ['o']
ntype = 'cv'
freqs = ['145']
else:
stype = ['s','n','o']
# load survey window
w, wn = prjlib.window(telescope,ascale=kwargs_cmb['ascale'])
# map -> alm for each freq
for freq in freqs:
p = prjlib.analysis_init(t=telescope,freq=freq,snmin=snmin,snmax=snmax,ntype=ntype) # define parameters, filenames
map2alm(p.telescope,p.rlz,freq,p.nside,p.lmax,p.fcmb,w,roll=p.roll,**kwargs_ov) # map -> alm
aps(p.rlz,p.lmax,p.fcmb,wn[2],stype=stype,**kwargs_ov)
# combine alm over freqs
if telescope in ['la','sa']:
p = prjlib.analysis_init(t=telescope,freq='com',snmin=snmin,snmax=snmax,ntype=ntype)
fmap = prjlib.filename_freqs(freqs,t=telescope,ntype=ntype)
alm_comb_freq(p.rlz,fmap,p.fcmb,roll=p.roll,**kwargs_ov)
aps(p.rlz,p.lmax,p.fcmb,wn[2],**kwargs_ov)
elif kwargs_cmb['fltr'] == 'cinv': # full wiener filtering
if telescope == 'sa':
sys.exit('does not support cinv filter case for SA')
pw = prjlib.analysis_init(t=telescope,freq='com',fltr='cinv',snmin=snmin,snmax=snmax,ntype=ntype)
pI = prjlib.analysis_init(t='id',ntype='cv',snmin=snmin,snmax=snmax) # for cross
wn = prjlib.wfac(telescope,binary=True)
if telescope == 'la':
mtypes = ['T','E','B']
# filenames
fmap = prjlib.filename_freqs(freqs,t=telescope,ntype=ntype)
# Temperature
cinv_params = {\
'chn' : 7, \
'eps' : [1e-4,.1,.1,.1,.1,.1,0.], \
'lmaxs' : [4096,2048,2048,1024,512,256,20], \
'nsides' : [2048,2048,1024,512,256,128,64], \
'itns' : [100,5,5,5,5,5,0], \
'ro' : 1, \
'filter' : 'W' \
}
cinv(1,pw.rlz,telescope,4096,ntype,fmap,pw.fcmb.alms['o'],pw.lcl,freqs=freqs,**cinv_params,**kwargs_ov)
# Polarization
cinv_params = {\
'chn' : 6, \
'eps' : [1e-5,.1,.1,.1,.1,0.], \
'lmaxs' : [4096,2048,1024,512,256,20], \
'nsides' : [2048,1024,512,256,128,64], \
'itns' : [100,7,5,3,3,0], \
'ro' : 1, \
'filter' : 'W' \
}
cinv(2,pw.rlz,telescope,4096,ntype,fmap,pw.fcmb.alms['o'],pw.lcl,freqs=freqs,**cinv_params,**kwargs_ov)
if telescope == 'co':
mtypes = ['E','B']
cinv_params = {\
'chn' : 6, \
'eps' : [1e-5,.1,.1,.1,.1,0.], \
'lmaxs' : [2048,1000,400,200,100,20], \
'nsides0' : [1024,512,256,128,128,64], \
'nsides1' : [512,256,256,128,64,64], \
'itns' : [200,9,3,3,7,0], \
'ro' : 1, \
'reducmn' : 2, \
'filter' : 'W' \
}
cinv_params = {\
'chn' : 1, \
'eps' : [1e-5], \
'lmaxs' : [2048], \
'nsides0' : [1024], \
'nsides1' : [512], \
'itns' : [1000], \
'ro' : 1, \
'reducmn' : 0, \
'filter' : 'W' \
}
fmapla = prjlib.filename_freqs(freqs,t='la',ntype=ntype)
fmapsa = prjlib.filename_freqs(freqs,t='sa',ntype=ntype)
cinv(2,pw.rlz,telescope,2048,ntype,fmapla,pw.fcmb.alms['o'],pw.lcl,freqs=freqs,fmapsa=fmapsa,**cinv_params,**kwargs_ov)
# aps
aps(pw.rlz,pw.lmax,pw.fcmb,wn[0],stype=['o'],mtype=mtypes,**kwargs_ov)
apsx(pw.rlz,pw.lmax,pw.fcmb,pI.fcmb,wn[0],mtype=mtypes,**kwargs_ov)
def interface(run=[], kwargs_ov={}, kwargs_cmb={}, kwargs_qrec={}, ep=1e-30):
if kwargs_cmb['t'] != 'la':
sys.exit('only la is supported')
# Define parameters, filenames for input CMB
p = prjlib.analysis_init(**kwargs_cmb)
# Load pre-computed w-factor which is used for correction normalization of spectrum
wn = prjlib.wfac(p.telescope)
# Compute filtering
if p.fltr == 'none': # for none-filtered alm
# Load "observed" aps containing signal, noise, and some residual.
# This aps will be used for normalization calculation
ocl = prjlib.loadocl(p.fcmb.scl['o'], lTmin=p.lTmin, lTmax=p.lTmax)
# CMB alm will be multiplied by 1/ifl before reconstruction process
ifl = ocl #p.lcl[0:3,:]
elif p.fltr == 'cinv': # for C^-1 wiener-filtered alm
pc = prjlib.analysis_init(t=p.telescope,
freq='com',
fltr='none',
ntype=p.ntype)
# Compute aps appropriate for C^-1 filtering case.
ocl, ifl = quad_filter(p.fcmb.scl,
pc.fcmb.scl,
p.lmax,
p.lcl,
lTmin=p.lTmin,
lTmax=p.lTmax)
ocl[ocl <= 0.] = 1e30
ifl[ifl <= 0.] = 1e30
wn[:] = wn[0]
else:
sys.exit('unknown filtering')
if 'iso' in p.ntype: #fullsky case
wn[:] = 1.
d = prjlib.data_directory()
ids = prjlib.rlz_index(doreal=p.doreal)
qobj = quad_func.reconstruction(d['root'],
ids,
rlz=p.rlz,
stag=p.stag,
run=run,
wn=wn,
lcl=p.lcl,
ocl=ocl,
ifl=ifl,
falm=p.fcmb.alms['o'],
**kwargs_ov,
**kwargs_qrec)
# Aps of reconstructed phi
if 'aps' in run:
aps(p.fltr, qobj, p.rlz, p.fpalm, wn)
# Cinv kappa
if 'kcinv' in run:
compute_kcninv(qobj.f,
p.rlz,
p.fltr,
p.kk[:qobj.olmax + 1],
p.fpalm,
Snmin=p.snmin,
Snmax=p.snmax,
qlist=qobj.qlist,
**kwargs_ov)