acl = hp.alm2cl(recon_alms,recon_alms) # reconstruction raw autopower
xcl = hp.alm2cl(recon_alms,kalms) # cross-power of input and reconstruction
icl = hp.alm2cl(kalms,kalms) # autopower of input
# Apply mask corrections and add to stats collecter
s.add_to_stats('acl',acl/w4)
s.add_to_stats('xcl',xcl/w3)
s.add_to_stats('icl',icl/w2)
# Stack meanfield alms
if args.write_meanfield:
s.add_to_stack('rmf',recon_alms.real)
s.add_to_stack('imf',recon_alms.imag)
with io.nostdout():
s.get_stats()
s.get_stacks()
if rank==0:
# Collect statistics and plot
with io.nostdout():
acl = s.stats['acl']['mean']
xcl = s.stats['xcl']['mean']
icl = s.stats['icl']['mean']
if args.write_meanfield:
mf_alm = s.stacks['rmf'] + 1j*s.stacks['imf']
hp.write_alm(f'{solenspipe.opath}/mf_{args.label}_{args.polcomb}_{isostr}_alm.fits',mf_alm,overwrite=True)
def _init_qests(self):
mlist = ['e', 's', 'r']
self.qest = {}
tellminY = 500
tellmaxY = 3000
pellminY = 500
pellmaxY = 3000
tellminX = 500
tellmaxX = 3000
pellminX = 500
pellmaxX = 3000
kellmin = 80
kellmax = 3000
self.kellmin = kellmin
self.kellmax = kellmax
for m in mlist:
modlmap_dat = enmap.modlmap(self.shape[m], self.wcs[m])
nT = modlmap_dat.copy() * 0.
nP = modlmap_dat.copy() * 0.
lbeam = modlmap_dat.copy() * 0. + 1.
fMaskCMB_TX = fmaps.mask_kspace(self.shape[m],
self.wcs[m],
lmin=tellminX,
lmax=tellmaxX)
fMaskCMB_TY = fmaps.mask_kspace(self.shape[m],
self.wcs[m],
lmin=tellminY,
lmax=tellmaxY)
fMaskCMB_PX = fmaps.mask_kspace(self.shape[m],
self.wcs[m],
lmin=pellminX,
lmax=pellmaxX)
fMaskCMB_PY = fmaps.mask_kspace(self.shape[m],
self.wcs[m],
lmin=pellminY,
lmax=pellmaxY)
fMask = fmaps.mask_kspace(self.shape[m],
self.wcs[m],
lmin=kellmin,
lmax=kellmax)
with io.nostdout():
self.qest[m] = Estimator(
self.shape[m],
self.wcs[m],
self.theory,
theorySpectraForNorm=None,
noiseX2dTEB=[nT, nP, nP],
noiseY2dTEB=[nT, nP, nP],
fmaskX2dTEB=[fMaskCMB_TX, fMaskCMB_PX, fMaskCMB_PX],
fmaskY2dTEB=[fMaskCMB_TY, fMaskCMB_PY, fMaskCMB_PY],
fmaskKappa=fMask,
kBeamX=lbeam,
kBeamY=lbeam,
doCurl=False,
TOnly=True,
halo=True,
uEqualsL=True,
gradCut=None,
verbose=False,
bigell=self.lmax)