def get_maps_cl(frec, fconv=None, lmin=20, delta_ell=40, apodization_degrees=5.):
mrec, resid, seenmap = get_maps_residuals(frec, fconv=fconv)
sh = np.shape(mrec)
print(sh, np.shape(resid))
nbsub = sh[1]
ns = hp.npix2nside(sh[2])
from qubic import apodize_mask
mymask = apodize_mask(seenmap, apodization_degrees)
# Create XPol object
from qubic import Xpol
lmax = 2 * ns
xpol = Xpol(mymask, lmin, lmax, delta_ell)
ell_binned = xpol.ell_binned
nbins = len(ell_binned)
# Pixel window function
pw = hp.pixwin(ns)
pwb = xpol.bin_spectra(pw[:lmax + 1])
# Calculate all crosses and auto
m_autos = np.zeros((nbsub, 6, nbins))
s_autos = np.zeros((nbsub, 6, nbins))
m_cross = np.zeros((nbsub, 6, nbins))
s_cross = np.zeros((nbsub, 6, nbins))
fact = ell_binned * (ell_binned + 1) / 2. / np.pi
for isub in range(nbsub):
m_autos[isub, :, :], s_autos[isub, :, :], m_cross[isub, :, :], s_cross[isub, :, :] = \
allcross_par(xpol, mrec[:, isub, :, :], silent=False, verbose=0)
return mrec, resid, seenmap, ell_binned, m_autos * fact / pwb ** 2, \
s_autos * fact / pwb ** 2, m_cross * fact / pwb ** 2, s_cross * fact / pwb ** 2
def get_xpol(seenmap, ns, lmin=20, delta_ell=20, apodization_degrees=5.):
"""
Returns a Xpoll object to get spectra, the bin used and the pixel window function.
"""
# Create a mask
mymask = apodize_mask(seenmap, apodization_degrees)
# Create XPol object
lmax = 2 * ns
xpol = Xpol(mymask, lmin, lmax, delta_ell)
ell_binned = xpol.ell_binned
# Pixel window function
pw = hp.pixwin(ns)
pwb = xpol.bin_spectra(pw[:lmax + 1])
return xpol, ell_binned, pwb
# mean_rms_cov = np.sqrt(np.mean(rmsmap_cov**2, axis=2))
# plt.plot(nsubvals, np.sqrt(nsubvals), 'k', label='Optimal $\sqrt{N}$', lw=2)
# for i in xrange(3):
# plt.plot(nsubvals, mean_rms_cov[:,i] / mean_rms_cov[0,i] * np.sqrt(nsubvals), label=stokes[i], lw=2, ls='--')
# plt.xlabel('Number of sub-frequencies')
# plt.ylabel('Relative maps RMS')
# plt.legend()
#======================= Apply Xpoll to get spectra ============================
lmin = 20
lmax = 2 * ns
delta_ell = 20
#Xpoll needs a mask
mymask = apodize_mask(seenmap_conv, 5)
xpol = Xpol(mymask, lmin, lmax, delta_ell)
ell_binned = xpol.ell_binned
nbins = len(ell_binned)
print('nbins = {}'.format(nbins))
mcls, mcls_in = [], []
scls, scls_in = [], []
#Input : what we should find
mapsconv = np.zeros((12 * ns**2, 3))
#Output, what we find
maps_recon = np.zeros((12 * ns**2, 3))
for isub in xrange(len(nsubvals)):
# compute apodization mask nside = 256 lmin = 20 lmax = 2*nside-1 delta_ell = 20 racenter = 0.0 deccenter = -57.0 maxang = 20. center = equ2gal(racenter, deccenter) veccenter = hp.ang2vec(pi/2-np.radians(center[1]), np.radians(center[0])) vecpix = hp.pix2vec(nside, np.arange(12*nside**2)) cosang = np.dot(veccenter, vecpix) maskok = np.degrees(np.arccos(cosang)) < maxang maskmap = apodize_mask(maskok, 5) hp.gnomview(maskmap, rot=[racenter, deccenter], coord=['G', 'C'], reso=15) # Xpol estimation through MC np.random.seed(0) xpol = Xpol(maskmap, lmin, lmax, delta_ell) ell_binned = xpol.ell_binned spectra_binned = xpol.bin_spectra(spectra) nbins = len(ell_binned) nbmc = 100 allclsout = np.zeros((nbmc, 6, nbins)) allcls = np.zeros((nbmc, 6, lmax+1)) bar = progress_bar(nbmc) for i in np.arange(nbmc):
# compute apodization mask
nside = 256
lmin = 20
lmax = 2 * nside - 1
delta_ell = 20
racenter = 0.0
deccenter = -57.0
maxang = 20.
center = equ2gal(racenter, deccenter)
veccenter = hp.ang2vec(pi / 2 - np.radians(center[1]), np.radians(center[0]))
vecpix = hp.pix2vec(nside, np.arange(12 * nside**2))
cosang = np.dot(veccenter, vecpix)
maskok = np.degrees(np.arccos(cosang)) < maxang
maskmap = apodize_mask(maskok, 5)
hp.gnomview(maskmap, rot=[racenter, deccenter], coord=['G', 'C'], reso=15)
# Xpol estimation through MC
np.random.seed(0)
xpol = Xpol(maskmap, lmin, lmax, delta_ell)
ell_binned = xpol.ell_binned
spectra_binned = xpol.bin_spectra(spectra)
nbins = len(ell_binned)
nbmc = 100
allclsout = np.zeros((nbmc, 6, nbins))
allcls = np.zeros((nbmc, 6, lmax + 1))
bar = progress_bar(nbmc)
for i in np.arange(nbmc):
maps = hp.synfast(spectra,