for ar_id, ar in enumerate(arrays):
win_T = so_map.read_map(d["window_T_%s_%s" % (sv, ar)])
win_pol = so_map.read_map(d["window_pol_%s_%s" % (sv, ar)])
window_tuple = (win_T, win_pol)
del win_T, win_pol
# we add fg alms to cmb alms in temperature
alms_beamed = alms.copy()
alms_beamed[0] += fglms[id_freq[d["nu_eff_%s_%s" % (sv, ar)]]]
# we convolve signal + foreground with the beam of the array
l, bl = pspy_utils.read_beam_file(d["beam_%s_%s" % (sv, ar)])
alms_beamed = curvedsky.almxfl(alms_beamed, bl)
if scenario == "noE": alms_beamed[1] *= 0
if scenario == "noB": alms_beamed[2] *= 0
# generate our signal only sim
split = sph_tools.alm2map(alms_beamed, template[sv])
# compute the alms of the sim
master_alms[sv, ar, "nofilter"] = sph_tools.get_alms(
split, window_tuple, niter, lmax, dtype=sim_alm_dtype)
# apply the k-space filter
sv2_list += [sv2]
ar2_list += [ar2]
n_mcms += 1
print("number of mcm matrices to compute : %s" % n_mcms)
so_mpi.init(True)
subtasks = so_mpi.taskrange(imin=0, imax=n_mcms - 1)
print(subtasks)
for task in subtasks:
task = int(task)
sv1, ar1, sv2, ar2 = sv1_list[task], ar1_list[task], sv2_list[
task], ar2_list[task]
print("%s_%s x %s_%s" % (sv1, ar1, sv2, ar2))
l, bl1 = pspy_utils.read_beam_file(d["beam_%s_%s" % (sv1, ar1)])
win1_T = so_map.read_map(d["window_T_%s_%s" % (sv1, ar1)])
win1_pol = so_map.read_map(d["window_pol_%s_%s" % (sv1, ar1)])
l, bl2 = pspy_utils.read_beam_file(d["beam_%s_%s" % (sv2, ar2)])
win2_T = so_map.read_map(d["window_T_%s_%s" % (sv2, ar2)])
win2_pol = so_map.read_map(d["window_pol_%s_%s" % (sv2, ar2)])
mbb_inv, Bbl = so_mcm.mcm_and_bbl_spin0and2(win1=(win1_T, win1_pol),
win2=(win2_T, win2_pol),
bl1=(bl1, bl1),
bl2=(bl2, bl2),
binning_file=d["binning_file"],
niter=d["niter"],
lmax=d["lmax"],
type=d["type"],
pspy_utils.create_directory(plot_dir)
spectra = ["TT", "TE", "TB", "ET", "BT", "EE", "EB", "BE", "BB"]
surveys = d["surveys"]
lmax = d["lmax"]
type = d["type"]
binning_file = d["binning_file"]
lth = np.arange(2, lmax + 2)
for sv in surveys:
arrays = d["arrays_%s" % sv]
for id_ar1, ar1 in enumerate(arrays):
for id_ar2, ar2 in enumerate(arrays):
if id_ar1 > id_ar2: continue
l, bl_ar1 = pspy_utils.read_beam_file(d["beam_%s_%s" % (sv, ar1)])
l, bl_ar2 = pspy_utils.read_beam_file(d["beam_%s_%s" % (sv, ar2)])
lb, bb_ar1 = pspy_utils.naive_binning(l, bl_ar1, binning_file,
lmax)
lb, bb_ar2 = pspy_utils.naive_binning(l, bl_ar2, binning_file,
lmax)
nsplits = len(d["maps_%s_%s" % (sv, ar1)])
spec_name_noise = "%s_%s_%sx%s_%s_noise" % (type, sv, ar1, sv, ar2)
print(spec_name_noise)
lb, nbs = so_spectra.read_ps("%s/%s.dat" %
(spectra_dir, spec_name_noise),
spectra=spectra)