# the templates for the CMB splits
template = so_map.car_template(ncomp, ra0, ra1, dec0, dec1, res)
# the templates for the binary mask
binary = so_map.car_template(1, ra0, ra1, dec0, dec1, res)
# for CAR we set pixels inside the survey at 1 and at the border to be zero
binary.data[:] = 0
binary.data[1:-1, 1:-1] = 1
print("Generate CMB realisation")
#First let's generate a CMB realisation
cmb = template.synfast(clfile)
split = cmb.copy()
#let's add noise to it with rms 20 uk.arcmin
noise = so_map.white_noise(split, rms_uKarcmin_T=rms_uKarcmin_T)
split.data += noise.data
#First let's generate a CMB realisation
cmb = template.synfast(clfile)
split = cmb.copy()
#let's add noise to it with rms 20 uk.arcmin in T ans sqrt(2)xthat in pol
noise = so_map.white_noise(split, rms_uKarcmin_T=rms_uKarcmin_T)
split.data += noise.data
split.plot(file_name="%s/noisy_cmb" % (test_dir), ticks_spacing_car=4)
print("Generate window function")
#we then apodize the survey mask
map_U = d['map_U_%s' % ar][0]
print("compute harmonic transform ...")
so_mpi.init(True)
subtasks = so_mpi.taskrange(imin=d['iStart'], imax=d['iStop'])
for iii in range(subtasks):
t0 = time.time()
print(iii)
template = so_map.from_components(map_T, map_Q, map_U)
template = so_map.get_submap_car(template, box, mode='floor')
cmb_car = template.synfast(clfile)
noise0 = so_map.white_noise(template, rms_uKarcmin_T=15)
noise1 = so_map.white_noise(template, rms_uKarcmin_T=15)
split0 = cmb_car.copy()
split0.data += noise0.data
split1 = cmb_car.copy()
split1.data += noise1.data
split0_filt = split0.copy()
split1_filt = split1.copy()
split0_filt = so_map_preprocessing.get_map_kx_ky_filtered_pyfftw(
split0_filt, apo, d['filter_dict'])
split1_filt = so_map_preprocessing.get_map_kx_ky_filtered_pyfftw(
split1_filt, apo, d['filter_dict'])