def qu2eb(qmap, umap):
import polTools
qtemp = qmap.to_flipper()
utemp = umap.to_flipper()
emap, bmap = polTools.convertToEB(qtemp, utemp, True, False)
emap = enmap.from_flipper(emap)
bmap = enmap.from_flipper(bmap)
return (emap, bmap)
def get_sim(sim_idx):
ret = act_sim.getActpolCmbSim(None, coords, sim_idx, cmb_dir, doBeam=False, pixelFac= 2)
for i in range(len(ret)):
ret[i] = enmap.from_flipper(ret[i])
ret[i] -= np.mean(ret[i])
return (ret[0], ret[1], ret[2]) # TQU
def get_sim(sim_idx, beam_fwhm=beam_fwhm, noise_level=noise_level):
ret = act_sim.getActpolCmbSim(None,
coords,
sim_idx,
cmb_dir,
doBeam=False,
pixelFac=1)
np.random.seed(sim_idx)
# handle mean
for i in range(len(ret)):
ret[i].data -= np.mean(ret[i].data)
ret[i] = enmap.from_flipper(ret[i])
# beam convolve
owcs, shape = (ret[0].wcs.copy(), ret[0].shape)
tqu = np.zeros((3, ) + ret[0].shape)
tqu[0], tqu[1], tqu[2] = (ret[0], ret[1], ret[2])
tqu = enmap.enmap(tqu, owcs)
alm = curvedsky.map2alm(tqu, lmax=lmax)
del ret
_, beam = cmblens.theory.get_gauss_beam(np.arange(lmax + 1), beam_fwhm)
fl = np.sqrt(beam)
log.info("beam convolution")
for i in range(alm.shape[0]):
alm[i] = hp.sphtfunc.almxfl(alm[i], fl)
tqu = curvedsky.alm2map(alm[:, None], tqu.copy()[:, None])[:, 0]
if noise_level > 0:
log.info("adding noise")
for i in range(len(tqu)):
noise = enmap.to_flipper(tqu[i]).getTemplate()
l_n = np.arange(lmax + 1000)
noise_fact = 1. if i == 0 else np.sqrt(2)
nl = cmblens.theory.get_white_noise_power(l_n,
noise_level * noise_fact)
ps = nl.reshape((1, 1, nl.size))
noise = curvedsky.rand_map(shape, owcs, ps, lmax=(lmax + 1000))
#noise.fillWithGaussianRandomField(l_n, nl, bufferFactor=1)
tqu[i] += noise
del noise
# beam deconvolve
log.info("beam deconvolution")
alm = curvedsky.map2alm(tqu, lmax=lmax)
for i in range(alm.shape[0]):
alm[i] = hp.sphtfunc.almxfl(alm[i], 1. / fl)
tqu = curvedsky.alm2map(alm[:, None], tqu.copy()[:, None])[:, 0]
return (tqu[0], tqu[1], tqu[2]) # TQU
def get_sim(sim_idx, mode='flat'):
assert (mode in ['flat', 'actsim'])
ret = None
if mode == 'flat':
assert (False)
ret = mg.get_map(seed=sim_idx)
elif mode == 'actsim':
ret = act_sim.getActpolCmbSim(None,
coords,
sim_idx,
cmb_dir,
doBeam=False)
else:
assert (1)
for i in range(len(ret)):
ret[i] = enmap.from_flipper(ret[i])
ret[i] -= np.mean(ret[i])
return (ret[0], ret[1], ret[2]) # TQU