def rand_map_flat(shape,
wcs,
ps,
lmax=None,
lens=True,
aberrate=True,
beta=None,
dir=None,
seed=None,
dtype=None,
verbose=False,
recenter=False,
pad=0):
"""Simulate a random flat-sky map. The input spectrum should be
[{phi,T,E,B},{phi,T,E,b},nl] of lens is True, and just [{T,E,B},{T,E,B},nl]
otherwise."""
if dtype is None: dtype = np.float64
if dir is None: dir = aberration.dir_equ
if beta is None: beta = aberration.beta
ctype = np.result_type(dtype, 0j)
if verbose: print "Generating unlensed cmb"
# No position calculation necessary if we're not lensing or aberrating.
if not lens and not aberrate:
return enmap.rand_map(shape, wcs, ps, seed=seed)
# Otherwise we must deal with various displacements
if aberrate: pad += np.pi * beta * 1.2
pad_pix = int(pad / enmap.pixsize(shape, wcs)**0.5)
if pad_pix > 0:
if verbose: print "Padding"
template = enmap.zeros(shape, wcs, np.int16)
template, pslice = enmap.pad(template, pad_pix, return_slice=True)
pshape, pwcs = template.shape, template.wcs
else:
pshape, pwcs = shape, wcs
# Simulate (padded) lensing map
if lens:
maps = enmap.rand_map((ps.shape[0], ) + pshape[-2:], pwcs, ps)
phi, unlensed = maps[0], maps[1:]
if verbose: print "Lensing"
m = lensing.lens_map_flat(unlensed, phi)
else:
m = enmap.rand_map((ps.shape[0], ) + pshape[-2:], pwcs, ps)
# Then handle aberration if necessary
if aberrate:
if verbose: print "Computing aberration displacement"
pos = m.posmap()
pos = enmap.samewcs(
aberration.remap(pos[1::-1], dir=dir, beta=beta,
recenter=recenter), pos)
amp = pos[3]
pos = pos[1::-1]
if verbose: print "Interpolating aberration"
m = enmap.samewcs(m.at(pos, mask_nan=False), m)
if verbose: print "Applying modulation"
m *= amp
if pad_pix > 0:
if verbose: print "Unpadding"
m = m[pslice]
return m
ps = powspec.read_camb_full_lens(args.powspec).astype(dtype)
if args.beam:
raise NotImplementedError("Beam not supported for lensed sims yet")
if args.geometry == "curved":
m, = lensing.rand_map(shape,
wcs,
ps,
lmax=lmax,
maplmax=maplmax,
seed=(seed, i),
verbose=verbose,
dtype=dtype)
else:
maps = enmap.rand_map((shape[0] + 1, ) + shape[1:], wcs, ps)
phi, unlensed = maps[0], maps[1:]
m = lensing.lens_map_flat(unlensed, phi)
else:
ps = powspec.read_spectrum(args.powspec).astype(type)
beam = make_beam(ps.shape[-1], args.beam * utils.arcmin * utils.fwhm)
ps *= beam
if args.geometry == "curved":
m = curvedsky.rand_map(shape,
wcs,
ps,
lmax=lmax,
seed=(seed, i),
method=args.method,
direct=args.direct,
dtype=dtype,
verbose=verbose)
else:
enmap.write_map("%s/%02d_%s_tqu.hdf" % (dir,i+1,desc), tqu)
enmap.write_map("%s/%02d_%s_teb.hdf" % (dir,i+1,desc), teb)
cl_scal, cl_phi = powspec.read_camb_scalar(args.scal_cls, expand=True)
cl_tens = powspec.read_spectrum(args.tens_cls, expand="diag")
cl_cmb = cl_scal+cl_tens
np.random.seed(args.seed)
res = bunch.Bunch(tqu=[],teb=[],desc=[])
# 1. Start with last scattering
cmb = enmap.rand_map(shape, wcs, cl_cmb)
m = cmb; add(res, m, "cmb")
# 2. Add lensing
phi = enmap.rand_map(shape[-2:], wcs, cl_phi)
lcmb = lensing.lens_map_flat(cmb, phi)
m = lcmb; add(res, m, "lens")
# 3. Add point sources
pinfo = parse_points(args.ptsrc)
pmap = sim_points(shape, wcs, pinfo)
m += pmap; add(res, m, "ptsrc")
# 4. Add sz clusters
zinfo = parse_points(args.sz)
zmap = sim_points(shape, wcs, zinfo)
m += zmap; add(res, m, "sz")
# 5. Add faraday rotation (probably invisible)
m = enmap.rotate_pol(m, args.faraday)
add(res, m, "faraday")
# 6. Add dust (as a representative galactic foreground)
cl_dust = parse_powlaw(args.dust)
dust = enmap.rand_map(shape, wcs, cl_dust)
verbose = args.verbose - args.quiet > 0
def make_beam(nl, bsize):
l = np.arange(nl)
return np.exp(-l*(l+1)*bsize**2)
for i in range(comm.rank, args.nsim, comm.size):
if args.lensed:
ps = powspec.read_camb_full_lens(args.powspec).astype(dtype)
if args.beam:
raise NotImplementedError("Beam not supported for lensed sims yet")
if args.geometry == "curved":
m, = lensing.rand_map(shape, wcs, ps, lmax=lmax, maplmax=maplmax, seed=(seed,i), verbose=verbose, dtype=dtype)
else:
maps = enmap.rand_map((shape[0]+1,)+shape[1:], wcs, ps)
phi, unlensed = maps[0], maps[1:]
m = lensing.lens_map_flat(unlensed, phi)
else:
ps = powspec.read_spectrum(args.powspec).astype(type)
beam = make_beam(ps.shape[-1], args.beam*utils.arcmin*utils.fwhm)
ps *= beam
if args.geometry == "curved":
m = curvedsky.rand_map(shape, wcs, ps, lmax=lmax, seed=(seed,i), method=args.method, direct=args.direct, dtype=dtype, verbose=verbose)
else:
m = enmap.rand_map(shape, wcs, ps)
if args.nsim == 1:
if verbose: print "Writing %s" % args.ofile
enmap.write_map(args.ofile, m)
else:
if verbose: print "Writing %s" % (args.ofile % i)
enmap.write_map(args.ofile % i, m)
box = np.array([[-w,-w],[w,w]])/2 wcs = enmap.create_wcs(shape, box) cl_scal, cl_phi = powspec.read_camb_scalar(args.scal_cls, expand=True) cl_tens = powspec.read_spectrum(args.tens_cls, expand="diag") ## Generate scalar-only lensed and unlensed map #m_scal_u, m_scal_l = lensing.rand_map(shape, wcs, cl_scal, cl_phi, seed=args.seed, output="ul", verbose=args.verbose) ## Generate tensor-only lensed and unlensed map #m_tens_u, m_tens_l = lensing.rand_map(shape, wcs, cl_tens, cl_phi, seed=args.seed, output="ul", verbose=args.verbose) np.random.seed(args.seed) phi = enmap.rand_map(shape[-2:], wcs, cl_phi) m_scal_u = enmap.rand_map(shape, wcs, cl_scal) m_tens_u = enmap.rand_map(shape, wcs, cl_tens) m_scal_l = lensing.lens_map_flat(m_scal_u, phi) m_tens_l = lensing.lens_map_flat(m_tens_u, phi) # And the sums m_tot_u = m_scal_u + m_tens_u m_tot_l = m_scal_l + m_tens_l # Convert from TQU to TEB and downgrade def to_eb(m): return enmap.ifft(enmap.map2harm(m)).real m_scal_u, m_scal_l, m_tens_u, m_tens_l, m_tot_u, m_tot_l = [enmap.downgrade(to_eb(i),os) for i in [m_scal_u, m_scal_l, m_tens_u, m_tens_l, m_tot_u, m_tot_l]] # And output utils.mkdir(args.odir) enmap.write_map(args.odir + "/map_scalar.fits", m_scal_u) enmap.write_map(args.odir + "/map_tensor.fits", m_tens_u) enmap.write_map(args.odir + "/map_tot.fits", m_tot_u)
