def calc_b(self):
PNd = self.PT(en.map_mul(self.iN, self.d))
Uw1_s = en.harm2map(
en.map_mul(self.hS,
en.rand_gauss_harm(self.d.shape[-3:], self.d.wcs)))
Uw1_a = np.zeros(self.T.shape[0])
Uw1 = self.dof.zip(Uw1_s, Uw1_a)
PNw2 = self.PT(
en.map_mul(self.hN, en.rand_gauss(self.d.shape, self.d.wcs)))
return PNd + Uw1 + PNw2
m += dust; add(res, m, "dust") # 7. Add zodiacal light (invisible) # 8. Add refraction (shift everything by about 1 arcmin for simplicity) # 9. Add the atmosphere (large-scale blobs, high amplitude) cl_atm = parse_powlaw(args.atm) atm = enmap.rand_map(shape, wcs, cl_atm) m += atm; add(res, m, "atm") # 10. Add polarization angle errors (3 degrees, say) m = enmap.rotate_pol(m, args.angerr*np.pi/180) add(res, m, "polerr") # 11. Sidelobe linfo = parse_sidelobe(args.sidelobe) lobe = sim_sidelobe(shape, wcs, linfo) m += lobe; add(res, m, "sidelobe") # 12. Blur m = blur(m, args.beam*np.pi/180/60/(8*np.log(2))*0.5) add(res, m, "beam") # 13. Add white noise white = enmap.rand_gauss(shape, wcs)*(np.array([args.white]+[args.white*2**0.5]*2)/args.res)[:,None,None] m += white; add(res, m, "noise") # 14. Add glitches (localized features with even higher amplitude) ginfo = parse_points(args.glitch) glitch = sim_points(shape, wcs, ginfo) m += glitch; add(res, m, "glitch") output(res, args.odir)
wibox = ibox.copy()
wibox[:, :] = utils.widen_box(ibox[:, :])
srate = nsamp / wt
# output box
icorners = utils.box2corners(ibox)
ocorners = hor2cel(icorners.T, t0)
obox = utils.minmax(ocorners, -1)[:, :2]
wobox = utils.widen_box(obox)
# define a pixelization
shape, wcs = enmap.geometry(pos=wobox[:, ::-1],
res=args.res * utils.arcmin,
proj="cea")
nphi = int(2 * np.pi / (args.res * utils.arcmin))
map_orig = enmap.rand_gauss((ncomp, ) + shape, wcs).astype(dtype)
print "map shape %s" % str(map_orig.shape)
pbox = np.array([[0, 0], shape], dtype=int)
# define a test tod
bore = np.zeros([nsamp, 3], dtype=ptype)
bore[:, 0] = (wt * np.linspace(0, 1, nsamp, endpoint=False))
bore[:, 1] = (args.az + args.waz / 2 * utils.triangle_wave(
np.linspace(0, 1, nsamp, endpoint=False) * 20)) * utils.degree
bore[:, 2] = (args.el + args.wel / 2 * utils.triangle_wave(
np.linspace(0, 1, nsamp, endpoint=False))) * utils.degree
#bore = (ibox[None,0] + np.random.uniform(0,1,size=(nsamp,3))*(ibox[1]-ibox[0])[None,:]).astype(ptype)
tod = np.zeros((ndet, nsamp), dtype=dtype)
psi = np.arange(nsamp) * 2 * np.pi / 100
hwp = np.zeros([nsamp, 2])
hwp[:, 0] = np.cos(psi)
return enmap.samewcs(solver.x.reshape(b.shape), b)
# Try solving
trifilter = Trifilter(map, iP, S, N)
L.info("Filtering map")
pmap = trifilter.solve(map, verbose=args.verbose, nmin=nmin)
L.info("Writing pmap")
enmap.write_map(args.odir + "/pmap.fits", pmap[0])
# Estimate uncertainty with a couple of other realizations
varmap = inoise * 0
nsim = 2
for i in range(nsim):
L.info("Filtering sim %d" % i)
r = enmap.rand_gauss(map.shape,
map.wcs) * (inoise + np.max(inoise) * 1e-4)[0]**-0.5
c = enmap.rand_map(map.shape, map.wcs, ps_cmb)
sim = r + c
sim_flt = trifilter.solve(sim, verbose=args.verbose, nmin=nmin)
enmap.write_map(args.odir + "/sim%d.fits" % i, sim[0])
enmap.write_map(args.odir + "/sim_flt%d.fits" % i, sim_flt[0])
varmap += sim_flt[None, :] * sim_flt[:, None]
varmap /= nsim
L.info("Writing pstd_raw")
enmap.write_map(args.odir + "/pstd_raw.fits", varmap[0, 0]**0.5)
# Smooth var map to reduce noise
L.info("Computing significance")
varmap = enmap.smooth_gauss(varmap[0, 0], 15 * np.pi / 180 / 60)[None, None]
# Create signal-to-noise map
def calc_b(self):
rand_term = [
self.Tmul(c, mat, enmap.rand_gauss(self.d.shape, self.d.wcs))
for c, mat in zip(self.mode, self.hmats)
]
return self.Nd + np.sum(rand_term, 0)
# units ibox[:,1:] *= utils.degree wibox = ibox.copy() wibox[:,:] = utils.widen_box(ibox[:,:]) srate = nsamp/wt # output box icorners = utils.box2corners(ibox) ocorners = hor2cel(icorners.T, t0) obox = utils.minmax(ocorners, -1)[:,:2] wobox = utils.widen_box(obox) # define a pixelization shape, wcs = enmap.geometry(pos=wobox[:,::-1], res=args.res*utils.arcmin, proj="cea") nphi = int(2*np.pi/(args.res*utils.arcmin)) map_orig = enmap.rand_gauss((ncomp,)+shape, wcs).astype(dtype) print "map shape %s" % str(map_orig.shape) pbox = np.array([[0,0],shape],dtype=int) # define a test tod bore = np.zeros([nsamp,3],dtype=ptype) bore[:,0] = (wt*np.linspace(0,1,nsamp,endpoint=False)) bore[:,1] = (args.az + args.waz/2*utils.triangle_wave(np.linspace(0,1,nsamp,endpoint=False)*20))*utils.degree bore[:,2] = (args.el + args.wel/2*utils.triangle_wave(np.linspace(0,1,nsamp,endpoint=False)))*utils.degree #bore = (ibox[None,0] + np.random.uniform(0,1,size=(nsamp,3))*(ibox[1]-ibox[0])[None,:]).astype(ptype) tod = np.zeros((ndet,nsamp),dtype=dtype) psi = np.arange(nsamp)*2*np.pi/100 hwp = np.zeros([nsamp,2]) hwp[:,0] = np.cos(psi) hwp[:,1] = np.sin(psi) if not args.hwp: hwp[0] = 0