fname = f"/scratch/r/rbond/msyriac/data/scratch/tilec/test_sim_galtest_nofg_{version}_00_00{seed}_deep56/scovs_{i}_{j}.npy"
scov = enmap.enmap(np.load(fname),modlmap.wcs)
fname = f"/scratch/r/rbond/msyriac/data/scratch/tilec/test_sim_galtest_nofg_{version}_00_00{seed}_deep56/unsmoothed_noise_cov_{i}_{j}.npy"
try:
ncov = enmap.enmap(np.load(fname),modlmap.wcs)
except:
ncov = 0
ccov = scov + ncov
else:
fname = f"/scratch/r/rbond/msyriac/data/scratch/tilec/test_sim_galtest_nofg_{version}_00_00{seed}_deep56/coadd_cov_{i}_{j}.npy"
ccov = enmap.enmap(np.load(fname),modlmap.wcs)
usig[...,i,j] = usig[...,j,i] = ccov.copy()
print(i,j)
print("eigs...")
emap = modlmap*0
# v = np.linalg.eigh(usig[modlmap<6000,...][500,...])[0]
# print(v)
# print(v.shape)
emap[modlmap<6000] = np.linalg.eigh(usig[modlmap<6000,...])[0][...,0]
#emap = np.linalg.eigh(usig)[0][:,:,0]
np.save("emap_tot",emap)
else:
emap = np.load("emap_tot.npy")
emap[emap<-1e-10] = np.nan
io.power_crop(np.fft.fftshift(emap),300,"eigmapdet.png",ftrans=False,lim=[-0.01,0.01])
return p, cents, p1d
seeds = [12, 13]
narrays = len(qids)
for comp in ['cmb']:
pl1 = io.Plotter('Cell', xyscale='loglin', ylabel='$W$')
pl2 = io.Plotter('Cell')
for seed in seeds:
mname = f"/scratch/r/rbond/msyriac/data/depot/tilec/map_joint_{version}_00_00{seed}_deep56/tilec_single_tile_deep56_cmb_map_joint_{version}_00_00{seed}.fits"
p2d, cents, p1d = pow(enmap.read_map(mname))
io.power_crop(p2d, 150, f"det2d{seed}comp.png", lim=[-10, 1])
#io.plot_img(np.log10(p2d),f"det2d{seed}comp.png",lim=[-10,1],aspect='auto')
#continue # !!!
for i in range(narrays):
qid = qids[i]
#if qid!='p08': continue
fname = f"/scratch/r/rbond/msyriac/data/depot/tilec/map_joint_{version}_00_00{seed}_deep56/tilec_single_tile_deep56_cmb_map_joint_{version}_00_00{seed}_{qid}_weight.fits"
w2d = enmap.read_map(fname)
cents, w1d = binner.bin(w2d)
pl1.add(cents, w1d, ls={12: '-', 13: '--'}[seed], color=f'C{i}')
io.power_crop(np.fft.fftshift(w2d),
150,
lmap = mask.lmap()
lymap,lxmap = lmap
# def model(x,width,amplitude,sigma):
# mmap = 1-amplitude * np.exp(-lymap**2./2./sigma**2.)
# mmap[lxmap>width/2.] = 1
# mmap[lxmap<-width/2.] = 1
# return mmap
def model(x,width,amplitude,sigma):
mmap = (1-amplitude * np.exp(-lymap**2./2./sigma**2.))* (1-np.exp(-lxmap**2./2./width**2.))
return mmap
m = model(0,100,1,3000)
io.power_crop(np.fft.fftshift(m),Ncrop,'model.png',ftrans=False)
# sys.exit()
# io.hplot(enmap.downgrade(isim,4),'isim')
# io.hplot(enmap.downgrade(tmap,4),'tmap')
kisim1 = ffunc(isim1[0])
kisim2 = ffunc(isim2[0])
ktmap1 = ffunc(tmap1[0])
ktmap2 = ffunc(tmap2[0])
pcross2d1 = pfunc(kisim1,ktmap1)
pcross2d2 = pfunc(kisim2,ktmap2)
psim2d1 = pfunc(kisim1,kisim1)
psim2d2 = pfunc(kisim2,kisim2)
from __future__ import print_function
from orphics import maps,io,cosmology,stats
from pixell import enmap
import numpy as np
import os,sys
from tilec import covtools
from tilec.ilc import CTheory
qid = 'p01'
scov = enmap.read_map("/scratch/r/rbond/msyriac/dump/unsmoothed_debeamed_%s_%s.fits" % (qid,qid))
dncov = enmap.read_map("/scratch/r/rbond/msyriac/dump/smoothed_noise_%s_%s.fits" % (qid,qid))
beamsq = enmap.read_map("/scratch/r/rbond/msyriac/dump/beamsq_%s_%s.fits" % (qid,qid))
io.power_crop(scov,200,"inv_scov.png")
io.power_crop(dncov,200,"inv_dncov.png")
io.power_crop(beamsq,200,"inv_beamsq.png")
bin_edges = np.arange(80,3000,20)
modlmap = scov.modlmap()
binner = stats.bin2D(modlmap,bin_edges)
# fwhm = 33.
# lefts = bin_edges[:-1]
# rights = bin_edges[1:]
# cents = binner.centers
# ms = maps.gauss_beam(rights,fwhm)/maps.gauss_beam(lefts,fwhm)
# pl = io.Plotter(xyscale='linlin',xlabel='l',ylabel='Bright/Bleft')
# pl.add(cents,ms)
# pl.done("inv_brat.png")
# sys.exit()
# print(ksol[px[0]-11,px[1]])
# print(optile[px[0],px[1]])
# print(optile[px[0]-1,px[1]])
# print(modlmap[px[0],px[1]])
# print(modlmap[px[0]-1,px[1]])
# # pftile = ptile
# # pftile[modlmap>300] = 0
# # print(np.sort(pftile[pftile>0]))
# # print(modlmap[np.isclose(ptile,1.52256073e+02)])
# # io.plot_img(np.log10(np.fft.fftshift(ptile)),os.environ['WORK']+"/tiling/ptile_%d_smap" % i)
# # io.hplot(enmap.enmap(np.log10(np.fft.fftshift(ptile)),ewcs),os.environ['WORK']+"/tiling/phtile_%d_smap" % i)
smap = enmap.ifft(kbeam * enmap.enmap(ksol, ewcs),
normalize='phys').real
if solution == 'CMB':
io.hplot(smap, os.environ['WORK'] + "/tiling/tile_%d_smap" % i)
io.power_crop(np.real(ksol * ksol.conj()), 100,
os.environ['WORK'] + "/tiling/ptile_%d.png" % i)
# sys.exit()
ta.update_output(solution, smap, inserter)
#ta.update_output("processed",c*civar,inserter)
#ta.update_output("processed_ivar",civar,inserter)
#pmap = ilc.do_ilc
#ta.update_output("processed",pmap,inserter)
print("Rank %d done" % comm.rank)
for solution in solutions:
pmap = ta.get_final_output(solution)
if comm.rank == 0:
io.hplot(pmap, os.environ['WORK'] + "/tiling/map_%s" % solution)
mask = sints.get_act_mr3_crosslinked_mask("deep56")
io.hplot(
enmap.extract(pmap, mask.shape, mask.wcs) * mask,
os.environ['WORK'] + "/tiling/mmap_%s" % solution)
version = "noLFI_nohigh_test"
mask = sints.get_act_mr3_crosslinked_mask(region)
modlmap = mask.modlmap()
lmap = mask.lmap()
bin_edges = np.arange(20, 6000, 80)
binner = stats.bin2D(modlmap, bin_edges)
def pow(x, y=None):
k = enmap.fft(x, normalize='phys')
ky = enmap.fft(y, normalize='phys') if y is not None else k
p = (k * ky.conj()).real
cents, p1d = binner.bin(p)
return p, cents, p1d
seeds = [12] #,13]
qids = "d56_04,d56_05,d56_06,p04,p05,p06".split(',')
narrays = len(qids)
for comp in ['cmb']:
for i in range(narrays):
qid = qids[i]
for seed in seeds:
fname = f"/scratch/r/rbond/msyriac/data/scratch/tilec/test_sim_galtest_nofg_{version}_00_00{seed}_deep56/dncovs_{i}_{i}.npy"
scov = enmap.enmap(np.load(fname), modlmap.wcs)
io.power_crop(scov, 600, f"dn2d_det_{qid}_{seed}.png")
# seeds = [12]
versions = ['test_sim_galtest_final']
seeds = [12,13]
for version in versions:
pl = io.Plotter(xyscale='linlog',scalefn = lambda x: x**2./2./np.pi,xlabel='l',ylabel='D')
for seed in seeds:
csfile = tutils.get_generic_fname(tdir,region,'cmb',deproject=None,data_comb=dcomb,version=version,sim_index=seed)
imap = enmap.read_map(csfile)
modlmap = imap.modlmap()
k = enmap.fft(imap,normalize='phys')
p2d = p(k)
io.power_crop(p2d,300,f"cp2d_{version}.png")
binner = stats.bin2D(modlmap,bin_edges)
cents,p1d = binner.bin(p2d)
pl.add(cents,p1d,lw=1,alpha=0.8,label=f'{seed}')
pl._ax.set_ylim(10,3e5)
pl.done("cpowall_%s.png" % version)
# #This snippet discovered that sim_index=12 is the first instance of break-down
# nsims = 13
# p = lambda x: (x*x.conj()).real
# bin_edges = np.arange(20,6000,20)
# pl = io.Plotter(xyscale='linlog',scalefn = lambda x: x**2./2./np.pi,xlabel='l',ylabel='D')
#omap = enmap.read_map('/scratch/r/rbond/msyriac/data/tilec/omar/dataCoadd_combined_I_s14&15_deep56.fits')
omap = enmap.read_map(
'/scratch/r/rbond/msyriac/data/tilec/omar/preparedMap_T_s14&15_deep56.fits'
) * 2.726e6
omar_mask = enmap.read_map(
'/scratch/r/rbond/msyriac/data/tilec/omar/mask_s14&15_deep56.fits')
omar_w2 = np.mean(omar_mask**2.)
# io.hplot(enmap.downgrade(omap,4),"omap")
# io.hplot(enmap.downgrade(omask,4),"omask")
# sys.exit()
okmap = enmap.fft(omap, normalize='phys')
op2d = np.real(okmap * okmap.conj())
io.power_crop(p2d,
200,
"pimg_%s_%s.png" % (args.solution, args.region),
lim=lim)
io.power_crop(nmap,
200,
"nimg_%s_%s.png" % (args.solution, args.region),
lim=lim)
sel = np.logical_and(modlmap > lmin, modlmap < lmax)
xs = modlmap[sel].reshape(-1)
ys = p2d[sel].reshape(-1)
pl = io.Plotter(xyscale='linlog', xlabel='l', ylabel='C')
pl._ax.scatter(xs, ys)
#pl._ax.set_ylim(lim[0],lim[1])
pl.done("pscatter_%s_%s.png" % (args.solution, args.region))
"""
# ti_noise2d = enmap.read_map("%stilec_single_tile_%s_cmb_map_v1.0.0_rc_joint_noise.fits" % (tpath,region))
# ti_nosz_noise2d = enmap.read_map("%stilec_single_tile_%s_cmb_deprojects_comptony_map_v1.0.0_rc_joint_noise.fits" % (tpath,region))
# ti_cross_noise2d = enmap.read_map("%stilec_single_tile_%s_cmb_deprojects_comptony_map_v1.0.0_rc_joint_cross_noise.fits" % (tpath,region))
ti_map = enmap.read_map("%stilec_single_tile_%s_cmb_map_v1.0.0_rc_joint.fits" %
(tpath, region))
ti_nosz_map = enmap.read_map(
"%stilec_single_tile_%s_cmb_deprojects_comptony_map_v1.0.0_rc_joint.fits" %
(tpath, region))
ti_noise2d = pow2(ti_map, ti_map, tkbeam, tkbeam)
ti_nosz_noise2d = pow2(ti_nosz_map, ti_nosz_map, tkbeam_nosz, tkbeam_nosz)
ti_cross_noise2d = pow2(ti_map, ti_nosz_map, tkbeam, tkbeam_nosz)
io.power_crop(ti_noise2d, Nplot, "ti_noise2d.png", ftrans=True)
io.power_crop(ti_nosz_noise2d, Nplot, "ti_nosz_noise2d.png", ftrans=True)
io.power_crop(ti_cross_noise2d, Nplot, "ti_cross_noise2d.png", ftrans=True)
tmap = enmap.read_map("%sdataCoadd_combined_I_s14&15_%s.fits" %
(opath, region))
oi_noise2d = pow(tmap)
io.power_crop(oi_noise2d, Nplot, "oi_noise2d.png", ftrans=True)
cents, ti_noise1d = binner.bin(ti_noise2d)
cents, ti_nosz_noise1d = binner.bin(ti_nosz_noise2d)
cents, ti_cross_noise1d = binner.bin(ti_cross_noise2d)
cents, oi_noise1d = binner.bin(oi_noise2d)
pl = io.Plotter(xlabel='l', ylabel='C', xyscale='linlog')
p2d, cents, p1d = pow(imap)
lp2d = np.log10(p2d)
sel = np.logical_and(modlmap < 1300, modlmap > 1100)
vals = lp2d[sel]
# print(vals)
# print(vals.mean(),vals.max(),vals.min(),vals.std())
hist, edges = np.histogram(vals, bins=np.linspace(-15, 5, 300))
hcents = (edges[1:] + edges[:-1]) / 2.
pl2 = io.Plotter(xlabel='v', ylabel='N')
pl2.add(hcents, hist)
pl2.done(f"detvalhist{seed}.png")
pl.add(cents, p1d, label=f"{seed}")
llim = 0
io.power_crop(p2d, 150, f"det2d{seed}comp.png", lim=[-10, 1])
badinds = np.argwhere(np.logical_and(np.log10(p2d) > llim, modlmap > 1000))
print(modlmap[np.logical_and(np.log10(p2d) > llim, modlmap > 1000)])
#sys.exit()
badinds = np.argwhere(np.logical_and(np.log10(p2d) > llim, modlmap > 1000))
if len(badinds) > 0:
ind = 0
print(badinds[ind])
print(modlmap[badinds[ind][0], badinds[ind][1]])
print(modlmap[badinds[ind][0] + 10, badinds[ind][1] + 10])
print(p2d[badinds[ind][0], badinds[ind][1]])
print(p2d[badinds[ind][0] + 10, badinds[ind][1] + 10])
p2d[np.logical_and(np.log10(p2d) > llim, modlmap > 1000)] = np.nan
#p2d[sel] = np.nan
io.power_crop(p2d, 150, f"mdet2d{seed}comp.png", lim=[-10, 1])