def inpaint_map_const_cov(imap,mask,union_sources_version=None,noise_pix = 20,hole_radius = 3.,plots=False):
"""
Inpaints a map under the assumption of constant 2D Fourier covariance. This uses the average PS
of the full map for the noise model at each source location and thus does not handle inhomogenity.
Pros: no products needed other than map-maker outputs of map
Cons:
imap -- (npol,Ny,Nx)
ivar -- (Ny,Nx)
"""
ras,decs = sints.get_act_mr3f_union_sources(version=union_sources_version)
kmap = enmap.fft(mask*imap,normalize='phys')
gtags = []
gdicts = {}
pcoords = []
for i,(ra,dec) in enumerate(zip(ras,decs)):
sel = reproject.cutout(ivar, ra=np.deg2rad(ra), dec=np.deg2rad(dec), pad=1, corner=False,npix=noise_pix,return_slice=True)
if sel is None: continue
civar = ivar[sel]
if np.any(civar<=0): continue
modrmap = civar.modrmap()
modlmap = civar.modlmap()
res = maps.resolution(civar.shape,civar.wcs)
cimap = imap[sel]
print(ra,dec)
if plots:
for p in range(3): io.plot_img(cimap[p],os.environ['WORK']+"/cimap_%d_%s" % (p,str(i).zfill(2)))
mimap = cimap.copy()
mimap[...,modrmap<np.deg2rad(hole_radius/60.)] = np.nan
for p in range(3): io.plot_img(mimap[p],os.environ['WORK']+"/masked_cimap_%d_%s" % (p,str(i).zfill(2)))
scov = pixcov.scov_from_theory(modlmap,cmb_theory_fn,fn_beam,iau=False)
ncov = pixcov.ncov_from_ivar(civar)
pcov = scov + ncov
gdicts[i] = pixcov.make_geometry(hole_radius=np.deg2rad(hole_radius/60.),n=noise_pix,deproject=True,iau=False,pcov=pcov,res=res)
pcoords.append(np.array((dec,ra)))
gtags.append(i)
if len(gtags)>0:
pcoords = np.stack(pcoords).swapaxes(0,1)
result = pixcov.inpaint(imap,pcoords,deproject=True,iau=False,geometry_tags=gtags,geometry_dicts=gdicts,verbose=True)
if plots:
for i,(ra,dec) in enumerate(zip(ras,decs)):
sel = reproject.cutout(ivar, ra=np.deg2rad(ra), dec=np.deg2rad(dec), pad=1, corner=False,npix=noise_pix,return_slice=True)
if sel is None: continue
civar = ivar[sel]
if np.any(civar<=0): continue
modrmap = civar.modrmap()
modlmap = civar.modlmap()
res = maps.resolution(civar.shape,civar.wcs)
cimap = result[sel]
print("Inpainted ", ra,dec)
if plots:
for p in range(3): io.plot_img(cimap[p],os.environ['WORK']+"/inpainted_cimap_%d_%s" % (p,str(i).zfill(2)))
return result
def create_ptsr_mask(nside, ascale=0.5, threshold=.0, radius=10., ptsr='base'):
# from catalogue
#ras, decs, size = np.loadtxt('data_local/input/cat_crossmatched.txt',unpack=True,usecols=(0,1,5))
#RAs = ras[size>threshold]
#DECs = decs[size>threshold]
#arcm = size[size>threshold] * extend
#RAs, DECs = interfaces.get_act_mr3f_union_sources(version='20200503_sncut_40')
RAs, DECs = interfaces.get_act_mr3f_union_sources(
version='20210209_sncut_10_aggressive')
arcm = np.ones(len(RAs)) * radius
# additional mask
if ptsr == 'PT':
RAs_add = np.array([187.3])
DECs_add = np.array([2.])
arcm_add = np.array([40.])
# add
RAs = np.concatenate((RAs, RAs_add))
DECs = np.concatenate((DECs, DECs_add))
arcm = np.concatenate((arcm, arcm_add))
# compute 3D positions
v = hp.pixelfunc.ang2vec(RAs, DECs, lonlat=True)
# create mask
maskpt = np.ones(12 * nside**2)
for i in range(len(arcm)):
pix = hp.query_disc(nside, v[i], arcm[i] * np.pi / 10800.)
maskpt[pix] = 0.
if ascale != 0.:
maskpt = curvedsky.utils.apodize(nside, maskpt, ascale)
return maskpt
print("Number of bright extended sources : ", len(eras))
bras, bdecs = sints.get_act_mr3f_cut_sources()
print("Number of bright cut sources : ", len(bras))
debug = False
rlim = 1.0
jras = np.append(eras, bras)
jdecs = np.append(edecs, bdecs)
ocat = merge_duplicates(jras * utils.degree,
jdecs * utils.degree,
rlim=rlim * utils.arcmin) / utils.degree
io.save_cols("union_catalog_06192019.csv", (ocat[:, 0], ocat[:, 1]),
delimiter=',',
header='ra(deg),dec(deg) | Made using actsims/bin/union_srcs.py.',
fmt='%.5f')
ras, decs = sints.get_act_mr3f_union_sources()
assert np.all(np.isclose(ras, ocat[:, 0]))
assert np.all(np.isclose(decs, ocat[:, 1]))
if debug:
xmin = -190
xmax = 190
ymin = -70
ymax = 35
s = 0.1
dpi = 100
plt.scatter(jras, jdecs, s=s, marker=',')
plt.xlim(xmin, xmax)
plt.ylim(ymin, ymax)
plt.savefig("scatter.png", dpi=dpi)
def inpaint_map_white(imap,ivar,fn_beam,union_sources_version=None,noise_pix = 40,hole_radius = 6.,plots=False,cache_name=None,verbose=True):
"""
Inpaints a map under the assumption of inhomogenous but white uncorrelated instrument noise.
Pros: no products needed other than map-maker outputs of map and ivar, good inpainting despite crappy
noise model.
Cons: noise model has to be built for each source, so this is actually quite slow.
imap -- (npol,Ny,Nx)
ivar -- (Ny,Nx)
fn_beam -- lambda ells: beam(ells)
cache_name -- a unique string identifying the catalog+map/array/frequency/split combination to/from which the geometries are cached
"""
if cache_name is not None:
cache_name = cache_name + "_catversion_%s" % union_sources_version
try:
ras,decs,gtags,pcoords,gdicts = load_cached_inpaint_geometries(cache_name)
do_geoms = False
if verbose: print("actsims.inpaint: loaded cached geometries for ", cache_name)
except:
if verbose: print("actsims.inpaint: no cached geometries found for ", cache_name, ". Generating and saving...")
do_geoms = True
else:
do_geoms = True
if do_geoms:
ras,decs = sints.get_act_mr3f_union_sources(version=union_sources_version)
cmb_theory_fn = lambda s,l: cosmology.default_theory().lCl(s,l)
gtags = []
gdicts = {}
pcoords = []
for i,(ra,dec) in enumerate(zip(ras,decs)):
sel = reproject.cutout(ivar, ra=np.deg2rad(ra), dec=np.deg2rad(dec), pad=1, corner=False,npix=noise_pix,return_slice=True)
if sel is None: continue
civar = ivar[sel]
if np.any(civar<=0): continue
modrmap = civar.modrmap()
modlmap = civar.modlmap()
res = maps.resolution(civar.shape,civar.wcs)
cimap = imap[sel]
if verbose: print("actsims.inpaint: built noise model for source ",i," / ",len(ras))
scov = pixcov.scov_from_theory(modlmap,cmb_theory_fn,fn_beam,iau=False)
ncov = pixcov.ncov_from_ivar(civar)
pcov = scov + ncov
gdicts[i] = pixcov.make_geometry(hole_radius=np.deg2rad(hole_radius/60.),n=noise_pix,deproject=True,iau=False,pcov=pcov,res=res)
pcoords.append(np.array((dec,ra)))
gtags.append(i)
if len(gtags)>0:
pcoords = np.stack(pcoords).swapaxes(0,1)
if cache_name is not None:
save_cached_inpaint_geometries(cache_name,ras,decs,gtags,pcoords,gdicts)
if verbose: print("actsims.inpaint: cached geometries for ",cache_name)
if len(gtags)>0: result = pixcov.inpaint(imap,pcoords,deproject=True,iau=False,geometry_tags=gtags,geometry_dicts=gdicts,verbose=verbose)
if plots:
for i,(ra,dec) in enumerate(zip(ras,decs)):
sel = reproject.cutout(ivar, ra=np.deg2rad(ra), dec=np.deg2rad(dec), pad=1, corner=False,npix=noise_pix,return_slice=True)
if sel is None: continue
civar = ivar[sel]
if np.any(civar<=0): continue
modrmap = civar.modrmap()
modlmap = civar.modlmap()
res = maps.resolution(civar.shape,civar.wcs)
cimap = imap[sel]
for p in range(3): io.plot_img(cimap[p],os.environ['WORK']+"/cimap_%d_%s" % (p,str(i).zfill(2)))
mimap = cimap.copy()
mimap[...,modrmap<np.deg2rad(hole_radius/60.)] = np.nan
for p in range(3): io.plot_img(mimap[p],os.environ['WORK']+"/masked_cimap_%d_%s" % (p,str(i).zfill(2)))
cimap = result[sel]
for p in range(3): io.plot_img(cimap[p],os.environ['WORK']+"/inpainted_cimap_%d_%s" % (p,str(i).zfill(2)))
return result