def __init__(self,full_sky_pix,wdeg,hdeg,yoffset,mpi_comm=None,nsims=1,lmax=7000,pix_intermediate=None,bin_lmax=3000):
self.dtype = np.float32
self.bin_edges = np.arange(80,bin_lmax,100)
self.fshape, self.fwcs = enmap.fullsky_geometry(res=full_sky_pix*np.pi/180./60., proj="car")
self.fshape = self.fshape[-2:]
self.shape = {}
self.wcs = {}
self.taper = {}
self.w2 = {}
self.w3 = {}
self.w4 = {}
self.pix_intermediate = full_sky_pix if (pix_intermediate is None) else pix_intermediate
self.wdeg = wdeg
self.hdeg = hdeg
degree = u.degree
vwidth = hdeg/2.
hwidth = wdeg/2.
self.pos_south=np.array([[-vwidth+yoffset,-hwidth],[vwidth+yoffset,hwidth]])*degree
self.pos_eq=np.array([[-vwidth,-hwidth],[vwidth,hwidth]])*degree
# Get MPI comm
self.comm = mpi_comm
try:
self.rank = mpi_comm.Get_rank()
self.numcores = mpi_comm.Get_size()
except:
self.rank = 0
self.numcores = 1
if self.rank==0:
self.logger = io.get_logger("rotrecon")
num_each,each_tasks = mpi_distribute(nsims,self.numcores)
self.mpibox = MPIStats(self.comm,num_each,tag_start=333)
if self.rank==0: self.logger.info( "At most "+ str(max(num_each)) + " tasks...")
self.tasks = each_tasks[self.rank]
theory_file_root = "data/Aug6_highAcc_CDM"
powspec_file = "data/Aug6_highAcc_CDM_lenspotentialCls.dat"
self.ps = powspec.read_camb_full_lens(powspec_file).astype(self.dtype)
self.theory = cmb.loadTheorySpectraFromCAMB(theory_file_root,unlensedEqualsLensed=False,
useTotal=False,TCMB = 2.7255e6,lpad=9000,get_dimensionless=False)
self.lmax = lmax
self.count = 0
l, beamells = np.loadtxt(beamPath, unpack=True, usecols=[0, 1])
cmbellmin = 100
cmbellmax = 3000
kellmin = 100
kellmax = 3000
#cambRoot = "/astro/u/msyriac/repos/cmb-lensing-projections/data/TheorySpectra/ell28k_highacc"
cambRoot = "/astro/u/msyriac/repos/actpLens/data/non-linear"
TCMB = 2.7255e6
#theory = loadTheorySpectraFromCAMB(cambRoot,unlensedEqualsLensed=False,useTotal=False,TCMB = TCMB,lpad=4000)
# !!!!!!!!!!!!! N2 bias
theory = loadTheorySpectraFromCAMB(cambRoot,
unlensedEqualsLensed=True,
useTotal=False,
TCMB=TCMB,
lpad=(cmbellmax + 500))
ellkk = np.arange(2, 9000, 1)
Clkk = theory.gCl("kk", ellkk)
N = int(sys.argv[1])
assert N % numcores == 0
num_each = (N / numcores)
startIndex = rank * num_each
endIndex = startIndex + num_each
myIs = range(N)[startIndex:endIndex]
noiseY = float(sys.argv[1])
tellminY = int(sys.argv[2])
pellminY = int(sys.argv[3])
#beamRange = np.arange(0.5,5.0,0.5)
beamRange = np.arange(5.0, 10.5, 0.5)
beamscale = lambda b: np.sqrt(8. * np.log(2.)) * 60. * 180. / np.pi / b
kmin = 40
deg = 10.
#px = 0.2
px = 0.5
dell = 10
theory = loadTheorySpectraFromCAMB(cambRoot,
unlensedEqualsLensed=False,
useTotal=False,
lpad=9000)
lmap = lm.makeEmptyCEATemplate(raSizeDeg=deg,
decSizeDeg=deg,
pixScaleXarcmin=px,
pixScaleYarcmin=px)
print((lmap.data.shape))
i = 0
for gradCut in [10000, 2000]:
myNls = NlGenerator(lmap, theory, gradCut=gradCut)
for polComb in ['TT', 'TE', 'EE', 'EB', 'ET', 'TB']:
for beamY in beamRange:
beamell = beamscale(beamY)
for tellmaxY, pellmaxY in [(3000, 5000), (beamell, beamell)]:
namells, namclkk = np.loadtxt("data/nam_clkk.csv", delimiter=',', unpack=True)
pl.add(namells, namclkk, marker="o", ls="none", color="C3")
cdmfile = "data/May21_matter2lens_WF_CDM_cut_ibarrier_iconc_fCls.csv"
fdmfile = "data/May21_matter2lens_WF_FDM_1.0_cut_ibarrier_iconc_fCls.csv"
lcdm, ckkcdm = np.loadtxt(cdmfile, unpack=True)
lfdm, ckkfdm = np.loadtxt(fdmfile, unpack=True)
pl.add(lcdm, ckkcdm, color="C4")
pl.add(lfdm, ckkfdm, color="C5")
for cambRoot, lab, col in zip(clist, lablist, colist):
theory = cmb.loadTheorySpectraFromCAMB(cambRoot,
unlensedEqualsLensed=False,
useTotal=False,
TCMB=2.7255e6,
lpad=lmax)
ls, Nls, ellbb, dlbb, efficiency, cc = lensNoise(
Config,
expName,
lensName,
beamOverride=None,
noiseTOverride=None,
lkneeTOverride=None,
lkneePOverride=None,
alphaTOverride=None,
alphaPOverride=None,
gradCut=2000,
deg=2.,
TCMB = 2.7255e6
hugeTemplate = lm.makeEmptyCEATemplate(degx,degy,pixScaleXarcmin=px,pixScaleYarcmin=px)
lxMap,lyMap,modLMap,thetaMap,lx,ly = fmaps.getFTAttributesFromLiteMap(hugeTemplate)
nfreq = modLMap.max()
assert nfreq>cmbellmax
assert nfreq>kellmax
from orphics.tools.cmb import loadTheorySpectraFromCAMB
cambRoot = os.environ['HOME']+"/repos/cmb-lensing-projections/data/TheorySpectra/ell28k_highacc"
theory = loadTheorySpectraFromCAMB(cambRoot,unlensedEqualsLensed=True,useTotal=False,TCMB = 2.7255e6,lpad=9000)
#theory = loadTheorySpectraFromCAMB(cambRoot,unlensedEqualsLensed=False,useTotal=False,TCMB = 2.7255e6,lpad=9000)
Nlfuncdict={}
Nlfuncdict['TT'] = cmb.get_noise_func(beamArcmin,noiseT,TCMB=TCMB)
Nlfuncdict['EE'] = cmb.get_noise_func(beamArcmin,noiseP,TCMB=TCMB)
Nlfuncdict['BB'] = cmb.get_noise_func(beamArcmin,noiseP,TCMB=TCMB)
print modLMap.shape
dlx = np.diff(lxMap,axis=1)[0,0]
dly = np.diff(lyMap,axis=0)[0,0]
Lmin = kellmin #10.
Lmax = kellmax #2000.
Nsims = 16
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
numcores = comm.Get_size()
Ntot = Nsims
num_each, each_tasks = mpi_distribute(Ntot, numcores)
mpibox = MPIStats(comm, num_each, tag_start=333)
if rank == 0: print(("At most ", max(num_each), " tasks..."))
my_tasks = each_tasks[rank]
theory_file_root = "data/Aug6_highAcc_CDM"
theory = cmb.loadTheorySpectraFromCAMB(theory_file_root,
unlensedEqualsLensed=False,
useTotal=False,
TCMB=2.7255e6,
lpad=9000,
get_dimensionless=False)
ells = np.arange(0, 7000, 1)
#pfunc = lambda x: theory.lCl('TT',x)
#pfunc = lambda x: x*0.+1.
pfunc = lambda x: x * 0. + (10. * np.pi / 180. / 60.)**2. #theory.gCl('kk',x)
ps = pfunc(ells).reshape((1, 1, 7000))
wdeg = 40.
hdeg = 15.
yoffset = 60.
pix = 0.5
lmax = 7000
fshape, fwcs = enmap.fullsky_geometry(res=pix * np.pi / 180. / 60., proj="car")
def theory_from_config(Config, theory_section, dimensionless=True):
sec_type = Config.get(theory_section, "cosmo_type")
lmax = Config.getint(theory_section, "lmax")
cc = None
if sec_type == "pycamb_params":
raise NotImplementedError
elif sec_type == "cluster":
from szar.counts import ClusterCosmology
with oio.nostdout():
with warnings.catch_warnings():
warnings.simplefilter("ignore")
logger.disabled = True
cc = ClusterCosmology(lmax=lmax,
pickling=True,
dimensionless=dimensionless)
theory = cc.theory
logger.disabled = False
elif sec_type == "default":
from orphics.theory.cosmology import Cosmology
with oio.nostdout():
with warnings.catch_warnings():
warnings.simplefilter("ignore")
logger.disabled = True
cc = Cosmology(lmax=lmax,
pickling=True,
dimensionless=dimensionless)
theory = cc.theory
logger.disabled = False
elif sec_type == "camb_file":
cc = None
import orphics.tools.cmb as cmb
file_root = Config.get(theory_section, "camb_file_root")
theory = cmb.loadTheorySpectraFromCAMB(file_root,
unlensedEqualsLensed=False,
useTotal=False,
TCMB=2.7255e6,
lpad=lmax,
get_dimensionless=dimensionless)
try:
cforce = Config.getboolean(theory_section, "cluster_force")
except:
cforce = False
if cforce:
from szar.counts import ClusterCosmology
cc = ClusterCosmology(skipCls=True, dimensionless=dimensionless)
cc.theory = theory
elif sec_type == "enlib_file":
import orphics.tools.cmb as cmb
file_root = Config.get(theory_section, "enlib_file_root")
theory = cmb.load_theory_spectra_from_enlib(
file_root, lpad=lmax, get_dimensionless=dimensionless)
cc = None
else:
print(sec_type)
raise ValueError
return theory, cc, lmax
