def recon_from_config(Config,
recon_section,
parray,
theory,
lmax,
grad_cut=None,
pol=False,
u_equals_l=True):
min_ell = fmaps.minimum_ell(parray.shape, parray.wcs)
lb = ellbounds_from_config(Config, recon_section, min_ell)
tellmin = lb['tellminY']
tellmax = lb['tellmaxY']
pellmin = lb['pellminY']
pellmax = lb['pellmaxY']
kellmin = lb['kellmin']
kellmax = lb['kellmax']
lxmap_dat, lymap_dat, modlmap_dat, angmap_dat, lx_dat, ly_dat = fmaps.get_ft_attributes_enmap(
parray.shape, parray.wcs)
template_dat = fmaps.simple_flipper_template_from_enmap(
parray.shape, parray.wcs)
nT = parray.nT
nP = parray.nP
kbeam_dat = parray.lbeam
fMaskCMB_T = fmaps.fourierMask(lx_dat,
ly_dat,
modlmap_dat,
lmin=tellmin,
lmax=tellmax)
fMaskCMB_P = fmaps.fourierMask(lx_dat,
ly_dat,
modlmap_dat,
lmin=pellmin,
lmax=pellmax)
fMask = fmaps.fourierMask(lx_dat,
ly_dat,
modlmap_dat,
lmin=kellmin,
lmax=kellmax)
with oio.nostdout():
from alhazen.quadraticEstimator import Estimator
qest = Estimator(template_dat,
theory,
theorySpectraForNorm=None,
noiseX2dTEB=[nT, nP, nP],
noiseY2dTEB=[nT, nP, nP],
fmaskX2dTEB=[fMaskCMB_T, fMaskCMB_P, fMaskCMB_P],
fmaskY2dTEB=[fMaskCMB_T, fMaskCMB_P, fMaskCMB_P],
fmaskKappa=fMask,
kBeamX=kbeam_dat,
kBeamY=kbeam_dat,
doCurl=False,
TOnly=not (pol),
halo=True,
uEqualsL=u_equals_l,
gradCut=grad_cut,
bigell=lmax)
return tellmin, tellmax, pellmin, pellmax, kellmin, kellmax, qest
def _init_qests(self):
mlist = ['e','s','r']
self.qest = {}
tellminY = 500
tellmaxY = 3000
pellminY = 500
pellmaxY = 3000
tellminX = 500
tellmaxX = 3000
pellminX = 500
pellmaxX = 3000
kellmin = 80
kellmax = 3000
self.kellmin = kellmin
self.kellmax = kellmax
for m in mlist:
lxmap_dat,lymap_dat,modlmap_dat,angmap_dat,lx_dat,ly_dat = fmaps.get_ft_attributes_enmap(self.shape[m],self.wcs[m])
nT = modlmap_dat.copy()*0.
nP = modlmap_dat.copy()*0.
lbeam = modlmap_dat.copy()*0.+1.
template_dat = fmaps.simple_flipper_template_from_enmap(self.shape[m],self.wcs[m])
fMaskCMB_TX = fmaps.fourierMask(lx_dat,ly_dat,modlmap_dat,lmin=tellminX,lmax=tellmaxX)
fMaskCMB_TY = fmaps.fourierMask(lx_dat,ly_dat,modlmap_dat,lmin=tellminY,lmax=tellmaxY)
fMaskCMB_PX = fmaps.fourierMask(lx_dat,ly_dat,modlmap_dat,lmin=pellminX,lmax=pellmaxX)
fMaskCMB_PY = fmaps.fourierMask(lx_dat,ly_dat,modlmap_dat,lmin=pellminY,lmax=pellmaxY)
fMask = fmaps.fourierMask(lx_dat,ly_dat,modlmap_dat,lmin=kellmin,lmax=kellmax)
with io.nostdout():
self.qest[m] = Estimator(template_dat,
self.theory,
theorySpectraForNorm=None,
noiseX2dTEB=[nT,nP,nP],
noiseY2dTEB=[nT,nP,nP],
fmaskX2dTEB=[fMaskCMB_TX,fMaskCMB_PX,fMaskCMB_PX],
fmaskY2dTEB=[fMaskCMB_TY,fMaskCMB_PY,fMaskCMB_PY],
fmaskKappa=fMask,
kBeamX = lbeam,
kBeamY = lbeam,
doCurl=False,
TOnly=True,
halo=True,
uEqualsL=True,
gradCut=None,verbose=False,
bigell=self.lmax)
import numpy as np
import sys, os, glob
from orphics.analysis.pipeline import mpi_distribute, MPIStats, SpectrumVerification
import orphics.tools.stats as stats
import alhazen.io as aio
import orphics.tools.io as io
import orphics.analysis.flatMaps as fmaps
import warnings
import logging
logger = logging.getLogger()
with io.nostdout():
with warnings.catch_warnings():
warnings.simplefilter("ignore")
from enlib import enmap, lensing, resample
from alhazen.quadraticEstimator import Estimator
import alhazen.lensTools as lt
from configparser import SafeConfigParser
from szar.counts import ClusterCosmology
import enlib.fft as fftfast
import argparse
from mpi4py import MPI
# Get MPI comm
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
numcores = comm.Get_size()
out_dir = "./"
analysis_section = "analysis"
sim_section = "sims"
expf_name = "experiment_noiseless"
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
