try:
ellee,nee = np.loadtxt(args.pp,usecols=[0,1],unpack=True)
noise_func_ee = interp1d(ellee,nee,bounds_error=False,fill_value=np.inf)
except:
noise_func_ee = None
TCMB = 2.7255e6
# Read config
iniFile = "input/params.ini"
Config = SafeConfigParser()
Config.optionxform=str
Config.read(iniFile)
ls,Nls,ellbb,dlbb,efficiency,cc = lensNoise(Config,expName,lensName,beamOverride=None,noiseTOverride=None,lkneeTOverride=None,lkneePOverride=None,alphaTOverride=None,alphaPOverride=None,noiseFuncT=noise_func_tt,noiseFuncP=noise_func_ee)
# File root name for Fisher derivatives
derivRoot = Config.get("fisher","derivRoot")
# Get list of parameters
paramList = Config.get("fisher","paramList").split(',')
# Load fiducials and derivatives
fidCls = tryLoad(derivRoot+'_fCls.csv',',')
dCls = {}
for paramName in paramList:
dCls[paramName] = tryLoad(derivRoot+'_dCls_'+paramName+'.csv',',')
# Get CMB noise functions and ell ranges.
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.,
px=0.1,
theoryOverride=theory,
bigell=lmax,
lensedEqualsUnlensed=False)
ells = np.arange(2, lmax, 1)
clkk = theory.gCl("kk", ells)
pl.add(ells, clkk, label=lab, ls="-", color=col)
pl.add(ls, Nls, label=lab + " Nl", ls="--", color=col)
ls, Nlslimit, ellbb, dlbb, efficiency, cc = lensNoise(
efficiencies = []
mnus = []
sns = []
rs = []
rdelens = []
if True:
# Get lensing noise curve. If you want to override something from the Config file in order to make plots varying it,
# change from None to the value you want.
ls, Nls, ellbb, dlbb, efficiency = lensNoise(Config,
expName,
lensName,
beamOverride=None,
noiseTOverride=None,
lkneeTOverride=None,
lkneePOverride=None,
alphaTOverride=None,
alphaPOverride=None)
efficiencies.append(efficiency)
printC("Delensing efficiency: " + str(efficiency) + " %",
color="green",
bold=True)
# File root name for Fisher derivatives
derivRoot = Config.get("fisher", "derivRoot")
# Get list of parameters
def fisher_from_config(fidCls,
dCls,
paramList,
Config,
expName,
lensName=None,
TCMB=2.7255e6,
beamsOverride=None,
noisesOverride=None,
lkneeTOverride=None,
lkneePOverride=None,
alphaTOverride=None,
alphaPOverride=None,
tellminOverride=None,
pellminOverride=None,
tellmaxOverride=None,
pellmaxOverride=None):
fnTT, fnEE = noiseFromConfig(Config, expName, TCMB, beamsOverride,
noisesOverride, lkneeTOverride,
lkneePOverride, alphaTOverride,
alphaPOverride, tellminOverride,
pellminOverride, tellmaxOverride,
pellmaxOverride)
tellmin, tellmax = list_from_config(Config, expName, 'tellrange')
pellmin, pellmax = list_from_config(Config, expName, 'pellrange')
if tellminOverride is not None: tellmin = tellminOverride
if tellmaxOverride is not None: tellmax = tellmaxOverride
if pellminOverride is not None: pellmin = pellminOverride
if pellmaxOverride is not None: pellmax = pellmaxOverride
if lensName is not None:
doLens = True
ls, Nls, ellbb, dlbb, efficiency, cc = lensNoise(
Config, expName, lensName, beamsOverride, noisesOverride,
lkneeTOverride, lkneePOverride, alphaTOverride, alphaPOverride)
# Pad CMB lensing noise with infinity outside L ranges
kellmin, kellmax = list_from_config(Config, lensName, 'Lrange')
fnKK = cosmo.noise_pad_infinity(
interp1d(ls, Nls, fill_value=np.inf, bounds_error=False), kellmin,
kellmax)
else:
doLens = False
fnKK = lambda x: np.nan
kellmin = np.inf
kellmax = -np.inf
# Decide on what ell range to calculate the Fisher matrix
ellrange = np.arange(min(tellmin, pellmin, kellmin),
max(tellmax, pellmax, kellmax)).astype(int)
# Get fsky
fsky = Config.getfloat(expName, 'fsky')
# Calculate the Fisher matrix and add to other Fishers
Fisher = calcFisher(paramList,
ellrange,
fidCls,
dCls,
lambda x: fnTT(x) * TCMB**2.,
lambda x: fnEE(x) * TCMB**2.,
fnKK,
fsky,
lensing=doLens,
verbose=True)
return Fisher
lpad=bigell) #,get_dimensionless=True)
#theoryOverride = None
tellmin, tellmax = list_from_config(Config, expName, 'tellrange')
pellmin, pellmax = list_from_config(Config, expName, 'pellrange')
px = np.round(180. / max(tellmax, pellmax) * 60. * 0.95, 2)
ls, Nls, ellbb, dclbb, efficiency, cc = lensNoise(
Config,
expName,
lensName,
beamOverride=None,
lkneeTOverride=None,
lkneePOverride=None,
alphaTOverride=None,
alphaPOverride=None,
deg=deg,
px=px,
gradCut=gradCut,
bigell=bigell,
theoryOverride=theoryOverride,
noiseFuncT=None,
noiseFuncP=None,
nIter=nIter)
kellmin, kellmax = list_from_config(Config, lensName, 'Lrange')
fnKK = cosmo.noise_pad_infinity(
interp1d(ls, Nls, fill_value=np.inf, bounds_error=False), kellmin, kellmax)
Lrange = np.arange(kellmin, kellmax)
#np.savetxt(outDir+'nlkk'+iterName+'.csv',np.vstack([Lrange,fnKK(Lrange)]).T)
cprint("Delensing efficiency: " + str(efficiency) + " %",
# Read config
iniFile = "input/params.ini"
Config = SafeConfigParser()
Config.optionxform = str
Config.read(iniFile)
px = 180 * 60 / 60000.
gradCut = 60000.
expName = "DM-18arcsec"
lensName = "lensing"
ls, Nls, ellbb, dlbb, efficiency = lensNoise(Config,
expName,
lensName,
px=px,
gradCut=gradCut,
bigell=gradCut,
plot=True)
print efficiency
print ls
print Nls
from orphics.tools.io import Plotter
pl = Plotter(scaleY='log')
pl.add(ls, Nls)
pl._ax.set_ylim(1e-12, 1e-6)
#pl._ax.set_xlim(2,4000)
pl.done("nls.png")