ellin, clkszin = np.loadtxt("data/clkszkk_lmax3000.csv",
delimiter=',',
unpack=True)
clkzfunc = interp1d(ellin, clkszin, bounds_error=False, fill_value=0.)
clksz = clkzfunc(frange)
clksz_bias = clksz * Clkk
sigCls = fidCls.copy() * 0.
sigCls[:, 4] = clksz_bias.copy()
# Calculate the Fisher matrix and add to other Fishers
cmbFisher = calcFisher(paramList,
ellrange,
fidCls,
dCls,
fnTT,
fnEE,
fnKK,
fsky,
verbose=True)
Fisher = otherFisher + cmbFisher
# Get prior sigmas and add to Fisher
priorList = Config.get("fisher", "priorList").split(',')
for prior, param in zip(priorList, paramList):
try:
priorSigma = float(prior)
except ValueError:
continue
ind = paramList.index(param)
Fisher[ind, ind] += 1. / priorSigma**2.
dCls = {}
for paramName in paramList:
dCls[paramName] = tryLoad(derivRoot+'_dCls_'+paramName+'.csv',',')
# Get CMB noise functions and ell ranges.
if (noise_func_tt is None) or (noise_func_ee is None):
fnTT, fnEE = noiseFromConfig(Config,expName,TCMB=TCMB,beamsOverride=None,noisesOverride=None,lkneeTOverride=None,lkneePOverride=None,alphaTOverride=None,alphaPOverride=None)
tellmin,tellmax = list_from_config(Config,expName,'tellrange')
pellmin,pellmax = list_from_config(Config,expName,'pellrange')
if (noise_func_tt is not None):
fnTT = cosmology.noise_pad_infinity(noise_func_tt,tellmin,tellmax)
if (noise_func_ee is not None):
fnEE = cosmology.noise_pad_infinity(noise_func_ee,pellmin,pellmax)
# Pad CMB lensing noise with infinity outside L ranges
kellmin,kellmax = list_from_config(Config,'lensing','Lrange')
fnKK = cosmology.noise_pad_infinity(interp1d(ls,Nls,fill_value=np.inf,bounds_error=False),kellmin,kellmax)
# 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,verbose=True)
np.savetxt(saveName,Fisher)
else:
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
if noLens:
Fisher = otherFisher + calcFisher(paramList,
ellrange,
fidCls,
dCls,
lambda x: fnTT(x) * TCMB**2.,
lambda x: fnEE(x) * TCMB**2.,
None,
fsky,
lensing=False,
verbose=True)
else:
Fisher = otherFisher + calcFisher(paramList,
ellrange,
fidCls,
dCls,
fnTT,
fnEE,
fnKK,
fsky,
lensing=True,
verbose=True)