def explore_sigma(theparams, num, mini, maxi, prior=None): theprior=None if prior is not None: dum, dum, dum, dum, theprior, dum = Fisher.get_tratio_accuracy(params, prior[0], prior[1], prior[3], prior[2], der=der_nt, spectra=spectra_nt, consistency=False, fixed=1) nn=100 parvals = np.zeros((4,100)) parvals[0,:] += theparams[0] parvals[1,:] += theparams[1] parvals[2,:] += theparams[2] parvals[3,:] += theparams[3] x = linspace(mini,maxi,nn) parvals[num,:] = x s = np.zeros((3,nn)) s_svl = np.zeros((3,nn)) for i in np.arange(nn): a, b, dum, dum, fmnt, fmntsvl = Fisher.get_tratio_accuracy(params, parvals[0,i], parvals[1,i], parvals[3,i], parvals[2,i], der=der_nt, spectra=spectra_nt, consistency=False, fixed=1, prior=theprior) s[:,i]=a s_svl[:,i]=b return s, s_svl, x
scalar_amp = np.exp(3.098)/1.E10
omegav = h2 - omegab - omegac
Omegab = omegab/h2
Omegac = omegac/h2
rvalue = 0.2
print 'Omegab = ',omegab/h2,'Omegam = ',(omegac+omegab)/h2,'Omegav = ',omegav/h2
params = {'H0':H0,'omegab':Omegab,'omegac':Omegac,'omegak':0,'scalar_index':0.9624,
'reion__use_optical_depth':True,'reion__optical_depth':0.0925,
'tensor_ratio':rvalue,'WantTensors':True,'scalar_amp':scalar_amp,'DoLensing':False,
'tensor_index':-rvalue/8, 'lensing_amplitude':1.}
##### Fisher Analysis
## First run to get the derivatives and spectra
deltal = 25
s_nt, ssvl_nt, der_nt, spectra_nt, fmnt, fmntsvl = Fisher.get_tratio_accuracy(params, 1., 1., 0.5, 1.,
der=None, spectra = None, consistency = False, deltal=deltal)
# QUBIC
fsky = 0.01
mukarcmin = 4.
lens_res = 1
fwhmdeg = 0.52
squbic, s_svl, dum, dum, fmnt_qubic, fmntsvl_qubic = Fisher.get_tratio_accuracy(params, fsky, mukarcmin, fwhmdeg, lens_res,
der=der_nt, spectra=spectra_nt, deltal=deltal, consistency=False, plotmat=True, fixed=1)
# BICEP prediction should find s[0] ~ 0.05
fsky = 384/41000
fill_between(ell,(1+svfact)*cbbtot, ((1-svfact)*cbbtot).clip(min=1e-6), color='r', alpha=al)
a0,=plot(ell, cbbprim, 'b--', label='Primordial r=0.2',lw=3)
a1,=plot(ell, cbblensing, 'g--', label='Lensing',lw=3)
a2,=plot(ell, cbbtot, 'r', label='Total',lw=3)
yscale('log')
ylim(7e-4,0.1)
legend([a0,a1,a2],['Primordial r={0:.1g}'.format(rvalue), 'Lensing', 'Total'], loc='upper left')
xlabel('\ell')
ylabel('$\ell(\ell +1)C_\ell /2\pi$ $[\mu K^2]$')
title('B-modes with sample variance ($\Delta\ell=${0:.0f}, $f_s=${1:.2f})'.format(deltal,fsky))
savefig('bmodes.png')
##### Fisher Analysis
## First run to get the derivatives and spectra
s, ssvl, der, spectra, fmrt, fmrtsvl = Fisher.get_tratio_accuracy(params, 1., 1., 0.5, 1., der=None, spectra =None, consistency=True)
s_nt, ssvl_nt, der_nt, spectra_nt, fmnt, fmntsvl = Fisher.get_tratio_accuracy(params, 1., 1., 0.5, 1., der=None, spectra = None, consistency = False)
# BICEP prediction should find s[0] ~ 0.05
fsky = 384/41000
mukarcmin = 87/1000*60
lens_res = 1
fwhmdeg = 0.52
s, s_svl, dum, dum, fmnt_bicep, fmntsvl_bicep = Fisher.get_tratio_accuracy(params, fsky, mukarcmin, fwhmdeg, lens_res,
der=der_nt, spectra=spectra_nt, consistency=False, plotmat=True,fixed=1)
# QUBIC
fsky = 0.01
scalar_amp = np.exp(3.098)/1.E10
omegav = h2 - omegab - omegac
Omegab = omegab/h2
Omegac = omegac/h2
rvalue = 0.2
print 'Omegab = ',omegab/h2,'Omegam = ',(omegac+omegab)/h2,'Omegav = ',omegav/h2
params = {'H0':H0,'omegab':Omegab,'omegac':Omegac,'omegak':0,'scalar_index':0.9624,
'reion__use_optical_depth':True,'reion__optical_depth':0.0925,
'tensor_ratio':rvalue,'WantTensors':True,'scalar_amp':scalar_amp,'DoLensing':False,
'tensor_index':-rvalue/8, 'lensing_amplitude':1.}
##### Fisher Analysis
## First run to get the derivatives and spectra
deltal = 5
s_nt, ssvl_nt, der_nt, spectra_nt, fmnt, fmntsvl = Fisher.get_tratio_accuracy(params, 1., 1., 0.5, 1., der=None, spectra = None, consistency = False, deltal=deltal)
#### Assume a CMB stage 4 experiment
fsky = 0.5*0.8
mukarcmin = 1.
lens_res = 0.1
fwhmdeg = 3./60
stage4 = [fsky, mukarcmin, lens_res, fwhmdeg]
s_s4, s_s4_svl, dum, dum, fmnt_s4, fmntsvl_s4 = Fisher.get_tratio_accuracy(params, fsky, mukarcmin, fwhmdeg, lens_res, der=der_nt, spectra=spectra_nt, consistency=False, plotmat=True, fixed=1, title='CMBS4')
