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, consistency=False, plotmat=True, fixed=1)
ylim(0,0.04)
xlim(0,300)
savefig('qubicnow.png')
##### COmpare BICEP2 and QUBIC
vals = [rvalue, -0.025, 1.]
parnames = ['$r$','$n_t$','$a_l$']
lim = [[rvalue-0.1,rvalue+0.1],[0.,2]]
clf()
a1,l1 = Fisher.plot_fisher(fmnt_bicep, vals, parnames,'b',limits=lim,fixed=1)
a0,l0 = Fisher.plot_fisher(fmnt_qubic, vals, parnames,'r',limits=lim,fixed=1)
subplot(3,3,3)
axis('off')
legend([a1,a0],['BICEP2 : '+l1, 'QUBIC 1 year : '+l0])
savefig('compare_bicep2-qubic.png')
###### Optimizing limit on r with QUBIC by changing fsky ?
fskyvals = linspace(0.005, 0.1, 101)
s_r = np.zeros(len(fskyvals))
svl_r = np.zeros(len(fskyvals))
sn_r = np.zeros(len(fskyvals))
for i in np.arange(len(fskyvals)):
fsky = fskyvals[i]
mukarcmin = 4.*(fsky/0.01)**0.5
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, plotcl=True, fixed=[1,2])
ylim(0,0.04)
xlim(0,300)
savefig('qubicnow.png')
##### COmpare BICEP2 and QUBIC
vals = [rvalue, params['scalar_index'],-0.025, 1.]
parnames = ['$r$','$n_s$', '$n_t$','$a_l$']
lim = [[rvalue-0.1,rvalue+0.1],[0.,2]]
clf()
a1,l1 = Fisher.plot_fisher(fmnt_bicep, vals, parnames,'b',limits=lim,fixed=[1,2])
a0,l0 = Fisher.plot_fisher(fmnt_qubic, vals, parnames,'r',limits=lim,fixed=[1,2])
subplot(3,3,3)
axis('off')
legend([a1,a0],['BICEP2 : '+l1, 'QUBIC 1 year : '+l0])
###### Optimizing limit on r with QUBIC by changing fsky ?
fskyvals = linspace(0.005, 0.1, 101)
s_r = np.zeros(len(fskyvals))
svl_r = np.zeros(len(fskyvals))
sn_r = np.zeros(len(fskyvals))
for i in np.arange(len(fskyvals)):
fsky = fskyvals[i]
mukarcmin = 4.*(fsky/0.01)**0.5
print(mukarcmin)
fsky = 1.*0.8
mukarcmin = 0.5
lens_res = 0.1
fwhmdeg = 5./60
satplus = [fsky, mukarcmin, lens_res, fwhmdeg]
s_satplus, s_satplus_svl, dum, dum, fmnt_satplus, fmntsvl_satplus = Fisher.get_tratio_accuracy(params, fsky, mukarcmin, fwhmdeg, lens_res, der=der_nt, spectra=spectra_nt, consistency=False, plotmat=True, fixed=1, title='HRS++')
vals = [rvalue, 1., -rvalue/8, 1.]
parnames = ['$r$','$n_s$', '$n_t$','$a_l$']
lim = [[vals[0]-0.03,vals[0]+0.03],[vals[2]-0.1,vals[2]+0.1],[0.997,1.003]]
clf()
a1,l1 = Fisher.plot_fisher(fmnt_lo, vals, parnames,'g',limits=lim, fixed=1, onesigma=True)
a0,l0 = Fisher.plot_fisher(fmnt_s4, vals, parnames,'b',limits=lim, fixed=1, onesigma=True)
a3,l3 = Fisher.plot_fisher(fmnt_s4+fmnt_lo, vals, parnames,'r',limits=lim, fixed=1, onesigma=True)
a4,l4 = Fisher.plot_fisher(fmnt_sat, vals, parnames,'k',limits=lim, fixed=1, onesigma=True)
a5,l5 = Fisher.plot_fisher(fmnt_satplus, vals, parnames,'m',limits=lim, fixed=1, onesigma=True)
subplot(3,3,3)
axis('off')
legend([a1,a0,a3,a4,a5],['Low Res Sat : '+l1, 'CMB S4 : '+l0, 'Low Res Sat + CMB S4 : '+l3, 'High Res Sat : '+l4, 'High Res Sat ++: '+l5], fontsize=10,title='$r = ${0:.2g}'.format(rvalue))
savefig('compare_satellites_r{0:.2g}'.format(rvalue)+'.png')
######################### Various plots #####################
#### error on ns from Planck TT alone 0.9624 +/- 0.0094
errns = 0.0094
fmnt_los4 = fmnt_lo + fmnt_s4
