parnames = ['$r$','$n_s$', '$n_t$','$a_l$']
lim = [[0,0.5],[0.9,1],[0.,2]]
clf()
a1,l1 = Fisher.plot_fisher(fmnt_bicep, vals, parnames,'k',limits=lim,onesigma=True, fixed=2)
a0,l0 = Fisher.plot_fisher(fmnt_qubic, vals, parnames,'b',limits=lim,onesigma=True, fixed=2)
a2,l2 = Fisher.plot_fisher(fmnt_qubicnew, vals, parnames,'g',limits=lim,onesigma=True, fixed=2)
a3,l3 = Fisher.plot_fisher(fmnt_qubicnew6, vals, parnames,'r',limits=lim,onesigma=True, fixed=2)
subplot(3,3,3)
axis('off')
legend([a1,a0,a2,a3],['BICEP2 : '+l1, 'QUBIC 1 year, fsky=0.01 : '+l0,
'QUBIC 1 year, fsky={0:.2g} : '.format(fsky_reopt)+l2,
'QUBIC 6 modules, fsky={0:.2g} : '.format(fsky_reopt)+l3], fontsize=10)
#### get the correct matrix for r and ns
## fix nt
sub_fmnt_bicep = Fisher.submatrix(fmnt_bicep,[0,1,3])
sub_fmnt_qubic = Fisher.submatrix(fmnt_qubic,[0,1,3])
sub_fmnt_qubicnew = Fisher.submatrix(fmnt_qubicnew,[0,1,3])
sub_fmnt_qubicnew6 = Fisher.submatrix(fmnt_qubicnew6,[0,1,3])
## Marginalize over al and reverse order for having ns, r
cov_nsr_bicep = Fisher.submatrix(np.linalg.inv(sub_fmnt_bicep), [1,0])
cov_nsr_qubic = Fisher.submatrix(np.linalg.inv(sub_fmnt_qubic), [1,0])
cov_nsr_qubicnew = Fisher.submatrix(np.linalg.inv(sub_fmnt_qubicnew), [1,0])
cov_nsr_qubicnew6 = Fisher.submatrix(np.linalg.inv(sub_fmnt_qubicnew6), [1,0])
fm_nsr_bicep = np.linalg.inv(cov_nsr_bicep)
fm_nsr_qubic = np.linalg.inv(cov_nsr_qubic)
fm_nsr_qubicnew = np.linalg.inv(cov_nsr_qubicnew)
fm_nsr_qubicnew6 = np.linalg.inv(cov_nsr_qubicnew6)
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
fmnt_los4[1,1] = 1./errns**2
fmnt_lo[1,1] = 1./errns**2
fmnt_s4[1,1] = 1./errns**2
fmnt_sat[1,1] = 1./errns**2
fmnt_satplus[1,1] = 1./errns**2
#### get the correct matrix for r and ns
## fix nt
sub_fmnt_lo = Fisher.submatrix(fmnt_lo,[0,1,3])
sub_fmnt_s4 = Fisher.submatrix(fmnt_s4,[0,1,3])
sub_fmnt_los4 = Fisher.submatrix(fmnt_los4,[0,1,3])
sub_fmnt_sat = Fisher.submatrix(fmnt_sat,[0,1,3])
sub_fmnt_satplus = Fisher.submatrix(fmnt_satplus,[0,1,3])
## Marginalize over al and reverse order for having ns, r
cov_nsr_lo = Fisher.submatrix(np.linalg.inv(sub_fmnt_lo), [1,0])
cov_nsr_s4 = Fisher.submatrix(np.linalg.inv(sub_fmnt_s4), [1,0])
cov_nsr_los4 = Fisher.submatrix(np.linalg.inv(sub_fmnt_los4), [1,0])
cov_nsr_sat = Fisher.submatrix(np.linalg.inv(sub_fmnt_sat), [1,0])
cov_nsr_satplus = Fisher.submatrix(np.linalg.inv(sub_fmnt_satplus), [1,0])
fm_nsr_lo = np.linalg.inv(cov_nsr_lo)
fm_nsr_s4 = np.linalg.inv(cov_nsr_s4)
fm_nsr_los4 = np.linalg.inv(cov_nsr_los4)
