'tensor_index':-rvalue/8}
rvalues = [0.01,0.05, 0.1, 0.2]
allder = []
allbasic_spec = []
for rr in rvalues:
################# satellites
pars = {'tensor_ratio':rr, 'tensor_index':-0.025, 'lensing_residual':1, 'scalar_index':0.9624}
varnames = {'tensor_ratio':'$r$', 'tensor_index':'$n_T$', 'lensing_residual':'$a_L$', 'scalar_index':'$n_S$'}
fsky=0.01
mukarcminT=1
fwhmdeg=0.1
fm, basic_spec, der, lcenter, data, error = CMBspectra.fisher_analysis(pars, fsky, mukarcminT, fwhmdeg, deltal=25)
nbins=len(data)/4
noT=False
noE=False
noTE=False
allder.append(der)
allbasic_spec.append(basic_spec)
fm_nsr_lrs = []
fm_nsr_stage4 = []
fm_nsr_lrs_stage4 = []
fm_nsr_hrs = []
fm_nsr_hrsplus = []
Omegac = omegac/h2
rvalue = 0.1
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}
################## First run to calculate derivatives
fsky = 384/41000
mukarcminT = 87/1000*60
fwhmdeg = 0.52
pars = {'tensor_ratio':0.2, 'tensor_index':-0.025, 'lensing_residual':1, 'scalar_index':0.9624}
varnames = {'tensor_ratio':'$r$', 'tensor_index':'$n_T$', 'lensing_residual':'$a_L$', 'scalar_index':'$n_S$'}
fm, basic_spec, der, lcenter, data, error = CMBspectra.fisher_analysis(pars, fsky, mukarcminT, fwhmdeg, deltal=25)
clf()
nbins = len(data)/4
yscale('log')
ylim(1e-4,1e4)
#xlim(0,np.max(lmax[mask]))
plot(basic_spec[0], basic_spec[1],'k', lw=2)
plot(basic_spec[0], basic_spec[2],'g', lw=2)
plot(basic_spec[0], np.abs(basic_spec[3]),'b', lw=2)
plot(basic_spec[0], basic_spec[4],'m', lw=2)
plot(basic_spec[0], basic_spec[5],'y', lw=2)
plot(basic_spec[0], basic_spec[4]+pars['lensing_residual']*basic_spec[5],'r', lw=2)
errorbar(lcenter, data[0*nbins:1*nbins], yerr=error[0*nbins:1*nbins], fmt='ko', alpha=0.6)
errorbar(lcenter, data[1*nbins:2*nbins], yerr=error[1*nbins:2*nbins], fmt='go', alpha=0.6)
errorbar(lcenter, np.abs(data[2*nbins:3*nbins]), yerr=error[2*nbins:3*nbins], fmt='bo', alpha=0.6)
