# chain_F_r_dl_b = data4mcmc.readchains(rep+'instrumentF_r_dl_b.db') # rep = 'ChainsSites/Atacama/' # site = 'Atacama' # chain_A_r_dl_b = data4mcmc.readchains(rep+'instrumentAa_r_dl_b.db') # chain_B_r_dl_b = data4mcmc.readchains(rep+'instrumentBa_r_dl_b.db') # chain_C_r_dl_b = data4mcmc.readchains(rep+'instrumentCa_r_dl_b.db') # chain_D_r_dl_b = data4mcmc.readchains(rep+'instrumentDa_r_dl_b.db') # chain_E_r_dl_b = data4mcmc.readchains(rep+'instrumentEa_r_dl_b.db') # chain_F_r_dl_b = data4mcmc.readchains(rep+'instrumentFa_r_dl_b.db') ####### Chains for ANR 2015 simulations rep = '/Users/hamilton/CMB/Interfero/DualBand/SimsANR2015/' chain_A_r_dl_b = data4mcmc.readchains(rep+'instrumentA_r_dl_b.db') chain_B_r_dl_b = data4mcmc.readchains(rep+'instrumentB_r_dl_b.db') chain_C_r_dl_b = data4mcmc.readchains(rep+'instrumentC_r_dl_b.db') chain_D_r_dl_b = data4mcmc.readchains(rep+'instrumentD_r_dl_b.db') chain_nofg_r = data4mcmc.readchains(rep+'instrumentNofg_r.db') def upperlimit(chain,key,level=0.95): sorteddata = np.sort(chain[key]) return sorteddata[level*len(sorteddata)] truer = 0. truebeta = 1.59
truer = 0. truebeta = 1.59 truedl = 13.4 * 0.45 truealpha = -2.42 trueT = 19.6 level =0.95 cl = int(level*100) ####### Chains for ANR 2015 simulations rep = '/Users/hamilton/CMB/Interfero/DualBand/SimsANR2015/' site = 'Concordia' config = ' $(\epsilon=1)$ ' chain_A_r_dl_b = data4mcmc.readchains(rep+'instrumentA_r_dl_b.db') chain_B_r_dl_b = data4mcmc.readchains(rep+'instrumentB_r_dl_b.db') chain_C_r_dl_b = data4mcmc.readchains(rep+'instrumentC_r_dl_b.db') chain_D_r_dl_b = data4mcmc.readchains(rep+'instrumentD_r_dl_b.db') chain_nofg_r = data4mcmc.readchains(rep+'instrumentNofg_r.db') ########### r dl and beta figure(0) sm=3 histn=3 alpha =0.5 nbins=100 from scipy.ndimage import gaussian_filter1d bla = np.histogram(chain_nofg_r['r'],bins=nbins,normed=True) xhist=(bla[1][0:nbins]+bla[1][1:nbins+1])/2
