subplot(3,1,2) hist(aa[cut,1],bins=100,range=[-rr,rr],color='blue',alpha=0.2,label='All detectors:'+statstr(aa[cut,1])) hist(bb[covmin > 40,1],bins=100,range=[-rr,rr],color='red',alpha=0.2,label='Per detectors:'+statstr(bb[cut,1])) legend() subplot(3,1,3) hist(aa[cut,2],bins=100,range=[-rr,rr],color='blue',alpha=0.2,label='All detectors:'+statstr(aa[cut,2])) hist(bb[cut,2],bins=100,range=[-rr,rr],color='red',alpha=0.2,label='Per detectors:'+statstr(bb[cut,2])) legend() QUall=[output_maps_all[:,1],output_maps_all[:,2]] QUdet=[output_maps_det[:,1],output_maps_det[:,2]] QUall_spoiled=[output_maps_all_spoiled[:,1],output_maps_all_spoiled[:,2]] QUdet_spoiled=[output_maps_det_spoiled[:,1],output_maps_det_spoiled[:,2]] ### Get Rho and epsilon rho_all,eps_all=mm.rhoepsilon_from_maps(QUall,QUall_spoiled,goodpix=covmin>40) rho_det,eps_det=mm.rhoepsilon_from_maps(QUdet,QUdet_spoiled,goodpix=covmin>40) ################### Make a MC dtheta=15. npointings=5000 calerror=1e-2 rho_all=[] eps_all=[] rho_det=[] eps_det=[] nbmc=100 for n in np.arange(nbmc): print(' ') print(' ')