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(' ')
