def objfunc(logim):
Frames = np.exp(logim.reshape((-1, N_pixel, N_pixel)))
if entropy == "simple":
s = np.sum(-mx.ssimple(Frames[i].ravel(), nprior_List[i]) for i in range(N_frame))
elif entropy == "l1":
s = np.sum(-mx.sl1(Frames[i].ravel(), nprior_List[i]) for i in range(N_frame))
elif entropy == "gs":
s = np.sum(-mx.sgs(Frames[i].ravel(), nprior_List[i]) for i in range(N_frame))
elif entropy == "tv":
s = np.sum(-mx.stv(Frames[i].ravel(), Prior_List[0].xdim, Prior_List[0].ydim) for i in range(N_frame))
chisq_total = np.sum(mx.chisq_bi(Frames[i].ravel(), A_List[i], bi_List[i], sigma_List[i]) for i in range(N_frame))/N_frame
s_dynamic = dynamic_regularizer(Frames, gauss)
t = np.sum( [ gamma * (np.sum(Frames[i].ravel()) - Flux_List[i])**2 for i in range(N_frame)] )/N_frame
return s + beta * s_dynamic + alpha * (chisq_total - 1.) + t
def objfunc(logim):
Frames = np.exp(logim.reshape((-1, N_pixel, N_pixel)))
if entropy == "simple":
s = np.sum(-mx.ssimple(Frames[i].ravel(), nprior_List[i]) for i in range(N_frame))
elif entropy == "l1":
s = np.sum(-mx.sl1(Frames[i].ravel(), nprior_List[i]) for i in range(N_frame))
elif entropy == "gs":
s = np.sum(-mx.sgs(Frames[i].ravel(), nprior_List[i]) for i in range(N_frame))
elif entropy == "tv":
s = np.sum(-mx.stv(Frames[i].ravel(), Prior_List[0].xdim, Prior_List[0].ydim) for i in range(N_frame))
chisq_total = np.sum(mx.chisq(Frames[i].ravel(), A_List[i], vis_List[i], sigma_List[i]) for i in range(N_frame))/N_frame
#print ("chisq_total ",chisq_total)
s_dynamic = dynamic_regularizer(Frames, gauss)
#print ("s_dynamic ",s_dynamic)
#return s_dynamic
return s + beta * s_dynamic + alpha * (chisq_total - 1.)