def objgrad(logim):
Frames = np.exp(logim.reshape((-1, N_pixel, N_pixel)))
if entropy == "simple":
s = np.concatenate([-mx.ssimplegrad(Frames[i].ravel(), nprior_List[i])*Frames[i].ravel() for i in range(N_frame)])
elif entropy == "l1":
s = np.concatenate([-mx.sl1grad(Frames[i].ravel(), nprior_List[i])*Frames[i].ravel() for i in range(N_frame)])
elif entropy == "gs":
s = np.concatenate([-mx.sgsgrad(Frames[i].ravel(), nprior_List[i])*Frames[i].ravel() for i in range(N_frame)])
elif entropy == "tv":
s = np.concatenate([-mx.stvgrad(Frames[i].ravel(), Prior_List[0].xdim, Prior_List[0].ydim)*Frames[i].ravel() for i in range(N_frame)])
chisq_total_grad = np.concatenate([mx.chisqgrad_bi(Frames[i].ravel(), A_List[i], bi_List[i], sigma_List[i])*Frames[i].ravel()/N_frame for i in range(N_frame)])
s_dynamic_grad = dynamic_regularizer_gradient(Frames, gauss)
t = np.concatenate( [ 2.0 * gamma * (np.sum(Frames[i].ravel()) - Flux_List[i]) * Frames[i].ravel()/N_frame for i in range(N_frame)] )
return (s + beta * s_dynamic_grad + alpha * chisq_total_grad + t)
def objgrad(logim):
Frames = np.exp(logim.reshape((-1, N_pixel, N_pixel)))
if entropy == "simple":
s = np.concatenate([-mx.ssimplegrad(Frames[i].ravel(), nprior_List[i])*Frames[i].ravel() for i in range(N_frame)])
elif entropy == "l1":
s = np.concatenate([-mx.sl1grad(Frames[i].ravel(), nprior_List[i])*Frames[i].ravel() for i in range(N_frame)])
elif entropy == "gs":
s = np.concatenate([-mx.sgsgrad(Frames[i].ravel(), nprior_List[i])*Frames[i].ravel() for i in range(N_frame)])
elif entropy == "tv":
s = np.concatenate([-mx.stvgrad(Frames[i].ravel(), Prior_List[0].xdim, Prior_List[0].ydim)*Frames[i].ravel() for i in range(N_frame)])
#s = [grad for i in range(N_frame) for grad in -stvgrad(Frames[i].ravel(), Prior_List[0].xdim, Prior_List[0].ydim)*Frames[i].ravel()]
#s = np.concatenate(s)
chisq_total_grad = np.concatenate([mx.chisqgrad(Frames[i].ravel(), A_List[i], vis_List[i], sigma_List[i])*Frames[i].ravel()/N_frame for i in range(N_frame)])
s_dynamic_grad = dynamic_regularizer_gradient(Frames, gauss)
#return s_dynamic_grad
return (s + beta * s_dynamic_grad + alpha * chisq_total_grad)
