# mpi barrier
comm.Barrier()
# init ctqmc impurity solver
ctqmc.cat_init_ctqmc(comm.rank, comm.size)
# setup hybridization function
# for the first iteration, we just use the default value
if i > 0: ctqmc.cat_set_hybf(size_t, hybf)
# exec ctqmc impurity solver
ctqmc.cat_exec_ctqmc(i + 1)
# get green's function
grnf = ctqmc.cat_get_grnf(size_t)
# get new hybridization function
hybf = do_dmft_loop(mfreq, norbs, grnf)
# get occupation number
nmat = ctqmc.cat_get_nmat(norbs)
# calculate new chemical potential
mune = mune + 0.3 * float(occup - sum(nmat))
# convergence analysis
grnf_s = (grnf + grnf_s) / 2.0
if comm.rank == 0:
print 'MAX_ERROR:', (numpy.absolute(grnf - grnf_s)).max()
print 'curr_mune:', mune, 'curr_occu:', sum(nmat), 'need_occu:', occup
# mpi barrier
comm.Barrier()
# init ctqmc impurity solver
ctqmc.cat_init_ctqmc(comm.rank, comm.size)
# setup hybridization function
# for the first iteration, we just use the default value
if i > 0: ctqmc.cat_set_hybf(size_t, hybf)
# exec ctqmc impurity solver
ctqmc.cat_exec_ctqmc(i+1)
# get green's function
grnf = ctqmc.cat_get_grnf(size_t)
# get new hybridization function
hybf = do_dmft_loop(mfreq, norbs, grnf)
# get occupation number
nmat = ctqmc.cat_get_nmat(norbs)
# calculate new chemical potential
mune = mune + 0.3 * float( occup - sum(nmat) )
# convergence analysis
grnf_s = (grnf + grnf_s) / 2.0
if comm.rank == 0:
print 'MAX_ERROR:', (numpy.absolute(grnf - grnf_s)).max()
print 'curr_mune:', mune, 'curr_occu:', sum(nmat), 'need_occu:', occup