type=str,
default="./data/wi29.tsp",
help="specify a file which contains cities's information.")
parser.add_argument("--trotter_dim", type=int, default=10)
parser.add_argument("--ann_para",
type=float,
default=1.0,
help="initial annealing parameter")
parser.add_argument("--ann_step", type=int, default=1000)
parser.add_argument("--mc_step", type=int, default=5000)
parser.add_argument("--beta", type=float, default=float(36))
parser.add_argument("--reduc_para", type=float, default=0.999)
args = parser.parse_args()
# prepare annealer
anneal = qmc.QMC(args.trotter_dim, args.ann_para, args.ann_step,
args.mc_step, args.beta, args.reduc_para)
anneal.read(args.file)
anneal.calc_max_distance()
config_at_init_time = list(-np.ones(anneal.NCITY, dtype=np.int))
config_at_init_time[0] = 1
print("start...")
t0 = time.clock()
np.random.seed(100)
spin = anneal.getSpinConf(config_at_init_time)
LengthList = list()
for t in range(anneal.ANN_STEP):
for i in range(anneal.MC_STEP):
def run_qmc(config):
#construct wf
wavefunction = build_wf(config)
#run qmc
qmc.QMC(wavefunction, config).run()
return