Esempio n. 1
0
def mc(
        target_acceptance=0.25,
        tunable_param=0.1,
        density=0.85,
        cutoff=4,
        temperature=0.88,
        steps_per=int(1e6),
):
    box_length = 2 * cutoff
    file_app = "_a" + str(target_acceptance) + "_r" + str(cutoff)
    num_particles = int(density * box_length**3)
    print('num_particles', num_particles)
    print('target_acceptance', target_acceptance)
    print('tunable_param', tunable_param)

    monte_carlo = feasst.Prefetch(feasst.args({"steps_per_check": "10000000"}))
    monte_carlo.activate_prefetch(False)
    monte_carlo.set(lj_system(box_length=box_length, cutoff=cutoff))
    monte_carlo.set(
        feasst.MakeMetropolis(
            feasst.args({
                "beta": str(1. / temperature),
                "chemical_potential": "1.",
            })))
    monte_carlo.add(
        feasst.MakeTrialTranslate(
            feasst.args({
                "weight": "1.",
                "tunable_param": str(tunable_param),
                "tunable_target_acceptance": str(target_acceptance),
                "tunable_percent_change": "0.01",
                # "num_steps": "4",
                # "reference_index": "0",
            })))
    feasst.SeekNumParticles(num_particles).with_trial_add().run(monte_carlo)
    monte_carlo.add(
        feasst.MakeLog(
            feasst.args({
                "steps_per": str(steps_per),
                "file_name": "log" + file_app + ".txt",
                "clear_file": "true"
            })))
    monte_carlo.add(
        feasst.MakeCheckEnergy(
            feasst.args({
                "steps_per": str(steps_per),
                "tolerance": str(1e-8)
            })))
    monte_carlo.add(feasst.MakeTune(feasst.args({"steps_per":
                                                 str(steps_per)})))

    #equilibrate
    monte_carlo.attempt(int(1e7))

    if not args.nopipe:
        monte_carlo.activate_prefetch(True)
    monte_carlo.add(
        feasst.MakeMeanSquaredDisplacement(
            feasst.args({
                "steps_per_update": "10000",
                "updates_per_origin": "1000",
                "file_name": "msd" + file_app + ".txt",
                "steps_per_write": str(int(1e5))
            })))

    monte_carlo.add(
        feasst.MakeCPUTime(
            feasst.args({
                "steps_per_update": str(steps_per),
                "steps_per_write": str(steps_per),
                "file_name": "cpu" + file_app + ".txt",
            })))

    #h0 = feasst.cpu_hours()
    monte_carlo.attempt(int(1e8))
Esempio n. 2
0
def mc(
       trials_per=int(1e6),
       ):
    box_length = 2.*args.cutoff
    file_app = "_a" + str(args.rel_disp_prob) + "_rc" + str(args.cutoff)

    monte_carlo = feasst.Prefetch(feasst.args({"trials_per_check": str(int(1e7))}))
    monte_carlo.activate_prefetch(False)
    # monte_carlo.set(feasst.MakeRandomMT19937(feasst.args({"seed": "1578687129"})))
    monte_carlo.set(lj_system(box_length=box_length))
    monte_carlo.set(feasst.MakeMetropolis(feasst.args({
        "beta": str(1./args.temperature),
        "chemical_potential": str(args.chemical_potential),
    })))
    monte_carlo.add(feasst.MakeTrialTranslate(feasst.args({
        "weight": str(args.rel_disp_prob),
        "tunable_param": str(args.max_move),
        "tunable_target_acceptance": str(args.target_prob),
        "tunable_percent_change": "0.1",
    })))
    num_particles = int(args.density*box_length**3)
    nmin = num_particles - args.window_half_width
    nmax = num_particles + args.window_half_width
    if not args.nofh:
        feasst.SeekNumParticles(nmin).with_trial_add().run(monte_carlo)
    monte_carlo.add(feasst.MakeTrialTransfer(feasst.args({
        "weight": "1",
        "particle_type": "0"})))
    if not args.nofh:
        monte_carlo.set(fh.criteria_flathist(
            temperature=args.temperature,
            chemical_potential=args.chemical_potential,
            macro_max=nmax,
            macro_min=nmin,
            iterations=args.iterations,
            ))
        monte_carlo.add(feasst.MakeCriteriaUpdater(feasst.args({"trials_per": str(trials_per)})))
        monte_carlo.add(feasst.MakeCriteriaWriter(feasst.args(
            {"trials_per": str(trials_per), "file_name": "crit"+file_app+".txt"})))
    else:
        monte_carlo.add(feasst.MakeNumParticles(feasst.args({
            "file_name": "num"+file_app+".txt",
            "trials_per_write": str(trials_per),
        })))
    analyze.add(monte_carlo,
        trials_per,
        proc=file_app,
        log="log"+file_app+".txt",
        )

    if not args.nopara:
        monte_carlo.activate_prefetch(True)

    monte_carlo.add(feasst.MakeCPUTime(feasst.args({
        "trials_per_update": str(trials_per),
        "trials_per_write": str(trials_per),
        "file_name": "cpu" + file_app + ".txt",
    })))

    monte_carlo.add(feasst.MakeEnergy(feasst.args(
        {"file_name": "energy"+file_app+".txt",
         "trials_per_update": "1",
         "trials_per_write": str(trials_per),
         "multistate": "true"})))

    monte_carlo.set(feasst.MakeCheckpoint(feasst.args(
        {"file_name": "checkpoint"+file_app+".txt", "num_hours": "0.1"})))

    # run until complete is not pprefetched correctly
    monte_carlo.run_until_complete()