Exemple #1
0
def main():

    args = _parse_args()

    with_xhatshuffle = args.with_xhatshuffle
    with_lagrangian = args.with_lagrangian

    # This is multi-stage, so we need to supply node names
    hydro = PySPModel("./PySP/models/", "./PySP/nodedata/")
    rho_setter = None

    # Things needed for vanilla cylinders
    beans = (args, hydro.scenario_creator, hydro.scenario_denouement,
             hydro.all_scenario_names)

    # Vanilla PH hub
    hub_dict = vanilla.ph_hub(*beans,
                              ph_extensions=None,
                              rho_setter=rho_setter,
                              all_nodenames=hydro.all_nodenames)

    # Standard Lagrangian bound spoke
    if with_lagrangian:
        lagrangian_spoke = vanilla.lagrangian_spoke(
            *beans, rho_setter=rho_setter, all_nodenames=hydro.all_nodenames)

    if with_xhatshuffle:
        xhatshuffle_spoke = vanilla.xhatshuffle_spoke(*beans,
                                                      hydro.all_nodenames)

    list_of_spoke_dict = list()
    if with_lagrangian:
        list_of_spoke_dict.append(lagrangian_spoke)
    if with_xhatshuffle:
        list_of_spoke_dict.append(xhatshuffle_spoke)

    wheel = WheelSpinner(hub_dict, list_of_spoke_dict)
    wheel.spin()

    if wheel.global_rank == 0:  # we are the reporting hub rank
        print(
            f"BestInnerBound={wheel.BestInnerBound} and BestOuterBound={wheel.BestOuterBound}"
        )

    if write_solution:
        wheel.write_first_stage_solution('hydro_first_stage.csv')
        wheel.write_tree_solution('hydro_full_solution')

    hydro.close()
Exemple #2
0
def main():

    args = _parse_args()

    num_scen = args.num_scens

    with_fwph = args.with_fwph
    with_xhatlooper = args.with_xhatlooper
    with_xhatshuffle = args.with_xhatshuffle
    with_lagrangian = args.with_lagrangian
    with_fixer = args.with_fixer
    fixer_tol = args.fixer_tol
    with_cross_scenario_cuts = args.with_cross_scenario_cuts

    scensavail = [3, 5, 10, 25, 50, 100]
    if num_scen not in scensavail:
        raise RuntimeError("num-scen was {}, but must be in {}".\
                           format(num_scen, scensavail))

    scenario_creator_kwargs = {
        "scenario_count": num_scen,
        "path": str(num_scen) + "scenarios_r1",
    }
    scenario_creator = uc.scenario_creator
    scenario_denouement = uc.scenario_denouement
    all_scenario_names = [f"Scenario{i+1}" for i in range(num_scen)]
    rho_setter = uc._rho_setter

    # Things needed for vanilla cylinders
    beans = (args, scenario_creator, scenario_denouement, all_scenario_names)

    ### start ph spoke ###
    if args.run_aph:
        hub_dict = vanilla.aph_hub(
            *beans,
            scenario_creator_kwargs=scenario_creator_kwargs,
            ph_extensions=MultiExtension,
            rho_setter=rho_setter)
    else:
        hub_dict = vanilla.ph_hub(
            *beans,
            scenario_creator_kwargs=scenario_creator_kwargs,
            ph_extensions=MultiExtension,
            rho_setter=rho_setter)

    # Extend and/or correct the vanilla dictionary
    ext_classes = [Gapper]
    if with_fixer:
        ext_classes.append(Fixer)
    if with_cross_scenario_cuts:
        ext_classes.append(CrossScenarioExtension)
    if args.xhat_closest_tree:
        ext_classes.append(XhatClosest)

    hub_dict["opt_kwargs"]["extension_kwargs"] = {"ext_classes": ext_classes}
    if with_cross_scenario_cuts:
        hub_dict["opt_kwargs"]["options"]["cross_scen_options"]\
            = {"check_bound_improve_iterations" : args.cross_scenario_iter_cnt}

    if with_fixer:
        hub_dict["opt_kwargs"]["options"]["fixeroptions"] = {
            "verbose": args.with_verbose,
            "boundtol": fixer_tol,
            "id_fix_list_fct": uc.id_fix_list_fct,
        }
    if args.xhat_closest_tree:
        hub_dict["opt_kwargs"]["options"]["xhat_closest_options"] = {
            "xhat_solver_options": dict(),
            "keep_solution": True
        }

    if args.ph_mipgaps_json is not None:
        with open(args.ph_mipgaps_json) as fin:
            din = json.load(fin)
        mipgapdict = {int(i): din[i] for i in din}
    else:
        mipgapdict = None
    hub_dict["opt_kwargs"]["options"]["gapperoptions"] = {
        "verbose": args.with_verbose,
        "mipgapdict": mipgapdict
    }

    if args.default_rho is None:
        # since we are using a rho_setter anyway
        hub_dict.opt_kwargs.options["defaultPHrho"] = 1
    ### end ph spoke ###

    # FWPH spoke
    if with_fwph:
        fw_spoke = vanilla.fwph_spoke(
            *beans, scenario_creator_kwargs=scenario_creator_kwargs)

    # Standard Lagrangian bound spoke
    if with_lagrangian:
        lagrangian_spoke = vanilla.lagrangian_spoke(
            *beans,
            scenario_creator_kwargs=scenario_creator_kwargs,
            rho_setter=rho_setter)

    # xhat looper bound spoke
    if with_xhatlooper:
        xhatlooper_spoke = vanilla.xhatlooper_spoke(
            *beans, scenario_creator_kwargs=scenario_creator_kwargs)

    # xhat shuffle bound spoke
    if with_xhatshuffle:
        xhatshuffle_spoke = vanilla.xhatshuffle_spoke(
            *beans, scenario_creator_kwargs=scenario_creator_kwargs)

    # cross scenario cut spoke
    if with_cross_scenario_cuts:
        cross_scenario_cuts_spoke = vanilla.cross_scenario_cuts_spoke(
            *beans, scenario_creator_kwargs=scenario_creator_kwargs)

    list_of_spoke_dict = list()
    if with_fwph:
        list_of_spoke_dict.append(fw_spoke)
    if with_lagrangian:
        list_of_spoke_dict.append(lagrangian_spoke)
    if with_xhatlooper:
        list_of_spoke_dict.append(xhatlooper_spoke)
    if with_xhatshuffle:
        list_of_spoke_dict.append(xhatshuffle_spoke)
    if with_cross_scenario_cuts:
        list_of_spoke_dict.append(cross_scenario_cuts_spoke)

    wheel = WheelSpinner(hub_dict, list_of_spoke_dict)
    wheel.spin()

    if args.solution_dir is not None:
        wheel.write_tree_solution(args.solution_dir,
                                  uc.scenario_tree_solution_writer)

    wheel.write_first_stage_solution(
        'uc_cyl_nonants.npy',
        first_stage_solution_writer=sputils.first_stage_nonant_npy_serializer)
def main():

    args = _parse_args()

    BFs = args.branching_factors

    xhat_scenario_dict = make_node_scenario_dict_balanced(BFs)
    all_nodenames = list(xhat_scenario_dict.keys())

    with_xhatspecific = args.with_xhatspecific
    with_lagrangian = args.with_lagrangian
    with_xhatshuffle = args.with_xhatshuffle

    # This is multi-stage, so we need to supply node names
    #all_nodenames = ["ROOT"] # all trees must have this node
    # The rest is a naming convention invented for this problem.
    # Note that mpisppy does not have nodes at the leaves,
    # and node names must end in a serial number.

    ScenCount = np.prod(BFs)
    #ScenCount = _get_num_leaves(BFs)
    sc_options = {"args": args}
    scenario_creator_kwargs = aircond.kw_creator(sc_options)

    all_scenario_names = [f"scen{i}"
                          for i in range(ScenCount)]  #Scens are 0-based
    # print(all_scenario_names)
    scenario_creator = aircond.scenario_creator
    scenario_denouement = aircond.scenario_denouement
    primal_rho_setter = aircond.primal_rho_setter
    dual_rho_setter = aircond.dual_rho_setter

    # Things needed for vanilla cylinders
    beans = (args, scenario_creator, scenario_denouement, all_scenario_names)

    # Vanilla PH hub
    hub_dict = vanilla.ph_hub(*beans,
                              scenario_creator_kwargs=scenario_creator_kwargs,
                              ph_extensions=None,
                              rho_setter=primal_rho_setter,
                              all_nodenames=all_nodenames)

    # Standard Lagrangian bound spoke
    if with_lagrangian:
        lagrangian_spoke = vanilla.lagrangian_spoke(
            *beans,
            scenario_creator_kwargs=scenario_creator_kwargs,
            rho_setter=primal_rho_setter,
            all_nodenames=all_nodenames)

    # xhat specific bound spoke
    if with_xhatspecific:
        xhatspecific_spoke = vanilla.xhatspecific_spoke(
            *beans,
            xhat_scenario_dict,
            all_nodenames=all_nodenames,
            scenario_creator_kwargs=scenario_creator_kwargs)

    #xhat shuffle looper bound spoke

    if with_xhatshuffle:
        xhatshuffle_spoke = vanilla.xhatshuffle_spoke(
            *beans,
            all_nodenames=all_nodenames,
            scenario_creator_kwargs=scenario_creator_kwargs)
    list_of_spoke_dict = list()
    if with_lagrangian:
        list_of_spoke_dict.append(lagrangian_spoke)
    if with_xhatspecific:
        list_of_spoke_dict.append(xhatspecific_spoke)
    if with_xhatshuffle:
        list_of_spoke_dict.append(xhatshuffle_spoke)

    wheel = WheelSpinner(hub_dict, list_of_spoke_dict)
    wheel.spin()

    fname = 'aircond_cyl_nonants.npy'
    if wheel.global_rank == 0:
        print("BestInnerBound={} and BestOuterBound={}".\
              format(wheel.BestInnerBound, wheel.BestOuterBound))
        if write_solution:
            print(f"Writing first stage solution to {fname}")
    # all ranks need to participate because only the winner will write
    if write_solution:
        wheel.write_first_stage_solution('aircond_first_stage.csv')
        wheel.write_tree_solution('aircond_full_solution')
        wheel.write_first_stage_solution(
            fname,
            first_stage_solution_writer=first_stage_nonant_npy_serializer)
Exemple #4
0
def main():
    args = _parse_args()
    inst = args.instance_name
    num_scen = int(inst.split("-")[-3])
    if args.num_scens is not None and args.num_scens != num_scen:
        raise RuntimeError("Argument num-scens={} does not match the number "
                           "implied by instance name={} "
                           "\n(--num-scens is not needed for netdes)")

    with_fwph = args.with_fwph
    with_xhatlooper = args.with_xhatlooper
    with_xhatshuffle = args.with_xhatshuffle
    with_lagrangian = args.with_lagrangian
    with_slamup = args.with_slamup
    with_cross_scenario_cuts = args.with_cross_scenario_cuts

    if args.default_rho is None:
        raise RuntimeError("The --default-rho option must be specified")

    path = f"{netdes.__file__[:-10]}/data/{inst}.dat"
    scenario_creator = netdes.scenario_creator
    scenario_denouement = netdes.scenario_denouement
    all_scenario_names = [f"Scen{i}" for i in range(num_scen)]
    scenario_creator_kwargs = {"path": path}

    # Things needed for vanilla cylinders
    beans = (args, scenario_creator, scenario_denouement, all_scenario_names)

    if with_cross_scenario_cuts:
        ph_ext = CrossScenarioExtension
    else:
        ph_ext = None

    # Vanilla PH hub
    hub_dict = vanilla.ph_hub(*beans,
                              scenario_creator_kwargs=scenario_creator_kwargs,
                              ph_extensions=ph_ext,
                              rho_setter=None)

    if with_cross_scenario_cuts:
        hub_dict["opt_kwargs"]["options"]["cross_scen_options"]\
            = {"check_bound_improve_iterations" : args.cross_scenario_iter_cnt}

    # FWPH spoke
    if with_fwph:
        fw_spoke = vanilla.fwph_spoke(
            *beans, scenario_creator_kwargs=scenario_creator_kwargs)

    # Standard Lagrangian bound spoke
    if with_lagrangian:
        lagrangian_spoke = vanilla.lagrangian_spoke(
            *beans,
            scenario_creator_kwargs=scenario_creator_kwargs,
            rho_setter=None)

    # xhat looper bound spoke
    if with_xhatlooper:
        xhatlooper_spoke = vanilla.xhatlooper_spoke(
            *beans, scenario_creator_kwargs=scenario_creator_kwargs)

    # xhat shuffle bound spoke
    if with_xhatshuffle:
        xhatshuffle_spoke = vanilla.xhatshuffle_spoke(
            *beans, scenario_creator_kwargs=scenario_creator_kwargs)

    # slam up bound spoke
    if with_slamup:
        slamup_spoke = vanilla.slamup_spoke(
            *beans, scenario_creator_kwargs=scenario_creator_kwargs)

    # cross scenario cuts spoke
    if with_cross_scenario_cuts:
        cross_scenario_cuts_spoke = vanilla.cross_scenario_cuts_spoke(
            *beans, scenario_creator_kwargs=scenario_creator_kwargs)

    list_of_spoke_dict = list()
    if with_fwph:
        list_of_spoke_dict.append(fw_spoke)
    if with_lagrangian:
        list_of_spoke_dict.append(lagrangian_spoke)
    if with_xhatlooper:
        list_of_spoke_dict.append(xhatlooper_spoke)
    if with_xhatshuffle:
        list_of_spoke_dict.append(xhatshuffle_spoke)
    if with_slamup:
        list_of_spoke_dict.append(slamup_spoke)
    if with_cross_scenario_cuts:
        list_of_spoke_dict.append(cross_scenario_cuts_spoke)

    wheel = WheelSpinner(hub_dict, list_of_spoke_dict)
    wheel.spin()

    if write_solution:
        wheel.write_first_stage_solution('netdes_build.csv')
        wheel.write_tree_solution('netdes_full_solution')
Exemple #5
0
def main():

    args = _parse_args()

    num_scen = args.num_scens
    crops_multiplier = args.crops_mult

    rho_setter = farmer._rho_setter if hasattr(farmer, '_rho_setter') else None
    if args.default_rho is None and rho_setter is None:
        raise RuntimeError(
            "No rho_setter so a default must be specified via --default-rho")

    if args.use_norm_rho_converger:
        if not args.use_norm_rho_updater:
            raise RuntimeError(
                "--use-norm-rho-converger requires --use-norm-rho-updater")
        else:
            ph_converger = NormRhoConverger
    else:
        ph_converger = None

    scenario_creator = farmer.scenario_creator
    scenario_denouement = farmer.scenario_denouement
    all_scenario_names = ['scen{}'.format(sn) for sn in range(num_scen)]
    scenario_creator_kwargs = {
        'use_integer': False,
        "crops_multiplier": crops_multiplier,
    }
    scenario_names = [f"Scenario{i+1}" for i in range(num_scen)]

    # Things needed for vanilla cylinders
    beans = (args, scenario_creator, scenario_denouement, all_scenario_names)

    if args.run_async:
        # Vanilla APH hub
        hub_dict = vanilla.aph_hub(
            *beans,
            scenario_creator_kwargs=scenario_creator_kwargs,
            ph_extensions=None,
            rho_setter=rho_setter)
    else:
        # Vanilla PH hub
        hub_dict = vanilla.ph_hub(
            *beans,
            scenario_creator_kwargs=scenario_creator_kwargs,
            ph_extensions=None,
            ph_converger=ph_converger,
            rho_setter=rho_setter)

    ## hack in adaptive rho
    if args.use_norm_rho_updater:
        hub_dict['opt_kwargs']['extensions'] = NormRhoUpdater
        hub_dict['opt_kwargs']['options']['norm_rho_options'] = {
            'verbose': True
        }

    # FWPH spoke
    if args.with_fwph:
        fw_spoke = vanilla.fwph_spoke(
            *beans, scenario_creator_kwargs=scenario_creator_kwargs)

    # Standard Lagrangian bound spoke
    if args.with_lagrangian:
        lagrangian_spoke = vanilla.lagrangian_spoke(
            *beans,
            scenario_creator_kwargs=scenario_creator_kwargs,
            rho_setter=rho_setter)

    # xhat looper bound spoke
    if args.with_xhatlooper:
        xhatlooper_spoke = vanilla.xhatlooper_spoke(
            *beans, scenario_creator_kwargs=scenario_creator_kwargs)

    # xhat shuffle bound spoke
    if args.with_xhatshuffle:
        xhatshuffle_spoke = vanilla.xhatshuffle_spoke(
            *beans, scenario_creator_kwargs=scenario_creator_kwargs)

    list_of_spoke_dict = list()
    if args.with_fwph:
        list_of_spoke_dict.append(fw_spoke)
    if args.with_lagrangian:
        list_of_spoke_dict.append(lagrangian_spoke)
    if args.with_xhatlooper:
        list_of_spoke_dict.append(xhatlooper_spoke)
    if args.with_xhatshuffle:
        list_of_spoke_dict.append(xhatshuffle_spoke)

    wheel = WheelSpinner(hub_dict, list_of_spoke_dict)
    wheel.spin()

    if write_solution:
        wheel.write_first_stage_solution('farmer_plant.csv')
        wheel.write_first_stage_solution('farmer_cyl_nonants.npy',
                                         first_stage_solution_writer=sputils.
                                         first_stage_nonant_npy_serializer)
        wheel.write_tree_solution('farmer_full_solution')
Exemple #6
0
            'scenario_creator': scenario_creator,
            'scenario_denouement': scenario_denouement,
            "scenario_creator_kwargs": scenario_creator_kwargs
        },
    }

    lagrangian_spoke = {
        "spoke_class": LagrangianOuterBound,
        "spoke_kwargs": dict(),
        "opt_class": PHBase,   
        'opt_kwargs': {
            'options': hub_ph_options,
            'all_scenario_names': all_scenario_names,
            'scenario_creator': scenario_creator,
            "scenario_creator_kwargs": scenario_creator_kwargs,
            'scenario_denouement': scenario_denouement,
        },
    }

    list_of_spoke_dict = (ub_spoke, cut_spoke, ) #lagrangian_spoke)
    #list_of_spoke_dict = (ub_spoke, )

    wheel = WheelSpinner(hub_dict, list_of_spoke_dict)
    wheel.spin()

    if wheel.global_rank == 0:  # we are the reporting hub rank
        print(f"BestInnerBound={wheel.BestInnerBound} and BestOuterBound={wheel.BestOuterBound}")

    print("End time={} for global rank={}". \
          format(datetime.datetime.now(), global_rank))
Exemple #7
0
def main():
    start_time = dt.datetime.now()
    # start options
    casename = "pglib-opf-master/pglib_opf_case14_ieee.m"
    # pglib_opf_case3_lmbd.m
    # pglib_opf_case118_ieee.m
    # pglib_opf_case300_ieee.m
    # pglib_opf_case2383wp_k.m
    # pglib_opf_case2000_tamu.m
    # do not use pglib_opf_case89_pegase
    egret_path_to_data = "/thirdparty/"+casename
    number_of_stages = 3
    stage_duration_minutes = [5, 15, 30]
    if len(sys.argv) != number_of_stages + 3:
        print ("Usage: python ccop_multistage bf1 bf2 iters scenperbun(!) solver")
        exit(1)
    branching_factors = [int(sys.argv[1]), int(sys.argv[2])]
    PHIterLimit = int(sys.argv[3])
    scenperbun = int(sys.argv[4])
    solvername = sys.argv[5]

    seed = 1134
    a_line_fails_prob = 0.1
    repair_fct = FixFast
    verbose = False
    # end options
    # create an arbitrary xhat for xhatspecific to use
    xhat_dict = {"ROOT": "Scenario_1"}
    for i in range(branching_factors[0]):
        xhat_dict["ROOT_"+str(i)] = "Scenario_"+str(1 + i*branching_factors[1])

    scenario_creator_kwargs = {
        "convex_relaxation": True,
        "epath": egret_path_to_data,
    }
    if scenario_creator_kwargs["convex_relaxation"]:
        # for initialization solve
        solver = pyo.SolverFactory(solvername)
        scenario_creator_kwargs["solver"] = None
        ##if "gurobi" in solvername:
            ##solver.options["BarHomogeneous"] = 1
    else:
        solver = pyo.SolverFactory(solvername)
        if "gurobi" in solvername:
            solver.options["BarHomogeneous"] = 1
        scenario_creator_kwargs["solver"] = solver
    md_dict = _md_dict(scenario_creator_kwargs["epath"])

    if verbose:
        print("start data dump")
        print(list(md_dict.elements("generator")))
        for this_branch in md_dict.elements("branch"): 
            print("TYPE=",type(this_branch))
            print("B=",this_branch)
            print("IN SERVICE=",this_branch[1]["in_service"])
        print("GENERATOR SET=",md_dict.attributes("generator"))
        print("end data dump")

    lines = list()
    for this_branch in md_dict.elements("branch"):
        lines.append(this_branch[0])

    acstream = np.random.RandomState()
        
    scenario_creator_kwargs["etree"] = etree.ACTree(number_of_stages,
                                    branching_factors,
                                    seed,
                                    acstream,
                                    a_line_fails_prob,
                                    stage_duration_minutes,
                                    repair_fct,
                                    lines)
    scenario_creator_kwargs["acstream"] = acstream

    all_scenario_names=["Scenario_"+str(i)\
                        for i in range(1,len(scenario_creator_kwargs["etree"].\
                                             rootnode.ScenarioList)+1)]
    all_nodenames = scenario_creator_kwargs["etree"].All_Nodenames()

    options = dict()
    if scenario_creator_kwargs["convex_relaxation"]:
        options["solvername"] = solvername
        if "gurobi" in options["solvername"]:
            options["iter0_solver_options"] = {"BarHomogeneous": 1}
            options["iterk_solver_options"] = {"BarHomogeneous": 1}
        else:
            options["iter0_solver_options"] = None
            options["iterk_solver_options"] = None
    else:
        options["solvername"] = solvername  # needs to be ipopt
        options["iter0_solver_options"] = None
        options["iterk_solver_options"] = None
    options["PHIterLimit"] = PHIterLimit
    options["defaultPHrho"] = 1
    options["convthresh"] = 0.001
    options["subsolvedirectives"] = None
    options["verbose"] = False
    options["display_timing"] = False
    options["display_progress"] = True
    options["iter0_solver_options"] = None
    options["iterk_solver_options"] = None
    options["branching_factors"] = branching_factors

    # try to do something interesting for bundles per rank
    if scenperbun > 0:
        nscen = branching_factors[0] * branching_factors[1]
        options["bundles_per_rank"] = int((nscen / n_proc) / scenperbun)
    if global_rank == 0:
        appfile = "acopf.app"
        if not os.path.isfile(appfile):
            with open(appfile, "w") as f:
                f.write("datetime, hostname, BF1, BF2, seed, solver, n_proc")
                f.write(", bunperank, PHIterLimit, convthresh")
                f.write(", PH_IB, PH_OB")
                f.write(", PH_lastiter, PH_wallclock, aph_frac_needed")
                f.write(", APH_IB, APH_OB")
                f.write(", APH_lastiter, APH_wallclock")
        if "bundles_per_rank" in options:
            nbunstr = str(options["bundles_per_rank"])
        else:
            nbunstr = "0"
        oline = "\n"+ str(start_time)+","+socket.gethostname()
        oline += ","+str(branching_factors[0])+","+str(branching_factors[1])
        oline += ", "+str(seed) + ", "+str(options["solvername"])
        oline += ", "+str(n_proc) + ", "+ nbunstr
        oline += ", "+str(options["PHIterLimit"])
        oline += ", "+str(options["convthresh"])

        with open(appfile, "a") as f:
            f.write(oline)
        print(oline)


    # PH hub
    options["tee-rank0-solves"] = True
    hub_dict = {
        "hub_class": PHHub,
        "hub_kwargs": {"options": None},
        "opt_class": PH,
        "opt_kwargs": {
            "options": options,
            "all_scenario_names": all_scenario_names,
            "scenario_creator": pysp2_callback,
            'scenario_denouement': scenario_denouement,
            "scenario_creator_kwargs": scenario_creator_kwargs,
            "rho_setter": rho_setter.ph_rhosetter_callback,
            "extensions": None,
            "all_nodenames":all_nodenames,
        }
    }

    xhat_options = options.copy()
    xhat_options['bundles_per_rank'] = 0 #  no bundles for xhat
    xhat_options["xhat_specific_options"] = {"xhat_solver_options":
                                          options["iterk_solver_options"],
                                          "xhat_scenario_dict": xhat_dict,
                                          "csvname": "specific.csv"}

    ub2 = {
        'spoke_class': XhatSpecificInnerBound,
        "spoke_kwargs": dict(),
        "opt_class": Xhat_Eval,
        'opt_kwargs': {
            'options': xhat_options,
            'all_scenario_names': all_scenario_names,
            'scenario_creator': pysp2_callback,
            'scenario_denouement': scenario_denouement,
            "scenario_creator_kwargs": scenario_creator_kwargs,
            'all_nodenames': all_nodenames
        },
    }
    
    list_of_spoke_dict = [ub2]
    wheel_spinner = WheelSpinner(hub_dict, list_of_spoke_dict)
    wheel_spinner.spin()
    spcomm = wheel_spinner.spcomm
    if wheel_spinner.global_rank == 0:
        ph_end_time = dt.datetime.now()
        IB = wheel_spinner.BestInnerBound
        OB = wheel_spinner.BestOuterBound
        print("BestInnerBound={} and BestOuterBound={}".\
              format(IB, OB))
        with open(appfile, "a") as f:
            f.write(", "+str(IB)+", "+str(OB)+", "+str(spcomm.opt._PHIter))
            f.write(", "+str((ph_end_time - start_time).total_seconds()))
Exemple #8
0
def main():

    args = _parse_args()

    BFs = args.branching_factors
    if len(BFs) != 2:
        raise RuntimeError("Hydro is a three stage problem, so it needs 2 BFs")

    with_xhatshuffle = args.with_xhatshuffle
    with_lagrangian = args.with_lagrangian

    # This is multi-stage, so we need to supply node names
    all_nodenames = sputils.create_nodenames_from_branching_factors(BFs)

    ScenCount = BFs[0] * BFs[1]
    scenario_creator_kwargs = {"branching_factors": BFs}
    all_scenario_names = [f"Scen{i+1}" for i in range(ScenCount)]
    scenario_creator = hydro.scenario_creator
    scenario_denouement = hydro.scenario_denouement
    rho_setter = None

    # Things needed for vanilla cylinders
    beans = (args, scenario_creator, scenario_denouement, all_scenario_names)

    # Vanilla PH hub
    hub_dict = vanilla.ph_hub(*beans,
                              scenario_creator_kwargs=scenario_creator_kwargs,
                              ph_extensions=None,
                              rho_setter=rho_setter,
                              all_nodenames=all_nodenames,
                              spoke_sleep_time=SPOKE_SLEEP_TIME)

    # Standard Lagrangian bound spoke
    if with_lagrangian:
        lagrangian_spoke = vanilla.lagrangian_spoke(
            *beans,
            scenario_creator_kwargs=scenario_creator_kwargs,
            rho_setter=rho_setter,
            all_nodenames=all_nodenames,
            spoke_sleep_time=SPOKE_SLEEP_TIME)

    # xhat looper bound spoke

    if with_xhatshuffle:
        xhatshuffle_spoke = vanilla.xhatshuffle_spoke(
            *beans,
            all_nodenames=all_nodenames,
            scenario_creator_kwargs=scenario_creator_kwargs,
            spoke_sleep_time=SPOKE_SLEEP_TIME)

    list_of_spoke_dict = list()
    if with_lagrangian:
        list_of_spoke_dict.append(lagrangian_spoke)
    if with_xhatshuffle:
        list_of_spoke_dict.append(xhatshuffle_spoke)

    wheel = WheelSpinner(hub_dict, list_of_spoke_dict)
    wheel.spin()

    if wheel.global_rank == 0:  # we are the reporting hub rank
        print(
            f"BestInnerBound={wheel.BestInnerBound} and BestOuterBound={wheel.BestOuterBound}"
        )

    if write_solution:
        wheel.write_first_stage_solution('hydro_first_stage.csv')
        wheel.write_tree_solution('hydro_full_solution')