Python evaluate_policyの例

コード例 #1

ファイル: test_mfg_model.py プロジェクト: gitter-badger/dolo

def test_mfg_model():

    from dolo import yaml_import

    # from dolo.algos.commands import time_iteration, simulate, evaluate_policy
    from dolo.algos.dtmscc.time_iteration import time_iteration
    from dolo.algos.dtmscc.value_iteration import evaluate_policy
    from dolo.algos.dtmscc.simulations import simulate, plot_decision_rule


    model = yaml_import("examples/models/sudden_stop.yaml")

    mdr = time_iteration(model)

    #
    sim = simulate(model, mdr, 0, horizon=50, n_exp=0) # irf
    assert(sim.shape==(50,6))
    sim = simulate(model, mdr, 0, horizon=50, n_exp=1) # one stochastic simulation
    assert(sim.shape==(50,6))
    sim = simulate(model, mdr, 0, horizon=50, n_exp=10) # many stochastic simulations
    assert(sim.shape==(10,50,6))


    mv = evaluate_policy(model, mdr, verbose=True, maxit=500)

    mv = evaluate_policy(model, mdr, verbose=True, maxit=500, initial_guess=mv)

    sim_v = simulate(model, mdr, 0, drv=mv, horizon=50, n_exp=10)
    sim_irf = simulate(model, mdr, 0, drv=mv, horizon=50, n_exp=0)

    sim_dr = plot_decision_rule(model, mdr, 'l')
    print(sim_dr)

コード例 #2

def test_mfg_model():

    from dolo import yaml_import

    # from dolo.algos.commands import time_iteration, simulate, evaluate_policy
    from dolo.algos.dtmscc.time_iteration import time_iteration
    from dolo.algos.dtmscc.value_iteration import evaluate_policy
    from dolo.algos.dtmscc.simulations import simulate, plot_decision_rule

    model = yaml_import("examples/models/compat/sudden_stop.yaml")
    print(model.exogenous)
    print(model.is_dtmscc())
    mdr = time_iteration(model)

    #
    sim = simulate(model, mdr, 0, horizon=50, n_exp=0)  # irf
    assert (sim.shape == (50, 6))
    sim = simulate(model, mdr, 0, horizon=50,
                   n_exp=1)  # one stochastic simulation
    assert (sim.shape == (50, 6))
    sim = simulate(model, mdr, 0, horizon=50,
                   n_exp=10)  # many stochastic simulations
    assert (sim.shape == (10, 50, 6))

    mv = evaluate_policy(model, mdr, verbose=True, maxit=500)

    mv = evaluate_policy(model, mdr, verbose=True, maxit=500, initial_guess=mv)

    sim_v = simulate(model, mdr, 0, drv=mv, horizon=50, n_exp=10)
    sim_irf = simulate(model, mdr, 0, drv=mv, horizon=50, n_exp=0)

    sim_dr = plot_decision_rule(model, mdr, 'l')
    print(sim_dr)

コード例 #3

ファイル: commands.py プロジェクト: gitter-badger/dolo

def evaluate_policy(model, *args, **kwargs):

    if model.model_type == 'dtmscc':
        from dolo.algos.dtmscc.value_iteration import evaluate_policy
    else:
        raise Exception("Model type {} not supported.".format(model.model_type))

    return evaluate_policy(model, *args, **kwargs)

コード例 #4

def evaluate_policy(model, *args, **kwargs):

    if model.model_type == 'dtmscc':
        from dolo.algos.dtmscc.value_iteration import evaluate_policy
    else:
        raise Exception("Model type {} not supported.".format(
            model.model_type))

    return evaluate_policy(model, *args, **kwargs)