Logging

import numpy as np
from matplotlib import pyplot as plt

from smt_optim.benchmarks.registry import get_problem

from smt_optim.core import Driver, ObjectiveConfig, ConstraintConfig, DriverConfig, Problem

from smt_optim.surrogate_models.smt import SmtAutoModel

from smt_optim.acquisition_strategies import MFSEGO

problem = get_problem("Branin1")

obj_config = ObjectiveConfig(
    objective=[problem.objective[-1]],
    type="minimize",
    surrogate=SmtAutoModel,           # set which GP to model the objective
)

prob_definition = Problem(
    obj_configs=[obj_config],
    design_space=problem.bounds
)

Verbose

driver_config = DriverConfig(
    max_iter = 10,              # stopping criterion
    nt_init = 5,                # number of sample in the initial DoE
    scaling = True,             # standardize every QoI
    seed=42,
    verbose = True,
)

# configure the optimizer
driver = Driver(prob_definition, driver_config, MFSEGO)

# start optimization
state = driver.optimize()

          iter         budget           fmin       fidelity        gp_time       acq_time
             1              6    7.30174e+00              1          0.204          0.296
             2              7    7.30174e+00              1          0.315          0.253
             3              8    7.30174e+00              1          0.301          0.207
             4              9    6.62931e+00              1          0.317          0.348
             5             10    4.83559e+00              1          0.332          0.318
             6             11    4.83559e+00              1          0.301          0.335
             7             12    1.73269e+00              1          0.303          0.453
             8             13    1.34048e+00              1          0.326          0.428
             9             14    1.07063e+00              1          0.314          0.389
            10             15    1.07063e+00              1          0.331          0.411

Logging the DoE

driver_config = DriverConfig(
    max_iter = 5,              # stopping criterion
    nt_init = 5,                # number of sample in the initial DoE
    scaling = True,             # standardize every QoI
    seed=42,
    verbose = True,
    log_doe = True,
)

# configure the optimizer
driver = Driver(prob_definition, driver_config, MFSEGO)

# start optimization
state = driver.optimize()

          iter         budget           fmin       fidelity        gp_time       acq_time
             1              6    7.30174e+00              1          0.207          0.327
             2              7    7.30174e+00              1          0.355          0.257
             3              8    7.30174e+00              1          0.323          0.229
             4              9    6.62931e+00              1          0.322          0.390
             5             10    4.83559e+00              1          0.348          0.304

Logging statistics

driver_config = DriverConfig(
    max_iter = 5,              # stopping criterion
    nt_init = 5,                # number of sample in the initial DoE
    scaling = True,             # standardize every QoI
    seed=42,
    verbose = True,
    log_doe = True,
    log_stats = True,
)

# configure the optimizer
driver = Driver(prob_definition, driver_config, MFSEGO)

# start optimization
state = driver.optimize()

          iter         budget           fmin       fidelity        gp_time       acq_time
             1              6    7.30174e+00              1          0.207          0.293
             2              7    7.30174e+00              1          0.319          0.260
             3              8    7.30174e+00              1          0.308          0.208
             4              9    6.62931e+00              1          0.316          0.282
             5             10    4.83559e+00              1          0.321          0.353