Simple disciplinary DOE example on the Sobieski SSBJ test case

from __future__ import annotations

from gemseo import configure_logger
from gemseo import create_discipline
from gemseo import create_scenario
from gemseo.problems.sobieski.core.design_space import SobieskiDesignSpace

configure_logger()

<RootLogger root (INFO)>

Instantiate the discipline

discipline = create_discipline("SobieskiMission")

Create the design space

design_space = SobieskiDesignSpace()
design_space.filter(["y_24", "y_34"])

Sobieski design space:

Name	Lower bound	Value	Upper bound	Type
y_24	0.44	4.15006276	11.13	float
y_34	0.44	1.10754577	1.98	float

Create the scenario

Build scenario which links the disciplines with the formulation and The DOE algorithm.

scenario = create_scenario(
    [discipline],
    "DisciplinaryOpt",
    "y_4",
    design_space,
    maximize_objective=True,
    scenario_type="DOE",
)

Execute the scenario

Here we use a latin hypercube sampling algorithm with 30 samples.

scenario.execute({"n_samples": 30, "algo": "lhs"})

    INFO - 09:00:52:
    INFO - 09:00:52: *** Start DOEScenario execution ***
    INFO - 09:00:52: DOEScenario
    INFO - 09:00:52:    Disciplines: SobieskiMission
    INFO - 09:00:52:    MDO formulation: DisciplinaryOpt
    INFO - 09:00:52: Optimization problem:
    INFO - 09:00:52:    minimize -y_4(y_24, y_34)
    INFO - 09:00:52:    with respect to y_24, y_34
    INFO - 09:00:52:    over the design space:
    INFO - 09:00:52:       +------+-------------+------------+-------------+-------+
    INFO - 09:00:52:       | Name | Lower bound |   Value    | Upper bound | Type  |
    INFO - 09:00:52:       +------+-------------+------------+-------------+-------+
    INFO - 09:00:52:       | y_24 |     0.44    | 4.15006276 |    11.13    | float |
    INFO - 09:00:52:       | y_34 |     0.44    | 1.10754577 |     1.98    | float |
    INFO - 09:00:52:       +------+-------------+------------+-------------+-------+
    INFO - 09:00:52: Solving optimization problem with algorithm lhs:
    INFO - 09:00:52:      3%|▎         | 1/30 [00:00<00:00, 253.22 it/sec, obj=-1.53e+3]
    INFO - 09:00:52:      7%|▋         | 2/30 [00:00<00:00, 414.31 it/sec, obj=-1.66e+3]
    INFO - 09:00:52:     10%|█         | 3/30 [00:00<00:00, 542.02 it/sec, obj=-832]
    INFO - 09:00:52:     13%|█▎        | 4/30 [00:00<00:00, 646.30 it/sec, obj=-1.62e+3]
    INFO - 09:00:52:     17%|█▋        | 5/30 [00:00<00:00, 726.21 it/sec, obj=-994]
    INFO - 09:00:52:     20%|██        | 6/30 [00:00<00:00, 796.54 it/sec, obj=-601]
    INFO - 09:00:52:     23%|██▎       | 7/30 [00:00<00:00, 856.40 it/sec, obj=-180]
    INFO - 09:00:52:     27%|██▋       | 8/30 [00:00<00:00, 907.59 it/sec, obj=-755]
    INFO - 09:00:52:     30%|███       | 9/30 [00:00<00:00, 949.06 it/sec, obj=-691]
    INFO - 09:00:52:     33%|███▎      | 10/30 [00:00<00:00, 986.83 it/sec, obj=-393]
    INFO - 09:00:52:     37%|███▋      | 11/30 [00:00<00:00, 1014.63 it/sec, obj=-362]
    INFO - 09:00:52:     40%|████      | 12/30 [00:00<00:00, 1043.79 it/sec, obj=-748]
    INFO - 09:00:52:     43%|████▎     | 13/30 [00:00<00:00, 1070.52 it/sec, obj=-719]
    INFO - 09:00:52:     47%|████▋     | 14/30 [00:00<00:00, 1094.77 it/sec, obj=-293]
    INFO - 09:00:52:     50%|█████     | 15/30 [00:00<00:00, 1114.28 it/sec, obj=-931]
    INFO - 09:00:52:     53%|█████▎    | 16/30 [00:00<00:00, 1133.96 it/sec, obj=-264]
    INFO - 09:00:52:     57%|█████▋    | 17/30 [00:00<00:00, 1147.87 it/sec, obj=-1.17e+3]
    INFO - 09:00:52:     60%|██████    | 18/30 [00:00<00:00, 1163.97 it/sec, obj=-495]
    INFO - 09:00:52:     63%|██████▎   | 19/30 [00:00<00:00, 1179.47 it/sec, obj=-189]
    INFO - 09:00:52:     67%|██████▋   | 20/30 [00:00<00:00, 1193.65 it/sec, obj=-2.23e+3]
    INFO - 09:00:52:     70%|███████   | 21/30 [00:00<00:00, 1205.29 it/sec, obj=-344]
    INFO - 09:00:52:     73%|███████▎  | 22/30 [00:00<00:00, 1217.30 it/sec, obj=-799]
    INFO - 09:00:52:     77%|███████▋  | 23/30 [00:00<00:00, 1226.08 it/sec, obj=-55.9]
    INFO - 09:00:52:     80%|████████  | 24/30 [00:00<00:00, 1236.67 it/sec, obj=-123]
    INFO - 09:00:52:     83%|████████▎ | 25/30 [00:00<00:00, 1247.01 it/sec, obj=-875]
    INFO - 09:00:52:     87%|████████▋ | 26/30 [00:00<00:00, 1254.64 it/sec, obj=-726]
    INFO - 09:00:52:     90%|█████████ | 27/30 [00:00<00:00, 1260.60 it/sec, obj=-69.6]
    INFO - 09:00:52:     93%|█████████▎| 28/30 [00:00<00:00, 1265.77 it/sec, obj=-1.51e+3]
    INFO - 09:00:52:     97%|█████████▋| 29/30 [00:00<00:00, 1271.00 it/sec, obj=-1.15e+3]
    INFO - 09:00:52:    100%|██████████| 30/30 [00:00<00:00, 1278.43 it/sec, obj=-2.73e+3]
    INFO - 09:00:52: Optimization result:
    INFO - 09:00:52:    Optimizer info:
    INFO - 09:00:52:       Status: None
    INFO - 09:00:52:       Message: None
    INFO - 09:00:52:       Number of calls to the objective function by the optimizer: 30
    INFO - 09:00:52:    Solution:
    INFO - 09:00:52:       Objective: -2726.3660548732214
    INFO - 09:00:52:       Design space:
    INFO - 09:00:52:          +------+-------------+--------------------+-------------+-------+
    INFO - 09:00:52:          | Name | Lower bound |       Value        | Upper bound | Type  |
    INFO - 09:00:52:          +------+-------------+--------------------+-------------+-------+
    INFO - 09:00:52:          | y_24 |     0.44    | 9.094543945649603  |    11.13    | float |
    INFO - 09:00:52:          | y_34 |     0.44    | 0.4769766573300308 |     1.98    | float |
    INFO - 09:00:52:          +------+-------------+--------------------+-------------+-------+
    INFO - 09:00:52: *** End DOEScenario execution (time: 0:00:00.037659) ***

{'eval_jac': False, 'n_samples': 30, 'algo': 'lhs'}

Plot optimization history view

scenario.post_process("OptHistoryView", save=False, show=True)

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<gemseo.post.opt_history_view.OptHistoryView object at 0x7f8ade6780d0>

Plot parallel coordinates

scenario.post_process(
    "ScatterPlotMatrix",
    variable_names=["y_4", "y_24", "y_34"],
    save=False,
    show=True,
)

<gemseo.post.scatter_mat.ScatterPlotMatrix object at 0x7f8ae33655e0>