Basic history

In this example, we illustrate the use of the Gantt chart plot on the Sobieski’s SSBJ problem.

Import

The first step is to import some functions from the API and a method to get the design space.

from __future__ import division, unicode_literals

from gemseo.api import configure_logger, create_discipline, create_scenario
from gemseo.core.discipline import MDODiscipline
from gemseo.post.core.gantt_chart import create_gantt_chart
from gemseo.problems.sobieski.core import SobieskiProblem

configure_logger()

Out:

<RootLogger root (INFO)>

Create disciplines

Then, we instantiate the disciplines of the Sobieski’s SSBJ problem: Propulsion, Aerodynamics, Structure and Mission

disciplines = create_discipline(
    [
        "SobieskiPropulsion",
        "SobieskiAerodynamics",
        "SobieskiStructure",
        "SobieskiMission",
    ]
)

Create design space

We also read the design space from the SobieskiProblem.

design_space = SobieskiProblem().read_design_space()

Create and execute scenario

The next step is to build an MDO scenario in order to maximize the range, encoded ‘y_4’, with respect to the design parameters, while satisfying the inequality constraints ‘g_1’, ‘g_2’ and ‘g_3’. We can use the MDF formulation, the SLSQP optimization algorithm and a maximum number of iterations equal to 100.

scenario = create_scenario(
    disciplines,
    formulation="MDF",
    objective_name="y_4",
    maximize_objective=True,
    design_space=design_space,
)

for constraint in ["g_1", "g_2", "g_3"]:
    scenario.add_constraint(constraint, "ineq")

Activate time stamps

In order to record all time stamps recording, we have to call this method before the execution of the scenarios

MDODiscipline.activate_time_stamps()

scenario.execute({"algo": "SLSQP", "max_iter": 10})

Out:

    INFO - 09:25:12:
    INFO - 09:25:12: *** Start MDO Scenario execution ***
    INFO - 09:25:12: MDOScenario
    INFO - 09:25:12:    Disciplines: SobieskiPropulsion SobieskiAerodynamics SobieskiStructure SobieskiMission
    INFO - 09:25:12:    MDOFormulation: MDF
    INFO - 09:25:12:    Algorithm: SLSQP
    INFO - 09:25:12: Optimization problem:
    INFO - 09:25:12:    Minimize: -y_4(x_shared, x_1, x_2, x_3)
    INFO - 09:25:12:    With respect to: x_shared, x_1, x_2, x_3
    INFO - 09:25:12:    Subject to constraints:
    INFO - 09:25:12:       g_1(x_shared, x_1, x_2, x_3) <= 0.0
    INFO - 09:25:12:       g_2(x_shared, x_1, x_2, x_3) <= 0.0
    INFO - 09:25:12:       g_3(x_shared, x_1, x_2, x_3) <= 0.0
    INFO - 09:25:12: Design Space:
    INFO - 09:25:12: +----------+-------------+-------+-------------+-------+
    INFO - 09:25:12: | name     | lower_bound | value | upper_bound | type  |
    INFO - 09:25:12: +----------+-------------+-------+-------------+-------+
    INFO - 09:25:12: | x_shared |     0.01    |  0.05 |     0.09    | float |
    INFO - 09:25:12: | x_shared |    30000    | 45000 |    60000    | float |
    INFO - 09:25:12: | x_shared |     1.4     |  1.6  |     1.8     | float |
    INFO - 09:25:12: | x_shared |     2.5     |  5.5  |     8.5     | float |
    INFO - 09:25:12: | x_shared |      40     |   55  |      70     | float |
    INFO - 09:25:12: | x_shared |     500     |  1000 |     1500    | float |
    INFO - 09:25:12: | x_1      |     0.1     |  0.25 |     0.4     | float |
    INFO - 09:25:12: | x_1      |     0.75    |   1   |     1.25    | float |
    INFO - 09:25:12: | x_2      |     0.75    |   1   |     1.25    | float |
    INFO - 09:25:12: | x_3      |     0.1     |  0.5  |      1      | float |
    INFO - 09:25:12: +----------+-------------+-------+-------------+-------+
    INFO - 09:25:12: Optimization:   0%|          | 0/10 [00:00<?, ?it]
    INFO - 09:25:12: Optimization:  20%|██        | 2/10 [00:00<00:00, 40.81 it/sec, obj=536]
    INFO - 09:25:12: Optimization:  30%|███       | 3/10 [00:00<00:00, 20.72 it/sec, obj=2.12e+3]
    INFO - 09:25:13: Optimization:  40%|████      | 4/10 [00:00<00:00, 12.27 it/sec, obj=3.8e+3]
 WARNING - 09:25:13: Optimization found no feasible point !  The least infeasible point is selected.
    INFO - 09:25:13: Optimization:  40%|████      | 4/10 [00:01<00:00,  9.18 it/sec, obj=3.96e+3]
    INFO - 09:25:13: Optimization result:
    INFO - 09:25:13: Objective value = 3795.0851933441872
    INFO - 09:25:13: The result is not feasible.
    INFO - 09:25:13: Status: 8
    INFO - 09:25:13: Optimizer message: Positive directional derivative for linesearch
    INFO - 09:25:13: Number of calls to the objective function by the optimizer: 5
    INFO - 09:25:13: Constraints values w.r.t. 0:
    INFO - 09:25:13:    g_1 = [-0.01940553 -0.03430815 -0.04499528 -0.05244303 -0.05783964 -0.13706197
    INFO - 09:25:13:  -0.10293803]
    INFO - 09:25:13:    g_2 = 0.0003917260521535404
    INFO - 09:25:13:    g_3 = [-0.6301543  -0.3698457  -0.14096439 -0.18315803]
    INFO - 09:25:13: Design Space:
    INFO - 09:25:13: +----------+-------------+---------------------+-------------+-------+
    INFO - 09:25:13: | name     | lower_bound |        value        | upper_bound | type  |
    INFO - 09:25:13: +----------+-------------+---------------------+-------------+-------+
    INFO - 09:25:13: | x_shared |     0.01    | 0.06009793151303839 |     0.09    | float |
    INFO - 09:25:13: | x_shared |    30000    |        60000        |    60000    | float |
    INFO - 09:25:13: | x_shared |     1.4     |  1.400744940049757  |     1.8     | float |
    INFO - 09:25:13: | x_shared |     2.5     |         2.5         |     8.5     | float |
    INFO - 09:25:13: | x_shared |      40     |          70         |      70     | float |
    INFO - 09:25:13: | x_shared |     500     |         1500        |     1500    | float |
    INFO - 09:25:13: | x_1      |     0.1     |  0.3991428961174674 |     0.4     | float |
    INFO - 09:25:13: | x_1      |     0.75    |         0.75        |     1.25    | float |
    INFO - 09:25:13: | x_2      |     0.75    |         0.75        |     1.25    | float |
    INFO - 09:25:13: | x_3      |     0.1     |  0.1343078243802689 |      1      | float |
    INFO - 09:25:13: +----------+-------------+---------------------+-------------+-------+
    INFO - 09:25:13: *** MDO Scenario run terminated in 0:00:01.109535 ***

{'algo': 'SLSQP', 'max_iter': 10}

Post-process scenario

Lastly, we plot the Gantt chart.

create_gantt_chart(show=True, save=False)

# Finally, we deactivate the time stamps for other executions
MDODiscipline.deactivate_time_stamps()

Out:

/home/docs/checkouts/readthedocs.org/user_builds/gemseo/conda/3.1.0/lib/python3.8/site-packages/gemseo/post/core/gantt_chart.py:92: UserWarning: FixedFormatter should only be used together with FixedLocator
  ax.set_yticklabels(disc_names)