Note
Go to the end to download the full example code.
Radar chart#
In this example, we illustrate the use of the
RadarChart plot
on the Sobieski's SSBJ problem.
from __future__ import annotations
from gemseo import configure_logger
from gemseo import create_discipline
from gemseo import create_scenario
from gemseo.problems.mdo.sobieski.core.design_space import SobieskiDesignSpace
Import#
The first step is to import some functions from the API and a method to get the design space.
configure_logger()
<RootLogger root (INFO)>
Description#
The RadarChart post-processing
plots on a radar style chart a list of constraint functions
at a given iteration.
By default, the last iteration is used. This plot scales better with the number of constraints than the constraint plot provided by the opt_history_view.
Create disciplines#
At this point, we instantiate the disciplines of Sobieski's SSBJ problem: Propulsion, Aerodynamics, Structure and Mission
disciplines = create_discipline([
"SobieskiPropulsion",
"SobieskiAerodynamics",
"SobieskiStructure",
"SobieskiMission",
])
Create design space#
We also create the SobieskiDesignSpace.
design_space = SobieskiDesignSpace()
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,
"y_4",
design_space,
formulation_name="MDF",
maximize_objective=True,
)
scenario.set_differentiation_method()
for constraint in ["g_1", "g_2", "g_3"]:
scenario.add_constraint(constraint, constraint_type="ineq")
scenario.execute(algo_name="SLSQP", max_iter=10)
WARNING - 08:38:50: Unsupported feature 'minItems' in JSONGrammar 'SobieskiMission_discipline_output' for property 'y_4' in conversion to SimpleGrammar.
WARNING - 08:38:50: Unsupported feature 'maxItems' in JSONGrammar 'SobieskiMission_discipline_output' for property 'y_4' in conversion to SimpleGrammar.
INFO - 08:38:50:
INFO - 08:38:50: *** Start MDOScenario execution ***
INFO - 08:38:50: MDOScenario
INFO - 08:38:50: Disciplines: SobieskiAerodynamics SobieskiMission SobieskiPropulsion SobieskiStructure
INFO - 08:38:50: MDO formulation: MDF
INFO - 08:38:50: Optimization problem:
INFO - 08:38:50: minimize -y_4(x_shared, x_1, x_2, x_3)
INFO - 08:38:50: with respect to x_1, x_2, x_3, x_shared
INFO - 08:38:50: subject to constraints:
INFO - 08:38:50: g_1(x_shared, x_1, x_2, x_3) <= 0
INFO - 08:38:50: g_2(x_shared, x_1, x_2, x_3) <= 0
INFO - 08:38:50: g_3(x_shared, x_1, x_2, x_3) <= 0
INFO - 08:38:50: over the design space:
INFO - 08:38:50: +-------------+-------------+-------+-------------+-------+
INFO - 08:38:50: | Name | Lower bound | Value | Upper bound | Type |
INFO - 08:38:50: +-------------+-------------+-------+-------------+-------+
INFO - 08:38:50: | x_shared[0] | 0.01 | 0.05 | 0.09 | float |
INFO - 08:38:50: | x_shared[1] | 30000 | 45000 | 60000 | float |
INFO - 08:38:50: | x_shared[2] | 1.4 | 1.6 | 1.8 | float |
INFO - 08:38:50: | x_shared[3] | 2.5 | 5.5 | 8.5 | float |
INFO - 08:38:50: | x_shared[4] | 40 | 55 | 70 | float |
INFO - 08:38:50: | x_shared[5] | 500 | 1000 | 1500 | float |
INFO - 08:38:50: | x_1[0] | 0.1 | 0.25 | 0.4 | float |
INFO - 08:38:50: | x_1[1] | 0.75 | 1 | 1.25 | float |
INFO - 08:38:50: | x_2 | 0.75 | 1 | 1.25 | float |
INFO - 08:38:50: | x_3 | 0.1 | 0.5 | 1 | float |
INFO - 08:38:50: +-------------+-------------+-------+-------------+-------+
INFO - 08:38:50: Solving optimization problem with algorithm SLSQP:
INFO - 08:38:50: 10%|█ | 1/10 [00:00<00:00, 18.98 it/sec, obj=-536]
INFO - 08:38:51: 20%|██ | 2/10 [00:00<00:00, 14.07 it/sec, obj=-2.12e+3]
WARNING - 08:38:51: MDAJacobi has reached its maximum number of iterations but the normed residual 5.741449586530469e-06 is still above the tolerance 1e-06.
INFO - 08:38:51: 30%|███ | 3/10 [00:00<00:00, 11.41 it/sec, obj=-3.46e+3]
INFO - 08:38:51: 40%|████ | 4/10 [00:00<00:00, 10.91 it/sec, obj=-3.96e+3]
INFO - 08:38:51: 50%|█████ | 5/10 [00:00<00:00, 11.14 it/sec, obj=-4.61e+3]
INFO - 08:38:51: 60%|██████ | 6/10 [00:00<00:00, 11.88 it/sec, obj=-4.5e+3]
INFO - 08:38:51: 70%|███████ | 7/10 [00:00<00:00, 12.29 it/sec, obj=-4.26e+3]
INFO - 08:38:51: 80%|████████ | 8/10 [00:00<00:00, 12.62 it/sec, obj=-4.11e+3]
INFO - 08:38:51: 90%|█████████ | 9/10 [00:00<00:00, 12.89 it/sec, obj=-4.02e+3]
INFO - 08:38:51: 100%|██████████| 10/10 [00:00<00:00, 13.12 it/sec, obj=-3.99e+3]
INFO - 08:38:51: Optimization result:
INFO - 08:38:51: Optimizer info:
INFO - 08:38:51: Status: None
INFO - 08:38:51: Message: Maximum number of iterations reached. GEMSEO stopped the driver.
INFO - 08:38:51: Number of calls to the objective function by the optimizer: 12
INFO - 08:38:51: Solution:
INFO - 08:38:51: The solution is feasible.
INFO - 08:38:51: Objective: -3463.120411437138
INFO - 08:38:51: Standardized constraints:
INFO - 08:38:51: g_1 = [-0.01112145 -0.02847064 -0.04049911 -0.04878943 -0.05476349 -0.14014207
INFO - 08:38:51: -0.09985793]
INFO - 08:38:51: g_2 = -0.0020925663903177405
INFO - 08:38:51: g_3 = [-0.71359843 -0.28640157 -0.05926796 -0.183255 ]
INFO - 08:38:51: Design space:
INFO - 08:38:51: +-------------+-------------+---------------------+-------------+-------+
INFO - 08:38:51: | Name | Lower bound | Value | Upper bound | Type |
INFO - 08:38:51: +-------------+-------------+---------------------+-------------+-------+
INFO - 08:38:51: | x_shared[0] | 0.01 | 0.05947685840242058 | 0.09 | float |
INFO - 08:38:51: | x_shared[1] | 30000 | 59246.692998739 | 60000 | float |
INFO - 08:38:51: | x_shared[2] | 1.4 | 1.4 | 1.8 | float |
INFO - 08:38:51: | x_shared[3] | 2.5 | 2.64097355362077 | 8.5 | float |
INFO - 08:38:51: | x_shared[4] | 40 | 69.32144380869019 | 70 | float |
INFO - 08:38:51: | x_shared[5] | 500 | 1478.031626737187 | 1500 | float |
INFO - 08:38:51: | x_1[0] | 0.1 | 0.4 | 0.4 | float |
INFO - 08:38:51: | x_1[1] | 0.75 | 0.7608797907508461 | 1.25 | float |
INFO - 08:38:51: | x_2 | 0.75 | 0.7607584987262048 | 1.25 | float |
INFO - 08:38:51: | x_3 | 0.1 | 0.1514057659459843 | 1 | float |
INFO - 08:38:51: +-------------+-------------+---------------------+-------------+-------+
INFO - 08:38:51: *** End MDOScenario execution (time: 0:00:00.771547) ***
Post-process scenario#
Lastly, we post-process the scenario by means of the
RadarChart.
Tip
Each post-processing method requires different inputs and offers a variety
of customization options. Use the API function
get_post_processing_options_schema() to print a table with
the options for any post-processing algorithm.
Or refer to our dedicated page:
Post-processing algorithms.
scenario.post_process(
post_name="RadarChart",
constraint_names=["g_1", "g_2", "g_3"],
save=False,
show=True,
fig_size=(5, 5),
)

/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/6.0.0/lib/python3.9/site-packages/gemseo/post/dataset/plots/_matplotlib/plot.py:87: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.
figure.tight_layout()
<gemseo.post.radar_chart.RadarChart object at 0x7f6dc104b6a0>
Total running time of the script: (0 minutes 1.071 seconds)