Note
Go to the end to download the full example code
Post-process a scenario¶
from __future__ import annotations
from gemseo import create_design_space
from gemseo import create_discipline
from gemseo import create_scenario
from gemseo import execute_post
We consider a minimization problem over the interval \([0,1]\) of the \(f(x)=x^2\) objective function:
discipline = create_discipline("AnalyticDiscipline", expressions={"y": "x**2"})
design_space = create_design_space()
design_space.add_variable("x", l_b=0.0, u_b=1.0)
scenario = create_scenario([discipline], "DisciplinaryOpt", "y", design_space)
We solve this optimization problem with the gradient-free algorithm COBYLA:
scenario.execute({"algo": "NLOPT_COBYLA", "max_iter": 10})
Then,
we can post-process this MDOScenario
either with its method post_process()
:
scenario.post_process("BasicHistory", variable_names=["y"])
or with the function execute_post()
:
execute_post(scenario, "BasicHistory", variable_names=["y"])
Note
By default, GEMSEO saves the images on the disk.
Use save=False
to not save figures and show=True
to display them on the screen.
See also