Note
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Post-process an optimization problem¶
from __future__ import annotations
from gemseo import create_design_space
from gemseo import execute_algo
from gemseo import execute_post
from gemseo.algos.opt_problem import OptimizationProblem
from gemseo.core.mdofunctions.mdo_function import MDOFunction
We consider a minimization problem over the interval \([0,1]\) of the \(f(x)=x^2\) objective function:
objective = MDOFunction(lambda x: x**2, "f", input_names=["x"], output_names=["y"])
design_space = create_design_space()
design_space.add_variable("x", l_b=0.0, u_b=1.0)
optimization_problem = OptimizationProblem(design_space)
optimization_problem.objective = objective
We solve this optimization problem with the gradient-free algorithm COBYLA:
execute_algo(optimization_problem, "NLOPT_COBYLA", max_iter=10)
Then,
we can post-process this OptimizationProblem
with the function execute_post():
execute_post(optimization_problem, "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