Design space

In this example, we will discover the different functions of the API related to design space, which is a key element to represent the space of parameters on which a scenario will evaluate a list of disciplines.

from __future__ import annotations

from numpy import array

from gemseo import configure_logger
from gemseo import create_design_space
from gemseo import read_design_space
from gemseo import write_design_space

configure_logger()

<RootLogger root (INFO)>

Create a design space

To create a standard DesignSpace, the API function create_design_space() can be used.

• This function does not take any argument.

• This function returns an empty instance of DesignSpace.

design_space = create_design_space()
design_space

Design space:

Name	Lower bound	Value	Upper bound	Type

Once built, we can add variables. E.g.

design_space.add_variable(
    "x", 2, l_b=array([0.0] * 2), u_b=array([1.0] * 2), value=array([0.5] * 2)
)
design_space

Design space:

Name	Lower bound	Value	Upper bound	Type
x[0]	0	0.5	1	float
x[1]	0	0.5	1	float

Read a design space

In presence of a design space specified in a CSV file, the API function read_design_space() can be used.

• Its first argument is the file path of the design space. Its second argument is the list of fields available in the file and is optional.

• By default, the design space reads these information from the file.

• This function returns an instance of DesignSpace.

design_space.to_csv("saved_design_space.csv")
loaded_design_space = read_design_space("saved_design_space.csv")

Write a design space

To export an instance of DesignSpace into an HDF or CSV file, the write_design_space() API function can be used:

loaded_design_space.add_variable("y", l_b=-1, u_b=3, value=0.0)
write_design_space(loaded_design_space, "saved_design_space.csv")
read_design_space("saved_design_space.csv")

Design space:

Name	Lower bound	Value	Upper bound	Type
x[0]	0	0.5	1	float
x[1]	0	0.5	1	float
y	-1	0	3	float