gemseo / problems / scalable / parametric / core

# design_space module¶

## Scalable problem - Design space¶

class gemseo.problems.scalable.parametric.core.design_space.TMDesignSpace(n_shared=1, n_local=None, n_coupling=None, default_inputs=None, dtype='float64')[source]

Bases: object

The design space for the scalable problem introduced by Tedford and Martins (2010) defines the lower and upper bounds of both local design parameters, shared design parameters and coupling variables, as well as default values.

The lower bounds are all equal to 0, the upper bounds are all equal to 1 and default values are all equal to 0.5.

The construction of the design space requires the number of shared design parameters, the number of local design parameters per discipline and the number of coupling variables per discipline. The two latter arguments must be list of integers with the same length which corresponds to the number of strongly coupled disciplines. By default, the design space considers two disciplines.

Parameters
• n_shared (int) –

size of the shared design parameters. Default: 1.

By default it is set to 1.

• n_local (list(int)) –

sizes of the local design parameters. If None, use [1, 1]. Default: None.

By default it is set to None.

• n_coupling (list(int)) –

sizes of the coupling parameters. If None, use [1, 1]. Default: None.

By default it is set to None.

• default_inputs (dict) –

default inputs. Default: None.

By default it is set to None.

• dtype

numpy data type. Default: ‘float64’.

By default it is set to float64.