gemseo / algos / aggregation

aggregation_func module¶

Constraint aggregation methods.

Transform a constraint vector into one scalar equivalent or quasi equivalent constraint.

Functions:

 aggregate_iks(constr_fct[, indices, rho, scale]) Constraints aggregation method for inequality constraints. aggregate_ks(constr_fct[, indices, rho, scale]) Aggregate constraints for inequality constraints. aggregate_max(constr_fct[, indices, scale]) Transform a vector of equalities into a max of all values. aggregate_sum_square(constr_fct[, indices, ...]) Transform a vector of equalities into a sum of squared constraints. check_constraint_type(function_type) Decorate a function to check whether it is of the expected type.
gemseo.algos.aggregation.aggregation_func.aggregate_iks(constr_fct, indices=None, rho=100.0, scale=1.0)[source]

Constraints aggregation method for inequality constraints.

See [KH15].

Parameters
• constr_fct (gemseo.core.mdofunctions.mdo_function.MDOFunction) – The initial constraint function.

• indices (Optional[Sequence[int]]) –

The indices to generate a subset of the outputs to aggregate. If None, aggregate all the outputs.

By default it is set to None.

• scale (Union[float, numpy.ndarray]) –

The scaling factor for multiplying the constraints.

By default it is set to 1.0.

• rho (float) –

The multiplicative parameter in the exponential.

By default it is set to 100.0.

Returns

The aggregated function.

Return type

gemseo.core.mdofunctions.mdo_function.MDOFunction

gemseo.algos.aggregation.aggregation_func.aggregate_ks(constr_fct, indices=None, rho=100.0, scale=1.0)[source]

Aggregate constraints for inequality constraints.

See [KH15] and [KS83].

Parameters
• constr_fct (gemseo.core.mdofunctions.mdo_function.MDOFunction) – The initial constraint function.

• indices (Optional[Sequence[int]]) –

The indices to generate a subset of the outputs to aggregate. If None, aggregate all the outputs.

By default it is set to None.

• scale (Union[float, numpy.ndarray]) –

The scaling factor for multiplying the constraints.

By default it is set to 1.0.

• rho (float) –

The multiplicative parameter in the exponential.

By default it is set to 100.0.

Returns

The aggregated function.

Return type

gemseo.core.mdofunctions.mdo_function.MDOFunction

gemseo.algos.aggregation.aggregation_func.aggregate_max(constr_fct, indices=None, scale=1.0)[source]

Transform a vector of equalities into a max of all values.

Parameters
• constr_fct (gemseo.core.mdofunctions.mdo_function.MDOFunction) – The initial constraint function.

• indices (Optional[Sequence[int]]) –

The indices to generate a subset of the outputs to aggregate. If None, aggregate all the outputs.

By default it is set to None.

• scale (Union[float, numpy.ndarray]) –

The scaling factor for multiplying the constraints.

By default it is set to 1.0.

Returns

The aggregated function.

Return type

gemseo.core.mdofunctions.mdo_function.MDOFunction

gemseo.algos.aggregation.aggregation_func.aggregate_sum_square(constr_fct, indices=None, scale=1.0)[source]

Transform a vector of equalities into a sum of squared constraints.

Parameters
• constr_fct (gemseo.core.mdofunctions.mdo_function.MDOFunction) – The initial constraint function.

• indices (Optional[Sequence[int]]) –

The indices to generate a subset of the outputs to aggregate. If None, aggregate all the outputs.

By default it is set to None.

• scale (Union[float, numpy.ndarray]) –

The scaling factor for multiplying the constraints.

By default it is set to 1.0.

Returns

The aggregated function.

Return type

gemseo.core.mdofunctions.mdo_function.MDOFunction

gemseo.algos.aggregation.aggregation_func.check_constraint_type(function_type)[source]

Decorate a function to check whether it is of the expected type.

Parameters

function_type (str) – The expected function type, "ineq" or "eq".

Returns

The decorated function.

Return type

Callable[[Callable[[Any], Any]], Callable[[Any], Any]]