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)

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)

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)

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)

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)

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]]