aggregation_func module¶
Constraint aggregation methods.
Transform a constraint vector into one scalar equivalent or quasi equivalent constraint.
- 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 (MDOFunction) – The initial constraint function.
indices (Sequence[int] | None) – The indices to generate a subset of the outputs to aggregate. If
None
, aggregate all the outputs.scale (float | 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.algos.aggregation.aggregation_func.aggregate_lower_bound_ks(constr_fct, indices=None, rho=100.0, scale=1.0)[source]
Aggregate constraints for inequality constraints.
- Parameters:
constr_fct (MDOFunction) – The initial constraint function.
indices (Sequence[int] | None) – The indices to generate a subset of the outputs to aggregate. If
None
, aggregate all the outputs.scale (float | 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.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 (MDOFunction) – The initial constraint function.
indices (Sequence[int] | None) – The indices to generate a subset of the outputs to aggregate. If
None
, aggregate all the outputs.scale (float | ndarray) –
The scaling factor for multiplying the constraints.
By default it is set to 1.0.
- Returns:
The aggregated function.
- Return type:
- gemseo.algos.aggregation.aggregation_func.aggregate_positive_sum_square(constr_fct, indices=None, scale=1.0)[source]
Transform a vector of equalities into a sum of squared constraints.
- Parameters:
constr_fct (MDOFunction) – The initial constraint function.
indices (Sequence[int] | None) – The indices to generate a subset of the outputs to aggregate. If
None
, aggregate all the outputs.scale (float | ndarray) –
The scaling factor for multiplying the constraints.
By default it is set to 1.0.
- Returns:
The aggregated function.
- Return type:
- 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 (MDOFunction) – The initial constraint function.
indices (Sequence[int] | None) – The indices to generate a subset of the outputs to aggregate. If
None
, aggregate all the outputs.scale (float | ndarray) –
The scaling factor for multiplying the constraints.
By default it is set to 1.0.
- Returns:
The aggregated function.
- Return type:
- gemseo.algos.aggregation.aggregation_func.aggregate_upper_bound_ks(constr_fct, indices=None, rho=100.0, scale=1.0)[source]
Aggregate constraints for inequality constraints.
- Parameters:
constr_fct (MDOFunction) – The initial constraint function.
indices (Sequence[int] | None) – The indices to generate a subset of the outputs to aggregate. If
None
, aggregate all the outputs.scale (float | 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.algos.aggregation.aggregation_func.check_constraint_type(function_type)[source]
Decorate a function to check whether it is of the expected type.