OpenPisco.Optim.Problems.OptimProblemDerived module#

OpenPisco.Optim.Problems.OptimProblemDerived.CheckIntegrity()[source]#
class OpenPisco.Optim.Problems.OptimProblemDerived.OptimProblemAddAllContributions(other=None, dataDeepCopy=True)[source]#

Bases: OptimProblemDerived

GetInequalityConstraintSensitivityVal(i)[source]#
GetInequalityConstraintVal(i)[source]#
GetNumberOfInequalityConstraints()[source]#
GetObjectiveFunctionSensitivity()[source]#
GetObjectiveFunctionVal()[source]#
class OpenPisco.Optim.Problems.OptimProblemDerived.OptimProblemDerived(other=None, dataDeepCopy=True)[source]#

Bases: OptimProblemBase

Decorator base class for OptimProblemBase.

Parameters

  • other (OptimProblemBase) – The underlying optimisation problem.

  • dataDeepCopy (bool, optional) – Whether other must be cloned (default is True).

internalOptimProblem#

The underlying optimisation problem.

Type

OptimProblemBase

Notes

This class implements a trivial decorator (An instance behaves exactly as the original object). Non-trivial decorators can be created subclassing OptimProblemDerived and overriding its methods.

Advance(direction, stepSize)[source]#
Parameters

  • direction (np.ndarray) – Vector-valued direction.

  • stepSize (scalar) – A multiplicative factor for direction.

Returns

Whether the advance succeeded

Return type

bool

GetCurrentPoint()[source]#
GetDirectionFromGradient(grad)[source]#
GetInequalityConstraintName(i)[source]#
GetInequalityConstraintSlacks()[source]#
GetInequalityConstraintStatus(i)[source]#
GetInequalityConstraintUpperBound(i)[source]#
GetInequalityConstraintUpperBoundOriginal(i)[source]#
GetInequalityConstraintVal(i)[source]#
GetInequalityConstraintValOriginal(i)[source]#
GetNumberOfEqualityConstraints()[source]#
GetNumberOfInequalityConstraints()[source]#
GetObjectiveFunctionSensitivity()[source]#
GetObjectiveFunctionVal()[source]#
PrintCurrentState(newPoint)[source]#
PrintHeader()[source]#
PrintState()[source]#
PrintStateHeader()[source]#
SaveData(data, point=None, gradient=None, direction=None)[source]#
SetInternalOptimProblem(of)[source]#
TakeValuesFrom(other)[source]#
UpdateProblemWhenIterationAccepted()[source]#
UpdateValues()[source]#
class OpenPisco.Optim.Problems.OptimProblemDerived.OptimProblemPenalized(other=None, dataDeepCopy=True)[source]#

Bases: OptimProblemDerived

GetInequalityConstraintSensitivityVal(i)[source]#
GetInequalityConstraintVal(i)[source]#
GetPenal(name)[source]#
PrintHeader()[source]#
SetPenal(name, penal)[source]#

Set the value of the penalty factor.

Parameters

  • penal (scalar or iterable of scalars) – Value of the penalty factor.

  • nb (int, optional) – The index of the constraint for which a penalty factor is set. If None, the same penalty factor is used for all the constraints when penal is a scalar, or each constraint has its own penalty factor when penal is iterable.

SetPenals(dic)[source]#
TakeValuesFrom(other)[source]#
UpdateValues()[source]#
class OpenPisco.Optim.Problems.OptimProblemDerived.OptimProblemPenaltyL1(other=None, dataDeepCopy=True)[source]#

Bases: OptimProblemPenalized

L1 penalty function

GetInequalityConstraintSensitivityVal(i)[source]#
GetInequalityConstraintVal(i)[source]#
PrintHeader()[source]#
TakeValuesFrom(other)[source]#
UpdateValues()[source]#
class OpenPisco.Optim.Problems.OptimProblemDerived.OptimProblemSquared(other=None, dataDeepCopy=True)[source]#

Bases: OptimProblemDerived

Replaces an optimization problem by one where constraint violation are squared.

GetInequalityConstraintSensitivityVal(i)[source]#
GetInequalityConstraintUpperBound(i)[source]#
GetInequalityConstraintVal(i)[source]#
UpdateValues()[source]#