pyHarm.Predictors.PredictorSecant

Classes

PredictorSecant

Define the Secant predictor. From the last two solution points, generates the adequate direction. When only one solution point is available, makes use of the tangent predictor.

Module Contents

class pyHarm.Predictors.PredictorSecant.PredictorSecant(sign_ds, **kwargs)

Bases: pyHarm.Predictors.PredictorTangent.PredictorTangent

Define the Secant predictor. From the last two solution points, generates the adequate direction. When only one solution point is available, makes use of the tangent predictor.

predictor_name = 'Secant Predictor'

keyword that is used to call the creation of this class in the system factory.

Type:

str

factory_keyword: str = 'secant'

keyword that is used to call the creation of this class in the system factory.

Type:

str

predict_usingtan(sollist: list, ds: float, k_imposed=None) → tuple[numpy.ndarray, pyHarm.Solver.SystemSolution, float]

Predicts the next starting point using the tangent.

Parameters:

• sollist (list[SystemSolution]) – list of SystemSolution already solved during the analysis.

• ds (float) – step size for the prediction.

• k_imposed (None | int) – if not None, uses the k_imposed as the index of the last solution pointer.

Returns:

next predicted starting point. SystemSolution: last accepted point in the list of solutions. float: sign of the prediction used (-1 | 1)

Return type:

np.ndarray

predict(sollist: list, ds: float, k_imposed=None) → tuple[numpy.ndarray, pyHarm.Solver.SystemSolution, float]

Predicts the next starting point using secant prediction.

Parameters:

• sollist (list[SystemSolution]) – list of SystemSolution already solved during the analysis.

• ds (float) – step size for the prediction.

• k_imposed (None | int) – if not None, uses the k_imposed as the index of the last solution pointer.

Returns:

next predicted starting point. SystemSolution: last accepted point in the list of solutions. float: sign of the prediction used (-1 | 1)

Return type:

np.ndarray