cashocs.verification.control_gradient_test

cashocs.verification.control_gradient_test(

ocp: optimal_control.OptimalControlProblem,

u: list[fenics.Function] | None = None,

h: list[fenics.Function] | None = None,

rng: np.random.RandomState | None = None,

verbose: bool = True,

) → float

Performs a Taylor test to verify that the computed gradient is correct.

Parameters:

• ocp (optimal_control.OptimalControlProblem) – The underlying optimal control problem, for which the gradient of the reduced cost function shall be verified.

• u (list[fenics.Function] | None) – The point, at which the gradient shall be verified. If this is None, then the current controls of the optimization problem are used. Default is None.

• h (list[fenics.Function] | None) – The direction(s) for the directional (Gâteaux) derivative. If this is None, one random direction is chosen. Default is None.

• rng (np.random.RandomState | None) – A numpy random state for calculating a random direction

• verbose (bool) – Prints the result to the console, if True. Default is True.

Returns:

The convergence order from the Taylor test. If this is (approximately) 2 or larger, everything works as expected.

Return type:

float