dde_rk4_step

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dde_rk4_step#

class braintools.quad.dde_rk4_step(f, y, t, history_fn, delays, *args, **kwargs)#

Fourth-order Runge-Kutta method for delay differential equations.

Classic RK4 extended to handle delayed terms.

Parameters:

  • f (Callable[[Array | ndarray | bool | number | bool | int | float | complex | Quantity, PyTree, PyTree, ...], PyTree]) – Same as dde_euler_step.

  • y (PyTree) – Same as dde_euler_step.

  • t (Array | ndarray | bool | number | bool | int | float | complex | Quantity) – Same as dde_euler_step.

  • history_fn (Callable[[Array | ndarray | bool | number | bool | int | float | complex | Quantity], PyTree]) – Same as dde_euler_step.

  • delays (Array | ndarray | bool | number | bool | int | float | complex | Quantity | Sequence[Array | ndarray | bool | number | bool | int | float | complex | Quantity]) – Same as dde_euler_step.

  • *args – Same as dde_euler_step.

Returns:

The updated state after one RK4 step (fourth-order accurate).

Return type:

PyTree

Notes

Uses the standard RK4 tableau with delayed terms evaluated at the appropriate times for each stage.

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