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mode_cycle

Scalable location-cycle benchmark with clock resets.

mode_cycle(modes=4, dimension=4, dwell_time=0.5, initial_state=None)

Create a scalable hybrid system that cycles through locations.

The system has modes locations, each with linear dynamics active for dwell_time. A clock state is appended and reset on each transition, making the number of locations and state dimension scalable for benchmarking.

Parameters:

Name Type Description Default
modes int

Number of locations in the cycle.

 4
dimension int

Dimension of the continuous state (excluding the clock).

 4
dwell_time float

Time to stay in each location.

 0.5
initial_state ndarray | None

Optional initial state (length dimension + 1).

 None

Returns:

Type Description
HybridSystem

HybridSystem cycling through multiple linear locations.
Source code in src/flowcean/hybrid/benchmarks/mode_cycle.py 
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def mode_cycle(
    modes: int = 4,
    dimension: int = 4,
    dwell_time: float = 0.5,
    initial_state: np.ndarray | None = None,
) -> HybridSystem:
    """Create a scalable hybrid system that cycles through locations.

    The system has `modes` locations, each with linear dynamics active for
    `dwell_time`.
    A clock state is appended and reset on each transition, making the number
    of locations and state dimension scalable for benchmarking.

    Args:
        modes: Number of locations in the cycle.
        dimension: Dimension of the continuous state (excluding the clock).
        dwell_time: Time to stay in each location.
        initial_state: Optional initial state (length dimension + 1).

    Returns:
        HybridSystem cycling through multiple linear locations.
    """
    if modes < MIN_MODES:
        message = f"modes must be at least {MIN_MODES}."
        raise ValueError(message)
    if dimension < MIN_DIMENSION:
        message = f"dimension must be at least {MIN_DIMENSION}."
        raise ValueError(message)

    matrices = [_make_matrix(dimension, idx) for idx in range(modes)]
    event = EventSurface(
        _event_surface_clock,
        direction=CrossingDirection.RISING,
        label="dwell",
    )
    reset = Reset(_reset_clock, label="reset_clock")
    locations, transitions = _build_locations_and_transitions(
        matrices,
        reset,
        event,
    )

    if initial_state is None:
        initial_state = np.zeros(dimension + 1, dtype=float)
        initial_state[0] = 1.0

    return HybridSystem(
        locations=locations,
        transitions=transitions,
        initial_location=locations[0],
        initial_state=initial_state,
        parameters={"dwell_time": dwell_time},
    )