def run(self, t_start: float, t_end: float, log_callback: Callable = None): t = t_start outputs = {name: {} for name in self.models} while t < t_end - 1e-12: # Gather all inputs for each model from previous outputs inputs_for = {name: {} for name in self.models} for fm, fp, tm, tp in self.connections: if fm in outputs and fp in outputs[fm]: inputs_for[tm][tp] = outputs[fm][fp] # Step each model new_outputs = {} for name, model in self.models.items(): step_result = model.step(t, self.dt, inputs_for[name]) new_outputs[name] = step_result.outputs outputs = new_outputs t += self.dt if log_callback: log_callback(t, outputs)
def __init__(self, name: str, Kp: float, x_ref: float = 0.0): super().__init__(name) self.Kp = Kp self.x_ref = x_ref self.input_ports = [XModPort("x_measured")] self.output_ports = [XModPort("F_cmd")] xmod co-simulation
@abstractmethod def step(self, t: float, dt: float, inputs: Dict[str, np.ndarray]) -> XModStep: """Advance model by dt from t with given inputs.""" pass model in self.models.items(): step_result = model.step(t
class XModModel(ABC): """Base class for an xmod co-simulation component.""" outputs) def __init__(self