automata4cps.cps.CPSComponent

class automata4cps.cps.CPSComponent(id, t=0, initial_q=(), initial_xt: list = (), initial_xk: list = (), dt=-1.0, p=None, cont_state_names=None, discr_state_names=None, discr_output_names=None, cont_output_names=None, unknown_state='Unknown')

General hybrid system class based on scipy and simpy.

__init__(id, t=0, initial_q=(), initial_xt: list = (), initial_xk: list = (), dt=-1.0, p=None, cont_state_names=None, discr_state_names=None, discr_output_names=None, cont_output_names=None, unknown_state='Unknown')

Methods

__init__(id[, t, initial_q, initial_xt, ...])
apply_sim_event(e)	The event e is applied in this component's simpy execution, this means that the process must wait for an event.
context(q, past_t, past_p, t)
finish(t, **kwargs)
finish_condition()
get_alternatives(state, system_state)
get_decision_state(state, overall_state)
get_execution_data()
get_sim_state()
input(q, clock)
invariants(q, clock, xc, xd, y)
is_decision(state, overall_state)
load_context(context)	Loads artifacts from the specified PythonModelContext that can be used by predict() when evaluating inputs.
on_entry(q, context)
output(q, e, clock, xt, xk, u, p)
predict(context, model_input)	Evaluates a pyfunc-compatible input and produces a pyfunc-compatible output.
predict_stream(context, model_input[, params])	Evaluates a pyfunc-compatible input and produces an iterator of output.
read_event(t, e[, clear_p, keep_p])
reinitialize(t[, state])
set_sim_state(q, e, p, y, block_event)
simulate(finish_time)
simulation_process_simpy(env, max_time[, ...])	The function simulates single concurrent thread of one component (CPSComponent).
stop_condition(t)	Simulation stop condition which can be overridden by the subclasses.
time_continuous_dynamics(t, xt, xk, q, u, p, y)
time_discrete_dynamics(t, xt, xk, q, u, p, y)
timed_event(q, xc, xd)	Calculates if and when the next time event will happen and the new state values.
update_input(u)
wait(q)

Attributes

full_id
overall_system
state	System state is a vector of all state variables.