State Machine

The state_machine.py file contains the engine behind the simulation, namely the StateMachine Class. When initializing the StateMachine, the predicates, sorts, scenario, max_t, and rules should be specified. After initializing the StateMachine, the StateMachine can be run. This is done by performing the .run() function --> StateMachine.run(). If you want to enable Debug mode, "True" should be passed as argument. The StateMachine Class contains several functions and variables, which will be described underneath.

Functions

  • filter_predicate_sorts(predicate)

    • This function filters all the sorts of the predicate.

  • create_predicate_dict(self, predicates)

    • This function creates a dictionary from the predicates.txt file of all predicates.

  • filter_sort_values(sort)

    • This function retrieves all possible values a sort can have.

  • sort_sorts(self, sorts)

    • This function creates a dictionary from the sorts.txt file of all sorts.

  • create_states(self)

    • This function creates a fixed number of empty states (dependent on the max_t) and stores them to the self.states list.

  • check_validity_pred(self, predicate_name, agent, value)

    • This function checks the validity of a predicate with predicate name *predicate_name*. It checks whether the agent corresponding to the predicate is a valid agent and whether the sorts used in the predicate are valid sorts. This function will print warning messages if there are inconsistencies. The name of the function, *func_name*, is passed as argument to, in order to know which rule causes the warning messages.

  • fill_states(self, scenario)

    • This function fills the states, solely on the basis of the scenarios.txt file

  • show_debug_info(self)

    • This function prints the debug information about all sorts and all predicates.

  • run

    • This function runs the StateMachine (and hence the simulation). All rules that are defined are executed for each timestep, starting from 1, till the max_t.

  • filter_nested_predicate_info(self, predicate)

    • This function filters information about a nested predicate from the scenarios file. It returns the name of the predicate, the agent(s), and the value(s)

  • filter_predicate_info(predicate)

    • This function filters information about a predicate from the scenarios file. It returns the name of the predicate, the agent(s), and the value(s)

  • filter_predicate_time(self, time)

    • This function filters the time relevant information of a predicate from the scenarios file. It returns the start -and end time.

  • insert_single_predicate(self, predicate, agent, value, start_time, end_time)

    • This functions creates an instance of Class Predicate with information *predicate* (name of the predicate), *agent*, and *value*, and inserts it in the states between the *start_time* and *end_time*.

  • insert_nested_predicate(self, nest_name, agent, value, start_time, end_time)

    • This functions creates an instance of Class Predicate with information *predicate* (name of the (overarching) predicate), *agent*, and *value*, and inserts it as nested predicate in the states between the *start_time* and *end_time*.

  • insert_predicate(self, predicate, agent, value, start_time, end_time)

    • This function either calls insert_single_predicate or insert_nested_predicate (based on whether the predicate is a nested predicate or not).

Variables

  • max_t

    • The max_t indicates for how many timesteps the simulation should run (max_t is the maximum t --> end t).

  • rules

    • A list of functions which are executed for every timestep. The rules are defined in the Jupyter Notebook.

  • predicates

    • A dictionary of all possible predicates. The key is the name of the predicate and the value is a list of the corresponding sorts.

  • sorts

    • A dictionary of all sorts. The key is the name of the sort and the value is a list of all possible values for that sort. The sorts Boolean and Real are not included.

  • states

    • A list of all states, ranging from state 1 till state max_t.