Exemplo n.º 1
0
def apply_from_variant(variant, petri_net, initial_marking, final_marking, parameters=None):
    """
    Apply the alignments from the specification of a single variant

    Parameters
    -------------
    variant
        Variant (as string delimited by the "variant_delimiter" parameter)
    petri_net
        Petri net
    initial_marking
        Initial marking
    final_marking
        Final marking
    parameters
        Parameters of the algorithm (same as 'apply' method, plus 'variant_delimiter' that is , by default)

    Returns
    ------------
    dictionary: `dict` with keys **alignment**, **cost**, **visited_states**, **queued_states** and **traversed_arcs**
    """
    if parameters is None:
        parameters = {}
    activity_key = DEFAULT_NAME_KEY if parameters is None or PARAMETER_CONSTANT_ACTIVITY_KEY not in parameters else \
        parameters[
            pm4pyutil.constants.PARAMETER_CONSTANT_ACTIVITY_KEY]
    trace = log_implementation.Trace()
    variant_delimiter = exec_utils.get_param_value(Parameters.PARAMETER_VARIANT_DELIMITER, parameters,
                                                   pm4pyutil.constants.DEFAULT_VARIANT_SEP)
    variant_split = variant.split(variant_delimiter) if type(variant) is str else variant
    for i in range(len(variant_split)):
        trace.append(log_implementation.Event({activity_key: variant_split[i]}))
    return apply(trace, petri_net, initial_marking, final_marking, parameters=parameters)
Exemplo n.º 2
0
def apply_playout(net,
                  initial_marking,
                  no_traces=100,
                  max_trace_length=100,
                  case_id_key=xes_constants.DEFAULT_TRACEID_KEY,
                  activity_key=xes_constants.DEFAULT_NAME_KEY,
                  timestamp_key=xes_constants.DEFAULT_TIMESTAMP_KEY,
                  final_marking=None,
                  smap=None,
                  log=None,
                  return_visited_elements=False):
    """
    Do the playout of a Petrinet generating a log

    Parameters
    ----------
    net
        Petri net to play-out
    initial_marking
        Initial marking of the Petri net
    no_traces
        Number of traces to generate
    max_trace_length
        Maximum number of events per trace (do break)
    case_id_key
        Trace attribute that is the case ID
    activity_key
        Event attribute that corresponds to the activity
    timestamp_key
        Event attribute that corresponds to the timestamp
    final_marking
        If provided, the final marking of the Petri net
    smap
        Stochastic map
    log
        Log
    """
    if final_marking is None:
        # infer the final marking from the net
        final_marking = final_marking_discovery.discover_final_marking(net)
    if smap is None:
        if log is None:
            raise Exception(
                "please provide at least one between stochastic map and log")
        smap = replay.get_map_from_log_and_net(log,
                                               net,
                                               initial_marking,
                                               final_marking,
                                               parameters={
                                                   Parameters.ACTIVITY_KEY:
                                                   activity_key,
                                                   Parameters.TIMESTAMP_KEY:
                                                   timestamp_key
                                               })
    # assigns to each event an increased timestamp from 1970
    curr_timestamp = 10000000
    all_visited_elements = []

    for i in range(no_traces):
        visited_elements = []
        visible_transitions_visited = []
        marking = copy(initial_marking)

        while len(visible_transitions_visited) < max_trace_length:
            visited_elements.append(marking)

            if not semantics.enabled_transitions(
                    net, marking):  # supports nets with possible deadlocks
                break
            all_enabled_trans = semantics.enabled_transitions(net, marking)
            if final_marking is not None and marking == final_marking:
                en_t_list = list(all_enabled_trans.union({None}))
            else:
                en_t_list = list(all_enabled_trans)

            trans = stochastic_utils.pick_transition(en_t_list, smap)

            if trans is None:
                break

            visited_elements.append(trans)
            if trans.label is not None:
                visible_transitions_visited.append(trans)

            marking = semantics.execute(trans, net, marking)

        all_visited_elements.append(tuple(visited_elements))

    if return_visited_elements:
        return all_visited_elements

    log = log_instance.EventLog()

    for index, visited_elements in enumerate(all_visited_elements):
        trace = log_instance.Trace()
        trace.attributes[case_id_key] = str(index)
        for element in visited_elements:
            if type(element
                    ) is PetriNet.Transition and element.label is not None:
                event = log_instance.Event()
                event[activity_key] = element.label
                event[timestamp_key] = datetime.datetime.fromtimestamp(
                    curr_timestamp)
                trace.append(event)
                # increases by 1 second
                curr_timestamp += 1
        log.append(trace)

    return log
Exemplo n.º 3
0
def apply(net: PetriNet, initial_marking: Marking, final_marking: Marking = None,
          parameters: Optional[Dict[Union[str, Parameters], Any]] = None) -> EventLog:
    """
    Do the playout of a Petrinet generating a log (extensive search; stop at the maximum
    trace length specified

    Parameters
    -----------
    net
        Petri net to play-out
    initial_marking
        Initial marking of the Petri net
    final_marking
        If provided, the final marking of the Petri net
    parameters
        Parameters of the algorithm:
            Parameters.MAX_TRACE_LENGTH -> Maximum trace length
            Parameters.PETRI_SEMANTICS -> Petri net semantics
    """
    if parameters is None:
        parameters = {}

    case_id_key = exec_utils.get_param_value(Parameters.CASE_ID_KEY, parameters, xes_constants.DEFAULT_TRACEID_KEY)
    activity_key = exec_utils.get_param_value(Parameters.ACTIVITY_KEY, parameters, xes_constants.DEFAULT_NAME_KEY)
    timestamp_key = exec_utils.get_param_value(Parameters.TIMESTAMP_KEY, parameters,
                                               xes_constants.DEFAULT_TIMESTAMP_KEY)
    max_trace_length = exec_utils.get_param_value(Parameters.MAX_TRACE_LENGTH, parameters, 10)
    return_elements = exec_utils.get_param_value(Parameters.RETURN_ELEMENTS, parameters, False)
    max_marking_occ = exec_utils.get_param_value(Parameters.MAX_MARKING_OCC, parameters, sys.maxsize)
    semantics = exec_utils.get_param_value(Parameters.PETRI_SEMANTICS, parameters, petri_net.semantics.ClassicSemantics())

    # assigns to each event an increased timestamp from 1970
    curr_timestamp = 10000000

    feasible_elements = []

    to_visit = [(initial_marking, (), ())]
    visited = set()

    while len(to_visit) > 0:
        state = to_visit.pop(0)

        m = state[POSITION_MARKING]
        trace = state[POSITION_TRACE]
        elements = state[POSITION_ELEMENTS]

        if (m, trace) in visited:
            continue
        visited.add((m, trace))

        en_t = semantics.enabled_transitions(net, m)

        if (final_marking is not None and m == final_marking) or (final_marking is None and len(en_t) == 0):
            if len(trace) <= max_trace_length:
                feasible_elements.append(elements)

        for t in en_t:
            new_elements = elements + (m,)
            new_elements = new_elements + (t,)

            counter_elements = Counter(new_elements)

            if counter_elements[m] > max_marking_occ:
                continue

            new_m = semantics.weak_execute(t, net, m)
            if t.label is not None:
                new_trace = trace + (t.label,)
            else:
                new_trace = trace

            new_state = (new_m, new_trace, new_elements)

            if new_state in visited or len(new_trace) > max_trace_length:
                continue
            to_visit.append(new_state)

    if return_elements:
        return feasible_elements

    log = log_instance.EventLog()
    for elements in feasible_elements:
        log_trace = log_instance.Trace()
        log_trace.attributes[case_id_key] = str(len(log))
        activities = [x.label for x in elements if type(x) is PetriNet.Transition and x.label is not None]
        for act in activities:
            curr_timestamp = curr_timestamp + 1
            log_trace.append(
                log_instance.Event({activity_key: act, timestamp_key: datetime.datetime.fromtimestamp(curr_timestamp)}))
        log.append(log_trace)

    return log
Exemplo n.º 4
0
def apply_playout(net, initial_marking, no_traces=100, max_trace_length=100,
                  initial_timestamp=10000000, initial_case_id=0,
                  case_id_key=xes_constants.DEFAULT_TRACEID_KEY,
                  activity_key=xes_constants.DEFAULT_NAME_KEY, timestamp_key=xes_constants.DEFAULT_TIMESTAMP_KEY,
                  final_marking=None, return_visited_elements=False, semantics=petri_net.semantics.ClassicSemantics()):
    """
    Do the playout of a Petrinet generating a log

    Parameters
    ----------
    net
        Petri net to play-out
    initial_marking
        Initial marking of the Petri net
    no_traces
        Number of traces to generate
    max_trace_length
        Maximum number of events per trace (do break)
    initial_timestamp
        Increased timestamp from 1970 for the first event
    initial_case_id
        Case id of the first event
    case_id_key
        Trace attribute that is the case ID
    activity_key
        Event attribute that corresponds to the activity
    timestamp_key
        Event attribute that corresponds to the timestamp
    final_marking
        If provided, the final marking of the Petri net
    semantics
        Semantics of the Petri net to be used (default: petri_net.semantics.ClassicSemantics())
    """
    # assigns to each event an increased timestamp from 1970
    curr_timestamp = initial_timestamp
    all_visited_elements = []

    for i in range(no_traces):
        visited_elements = []
        visible_transitions_visited = []

        marking = copy(initial_marking)
        while len(visible_transitions_visited) < max_trace_length:
            visited_elements.append(marking)

            if not semantics.enabled_transitions(net, marking):  # supports nets with possible deadlocks
                break
            all_enabled_trans = semantics.enabled_transitions(net, marking)
            if final_marking is not None and marking == final_marking:
                trans = choice(list(all_enabled_trans.union({None})))
            else:
                trans = choice(list(all_enabled_trans))
            if trans is None:
                break

            visited_elements.append(trans)
            if trans.label is not None:
                visible_transitions_visited.append(trans)

            marking = semantics.execute(trans, net, marking)

        all_visited_elements.append(tuple(visited_elements))

    if return_visited_elements:
        return all_visited_elements

    log = log_instance.EventLog()

    for index, visited_elements in enumerate(all_visited_elements):
        trace = log_instance.Trace()
        trace.attributes[case_id_key] = str(index+initial_case_id)
        for element in visited_elements:
            if type(element) is PetriNet.Transition and element.label is not None:
                event = log_instance.Event()
                event[activity_key] = element.label
                event[timestamp_key] = datetime.datetime.fromtimestamp(curr_timestamp)
                trace.append(event)
                # increases by 1 second
                curr_timestamp += 1
        log.append(trace)

    return log