def construct_trace_net(trace,
trace_name_key=xes_util.DEFAULT_NAME_KEY,
activity_key=xes_util.DEFAULT_NAME_KEY):
"""
Creates a trace net, i.e. a trace in Petri net form.
Parameters
----------
trace: :class:`list` input trace, assumed to be a list of events
trace_name_key: :class:`str` key of the attribute that defines the name of the trace
activity_key: :class:`str` key of the attribute of the events that defines the activity name
Returns
-------
tuple: :class:`tuple` of the net, initial marking and the final marking
"""
net = PetriNet('trace net of %s' %
trace.attributes[trace_name_key] if trace_name_key in
trace.attributes else ' ')
place_map = {0: PetriNet.Place('p_0')}
net.places.add(place_map[0])
for i in range(0, len(trace)):
t = PetriNet.Transition('t_' + trace[i][activity_key] + '_' + str(i),
trace[i][activity_key])
# 16/02/2021: set the trace index as property of the transition of the trace net
t.properties[properties.TRACE_NET_TRANS_INDEX] = i
net.transitions.add(t)
place_map[i + 1] = PetriNet.Place('p_' + str(i + 1))
# 16/02/2021: set the place index as property of the place of the trace net
place_map[i + 1].properties[properties.TRACE_NET_PLACE_INDEX] = i + 1
net.places.add(place_map[i + 1])
add_arc_from_to(place_map[i], t, net)
add_arc_from_to(t, place_map[i + 1], net)
return net, Marking({place_map[0]: 1}), Marking({place_map[len(trace)]: 1})
def __copy_into(source_net, target_net, upper, skip):
t_map = {}
p_map = {}
for t in source_net.transitions:
name = (t.name, skip) if upper else (skip, t.name)
label = (t.label, skip) if upper else (skip, t.label)
t_map[t] = PetriNet.Transition(name, label)
if properties.TRACE_NET_TRANS_INDEX in t.properties:
# 16/02/2021: copy the index property from the transition of the trace net
t_map[t].properties[properties.TRACE_NET_TRANS_INDEX] = t.properties[properties.TRACE_NET_TRANS_INDEX]
target_net.transitions.add(t_map[t])
for p in source_net.places:
name = (p.name, skip) if upper else (skip, p.name)
p_map[p] = PetriNet.Place(name)
if properties.TRACE_NET_PLACE_INDEX in p.properties:
# 16/02/2021: copy the index property from the place of the trace net
p_map[p].properties[properties.TRACE_NET_PLACE_INDEX] = p.properties[properties.TRACE_NET_PLACE_INDEX]
target_net.places.add(p_map[p])
for t in source_net.transitions:
for a in t.in_arcs:
add_arc_from_to(p_map[a.source], t_map[t], target_net)
for a in t.out_arcs:
add_arc_from_to(t_map[t], p_map[a.target], target_net)
return t_map, p_map
def construct(pn1, im1, fm1, pn2, im2, fm2, skip):
"""
Constructs the synchronous product net of two given Petri nets.
:param pn1: Petri net 1
:param im1: Initial marking of Petri net 1
:param fm1: Final marking of Petri net 1
:param pn2: Petri net 2
:param im2: Initial marking of Petri net 2
:param fm2: Final marking of Petri net 2
:param skip: Symbol to be used as skip
Returns
-------
:return: Synchronous product net and associated marking labels are of the form (a,>>)
"""
sync_net = PetriNet('synchronous_product_net of %s and %s' % (pn1.name, pn2.name))
t1_map, p1_map = __copy_into(pn1, sync_net, True, skip)
t2_map, p2_map = __copy_into(pn2, sync_net, False, skip)
for t1 in pn1.transitions:
for t2 in pn2.transitions:
if t1.label == t2.label:
sync = PetriNet.Transition((t1.name, t2.name), (t1.label, t2.label))
sync_net.transitions.add(sync)
# copy the properties of the transitions inside the transition of the sync net
for p1 in t1.properties:
sync.properties[p1] = t1.properties[p1]
for p2 in t2.properties:
sync.properties[p2] = t2.properties[p2]
for a in t1.in_arcs:
add_arc_from_to(p1_map[a.source], sync, sync_net)
for a in t2.in_arcs:
add_arc_from_to(p2_map[a.source], sync, sync_net)
for a in t1.out_arcs:
add_arc_from_to(sync, p1_map[a.target], sync_net)
for a in t2.out_arcs:
add_arc_from_to(sync, p2_map[a.target], sync_net)
sync_im = Marking()
sync_fm = Marking()
for p in im1:
sync_im[p1_map[p]] = im1[p]
for p in im2:
sync_im[p2_map[p]] = im2[p]
for p in fm1:
sync_fm[p1_map[p]] = fm1[p]
for p in fm2:
sync_fm[p2_map[p]] = fm2[p]
# update 06/02/2021: to distinguish the sync nets that are output of this method, put a property in the sync net
sync_net.properties[properties.IS_SYNC_NET] = True
return sync_net, sync_im, sync_fm
def add_transition(net, name=None, label=None):
name = name if name is not None else 't_' + str(len(
net.transitions)) + '_' + str(time.time()) + str(
random.randint(0, 10000))
t = PetriNet.Transition(name=name, label=label)
net.transitions.add(t)
return t
def merge(trgt=None, nets=None):
trgt = trgt if trgt is not None else PetriNet()
nets = nets if nets is not None else list()
for net in nets:
trgt.transitions.update(net.transitions)
trgt.places.update(net.places)
trgt.arcs.update(net.arcs)
return trgt
def get_strongly_connected_subnets(net):
"""
Get the strongly connected components subnets in the Petri net
Parameters
-------------
net
Petri net
Returns
-------------
strongly_connected_transitions
List of strongly connected transitions of the Petri net
"""
import networkx as nx
graph, inv_dictionary = create_networkx_directed_graph(net)
sccg = list(nx.strongly_connected_components(graph))
strongly_connected_subnets = []
for sg in list(sccg):
if len(sg) > 1:
subnet = PetriNet()
imarking = Marking()
fmarking = Marking()
corr = {}
for node in sg:
if node in inv_dictionary:
if type(inv_dictionary[node]) is PetriNet.Transition:
prev_trans = inv_dictionary[node]
new_trans = PetriNet.Transition(
prev_trans.name, prev_trans.label)
corr[node] = new_trans
subnet.transitions.add(new_trans)
if type(inv_dictionary[node]) is PetriNet.Place:
prev_place = inv_dictionary[node]
new_place = PetriNet.Place(prev_place.name)
corr[node] = new_place
subnet.places.add(new_place)
for edge in graph.edges:
if edge[0] in sg and edge[1] in sg:
add_arc_from_to(corr[edge[0]], corr[edge[1]], subnet)
strongly_connected_subnets.append([subnet, imarking, fmarking])
return strongly_connected_subnets
def add_arc_from_to(fr, to, net, weight=1):
"""
Adds an arc from a specific element to another element in some net. Assumes from and to are in the net!
Parameters
----------
fr: transition/place from
to: transition/place to
net: net to use
weight: weight associated to the arc
Returns
-------
None
"""
a = PetriNet.Arc(fr, to, weight)
net.arcs.add(a)
fr.out_arcs.add(a)
to.in_arcs.add(a)
return a
def add_place(net, name=None):
name = name if name is not None else 'p_' + str(len(
net.places)) + '_' + str(time.time()) + str(random.randint(0, 10000))
p = PetriNet.Place(name=name)
net.places.add(p)
return p
def decompose(net, im, fm):
places = {x.name: x for x in net.places}
inv_trans = {x.name: x for x in net.transitions if x.label is None}
tmap = {}
for t in net.transitions:
if t.label is not None:
if t.label not in tmap:
tmap[t.label] = []
tmap[t.label].append(t)
trans_dup_label = {
x.label: x
for x in net.transitions
if x.label is not None and len(tmap[x.label]) > 1
}
trans_labels = {x.name: x.label for x in net.transitions}
conn_comp = get_graph_components(places, inv_trans, trans_dup_label, tmap)
list_nets = []
for cmp in conn_comp:
net_new = PetriNet("")
im_new = Marking()
fm_new = Marking()
lmap = {}
for el in cmp:
if el in places:
lmap[el] = PetriNet.Place(el)
net_new.places.add(lmap[el])
elif el in inv_trans:
lmap[el] = PetriNet.Transition(el, None)
net_new.transitions.add(lmap[el])
elif el in trans_labels:
lmap[el] = PetriNet.Transition(el, trans_labels[el])
net_new.transitions.add(lmap[el])
for el in cmp:
if el in places:
old_place = places[el]
for arc in old_place.in_arcs:
st = arc.source
if st.name not in lmap:
lmap[st.name] = PetriNet.Transition(
st.name, trans_labels[st.name])
net_new.transitions.add(lmap[st.name])
add_arc_from_to(lmap[st.name], lmap[el], net_new)
for arc in old_place.out_arcs:
st = arc.target
if st.name not in lmap:
lmap[st.name] = PetriNet.Transition(
st.name, trans_labels[st.name])
net_new.transitions.add(lmap[st.name])
add_arc_from_to(lmap[el], lmap[st.name], net_new)
if old_place in im:
im_new[lmap[el]] = im[old_place]
if old_place in fm:
fm_new[lmap[el]] = fm[old_place]
lvis_labels = sorted(
[t.label for t in net_new.transitions if t.label is not None])
t_tuple = tuple(
sorted(
list(
int(
hashlib.md5(t.name.encode(
constants.DEFAULT_ENCODING)).hexdigest(), 16)
for t in net_new.transitions)))
net_new.lvis_labels = lvis_labels
net_new.t_tuple = t_tuple
if len(net_new.places) > 0 or len(net_new.transitions) > 0:
list_nets.append((net_new, im_new, fm_new))
return list_nets
def merge_comp(comp1, comp2):
net = PetriNet("")
im = Marking()
fm = Marking()
places = {}
trans = {}
for pl in comp1[0].places:
places[pl.name] = PetriNet.Place(pl.name)
net.places.add(places[pl.name])
if pl in comp1[1]:
im[places[pl.name]] = comp1[1][pl]
if pl in comp1[2]:
fm[places[pl.name]] = comp1[2][pl]
for pl in comp2[0].places:
places[pl.name] = PetriNet.Place(pl.name)
net.places.add(places[pl.name])
if pl in comp2[1]:
im[places[pl.name]] = comp2[1][pl]
if pl in comp2[2]:
fm[places[pl.name]] = comp2[2][pl]
for tr in comp1[0].transitions:
trans[tr.name] = PetriNet.Transition(tr.name, tr.label)
net.transitions.add(trans[tr.name])
for tr in comp2[0].transitions:
if not tr.name in trans:
trans[tr.name] = PetriNet.Transition(tr.name, tr.label)
net.transitions.add(trans[tr.name])
for arc in comp1[0].arcs:
if type(arc.source) is PetriNet.Place:
add_arc_from_to(places[arc.source.name], trans[arc.target.name],
net)
else:
add_arc_from_to(trans[arc.source.name], places[arc.target.name],
net)
for arc in comp2[0].arcs:
if type(arc.source) is PetriNet.Place:
add_arc_from_to(places[arc.source.name], trans[arc.target.name],
net)
else:
add_arc_from_to(trans[arc.source.name], places[arc.target.name],
net)
lvis_labels = sorted(
[t.label for t in net.transitions if t.label is not None])
t_tuple = tuple(
sorted(
list(
int(
hashlib.md5(t.name.encode(
constants.DEFAULT_ENCODING)).hexdigest(), 16)
for t in net.transitions)))
net.lvis_labels = lvis_labels
net.t_tuple = t_tuple
return (net, im, fm)
def import_net_from_xml_object(root, parameters=None):
"""
Import a Petri net from an etree XML object
Parameters
----------
root
Root object of the XML
parameters
Other parameters of the algorithm
"""
if parameters is None:
parameters = {}
net = PetriNet('imported_' + str(time.time()))
marking = Marking()
fmarking = Marking()
nett = None
page = None
finalmarkings = None
stochastic_information = {}
for child in root:
nett = child
places_dict = {}
trans_dict = {}
if nett is not None:
for child in nett:
if "page" in child.tag:
page = child
if "finalmarkings" in child.tag:
finalmarkings = child
if page is None:
page = nett
if page is not None:
for child in page:
if "place" in child.tag:
position_X = None
position_Y = None
dimension_X = None
dimension_Y = None
place_id = child.get("id")
place_name = place_id
number = 0
for child2 in child:
if child2.tag.endswith('name'):
for child3 in child2:
if child3.text:
place_name = child3.text
if child2.tag.endswith('initialMarking'):
for child3 in child2:
if child3.tag.endswith("text"):
number = int(child3.text)
if child2.tag.endswith('graphics'):
for child3 in child2:
if child3.tag.endswith('position'):
position_X = float(child3.get("x"))
position_Y = float(child3.get("y"))
elif child3.tag.endswith("dimension"):
dimension_X = float(child3.get("x"))
dimension_Y = float(child3.get("y"))
places_dict[place_id] = PetriNet.Place(place_id)
places_dict[place_id].properties[constants.PLACE_NAME_TAG] = place_name
net.places.add(places_dict[place_id])
if position_X is not None and position_Y is not None and dimension_X is not None and dimension_Y is not None:
places_dict[place_id].properties[constants.LAYOUT_INFORMATION_PETRI] = (
(position_X, position_Y), (dimension_X, dimension_Y))
if number > 0:
marking[places_dict[place_id]] = number
del place_name
if page is not None:
for child in page:
if child.tag.endswith("transition"):
position_X = None
position_Y = None
dimension_X = None
dimension_Y = None
trans_id = child.get("id")
trans_name = trans_id
trans_visible = True
random_variable = None
for child2 in child:
if child2.tag.endswith("name"):
for child3 in child2:
if child3.text:
if trans_name == trans_id:
trans_name = child3.text
if child2.tag.endswith("graphics"):
for child3 in child2:
if child3.tag.endswith("position"):
position_X = float(child3.get("x"))
position_Y = float(child3.get("y"))
elif child3.tag.endswith("dimension"):
dimension_X = float(child3.get("x"))
dimension_Y = float(child3.get("y"))
if child2.tag.endswith("toolspecific"):
tool = child2.get("tool")
if "ProM" in tool:
activity = child2.get("activity")
if "invisible" in activity:
trans_visible = False
elif "StochasticPetriNet" in tool:
distribution_type = None
distribution_parameters = None
priority = None
weight = None
for child3 in child2:
key = child3.get("key")
value = child3.text
if key == "distributionType":
distribution_type = value
elif key == "distributionParameters":
distribution_parameters = value
elif key == "priority":
priority = int(value)
elif key == "weight":
weight = float(value)
random_variable = RandomVariable()
random_variable.read_from_string(distribution_type, distribution_parameters)
random_variable.set_priority(priority)
random_variable.set_weight(weight)
# 15/02/2021: the name associated in the PNML to invisible transitions was lost.
# at least save that as property.
if trans_visible:
trans_label = trans_name
else:
trans_label = None
trans_dict[trans_id] = PetriNet.Transition(trans_id, trans_label)
trans_dict[trans_id].properties[constants.TRANS_NAME_TAG] = trans_name
net.transitions.add(trans_dict[trans_id])
if random_variable is not None:
trans_dict[trans_id].properties[constants.STOCHASTIC_DISTRIBUTION] = random_variable
if position_X is not None and position_Y is not None and dimension_X is not None and dimension_Y is not None:
trans_dict[trans_id].properties[constants.LAYOUT_INFORMATION_PETRI] = (
(position_X, position_Y), (dimension_X, dimension_Y))
if page is not None:
for child in page:
if child.tag.endswith("arc"):
arc_source = child.get("source")
arc_target = child.get("target")
arc_weight = 1
for arc_child in child:
if arc_child.tag.endswith("inscription"):
for text_arcweight in arc_child:
if text_arcweight.tag.endswith("text"):
arc_weight = int(text_arcweight.text)
if arc_source in places_dict and arc_target in trans_dict:
add_arc_from_to(places_dict[arc_source], trans_dict[arc_target], net, weight=arc_weight)
elif arc_target in places_dict and arc_source in trans_dict:
add_arc_from_to(trans_dict[arc_source], places_dict[arc_target], net, weight=arc_weight)
if finalmarkings is not None:
for child in finalmarkings:
for child2 in child:
place_id = child2.get("idref")
for child3 in child2:
if child3.tag.endswith("text"):
number = int(child3.text)
if number > 0:
fmarking[places_dict[place_id]] = number
# generate the final marking in the case has not been found
if len(fmarking) == 0:
fmarking = final_marking.discover_final_marking(net)
return net, marking, fmarking