def apply(tree, parameters=None):
"""
Converts the process tree into a BPMN diagram
Parameters
--------------
tree
Process tree
parameters
Parameters of the algorithm
Returns
--------------
bpmn_graph
BPMN diagram
"""
from pm4py.objects.bpmn.obj import BPMN
counts = Counts()
bpmn = BPMN()
start_event = BPMN.StartEvent(name="start", isInterrupting=True)
end_event = BPMN.EndEvent(name="end")
bpmn.add_node(start_event)
bpmn.add_node(end_event)
bpmn, counts, _, _ = recursively_add_tree(tree, tree, bpmn, start_event,
end_event, counts, 0)
bpmn = delete_tau_transitions(bpmn, counts)
return bpmn
def parse_element(bpmn_graph, counts, curr_el, parents, incoming_dict, outgoing_dict, nodes_dict, nodes_bounds,
flow_info, process=None, node=None, bpmn_element=None, flow=None, rec_depth=0):
"""
Parses a BPMN element from the XML file
"""
tag = curr_el.tag.lower()
if tag.endswith("process"):
process = curr_el.get("id")
elif tag.endswith("shape"):
bpmn_element = curr_el.get("bpmnElement")
elif tag.endswith("task"):
id = curr_el.get("id")
name = curr_el.get("name").replace("\r", "").replace("\n", "")
this_type = str(curr_el.tag)
this_type = this_type[this_type.index("}") + 1:]
task = BPMN.Task(name=name, type=this_type)
bpmn_graph.add_node(task)
node = task
nodes_dict[id] = node
elif tag.endswith("startevent"):
id = curr_el.get("id")
name = curr_el.get("name").replace("\r", " ").replace("\n", " ") if "name" in curr_el else str(uuid.uuid4())
start_event = BPMN.StartEvent(name=name)
bpmn_graph.add_node(start_event)
node = start_event
nodes_dict[id] = node
elif tag.endswith("endevent"):
id = curr_el.get("id")
name = curr_el.get("name").replace("\r", " ").replace("\n", " ") if "name" in curr_el else str(uuid.uuid4())
end_event = BPMN.EndEvent(name=name)
bpmn_graph.add_node(end_event)
node = end_event
nodes_dict[id] = node
elif tag.endswith("event"):
id = curr_el.get("id")
name = curr_el.get("name").replace("\r", " ").replace("\n", " ") if "name" in curr_el else str(uuid.uuid4())
this_type = str(curr_el.tag)
this_type = this_type[this_type.index("}") + 1:]
other_event = BPMN.OtherEvent(name=name, type=this_type)
bpmn_graph.add_node(other_event)
node = other_event
nodes_dict[id] = node
elif tag.endswith("edge"):
bpmnElement = curr_el.get("bpmnElement")
flow = bpmnElement
elif tag.endswith("exclusivegateway"):
id = curr_el.get("id")
name = curr_el.get("name").replace("\r", "").replace("\n", "") if "name" in curr_el else str(uuid.uuid4())
exclusive_gateway = BPMN.ExclusiveGateway(name=name)
bpmn_graph.add_node(exclusive_gateway)
node = exclusive_gateway
nodes_dict[id] = node
elif tag.endswith("parallelgateway"):
id = curr_el.get("id")
name = curr_el.get("name").replace("\r", "").replace("\n", "") if "name" in curr_el else str(uuid.uuid4())
parallel_gateway = BPMN.ParallelGateway(name=name)
bpmn_graph.add_node(parallel_gateway)
node = parallel_gateway
nodes_dict[id] = node
elif tag.endswith("inclusivegateway"):
id = curr_el.get("id")
name = curr_el.get("name").replace("\r", "").replace("\n", "") if "name" in curr_el else str(uuid.uuid4())
inclusive_gateway = BPMN.InclusiveGateway(name=name)
bpmn_graph.add_node(inclusive_gateway)
node = inclusive_gateway
nodes_dict[id] = node
elif tag.endswith("incoming"):
if node is not None:
incoming_dict[curr_el.text.strip()] = node
elif tag.endswith("outgoing"):
if node is not None:
outgoing_dict[curr_el.text.strip()] = node
elif tag.endswith("sequenceflow"):
seq_flow_id = curr_el.get("id")
source_ref = curr_el.get("sourceRef")
target_ref = curr_el.get("targetRef")
# fix 28/04/2021: do not assume anymore to read the nodes before the edges
incoming_dict[seq_flow_id] = target_ref
outgoing_dict[seq_flow_id] = source_ref
elif tag.endswith("waypoint"):
if flow is not None:
x = float(curr_el.get("x"))
y = float(curr_el.get("y"))
if not flow in flow_info:
flow_info[flow] = []
flow_info[flow].append((x, y))
elif tag.endswith("label"):
bpmn_element = None
elif tag.endswith("bounds"):
if bpmn_element is not None:
x = float(curr_el.get("x"))
y = float(curr_el.get("y"))
width = float(curr_el.get("width"))
height = float(curr_el.get("height"))
nodes_bounds[bpmn_element] = {"x": x, "y": y, "width": width, "height": height}
for child in curr_el:
bpmn_graph = parse_element(bpmn_graph, counts, child, list(parents) + [child], incoming_dict, outgoing_dict,
nodes_dict, nodes_bounds, flow_info, process=process, node=node,
bpmn_element=bpmn_element,
flow=flow, rec_depth=rec_depth + 1)
if rec_depth == 0:
for seq_flow_id in incoming_dict:
if incoming_dict[seq_flow_id] in nodes_dict:
incoming_dict[seq_flow_id] = nodes_dict[incoming_dict[seq_flow_id]]
for seq_flow_id in outgoing_dict:
if outgoing_dict[seq_flow_id] in nodes_dict:
outgoing_dict[seq_flow_id] = nodes_dict[outgoing_dict[seq_flow_id]]
for flow_id in flow_info:
if flow_id in outgoing_dict and flow_id in incoming_dict:
flow = BPMN.Flow(outgoing_dict[flow_id], incoming_dict[flow_id])
bpmn_graph.add_flow(flow)
flow.del_waypoints()
for waypoint in flow_info[flow_id]:
flow.add_waypoint(waypoint)
for node_id in nodes_bounds:
if node_id in nodes_dict:
bounds = nodes_bounds[node_id]
node = nodes_dict[node_id]
node.set_x(bounds["x"])
node.set_y(bounds["y"])
node.set_width(bounds["width"])
node.set_height(bounds["height"])
return bpmn_graph
def apply(net, im, fm, parameters=None):
"""
Converts an accepting Petri net into a BPMN diagram
Parameters
--------------
accepting_petri_net
Accepting Petri net (list containing net + im + fm)
parameters
Parameters of the algorithm
Returns
--------------
bpmn_graph
BPMN diagram
"""
if parameters is None:
parameters = {}
from pm4py.objects.bpmn.obj import BPMN
from pm4py.objects.bpmn.util import reduction
bpmn_graph = BPMN()
entering_dictio = {}
exiting_dictio = {}
for place in net.places:
node = BPMN.ExclusiveGateway()
bpmn_graph.add_node(node)
entering_dictio[place] = node
exiting_dictio[place] = node
for trans in net.transitions:
if trans.label is None:
if len(trans.in_arcs) > 1 or len(trans.out_arcs) > 1:
node = BPMN.ParallelGateway()
else:
node = BPMN.ExclusiveGateway()
bpmn_graph.add_node(node)
entering_dictio[trans] = node
exiting_dictio[trans] = node
else:
if len(trans.in_arcs) > 1:
entering_node = BPMN.ParallelGateway()
else:
entering_node = BPMN.ExclusiveGateway()
if len(trans.out_arcs) > 1:
exiting_node = BPMN.ParallelGateway()
else:
exiting_node = BPMN.ExclusiveGateway()
task = BPMN.Task(name=trans.label)
bpmn_graph.add_node(task)
bpmn_graph.add_flow(BPMN.Flow(entering_node, task))
bpmn_graph.add_flow(BPMN.Flow(task, exiting_node))
entering_dictio[trans] = entering_node
exiting_dictio[trans] = exiting_node
for arc in net.arcs:
bpmn_graph.add_flow(
BPMN.Flow(exiting_dictio[arc.source], entering_dictio[arc.target]))
start_node = BPMN.StartEvent()
end_node = BPMN.EndEvent()
bpmn_graph.add_node(start_node)
bpmn_graph.add_node(end_node)
for place in im:
bpmn_graph.add_flow(BPMN.Flow(start_node, entering_dictio[place]))
for place in fm:
bpmn_graph.add_flow(BPMN.Flow(exiting_dictio[place], end_node))
bpmn_graph = reduction.apply(bpmn_graph)
return bpmn_graph