def test_bpmn_exporting(self):
bpmn_graph = bpmn_importer.apply(
os.path.join("input_data", "running-example.bpmn"))
bpmn_exporter.apply(
bpmn_graph, os.path.join("test_output_data",
"running-example.bpmn"))
os.remove(os.path.join("test_output_data", "running-example.bpmn"))
def test_bpmn_to_petri_net(self):
log = pm4py.read_xes(os.path.join("input_data", "running-example.xes"))
bpmn_graph = bpmn_importer.apply(
os.path.join("input_data", "running-example.bpmn"))
net, im, fm = bpmn_converter.apply(
bpmn_graph, variant=bpmn_converter.Variants.TO_PETRI_NET)
fitness_tbr = pm4py.fitness_token_based_replay(log, net, im, fm)
def execute_script():
log = pm4py.read_xes(os.path.join("..", "tests", "input_data", "running-example.xes"))
bpmn_graph = bpmn_importer.apply(os.path.join("..", "tests", "input_data", "running-example.bpmn"))
net, im, fm = bpmn_converter.apply(bpmn_graph, variant=bpmn_converter.Variants.TO_PETRI_NET)
precision_tbr = pm4py.precision_token_based_replay(log, net, im, fm)
print("precision", precision_tbr)
fitness_tbr = pm4py.precision_token_based_replay(log, net, im, fm)
print("fitness", fitness_tbr)
print(pm4py.check_soundness(net, im, fm))
def read_bpmn(file_path):
"""
Reads a BPMN from a .bpmn file
Parameters
---------------
file_path
File path
Returns
---------------
bpmn_graph
BPMN graph
"""
from pm4py.objects.bpmn.importer import importer as bpmn_importer
bpmn_graph = bpmn_importer.apply(file_path)
return bpmn_graph
bpmn_output_path = bpmn_output_path.name
log_path = os.path.join(LOGS_FOLDER, log_name)
print("")
print(log_path)
log = pm4py.read_xes(log_path)
fp_log = pm4py.algo.discovery.footprints.log.variants.entire_event_log.apply(
log)
net, im, fm = pm4py.discover_petri_net_heuristics(log)
fitness0 = pm4py.evaluate_fitness_alignments(log, net, im, fm)
precision0 = pm4py.evaluate_precision_alignments(log, net, im, fm)
print("fitness 0", fitness0)
print("precision 0", precision0)
bpmn_graph = pm4py.objects.conversion.wf_net.variants.to_bpmn.apply(
net, im, fm)
bpmn_graph = layouter.apply(bpmn_graph)
exporter.apply(bpmn_graph, bpmn_output_path)
bpmn_graph = importer.apply(bpmn_output_path)
bpmn_graph = layouter.apply(bpmn_graph)
# gets the net back
net, im, fm = pm4py.objects.conversion.bpmn.variants.to_petri_net.apply(
bpmn_graph)
gviz = pn_visualizer.apply(net, im, fm)
pn_visualizer.view(gviz)
fitness1 = pm4py.evaluate_fitness_alignments(log, net, im, fm)
precision1 = pm4py.evaluate_precision_alignments(log, net, im, fm)
print("fitness 1", fitness1, fitness0 == fitness1)
print("precision 1", precision1, precision0 == precision1)
if not (fitness0 == fitness1 and precision0 == precision1):
print("ALERT")
input()
def test_bpmn_importing_and_layouting(self):
bpmn_graph = bpmn_importer.apply(os.path.join("input_data", "running-example.bpmn"))
bpmn_graph = bpmn_layouter.apply(bpmn_graph)