from pm4py.objects.log.importer.xes import importer from pm4py.algo.filtering.log.variants import variants_filter from pm4py.algo.discovery.inductive import algorithm as inductive_miner from pm4py.objects.conversion.process_tree import converter from pm4py.algo.discovery.footprints import algorithm as footprints_discovery from pm4py.algo.conformance.footprints import algorithm as footprints_conformance import os from examples import examples_conf import importlib.util def execute_script(): # import a log log = importer.apply(os.path.join("..", "tests", "input_data", "receipt.xes")) # found a filtered version of the log that is used to discover a process model filtered_log = variants_filter.filter_log_variants_percentage(log, 0.2) # discover a process tree using inductive miner tree = inductive_miner.apply(filtered_log) print(tree) # apply the conversion of a process tree into a Petri net net, im, fm = converter.apply(tree) # Footprints discovery: discover a list of footprints # for all the cases of the log fp_log = footprints_discovery.apply(log) # discover the footpritns from the process tree fp_tree = footprints_discovery.apply(tree) # discover the footpritns from the Petri net fp_net = footprints_discovery.apply(net, im) print(len(fp_tree["sequence"]), len(fp_tree["parallel"]), len(fp_net["sequence"]), len(fp_net["parallel"])) print(fp_tree["sequence"] == fp_net["sequence"] and fp_tree["parallel"] == fp_net["parallel"]) # apply the footprints conformance checking conf = footprints_conformance.apply(fp_log, fp_net) for trace_an in conf: if trace_an: # print the first anomalous trace (containing deviations # that are contained in the trace but not allowed by the model) print(trace_an) break # finds the footprints for the entire log (not case-by-case, but taking # the relations that appear inside the entire log) fp_log_entire = footprints_discovery.apply(log, variant=footprints_discovery.Variants.ENTIRE_EVENT_LOG) if importlib.util.find_spec("graphviz"): # visualize the footprint table from pm4py.visualization.footprints import visualizer as fp_visualizer gviz = fp_visualizer.apply(fp_log_entire, fp_net, parameters={"format": examples_conf.TARGET_IMG_FORMAT}) fp_visualizer.view(gviz) if __name__ == "__main__": execute_script()