pm4py/examples/extended_marking_equation.py

import pm4py
from pm4py.algo.discovery.inductive import algorithm as inductive_miner
from pm4py.algo.analysis.marking_equation import algorithm as marking_equation
from pm4py.algo.analysis.extended_marking_equation import algorithm as extended_marking_equation
from pm4py.objects.conversion.process_tree import converter as process_tree_converter
import os
from pm4py.objects.log.importer.xes import importer as xes_importer



def execute_script():
    log = xes_importer.apply(os.path.join("..", "tests", "input_data", "receipt.xes"))
    process_tree = inductive_miner.apply(log)
    net, im, fm = process_tree_converter.apply(process_tree)
    idx = 0
    # try to resolve the marking equation to find an heuristics and possible a vector of transitions
    # leading from im to fm
    sync_net, sync_im, sync_fm = pm4py.construct_synchronous_product_net(log[idx], net, im, fm)
    me_solver = marking_equation.build(sync_net, sync_im, sync_fm)
    h, x = me_solver.solve()
    firing_sequence, reach_fm1, explained_events = me_solver.get_firing_sequence(x)
    print("for trace at index "+str(idx)+": marking equation h = ", h)
    print("x vector reaches fm = ", reach_fm1)
    print("firing sequence = ", firing_sequence)
    # it fails and the value of heuristics is low
    #
    # now let's try with extended marking equation to find the heuristics and the vector!
    eme_solver = extended_marking_equation.build(log[idx], sync_net, sync_im, sync_fm)
    h, x = eme_solver.solve()
    # the heuristics is much better
    firing_sequence, reach_fm2, explained_events = eme_solver.get_firing_sequence(x)
    print("for trace at index "+str(idx)+": extended marking equation h = ", h)
    print("x vector reaches fm = ", reach_fm2)
    print("firing sequence = ", firing_sequence)


if __name__ == "__main__":
    execute_script()