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Runtime error
Runtime error
| from pm4py.objects.log.importer.xes import importer as xes_importer | |
| from pm4py.algo.discovery.inductive import algorithm as inductive_miner | |
| from pm4py.algo.conformance.alignments.decomposed import algorithm as dec_align | |
| from pm4py.algo.evaluation.replay_fitness import algorithm as rep_fit | |
| from pm4py.objects.conversion.process_tree import converter as process_tree_converter | |
| import os | |
| import time | |
| def execute_script(): | |
| # import the a32f0n00 log | |
| log = xes_importer.apply(os.path.join("..", "tests", "compressed_input_data", "09_a32f0n00.xes.gz")) | |
| # discover a model using the inductive miner | |
| process_tree = inductive_miner.apply(log) | |
| net, im, fm = process_tree_converter.apply(process_tree) | |
| # apply the alignments decomposition with a maximal number of border disagreements set to 5 | |
| aa = time.time() | |
| aligned_traces = dec_align.apply(log, net, im, fm, parameters={ | |
| dec_align.Variants.RECOMPOS_MAXIMAL.value.Parameters.PARAM_THRESHOLD_BORDER_AGREEMENT: 5}) | |
| bb = time.time() | |
| print(bb-aa) | |
| # print(aligned_traces) | |
| # calculate the fitness over the recomposed alignment (use the classical evaluation) | |
| fitness = rep_fit.evaluate(aligned_traces, variant=rep_fit.Variants.ALIGNMENT_BASED) | |
| print(fitness) | |
| if __name__ == "__main__": | |
| execute_script() | |