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| import os | |
| import unittest | |
| from pm4py.algo.discovery.heuristics import algorithm as heuristics_miner | |
| from pm4py.objects.log.util import dataframe_utils | |
| from pm4py.objects.log.importer.xes import importer as xes_importer | |
| from pm4py.visualization.heuristics_net import visualizer as hn_vis | |
| from pm4py.visualization.petri_net import visualizer as pn_vis | |
| from pm4py.util import constants, pandas_utils | |
| from tests.constants import INPUT_DATA_DIR | |
| class HeuMinerTest(unittest.TestCase): | |
| def test_heunet_running_example(self): | |
| # to avoid static method warnings in tests, | |
| # that by construction of the unittest package have to be expressed in such way | |
| self.dummy_variable = "dummy_value" | |
| log = xes_importer.apply(os.path.join(INPUT_DATA_DIR, "running-example.xes")) | |
| heu_net = heuristics_miner.apply_heu(log) | |
| gviz = hn_vis.apply(heu_net) | |
| del gviz | |
| def test_petrinet_running_example(self): | |
| # to avoid static method warnings in tests, | |
| # that by construction of the unittest package have to be expressed in such way | |
| self.dummy_variable = "dummy_value" | |
| log = xes_importer.apply(os.path.join(INPUT_DATA_DIR, "running-example.xes")) | |
| net, im, fm = heuristics_miner.apply(log) | |
| gviz = pn_vis.apply(net, im, fm) | |
| del gviz | |
| def test_petrinet_receipt_df(self): | |
| # to avoid static method warnings in tests, | |
| # that by construction of the unittest package have to be expressed in such way | |
| self.dummy_variable = "dummy_value" | |
| df = pandas_utils.read_csv(os.path.join(INPUT_DATA_DIR, "receipt.csv")) | |
| df = dataframe_utils.convert_timestamp_columns_in_df(df, timest_format=constants.DEFAULT_TIMESTAMP_PARSE_FORMAT) | |
| net, im, fm = heuristics_miner.apply(df) | |
| gviz = pn_vis.apply(net, im, fm) | |
| del gviz | |
| def test_heuplusplus_perf_df(self): | |
| df = pandas_utils.read_csv(os.path.join(INPUT_DATA_DIR, "interval_event_log.csv")) | |
| df = dataframe_utils.convert_timestamp_columns_in_df(df, timest_format=constants.DEFAULT_TIMESTAMP_PARSE_FORMAT) | |
| heu_net = heuristics_miner.Variants.PLUSPLUS.value.apply_heu_pandas(df, parameters={"heu_net_decoration": "performance"}) | |
| gviz = hn_vis.apply(heu_net) | |
| def test_heuplusplus_perf_log(self): | |
| log = xes_importer.apply(os.path.join(INPUT_DATA_DIR, "interval_event_log.xes")) | |
| heu_net = heuristics_miner.apply_heu(log, variant=heuristics_miner.Variants.PLUSPLUS, parameters={"heu_net_decoration": "performance"}) | |
| gviz = hn_vis.apply(heu_net) | |
| def test_heuplusplus_petri_df(self): | |
| df = pandas_utils.read_csv(os.path.join(INPUT_DATA_DIR, "interval_event_log.csv")) | |
| df = dataframe_utils.convert_timestamp_columns_in_df(df, timest_format=constants.DEFAULT_TIMESTAMP_PARSE_FORMAT) | |
| net, im, fm = heuristics_miner.Variants.PLUSPLUS.value.apply_pandas(df) | |
| gviz = pn_vis.apply(net, im, fm) | |
| def test_heuplusplus_petri_log(self): | |
| log = xes_importer.apply(os.path.join(INPUT_DATA_DIR, "interval_event_log.xes")) | |
| net, im, fm = heuristics_miner.apply(log, variant=heuristics_miner.Variants.PLUSPLUS) | |
| gviz = pn_vis.apply(net, im, fm) | |
| if __name__ == "__main__": | |
| unittest.main() | |