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| import pm4py | |
| import os | |
| from pm4py.util import constants, pandas_utils | |
| import importlib.util | |
| import unittest | |
| class SimplifiedInterface2Test(unittest.TestCase): | |
| def test_import_ocel_sqlite_1(self): | |
| ocel = pm4py.read_ocel("input_data/ocel/newocel.sqlite") | |
| def test_import_ocel_sqlite_2(self): | |
| ocel = pm4py.read_ocel_sqlite("input_data/ocel/newocel.sqlite") | |
| def test_export_ocel_sqlite(self): | |
| ocel = pm4py.read_ocel("input_data/ocel/newocel.jsonocel") | |
| pm4py.write_ocel(ocel, "test_output_data/newocel2.sqlite") | |
| os.remove("test_output_data/newocel2.sqlite") | |
| def test_reduce_invisibles(self): | |
| net, im, fm = pm4py.read_pnml("input_data/running-example.pnml") | |
| pm4py.reduce_petri_net_invisibles(net) | |
| def test_reduce_implicit_places(self): | |
| net, im, fm = pm4py.read_pnml("input_data/running-example.pnml") | |
| pm4py.reduce_petri_net_implicit_places(net, im, fm) | |
| def test_language_df(self): | |
| for legacy_obj in [True, False]: | |
| log = pm4py.read_xes("input_data/running-example.xes", return_legacy_log_object=legacy_obj) | |
| pm4py.get_stochastic_language(log) | |
| def test_language_log(self): | |
| log = pm4py.read_xes("input_data/running-example.xes", return_legacy_log_object=True) | |
| pm4py.get_stochastic_language(log) | |
| def test_language_model(self): | |
| net, im, fm = pm4py.read_pnml("input_data/running-example.pnml") | |
| pm4py.get_stochastic_language(net, im, fm) | |
| def test_conversion_df_to_nx(self): | |
| for legacy_obj in [True, False]: | |
| log = pm4py.read_xes("input_data/running-example.xes", return_legacy_log_object=legacy_obj) | |
| pm4py.convert_log_to_networkx(log) | |
| def test_conversion_log_to_nx(self): | |
| log = pm4py.read_xes("input_data/running-example.xes", return_legacy_log_object=True) | |
| pm4py.convert_log_to_networkx(log) | |
| def test_conversion_ocel_to_nx(self): | |
| ocel = pm4py.read_ocel("input_data/ocel/example_log.jsonocel") | |
| pm4py.convert_ocel_to_networkx(ocel) | |
| def test_conversion_df_to_ocel(self): | |
| for legacy_obj in [True, False]: | |
| log = pm4py.read_xes("input_data/running-example.xes", return_legacy_log_object=legacy_obj) | |
| pm4py.convert_log_to_ocel(log) | |
| def test_conversion_log_to_ocel(self): | |
| log = pm4py.read_xes("input_data/running-example.xes", return_legacy_log_object=True) | |
| pm4py.convert_log_to_ocel(log) | |
| def test_conversion_ocelcsv_to_ocel(self): | |
| dataframe = pandas_utils.read_csv("input_data/ocel/example_log.csv") | |
| pm4py.convert_log_to_ocel(dataframe, activity_column="ocel:activity", timestamp_column="ocel:timestamp") | |
| def test_conversion_petri_to_nx(self): | |
| net, im, fm = pm4py.read_pnml("input_data/running-example.pnml") | |
| nx_digraph = pm4py.convert_petri_net_to_networkx(net, im, fm) | |
| def test_stochastic_language(self): | |
| if importlib.util.find_spec("pyemd"): | |
| log1 = pm4py.read_xes("input_data/running-example.xes") | |
| log2 = pm4py.read_xes("input_data/running-example.xes", return_legacy_log_object=True) | |
| lang1 = pm4py.get_stochastic_language(log1) | |
| lang2 = pm4py.get_stochastic_language(log2) | |
| pm4py.compute_emd(lang1, lang2) | |
| def test_hybrid_ilp_miner(self): | |
| for legacy_obj in [True, False]: | |
| log = pm4py.read_xes("input_data/running-example.xes", return_legacy_log_object=legacy_obj) | |
| pm4py.discover_petri_net_ilp(log) | |
| if __name__ == "__main__": | |
| unittest.main() | |