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| import os | |
| import pm4py | |
| from pm4py.util import constants, pandas_utils | |
| from pm4py.algo.discovery.dfg.adapters.pandas import df_statistics | |
| from pm4py.objects.conversion.dfg import converter as dfg_conv | |
| from pm4py.statistics.attributes.pandas import get as att_get | |
| from pm4py.statistics.end_activities.pandas import get as ea_get | |
| from pm4py.statistics.service_time.pandas import get as soj_time_get | |
| from pm4py.statistics.concurrent_activities.pandas import get as conc_act_get | |
| from pm4py.statistics.eventually_follows.pandas import get as efg_get | |
| from pm4py.statistics.start_activities.pandas import get as sa_get | |
| from examples import examples_conf | |
| import importlib.util | |
| def execute_script(): | |
| log_path = os.path.join("..", "tests", "input_data", "interval_event_log.csv") | |
| dataframe = pandas_utils.read_csv(log_path) | |
| log_path = os.path.join("..", "tests", "input_data", "reviewing.xes") | |
| log = pm4py.read_xes(log_path) | |
| dataframe = pm4py.convert_to_dataframe(log) | |
| parameters = {} | |
| #parameters[constants.PARAMETER_CONSTANT_START_TIMESTAMP_KEY] = "start_timestamp" | |
| parameters[constants.PARAMETER_CONSTANT_TIMESTAMP_KEY] = "time:timestamp" | |
| parameters[constants.PARAMETER_CONSTANT_ACTIVITY_KEY] = "concept:name" | |
| parameters[constants.PARAMETER_CONSTANT_CASEID_KEY] = "case:concept:name" | |
| parameters["strict"] = True | |
| parameters["format"] = examples_conf.TARGET_IMG_FORMAT | |
| start_activities = sa_get.get_start_activities(dataframe, parameters=parameters) | |
| end_activities = ea_get.get_end_activities(dataframe, parameters=parameters) | |
| att_count = att_get.get_attribute_values(dataframe, "concept:name", parameters=parameters) | |
| parameters["start_activities"] = start_activities | |
| parameters["end_activities"] = end_activities | |
| soj_time = soj_time_get.apply(dataframe, parameters=parameters) | |
| print("soj_time") | |
| print(soj_time) | |
| conc_act = conc_act_get.apply(dataframe, parameters=parameters) | |
| print("conc_act") | |
| print(conc_act) | |
| efg = efg_get.apply(dataframe, parameters=parameters) | |
| print("efg") | |
| print(efg) | |
| if importlib.util.find_spec("graphviz"): | |
| from pm4py.visualization.dfg import visualizer as dfg_vis_fact | |
| from pm4py.visualization.petri_net import visualizer as pn_vis | |
| dfg_freq, dfg_perf = df_statistics.get_dfg_graph(dataframe, measure="both", start_timestamp_key="start_timestamp") | |
| dfg_gv_freq = dfg_vis_fact.apply(dfg_freq, activities_count=att_count, variant=dfg_vis_fact.Variants.FREQUENCY, | |
| serv_time=soj_time, parameters=parameters) | |
| dfg_vis_fact.view(dfg_gv_freq) | |
| dfg_gv_perf = dfg_vis_fact.apply(dfg_perf, activities_count=att_count, variant=dfg_vis_fact.Variants.PERFORMANCE, | |
| serv_time=soj_time, parameters=parameters) | |
| dfg_vis_fact.view(dfg_gv_perf) | |
| net, im, fm = dfg_conv.apply(dfg_freq) | |
| gviz = pn_vis.apply(net, im, fm, parameters=parameters) | |
| pn_vis.view(gviz) | |
| if __name__ == "__main__": | |
| execute_script() | |