58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
%reset
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import pm4py
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import pandas as pd
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import numpy as np
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import matplotlib.pyplot as plt
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from pm4py.visualization.petri_net import visualizer as pn_visualizer
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parameters = {pn_visualizer.Variants.FREQUENCY.value.Parameters.FORMAT: "png"}
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###### Load data and create event logs ######
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dat = pd.read_csv("results/haum/event_logfiles_2024-01-02_19-44-50.csv", sep = ";")
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dat = dat[dat["date.start"] < "2020-03-13"]
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dat = dat[dat["path"] != 81621] # exclude broken trace
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# --> only pre corona (before artworks were updated)
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event_log = pm4py.format_dataframe(dat, case_id='case', activity_key='event',
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timestamp_key='date.start')
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event_log.event.value_counts()
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event_log.event.value_counts(normalize=True)
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dfg, start_activities, end_activities = pm4py.discover_dfg(event_log)
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pm4py.view_dfg(dfg, start_activities, end_activities)
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#filtered_log = pm4py.filter_event_attribute_values(event_log, 'item', [80])
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i_net, im, fm = pm4py.discover_petri_net_inductive(event_log)
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pm4py.vis.view_petri_net(i_net, im, fm)
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gviz = pn_visualizer.apply(i_net, im, fm, parameters=parameters,
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variant=pn_visualizer.Variants.FREQUENCY,
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log=event_log)
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pn_visualizer.view(gviz)
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len(i_net.places)
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len(i_net.transitions)
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len(i_net.arcs)
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a_net, im, fm = pm4py.discover_petri_net_alpha(event_log)
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pm4py.vis.view_petri_net(a_net, im, fm)
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gviz = pn_visualizer.apply(a_net, im, fm, parameters=parameters,
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variant=pn_visualizer.Variants.FREQUENCY,
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log=event_log)
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pn_visualizer.view(gviz)
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len(a_net.places)
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len(a_net.transitions)
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len(a_net.arcs)
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h_net, im, fm = pm4py.discover_petri_net_heuristics(filtered_log)
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pm4py.vis.view_petri_net(h_net, im, fm)
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len(h_net.places)
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len(h_net.transitions)
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len(h_net.arcs)
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