PM: Transition System Miner
Revision as of 15:58, 13 September 2025 by Onnowpurbo (talk | contribs)
Siap! Berikut script Transition System Miner dengan PM4Py yang membaca file XES terlampir (`/mnt/data/BPIC_2012_A.xes`), menambang Transition System (TS), lalu:
- Cetak ringkasan jumlah state dan transition
- Simpan gambar TS (`transition_system.png`)
- Ekspor daftar state (`ts_states.csv`) dan transition (`ts_transitions.csv`)
Install dulu (sekali saja):
pip install pm4py pandas graphviz # pastikan sistem punya Graphviz binary (dot). Linux (Debian/Ubuntu): # sudo apt-get install graphviz
transition_system_miner.py
#!/usr/bin/env python3 # -*- coding: utf-8 -*- import argparse import sys from pathlib import Path import pandas as pd from pm4py.objects.log.importer.xes import importer as xes_importer from pm4py.algo.discovery.transition_system import algorithm as ts_discovery from pm4py.visualization.transition_system import visualizer as ts_visualizer
def discover_transition_system(xes_path: Path, image_out: Path, states_out: Path, trans_out: Path): # 1) Load event log log = xes_importer.apply(str(xes_path)) # 2) Discover Transition System # Parameter kunci (ubah jika perlu) parameters = { "case_glue": "case:concept:name", "activity_key": "concept:name", "timestamp_key": "time:timestamp", } ts = ts_discovery.apply(log, parameters=parameters) # 3) Visualisasi & simpan ke file gviz = ts_visualizer.apply(ts) ts_visualizer.save(gviz, str(image_out)) # 4) Ekspor states & transitions ke CSV # Struktur objek TS di PM4Py: ts.states (set of State), ts.transitions (set of Transition) # State biasanya memiliki 'name' (id) dan 'label' (representasi state) states_rows = [] for s in ts.states: sid = getattr(s, "name", None) slabel = getattr(s, "label", None) # fallback agar tetap terisi if sid is None: sid = str(s) if slabel is None: slabel = str(s) states_rows.append({"state_id": sid, "state_label": slabel}) trans_rows = [] for t in ts.transitions: # transition memiliki source (from), target (to), label (activity/event class) src = getattr(t, "from_state", getattr(t, "from", None)) dst = getattr(t, "to_state", getattr(t, "to", None)) lab = getattr(t, "label", None) # Ambil id/label state sumber & tujuan def state_id_label(state_obj): if state_obj is None: return None, None sid = getattr(state_obj, "name", None) or str(state_obj) slb = getattr(state_obj, "label", None) or str(state_obj) return sid, slb src_id, src_label = state_id_label(src) dst_id, dst_label = state_id_label(dst) trans_rows.append({ "source_id": src_id, "source_label": src_label, "target_id": dst_id, "target_label": dst_label, "transition_label": lab if lab is not None else "" }) pd.DataFrame(states_rows).to_csv(states_out, index=False) pd.DataFrame(trans_rows).to_csv(trans_out, index=False) # 5) Ringkasan print("=== Transition System Summary ===") print(f"States : {len(states_rows)}") print(f"Transitions: {len(trans_rows)}") print(f"Gambar : {image_out}") print(f"States CSV : {states_out}") print(f"Trans CSV : {trans_out}") def main(): ap = argparse.ArgumentParser(description="Transition System Miner using PM4Py (from XES)") ap.add_argument("xes_path", type=str, help="Path ke file .xes") ap.add_argument("--img", type=str, default="transition_system.png", help="Output image (PNG)") ap.add_argument("--states_csv", type=str, default="ts_states.csv", help="Output CSV daftar state") ap.add_argument("--trans_csv", type=str, default="ts_transitions.csv", help="Output CSV daftar transition") args = ap.parse_args() xes_path = Path(args.xes_path) if not xes_path.exists(): print(f"[ERROR] File tidak ditemukan: {xes_path}", file=sys.stderr) sys.exit(1) discover_transition_system( xes_path=xes_path, image_out=Path(args.img), states_out=Path(args.states_csv), trans_out=Path(args.trans_csv), ) if __name__ == "__main__": main()
Cara menjalankan (pakai file terlampir)
python transition_system_miner.py /mnt/data/BPIC_2012_A.xes \ --img ts_BPICA.png \ --states_csv ts_BPICA_states.csv \ --trans_csv ts_BPICA_transitions.csv
Opsi & catatan
- Kolom kunci diset ke standar PM4Py:
`case:concept:name`, `concept:name`, `time:timestamp`. Jika log Anda memakai nama kolom berbeda, ubah di `parameters`.
- Graphviz diperlukan agar file PNG bisa disimpan. Jika belum ada, install `graphviz` (OS) selain paket Python-nya.
- Untuk log besar, TS bisa sangat besar. Anda bisa mulai dari subset (filtering case/variant) sebelum menambang TS:
- Filter variant Top-K, atau
- Filter rentang tanggal tertentu.
- Jika ingin lihat langsung (open viewer), ganti `ts_visualizer.save(...)` menjadi `ts_visualizer.view(gviz)` (akan membuka jendela viewer apabila environment mendukung).