Difference between revisions of "PM: Transition System Miner"
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| − | Siap! Berikut script | + | 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 | + | * Cetak ringkasan jumlah '''state''' dan '''transition''' |
| − | * Simpan | + | * Simpan '''gambar TS''' (`transition_system.png`) |
| − | * Ekspor daftar | + | * Ekspor daftar '''state''' (`ts_states.csv`) dan '''transition''' (`ts_transitions.csv`) |
| − | + | '''Install dulu (sekali saja):''' | |
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| − | ## | + | pip install pm4py pandas graphviz |
| + | # pastikan sistem punya Graphviz binary (dot). Linux (Debian/Ubuntu): | ||
| + | # sudo apt-get install graphviz | ||
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| − | + | ==transition_system_miner.py== | |
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| − | from pm4py.objects.log.importer.xes import importer as xes_importer | + | #!/usr/bin/env python3 |
| − | from pm4py.algo.discovery.transition_system import algorithm as ts_discovery | + | # -*- coding: utf-8 -*- |
| − | from pm4py.visualization.transition_system import visualizer as ts_visualizer | + | |
| + | import argparse | ||
| + | import sys | ||
| + | from pathlib import Path | ||
| + | import pandas as pd | ||
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| + | 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) | ||
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| + | # 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 "" | ||
| + | }) | ||
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| + | 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}") | ||
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| + | 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), | ||
| + | ) | ||
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| + | |||
| + | if __name__ == "__main__": | ||
| + | main() | ||
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| − | + | ==Cara menjalankan (pakai file terlampir)== | |
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| − | + | 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 | ||
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| − | + | ==Opsi & catatan== | |
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| − | + | * '''Kolom kunci''' diset ke standar PM4Py: | |
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`case:concept:name`, `concept:name`, `time:timestamp`. | `case:concept:name`, `concept:name`, `time:timestamp`. | ||
Jika log Anda memakai nama kolom berbeda, ubah di `parameters`. | 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: | * 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). | |
| − | * Jika ingin | ||
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Latest revision as of 15:58, 13 September 2025
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).