Quick Start

Complete Pipeline

import ergminer

# 1. Load
log = ergminer.read_csv(
    "data/event_log.csv",
    case_id_col="case_id",
    activity_col="activity_name",
    timestamp_col="timestamp",
    resource_col="resource_id",
)

# 2. Discover
erg = ergminer.discover_erg(log, verbose=True)
erg.print_summary()

# 3. Export
ergminer.write_ergml(erg,    "output/erg.ergml", sim_time=10000.0)
ergminer.write_erg_json(erg, "output/erg.json")
ergminer.write_dot(erg,      "output/erg.dot")

# 4. Visualise
ergminer.save_vis_erg(erg, "output/erg.png", show_probabilities=True)

# 5. Simulate
sim_log = ergminer.play_out(erg, n=10, sim_time=10000.0, seed=42)

# 6. Conformance
result = ergminer.conformance_erg(log, erg, sim_log=sim_log, verbose=True)
result.print_report()

scores = {grp: info["score"] for grp, info in result.group_scores.items()}
print("Group scores:", scores)

Run the Example Script

A fully configured pipeline script is included:

python examples/basic_usage.py

Edit the CONFIG section at the top of the file to change the input log, column names, or simulation parameters.