Stochastic Robustness Explorer

Analyse stochastic playback ensembles for the synthetic medium bundle using preset sampling configurations.

import sys
from pathlib import Path

PROJECT_ROOT = Path.cwd().resolve()
while PROJECT_ROOT != PROJECT_ROOT.parent and not (PROJECT_ROOT / "pyproject.toml").exists():
    PROJECT_ROOT = PROJECT_ROOT.parent
if not (PROJECT_ROOT / "pyproject.toml").exists():
    raise RuntimeError(
        "Notebook must be executed within a FHOPS checkout (pyproject.toml not found)."
    )
if str(PROJECT_ROOT) not in sys.path:
    sys.path.insert(0, str(PROJECT_ROOT))

from docs.examples.analytics import utils

SCENARIO = PROJECT_ROOT / "examples/synthetic/medium/scenario.yaml"
ASSIGNMENTS = (
    PROJECT_ROOT / "docs/examples/analytics/data/scaling_medium_sa_assignments.csv"
)  # update with fresh assignments if desired

(tables, sampling_config) = utils.run_stochastic_summary(SCENARIO, ASSIGNMENTS, tier="medium")
print(f"Samples: {sampling_config.samples}")
tables.shift.head()

Samples: 12

	day	shift_id	machine_id	machine_role	sample_id	production_units	total_hours	idle_hours	mobilisation_cost	sequencing_violations	blackout_conflicts	available_hours	utilisation_ratio	downtime_hours	downtime_events	weather_severity_total
0	1	S1	M2	forwarder	0	14.589	8.0	0.0	0.0	0	0	8.0	1.0	0.0	0	0.1
1	2	S1	M2	forwarder	0	6.484	8.0	0.0	0.0	0	0	8.0	1.0	0.0	0	0.6
2	8	S1	M1	harvester	0	15.034	8.0	0.0	0.0	0	0	8.0	1.0	0.0	0	0.0
3	1	S1	M1	harvester	1	9.251	8.0	0.0	0.0	0	0	0.0	NaN	0.0	0	0.0
4	2	S1	M2	forwarder	1	16.210	8.0	0.0	0.0	0	0	8.0	1.0	0.0	0	0.0

Production Distribution

Inspect the distribution of production across ensemble samples.

utils.plot_distribution(
    tables.shift.groupby("sample_id")["production_units"].sum(),
    title="Production Distribution",
    xlabel="Production Units",
)