Example scripts¤

The examples/ folder of the repository has one script per area of the library. Each script generates its own synthetic data and runs without input files:

python examples/quality_events_demo.py

Some scripts use optional extras; install them with pip install "ts-shape[all]" or pip install -e ".[dev]" in a clone.

Detectors by pack¤

Script	Shows
`quality_events_demo.py`	Outlier detection, SPC rules and tolerance deviation
`production_events_demo.py`	Machine state, throughput, changeover, flow constraints, OEE, alarms, batches, downtime and shift reports
`production_tracking_demo.py`	Parts, cycle times, downtime, quality and shift reports
`line_flow_analytics_demo.py`	Line balancing and takt, flow metrics and Little's law
`unit_runtime_demo.py`	Unit conversion (needs `ts-shape[units]`) and operating-hours accounting
`setpoint_events_advanced_usage.py`	Setpoint changes on simulated control loops: noise filtering, percentage and derivative settling, overshoot, control-quality KPIs, a before/after tuning comparison
`maintenance_events_demo.py`	Degradation, failure prediction and vibration analysis
`energy_events_demo.py`	Energy consumption and efficiency
`correlation_events_demo.py`	Signal correlation and anomaly correlation
`supplychain_events_demo.py`	Inventory, lead time and demand patterns

Loading, transforms and features¤

Script	Shows
`loader_usage_demo.py`	Timeseries and metadata from parquet and JSON, combined on `uuid`
`transform_operations_demo.py`	Filters, calculations and time-zone shifts
`features_statistics_demo.py`	Numeric, string, boolean and timestamp statistics (including missing values), feature tables, time-grouped statistics and cycle processing
`cycle_extractor_enhancements_demo.py`	Cycle extraction, method suggestion and validation
`context_enricher_demo.py`	Enriching signals with descriptions, units, limits and value mappings
`pipeline_demo.py`	Transforms and detectors chained in a `Pipeline`

Event log¤

Script	Shows
`eventlog_demo.py`	Detector output as an OCEL 2.0 event log, exported XES-style and as OCEL tables
`object_detection_demo.py`	OCEL objects (batches, serials) derived from id signals
`lambda_rules_demo.py`	Detectors declared as lambda rules (with `lambda_rules_demo.yaml`)