BeTiSe — Benchmark Time Series Generator for synthetic dataset creation
Project description
BeTiSe — Benchmark Time Series Generator
A Python library for generating synthetic time series datasets with configurable statistical properties and rich metadata.
Installation
pip install betise
Quick Start
from betise import generate_dataframe, load_config
cfg = load_config(dataset={"base_series": "arma", "num_series": 5, "length_range": [300, 500]})
df, ctx = generate_dataframe(cfg)
print(df[["series_id", "time", "data", "primary_category"]].head())
Save to parquet and add feature overlays:
from betise import run, load_config
cfg = load_config(dataset={
"base_series": "ar",
"num_series": 100,
"length_range": [300, 700],
"output_dir": "output",
"output_name": "ar_trend.parquet",
"features": {
"linear_trend": {"enabled": True, "direction": "upward"},
"single_seasonality": {"enabled": True},
"point_anomaly": {"enabled": True, "is_spike": True},
},
})
run(cfg)
Series Types
| Category | Base types |
|---|---|
| Stationary | ar, ma, arma, white_noise |
| Stochastic trend | random_walk, random_walk_drift, ari, ima, arima |
| Seasonal | sarma, sarima |
| Volatility | arch, garch, egarch, aparch |
Feature Overlays
Multiple features can be stacked on top of any base type:
| Category | Features |
|---|---|
| Trend | linear_trend, quadratic_trend, cubic_trend, exponential_trend |
| Seasonality | single_seasonality, multiple_seasonality |
| Anomaly | point_anomaly, collective_anomaly, contextual_anomaly |
| Structural break | mean_shift, variance_shift, trend_shift |
Published Dataset
A large-scale benchmark dataset (120,000 series, 23.8 GB) generated with BeTiSe is available on Zenodo:
- DOI: 10.5281/zenodo.18513505
- Conference: Submitted to ITISE 2026
Documentation & Examples
Full usage guide, config reference, and ready-to-run examples are on GitHub:
github.com/ismailguzel/betise
Citation
@dataset{betise2026,
author = {Yazıcı, Pınar Cemre and Erkaya, Pelin and
Türkmen, Yağmur and Güzel, İsmail and
Karagöz, Pınar and Yozgatlıgil, Ceylan},
title = {{BeTiSe: A Benchmark Time Series Dataset for Stationarity
and Structural Analysis}},
year = {2026},
publisher = {Zenodo},
doi = {10.5281/zenodo.18513505},
url = {https://doi.org/10.5281/zenodo.18513505}
}
Contact
İsmail Güzel — ismailgzel@gmail.com
License
MIT — see LICENSE.
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