sinergym.utils.common.ornstein_uhlenbeck_process

sinergym.utils.common.ornstein_uhlenbeck_process(data: DataFrame, variability_config: Dict[str, Tuple[float, float, float] | Tuple[float, float, float, Tuple[float, float]]], np_random: Generator | None = None) → DataFrame

Add noise to the data using the Ornstein-Uhlenbeck process.

Parameters:

  • data (pd.DataFrame) – Data to be modified.

  • variability_config (dict) – Noise parameters. Can be: - (sigma, mu, tau) - (sigma, mu, tau, var_range)

  • np_random (Optional[np.random.Generator]) – Random number generator for reproducible randomness. If None, uses np.random (legacy mode). Defaults to None.

Returns:

Data with noise added. Clipping applied only if var_range is provided.

Return type:

pd.DataFrame