derivkit.forecasting.dali_bias module#

DALI systematic-bias tensor utilities.

derivkit.forecasting.dali_bias.build_dali_bias_tensor(function: Callable[[Sequence[float] | NDArray[floating]], floating | NDArray[floating]], theta0: Sequence[float] | NDArray[floating], cov: Sequence[Sequence[float]] | NDArray[floating], delta_nu: Sequence[float] | NDArray[floating] | Sequence[Sequence[float]], *, bias_order: int = 3, method: str | None = None, n_workers: int = 1, **dk_kwargs: Any) → dict[int, NDArray[float64]]#

Builds the systematic mismatch tensors entering the DALI bias expansion.

The tensors describe how the data-model mismatch delta_nu couples to successive derivatives of the model.

Parameters:

  • function – The scalar or vector-valued model function.

  • theta0 – Fiducial parameter values at which derivatives are evaluated.

  • cov – Covariance matrix of the observables.

  • delta_nu – Difference between two data vectors, which may represent a systematic mismatch or a difference between model predictions. Accepts a 1D array or a column vector of shape (n_observables, 1). The input is flattened internally.

  • bias_order – Highest mismatch tensor order to compute. Supported values are given in derivkit.forecasting.forecast_core.SUPPORTED_DERIVATIVE_ORDERS.

  • method – Numerical differentiation method. If None, the derivkit.derivative_kit.DerivativeKit default is used.

  • n_workers – Number of workers for per-parameter parallelization/threads. Default 1 (serial).

  • **dk_kwargs – Additional keyword arguments passed to DerivKit’s differentiation machinery.

Returns:

A dictionary mapping derivative orders 1 through bias_order to their corresponding mismatch tensors. Zeroth-order terms are omitted because they are independent of the parameter displacement.

Raises:

  • TypeError – If bias_order is not an integer.

  • ValueError – If bias_order is unsupported, theta0 is empty, or the data mismatch does not match the number of observables.