derivkit.calculus.gradient module

Contains functions used to construct the gradient of scalar-valued functions.

derivkit.calculus.gradient.build_gradient(function: Callable, theta0: ndarray, method: str | None = None, n_workers=1, **dk_kwargs: dict) → ndarray

Returns the gradient of a scalar-valued function.

Parameters:

  • function (Callable) – The function to be differentiated.

  • theta0 (array-like) – The parameter vector at which the gradient is evaluated.

  • method – Method name or alias (e.g., “adaptive”, “finite”). If None, the DerivativeKit default (“adaptive”) is used.

  • n_workers (int) – Number of workers used by DerivativeKit.adaptive.differentiate. This setting does not parallelize across parameters. Default is 1.

  • dk_kwargs (dict, optional) – Additional keyword arguments passed to DerivativeKit.differentiate.

Returns:

A 1D array representing the gradient.

Raises:

TypeError – If function does not return a scalar value.