derivkit.derivatives.local_polynomial_derivative.local_poly_config module#

Configuration for the local polynomial regression baseline.

This config controls how derivkit.local_polynomial_derivative.local_polynomial_derivative.LocalPolynomialDerivative chooses sample locations, fits the local polynomial, and decides whether the fit is trustworthy enough to mark ok=True in diagnostics.

class derivkit.derivatives.local_polynomial_derivative.local_poly_config.LocalPolyConfig(rel_steps=(0.01, 0.02, 0.04, 0.08), tol_rel: float = 0.01, tol_abs: float = 1e-10, min_samples: int = 9, max_trim: int = 10, max_degree: int = 7, center: bool = True)#

Bases: object

Configuration for the local polynomial regression baseline.

This config controls how derivkit.local_polynomial_derivative.local_polynomial_derivative.LocalPolynomialDerivative chooses sample locations, fits the local polynomial, and decides whether the fit is trustworthy enough to mark ok=True in diagnostics.

Initialize configuration.

Parameters:

  • rel_steps –

    Symmetric relative offsets around x0 used to build the default sample grid.

    • For x0 != 0 the grid is x = x0 * (1 ± rel_steps[i]).

    • For x0 == 0 the grid is x = ± rel_steps[i].

    Values are deduplicated and sorted; must be a non-empty 1D sequence.

  • tol_rel – Relative residual tolerance used when deciding whether a sample row is consistent with the current polynomial fit. A row is flagged as “bad” if any component satisfies |y_fit - y| / max(|y|, tol_abs) > tol_rel. Lower values make trimming more aggressive.

  • tol_abs – Absolute floor in the residual normalization. Prevents division by very small |y| when computing relative errors. Used as denom = max(|y|, tol_abs).

  • min_samples – Minimum number of sample points that must remain after trimming for a fit to be considered. Also used (together with max_degree) to ensure the system is not underdetermined. If trimming would reduce the usable samples below this threshold, trimming stops.

  • max_trim – Maximum number of trimming iterations. Each iteration may remove at most one point from each edge of the grid. Acts as a safety bound to avoid pathological loops on extremely noisy or adversarial data.

  • max_degree – Maximum polynomial degree allowed for the local fit. The actual degree used in differentiate() is min(max_degree, chosen_degree) where chosen_degree is usually max(order + 2, 3) or an explicit degree= passed by the caller.

  • center – If True, the polynomial is expressed in powers of (x - x0); derivatives at x0 are then read off as k! * a_k. If False, the polynomial is in powers of x directly. Centering generally improves numerical stability and is recommended.