Module interpolation 

Interpolation & function approximation (Gap analysis §3.7).

• lagrange — Lagrange and Newton divided-difference polynomial interpolation.
• spline — natural cubic spline (tridiagonal Thomas solve) and linear interpolation.
• least_squares — polynomial least-squares fit via the normal equations.

Fail-closed (InterpolationError): empty/mismatched data, duplicate nodes, an over-high fit degree, or a singular system return an error rather than a fabricated curve.

Re-exports

pub use lagrange::lagrange_eval;

pub use lagrange::newton_coefficients;

pub use lagrange::newton_eval;

pub use least_squares::poly_eval;

pub use least_squares::poly_fit;

pub use spline::linear_interp;

pub use spline::CubicSpline;

Modules

lagrange

Polynomial interpolation through n points: the Lagrange form (direct evaluation) and the Newton divided-difference form (build coefficients once, evaluate cheaply).

least_squares

Polynomial least-squares fitting via the normal equations (VᵀV) c = Vᵀy, solved by Gaussian elimination with partial pivoting (the small (d+1)×(d+1) system).

spline

Natural cubic spline interpolation (the tridiagonal system for the second derivatives is solved with the Thomas algorithm) and piecewise-linear interpolation.

Enums

InterpolationError