Struct rgsl::types::roots::RootFdfSolverType

pub struct RootFdfSolverType { /* private fields */ }

The root polishing algorithms described in this section require an initial guess for the location of the root. There is no absolute guarantee of convergence—the function must be suitable for this technique and the initial guess must be sufficiently close to the root for it to work. When these conditions are satisfied then convergence is quadratic. These algorithms make use of both the function and its derivative.

Implementations

impl RootFdfSolverType

pub fn newton() -> RootFdfSolverType

Newton’s Method is the standard root-polishing algorithm. The algorithm begins with an initial guess for the location of the root. On each iteration, a line tangent to the function f is drawn at that position. The point where this line crosses the x-axis becomes the new guess.

pub fn secant() -> RootFdfSolverType

The secant method is a simplified version of Newton’s method which does not require the computation of the derivative on every step.

pub fn steffenson() -> RootFdfSolverType

The Steffenson Method 1 provides the fastest convergence of all the routines. It com- bines the basic Newton algorithm with an Aitken “delta-squared” acceleration.

Trait Implementations

impl Clone for RootFdfSolverType

fn clone(&self) -> RootFdfSolverType

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Copy for RootFdfSolverType