Struct rgsl::types::roots::RootFdfSolverType
source · pub struct RootFdfSolverType { /* private fields */ }
Expand description
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§
source§impl RootFdfSolverType
impl RootFdfSolverType
sourcepub fn newton() -> 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.
sourcepub fn secant() -> RootFdfSolverType
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.
sourcepub fn steffenson() -> RootFdfSolverType
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§
source§impl Clone for RootFdfSolverType
impl Clone for RootFdfSolverType
source§fn clone(&self) -> RootFdfSolverType
fn clone(&self) -> RootFdfSolverType
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
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