[−][src]Struct gauss_quad::GaussLaguerre

pub struct GaussLaguerre {
    pub nodes: Vec<f64>,
    pub weights: Vec<f64>,
}

Fields

nodes: Vec<f64>weights: Vec<f64>

Implementations

impl GaussLaguerre[src]

pub fn init(deg: usize, alpha: f64) -> GaussLaguerre[src]

pub fn nodes_and_weights(deg: usize, alpha: f64) -> (Vec<f64>, Vec<f64>)[src]

Apply Golub-Welsch algorithm to determine Gauss-Laguerre nodes & weights construct companion matrix A for the Laguerre Polynomial using the relation: -n L_{n-1} + (2n+1) L_{n} -(n+1) L_{n+1} = x L_n The constructed matrix is symmetric and tridiagonal with (2n+1) on the diagonal & -(n+1) on the off-diagonal (n = row number). Root & weight finding are equivalent to eigenvalue problem. see Gil, Segura, Temme - Numerical Methods for Special Functions

pub fn integrate<F>(&self, integrand: F) -> f64 where
    F: Fn(f64) -> f64, [src]

Perform quadrature of integrand using given nodes x and weights w

Auto Trait Implementations

Blanket Implementations

impl<T> Any for T where
    T: 'static + ?Sized, [src]

impl<T> Borrow<T> for T where
    T: ?Sized, [src]

impl<T> BorrowMut<T> for T where
    T: ?Sized, [src]

impl<T> From<T> for T[src]

impl<T, U> Into<U> for T where
    U: From<T>, [src]

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type Output = T

Should always be Self

impl<SS, SP> SupersetOf<SS> for SP where
    SS: SubsetOf<SP>, 

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    U: Into<T>, [src]

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    U: TryFrom<T>, [src]

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