Struct RandomField 

pub struct RandomField {
    pub grid: Array2<f64>,
    pub covariance: CorrelationFunction,
}

A realised random field on a 2-D grid.

Fields

grid: Array2<f64>

Grid values, shape [nx, ny].

covariance: CorrelationFunction

Covariance structure used to generate this field.

Implementations

impl RandomField

pub fn sample_circulant_embedding( grid_x: ArrayView1<'_, f64>, grid_y: ArrayView1<'_, f64>, cov: CorrelationFunction, rng: &mut StdRng, ) -> IntegrateResult<Array2<f64>>

Sample a Gaussian random field using the circulant embedding method.

Embeds the covariance into a [2nx × 2ny] circulant block matrix, computes eigenvalues via 2-D FFT, and multiplies complex Gaussian noise by the square-root eigenvalues in the frequency domain.

Errors

Returns an error if nx or ny is zero.

pub fn sample_kl_expansion( grid_x: ArrayView1<'_, f64>, grid_y: ArrayView1<'_, f64>, cov: CorrelationFunction, n_terms: usize, rng: &mut StdRng, ) -> IntegrateResult<Array2<f64>>

Sample a Gaussian random field using the Karhunen-Loève expansion.

Builds the discrete covariance matrix over a flattened [nx × ny] grid, extracts leading n_terms eigenpairs via power iteration, then assembles:

u(x) = Σ_{k=1}^{n_terms} sqrt(λ_k) * ξ_k * φ_k(x)

Errors

Returns an error if the grid or n_terms is invalid.

pub fn sample_fourier( nx: usize, ny: usize, lx: f64, ly: f64, cov: CorrelationFunction, rng: &mut StdRng, ) -> IntegrateResult<Array2<f64>>

Sample a Gaussian random field using the Fourier spectral method.

Assumes periodic BCs and separable (isotropic) covariance.

Errors

Returns an error if nx or ny is zero.

Trait Implementations

impl Clone for RandomField

fn clone(&self) -> RandomField

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for RandomField

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.