ScientificRandomExt

scirs2_core::ndarray_ext::random

Trait ScientificRandomExt 

Source 
pub trait ScientificRandomExt<A, D: Dimension> {
    // Required methods
    fn dirichlet<R>(shape: D, alpha: &[f64], rng: &mut Random<R>) -> Self
       where A: From<f64>,
             R: Rng;
    fn von_mises<R>(shape: D, mu: f64, kappa: f64, rng: &mut Random<R>) -> Self
       where A: From<f64>,
             R: Rng;
    fn multivariate_normal<R>(
        mean: Vec<f64>,
        covariance: Vec<Vec<f64>>,
        n_samples: usize,
        rng: &mut Random<R>,
    ) -> Array<A, Ix2>
       where A: From<f64>,
             R: Rng;
    fn categorical<R, T>(
        shape: D,
        choices: &[T],
        probabilities: &[f64],
        rng: &mut Random<R>,
    ) -> Array<T, D>
       where T: Clone,
             R: Rng;
    fn correlated_normal<R>(
        shape: D,
        correlation_matrix: &Array<f64, Ix2>,
        rng: &mut Random<R>,
    ) -> Self
       where A: From<f64>,
             R: Rng;
    fn sparse<R, Dist>(
        shape: D,
        density: f64,
        distribution: Dist,
        rng: &mut Random<R>,
    ) -> Self
       where A: Clone + Default,
             R: Rng,
             Dist: Distribution<A>;
}
Expand description

Scientific computing specific random array extensions

Required Methods§

Source

fn dirichlet<R>(shape: D, alpha: &[f64], rng: &mut Random<R>) -> Self
where A: From<f64>, R: Rng,

Generate random array from Dirichlet distribution

Source

fn von_mises<R>(shape: D, mu: f64, kappa: f64, rng: &mut Random<R>) -> Self
where A: From<f64>, R: Rng,

Generate random array from Von Mises distribution (circular)

Source

fn multivariate_normal<R>( mean: Vec<f64>, covariance: Vec<Vec<f64>>, n_samples: usize, rng: &mut Random<R>, ) -> Array<A, Ix2>
where A: From<f64>, R: Rng,

Generate multivariate normal samples

Source

fn categorical<R, T>( shape: D, choices: &[T], probabilities: &[f64], rng: &mut Random<R>, ) -> Array<T, D>
where T: Clone, R: Rng,

Generate samples from categorical distribution

Source

fn correlated_normal<R>( shape: D, correlation_matrix: &Array<f64, Ix2>, rng: &mut Random<R>, ) -> Self
where A: From<f64>, R: Rng,

Generate correlated random arrays using Cholesky decomposition

Source

fn sparse<R, Dist>( shape: D, density: f64, distribution: Dist, rng: &mut Random<R>, ) -> Self
where A: Clone + Default, R: Rng, Dist: Distribution<A>,

Generate random sparse arrays with specified density

Dyn Compatibility§

This trait is not dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety", so this trait is not object safe.

Implementors§

Source§

impl<A, S, D> ScientificRandomExt<A, D> for ArrayBase<S, D>
where S: DataOwned<Elem = A>, D: Dimension, A: Clone,