Trait Convolution 

pub trait Convolution<const N: usize> {
    // Required methods
    fn border_width(&self, axis: usize) -> usize;
    fn interior(&self, axis: usize) -> &[f64];
    fn free(&self, border: Border, axis: usize) -> &[f64];
    fn scale(&self, spacing: [f64; N]) -> f64;
}

A N-dimensional tensor product of several seperable kernels.

Required Methods

fn border_width(&self, axis: usize) -> usize

fn interior(&self, axis: usize) -> &[f64]

fn free(&self, border: Border, axis: usize) -> &[f64]

fn scale(&self, spacing: [f64; N]) -> f64

Implementations on Foreign Types

impl<K0: Kernel> Convolution<1> for (K0,)

fn border_width(&self, axis: usize) -> usize

fn interior(&self, axis: usize) -> &[f64]

fn free(&self, border: Border, axis: usize) -> &[f64]

fn scale(&self, spacing: [f64; 1]) -> f64

impl<K0: Kernel, K1: Kernel> Convolution<2> for (K0, K1)

fn border_width(&self, axis: usize) -> usize

fn interior(&self, axis: usize) -> &[f64]

fn free(&self, border: Border, axis: usize) -> &[f64]

fn scale(&self, spacing: [f64; 2]) -> f64

impl<K0: Kernel, K1: Kernel, K2: Kernel> Convolution<3> for (K0, K1, K2)

fn border_width(&self, axis: usize) -> usize

fn interior(&self, axis: usize) -> &[f64]

fn free(&self, border: Border, axis: usize) -> &[f64]

fn scale(&self, spacing: [f64; 3]) -> f64

impl<K0: Kernel, K1: Kernel, K2: Kernel, K3: Kernel> Convolution<4> for (K0, K1, K2, K3)

fn border_width(&self, axis: usize) -> usize

fn interior(&self, axis: usize) -> &[f64]

fn free(&self, border: Border, axis: usize) -> &[f64]

fn scale(&self, spacing: [f64; 4]) -> f64

Implementors

impl<const N: usize, const ORDER: usize> Convolution<N> for Gradient<ORDER>

impl<const N: usize, const ORDER: usize> Convolution<N> for Hessian<ORDER>