Struct worley_noise::WorleyNoise

pub struct WorleyNoise { /* fields omitted */ }

The base noise struct

Caches already sampled values

Methods

impl WorleyNoise

fn new() -> Self

Creates a new noise struct with random permutation arrays

Uses a default density of 3.0 and a cache capacity of 1000

fn with_cache_capacity(capacity: usize) -> Self

Initializes the struct with the specified cache capacity

fn permutate(&mut self, permutation_table_bit_length: usize)

Calls permutate_seeded with a random seed

fn permutate_seeded(&mut self, permutation_table_bit_length: usize, seed: usize)

Randomizes the internal permutation arrays

Might be slow

fn set_density(&mut self, density: f64)

Sets the density

Might be slow since it precomputes a lot of stuff

Default is 3.0

fn set_distance_function<F>(&mut self, function: F) where
    F: FnMut(f64, f64) -> f64 + 'static, 

Sets the function to calculate the distance between feature points

Default is the squared Euclidean distance

fn set_value_function<F>(&mut self, function: F) where
    F: FnMut(Vec<f64>) -> f64 + 'static, 

Sets the function to pick the final value from the nearby feature points

The values are in no particular order

Default is the minimum value

fn set_radius(&mut self, radius: u16)

Specifies how many adjacent cells should be included in the calculation

A higher radius reduces the amount of possible errors but slows down sampling of individual points

Shouldn't affect performance too much when iterating over a lot of points since the values get cached anyway

Default is 1

fn value(&mut self, x: f64, y: f64) -> f64

Calculates the noise value for the given point