Struct worley_noise::WorleyNoise

pub struct WorleyNoise { /* fields omitted */ }

The base noise struct.

Caches already sampled values.

Sampling individual points is relatively slow due to the internal locks.

Use the WorleyNoise::values function if possible.

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: Fn(f64, f64) -> f64 + Sync + '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: Fn(Vec<f64>) -> f64 + Sync + '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(&self, x: f64, y: f64) -> f64

Calculates the noise value for the given point.

fn values(&self, points: &Vec<(f64, f64)>) -> Vec<f64>

Calculates the noise values for the given points.

Uses multiple threads.