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//!
//! Fuss - Small, lightweight simplex noise generator for Rust
//!
//! Ported from http://staffwww.itn.liu.se/~stegu/simplexnoise/simplexnoise.pdf
//! originally in Java.
//!
#![crate_type = "lib"]
#![crate_name = "fuss"]
mod test;
extern crate rand;
use rand::{thread_rng, SeedableRng, Rng, StdRng};
// Constants
// Skew 2D
const F2 : f32 = 0.366025403;
// Unskew 2D
const G2 : f32 = 0.211324865;
// Skew 3D
const F3 : f32 = 1.0/3.0;
// Unskew 3D
const G3 : f32 = 1.0/6.0;
const GRAD3: [(i8, i8, i8); 12] = [
(1, 1, 0), (-1, 1, 0), (1, -1, 0), (-1, -1, 0),
(1, 0, 1), (-1, 0, 1), (1, 0, -1), (-1, 0, -1),
(0, 1, 1), (0, -1, 1), (0, 1, -1), (0, -1, -1),
];
// Vector math
///
/// Find dot product of a vector in 2 dimensions
///
#[inline]
fn dot2(g: (i8, i8, i8), x: f32, y: f32) -> f32 {
g.0 as f32 * x + g.1 as f32 * y
}
///
/// Find dot product of a vector in 3 dimensions
///
#[inline]
fn dot3(g: (i8, i8, i8), x: f32, y: f32, z: f32) -> f32 {
g.0 as f32 * x + g.1 as f32 * y + g.2 as f32 * z
}
// Generate a seed
#[inline]
pub fn generate_seed() -> Vec<usize> {
thread_rng().gen_iter::<usize>().take(256).collect::<Vec<usize>>()
}
///
/// Hold the proper permutation tables and methods for generating 2D and 3D noise.
///
/// It is intended for you to get a `Simplex` through `Simplex::new()` since that
/// creates the necessary permutation tables needed to generate noise.
///
/// Noise generated by `Simplex` is random every time.
///
/// * `seed` - Seed that will be used by `Simplex` to generate it's permutation table
///
pub struct Simplex {
pub seed: Vec<usize>,
perm: Vec<u8>,
}
impl Simplex {
///
/// Return a new `Simplex` with a new random permutation table
///
/// Necessary to generate the proper permutation tables (GRAD3)
/// used by `noise_2d()` and `noise_3d`.
///
/// # Examples
///
/// ```
/// use fuss::Simplex;
///
/// let sn = Simplex::new();
/// ```
///
pub fn new() -> Simplex {
return Simplex::from_seed(generate_seed());
}
///
/// Seed the random number generator with a specific
/// seed
///
/// A seed is just a vector of usizes that will be passed into
/// `StdRng::from_seed` as a slice.
///
/// # Examples
///
/// ```
/// use fuss::Simplex;
///
/// let mut sn = Simplex::from_seed(vec![1, 2, 3]);
/// let mut other_sn = Simplex::from_seed(vec![1, 2, 3]);
///
/// assert_eq!(other_sn.noise_2d(1.0, 14.2), sn.noise_2d(1.0, 14.2));
/// assert_eq!(other_sn.noise_3d(1.0, 14.2, -5.4), sn.noise_3d(1.0, 14.2, -5.4));
///
/// sn = Simplex::from_seed(vec![4, 5, 6]);
/// let mut other_sn = Simplex::from_seed(vec![1, 2, 3]);
/// assert!(other_sn.noise_2d(1.0, 14.2) != sn.noise_2d(1.0, 14.2));
/// assert!(other_sn.noise_3d(1.0, 14.2, -5.4) != sn.noise_3d(1.0, 14.2, -5.4));
/// ```
///
pub fn from_seed(seed: Vec<usize>) -> Simplex {
let mut sn = Simplex {
seed: seed,
perm: Vec::new() // Gets overwritten
};
sn.generate_perms();
return sn;
}
///
/// Generate the permutation table
///
/// This method will overwrite the `Simplex`'s current `perm` vector
/// with another random permutation table used by `noise_2d()` and
/// `noise_3d`
///
fn generate_perms(&mut self) {
let p : Vec<u8> = StdRng::from_seed(&self.seed).gen_iter().take(256).collect::<Vec<u8>>();
self.perm = Vec::<u8>::new();
for i in 0..512 {
self.perm.push(p[(i & 255) as usize]);
}
}
///
/// Smooth the output from `noise_2d` based on fractal Brownian motion.
///
/// Returns an f32 in [-1, 1]
///
/// # Examples
///
/// ```
/// use fuss::Simplex;
///
/// let sn = Simplex::new();
///
/// let mut luminance = Vec::<Vec<f32>>::new();
/// for x in 0..100 {
/// luminance.push(Vec::<f32>::new());
/// for y in 0..100 {
/// luminance[x as usize].push(sn.sum_octave_2d(16, x as f32, y as f32, 0.5, 0.008));
/// }
/// }
/// ```
///
pub fn sum_octave_2d(&self, num_iterations: isize, xin: f32, yin: f32, persistence : f32, scale : f32) -> f32 {
let mut max_amp = 0.0;
let mut amp = 1.0;
let mut freq = scale;
let mut noise = 0.0;
// Add successively smaller, higher-frequency terms
for _ in 0..num_iterations {
noise += self.noise_2d(xin * freq, yin * freq) * amp;
max_amp += amp;
amp *= persistence;
freq *= 2.0;
}
// Take the average value of the iterations
return noise / max_amp;
}
///
/// Smooth the output from `noise_3d` based on fractal Brownian motion.
///
/// Returns an f32 in [-1, 1]
///
/// # Examples
///
/// ```
/// use fuss::Simplex;
///
/// let sn = Simplex::new();
///
/// let mut luminance = Vec::<Vec<Vec<f32>>>::new();
/// for x in 0..10 {
/// luminance.push(Vec::<Vec<f32>>::new());
/// for y in 0..10 {
/// luminance[x as usize].push(Vec::<f32>::new());
/// for z in 0..10 {
/// luminance[x as usize][y as usize].push(sn.sum_octave_3d(16, x as f32, y as f32, z as f32, 0.5, 0.008));
/// }
/// }
/// }
/// ```
///
pub fn sum_octave_3d(&self, num_iterations: isize, xin: f32, yin: f32, zin: f32, persistence : f32, scale : f32) -> f32 {
let mut max_amp = 0.0;
let mut amp = 1.0;
let mut freq = scale;
let mut noise = 0.0;
// Add successively smaller, higher-frequency terms
for _ in 0..num_iterations {
noise += self.noise_3d(xin * freq, yin * freq, zin * freq) * amp;
max_amp += amp;
amp *= persistence;
freq *= 2.0;
}
// Take the average value of the iterations
return noise / max_amp;
}
///
/// Generate 2D simplex noise for a specific point
///
/// Returns an f32 in [-1, 1].
///
/// # Examples
///
/// ```
/// use fuss::Simplex;
///
/// let sn = Simplex::from_seed(vec![5, 3, 2, 1, 1]);
/// println!("{}", sn.noise_2d(50.1912, 30.50102));
///
/// // Simplex will return the same thing for the same points
/// assert_eq!(sn.noise_2d(1.5, -0.5), sn.noise_2d(1.5, -0.5));
///
/// let other_sn = Simplex::from_seed(vec![0, 1, 2, 3, 4, 5]);
///
/// // However each `Simplex` has it's own set of permutations, therefore
/// // each one is different. If you want consistency, try the `from_seed()` method.
/// assert!(sn.noise_2d(1.5, -0.5) != other_sn.noise_2d(1.5, -0.5));
/// ```
///
pub fn noise_2d(&self, xin: f32, yin: f32) -> f32 {
// Noise contributions from the three corners
let n0 : f32;
let n1 : f32;
let n2 : f32;
// Hairy factor for 2D
let s = (xin + yin) * F2;
let i = (xin + s).floor() as isize;
let j = (yin + s).floor() as isize;
let t = (i + j) as f32 * G2;
// Unskew the cell origin back to (x,y) space
// and get he x,y distances from the cell origin
let x0 = xin - (i as f32 - t);
let y0 = yin - (j as f32 - t);
// For the 2D case, the simplex shape is an equilateral triangle.
// Determine which simplex we are in.
// Offsets for second (middle) corner of simplex in (i,j) coords
let i1 : isize;
let j1 : isize;
// lower triangle, XY order: (0,0)->(1,0)->(1,1)
if x0 > y0 {
i1 = 1;
j1 = 0;
}
// upper triangle, YX order: (0,0)->(0,1)->(1,1)
else {
i1 = 0;
j1 = 1;
}
// A step of (1,0) in (i,j) means a step of (1-c,-c) in (x,y), and
// a step of (0,1) in (i,j) means a step of (-c,1-c) in (x,y), where
// c = (3-sqrt(3))/6
// Offsets for middle corner in (x,y) unskewed coords
let x1 = x0 - i1 as f32 + G2;
let y1 = y0 - j1 as f32 + G2;
// Offsets for last corner in (x,y) unskewed coords
let x2 = x0 - 1.0 + 2.0 * G2;
let y2 = y0 - 1.0 + 2.0 * G2;
// Work out the hashed gradient indices of the three simplex corners
let ii = i & 255;
let jj = j & 255;
let gi0 = self.perm[(ii + self.perm[jj as usize] as isize) as usize ] % 12;
let gi1 = self.perm[(ii + i1 + self.perm[(jj + j1) as usize] as isize) as usize ] % 12;
let gi2 = self.perm[(ii + 1 + self.perm[ (jj + 1) as usize] as isize) as usize] % 12;
let mut t0 = 0.5 - x0*x0-y0*y0;
if t0 < 0.0 {
n0 = 0.0;
} else {
t0 *= t0;
n0 = t0 * t0 * dot2(GRAD3[gi0 as usize], x0, y0);
}
let mut t1 = 0.5 - x1*x1-y1*y1;
if t1 < 0. {
n1 = 0.0;
} else {
t1 *= t1;
n1 = t1 * t1 * dot2(GRAD3[gi1 as usize], x1, y1);
}
let mut t2 = 0.5 - x2*x2-y2*y2;
if t2 < 0.0 {
n2 = 0.0;
}
else {
t2 *= t2;
n2 = t2 * t2 * dot2(GRAD3[gi2 as usize], x2, y2);
}
// Add contributions from each corner to get the final noise value.
// The result is scaled to return values in the interval [-1,1].
return 70.0 * (n0 + n1 + n2);
}
///
/// Generate 3D simplex noise for a specific point
///
/// Returns an f32 in [-1, 1].
///
/// # Examples
///
/// ```
/// use fuss::Simplex;
///
/// let sn = Simplex::new();
/// println!("{}", sn.noise_2d(50.1912, 30.50102));
///
/// // Simplex will return the same thing for the same points
/// assert_eq!(sn.noise_3d(1.5, -0.5, 2.1), sn.noise_3d(1.5, -0.5, 2.1));
///
/// let other_sn = Simplex::new();
///
/// // However each `Simplex` has it's own set of permutations, therefore
/// // each one is different. If you want consistency, try the `from_seed()` method.
/// assert!(sn.noise_3d(1.5, -0.5, 2.1) != other_sn.noise_3d(1.5, -0.5, 2.1));
/// ```
///
pub fn noise_3d(&self, xin: f32, yin: f32, zin: f32) -> f32 {
// Noise contributions from the four corners
let n0 : f32;
let n1 : f32;
let n2 : f32;
let n3 : f32;
// Very nice and simple skew factor for 3D
let s = (xin + yin + zin) * F3;
let i = (xin + s).floor();
let j = (yin + s).floor();
let k = (zin + s).floor();
// Unskew the cell origin back to (x,y,z) space
let t = (i + j + k) * G3;
// The x,y,z distances from the cell origin
let x0 = xin - (i - t);
let y0 = yin - (j - t);
let z0 = zin - (k - t);
// For the 3D case, the simplex shape is a slightly
// irregular tetrahedron.
// Determine which simplex we are in.
// Offsets for second corner of simplex in (i,j,k) coords
let i1 : isize;
let j1 : isize;
let k1 : isize;
// Offsets for third corner of simplex in (i,j,k) coords
let i2 : isize;
let j2 : isize;
let k2 : isize;
if x0 >= y0 {
if y0 >= z0 {
// X Y Z order
i1 = 1;
j1 = 0;
k1 = 0;
i2 = 1;
j2 = 1;
k2 = 0;
} else if x0 >= z0 {
// X Z Y order
i1=1;
j1=0;
k1=0;
i2=1;
j2=0;
k2=1;
} else {
// Z X Y order
i1=0;
j1=0;
k1=1;
i2=1;
j2=0;
k2=1;
}
}
// x0 < y0
else {
if y0 < z0 {
// Z Y X order
i1=0;
j1=0;
k1=1;
i2=0;
j2=1;
k2=1;
} else if x0 < z0 {
// Y Z X order
i1=0;
j1=1;
k1=0;
i2=0;
j2=1;
k2=1;
} else {
// Y X Z order
i1=0;
j1=1;
k1=0;
i2=1;
j2=1;
k2=0;
}
}
// A step of (1,0,0) in (i,j,k) means a step of (1-c,-c,-c) in (x,y,z),
// a step of (0,1,0) in (i,j,k) means a step of (-c,1-c,-c) in (x,y,z), and
// a step of (0,0,1) in (i,j,k) means a step of (-c,-c,1-c) in (x,y,z), where
// c = 1/6.
// Offsets for second corner in (x,y,z) coords
let x1 = x0 - i1 as f32 + G3;
let y1 = y0 - j1 as f32 + G3;
let z1 = z0 - k1 as f32 + G3;
// Offsets for third corner in (x,y,z) coords
let x2 = x0 - i2 as f32 + 2.0*G3;
let y2 = y0 - j2 as f32 + 2.0*G3;
let z2 = z0 - k2 as f32 + 2.0*G3;
// Offsets for last corner in (x,y,z) coords
let x3 = x0 - 1.0 + 3.0*G3;
let y3 = y0 - 1.0 + 3.0*G3;
let z3 = z0 - 1.0 + 3.0*G3;
// Work out the hashed gradient indices of the four simplex corners
let ii = i as isize & 255;
let jj = j as isize & 255;
let kk = k as isize & 255;
let gi0 = self.perm[(ii + self.perm[(jj + self.perm[kk as usize] as isize) as usize] as isize) as usize] % 12;
let gi1 = self.perm[(ii + i1 + self.perm[(jj + j1 + self.perm[(kk + k1) as usize] as isize) as usize] as isize) as usize] % 12;
let gi2 = self.perm[(ii + i2 + self.perm[(jj + j2 + self.perm[(kk + k2) as usize] as isize) as usize] as isize) as usize] % 12;
let gi3 = self.perm[(ii + 1 + self.perm [(jj + 1 + self.perm[kk as usize + 1] as isize) as usize] as isize) as usize] % 12;
// Calculate the contribution from the four corners
let mut t0 = 0.6 - x0*x0 - y0*y0 - z0*z0;
if t0 < 0.0 {
n0 = 0.0;
}
else {
t0 *= t0;
n0 = t0 * t0 * dot3(GRAD3[gi0 as usize], x0, y0, z0);
}
let mut t1 = 0.6 - x1*x1 - y1*y1 - z1*z1;
if t1 < 0.0 {
n1 = 0.0;
} else {
t1 *= t1;
n1 = t1 * t1 * dot3(GRAD3[gi1 as usize], x1, y1, z1);
}
let mut t2 = 0.6 - x2*x2 - y2*y2 - z2*z2;
if t2 < 0.0 {
n2 = 0.0;
}
else {
t2 *= t2;
n2 = t2 * t2 * dot3(GRAD3[gi2 as usize], x2, y2, z2);
}
let mut t3 = 0.6 - x3*x3 - y3*y3 - z3*z3;
if t3 < 0.0 {
n3 = 0.0;
} else {
t3 *= t3;
n3 = t3 * t3 * dot3(GRAD3[gi3 as usize], x3, y3, z3);
}
// Add contributions from each corner to get the final noise value.
// The result is scaled to stay just inside [-1,1]
return 32.0*(n0 + n1 + n2 + n3);
}
}