turbulence + tuning
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00000010da
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0000002087
6 changed files with 160 additions and 90 deletions
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@ -1,28 +1,43 @@
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use std::{fs::File, path::PathBuf};
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use std::{fs::File, path::PathBuf};
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use anyhow::Result;
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use anyhow::Result;
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use clap::Parser;
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use clap::{Parser, ValueEnum};
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use turbulence::generate_turbulence;
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use crate::value_noise::generate_noise;
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use crate::value_noise::generate_noise;
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mod ppm;
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mod ppm;
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mod turbulence;
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mod value_noise;
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mod value_noise;
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mod vec2;
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mod vec2;
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#[derive(Parser)]
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#[derive(Parser)]
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struct Opt {
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struct Opt {
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#[clap(long = "algorithm", default_value = "turbulence")]
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algorithm: Algorithm,
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#[clap(long = "size", default_value = "1024")]
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size: usize,
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#[clap(short = 'o', long = "out", default_value = "out.ppm")]
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#[clap(short = 'o', long = "out", default_value = "out.ppm")]
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output_path: PathBuf,
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output_path: PathBuf,
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}
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}
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#[derive(ValueEnum, Clone)]
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enum Algorithm {
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Noise,
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Turbulence,
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}
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fn main() -> Result<()> {
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fn main() -> Result<()> {
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let opt = Opt::parse();
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let opt = Opt::parse();
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let rng = rand::thread_rng();
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let rng = rand::thread_rng();
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let width = 256;
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let ppm = match opt.algorithm {
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let height = 256;
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Algorithm::Noise => generate_noise(opt.size, opt.size, rng),
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let ppm = generate_noise(width, height, rng);
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Algorithm::Turbulence => generate_turbulence(opt.size, opt.size, rng),
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};
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{
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{
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let file = File::create(opt.output_path)?;
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let file = File::create(opt.output_path)?;
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51
assignment-0/src/turbulence.rs
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51
assignment-0/src/turbulence.rs
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@ -0,0 +1,51 @@
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// https://www.scratchapixel.com/lessons/procedural-generation-virtual-worlds/procedural-patterns-noise-part-1/simple-pattern-examples.html
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use rand::RngCore;
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use crate::ppm::{Pixel, Ppm};
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use crate::value_noise::ValueNoise;
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use crate::vec2::Vec2;
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pub fn generate_turbulence(
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width: usize,
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height: usize,
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rng: impl RngCore,
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) -> Ppm {
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let mut noise_map = vec![0.0; width * height];
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let noise = ValueNoise::new(rng);
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let frequency = 0.02;
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let frequency_mult = 1.8;
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let amplitude_mult = 0.35;
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let num_layers = 5;
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let mut max_noise_val = 0.0f64;
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for j in 0..height {
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for i in 0..width {
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let mut noise_point = Vec2::new(i as f64, j as f64) * frequency;
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let mut amplitude = 1.0;
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for _ in 0..num_layers {
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noise_map[j * width + i] =
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(2.0 * noise.eval(noise_point) - 1.0).abs() * amplitude;
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noise_point = noise_point * frequency_mult;
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amplitude *= amplitude_mult;
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}
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max_noise_val = max_noise_val.max(noise_map[j * width + i]);
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}
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}
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let data = noise_map
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.into_iter()
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.map(|f| {
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let v = (f / max_noise_val * 192.0 + 32.0).floor() as u8;
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Pixel(v, v, v)
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})
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.collect();
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Ppm {
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width,
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height,
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data,
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}
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}
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@ -1,6 +1,6 @@
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// https://www.scratchapixel.com/lessons/procedural-generation-virtual-worlds/procedural-patterns-noise-part-1/creating-simple-2D-noise.html
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// https://www.scratchapixel.com/lessons/procedural-generation-virtual-worlds/procedural-patterns-noise-part-1/creating-simple-2D-noise.html
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use std::mem::{self};
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use std::mem;
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use rand::{Rng, RngCore};
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use rand::{Rng, RngCore};
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@ -42,7 +42,8 @@ pub struct ValueNoise {
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impl ValueNoise {
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impl ValueNoise {
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pub fn new(mut rng: impl RngCore) -> Self {
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pub fn new(mut rng: impl RngCore) -> Self {
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let mut r: [f64; MAX_TABLE_SIZE * MAX_TABLE_SIZE] = unsafe { mem::zeroed() };
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let mut r: [f64; MAX_TABLE_SIZE * MAX_TABLE_SIZE] =
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unsafe { mem::zeroed() };
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for k in 0..MAX_TABLE_SIZE * MAX_TABLE_SIZE {
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for k in 0..MAX_TABLE_SIZE * MAX_TABLE_SIZE {
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r[k] = rng.gen_range(0.0..1.0);
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r[k] = rng.gen_range(0.0..1.0);
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}
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}
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use std::ops::Mul;
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use std::ops::Mul;
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#[derive(Copy, Clone)]
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pub struct Vec2<T = f64> {
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pub struct Vec2<T = f64> {
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pub x: T,
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pub x: T,
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pub y: T,
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pub y: T,
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2
rustfmt.toml
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2
rustfmt.toml
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max_width = 80
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tab_spaces = 2
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