Merge pull request #7 from dancixx/dev

feat: make rand complex to multithread

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "stochastic-rs"
-version = "0.7.0"
+version = "0.7.1"
 edition = "2021"
 license = "MIT"
 description = "A Rust library for stochastic processes"

src/main.rs

@@ -21,4 +21,14 @@ fn main() {
   let sum: f32 = runs.iter().sum();
   let average = sum / runs.len() as f32;
   println!("Average time: {}", average);
+
+  let start = std::time::Instant::now();
+  let fbm = Fbm::new(0.75, 10000, Some(1.0), Some(1000));
+  let data = fbm.sample_par();
+  println!("Data: {:?}", data);
+  let duration = start.elapsed();
+  println!(
+    "Time elapsed in expensive_function() is: {:?}",
+    duration.as_secs_f32()
+  );
 }

src/noises/fgn.rs

@@ -3,7 +3,7 @@
 //! The `FgnFft` struct provides methods to generate fractional Gaussian noise (FGN)
 //! using the Fast Fourier Transform (FFT) approach.
 
-use std::sync::Arc;
+use std::sync::{Arc, Mutex};
 
 use crate::utils::Generator;
 use ndarray::parallel::prelude::*;
@@ -101,11 +101,23 @@ impl Generator for FgnFft {
   /// let sample = fgn_fft.sample();
   /// ```
   fn sample(&self) -> Array1<f64> {
-    let rnd = Array1::<Complex<f64>>::random(
-      2 * self.n,
-      ComplexDistribution::new(StandardNormal, StandardNormal),
-    );
-    let fgn = &*self.sqrt_eigenvalues * &rnd;
+    let num_threads = rayon::current_num_threads();
+    let chunk_size = (2 * self.n) / num_threads;
+    let rnd = Arc::new(Mutex::new(Array1::<Complex<f64>>::zeros(2 * self.n)));
+
+    (0..num_threads).into_par_iter().for_each(|i| {
+      let chunk = Array1::<Complex<f64>>::random(
+        chunk_size,
+        ComplexDistribution::new(StandardNormal, StandardNormal),
+      );
+
+      let mut result_lock = rnd.lock().unwrap();
+      result_lock
+        .slice_mut(s![i * chunk_size..(i + 1) * chunk_size])
+        .assign(&chunk);
+    });
+
+    let fgn = &*self.sqrt_eigenvalues * &*rnd.lock().unwrap();
     let mut fgn_fft = Array1::<Complex<f64>>::zeros(2 * self.n);
     ndfft(&fgn, &mut fgn_fft, &*self.fft_handler, 0);
     let scale = (self.n as f64).powf(-self.hurst) * self.t.powf(self.hurst);