chore: merge main

Author: dancixx

src/main.rs

@@ -1,11 +1,14 @@
 use ndarray::Array1;
-use prettytable::{format, row, Table};
+use prettytable::{format, row, Cell, Row, Table};
 use stochastic_rs::plot_1d;
 use stochastic_rs::stochastic::noise::fgn::FGN;
 use stochastic_rs::stochastic::Sampling;
 use std::error::Error;
 use std::fs::File;
 use std::io::{BufRead, BufReader};
+use std::time::Instant;
+use stochastic_rs::stochastic::noise::fgn::FGN;
+use stochastic_rs::stochastic::Sampling;
 
 use stochastic_rs::stats::fd::FractalDim;
 use stochastic_rs::stats::fou_estimator::{
@@ -14,7 +17,7 @@ use stochastic_rs::stats::fou_estimator::{
 
 // Import your estimator modules and types here
 // use your_crate::{FOUParameterEstimationV1, FOUParameterEstimationV2, FilterType};
-
+const N: usize = 10000;
 fn main() -> Result<(), Box<dyn Error>> {
   let fbm = FGN::new(0.7, 10_000, Some(1.0), Some(10000));
   let fgn = fbm.sample_cuda().unwrap();

src/stochastic/noise/fgn.rs

@@ -1,5 +1,5 @@
 use std::error::Error;
-use std::sync::{Arc, Mutex};
+use std::sync::{Arc, RwLock};
 
 use ndarray::parallel::prelude::*;
 use ndarray::{concatenate, prelude::*};
@@ -70,21 +70,21 @@ impl Sampling<f64> for FGN {
     // );
     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)));
+    let rnd = Arc::new(RwLock::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();
+      let mut result_lock = rnd.write().unwrap();
       result_lock
         .slice_mut(s![i * chunk_size..(i + 1) * chunk_size])
         .assign(&chunk);
     });
 
-    let fgn = &*self.sqrt_eigenvalues * &*rnd.lock().unwrap();
+    let fgn = &*self.sqrt_eigenvalues * &rnd;
     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.unwrap_or(1.0).powf(self.hurst);