fix: index errors

stochastic-rs-core/src/diffusion/fcir.rs

@@ -1,4 +1,4 @@
-use ndarray::Array1;
+use ndarray::{s, Array1};
 
 use crate::{noise::fgn::Fgn, Sampling};
 
@@ -57,7 +57,7 @@ impl Sampling<f64> for Fcir {
       fcir[i] = fcir[i - 1] + self.theta * (self.mu - fcir[i - 1]) * dt + random
     }
 
-    fcir
+    fcir.slice(s![..self.n()]).to_owned()
   }
 
   fn n(&self) -> usize {

stochastic-rs-core/src/diffusion/fgbm.rs

@@ -1,4 +1,4 @@
-use ndarray::Array1;
+use ndarray::{s, Array1};
 
 use crate::{noise::fgn::Fgn, Sampling};
 
@@ -49,7 +49,7 @@ impl Sampling<f64> for Fgbm {
       fgbm[i] = fgbm[i - 1] + self.mu * fgbm[i - 1] * dt + self.sigma * fgbm[i - 1] * fgn[i - 1]
     }
 
-    fgbm
+    fgbm.slice(s![..self.n()]).to_owned()
   }
 
   fn n(&self) -> usize {

stochastic-rs-core/src/diffusion/fjacobi.rs

@@ -1,4 +1,4 @@
-use ndarray::Array1;
+use ndarray::{s, Array1};
 
 use crate::{noise::fgn::Fgn, Sampling};
 
@@ -63,7 +63,7 @@ impl Sampling<f64> for Fjacobi {
       }
     }
 
-    fjacobi
+    fjacobi.slice(s![..self.n()]).to_owned()
   }
 
   fn n(&self) -> usize {

stochastic-rs-core/src/diffusion/fou.rs

@@ -1,4 +1,4 @@
-use ndarray::Array1;
+use ndarray::{s, Array1};
 
 use crate::{noise::fgn::Fgn, Sampling};
 
@@ -51,7 +51,7 @@ impl Sampling<f64> for Fou {
       fou[i] = fou[i - 1] + self.theta * (self.mu - fou[i - 1]) * dt + self.sigma * fgn[i - 1]
     }
 
-    fou
+    fou.slice(s![..self.n()]).to_owned()
   }
 
   fn n(&self) -> usize {

stochastic-rs-core/src/jump/jump_fou.rs

@@ -1,4 +1,4 @@
-use ndarray::Array1;
+use ndarray::{s, Array1};
 
 use crate::{
   noise::fgn::Fgn, process::cpoisson::CompoundPoisson, ProcessDistribution, Sampling, Sampling3D,
@@ -75,7 +75,7 @@ impl<D: ProcessDistribution> Sampling<f64> for JumpFou<D> {
         + jumps.sum();
     }
 
-    jump_fou
+    jump_fou.slice(s![..self.n()]).to_owned()
   }
 
   fn n(&self) -> usize {

stochastic-rs-core/src/lib.rs

@@ -49,7 +49,7 @@ pub trait Sampling<T: Clone + Send + Sync + Zero>: Send + Sync {
       panic!("m must be specified for parallel sampling");
     }
 
-    let mut xs = Array2::zeros((self.m().unwrap(), self.n() + 1));
+    let mut xs = Array2::zeros((self.m().unwrap(), self.n()));
 
     xs.axis_iter_mut(Axis(0)).into_par_iter().for_each(|mut x| {
       x.assign(&self.sample());

stochastic-rs-core/src/main.rs

@@ -1,31 +1,50 @@
 use stochastic_rs::{process::fbm::Fbm, Sampling};
 
 fn main() {
+  // let fbm = Fbm::new(&Fbm {
+  //   hurst: 0.9,
+  //   n: 10000,
+  //   t: None,
+  //   m: Some(100),
+  //   ..Default::default()
+  // });
+
+  // let mut runs = Vec::new();
+
+  // for _ in 0..20 {
+  //   let start = std::time::Instant::now();
+  //   for _ in 0..1000 {
+  //     let _ = fbm.sample_par();
+  //   }
+
+  //   let duration = start.elapsed();
+  //   println!(
+  //     "Time elapsed in expensive_function() is: {:?}",
+  //     duration.as_secs_f32()
+  //   );
+  //   runs.push(duration.as_secs_f32());
+  // }
+
+  // let sum: f32 = runs.iter().sum();
+  // let average = sum / runs.len() as f32;
+  // println!("Average time: {}", average);
   let fbm = Fbm::new(&Fbm {
     hurst: 0.9,
     n: 10000,
     t: None,
     m: Some(100),
     ..Default::default()
   });
-  println!("{:?}", fbm.fgn.hurst);
-  let mut runs = Vec::new();
 
-  for _ in 0..20 {
+  for _ in 0..10 {
     let start = std::time::Instant::now();
     for _ in 0..1000 {
-      let _ = fbm.sample_par();
+      let _ = fbm.sample();
     }
-
     let duration = start.elapsed();
     println!(
       "Time elapsed in expensive_function() is: {:?}",
       duration.as_secs_f32()
     );
-    runs.push(duration.as_secs_f32());
   }
-
-  let sum: f32 = runs.iter().sum();
-  let average = sum / runs.len() as f32;
-  println!("Average time: {}", average);
 }

stochastic-rs-core/src/noise/cfgns.rs

@@ -1,4 +1,4 @@
-use ndarray::{Array1, Array2};
+use ndarray::{s, Array1, Array2};
 
 use crate::{Sampling, Sampling2D};
 
@@ -50,7 +50,10 @@ impl Sampling2D<f64> for Cfgns {
       cfgns[[1, i]] = self.rho * fgn1[i - 1] + (1.0 - self.rho.powi(2)).sqrt() * fgn2[i - 1];
     }
 
-    [cfgns.row(0).into_owned(), cfgns.row(1).into_owned()]
+    [
+      cfgns.row(0).slice(s![..self.n()]).into_owned(),
+      cfgns.row(1).slice(s![..self.n()]).into_owned(),
+    ]
   }
 
   fn n(&self) -> usize {

stochastic-rs-core/src/noise/fgn.rs

@@ -31,9 +31,9 @@ impl Fgn {
     if !(0.0..=1.0).contains(&hurst) {
       panic!("Hurst parameter must be between 0 and 1");
     }
-    let n_ = n.next_power_of_two();
-    let offset = n_ - n;
-    let n = n_;
+
+    let offset = n.next_power_of_two() - n;
+    let n = n.next_power_of_two();
     let mut r = Array1::linspace(0.0, n as f64, n + 1);
     r.mapv_inplace(|x| {
       if x == 0.0 {
@@ -96,7 +96,7 @@ impl Sampling<f64> for Fgn {
   }
 
   fn n(&self) -> usize {
-    self.n
+    self.n - self.offset
   }
 
   fn m(&self) -> Option<usize> {
@@ -112,7 +112,7 @@ mod tests {
 
   #[test]
   fn plot() {
-    let fgn = Fgn::new(0.7, 1024, Some(1.0), Some(1));
+    let fgn = Fgn::new(0.7, 1000, Some(1.0), Some(1));
     let mut plot = Plot::new();
     let d = fgn.sample_par();
     for data in d.axis_iter(Axis(0)) {

stochastic-rs-core/src/process/fbm.rs

@@ -32,15 +32,14 @@ impl Fbm {
 impl Sampling<f64> for Fbm {
   fn sample(&self) -> Array1<f64> {
     let fgn = self.fgn.sample();
-
     let mut fbm = Array1::<f64>::zeros(self.n + 1);
     fbm.slice_mut(s![1..]).assign(&fgn);
 
     for i in 1..(self.n + 1) {
       fbm[i] += fbm[i - 1];
     }
 
-    fbm
+    fbm.slice(s![..self.n()]).to_owned()
   }
 
   fn n(&self) -> usize {
@@ -68,6 +67,7 @@ mod tests {
       m: Some(1),
       ..Default::default()
     });
+
     let mut plot = Plot::new();
     let d = fbm.sample_par();
     for data in d.axis_iter(Axis(0)) {