rand 0.9 and rand-distr 0.5

Author: hombit

Cargo.toml

@@ -65,8 +65,8 @@ hyperdual = "1.1"
 light-curve-common = "0.1.0"
 plotters = { version = "0.3.5", default-features = false, features = ["errorbar", "line_series", "ttf"] }
 plotters-bitmap = "0.3.3"
-rand = "0.8"
-rand_distr = "0.4"
+rand = "0.9"
+rand_distr = "0.5"
 rayon = "1.5"
 realfft = "3.1"
 rustfft = "6.1"

benches/extractor.rs

@@ -179,7 +179,7 @@ where
 {
     (0..n)
         .map(|_| {
-            let x: T = thread_rng().sample(StandardNormal);
+            let x: T = rand::rng().sample(StandardNormal);
             x
         })
         .collect()

benches/fft_crates.rs

@@ -198,11 +198,11 @@ struct Randoms {}
 impl<T> Series<T> for Randoms
 where
     T: FftNum,
-    rand::distributions::Standard: Distribution<T>,
+    rand::distr::StandardUniform: Distribution<T>,
 {
     fn series(&self, n: usize) -> Vec<T> {
         let mut rng = StdRng::seed_from_u64(0);
-        (0..n).map(|_| rng.gen::<T>()).collect()
+        (0..n).map(|_| rng.random::<T>()).collect()
     }
 }
 
@@ -218,7 +218,7 @@ where
     FftwComplex<T>: AlignedAllocable,
     Plan<T, FftwComplex<T>, T::Plan>: R2CPlan<Real = T, Complex = FftwComplex<T>>,
     Vec<T>: fmt::Debug,
-    rand::distributions::Standard: Distribution<T>,
+    rand::distr::StandardUniform: Distribution<T>,
 {
     let counts: Vec<_> = (8..=20).step_by(4).map(|i| 1_usize << i).collect();
     let series: Vec<Box<dyn Series<T>>> = vec![Box::new(Ones {}), Box::new(Randoms {})];

benches/fit.rs

@@ -14,10 +14,10 @@ pub fn bench_fit_straight_line(c: &mut Criterion) {
     const N: usize = 1000;
 
     let x = linspace(0.0_f64, 1.0, N);
-    let y: Vec<_> = x.iter().map(|&x| x + thread_rng().gen::<f64>()).collect();
+    let y: Vec<_> = x.iter().map(|&x| x + rand::rng().random::<f64>()).collect();
     let w: Vec<_> = x
         .iter()
-        .map(|_| thread_rng().gen_range(10.0..100.0))
+        .map(|_| rand::rng().random_range(10.0..100.0))
         .collect();
     let ts = TimeSeries::new(&x, &y, &w);
 

src/features/periodogram.rs

@@ -546,7 +546,7 @@ mod tests {
             .map(|&x| {
                 3.0 * f32::sin(2.0 * std::f32::consts::PI / period * x + 0.5)
                     + 4.0
-                    + 0.01 * rng.gen::<f32>() // noise stabilizes solution
+                    + 0.01 * rng.random::<f32>() // noise stabilizes solution
             })
             .collect();
         let mut ts = TimeSeries::new_without_weight(&x[..], &y[..]);
@@ -560,7 +560,7 @@ mod tests {
         let periodogram: Periodogram<_, Feature<_>> = Periodogram::default();
         let period = 0.17;
         let mut rng = StdRng::seed_from_u64(0);
-        let mut x: Vec<f32> = (0..100).map(|_| rng.gen()).collect();
+        let mut x: Vec<f32> = (0..100).map(|_| rng.random()).collect();
         x[..].sort_unstable_by(|a, b| a.partial_cmp(b).unwrap());
         let y: Vec<_> = x
             .iter()
@@ -580,7 +580,7 @@ mod tests {
         ]);
         let period = 0.17;
         let mut rng = StdRng::seed_from_u64(0);
-        let mut x: Vec<f32> = (0..100).map(|_| rng.gen()).collect();
+        let mut x: Vec<f32> = (0..100).map(|_| rng.random()).collect();
         x[..].sort_unstable_by(|a, b| a.partial_cmp(b).unwrap());
         let y: Vec<_> = x
             .iter()
@@ -601,7 +601,7 @@ mod tests {
         let period1 = 0.0753;
         let period2 = 0.45;
         let mut rng = StdRng::seed_from_u64(0);
-        let mut x: Vec<f32> = (0..1000).map(|_| rng.gen()).collect();
+        let mut x: Vec<f32> = (0..1000).map(|_| rng.random()).collect();
         x[..].sort_unstable_by(|a, b| a.partial_cmp(b).unwrap());
         let y: Vec<_> = x
             .iter()
@@ -625,14 +625,14 @@ mod tests {
         let period1 = 0.0753;
         let period2 = 0.46;
         let mut rng = StdRng::seed_from_u64(0);
-        let mut x: Vec<f32> = (0..1000).map(|_| rng.gen()).collect();
+        let mut x: Vec<f32> = (0..1000).map(|_| rng.random()).collect();
         x[..].sort_unstable_by(|a, b| a.partial_cmp(b).unwrap());
         let y: Vec<_> = x
             .iter()
             .map(|&x| {
                 3.0 * f32::sin(2.0 * std::f32::consts::PI / period1 * x + 0.5)
                     + -5.0 * f32::cos(2.0 * std::f32::consts::PI / period2 * x + 0.5)
-                    + 10.0 * rng.gen::<f32>()
+                    + 10.0 * rng.random::<f32>()
                     + 4.0
             })
             .collect();

src/periodogram/mod.rs

@@ -252,15 +252,15 @@ mod tests {
 
         let mut rng = StdRng::seed_from_u64(0);
         let t: SortedArray<_> = (0..N)
-            .map(|_| rng.gen::<f64>() * (N - 1) as f64)
+            .map(|_| rng.random::<f64>() * (N - 1) as f64)
             .collect::<Vec<_>>()
             .into();
         let m: Vec<_> = t
             .iter()
             .map(|&x| {
                 f64::sin(OMEGA1 * x)
                     + AMPLITUDE2 * f64::cos(OMEGA2 * x)
-                    + NOISE_AMPLITUDE * rng.gen::<f64>()
+                    + NOISE_AMPLITUDE * rng.random::<f64>()
             })
             .collect();
         let mut ts = TimeSeries::new_without_weight(&t, &m);

src/periodogram/power_fft.rs

@@ -344,7 +344,7 @@ mod tests {
         let mut rng = StdRng::seed_from_u64(0);
 
         let t = linspace(0.0, (N - 1) as f64, N);
-        let m: Vec<f64> = (0..N).map(|_| rng.gen()).collect();
+        let m: Vec<f64> = (0..N).map(|_| rng.random()).collect();
         let mut ts = TimeSeries::new_without_weight(&t[..], &m[..]);
 
         let nyquist = AverageNyquistFreq.into();
@@ -374,7 +374,7 @@ mod tests {
         let mut rng = StdRng::seed_from_u64(0);
 
         let t = linspace(0.0, (N - 1) as f64, N);
-        let m: Vec<f64> = (0..N).map(|_| rng.gen()).collect();
+        let m: Vec<f64> = (0..N).map(|_| rng.random()).collect();
         let mut ts = TimeSeries::new_without_weight(&t[..], &m[..]);
 
         let nyquist = AverageNyquistFreq.into();

src/tests.rs

@@ -389,12 +389,12 @@ macro_rules! check_fit_model_derivatives {
 
             let mut rng = StdRng::seed_from_u64(0);
             for _ in 0..REPEAT {
-                let t = 10.0 * rng.gen::<f64>();
+                let t = 10.0 * rng.random::<f64>();
 
                 let param = {
                     let mut param = [0.0; NPARAMS];
                     for x in param.iter_mut() {
-                        *x = rng.gen::<f64>() - 0.5;
+                        *x = rng.random::<f64>() - 0.5;
                     }
                     param
                 };