Upgrade rand to 0.9 and adjust implementation accordingly

Author: adamreichold

Cargo.toml

@@ -1,7 +1,7 @@
 [package]
 name = "hammer-and-sample"
 description = "Simplistic MCMC ensemble sampler based on emcee, the MCMC hammer"
-version = "0.2.0"
+version = "0.3.0"
 edition = "2021"
 license = "MIT OR Apache-2.0"
 readme = "README.md"
@@ -14,12 +14,12 @@ categories = ["science", "mathematics", "algorithms"]
 test = false
 
 [dependencies]
-rand = { version = "0.8", default-features = false }
+rand = { version = "0.9", default-features = false }
 rayon = { version = "1.5", optional = true }
 
 [dev-dependencies]
-rand_distr = "0.4"
-rand_pcg = "0.3"
+rand_distr = "0.5"
+rand_pcg = "0.9"
 
 [package.metadata.docs.rs]
 all-features = true

src/lib.rs

@@ -50,7 +50,7 @@
 use std::ops::ControlFlow;
 
 use rand::{
-    distributions::{Distribution, Standard, Uniform},
+    distr::{Distribution, StandardUniform, Uniform},
     Rng,
 };
 #[cfg(feature = "rayon")]
@@ -158,7 +158,7 @@ where
     let half = walkers.len() / 2;
     let (lower_half, upper_half) = walkers.split_at_mut(half);
 
-    let random_index = Uniform::new(0, half);
+    let random_index = Uniform::new(0, half).unwrap();
 
     let update_walker = move |walker: &mut Walker<M, R>, other_walkers: &[Walker<M, R>]| {
         let other = &other_walkers[random_index.sample(&mut walker.rng)];
@@ -232,7 +232,7 @@ fn gen_unit<R>(rng: &mut R) -> f64
 where
     R: Rng,
 {
-    Standard.sample(rng)
+    StandardUniform.sample(rng)
 }
 
 /// Estimate the integrated auto-correlation time

tests/coin_flip.rs

@@ -1,5 +1,5 @@
 use rand::{
-    distributions::{Bernoulli, Distribution, Standard},
+    distr::{Bernoulli, Distribution, StandardUniform},
     SeedableRng,
 };
 use rand_pcg::Pcg64Mcg;
@@ -41,9 +41,9 @@ fn coin_flip() {
     };
 
     let walkers = (0..100).map(|_| {
-        let mut rng = Pcg64Mcg::from_rng(&mut rng).unwrap();
+        let mut rng = Pcg64Mcg::from_rng(&mut rng);
 
-        let guess_p = Distribution::<f64>::sample(&Standard, &mut rng);
+        let guess_p = Distribution::<f64>::sample(&StandardUniform, &mut rng);
 
         ([guess_p], rng)
     });

tests/hierarchical.rs

@@ -96,7 +96,7 @@ fn hierarchical() {
     let prior_sigma = Normal::<f64>::new(0., 2.).unwrap();
 
     let walkers = (0..WALKERS).map(|_| {
-        let mut rng = Pcg64Mcg::from_rng(&mut rng).unwrap();
+        let mut rng = Pcg64Mcg::from_rng(&mut rng);
 
         let guess_logit_theta = prior_logit_theta.sample(&mut rng);
         let guess_sigma = prior_sigma.sample(&mut rng).abs();