chore: release v0.5.1

Cargo.toml

@@ -3,7 +3,7 @@ members = ["optimizer-derive"]
 
 [package]
 name = "optimizer"
-version = "0.5.0"
+version = "0.5.1"
 edition = "2024"
 rust-version = "1.88"
 license = "MIT"
@@ -16,7 +16,7 @@ categories = ["algorithm", "science", "data-structures"]
 readme = "README.md"
 
 [dependencies]
-rand = "0.9"
+rand = "0.10"
 thiserror = "2"
 parking_lot = "0.12"
 tokio = { version = "1", features = ["sync", "rt-multi-thread"], optional = true }

src/kde/multivariate.rs

@@ -5,7 +5,7 @@
 //! parameter independently, the multivariate KDE models the joint distribution
 //! to better capture correlations between parameters.
 
-use rand::Rng;
+use rand::{Rng, RngExt};
 
 use crate::error::{Error, Result};
 

src/kde/univariate.rs

@@ -3,7 +3,7 @@
 //! This module provides a Gaussian kernel density estimator used by the TPE
 //! sampler to model probability distributions over good and bad trial regions.
 
-use rand::Rng;
+use rand::{Rng, RngExt};
 
 use crate::error::{Error, Result};
 

src/sampler/random.rs

@@ -2,7 +2,7 @@
 
 use parking_lot::Mutex;
 use rand::rngs::StdRng;
-use rand::{Rng, SeedableRng};
+use rand::{RngExt, SeedableRng};
 
 use crate::distribution::Distribution;
 use crate::param::ParamValue;
@@ -34,7 +34,7 @@ impl RandomSampler {
     #[must_use]
     pub fn new() -> Self {
         Self {
-            rng: Mutex::new(StdRng::from_os_rng()),
+            rng: Mutex::new(rand::make_rng()),
         }
     }
 

src/sampler/tpe/multivariate.rs

@@ -116,8 +116,8 @@ use std::collections::HashMap;
 use std::sync::Arc;
 
 use parking_lot::Mutex;
-use rand::SeedableRng;
 use rand::rngs::StdRng;
+use rand::{RngExt, SeedableRng};
 
 use super::{FixedGamma, GammaStrategy};
 use crate::distribution::Distribution;
@@ -219,7 +219,7 @@ impl MultivariateTpeSampler {
             n_ei_candidates: 24,
             group: false,
             constant_liar: ConstantLiarStrategy::None,
-            rng: Mutex::new(StdRng::from_os_rng()),
+            rng: Mutex::new(rand::make_rng()),
             joint_sample_cache: Mutex::new(None),
         }
     }
@@ -782,8 +782,6 @@ impl MultivariateTpeSampler {
         distribution: &Distribution,
         rng: &mut rand::rngs::StdRng,
     ) -> ParamValue {
-        use rand::Rng;
-
         match distribution {
             Distribution::Float(d) => {
                 let value = if d.log_scale {
@@ -1374,8 +1372,6 @@ impl MultivariateTpeSampler {
         bad_values: Vec<f64>,
         rng: &mut StdRng,
     ) -> f64 {
-        use rand::Rng;
-
         use crate::kde::KernelDensityEstimator;
 
         // Transform to internal space (log space if needed)
@@ -1568,8 +1564,6 @@ impl MultivariateTpeSampler {
         bad_indices: &[usize],
         rng: &mut rand::rngs::StdRng,
     ) -> usize {
-        use rand::Rng;
-
         // Count occurrences in good and bad groups
         let mut good_counts = vec![0usize; n_choices];
         let mut bad_counts = vec![0usize; n_choices];
@@ -2076,7 +2070,7 @@ impl MultivariateTpeSamplerBuilder {
 
         let rng = match self.seed {
             Some(s) => StdRng::seed_from_u64(s),
-            None => StdRng::from_os_rng(),
+            None => rand::make_rng(),
         };
 
         Ok(MultivariateTpeSampler {

src/sampler/tpe/sampler.rs

@@ -60,7 +60,7 @@ use std::sync::Arc;
 
 use parking_lot::Mutex;
 use rand::rngs::StdRng;
-use rand::{Rng, SeedableRng};
+use rand::{RngExt, SeedableRng};
 
 use crate::distribution::Distribution;
 use crate::error::{Error, Result};
@@ -149,7 +149,7 @@ impl TpeSampler {
             n_startup_trials: 10,
             n_ei_candidates: 24,
             kde_bandwidth: None,
-            rng: Mutex::new(StdRng::from_os_rng()),
+            rng: Mutex::new(rand::make_rng()),
         }
     }
 
@@ -251,7 +251,7 @@ impl TpeSampler {
 
         let rng = match seed {
             Some(s) => StdRng::seed_from_u64(s),
-            None => StdRng::from_os_rng(),
+            None => rand::make_rng(),
         };
 
         Ok(Self {
@@ -857,7 +857,7 @@ impl TpeSamplerBuilder {
 
         let rng = match self.seed {
             Some(s) => StdRng::seed_from_u64(s),
-            None => StdRng::from_os_rng(),
+            None => rand::make_rng(),
         };
 
         Ok(TpeSampler {