Upgrade to rand 0.9

sprs-rand/Cargo.toml

@@ -9,7 +9,7 @@ license.workspace = true
 edition.workspace = true
 
 [dependencies]
-rand = "0.8.5"
-rand_distr = "0.4.3"
-rand_pcg = "0.3.1"
+rand = "0.9.0"
+rand_distr = "0.5.0"
+rand_pcg = "0.9.0"
 sprs = { version = "0.11.0", path = "../sprs" }

sprs-rand/src/lib.rs

@@ -1,6 +1,6 @@
 //! Random sparse matrix generation
 
-use crate::rand::distributions::Distribution;
+use crate::rand::distr::Distribution;
 use crate::rand::Rng;
 use crate::rand::SeedableRng;
 use sprs::indexing::SpIndex;
@@ -40,7 +40,7 @@ where
     let mut data = Vec::with_capacity(exp_nnz);
     // sample row indices
     for _ in 0..exp_nnz {
-        indices.push(I::from_usize(rng.gen_range(0..shape.0)));
+        indices.push(I::from_usize(rng.random_range(0..shape.0)));
         // Note: there won't be any correspondence between the data
         // sampled here and the row sampled before, but this does not matter
         // as we are sampling.
@@ -65,7 +65,7 @@ where
         let end = indptr[row + 1].index();
         for _ in start..end {
             loop {
-                let col = I::from_usize(rng.gen_range(0..shape.1));
+                let col = I::from_usize(rng.random_range(0..shape.1));
                 let loc = indices[start..].binary_search(&col);
                 match loc {
                     Ok(_) => {
@@ -87,34 +87,34 @@ where
 /// Convenient wrapper for the common case of sampling a matrix with standard
 /// normal distribution of the nnz values, using a lightweight rng.
 pub fn rand_csr_std(shape: (usize, usize), density: f64) -> CsMat<f64> {
-    let mut rng = rand_pcg::Pcg64Mcg::from_entropy();
+    let mut rng = rand_pcg::Pcg64Mcg::from_rng(&mut rand::rng());
     rand_csr(&mut rng, crate::rand_distr::StandardNormal, shape, density)
 }
 
 #[cfg(test)]
 mod tests {
-    use rand::distributions::Standard;
+    use rand::distr::StandardUniform;
     use rand::SeedableRng;
     use sprs::CsMat;
 
     #[test]
     fn empty_random_mat() {
-        let mut rng = rand::thread_rng();
+        let mut rng = rand::rng();
         let empty: CsMat<f64> =
-            super::rand_csr(&mut rng, Standard, (0, 0), 0.3);
+            super::rand_csr(&mut rng, StandardUniform, (0, 0), 0.3);
         assert_eq!(empty.nnz(), 0);
     }
 
     #[test]
     fn random_csr() {
         let mut rng = rand::rngs::StdRng::seed_from_u64(1234);
         let mat: CsMat<f64> =
-            super::rand_csr(&mut rng, Standard, (100, 70), 0.3);
+            super::rand_csr(&mut rng, StandardUniform, (100, 70), 0.3);
         assert!(mat.density() > 0.25);
         assert!(mat.density() < 0.35);
 
         let mat: CsMat<f64> =
-            super::rand_csr(&mut rng, Standard, (1, 10000), 0.3);
+            super::rand_csr(&mut rng, StandardUniform, (1, 10000), 0.3);
         assert!(mat.density() > 0.28);
         assert!(mat.density() < 0.32);
     }

sprs/Cargo.toml

@@ -37,7 +37,7 @@ tempfile = "3.1.0"
 bincode = "1.2.0"
 tobj = "4.0"
 image = { version = "0.25.2", default-features = false, features = ["png"] }
-rand = { version = "0.8", default-features = false, features = ["small_rng"] }
+rand = { version = "0.9", default-features = false, features = ["small_rng"] }
 
 [[bench]]
 name = "suite"