Move to rust 2024 edition (#1523)

* Move to rust 2024 edition

* chore: cargo fmt

* chore: use less _ matches

* chore: clippy fixes

* chore: fix MSRV to 1.84 (for edition 2024)

* chore: more 2024 idioms fixes

* fix compilation of nalgebra-sparse

---------

Co-authored-by: Sébastien Crozet <sebcrozet@dimforge.com>

Author: TimTheBig

.github/workflows/nalgebra-ci-build.yml

@@ -60,7 +60,7 @@ jobs:
       - name: Select rustc  version
         uses: actions-rs/toolchain@v1
         with:
-          toolchain: 1.79.0
+          toolchain: 1.85.0
           override: true
       - uses: actions/checkout@v4
       - name: check
@@ -77,7 +77,7 @@ jobs:
       - name: Select rustc  version
         uses: actions-rs/toolchain@v1
         with:
-          toolchain: 1.81.0
+          toolchain: 1.85.0
           override: true
       - uses: actions/checkout@v4
       - name: test

CHANGELOG.md

@@ -11,6 +11,10 @@ This project adheres to [Semantic Versioning](https://semver.org/).
 
 - Add the `convert-glam030` feature to enable conversion from/to types from `glam` v0.30.
 
+### Changed
+
+- Moved to Rust 2024 edition.
+
 ## [0.33.2] (29 October 2024)
 
 ### Added

Cargo.toml

@@ -11,7 +11,8 @@ readme = "README.md"
 categories = ["science", "mathematics", "wasm", "no-std"]
 keywords = ["linear", "algebra", "matrix", "vector", "math"]
 license = "Apache-2.0"
-edition = "2018"
+edition = "2024"
+rust-version = "1.85.0"
 exclude = ["/ci/*", "/.travis.yml", "/Makefile"]
 
 [badges]
@@ -103,6 +104,7 @@ matrixmultiply = { version = "0.3", optional = true }
 serde = { version = "1.0", default-features = false, features = [
     "derive",
 ], optional = true }
+# TODO: once rkyv is updated to 0.8, we could consider removing the `allow(unsafe_op_in_unsafe_fn)`.
 rkyv = { version = "0.7.41", default-features = false, optional = true }
 mint = { version = "0.5", optional = true }
 quickcheck = { version = "1", optional = true }
@@ -134,7 +136,7 @@ rayon = { version = "1.6", optional = true }
 [dev-dependencies]
 serde_json = "1.0"
 rand_xorshift = "0.4"
-rand_isaac = "0.3"
+rand_isaac = "0.4"
 criterion = { version = "0.4", features = ["html_reports"] }
 nalgebra = { path = ".", features = ["debug", "compare", "rand", "macros"] }
 

benches/common/macros.rs

@@ -5,8 +5,8 @@ macro_rules! bench_binop(
         fn $name(bh: &mut criterion::Criterion) {
             use rand::SeedableRng;
             let mut rng = IsaacRng::seed_from_u64(0);
-            let a = rng.gen::<$t1>();
-            let b = rng.gen::<$t2>();
+            let a = rng.random::<$t1>();
+            let b = rng.random::<$t2>();
 
             bh.bench_function(stringify!($name), move |bh| bh.iter(|| {
                 a.$binop(b)
@@ -20,8 +20,8 @@ macro_rules! bench_binop_ref(
         fn $name(bh: &mut criterion::Criterion) {
             use rand::SeedableRng;
             let mut rng = IsaacRng::seed_from_u64(0);
-            let a = rng.gen::<$t1>();
-            let b = rng.gen::<$t2>();
+            let a = rng.random::<$t1>();
+            let b = rng.random::<$t2>();
 
             bh.bench_function(stringify!($name), move |bh| bh.iter(|| {
                 a.$binop(&b)
@@ -35,8 +35,8 @@ macro_rules! bench_binop_fn(
         fn $name(bh: &mut criterion::Criterion) {
             use rand::SeedableRng;
             let mut rng = IsaacRng::seed_from_u64(0);
-            let a = rng.gen::<$t1>();
-            let b = rng.gen::<$t2>();
+            let a = rng.random::<$t1>();
+            let b = rng.random::<$t2>();
 
             bh.bench_function(stringify!($name), move |bh| bh.iter(|| {
                 $binop(&a, &b)
@@ -53,7 +53,7 @@ macro_rules! bench_unop_na(
             use rand::SeedableRng;
             let mut rng = IsaacRng::seed_from_u64(0);
 
-            let elems: Vec<$t> =  (0usize .. LEN).map(|_| rng.gen::<$t>()).collect();
+            let elems: Vec<$t> =  (0usize .. LEN).map(|_| rng.random::<$t>()).collect();
             let mut i = 0;
 
             bh.bench_function(stringify!($name), move |bh| bh.iter(|| {
@@ -75,7 +75,7 @@ macro_rules! bench_unop(
             use rand::SeedableRng;
             let mut rng = IsaacRng::seed_from_u64(0);
 
-            let mut elems: Vec<$t> =  (0usize .. LEN).map(|_| rng.gen::<$t>()).collect();
+            let mut elems: Vec<$t> =  (0usize .. LEN).map(|_| rng.random::<$t>()).collect();
             let mut i = 0;
 
             bh.bench_function(stringify!($name), move |bh| bh.iter(|| {
@@ -97,7 +97,7 @@ macro_rules! bench_construction(
             use rand::SeedableRng;
             let mut rng = IsaacRng::seed_from_u64(0);
 
-            $(let $args: Vec<$types> = (0usize .. LEN).map(|_| rng.gen::<$types>()).collect();)*
+            $(let $args: Vec<$types> = (0usize .. LEN).map(|_| rng.random::<$types>()).collect();)*
             let mut i = 0;
 
             bh.bench_function(stringify!($name), move |bh| bh.iter(|| {

benches/core/matrix.rs

@@ -1,4 +1,4 @@
-use na::{DMatrix, DVector, Matrix2, Matrix3, Matrix4, OMatrix, Vector2, Vector3, Vector4, U10};
+use na::{DMatrix, DVector, Matrix2, Matrix3, Matrix4, OMatrix, U10, Vector2, Vector3, Vector4};
 use rand::Rng;
 use rand_isaac::IsaacRng;
 use std::ops::{Add, Div, Mul, Sub};

benches/core/vector.rs

@@ -52,7 +52,7 @@ fn vec10000_axpy_f64(bh: &mut criterion::Criterion) {
     let mut rng = IsaacRng::seed_from_u64(0);
     let mut a = DVector::new_random(10000);
     let b = DVector::new_random(10000);
-    let n = rng.gen::<f64>();
+    let n = rng.random::<f64>();
 
     bh.bench_function("vec10000_axpy_f64", move |bh| {
         bh.iter(|| a.axpy(n, &b, 1.0))
@@ -64,8 +64,8 @@ fn vec10000_axpy_beta_f64(bh: &mut criterion::Criterion) {
     let mut rng = IsaacRng::seed_from_u64(0);
     let mut a = DVector::new_random(10000);
     let b = DVector::new_random(10000);
-    let n = rng.gen::<f64>();
-    let beta = rng.gen::<f64>();
+    let n = rng.random::<f64>();
+    let beta = rng.random::<f64>();
 
     bh.bench_function("vec10000_axpy_beta_f64", move |bh| {
         bh.iter(|| a.axpy(n, &b, beta))
@@ -77,7 +77,7 @@ fn vec10000_axpy_f64_slice(bh: &mut criterion::Criterion) {
     let mut rng = IsaacRng::seed_from_u64(0);
     let mut a = DVector::new_random(10000);
     let b = DVector::new_random(10000);
-    let n = rng.gen::<f64>();
+    let n = rng.random::<f64>();
 
     bh.bench_function("vec10000_axpy_f64_slice", move |bh| {
         bh.iter(|| {
@@ -94,7 +94,7 @@ fn vec10000_axpy_f64_static(bh: &mut criterion::Criterion) {
     let mut rng = IsaacRng::seed_from_u64(0);
     let mut a = SVector::<f64, 10000>::new_random();
     let b = SVector::<f64, 10000>::new_random();
-    let n = rng.gen::<f64>();
+    let n = rng.random::<f64>();
 
     // NOTE: for some reasons, it is much faster if the argument are boxed (Box::new(OVector...)).
     bh.bench_function("vec10000_axpy_f64_static", move |bh| {
@@ -107,7 +107,7 @@ fn vec10000_axpy_f32(bh: &mut criterion::Criterion) {
     let mut rng = IsaacRng::seed_from_u64(0);
     let mut a = DVector::new_random(10000);
     let b = DVector::new_random(10000);
-    let n = rng.gen::<f32>();
+    let n = rng.random::<f32>();
 
     bh.bench_function("vec10000_axpy_f32", move |bh| {
         bh.iter(|| a.axpy(n, &b, 1.0))
@@ -119,8 +119,8 @@ fn vec10000_axpy_beta_f32(bh: &mut criterion::Criterion) {
     let mut rng = IsaacRng::seed_from_u64(0);
     let mut a = DVector::new_random(10000);
     let b = DVector::new_random(10000);
-    let n = rng.gen::<f32>();
-    let beta = rng.gen::<f32>();
+    let n = rng.random::<f32>();
+    let beta = rng.random::<f32>();
 
     bh.bench_function("vec10000_axpy_beta_f32", move |bh| {
         bh.iter(|| a.axpy(n, &b, beta))

benches/lib.rs

@@ -17,7 +17,7 @@ pub mod linalg;
 fn reproducible_dmatrix(nrows: usize, ncols: usize) -> DMatrix<f64> {
     use rand::SeedableRng;
     let mut rng = IsaacRng::seed_from_u64(0);
-    DMatrix::<f64>::from_fn(nrows, ncols, |_, _| rng.gen())
+    DMatrix::<f64>::from_fn(nrows, ncols, |_, _| rng.random())
 }
 
 criterion_main!(

nalgebra-glm/Cargo.toml

@@ -11,7 +11,7 @@ readme = "../README.md"
 categories = ["science", "mathematics", "wasm", "no standard library"]
 keywords = ["linear", "algebra", "matrix", "vector", "math"]
 license = "Apache-2.0"
-edition = "2018"
+edition = "2024"
 
 [badges]
 maintenance = { status = "actively-developed" }

nalgebra-glm/src/common.rs

@@ -1,8 +1,8 @@
 use core::mem;
 
+use crate::RealNumber;
 use crate::aliases::{TMat, TVec};
 use crate::traits::Number;
-use crate::RealNumber;
 
 /// For each matrix or vector component `x` if `x >= 0`; otherwise, it returns `-x`.
 ///
@@ -515,11 +515,7 @@ pub fn smoothstep<T: RealNumber>(edge0: T, edge1: T, x: T) -> T {
 
 /// Returns 0.0 if `x < edge`, otherwise it returns 1.0.
 pub fn step_scalar<T: Number>(edge: T, x: T) -> T {
-    if edge > x {
-        T::zero()
-    } else {
-        T::one()
-    }
+    if edge > x { T::zero() } else { T::one() }
 }
 
 /// Returns 0.0 if `x[i] < edge`, otherwise it returns 1.0.

nalgebra-glm/src/constructors.rs

@@ -1,8 +1,8 @@
+use crate::RealNumber;
 use crate::aliases::{
     Qua, TMat, TMat2, TMat2x3, TMat2x4, TMat3, TMat3x2, TMat3x4, TMat4, TMat4x2, TMat4x3, TVec1,
     TVec2, TVec3, TVec4,
 };
-use crate::RealNumber;
 use na::Scalar;
 
 /// Creates a new 1D vector.