Release v0.33.0 (#1417)

* Add Storage::forget

* Adjust implementations of Reallocator to use Storage::forget

* Fix formatting

* Rename forget to forget_elements and add safety comments

* Update comments in Reallocator implementations

---------

Co-authored-by: Nick Mertin <nickmertin@gmail.com>

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

@@ -13,52 +13,59 @@ jobs:
   check-fmt:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v2
-    - name: Check formatting
-      run: cargo fmt -- --check
+      - uses: actions/checkout@v2
+      - name: Check formatting
+        run: cargo fmt -- --check
   clippy:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v2
-    - name: Install clippy
-      run: rustup component add clippy
-    - name: Run clippy
-      run: cargo clippy
+      - uses: actions/checkout@v2
+      - name: Install clippy
+        run: rustup component add clippy
+      - name: Run clippy
+        run: cargo clippy
   build-nalgebra:
     runs-on: ubuntu-latest
-#    env:
-#      RUSTFLAGS: -D warnings
+    #    env:
+    #      RUSTFLAGS: -D warnings
     steps:
-    - uses: actions/checkout@v2
-    - name: Build --no-default-feature
-      run: cargo build --no-default-features;
-    - name: Build (default features)
-      run: cargo build;
-    - name: Build --features serde-serialize
-      run: cargo build --features serde-serialize
-    - name: Build nalgebra-lapack
-      run: cd nalgebra-lapack; cargo build;
-    - name: Build nalgebra-sparse --no-default-features
-      run: cd nalgebra-sparse; cargo build --no-default-features;
-    - name: Build nalgebra-sparse (default features)
-      run: cd nalgebra-sparse; cargo build;
-    - name: Build nalgebra-sparse --all-features
-      run: cd nalgebra-sparse; cargo build --all-features;
+      - uses: actions/checkout@v2
+      - name: Build --no-default-feature
+        run: cargo build --no-default-features;
+      - name: Build (default features)
+        run: cargo build;
+      - name: Build --features serde-serialize
+        run: cargo build --features serde-serialize
+      - name: Build nalgebra-lapack
+        run: cd nalgebra-lapack; cargo build;
+      - name: Build nalgebra-sparse --no-default-features
+        run: cd nalgebra-sparse; cargo build --no-default-features;
+      - name: Build nalgebra-sparse (default features)
+        run: cd nalgebra-sparse; cargo build;
+      - name: Build nalgebra-sparse --all-features
+        run: cd nalgebra-sparse; cargo build --all-features;
   # Run this on it’s own job because it alone takes a lot of time.
   # So it’s best to let it run in parallel to the other jobs.
   build-nalgebra-all-features:
     runs-on: ubuntu-latest
     steps:
-      # Needed because the --all-features build which enables cuda support.
-      - uses: Jimver/cuda-toolkit@v0.2.8
       - uses: actions/checkout@v2
       - run: cargo build --all-features;
       - run: cargo build -p nalgebra-glm --all-features;
   test-nalgebra:
     runs-on: ubuntu-latest
-#    env:
-#      RUSTFLAGS: -D warnings
+    #    env:
+    #      RUSTFLAGS: -D warnings
     steps:
+      # Tests are run with a specific version of the compiler to avoid
+      # trybuild errors when a new compiler version is out. This can be
+      # bumped as needed after running the tests with TRYBUILD=overwrite
+      # to re-generate the error reference.
+      - name: Select rustc  version
+        uses: actions-rs/toolchain@v1
+        with:
+          toolchain: 1.79.0
+          override: true
       - uses: actions/checkout@v2
       - name: test
         run: cargo test --features arbitrary,rand,serde-serialize,sparse,debug,io,compare,libm,proptest-support,slow-tests,rkyv-safe-deser,rayon;
@@ -87,8 +94,8 @@ jobs:
         run: cargo test -p nalgebra-macros
   build-wasm:
     runs-on: ubuntu-latest
-#    env:
-#      RUSTFLAGS: -D warnings
+    #    env:
+    #      RUSTFLAGS: -D warnings
     steps:
       - uses: actions/checkout@v2
       - run: rustup target add wasm32-unknown-unknown
@@ -120,26 +127,9 @@ jobs:
         run: xargo build --verbose --no-default-features -p nalgebra-glm --target=x86_64-unknown-linux-gnu;
       - name: build thumbv7em-none-eabihf nalgebra-glm
         run: xargo build --verbose --no-default-features -p nalgebra-glm --target=thumbv7em-none-eabihf;
-  build-cuda:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: Jimver/cuda-toolkit@v0.2.8
-        with:
-          cuda: '11.5.0'
-      - name: Install nightly-2021-12-04
-        uses: actions-rs/toolchain@v1
-        with:
-          toolchain: nightly-2021-12-04
-          override: true
-      - uses: actions/checkout@v2
-      - run: rustup target add nvptx64-nvidia-cuda
-      - run: cargo build --no-default-features --features cuda
-      - run: cargo build --no-default-features --features cuda --target=nvptx64-nvidia-cuda
-        env: 
-          CUDA_ARCH: "350"
   docs:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v2
-    - name: Generate documentation
-      run: cargo doc
+      - uses: actions/checkout@v2
+      - name: Generate documentation
+        run: cargo doc

Cargo.toml

@@ -1,16 +1,16 @@
 [package]
-name    = "nalgebra"
-version = "0.32.3"
-authors = [ "Sébastien Crozet <developer@crozet.re>" ]
+name = "nalgebra"
+version = "0.33.0"
+authors = ["Sébastien Crozet <developer@crozet.re>"]
 
 description = "General-purpose linear algebra library with transformations and statically-sized or dynamically-sized matrices."
 documentation = "https://www.nalgebra.org/docs"
 homepage = "https://nalgebra.org"
 repository = "https://github.com/dimforge/nalgebra"
 readme = "README.md"
-categories = [ "science", "mathematics", "wasm", "no-std" ]
-keywords = [ "linear", "algebra", "matrix", "vector", "math" ]
-license = "BSD-3-Clause"
+categories = ["science", "mathematics", "wasm", "no-std"]
+keywords = ["linear", "algebra", "matrix", "vector", "math"]
+license = "Apache-2.0"
 edition = "2018"
 exclude = ["/ci/*", "/.travis.yml", "/Makefile"]
 
@@ -22,104 +22,112 @@ name = "nalgebra"
 path = "src/lib.rs"
 
 [features]
-default = [ "std", "macros" ]
-std     = [ "matrixmultiply", "simba/std" ]
-sparse  = [ ]
-debug   = [ "approx/num-complex", "rand" ]
-alloc   = [ ]
-io      = [ "pest", "pest_derive" ]
-compare = [ "matrixcompare-core" ]
-libm    = [ "simba/libm" ]
-libm-force = [ "simba/libm_force" ]
-macros = [ "nalgebra-macros" ]
-cuda   = [ "cust_core", "simba/cuda" ]
-
+default = ["std", "macros"]
+std = ["matrixmultiply", "num-traits/std", "num-complex/std", "num-rational/std", "approx/std", "simba/std"]
+sparse = []
+debug = ["approx/num-complex", "rand"]
+alloc = []
+io = ["pest", "pest_derive"]
+compare = ["matrixcompare-core"]
+libm = ["simba/libm"]
+libm-force = ["simba/libm_force"]
+macros = ["nalgebra-macros"]
 
 # Conversion
-convert-mint = [ "mint" ]
-convert-bytemuck = [ "bytemuck" ]
-convert-glam014 = [ "glam014" ]
-convert-glam015 = [ "glam015" ]
-convert-glam016 = [ "glam016" ]
-convert-glam017 = [ "glam017" ]
-convert-glam018 = [ "glam018" ]
-convert-glam019 = [ "glam019" ]
-convert-glam020 = [ "glam020" ]
-convert-glam021 = [ "glam021" ]
-convert-glam022 = [ "glam022" ]
-convert-glam023 = [ "glam023" ]
-convert-glam024 = [ "glam024" ]
+convert-mint = ["mint"]
+convert-bytemuck = ["bytemuck"]
+convert-glam014 = ["glam014"]
+convert-glam015 = ["glam015"]
+convert-glam016 = ["glam016"]
+convert-glam017 = ["glam017"]
+convert-glam018 = ["glam018"]
+convert-glam019 = ["glam019"]
+convert-glam020 = ["glam020"]
+convert-glam021 = ["glam021"]
+convert-glam022 = ["glam022"]
+convert-glam023 = ["glam023"]
+convert-glam024 = ["glam024"]
+convert-glam025 = ["glam025"]
+convert-glam027 = ["glam027"]
+convert-glam028 = ["glam028"]
 
 # Serialization
 ## To use serde in a #[no-std] environment, enable the
 ## `serde-serialize-no-std` feature instead of `serde-serialize`.
 ## Serialization of dynamically-sized matrices/vectors require
 ## `serde-serialize`.
-serde-serialize-no-std = [ "serde", "num-complex/serde" ]
-serde-serialize        = [ "serde-serialize-no-std", "serde/std" ]
-rkyv-serialize-no-std  = [ "rkyv/size_32" ]
-rkyv-serialize         = [ "rkyv-serialize-no-std", "rkyv/std", "rkyv/validation" ]
+serde-serialize-no-std = ["serde", "num-complex/serde"]
+serde-serialize = ["serde-serialize-no-std", "serde/std"]
+rkyv-serialize-no-std = ["rkyv/size_32"]
+rkyv-serialize = ["rkyv-serialize-no-std", "rkyv/std", "rkyv/validation"]
 
 # Randomness
 ## To use rand in a #[no-std] environment, enable the
 ## `rand-no-std` feature instead of `rand`.
-rand-no-std = [ "rand-package" ]
-rand        = [ "rand-no-std", "rand-package/std", "rand-package/std_rng", "rand_distr" ]
+rand-no-std = ["rand-package"]
+rand = ["rand-no-std", "rand-package/std", "rand-package/std_rng", "rand_distr"]
 
 # Tests
-arbitrary        = [ "quickcheck" ]
-proptest-support = [ "proptest" ]
-slow-tests       = []
-rkyv-safe-deser  = [ "rkyv-serialize", "rkyv/validation" ]
+arbitrary = ["quickcheck"]
+proptest-support = ["proptest"]
+slow-tests = []
+rkyv-safe-deser = ["rkyv-serialize", "rkyv/validation"]
 
 [dependencies]
-nalgebra-macros = { version = "0.2.1", path = "nalgebra-macros", optional = true }
-typenum        = "1.12"
-rand-package   = { package = "rand", version = "0.8", optional = true, default-features = false }
-num-traits     = { version = "0.2", default-features = false }
-num-complex    = { version = "0.4", default-features = false }
-num-rational   = { version = "0.4", default-features = false }
-approx         = { version = "0.5", default-features = false }
-simba          = { version = "0.8", default-features = false }
-alga           = { version = "0.9", default-features = false, optional = true }
-rand_distr     = { version = "0.4", default-features = false, optional = true }
+nalgebra-macros = { version = "0.2.2", path = "nalgebra-macros", optional = true }
+typenum = "1.12"
+rand-package = { package = "rand", version = "0.8", optional = true, default-features = false }
+num-traits = { version = "0.2", default-features = false }
+num-complex = { version = "0.4", default-features = false }
+num-rational = { version = "0.4", default-features = false }
+approx = { version = "0.5", default-features = false }
+simba = { version = "0.9", default-features = false }
+alga = { version = "0.9", default-features = false, optional = true }
+rand_distr = { version = "0.4", default-features = false, optional = true }
 matrixmultiply = { version = "0.3", optional = true }
-serde          = { version = "1.0", default-features = false, features = [ "derive" ], optional = true }
-rkyv           = { version = "0.7.41", default-features = false, optional = true }
-mint           = { version = "0.5", optional = true }
-quickcheck     = { version = "1", optional = true }
-pest           = { version = "2", optional = true }
-pest_derive    = { version = "2", optional = true }
-bytemuck       = { version = "1.5", optional = true }
+serde = { version = "1.0", default-features = false, features = ["derive"], optional = true }
+rkyv = { version = "0.7.41", default-features = false, optional = true }
+mint = { version = "0.5", optional = true }
+quickcheck = { version = "1", optional = true }
+pest = { version = "2", optional = true }
+pest_derive = { version = "2", optional = true }
+bytemuck = { version = "1.5", optional = true }
 matrixcompare-core = { version = "0.1", optional = true }
-proptest       = { version = "1", optional = true, default-features = false, features = ["std"] }
-glam014        = { package = "glam", version = "0.14", optional = true }
-glam015        = { package = "glam", version = "0.15", optional = true }
-glam016        = { package = "glam", version = "0.16", optional = true }
-glam017        = { package = "glam", version = "0.17", optional = true }
-glam018        = { package = "glam", version = "0.18", optional = true }
-glam019        = { package = "glam", version = "0.19", optional = true }
-glam020        = { package = "glam", version = "0.20", optional = true }
-glam021        = { package = "glam", version = "0.21", optional = true }
-glam022        = { package = "glam", version = "0.22", optional = true }
-glam023        = { package = "glam", version = "0.23", optional = true }
-glam024        = { package = "glam", version = "0.24", optional = true }
-cust_core      = { version = "0.1", optional = true }
-rayon          = { version = "1.6", optional = true }
+proptest = { version = "1", optional = true, default-features = false, features = ["std"] }
+glam014 = { package = "glam", version = "0.14", optional = true }
+glam015 = { package = "glam", version = "0.15", optional = true }
+glam016 = { package = "glam", version = "0.16", optional = true }
+glam017 = { package = "glam", version = "0.17", optional = true }
+glam018 = { package = "glam", version = "0.18", optional = true }
+glam019 = { package = "glam", version = "0.19", optional = true }
+glam020 = { package = "glam", version = "0.20", optional = true }
+glam021 = { package = "glam", version = "0.21", optional = true }
+glam022 = { package = "glam", version = "0.22", optional = true }
+glam023 = { package = "glam", version = "0.23", optional = true }
+glam024 = { package = "glam", version = "0.24", optional = true }
+glam025 = { package = "glam", version = "0.25", optional = true }
+glam027 = { package = "glam", version = "0.27", optional = true }
+glam028 = { package = "glam", version = "0.28", optional = true }
+rayon = { version = "1.6", optional = true }
 
 [dev-dependencies]
 serde_json = "1.0"
 rand_xorshift = "0.3"
 rand_isaac = "0.3"
 criterion = { version = "0.4", features = ["html_reports"] }
-nalgebra = { path = ".", features = ["debug", "compare", "rand", "macros"]}
+nalgebra = { path = ".", features = ["debug", "compare", "rand", "macros"] }
 
 # For matrix comparison macro
 matrixcompare = "0.3.0"
-itertools = "0.10"
+itertools = "0.13"
+
+# For macro testing
+trybuild = "1.0.90"
+
+cool_asserts = "2.0.3"
 
 [workspace]
-members = [ "nalgebra-lapack", "nalgebra-glm", "nalgebra-sparse", "nalgebra-macros" ]
+members = ["nalgebra-lapack", "nalgebra-glm", "nalgebra-sparse", "nalgebra-macros"]
 resolver = "2"
 
 [[example]]

README.md

@@ -5,9 +5,6 @@
     <a href="https://discord.gg/vt9DJSW">
         <img src="https://img.shields.io/discord/507548572338880513.svg?logo=discord&colorB=7289DA">
     </a>
-    <a href="https://circleci.com/gh/dimforge/nalgebra">
-        <img src="https://circleci.com/gh/dimforge/nalgebra.svg?style=svg" alt="Build status">
-    </a>
     <a href="https://crates.io/crates/nalgebra">
          <img src="https://img.shields.io/crates/v/nalgebra.svg?style=flat-square" alt="crates.io">
     </a>
@@ -17,7 +14,7 @@
 </p>
 <p align = "center">
     <strong>
-        <a href="https://nalgebra.org">Users guide</a> | <a href="https://docs.rs/nalgebra/latest/nalgebra/">Documentation</a> | <a href="https://discourse.nphysics.org/c/nalgebra">Forum</a>
+        <a href="https://nalgebra.org">Users guide</a> | <a href="https://docs.rs/nalgebra/latest/nalgebra/">Documentation</a>
     </strong>
 </p>
 

benches/core/matrix.rs

@@ -142,7 +142,7 @@ fn iter(bench: &mut criterion::Criterion) {
     bench.bench_function("iter", move |bh| {
         bh.iter(|| {
             for value in a.iter() {
-                criterion::black_box(value);
+                std::hint::black_box(value);
             }
         })
     });
@@ -154,7 +154,7 @@ fn iter_rev(bench: &mut criterion::Criterion) {
     bench.bench_function("iter_rev", move |bh| {
         bh.iter(|| {
             for value in a.iter().rev() {
-                criterion::black_box(value);
+                std::hint::black_box(value);
             }
         })
     });

benches/lib.rs

@@ -1,4 +1,3 @@
-#![feature(bench_black_box)]
 #![allow(unused_macros)]
 
 extern crate nalgebra as na;

examples/cargo/Cargo.toml

@@ -1,10 +1,10 @@
 [package]
-name    = "example-using-nalgebra"
+name = "example-using-nalgebra"
 version = "0.0.0"
-authors = [ "You" ]
+authors = ["You"]
 
 [dependencies]
-nalgebra = "0.32.0"
+nalgebra = "0.33.0"
 
 [[bin]]
 name = "example"

examples/dimensional_genericity.rs

@@ -12,7 +12,7 @@ fn reflect_wrt_hyperplane_with_dimensional_genericity<T: RealField, D: Dim>(
 where
     T: RealField,
     D: Dim,
-    DefaultAllocator: Allocator<T, D>,
+    DefaultAllocator: Allocator<D>,
 {
     let n = plane_normal.as_ref(); // Get the underlying V.
     vector - n * (n.dot(vector) * na::convert(2.0))
@@ -28,7 +28,7 @@ where
 }
 
 /// Reflects a 3D vector wrt. the 3D plane with normal `plane_normal`.
-/// /!\ This is an exact replicate of `reflect_wrt_hyperplane2, but for 3D.
+/// /!\ This is an exact replicate of `reflect_wrt_hyperplane2`, but for 3D.
 fn reflect_wrt_hyperplane3<T>(plane_normal: &Unit<Vector3<T>>, vector: &Vector3<T>) -> Vector3<T>
 where
     T: RealField,

nalgebra-glm/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "nalgebra-glm"
-version = "0.18.0"
+version = "0.19.0"
 authors = ["sebcrozet <developer@crozet.re>"]
 
 description = "A computer-graphics oriented API for nalgebra, inspired by the C++ GLM library."
@@ -8,32 +8,31 @@ documentation = "https://www.nalgebra.org/docs"
 homepage = "https://nalgebra.org"
 repository = "https://github.com/dimforge/nalgebra"
 readme = "../README.md"
-categories = [ "science", "mathematics", "wasm", "no standard library" ]
-keywords = [ "linear", "algebra", "matrix", "vector", "math" ]
-license = "BSD-3-Clause"
+categories = ["science", "mathematics", "wasm", "no standard library"]
+keywords = ["linear", "algebra", "matrix", "vector", "math"]
+license = "Apache-2.0"
 edition = "2018"
 
 [badges]
 maintenance = { status = "actively-developed" }
 
 [features]
-default               = [ "std" ]
-std                   = [ "nalgebra/std", "simba/std" ]
-arbitrary             = [ "nalgebra/arbitrary" ]
-serde-serialize       = [ "nalgebra/serde-serialize-no-std" ]
-cuda                  = [ "nalgebra/cuda" ]
+default = ["std"]
+std = ["nalgebra/std", "simba/std"]
+arbitrary = ["nalgebra/arbitrary"]
+serde-serialize = ["nalgebra/serde-serialize-no-std"]
 
 # Conversion
-convert-mint = [ "nalgebra/mint" ]
-convert-bytemuck = [ "nalgebra/bytemuck" ]
-convert-glam014 = [ "nalgebra/glam014" ]
-convert-glam015 = [ "nalgebra/glam015" ]
-convert-glam016 = [ "nalgebra/glam016" ]
-convert-glam017 = [ "nalgebra/glam017" ]
-convert-glam018 = [ "nalgebra/glam018" ]
+convert-mint = ["nalgebra/mint"]
+convert-bytemuck = ["nalgebra/bytemuck"]
+convert-glam014 = ["nalgebra/glam014"]
+convert-glam015 = ["nalgebra/glam015"]
+convert-glam016 = ["nalgebra/glam016"]
+convert-glam017 = ["nalgebra/glam017"]
+convert-glam018 = ["nalgebra/glam018"]
 
 [dependencies]
 num-traits = { version = "0.2", default-features = false }
 approx = { version = "0.5", default-features = false }
-simba = { version = "0.8", default-features = false }
-nalgebra = { path =  "..", version = "0.32", default-features = false }
+simba = { version = "0.9", default-features = false }
+nalgebra = { path = "..", version = "0.33", default-features = false }

nalgebra-glm/LICENSE

@@ -0,0 +1 @@
+../LICENSE

nalgebra-glm/src/aliases.rs

@@ -5,38 +5,38 @@ use na::{
 
 /// A matrix with components of type `T`. It has `R` rows, and `C` columns.
 ///
-/// In this library, vectors, represented as [`TVec`](type.TVec.html) and
+/// In this library, vectors, represented as [`TVec`] and
 /// friends, are also matrices. Operations that operate on a matrix will
 /// also work on a vector.
 ///
 /// # See also:
 ///
-/// * [`TMat2`](type.TMat2.html)
-/// * [`TMat2x2`](type.TMat2x2.html)
-/// * [`TMat2x3`](type.TMat2x3.html)
-/// * [`TMat2x4`](type.TMat2x4.html)
-/// * [`TMat3`](type.TMat3.html)
-/// * [`TMat3x2`](type.TMat3x2.html)
-/// * [`TMat3x3`](type.TMat3x3.html)
-/// * [`TMat3x4`](type.TMat3x4.html)
-/// * [`TMat4`](type.TMat4.html)
-/// * [`TMat4x2`](type.TMat4x2.html)
-/// * [`TMat4x3`](type.TMat4x3.html)
-/// * [`TMat4x4`](type.TMat4x4.html)
-/// * [`TVec`](type.TVec.html)
+/// * [`TMat2`]
+/// * [`TMat2x2`]
+/// * [`TMat2x3`]
+/// * [`TMat2x4`]
+/// * [`TMat3`]
+/// * [`TMat3x2`]
+/// * [`TMat3x3`]
+/// * [`TMat3x4`]
+/// * [`TMat4`]
+/// * [`TMat4x2`]
+/// * [`TMat4x3`]
+/// * [`TMat4x4`]
+/// * [`TVec`]
 pub type TMat<T, const R: usize, const C: usize> = SMatrix<T, R, C>;
 /// A column vector with components of type `T`. It has `D` rows (and one column).
 ///
 /// In this library, vectors are represented as a single column matrix, so
-/// operations on [`TMat`](type.TMat.html) are also valid on vectors.
+/// operations on [`TMat`] are also valid on vectors.
 ///
 /// # See also:
 ///
-/// * [`TMat`](type.TMat.html)
-/// * [`TVec1`](type.TVec1.html)
-/// * [`TVec2`](type.TVec2.html)
-/// * [`TVec3`](type.TVec3.html)
-/// * [`TVec4`](type.TVec4.html)
+/// * [`TMat`]
+/// * [`TVec1`]
+/// * [`TVec2`]
+/// * [`TVec3`]
+/// * [`TVec4`]
 pub type TVec<T, const R: usize> = SVector<T, R>;
 /// A quaternion with components of type `T`.
 pub type Qua<T> = Quaternion<T>;
@@ -47,28 +47,28 @@ pub type Qua<T> = Quaternion<T>;
 ///
 /// ## Constructors:
 ///
-/// * [`make_vec1`](fn.make_vec1.html)
-/// * [`vec1`](fn.vec1.html)
-/// * [`vec2_to_vec1`](fn.vec2_to_vec1.html)
-/// * [`vec3_to_vec1`](fn.vec3_to_vec1.html)
-/// * [`vec4_to_vec1`](fn.vec4_to_vec1.html)
+/// * [`make_vec1()`](crate::make_vec1)
+/// * [`vec1()`](crate::vec1)
+/// * [`vec2_to_vec1()`](crate::vec2_to_vec1)
+/// * [`vec3_to_vec1()`](crate::vec3_to_vec1)
+/// * [`vec4_to_vec1()`](crate::vec4_to_vec1)
 ///
 /// ## Related types:
 ///
-/// * [`BVec1`](type.BVec1.html)
-/// * [`DVec1`](type.DVec1.html)
-/// * [`IVec1`](type.IVec1.html)
-/// * [`I16Vec1`](type.I16Vec1.html)
-/// * [`I32Vec1`](type.I32Vec1.html)
-/// * [`I64Vec1`](type.I64Vec1.html)
-/// * [`I8Vec1`](type.I8Vec1.html)
-/// * [`TVec`](type.TVec.html)
-/// * [`UVec1`](type.UVec1.html)
-/// * [`U16Vec1`](type.U16Vec1.html)
-/// * [`U32Vec1`](type.U32Vec1.html)
-/// * [`U64Vec1`](type.U64Vec1.html)
-/// * [`U8Vec1`](type.U8Vec1.html)
-/// * [`Vec1`](type.Vec1.html)
+/// * [`BVec1`]
+/// * [`DVec1`]
+/// * [`IVec1`]
+/// * [`I16Vec1`]
+/// * [`I32Vec1`]
+/// * [`I64Vec1`]
+/// * [`I8Vec1`]
+/// * [`TVec`]
+/// * [`UVec1`]
+/// * [`U16Vec1`]
+/// * [`U32Vec1`]
+/// * [`U64Vec1`]
+/// * [`U8Vec1`]
+/// * [`Vec1`]
 pub type TVec1<T> = TVec<T, 1>;
 /// A 2D vector with components of type `T`.
 ///
@@ -76,29 +76,28 @@ pub type TVec1<T> = TVec<T, 1>;
 ///
 /// ## Constructors:
 ///
-/// * [`make_vec2`](fn.make_vec2.html)
-/// * [`vec2`](fn.vec2.html)
-/// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
-/// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
-/// * [`vec4_to_vec2`](fn.vec4_to_vec2.html)
+/// * [`make_vec2()`](crate::make_vec2)
+/// * [`vec2()`](crate::vec2)
+/// * [`vec1_to_vec2()`](crate::vec1_to_vec2)
+/// * [`vec3_to_vec2()`](crate::vec3_to_vec2)
+/// * [`vec4_to_vec2()`](crate::vec4_to_vec2)
 ///
 /// ## Related types:
 ///
-/// * [`vec2`](fn.vec2.html)
-/// * [`BVec2`](type.BVec2.html)
-/// * [`DVec2`](type.DVec2.html)
-/// * [`IVec2`](type.IVec2.html)
-/// * [`I16Vec2`](type.I16Vec2.html)
-/// * [`I32Vec2`](type.I32Vec2.html)
-/// * [`I64Vec2`](type.I64Vec2.html)
-/// * [`I8Vec2`](type.I8Vec2.html)
-/// * [`TVec`](type.TVec.html)
-/// * [`UVec2`](type.UVec2.html)
-/// * [`U16Vec2`](type.U16Vec2.html)
-/// * [`U32Vec2`](type.U32Vec2.html)
-/// * [`U64Vec2`](type.U64Vec2.html)
-/// * [`U8Vec2`](type.U8Vec2.html)
-/// * [`Vec2`](type.Vec2.html)
+/// * [`BVec2`]
+/// * [`DVec2`]
+/// * [`IVec2`]
+/// * [`I16Vec2`]
+/// * [`I32Vec2`]
+/// * [`I64Vec2`]
+/// * [`I8Vec2`]
+/// * [`TVec`]
+/// * [`UVec2`]
+/// * [`U16Vec2`]
+/// * [`U32Vec2`]
+/// * [`U64Vec2`]
+/// * [`U8Vec2`]
+/// * [`Vec2`]
 pub type TVec2<T> = TVec<T, 2>;
 /// A 3D vector with components of type `T`.
 ///
@@ -106,29 +105,28 @@ pub type TVec2<T> = TVec<T, 2>;
 ///
 /// ## Constructors:
 ///
-/// * [`make_vec3`](fn.make_vec3.html)
-/// * [`vec3`](fn.vec3.html)
-/// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
-/// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
-/// * [`vec4_to_vec3`](fn.vec4_to_vec3.html)
+/// * [`make_vec3()`](crate::make_vec3)
+/// * [`vec3()`](crate::vec3)
+/// * [`vec1_to_vec3()`](crate::vec1_to_vec3)
+/// * [`vec2_to_vec3()`](crate::vec2_to_vec3)
+/// * [`vec4_to_vec3()`](crate::vec4_to_vec3)
 ///
 /// ## Related types:
 ///
-/// * [`vec3`](fn.vec3.html)
-/// * [`BVec3`](type.BVec3.html)
-/// * [`DVec3`](type.DVec3.html)
-/// * [`IVec3`](type.IVec3.html)
-/// * [`I16Vec3`](type.I16Vec3.html)
-/// * [`I32Vec3`](type.I32Vec3.html)
-/// * [`I64Vec3`](type.I64Vec3.html)
-/// * [`I8Vec3`](type.I8Vec3.html)
-/// * [`TVec`](type.TVec.html)
-/// * [`UVec3`](type.UVec3.html)
-/// * [`U16Vec3`](type.U16Vec3.html)
-/// * [`U32Vec3`](type.U32Vec3.html)
-/// * [`U64Vec3`](type.U64Vec3.html)
-/// * [`U8Vec3`](type.U8Vec3.html)
-/// * [`Vec3`](type.Vec3.html)
+/// * [`BVec3`]
+/// * [`DVec3`]
+/// * [`IVec3`]
+/// * [`I16Vec3`]
+/// * [`I32Vec3`]
+/// * [`I64Vec3`]
+/// * [`I8Vec3`]
+/// * [`TVec`]
+/// * [`UVec3`]
+/// * [`U16Vec3`]
+/// * [`U32Vec3`]
+/// * [`U64Vec3`]
+/// * [`U8Vec3`]
+/// * [`Vec3`]
 pub type TVec3<T> = TVec<T, 3>;
 /// A 4D vector with components of type `T`.
 ///
@@ -136,28 +134,27 @@ pub type TVec3<T> = TVec<T, 3>;
 ///
 /// ## Constructors:
 ///
-/// * [`make_vec4`](fn.make_vec4.html)
-/// * [`vec4`](fn.vec4.html)
-/// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
-/// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
-/// * [`vec3_to_vec4`](fn.vec3_to_vec4.html)
+/// * [`make_vec4()`](crate::make_vec4)
+/// * [`vec4()`](crate::vec4)
+/// * [`vec1_to_vec4()`](crate::vec1_to_vec4)
+/// * [`vec2_to_vec4()`](crate::vec2_to_vec4)
+/// * [`vec3_to_vec4()`](crate::vec3_to_vec4)
 ///
 /// ## Related types:
 ///
-/// * [`vec4`](fn.vec4.html)
-/// * [`BVec4`](type.BVec4.html)
-/// * [`DVec4`](type.DVec4.html)
-/// * [`IVec4`](type.IVec4.html)
-/// * [`I16Vec4`](type.I16Vec4.html)
-/// * [`I32Vec4`](type.I32Vec4.html)
-/// * [`I64Vec4`](type.I64Vec4.html)
-/// * [`I8Vec4`](type.I8Vec4.html)
-/// * [`UVec4`](type.UVec4.html)
-/// * [`U16Vec4`](type.U16Vec4.html)
-/// * [`U32Vec4`](type.U32Vec4.html)
-/// * [`U64Vec4`](type.U64Vec4.html)
-/// * [`U8Vec4`](type.U8Vec4.html)
-/// * [`Vec4`](type.Vec4.html)
+/// * [`BVec4`]
+/// * [`DVec4`]
+/// * [`IVec4`]
+/// * [`I16Vec4`]
+/// * [`I32Vec4`]
+/// * [`I64Vec4`]
+/// * [`I8Vec4`]
+/// * [`UVec4`]
+/// * [`U16Vec4`]
+/// * [`U32Vec4`]
+/// * [`U64Vec4`]
+/// * [`U8Vec4`]
+/// * [`Vec4`]
 pub type TVec4<T> = TVec<T, 4>;
 /// A 1D vector with boolean components.
 pub type BVec1 = TVec1<bool>;

nalgebra-glm/src/common.rs

@@ -1,5 +1,4 @@
 use core::mem;
-use na;
 
 use crate::aliases::{TMat, TVec};
 use crate::traits::Number;
@@ -20,7 +19,7 @@ use crate::RealNumber;
 ///
 /// # See also:
 ///
-/// * [`sign`](fn.sign.html)
+/// * [`sign()`]
 pub fn abs<T: Number, const R: usize, const C: usize>(x: &TMat<T, R, C>) -> TMat<T, R, C> {
     x.abs()
 }
@@ -37,11 +36,11 @@ pub fn abs<T: Number, const R: usize, const C: usize>(x: &TMat<T, R, C>) -> TMat
 ///
 /// # See also:
 ///
-/// * [`ceil`](fn.ceil.html)
-/// * [`floor`](fn.floor.html)
-/// * [`fract`](fn.fract.html)
-/// * [`round`](fn.round.html)
-/// * [`trunc`](fn.trunc.html)
+/// * [`ceil()`]
+/// * [`floor()`]
+/// * [`fract()`]
+/// * [`round()`]
+/// * [`trunc()`]
 pub fn ceil<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.ceil())
 }
@@ -65,8 +64,8 @@ pub fn ceil<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
 ///
 /// # See also:
 ///
-/// * [`clamp`](fn.clamp.html)
-/// * [`clamp_vec`](fn.clamp_vec.html)
+/// * [`clamp()`]
+/// * [`clamp_vec()`]
 pub fn clamp_scalar<T: Number>(x: T, min_val: T, max_val: T) -> T {
     na::clamp(x, min_val, max_val)
 }
@@ -89,8 +88,8 @@ pub fn clamp_scalar<T: Number>(x: T, min_val: T, max_val: T) -> T {
 ///
 /// # See also:
 ///
-/// * [`clamp_scalar`](fn.clamp_scalar.html)
-/// * [`clamp_vec`](fn.clamp_vec.html)
+/// * [`clamp_scalar()`]
+/// * [`clamp_vec()`]
 pub fn clamp<T: Number, const D: usize>(x: &TVec<T, D>, min_val: T, max_val: T) -> TVec<T, D> {
     x.map(|x| na::clamp(x, min_val, max_val))
 }
@@ -120,8 +119,8 @@ pub fn clamp<T: Number, const D: usize>(x: &TVec<T, D>, min_val: T, max_val: T)
 ///
 /// # See also:
 ///
-/// * [`clamp_scalar`](fn.clamp_scalar.html)
-/// * [`clamp`](fn.clamp.html)
+/// * [`clamp_scalar()`]
+/// * [`clamp()`]
 pub fn clamp_vec<T: Number, const D: usize>(
     x: &TVec<T, D>,
     min_val: &TVec<T, D>,
@@ -136,13 +135,13 @@ pub fn clamp_vec<T: Number, const D: usize>(
 ///
 /// # See also:
 ///
-/// * [`float_bits_to_int_vec`](fn.float_bits_to_int_vec.html)
-/// * [`float_bits_to_uint`](fn.float_bits_to_uint.html)
-/// * [`float_bits_to_uint_vec`](fn.float_bits_to_uint_vec.html)
-/// * [`int_bits_to_float`](fn.int_bits_to_float.html)
-/// * [`int_bits_to_float_vec`](fn.int_bits_to_float_vec.html)
-/// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
-/// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
+/// * [`float_bits_to_int_vec()`]
+/// * [`float_bits_to_uint()`]
+/// * [`float_bits_to_uint_vec()`]
+/// * [`int_bits_to_float()`]
+/// * [`int_bits_to_float_vec()`]
+/// * [`uint_bits_to_float()`]
+/// * [`uint_bits_to_float_scalar()`]
 pub fn float_bits_to_int(v: f32) -> i32 {
     unsafe { mem::transmute(v) }
 }
@@ -153,13 +152,13 @@ pub fn float_bits_to_int(v: f32) -> i32 {
 ///
 /// # See also:
 ///
-/// * [`float_bits_to_int`](fn.float_bits_to_int.html)
-/// * [`float_bits_to_uint`](fn.float_bits_to_uint.html)
-/// * [`float_bits_to_uint_vec`](fn.float_bits_to_uint_vec.html)
-/// * [`int_bits_to_float`](fn.int_bits_to_float.html)
-/// * [`int_bits_to_float_vec`](fn.int_bits_to_float_vec.html)
-/// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
-/// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
+/// * [`float_bits_to_int()`]
+/// * [`float_bits_to_uint()`]
+/// * [`float_bits_to_uint_vec()`]
+/// * [`int_bits_to_float()`]
+/// * [`int_bits_to_float_vec()`]
+/// * [`uint_bits_to_float()`]
+/// * [`uint_bits_to_float_scalar()`]
 pub fn float_bits_to_int_vec<const D: usize>(v: &TVec<f32, D>) -> TVec<i32, D> {
     v.map(float_bits_to_int)
 }
@@ -170,13 +169,13 @@ pub fn float_bits_to_int_vec<const D: usize>(v: &TVec<f32, D>) -> TVec<i32, D> {
 ///
 /// # See also:
 ///
-/// * [`float_bits_to_int`](fn.float_bits_to_int.html)
-/// * [`float_bits_to_int_vec`](fn.float_bits_to_int_vec.html)
-/// * [`float_bits_to_uint_vec`](fn.float_bits_to_uint_vec.html)
-/// * [`int_bits_to_float`](fn.int_bits_to_float.html)
-/// * [`int_bits_to_float_vec`](fn.int_bits_to_float_vec.html)
-/// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
-/// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
+/// * [`float_bits_to_int()`]
+/// * [`float_bits_to_int_vec()`]
+/// * [`float_bits_to_uint_vec()`]
+/// * [`int_bits_to_float()`]
+/// * [`int_bits_to_float_vec()`]
+/// * [`uint_bits_to_float()`]
+/// * [`uint_bits_to_float_scalar()`]
 pub fn float_bits_to_uint(v: f32) -> u32 {
     unsafe { mem::transmute(v) }
 }
@@ -187,13 +186,13 @@ pub fn float_bits_to_uint(v: f32) -> u32 {
 ///
 /// # See also:
 ///
-/// * [`float_bits_to_int`](fn.float_bits_to_int.html)
-/// * [`float_bits_to_int_vec`](fn.float_bits_to_int_vec.html)
-/// * [`float_bits_to_uint`](fn.float_bits_to_uint.html)
-/// * [`int_bits_to_float`](fn.int_bits_to_float.html)
-/// * [`int_bits_to_float_vec`](fn.int_bits_to_float_vec.html)
-/// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
-/// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
+/// * [`float_bits_to_int()`]
+/// * [`float_bits_to_int_vec()`]
+/// * [`float_bits_to_uint()`]
+/// * [`int_bits_to_float()`]
+/// * [`int_bits_to_float_vec()`]
+/// * [`uint_bits_to_float()`]
+/// * [`uint_bits_to_float_scalar()`]
 pub fn float_bits_to_uint_vec<const D: usize>(v: &TVec<f32, D>) -> TVec<u32, D> {
     v.map(float_bits_to_uint)
 }
@@ -210,10 +209,10 @@ pub fn float_bits_to_uint_vec<const D: usize>(v: &TVec<f32, D>) -> TVec<u32, D>
 ///
 /// # See also:
 ///
-/// * [`ceil`](fn.ceil.html)
-/// * [`fract`](fn.fract.html)
-/// * [`round`](fn.round.html)
-/// * [`trunc`](fn.trunc.html)
+/// * [`ceil()`]
+/// * [`fract()`]
+/// * [`round()`]
+/// * [`trunc()`]
 pub fn floor<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.floor())
 }
@@ -236,10 +235,10 @@ pub fn floor<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
 ///
 /// # See also:
 ///
-/// * [`ceil`](fn.ceil.html)
-/// * [`floor`](fn.floor.html)
-/// * [`round`](fn.round.html)
-/// * [`trunc`](fn.trunc.html)
+/// * [`ceil()`]
+/// * [`floor()`]
+/// * [`round()`]
+/// * [`trunc()`]
 pub fn fract<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.fract())
 }
@@ -258,13 +257,13 @@ pub fn fract<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
 ///
 /// # See also:
 ///
-/// * [`float_bits_to_int`](fn.float_bits_to_int.html)
-/// * [`float_bits_to_int_vec`](fn.float_bits_to_int_vec.html)
-/// * [`float_bits_to_uint`](fn.float_bits_to_uint.html)
-/// * [`float_bits_to_uint_vec`](fn.float_bits_to_uint_vec.html)
-/// * [`int_bits_to_float_vec`](fn.int_bits_to_float_vec.html)
-/// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
-/// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
+/// * [`float_bits_to_int()`]
+/// * [`float_bits_to_int_vec()`]
+/// * [`float_bits_to_uint()`]
+/// * [`float_bits_to_uint_vec()`]
+/// * [`int_bits_to_float_vec()`]
+/// * [`uint_bits_to_float()`]
+/// * [`uint_bits_to_float_scalar()`]
 pub fn int_bits_to_float(v: i32) -> f32 {
     f32::from_bits(v as u32)
 }
@@ -275,13 +274,13 @@ pub fn int_bits_to_float(v: i32) -> f32 {
 ///
 /// # See also:
 ///
-/// * [`float_bits_to_int`](fn.float_bits_to_int.html)
-/// * [`float_bits_to_int_vec`](fn.float_bits_to_int_vec.html)
-/// * [`float_bits_to_uint`](fn.float_bits_to_uint.html)
-/// * [`float_bits_to_uint_vec`](fn.float_bits_to_uint_vec.html)
-/// * [`int_bits_to_float`](fn.int_bits_to_float.html)
-/// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
-/// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
+/// * [`float_bits_to_int()`]
+/// * [`float_bits_to_int_vec()`]
+/// * [`float_bits_to_uint()`]
+/// * [`float_bits_to_uint_vec()`]
+/// * [`int_bits_to_float()`]
+/// * [`uint_bits_to_float()`]
+/// * [`uint_bits_to_float_scalar()`]
 pub fn int_bits_to_float_vec<const D: usize>(v: &TVec<i32, D>) -> TVec<f32, D> {
     v.map(int_bits_to_float)
 }
@@ -315,8 +314,8 @@ pub fn int_bits_to_float_vec<const D: usize>(v: &TVec<i32, D>) -> TVec<f32, D> {
 ///
 /// # See also:
 ///
-/// * [`mix`](fn.mix.html)
-/// * [`mix_vec`](fn.mix_vec.html)
+/// * [`mix()`]
+/// * [`mix_vec()`]
 pub fn mix_scalar<T: Number>(x: T, y: T, a: T) -> T {
     x * (T::one() - a) + y * a
 }
@@ -336,8 +335,8 @@ pub fn mix_scalar<T: Number>(x: T, y: T, a: T) -> T {
 ///
 /// # See also:
 ///
-/// * [`mix_scalar`](fn.mix_scalar.html)
-/// * [`mix_vec`](fn.mix_vec.html)
+/// * [`mix_scalar()`]
+/// * [`mix_vec()`]
 pub fn mix<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, a: T) -> TVec<T, D> {
     x * (T::one() - a) + y * a
 }
@@ -359,14 +358,14 @@ pub fn mix<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, a: T) -> T
 ///
 /// # See also:
 ///
-/// * [`mix_scalar`](fn.mix_scalar.html)
-/// * [`mix`](fn.mix.html)
+/// * [`mix_scalar()`]
+/// * [`mix()`]
 pub fn mix_vec<T: Number, const D: usize>(
     x: &TVec<T, D>,
     y: &TVec<T, D>,
     a: &TVec<T, D>,
 ) -> TVec<T, D> {
-    x.component_mul(&(TVec::<T, D>::repeat(T::one()) - a)) + y.component_mul(&a)
+    x.component_mul(&(TVec::<T, D>::repeat(T::one()) - a)) + y.component_mul(a)
 }
 
 /// Returns `x * (1.0 - a) + y * a`, i.e., the linear blend of the scalars x and y using the scalar value a.
@@ -383,8 +382,8 @@ pub fn mix_vec<T: Number, const D: usize>(
 ///
 /// # See also:
 ///
-/// * [`lerp`](fn.lerp.html)
-/// * [`lerp_vec`](fn.lerp_vec.html)
+/// * [`lerp()`]
+/// * [`lerp_vec()`]
 pub fn lerp_scalar<T: Number>(x: T, y: T, a: T) -> T {
     mix_scalar(x, y, a)
 }
@@ -405,8 +404,8 @@ pub fn lerp_scalar<T: Number>(x: T, y: T, a: T) -> T {
 ///
 /// # See also:
 ///
-/// * [`lerp_scalar`](fn.lerp_scalar.html)
-/// * [`lerp_vec`](fn.lerp_vec.html)
+/// * [`lerp_scalar()`]
+/// * [`lerp_vec()`]
 pub fn lerp<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, a: T) -> TVec<T, D> {
     mix(x, y, a)
 }
@@ -429,8 +428,8 @@ pub fn lerp<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, a: T) ->
 ///
 /// # See also:
 ///
-/// * [`lerp_scalar`](fn.lerp_scalar.html)
-/// * [`lerp`](fn.lerp.html)
+/// * [`lerp_scalar()`]
+/// * [`lerp()`]
 pub fn lerp_vec<T: Number, const D: usize>(
     x: &TVec<T, D>,
     y: &TVec<T, D>,
@@ -445,7 +444,7 @@ pub fn lerp_vec<T: Number, const D: usize>(
 ///
 /// # See also:
 ///
-/// * [`modf`](fn.modf.html)
+/// * [`modf()`]
 pub fn modf_vec<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<T, D> {
     x.zip_map(y, |x, y| x % y)
 }
@@ -454,7 +453,7 @@ pub fn modf_vec<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TV
 ///
 /// # See also:
 ///
-/// * [`modf_vec`](fn.modf_vec.html)
+/// * [`modf_vec()`]
 pub fn modf<T: Number>(x: T, i: T) -> T {
     x % i
 }
@@ -473,10 +472,10 @@ pub fn modf<T: Number>(x: T, i: T) -> T {
 ///
 /// # See also:
 ///
-/// * [`ceil`](fn.ceil.html)
-/// * [`floor`](fn.floor.html)
-/// * [`fract`](fn.fract.html)
-/// * [`trunc`](fn.trunc.html)
+/// * [`ceil()`]
+/// * [`floor()`]
+/// * [`fract()`]
+/// * [`trunc()`]
 pub fn round<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.round())
 }
@@ -497,7 +496,7 @@ pub fn round<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
 ///
 /// # See also:
 ///
-/// * [`abs`](fn.abs.html)
+/// * [`abs()`]
 ///
 pub fn sign<T: Number, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| if x.is_zero() { T::zero() } else { x.signum() })
@@ -545,10 +544,10 @@ pub fn step_vec<T: Number, const D: usize>(edge: &TVec<T, D>, x: &TVec<T, D>) ->
 ///
 /// # See also:
 ///
-/// * [`ceil`](fn.ceil.html)
-/// * [`floor`](fn.floor.html)
-/// * [`fract`](fn.fract.html)
-/// * [`round`](fn.round.html)
+/// * [`ceil()`]
+/// * [`floor()`]
+/// * [`fract()`]
+/// * [`round()`]
 pub fn trunc<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.trunc())
 }
@@ -559,13 +558,13 @@ pub fn trunc<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
 ///
 /// # See also:
 ///
-/// * [`float_bits_to_int`](fn.float_bits_to_int.html)
-/// * [`float_bits_to_int_vec`](fn.float_bits_to_int_vec.html)
-/// * [`float_bits_to_uint`](fn.float_bits_to_uint.html)
-/// * [`float_bits_to_uint_vec`](fn.float_bits_to_uint_vec.html)
-/// * [`int_bits_to_float`](fn.int_bits_to_float.html)
-/// * [`int_bits_to_float_vec`](fn.int_bits_to_float_vec.html)
-/// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
+/// * [`float_bits_to_int()`]
+/// * [`float_bits_to_int_vec()`]
+/// * [`float_bits_to_uint()`]
+/// * [`float_bits_to_uint_vec()`]
+/// * [`int_bits_to_float()`]
+/// * [`int_bits_to_float_vec()`]
+/// * [`uint_bits_to_float()`]
 pub fn uint_bits_to_float_scalar(v: u32) -> f32 {
     f32::from_bits(v)
 }
@@ -576,13 +575,13 @@ pub fn uint_bits_to_float_scalar(v: u32) -> f32 {
 ///
 /// # See also:
 ///
-/// * [`float_bits_to_int`](fn.float_bits_to_int.html)
-/// * [`float_bits_to_int_vec`](fn.float_bits_to_int_vec.html)
-/// * [`float_bits_to_uint`](fn.float_bits_to_uint.html)
-/// * [`float_bits_to_uint_vec`](fn.float_bits_to_uint_vec.html)
-/// * [`int_bits_to_float`](fn.int_bits_to_float.html)
-/// * [`int_bits_to_float_vec`](fn.int_bits_to_float_vec.html)
-/// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
+/// * [`float_bits_to_int()`]
+/// * [`float_bits_to_int_vec()`]
+/// * [`float_bits_to_uint()`]
+/// * [`float_bits_to_uint_vec()`]
+/// * [`int_bits_to_float()`]
+/// * [`int_bits_to_float_vec()`]
+/// * [`uint_bits_to_float_scalar()`]
 pub fn uint_bits_to_float<const D: usize>(v: &TVec<u32, D>) -> TVec<f32, D> {
     v.map(uint_bits_to_float_scalar)
 }

nalgebra-glm/src/constructors.rs

@@ -91,6 +91,7 @@ pub fn mat2x4<T: Scalar>(m11: T, m12: T, m13: T, m14: T,
 /// );
 /// ```
 #[rustfmt::skip]
+#[allow(clippy::too_many_arguments)]
 pub fn mat3<T: Scalar>(m11: T, m12: T, m13: T,
                        m21: T, m22: T, m23: T,
                        m31: T, m32: T, m33: T) -> TMat3<T> {
@@ -115,6 +116,7 @@ pub fn mat3x2<T: Scalar>(m11: T, m12: T,
 
 /// Create a new 3x3 matrix.
 #[rustfmt::skip]
+#[allow(clippy::too_many_arguments)]
 pub fn mat3x3<T: Scalar>(m11: T, m12: T, m13: T,
                          m21: T, m22: T, m23: T,
                          m31: T, m32: T, m33: T) -> TMat3<T> {
@@ -127,6 +129,7 @@ pub fn mat3x3<T: Scalar>(m11: T, m12: T, m13: T,
 
 /// Create a new 3x4 matrix.
 #[rustfmt::skip]
+#[allow(clippy::too_many_arguments)]
 pub fn mat3x4<T: Scalar>(m11: T, m12: T, m13: T, m14: T,
                          m21: T, m22: T, m23: T, m24: T,
                          m31: T, m32: T, m33: T, m34: T) -> TMat3x4<T> {
@@ -153,6 +156,7 @@ pub fn mat4x2<T: Scalar>(m11: T, m12: T,
 
 /// Create a new 4x3 matrix.
 #[rustfmt::skip]
+#[allow(clippy::too_many_arguments)]
 pub fn mat4x3<T: Scalar>(m11: T, m12: T, m13: T,
                          m21: T, m22: T, m23: T,
                          m31: T, m32: T, m33: T,
@@ -167,6 +171,7 @@ pub fn mat4x3<T: Scalar>(m11: T, m12: T, m13: T,
 
 /// Create a new 4x4 matrix.
 #[rustfmt::skip]
+#[allow(clippy::too_many_arguments)]
 pub fn mat4x4<T: Scalar>(m11: T, m12: T, m13: T, m14: T,
                          m21: T, m22: T, m23: T, m24: T,
                          m31: T, m32: T, m33: T, m34: T,
@@ -181,6 +186,7 @@ pub fn mat4x4<T: Scalar>(m11: T, m12: T, m13: T, m14: T,
 
 /// Create a new 4x4 matrix.
 #[rustfmt::skip]
+#[allow(clippy::too_many_arguments)]
 pub fn mat4<T: Scalar>(m11: T, m12: T, m13: T, m14: T,
                        m21: T, m22: T, m23: T, m24: T,
                        m31: T, m32: T, m33: T, m34: T,

nalgebra-glm/src/exponential.rs

@@ -5,7 +5,7 @@ use crate::RealNumber;
 ///
 /// # See also:
 ///
-/// * [`exp2`](fn.exp2.html)
+/// * [`exp2()`]
 pub fn exp<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.exp())
 }
@@ -14,7 +14,7 @@ pub fn exp<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
 ///
 /// # See also:
 ///
-/// * [`exp`](fn.exp.html)
+/// * [`exp()`]
 pub fn exp2<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.exp2())
 }
@@ -23,7 +23,7 @@ pub fn exp2<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
 ///
 /// # See also:
 ///
-/// * [`sqrt`](fn.sqrt.html)
+/// * [`sqrt()`]
 pub fn inversesqrt<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| T::one() / x.sqrt())
 }
@@ -32,7 +32,7 @@ pub fn inversesqrt<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D>
 ///
 /// # See also:
 ///
-/// * [`log2`](fn.log2.html)
+/// * [`log2()`]
 pub fn log<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.ln())
 }
@@ -41,7 +41,7 @@ pub fn log<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
 ///
 /// # See also:
 ///
-/// * [`log`](fn.log.html)
+/// * [`log()`]
 pub fn log2<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.log2())
 }
@@ -55,10 +55,10 @@ pub fn pow<T: RealNumber, const D: usize>(base: &TVec<T, D>, exponent: &TVec<T,
 ///
 /// # See also:
 ///
-/// * [`exp`](fn.exp.html)
-/// * [`exp2`](fn.exp2.html)
-/// * [`inversesqrt`](fn.inversesqrt.html)
-/// * [`pow`](fn.pow.html)
+/// * [`exp()`]
+/// * [`exp2()`]
+/// * [`inversesqrt()`]
+/// * [`pow`]
 pub fn sqrt<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.sqrt())
 }

nalgebra-glm/src/ext/matrix_projection.rs

@@ -1,5 +1,3 @@
-use na;
-
 use crate::aliases::{TMat4, TVec2, TVec3, TVec4};
 use crate::RealNumber;
 
@@ -41,11 +39,11 @@ pub fn pick_matrix<T: RealNumber>(
 ///
 /// # See also:
 ///
-/// * [`project_no`](fn.project_no.html)
-/// * [`project_zo`](fn.project_zo.html)
-/// * [`unproject`](fn.unproject.html)
-/// * [`unproject_no`](fn.unproject_no.html)
-/// * [`unproject_zo`](fn.unproject_zo.html)
+/// * [`project_no()`]
+/// * [`project_zo()`]
+/// * [`unproject()`]
+/// * [`unproject_no()`]
+/// * [`unproject_zo()`]
 pub fn project<T: RealNumber>(
     obj: &TVec3<T>,
     model: &TMat4<T>,
@@ -68,11 +66,11 @@ pub fn project<T: RealNumber>(
 ///
 /// # See also:
 ///
-/// * [`project`](fn.project.html)
-/// * [`project_zo`](fn.project_zo.html)
-/// * [`unproject`](fn.unproject.html)
-/// * [`unproject_no`](fn.unproject_no.html)
-/// * [`unproject_zo`](fn.unproject_zo.html)
+/// * [`project()`]
+/// * [`project_zo()`]
+/// * [`unproject()`]
+/// * [`unproject_no()`]
+/// * [`unproject_zo()`]
 pub fn project_no<T: RealNumber>(
     obj: &TVec3<T>,
     model: &TMat4<T>,
@@ -96,11 +94,11 @@ pub fn project_no<T: RealNumber>(
 ///
 /// # See also:
 ///
-/// * [`project`](fn.project.html)
-/// * [`project_no`](fn.project_no.html)
-/// * [`unproject`](fn.unproject.html)
-/// * [`unproject_no`](fn.unproject_no.html)
-/// * [`unproject_zo`](fn.unproject_zo.html)
+/// * [`project()`]
+/// * [`project_no()`]
+/// * [`unproject()`]
+/// * [`unproject_no()`]
+/// * [`unproject_zo()`]
 pub fn project_zo<T: RealNumber>(
     obj: &TVec3<T>,
     model: &TMat4<T>,
@@ -129,11 +127,11 @@ pub fn project_zo<T: RealNumber>(
 ///
 /// # See also:
 ///
-/// * [`project`](fn.project.html)
-/// * [`project_no`](fn.project_no.html)
-/// * [`project_zo`](fn.project_zo.html)
-/// * [`unproject_no`](fn.unproject_no.html)
-/// * [`unproject_zo`](fn.unproject_zo.html)
+/// * [`project()`]
+/// * [`project_no()`]
+/// * [`project_zo()`]
+/// * [`unproject_no()`]
+/// * [`unproject_zo()`]
 pub fn unproject<T: RealNumber>(
     win: &TVec3<T>,
     model: &TMat4<T>,
@@ -156,11 +154,11 @@ pub fn unproject<T: RealNumber>(
 ///
 /// # See also:
 ///
-/// * [`project`](fn.project.html)
-/// * [`project_no`](fn.project_no.html)
-/// * [`project_zo`](fn.project_zo.html)
-/// * [`unproject`](fn.unproject.html)
-/// * [`unproject_zo`](fn.unproject_zo.html)
+/// * [`project()`]
+/// * [`project_no()`]
+/// * [`project_zo()`]
+/// * [`unproject()`]
+/// * [`unproject_zo()`]
 pub fn unproject_no<T: RealNumber>(
     win: &TVec3<T>,
     model: &TMat4<T>,
@@ -193,11 +191,11 @@ pub fn unproject_no<T: RealNumber>(
 ///
 /// # See also:
 ///
-/// * [`project`](fn.project.html)
-/// * [`project_no`](fn.project_no.html)
-/// * [`project_zo`](fn.project_zo.html)
-/// * [`unproject`](fn.unproject.html)
-/// * [`unproject_no`](fn.unproject_no.html)
+/// * [`project()`]
+/// * [`project_no()`]
+/// * [`project_zo()`]
+/// * [`unproject()`]
+/// * [`unproject_no()`]
 pub fn unproject_zo<T: RealNumber>(
     win: &TVec3<T>,
     model: &TMat4<T>,

nalgebra-glm/src/ext/matrix_transform.rs

@@ -18,8 +18,8 @@ pub fn identity<T: Number, const D: usize>() -> TMat<T, D, D> {
 ///
 /// # See also:
 ///
-/// * [`look_at_lh`](fn.look_at_lh.html)
-/// * [`look_at_rh`](fn.look_at_rh.html)
+/// * [`look_at_lh()`]
+/// * [`look_at_rh()`]
 pub fn look_at<T: RealNumber>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
     look_at_rh(eye, center, up)
 }
@@ -34,8 +34,8 @@ pub fn look_at<T: RealNumber>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>)
 ///
 /// # See also:
 ///
-/// * [`look_at`](fn.look_at.html)
-/// * [`look_at_rh`](fn.look_at_rh.html)
+/// * [`look_at()`]
+/// * [`look_at_rh()`]
 pub fn look_at_lh<T: RealNumber>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
     TMat::look_at_lh(&Point3::from(*eye), &Point3::from(*center), up)
 }
@@ -50,8 +50,8 @@ pub fn look_at_lh<T: RealNumber>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T
 ///
 /// # See also:
 ///
-/// * [`look_at`](fn.look_at.html)
-/// * [`look_at_lh`](fn.look_at_lh.html)
+/// * [`look_at()`]
+/// * [`look_at_lh()`]
 pub fn look_at_rh<T: RealNumber>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
     TMat::look_at_rh(&Point3::from(*eye), &Point3::from(*center), up)
 }
@@ -66,11 +66,11 @@ pub fn look_at_rh<T: RealNumber>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T
 ///
 /// # See also:
 ///
-/// * [`rotate_x`](fn.rotate_x.html)
-/// * [`rotate_y`](fn.rotate_y.html)
-/// * [`rotate_z`](fn.rotate_z.html)
-/// * [`scale`](fn.scale.html)
-/// * [`translate`](fn.translate.html)
+/// * [`rotate_x()`]
+/// * [`rotate_y()`]
+/// * [`rotate_z()`]
+/// * [`scale()`]
+/// * [`translate()`]
 pub fn rotate<T: RealNumber>(m: &TMat4<T>, angle: T, axis: &TVec3<T>) -> TMat4<T> {
     m * Rotation3::from_axis_angle(&Unit::new_normalize(*axis), angle).to_homogeneous()
 }
@@ -84,11 +84,11 @@ pub fn rotate<T: RealNumber>(m: &TMat4<T>, angle: T, axis: &TVec3<T>) -> TMat4<T
 ///
 /// # See also:
 ///
-/// * [`rotate`](fn.rotate.html)
-/// * [`rotate_y`](fn.rotate_y.html)
-/// * [`rotate_z`](fn.rotate_z.html)
-/// * [`scale`](fn.scale.html)
-/// * [`translate`](fn.translate.html)
+/// * [`rotate()`]
+/// * [`rotate_y()`]
+/// * [`rotate_z()`]
+/// * [`scale()`]
+/// * [`translate()`]
 pub fn rotate_x<T: RealNumber>(m: &TMat4<T>, angle: T) -> TMat4<T> {
     rotate(m, angle, &TVec::x())
 }
@@ -102,11 +102,11 @@ pub fn rotate_x<T: RealNumber>(m: &TMat4<T>, angle: T) -> TMat4<T> {
 ///
 /// # See also:
 ///
-/// * [`rotate`](fn.rotate.html)
-/// * [`rotate_x`](fn.rotate_x.html)
-/// * [`rotate_z`](fn.rotate_z.html)
-/// * [`scale`](fn.scale.html)
-/// * [`translate`](fn.translate.html)
+/// * [`rotate()`]
+/// * [`rotate_x()`]
+/// * [`rotate_z()`]
+/// * [`scale()`]
+/// * [`translate()`]
 pub fn rotate_y<T: RealNumber>(m: &TMat4<T>, angle: T) -> TMat4<T> {
     rotate(m, angle, &TVec::y())
 }
@@ -120,11 +120,11 @@ pub fn rotate_y<T: RealNumber>(m: &TMat4<T>, angle: T) -> TMat4<T> {
 ///
 /// # See also:
 ///
-/// * [`rotate`](fn.rotate.html)
-/// * [`rotate_x`](fn.rotate_x.html)
-/// * [`rotate_y`](fn.rotate_y.html)
-/// * [`scale`](fn.scale.html)
-/// * [`translate`](fn.translate.html)
+/// * [`rotate()`]
+/// * [`rotate_x()`]
+/// * [`rotate_y()`]
+/// * [`scale()`]
+/// * [`translate()`]
 pub fn rotate_z<T: RealNumber>(m: &TMat4<T>, angle: T) -> TMat4<T> {
     rotate(m, angle, &TVec::z())
 }
@@ -138,11 +138,11 @@ pub fn rotate_z<T: RealNumber>(m: &TMat4<T>, angle: T) -> TMat4<T> {
 ///
 /// # See also:
 ///
-/// * [`rotate`](fn.rotate.html)
-/// * [`rotate_x`](fn.rotate_x.html)
-/// * [`rotate_y`](fn.rotate_y.html)
-/// * [`rotate_z`](fn.rotate_z.html)
-/// * [`translate`](fn.translate.html)
+/// * [`rotate()`]
+/// * [`rotate_x()`]
+/// * [`rotate_y()`]
+/// * [`rotate_z()`]
+/// * [`translate()`]
 pub fn scale<T: Number>(m: &TMat4<T>, v: &TVec3<T>) -> TMat4<T> {
     m.prepend_nonuniform_scaling(v)
 }
@@ -156,11 +156,11 @@ pub fn scale<T: Number>(m: &TMat4<T>, v: &TVec3<T>) -> TMat4<T> {
 ///
 /// # See also:
 ///
-/// * [`rotate`](fn.rotate.html)
-/// * [`rotate_x`](fn.rotate_x.html)
-/// * [`rotate_y`](fn.rotate_y.html)
-/// * [`rotate_z`](fn.rotate_z.html)
-/// * [`scale`](fn.scale.html)
+/// * [`rotate()`]
+/// * [`rotate_x()`]
+/// * [`rotate_y()`]
+/// * [`rotate_z()`]
+/// * [`scale()`]
 pub fn translate<T: Number>(m: &TMat4<T>, v: &TVec3<T>) -> TMat4<T> {
     m.prepend_translation(v)
 }

nalgebra-glm/src/ext/quaternion_common.rs

@@ -1,4 +1,4 @@
-use na::{self, Unit};
+use na::Unit;
 
 use crate::aliases::Qua;
 use crate::RealNumber;

nalgebra-glm/src/ext/scalar_common.rs

@@ -12,9 +12,9 @@ use crate::traits::Number;
 ///
 /// # See also:
 ///
-/// * [`max4_scalar`](fn.max4_scalar.html)
-/// * [`min3_scalar`](fn.min3_scalar.html)
-/// * [`min4_scalar`](fn.min4_scalar.html)
+/// * [`max4_scalar()`]
+/// * [`min3_scalar()`]
+/// * [`min4_scalar()`]
 pub fn max2_scalar<T: Number>(a: T, b: T) -> T {
     if a >= b {
         a
@@ -35,9 +35,9 @@ pub fn max2_scalar<T: Number>(a: T, b: T) -> T {
 ///
 /// # See also:
 ///
-/// * [`max4_scalar`](fn.max4_scalar.html)
-/// * [`min3_scalar`](fn.min3_scalar.html)
-/// * [`min4_scalar`](fn.min4_scalar.html)
+/// * [`max4_scalar()`]
+/// * [`min3_scalar()`]
+/// * [`min4_scalar()`]
 pub fn min2_scalar<T: Number>(a: T, b: T) -> T {
     if a <= b {
         a
@@ -58,9 +58,9 @@ pub fn min2_scalar<T: Number>(a: T, b: T) -> T {
 ///
 /// # See also:
 ///
-/// * [`max4_scalar`](fn.max4_scalar.html)
-/// * [`min3_scalar`](fn.min3_scalar.html)
-/// * [`min4_scalar`](fn.min4_scalar.html)
+/// * [`max4_scalar()`]
+/// * [`min3_scalar()`]
+/// * [`min4_scalar()`]
 pub fn max3_scalar<T: Number>(a: T, b: T, c: T) -> T {
     max2_scalar(max2_scalar(a, b), c)
 }
@@ -77,9 +77,9 @@ pub fn max3_scalar<T: Number>(a: T, b: T, c: T) -> T {
 ///
 /// # See also:
 ///
-/// * [`max3_scalar`](fn.max3_scalar.html)
-/// * [`min3_scalar`](fn.min3_scalar.html)
-/// * [`min4_scalar`](fn.min4_scalar.html)
+/// * [`max3_scalar()`]
+/// * [`min3_scalar()`]
+/// * [`min4_scalar()`]
 pub fn max4_scalar<T: Number>(a: T, b: T, c: T, d: T) -> T {
     max2_scalar(max2_scalar(a, b), max2_scalar(c, d))
 }
@@ -96,9 +96,9 @@ pub fn max4_scalar<T: Number>(a: T, b: T, c: T, d: T) -> T {
 ///
 /// # See also:
 ///
-/// * [`max3_scalar`](fn.max3_scalar.html)
-/// * [`max4_scalar`](fn.max4_scalar.html)
-/// * [`min4_scalar`](fn.min4_scalar.html)
+/// * [`max3_scalar()`]
+/// * [`max4_scalar()`]
+/// * [`min4_scalar()`]
 pub fn min3_scalar<T: Number>(a: T, b: T, c: T) -> T {
     min2_scalar(min2_scalar(a, b), c)
 }
@@ -115,9 +115,9 @@ pub fn min3_scalar<T: Number>(a: T, b: T, c: T) -> T {
 ///
 /// # See also:
 ///
-/// * [`max3_scalar`](fn.max3_scalar.html)
-/// * [`max4_scalar`](fn.max4_scalar.html)
-/// * [`min3_scalar`](fn.min3_scalar.html)
+/// * [`max3_scalar()`]
+/// * [`max4_scalar()`]
+/// * [`min3_scalar()`]
 pub fn min4_scalar<T: Number>(a: T, b: T, c: T, d: T) -> T {
     min2_scalar(min2_scalar(a, b), min2_scalar(c, d))
 }

nalgebra-glm/src/ext/scalar_constants.rs

@@ -10,18 +10,18 @@ pub fn epsilon<T: AbsDiffEq<Epsilon = T>>() -> T {
 ///
 /// # See also:
 ///
-/// * [`four_over_pi`](fn.four_over_pi.html)
-/// * [`half_pi`](fn.half_pi.html)
-/// * [`one_over_pi`](fn.one_over_pi.html)
-/// * [`one_over_two_pi`](fn.one_over_two_pi.html)
-/// * [`quarter_pi`](fn.quarter_pi.html)
-/// * [`root_half_pi`](fn.root_half_pi.html)
-/// * [`root_pi`](fn.root_pi.html)
-/// * [`root_two_pi`](fn.root_two_pi.html)
-/// * [`three_over_two_pi`](fn.three_over_two_pi.html)
-/// * [`two_over_pi`](fn.two_over_pi.html)
-/// * [`two_over_root_pi`](fn.two_over_root_pi.html)
-/// * [`two_pi`](fn.two_pi.html)
+/// * [`four_over_pi()`](crate::four_over_pi)
+/// * [`half_pi()`](crate::half_pi)
+/// * [`one_over_pi()`](crate::one_over_pi)
+/// * [`one_over_two_pi()`](crate::one_over_two_pi)
+/// * [`quarter_pi()`](crate::quarter_pi)
+/// * [`root_half_pi()`](crate::root_half_pi)
+/// * [`root_pi()`](crate::root_pi)
+/// * [`root_two_pi()`](crate::root_two_pi)
+/// * [`three_over_two_pi()`](crate::three_over_two_pi)
+/// * [`two_over_pi()`](crate::two_over_pi)
+/// * [`two_over_root_pi()`](crate::two_over_root_pi)
+/// * [`two_pi()`](crate::two_pi)
 pub fn pi<T: RealNumber>() -> T {
     T::pi()
 }

nalgebra-glm/src/ext/vector_common.rs

@@ -5,15 +5,15 @@ use crate::traits::Number;
 ///
 /// # See also:
 ///
-/// * [`comp_max`](fn.comp_max.html)
-/// * [`comp_min`](fn.comp_min.html)
-/// * [`max2`](fn.max2.html)
-/// * [`max3`](fn.max3.html)
-/// * [`max4`](fn.max4.html)
-/// * [`min`](fn.min.html)
-/// * [`min2`](fn.min2.html)
-/// * [`min3`](fn.min3.html)
-/// * [`min4`](fn.min4.html)
+/// * [`comp_max()`](crate::comp_max)
+/// * [`comp_min()`](crate::comp_min)
+/// * [`max2()`]
+/// * [`max3()`]
+/// * [`max4()`]
+/// * [`min()`]
+/// * [`min2()`]
+/// * [`min3()`]
+/// * [`min4()`]
 pub fn max<T: Number, const D: usize>(a: &TVec<T, D>, b: T) -> TVec<T, D> {
     a.map(|a| crate::max2_scalar(a, b))
 }
@@ -22,15 +22,15 @@ pub fn max<T: Number, const D: usize>(a: &TVec<T, D>, b: T) -> TVec<T, D> {
 ///
 /// # See also:
 ///
-/// * [`comp_max`](fn.comp_max.html)
-/// * [`comp_min`](fn.comp_min.html)
-/// * [`max`](fn.max.html)
-/// * [`max3`](fn.max3.html)
-/// * [`max4`](fn.max4.html)
-/// * [`min`](fn.min.html)
-/// * [`min2`](fn.min2.html)
-/// * [`min3`](fn.min3.html)
-/// * [`min4`](fn.min4.html)
+/// * [`comp_max()`](crate::comp_max)
+/// * [`comp_min()`](crate::comp_min)
+/// * [`max()`]
+/// * [`max3()`]
+/// * [`max4()`]
+/// * [`min()`]
+/// * [`min2()`]
+/// * [`min3()`]
+/// * [`min4()`]
 pub fn max2<T: Number, const D: usize>(a: &TVec<T, D>, b: &TVec<T, D>) -> TVec<T, D> {
     a.zip_map(b, |a, b| crate::max2_scalar(a, b))
 }
@@ -39,15 +39,15 @@ pub fn max2<T: Number, const D: usize>(a: &TVec<T, D>, b: &TVec<T, D>) -> TVec<T
 ///
 /// # See also:
 ///
-/// * [`comp_max`](fn.comp_max.html)
-/// * [`comp_min`](fn.comp_min.html)
-/// * [`max`](fn.max.html)
-/// * [`max2`](fn.max2.html)
-/// * [`max4`](fn.max4.html)
-/// * [`min`](fn.min.html)
-/// * [`min2`](fn.min2.html)
-/// * [`min3`](fn.min3.html)
-/// * [`min4`](fn.min4.html)
+/// * [`comp_max()`](crate::comp_max)
+/// * [`comp_min()`](crate::comp_min)
+/// * [`max()`]
+/// * [`max2()`]
+/// * [`max4()`]
+/// * [`min()`]
+/// * [`min2()`]
+/// * [`min3()`]
+/// * [`min4()`]
 pub fn max3<T: Number, const D: usize>(
     a: &TVec<T, D>,
     b: &TVec<T, D>,
@@ -60,15 +60,15 @@ pub fn max3<T: Number, const D: usize>(
 ///
 /// # See also:
 ///
-/// * [`comp_max`](fn.comp_max.html)
-/// * [`comp_min`](fn.comp_min.html)
-/// * [`max`](fn.max.html)
-/// * [`max2`](fn.max2.html)
-/// * [`max3`](fn.max3.html)
-/// * [`min`](fn.min.html)
-/// * [`min2`](fn.min2.html)
-/// * [`min3`](fn.min3.html)
-/// * [`min4`](fn.min4.html)
+/// * [`comp_max()`](crate::comp_max)
+/// * [`comp_min()`](crate::comp_min)
+/// * [`max()`]
+/// * [`max2()`]
+/// * [`max3()`]
+/// * [`min()`]
+/// * [`min2()`]
+/// * [`min3()`]
+/// * [`min4()`]
 pub fn max4<T: Number, const D: usize>(
     a: &TVec<T, D>,
     b: &TVec<T, D>,
@@ -82,15 +82,15 @@ pub fn max4<T: Number, const D: usize>(
 ///
 /// # See also:
 ///
-/// * [`comp_max`](fn.comp_max.html)
-/// * [`comp_min`](fn.comp_min.html)
-/// * [`max`](fn.max.html)
-/// * [`max2`](fn.max2.html)
-/// * [`max3`](fn.max3.html)
-/// * [`max4`](fn.max4.html)
-/// * [`min2`](fn.min2.html)
-/// * [`min3`](fn.min3.html)
-/// * [`min4`](fn.min4.html)
+/// * [`comp_max()`](crate::comp_max)
+/// * [`comp_min()`](crate::comp_min)
+/// * [`max()`]
+/// * [`max2()`]
+/// * [`max3()`]
+/// * [`max4()`]
+/// * [`min2()`]
+/// * [`min3()`]
+/// * [`min4()`]
 pub fn min<T: Number, const D: usize>(x: &TVec<T, D>, y: T) -> TVec<T, D> {
     x.map(|x| crate::min2_scalar(x, y))
 }
@@ -99,15 +99,15 @@ pub fn min<T: Number, const D: usize>(x: &TVec<T, D>, y: T) -> TVec<T, D> {
 ///
 /// # See also:
 ///
-/// * [`comp_max`](fn.comp_max.html)
-/// * [`comp_min`](fn.comp_min.html)
-/// * [`max`](fn.max.html)
-/// * [`max2`](fn.max2.html)
-/// * [`max3`](fn.max3.html)
-/// * [`max4`](fn.max4.html)
-/// * [`min`](fn.min.html)
-/// * [`min3`](fn.min3.html)
-/// * [`min4`](fn.min4.html)
+/// * [`comp_max()`](crate::comp_max)
+/// * [`comp_min()`](crate::comp_min)
+/// * [`max()`]
+/// * [`max2()`]
+/// * [`max3()`]
+/// * [`max4()`]
+/// * [`min()`]
+/// * [`min3()`]
+/// * [`min4()`]
 pub fn min2<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<T, D> {
     x.zip_map(y, |a, b| crate::min2_scalar(a, b))
 }
@@ -116,15 +116,15 @@ pub fn min2<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<T
 ///
 /// # See also:
 ///
-/// * [`comp_max`](fn.comp_max.html)
-/// * [`comp_min`](fn.comp_min.html)
-/// * [`max`](fn.max.html)
-/// * [`max2`](fn.max2.html)
-/// * [`max3`](fn.max3.html)
-/// * [`max4`](fn.max4.html)
-/// * [`min`](fn.min.html)
-/// * [`min2`](fn.min2.html)
-/// * [`min4`](fn.min4.html)
+/// * [`comp_max()`](crate::comp_max)
+/// * [`comp_min()`](crate::comp_min)
+/// * [`max()`]
+/// * [`max2()`]
+/// * [`max3()`]
+/// * [`max4()`]
+/// * [`min()`]
+/// * [`min2()`]
+/// * [`min4()`]
 pub fn min3<T: Number, const D: usize>(
     a: &TVec<T, D>,
     b: &TVec<T, D>,
@@ -137,15 +137,15 @@ pub fn min3<T: Number, const D: usize>(
 ///
 /// # See also:
 ///
-/// * [`comp_max`](fn.comp_max.html)
-/// * [`comp_min`](fn.comp_min.html)
-/// * [`max`](fn.max.html)
-/// * [`max2`](fn.max2.html)
-/// * [`max3`](fn.max3.html)
-/// * [`max4`](fn.max4.html)
-/// * [`min`](fn.min.html)
-/// * [`min2`](fn.min2.html)
-/// * [`min3`](fn.min3.html)
+/// * [`comp_max()`](crate::comp_max)
+/// * [`comp_min()`](crate::comp_min)
+/// * [`max()`]
+/// * [`max2()`]
+/// * [`max3()`]
+/// * [`max4()`]
+/// * [`min()`]
+/// * [`min2()`]
+/// * [`min3()`]
 pub fn min4<T: Number, const D: usize>(
     a: &TVec<T, D>,
     b: &TVec<T, D>,

nalgebra-glm/src/ext/vector_relational.rs

@@ -5,9 +5,9 @@ use crate::traits::Number;
 ///
 /// # See also:
 ///
-/// * [`equal_eps_vec`](fn.equal_eps_vec.html)
-/// * [`not_equal_eps`](fn.not_equal_eps.html)
-/// * [`not_equal_eps_vec`](fn.not_equal_eps_vec.html)
+/// * [`equal_eps_vec()`]
+/// * [`not_equal_eps()`]
+/// * [`not_equal_eps_vec()`]
 pub fn equal_eps<T: Number, const D: usize>(
     x: &TVec<T, D>,
     y: &TVec<T, D>,
@@ -20,9 +20,9 @@ pub fn equal_eps<T: Number, const D: usize>(
 ///
 /// # See also:
 ///
-/// * [`equal_eps`](fn.equal_eps.html)
-/// * [`not_equal_eps`](fn.not_equal_eps.html)
-/// * [`not_equal_eps_vec`](fn.not_equal_eps_vec.html)
+/// * [`equal_eps()`]
+/// * [`not_equal_eps()`]
+/// * [`not_equal_eps_vec()`]
 pub fn equal_eps_vec<T: Number, const D: usize>(
     x: &TVec<T, D>,
     y: &TVec<T, D>,
@@ -35,9 +35,9 @@ pub fn equal_eps_vec<T: Number, const D: usize>(
 ///
 /// # See also:
 ///
-/// * [`equal_eps`](fn.equal_eps.html)
-/// * [`equal_eps_vec`](fn.equal_eps_vec.html)
-/// * [`not_equal_eps_vec`](fn.not_equal_eps_vec.html)
+/// * [`equal_eps()`]
+/// * [`equal_eps_vec()`]
+/// * [`not_equal_eps_vec()`]
 pub fn not_equal_eps<T: Number, const D: usize>(
     x: &TVec<T, D>,
     y: &TVec<T, D>,
@@ -50,9 +50,9 @@ pub fn not_equal_eps<T: Number, const D: usize>(
 ///
 /// # See also:
 ///
-/// * [`equal_eps`](fn.equal_eps.html)
-/// * [`equal_eps_vec`](fn.equal_eps_vec.html)
-/// * [`not_equal_eps`](fn.not_equal_eps.html)
+/// * [`equal_eps()`]
+/// * [`equal_eps_vec()`]
+/// * [`not_equal_eps()`]
 pub fn not_equal_eps_vec<T: Number, const D: usize>(
     x: &TVec<T, D>,
     y: &TVec<T, D>,

nalgebra-glm/src/geometric.rs

@@ -12,7 +12,7 @@ pub fn cross<T: Number>(x: &TVec3<T>, y: &TVec3<T>) -> TVec3<T> {
 ///
 /// # See also:
 ///
-/// * [`distance2`](fn.distance2.html)
+/// * [`distance2()`](crate::distance2)
 pub fn distance<T: RealNumber, const D: usize>(p0: &TVec<T, D>, p1: &TVec<T, D>) -> T {
     (p1 - p0).norm()
 }
@@ -37,13 +37,13 @@ pub fn faceforward<T: Number, const D: usize>(
 
 /// The magnitude of a vector.
 ///
-/// A synonym for [`magnitude`](fn.magnitude.html).
+/// A synonym for [`magnitude()`].
 ///
 /// # See also:
 ///
-/// * [`length2`](fn.length2.html)
-/// * [`magnitude`](fn.magnitude.html)
-/// * [`magnitude2`](fn.magnitude2.html)
+/// * [`length2()`](crate::length2)
+/// * [`magnitude()`]
+/// * [`magnitude2()`](crate::magnitude2)
 pub fn length<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm()
 }
@@ -54,8 +54,8 @@ pub fn length<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> T {
 ///
 /// # See also:
 ///
-/// * [`length`](fn.length.html)
-/// * [`magnitude2`](fn.magnitude2.html)
+/// * [`length()`]
+/// * [`magnitude2()`](crate::magnitude2)
 /// * [`nalgebra::norm`](../nalgebra/fn.norm.html)
 pub fn magnitude<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm()

nalgebra-glm/src/gtc/constants.rs

@@ -1,9 +1,8 @@
 use crate::RealNumber;
-use na;
 
 /// The Euler constant.
 ///
-/// This is a shorthand alias for [`euler`](fn.euler.html).
+/// This is a shorthand alias for [`euler()`].
 pub fn e<T: RealNumber>() -> T {
     T::e()
 }
@@ -17,18 +16,18 @@ pub fn euler<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`half_pi`](fn.half_pi.html)
-/// * [`one_over_pi`](fn.one_over_pi.html)
-/// * [`one_over_two_pi`](fn.one_over_two_pi.html)
-/// * [`pi`](fn.pi.html)
-/// * [`quarter_pi`](fn.quarter_pi.html)
-/// * [`root_half_pi`](fn.root_half_pi.html)
-/// * [`root_pi`](fn.root_pi.html)
-/// * [`root_two_pi`](fn.root_two_pi.html)
-/// * [`three_over_two_pi`](fn.three_over_two_pi.html)
-/// * [`two_over_pi`](fn.two_over_pi.html)
-/// * [`two_over_root_pi`](fn.two_over_root_pi.html)
-/// * [`two_pi`](fn.two_pi.html)
+/// * [`half_pi()`]
+/// * [`one_over_pi()`]
+/// * [`one_over_two_pi()`]
+/// * [`pi()`](crate::pi)
+/// * [`quarter_pi()`]
+/// * [`root_half_pi()`]
+/// * [`root_pi()`]
+/// * [`root_two_pi()`]
+/// * [`three_over_two_pi()`]
+/// * [`two_over_pi()`]
+/// * [`two_over_root_pi()`]
+/// * [`two_pi()`]
 pub fn four_over_pi<T: RealNumber>() -> T {
     na::convert::<_, T>(4.0) / T::pi()
 }
@@ -42,18 +41,18 @@ pub fn golden_ratio<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`four_over_pi`](fn.four_over_pi.html)
-/// * [`one_over_pi`](fn.one_over_pi.html)
-/// * [`one_over_two_pi`](fn.one_over_two_pi.html)
-/// * [`pi`](fn.pi.html)
-/// * [`quarter_pi`](fn.quarter_pi.html)
-/// * [`root_half_pi`](fn.root_half_pi.html)
-/// * [`root_pi`](fn.root_pi.html)
-/// * [`root_two_pi`](fn.root_two_pi.html)
-/// * [`three_over_two_pi`](fn.three_over_two_pi.html)
-/// * [`two_over_pi`](fn.two_over_pi.html)
-/// * [`two_over_root_pi`](fn.two_over_root_pi.html)
-/// * [`two_pi`](fn.two_pi.html)
+/// * [`four_over_pi()`]
+/// * [`one_over_pi()`]
+/// * [`one_over_two_pi()`]
+/// * [`pi()`](crate::pi)
+/// * [`quarter_pi()`]
+/// * [`root_half_pi()`]
+/// * [`root_pi()`]
+/// * [`root_two_pi()`]
+/// * [`three_over_two_pi()`]
+/// * [`two_over_pi()`]
+/// * [`two_over_root_pi()`]
+/// * [`two_pi()`]
 pub fn half_pi<T: RealNumber>() -> T {
     T::frac_pi_2()
 }
@@ -62,8 +61,8 @@ pub fn half_pi<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`ln_ten`](fn.ln_ten.html)
-/// * [`ln_two`](fn.ln_two.html)
+/// * [`ln_ten()`]
+/// * [`ln_two()`]
 pub fn ln_ln_two<T: RealNumber>() -> T {
     T::ln_2().ln()
 }
@@ -72,8 +71,8 @@ pub fn ln_ln_two<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`ln_ln_two`](fn.ln_ln_two.html)
-/// * [`ln_two`](fn.ln_two.html)
+/// * [`ln_ln_two()`]
+/// * [`ln_two()`]
 pub fn ln_ten<T: RealNumber>() -> T {
     T::ln_10()
 }
@@ -82,8 +81,8 @@ pub fn ln_ten<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`ln_ln_two`](fn.ln_ln_two.html)
-/// * [`ln_ten`](fn.ln_ten.html)
+/// * [`ln_ln_two()`]
+/// * [`ln_ten()`]
 pub fn ln_two<T: RealNumber>() -> T {
     T::ln_2()
 }
@@ -95,18 +94,18 @@ pub use na::one;
 ///
 /// # See also:
 ///
-/// * [`four_over_pi`](fn.four_over_pi.html)
-/// * [`half_pi`](fn.half_pi.html)
-/// * [`one_over_two_pi`](fn.one_over_two_pi.html)
-/// * [`pi`](fn.pi.html)
-/// * [`quarter_pi`](fn.quarter_pi.html)
-/// * [`root_half_pi`](fn.root_half_pi.html)
-/// * [`root_pi`](fn.root_pi.html)
-/// * [`root_two_pi`](fn.root_two_pi.html)
-/// * [`three_over_two_pi`](fn.three_over_two_pi.html)
-/// * [`two_over_pi`](fn.two_over_pi.html)
-/// * [`two_over_root_pi`](fn.two_over_root_pi.html)
-/// * [`two_pi`](fn.two_pi.html)
+/// * [`four_over_pi()`]
+/// * [`half_pi()`]
+/// * [`one_over_two_pi()`]
+/// * [`pi()`](crate::pi)
+/// * [`quarter_pi()`]
+/// * [`root_half_pi()`]
+/// * [`root_pi()`]
+/// * [`root_two_pi()`]
+/// * [`three_over_two_pi()`]
+/// * [`two_over_pi()`]
+/// * [`two_over_root_pi()`]
+/// * [`two_pi()`]
 pub fn one_over_pi<T: RealNumber>() -> T {
     T::frac_1_pi()
 }
@@ -120,18 +119,18 @@ pub fn one_over_root_two<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`four_over_pi`](fn.four_over_pi.html)
-/// * [`half_pi`](fn.half_pi.html)
-/// * [`one_over_pi`](fn.one_over_pi.html)
-/// * [`pi`](fn.pi.html)
-/// * [`quarter_pi`](fn.quarter_pi.html)
-/// * [`root_half_pi`](fn.root_half_pi.html)
-/// * [`root_pi`](fn.root_pi.html)
-/// * [`root_two_pi`](fn.root_two_pi.html)
-/// * [`three_over_two_pi`](fn.three_over_two_pi.html)
-/// * [`two_over_pi`](fn.two_over_pi.html)
-/// * [`two_over_root_pi`](fn.two_over_root_pi.html)
-/// * [`two_pi`](fn.two_pi.html)
+/// * [`four_over_pi()`]
+/// * [`half_pi()`]
+/// * [`one_over_pi()`]
+/// * [`pi()`](crate::pi)
+/// * [`quarter_pi()`]
+/// * [`root_half_pi()`]
+/// * [`root_pi()`]
+/// * [`root_two_pi()`]
+/// * [`three_over_two_pi()`]
+/// * [`two_over_pi()`]
+/// * [`two_over_root_pi()`]
+/// * [`two_pi()`]
 pub fn one_over_two_pi<T: RealNumber>() -> T {
     T::frac_1_pi() * na::convert(0.5)
 }
@@ -140,18 +139,18 @@ pub fn one_over_two_pi<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`four_over_pi`](fn.four_over_pi.html)
-/// * [`half_pi`](fn.half_pi.html)
-/// * [`one_over_pi`](fn.one_over_pi.html)
-/// * [`one_over_two_pi`](fn.one_over_two_pi.html)
-/// * [`pi`](fn.pi.html)
-/// * [`root_half_pi`](fn.root_half_pi.html)
-/// * [`root_pi`](fn.root_pi.html)
-/// * [`root_two_pi`](fn.root_two_pi.html)
-/// * [`three_over_two_pi`](fn.three_over_two_pi.html)
-/// * [`two_over_pi`](fn.two_over_pi.html)
-/// * [`two_over_root_pi`](fn.two_over_root_pi.html)
-/// * [`two_pi`](fn.two_pi.html)
+/// * [`four_over_pi()`]
+/// * [`half_pi()`]
+/// * [`one_over_pi()`]
+/// * [`one_over_two_pi()`]
+/// * [`pi()`](crate::pi)
+/// * [`root_half_pi()`]
+/// * [`root_pi()`]
+/// * [`root_two_pi()`]
+/// * [`three_over_two_pi()`]
+/// * [`two_over_pi()`]
+/// * [`two_over_root_pi()`]
+/// * [`two_pi()`]
 pub fn quarter_pi<T: RealNumber>() -> T {
     T::frac_pi_4()
 }
@@ -160,8 +159,8 @@ pub fn quarter_pi<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`root_three`](fn.root_three.html)
-/// * [`root_two`](fn.root_two.html)
+/// * [`root_three()`]
+/// * [`root_two()`]
 pub fn root_five<T: RealNumber>() -> T {
     na::convert::<_, T>(5.0).sqrt()
 }
@@ -170,18 +169,18 @@ pub fn root_five<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`four_over_pi`](fn.four_over_pi.html)
-/// * [`half_pi`](fn.half_pi.html)
-/// * [`one_over_pi`](fn.one_over_pi.html)
-/// * [`one_over_two_pi`](fn.one_over_two_pi.html)
-/// * [`pi`](fn.pi.html)
-/// * [`quarter_pi`](fn.quarter_pi.html)
-/// * [`root_pi`](fn.root_pi.html)
-/// * [`root_two_pi`](fn.root_two_pi.html)
-/// * [`three_over_two_pi`](fn.three_over_two_pi.html)
-/// * [`two_over_pi`](fn.two_over_pi.html)
-/// * [`two_over_root_pi`](fn.two_over_root_pi.html)
-/// * [`two_pi`](fn.two_pi.html)
+/// * [`four_over_pi()`]
+/// * [`half_pi()`]
+/// * [`one_over_pi()`]
+/// * [`one_over_two_pi()`]
+/// * [`pi()`](crate::pi)
+/// * [`quarter_pi()`]
+/// * [`root_pi()`]
+/// * [`root_two_pi()`]
+/// * [`three_over_two_pi()`]
+/// * [`two_over_pi()`]
+/// * [`two_over_root_pi()`]
+/// * [`two_pi()`]
 pub fn root_half_pi<T: RealNumber>() -> T {
     (T::pi() / na::convert(2.0)).sqrt()
 }
@@ -195,18 +194,18 @@ pub fn root_ln_four<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`four_over_pi`](fn.four_over_pi.html)
-/// * [`half_pi`](fn.half_pi.html)
-/// * [`one_over_pi`](fn.one_over_pi.html)
-/// * [`one_over_two_pi`](fn.one_over_two_pi.html)
-/// * [`pi`](fn.pi.html)
-/// * [`quarter_pi`](fn.quarter_pi.html)
-/// * [`root_half_pi`](fn.root_half_pi.html)
-/// * [`root_two_pi`](fn.root_two_pi.html)
-/// * [`three_over_two_pi`](fn.three_over_two_pi.html)
-/// * [`two_over_pi`](fn.two_over_pi.html)
-/// * [`two_over_root_pi`](fn.two_over_root_pi.html)
-/// * [`two_pi`](fn.two_pi.html)
+/// * [`four_over_pi()`]
+/// * [`half_pi()`]
+/// * [`one_over_pi()`]
+/// * [`one_over_two_pi()`]
+/// * [`pi()`](crate::pi)
+/// * [`quarter_pi()`]
+/// * [`root_half_pi()`]
+/// * [`root_two_pi()`]
+/// * [`three_over_two_pi()`]
+/// * [`two_over_pi()`]
+/// * [`two_over_root_pi()`]
+/// * [`two_pi()`]
 pub fn root_pi<T: RealNumber>() -> T {
     T::pi().sqrt()
 }
@@ -215,8 +214,8 @@ pub fn root_pi<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`root_five`](fn.root_five.html)
-/// * [`root_two`](fn.root_two.html)
+/// * [`root_five()`]
+/// * [`root_two()`]
 pub fn root_three<T: RealNumber>() -> T {
     na::convert::<_, T>(3.0).sqrt()
 }
@@ -225,8 +224,8 @@ pub fn root_three<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`root_five`](fn.root_five.html)
-/// * [`root_three`](fn.root_three.html)
+/// * [`root_five()`]
+/// * [`root_three()`]
 pub fn root_two<T: RealNumber>() -> T {
     // TODO: there should be a crate::sqrt_2() on the RealNumber trait.
     na::convert::<_, T>(2.0).sqrt()
@@ -236,18 +235,18 @@ pub fn root_two<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`four_over_pi`](fn.four_over_pi.html)
-/// * [`half_pi`](fn.half_pi.html)
-/// * [`one_over_pi`](fn.one_over_pi.html)
-/// * [`one_over_two_pi`](fn.one_over_two_pi.html)
-/// * [`pi`](fn.pi.html)
-/// * [`quarter_pi`](fn.quarter_pi.html)
-/// * [`root_half_pi`](fn.root_half_pi.html)
-/// * [`root_pi`](fn.root_pi.html)
-/// * [`three_over_two_pi`](fn.three_over_two_pi.html)
-/// * [`two_over_pi`](fn.two_over_pi.html)
-/// * [`two_over_root_pi`](fn.two_over_root_pi.html)
-/// * [`two_pi`](fn.two_pi.html)
+/// * [`four_over_pi()`]
+/// * [`half_pi()`]
+/// * [`one_over_pi()`]
+/// * [`one_over_two_pi()`]
+/// * [`pi()`](crate::pi)
+/// * [`quarter_pi()`]
+/// * [`root_half_pi()`]
+/// * [`root_pi()`]
+/// * [`three_over_two_pi()`]
+/// * [`two_over_pi()`]
+/// * [`two_over_root_pi()`]
+/// * [`two_pi()`]
 pub fn root_two_pi<T: RealNumber>() -> T {
     T::two_pi().sqrt()
 }
@@ -256,7 +255,7 @@ pub fn root_two_pi<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`two_thirds`](fn.two_thirds.html)
+/// * [`two_thirds()`]
 pub fn third<T: RealNumber>() -> T {
     na::convert(1.0 / 3.0)
 }
@@ -265,18 +264,18 @@ pub fn third<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`four_over_pi`](fn.four_over_pi.html)
-/// * [`half_pi`](fn.half_pi.html)
-/// * [`one_over_pi`](fn.one_over_pi.html)
-/// * [`one_over_two_pi`](fn.one_over_two_pi.html)
-/// * [`pi`](fn.pi.html)
-/// * [`quarter_pi`](fn.quarter_pi.html)
-/// * [`root_half_pi`](fn.root_half_pi.html)
-/// * [`root_pi`](fn.root_pi.html)
-/// * [`root_two_pi`](fn.root_two_pi.html)
-/// * [`two_over_pi`](fn.two_over_pi.html)
-/// * [`two_over_root_pi`](fn.two_over_root_pi.html)
-/// * [`two_pi`](fn.two_pi.html)
+/// * [`four_over_pi()`]
+/// * [`half_pi()`]
+/// * [`one_over_pi()`]
+/// * [`one_over_two_pi()`]
+/// * [`pi()`](crate::pi)
+/// * [`quarter_pi()`]
+/// * [`root_half_pi()`]
+/// * [`root_pi()`]
+/// * [`root_two_pi()`]
+/// * [`two_over_pi()`]
+/// * [`two_over_root_pi()`]
+/// * [`two_pi()`]
 pub fn three_over_two_pi<T: RealNumber>() -> T {
     na::convert::<_, T>(3.0) / T::two_pi()
 }
@@ -285,17 +284,18 @@ pub fn three_over_two_pi<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`four_over_pi`](fn.four_over_pi.html)
-/// * [`half_pi`](fn.half_pi.html)
-/// * [`one_over_pi`](fn.one_over_pi.html)
-/// * [`one_over_two_pi`](fn.one_over_two_pi.html)
-/// * [`quarter_pi`](fn.quarter_pi.html)
-/// * [`root_half_pi`](fn.root_half_pi.html)
-/// * [`root_pi`](fn.root_pi.html)
-/// * [`root_two_pi`](fn.root_two_pi.html)
-/// * [`three_over_two_pi`](fn.three_over_two_pi.html)
-/// * [`two_over_root_pi`](fn.two_over_root_pi.html)
-/// * [`two_pi`](fn.two_pi.html)
+/// * [`four_over_pi()`]
+/// * [`half_pi()`]
+/// * [`one_over_pi()`]
+/// * [`one_over_two_pi()`]
+/// * [`pi()`](crate::pi)
+/// * [`quarter_pi()`]
+/// * [`root_half_pi()`]
+/// * [`root_pi()`]
+/// * [`root_two_pi()`]
+/// * [`three_over_two_pi()`]
+/// * [`two_over_root_pi()`]
+/// * [`two_pi()`]
 pub fn two_over_pi<T: RealNumber>() -> T {
     T::frac_2_pi()
 }
@@ -304,18 +304,18 @@ pub fn two_over_pi<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`four_over_pi`](fn.four_over_pi.html)
-/// * [`half_pi`](fn.half_pi.html)
-/// * [`one_over_pi`](fn.one_over_pi.html)
-/// * [`one_over_two_pi`](fn.one_over_two_pi.html)
-/// * [`pi`](fn.pi.html)
-/// * [`quarter_pi`](fn.quarter_pi.html)
-/// * [`root_half_pi`](fn.root_half_pi.html)
-/// * [`root_pi`](fn.root_pi.html)
-/// * [`root_two_pi`](fn.root_two_pi.html)
-/// * [`three_over_two_pi`](fn.three_over_two_pi.html)
-/// * [`two_over_pi`](fn.two_over_pi.html)
-/// * [`two_pi`](fn.two_pi.html)
+/// * [`four_over_pi()`]
+/// * [`half_pi()`]
+/// * [`one_over_pi()`]
+/// * [`one_over_two_pi()`]
+/// * [`pi()`](crate::pi)
+/// * [`quarter_pi()`]
+/// * [`root_half_pi()`]
+/// * [`root_pi()`]
+/// * [`root_two_pi()`]
+/// * [`three_over_two_pi()`]
+/// * [`two_over_pi()`]
+/// * [`two_pi()`]
 pub fn two_over_root_pi<T: RealNumber>() -> T {
     T::frac_2_sqrt_pi()
 }
@@ -324,18 +324,18 @@ pub fn two_over_root_pi<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`four_over_pi`](fn.four_over_pi.html)
-/// * [`half_pi`](fn.half_pi.html)
-/// * [`one_over_pi`](fn.one_over_pi.html)
-/// * [`one_over_two_pi`](fn.one_over_two_pi.html)
-/// * [`pi`](fn.pi.html)
-/// * [`quarter_pi`](fn.quarter_pi.html)
-/// * [`root_half_pi`](fn.root_half_pi.html)
-/// * [`root_pi`](fn.root_pi.html)
-/// * [`root_two_pi`](fn.root_two_pi.html)
-/// * [`three_over_two_pi`](fn.three_over_two_pi.html)
-/// * [`two_over_pi`](fn.two_over_pi.html)
-/// * [`two_over_root_pi`](fn.two_over_root_pi.html)
+/// * [`four_over_pi()`]
+/// * [`half_pi()`]
+/// * [`one_over_pi()`]
+/// * [`one_over_two_pi()`]
+/// * [`pi()`](crate::pi)
+/// * [`quarter_pi()`]
+/// * [`root_half_pi()`]
+/// * [`root_pi()`]
+/// * [`root_two_pi()`]
+/// * [`three_over_two_pi()`]
+/// * [`two_over_pi()`]
+/// * [`two_over_root_pi()`]
 pub fn two_pi<T: RealNumber>() -> T {
     T::two_pi()
 }
@@ -344,7 +344,7 @@ pub fn two_pi<T: RealNumber>() -> T {
 ///
 /// # See also:
 ///
-/// * [`third`](fn.third.html)
+/// * [`third()`]
 pub fn two_thirds<T: RealNumber>() -> T {
     na::convert(2.0 / 3.0)
 }

nalgebra-glm/src/gtc/matrix_access.rs

@@ -6,9 +6,9 @@ use crate::aliases::{TMat, TVec};
 ///
 /// # See also:
 ///
-/// * [`row`](fn.row.html)
-/// * [`set_column`](fn.set_column.html)
-/// * [`set_row`](fn.set_row.html)
+/// * [`row()`]
+/// * [`set_column()`]
+/// * [`set_row()`]
 pub fn column<T: Scalar, const R: usize, const C: usize>(
     m: &TMat<T, R, C>,
     index: usize,
@@ -20,9 +20,9 @@ pub fn column<T: Scalar, const R: usize, const C: usize>(
 ///
 /// # See also:
 ///
-/// * [`column`](fn.column.html)
-/// * [`row`](fn.row.html)
-/// * [`set_row`](fn.set_row.html)
+/// * [`column()`]
+/// * [`row()`]
+/// * [`set_row()`]
 pub fn set_column<T: Scalar, const R: usize, const C: usize>(
     m: &TMat<T, R, C>,
     index: usize,
@@ -37,9 +37,9 @@ pub fn set_column<T: Scalar, const R: usize, const C: usize>(
 ///
 /// # See also:
 ///
-/// * [`column`](fn.column.html)
-/// * [`set_column`](fn.set_column.html)
-/// * [`set_row`](fn.set_row.html)
+/// * [`column()`]
+/// * [`set_column()`]
+/// * [`set_row()`]
 pub fn row<T: Scalar, const R: usize, const C: usize>(
     m: &TMat<T, R, C>,
     index: usize,
@@ -51,9 +51,9 @@ pub fn row<T: Scalar, const R: usize, const C: usize>(
 ///
 /// # See also:
 ///
-/// * [`column`](fn.column.html)
-/// * [`row`](fn.row.html)
-/// * [`set_column`](fn.set_column.html)
+/// * [`column()`]
+/// * [`row()`]
+/// * [`set_column()`]
 pub fn set_row<T: Scalar, const R: usize, const C: usize>(
     m: &TMat<T, R, C>,
     index: usize,

nalgebra-glm/src/gtc/type_ptr.rs

@@ -128,9 +128,9 @@ pub fn make_quat<T: RealNumber>(ptr: &[T]) -> Qua<T> {
 ///
 /// # See also:
 ///
-/// * [`make_vec2`](fn.make_vec2.html)
-/// * [`make_vec3`](fn.make_vec3.html)
-/// * [`make_vec4`](fn.make_vec4.html)
+/// * [`make_vec2()`]
+/// * [`make_vec3()`]
+/// * [`make_vec4()`]
 pub fn make_vec1<T: Scalar>(v: &TVec1<T>) -> TVec1<T> {
     v.clone()
 }
@@ -139,12 +139,11 @@ pub fn make_vec1<T: Scalar>(v: &TVec1<T>) -> TVec1<T> {
 ///
 /// # See also:
 ///
-/// * [`vec1_to_vec1`](fn.vec1_to_vec1.html)
-/// * [`vec3_to_vec1`](fn.vec3_to_vec1.html)
-/// * [`vec4_to_vec1`](fn.vec4_to_vec1.html)
-/// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
-/// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
-/// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
+/// * [`vec3_to_vec1()`]
+/// * [`vec4_to_vec1()`]
+/// * [`vec1_to_vec2()`]
+/// * [`vec1_to_vec3()`]
+/// * [`vec1_to_vec4()`]
 pub fn vec2_to_vec1<T: Scalar>(v: &TVec2<T>) -> TVec1<T> {
     TVec1::new(v.x.clone())
 }
@@ -153,12 +152,11 @@ pub fn vec2_to_vec1<T: Scalar>(v: &TVec2<T>) -> TVec1<T> {
 ///
 /// # See also:
 ///
-/// * [`vec1_to_vec1`](fn.vec1_to_vec1.html)
-/// * [`vec2_to_vec1`](fn.vec2_to_vec1.html)
-/// * [`vec4_to_vec1`](fn.vec4_to_vec1.html)
-/// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
-/// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
-/// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
+/// * [`vec2_to_vec1()`]
+/// * [`vec4_to_vec1()`]
+/// * [`vec1_to_vec2()`]
+/// * [`vec1_to_vec3()`]
+/// * [`vec1_to_vec4()`]
 pub fn vec3_to_vec1<T: Scalar>(v: &TVec3<T>) -> TVec1<T> {
     TVec1::new(v.x.clone())
 }
@@ -167,12 +165,11 @@ pub fn vec3_to_vec1<T: Scalar>(v: &TVec3<T>) -> TVec1<T> {
 ///
 /// # See also:
 ///
-/// * [`vec1_to_vec1`](fn.vec1_to_vec1.html)
-/// * [`vec2_to_vec1`](fn.vec2_to_vec1.html)
-/// * [`vec3_to_vec1`](fn.vec3_to_vec1.html)
-/// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
-/// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
-/// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
+/// * [`vec2_to_vec1()`]
+/// * [`vec3_to_vec1()`]
+/// * [`vec1_to_vec2()`]
+/// * [`vec1_to_vec3()`]
+/// * [`vec1_to_vec4()`]
 pub fn vec4_to_vec1<T: Scalar>(v: &TVec4<T>) -> TVec1<T> {
     TVec1::new(v.x.clone())
 }
@@ -183,12 +180,12 @@ pub fn vec4_to_vec1<T: Scalar>(v: &TVec4<T>) -> TVec1<T> {
 ///
 /// # See also:
 ///
-/// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
-/// * [`vec4_to_vec2`](fn.vec4_to_vec2.html)
-/// * [`vec2_to_vec1`](fn.vec2_to_vec1.html)
-/// * [`vec2_to_vec2`](fn.vec2_to_vec2.html)
-/// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
-/// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
+/// * [`vec3_to_vec2()`]
+/// * [`vec4_to_vec2()`]
+/// * [`vec2_to_vec1()`]
+/// * [`vec2_to_vec2()`]
+/// * [`vec2_to_vec3()`]
+/// * [`vec2_to_vec4()`]
 pub fn vec1_to_vec2<T: Number>(v: &TVec1<T>) -> TVec2<T> {
     TVec2::new(v.x.clone(), T::zero())
 }
@@ -197,13 +194,13 @@ pub fn vec1_to_vec2<T: Number>(v: &TVec1<T>) -> TVec2<T> {
 ///
 /// # See also:
 ///
-/// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
-/// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
-/// * [`vec4_to_vec2`](fn.vec4_to_vec2.html)
-/// * [`vec2_to_vec1`](fn.vec2_to_vec1.html)
-/// * [`vec2_to_vec2`](fn.vec2_to_vec2.html)
-/// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
-/// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
+/// * [`vec1_to_vec2()`]
+/// * [`vec3_to_vec2()`]
+/// * [`vec4_to_vec2()`]
+/// * [`vec2_to_vec1()`]
+/// * [`vec2_to_vec2()`]
+/// * [`vec2_to_vec3()`]
+/// * [`vec2_to_vec4()`]
 pub fn vec2_to_vec2<T: Scalar>(v: &TVec2<T>) -> TVec2<T> {
     v.clone()
 }
@@ -212,12 +209,12 @@ pub fn vec2_to_vec2<T: Scalar>(v: &TVec2<T>) -> TVec2<T> {
 ///
 /// # See also:
 ///
-/// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
-/// * [`vec4_to_vec2`](fn.vec4_to_vec2.html)
-/// * [`vec2_to_vec1`](fn.vec2_to_vec1.html)
-/// * [`vec2_to_vec2`](fn.vec2_to_vec2.html)
-/// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
-/// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
+/// * [`vec1_to_vec2()`]
+/// * [`vec4_to_vec2()`]
+/// * [`vec2_to_vec1()`]
+/// * [`vec2_to_vec2()`]
+/// * [`vec2_to_vec3()`]
+/// * [`vec2_to_vec4()`]
 pub fn vec3_to_vec2<T: Scalar>(v: &TVec3<T>) -> TVec2<T> {
     TVec2::new(v.x.clone(), v.y.clone())
 }
@@ -226,12 +223,12 @@ pub fn vec3_to_vec2<T: Scalar>(v: &TVec3<T>) -> TVec2<T> {
 ///
 /// # See also:
 ///
-/// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
-/// * [`vec3_to_vec2`](fn.vec4_to_vec2.html)
-/// * [`vec2_to_vec1`](fn.vec2_to_vec1.html)
-/// * [`vec2_to_vec2`](fn.vec2_to_vec2.html)
-/// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
-/// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
+/// * [`vec1_to_vec2()`]
+/// * [`vec3_to_vec2()`]
+/// * [`vec2_to_vec1()`]
+/// * [`vec2_to_vec2()`]
+/// * [`vec2_to_vec3()`]
+/// * [`vec2_to_vec4()`]
 pub fn vec4_to_vec2<T: Scalar>(v: &TVec4<T>) -> TVec2<T> {
     TVec2::new(v.x.clone(), v.y.clone())
 }
@@ -240,9 +237,9 @@ pub fn vec4_to_vec2<T: Scalar>(v: &TVec4<T>) -> TVec2<T> {
 ///
 /// # See also:
 ///
-/// * [`make_vec1`](fn.make_vec1.html)
-/// * [`make_vec3`](fn.make_vec3.html)
-/// * [`make_vec4`](fn.make_vec4.html)
+/// * [`make_vec1()`]
+/// * [`make_vec3()`]
+/// * [`make_vec4()`]
 pub fn make_vec2<T: Scalar>(ptr: &[T]) -> TVec2<T> {
     TVec2::from_column_slice(ptr)
 }
@@ -253,11 +250,11 @@ pub fn make_vec2<T: Scalar>(ptr: &[T]) -> TVec2<T> {
 ///
 /// # See also:
 ///
-/// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
-/// * [`vec3_to_vec3`](fn.vec3_to_vec3.html)
-/// * [`vec4_to_vec3`](fn.vec4_to_vec3.html)
-/// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
-/// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
+/// * [`vec2_to_vec3()`]
+/// * [`vec3_to_vec3()`]
+/// * [`vec4_to_vec3()`]
+/// * [`vec1_to_vec2()`]
+/// * [`vec1_to_vec4()`]
 pub fn vec1_to_vec3<T: Number>(v: &TVec1<T>) -> TVec3<T> {
     TVec3::new(v.x.clone(), T::zero(), T::zero())
 }
@@ -268,12 +265,12 @@ pub fn vec1_to_vec3<T: Number>(v: &TVec1<T>) -> TVec3<T> {
 ///
 /// # See also:
 ///
-/// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
-/// * [`vec3_to_vec3`](fn.vec3_to_vec3.html)
-/// * [`vec4_to_vec3`](fn.vec4_to_vec3.html)
-/// * [`vec3_to_vec1`](fn.vec3_to_vec1.html)
-/// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
-/// * [`vec3_to_vec4`](fn.vec3_to_vec4.html)
+/// * [`vec1_to_vec3()`]
+/// * [`vec3_to_vec3()`]
+/// * [`vec4_to_vec3()`]
+/// * [`vec3_to_vec1()`]
+/// * [`vec3_to_vec2()`]
+/// * [`vec3_to_vec4()`]
 pub fn vec2_to_vec3<T: Number>(v: &TVec2<T>) -> TVec3<T> {
     TVec3::new(v.x.clone(), v.y.clone(), T::zero())
 }
@@ -282,12 +279,12 @@ pub fn vec2_to_vec3<T: Number>(v: &TVec2<T>) -> TVec3<T> {
 ///
 /// # See also:
 ///
-/// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
-/// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
-/// * [`vec4_to_vec3`](fn.vec4_to_vec3.html)
-/// * [`vec3_to_vec1`](fn.vec3_to_vec1.html)
-/// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
-/// * [`vec3_to_vec4`](fn.vec3_to_vec4.html)
+/// * [`vec1_to_vec3()`]
+/// * [`vec2_to_vec3()`]
+/// * [`vec4_to_vec3()`]
+/// * [`vec3_to_vec1()`]
+/// * [`vec3_to_vec2()`]
+/// * [`vec3_to_vec4()`]
 pub fn vec3_to_vec3<T: Scalar>(v: &TVec3<T>) -> TVec3<T> {
     v.clone()
 }
@@ -296,12 +293,12 @@ pub fn vec3_to_vec3<T: Scalar>(v: &TVec3<T>) -> TVec3<T> {
 ///
 /// # See also:
 ///
-/// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
-/// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
-/// * [`vec3_to_vec3`](fn.vec3_to_vec3.html)
-/// * [`vec3_to_vec1`](fn.vec3_to_vec1.html)
-/// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
-/// * [`vec3_to_vec4`](fn.vec3_to_vec4.html)
+/// * [`vec1_to_vec3()`]
+/// * [`vec2_to_vec3()`]
+/// * [`vec3_to_vec3()`]
+/// * [`vec3_to_vec1()`]
+/// * [`vec3_to_vec2()`]
+/// * [`vec3_to_vec4()`]
 pub fn vec4_to_vec3<T: Scalar>(v: &TVec4<T>) -> TVec3<T> {
     TVec3::new(v.x.clone(), v.y.clone(), v.z.clone())
 }
@@ -310,9 +307,9 @@ pub fn vec4_to_vec3<T: Scalar>(v: &TVec4<T>) -> TVec3<T> {
 ///
 /// # See also:
 ///
-/// * [`make_vec1`](fn.make_vec1.html)
-/// * [`make_vec2`](fn.make_vec2.html)
-/// * [`make_vec4`](fn.make_vec4.html)
+/// * [`make_vec1()`]
+/// * [`make_vec2()`]
+/// * [`make_vec4()`]
 pub fn make_vec3<T: Scalar>(ptr: &[T]) -> TVec3<T> {
     TVec3::from_column_slice(ptr)
 }
@@ -323,12 +320,12 @@ pub fn make_vec3<T: Scalar>(ptr: &[T]) -> TVec3<T> {
 ///
 /// # See also:
 ///
-/// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
-/// * [`vec3_to_vec4`](fn.vec3_to_vec4.html)
-/// * [`vec4_to_vec4`](fn.vec4_to_vec4.html)
-/// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
-/// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
-/// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
+/// * [`vec2_to_vec4()`]
+/// * [`vec3_to_vec4()`]
+/// * [`vec4_to_vec4()`]
+/// * [`vec1_to_vec2()`]
+/// * [`vec1_to_vec3()`]
+/// * [`vec1_to_vec4()`]
 pub fn vec1_to_vec4<T: Number>(v: &TVec1<T>) -> TVec4<T> {
     TVec4::new(v.x, T::zero(), T::zero(), T::zero())
 }
@@ -339,12 +336,12 @@ pub fn vec1_to_vec4<T: Number>(v: &TVec1<T>) -> TVec4<T> {
 ///
 /// # See also:
 ///
-/// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
-/// * [`vec3_to_vec4`](fn.vec3_to_vec4.html)
-/// * [`vec4_to_vec4`](fn.vec4_to_vec4.html)
-/// * [`vec2_to_vec1`](fn.vec2_to_vec1.html)
-/// * [`vec2_to_vec2`](fn.vec2_to_vec2.html)
-/// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
+/// * [`vec1_to_vec4()`]
+/// * [`vec3_to_vec4()`]
+/// * [`vec4_to_vec4()`]
+/// * [`vec2_to_vec1()`]
+/// * [`vec2_to_vec2()`]
+/// * [`vec2_to_vec3()`]
 pub fn vec2_to_vec4<T: Number>(v: &TVec2<T>) -> TVec4<T> {
     TVec4::new(v.x, v.y, T::zero(), T::zero())
 }
@@ -355,12 +352,12 @@ pub fn vec2_to_vec4<T: Number>(v: &TVec2<T>) -> TVec4<T> {
 ///
 /// # See also:
 ///
-/// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
-/// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
-/// * [`vec4_to_vec4`](fn.vec4_to_vec4.html)
-/// * [`vec3_to_vec1`](fn.vec3_to_vec1.html)
-/// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
-/// * [`vec3_to_vec3`](fn.vec3_to_vec3.html)
+/// * [`vec1_to_vec4()`]
+/// * [`vec2_to_vec4()`]
+/// * [`vec4_to_vec4()`]
+/// * [`vec3_to_vec1()`]
+/// * [`vec3_to_vec2()`]
+/// * [`vec3_to_vec3()`]
 pub fn vec3_to_vec4<T: Number>(v: &TVec3<T>) -> TVec4<T> {
     TVec4::new(v.x, v.y, v.z, T::zero())
 }
@@ -369,12 +366,12 @@ pub fn vec3_to_vec4<T: Number>(v: &TVec3<T>) -> TVec4<T> {
 ///
 /// # See also:
 ///
-/// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
-/// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
-/// * [`vec3_to_vec4`](fn.vec3_to_vec4.html)
-/// * [`vec4_to_vec1`](fn.vec4_to_vec1.html)
-/// * [`vec4_to_vec2`](fn.vec4_to_vec2.html)
-/// * [`vec4_to_vec3`](fn.vec4_to_vec3.html)
+/// * [`vec1_to_vec4()`]
+/// * [`vec2_to_vec4()`]
+/// * [`vec3_to_vec4()`]
+/// * [`vec4_to_vec1()`]
+/// * [`vec4_to_vec2()`]
+/// * [`vec4_to_vec3()`]
 pub fn vec4_to_vec4<T: Scalar>(v: &TVec4<T>) -> TVec4<T> {
     v.clone()
 }
@@ -383,9 +380,9 @@ pub fn vec4_to_vec4<T: Scalar>(v: &TVec4<T>) -> TVec4<T> {
 ///
 /// # See also:
 ///
-/// * [`make_vec1`](fn.make_vec1.html)
-/// * [`make_vec2`](fn.make_vec2.html)
-/// * [`make_vec3`](fn.make_vec3.html)
+/// * [`make_vec1()`]
+/// * [`make_vec2()`]
+/// * [`make_vec3()`]
 pub fn make_vec4<T: Scalar>(ptr: &[T]) -> TVec4<T> {
     TVec4::from_column_slice(ptr)
 }

nalgebra-glm/src/gtx/component_wise.rs

@@ -16,9 +16,9 @@ use crate::traits::Number;
 ///
 /// # See also:
 ///
-/// * [`comp_max`](fn.comp_max.html)
-/// * [`comp_min`](fn.comp_min.html)
-/// * [`comp_mul`](fn.comp_mul.html)
+/// * [`comp_max()`]
+/// * [`comp_min()`]
+/// * [`comp_mul()`]
 pub fn comp_add<T: Number, const R: usize, const C: usize>(m: &TMat<T, R, C>) -> T {
     m.iter().fold(T::zero(), |x, y| x + *y)
 }
@@ -38,13 +38,13 @@ pub fn comp_add<T: Number, const R: usize, const C: usize>(m: &TMat<T, R, C>) ->
 ///
 /// # See also:
 ///
-/// * [`comp_add`](fn.comp_add.html)
-/// * [`comp_max`](fn.comp_max.html)
-/// * [`comp_min`](fn.comp_min.html)
-/// * [`max`](fn.max.html)
-/// * [`max2`](fn.max2.html)
-/// * [`max3`](fn.max3.html)
-/// * [`max4`](fn.max4.html)
+/// * [`comp_add()`]
+/// * [`comp_max()`]
+/// * [`comp_min()`]
+/// * [`max()`](crate::max)
+/// * [`max2()`](crate::max2)
+/// * [`max3()`](crate::max3)
+/// * [`max4()`](crate::max4)
 pub fn comp_max<T: Number, const R: usize, const C: usize>(m: &TMat<T, R, C>) -> T {
     m.iter()
         .fold(T::min_value(), |x, y| crate::max2_scalar(x, *y))
@@ -65,13 +65,13 @@ pub fn comp_max<T: Number, const R: usize, const C: usize>(m: &TMat<T, R, C>) ->
 ///
 /// # See also:
 ///
-/// * [`comp_add`](fn.comp_add.html)
-/// * [`comp_max`](fn.comp_max.html)
-/// * [`comp_mul`](fn.comp_mul.html)
-/// * [`min`](fn.min.html)
-/// * [`min2`](fn.min2.html)
-/// * [`min3`](fn.min3.html)
-/// * [`min4`](fn.min4.html)
+/// * [`comp_add()`]
+/// * [`comp_max()`]
+/// * [`comp_mul()`]
+/// * [`min()`](crate::min)
+/// * [`min2()`](crate::min2)
+/// * [`min3()`](crate::min3)
+/// * [`min4()`](crate::min4)
 pub fn comp_min<T: Number, const R: usize, const C: usize>(m: &TMat<T, R, C>) -> T {
     m.iter()
         .fold(T::max_value(), |x, y| crate::min2_scalar(x, *y))
@@ -92,9 +92,9 @@ pub fn comp_min<T: Number, const R: usize, const C: usize>(m: &TMat<T, R, C>) ->
 ///
 /// # See also:
 ///
-/// * [`comp_add`](fn.comp_add.html)
-/// * [`comp_max`](fn.comp_max.html)
-/// * [`comp_min`](fn.comp_min.html)
+/// * [`comp_add()`]
+/// * [`comp_max()`]
+/// * [`comp_min()`]
 pub fn comp_mul<T: Number, const R: usize, const C: usize>(m: &TMat<T, R, C>) -> T {
     m.iter().fold(T::one(), |x, y| x * *y)
 }

nalgebra-glm/src/gtx/handed_coordinate_space.rs

@@ -5,7 +5,7 @@ use crate::traits::Number;
 ///
 /// # See also:
 ///
-/// * [`right_handed`](fn.right_handed.html)
+/// * [`right_handed()`]
 pub fn left_handed<T: Number>(a: &TVec3<T>, b: &TVec3<T>, c: &TVec3<T>) -> bool {
     a.cross(b).dot(c) < T::zero()
 }
@@ -14,7 +14,7 @@ pub fn left_handed<T: Number>(a: &TVec3<T>, b: &TVec3<T>, c: &TVec3<T>) -> bool
 ///
 /// # See also:
 ///
-/// * [`left_handed`](fn.left_handed.html)
+/// * [`left_handed()`]
 pub fn right_handed<T: Number>(a: &TVec3<T>, b: &TVec3<T>, c: &TVec3<T>) -> bool {
     a.cross(b).dot(c) > T::zero()
 }

nalgebra-glm/src/gtx/matrix_cross_product.rs

@@ -5,7 +5,7 @@ use crate::RealNumber;
 ///
 /// # See also:
 ///
-/// * [`matrix_cross`](fn.matrix_cross.html)
+/// * [`matrix_cross()`]
 pub fn matrix_cross3<T: RealNumber>(x: &TVec3<T>) -> TMat3<T> {
     x.cross_matrix()
 }
@@ -14,7 +14,7 @@ pub fn matrix_cross3<T: RealNumber>(x: &TVec3<T>) -> TMat3<T> {
 ///
 /// # See also:
 ///
-/// * [`matrix_cross3`](fn.matrix_cross3.html)
+/// * [`matrix_cross3()`]
 pub fn matrix_cross<T: RealNumber>(x: &TVec3<T>) -> TMat4<T> {
     crate::mat3_to_mat4(&x.cross_matrix())
 }

nalgebra-glm/src/gtx/matrix_operation.rs

@@ -7,14 +7,14 @@ use crate::traits::Number;
 ///
 /// # See also:
 ///
-/// * [`diagonal2x3`](fn.diagonal2x3.html)
-/// * [`diagonal2x4`](fn.diagonal2x4.html)
-/// * [`diagonal3x2`](fn.diagonal3x2.html)
-/// * [`diagonal3x3`](fn.diagonal3x3.html)
-/// * [`diagonal3x4`](fn.diagonal3x4.html)
-/// * [`diagonal4x2`](fn.diagonal4x2.html)
-/// * [`diagonal4x3`](fn.diagonal4x3.html)
-/// * [`diagonal4x4`](fn.diagonal4x4.html)
+/// * [`diagonal2x3()`]
+/// * [`diagonal2x4()`]
+/// * [`diagonal3x2()`]
+/// * [`diagonal3x3()`]
+/// * [`diagonal3x4()`]
+/// * [`diagonal4x2()`]
+/// * [`diagonal4x3()`]
+/// * [`diagonal4x4()`]
 pub fn diagonal2x2<T: Number>(v: &TVec2<T>) -> TMat2<T> {
     TMat2::from_diagonal(v)
 }
@@ -23,14 +23,14 @@ pub fn diagonal2x2<T: Number>(v: &TVec2<T>) -> TMat2<T> {
 ///
 /// # See also:
 ///
-/// * [`diagonal2x2`](fn.diagonal2x2.html)
-/// * [`diagonal2x4`](fn.diagonal2x4.html)
-/// * [`diagonal3x2`](fn.diagonal3x2.html)
-/// * [`diagonal3x3`](fn.diagonal3x3.html)
-/// * [`diagonal3x4`](fn.diagonal3x4.html)
-/// * [`diagonal4x2`](fn.diagonal4x2.html)
-/// * [`diagonal4x3`](fn.diagonal4x3.html)
-/// * [`diagonal4x4`](fn.diagonal4x4.html)
+/// * [`diagonal2x2()`]
+/// * [`diagonal2x4()`]
+/// * [`diagonal3x2()`]
+/// * [`diagonal3x3()`]
+/// * [`diagonal3x4()`]
+/// * [`diagonal4x2()`]
+/// * [`diagonal4x3()`]
+/// * [`diagonal4x4()`]
 pub fn diagonal2x3<T: Number>(v: &TVec2<T>) -> TMat2x3<T> {
     TMat2x3::from_partial_diagonal(v.as_slice())
 }
@@ -39,14 +39,14 @@ pub fn diagonal2x3<T: Number>(v: &TVec2<T>) -> TMat2x3<T> {
 ///
 /// # See also:
 ///
-/// * [`diagonal2x2`](fn.diagonal2x2.html)
-/// * [`diagonal2x3`](fn.diagonal2x3.html)
-/// * [`diagonal3x2`](fn.diagonal3x2.html)
-/// * [`diagonal3x3`](fn.diagonal3x3.html)
-/// * [`diagonal3x4`](fn.diagonal3x4.html)
-/// * [`diagonal4x2`](fn.diagonal4x2.html)
-/// * [`diagonal4x3`](fn.diagonal4x3.html)
-/// * [`diagonal4x4`](fn.diagonal4x4.html)
+/// * [`diagonal2x2()`]
+/// * [`diagonal2x3()`]
+/// * [`diagonal3x2()`]
+/// * [`diagonal3x3()`]
+/// * [`diagonal3x4()`]
+/// * [`diagonal4x2()`]
+/// * [`diagonal4x3()`]
+/// * [`diagonal4x4()`]
 pub fn diagonal2x4<T: Number>(v: &TVec2<T>) -> TMat2x4<T> {
     TMat2x4::from_partial_diagonal(v.as_slice())
 }
@@ -55,14 +55,14 @@ pub fn diagonal2x4<T: Number>(v: &TVec2<T>) -> TMat2x4<T> {
 ///
 /// # See also:
 ///
-/// * [`diagonal2x2`](fn.diagonal2x2.html)
-/// * [`diagonal2x3`](fn.diagonal2x3.html)
-/// * [`diagonal2x4`](fn.diagonal2x4.html)
-/// * [`diagonal3x3`](fn.diagonal3x3.html)
-/// * [`diagonal3x4`](fn.diagonal3x4.html)
-/// * [`diagonal4x2`](fn.diagonal4x2.html)
-/// * [`diagonal4x3`](fn.diagonal4x3.html)
-/// * [`diagonal4x4`](fn.diagonal4x4.html)
+/// * [`diagonal2x2()`]
+/// * [`diagonal2x3()`]
+/// * [`diagonal2x4()`]
+/// * [`diagonal3x3()`]
+/// * [`diagonal3x4()`]
+/// * [`diagonal4x2()`]
+/// * [`diagonal4x3()`]
+/// * [`diagonal4x4()`]
 pub fn diagonal3x2<T: Number>(v: &TVec2<T>) -> TMat3x2<T> {
     TMat3x2::from_partial_diagonal(v.as_slice())
 }
@@ -71,14 +71,14 @@ pub fn diagonal3x2<T: Number>(v: &TVec2<T>) -> TMat3x2<T> {
 ///
 /// # See also:
 ///
-/// * [`diagonal2x2`](fn.diagonal2x2.html)
-/// * [`diagonal2x3`](fn.diagonal2x3.html)
-/// * [`diagonal2x4`](fn.diagonal2x4.html)
-/// * [`diagonal3x2`](fn.diagonal3x2.html)
-/// * [`diagonal3x4`](fn.diagonal3x4.html)
-/// * [`diagonal4x2`](fn.diagonal4x2.html)
-/// * [`diagonal4x3`](fn.diagonal4x3.html)
-/// * [`diagonal4x4`](fn.diagonal4x4.html)
+/// * [`diagonal2x2()`]
+/// * [`diagonal2x3()`]
+/// * [`diagonal2x4()`]
+/// * [`diagonal3x2()`]
+/// * [`diagonal3x4()`]
+/// * [`diagonal4x2()`]
+/// * [`diagonal4x3()`]
+/// * [`diagonal4x4()`]
 pub fn diagonal3x3<T: Number>(v: &TVec3<T>) -> TMat3<T> {
     TMat3::from_diagonal(v)
 }
@@ -87,14 +87,14 @@ pub fn diagonal3x3<T: Number>(v: &TVec3<T>) -> TMat3<T> {
 ///
 /// # See also:
 ///
-/// * [`diagonal2x2`](fn.diagonal2x2.html)
-/// * [`diagonal2x3`](fn.diagonal2x3.html)
-/// * [`diagonal2x4`](fn.diagonal2x4.html)
-/// * [`diagonal3x2`](fn.diagonal3x2.html)
-/// * [`diagonal3x3`](fn.diagonal3x3.html)
-/// * [`diagonal4x2`](fn.diagonal4x2.html)
-/// * [`diagonal4x3`](fn.diagonal4x3.html)
-/// * [`diagonal4x4`](fn.diagonal4x4.html)
+/// * [`diagonal2x2()`]
+/// * [`diagonal2x3()`]
+/// * [`diagonal2x4()`]
+/// * [`diagonal3x2()`]
+/// * [`diagonal3x3()`]
+/// * [`diagonal4x2()`]
+/// * [`diagonal4x3()`]
+/// * [`diagonal4x4()`]
 pub fn diagonal3x4<T: Number>(v: &TVec3<T>) -> TMat3x4<T> {
     TMat3x4::from_partial_diagonal(v.as_slice())
 }
@@ -103,14 +103,14 @@ pub fn diagonal3x4<T: Number>(v: &TVec3<T>) -> TMat3x4<T> {
 ///
 /// # See also:
 ///
-/// * [`diagonal2x2`](fn.diagonal2x2.html)
-/// * [`diagonal2x3`](fn.diagonal2x3.html)
-/// * [`diagonal2x4`](fn.diagonal2x4.html)
-/// * [`diagonal3x2`](fn.diagonal3x2.html)
-/// * [`diagonal3x3`](fn.diagonal3x3.html)
-/// * [`diagonal3x4`](fn.diagonal3x4.html)
-/// * [`diagonal4x3`](fn.diagonal4x3.html)
-/// * [`diagonal4x4`](fn.diagonal4x4.html)
+/// * [`diagonal2x2()`]
+/// * [`diagonal2x3()`]
+/// * [`diagonal2x4()`]
+/// * [`diagonal3x2()`]
+/// * [`diagonal3x3()`]
+/// * [`diagonal3x4()`]
+/// * [`diagonal4x3()`]
+/// * [`diagonal4x4()`]
 pub fn diagonal4x2<T: Number>(v: &TVec2<T>) -> TMat4x2<T> {
     TMat4x2::from_partial_diagonal(v.as_slice())
 }
@@ -119,14 +119,14 @@ pub fn diagonal4x2<T: Number>(v: &TVec2<T>) -> TMat4x2<T> {
 ///
 /// # See also:
 ///
-/// * [`diagonal2x2`](fn.diagonal2x2.html)
-/// * [`diagonal2x3`](fn.diagonal2x3.html)
-/// * [`diagonal2x4`](fn.diagonal2x4.html)
-/// * [`diagonal3x2`](fn.diagonal3x2.html)
-/// * [`diagonal3x3`](fn.diagonal3x3.html)
-/// * [`diagonal3x4`](fn.diagonal3x4.html)
-/// * [`diagonal4x2`](fn.diagonal4x2.html)
-/// * [`diagonal4x4`](fn.diagonal4x4.html)
+/// * [`diagonal2x2()`]
+/// * [`diagonal2x3()`]
+/// * [`diagonal2x4()`]
+/// * [`diagonal3x2()`]
+/// * [`diagonal3x3()`]
+/// * [`diagonal3x4()`]
+/// * [`diagonal4x2()`]
+/// * [`diagonal4x4()`]
 pub fn diagonal4x3<T: Number>(v: &TVec3<T>) -> TMat4x3<T> {
     TMat4x3::from_partial_diagonal(v.as_slice())
 }
@@ -135,14 +135,14 @@ pub fn diagonal4x3<T: Number>(v: &TVec3<T>) -> TMat4x3<T> {
 ///
 /// # See also:
 ///
-/// * [`diagonal2x2`](fn.diagonal2x2.html)
-/// * [`diagonal2x3`](fn.diagonal2x3.html)
-/// * [`diagonal2x4`](fn.diagonal2x4.html)
-/// * [`diagonal3x2`](fn.diagonal3x2.html)
-/// * [`diagonal3x3`](fn.diagonal3x3.html)
-/// * [`diagonal3x4`](fn.diagonal3x4.html)
-/// * [`diagonal4x2`](fn.diagonal4x2.html)
-/// * [`diagonal4x3`](fn.diagonal4x3.html)
+/// * [`diagonal2x2()`]
+/// * [`diagonal2x3()`]
+/// * [`diagonal2x4()`]
+/// * [`diagonal3x2()`]
+/// * [`diagonal3x3()`]
+/// * [`diagonal3x4()`]
+/// * [`diagonal4x2()`]
+/// * [`diagonal4x3()`]
 pub fn diagonal4x4<T: Number>(v: &TVec4<T>) -> TMat4<T> {
     TMat4::from_diagonal(v)
 }

nalgebra-glm/src/gtx/norm.rs

@@ -5,7 +5,7 @@ use crate::RealNumber;
 ///
 /// # See also:
 ///
-/// * [`distance`](fn.distance.html)
+/// * [`distance()`](crate::distance)
 pub fn distance2<T: RealNumber, const D: usize>(p0: &TVec<T, D>, p1: &TVec<T, D>) -> T {
     (p1 - p0).norm_squared()
 }
@@ -14,9 +14,9 @@ pub fn distance2<T: RealNumber, const D: usize>(p0: &TVec<T, D>, p1: &TVec<T, D>
 ///
 /// # See also:
 ///
-/// * [`l1_norm`](fn.l1_norm.html)
-/// * [`l2_distance`](fn.l2_distance.html)
-/// * [`l2_norm`](fn.l2_norm.html)
+/// * [`l1_norm()`]
+/// * [`l2_distance()`]
+/// * [`l2_norm()`]
 pub fn l1_distance<T: RealNumber, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
     l1_norm(&(y - x))
 }
@@ -28,27 +28,27 @@ pub fn l1_distance<T: RealNumber, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>
 ///
 /// # See also:
 ///
-/// * [`l1_distance`](fn.l1_distance.html)
-/// * [`l2_distance`](fn.l2_distance.html)
-/// * [`l2_norm`](fn.l2_norm.html)
+/// * [`l1_distance()`]
+/// * [`l2_distance()`]
+/// * [`l2_norm()`]
 pub fn l1_norm<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> T {
     crate::comp_add(&v.abs())
 }
 
 /// The l2-norm of `x - y`.
 ///
-/// This is the same value as returned by [`length2`](fn.length2.html) and
-/// [`magnitude2`](fn.magnitude2.html).
+/// This is the same value as returned by [`length2()`] and
+/// [`magnitude2()`].
 ///
 /// # See also:
 ///
-/// * [`l1_distance`](fn.l1_distance.html)
-/// * [`l1_norm`](fn.l1_norm.html)
-/// * [`l2_norm`](fn.l2_norm.html)
-/// * [`length`](fn.length.html)
-/// * [`length2`](fn.length2.html)
-/// * [`magnitude`](fn.magnitude.html)
-/// * [`magnitude2`](fn.magnitude2.html)
+/// * [`l1_distance()`]
+/// * [`l1_norm()`]
+/// * [`l2_norm()`]
+/// * [`length()`](crate::length)
+/// * [`length2()`]
+/// * [`magnitude()`](crate::magnitude)
+/// * [`magnitude2()`]
 pub fn l2_distance<T: RealNumber, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
     l2_norm(&(y - x))
 }
@@ -57,33 +57,33 @@ pub fn l2_distance<T: RealNumber, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>
 ///
 /// This is also known as the Euclidean norm.
 ///
-/// This is the same value as returned by [`length`](fn.length.html) and
-/// [`magnitude`](fn.magnitude.html).
+/// This is the same value as returned by [`length()`](crate::length) and
+/// [`magnitude()`](crate::magnitude).
 ///
 /// # See also:
 ///
-/// * [`l1_distance`](fn.l1_distance.html)
-/// * [`l1_norm`](fn.l1_norm.html)
-/// * [`l2_distance`](fn.l2_distance.html)
-/// * [`length`](fn.length.html)
-/// * [`length2`](fn.length2.html)
-/// * [`magnitude`](fn.magnitude.html)
-/// * [`magnitude2`](fn.magnitude2.html)
+/// * [`l1_distance()`]
+/// * [`l1_norm()`]
+/// * [`l2_distance()`]
+/// * [`length()`](crate::length)
+/// * [`length2()`]
+/// * [`magnitude()`](crate::magnitude)
+/// * [`magnitude2()`]
 pub fn l2_norm<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm()
 }
 
 /// The squared magnitude of `x`.
 ///
-/// A synonym for [`magnitude2`](fn.magnitude2.html).
+/// A synonym for [`magnitude2()`].
 ///
 /// # See also:
 ///
-/// * [`distance`](fn.distance.html)
-/// * [`distance2`](fn.distance2.html)
-/// * [`length`](fn.length.html)
-/// * [`magnitude`](fn.magnitude.html)
-/// * [`magnitude2`](fn.magnitude2.html)
+/// * [`distance()`](crate::distance)
+/// * [`distance2()`]
+/// * [`length()`](crate::length)
+/// * [`magnitude()`](crate::magnitude)
+/// * [`magnitude2()`]
 pub fn length2<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm_squared()
 }
@@ -94,10 +94,10 @@ pub fn length2<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> T {
 ///
 /// # See also:
 ///
-/// * [`distance`](fn.distance.html)
-/// * [`distance2`](fn.distance2.html)
-/// * [`length2`](fn.length2.html)
-/// * [`magnitude`](fn.magnitude.html)
+/// * [`distance()`](crate::distance)
+/// * [`distance2()`]
+/// * [`length2()`]
+/// * [`magnitude()`](crate::magnitude)
 /// * [`nalgebra::norm_squared`](../nalgebra/fn.norm_squared.html)
 pub fn magnitude2<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm_squared()

nalgebra-glm/src/gtx/normalize_dot.rs

@@ -4,11 +4,11 @@ use crate::aliases::TVec;
 
 /// The dot product of the normalized version of `x` and `y`.
 ///
-/// This is currently the same as [`normalize_dot`](fn.normalize_dot.html).
+/// This is currently the same as [`normalize_dot()`]
 ///
 /// # See also:
 ///
-/// * [`normalize_dot`](fn.normalize_dot.html`)
+/// * [`normalize_dot()`]
 pub fn fast_normalize_dot<T: RealNumber, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
     // XXX: improve those.
     x.normalize().dot(&y.normalize())
@@ -18,7 +18,7 @@ pub fn fast_normalize_dot<T: RealNumber, const D: usize>(x: &TVec<T, D>, y: &TVe
 ///
 /// # See also:
 ///
-/// * [`fast_normalize_dot`](fn.fast_normalize_dot.html`)
+/// * [`fast_normalize_dot()`]
 pub fn normalize_dot<T: RealNumber, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
     // XXX: improve those.
     x.normalize().dot(&y.normalize())

nalgebra-glm/src/gtx/transform.rs

@@ -7,11 +7,11 @@ use crate::traits::{Number, RealNumber};
 ///
 /// # See also:
 ///
-/// * [`scaling`](fn.scaling.html)
-/// * [`translation`](fn.translation.html)
-/// * [`rotation2d`](fn.rotation2d.html)
-/// * [`scaling2d`](fn.scaling2d.html)
-/// * [`translation2d`](fn.translation2d.html)
+/// * [`scaling()`]
+/// * [`translation()`]
+/// * [`rotation2d()`]
+/// * [`scaling2d()`]
+/// * [`translation2d()`]
 pub fn rotation<T: RealNumber>(angle: T, v: &TVec3<T>) -> TMat4<T> {
     Rotation3::from_axis_angle(&Unit::new_normalize(*v), angle).to_homogeneous()
 }
@@ -20,11 +20,11 @@ pub fn rotation<T: RealNumber>(angle: T, v: &TVec3<T>) -> TMat4<T> {
 ///
 /// # See also:
 ///
-/// * [`rotation`](fn.rotation.html)
-/// * [`translation`](fn.translation.html)
-/// * [`rotation2d`](fn.rotation2d.html)
-/// * [`scaling2d`](fn.scaling2d.html)
-/// * [`translation2d`](fn.translation2d.html)
+/// * [`rotation()`]
+/// * [`translation()`]
+/// * [`rotation2d()`]
+/// * [`scaling2d()`]
+/// * [`translation2d()`]
 pub fn scaling<T: Number>(v: &TVec3<T>) -> TMat4<T> {
     TMat4::new_nonuniform_scaling(v)
 }
@@ -33,11 +33,11 @@ pub fn scaling<T: Number>(v: &TVec3<T>) -> TMat4<T> {
 ///
 /// # See also:
 ///
-/// * [`rotation`](fn.rotation.html)
-/// * [`scaling`](fn.scaling.html)
-/// * [`rotation2d`](fn.rotation2d.html)
-/// * [`scaling2d`](fn.scaling2d.html)
-/// * [`translation2d`](fn.translation2d.html)
+/// * [`rotation()`]
+/// * [`scaling()`]
+/// * [`rotation2d()`]
+/// * [`scaling2d()`]
+/// * [`translation2d()`]
 pub fn translation<T: Number>(v: &TVec3<T>) -> TMat4<T> {
     TMat4::new_translation(v)
 }
@@ -46,11 +46,11 @@ pub fn translation<T: Number>(v: &TVec3<T>) -> TMat4<T> {
 ///
 /// # See also:
 ///
-/// * [`rotation`](fn.rotation.html)
-/// * [`scaling`](fn.scaling.html)
-/// * [`translation`](fn.translation.html)
-/// * [`scaling2d`](fn.scaling2d.html)
-/// * [`translation2d`](fn.translation2d.html)
+/// * [`rotation()`]
+/// * [`scaling()`]
+/// * [`translation()`]
+/// * [`scaling2d()`]
+/// * [`translation2d()`]
 pub fn rotation2d<T: RealNumber>(angle: T) -> TMat3<T> {
     Rotation2::new(angle).to_homogeneous()
 }
@@ -59,11 +59,11 @@ pub fn rotation2d<T: RealNumber>(angle: T) -> TMat3<T> {
 ///
 /// # See also:
 ///
-/// * [`rotation`](fn.rotation.html)
-/// * [`scaling`](fn.scaling.html)
-/// * [`translation`](fn.translation.html)
-/// * [`rotation2d`](fn.rotation2d.html)
-/// * [`translation2d`](fn.translation2d.html)
+/// * [`rotation()`]
+/// * [`scaling()`]
+/// * [`translation()`]
+/// * [`rotation2d()`]
+/// * [`translation2d()`]
 pub fn scaling2d<T: Number>(v: &TVec2<T>) -> TMat3<T> {
     TMat3::new_nonuniform_scaling(v)
 }
@@ -72,11 +72,11 @@ pub fn scaling2d<T: Number>(v: &TVec2<T>) -> TMat3<T> {
 ///
 /// # See also:
 ///
-/// * [`rotation`](fn.rotation.html)
-/// * [`scaling`](fn.scaling.html)
-/// * [`translation`](fn.translation.html)
-/// * [`rotation2d`](fn.rotation2d.html)
-/// * [`scaling2d`](fn.scaling2d.html)
+/// * [`rotation()`]
+/// * [`scaling()`]
+/// * [`translation()`]
+/// * [`rotation2d()`]
+/// * [`scaling2d()`]
 pub fn translation2d<T: Number>(v: &TVec2<T>) -> TMat3<T> {
     TMat3::new_translation(v)
 }

nalgebra-glm/src/gtx/transform2d.rs

@@ -7,11 +7,11 @@ use crate::traits::{Number, RealNumber};
 ///
 /// # See also:
 ///
-/// * [`rotation2d`](fn.rotation2d.html)
-/// * [`scale2d`](fn.scale2d.html)
-/// * [`scaling2d`](fn.scaling2d.html)
-/// * [`translate2d`](fn.translate2d.html)
-/// * [`translation2d`](fn.translation2d.html)
+/// * [`rotation2d()`](crate::rotation2d)
+/// * [`scale2d()`]
+/// * [`scaling2d()`](crate::scaling2d)
+/// * [`translate2d()`]
+/// * [`translation2d()`](crate::translation2d)
 pub fn rotate2d<T: RealNumber>(m: &TMat3<T>, angle: T) -> TMat3<T> {
     m * UnitComplex::new(angle).to_homogeneous()
 }
@@ -20,11 +20,11 @@ pub fn rotate2d<T: RealNumber>(m: &TMat3<T>, angle: T) -> TMat3<T> {
 ///
 /// # See also:
 ///
-/// * [`rotate2d`](fn.rotate2d.html)
-/// * [`rotation2d`](fn.rotation2d.html)
-/// * [`scaling2d`](fn.scaling2d.html)
-/// * [`translate2d`](fn.translate2d.html)
-/// * [`translation2d`](fn.translation2d.html)
+/// * [`rotate2d()`]
+/// * [`rotation2d()`](crate::rotation2d)
+/// * [`scaling2d()`](crate::scaling2d)
+/// * [`translate2d()`]
+/// * [`translation2d()`](crate::translation2d)
 pub fn scale2d<T: Number>(m: &TMat3<T>, v: &TVec2<T>) -> TMat3<T> {
     m.prepend_nonuniform_scaling(v)
 }
@@ -33,11 +33,11 @@ pub fn scale2d<T: Number>(m: &TMat3<T>, v: &TVec2<T>) -> TMat3<T> {
 ///
 /// # See also:
 ///
-/// * [`rotate2d`](fn.rotate2d.html)
-/// * [`rotation2d`](fn.rotation2d.html)
-/// * [`scale2d`](fn.scale2d.html)
-/// * [`scaling2d`](fn.scaling2d.html)
-/// * [`translation2d`](fn.translation2d.html)
+/// * [`rotate2d()`]
+/// * [`rotation2d()`](crate::rotation2d)
+/// * [`scale2d()`]
+/// * [`scaling2d()`](crate::scaling2d)
+/// * [`translation2d()`](crate::translation2d)
 pub fn translate2d<T: Number>(m: &TMat3<T>, v: &TVec2<T>) -> TMat3<T> {
     m.prepend_translation(v)
 }

nalgebra-glm/src/gtx/vector_query.rs

@@ -7,16 +7,16 @@ use crate::traits::Number;
 ///
 /// # See also:
 ///
-/// * [`are_collinear2d`](fn.are_collinear2d.html)
+/// * [`are_collinear2d()`]
 pub fn are_collinear<T: Number>(v0: &TVec3<T>, v1: &TVec3<T>, epsilon: T) -> bool {
-    is_null(&v0.cross(v1), epsilon)
+    abs_diff_eq!(v0.cross(v1), TVec3::<T>::zeros(), epsilon = epsilon)
 }
 
 /// Returns `true` if two 2D vectors are collinear (up to an epsilon).
 ///
 /// # See also:
 ///
-/// * [`are_collinear`](fn.are_collinear.html)
+/// * [`are_collinear()`]
 pub fn are_collinear2d<T: Number>(v0: &TVec2<T>, v1: &TVec2<T>, epsilon: T) -> bool {
     abs_diff_eq!(v0.perp(v1), T::zero(), epsilon = epsilon)
 }
@@ -41,10 +41,13 @@ pub fn is_comp_null<T: Number, const D: usize>(v: &TVec<T, D>, epsilon: T) -> TV
 
 /// Returns `true` if `v` has a magnitude of 1 (up to an epsilon).
 pub fn is_normalized<T: RealNumber, const D: usize>(v: &TVec<T, D>, epsilon: T) -> bool {
-    abs_diff_eq!(v.norm_squared(), T::one(), epsilon = epsilon * epsilon)
+    // sqrt(1 + epsilon_{norm²} = 1 + epsilon_{norm}
+    // ==> epsilon_{norm²} = epsilon_{norm}² + 2*epsilon_{norm}
+    // For small epsilon, epsilon² is basically zero, so use 2*epsilon.
+    abs_diff_eq!(v.norm_squared(), T::one(), epsilon = epsilon + epsilon)
 }
 
 /// Returns `true` if `v` is zero (up to an epsilon).
-pub fn is_null<T: Number, const D: usize>(v: &TVec<T, D>, epsilon: T) -> bool {
-    abs_diff_eq!(*v, TVec::<T, D>::zeros(), epsilon = epsilon)
+pub fn is_null<T: RealNumber, const D: usize>(v: &TVec<T, D>, epsilon: T) -> bool {
+    abs_diff_eq!(v.norm_squared(), T::zero(), epsilon = epsilon * epsilon)
 }

nalgebra-glm/src/lib.rs

@@ -38,7 +38,7 @@
    * All function names use `snake_case`, which is the Rust convention.
    * All type names use `CamelCase`, which is the Rust convention.
    * All function arguments, except for scalars, are all passed by-reference.
-   * The most generic vector and matrix types are [`TMat`](type.TMat.html) and [`TVec`](type.TVec.html) instead of `mat` and `vec`.
+   * The most generic vector and matrix types are [`TMat`] and [`TVec`] instead of `mat` and `vec`.
    * Some feature are not yet implemented and should be added in the future. In particular, no packing
    functions are available.
    * A few features are not implemented and will never be. This includes functions related to color
@@ -47,17 +47,17 @@
 
    In addition, because Rust does not allows function overloading, all functions must be given a unique name.
    Here are a few rules chosen arbitrarily for **nalgebra-glm**:
-   * Functions operating in 2d will usually end with the `2d` suffix, e.g., [`glm::rotate2d`](fn.rotate2d.html) is for 2D while [`glm::rotate`](fn.rotate.html) is for 3D.
-   * Functions operating on vectors will often end with the `_vec` suffix, possibly followed by the dimension of vector, e.g., [`glm::rotate_vec2`](fn.rotate_vec2.html).
-   * Every function related to quaternions start with the `quat_` prefix, e.g., [`glm::quat_dot(q1, q2)`](fn.quat_dot.html).
+   * Functions operating in 2d will usually end with the `2d` suffix, e.g., [`glm::rotate2d()`](crate::rotate2d) is for 2D while [`glm::rotate()`](crate::rotate) is for 3D.
+   * Functions operating on vectors will often end with the `_vec` suffix, possibly followed by the dimension of vector, e.g., [`glm::rotate_vec2()`](crate::rotate_vec2).
+   * Every function related to quaternions start with the `quat_` prefix, e.g., [`glm::quat_dot(q1, q2)`](crate::quat_dot).
    * All the conversion functions have unique names as described [below](#conversions).
    ### Vector and matrix construction
    Vectors, matrices, and quaternions can be constructed using several approaches:
-   * Using functions with the same name as their type in lower-case. For example [`glm::vec3(x, y, z)`](fn.vec3.html) will create a 3D vector.
+   * Using functions with the same name as their type in lower-case. For example [`glm::vec3(x, y, z)`](crate::vec3) will create a 3D vector.
    * Using the `::new` constructor. For example [`Vec3::new(x, y, z)`](../nalgebra/base/type.OMatrix.html#method.new-27) will create a 3D vector.
-   * Using the functions prefixed by `make_` to build a vector a matrix from a slice. For example [`glm::make_vec3(&[x, y, z])`](fn.make_vec3.html) will create a 3D vector.
+   * Using the functions prefixed by `make_` to build a vector a matrix from a slice. For example [`glm::make_vec3(&[x, y, z])`](crate::make_vec3) will create a 3D vector.
    Keep in mind that constructing a matrix using this type of functions require its components to be arranged in column-major order on the slice.
-   * Using a geometric construction function. For example [`glm::rotation(angle, axis)`](fn.rotation.html) will build a 4x4 homogeneous rotation matrix from an angle (in radians) and an axis.
+   * Using a geometric construction function. For example [`glm::rotation(angle, axis)`](crate::rotation) will build a 4x4 homogeneous rotation matrix from an angle (in radians) and an axis.
    * Using swizzling and conversions as described in the next sections.
    ### Swizzling
    Vector swizzling is a native feature of **nalgebra** itself. Therefore, you can use it with all
@@ -75,9 +75,9 @@
    It is often useful to convert one algebraic type to another. There are two main approaches for converting
    between types in `nalgebra-glm`:
    * Using function with the form `type1_to_type2` in order to convert an instance of `type1` into an instance of `type2`.
-   For example [`glm::mat3_to_mat4(m)`](fn.mat3_to_mat4.html) will convert the 3x3 matrix `m` to a 4x4 matrix by appending one column on the right
+   For example [`glm::mat3_to_mat4(m)`](crate::mat3_to_mat4) will convert the 3x3 matrix `m` to a 4x4 matrix by appending one column on the right
    and one row on the left. Those now row and columns are filled with 0 except for the diagonal element which is set to 1.
-   * Using one of the [`convert`](fn.convert.html), [`try_convert`](fn.try_convert.html), or [`convert_unchecked`](fn.convert_unchecked.html) functions.
+   * Using one of the [`convert`](crate::convert), [`try_convert`](crate::try_convert), or [`convert_unchecked`](crate::convert_unchecked) functions.
    These functions are directly re-exported from nalgebra and are extremely versatile:
        1. The `convert` function can convert any type (especially geometric types from nalgebra like `Isometry3`) into another algebraic type which is equivalent but more general. For example,
    `let sim: Similarity3<_> = na::convert(isometry)` will convert an `Isometry3` into a `Similarity3`.

nalgebra-glm/src/traits.rs

@@ -1,18 +1,17 @@
 use approx::AbsDiffEq;
 use num::{Bounded, Signed};
 
-use core::cmp::PartialOrd;
 use na::Scalar;
-use simba::scalar::{ClosedAdd, ClosedMul, ClosedSub, RealField};
+use simba::scalar::{ClosedAddAssign, ClosedMulAssign, ClosedSubAssign, RealField};
 
 /// A number that can either be an integer or a float.
 pub trait Number:
     Scalar
     + Copy
     + PartialOrd
-    + ClosedAdd
-    + ClosedSub
-    + ClosedMul
+    + ClosedAddAssign
+    + ClosedSubAssign
+    + ClosedMulAssign
     + AbsDiffEq<Epsilon = Self>
     + Signed
     + Bounded
@@ -23,9 +22,9 @@ impl<
         T: Scalar
             + Copy
             + PartialOrd
-            + ClosedAdd
-            + ClosedSub
-            + ClosedMul
+            + ClosedAddAssign
+            + ClosedSubAssign
+            + ClosedMulAssign
             + AbsDiffEq<Epsilon = Self>
             + Signed
             + Bounded,

nalgebra-glm/src/trigonometric.rs

@@ -1,5 +1,3 @@
-use na;
-
 use crate::aliases::TVec;
 use crate::RealNumber;
 

nalgebra-glm/src/vector_relational.rs

@@ -16,8 +16,8 @@ use crate::traits::Number;
 ///
 /// # See also:
 ///
-/// * [`any`](fn.any.html)
-/// * [`not`](fn.not.html)
+/// * [`any()`]
+/// * [`not()`]
 pub fn all<const D: usize>(v: &TVec<bool, D>) -> bool {
     v.iter().all(|x| *x)
 }
@@ -40,8 +40,8 @@ pub fn all<const D: usize>(v: &TVec<bool, D>) -> bool {
 ///
 /// # See also:
 ///
-/// * [`all`](fn.all.html)
-/// * [`not`](fn.not.html)
+/// * [`all()`]
+/// * [`not()`]
 pub fn any<const D: usize>(v: &TVec<bool, D>) -> bool {
     v.iter().any(|x| *x)
 }
@@ -59,12 +59,12 @@ pub fn any<const D: usize>(v: &TVec<bool, D>) -> bool {
 ///
 /// # See also:
 ///
-/// * [`greater_than`](fn.greater_than.html)
-/// * [`greater_than_equal`](fn.greater_than_equal.html)
-/// * [`less_than`](fn.less_than.html)
-/// * [`less_than_equal`](fn.less_than_equal.html)
-/// * [`not`](fn.not.html)
-/// * [`not_equal`](fn.not_equal.html)
+/// * [`greater_than()`]
+/// * [`greater_than_equal()`]
+/// * [`less_than()`]
+/// * [`less_than_equal()`]
+/// * [`not()`]
+/// * [`not_equal()`]
 pub fn equal<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<bool, D> {
     x.zip_map(y, |x, y| x == y)
 }
@@ -82,12 +82,12 @@ pub fn equal<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<
 ///
 /// # See also:
 ///
-/// * [`equal`](fn.equal.html)
-/// * [`greater_than_equal`](fn.greater_than_equal.html)
-/// * [`less_than`](fn.less_than.html)
-/// * [`less_than_equal`](fn.less_than_equal.html)
-/// * [`not`](fn.not.html)
-/// * [`not_equal`](fn.not_equal.html)
+/// * [`equal()`]
+/// * [`greater_than_equal()`]
+/// * [`less_than()`]
+/// * [`less_than_equal()`]
+/// * [`not()`]
+/// * [`not_equal()`]
 pub fn greater_than<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<bool, D> {
     x.zip_map(y, |x, y| x > y)
 }
@@ -105,12 +105,12 @@ pub fn greater_than<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -
 ///
 /// # See also:
 ///
-/// * [`equal`](fn.equal.html)
-/// * [`greater_than`](fn.greater_than.html)
-/// * [`less_than`](fn.less_than.html)
-/// * [`less_than_equal`](fn.less_than_equal.html)
-/// * [`not`](fn.not.html)
-/// * [`not_equal`](fn.not_equal.html)
+/// * [`equal()`]
+/// * [`greater_than()`]
+/// * [`less_than()`]
+/// * [`less_than_equal()`]
+/// * [`not()`]
+/// * [`not_equal()`]
 pub fn greater_than_equal<T: Number, const D: usize>(
     x: &TVec<T, D>,
     y: &TVec<T, D>,
@@ -131,17 +131,17 @@ pub fn greater_than_equal<T: Number, const D: usize>(
 ///
 /// # See also:
 ///
-/// * [`equal`](fn.equal.html)
-/// * [`greater_than`](fn.greater_than.html)
-/// * [`greater_than_equal`](fn.greater_than_equal.html)
-/// * [`less_than_equal`](fn.less_than_equal.html)
-/// * [`not`](fn.not.html)
-/// * [`not_equal`](fn.not_equal.html)
+/// * [`equal()`]
+/// * [`greater_than()`]
+/// * [`greater_than_equal()`]
+/// * [`less_than_equal()`]
+/// * [`not()`]
+/// * [`not_equal()`]
 pub fn less_than<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<bool, D> {
     x.zip_map(y, |x, y| x < y)
 }
 
-/// Component-wise `>=` comparison.
+/// Component-wise `<=` comparison.
 ///
 /// # Examples:
 ///
@@ -154,12 +154,12 @@ pub fn less_than<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T
 ///
 /// # See also:
 ///
-/// * [`equal`](fn.equal.html)
-/// * [`greater_than`](fn.greater_than.html)
-/// * [`greater_than_equal`](fn.greater_than_equal.html)
-/// * [`less_than`](fn.less_than.html)
-/// * [`not`](fn.not.html)
-/// * [`not_equal`](fn.not_equal.html)
+/// * [`equal()`]
+/// * [`greater_than()`]
+/// * [`greater_than_equal()`]
+/// * [`less_than()`]
+/// * [`not()`]
+/// * [`not_equal()`]
 pub fn less_than_equal<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<bool, D> {
     x.zip_map(y, |x, y| x <= y)
 }
@@ -176,14 +176,14 @@ pub fn less_than_equal<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>
 ///
 /// # See also:
 ///
-/// * [`all`](fn.all.html)
-/// * [`any`](fn.any.html)
-/// * [`equal`](fn.equal.html)
-/// * [`greater_than`](fn.greater_than.html)
-/// * [`greater_than_equal`](fn.greater_than_equal.html)
-/// * [`less_than`](fn.less_than.html)
-/// * [`less_than_equal`](fn.less_than_equal.html)
-/// * [`not_equal`](fn.not_equal.html)
+/// * [`all()`]
+/// * [`any()`]
+/// * [`equal()`]
+/// * [`greater_than()`]
+/// * [`greater_than_equal()`]
+/// * [`less_than()`]
+/// * [`less_than_equal()`]
+/// * [`not_equal()`]
 pub fn not<const D: usize>(v: &TVec<bool, D>) -> TVec<bool, D> {
     v.map(|x| !x)
 }
@@ -201,12 +201,12 @@ pub fn not<const D: usize>(v: &TVec<bool, D>) -> TVec<bool, D> {
 ///
 /// # See also:
 ///
-/// * [`equal`](fn.equal.html)
-/// * [`greater_than`](fn.greater_than.html)
-/// * [`greater_than_equal`](fn.greater_than_equal.html)
-/// * [`less_than`](fn.less_than.html)
-/// * [`less_than_equal`](fn.less_than_equal.html)
-/// * [`not`](fn.not.html)
+/// * [`equal()`]
+/// * [`greater_than()`]
+/// * [`greater_than_equal()`]
+/// * [`less_than()`]
+/// * [`less_than_equal()`]
+/// * [`not()`]
 pub fn not_equal<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<bool, D> {
     x.zip_map(y, |x, y| x != y)
 }

nalgebra-lapack/Cargo.toml

@@ -1,47 +1,47 @@
 [package]
-name    = "nalgebra-lapack"
-version = "0.24.0"
-authors = [ "Sébastien Crozet <developer@crozet.re>", "Andrew Straw <strawman@astraw.com>" ]
+name = "nalgebra-lapack"
+version = "0.25.0"
+authors = ["Sébastien Crozet <developer@crozet.re>", "Andrew Straw <strawman@astraw.com>"]
 
-description   = "Matrix decompositions using nalgebra matrices and Lapack bindings."
+description = "Matrix decompositions using nalgebra matrices and Lapack bindings."
 documentation = "https://www.nalgebra.org/docs"
 homepage = "https://nalgebra.org"
 repository = "https://github.com/dimforge/nalgebra"
 readme = "../README.md"
-categories = [ "science", "mathematics" ]
-keywords = [ "linear", "algebra", "matrix", "vector", "lapack" ]
-license = "BSD-3-Clause"
+categories = ["science", "mathematics"]
+keywords = ["linear", "algebra", "matrix", "vector", "lapack"]
+license = "MIT"
 edition = "2018"
 
 [badges]
 maintenance = { status = "actively-developed" }
 
 [features]
-serde-serialize  = [ "serde", "nalgebra/serde-serialize" ]
-proptest-support = [ "nalgebra/proptest-support" ]
-arbitrary        = [ "nalgebra/arbitrary" ]
+serde-serialize = ["serde", "nalgebra/serde-serialize"]
+proptest-support = ["nalgebra/proptest-support"]
+arbitrary = ["nalgebra/arbitrary"]
 
 # For BLAS/LAPACK
-default    = ["netlib"]
-openblas   = ["lapack-src/openblas"]
-netlib     = ["lapack-src/netlib"]
+default = ["netlib"]
+openblas = ["lapack-src/openblas"]
+netlib = ["lapack-src/netlib"]
 accelerate = ["lapack-src/accelerate"]
-intel-mkl  = ["lapack-src/intel-mkl"]
+intel-mkl = ["lapack-src/intel-mkl"]
 
 [dependencies]
-nalgebra      = { version = "0.32", path = ".." }
-num-traits    = "0.2"
-num-complex   = { version = "0.4", default-features = false }
-simba         = "0.8"
-serde         = { version = "1.0", features = [ "derive" ], optional = true }
-lapack        = { version = "0.19", default-features = false }
-lapack-src    = { version = "0.8", default-features = false }
+nalgebra = { version = "0.33", path = ".." }
+num-traits = "0.2"
+num-complex = { version = "0.4", default-features = false }
+simba = "0.9"
+serde = { version = "1.0", features = ["derive"], optional = true }
+lapack = { version = "0.19", default-features = false }
+lapack-src = { version = "0.8", default-features = false }
 # clippy = "*"
 
 [dev-dependencies]
-nalgebra   = { version = "0.32", features = [ "arbitrary", "rand" ], path = ".." }
-proptest   = { version = "1", default-features = false, features = ["std"] }
+nalgebra = { version = "0.33", features = ["arbitrary", "rand"], path = ".." }
+proptest = { version = "1", default-features = false, features = ["std"] }
 quickcheck = "1"
-approx     = "0.5"
-rand       = "0.8"
+approx = "0.5"
+rand = "0.8"
 

nalgebra-lapack/src/cholesky.rs

@@ -15,32 +15,32 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<T, D>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<D>,
          OMatrix<T, D, D>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(deserialize = "DefaultAllocator: Allocator<T, D>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<D>,
          OMatrix<T, D, D>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
 pub struct Cholesky<T: Scalar, D: Dim>
 where
-    DefaultAllocator: Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D, D>,
 {
     l: OMatrix<T, D, D>,
 }
 
 impl<T: Scalar + Copy, D: Dim> Copy for Cholesky<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D, D>,
     OMatrix<T, D, D>: Copy,
 {
 }
 
 impl<T: CholeskyScalar + Zero, D: Dim> Cholesky<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D, D>,
 {
     /// Computes the cholesky decomposition of the given symmetric-definite-positive square
     /// matrix.
@@ -105,7 +105,7 @@ where
     ) -> Option<OMatrix<T, R2, C2>>
     where
         S2: Storage<T, R2, C2>,
-        DefaultAllocator: Allocator<T, R2, C2>,
+        DefaultAllocator: Allocator<R2, C2>,
     {
         let mut res = b.clone_owned();
         if self.solve_mut(&mut res) {
@@ -119,7 +119,7 @@ where
     /// the unknown to be determined.
     pub fn solve_mut<R2: Dim, C2: Dim>(&self, b: &mut OMatrix<T, R2, C2>) -> bool
     where
-        DefaultAllocator: Allocator<T, R2, C2>,
+        DefaultAllocator: Allocator<R2, C2>,
     {
         let dim = self.l.nrows();
 

nalgebra-lapack/src/eigen.rs

@@ -16,24 +16,20 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(serialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<D, D> + Allocator<D>,
          OVector<T, D>: Serialize,
-         OMatrix<T, D, D>: Serialize")
-    )
+         OMatrix<T, D, D>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(deserialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<D, D> + Allocator<D>,
          OVector<T, D>: Serialize,
-         OMatrix<T, D, D>: Deserialize<'de>")
-    )
+         OMatrix<T, D, D>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
 pub struct Eigen<T: Scalar, D: Dim>
 where
-    DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D> + Allocator<D, D>,
 {
     /// The real parts of eigenvalues of the decomposed matrix.
     pub eigenvalues_re: OVector<T, D>,
@@ -47,7 +43,7 @@ where
 
 impl<T: Scalar + Copy, D: Dim> Copy for Eigen<T, D>
 where
-    DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D> + Allocator<D, D>,
     OVector<T, D>: Copy,
     OMatrix<T, D, D>: Copy,
 {
@@ -55,7 +51,7 @@ where
 
 impl<T: EigenScalar + RealField, D: Dim> Eigen<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    DefaultAllocator: Allocator<D, D> + Allocator<D>,
 {
     /// Computes the eigenvalues and eigenvectors of the square matrix `m`.
     ///
@@ -177,7 +173,7 @@ where
         Option<Vec<OVector<T, D>>>,
     )
     where
-        DefaultAllocator: Allocator<T, D>,
+        DefaultAllocator: Allocator<D>,
     {
         let (number_of_elements, _) = self.eigenvalues_re.shape_generic();
         let number_of_elements_value = number_of_elements.value();
@@ -200,17 +196,16 @@ where
             eigenvalues.push(self.eigenvalues_re[c].clone());
 
             if eigenvectors.is_some() {
-                eigenvectors.as_mut().unwrap().push(
-                    (&self.eigenvectors.as_ref())
-                        .unwrap()
-                        .column(c)
-                        .into_owned(),
-                );
+                eigenvectors
+                    .as_mut()
+                    .unwrap()
+                    .push(self.eigenvectors.as_ref().unwrap().column(c).into_owned());
             }
 
             if left_eigenvectors.is_some() {
                 left_eigenvectors.as_mut().unwrap().push(
-                    (&self.left_eigenvectors.as_ref())
+                    self.left_eigenvectors
+                        .as_ref()
                         .unwrap()
                         .column(c)
                         .into_owned(),
@@ -235,7 +230,7 @@ where
         Option<Vec<OVector<Complex<T>, D>>>,
     )
     where
-        DefaultAllocator: Allocator<Complex<T>, D>,
+        DefaultAllocator: Allocator<D>,
     {
         match self.eigenvalues_are_real() {
             true => (None, None, None),
@@ -285,12 +280,12 @@ where
 
                             for r in 0..number_of_elements_value {
                                 vec[r] = Complex::<T>::new(
-                                    (&self.eigenvectors.as_ref()).unwrap()[(r, c)].clone(),
-                                    (&self.eigenvectors.as_ref()).unwrap()[(r, c + 1)].clone(),
+                                    self.eigenvectors.as_ref().unwrap()[(r, c)].clone(),
+                                    self.eigenvectors.as_ref().unwrap()[(r, c + 1)].clone(),
                                 );
                                 vec_conj[r] = Complex::<T>::new(
-                                    (&self.eigenvectors.as_ref()).unwrap()[(r, c)].clone(),
-                                    (&self.eigenvectors.as_ref()).unwrap()[(r, c + 1)].clone(),
+                                    self.eigenvectors.as_ref().unwrap()[(r, c)].clone(),
+                                    self.eigenvectors.as_ref().unwrap()[(r, c + 1)].clone(),
                                 );
                             }
 
@@ -310,12 +305,12 @@ where
 
                             for r in 0..number_of_elements_value {
                                 vec[r] = Complex::<T>::new(
-                                    (&self.left_eigenvectors.as_ref()).unwrap()[(r, c)].clone(),
-                                    (&self.left_eigenvectors.as_ref()).unwrap()[(r, c + 1)].clone(),
+                                    self.left_eigenvectors.as_ref().unwrap()[(r, c)].clone(),
+                                    self.left_eigenvectors.as_ref().unwrap()[(r, c + 1)].clone(),
                                 );
                                 vec_conj[r] = Complex::<T>::new(
-                                    (&self.left_eigenvectors.as_ref()).unwrap()[(r, c)].clone(),
-                                    (&self.left_eigenvectors.as_ref()).unwrap()[(r, c + 1)].clone(),
+                                    self.left_eigenvectors.as_ref().unwrap()[(r, c)].clone(),
+                                    self.left_eigenvectors.as_ref().unwrap()[(r, c + 1)].clone(),
                                 );
                             }
 

nalgebra-lapack/src/generalized_eigenvalues.rs

@@ -30,24 +30,20 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(serialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<D, D> + Allocator<D>,
          OVector<T, D>: Serialize,
-         OMatrix<T, D, D>: Serialize")
-    )
+         OMatrix<T, D, D>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(deserialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<D, D> + Allocator<D>,
          OVector<T, D>: Deserialize<'de>,
-         OMatrix<T, D, D>: Deserialize<'de>")
-    )
+         OMatrix<T, D, D>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
 pub struct GeneralizedEigen<T: Scalar, D: Dim>
 where
-    DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D> + Allocator<D, D>,
 {
     alphar: OVector<T, D>,
     alphai: OVector<T, D>,
@@ -58,7 +54,7 @@ where
 
 impl<T: Scalar + Copy, D: Dim> Copy for GeneralizedEigen<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    DefaultAllocator: Allocator<D, D> + Allocator<D>,
     OMatrix<T, D, D>: Copy,
     OVector<T, D>: Copy,
 {
@@ -66,7 +62,7 @@ where
 
 impl<T: GeneralizedEigenScalar + RealField + Copy, D: Dim> GeneralizedEigen<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    DefaultAllocator: Allocator<D, D> + Allocator<D>,
 {
     /// Attempts to compute the generalized eigenvalues, and left and right associated eigenvectors
     /// via the raw returns from LAPACK's dggev and sggev routines
@@ -162,8 +158,7 @@ where
     /// as columns.
     pub fn eigenvectors(&self) -> (OMatrix<Complex<T>, D, D>, OMatrix<Complex<T>, D, D>)
     where
-        DefaultAllocator:
-            Allocator<Complex<T>, D, D> + Allocator<Complex<T>, D> + Allocator<(Complex<T>, T), D>,
+        DefaultAllocator: Allocator<D, D> + Allocator<D>,
     {
         /*
          How the eigenvectors are built up:
@@ -230,7 +225,7 @@ where
     #[must_use]
     pub fn raw_eigenvalues(&self) -> OVector<(Complex<T>, T), D>
     where
-        DefaultAllocator: Allocator<(Complex<T>, T), D>,
+        DefaultAllocator: Allocator<D>,
     {
         let mut out = Matrix::from_element_generic(
             self.vsl.shape_generic().0,

nalgebra-lapack/src/hessenberg.rs

@@ -12,22 +12,22 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<T, D, D> +
-                           Allocator<T, DimDiff<D, U1>>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<D, D> +
+                           Allocator<DimDiff<D, U1>>,
          OMatrix<T, D, D>: Serialize,
          OVector<T, DimDiff<D, U1>>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(deserialize = "DefaultAllocator: Allocator<T, D, D> +
-                           Allocator<T, DimDiff<D, U1>>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<D, D> +
+                           Allocator<DimDiff<D, U1>>,
          OMatrix<T, D, D>: Deserialize<'de>,
          OVector<T, DimDiff<D, U1>>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
 pub struct Hessenberg<T: Scalar, D: DimSub<U1>>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
+    DefaultAllocator: Allocator<D, D> + Allocator<DimDiff<D, U1>>,
 {
     h: OMatrix<T, D, D>,
     tau: OVector<T, DimDiff<D, U1>>,
@@ -35,7 +35,7 @@ where
 
 impl<T: Scalar + Copy, D: DimSub<U1>> Copy for Hessenberg<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
+    DefaultAllocator: Allocator<D, D> + Allocator<DimDiff<D, U1>>,
     OMatrix<T, D, D>: Copy,
     OVector<T, DimDiff<D, U1>>: Copy,
 {
@@ -43,7 +43,7 @@ where
 
 impl<T: HessenbergScalar + Zero, D: DimSub<U1>> Hessenberg<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
+    DefaultAllocator: Allocator<D, D> + Allocator<DimDiff<D, U1>>,
 {
     /// Computes the hessenberg decomposition of the matrix `m`.
     pub fn new(mut m: OMatrix<T, D, D>) -> Self {
@@ -97,7 +97,7 @@ where
 
 impl<T: HessenbergReal + Zero, D: DimSub<U1>> Hessenberg<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
+    DefaultAllocator: Allocator<D, D> + Allocator<DimDiff<D, U1>>,
 {
     /// Computes the matrices `(Q, H)` of this decomposition.
     #[inline]

nalgebra-lapack/src/lu.rs

@@ -20,22 +20,22 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<T, R, C> +
-                           Allocator<i32, DimMinimum<R, C>>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<R, C> +
+                           Allocator<DimMinimum<R, C>>,
          OMatrix<T, R, C>: Serialize,
          PermutationSequence<DimMinimum<R, C>>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(deserialize = "DefaultAllocator: Allocator<T, R, C> +
-                           Allocator<i32, DimMinimum<R, C>>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<R, C> +
+                           Allocator<DimMinimum<R, C>>,
          OMatrix<T, R, C>: Deserialize<'de>,
          PermutationSequence<DimMinimum<R, C>>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
 pub struct LU<T: Scalar, R: DimMin<C>, C: Dim>
 where
-    DefaultAllocator: Allocator<i32, DimMinimum<R, C>> + Allocator<T, R, C>,
+    DefaultAllocator: Allocator<DimMinimum<R, C>> + Allocator<R, C>,
 {
     lu: OMatrix<T, R, C>,
     p: OVector<i32, DimMinimum<R, C>>,
@@ -43,7 +43,7 @@ where
 
 impl<T: Scalar + Copy, R: DimMin<C>, C: Dim> Copy for LU<T, R, C>
 where
-    DefaultAllocator: Allocator<T, R, C> + Allocator<i32, DimMinimum<R, C>>,
+    DefaultAllocator: Allocator<R, C> + Allocator<DimMinimum<R, C>>,
     OMatrix<T, R, C>: Copy,
     OVector<i32, DimMinimum<R, C>>: Copy,
 {
@@ -53,11 +53,11 @@ impl<T: LUScalar, R: Dim, C: Dim> LU<T, R, C>
 where
     T: Zero + One,
     R: DimMin<C>,
-    DefaultAllocator: Allocator<T, R, C>
-        + Allocator<T, R, R>
-        + Allocator<T, R, DimMinimum<R, C>>
-        + Allocator<T, DimMinimum<R, C>, C>
-        + Allocator<i32, DimMinimum<R, C>>,
+    DefaultAllocator: Allocator<R, C>
+        + Allocator<R, R>
+        + Allocator<R, DimMinimum<R, C>>
+        + Allocator<DimMinimum<R, C>, C>
+        + Allocator<DimMinimum<R, C>>,
 {
     /// Computes the LU decomposition with partial (row) pivoting of `matrix`.
     pub fn new(mut m: OMatrix<T, R, C>) -> Self {
@@ -136,7 +136,7 @@ where
     #[inline]
     pub fn permute<C2: Dim>(&self, rhs: &mut OMatrix<T, R, C2>)
     where
-        DefaultAllocator: Allocator<T, R, C2>,
+        DefaultAllocator: Allocator<R, C2>,
     {
         let (nrows, ncols) = rhs.shape();
 
@@ -153,7 +153,7 @@ where
 
     fn generic_solve_mut<R2: Dim, C2: Dim>(&self, trans: u8, b: &mut OMatrix<T, R2, C2>) -> bool
     where
-        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
+        DefaultAllocator: Allocator<R2, C2> + Allocator<R2>,
     {
         let dim = self.lu.nrows();
 
@@ -192,7 +192,7 @@ where
     ) -> Option<OMatrix<T, R2, C2>>
     where
         S2: Storage<T, R2, C2>,
-        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
+        DefaultAllocator: Allocator<R2, C2> + Allocator<R2>,
     {
         let mut res = b.clone_owned();
         if self.generic_solve_mut(b'T', &mut res) {
@@ -210,7 +210,7 @@ where
     ) -> Option<OMatrix<T, R2, C2>>
     where
         S2: Storage<T, R2, C2>,
-        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
+        DefaultAllocator: Allocator<R2, C2> + Allocator<R2>,
     {
         let mut res = b.clone_owned();
         if self.generic_solve_mut(b'T', &mut res) {
@@ -228,7 +228,7 @@ where
     ) -> Option<OMatrix<T, R2, C2>>
     where
         S2: Storage<T, R2, C2>,
-        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
+        DefaultAllocator: Allocator<R2, C2> + Allocator<R2>,
     {
         let mut res = b.clone_owned();
         if self.generic_solve_mut(b'T', &mut res) {
@@ -243,7 +243,7 @@ where
     /// Returns `false` if no solution was found (the decomposed matrix is singular).
     pub fn solve_mut<R2: Dim, C2: Dim>(&self, b: &mut OMatrix<T, R2, C2>) -> bool
     where
-        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
+        DefaultAllocator: Allocator<R2, C2> + Allocator<R2>,
     {
         self.generic_solve_mut(b'T', b)
     }
@@ -254,7 +254,7 @@ where
     /// Returns `false` if no solution was found (the decomposed matrix is singular).
     pub fn solve_transpose_mut<R2: Dim, C2: Dim>(&self, b: &mut OMatrix<T, R2, C2>) -> bool
     where
-        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
+        DefaultAllocator: Allocator<R2, C2> + Allocator<R2>,
     {
         self.generic_solve_mut(b'T', b)
     }
@@ -265,7 +265,7 @@ where
     /// Returns `false` if no solution was found (the decomposed matrix is singular).
     pub fn solve_adjoint_mut<R2: Dim, C2: Dim>(&self, b: &mut OMatrix<T, R2, C2>) -> bool
     where
-        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
+        DefaultAllocator: Allocator<R2, C2> + Allocator<R2>,
     {
         self.generic_solve_mut(b'T', b)
     }
@@ -275,7 +275,7 @@ impl<T: LUScalar, D: Dim> LU<T, D, D>
 where
     T: Zero + One,
     D: DimMin<D, Output = D>,
-    DefaultAllocator: Allocator<T, D, D> + Allocator<i32, D>,
+    DefaultAllocator: Allocator<D, D> + Allocator<D>,
 {
     /// Computes the inverse of the decomposed matrix.
     pub fn inverse(mut self) -> Option<OMatrix<T, D, D>> {

nalgebra-lapack/src/qr.rs

@@ -15,22 +15,22 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<T, R, C> +
-                           Allocator<T, DimMinimum<R, C>>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<R, C> +
+                           Allocator<DimMinimum<R, C>>,
          OMatrix<T, R, C>: Serialize,
          OVector<T, DimMinimum<R, C>>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(deserialize = "DefaultAllocator: Allocator<T, R, C> +
-                           Allocator<T, DimMinimum<R, C>>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<R, C> +
+                           Allocator<DimMinimum<R, C>>,
          OMatrix<T, R, C>: Deserialize<'de>,
          OVector<T, DimMinimum<R, C>>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
 pub struct QR<T: Scalar, R: DimMin<C>, C: Dim>
 where
-    DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>>,
+    DefaultAllocator: Allocator<R, C> + Allocator<DimMinimum<R, C>>,
 {
     qr: OMatrix<T, R, C>,
     tau: OVector<T, DimMinimum<R, C>>,
@@ -38,7 +38,7 @@ where
 
 impl<T: Scalar + Copy, R: DimMin<C>, C: Dim> Copy for QR<T, R, C>
 where
-    DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>>,
+    DefaultAllocator: Allocator<R, C> + Allocator<DimMinimum<R, C>>,
     OMatrix<T, R, C>: Copy,
     OVector<T, DimMinimum<R, C>>: Copy,
 {
@@ -46,10 +46,10 @@ where
 
 impl<T: QRScalar + Zero, R: DimMin<C>, C: Dim> QR<T, R, C>
 where
-    DefaultAllocator: Allocator<T, R, C>
-        + Allocator<T, R, DimMinimum<R, C>>
-        + Allocator<T, DimMinimum<R, C>, C>
-        + Allocator<T, DimMinimum<R, C>>,
+    DefaultAllocator: Allocator<R, C>
+        + Allocator<R, DimMinimum<R, C>>
+        + Allocator<DimMinimum<R, C>, C>
+        + Allocator<DimMinimum<R, C>>,
 {
     /// Computes the QR decomposition of the matrix `m`.
     pub fn new(mut m: OMatrix<T, R, C>) -> Self {
@@ -98,10 +98,10 @@ where
 
 impl<T: QRReal + Zero, R: DimMin<C>, C: Dim> QR<T, R, C>
 where
-    DefaultAllocator: Allocator<T, R, C>
-        + Allocator<T, R, DimMinimum<R, C>>
-        + Allocator<T, DimMinimum<R, C>, C>
-        + Allocator<T, DimMinimum<R, C>>,
+    DefaultAllocator: Allocator<R, C>
+        + Allocator<R, DimMinimum<R, C>>
+        + Allocator<DimMinimum<R, C>, C>
+        + Allocator<DimMinimum<R, C>>,
 {
     /// Retrieves the matrices `(Q, R)` of this decompositions.
     pub fn unpack(

nalgebra-lapack/src/qz.rs

@@ -22,24 +22,20 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(serialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<D, D> + Allocator<D>,
          OVector<T, D>: Serialize,
-         OMatrix<T, D, D>: Serialize")
-    )
+         OMatrix<T, D, D>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(deserialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<D, D> + Allocator<D>,
          OVector<T, D>: Deserialize<'de>,
-         OMatrix<T, D, D>: Deserialize<'de>")
-    )
+         OMatrix<T, D, D>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
 pub struct QZ<T: Scalar, D: Dim>
 where
-    DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D> + Allocator<D, D>,
 {
     alphar: OVector<T, D>,
     alphai: OVector<T, D>,
@@ -52,7 +48,7 @@ where
 
 impl<T: Scalar + Copy, D: Dim> Copy for QZ<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    DefaultAllocator: Allocator<D, D> + Allocator<D>,
     OMatrix<T, D, D>: Copy,
     OVector<T, D>: Copy,
 {
@@ -60,7 +56,7 @@ where
 
 impl<T: QZScalar + RealField, D: Dim> QZ<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    DefaultAllocator: Allocator<D, D> + Allocator<D>,
 {
     /// Attempts to compute the QZ decomposition of input real square matrices `a` and `b`.
     ///
@@ -182,7 +178,7 @@ where
     #[must_use]
     pub fn raw_eigenvalues(&self) -> OVector<(Complex<T>, T), D>
     where
-        DefaultAllocator: Allocator<(Complex<T>, T), D>,
+        DefaultAllocator: Allocator<D>,
     {
         let mut out = Matrix::from_element_generic(
             self.vsl.shape_generic().0,

nalgebra-lapack/src/schur.rs

@@ -17,24 +17,20 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(serialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<D, D> + Allocator<D>,
          OVector<T, D>: Serialize,
-         OMatrix<T, D, D>: Serialize")
-    )
+         OMatrix<T, D, D>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(deserialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<D, D> + Allocator<D>,
          OVector<T, D>: Serialize,
-         OMatrix<T, D, D>: Deserialize<'de>")
-    )
+         OMatrix<T, D, D>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
 pub struct Schur<T: Scalar, D: Dim>
 where
-    DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D> + Allocator<D, D>,
 {
     re: OVector<T, D>,
     im: OVector<T, D>,
@@ -44,7 +40,7 @@ where
 
 impl<T: Scalar + Copy, D: Dim> Copy for Schur<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    DefaultAllocator: Allocator<D, D> + Allocator<D>,
     OMatrix<T, D, D>: Copy,
     OVector<T, D>: Copy,
 {
@@ -52,7 +48,7 @@ where
 
 impl<T: SchurScalar + RealField, D: Dim> Schur<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    DefaultAllocator: Allocator<D, D> + Allocator<D>,
 {
     /// Computes the eigenvalues and real Schur form of the matrix `m`.
     ///
@@ -150,7 +146,7 @@ where
     #[must_use]
     pub fn complex_eigenvalues(&self) -> OVector<Complex<T>, D>
     where
-        DefaultAllocator: Allocator<Complex<T>, D>,
+        DefaultAllocator: Allocator<D>,
     {
         let mut out = Matrix::zeros_generic(self.t.shape_generic().0, Const::<1>);
 

nalgebra-lapack/src/svd.rs

@@ -14,18 +14,18 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<T, DimMinimum<R, C>> +
-                           Allocator<T, R, R> +
-                           Allocator<T, C, C>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<DimMinimum<R, C>> +
+                           Allocator<R, R> +
+                           Allocator<C, C>,
          OMatrix<T, R>: Serialize,
          OMatrix<T, C>: Serialize,
          OVector<T, DimMinimum<R, C>>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<T, DimMinimum<R, C>> +
-                           Allocator<T, R, R> +
-                           Allocator<T, C, C>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<DimMinimum<R, C>> +
+                           Allocator<R, R> +
+                           Allocator<C, C>,
          OMatrix<T, R>: Deserialize<'de>,
          OMatrix<T, C>: Deserialize<'de>,
          OVector<T, DimMinimum<R, C>>: Deserialize<'de>"))
@@ -33,7 +33,7 @@ use lapack;
 #[derive(Clone, Debug)]
 pub struct SVD<T: Scalar, R: DimMin<C>, C: Dim>
 where
-    DefaultAllocator: Allocator<T, R, R> + Allocator<T, DimMinimum<R, C>> + Allocator<T, C, C>,
+    DefaultAllocator: Allocator<R, R> + Allocator<DimMinimum<R, C>> + Allocator<C, C>,
 {
     /// The left-singular vectors `U` of this SVD.
     pub u: OMatrix<T, R, R>, // TODO: should be OMatrix<T, R, DimMinimum<R, C>>
@@ -45,7 +45,7 @@ where
 
 impl<T: Scalar + Copy, R: DimMin<C>, C: Dim> Copy for SVD<T, R, C>
 where
-    DefaultAllocator: Allocator<T, C, C> + Allocator<T, R, R> + Allocator<T, DimMinimum<R, C>>,
+    DefaultAllocator: Allocator<C, C> + Allocator<R, R> + Allocator<DimMinimum<R, C>>,
     OMatrix<T, R, R>: Copy,
     OMatrix<T, C, C>: Copy,
     OVector<T, DimMinimum<R, C>>: Copy,
@@ -56,10 +56,8 @@ where
 /// supported by the Singular Value Decompotition.
 pub trait SVDScalar<R: DimMin<C>, C: Dim>: Scalar
 where
-    DefaultAllocator: Allocator<Self, R, R>
-        + Allocator<Self, R, C>
-        + Allocator<Self, DimMinimum<R, C>>
-        + Allocator<Self, C, C>,
+    DefaultAllocator:
+        Allocator<R, R> + Allocator<R, C> + Allocator<DimMinimum<R, C>> + Allocator<C, C>,
 {
     /// Computes the SVD decomposition of `m`.
     fn compute(m: OMatrix<Self, R, C>) -> Option<SVD<Self, R, C>>;
@@ -67,10 +65,8 @@ where
 
 impl<T: SVDScalar<R, C>, R: DimMin<C>, C: Dim> SVD<T, R, C>
 where
-    DefaultAllocator: Allocator<T, R, R>
-        + Allocator<T, R, C>
-        + Allocator<T, DimMinimum<R, C>>
-        + Allocator<T, C, C>,
+    DefaultAllocator:
+        Allocator<R, R> + Allocator<R, C> + Allocator<DimMinimum<R, C>> + Allocator<C, C>,
 {
     /// Computes the Singular Value Decomposition of `matrix`.
     pub fn new(m: OMatrix<T, R, C>) -> Option<Self> {
@@ -82,10 +78,10 @@ macro_rules! svd_impl(
     ($t: ty, $lapack_func: path) => (
         impl<R: Dim, C: Dim> SVDScalar<R, C> for $t
                 where R: DimMin<C>,
-                      DefaultAllocator: Allocator<$t, R, C> +
-                                        Allocator<$t, R, R> +
-                                        Allocator<$t, C, C> +
-                                        Allocator<$t, DimMinimum<R, C>> {
+                      DefaultAllocator: Allocator<R, C> +
+                                        Allocator<R, R> +
+                                        Allocator<C, C> +
+                                        Allocator<DimMinimum<R, C>> {
 
             fn compute(mut m: OMatrix<$t, R, C>) -> Option<SVD<$t, R, C>> {
                 let (nrows, ncols) = m.shape_generic();
@@ -134,16 +130,16 @@ macro_rules! svd_impl(
 
         impl<R: DimMin<C>, C: Dim> SVD<$t, R, C>
             // TODO: All those bounds…
-            where DefaultAllocator: Allocator<$t, R, C>                 +
-                                    Allocator<$t, C, R>                 +
-                                    Allocator<$t, U1, R>                +
-                                    Allocator<$t, U1, C>                +
-                                    Allocator<$t, R, R>                 +
-                                    Allocator<$t, DimMinimum<R, C>> +
-                                    Allocator<$t, DimMinimum<R, C>, R>  +
-                                    Allocator<$t, DimMinimum<R, C>, C>  +
-                                    Allocator<$t, R, DimMinimum<R, C>>  +
-                                    Allocator<$t, C, C> {
+            where DefaultAllocator: Allocator<R, C>                 +
+                                    Allocator<C, R>                 +
+                                    Allocator<U1, R>                +
+                                    Allocator<U1, C>                +
+                                    Allocator<R, R>                 +
+                                    Allocator<DimMinimum<R, C>> +
+                                    Allocator<DimMinimum<R, C>, R>  +
+                                    Allocator<DimMinimum<R, C>, C>  +
+                                    Allocator<R, DimMinimum<R, C>>  +
+                                    Allocator<C, C> {
             /// Reconstructs the matrix from its decomposition.
             ///
             /// Useful if some components (e.g. some singular values) of this decomposition have
@@ -237,9 +233,9 @@ macro_rules! svd_complex_impl(
             where R: DimMin<C>,
                   S: ContiguousStorage<Complex<$t>, R, C>,
                   S::Alloc: OwnedAllocator<Complex<$t>, R, C, S> +
-                            Allocator<Complex<$t>, R, R>         +
-                            Allocator<Complex<$t>, C, C>         +
-                            Allocator<$t, DimMinimum<R, C>> {
+                            Allocator<R, R>         +
+                            Allocator<C, C>         +
+                            Allocator<DimMinimum<R, C>> {
             let (nrows, ncols) = m.shape_generic();
 
             if nrows.value() == 0 || ncols.value() == 0 {

nalgebra-lapack/src/symmetric_eigen.rs

@@ -17,22 +17,22 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<T, D, D> +
-                           Allocator<T, D>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<D, D> +
+                           Allocator<D>,
          OVector<T, D>: Serialize,
          OMatrix<T, D, D>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(deserialize = "DefaultAllocator: Allocator<T, D, D> +
-                           Allocator<T, D>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<D, D> +
+                           Allocator<D>,
          OVector<T, D>: Deserialize<'de>,
          OMatrix<T, D, D>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
 pub struct SymmetricEigen<T: Scalar, D: Dim>
 where
-    DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D> + Allocator<D, D>,
 {
     /// The eigenvectors of the decomposed matrix.
     pub eigenvectors: OMatrix<T, D, D>,
@@ -43,7 +43,7 @@ where
 
 impl<T: Scalar + Copy, D: Dim> Copy for SymmetricEigen<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    DefaultAllocator: Allocator<D, D> + Allocator<D>,
     OMatrix<T, D, D>: Copy,
     OVector<T, D>: Copy,
 {
@@ -51,7 +51,7 @@ where
 
 impl<T: SymmetricEigenScalar + RealField, D: Dim> SymmetricEigen<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    DefaultAllocator: Allocator<D, D> + Allocator<D>,
 {
     /// Computes the eigenvalues and eigenvectors of the symmetric matrix `m`.
     ///

nalgebra-macros/Cargo.toml

@@ -1,25 +1,24 @@
 [package]
 name = "nalgebra-macros"
-version = "0.2.1"
-authors = [ "Andreas Longva", "Sébastien Crozet <developer@crozet.re>" ]
+version = "0.2.2"
+authors = ["Andreas Longva", "Sébastien Crozet <developer@crozet.re>"]
 edition = "2018"
 description = "Procedural macros for nalgebra"
 documentation = "https://www.nalgebra.org/docs"
 homepage = "https://nalgebra.org"
 repository = "https://github.com/dimforge/nalgebra"
 readme = "../README.md"
-categories = [ "science", "mathematics" ]
-keywords = [ "linear", "algebra", "matrix", "vector", "math" ]
+categories = ["science", "mathematics"]
+keywords = ["linear", "algebra", "matrix", "vector", "math"]
 license = "Apache-2.0"
 
 [lib]
 proc-macro = true
 
 [dependencies]
-syn = { version="1.0", features = ["full"] }
+syn = { version = "2.0", features = ["full"] }
 quote = "1.0"
 proc-macro2 = "1.0"
 
 [dev-dependencies]
-nalgebra = { version = "0.32.0", path = ".." }
-trybuild = "1.0.42"
+nalgebra = { version = "0.33", path = ".." }

nalgebra-macros/LICENSE

@@ -0,0 +1 @@
+../LICENSE

nalgebra-macros/src/lib.rs

@@ -12,102 +12,19 @@
     future_incompatible,
     missing_copy_implementations,
     missing_debug_implementations,
-    clippy::all,
-    clippy::pedantic
+    clippy::all
 )]
 
+mod matrix_vector_impl;
+mod stack_impl;
+
+use matrix_vector_impl::{Matrix, Vector};
+
+use crate::matrix_vector_impl::{dmatrix_impl, dvector_impl, matrix_impl, vector_impl};
 use proc_macro::TokenStream;
-use quote::{quote, ToTokens, TokenStreamExt};
-use syn::parse::{Error, Parse, ParseStream, Result};
-use syn::punctuated::Punctuated;
-use syn::Expr;
-use syn::{parse_macro_input, Token};
-
-use proc_macro2::{Delimiter, Spacing, TokenStream as TokenStream2, TokenTree};
-use proc_macro2::{Group, Punct};
-
-struct Matrix {
-    // Represent the matrix as a row-major vector of vectors of expressions
-    rows: Vec<Vec<Expr>>,
-    ncols: usize,
-}
-
-impl Matrix {
-    fn nrows(&self) -> usize {
-        self.rows.len()
-    }
-
-    fn ncols(&self) -> usize {
-        self.ncols
-    }
-
-    /// Produces a stream of tokens representing this matrix as a column-major nested array.
-    fn to_col_major_nested_array_tokens(&self) -> TokenStream2 {
-        let mut result = TokenStream2::new();
-        for j in 0..self.ncols() {
-            let mut col = TokenStream2::new();
-            let col_iter = (0..self.nrows()).map(move |i| &self.rows[i][j]);
-            col.append_separated(col_iter, Punct::new(',', Spacing::Alone));
-            result.append(Group::new(Delimiter::Bracket, col));
-            result.append(Punct::new(',', Spacing::Alone));
-        }
-        TokenStream2::from(TokenTree::Group(Group::new(Delimiter::Bracket, result)))
-    }
-
-    /// Produces a stream of tokens representing this matrix as a column-major flat array
-    /// (suitable for representing e.g. a `DMatrix`).
-    fn to_col_major_flat_array_tokens(&self) -> TokenStream2 {
-        let mut data = TokenStream2::new();
-        for j in 0..self.ncols() {
-            for i in 0..self.nrows() {
-                self.rows[i][j].to_tokens(&mut data);
-                data.append(Punct::new(',', Spacing::Alone));
-            }
-        }
-        TokenStream2::from(TokenTree::Group(Group::new(Delimiter::Bracket, data)))
-    }
-}
-
-type MatrixRowSyntax = Punctuated<Expr, Token![,]>;
-
-impl Parse for Matrix {
-    fn parse(input: ParseStream<'_>) -> Result<Self> {
-        let mut rows = Vec::new();
-        let mut ncols = None;
-
-        while !input.is_empty() {
-            let row_span = input.span();
-            let row = MatrixRowSyntax::parse_separated_nonempty(input)?;
-
-            if let Some(ncols) = ncols {
-                if row.len() != ncols {
-                    let row_idx = rows.len();
-                    let error_msg = format!(
-                        "Unexpected number of entries in row {}. Expected {}, found {} entries.",
-                        row_idx,
-                        ncols,
-                        row.len()
-                    );
-                    return Err(Error::new(row_span, error_msg));
-                }
-            } else {
-                ncols = Some(row.len());
-            }
-            rows.push(row.into_iter().collect());
-
-            // We've just read a row, so if there are more tokens, there must be a semi-colon,
-            // otherwise the input is malformed
-            if !input.is_empty() {
-                input.parse::<Token![;]>()?;
-            }
-        }
-
-        Ok(Self {
-            rows,
-            ncols: ncols.unwrap_or(0),
-        })
-    }
-}
+use quote::quote;
+use stack_impl::stack_impl;
+use syn::parse_macro_input;
 
 /// Construct a fixed-size matrix directly from data.
 ///
@@ -145,20 +62,7 @@ impl Parse for Matrix {
 /// ```
 #[proc_macro]
 pub fn matrix(stream: TokenStream) -> TokenStream {
-    let matrix = parse_macro_input!(stream as Matrix);
-
-    let row_dim = matrix.nrows();
-    let col_dim = matrix.ncols();
-
-    let array_tokens = matrix.to_col_major_nested_array_tokens();
-
-    //  TODO: Use quote_spanned instead??
-    let output = quote! {
-        nalgebra::SMatrix::<_, #row_dim, #col_dim>
-            ::from_array_storage(nalgebra::ArrayStorage(#array_tokens))
-    };
-
-    proc_macro::TokenStream::from(output)
+    matrix_impl(stream)
 }
 
 /// Construct a dynamic matrix directly from data.
@@ -180,55 +84,7 @@ pub fn matrix(stream: TokenStream) -> TokenStream {
 /// ```
 #[proc_macro]
 pub fn dmatrix(stream: TokenStream) -> TokenStream {
-    let matrix = parse_macro_input!(stream as Matrix);
-
-    let row_dim = matrix.nrows();
-    let col_dim = matrix.ncols();
-
-    let array_tokens = matrix.to_col_major_flat_array_tokens();
-
-    //  TODO: Use quote_spanned instead??
-    let output = quote! {
-        nalgebra::DMatrix::<_>
-            ::from_vec_storage(nalgebra::VecStorage::new(
-                nalgebra::Dyn(#row_dim),
-                nalgebra::Dyn(#col_dim),
-                vec!#array_tokens))
-    };
-
-    proc_macro::TokenStream::from(output)
-}
-
-struct Vector {
-    elements: Vec<Expr>,
-}
-
-impl Vector {
-    fn to_array_tokens(&self) -> TokenStream2 {
-        let mut data = TokenStream2::new();
-        data.append_separated(&self.elements, Punct::new(',', Spacing::Alone));
-        TokenStream2::from(TokenTree::Group(Group::new(Delimiter::Bracket, data)))
-    }
-
-    fn len(&self) -> usize {
-        self.elements.len()
-    }
-}
-
-impl Parse for Vector {
-    fn parse(input: ParseStream<'_>) -> Result<Self> {
-        // The syntax of a vector is just the syntax of a single matrix row
-        if input.is_empty() {
-            Ok(Self {
-                elements: Vec::new(),
-            })
-        } else {
-            let elements = MatrixRowSyntax::parse_terminated(input)?
-                .into_iter()
-                .collect();
-            Ok(Self { elements })
-        }
-    }
+    dmatrix_impl(stream)
 }
 
 /// Construct a fixed-size column vector directly from data.
@@ -252,14 +108,7 @@ impl Parse for Vector {
 /// ```
 #[proc_macro]
 pub fn vector(stream: TokenStream) -> TokenStream {
-    let vector = parse_macro_input!(stream as Vector);
-    let len = vector.len();
-    let array_tokens = vector.to_array_tokens();
-    let output = quote! {
-        nalgebra::SVector::<_, #len>
-            ::from_array_storage(nalgebra::ArrayStorage([#array_tokens]))
-    };
-    proc_macro::TokenStream::from(output)
+    vector_impl(stream)
 }
 
 /// Construct a dynamic column vector directly from data.
@@ -279,17 +128,7 @@ pub fn vector(stream: TokenStream) -> TokenStream {
 /// ```
 #[proc_macro]
 pub fn dvector(stream: TokenStream) -> TokenStream {
-    let vector = parse_macro_input!(stream as Vector);
-    let len = vector.len();
-    let array_tokens = vector.to_array_tokens();
-    let output = quote! {
-        nalgebra::DVector::<_>
-            ::from_vec_storage(nalgebra::VecStorage::new(
-                nalgebra::Dyn(#len),
-                nalgebra::Const::<1>,
-                vec!#array_tokens))
-    };
-    proc_macro::TokenStream::from(output)
+    dvector_impl(stream)
 }
 
 /// Construct a fixed-size point directly from data.
@@ -321,3 +160,100 @@ pub fn point(stream: TokenStream) -> TokenStream {
     };
     proc_macro::TokenStream::from(output)
 }
+
+/// Construct a new matrix by stacking matrices in a block matrix.
+///
+/// **Note: Requires the `macros` feature to be enabled (enabled by default)**.
+///
+/// This macro facilitates the construction of
+/// [block matrices](https://en.wikipedia.org/wiki/Block_matrix)
+/// by stacking blocks (matrices) using the same MATLAB-like syntax as the [`matrix!`] and
+/// [`dmatrix!`] macros:
+///
+/// ```rust
+/// # use nalgebra::stack;
+/// #
+/// # fn main() {
+/// # let [a, b, c, d] = std::array::from_fn(|_| nalgebra::Matrix1::new(0));
+/// // a, b, c and d are matrices
+/// let block_matrix = stack![ a, b;
+///                            c, d ];
+/// # }
+/// ```
+///
+/// The resulting matrix is stack-allocated if the dimension of each block row and column
+/// can be determined at compile-time, otherwise it is heap-allocated.
+/// This is the case if, for every row, there is at least one matrix with a fixed number of rows,
+/// and, for every column, there is at least one matrix with a fixed number of columns.
+///
+/// [`stack!`] also supports special syntax to indicate zero blocks in a matrix:
+///
+/// ```rust
+/// # use nalgebra::stack;
+/// #
+/// # fn main() {
+/// # let [a, b, c, d] = std::array::from_fn(|_| nalgebra::Matrix1::new(0));
+/// // a and d are matrices
+/// let block_matrix = stack![ a, 0;
+///                            0, d ];
+/// # }
+/// ```
+/// Here, the `0` literal indicates a zero matrix of implicitly defined size.
+/// In order to infer the size of the zero blocks, there must be at least one matrix
+/// in every row and column of the matrix.
+/// In other words, no row or column can consist entirely of implicit zero blocks.
+///
+/// # Panics
+///
+/// Panics if dimensions are inconsistent and it cannot be determined at compile-time.
+///
+/// # Examples
+///
+/// ```
+/// use nalgebra::{matrix, SMatrix, stack};
+///
+/// let a = matrix![1, 2;
+///                 3, 4];
+/// let b = matrix![5, 6;
+///                 7, 8];
+/// let c = matrix![9, 10];
+///
+/// let block_matrix = stack![ a, b;
+///                            c, 0 ];
+///
+/// assert_eq!(block_matrix, matrix![1,  2,  5,  6;
+///                                  3,  4,  7,  8;
+///                                  9, 10,  0,  0]);
+///
+/// // Verify that the resulting block matrix is stack-allocated
+/// let _: SMatrix<_, 3, 4> = block_matrix;
+/// ```
+///
+/// The example above shows how stacking stack-allocated matrices results in a stack-allocated
+/// block matrix. If all row and column dimensions can not be determined at compile-time,
+/// the result is instead a dynamically allocated matrix:
+///
+/// ```
+/// use nalgebra::{dmatrix, DMatrix, Dyn, matrix, OMatrix, SMatrix, stack, U3};
+///
+/// # let a = matrix![1, 2; 3, 4]; let c = matrix![9, 10];
+/// // a and c as before, but b is a dynamic matrix this time
+/// let b = dmatrix![5, 6;
+///                  7, 8];
+///
+/// // In this case, the number of rows can be statically inferred to be 3 (U3),
+/// // but the number of columns cannot, hence it is dynamic
+/// let block_matrix: OMatrix<_, U3, Dyn> = stack![ a, b;
+///                                                 c, 0 ];
+///
+/// // If necessary, a fully dynamic matrix (DMatrix) can be obtained by reshaping
+/// let dyn_block_matrix: DMatrix<_> = block_matrix.reshape_generic(Dyn(3), Dyn(4));
+/// ```
+/// Note that explicitly annotating the types of `block_matrix` and `dyn_block_matrix` is
+/// only made for illustrative purposes, and is not generally necessary.
+///
+#[proc_macro]
+pub fn stack(stream: TokenStream) -> TokenStream {
+    let matrix = parse_macro_input!(stream as Matrix);
+    proc_macro::TokenStream::from(stack_impl(matrix).unwrap_or_else(syn::Error::into_compile_error))
+}

nalgebra-macros/src/matrix_vector_impl.rs

@@ -0,0 +1,201 @@
+use proc_macro::TokenStream;
+use quote::{quote, ToTokens, TokenStreamExt};
+use std::ops::Index;
+use syn::parse::{Error, Parse, ParseStream};
+use syn::punctuated::Punctuated;
+use syn::spanned::Spanned;
+use syn::Expr;
+use syn::{parse_macro_input, Token};
+
+use proc_macro2::{Delimiter, Spacing, TokenStream as TokenStream2, TokenTree};
+use proc_macro2::{Group, Punct};
+
+/// A matrix of expressions
+pub struct Matrix {
+    // Represent the matrix data in row-major format
+    data: Vec<Expr>,
+    nrows: usize,
+    ncols: usize,
+}
+
+impl Index<(usize, usize)> for Matrix {
+    type Output = Expr;
+
+    fn index(&self, (row, col): (usize, usize)) -> &Self::Output {
+        let linear_idx = self.ncols * row + col;
+        &self.data[linear_idx]
+    }
+}
+
+impl Matrix {
+    pub fn nrows(&self) -> usize {
+        self.nrows
+    }
+
+    pub fn ncols(&self) -> usize {
+        self.ncols
+    }
+
+    /// Produces a stream of tokens representing this matrix as a column-major nested array.
+    pub fn to_col_major_nested_array_tokens(&self) -> TokenStream2 {
+        let mut result = TokenStream2::new();
+        for j in 0..self.ncols() {
+            let mut col = TokenStream2::new();
+            let col_iter = (0..self.nrows()).map(|i| &self[(i, j)]);
+            col.append_separated(col_iter, Punct::new(',', Spacing::Alone));
+            result.append(Group::new(Delimiter::Bracket, col));
+            result.append(Punct::new(',', Spacing::Alone));
+        }
+        TokenStream2::from(TokenTree::Group(Group::new(Delimiter::Bracket, result)))
+    }
+
+    /// Produces a stream of tokens representing this matrix as a column-major flat array
+    /// (suitable for representing e.g. a `DMatrix`).
+    pub fn to_col_major_flat_array_tokens(&self) -> TokenStream2 {
+        let mut data = TokenStream2::new();
+        for j in 0..self.ncols() {
+            for i in 0..self.nrows() {
+                self[(i, j)].to_tokens(&mut data);
+                data.append(Punct::new(',', Spacing::Alone));
+            }
+        }
+        TokenStream2::from(TokenTree::Group(Group::new(Delimiter::Bracket, data)))
+    }
+}
+
+type MatrixRowSyntax = Punctuated<Expr, Token![,]>;
+
+impl Parse for Matrix {
+    fn parse(input: ParseStream<'_>) -> syn::Result<Self> {
+        let mut data = Vec::new();
+        let mut ncols = None;
+        let mut nrows = 0;
+
+        while !input.is_empty() {
+            let row = MatrixRowSyntax::parse_separated_nonempty(input)?;
+            let row_span = row.span();
+
+            if let Some(ncols) = ncols {
+                if row.len() != ncols {
+                    let error_msg = format!(
+                        "Unexpected number of entries in row {}. Expected {}, found {} entries.",
+                        nrows,
+                        ncols,
+                        row.len()
+                    );
+                    return Err(Error::new(row_span, error_msg));
+                }
+            } else {
+                ncols = Some(row.len());
+            }
+            data.extend(row.into_iter());
+            nrows += 1;
+
+            // We've just read a row, so if there are more tokens, there must be a semi-colon,
+            // otherwise the input is malformed
+            if !input.is_empty() {
+                input.parse::<Token![;]>()?;
+            }
+        }
+
+        Ok(Self {
+            data,
+            nrows,
+            ncols: ncols.unwrap_or(0),
+        })
+    }
+}
+
+pub struct Vector {
+    elements: Vec<Expr>,
+}
+
+impl Vector {
+    pub fn to_array_tokens(&self) -> TokenStream2 {
+        let mut data = TokenStream2::new();
+        data.append_separated(&self.elements, Punct::new(',', Spacing::Alone));
+        TokenStream2::from(TokenTree::Group(Group::new(Delimiter::Bracket, data)))
+    }
+
+    pub fn len(&self) -> usize {
+        self.elements.len()
+    }
+}
+
+impl Parse for Vector {
+    fn parse(input: ParseStream<'_>) -> syn::Result<Self> {
+        // The syntax of a vector is just the syntax of a single matrix row
+        if input.is_empty() {
+            Ok(Self {
+                elements: Vec::new(),
+            })
+        } else {
+            let elements = MatrixRowSyntax::parse_terminated(input)?
+                .into_iter()
+                .collect();
+            Ok(Self { elements })
+        }
+    }
+}
+
+pub fn matrix_impl(stream: TokenStream) -> TokenStream {
+    let matrix = parse_macro_input!(stream as Matrix);
+
+    let row_dim = matrix.nrows();
+    let col_dim = matrix.ncols();
+
+    let array_tokens = matrix.to_col_major_nested_array_tokens();
+
+    //  TODO: Use quote_spanned instead??
+    let output = quote! {
+        nalgebra::SMatrix::<_, #row_dim, #col_dim>
+            ::from_array_storage(nalgebra::ArrayStorage(#array_tokens))
+    };
+
+    proc_macro::TokenStream::from(output)
+}
+
+pub fn dmatrix_impl(stream: TokenStream) -> TokenStream {
+    let matrix = parse_macro_input!(stream as Matrix);
+
+    let row_dim = matrix.nrows();
+    let col_dim = matrix.ncols();
+
+    let array_tokens = matrix.to_col_major_flat_array_tokens();
+
+    //  TODO: Use quote_spanned instead??
+    let output = quote! {
+        nalgebra::DMatrix::<_>
+            ::from_vec_storage(nalgebra::VecStorage::new(
+                nalgebra::Dyn(#row_dim),
+                nalgebra::Dyn(#col_dim),
+                vec!#array_tokens))
+    };
+
+    proc_macro::TokenStream::from(output)
+}
+
+pub fn vector_impl(stream: TokenStream) -> TokenStream {
+    let vector = parse_macro_input!(stream as Vector);
+    let len = vector.len();
+    let array_tokens = vector.to_array_tokens();
+    let output = quote! {
+        nalgebra::SVector::<_, #len>
+            ::from_array_storage(nalgebra::ArrayStorage([#array_tokens]))
+    };
+    proc_macro::TokenStream::from(output)
+}
+
+pub fn dvector_impl(stream: TokenStream) -> TokenStream {
+    let vector = parse_macro_input!(stream as Vector);
+    let len = vector.len();
+    let array_tokens = vector.to_array_tokens();
+    let output = quote! {
+        nalgebra::DVector::<_>
+            ::from_vec_storage(nalgebra::VecStorage::new(
+                nalgebra::Dyn(#len),
+                nalgebra::Const::<1>,
+                vec!#array_tokens))
+    };
+    proc_macro::TokenStream::from(output)
+}

nalgebra-macros/src/stack_impl.rs

@@ -0,0 +1,302 @@
+use crate::Matrix;
+use proc_macro2::{Span, TokenStream as TokenStream2};
+use quote::{format_ident, quote, quote_spanned};
+use syn::spanned::Spanned;
+use syn::{Error, Expr, Lit};
+
+#[allow(clippy::too_many_lines)]
+pub fn stack_impl(matrix: Matrix) -> syn::Result<TokenStream2> {
+    // The prefix is used to construct variable names
+    // that are extremely unlikely to collide with variable names used in e.g. expressions
+    // by the user. Although we could use a long, pseudo-random string, this makes the generated
+    // code very painful to parse, so we settle for something more semantic that is still
+    // very unlikely to collide
+    let prefix = "___na";
+    let n_block_rows = matrix.nrows();
+    let n_block_cols = matrix.ncols();
+
+    let mut output = quote! {};
+
+    // First assign data and shape for each matrix entry to variables
+    // (this is important so that we, for example, don't evaluate an expression more than once)
+    for i in 0..n_block_rows {
+        for j in 0..n_block_cols {
+            let expr = &matrix[(i, j)];
+            if !is_literal_zero(expr) {
+                let ident_block = format_ident!("{prefix}_stack_{i}_{j}_block");
+                let ident_shape = format_ident!("{prefix}_stack_{i}_{j}_shape");
+                output.extend(std::iter::once(quote_spanned! {expr.span()=>
+                    let ref #ident_block = #expr;
+                    let #ident_shape = #ident_block.shape_generic();
+                }));
+            }
+        }
+    }
+
+    // Determine the number of rows (dimension) in each block row,
+    // and write out variables that define block row dimensions and offsets into the
+    // output matrix
+    for i in 0..n_block_rows {
+        // The dimension of the block row is the result of trying to unify the row shape of
+        // all blocks in the block row
+        let dim = (0 ..n_block_cols)
+            .filter_map(|j| {
+                let expr = &matrix[(i, j)];
+                if !is_literal_zero(expr) {
+                    let mut ident_shape = format_ident!("{prefix}_stack_{i}_{j}_shape");
+                    ident_shape.set_span(ident_shape.span().located_at(expr.span()));
+                    Some(quote_spanned!{expr.span()=> #ident_shape.0 })
+                } else {
+                    None
+                }
+            }).reduce(|a, b| {
+                let expect_msg = format!("All blocks in block row {i} must have the same number of rows");
+                quote_spanned!{b.span()=>
+                    <nalgebra::constraint::ShapeConstraint as nalgebra::constraint::SameNumberOfRows<_, _>>::representative(#a, #b)
+                        .expect(#expect_msg)
+                }
+            }).ok_or(Error::new(Span::call_site(), format!("Block row {i} cannot consist entirely of implicit zero blocks.")))?;
+
+        let dim_ident = format_ident!("{prefix}_stack_row_{i}_dim");
+        let offset_ident = format_ident!("{prefix}_stack_row_{i}_offset");
+
+        let offset = if i == 0 {
+            quote! { 0 }
+        } else {
+            let prev_offset_ident = format_ident!("{prefix}_stack_row_{}_offset", i - 1);
+            let prev_dim_ident = format_ident!("{prefix}_stack_row_{}_dim", i - 1);
+            quote! { #prev_offset_ident + <_ as nalgebra::Dim>::value(&#prev_dim_ident) }
+        };
+
+        output.extend(std::iter::once(quote! {
+            let #dim_ident = #dim;
+            let #offset_ident = #offset;
+        }));
+    }
+
+    // Do the same thing for the block columns
+    for j in 0..n_block_cols {
+        let dim = (0 ..n_block_rows)
+            .filter_map(|i| {
+                let expr = &matrix[(i, j)];
+                if !is_literal_zero(expr) {
+                    let mut ident_shape = format_ident!("{prefix}_stack_{i}_{j}_shape");
+                    ident_shape.set_span(ident_shape.span().located_at(expr.span()));
+                    Some(quote_spanned!{expr.span()=> #ident_shape.1 })
+                } else {
+                    None
+                }
+            }).reduce(|a, b| {
+                let expect_msg = format!("All blocks in block column {j} must have the same number of columns");
+                quote_spanned!{b.span()=>
+                        <nalgebra::constraint::ShapeConstraint as nalgebra::constraint::SameNumberOfColumns<_, _>>::representative(#a, #b)
+                            .expect(#expect_msg)
+                }
+            }).ok_or(Error::new(Span::call_site(), format!("Block column {j} cannot consist entirely of implicit zero blocks.")))?;
+
+        let dim_ident = format_ident!("{prefix}_stack_col_{j}_dim");
+        let offset_ident = format_ident!("{prefix}_stack_col_{j}_offset");
+
+        let offset = if j == 0 {
+            quote! { 0 }
+        } else {
+            let prev_offset_ident = format_ident!("{prefix}_stack_col_{}_offset", j - 1);
+            let prev_dim_ident = format_ident!("{prefix}_stack_col_{}_dim", j - 1);
+            quote! { #prev_offset_ident + <_ as nalgebra::Dim>::value(&#prev_dim_ident) }
+        };
+
+        output.extend(std::iter::once(quote! {
+            let #dim_ident = #dim;
+            let #offset_ident = #offset;
+        }));
+    }
+
+    // Determine number of rows and cols in output matrix,
+    // by adding together dimensions of all block rows/cols
+    let num_rows = (0..n_block_rows)
+        .map(|i| {
+            let ident = format_ident!("{prefix}_stack_row_{i}_dim");
+            quote! { #ident }
+        })
+        .reduce(|a, b| {
+            quote! {
+                <_ as nalgebra::DimAdd<_>>::add(#a, #b)
+            }
+        })
+        .unwrap_or(quote! { nalgebra::dimension::U0 });
+
+    let num_cols = (0..n_block_cols)
+        .map(|j| {
+            let ident = format_ident!("{prefix}_stack_col_{j}_dim");
+            quote! { #ident }
+        })
+        .reduce(|a, b| {
+            quote! {
+                <_ as nalgebra::DimAdd<_>>::add(#a, #b)
+            }
+        })
+        .unwrap_or(quote! { nalgebra::dimension::U0 });
+
+    // It should be possible to use `uninitialized_generic` here instead
+    // however that would mean that the macro needs to generate unsafe code
+    // which does not seem like a great idea.
+    output.extend(std::iter::once(quote! {
+        let mut matrix = nalgebra::Matrix::zeros_generic(#num_rows, #num_cols);
+    }));
+
+    for i in 0..n_block_rows {
+        for j in 0..n_block_cols {
+            let row_dim = format_ident!("{prefix}_stack_row_{i}_dim");
+            let col_dim = format_ident!("{prefix}_stack_col_{j}_dim");
+            let row_offset = format_ident!("{prefix}_stack_row_{i}_offset");
+            let col_offset = format_ident!("{prefix}_stack_col_{j}_offset");
+            let expr = &matrix[(i, j)];
+            if !is_literal_zero(expr) {
+                let expr_ident = format_ident!("{prefix}_stack_{i}_{j}_block");
+                output.extend(std::iter::once(quote! {
+                    let start = (#row_offset, #col_offset);
+                    let shape = (#row_dim, #col_dim);
+                    let input_view = #expr_ident.generic_view((0, 0), shape);
+                    let mut output_view = matrix.generic_view_mut(start, shape);
+                    output_view.copy_from(&input_view);
+                }));
+            }
+        }
+    }
+
+    Ok(quote! {
+        {
+            #output
+            matrix
+        }
+    })
+}
+
+fn is_literal_zero(expr: &Expr) -> bool {
+    matches!(expr,
+        Expr::Lit(syn::ExprLit { lit: Lit::Int(integer_literal), .. })
+        if integer_literal.base10_digits() == "0")
+}
+
+#[cfg(test)]
+mod tests {
+    use crate::stack_impl::stack_impl;
+    use crate::Matrix;
+    use quote::quote;
+
+    #[test]
+    fn stack_simple_generation() {
+        let input: Matrix = syn::parse_quote![
+            a, 0;
+            0, b;
+        ];
+
+        let result = stack_impl(input).unwrap();
+
+        let expected = quote! {{
+            let ref ___na_stack_0_0_block = a;
+            let ___na_stack_0_0_shape = ___na_stack_0_0_block.shape_generic();
+            let ref ___na_stack_1_1_block = b;
+            let ___na_stack_1_1_shape = ___na_stack_1_1_block.shape_generic();
+            let ___na_stack_row_0_dim = ___na_stack_0_0_shape.0;
+            let ___na_stack_row_0_offset = 0;
+            let ___na_stack_row_1_dim = ___na_stack_1_1_shape.0;
+            let ___na_stack_row_1_offset = ___na_stack_row_0_offset + <_ as nalgebra::Dim>::value(&___na_stack_row_0_dim);
+            let ___na_stack_col_0_dim = ___na_stack_0_0_shape.1;
+            let ___na_stack_col_0_offset = 0;
+            let ___na_stack_col_1_dim = ___na_stack_1_1_shape.1;
+            let ___na_stack_col_1_offset = ___na_stack_col_0_offset + <_ as nalgebra::Dim>::value(&___na_stack_col_0_dim);
+            let mut matrix = nalgebra::Matrix::zeros_generic(
+                <_ as nalgebra::DimAdd<_>>::add(___na_stack_row_0_dim, ___na_stack_row_1_dim),
+                <_ as nalgebra::DimAdd<_>>::add(___na_stack_col_0_dim, ___na_stack_col_1_dim)
+            );
+            let start = (___na_stack_row_0_offset, ___na_stack_col_0_offset);
+            let shape = (___na_stack_row_0_dim, ___na_stack_col_0_dim);
+            let input_view = ___na_stack_0_0_block.generic_view((0,0), shape);
+            let mut output_view = matrix.generic_view_mut(start, shape);
+            output_view.copy_from(&input_view);
+            let start = (___na_stack_row_1_offset, ___na_stack_col_1_offset);
+            let shape = (___na_stack_row_1_dim, ___na_stack_col_1_dim);
+            let input_view = ___na_stack_1_1_block.generic_view((0,0), shape);
+            let mut output_view = matrix.generic_view_mut(start, shape);
+            output_view.copy_from(&input_view);
+            matrix
+        }};
+
+        assert_eq!(format!("{result}"), format!("{}", expected));
+    }
+
+    #[test]
+    fn stack_complex_generation() {
+        let input: Matrix = syn::parse_quote![
+            a, 0, b;
+            0, c, d;
+            e, 0, 0;
+        ];
+
+        let result = stack_impl(input).unwrap();
+
+        let expected = quote! {{
+            let ref ___na_stack_0_0_block = a;
+            let ___na_stack_0_0_shape = ___na_stack_0_0_block.shape_generic();
+            let ref ___na_stack_0_2_block = b;
+            let ___na_stack_0_2_shape = ___na_stack_0_2_block.shape_generic();
+            let ref ___na_stack_1_1_block = c;
+            let ___na_stack_1_1_shape = ___na_stack_1_1_block.shape_generic();
+            let ref ___na_stack_1_2_block = d;
+            let ___na_stack_1_2_shape = ___na_stack_1_2_block.shape_generic();
+            let ref ___na_stack_2_0_block = e;
+            let ___na_stack_2_0_shape = ___na_stack_2_0_block.shape_generic();
+            let ___na_stack_row_0_dim = < nalgebra :: constraint :: ShapeConstraint as nalgebra :: constraint :: SameNumberOfRows < _ , _ >> :: representative (___na_stack_0_0_shape . 0 , ___na_stack_0_2_shape . 0) . expect ("All blocks in block row 0 must have the same number of rows") ;
+            let ___na_stack_row_0_offset = 0;
+            let ___na_stack_row_1_dim = < nalgebra :: constraint :: ShapeConstraint as nalgebra :: constraint :: SameNumberOfRows < _ , _ >> :: representative (___na_stack_1_1_shape . 0 , ___na_stack_1_2_shape . 0) . expect ("All blocks in block row 1 must have the same number of rows") ;
+            let ___na_stack_row_1_offset = ___na_stack_row_0_offset + <_ as nalgebra::Dim>::value(&___na_stack_row_0_dim);
+            let ___na_stack_row_2_dim = ___na_stack_2_0_shape.0;
+            let ___na_stack_row_2_offset = ___na_stack_row_1_offset + <_ as nalgebra::Dim>::value(&___na_stack_row_1_dim);
+            let ___na_stack_col_0_dim = < nalgebra :: constraint :: ShapeConstraint as nalgebra :: constraint :: SameNumberOfColumns < _ , _ >> :: representative (___na_stack_0_0_shape . 1 , ___na_stack_2_0_shape . 1) . expect ("All blocks in block column 0 must have the same number of columns") ;
+            let ___na_stack_col_0_offset = 0;
+            let ___na_stack_col_1_dim = ___na_stack_1_1_shape.1;
+            let ___na_stack_col_1_offset = ___na_stack_col_0_offset + <_ as nalgebra::Dim>::value(&___na_stack_col_0_dim);
+            let ___na_stack_col_2_dim = < nalgebra :: constraint :: ShapeConstraint as nalgebra :: constraint :: SameNumberOfColumns < _ , _ >> :: representative (___na_stack_0_2_shape . 1 , ___na_stack_1_2_shape . 1) . expect ("All blocks in block column 2 must have the same number of columns") ;
+            let ___na_stack_col_2_offset = ___na_stack_col_1_offset + <_ as nalgebra::Dim>::value(&___na_stack_col_1_dim);
+            let mut matrix = nalgebra::Matrix::zeros_generic(
+                <_ as nalgebra::DimAdd<_>>::add(
+                    <_ as nalgebra::DimAdd<_>>::add(___na_stack_row_0_dim, ___na_stack_row_1_dim),
+                    ___na_stack_row_2_dim
+                ),
+                <_ as nalgebra::DimAdd<_>>::add(
+                    <_ as nalgebra::DimAdd<_>>::add(___na_stack_col_0_dim, ___na_stack_col_1_dim),
+                    ___na_stack_col_2_dim
+                )
+            );
+            let start = (___na_stack_row_0_offset, ___na_stack_col_0_offset);
+            let shape = (___na_stack_row_0_dim, ___na_stack_col_0_dim);
+            let input_view = ___na_stack_0_0_block.generic_view((0,0), shape);
+            let mut output_view = matrix.generic_view_mut(start, shape);
+            output_view.copy_from(&input_view);
+            let start = (___na_stack_row_0_offset, ___na_stack_col_2_offset);
+            let shape = (___na_stack_row_0_dim, ___na_stack_col_2_dim);
+            let input_view = ___na_stack_0_2_block.generic_view((0,0), shape);
+            let mut output_view = matrix.generic_view_mut(start, shape);
+            output_view.copy_from(&input_view);
+            let start = (___na_stack_row_1_offset, ___na_stack_col_1_offset);
+            let shape = (___na_stack_row_1_dim, ___na_stack_col_1_dim);
+            let input_view = ___na_stack_1_1_block.generic_view((0,0), shape);
+            let mut output_view = matrix.generic_view_mut(start, shape);
+            output_view.copy_from(&input_view);
+            let start = (___na_stack_row_1_offset, ___na_stack_col_2_offset);
+            let shape = (___na_stack_row_1_dim, ___na_stack_col_2_dim);
+            let input_view = ___na_stack_1_2_block.generic_view((0,0), shape);
+            let mut output_view = matrix.generic_view_mut(start, shape);
+            output_view.copy_from(&input_view);
+            let start = (___na_stack_row_2_offset, ___na_stack_col_0_offset);
+            let shape = (___na_stack_row_2_dim, ___na_stack_col_0_dim);
+            let input_view = ___na_stack_2_0_block.generic_view((0,0), shape);
+            let mut output_view = matrix.generic_view_mut(start, shape);
+            output_view.copy_from(&input_view);
+            matrix
+        }};
+
+        assert_eq!(format!("{result}"), format!("{}", expected));
+    }
+}

nalgebra-sparse/Cargo.toml

@@ -1,44 +1,44 @@
 [package]
 name = "nalgebra-sparse"
-version = "0.9.0"
-authors = [ "Andreas Longva", "Sébastien Crozet <developer@crozet.re>" ]
+version = "0.10.0"
+authors = ["Andreas Longva", "Sébastien Crozet <developer@crozet.re>"]
 edition = "2018"
 description = "Sparse matrix computation based on nalgebra."
 documentation = "https://www.nalgebra.org/docs"
 homepage = "https://nalgebra.org"
 repository = "https://github.com/dimforge/nalgebra"
 readme = "../README.md"
-categories = [ "science", "mathematics", "wasm", "no-std" ]
-keywords = [ "linear", "algebra", "matrix", "vector", "math" ]
+categories = ["science", "mathematics", "wasm", "no-std"]
+keywords = ["linear", "algebra", "matrix", "vector", "math"]
 license = "Apache-2.0"
 
 [features]
 proptest-support = ["proptest", "nalgebra/proptest-support"]
-compare = [ "matrixcompare-core" ]
-serde-serialize = [ "serde/std" ]
+compare = ["matrixcompare-core"]
+serde-serialize = ["serde/std"]
 
 # Enable matrix market I/O
-io      = [ "pest", "pest_derive" ]
+io = ["pest", "pest_derive"]
 
 # Enable to enable running some tests that take a lot of time to run
 slow-tests = []
 
 [dependencies]
-nalgebra = { version="0.32", path = "../" }
+nalgebra = { version = "0.33", path = "../" }
 num-traits = { version = "0.2", default-features = false }
 proptest = { version = "1.0", optional = true }
 matrixcompare-core = { version = "0.1.0", optional = true }
-pest           = { version = "2", optional = true }
-pest_derive    = { version = "2", optional = true }
-serde = { version = "1.0", default-features = false, features = [ "derive" ], optional = true }
+pest = { version = "2", optional = true }
+pest_derive = { version = "2", optional = true }
+serde = { version = "1.0", default-features = false, features = ["derive"], optional = true }
 
 [dev-dependencies]
-itertools = "0.10"
-matrixcompare = { version = "0.3.0", features = [ "proptest-support" ] }
-nalgebra = { version="0.32", path = "../", features = ["compare"] }
+itertools = "0.13"
+matrixcompare = { version = "0.3.0", features = ["proptest-support"] }
+nalgebra = { version = "0.33", path = "../", features = ["compare"] }
 tempfile = "3.3"
 serde_json = "1.0"
 
 [package.metadata.docs.rs]
 # Enable certain features when building docs for docs.rs
-features = [ "proptest-support", "compare", "io"]
+features = ["proptest-support", "compare", "io"]

nalgebra-sparse/LICENSE

@@ -0,0 +1 @@
+../LICENSE

nalgebra-sparse/src/convert/impl_std_ops.rs

@@ -3,7 +3,7 @@ use crate::coo::CooMatrix;
 use crate::csc::CscMatrix;
 use crate::csr::CsrMatrix;
 use nalgebra::storage::RawStorage;
-use nalgebra::{ClosedAdd, DMatrix, Dim, Matrix, Scalar};
+use nalgebra::{ClosedAddAssign, DMatrix, Dim, Matrix, Scalar};
 use num_traits::Zero;
 
 impl<'a, T, R, C, S> From<&'a Matrix<T, R, C, S>> for CooMatrix<T>
@@ -20,7 +20,7 @@ where
 
 impl<'a, T> From<&'a CooMatrix<T>> for DMatrix<T>
 where
-    T: Scalar + Zero + ClosedAdd,
+    T: Scalar + Zero + ClosedAddAssign,
 {
     fn from(coo: &'a CooMatrix<T>) -> Self {
         convert_coo_dense(coo)
@@ -29,7 +29,7 @@ where
 
 impl<'a, T> From<&'a CooMatrix<T>> for CsrMatrix<T>
 where
-    T: Scalar + Zero + ClosedAdd,
+    T: Scalar + Zero + ClosedAddAssign,
 {
     fn from(matrix: &'a CooMatrix<T>) -> Self {
         convert_coo_csr(matrix)
@@ -38,7 +38,7 @@ where
 
 impl<'a, T> From<&'a CsrMatrix<T>> for CooMatrix<T>
 where
-    T: Scalar + Zero + ClosedAdd,
+    T: Scalar + Zero + ClosedAddAssign,
 {
     fn from(matrix: &'a CsrMatrix<T>) -> Self {
         convert_csr_coo(matrix)
@@ -59,7 +59,7 @@ where
 
 impl<'a, T> From<&'a CsrMatrix<T>> for DMatrix<T>
 where
-    T: Scalar + Zero + ClosedAdd,
+    T: Scalar + Zero + ClosedAddAssign,
 {
     fn from(matrix: &'a CsrMatrix<T>) -> Self {
         convert_csr_dense(matrix)
@@ -68,7 +68,7 @@ where
 
 impl<'a, T> From<&'a CooMatrix<T>> for CscMatrix<T>
 where
-    T: Scalar + Zero + ClosedAdd,
+    T: Scalar + Zero + ClosedAddAssign,
 {
     fn from(matrix: &'a CooMatrix<T>) -> Self {
         convert_coo_csc(matrix)
@@ -98,7 +98,7 @@ where
 
 impl<'a, T> From<&'a CscMatrix<T>> for DMatrix<T>
 where
-    T: Scalar + Zero + ClosedAdd,
+    T: Scalar + Zero + ClosedAddAssign,
 {
     fn from(matrix: &'a CscMatrix<T>) -> Self {
         convert_csc_dense(matrix)

nalgebra-sparse/src/convert/serial.rs

@@ -8,7 +8,7 @@ use std::ops::Add;
 use num_traits::Zero;
 
 use nalgebra::storage::RawStorage;
-use nalgebra::{ClosedAdd, DMatrix, Dim, Matrix, Scalar};
+use nalgebra::{ClosedAddAssign, DMatrix, Dim, Matrix, Scalar};
 
 use crate::coo::CooMatrix;
 use crate::cs;
@@ -41,7 +41,7 @@ where
 /// Converts a [`CooMatrix`] to a dense matrix.
 pub fn convert_coo_dense<T>(coo: &CooMatrix<T>) -> DMatrix<T>
 where
-    T: Scalar + Zero + ClosedAdd,
+    T: Scalar + Zero + ClosedAddAssign,
 {
     let mut output = DMatrix::repeat(coo.nrows(), coo.ncols(), T::zero());
     for (i, j, v) in coo.triplet_iter() {
@@ -80,7 +80,7 @@ pub fn convert_csr_coo<T: Scalar>(csr: &CsrMatrix<T>) -> CooMatrix<T> {
 /// Converts a [`CsrMatrix`] to a dense matrix.
 pub fn convert_csr_dense<T>(csr: &CsrMatrix<T>) -> DMatrix<T>
 where
-    T: Scalar + ClosedAdd + Zero,
+    T: Scalar + ClosedAddAssign + Zero,
 {
     let mut output = DMatrix::zeros(csr.nrows(), csr.ncols());
 
@@ -157,7 +157,7 @@ where
 /// Converts a [`CscMatrix`] to a dense matrix.
 pub fn convert_csc_dense<T>(csc: &CscMatrix<T>) -> DMatrix<T>
 where
-    T: Scalar + ClosedAdd + Zero,
+    T: Scalar + ClosedAddAssign + Zero,
 {
     let mut output = DMatrix::zeros(csc.nrows(), csc.ncols());
 
@@ -306,7 +306,7 @@ where
             |val| sorted_vals.push(val),
             &idx_workspace[..count],
             &values_workspace[..count],
-            &Add::add,
+            Add::add,
         );
 
         let new_col_count = sorted_minor_idx.len() - sorted_ja_current_len;

nalgebra-sparse/src/coo.rs

@@ -160,6 +160,25 @@ impl<T> CooMatrix<T> {
         }
     }
 
+    /// Try to construct a COO matrix from the given dimensions and a finite iterator of
+    /// (i, j, v) triplets.
+    ///
+    /// Returns an error if either row or column indices contain indices out of bounds.
+    /// Note that the COO format inherently supports duplicate entries, but they are not
+    /// eagerly summed.
+    ///
+    /// Implementation note:
+    /// Calls try_from_triplets so each value is scanned twice.
+    pub fn try_from_triplets_iter(
+        nrows: usize,
+        ncols: usize,
+        triplets: impl IntoIterator<Item = (usize, usize, T)>,
+    ) -> Result<Self, SparseFormatError> {
+        let (row_indices, (col_indices, values)) =
+            triplets.into_iter().map(|(r, c, v)| (r, (c, v))).unzip();
+        Self::try_from_triplets(nrows, ncols, row_indices, col_indices, values)
+    }
+
     /// An iterator over triplets (i, j, v).
     // TODO: Consider giving the iterator a concrete type instead of impl trait...?
     pub fn triplet_iter(&self) -> impl Iterator<Item = (usize, usize, &T)> {

nalgebra-sparse/src/cs.rs

@@ -1,4 +1,3 @@
-use std::mem::replace;
 use std::ops::Range;
 
 use num_traits::One;
@@ -226,6 +225,15 @@ impl<T> CsMatrix<T> {
     }
 }
 
+impl<T> Default for CsMatrix<T> {
+    fn default() -> Self {
+        Self {
+            sparsity_pattern: Default::default(),
+            values: vec![],
+        }
+    }
+}
+
 impl<T: Scalar + One> CsMatrix<T> {
     #[inline]
     pub fn identity(n: usize) -> Self {
@@ -360,7 +368,7 @@ where
         if let Some(minor_indices) = lane {
             let count = minor_indices.len();
 
-            let remaining = replace(&mut self.remaining_values, &mut []);
+            let remaining = std::mem::take(&mut self.remaining_values);
             let (values_in_lane, remaining) = remaining.split_at_mut(count);
             self.remaining_values = remaining;
             self.current_lane_idx += 1;
@@ -569,7 +577,7 @@ where
     } else if sort {
         unreachable!("Internal error: Sorting currently not supported if no values are present.");
     }
-    if major_offsets.len() == 0 {
+    if major_offsets.is_empty() {
         return Err(SparseFormatError::from_kind_and_msg(
             SparseFormatErrorKind::InvalidStructure,
             "Number of offsets should be greater than 0.",
@@ -615,12 +623,12 @@ where
                 ));
             }
 
-            let minor_idx_in_lane = minor_indices.get(range_start..range_end).ok_or(
+            let minor_idx_in_lane = minor_indices.get(range_start..range_end).ok_or_else(|| {
                 SparseFormatError::from_kind_and_msg(
                     SparseFormatErrorKind::IndexOutOfBounds,
                     "A major offset is out of bounds.",
-                ),
-            )?;
+                )
+            })?;
 
             // We test for in-bounds, uniqueness and monotonicity at the same time
             // to ensure that we only visit each minor index once
@@ -653,9 +661,9 @@ where
             if !monotonic && sort {
                 let range_size = range_end - range_start;
                 minor_index_permutation.resize(range_size, 0);
-                compute_sort_permutation(&mut minor_index_permutation, &minor_idx_in_lane);
+                compute_sort_permutation(&mut minor_index_permutation, minor_idx_in_lane);
                 minor_idx_buffer.clear();
-                minor_idx_buffer.extend_from_slice(&minor_idx_in_lane);
+                minor_idx_buffer.extend_from_slice(minor_idx_in_lane);
                 apply_permutation(
                     &mut minor_indices[range_start..range_end],
                     &minor_idx_buffer,

nalgebra-sparse/src/csc.rs

@@ -158,7 +158,7 @@ impl<T> CscMatrix<T> {
     /// an error is returned to indicate the failure.
     ///
     /// An error is returned if the data given does not conform to the CSC storage format.
-    /// See the documentation for [CscMatrix](struct.CscMatrix.html) for more information.
+    /// See the documentation for [`CscMatrix`] for more information.
     pub fn try_from_csc_data(
         num_rows: usize,
         num_cols: usize,
@@ -184,7 +184,7 @@ impl<T> CscMatrix<T> {
     ///
     /// An error is returned if the data given does not conform to the CSC storage format
     /// with the exception of having unsorted row indices and values.
-    /// See the documentation for [CscMatrix](struct.CscMatrix.html) for more information.
+    /// See the documentation for [`CscMatrix`] for more information.
     pub fn try_from_unsorted_csc_data(
         num_rows: usize,
         num_cols: usize,
@@ -574,6 +574,14 @@ impl<T> CscMatrix<T> {
     }
 }
 
+impl<T> Default for CscMatrix<T> {
+    fn default() -> Self {
+        Self {
+            cs: Default::default(),
+        }
+    }
+}
+
 /// Convert pattern format errors into more meaningful CSC-specific errors.
 ///
 /// This ensures that the terminology is consistent: we are talking about rows and columns,
@@ -617,6 +625,15 @@ pub struct CscTripletIter<'a, T> {
     values_iter: Iter<'a, T>,
 }
 
+impl<'a, T> Clone for CscTripletIter<'a, T> {
+    fn clone(&self) -> Self {
+        CscTripletIter {
+            pattern_iter: self.pattern_iter.clone(),
+            values_iter: self.values_iter.clone(),
+        }
+    }
+}
+
 impl<'a, T: Clone> CscTripletIter<'a, T> {
     /// Adapts the triplet iterator to return owned values.
     ///
@@ -748,7 +765,7 @@ impl<'a, T> CscColMut<'a, T> {
     }
 }
 
-/// Column iterator for [CscMatrix](struct.CscMatrix.html).
+/// Column iterator for [`CscMatrix`].
 pub struct CscColIter<'a, T> {
     lane_iter: CsLaneIter<'a, T>,
 }
@@ -761,7 +778,7 @@ impl<'a, T> Iterator for CscColIter<'a, T> {
     }
 }
 
-/// Mutable column iterator for [CscMatrix](struct.CscMatrix.html).
+/// Mutable column iterator for [`CscMatrix`].
 pub struct CscColIterMut<'a, T> {
     lane_iter: CsLaneIterMut<'a, T>,
 }

nalgebra-sparse/src/csr.rs

@@ -159,7 +159,7 @@ impl<T> CsrMatrix<T> {
     /// an error is returned to indicate the failure.
     ///
     /// An error is returned if the data given does not conform to the CSR storage format.
-    /// See the documentation for [CsrMatrix](struct.CsrMatrix.html) for more information.
+    /// See the documentation for [`CsrMatrix`] for more information.
     pub fn try_from_csr_data(
         num_rows: usize,
         num_cols: usize,
@@ -185,7 +185,7 @@ impl<T> CsrMatrix<T> {
     ///
     /// An error is returned if the data given does not conform to the CSR storage format
     /// with the exception of having unsorted column indices and values.
-    /// See the documentation for [CsrMatrix](struct.CsrMatrix.html) for more information.
+    /// See the documentation for [`CsrMatrix`] for more information.
     pub fn try_from_unsorted_csr_data(
         num_rows: usize,
         num_cols: usize,
@@ -575,6 +575,14 @@ impl<T> CsrMatrix<T> {
     }
 }
 
+impl<T> Default for CsrMatrix<T> {
+    fn default() -> Self {
+        Self {
+            cs: Default::default(),
+        }
+    }
+}
+
 /// Convert pattern format errors into more meaningful CSR-specific errors.
 ///
 /// This ensures that the terminology is consistent: we are talking about rows and columns,
@@ -618,6 +626,15 @@ pub struct CsrTripletIter<'a, T> {
     values_iter: Iter<'a, T>,
 }
 
+impl<'a, T> Clone for CsrTripletIter<'a, T> {
+    fn clone(&self) -> Self {
+        CsrTripletIter {
+            pattern_iter: self.pattern_iter.clone(),
+            values_iter: self.values_iter.clone(),
+        }
+    }
+}
+
 impl<'a, T: Clone> CsrTripletIter<'a, T> {
     /// Adapts the triplet iterator to return owned values.
     ///
@@ -753,7 +770,7 @@ impl<'a, T> CsrRowMut<'a, T> {
     }
 }
 
-/// Row iterator for [CsrMatrix](struct.CsrMatrix.html).
+/// Row iterator for [`CsrMatrix`].
 pub struct CsrRowIter<'a, T> {
     lane_iter: CsLaneIter<'a, T>,
 }
@@ -766,7 +783,7 @@ impl<'a, T> Iterator for CsrRowIter<'a, T> {
     }
 }
 
-/// Mutable row iterator for [CsrMatrix](struct.CsrMatrix.html).
+/// Mutable row iterator for [`CsrMatrix`].
 pub struct CsrRowIterMut<'a, T> {
     lane_iter: CsLaneIterMut<'a, T>,
 }

nalgebra-sparse/src/lib.rs

@@ -199,7 +199,7 @@ impl SparseFormatError {
     }
 }
 
-/// The type of format error described by a [SparseFormatError](struct.SparseFormatError.html).
+/// The type of format error described by a [`SparseFormatError`].
 #[non_exhaustive]
 #[derive(Debug, Copy, Clone, PartialEq, Eq)]
 pub enum SparseFormatErrorKind {

nalgebra-sparse/src/ops/impl_std_ops.rs

@@ -10,8 +10,8 @@ use nalgebra::allocator::Allocator;
 use nalgebra::base::storage::RawStorage;
 use nalgebra::constraint::{DimEq, ShapeConstraint};
 use nalgebra::{
-    ClosedAdd, ClosedDiv, ClosedMul, ClosedSub, DefaultAllocator, Dim, Dyn, Matrix, OMatrix,
-    Scalar, U1,
+    ClosedAddAssign, ClosedDivAssign, ClosedMulAssign, ClosedSubAssign, DefaultAllocator, Dim, Dyn,
+    Matrix, OMatrix, Scalar, U1,
 };
 use num_traits::{One, Zero};
 use std::ops::{Add, Div, DivAssign, Mul, MulAssign, Neg, Sub};
@@ -28,7 +28,7 @@ macro_rules! impl_bin_op {
             // Note: The Neg bound is currently required because we delegate e.g.
             // Sub to SpAdd with negative coefficients. This is not well-defined for
             // unsigned data types.
-            $($scalar_type: $($bounds + )? Scalar + ClosedAdd + ClosedSub + ClosedMul + Zero + One + Neg<Output=T>)?
+            $($scalar_type: $($bounds + )? Scalar + ClosedAddAssign + ClosedSubAssign + ClosedMulAssign + Zero + One + Neg<Output=T>)?
         {
             type Output = $ret;
             fn $method(self, $b: $b_type) -> Self::Output {
@@ -59,7 +59,7 @@ macro_rules! impl_sp_plus_minus {
             let mut result = $matrix_type::try_from_pattern_and_values(pattern, values)
                 .unwrap();
             $spadd_fn(T::zero(), &mut result, T::one(), Op::NoOp(&a)).unwrap();
-            $spadd_fn(T::one(), &mut result, $factor * T::one(), Op::NoOp(&b)).unwrap();
+            $spadd_fn(T::one(), &mut result, $factor, Op::NoOp(&b)).unwrap();
             result
         });
 
@@ -164,7 +164,7 @@ macro_rules! impl_scalar_mul {
 
         impl<T> MulAssign<T> for $matrix_type<T>
         where
-            T: Scalar + ClosedAdd + ClosedMul + Zero + One
+            T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One
         {
             fn mul_assign(&mut self, scalar: T) {
                 for val in self.values_mut() {
@@ -175,7 +175,7 @@ macro_rules! impl_scalar_mul {
 
         impl<'a, T> MulAssign<&'a T> for $matrix_type<T>
         where
-            T: Scalar + ClosedAdd + ClosedMul + Zero + One
+            T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One
         {
             fn mul_assign(&mut self, scalar: &'a T) {
                 for val in self.values_mut() {
@@ -227,15 +227,15 @@ impl_neg!(CscMatrix);
 
 macro_rules! impl_div {
     ($matrix_type:ident) => {
-        impl_bin_op!(Div, div, <T: ClosedDiv>(matrix: $matrix_type<T>, scalar: T) -> $matrix_type<T> {
+        impl_bin_op!(Div, div, <T: ClosedDivAssign>(matrix: $matrix_type<T>, scalar: T) -> $matrix_type<T> {
             let mut matrix = matrix;
             matrix /= scalar;
             matrix
         });
-        impl_bin_op!(Div, div, <'a, T: ClosedDiv>(matrix: $matrix_type<T>, scalar: &T) -> $matrix_type<T> {
+        impl_bin_op!(Div, div, <'a, T: ClosedDivAssign>(matrix: $matrix_type<T>, scalar: &T) -> $matrix_type<T> {
             matrix / scalar.clone()
         });
-        impl_bin_op!(Div, div, <'a, T: ClosedDiv>(matrix: &'a $matrix_type<T>, scalar: T) -> $matrix_type<T> {
+        impl_bin_op!(Div, div, <'a, T: ClosedDivAssign>(matrix: &'a $matrix_type<T>, scalar: T) -> $matrix_type<T> {
             let new_values = matrix.values()
                 .iter()
                 .map(|v_i| v_i.clone() / scalar.clone())
@@ -243,12 +243,12 @@ macro_rules! impl_div {
             $matrix_type::try_from_pattern_and_values(matrix.pattern().clone(), new_values)
                 .unwrap()
         });
-        impl_bin_op!(Div, div, <'a, T: ClosedDiv>(matrix: &'a $matrix_type<T>, scalar: &'a T) -> $matrix_type<T> {
+        impl_bin_op!(Div, div, <'a, T: ClosedDivAssign>(matrix: &'a $matrix_type<T>, scalar: &'a T) -> $matrix_type<T> {
             matrix / scalar.clone()
         });
 
         impl<T> DivAssign<T> for $matrix_type<T>
-            where T : Scalar + ClosedAdd + ClosedMul + ClosedDiv + Zero + One
+            where T : Scalar + ClosedAddAssign + ClosedMulAssign + ClosedDivAssign + Zero + One
         {
             fn div_assign(&mut self, scalar: T) {
                 self.values_mut().iter_mut().for_each(|v_i| *v_i /= scalar.clone());
@@ -256,7 +256,7 @@ macro_rules! impl_div {
         }
 
         impl<'a, T> DivAssign<&'a T> for $matrix_type<T>
-            where T : Scalar + ClosedAdd + ClosedMul + ClosedDiv + Zero + One
+            where T : Scalar + ClosedAddAssign + ClosedMulAssign + ClosedDivAssign + Zero + One
         {
             fn div_assign(&mut self, scalar: &'a T) {
                 *self /= scalar.clone();
@@ -298,17 +298,17 @@ macro_rules! impl_spmm_cs_dense {
     {
         impl<'a, T, R, C, S> Mul<$dense_matrix_type> for $sparse_matrix_type
         where
-            T: Scalar + ClosedMul + ClosedAdd + ClosedSub + ClosedDiv + Neg + Zero + One,
+            T: Scalar + ClosedMulAssign + ClosedAddAssign + ClosedSubAssign + ClosedDivAssign + Neg + Zero + One,
             R: Dim,
             C: Dim,
             S: RawStorage<T, R, C>,
-            DefaultAllocator: Allocator<T, Dyn, C>,
+            DefaultAllocator: Allocator<Dyn, C>,
             // TODO: Is it possible to simplify these bounds?
             ShapeConstraint:
                 // Bounds so that we can turn OMatrix<T, Dyn, C> into a DMatrixSliceMut
-                  DimEq<U1, <<DefaultAllocator as Allocator<T, Dyn, C>>::Buffer as RawStorage<T, Dyn, C>>::RStride>
+                  DimEq<U1, <<DefaultAllocator as Allocator<Dyn, C>>::Buffer<T> as RawStorage<T, Dyn, C>>::RStride>
                 + DimEq<C, Dyn>
-                + DimEq<Dyn, <<DefaultAllocator as Allocator<T, Dyn, C>>::Buffer as RawStorage<T, Dyn, C>>::CStride>
+                + DimEq<Dyn, <<DefaultAllocator as Allocator<Dyn, C>>::Buffer<T> as RawStorage<T, Dyn, C>>::CStride>
                 // Bounds so that we can turn &Matrix<T, R, C, S> into a DMatrixSlice
                 + DimEq<U1, S::RStride>
                 + DimEq<R, Dyn>

nalgebra-sparse/src/ops/mod.rs

@@ -149,8 +149,8 @@ impl<T> Op<T> {
     #[must_use]
     pub fn as_ref(&self) -> Op<&T> {
         match self {
-            Op::NoOp(obj) => Op::NoOp(&obj),
-            Op::Transpose(obj) => Op::Transpose(&obj),
+            Op::NoOp(obj) => Op::NoOp(obj),
+            Op::Transpose(obj) => Op::Transpose(obj),
         }
     }
 

nalgebra-sparse/src/ops/serial/cs.rs

@@ -2,7 +2,7 @@ use crate::cs::CsMatrix;
 use crate::ops::serial::{OperationError, OperationErrorKind};
 use crate::ops::Op;
 use crate::SparseEntryMut;
-use nalgebra::{ClosedAdd, ClosedMul, DMatrixView, DMatrixViewMut, Scalar};
+use nalgebra::{ClosedAddAssign, ClosedMulAssign, DMatrixView, DMatrixViewMut, Scalar};
 use num_traits::{One, Zero};
 
 fn spmm_cs_unexpected_entry() -> OperationError {
@@ -28,7 +28,7 @@ pub fn spmm_cs_prealloc_unchecked<T>(
     b: &CsMatrix<T>,
 ) -> Result<(), OperationError>
 where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     assert_eq!(c.pattern().major_dim(), a.pattern().major_dim());
     assert_eq!(c.pattern().minor_dim(), b.pattern().minor_dim());
@@ -73,7 +73,7 @@ pub fn spmm_cs_prealloc<T>(
     b: &CsMatrix<T>,
 ) -> Result<(), OperationError>
 where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     for i in 0..c.pattern().major_dim() {
         let a_lane_i = a.get_lane(i).unwrap();
@@ -119,7 +119,7 @@ pub fn spadd_cs_prealloc<T>(
     a: Op<&CsMatrix<T>>,
 ) -> Result<(), OperationError>
 where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     match a {
         Op::NoOp(a) => {
@@ -181,7 +181,7 @@ pub fn spmm_cs_dense<T>(
     a: Op<&CsMatrix<T>>,
     b: Op<DMatrixView<'_, T>>,
 ) where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     match a {
         Op::NoOp(a) => {

nalgebra-sparse/src/ops/serial/csc.rs

@@ -4,7 +4,7 @@ use crate::ops::serial::cs::{
 };
 use crate::ops::serial::{OperationError, OperationErrorKind};
 use crate::ops::Op;
-use nalgebra::{ClosedAdd, ClosedMul, DMatrixView, DMatrixViewMut, RealField, Scalar};
+use nalgebra::{ClosedAddAssign, ClosedMulAssign, DMatrixView, DMatrixViewMut, RealField, Scalar};
 use num_traits::{One, Zero};
 
 use std::borrow::Cow;
@@ -21,7 +21,7 @@ pub fn spmm_csc_dense<'a, T>(
     a: Op<&CscMatrix<T>>,
     b: Op<impl Into<DMatrixView<'a, T>>>,
 ) where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     let b = b.convert();
     spmm_csc_dense_(beta, c.into(), alpha, a, b)
@@ -34,7 +34,7 @@ fn spmm_csc_dense_<T>(
     a: Op<&CscMatrix<T>>,
     b: Op<DMatrixView<'_, T>>,
 ) where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     assert_compatible_spmm_dims!(c, a, b);
     // Need to interpret matrix as transposed since the spmm_cs_dense function assumes CSR layout
@@ -57,7 +57,7 @@ pub fn spadd_csc_prealloc<T>(
     a: Op<&CscMatrix<T>>,
 ) -> Result<(), OperationError>
 where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     assert_compatible_spadd_dims!(c, a);
     spadd_cs_prealloc(beta, &mut c.cs, alpha, a.map_same_op(|a| &a.cs))
@@ -81,14 +81,14 @@ pub fn spmm_csc_prealloc<T>(
     b: Op<&CscMatrix<T>>,
 ) -> Result<(), OperationError>
 where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     assert_compatible_spmm_dims!(c, a, b);
 
     use Op::NoOp;
 
     match (&a, &b) {
-        (NoOp(ref a), NoOp(ref b)) => {
+        (NoOp(a), NoOp(b)) => {
             // Note: We have to reverse the order for CSC matrices
             spmm_cs_prealloc(beta, &mut c.cs, alpha, &b.cs, &a.cs)
         }
@@ -109,14 +109,14 @@ pub fn spmm_csc_prealloc_unchecked<T>(
     b: Op<&CscMatrix<T>>,
 ) -> Result<(), OperationError>
 where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     assert_compatible_spmm_dims!(c, a, b);
 
     use Op::NoOp;
 
     match (&a, &b) {
-        (NoOp(ref a), NoOp(ref b)) => {
+        (NoOp(a), NoOp(b)) => {
             // Note: We have to reverse the order for CSC matrices
             spmm_cs_prealloc_unchecked(beta, &mut c.cs, alpha, &b.cs, &a.cs)
         }
@@ -133,7 +133,7 @@ fn spmm_csc_transposed<T, F>(
     spmm_kernel: F,
 ) -> Result<(), OperationError>
 where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
     F: Fn(
         T,
         &mut CscMatrix<T>,
@@ -152,9 +152,9 @@ where
         use Cow::*;
         match (&a, &b) {
             (NoOp(_), NoOp(_)) => unreachable!(),
-            (Transpose(ref a), NoOp(_)) => (Owned(a.transpose()), Borrowed(b_ref)),
-            (NoOp(_), Transpose(ref b)) => (Borrowed(a_ref), Owned(b.transpose())),
-            (Transpose(ref a), Transpose(ref b)) => (Owned(a.transpose()), Owned(b.transpose())),
+            (Transpose(a), NoOp(_)) => (Owned(a.transpose()), Borrowed(b_ref)),
+            (NoOp(_), Transpose(b)) => (Borrowed(a_ref), Owned(b.transpose())),
+            (Transpose(a), Transpose(b)) => (Owned(a.transpose()), Owned(b.transpose())),
         }
     };
     spmm_kernel(beta, c, alpha, NoOp(a.as_ref()), NoOp(b.as_ref()))

nalgebra-sparse/src/ops/serial/csr.rs

@@ -4,7 +4,7 @@ use crate::ops::serial::cs::{
 };
 use crate::ops::serial::OperationError;
 use crate::ops::Op;
-use nalgebra::{ClosedAdd, ClosedMul, DMatrixView, DMatrixViewMut, Scalar};
+use nalgebra::{ClosedAddAssign, ClosedMulAssign, DMatrixView, DMatrixViewMut, Scalar};
 use num_traits::{One, Zero};
 use std::borrow::Cow;
 
@@ -16,7 +16,7 @@ pub fn spmm_csr_dense<'a, T>(
     a: Op<&CsrMatrix<T>>,
     b: Op<impl Into<DMatrixView<'a, T>>>,
 ) where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     let b = b.convert();
     spmm_csr_dense_(beta, c.into(), alpha, a, b)
@@ -29,7 +29,7 @@ fn spmm_csr_dense_<T>(
     a: Op<&CsrMatrix<T>>,
     b: Op<DMatrixView<'_, T>>,
 ) where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     assert_compatible_spmm_dims!(c, a, b);
     spmm_cs_dense(beta, c, alpha, a.map_same_op(|a| &a.cs), b)
@@ -52,7 +52,7 @@ pub fn spadd_csr_prealloc<T>(
     a: Op<&CsrMatrix<T>>,
 ) -> Result<(), OperationError>
 where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     assert_compatible_spadd_dims!(c, a);
     spadd_cs_prealloc(beta, &mut c.cs, alpha, a.map_same_op(|a| &a.cs))
@@ -75,14 +75,14 @@ pub fn spmm_csr_prealloc<T>(
     b: Op<&CsrMatrix<T>>,
 ) -> Result<(), OperationError>
 where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     assert_compatible_spmm_dims!(c, a, b);
 
     use Op::NoOp;
 
     match (&a, &b) {
-        (NoOp(ref a), NoOp(ref b)) => spmm_cs_prealloc(beta, &mut c.cs, alpha, &a.cs, &b.cs),
+        (NoOp(a), NoOp(b)) => spmm_cs_prealloc(beta, &mut c.cs, alpha, &a.cs, &b.cs),
         _ => spmm_csr_transposed(beta, c, alpha, a, b, spmm_csr_prealloc),
     }
 }
@@ -100,16 +100,14 @@ pub fn spmm_csr_prealloc_unchecked<T>(
     b: Op<&CsrMatrix<T>>,
 ) -> Result<(), OperationError>
 where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
 {
     assert_compatible_spmm_dims!(c, a, b);
 
     use Op::NoOp;
 
     match (&a, &b) {
-        (NoOp(ref a), NoOp(ref b)) => {
-            spmm_cs_prealloc_unchecked(beta, &mut c.cs, alpha, &a.cs, &b.cs)
-        }
+        (NoOp(a), NoOp(b)) => spmm_cs_prealloc_unchecked(beta, &mut c.cs, alpha, &a.cs, &b.cs),
         _ => spmm_csr_transposed(beta, c, alpha, a, b, spmm_csr_prealloc_unchecked),
     }
 }
@@ -123,7 +121,7 @@ fn spmm_csr_transposed<T, F>(
     spmm_kernel: F,
 ) -> Result<(), OperationError>
 where
-    T: Scalar + ClosedAdd + ClosedMul + Zero + One,
+    T: Scalar + ClosedAddAssign + ClosedMulAssign + Zero + One,
     F: Fn(
         T,
         &mut CsrMatrix<T>,
@@ -142,9 +140,9 @@ where
         use Cow::*;
         match (&a, &b) {
             (NoOp(_), NoOp(_)) => unreachable!(),
-            (Transpose(ref a), NoOp(_)) => (Owned(a.transpose()), Borrowed(b_ref)),
-            (NoOp(_), Transpose(ref b)) => (Borrowed(a_ref), Owned(b.transpose())),
-            (Transpose(ref a), Transpose(ref b)) => (Owned(a.transpose()), Owned(b.transpose())),
+            (Transpose(a), NoOp(_)) => (Owned(a.transpose()), Borrowed(b_ref)),
+            (NoOp(_), Transpose(b)) => (Borrowed(a_ref), Owned(b.transpose())),
+            (Transpose(a), Transpose(b)) => (Owned(a.transpose()), Owned(b.transpose())),
         }
     };
     spmm_kernel(beta, c, alpha, NoOp(a.as_ref()), NoOp(b.as_ref()))

nalgebra-sparse/src/ops/serial/pattern.rs

@@ -125,18 +125,22 @@ fn iterate_union<'a>(
 ) -> impl Iterator<Item = usize> + 'a {
     iter::from_fn(move || {
         if let (Some(a_item), Some(b_item)) = (sorted_a.first(), sorted_b.first()) {
-            let item = if a_item < b_item {
-                sorted_a = &sorted_a[1..];
-                a_item
-            } else if b_item < a_item {
-                sorted_b = &sorted_b[1..];
-                b_item
-            } else {
-                // Both lists contain the same element, advance both slices to avoid
-                // duplicate entries in the result
-                sorted_a = &sorted_a[1..];
-                sorted_b = &sorted_b[1..];
-                a_item
+            let item = match a_item.cmp(b_item) {
+                std::cmp::Ordering::Less => {
+                    sorted_a = &sorted_a[1..];
+                    a_item
+                }
+                std::cmp::Ordering::Greater => {
+                    sorted_b = &sorted_b[1..];
+                    b_item
+                }
+                std::cmp::Ordering::Equal => {
+                    // Both lists contain the same element, advance both slices to avoid
+                    // duplicate entries in the result
+                    sorted_a = &sorted_a[1..];
+                    sorted_b = &sorted_b[1..];
+                    a_item
+                }
             };
             Some(*item)
         } else if let Some(a_item) = sorted_a.first() {

nalgebra-sparse/src/pattern.rs

@@ -80,7 +80,7 @@ impl SparsityPattern {
     #[inline]
     #[must_use]
     pub fn major_dim(&self) -> usize {
-        assert!(self.major_offsets.len() > 0);
+        assert!(!self.major_offsets.is_empty());
         self.major_offsets.len() - 1
     }
 
@@ -162,7 +162,7 @@ impl SparsityPattern {
                 // We test for in-bounds, uniqueness and monotonicity at the same time
                 // to ensure that we only visit each minor index once
                 let mut iter = minor_indices.iter();
-                let mut prev = None;
+                let mut prev: Option<usize> = None;
 
                 while let Some(next) = iter.next().copied() {
                     if next >= minor_dim {
@@ -170,10 +170,10 @@ impl SparsityPattern {
                     }
 
                     if let Some(prev) = prev {
-                        if prev > next {
-                            return Err(NonmonotonicMinorIndices);
-                        } else if prev == next {
-                            return Err(DuplicateEntry);
+                        match prev.cmp(&next) {
+                            std::cmp::Ordering::Greater => return Err(NonmonotonicMinorIndices),
+                            std::cmp::Ordering::Equal => return Err(DuplicateEntry),
+                            std::cmp::Ordering::Less => {}
                         }
                     }
                     prev = Some(next);
@@ -195,6 +195,14 @@ impl SparsityPattern {
     ///
     /// Panics if the number of major offsets is not exactly one greater than the major dimension
     /// or if major offsets do not start with 0 and end with the number of minor indices.
+    ///
+    /// # Safety
+    ///
+    /// Assumes that the major offsets and indices adhere to the requirements of being a valid
+    /// sparsity pattern.
+    /// Specifically, that major offsets is monotonically increasing, and
+    /// `major_offsets[i]..major_offsets[i+1]` refers to a major lane in the sparsity pattern,
+    /// and `minor_indices[major_offsets[i]..major_offsets[i+1]]` is monotonically increasing.
     pub unsafe fn from_offset_and_indices_unchecked(
         major_dim: usize,
         minor_dim: usize,
@@ -291,6 +299,16 @@ impl SparsityPattern {
     }
 }
 
+impl Default for SparsityPattern {
+    fn default() -> Self {
+        Self {
+            major_offsets: vec![0],
+            minor_indices: vec![],
+            minor_dim: 0,
+        }
+    }
+}
+
 /// Error type for `SparsityPattern` format errors.
 #[non_exhaustive]
 #[derive(Copy, Clone, Debug, PartialEq, Eq)]

nalgebra-sparse/tests/unit_tests/coo.rs

@@ -184,6 +184,31 @@ fn coo_try_from_triplets_reports_out_of_bounds_indices() {
     }
 }
 
+#[test]
+fn coo_try_from_triplets_iter() {
+    // Check that try_from_triplets_iter panics when the triplet vectors have different lengths
+    macro_rules! assert_errs {
+        ($result:expr) => {
+            assert!(matches!(
+                $result.unwrap_err().kind(),
+                SparseFormatErrorKind::IndexOutOfBounds
+            ))
+        };
+    }
+
+    assert_errs!(CooMatrix::<f32>::try_from_triplets_iter(
+        3,
+        5,
+        vec![(0, 6, 3.0)].into_iter(),
+    ));
+    assert!(CooMatrix::<f32>::try_from_triplets_iter(
+        3,
+        5,
+        vec![(0, 3, 3.0), (1, 2, 2.0), (0, 3, 1.0),].into_iter(),
+    )
+    .is_ok());
+}
+
 #[test]
 fn coo_try_from_triplets_panics_on_mismatched_vectors() {
     // Check that try_from_triplets panics when the triplet vectors have different lengths

nalgebra-sparse/tests/unit_tests/csc.rs

@@ -12,6 +12,18 @@ use crate::common::csc_strategy;
 
 use std::collections::HashSet;
 
+#[test]
+fn csc_matrix_default() {
+    let matrix: CscMatrix<f32> = CscMatrix::default();
+
+    assert_eq!(matrix.nrows(), 0);
+    assert_eq!(matrix.ncols(), 0);
+    assert_eq!(matrix.nnz(), 0);
+
+    assert_eq!(matrix.values(), &[]);
+    assert!(matrix.get_entry(0, 0).is_none());
+}
+
 #[test]
 fn csc_matrix_valid_data() {
     // Construct matrix from valid data and check that selected methods return results

nalgebra-sparse/tests/unit_tests/csr.rs

@@ -12,6 +12,18 @@ use crate::common::csr_strategy;
 
 use std::collections::HashSet;
 
+#[test]
+fn csr_matrix_default() {
+    let matrix: CsrMatrix<f32> = CsrMatrix::default();
+
+    assert_eq!(matrix.nrows(), 0);
+    assert_eq!(matrix.ncols(), 0);
+    assert_eq!(matrix.nnz(), 0);
+
+    assert_eq!(matrix.values(), &[]);
+    assert!(matrix.get_entry(0, 0).is_none());
+}
+
 #[test]
 fn csr_matrix_valid_data() {
     // Construct matrix from valid data and check that selected methods return results

nalgebra-sparse/tests/unit_tests/pattern.rs

@@ -1,5 +1,19 @@
 use nalgebra_sparse::pattern::{SparsityPattern, SparsityPatternFormatError};
 
+#[test]
+fn sparsity_pattern_default() {
+    // Check that the pattern created with `Default::default()` is equivalent to a zero-sized pattern.
+    let pattern = SparsityPattern::default();
+    let zero = SparsityPattern::zeros(0, 0);
+
+    assert_eq!(pattern.major_dim(), zero.major_dim());
+    assert_eq!(pattern.minor_dim(), zero.minor_dim());
+    assert_eq!(pattern.major_offsets(), zero.major_offsets());
+    assert_eq!(pattern.minor_indices(), zero.minor_indices());
+
+    assert_eq!(pattern.nnz(), 0);
+}
+
 #[test]
 fn sparsity_pattern_valid_data() {
     // Construct pattern from valid data and check that selected methods return results

src/base/alias_view.rs

@@ -10,285 +10,429 @@ use crate::base::{Const, Matrix};
  *
  */
 // NOTE: we can't provide defaults for the strides because it's not supported yet by min_const_generics.
-/// A column-major matrix view with dimensions known at compile-time.
+/// An immutable column-major matrix view with dimensions known at compile-time.
+///
+/// See [`SMatrixViewMut`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type SMatrixView<'a, T, const R: usize, const C: usize> =
     Matrix<T, Const<R>, Const<C>, ViewStorage<'a, T, Const<R>, Const<C>, Const<1>, Const<R>>>;
 
-/// A column-major matrix view dynamic numbers of rows and columns.
+/// An immutable column-major matrix view dynamic numbers of rows and columns.
+///
+/// See [`DMatrixViewMut`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type DMatrixView<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, RStride, CStride>>;
 
-/// A column-major 1x1 matrix view.
+/// An immutable column-major 1x1 matrix view.
+///
+/// See [`MatrixViewMut1`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView1<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U1, ViewStorage<'a, T, U1, U1, RStride, CStride>>;
-/// A column-major 2x2 matrix view.
+/// An immutable column-major 2x2 matrix view.
+///
+/// See [`MatrixViewMut2`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView2<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U2, ViewStorage<'a, T, U2, U2, RStride, CStride>>;
-/// A column-major 3x3 matrix view.
+/// An immutable column-major 3x3 matrix view.
+///
+/// See [`MatrixViewMut3`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView3<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U3, ViewStorage<'a, T, U3, U3, RStride, CStride>>;
-/// A column-major 4x4 matrix view.
+/// An immutable column-major 4x4 matrix view.
+///
+/// See [`MatrixViewMut4`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView4<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U4, ViewStorage<'a, T, U4, U4, RStride, CStride>>;
-/// A column-major 5x5 matrix view.
+/// An immutable column-major 5x5 matrix view.
+///
+/// See [`MatrixViewMut5`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView5<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U5, ViewStorage<'a, T, U5, U5, RStride, CStride>>;
-/// A column-major 6x6 matrix view.
+/// An immutable column-major 6x6 matrix view.
+///
+/// See [`MatrixViewMut6`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView6<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, U6, ViewStorage<'a, T, U6, U6, RStride, CStride>>;
 
-/// A column-major 1x2 matrix view.
+/// An immutable column-major 1x2 matrix view.
+///
+/// See [`MatrixViewMut1x2`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView1x2<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U2, ViewStorage<'a, T, U1, U2, RStride, CStride>>;
-/// A column-major 1x3 matrix view.
+/// An immutable column-major 1x3 matrix view.
+///
+/// See [`MatrixViewMut1x3`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView1x3<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U3, ViewStorage<'a, T, U1, U3, RStride, CStride>>;
-/// A column-major 1x4 matrix view.
+/// An immutable column-major 1x4 matrix view.
+///
+/// See [`MatrixViewMut1x4`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView1x4<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U4, ViewStorage<'a, T, U1, U4, RStride, CStride>>;
-/// A column-major 1x5 matrix view.
+/// An immutable column-major 1x5 matrix view.
+///
+/// See [`MatrixViewMut1x5`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView1x5<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U5, ViewStorage<'a, T, U1, U5, RStride, CStride>>;
-/// A column-major 1x6 matrix view.
+/// An immutable column-major 1x6 matrix view.
+///
+/// See [`MatrixViewMut1x6`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView1x6<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U6, ViewStorage<'a, T, U1, U6, RStride, CStride>>;
 
-/// A column-major 2x1 matrix view.
+/// An immutable column-major 2x1 matrix view.
+///
+/// See [`MatrixViewMut2x1`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView2x1<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U1, ViewStorage<'a, T, U2, U1, RStride, CStride>>;
-/// A column-major 2x3 matrix view.
+/// An immutable column-major 2x3 matrix view.
+///
+/// See [`MatrixViewMut2x3`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView2x3<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U3, ViewStorage<'a, T, U2, U3, RStride, CStride>>;
-/// A column-major 2x4 matrix view.
+/// An immutable column-major 2x4 matrix view.
+///
+/// See [`MatrixViewMut2x4`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView2x4<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U4, ViewStorage<'a, T, U2, U4, RStride, CStride>>;
-/// A column-major 2x5 matrix view.
+/// An immutable column-major 2x5 matrix view.
+///
+/// See [`MatrixViewMut2x5`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView2x5<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U5, ViewStorage<'a, T, U2, U5, RStride, CStride>>;
-/// A column-major 2x6 matrix view.
+/// An immutable column-major 2x6 matrix view.
+///
+/// See [`MatrixViewMut2x6`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView2x6<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U6, ViewStorage<'a, T, U2, U6, RStride, CStride>>;
 
-/// A column-major 3x1 matrix view.
+/// An immutable column-major 3x1 matrix view.
+///
+/// See [`MatrixViewMut3x1`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView3x1<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U1, ViewStorage<'a, T, U3, U1, RStride, CStride>>;
-/// A column-major 3x2 matrix view.
+/// An immutable column-major 3x2 matrix view.
+///
+/// See [`MatrixViewMut3x2`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView3x2<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U2, ViewStorage<'a, T, U3, U2, RStride, CStride>>;
-/// A column-major 3x4 matrix view.
+/// An immutable column-major 3x4 matrix view.
+///
+/// See [`MatrixViewMut3x4`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView3x4<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U4, ViewStorage<'a, T, U3, U4, RStride, CStride>>;
-/// A column-major 3x5 matrix view.
+/// An immutable column-major 3x5 matrix view.
+///
+/// See [`MatrixViewMut3x5`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView3x5<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U5, ViewStorage<'a, T, U3, U5, RStride, CStride>>;
-/// A column-major 3x6 matrix view.
+/// An immutable column-major 3x6 matrix view.
+///
+/// See [`MatrixViewMut3x6`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView3x6<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U6, ViewStorage<'a, T, U3, U6, RStride, CStride>>;
 
-/// A column-major 4x1 matrix view.
+/// An immutable column-major 4x1 matrix view.
+///
+/// See [`MatrixViewMut4x1`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView4x1<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U1, ViewStorage<'a, T, U4, U1, RStride, CStride>>;
-/// A column-major 4x2 matrix view.
+/// An immutable column-major 4x2 matrix view.
+///
+/// See [`MatrixViewMut4x2`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView4x2<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U2, ViewStorage<'a, T, U4, U2, RStride, CStride>>;
-/// A column-major 4x3 matrix view.
+/// An immutable column-major 4x3 matrix view.
+///
+/// See [`MatrixViewMut4x3`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView4x3<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U3, ViewStorage<'a, T, U4, U3, RStride, CStride>>;
-/// A column-major 4x5 matrix view.
+/// An immutable column-major 4x5 matrix view.
+///
+/// See [`MatrixViewMut4x5`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView4x5<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U5, ViewStorage<'a, T, U4, U5, RStride, CStride>>;
-/// A column-major 4x6 matrix view.
+/// An immutable column-major 4x6 matrix view.
+///
+/// See [`MatrixViewMut4x6`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView4x6<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U6, ViewStorage<'a, T, U4, U6, RStride, CStride>>;
 
-/// A column-major 5x1 matrix view.
+/// An immutable column-major 5x1 matrix view.
+///
+/// See [`MatrixViewMut5x1`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView5x1<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U1, ViewStorage<'a, T, U5, U1, RStride, CStride>>;
-/// A column-major 5x2 matrix view.
+/// An immutable column-major 5x2 matrix view.
+///
+/// See [`MatrixViewMut5x2`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView5x2<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U2, ViewStorage<'a, T, U5, U2, RStride, CStride>>;
-/// A column-major 5x3 matrix view.
+/// An immutable column-major 5x3 matrix view.
+///
+/// See [`MatrixViewMut5x3`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView5x3<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U3, ViewStorage<'a, T, U5, U3, RStride, CStride>>;
-/// A column-major 5x4 matrix view.
+/// An immutable column-major 5x4 matrix view.
+///
+/// See [`MatrixViewMut5x4`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView5x4<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U4, ViewStorage<'a, T, U5, U4, RStride, CStride>>;
-/// A column-major 5x6 matrix view.
+/// An immutable column-major 5x6 matrix view.
+///
+/// See [`MatrixViewMut5x6`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView5x6<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U6, ViewStorage<'a, T, U5, U6, RStride, CStride>>;
 
-/// A column-major 6x1 matrix view.
+/// An immutable column-major 6x1 matrix view.
+///
+/// See [`MatrixViewMut6x1`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView6x1<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, U1, ViewStorage<'a, T, U6, U1, RStride, CStride>>;
-/// A column-major 6x2 matrix view.
+/// An immutable column-major 6x2 matrix view.
+///
+/// See [`MatrixViewMut6x2`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView6x2<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, U2, ViewStorage<'a, T, U6, U2, RStride, CStride>>;
-/// A column-major 6x3 matrix view.
+/// An immutable column-major 6x3 matrix view.
+///
+/// See [`MatrixViewMut6x3`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView6x3<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, U3, ViewStorage<'a, T, U6, U3, RStride, CStride>>;
-/// A column-major 6x4 matrix view.
+/// An immutable column-major 6x4 matrix view.
+///
+/// See [`MatrixViewMut6x4`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView6x4<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, U4, ViewStorage<'a, T, U6, U4, RStride, CStride>>;
-/// A column-major 6x5 matrix view.
+/// An immutable column-major 6x5 matrix view.
+///
+/// See [`MatrixViewMut6x5`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView6x5<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, U5, ViewStorage<'a, T, U6, U5, RStride, CStride>>;
 
-/// A column-major matrix view with 1 row and a number of columns chosen at runtime.
+/// An immutable column-major matrix view with 1 row and a number of columns chosen at runtime.
+///
+/// See [`MatrixViewMut1xX`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView1xX<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, Dyn, ViewStorage<'a, T, U1, Dyn, RStride, CStride>>;
-/// A column-major matrix view with 2 rows and a number of columns chosen at runtime.
+/// An immutable column-major matrix view with 2 rows and a number of columns chosen at runtime.
+///
+/// See [`MatrixViewMut2xX`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView2xX<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, Dyn, ViewStorage<'a, T, U2, Dyn, RStride, CStride>>;
-/// A column-major matrix view with 3 rows and a number of columns chosen at runtime.
+/// An immutable column-major matrix view with 3 rows and a number of columns chosen at runtime.
+///
+/// See [`MatrixViewMut3xX`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView3xX<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, Dyn, ViewStorage<'a, T, U3, Dyn, RStride, CStride>>;
-/// A column-major matrix view with 4 rows and a number of columns chosen at runtime.
+/// An immutable column-major matrix view with 4 rows and a number of columns chosen at runtime.
+///
+/// See [`MatrixViewMut4xX`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView4xX<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, Dyn, ViewStorage<'a, T, U4, Dyn, RStride, CStride>>;
-/// A column-major matrix view with 5 rows and a number of columns chosen at runtime.
+/// An immutable column-major matrix view with 5 rows and a number of columns chosen at runtime.
+///
+/// See [`MatrixViewMut5xX`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView5xX<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, Dyn, ViewStorage<'a, T, U5, Dyn, RStride, CStride>>;
-/// A column-major matrix view with 6 rows and a number of columns chosen at runtime.
+/// An immutable column-major matrix view with 6 rows and a number of columns chosen at runtime.
+///
+/// See [`MatrixViewMut6xX`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixView6xX<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, Dyn, ViewStorage<'a, T, U6, Dyn, RStride, CStride>>;
 
-/// A column-major matrix view with a number of rows chosen at runtime and 1 column.
+/// An immutable column-major matrix view with a number of rows chosen at runtime and 1 column.
+///
+/// See [`MatrixViewMutXx1`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewXx1<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U1, ViewStorage<'a, T, Dyn, U1, RStride, CStride>>;
-/// A column-major matrix view with a number of rows chosen at runtime and 2 columns.
+/// An immutable column-major matrix view with a number of rows chosen at runtime and 2 columns.
+///
+/// See [`MatrixViewMutXx2`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewXx2<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U2, ViewStorage<'a, T, Dyn, U2, RStride, CStride>>;
-/// A column-major matrix view with a number of rows chosen at runtime and 3 columns.
+/// An immutable column-major matrix view with a number of rows chosen at runtime and 3 columns.
+///
+/// See [`MatrixViewMutXx3`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewXx3<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U3, ViewStorage<'a, T, Dyn, U3, RStride, CStride>>;
-/// A column-major matrix view with a number of rows chosen at runtime and 4 columns.
+/// An immutable column-major matrix view with a number of rows chosen at runtime and 4 columns.
+///
+/// See [`MatrixViewMutXx4`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewXx4<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U4, ViewStorage<'a, T, Dyn, U4, RStride, CStride>>;
-/// A column-major matrix view with a number of rows chosen at runtime and 5 columns.
+/// An immutable column-major matrix view with a number of rows chosen at runtime and 5 columns.
+///
+/// See [`MatrixViewMutXx5`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewXx5<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U5, ViewStorage<'a, T, Dyn, U5, RStride, CStride>>;
-/// A column-major matrix view with a number of rows chosen at runtime and 6 columns.
+/// An immutable column-major matrix view with a number of rows chosen at runtime and 6 columns.
+///
+/// See [`MatrixViewMutXx6`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewXx6<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U6, ViewStorage<'a, T, Dyn, U6, RStride, CStride>>;
 
-/// A column vector view with dimensions known at compile-time.
+/// An immutable column vector view with dimensions known at compile-time.
+///
+/// See [`VectorViewMut`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorView<'a, T, D, RStride = U1, CStride = D> =
     Matrix<T, D, U1, ViewStorage<'a, T, D, U1, RStride, CStride>>;
 
-/// A column vector view with dimensions known at compile-time.
+/// An immutable column vector view with dimensions known at compile-time.
+///
+/// See [`SVectorViewMut`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type SVectorView<'a, T, const D: usize> =
     Matrix<T, Const<D>, Const<1>, ViewStorage<'a, T, Const<D>, Const<1>, Const<1>, Const<D>>>;
 
-/// A column vector view dynamic numbers of rows and columns.
+/// An immutable column vector view dynamic numbers of rows and columns.
+///
+/// See [`DVectorViewMut`] for a mutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type DVectorView<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U1, ViewStorage<'a, T, Dyn, U1, RStride, CStride>>;
 
-/// A 1D column vector view.
+/// An immutable 1D column vector view.
+///
+/// See [`VectorViewMut1`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorView1<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U1, ViewStorage<'a, T, U1, U1, RStride, CStride>>;
-/// A 2D column vector view.
+/// An immutable 2D column vector view.
+///
+/// See [`VectorViewMut2`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorView2<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U1, ViewStorage<'a, T, U2, U1, RStride, CStride>>;
-/// A 3D column vector view.
+/// An immutable 3D column vector view.
+///
+/// See [`VectorViewMut3`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorView3<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U1, ViewStorage<'a, T, U3, U1, RStride, CStride>>;
-/// A 4D column vector view.
+/// An immutable 4D column vector view.
+///
+/// See [`VectorViewMut4`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorView4<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U1, ViewStorage<'a, T, U4, U1, RStride, CStride>>;
-/// A 5D column vector view.
+/// An immutable 5D column vector view.
+///
+/// See [`VectorViewMut5`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorView5<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U1, ViewStorage<'a, T, U5, U1, RStride, CStride>>;
-/// A 6D column vector view.
+/// An immutable 6D column vector view.
+///
+/// See [`VectorViewMut6`] for a mutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorView6<'a, T, RStride = U1, CStride = U6> =
@@ -302,287 +446,429 @@ pub type VectorView6<'a, T, RStride = U1, CStride = U6> =
  *
  */
 
-/// A column-major matrix view with dimensions known at compile-time.
+/// A mutable column-major matrix view with dimensions known at compile-time.
+///
+/// See [`SMatrixView`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type SMatrixViewMut<'a, T, const R: usize, const C: usize> =
     Matrix<T, Const<R>, Const<C>, ViewStorageMut<'a, T, Const<R>, Const<C>, Const<1>, Const<R>>>;
 
-/// A column-major matrix view dynamic numbers of rows and columns.
+/// A mutable column-major matrix view dynamic numbers of rows and columns.
+///
+/// See [`DMatrixView`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type DMatrixViewMut<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, RStride, CStride>>;
 
-/// A column-major 1x1 matrix view.
+/// A mutable column-major 1x1 matrix view.
+///
+/// See [`MatrixView1`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut1<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U1, ViewStorageMut<'a, T, U1, U1, RStride, CStride>>;
-/// A column-major 2x2 matrix view.
+/// A mutable column-major 2x2 matrix view.
+///
+/// See [`MatrixView2`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut2<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U2, ViewStorageMut<'a, T, U2, U2, RStride, CStride>>;
-/// A column-major 3x3 matrix view.
+/// A mutable column-major 3x3 matrix view.
+///
+/// See [`MatrixView3`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut3<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U3, ViewStorageMut<'a, T, U3, U3, RStride, CStride>>;
-/// A column-major 4x4 matrix view.
+/// A mutable column-major 4x4 matrix view.
+///
+/// See [`MatrixView4`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut4<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U4, ViewStorageMut<'a, T, U4, U4, RStride, CStride>>;
-/// A column-major 5x5 matrix view.
+/// A mutable column-major 5x5 matrix view.
+///
+/// See [`MatrixView5`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut5<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U5, ViewStorageMut<'a, T, U5, U5, RStride, CStride>>;
-/// A column-major 6x6 matrix view.
+/// A mutable column-major 6x6 matrix view.
+///
+/// See [`MatrixView6`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut6<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, U6, ViewStorageMut<'a, T, U6, U6, RStride, CStride>>;
 
-/// A column-major 1x2 matrix view.
+/// A mutable column-major 1x2 matrix view.
+///
+/// See [`MatrixView1x2`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut1x2<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U2, ViewStorageMut<'a, T, U1, U2, RStride, CStride>>;
-/// A column-major 1x3 matrix view.
+/// A mutable column-major 1x3 matrix view.
+///
+/// See [`MatrixView1x3`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut1x3<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U3, ViewStorageMut<'a, T, U1, U3, RStride, CStride>>;
-/// A column-major 1x4 matrix view.
+/// A mutable column-major 1x4 matrix view.
+///
+/// See [`MatrixView1x4`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut1x4<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U4, ViewStorageMut<'a, T, U1, U4, RStride, CStride>>;
-/// A column-major 1x5 matrix view.
+/// A mutable column-major 1x5 matrix view.
+///
+/// See [`MatrixView1x5`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut1x5<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U5, ViewStorageMut<'a, T, U1, U5, RStride, CStride>>;
-/// A column-major 1x6 matrix view.
+/// A mutable column-major 1x6 matrix view.
+///
+/// See [`MatrixView1x6`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut1x6<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U6, ViewStorageMut<'a, T, U1, U6, RStride, CStride>>;
 
-/// A column-major 2x1 matrix view.
+/// A mutable column-major 2x1 matrix view.
+///
+/// See [`MatrixView2x1`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut2x1<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U1, ViewStorageMut<'a, T, U2, U1, RStride, CStride>>;
-/// A column-major 2x3 matrix view.
+/// A mutable column-major 2x3 matrix view.
+///
+/// See [`MatrixView2x3`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut2x3<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U3, ViewStorageMut<'a, T, U2, U3, RStride, CStride>>;
-/// A column-major 2x4 matrix view.
+/// A mutable column-major 2x4 matrix view.
+///
+/// See [`MatrixView2x4`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut2x4<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U4, ViewStorageMut<'a, T, U2, U4, RStride, CStride>>;
-/// A column-major 2x5 matrix view.
+/// A mutable column-major 2x5 matrix view.
+///
+/// See [`MatrixView2x5`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut2x5<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U5, ViewStorageMut<'a, T, U2, U5, RStride, CStride>>;
-/// A column-major 2x6 matrix view.
+/// A mutable column-major 2x6 matrix view.
+///
+/// See [`MatrixView2x6`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut2x6<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U6, ViewStorageMut<'a, T, U2, U6, RStride, CStride>>;
 
-/// A column-major 3x1 matrix view.
+/// A mutable column-major 3x1 matrix view.
+///
+/// See [`MatrixView3x1`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut3x1<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U1, ViewStorageMut<'a, T, U3, U1, RStride, CStride>>;
-/// A column-major 3x2 matrix view.
+/// A mutable column-major 3x2 matrix view.
+///
+/// See [`MatrixView3x2`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut3x2<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U2, ViewStorageMut<'a, T, U3, U2, RStride, CStride>>;
-/// A column-major 3x4 matrix view.
+/// A mutable column-major 3x4 matrix view.
+///
+/// See [`MatrixView3x4`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut3x4<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U4, ViewStorageMut<'a, T, U3, U4, RStride, CStride>>;
-/// A column-major 3x5 matrix view.
+/// A mutable column-major 3x5 matrix view.
+///
+/// See [`MatrixView3x5`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut3x5<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U5, ViewStorageMut<'a, T, U3, U5, RStride, CStride>>;
-/// A column-major 3x6 matrix view.
+/// A mutable column-major 3x6 matrix view.
+///
+/// See [`MatrixView3x6`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut3x6<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U6, ViewStorageMut<'a, T, U3, U6, RStride, CStride>>;
 
-/// A column-major 4x1 matrix view.
+/// A mutable column-major 4x1 matrix view.
+///
+/// See [`MatrixView4x1`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut4x1<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U1, ViewStorageMut<'a, T, U4, U1, RStride, CStride>>;
-/// A column-major 4x2 matrix view.
+/// A mutable column-major 4x2 matrix view.
+///
+/// See [`MatrixView4x2`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut4x2<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U2, ViewStorageMut<'a, T, U4, U2, RStride, CStride>>;
-/// A column-major 4x3 matrix view.
+/// A mutable column-major 4x3 matrix view.
+///
+/// See [`MatrixView4x3`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut4x3<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U3, ViewStorageMut<'a, T, U4, U3, RStride, CStride>>;
-/// A column-major 4x5 matrix view.
+/// A mutable column-major 4x5 matrix view.
+///
+/// See [`MatrixView4x5`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut4x5<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U5, ViewStorageMut<'a, T, U4, U5, RStride, CStride>>;
-/// A column-major 4x6 matrix view.
+/// A mutable column-major 4x6 matrix view.
+///
+/// See [`MatrixView4x6`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut4x6<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U6, ViewStorageMut<'a, T, U4, U6, RStride, CStride>>;
 
-/// A column-major 5x1 matrix view.
+/// A mutable column-major 5x1 matrix view.
+///
+/// See [`MatrixView5x1`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut5x1<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U1, ViewStorageMut<'a, T, U5, U1, RStride, CStride>>;
-/// A column-major 5x2 matrix view.
+/// A mutable column-major 5x2 matrix view.
+///
+/// See [`MatrixView5x2`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut5x2<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U2, ViewStorageMut<'a, T, U5, U2, RStride, CStride>>;
-/// A column-major 5x3 matrix view.
+/// A mutable column-major 5x3 matrix view.
+///
+/// See [`MatrixView5x3`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut5x3<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U3, ViewStorageMut<'a, T, U5, U3, RStride, CStride>>;
-/// A column-major 5x4 matrix view.
+/// A mutable column-major 5x4 matrix view.
+///
+/// See [`MatrixView5x4`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut5x4<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U4, ViewStorageMut<'a, T, U5, U4, RStride, CStride>>;
-/// A column-major 5x6 matrix view.
+/// A mutable column-major 5x6 matrix view.
+///
+/// See [`MatrixView5x6`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut5x6<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U6, ViewStorageMut<'a, T, U5, U6, RStride, CStride>>;
 
-/// A column-major 6x1 matrix view.
+/// A mutable column-major 6x1 matrix view.
+///
+/// See [`MatrixView6x1`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut6x1<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, U1, ViewStorageMut<'a, T, U6, U1, RStride, CStride>>;
-/// A column-major 6x2 matrix view.
+/// A mutable column-major 6x2 matrix view.
+///
+/// See [`MatrixView6x2`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut6x2<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, U2, ViewStorageMut<'a, T, U6, U2, RStride, CStride>>;
-/// A column-major 6x3 matrix view.
+/// A mutable column-major 6x3 matrix view.
+///
+/// See [`MatrixView6x3`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut6x3<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, U3, ViewStorageMut<'a, T, U6, U3, RStride, CStride>>;
-/// A column-major 6x4 matrix view.
+/// A mutable column-major 6x4 matrix view.
+///
+/// See [`MatrixView6x4`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut6x4<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, U4, ViewStorageMut<'a, T, U6, U4, RStride, CStride>>;
-/// A column-major 6x5 matrix view.
+/// A mutable column-major 6x5 matrix view.
+///
+/// See [`MatrixView6x5`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut6x5<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, U5, ViewStorageMut<'a, T, U6, U5, RStride, CStride>>;
 
-/// A column-major matrix view with 1 row and a number of columns chosen at runtime.
+/// A mutable column-major matrix view with 1 row and a number of columns chosen at runtime.
+///
+/// See [`MatrixView1xX`] for an immutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut1xX<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, Dyn, ViewStorageMut<'a, T, U1, Dyn, RStride, CStride>>;
-/// A column-major matrix view with 2 rows and a number of columns chosen at runtime.
+/// A mutable column-major matrix view with 2 rows and a number of columns chosen at runtime.
+///
+/// See [`MatrixView2xX`] for an immutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut2xX<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, Dyn, ViewStorageMut<'a, T, U2, Dyn, RStride, CStride>>;
-/// A column-major matrix view with 3 rows and a number of columns chosen at runtime.
+/// A mutable column-major matrix view with 3 rows and a number of columns chosen at runtime.
+///
+/// See [`MatrixView3xX`] for an immutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut3xX<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, Dyn, ViewStorageMut<'a, T, U3, Dyn, RStride, CStride>>;
-/// A column-major matrix view with 4 rows and a number of columns chosen at runtime.
+/// A mutable column-major matrix view with 4 rows and a number of columns chosen at runtime.
+///
+/// See [`MatrixView4xX`] for an immutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut4xX<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, Dyn, ViewStorageMut<'a, T, U4, Dyn, RStride, CStride>>;
-/// A column-major matrix view with 5 rows and a number of columns chosen at runtime.
+/// A mutable column-major matrix view with 5 rows and a number of columns chosen at runtime.
+///
+/// See [`MatrixView5xX`] for an immutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut5xX<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, Dyn, ViewStorageMut<'a, T, U5, Dyn, RStride, CStride>>;
-/// A column-major matrix view with 6 rows and a number of columns chosen at runtime.
+/// A mutable column-major matrix view with 6 rows and a number of columns chosen at runtime.
+///
+/// See [`MatrixView6xX`] for an immutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMut6xX<'a, T, RStride = U1, CStride = U6> =
     Matrix<T, U6, Dyn, ViewStorageMut<'a, T, U6, Dyn, RStride, CStride>>;
 
-/// A column-major matrix view with a number of rows chosen at runtime and 1 column.
+/// A mutable column-major matrix view with a number of rows chosen at runtime and 1 column.
+///
+/// See [`MatrixViewXx1`] for an immutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMutXx1<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U1, ViewStorageMut<'a, T, Dyn, U1, RStride, CStride>>;
-/// A column-major matrix view with a number of rows chosen at runtime and 2 columns.
+/// A mutable column-major matrix view with a number of rows chosen at runtime and 2 columns.
+///
+/// See [`MatrixViewXx2`] for an immutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMutXx2<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U2, ViewStorageMut<'a, T, Dyn, U2, RStride, CStride>>;
-/// A column-major matrix view with a number of rows chosen at runtime and 3 columns.
+/// A mutable column-major matrix view with a number of rows chosen at runtime and 3 columns.
+///
+/// See [`MatrixViewXx3`] for an immutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMutXx3<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U3, ViewStorageMut<'a, T, Dyn, U3, RStride, CStride>>;
-/// A column-major matrix view with a number of rows chosen at runtime and 4 columns.
+/// A mutable column-major matrix view with a number of rows chosen at runtime and 4 columns.
+///
+/// See [`MatrixViewXx4`] for an immutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMutXx4<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U4, ViewStorageMut<'a, T, Dyn, U4, RStride, CStride>>;
-/// A column-major matrix view with a number of rows chosen at runtime and 5 columns.
+/// A mutable column-major matrix view with a number of rows chosen at runtime and 5 columns.
+///
+/// See [`MatrixViewXx5`] for an immutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMutXx5<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U5, ViewStorageMut<'a, T, Dyn, U5, RStride, CStride>>;
-/// A column-major matrix view with a number of rows chosen at runtime and 6 columns.
+/// A mutable column-major matrix view with a number of rows chosen at runtime and 6 columns.
+///
+/// See [`MatrixViewXx6`] for an immutable version of this type.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type MatrixViewMutXx6<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U6, ViewStorageMut<'a, T, Dyn, U6, RStride, CStride>>;
 
-/// A column vector view with dimensions known at compile-time.
+/// A mutable column vector view with dimensions known at compile-time.
+///
+/// See [`VectorView`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorViewMut<'a, T, D, RStride = U1, CStride = D> =
     Matrix<T, D, U1, ViewStorageMut<'a, T, D, U1, RStride, CStride>>;
 
-/// A column vector view with dimensions known at compile-time.
+/// A mutable column vector view with dimensions known at compile-time.
+///
+/// See [`SVectorView`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type SVectorViewMut<'a, T, const D: usize> =
     Matrix<T, Const<D>, Const<1>, ViewStorageMut<'a, T, Const<D>, Const<1>, Const<1>, Const<D>>>;
 
-/// A column vector view dynamic numbers of rows and columns.
+/// A mutable column vector view dynamic numbers of rows and columns.
+///
+/// See [`DVectorView`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type DVectorViewMut<'a, T, RStride = U1, CStride = Dyn> =
     Matrix<T, Dyn, U1, ViewStorageMut<'a, T, Dyn, U1, RStride, CStride>>;
 
-/// A 1D column vector view.
+/// A mutable 1D column vector view.
+///
+/// See [`VectorView1`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorViewMut1<'a, T, RStride = U1, CStride = U1> =
     Matrix<T, U1, U1, ViewStorageMut<'a, T, U1, U1, RStride, CStride>>;
-/// A 2D column vector view.
+/// A mutable 2D column vector view.
+///
+/// See [`VectorView2`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorViewMut2<'a, T, RStride = U1, CStride = U2> =
     Matrix<T, U2, U1, ViewStorageMut<'a, T, U2, U1, RStride, CStride>>;
-/// A 3D column vector view.
+/// A mutable 3D column vector view.
+///
+/// See [`VectorView3`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorViewMut3<'a, T, RStride = U1, CStride = U3> =
     Matrix<T, U3, U1, ViewStorageMut<'a, T, U3, U1, RStride, CStride>>;
-/// A 4D column vector view.
+/// A mutable 4D column vector view.
+///
+/// See [`VectorView4`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorViewMut4<'a, T, RStride = U1, CStride = U4> =
     Matrix<T, U4, U1, ViewStorageMut<'a, T, U4, U1, RStride, CStride>>;
-/// A 5D column vector view.
+/// A mutable 5D column vector view.
+///
+/// See [`VectorView5`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorViewMut5<'a, T, RStride = U1, CStride = U5> =
     Matrix<T, U5, U1, ViewStorageMut<'a, T, U5, U1, RStride, CStride>>;
-/// A 6D column vector view.
+/// A mutable 6D column vector view.
+///
+/// See [`VectorView6`] for an immutable version of this type.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type VectorViewMut6<'a, T, RStride = U1, CStride = U6> =

src/base/allocator.rs

@@ -19,36 +19,36 @@ use std::mem::MaybeUninit;
 ///
 /// Every allocator must be both static and dynamic. Though not all implementations may share the
 /// same `Buffer` type.
-pub trait Allocator<T, R: Dim, C: Dim = U1>: Any + Sized {
+pub trait Allocator<R: Dim, C: Dim = U1>: Any + Sized {
     /// The type of buffer this allocator can instantiate.
-    type Buffer: StorageMut<T, R, C> + IsContiguous + Clone + Debug;
+    type Buffer<T: Scalar>: StorageMut<T, R, C> + IsContiguous + Clone + Debug;
     /// The type of buffer with uninitialized components this allocator can instantiate.
-    type BufferUninit: RawStorageMut<MaybeUninit<T>, R, C> + IsContiguous;
+    type BufferUninit<T: Scalar>: RawStorageMut<MaybeUninit<T>, R, C> + IsContiguous;
 
     /// Allocates a buffer with the given number of rows and columns without initializing its content.
-    fn allocate_uninit(nrows: R, ncols: C) -> Self::BufferUninit;
+    fn allocate_uninit<T: Scalar>(nrows: R, ncols: C) -> Self::BufferUninit<T>;
 
     /// Assumes a data buffer to be initialized.
     ///
     /// # Safety
     /// The user must make sure that every single entry of the buffer has been initialized,
     /// or Undefined Behavior will immediately occur.    
-    unsafe fn assume_init(uninit: Self::BufferUninit) -> Self::Buffer;
+    unsafe fn assume_init<T: Scalar>(uninit: Self::BufferUninit<T>) -> Self::Buffer<T>;
 
     /// Allocates a buffer initialized with the content of the given iterator.
-    fn allocate_from_iterator<I: IntoIterator<Item = T>>(
+    fn allocate_from_iterator<T: Scalar, I: IntoIterator<Item = T>>(
         nrows: R,
         ncols: C,
         iter: I,
-    ) -> Self::Buffer;
+    ) -> Self::Buffer<T>;
 
     #[inline]
     /// Allocates a buffer initialized with the content of the given row-major order iterator.
-    fn allocate_from_row_iterator<I: IntoIterator<Item = T>>(
+    fn allocate_from_row_iterator<T: Scalar, I: IntoIterator<Item = T>>(
         nrows: R,
         ncols: C,
         iter: I,
-    ) -> Self::Buffer {
+    ) -> Self::Buffer<T> {
         let mut res = Self::allocate_uninit(nrows, ncols);
         let mut count = 0;
 
@@ -73,7 +73,7 @@ pub trait Allocator<T, R: Dim, C: Dim = U1>: Any + Sized {
                 "Matrix init. from row iterator: iterator not long enough."
             );
 
-            <Self as Allocator<T, R, C>>::assume_init(res)
+            <Self as Allocator<R, C>>::assume_init(res)
         }
     }
 }
@@ -81,7 +81,7 @@ pub trait Allocator<T, R: Dim, C: Dim = U1>: Any + Sized {
 /// A matrix reallocator. Changes the size of the memory buffer that initially contains (`RFrom` ×
 /// `CFrom`) elements to a smaller or larger size (`RTo`, `CTo`).
 pub trait Reallocator<T: Scalar, RFrom: Dim, CFrom: Dim, RTo: Dim, CTo: Dim>:
-    Allocator<T, RFrom, CFrom> + Allocator<T, RTo, CTo>
+    Allocator<RFrom, CFrom> + Allocator<RTo, CTo>
 {
     /// Reallocates a buffer of shape `(RTo, CTo)`, possibly reusing a previously allocated buffer
     /// `buf`. Data stored by `buf` are linearly copied to the output:
@@ -94,8 +94,8 @@ pub trait Reallocator<T: Scalar, RFrom: Dim, CFrom: Dim, RTo: Dim, CTo: Dim>:
     unsafe fn reallocate_copy(
         nrows: RTo,
         ncols: CTo,
-        buf: <Self as Allocator<T, RFrom, CFrom>>::Buffer,
-    ) -> <Self as Allocator<T, RTo, CTo>>::BufferUninit;
+        buf: <Self as Allocator<RFrom, CFrom>>::Buffer<T>,
+    ) -> <Self as Allocator<RTo, CTo>>::BufferUninit<T>;
 }
 
 /// The number of rows of the result of a componentwise operation on two matrices.
@@ -106,8 +106,8 @@ pub type SameShapeC<C1, C2> = <ShapeConstraint as SameNumberOfColumns<C1, C2>>::
 
 // TODO: Bad name.
 /// Restricts the given number of rows and columns to be respectively the same.
-pub trait SameShapeAllocator<T, R1, C1, R2, C2>:
-    Allocator<T, R1, C1> + Allocator<T, SameShapeR<R1, R2>, SameShapeC<C1, C2>>
+pub trait SameShapeAllocator<R1, C1, R2, C2>:
+    Allocator<R1, C1> + Allocator<SameShapeR<R1, R2>, SameShapeC<C1, C2>>
 where
     R1: Dim,
     R2: Dim,
@@ -117,21 +117,21 @@ where
 {
 }
 
-impl<T, R1, R2, C1, C2> SameShapeAllocator<T, R1, C1, R2, C2> for DefaultAllocator
+impl<R1, R2, C1, C2> SameShapeAllocator<R1, C1, R2, C2> for DefaultAllocator
 where
     R1: Dim,
     R2: Dim,
     C1: Dim,
     C2: Dim,
-    DefaultAllocator: Allocator<T, R1, C1> + Allocator<T, SameShapeR<R1, R2>, SameShapeC<C1, C2>>,
+    DefaultAllocator: Allocator<R1, C1> + Allocator<SameShapeR<R1, R2>, SameShapeC<C1, C2>>,
     ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
 {
 }
 
 // XXX: Bad name.
 /// Restricts the given number of rows to be equal.
-pub trait SameShapeVectorAllocator<T, R1, R2>:
-    Allocator<T, R1> + Allocator<T, SameShapeR<R1, R2>> + SameShapeAllocator<T, R1, U1, R2, U1>
+pub trait SameShapeVectorAllocator<R1, R2>:
+    Allocator<R1> + Allocator<SameShapeR<R1, R2>> + SameShapeAllocator<R1, U1, R2, U1>
 where
     R1: Dim,
     R2: Dim,
@@ -139,11 +139,11 @@ where
 {
 }
 
-impl<T, R1, R2> SameShapeVectorAllocator<T, R1, R2> for DefaultAllocator
+impl<R1, R2> SameShapeVectorAllocator<R1, R2> for DefaultAllocator
 where
     R1: Dim,
     R2: Dim,
-    DefaultAllocator: Allocator<T, R1, U1> + Allocator<T, SameShapeR<R1, R2>>,
+    DefaultAllocator: Allocator<R1, U1> + Allocator<SameShapeR<R1, R2>>,
     ShapeConstraint: SameNumberOfRows<R1, R2>,
 {
 }

src/base/array_storage.rs

@@ -27,7 +27,7 @@ use std::mem;
  * Static RawStorage.
  *
  */
-/// A array-based statically sized matrix data storage.
+/// An array-based statically sized matrix data storage.
 #[repr(transparent)]
 #[derive(Copy, Clone, PartialEq, Eq, Hash)]
 #[cfg_attr(
@@ -42,7 +42,6 @@ use std::mem;
     )
 )]
 #[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
-#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
 pub struct ArrayStorage<T, const R: usize, const C: usize>(pub [[T; R]; C]);
 
 impl<T, const R: usize, const C: usize> ArrayStorage<T, R, C> {
@@ -114,12 +113,12 @@ unsafe impl<T, const R: usize, const C: usize> RawStorage<T, Const<R>, Const<C>>
 unsafe impl<T: Scalar, const R: usize, const C: usize> Storage<T, Const<R>, Const<C>>
     for ArrayStorage<T, R, C>
 where
-    DefaultAllocator: Allocator<T, Const<R>, Const<C>, Buffer = Self>,
+    DefaultAllocator: Allocator<Const<R>, Const<C>, Buffer<T> = Self>,
 {
     #[inline]
     fn into_owned(self) -> Owned<T, Const<R>, Const<C>>
     where
-        DefaultAllocator: Allocator<T, Const<R>, Const<C>>,
+        DefaultAllocator: Allocator<Const<R>, Const<C>>,
     {
         self
     }
@@ -127,10 +126,16 @@ where
     #[inline]
     fn clone_owned(&self) -> Owned<T, Const<R>, Const<C>>
     where
-        DefaultAllocator: Allocator<T, Const<R>, Const<C>>,
+        DefaultAllocator: Allocator<Const<R>, Const<C>>,
     {
         self.clone()
     }
+
+    #[inline]
+    fn forget_elements(self) {
+        // No additional cleanup required.
+        std::mem::forget(self);
+    }
 }
 
 unsafe impl<T, const R: usize, const C: usize> RawStorageMut<T, Const<R>, Const<C>>
@@ -251,7 +256,7 @@ where
         V: SeqAccess<'a>,
     {
         let mut out: ArrayStorage<core::mem::MaybeUninit<T>, R, C> =
-            DefaultAllocator::allocate_uninit(Const::<R>, Const::<C>);
+            <DefaultAllocator as Allocator<_, _>>::allocate_uninit(Const::<R>, Const::<C>);
         let mut curr = 0;
 
         while let Some(value) = visitor.next_element()? {
@@ -264,7 +269,7 @@ where
 
         if curr == R * C {
             // Safety: all the elements have been initialized.
-            unsafe { Ok(<DefaultAllocator as Allocator<T, Const<R>, Const<C>>>::assume_init(out)) }
+            unsafe { Ok(<DefaultAllocator as Allocator<Const<R>, Const<C>>>::assume_init(out)) }
         } else {
             for i in 0..curr {
                 // Safety:

src/base/blas.rs

@@ -1,6 +1,6 @@
 use crate::{RawStorage, SimdComplexField};
 use num::{One, Zero};
-use simba::scalar::{ClosedAdd, ClosedMul};
+use simba::scalar::{ClosedAddAssign, ClosedMulAssign};
 
 use crate::base::allocator::Allocator;
 use crate::base::blas_uninit::{axcpy_uninit, gemm_uninit, gemv_uninit};
@@ -17,7 +17,7 @@ use crate::base::{
 /// # Dot/scalar product
 impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S>
 where
-    T: Scalar + Zero + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + ClosedAddAssign + ClosedMulAssign,
 {
     #[inline(always)]
     fn dotx<R2: Dim, C2: Dim, SB>(
@@ -275,7 +275,7 @@ where
 /// # BLAS functions
 impl<T, D: Dim, S> Vector<T, D, S>
 where
-    T: Scalar + Zero + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + ClosedAddAssign + ClosedMulAssign,
     S: StorageMut<T, D>,
 {
     /// Computes `self = a * x * c + b * self`.
@@ -609,7 +609,7 @@ where
 
 impl<T, R1: Dim, C1: Dim, S: StorageMut<T, R1, C1>> Matrix<T, R1, C1, S>
 where
-    T: Scalar + Zero + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + ClosedAddAssign + ClosedMulAssign,
 {
     #[inline(always)]
     fn gerx<D2: Dim, D3: Dim, SB, SC>(
@@ -862,7 +862,7 @@ where
 
 impl<T, R1: Dim, C1: Dim, S: StorageMut<T, R1, C1>> Matrix<T, R1, C1, S>
 where
-    T: Scalar + Zero + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + ClosedAddAssign + ClosedMulAssign,
 {
     #[inline(always)]
     fn xxgerx<D2: Dim, D3: Dim, SB, SC>(
@@ -1010,7 +1010,7 @@ where
 
 impl<T, D1: Dim, S: StorageMut<T, D1, D1>> SquareMatrix<T, D1, S>
 where
-    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + One + ClosedAddAssign + ClosedMulAssign,
 {
     /// Computes the quadratic form `self = alpha * lhs * mid * lhs.transpose() + beta * self`.
     ///
@@ -1098,7 +1098,7 @@ where
         S3: Storage<T, R3, C3>,
         S4: Storage<T, D4, D4>,
         ShapeConstraint: DimEq<D1, D1> + DimEq<D1, R3> + DimEq<C3, D4>,
-        DefaultAllocator: Allocator<T, D1>,
+        DefaultAllocator: Allocator<D1>,
     {
         // TODO: would it be useful to avoid the zero-initialization of the workspace data?
         let mut work = Matrix::zeros_generic(self.shape_generic().0, Const::<1>);
@@ -1196,7 +1196,7 @@ where
         S2: Storage<T, D2, D2>,
         S3: Storage<T, R3, C3>,
         ShapeConstraint: DimEq<D2, R3> + DimEq<D1, C3> + AreMultipliable<C3, R3, D2, U1>,
-        DefaultAllocator: Allocator<T, D2>,
+        DefaultAllocator: Allocator<D2>,
     {
         // TODO: would it be useful to avoid the zero-initialization of the workspace data?
         let mut work = Vector::zeros_generic(mid.shape_generic().0, Const::<1>);

src/base/blas_uninit.rs

@@ -11,18 +11,19 @@
 #[cfg(feature = "std")]
 use matrixmultiply;
 use num::{One, Zero};
-use simba::scalar::{ClosedAdd, ClosedMul};
+use simba::scalar::{ClosedAddAssign, ClosedMulAssign};
 #[cfg(feature = "std")]
-use std::mem;
+use std::{any::TypeId, mem};
 
 use crate::base::constraint::{
     AreMultipliable, DimEq, SameNumberOfColumns, SameNumberOfRows, ShapeConstraint,
 };
-use crate::base::dimension::{Dim, Dyn, U1};
+#[cfg(feature = "std")]
+use crate::base::dimension::Dyn;
+use crate::base::dimension::{Dim, U1};
 use crate::base::storage::{RawStorage, RawStorageMut};
 use crate::base::uninit::InitStatus;
 use crate::base::{Matrix, Scalar, Vector};
-use std::any::TypeId;
 
 // # Safety
 // The content of `y` must only contain values for which
@@ -40,7 +41,7 @@ unsafe fn array_axcpy<Status, T>(
     len: usize,
 ) where
     Status: InitStatus<T>,
-    T: Scalar + Zero + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + ClosedAddAssign + ClosedMulAssign,
 {
     for i in 0..len {
         let y = Status::assume_init_mut(y.get_unchecked_mut(i * stride1));
@@ -60,7 +61,7 @@ fn array_axc<Status, T>(
     len: usize,
 ) where
     Status: InitStatus<T>,
-    T: Scalar + Zero + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + ClosedAddAssign + ClosedMulAssign,
 {
     for i in 0..len {
         unsafe {
@@ -88,7 +89,7 @@ pub unsafe fn axcpy_uninit<Status, T, D1: Dim, D2: Dim, SA, SB>(
     c: T,
     b: T,
 ) where
-    T: Scalar + Zero + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + ClosedAddAssign + ClosedMulAssign,
     SA: RawStorageMut<Status::Value, D1>,
     SB: RawStorage<T, D2>,
     ShapeConstraint: DimEq<D1, D2>,
@@ -128,7 +129,7 @@ pub unsafe fn gemv_uninit<Status, T, D1: Dim, R2: Dim, C2: Dim, D3: Dim, SA, SB,
     beta: T,
 ) where
     Status: InitStatus<T>,
-    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + One + ClosedAddAssign + ClosedMulAssign,
     SA: RawStorageMut<Status::Value, D1>,
     SB: RawStorage<T, R2, C2>,
     SC: RawStorage<T, D3>,
@@ -198,7 +199,7 @@ pub unsafe fn gemm_uninit<
     beta: T,
 ) where
     Status: InitStatus<T>,
-    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + One + ClosedAddAssign + ClosedMulAssign,
     SA: RawStorageMut<Status::Value, R1, C1>,
     SB: RawStorage<T, R2, C2>,
     SC: RawStorage<T, R3, C3>,

src/base/cg.rs

@@ -19,13 +19,13 @@ use crate::geometry::{
     Rotation3,
 };
 
-use simba::scalar::{ClosedAdd, ClosedMul, RealField};
+use simba::scalar::{ClosedAddAssign, ClosedMulAssign, RealField};
 
 /// # Translation and scaling in any dimension
 impl<T, D: DimName> OMatrix<T, D, D>
 where
     T: Scalar + Zero + One,
-    DefaultAllocator: Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D, D>,
 {
     /// Creates a new homogeneous matrix that applies the same scaling factor on each dimension.
     #[inline]
@@ -207,8 +207,11 @@ impl<T: RealField> Matrix4<T> {
 }
 
 /// # Append/prepend translation and scaling
-impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D, D>>
-    SquareMatrix<T, D, S>
+impl<
+        T: Scalar + Zero + One + ClosedMulAssign + ClosedAddAssign,
+        D: DimName,
+        S: Storage<T, D, D>,
+    > SquareMatrix<T, D, S>
 {
     /// Computes the transformation equal to `self` followed by an uniform scaling factor.
     #[inline]
@@ -216,7 +219,7 @@ impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D
     pub fn append_scaling(&self, scaling: T) -> OMatrix<T, D, D>
     where
         D: DimNameSub<U1>,
-        DefaultAllocator: Allocator<T, D, D>,
+        DefaultAllocator: Allocator<D, D>,
     {
         let mut res = self.clone_owned();
         res.append_scaling_mut(scaling);
@@ -229,7 +232,7 @@ impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D
     pub fn prepend_scaling(&self, scaling: T) -> OMatrix<T, D, D>
     where
         D: DimNameSub<U1>,
-        DefaultAllocator: Allocator<T, D, D>,
+        DefaultAllocator: Allocator<D, D>,
     {
         let mut res = self.clone_owned();
         res.prepend_scaling_mut(scaling);
@@ -246,7 +249,7 @@ impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D
     where
         D: DimNameSub<U1>,
         SB: Storage<T, DimNameDiff<D, U1>>,
-        DefaultAllocator: Allocator<T, D, D>,
+        DefaultAllocator: Allocator<D, D>,
     {
         let mut res = self.clone_owned();
         res.append_nonuniform_scaling_mut(scaling);
@@ -263,7 +266,7 @@ impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D
     where
         D: DimNameSub<U1>,
         SB: Storage<T, DimNameDiff<D, U1>>,
-        DefaultAllocator: Allocator<T, D, D>,
+        DefaultAllocator: Allocator<D, D>,
     {
         let mut res = self.clone_owned();
         res.prepend_nonuniform_scaling_mut(scaling);
@@ -280,7 +283,7 @@ impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D
     where
         D: DimNameSub<U1>,
         SB: Storage<T, DimNameDiff<D, U1>>,
-        DefaultAllocator: Allocator<T, D, D>,
+        DefaultAllocator: Allocator<D, D>,
     {
         let mut res = self.clone_owned();
         res.append_translation_mut(shift);
@@ -297,7 +300,7 @@ impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D
     where
         D: DimNameSub<U1>,
         SB: Storage<T, DimNameDiff<D, U1>>,
-        DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimNameDiff<D, U1>>,
+        DefaultAllocator: Allocator<D, D> + Allocator<DimNameDiff<D, U1>>,
     {
         let mut res = self.clone_owned();
         res.prepend_translation_mut(shift);
@@ -379,7 +382,7 @@ impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D
         D: DimNameSub<U1>,
         S: StorageMut<T, D, D>,
         SB: Storage<T, DimNameDiff<D, U1>>,
-        DefaultAllocator: Allocator<T, DimNameDiff<D, U1>>,
+        DefaultAllocator: Allocator<DimNameDiff<D, U1>>,
     {
         let scale = self
             .generic_view(
@@ -405,9 +408,9 @@ impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D
 /// # Transformation of vectors and points
 impl<T: RealField, D: DimNameSub<U1>, S: Storage<T, D, D>> SquareMatrix<T, D, S>
 where
-    DefaultAllocator: Allocator<T, D, D>
-        + Allocator<T, DimNameDiff<D, U1>>
-        + Allocator<T, DimNameDiff<D, U1>, DimNameDiff<D, U1>>,
+    DefaultAllocator: Allocator<D, D>
+        + Allocator<DimNameDiff<D, U1>>
+        + Allocator<DimNameDiff<D, U1>, DimNameDiff<D, U1>>,
 {
     /// Transforms the given vector, assuming the matrix `self` uses homogeneous coordinates.
     #[inline]

src/base/componentwise.rs

@@ -3,7 +3,7 @@
 use num::{Signed, Zero};
 use std::ops::{Add, Mul};
 
-use simba::scalar::{ClosedDiv, ClosedMul};
+use simba::scalar::{ClosedDivAssign, ClosedMulAssign};
 use simba::simd::SimdPartialOrd;
 
 use crate::base::allocator::{Allocator, SameShapeAllocator};
@@ -11,7 +11,7 @@ use crate::base::constraint::{SameNumberOfColumns, SameNumberOfRows, ShapeConstr
 use crate::base::dimension::Dim;
 use crate::base::storage::{Storage, StorageMut};
 use crate::base::{DefaultAllocator, Matrix, MatrixSum, OMatrix, Scalar};
-use crate::ClosedAdd;
+use crate::ClosedAddAssign;
 
 /// The type of the result of a matrix component-wise operation.
 pub type MatrixComponentOp<T, R1, C1, R2, C2> = MatrixSum<T, R1, C1, R2, C2>;
@@ -32,7 +32,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     pub fn abs(&self) -> OMatrix<T, R, C>
     where
         T: Signed,
-        DefaultAllocator: Allocator<T, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         let mut res = self.clone_owned();
 
@@ -55,7 +55,7 @@ macro_rules! component_binop_impl(
             where T: $Trait,
                   R2: Dim, C2: Dim,
                   SB: Storage<T, R2, C2>,
-                  DefaultAllocator: SameShapeAllocator<T, R1, C1, R2, C2>,
+                  DefaultAllocator: SameShapeAllocator<R1, C1, R2, C2>,
                   ShapeConstraint:  SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
 
             assert_eq!(self.shape(), rhs.shape(), "Componentwise mul/div: mismatched matrix dimensions.");
@@ -148,7 +148,7 @@ macro_rules! component_binop_impl(
 /// # Componentwise operations
 impl<T: Scalar, R1: Dim, C1: Dim, SA: Storage<T, R1, C1>> Matrix<T, R1, C1, SA> {
     component_binop_impl!(
-        component_mul, component_mul_mut, component_mul_assign, cmpy, ClosedMul.mul.mul_assign,
+        component_mul, component_mul_mut, component_mul_assign, cmpy, ClosedMulAssign.mul.mul_assign,
         r"
         Componentwise matrix or vector multiplication.
 
@@ -193,7 +193,7 @@ impl<T: Scalar, R1: Dim, C1: Dim, SA: Storage<T, R1, C1>> Matrix<T, R1, C1, SA>
         assert_eq!(a, expected);
         ```
         ";
-        component_div, component_div_mut, component_div_assign, cdpy, ClosedDiv.div.div_assign,
+        component_div, component_div_mut, component_div_assign, cdpy, ClosedDivAssign.div.div_assign,
         r"
         Componentwise matrix or vector division.
 
@@ -257,7 +257,7 @@ impl<T: Scalar, R1: Dim, C1: Dim, SA: Storage<T, R1, C1>> Matrix<T, R1, C1, SA>
     pub fn inf(&self, other: &Self) -> OMatrix<T, R1, C1>
     where
         T: SimdPartialOrd,
-        DefaultAllocator: Allocator<T, R1, C1>,
+        DefaultAllocator: Allocator<R1, C1>,
     {
         self.zip_map(other, |a, b| a.simd_min(b))
     }
@@ -278,7 +278,7 @@ impl<T: Scalar, R1: Dim, C1: Dim, SA: Storage<T, R1, C1>> Matrix<T, R1, C1, SA>
     pub fn sup(&self, other: &Self) -> OMatrix<T, R1, C1>
     where
         T: SimdPartialOrd,
-        DefaultAllocator: Allocator<T, R1, C1>,
+        DefaultAllocator: Allocator<R1, C1>,
     {
         self.zip_map(other, |a, b| a.simd_max(b))
     }
@@ -299,7 +299,7 @@ impl<T: Scalar, R1: Dim, C1: Dim, SA: Storage<T, R1, C1>> Matrix<T, R1, C1, SA>
     pub fn inf_sup(&self, other: &Self) -> (OMatrix<T, R1, C1>, OMatrix<T, R1, C1>)
     where
         T: SimdPartialOrd,
-        DefaultAllocator: Allocator<T, R1, C1>,
+        DefaultAllocator: Allocator<R1, C1>,
     {
         // TODO: can this be optimized?
         (self.inf(other), self.sup(other))
@@ -320,8 +320,8 @@ impl<T: Scalar, R1: Dim, C1: Dim, SA: Storage<T, R1, C1>> Matrix<T, R1, C1, SA>
     #[must_use = "Did you mean to use add_scalar_mut()?"]
     pub fn add_scalar(&self, rhs: T) -> OMatrix<T, R1, C1>
     where
-        T: ClosedAdd,
-        DefaultAllocator: Allocator<T, R1, C1>,
+        T: ClosedAddAssign,
+        DefaultAllocator: Allocator<R1, C1>,
     {
         let mut res = self.clone_owned();
         res.add_scalar_mut(rhs);
@@ -343,7 +343,7 @@ impl<T: Scalar, R1: Dim, C1: Dim, SA: Storage<T, R1, C1>> Matrix<T, R1, C1, SA>
     #[inline]
     pub fn add_scalar_mut(&mut self, rhs: T)
     where
-        T: ClosedAdd,
+        T: ClosedAddAssign,
         SA: StorageMut<T, R1, C1>,
     {
         for e in self.iter_mut() {

src/base/constraint.rs

@@ -6,7 +6,7 @@ use crate::base::dimension::{Dim, DimName, Dyn};
 #[derive(Copy, Clone, Debug)]
 pub struct ShapeConstraint;
 
-/// Constraints `C1` and `R2` to be equivalent.
+/// Constrains `C1` and `R2` to be equivalent.
 pub trait AreMultipliable<R1: Dim, C1: Dim, R2: Dim, C2: Dim>: DimEq<C1, R2> {}
 
 impl<R1: Dim, C1: Dim, R2: Dim, C2: Dim> AreMultipliable<R1, C1, R2, C2> for ShapeConstraint where
@@ -14,11 +14,21 @@ impl<R1: Dim, C1: Dim, R2: Dim, C2: Dim> AreMultipliable<R1, C1, R2, C2> for Sha
 {
 }
 
-/// Constraints `D1` and `D2` to be equivalent.
+/// Constrains `D1` and `D2` to be equivalent.
 pub trait DimEq<D1: Dim, D2: Dim> {
     /// This is either equal to `D1` or `D2`, always choosing the one (if any) which is a type-level
     /// constant.
     type Representative: Dim;
+
+    /// This constructs a value of type `Representative` with the
+    /// correct value
+    fn representative(d1: D1, d2: D2) -> Option<Self::Representative> {
+        if d1.value() != d2.value() {
+            None
+        } else {
+            Some(Self::Representative::from_usize(d1.value()))
+        }
+    }
 }
 
 impl<D: Dim> DimEq<D, D> for ShapeConstraint {
@@ -35,12 +45,19 @@ impl<D: DimName> DimEq<Dyn, D> for ShapeConstraint {
 
 macro_rules! equality_trait_decl(
     ($($doc: expr, $Trait: ident),* $(,)*) => {$(
-        // XXX: we can't do something like `DimEq<D1> for D2` because we would require a blancket impl…
+        // XXX: we can't do something like `DimEq<D1> for D2` because we would require a blanket impl…
         #[doc = $doc]
         pub trait $Trait<D1: Dim, D2: Dim>: DimEq<D1, D2> + DimEq<D2, D1> {
             /// This is either equal to `D1` or `D2`, always choosing the one (if any) which is a type-level
             /// constant.
             type Representative: Dim;
+
+            /// Returns a representative dimension instance if the two are equal,
+            /// otherwise `None`.
+            fn representative(d1: D1, d2: D2) -> Option<<Self as $Trait<D1, D2>>::Representative> {
+                <Self as DimEq<D1, D2>>::representative(d1, d2)
+                    .map(|common_dim| <Self as $Trait<D1, D2>>::Representative::from_usize(common_dim.value()))
+            }
         }
 
         impl<D: Dim> $Trait<D, D> for ShapeConstraint {
@@ -58,17 +75,17 @@ macro_rules! equality_trait_decl(
 );
 
 equality_trait_decl!(
-    "Constraints `D1` and `D2` to be equivalent. \
+    "Constrains `D1` and `D2` to be equivalent. \
      They are both assumed to be the number of \
      rows of a matrix.",
     SameNumberOfRows,
-    "Constraints `D1` and `D2` to be equivalent. \
+    "Constrains `D1` and `D2` to be equivalent. \
      They are both assumed to be the number of \
      columns of a matrix.",
     SameNumberOfColumns
 );
 
-/// Constraints D1 and D2 to be equivalent, where they both designate dimensions of algebraic
+/// Constrains D1 and D2 to be equivalent, where they both designate dimensions of algebraic
 /// entities (e.g. square matrices).
 pub trait SameDimension<D1: Dim, D2: Dim>:
     SameNumberOfRows<D1, D2> + SameNumberOfColumns<D1, D2>

src/base/construction.rs

@@ -16,7 +16,7 @@ use rand::{
 use std::iter;
 use typenum::{self, Cmp, Greater};
 
-use simba::scalar::{ClosedAdd, ClosedMul};
+use simba::scalar::{ClosedAddAssign, ClosedMulAssign};
 
 use crate::base::allocator::Allocator;
 use crate::base::dimension::{Dim, DimName, Dyn, ToTypenum};
@@ -29,7 +29,7 @@ use std::mem::MaybeUninit;
 
 impl<T: Scalar, R: Dim, C: Dim> UninitMatrix<T, R, C>
 where
-    DefaultAllocator: Allocator<T, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     /// Builds a matrix with uninitialized elements of type `MaybeUninit<T>`.
     #[inline(always)]
@@ -50,7 +50,7 @@ where
 /// These functions should only be used when working on dimension-generic code.
 impl<T: Scalar, R: Dim, C: Dim> OMatrix<T, R, C>
 where
-    DefaultAllocator: Allocator<T, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     /// Creates a matrix with all its elements set to `elem`.
     #[inline]
@@ -226,7 +226,7 @@ where
         SB: RawStorage<T, Const<1>, C>,
     {
         assert!(!rows.is_empty(), "At least one row must be given.");
-        let nrows = R::try_to_usize().unwrap_or_else(|| rows.len());
+        let nrows = R::try_to_usize().unwrap_or(rows.len());
         let ncols = rows[0].len();
         assert!(
             rows.len() == nrows,
@@ -268,7 +268,7 @@ where
         SB: RawStorage<T, R>,
     {
         assert!(!columns.is_empty(), "At least one column must be given.");
-        let ncols = C::try_to_usize().unwrap_or_else(|| columns.len());
+        let ncols = C::try_to_usize().unwrap_or(columns.len());
         let nrows = columns[0].len();
         assert!(
             columns.len() == ncols,
@@ -338,7 +338,7 @@ where
 impl<T, D: Dim> OMatrix<T, D, D>
 where
     T: Scalar,
-    DefaultAllocator: Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D, D>,
 {
     /// Creates a square matrix with its diagonal set to `diag` and all other entries set to 0.
     ///
@@ -646,7 +646,7 @@ macro_rules! impl_constructors(
 /// # Constructors of statically-sized vectors or statically-sized matrices
 impl<T: Scalar, R: DimName, C: DimName> OMatrix<T, R, C>
 where
-    DefaultAllocator: Allocator<T, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     // TODO: this is not very pretty. We could find a better call syntax.
     impl_constructors!(R, C;                         // Arguments for Matrix<T, ..., S>
@@ -658,7 +658,7 @@ where
 /// # Constructors of matrices with a dynamic number of columns
 impl<T: Scalar, R: DimName> OMatrix<T, R, Dyn>
 where
-    DefaultAllocator: Allocator<T, R, Dyn>,
+    DefaultAllocator: Allocator<R, Dyn>,
 {
     impl_constructors!(R, Dyn;
                    => R: DimName;
@@ -669,7 +669,7 @@ where
 /// # Constructors of dynamic vectors and matrices with a dynamic number of rows
 impl<T: Scalar, C: DimName> OMatrix<T, Dyn, C>
 where
-    DefaultAllocator: Allocator<T, Dyn, C>,
+    DefaultAllocator: Allocator<Dyn, C>,
 {
     impl_constructors!(Dyn, C;
                    => C: DimName;
@@ -678,9 +678,10 @@ where
 }
 
 /// # Constructors of fully dynamic matrices
+#[cfg(any(feature = "std", feature = "alloc"))]
 impl<T: Scalar> OMatrix<T, Dyn, Dyn>
 where
-    DefaultAllocator: Allocator<T, Dyn, Dyn>,
+    DefaultAllocator: Allocator<Dyn, Dyn>,
 {
     impl_constructors!(Dyn, Dyn;
                    ;
@@ -697,7 +698,7 @@ where
 macro_rules! impl_constructors_from_data(
     ($data: ident; $($Dims: ty),*; $(=> $DimIdent: ident: $DimBound: ident),*; $($gargs: expr),*; $($args: ident),*) => {
         impl<T: Scalar, $($DimIdent: $DimBound, )*> OMatrix<T $(, $Dims)*>
-        where DefaultAllocator: Allocator<T $(, $Dims)*> {
+        where DefaultAllocator: Allocator<$($Dims),*> {
             /// Creates a matrix with its elements filled with the components provided by a slice
             /// in row-major order.
             ///
@@ -800,6 +801,7 @@ impl_constructors_from_data!(data; Dyn, C;
 Dyn(data.len() / C::dim()), C::name();
 );
 
+#[cfg(any(feature = "std", feature = "alloc"))]
 impl_constructors_from_data!(data; Dyn, Dyn;
                             ;
                             Dyn(nrows), Dyn(ncols);
@@ -812,8 +814,8 @@ impl_constructors_from_data!(data; Dyn, Dyn;
  */
 impl<T, R: DimName, C: DimName> Zero for OMatrix<T, R, C>
 where
-    T: Scalar + Zero + ClosedAdd,
-    DefaultAllocator: Allocator<T, R, C>,
+    T: Scalar + Zero + ClosedAddAssign,
+    DefaultAllocator: Allocator<R, C>,
 {
     #[inline]
     fn zero() -> Self {
@@ -828,8 +830,8 @@ where
 
 impl<T, D: DimName> One for OMatrix<T, D, D>
 where
-    T: Scalar + Zero + One + ClosedMul + ClosedAdd,
-    DefaultAllocator: Allocator<T, D, D>,
+    T: Scalar + Zero + One + ClosedMulAssign + ClosedAddAssign,
+    DefaultAllocator: Allocator<D, D>,
 {
     #[inline]
     fn one() -> Self {
@@ -840,7 +842,7 @@ where
 impl<T, R: DimName, C: DimName> Bounded for OMatrix<T, R, C>
 where
     T: Scalar + Bounded,
-    DefaultAllocator: Allocator<T, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     #[inline]
     fn max_value() -> Self {
@@ -856,7 +858,7 @@ where
 #[cfg(feature = "rand-no-std")]
 impl<T: Scalar, R: Dim, C: Dim> Distribution<OMatrix<T, R, C>> for Standard
 where
-    DefaultAllocator: Allocator<T, R, C>,
+    DefaultAllocator: Allocator<R, C>,
     Standard: Distribution<T>,
 {
     #[inline]
@@ -874,7 +876,7 @@ where
     R: Dim,
     C: Dim,
     T: Scalar + Arbitrary + Send,
-    DefaultAllocator: Allocator<T, R, C>,
+    DefaultAllocator: Allocator<R, C>,
     Owned<T, R, C>: Clone + Send,
 {
     #[inline]
@@ -892,7 +894,7 @@ where
 #[cfg(feature = "rand")]
 impl<T: crate::RealField, D: DimName> Distribution<Unit<OVector<T, D>>> for Standard
 where
-    DefaultAllocator: Allocator<T, D>,
+    DefaultAllocator: Allocator<D>,
     rand_distr::StandardNormal: Distribution<T>,
 {
     /// Generate a uniformly distributed random unit vector.
@@ -1111,7 +1113,7 @@ impl<T, R: DimName> OVector<T, R>
 where
     R: ToTypenum,
     T: Scalar + Zero + One,
-    DefaultAllocator: Allocator<T, R>,
+    DefaultAllocator: Allocator<R>,
 {
     /// The column vector with `val` as its i-th component.
     #[inline]

src/base/construction_view.rs

@@ -97,6 +97,8 @@ macro_rules! impl_constructors(
             }
 
             /// Creates, without bound checking, a new matrix view from the given data array.
+            /// # Safety
+            /// `data[start..start+rstride * cstride]` must be within bounds.
             #[inline]
             pub unsafe fn from_slice_unchecked(data: &'a [T], start: usize, $($args: usize),*) -> Self {
                 Self::from_slice_generic_unchecked(data, start, $($gargs),*)
@@ -113,6 +115,11 @@ macro_rules! impl_constructors(
             }
 
             /// Creates, without bound checking, a new matrix view with the specified strides from the given data array.
+            ///
+            /// # Safety
+            ///
+            /// `start`, `rstride`, and `cstride`, with the given matrix size will not index
+            /// outside of `data`.
             #[inline]
             pub unsafe fn from_slice_with_strides_unchecked(data: &'a [T], start: usize, $($args: usize,)* rstride: usize, cstride: usize) -> Self {
                 Self::from_slice_with_strides_generic_unchecked(data, start, $($gargs,)* Dyn(rstride), Dyn(cstride))
@@ -257,6 +264,10 @@ macro_rules! impl_constructors_mut(
             }
 
             /// Creates, without bound checking, a new mutable matrix view from the given data array.
+            ///
+            /// # Safety
+            ///
+            /// `data[start..start+(R * C)]` must be within bounds.
             #[inline]
             pub unsafe fn from_slice_unchecked(data: &'a mut [T], start: usize, $($args: usize),*) -> Self {
                 Self::from_slice_generic_unchecked(data, start, $($gargs),*)
@@ -274,6 +285,8 @@ macro_rules! impl_constructors_mut(
             }
 
             /// Creates, without bound checking, a new mutable matrix view with the specified strides from the given data array.
+            /// # Safety
+            /// `data[start..start+rstride * cstride]` must be within bounds.
             #[inline]
             pub unsafe fn from_slice_with_strides_unchecked(data: &'a mut [T], start: usize, $($args: usize,)* rstride: usize, cstride: usize) -> Self {
                 Self::from_slice_with_strides_generic_unchecked(

src/base/conversion.rs

@@ -8,11 +8,11 @@ use simba::simd::{PrimitiveSimdValue, SimdValue};
 
 use crate::base::allocator::{Allocator, SameShapeAllocator};
 use crate::base::constraint::{SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
-#[cfg(any(feature = "std", feature = "alloc"))]
-use crate::base::dimension::Dyn;
 use crate::base::dimension::{
-    Const, Dim, DimName, U1, U10, U11, U12, U13, U14, U15, U16, U2, U3, U4, U5, U6, U7, U8, U9,
+    Const, Dim, U1, U10, U11, U12, U13, U14, U15, U16, U2, U3, U4, U5, U6, U7, U8, U9,
 };
+#[cfg(any(feature = "std", feature = "alloc"))]
+use crate::base::dimension::{DimName, Dyn};
 use crate::base::iter::{MatrixIter, MatrixIterMut};
 use crate::base::storage::{IsContiguous, RawStorage, RawStorageMut};
 use crate::base::{
@@ -35,8 +35,7 @@ where
     C2: Dim,
     T1: Scalar,
     T2: Scalar + SupersetOf<T1>,
-    DefaultAllocator:
-        Allocator<T2, R2, C2> + Allocator<T1, R1, C1> + SameShapeAllocator<T1, R1, C1, R2, C2>,
+    DefaultAllocator: Allocator<R2, C2> + Allocator<R1, C1> + SameShapeAllocator<R1, C1, R2, C2>,
     ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
 {
     #[inline]
@@ -98,6 +97,18 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> IntoIterator
     }
 }
 
+impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> IntoIterator
+    for Matrix<T, R, C, ViewStorage<'a, T, R, C, RStride, CStride>>
+{
+    type Item = &'a T;
+    type IntoIter = MatrixIter<'a, T, R, C, ViewStorage<'a, T, R, C, RStride, CStride>>;
+
+    #[inline]
+    fn into_iter(self) -> Self::IntoIter {
+        MatrixIter::new_owned(self.data)
+    }
+}
+
 impl<'a, T: Scalar, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> IntoIterator
     for &'a mut Matrix<T, R, C, S>
 {
@@ -110,6 +121,18 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> IntoIterator
     }
 }
 
+impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> IntoIterator
+    for Matrix<T, R, C, ViewStorageMut<'a, T, R, C, RStride, CStride>>
+{
+    type Item = &'a mut T;
+    type IntoIter = MatrixIterMut<'a, T, R, C, ViewStorageMut<'a, T, R, C, RStride, CStride>>;
+
+    #[inline]
+    fn into_iter(self) -> Self::IntoIter {
+        MatrixIterMut::new_owned_mut(self.data)
+    }
+}
+
 impl<T: Scalar, const D: usize> From<[T; D]> for SVector<T, D> {
     #[inline]
     fn from(arr: [T; D]) -> Self {
@@ -473,7 +496,7 @@ where
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<'a, T: Scalar> From<Vec<T>> for DVector<T> {
+impl<T: Scalar> From<Vec<T>> for DVector<T> {
     #[inline]
     fn from(vec: Vec<T>) -> Self {
         Self::from_vec(vec)
@@ -481,7 +504,7 @@ impl<'a, T: Scalar> From<Vec<T>> for DVector<T> {
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<'a, T: Scalar> From<Vec<T>> for RowDVector<T> {
+impl<T: Scalar> From<Vec<T>> for RowDVector<T> {
     #[inline]
     fn from(vec: Vec<T>) -> Self {
         Self::from_vec(vec)
@@ -537,7 +560,7 @@ impl<T: Scalar + PrimitiveSimdValue, R: Dim, C: Dim> From<[OMatrix<T::Element, R
 where
     T: From<[<T as SimdValue>::Element; 2]>,
     T::Element: Scalar + SimdValue,
-    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     #[inline]
     fn from(arr: [OMatrix<T::Element, R, C>; 2]) -> Self {
@@ -554,7 +577,7 @@ impl<T: Scalar + PrimitiveSimdValue, R: Dim, C: Dim> From<[OMatrix<T::Element, R
 where
     T: From<[<T as SimdValue>::Element; 4]>,
     T::Element: Scalar + SimdValue,
-    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     #[inline]
     fn from(arr: [OMatrix<T::Element, R, C>; 4]) -> Self {
@@ -577,7 +600,7 @@ impl<T: Scalar + PrimitiveSimdValue, R: Dim, C: Dim> From<[OMatrix<T::Element, R
 where
     T: From<[<T as SimdValue>::Element; 8]>,
     T::Element: Scalar + SimdValue,
-    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     #[inline]
     fn from(arr: [OMatrix<T::Element, R, C>; 8]) -> Self {
@@ -604,7 +627,7 @@ impl<T: Scalar + PrimitiveSimdValue, R: Dim, C: Dim> From<[OMatrix<T::Element, R
 where
     T: From<[<T as SimdValue>::Element; 16]>,
     T::Element: Scalar + SimdValue,
-    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     fn from(arr: [OMatrix<T::Element, R, C>; 16]) -> Self {
         let (nrows, ncols) = arr[0].shape_generic();

src/base/default_allocator.rs

@@ -12,14 +12,16 @@ use alloc::vec::Vec;
 use super::Const;
 use crate::base::allocator::{Allocator, Reallocator};
 use crate::base::array_storage::ArrayStorage;
+use crate::base::dimension::Dim;
 #[cfg(any(feature = "alloc", feature = "std"))]
-use crate::base::dimension::Dyn;
-use crate::base::dimension::{Dim, DimName};
-use crate::base::storage::{RawStorage, RawStorageMut};
+use crate::base::dimension::{DimName, Dyn};
+use crate::base::storage::{RawStorage, RawStorageMut, Storage};
 #[cfg(any(feature = "std", feature = "alloc"))]
 use crate::base::vec_storage::VecStorage;
 use crate::base::Scalar;
-use std::mem::{ManuallyDrop, MaybeUninit};
+#[cfg(any(feature = "std", feature = "alloc"))]
+use std::mem::ManuallyDrop;
+use std::mem::MaybeUninit;
 
 /*
  *
@@ -32,21 +34,21 @@ use std::mem::{ManuallyDrop, MaybeUninit};
 pub struct DefaultAllocator;
 
 // Static - Static
-impl<T: Scalar, const R: usize, const C: usize> Allocator<T, Const<R>, Const<C>>
-    for DefaultAllocator
-{
-    type Buffer = ArrayStorage<T, R, C>;
-    type BufferUninit = ArrayStorage<MaybeUninit<T>, R, C>;
+impl<const R: usize, const C: usize> Allocator<Const<R>, Const<C>> for DefaultAllocator {
+    type Buffer<T: Scalar> = ArrayStorage<T, R, C>;
+    type BufferUninit<T: Scalar> = ArrayStorage<MaybeUninit<T>, R, C>;
 
     #[inline(always)]
-    fn allocate_uninit(_: Const<R>, _: Const<C>) -> ArrayStorage<MaybeUninit<T>, R, C> {
+    fn allocate_uninit<T: Scalar>(_: Const<R>, _: Const<C>) -> ArrayStorage<MaybeUninit<T>, R, C> {
         // SAFETY: An uninitialized `[MaybeUninit<_>; _]` is valid.
         let array: [[MaybeUninit<T>; R]; C] = unsafe { MaybeUninit::uninit().assume_init() };
         ArrayStorage(array)
     }
 
     #[inline(always)]
-    unsafe fn assume_init(uninit: ArrayStorage<MaybeUninit<T>, R, C>) -> ArrayStorage<T, R, C> {
+    unsafe fn assume_init<T: Scalar>(
+        uninit: ArrayStorage<MaybeUninit<T>, R, C>,
+    ) -> ArrayStorage<T, R, C> {
         // Safety:
         // * The caller guarantees that all elements of the array are initialized
         // * `MaybeUninit<T>` and T are guaranteed to have the same layout
@@ -56,11 +58,11 @@ impl<T: Scalar, const R: usize, const C: usize> Allocator<T, Const<R>, Const<C>>
     }
 
     #[inline]
-    fn allocate_from_iterator<I: IntoIterator<Item = T>>(
+    fn allocate_from_iterator<T: Scalar, I: IntoIterator<Item = T>>(
         nrows: Const<R>,
         ncols: Const<C>,
         iter: I,
-    ) -> Self::Buffer {
+    ) -> Self::Buffer<T> {
         let mut res = Self::allocate_uninit(nrows, ncols);
         let mut count = 0;
 
@@ -78,19 +80,19 @@ impl<T: Scalar, const R: usize, const C: usize> Allocator<T, Const<R>, Const<C>>
 
         // Safety: the assertion above made sure that the iterator
         //         yielded enough elements to initialize our matrix.
-        unsafe { <Self as Allocator<T, Const<R>, Const<C>>>::assume_init(res) }
+        unsafe { <Self as Allocator<Const<R>, Const<C>>>::assume_init(res) }
     }
 }
 
 // Dyn - Static
 // Dyn - Dyn
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<T: Scalar, C: Dim> Allocator<T, Dyn, C> for DefaultAllocator {
-    type Buffer = VecStorage<T, Dyn, C>;
-    type BufferUninit = VecStorage<MaybeUninit<T>, Dyn, C>;
+impl<C: Dim> Allocator<Dyn, C> for DefaultAllocator {
+    type Buffer<T: Scalar> = VecStorage<T, Dyn, C>;
+    type BufferUninit<T: Scalar> = VecStorage<MaybeUninit<T>, Dyn, C>;
 
     #[inline]
-    fn allocate_uninit(nrows: Dyn, ncols: C) -> VecStorage<MaybeUninit<T>, Dyn, C> {
+    fn allocate_uninit<T: Scalar>(nrows: Dyn, ncols: C) -> VecStorage<MaybeUninit<T>, Dyn, C> {
         let mut data = Vec::new();
         let length = nrows.value() * ncols.value();
         data.reserve_exact(length);
@@ -99,7 +101,9 @@ impl<T: Scalar, C: Dim> Allocator<T, Dyn, C> for DefaultAllocator {
     }
 
     #[inline]
-    unsafe fn assume_init(uninit: VecStorage<MaybeUninit<T>, Dyn, C>) -> VecStorage<T, Dyn, C> {
+    unsafe fn assume_init<T: Scalar>(
+        uninit: VecStorage<MaybeUninit<T>, Dyn, C>,
+    ) -> VecStorage<T, Dyn, C> {
         // Avoids a double-drop.
         let (nrows, ncols) = uninit.shape();
         let vec: Vec<_> = uninit.into();
@@ -114,11 +118,11 @@ impl<T: Scalar, C: Dim> Allocator<T, Dyn, C> for DefaultAllocator {
     }
 
     #[inline]
-    fn allocate_from_iterator<I: IntoIterator<Item = T>>(
+    fn allocate_from_iterator<T: Scalar, I: IntoIterator<Item = T>>(
         nrows: Dyn,
         ncols: C,
         iter: I,
-    ) -> Self::Buffer {
+    ) -> Self::Buffer<T> {
         let it = iter.into_iter();
         let res: Vec<T> = it.collect();
         assert!(res.len() == nrows.value() * ncols.value(),
@@ -130,12 +134,12 @@ impl<T: Scalar, C: Dim> Allocator<T, Dyn, C> for DefaultAllocator {
 
 // Static - Dyn
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<T: Scalar, R: DimName> Allocator<T, R, Dyn> for DefaultAllocator {
-    type Buffer = VecStorage<T, R, Dyn>;
-    type BufferUninit = VecStorage<MaybeUninit<T>, R, Dyn>;
+impl<R: DimName> Allocator<R, Dyn> for DefaultAllocator {
+    type Buffer<T: Scalar> = VecStorage<T, R, Dyn>;
+    type BufferUninit<T: Scalar> = VecStorage<MaybeUninit<T>, R, Dyn>;
 
     #[inline]
-    fn allocate_uninit(nrows: R, ncols: Dyn) -> VecStorage<MaybeUninit<T>, R, Dyn> {
+    fn allocate_uninit<T: Scalar>(nrows: R, ncols: Dyn) -> VecStorage<MaybeUninit<T>, R, Dyn> {
         let mut data = Vec::new();
         let length = nrows.value() * ncols.value();
         data.reserve_exact(length);
@@ -145,7 +149,9 @@ impl<T: Scalar, R: DimName> Allocator<T, R, Dyn> for DefaultAllocator {
     }
 
     #[inline]
-    unsafe fn assume_init(uninit: VecStorage<MaybeUninit<T>, R, Dyn>) -> VecStorage<T, R, Dyn> {
+    unsafe fn assume_init<T: Scalar>(
+        uninit: VecStorage<MaybeUninit<T>, R, Dyn>,
+    ) -> VecStorage<T, R, Dyn> {
         // Avoids a double-drop.
         let (nrows, ncols) = uninit.shape();
         let vec: Vec<_> = uninit.into();
@@ -160,11 +166,11 @@ impl<T: Scalar, R: DimName> Allocator<T, R, Dyn> for DefaultAllocator {
     }
 
     #[inline]
-    fn allocate_from_iterator<I: IntoIterator<Item = T>>(
+    fn allocate_from_iterator<T: Scalar, I: IntoIterator<Item = T>>(
         nrows: R,
         ncols: Dyn,
         iter: I,
-    ) -> Self::Buffer {
+    ) -> Self::Buffer<T> {
         let it = iter.into_iter();
         let res: Vec<T> = it.collect();
         assert!(res.len() == nrows.value() * ncols.value(),
@@ -185,15 +191,15 @@ impl<T: Scalar, RFrom, CFrom, const RTO: usize, const CTO: usize>
 where
     RFrom: Dim,
     CFrom: Dim,
-    Self: Allocator<T, RFrom, CFrom>,
+    Self: Allocator<RFrom, CFrom>,
 {
     #[inline]
     unsafe fn reallocate_copy(
         rto: Const<RTO>,
         cto: Const<CTO>,
-        buf: <Self as Allocator<T, RFrom, CFrom>>::Buffer,
+        buf: <Self as Allocator<RFrom, CFrom>>::Buffer<T>,
     ) -> ArrayStorage<MaybeUninit<T>, RTO, CTO> {
-        let mut res = <Self as Allocator<T, Const<RTO>, Const<CTO>>>::allocate_uninit(rto, cto);
+        let mut res = <Self as Allocator<Const<RTO>, Const<CTO>>>::allocate_uninit(rto, cto);
 
         let (rfrom, cfrom) = buf.shape();
 
@@ -204,8 +210,8 @@ where
 
         // Safety:
         // - We don’t care about dropping elements because the caller is responsible for dropping things.
-        // - We forget `buf` so that we don’t drop the other elements.
-        std::mem::forget(buf);
+        // - We forget `buf` so that we don’t drop the other elements, but ensure the buffer itself is cleaned up.
+        buf.forget_elements();
 
         res
     }
@@ -224,7 +230,7 @@ where
         cto: CTo,
         buf: ArrayStorage<T, RFROM, CFROM>,
     ) -> VecStorage<MaybeUninit<T>, Dyn, CTo> {
-        let mut res = <Self as Allocator<T, Dyn, CTo>>::allocate_uninit(rto, cto);
+        let mut res = <Self as Allocator<Dyn, CTo>>::allocate_uninit(rto, cto);
 
         let (rfrom, cfrom) = buf.shape();
 
@@ -235,8 +241,8 @@ where
 
         // Safety:
         // - We don’t care about dropping elements because the caller is responsible for dropping things.
-        // - We forget `buf` so that we don’t drop the other elements.
-        std::mem::forget(buf);
+        // - We forget `buf` so that we don’t drop the other elements, but ensure the buffer itself is cleaned up.
+        buf.forget_elements();
 
         res
     }
@@ -255,7 +261,7 @@ where
         cto: Dyn,
         buf: ArrayStorage<T, RFROM, CFROM>,
     ) -> VecStorage<MaybeUninit<T>, RTo, Dyn> {
-        let mut res = <Self as Allocator<T, RTo, Dyn>>::allocate_uninit(rto, cto);
+        let mut res = <Self as Allocator<RTo, Dyn>>::allocate_uninit(rto, cto);
 
         let (rfrom, cfrom) = buf.shape();
 
@@ -266,8 +272,8 @@ where
 
         // Safety:
         // - We don’t care about dropping elements because the caller is responsible for dropping things.
-        // - We forget `buf` so that we don’t drop the other elements.
-        std::mem::forget(buf);
+        // - We forget `buf` so that we don’t drop the other elements, but ensure the buffer itself is cleaned up.
+        buf.forget_elements();
 
         res
     }

src/base/dimension.rs

@@ -23,7 +23,6 @@ use serde::{Deserialize, Deserializer, Serialize, Serializer};
     feature = "rkyv-serialize",
     archive_attr(derive(bytecheck::CheckBytes))
 )]
-#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
 pub struct Dyn(pub usize);
 
 #[deprecated(note = "use Dyn instead.")]
@@ -68,6 +67,10 @@ impl IsNotStaticOne for Dyn {}
 
 /// Trait implemented by any type that can be used as a dimension. This includes type-level
 /// integers and `Dyn` (for dimensions not known at compile-time).
+///
+/// # Safety
+///
+/// Hoists integers to the type level, including binary operations.
 pub unsafe trait Dim: Any + Debug + Copy + PartialEq + Send + Sync {
     #[inline(always)]
     fn is<D: Dim>() -> bool {
@@ -216,7 +219,6 @@ dim_ops!(
     archive(as = "Self")
 )]
 #[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
-#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
 pub struct Const<const R: usize>;
 
 /// Trait implemented exclusively by type-level integers.

src/base/edition.rs

@@ -21,7 +21,7 @@ impl<T: Scalar + Zero, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn upper_triangle(&self) -> OMatrix<T, R, C>
     where
-        DefaultAllocator: Allocator<T, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         let mut res = self.clone_owned();
         res.fill_lower_triangle(T::zero(), 1);
@@ -34,7 +34,7 @@ impl<T: Scalar + Zero, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn lower_triangle(&self) -> OMatrix<T, R, C>
     where
-        DefaultAllocator: Allocator<T, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         let mut res = self.clone_owned();
         res.fill_upper_triangle(T::zero(), 1);
@@ -52,7 +52,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     where
         I: IntoIterator<Item = &'a usize>,
         I::IntoIter: ExactSizeIterator + Clone,
-        DefaultAllocator: Allocator<T, Dyn, C>,
+        DefaultAllocator: Allocator<Dyn, C>,
     {
         let irows = irows.into_iter();
         let ncols = self.shape_generic().1;
@@ -89,7 +89,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     where
         I: IntoIterator<Item = &'a usize>,
         I::IntoIter: ExactSizeIterator,
-        DefaultAllocator: Allocator<T, R, Dyn>,
+        DefaultAllocator: Allocator<R, Dyn>,
     {
         let icols = icols.into_iter();
         let nrows = self.shape_generic().0;
@@ -598,7 +598,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         if nremove.value() != 0 {
             unsafe {
                 compress_rows(
-                    &mut m.as_mut_slice(),
+                    m.as_mut_slice(),
                     nrows.value(),
                     ncols.value(),
                     i,
@@ -796,7 +796,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
 
         if ninsert.value() != 0 {
             extend_rows(
-                &mut res.as_mut_slice(),
+                res.as_mut_slice(),
                 nrows.value(),
                 ncols.value(),
                 i,
@@ -909,7 +909,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
             unsafe {
                 if new_nrows.value() < nrows {
                     compress_rows(
-                        &mut data.as_mut_slice(),
+                        data.as_mut_slice(),
                         nrows,
                         ncols,
                         new_nrows.value(),
@@ -923,7 +923,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
                         new_nrows, new_ncols, data.data,
                     ));
                     extend_rows(
-                        &mut res.as_mut_slice(),
+                        res.as_mut_slice(),
                         nrows,
                         new_ncols.value(),
                         nrows,
@@ -1037,7 +1037,7 @@ impl<T: Scalar> OMatrix<T, Dyn, Dyn> {
 #[cfg(any(feature = "std", feature = "alloc"))]
 impl<T: Scalar, C: Dim> OMatrix<T, Dyn, C>
 where
-    DefaultAllocator: Allocator<T, Dyn, C>,
+    DefaultAllocator: Allocator<Dyn, C>,
 {
     /// Changes the number of rows of this matrix in-place.
     ///
@@ -1058,7 +1058,7 @@ where
 #[cfg(any(feature = "std", feature = "alloc"))]
 impl<T: Scalar, R: Dim> OMatrix<T, R, Dyn>
 where
-    DefaultAllocator: Allocator<T, R, Dyn>,
+    DefaultAllocator: Allocator<R, Dyn>,
 {
     /// Changes the number of column of this matrix in-place.
     ///

src/base/indexing.rs

@@ -519,6 +519,10 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
 
     /// Produces a view of the data at the given index, without doing
     /// any bounds checking.
+    ///
+    /// # Safety
+    ///
+    /// `index` must within bounds of the array.
     #[inline]
     #[must_use]
     pub unsafe fn get_unchecked<'a, I>(&'a self, index: I) -> I::Output
@@ -530,6 +534,9 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
 
     /// Returns a mutable view of the data at the given index, without doing
     /// any bounds checking.
+    /// # Safety
+    ///
+    /// `index` must within bounds of the array.
     #[inline]
     #[must_use]
     pub unsafe fn get_unchecked_mut<'a, I>(&'a mut self, index: I) -> I::OutputMut

src/base/interpolation.rs

@@ -2,11 +2,14 @@ use crate::storage::Storage;
 use crate::{
     Allocator, DefaultAllocator, Dim, OVector, One, RealField, Scalar, Unit, Vector, Zero,
 };
-use simba::scalar::{ClosedAdd, ClosedMul, ClosedSub};
+use simba::scalar::{ClosedAddAssign, ClosedMulAssign, ClosedSubAssign};
 
 /// # Interpolation
-impl<T: Scalar + Zero + One + ClosedAdd + ClosedSub + ClosedMul, D: Dim, S: Storage<T, D>>
-    Vector<T, D, S>
+impl<
+        T: Scalar + Zero + One + ClosedAddAssign + ClosedSubAssign + ClosedMulAssign,
+        D: Dim,
+        S: Storage<T, D>,
+    > Vector<T, D, S>
 {
     /// Returns `self * (1.0 - t) + rhs * t`, i.e., the linear blend of the vectors x and y using the scalar value a.
     ///
@@ -23,7 +26,7 @@ impl<T: Scalar + Zero + One + ClosedAdd + ClosedSub + ClosedMul, D: Dim, S: Stor
     #[must_use]
     pub fn lerp<S2: Storage<T, D>>(&self, rhs: &Vector<T, D, S2>, t: T) -> OVector<T, D>
     where
-        DefaultAllocator: Allocator<T, D>,
+        DefaultAllocator: Allocator<D>,
     {
         let mut res = self.clone_owned();
         res.axpy(t.clone(), rhs, T::one() - t);
@@ -50,7 +53,7 @@ impl<T: Scalar + Zero + One + ClosedAdd + ClosedSub + ClosedMul, D: Dim, S: Stor
     pub fn slerp<S2: Storage<T, D>>(&self, rhs: &Vector<T, D, S2>, t: T) -> OVector<T, D>
     where
         T: RealField,
-        DefaultAllocator: Allocator<T, D>,
+        DefaultAllocator: Allocator<D>,
     {
         let me = Unit::new_normalize(self.clone_owned());
         let rhs = Unit::new_normalize(rhs.clone_owned());
@@ -81,7 +84,7 @@ impl<T: RealField, D: Dim, S: Storage<T, D>> Unit<Vector<T, D, S>> {
         t: T,
     ) -> Unit<OVector<T, D>>
     where
-        DefaultAllocator: Allocator<T, D>,
+        DefaultAllocator: Allocator<D>,
     {
         // TODO: the result is wrong when self and rhs are collinear with opposite direction.
         self.try_slerp(rhs, t, T::default_epsilon())
@@ -100,7 +103,7 @@ impl<T: RealField, D: Dim, S: Storage<T, D>> Unit<Vector<T, D, S>> {
         epsilon: T,
     ) -> Option<Unit<OVector<T, D>>>
     where
-        DefaultAllocator: Allocator<T, D>,
+        DefaultAllocator: Allocator<D>,
     {
         let c_hang = self.dot(rhs);
 

src/base/iter.rs

@@ -12,26 +12,29 @@ use std::mem;
 
 use crate::base::dimension::{Dim, U1};
 use crate::base::storage::{RawStorage, RawStorageMut};
-use crate::base::{Matrix, MatrixView, MatrixViewMut, Scalar};
+use crate::base::{Matrix, MatrixView, MatrixViewMut, Scalar, ViewStorage, ViewStorageMut};
+
+#[derive(Clone, Debug)]
+struct RawIter<Ptr, T, R: Dim, C: Dim, RStride: Dim, CStride: Dim> {
+    ptr: Ptr,
+    inner_ptr: Ptr,
+    inner_end: Ptr,
+    size: usize,
+    strides: (RStride, CStride),
+    _phantoms: PhantomData<(fn() -> T, R, C)>,
+}
 
 macro_rules! iterator {
     (struct $Name:ident for $Storage:ident.$ptr: ident -> $Ptr:ty, $Ref:ty, $SRef: ty, $($derives:ident),* $(,)?) => {
-        /// An iterator through a dense matrix with arbitrary strides matrix.
-        #[derive($($derives),*)]
-        pub struct $Name<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> {
-            ptr: $Ptr,
-            inner_ptr: $Ptr,
-            inner_end: $Ptr,
-            size: usize, // We can't use an end pointer here because a stride might be zero.
-            strides: (S::RStride, S::CStride),
-            _phantoms: PhantomData<($Ref, R, C, S)>,
-        }
-
         // TODO: we need to specialize for the case where the matrix storage is owned (in which
         // case the iterator is trivial because it does not have any stride).
-        impl<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> $Name<'a, T, R, C, S> {
+        impl<T, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
+            RawIter<$Ptr, T, R, C, RStride, CStride>
+        {
             /// Creates a new iterator for the given matrix storage.
-            pub fn new(storage: $SRef) -> $Name<'a, T, R, C, S> {
+            fn new<'a, S: $Storage<T, R, C, RStride = RStride, CStride = CStride>>(
+                storage: $SRef,
+            ) -> Self {
                 let shape = storage.shape();
                 let strides = storage.strides();
                 let inner_offset = shape.0.value() * strides.0.value();
@@ -55,7 +58,7 @@ macro_rules! iterator {
                     unsafe { ptr.add(inner_offset) }
                 };
 
-                $Name {
+                RawIter {
                     ptr,
                     inner_ptr: ptr,
                     inner_end,
@@ -66,11 +69,13 @@ macro_rules! iterator {
             }
         }
 
-        impl<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> Iterator for $Name<'a, T, R, C, S> {
-            type Item = $Ref;
+        impl<T, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Iterator
+            for RawIter<$Ptr, T, R, C, RStride, CStride>
+        {
+            type Item = $Ptr;
 
             #[inline]
-            fn next(&mut self) -> Option<$Ref> {
+            fn next(&mut self) -> Option<Self::Item> {
                 unsafe {
                     if self.size == 0 {
                         None
@@ -102,10 +107,7 @@ macro_rules! iterator {
                             self.ptr = self.ptr.add(stride);
                         }
 
-                        // We want either `& *last` or `&mut *last` here, depending
-                        // on the mutability of `$Ref`.
-                        #[allow(clippy::transmute_ptr_to_ref)]
-                        Some(mem::transmute(old))
+                        Some(old)
                     }
                 }
             }
@@ -121,11 +123,11 @@ macro_rules! iterator {
             }
         }
 
-        impl<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> DoubleEndedIterator
-            for $Name<'a, T, R, C, S>
+        impl<T, R: Dim, C: Dim, RStride: Dim, CStride: Dim> DoubleEndedIterator
+            for RawIter<$Ptr, T, R, C, RStride, CStride>
         {
             #[inline]
-            fn next_back(&mut self) -> Option<$Ref> {
+            fn next_back(&mut self) -> Option<Self::Item> {
                 unsafe {
                     if self.size == 0 {
                         None
@@ -152,21 +154,85 @@ macro_rules! iterator {
                             .ptr
                             .add((outer_remaining * outer_stride + inner_remaining * inner_stride));
 
-                        // We want either `& *last` or `&mut *last` here, depending
-                        // on the mutability of `$Ref`.
-                        #[allow(clippy::transmute_ptr_to_ref)]
-                        Some(mem::transmute(last))
+                        Some(last)
                     }
                 }
             }
         }
 
+        impl<T, R: Dim, C: Dim, RStride: Dim, CStride: Dim> ExactSizeIterator
+            for RawIter<$Ptr, T, R, C, RStride, CStride>
+        {
+            #[inline]
+            fn len(&self) -> usize {
+                self.size
+            }
+        }
+
+        impl<T, R: Dim, C: Dim, RStride: Dim, CStride: Dim> FusedIterator
+            for RawIter<$Ptr, T, R, C, RStride, CStride>
+        {
+        }
+
+        /// An iterator through a dense matrix with arbitrary strides matrix.
+        #[derive($($derives),*)]
+        pub struct $Name<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> {
+            inner: RawIter<$Ptr, T, R, C, S::RStride, S::CStride>,
+            _marker: PhantomData<$Ref>,
+        }
+
+        impl<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> $Name<'a, T, R, C, S> {
+            /// Creates a new iterator for the given matrix storage.
+            pub fn new(storage: $SRef) -> Self {
+                Self {
+                    inner: RawIter::<$Ptr, T, R, C, S::RStride, S::CStride>::new(storage),
+                    _marker: PhantomData,
+                }
+            }
+        }
+
+        impl<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> Iterator for $Name<'a, T, R, C, S> {
+            type Item = $Ref;
+
+            #[inline(always)]
+            fn next(&mut self) -> Option<Self::Item> {
+                // We want either `& *last` or `&mut *last` here, depending
+                // on the mutability of `$Ref`.
+                #[allow(clippy::transmute_ptr_to_ref)]
+                self.inner.next().map(|ptr| unsafe { mem::transmute(ptr) })
+            }
+
+            #[inline(always)]
+            fn size_hint(&self) -> (usize, Option<usize>) {
+                self.inner.size_hint()
+            }
+
+            #[inline(always)]
+            fn count(self) -> usize {
+                self.inner.count()
+            }
+        }
+
+        impl<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> DoubleEndedIterator
+            for $Name<'a, T, R, C, S>
+        {
+            #[inline(always)]
+            fn next_back(&mut self) -> Option<Self::Item> {
+                // We want either `& *last` or `&mut *last` here, depending
+                // on the mutability of `$Ref`.
+                #[allow(clippy::transmute_ptr_to_ref)]
+                self.inner
+                    .next_back()
+                    .map(|ptr| unsafe { mem::transmute(ptr) })
+            }
+        }
+
         impl<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> ExactSizeIterator
             for $Name<'a, T, R, C, S>
         {
-            #[inline]
+            #[inline(always)]
             fn len(&self) -> usize {
-                self.size
+                self.inner.len()
             }
         }
 
@@ -180,6 +246,30 @@ macro_rules! iterator {
 iterator!(struct MatrixIter for RawStorage.ptr -> *const T, &'a T, &'a S, Clone, Debug);
 iterator!(struct MatrixIterMut for RawStorageMut.ptr_mut -> *mut T, &'a mut T, &'a mut S, Debug);
 
+impl<'a, T, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
+    MatrixIter<'a, T, R, C, ViewStorage<'a, T, R, C, RStride, CStride>>
+{
+    /// Creates a new iterator for the given matrix storage view.
+    pub fn new_owned(storage: ViewStorage<'a, T, R, C, RStride, CStride>) -> Self {
+        Self {
+            inner: RawIter::<*const T, T, R, C, RStride, CStride>::new(&storage),
+            _marker: PhantomData,
+        }
+    }
+}
+
+impl<'a, T, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
+    MatrixIterMut<'a, T, R, C, ViewStorageMut<'a, T, R, C, RStride, CStride>>
+{
+    /// Creates a new iterator for the given matrix storage view.
+    pub fn new_owned_mut(mut storage: ViewStorageMut<'a, T, R, C, RStride, CStride>) -> Self {
+        Self {
+            inner: RawIter::<*mut T, T, R, C, RStride, CStride>::new(&mut storage),
+            _marker: PhantomData,
+        }
+    }
+}
+
 /*
  *
  * Row iterators.
@@ -313,8 +403,9 @@ impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> ColumnIter<'a, T, R, C,
         }
     }
 
+    #[cfg(feature = "rayon")]
     pub(crate) fn split_at(self, index: usize) -> (Self, Self) {
-        // SAFETY: this makes sur the generated ranges are valid.
+        // SAFETY: this makes sure the generated ranges are valid.
         let split_pos = (self.range.start + index).min(self.range.end);
 
         let left_iter = ColumnIter {
@@ -401,8 +492,9 @@ impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> ColumnIterMut<'a, T,
         }
     }
 
+    #[cfg(feature = "rayon")]
     pub(crate) fn split_at(self, index: usize) -> (Self, Self) {
-        // SAFETY: this makes sur the generated ranges are valid.
+        // SAFETY: this makes sure the generated ranges are valid.
         let split_pos = (self.range.start + index).min(self.range.end);
 
         let left_iter = ColumnIterMut {

src/base/matrix.rs

@@ -18,7 +18,7 @@ use rkyv::bytecheck;
 #[cfg(feature = "rkyv-serialize-no-std")]
 use rkyv::{with::With, Archive, Archived};
 
-use simba::scalar::{ClosedAdd, ClosedMul, ClosedSub, Field, SupersetOf};
+use simba::scalar::{ClosedAddAssign, ClosedMulAssign, ClosedSubAssign, Field, SupersetOf};
 use simba::simd::SimdPartialOrd;
 
 use crate::base::allocator::{Allocator, SameShapeAllocator, SameShapeC, SameShapeR};
@@ -171,7 +171,6 @@ pub type MatrixCross<T, R1, C1, R2, C2> =
     )
 )]
 #[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
-#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
 pub struct Matrix<T, R, C, S> {
     /// The data storage that contains all the matrix components. Disappointed?
     ///
@@ -313,6 +312,10 @@ where
 impl<T, R, C, S> Matrix<T, R, C, S> {
     /// Creates a new matrix with the given data without statically checking that the matrix
     /// dimension matches the storage dimension.
+    ///
+    /// # Safety
+    ///
+    /// The storage dimension must match the given dimensions.
     #[inline(always)]
     pub const unsafe fn from_data_statically_unchecked(data: S) -> Matrix<T, R, C, S> {
         Matrix {
@@ -380,9 +383,9 @@ impl<T> RowDVector<T> {
     }
 }
 
-impl<T, R: Dim, C: Dim> UninitMatrix<T, R, C>
+impl<T: Scalar, R: Dim, C: Dim> UninitMatrix<T, R, C>
 where
-    DefaultAllocator: Allocator<T, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     /// Assumes a matrix's entries to be initialized. This operation should be near zero-cost.
     ///
@@ -391,7 +394,7 @@ where
     /// or Undefined Behavior will immediately occur.
     #[inline(always)]
     pub unsafe fn assume_init(self) -> OMatrix<T, R, C> {
-        OMatrix::from_data(<DefaultAllocator as Allocator<T, R, C>>::assume_init(
+        OMatrix::from_data(<DefaultAllocator as Allocator<R, C>>::assume_init(
             self.data,
         ))
     }
@@ -530,7 +533,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
         max_relative: T::Epsilon,
     ) -> bool
     where
-        T: RelativeEq,
+        T: RelativeEq + Scalar,
         R2: Dim,
         C2: Dim,
         SB: Storage<T, R2, C2>,
@@ -565,7 +568,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     where
         T: Scalar,
         S: Storage<T, R, C>,
-        DefaultAllocator: Allocator<T, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         Matrix::from_data(self.data.into_owned())
     }
@@ -581,7 +584,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
         S: Storage<T, R, C>,
         R2: Dim,
         C2: Dim,
-        DefaultAllocator: SameShapeAllocator<T, R, C, R2, C2>,
+        DefaultAllocator: SameShapeAllocator<R, C, R2, C2>,
         ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
     {
         if TypeId::of::<SameShapeStorage<T, R, C, R2, C2>>() == TypeId::of::<Owned<T, R, C>>() {
@@ -606,7 +609,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     where
         T: Scalar,
         S: Storage<T, R, C>,
-        DefaultAllocator: Allocator<T, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         Matrix::from_data(self.data.clone_owned())
     }
@@ -621,7 +624,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
         S: Storage<T, R, C>,
         R2: Dim,
         C2: Dim,
-        DefaultAllocator: SameShapeAllocator<T, R, C, R2, C2>,
+        DefaultAllocator: SameShapeAllocator<R, C, R2, C2>,
         ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
     {
         let (nrows, ncols) = self.shape();
@@ -697,7 +700,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     pub fn transpose(&self) -> OMatrix<T, C, R>
     where
         T: Scalar,
-        DefaultAllocator: Allocator<T, C, R>,
+        DefaultAllocator: Allocator<C, R>,
     {
         let (nrows, ncols) = self.shape_generic();
 
@@ -716,7 +719,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     pub fn map<T2: Scalar, F: FnMut(T) -> T2>(&self, mut f: F) -> OMatrix<T2, R, C>
     where
         T: Scalar,
-        DefaultAllocator: Allocator<T2, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         let (nrows, ncols) = self.shape_generic();
         let mut res = Matrix::uninit(nrows, ncols);
@@ -748,7 +751,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     where
         T: Scalar,
         OMatrix<T2, R, C>: SupersetOf<Self>,
-        DefaultAllocator: Allocator<T2, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         crate::convert(self)
     }
@@ -766,7 +769,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     where
         T: Scalar,
         Self: SupersetOf<OMatrix<T2, R, C>>,
-        DefaultAllocator: Allocator<T2, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         crate::try_convert(self)
     }
@@ -803,7 +806,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     ) -> OMatrix<T2, R, C>
     where
         T: Scalar,
-        DefaultAllocator: Allocator<T2, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         let (nrows, ncols) = self.shape_generic();
         let mut res = Matrix::uninit(nrows, ncols);
@@ -833,7 +836,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
         N3: Scalar,
         S2: RawStorage<T2, R, C>,
         F: FnMut(T, T2) -> N3,
-        DefaultAllocator: Allocator<N3, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         let (nrows, ncols) = self.shape_generic();
         let mut res = Matrix::uninit(nrows, ncols);
@@ -877,7 +880,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
         S2: RawStorage<T2, R, C>,
         S3: RawStorage<N3, R, C>,
         F: FnMut(T, T2, N3) -> N4,
-        DefaultAllocator: Allocator<N4, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         let (nrows, ncols) = self.shape_generic();
         let mut res = Matrix::uninit(nrows, ncols);
@@ -1194,6 +1197,10 @@ impl<T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> Matrix<T, R, C, S> {
     }
 
     /// Swaps two entries without bound-checking.
+    ///
+    /// # Safety
+    ///
+    /// Both `(r, c)` must have `r < nrows(), c < ncols()`.
     #[inline]
     pub unsafe fn swap_unchecked(&mut self, row_cols1: (usize, usize), row_cols2: (usize, usize)) {
         debug_assert!(row_cols1.0 < self.nrows() && row_cols1.1 < self.ncols());
@@ -1300,6 +1307,8 @@ impl<T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> Matrix<T, R, C, S> {
 
 impl<T, D: Dim, S: RawStorage<T, D>> Vector<T, D, S> {
     /// Gets a reference to the i-th element of this column vector without bound checking.
+    /// # Safety
+    /// `i` must be less than `D`.
     #[inline]
     #[must_use]
     pub unsafe fn vget_unchecked(&self, i: usize) -> &T {
@@ -1311,6 +1320,8 @@ impl<T, D: Dim, S: RawStorage<T, D>> Vector<T, D, S> {
 
 impl<T, D: Dim, S: RawStorageMut<T, D>> Vector<T, D, S> {
     /// Gets a mutable reference to the i-th element of this column vector without bound checking.
+    /// # Safety
+    /// `i` must be less than `D`.
     #[inline]
     #[must_use]
     pub unsafe fn vget_unchecked_mut(&mut self, i: usize) -> &mut T {
@@ -1409,7 +1420,7 @@ impl<T: SimdComplexField, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C
     #[must_use = "Did you mean to use adjoint_mut()?"]
     pub fn adjoint(&self) -> OMatrix<T, C, R>
     where
-        DefaultAllocator: Allocator<T, C, R>,
+        DefaultAllocator: Allocator<C, R>,
     {
         let (nrows, ncols) = self.shape_generic();
 
@@ -1438,7 +1449,7 @@ impl<T: SimdComplexField, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C
     #[inline]
     pub fn conjugate_transpose(&self) -> OMatrix<T, C, R>
     where
-        DefaultAllocator: Allocator<T, C, R>,
+        DefaultAllocator: Allocator<C, R>,
     {
         self.adjoint()
     }
@@ -1448,7 +1459,7 @@ impl<T: SimdComplexField, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C
     #[must_use = "Did you mean to use conjugate_mut()?"]
     pub fn conjugate(&self) -> OMatrix<T, R, C>
     where
-        DefaultAllocator: Allocator<T, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         self.map(|e| e.simd_conjugate())
     }
@@ -1458,7 +1469,7 @@ impl<T: SimdComplexField, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C
     #[must_use = "Did you mean to use unscale_mut()?"]
     pub fn unscale(&self, real: T::SimdRealField) -> OMatrix<T, R, C>
     where
-        DefaultAllocator: Allocator<T, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         self.map(|e| e.simd_unscale(real.clone()))
     }
@@ -1468,7 +1479,7 @@ impl<T: SimdComplexField, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C
     #[must_use = "Did you mean to use scale_mut()?"]
     pub fn scale(&self, real: T::SimdRealField) -> OMatrix<T, R, C>
     where
-        DefaultAllocator: Allocator<T, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         self.map(|e| e.simd_scale(real.clone()))
     }
@@ -1536,7 +1547,7 @@ impl<T: Scalar, D: Dim, S: RawStorage<T, D, D>> SquareMatrix<T, D, S> {
     #[must_use]
     pub fn diagonal(&self) -> OVector<T, D>
     where
-        DefaultAllocator: Allocator<T, D>,
+        DefaultAllocator: Allocator<D>,
     {
         self.map_diagonal(|e| e)
     }
@@ -1548,7 +1559,7 @@ impl<T: Scalar, D: Dim, S: RawStorage<T, D, D>> SquareMatrix<T, D, S> {
     #[must_use]
     pub fn map_diagonal<T2: Scalar>(&self, mut f: impl FnMut(T) -> T2) -> OVector<T2, D>
     where
-        DefaultAllocator: Allocator<T2, D>,
+        DefaultAllocator: Allocator<D>,
     {
         assert!(
             self.is_square(),
@@ -1575,7 +1586,7 @@ impl<T: Scalar, D: Dim, S: RawStorage<T, D, D>> SquareMatrix<T, D, S> {
     #[must_use]
     pub fn trace(&self) -> T
     where
-        T: Scalar + Zero + ClosedAdd,
+        T: Scalar + Zero + ClosedAddAssign,
     {
         assert!(
             self.is_square(),
@@ -1599,7 +1610,7 @@ impl<T: SimdComplexField, D: Dim, S: Storage<T, D, D>> SquareMatrix<T, D, S> {
     #[must_use]
     pub fn symmetric_part(&self) -> OMatrix<T, D, D>
     where
-        DefaultAllocator: Allocator<T, D, D>,
+        DefaultAllocator: Allocator<D, D>,
     {
         assert!(
             self.is_square(),
@@ -1616,7 +1627,7 @@ impl<T: SimdComplexField, D: Dim, S: Storage<T, D, D>> SquareMatrix<T, D, S> {
     #[must_use]
     pub fn hermitian_part(&self) -> OMatrix<T, D, D>
     where
-        DefaultAllocator: Allocator<T, D, D>,
+        DefaultAllocator: Allocator<D, D>,
     {
         assert!(
             self.is_square(),
@@ -1639,7 +1650,7 @@ impl<T: Scalar + Zero + One, D: DimAdd<U1> + IsNotStaticOne, S: RawStorage<T, D,
     #[must_use]
     pub fn to_homogeneous(&self) -> OMatrix<T, DimSum<D, U1>, DimSum<D, U1>>
     where
-        DefaultAllocator: Allocator<T, DimSum<D, U1>, DimSum<D, U1>>,
+        DefaultAllocator: Allocator<DimSum<D, U1>, DimSum<D, U1>>,
     {
         assert!(
             self.is_square(),
@@ -1660,7 +1671,7 @@ impl<T: Scalar + Zero, D: DimAdd<U1>, S: RawStorage<T, D>> Vector<T, D, S> {
     #[must_use]
     pub fn to_homogeneous(&self) -> OVector<T, DimSum<D, U1>>
     where
-        DefaultAllocator: Allocator<T, DimSum<D, U1>>,
+        DefaultAllocator: Allocator<DimSum<D, U1>>,
     {
         self.push(T::zero())
     }
@@ -1671,7 +1682,7 @@ impl<T: Scalar + Zero, D: DimAdd<U1>, S: RawStorage<T, D>> Vector<T, D, S> {
     pub fn from_homogeneous<SB>(v: Vector<T, DimSum<D, U1>, SB>) -> Option<OVector<T, D>>
     where
         SB: RawStorage<T, DimSum<D, U1>>,
-        DefaultAllocator: Allocator<T, D>,
+        DefaultAllocator: Allocator<D>,
     {
         if v[v.len() - 1].is_zero() {
             let nrows = D::from_usize(v.len() - 1);
@@ -1688,7 +1699,7 @@ impl<T: Scalar, D: DimAdd<U1>, S: RawStorage<T, D>> Vector<T, D, S> {
     #[must_use]
     pub fn push(&self, element: T) -> OVector<T, DimSum<D, U1>>
     where
-        DefaultAllocator: Allocator<T, DimSum<D, U1>>,
+        DefaultAllocator: Allocator<DimSum<D, U1>>,
     {
         let len = self.len();
         let hnrows = DimSum::<D, U1>::from_usize(len + 1);
@@ -1991,8 +2002,12 @@ mod tests {
 }
 
 /// # Cross product
-impl<T: Scalar + ClosedAdd + ClosedSub + ClosedMul, R: Dim, C: Dim, S: RawStorage<T, R, C>>
-    Matrix<T, R, C, S>
+impl<
+        T: Scalar + ClosedAddAssign + ClosedSubAssign + ClosedMulAssign,
+        R: Dim,
+        C: Dim,
+        S: RawStorage<T, R, C>,
+    > Matrix<T, R, C, S>
 {
     /// The perpendicular product between two 2D column vectors, i.e. `a.x * b.y - a.y * b.x`.
     #[inline]
@@ -2041,7 +2056,7 @@ impl<T: Scalar + ClosedAdd + ClosedSub + ClosedMul, R: Dim, C: Dim, S: RawStorag
         R2: Dim,
         C2: Dim,
         SB: RawStorage<T, R2, C2>,
-        DefaultAllocator: SameShapeAllocator<T, R, C, R2, C2>,
+        DefaultAllocator: SameShapeAllocator<R, C, R2, C2>,
         ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
     {
         let shape = self.shape();
@@ -2241,7 +2256,7 @@ where
     where
         T: Scalar,
         OVector<T2, D>: SupersetOf<Vector<T, D, S>>,
-        DefaultAllocator: Allocator<T2, D, U1>,
+        DefaultAllocator: Allocator<D, U1>,
     {
         Unit::new_unchecked(crate::convert_ref(self.as_ref()))
     }

src/base/matrix_simba.rs

@@ -15,16 +15,12 @@ where
     R: Dim,
     C: Dim,
     T::Element: Scalar,
-    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
+    const LANES: usize = T::LANES;
     type Element = OMatrix<T::Element, R, C>;
     type SimdBool = T::SimdBool;
 
-    #[inline]
-    fn lanes() -> usize {
-        T::lanes()
-    }
-
     #[inline]
     fn splat(val: Self::Element) -> Self {
         val.map(T::splat)

src/base/matrix_view.rs

@@ -43,6 +43,10 @@ macro_rules! view_storage_impl (
 
         impl<'a, T, R: Dim, C: Dim, RStride: Dim, CStride: Dim> $T<'a, T, R, C, RStride, CStride> {
             /// Create a new matrix view without bounds checking and from a raw pointer.
+            ///
+            /// # Safety
+            ///
+            /// `*ptr` must point to memory that is valid `[T; R * C]`.
             #[inline]
             pub unsafe fn from_raw_parts(ptr:     $Ptr,
                                          shape:   (R, C),
@@ -63,6 +67,11 @@ macro_rules! view_storage_impl (
         // Dyn is arbitrary. It's just to be able to call the constructors with `Slice::`
         impl<'a, T, R: Dim, C: Dim> $T<'a, T, R, C, Dyn, Dyn> {
             /// Create a new matrix view without bounds checking.
+            ///
+            /// # Safety
+            ///
+            /// `storage` contains sufficient elements beyond `start + R * C` such that all
+            /// accesses are within bounds.
             #[inline]
             pub unsafe fn new_unchecked<RStor, CStor, S>(storage: $SRef, start: (usize, usize), shape: (R, C))
                 -> $T<'a, T, R, C, S::RStride, S::CStride>
@@ -75,6 +84,10 @@ macro_rules! view_storage_impl (
             }
 
             /// Create a new matrix view without bounds checking.
+            ///
+            /// # Safety
+            ///
+            /// `strides` must be a valid stride indexing.
             #[inline]
             pub unsafe fn new_with_strides_unchecked<S, RStor, CStor, RStride, CStride>(storage: $SRef,
                                                                                         start:   (usize, usize),
@@ -128,12 +141,7 @@ impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Clone
 {
     #[inline]
     fn clone(&self) -> Self {
-        Self {
-            ptr: self.ptr,
-            shape: self.shape,
-            strides: self.strides,
-            _phantoms: PhantomData,
-        }
+        *self
     }
 }
 
@@ -210,17 +218,22 @@ macro_rules! storage_impl(
             for $T<'a, T, R, C, RStride, CStride> {
             #[inline]
             fn into_owned(self) -> Owned<T, R, C>
-                where DefaultAllocator: Allocator<T, R, C> {
+                where DefaultAllocator: Allocator<R, C> {
                 self.clone_owned()
             }
 
             #[inline]
             fn clone_owned(&self) -> Owned<T, R, C>
-                where DefaultAllocator: Allocator<T, R, C> {
+                where DefaultAllocator: Allocator<R, C> {
                 let (nrows, ncols) = self.shape();
                 let it = MatrixIter::new(self).cloned();
                 DefaultAllocator::allocate_from_iterator(nrows, ncols, it)
             }
+
+            #[inline]
+            fn forget_elements(self) {
+                // No cleanup required.
+            }
         }
     )*}
 );
@@ -538,8 +551,8 @@ macro_rules! matrix_view_impl (
             $me.$generic_view_with_steps(start, shape, steps)
         }
 
-        /// Slices this matrix starting at its component `(irow, icol)` and with `(R::dim(),
-        /// CView::dim())` consecutive components.
+        /// Slices this matrix starting at its component `(irow, icol)` and with `(RVIEW, CVIEW)`
+        /// consecutive components.
         #[inline]
         #[deprecated = slice_deprecation_note!($fixed_view)]
         pub fn $fixed_slice<const RVIEW: usize, const CVIEW: usize>($me: $Me, irow: usize, icol: usize)
@@ -547,8 +560,8 @@ macro_rules! matrix_view_impl (
             $me.$fixed_view(irow, icol)
         }
 
-        /// Return a view of this matrix starting at its component `(irow, icol)` and with `(R::dim(),
-        /// CView::dim())` consecutive components.
+        /// Return a view of this matrix starting at its component `(irow, icol)` and with
+        /// `(RVIEW, CVIEW)` consecutive components.
         #[inline]
         pub fn $fixed_view<const RVIEW: usize, const CVIEW: usize>($me: $Me, irow: usize, icol: usize)
             -> $MatrixView<'_, T, Const<RVIEW>, Const<CVIEW>, S::RStride, S::CStride> {

src/base/norm.rs

@@ -301,7 +301,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     pub fn normalize(&self) -> OMatrix<T, R, C>
     where
         T: SimdComplexField,
-        DefaultAllocator: Allocator<T, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         self.unscale(self.norm())
     }
@@ -325,7 +325,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     where
         T: SimdComplexField,
         T::Element: Scalar,
-        DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         let n = self.norm();
         let le = n.clone().simd_le(min_norm);
@@ -336,7 +336,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     /// Sets the magnitude of this vector unless it is smaller than `min_magnitude`.
     ///
     /// If `self.magnitude()` is smaller than `min_magnitude`, it will be left unchanged.
-    /// Otherwise this is equivalent to: `*self = self.normalize() * magnitude.
+    /// Otherwise this is equivalent to: `*self = self.normalize() * magnitude`.
     #[inline]
     pub fn try_set_magnitude(&mut self, magnitude: T::RealField, min_magnitude: T::RealField)
     where
@@ -356,7 +356,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     pub fn cap_magnitude(&self, max: T::RealField) -> OMatrix<T, R, C>
     where
         T: ComplexField,
-        DefaultAllocator: Allocator<T, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         let n = self.norm();
 
@@ -374,7 +374,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     where
         T: SimdComplexField,
         T::Element: Scalar,
-        DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         let n = self.norm();
         let scaled = self.scale(max.clone() / n.clone());
@@ -390,7 +390,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     pub fn try_normalize(&self, min_norm: T::RealField) -> Option<OMatrix<T, R, C>>
     where
         T: ComplexField,
-        DefaultAllocator: Allocator<T, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         let n = self.norm();
 
@@ -430,7 +430,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
     where
         T: SimdComplexField,
         T::Element: Scalar,
-        DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
+        DefaultAllocator: Allocator<R, C>,
     {
         let n = self.norm();
         let le = n.clone().simd_le(min_norm);
@@ -459,7 +459,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
 
 impl<T: SimdComplexField, R: Dim, C: Dim> Normed for OMatrix<T, R, C>
 where
-    DefaultAllocator: Allocator<T, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     type Norm = T::SimdRealField;
 
@@ -486,7 +486,7 @@ where
 
 impl<T: Scalar + ClosedNeg, R: Dim, C: Dim> Neg for Unit<OMatrix<T, R, C>>
 where
-    DefaultAllocator: Allocator<T, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     type Output = Unit<OMatrix<T, R, C>>;
 
@@ -503,7 +503,7 @@ where
 /// # Basis and orthogonalization
 impl<T: ComplexField, D: DimName> OVector<T, D>
 where
-    DefaultAllocator: Allocator<T, D>,
+    DefaultAllocator: Allocator<D>,
 {
     /// The i-the canonical basis element.
     #[inline]
@@ -525,7 +525,7 @@ where
                 let (elt, basis) = vs[..i + 1].split_last_mut().unwrap();
 
                 for basis_element in &basis[..nbasis_elements] {
-                    *elt -= &*basis_element * elt.dot(basis_element)
+                    *elt -= basis_element * elt.dot(basis_element)
                 }
             }
 

src/base/ops.rs

@@ -4,7 +4,9 @@ use std::ops::{
     Add, AddAssign, Div, DivAssign, Index, IndexMut, Mul, MulAssign, Neg, Sub, SubAssign,
 };
 
-use simba::scalar::{ClosedAdd, ClosedDiv, ClosedMul, ClosedNeg, ClosedSub};
+use simba::scalar::{
+    ClosedAddAssign, ClosedDivAssign, ClosedMulAssign, ClosedNeg, ClosedSubAssign,
+};
 
 use crate::base::allocator::{Allocator, SameShapeAllocator, SameShapeC, SameShapeR};
 use crate::base::blas_uninit::gemm_uninit;
@@ -81,7 +83,7 @@ impl<T, R: Dim, C: Dim, S> Neg for Matrix<T, R, C, S>
 where
     T: Scalar + ClosedNeg,
     S: Storage<T, R, C>,
-    DefaultAllocator: Allocator<T, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     type Output = OMatrix<T, R, C>;
 
@@ -97,7 +99,7 @@ impl<'a, T, R: Dim, C: Dim, S> Neg for &'a Matrix<T, R, C, S>
 where
     T: Scalar + ClosedNeg,
     S: Storage<T, R, C>,
-    DefaultAllocator: Allocator<T, R, C>,
+    DefaultAllocator: Allocator<R, C>,
 {
     type Output = OMatrix<T, R, C>;
 
@@ -262,7 +264,7 @@ macro_rules! componentwise_binop_impl(
                   T: Scalar + $bound,
                   SA: Storage<T, R1, C1>,
                   SB: Storage<T, R2, C2>,
-                  DefaultAllocator: SameShapeAllocator<T, R1, C1, R2, C2>,
+                  DefaultAllocator: SameShapeAllocator<R1, C1, R2, C2>,
                   ShapeConstraint:  SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
             type Output = MatrixSum<T, R1, C1, R2, C2>;
 
@@ -280,7 +282,7 @@ macro_rules! componentwise_binop_impl(
                   T: Scalar + $bound,
                   SA: Storage<T, R1, C1>,
                   SB: Storage<T, R2, C2>,
-                  DefaultAllocator: SameShapeAllocator<T, R2, C2, R1, C1>,
+                  DefaultAllocator: SameShapeAllocator<R2, C2, R1, C1>,
                   ShapeConstraint:  SameNumberOfRows<R2, R1> + SameNumberOfColumns<C2, C1> {
             type Output = MatrixSum<T, R2, C2, R1, C1>;
 
@@ -298,7 +300,7 @@ macro_rules! componentwise_binop_impl(
                   T: Scalar + $bound,
                   SA: Storage<T, R1, C1>,
                   SB: Storage<T, R2, C2>,
-                  DefaultAllocator: SameShapeAllocator<T, R1, C1, R2, C2>,
+                  DefaultAllocator: SameShapeAllocator<R1, C1, R2, C2>,
                   ShapeConstraint:  SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
             type Output = MatrixSum<T, R1, C1, R2, C2>;
 
@@ -313,7 +315,7 @@ macro_rules! componentwise_binop_impl(
                   T: Scalar + $bound,
                   SA: Storage<T, R1, C1>,
                   SB: Storage<T, R2, C2>,
-                  DefaultAllocator: SameShapeAllocator<T, R1, C1, R2, C2>,
+                  DefaultAllocator: SameShapeAllocator<R1, C1, R2, C2>,
                   ShapeConstraint:  SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
             type Output = MatrixSum<T, R1, C1, R2, C2>;
 
@@ -357,17 +359,17 @@ macro_rules! componentwise_binop_impl(
     }
 );
 
-componentwise_binop_impl!(Add, add, ClosedAdd;
+componentwise_binop_impl!(Add, add, ClosedAddAssign;
                           AddAssign, add_assign, add_assign_statically_unchecked, add_assign_statically_unchecked_mut;
                           add_to, add_to_statically_unchecked_uninit);
-componentwise_binop_impl!(Sub, sub, ClosedSub;
+componentwise_binop_impl!(Sub, sub, ClosedSubAssign;
                           SubAssign, sub_assign, sub_assign_statically_unchecked, sub_assign_statically_unchecked_mut;
                           sub_to, sub_to_statically_unchecked_uninit);
 
 impl<T, R: DimName, C: DimName> iter::Sum for OMatrix<T, R, C>
 where
-    T: Scalar + ClosedAdd + Zero,
-    DefaultAllocator: Allocator<T, R, C>,
+    T: Scalar + ClosedAddAssign + Zero,
+    DefaultAllocator: Allocator<R, C>,
 {
     fn sum<I: Iterator<Item = OMatrix<T, R, C>>>(iter: I) -> OMatrix<T, R, C> {
         iter.fold(Matrix::zero(), |acc, x| acc + x)
@@ -376,8 +378,8 @@ where
 
 impl<T, C: Dim> iter::Sum for OMatrix<T, Dyn, C>
 where
-    T: Scalar + ClosedAdd + Zero,
-    DefaultAllocator: Allocator<T, Dyn, C>,
+    T: Scalar + ClosedAddAssign + Zero,
+    DefaultAllocator: Allocator<Dyn, C>,
 {
     /// # Example
     /// ```
@@ -406,8 +408,8 @@ where
 
 impl<'a, T, R: DimName, C: DimName> iter::Sum<&'a OMatrix<T, R, C>> for OMatrix<T, R, C>
 where
-    T: Scalar + ClosedAdd + Zero,
-    DefaultAllocator: Allocator<T, R, C>,
+    T: Scalar + ClosedAddAssign + Zero,
+    DefaultAllocator: Allocator<R, C>,
 {
     fn sum<I: Iterator<Item = &'a OMatrix<T, R, C>>>(iter: I) -> OMatrix<T, R, C> {
         iter.fold(Matrix::zero(), |acc, x| acc + x)
@@ -416,8 +418,8 @@ where
 
 impl<'a, T, C: Dim> iter::Sum<&'a OMatrix<T, Dyn, C>> for OMatrix<T, Dyn, C>
 where
-    T: Scalar + ClosedAdd + Zero,
-    DefaultAllocator: Allocator<T, Dyn, C>,
+    T: Scalar + ClosedAddAssign + Zero,
+    DefaultAllocator: Allocator<Dyn, C>,
 {
     /// # Example
     /// ```
@@ -458,7 +460,7 @@ macro_rules! componentwise_scalarop_impl(
         impl<T, R: Dim, C: Dim, S> $Trait<T> for Matrix<T, R, C, S>
             where T: Scalar + $bound,
                   S: Storage<T, R, C>,
-                  DefaultAllocator: Allocator<T, R, C> {
+                  DefaultAllocator: Allocator<R, C> {
             type Output = OMatrix<T, R, C>;
 
             #[inline]
@@ -482,7 +484,7 @@ macro_rules! componentwise_scalarop_impl(
         impl<'a, T, R: Dim, C: Dim, S> $Trait<T> for &'a Matrix<T, R, C, S>
             where T: Scalar + $bound,
                   S: Storage<T, R, C>,
-                  DefaultAllocator: Allocator<T, R, C> {
+                  DefaultAllocator: Allocator<R, C> {
             type Output = OMatrix<T, R, C>;
 
             #[inline]
@@ -506,13 +508,13 @@ macro_rules! componentwise_scalarop_impl(
     }
 );
 
-componentwise_scalarop_impl!(Mul, mul, ClosedMul; MulAssign, mul_assign);
-componentwise_scalarop_impl!(Div, div, ClosedDiv; DivAssign, div_assign);
+componentwise_scalarop_impl!(Mul, mul, ClosedMulAssign; MulAssign, mul_assign);
+componentwise_scalarop_impl!(Div, div, ClosedDivAssign; DivAssign, div_assign);
 
 macro_rules! left_scalar_mul_impl(
     ($($T: ty),* $(,)*) => {$(
         impl<R: Dim, C: Dim, S: Storage<$T, R, C>> Mul<Matrix<$T, R, C, S>> for $T
-            where DefaultAllocator: Allocator<$T, R, C> {
+            where DefaultAllocator: Allocator<R, C> {
             type Output = OMatrix<$T, R, C>;
 
             #[inline]
@@ -534,7 +536,7 @@ macro_rules! left_scalar_mul_impl(
         }
 
         impl<'b, R: Dim, C: Dim, S: Storage<$T, R, C>> Mul<&'b Matrix<$T, R, C, S>> for $T
-            where DefaultAllocator: Allocator<$T, R, C> {
+            where DefaultAllocator: Allocator<R, C> {
             type Output = OMatrix<$T, R, C>;
 
             #[inline]
@@ -551,10 +553,10 @@ left_scalar_mul_impl!(u8, u16, u32, u64, usize, i8, i16, i32, i64, isize, f32, f
 impl<'a, 'b, T, R1: Dim, C1: Dim, R2: Dim, C2: Dim, SA, SB> Mul<&'b Matrix<T, R2, C2, SB>>
     for &'a Matrix<T, R1, C1, SA>
 where
-    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + One + ClosedAddAssign + ClosedMulAssign,
     SA: Storage<T, R1, C1>,
     SB: Storage<T, R2, C2>,
-    DefaultAllocator: Allocator<T, R1, C2>,
+    DefaultAllocator: Allocator<R1, C2>,
     ShapeConstraint: AreMultipliable<R1, C1, R2, C2>,
 {
     type Output = OMatrix<T, R1, C2>;
@@ -573,10 +575,10 @@ where
 impl<'a, T, R1: Dim, C1: Dim, R2: Dim, C2: Dim, SA, SB> Mul<Matrix<T, R2, C2, SB>>
     for &'a Matrix<T, R1, C1, SA>
 where
-    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + One + ClosedAddAssign + ClosedMulAssign,
     SB: Storage<T, R2, C2>,
     SA: Storage<T, R1, C1>,
-    DefaultAllocator: Allocator<T, R1, C2>,
+    DefaultAllocator: Allocator<R1, C2>,
     ShapeConstraint: AreMultipliable<R1, C1, R2, C2>,
 {
     type Output = OMatrix<T, R1, C2>;
@@ -590,10 +592,10 @@ where
 impl<'b, T, R1: Dim, C1: Dim, R2: Dim, C2: Dim, SA, SB> Mul<&'b Matrix<T, R2, C2, SB>>
     for Matrix<T, R1, C1, SA>
 where
-    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + One + ClosedAddAssign + ClosedMulAssign,
     SB: Storage<T, R2, C2>,
     SA: Storage<T, R1, C1>,
-    DefaultAllocator: Allocator<T, R1, C2>,
+    DefaultAllocator: Allocator<R1, C2>,
     ShapeConstraint: AreMultipliable<R1, C1, R2, C2>,
 {
     type Output = OMatrix<T, R1, C2>;
@@ -607,10 +609,10 @@ where
 impl<T, R1: Dim, C1: Dim, R2: Dim, C2: Dim, SA, SB> Mul<Matrix<T, R2, C2, SB>>
     for Matrix<T, R1, C1, SA>
 where
-    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + One + ClosedAddAssign + ClosedMulAssign,
     SB: Storage<T, R2, C2>,
     SA: Storage<T, R1, C1>,
-    DefaultAllocator: Allocator<T, R1, C2>,
+    DefaultAllocator: Allocator<R1, C2>,
     ShapeConstraint: AreMultipliable<R1, C1, R2, C2>,
 {
     type Output = OMatrix<T, R1, C2>;
@@ -629,11 +631,11 @@ where
     R1: Dim,
     C1: Dim,
     R2: Dim,
-    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + One + ClosedAddAssign + ClosedMulAssign,
     SB: Storage<T, R2, C1>,
     SA: StorageMut<T, R1, C1> + IsContiguous + Clone, // TODO: get rid of the IsContiguous
     ShapeConstraint: AreMultipliable<R1, C1, R2, C1>,
-    DefaultAllocator: Allocator<T, R1, C1, Buffer = SA>,
+    DefaultAllocator: Allocator<R1, C1, Buffer<T> = SA>,
 {
     #[inline]
     fn mul_assign(&mut self, rhs: Matrix<T, R2, C1, SB>) {
@@ -646,12 +648,12 @@ where
     R1: Dim,
     C1: Dim,
     R2: Dim,
-    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + One + ClosedAddAssign + ClosedMulAssign,
     SB: Storage<T, R2, C1>,
     SA: StorageMut<T, R1, C1> + IsContiguous + Clone, // TODO: get rid of the IsContiguous
     ShapeConstraint: AreMultipliable<R1, C1, R2, C1>,
     // TODO: this is too restrictive. See comments for the non-ref version.
-    DefaultAllocator: Allocator<T, R1, C1, Buffer = SA>,
+    DefaultAllocator: Allocator<R1, C1, Buffer<T> = SA>,
 {
     #[inline]
     fn mul_assign(&mut self, rhs: &'b Matrix<T, R2, C1, SB>) {
@@ -662,7 +664,7 @@ where
 /// # Special multiplications.
 impl<T, R1: Dim, C1: Dim, SA> Matrix<T, R1, C1, SA>
 where
-    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + One + ClosedAddAssign + ClosedMulAssign,
     SA: Storage<T, R1, C1>,
 {
     /// Equivalent to `self.transpose() * rhs`.
@@ -671,7 +673,7 @@ where
     pub fn tr_mul<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> OMatrix<T, C1, C2>
     where
         SB: Storage<T, R2, C2>,
-        DefaultAllocator: Allocator<T, C1, C2>,
+        DefaultAllocator: Allocator<C1, C2>,
         ShapeConstraint: SameNumberOfRows<R1, R2>,
     {
         let mut res = Matrix::uninit(self.shape_generic().1, rhs.shape_generic().1);
@@ -687,7 +689,7 @@ where
     where
         T: SimdComplexField,
         SB: Storage<T, R2, C2>,
-        DefaultAllocator: Allocator<T, C1, C2>,
+        DefaultAllocator: Allocator<C1, C2>,
         ShapeConstraint: SameNumberOfRows<R1, R2>,
     {
         let mut res = Matrix::uninit(self.shape_generic().1, rhs.shape_generic().1);
@@ -799,11 +801,11 @@ where
         rhs: &Matrix<T, R2, C2, SB>,
     ) -> OMatrix<T, DimProd<R1, R2>, DimProd<C1, C2>>
     where
-        T: ClosedMul,
+        T: ClosedMulAssign,
         R1: DimMul<R2>,
         C1: DimMul<C2>,
         SB: Storage<T, R2, C2>,
-        DefaultAllocator: Allocator<T, DimProd<R1, R2>, DimProd<C1, C2>>,
+        DefaultAllocator: Allocator<DimProd<R1, R2>, DimProd<C1, C2>>,
     {
         let (nrows1, ncols1) = self.shape_generic();
         let (nrows2, ncols2) = rhs.shape_generic();
@@ -835,8 +837,8 @@ where
 
 impl<T, D: DimName> iter::Product for OMatrix<T, D, D>
 where
-    T: Scalar + Zero + One + ClosedMul + ClosedAdd,
-    DefaultAllocator: Allocator<T, D, D>,
+    T: Scalar + Zero + One + ClosedMulAssign + ClosedAddAssign,
+    DefaultAllocator: Allocator<D, D>,
 {
     fn product<I: Iterator<Item = OMatrix<T, D, D>>>(iter: I) -> OMatrix<T, D, D> {
         iter.fold(Matrix::one(), |acc, x| acc * x)
@@ -845,8 +847,8 @@ where
 
 impl<'a, T, D: DimName> iter::Product<&'a OMatrix<T, D, D>> for OMatrix<T, D, D>
 where
-    T: Scalar + Zero + One + ClosedMul + ClosedAdd,
-    DefaultAllocator: Allocator<T, D, D>,
+    T: Scalar + Zero + One + ClosedMulAssign + ClosedAddAssign,
+    DefaultAllocator: Allocator<D, D>,
 {
     fn product<I: Iterator<Item = &'a OMatrix<T, D, D>>>(iter: I) -> OMatrix<T, D, D> {
         iter.fold(Matrix::one(), |acc, x| acc * x)

src/base/properties.rs

@@ -2,7 +2,7 @@
 use approx::RelativeEq;
 use num::{One, Zero};
 
-use simba::scalar::{ClosedAdd, ClosedMul, ComplexField, RealField};
+use simba::scalar::{ClosedAddAssign, ClosedMulAssign, ComplexField, RealField};
 
 use crate::base::allocator::Allocator;
 use crate::base::dimension::{Dim, DimMin};
@@ -88,10 +88,10 @@ impl<T: ComplexField, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn is_orthogonal(&self, eps: T::Epsilon) -> bool
     where
-        T: Zero + One + ClosedAdd + ClosedMul + RelativeEq,
+        T: Zero + One + ClosedAddAssign + ClosedMulAssign + RelativeEq,
         S: Storage<T, R, C>,
         T::Epsilon: Clone,
-        DefaultAllocator: Allocator<T, R, C> + Allocator<T, C, C>,
+        DefaultAllocator: Allocator<R, C> + Allocator<C, C>,
     {
         (self.ad_mul(self)).is_identity(eps)
     }
@@ -99,7 +99,7 @@ impl<T: ComplexField, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
 
 impl<T: RealField, D: Dim, S: Storage<T, D, D>> SquareMatrix<T, D, S>
 where
-    DefaultAllocator: Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D, D>,
 {
     /// Checks that this matrix is orthogonal and has a determinant equal to 1.
     #[inline]
@@ -107,7 +107,7 @@ where
     pub fn is_special_orthogonal(&self, eps: T) -> bool
     where
         D: DimMin<D, Output = D>,
-        DefaultAllocator: Allocator<(usize, usize), D>,
+        DefaultAllocator: Allocator<D>,
     {
         self.is_square() && self.is_orthogonal(eps) && self.determinant() > T::zero()
     }

src/base/rkyv_wrappers.rs

@@ -1,6 +1,6 @@
 //! Wrapper that allows changing the generic type of a PhantomData<T>
 //!
-//! Copied from https://github.com/rkyv/rkyv_contrib (MIT-Apache2 licences) which isn’t published yet.
+//! Copied from <https://github.com/rkyv/rkyv_contrib> (MIT-Apache2 licences) which isn’t published yet.
 
 use rkyv::{
     with::{ArchiveWith, DeserializeWith, SerializeWith},
@@ -8,7 +8,7 @@ use rkyv::{
 };
 use std::marker::PhantomData;
 
-/// A wrapper that allows for changing the generic type of a PhantomData<T>.
+/// A wrapper that allows for changing the generic type of a `PhantomData<T>`.
 pub struct CustomPhantom<NT: ?Sized> {
     _data: PhantomData<*const NT>,
 }

src/base/statistics.rs

@@ -2,7 +2,7 @@ use crate::allocator::Allocator;
 use crate::storage::RawStorage;
 use crate::{Const, DefaultAllocator, Dim, Matrix, OVector, RowOVector, Scalar, VectorView, U1};
 use num::{One, Zero};
-use simba::scalar::{ClosedAdd, ClosedMul, Field, SupersetOf};
+use simba::scalar::{ClosedAddAssign, ClosedMulAssign, Field, SupersetOf};
 use std::mem::MaybeUninit;
 
 /// # Folding on columns and rows
@@ -16,7 +16,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
         f: impl Fn(VectorView<'_, T, R, S::RStride, S::CStride>) -> T,
     ) -> RowOVector<T, C>
     where
-        DefaultAllocator: Allocator<T, U1, C>,
+        DefaultAllocator: Allocator<U1, C>,
     {
         let ncols = self.shape_generic().1;
         let mut res = Matrix::uninit(Const::<1>, ncols);
@@ -44,7 +44,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
         f: impl Fn(VectorView<'_, T, R, S::RStride, S::CStride>) -> T,
     ) -> OVector<T, C>
     where
-        DefaultAllocator: Allocator<T, C>,
+        DefaultAllocator: Allocator<C>,
     {
         let ncols = self.shape_generic().1;
         let mut res = Matrix::uninit(ncols, Const::<1>);
@@ -70,7 +70,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
         f: impl Fn(&mut OVector<T, R>, VectorView<'_, T, R, S::RStride, S::CStride>),
     ) -> OVector<T, R>
     where
-        DefaultAllocator: Allocator<T, R>,
+        DefaultAllocator: Allocator<R>,
     {
         let mut res = init;
 
@@ -104,7 +104,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn sum(&self) -> T
     where
-        T: ClosedAdd + Zero,
+        T: ClosedAddAssign + Zero,
     {
         self.iter().cloned().fold(T::zero(), |a, b| a + b)
     }
@@ -132,8 +132,8 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn row_sum(&self) -> RowOVector<T, C>
     where
-        T: ClosedAdd + Zero,
-        DefaultAllocator: Allocator<T, U1, C>,
+        T: ClosedAddAssign + Zero,
+        DefaultAllocator: Allocator<U1, C>,
     {
         self.compress_rows(|col| col.sum())
     }
@@ -159,8 +159,8 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn row_sum_tr(&self) -> OVector<T, C>
     where
-        T: ClosedAdd + Zero,
-        DefaultAllocator: Allocator<T, C>,
+        T: ClosedAddAssign + Zero,
+        DefaultAllocator: Allocator<C>,
     {
         self.compress_rows_tr(|col| col.sum())
     }
@@ -186,8 +186,8 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn column_sum(&self) -> OVector<T, R>
     where
-        T: ClosedAdd + Zero,
-        DefaultAllocator: Allocator<T, R>,
+        T: ClosedAddAssign + Zero,
+        DefaultAllocator: Allocator<R>,
     {
         let nrows = self.shape_generic().0;
         self.compress_columns(OVector::zeros_generic(nrows, Const::<1>), |out, col| {
@@ -215,7 +215,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn product(&self) -> T
     where
-        T: ClosedMul + One,
+        T: ClosedMulAssign + One,
     {
         self.iter().cloned().fold(T::one(), |a, b| a * b)
     }
@@ -243,8 +243,8 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn row_product(&self) -> RowOVector<T, C>
     where
-        T: ClosedMul + One,
-        DefaultAllocator: Allocator<T, U1, C>,
+        T: ClosedMulAssign + One,
+        DefaultAllocator: Allocator<U1, C>,
     {
         self.compress_rows(|col| col.product())
     }
@@ -270,8 +270,8 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn row_product_tr(&self) -> OVector<T, C>
     where
-        T: ClosedMul + One,
-        DefaultAllocator: Allocator<T, C>,
+        T: ClosedMulAssign + One,
+        DefaultAllocator: Allocator<C>,
     {
         self.compress_rows_tr(|col| col.product())
     }
@@ -297,8 +297,8 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn column_product(&self) -> OVector<T, R>
     where
-        T: ClosedMul + One,
-        DefaultAllocator: Allocator<T, R>,
+        T: ClosedMulAssign + One,
+        DefaultAllocator: Allocator<R>,
     {
         let nrows = self.shape_generic().0;
         self.compress_columns(
@@ -339,7 +339,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
             let mean = self.mean();
 
             self.iter().cloned().fold(T::zero(), |acc, x| {
-                acc + (x.clone() - mean.clone()) * (x.clone() - mean.clone())
+                acc + (x.clone() - mean.clone()) * (x - mean.clone())
             }) / n_elements
         }
     }
@@ -361,7 +361,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     pub fn row_variance(&self) -> RowOVector<T, C>
     where
         T: Field + SupersetOf<f64>,
-        DefaultAllocator: Allocator<T, U1, C>,
+        DefaultAllocator: Allocator<U1, C>,
     {
         self.compress_rows(|col| col.variance())
     }
@@ -382,7 +382,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     pub fn row_variance_tr(&self) -> OVector<T, C>
     where
         T: Field + SupersetOf<f64>,
-        DefaultAllocator: Allocator<T, C>,
+        DefaultAllocator: Allocator<C>,
     {
         self.compress_rows_tr(|col| col.variance())
     }
@@ -404,7 +404,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     pub fn column_variance(&self) -> OVector<T, R>
     where
         T: Field + SupersetOf<f64>,
-        DefaultAllocator: Allocator<T, R>,
+        DefaultAllocator: Allocator<R>,
     {
         let (nrows, ncols) = self.shape_generic();
 
@@ -469,7 +469,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     pub fn row_mean(&self) -> RowOVector<T, C>
     where
         T: Field + SupersetOf<f64>,
-        DefaultAllocator: Allocator<T, U1, C>,
+        DefaultAllocator: Allocator<U1, C>,
     {
         self.compress_rows(|col| col.mean())
     }
@@ -490,7 +490,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     pub fn row_mean_tr(&self) -> OVector<T, C>
     where
         T: Field + SupersetOf<f64>,
-        DefaultAllocator: Allocator<T, C>,
+        DefaultAllocator: Allocator<C>,
     {
         self.compress_rows_tr(|col| col.mean())
     }
@@ -511,7 +511,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     pub fn column_mean(&self) -> OVector<T, R>
     where
         T: Field + SupersetOf<f64>,
-        DefaultAllocator: Allocator<T, R>,
+        DefaultAllocator: Allocator<R>,
     {
         let (nrows, ncols) = self.shape_generic();
         let denom = T::one() / crate::convert::<_, T>(ncols.value() as f64);