Merge pull request #966 from dimforge/dev

Release v0.29.0

CHANGELOG.md

@@ -4,6 +4,35 @@ documented here.
 
 This project adheres to [Semantic Versioning](https://semver.org/).
 
+## [0.29.0]
+### Breaking changes
+- We updated to the version 0.6 of `simba`. This means that the trait bounds `T: na::RealField`, `na::ComplexField`,
+ `na::SimdRealField`, `na:SimdComplexField` no imply that `T: Copy` (they only imply that `T: Clone`). This may affect
+  generic code.
+- The closure given to `apply`, `zip_apply`, `zip_zip_apply` must now modify the
+  first argument inplace, instead of returning a new value. This makes these
+  methods more versatile, and avoid useless clones when using non-Copy scalar
+  types.
+- The `Allocator` trait signature has been significantly modified in order to handle uninitialized matrices in a sound
+  way.
+
+### Modified
+- `Orthographic3::from_matrix_unchecked` is now `const fn`.
+- `Perspective3::from_matrix_unchecked` is now `const fn`.
+- `Rotation::from_matrix_unchecked` is now `const fn`.
+- The `Scalar` is now automatically implemented for most `'static + Clone` types. Type that implement `Clone` but not
+  `Copy` are now much safer to work with thanks to the refactoring of the `Allocator` system.
+
+### Added
+- The conversion traits form the `bytemuck` crates are now implemented for the geometric types too.
+- Added operator overloading for `Transform * UnitComplex`, `UnitComplex * Transform`, `Transform ×= UnitComplex`,
+  `Transform ÷= UnitComplex`.
+- Added `Reflection::bias()` to retrieve the bias of the reflection.
+- Added `Reflection1..Reflection6` aliases for 1D to 6D reflections.
+- Added implementation of `From` and `Into` for converting between `nalgebra` types and types from
+  `glam 0.16` and `glam 0.17`. These can be enabled by enabling the `convert-glam016`, and/or `convert-glam017`
+  cargo features.
+
 ## [0.28.0]
 ### Added
 - Implement `Hash` for `Transform`.

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name    = "nalgebra"
-version = "0.28.0"
+version = "0.29.0"
 authors = [ "Sébastien Crozet <developer@crozet.re>" ]
 
 description = "General-purpose linear algebra library with transformations and statically-sized or dynamically-sized matrices."
@@ -31,7 +31,6 @@ io      = [ "pest", "pest_derive" ]
 compare = [ "matrixcompare-core" ]
 libm    = [ "simba/libm" ]
 libm-force = [ "simba/libm_force" ]
-no_unsound_assume_init = [ ]
 macros = [ "nalgebra-macros" ]
 
 # Conversion
@@ -40,6 +39,8 @@ convert-bytemuck = [ "bytemuck" ]
 convert-glam013 = [ "glam013" ]
 convert-glam014 = [ "glam014" ]
 convert-glam015 = [ "glam015" ]
+convert-glam016 = [ "glam016" ]
+convert-glam017 = [ "glam017" ]
 
 # Serialization
 ## To use serde in a #[no-std] environment, enable the
@@ -71,7 +72,7 @@ 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 = "0.5", default-features = false }
+simba          = { version = "0.6", 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 }
@@ -88,6 +89,8 @@ proptest           = { version = "1", optional = true, default-features = false,
 glam013        = { package = "glam", version = "0.13", optional = true }
 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 }
 
 
 [dev-dependencies]
@@ -114,9 +117,13 @@ harness = false
 path = "benches/lib.rs"
 required-features = ["rand"]
 
+#[profile.bench]
+#opt-level = 0
+#lto = false
+
 [profile.bench]
 lto = true
 
 [package.metadata.docs.rs]
 # Enable certain features when building docs for docs.rs
-features = [ "proptest-support", "compare", "macros" ]
+features = [ "proptest-support", "compare", "macros", "rand" ]

clippy.toml

@@ -0,0 +1,2 @@
+too-many-arguments-threshold = 8
+type-complexity-threshold = 675

examples/cargo/Cargo.toml

@@ -4,7 +4,7 @@ version = "0.0.0"
 authors = [ "You" ]
 
 [dependencies]
-nalgebra = "0.28.0"
+nalgebra = "0.29.0"
 
 [[bin]]
 name = "example"

nalgebra-glm/Cargo.toml

@@ -26,5 +26,5 @@ abomonation-serialize = [ "nalgebra/abomonation-serialize" ]
 [dependencies]
 num-traits = { version = "0.2", default-features = false }
 approx = { version = "0.5", default-features = false }
-simba = { version = "0.5", default-features = false }
-nalgebra = { path =  "..", version = "0.28", default-features = false }
+simba = { version = "0.6", default-features = false }
+nalgebra = { path =  "..", version = "0.29", default-features = false }

nalgebra-glm/src/aliases.rs

@@ -320,7 +320,7 @@ pub type DMat4x4 = Matrix4<f64>;
 pub type Mat2 = Matrix2<f32>;
 /// A 2x2 matrix with `f32` components.
 pub type Mat2x2 = Matrix2<f32>;
-/// A 2x2 matrix with `f32` components.
+/// A 2x3 matrix with `f32` components.
 pub type Mat2x3 = Matrix2x3<f32>;
 /// A 2x4 matrix with `f32` components.
 pub type Mat2x4 = Matrix2x4<f32>;

nalgebra-glm/src/common.rs

@@ -1,9 +1,9 @@
 use core::mem;
-use na::{self, RealField};
-use num::FromPrimitive;
+use na;
 
 use crate::aliases::{TMat, TVec};
 use crate::traits::Number;
+use crate::RealNumber;
 
 /// For each matrix or vector component `x` if `x >= 0`; otherwise, it returns `-x`.
 ///
@@ -42,7 +42,7 @@ pub fn abs<T: Number, const R: usize, const C: usize>(x: &TMat<T, R, C>) -> TMat
 /// * [`fract`](fn.fract.html)
 /// * [`round`](fn.round.html)
 /// * [`trunc`](fn.trunc.html)
-pub fn ceil<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
+pub fn ceil<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.ceil())
 }
 
@@ -214,7 +214,7 @@ pub fn float_bits_to_uint_vec<const D: usize>(v: &TVec<f32, D>) -> TVec<u32, D>
 /// * [`fract`](fn.fract.html)
 /// * [`round`](fn.round.html)
 /// * [`trunc`](fn.trunc.html)
-pub fn floor<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
+pub fn floor<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.floor())
 }
 
@@ -240,13 +240,13 @@ pub fn floor<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
 /// * [`floor`](fn.floor.html)
 /// * [`round`](fn.round.html)
 /// * [`trunc`](fn.trunc.html)
-pub fn fract<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
+pub fn fract<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.fract())
 }
 
 //// TODO: should be implemented for TVec/TMat?
 ///// Returns the (significant, exponent) of this float number.
-//pub fn frexp<T: RealField>(x: T, exp: T) -> (T, T) {
+//pub fn frexp<T: RealNumber>(x: T, exp: T) -> (T, T) {
 //    // TODO: is there a better approach?
 //    let e = x.log2().ceil();
 //    (x * (-e).exp2(), e)
@@ -297,7 +297,7 @@ pub fn int_bits_to_float_vec<const D: usize>(v: &TVec<i32, D>) -> TVec<f32, D> {
 //}
 
 ///// Returns the (significant, exponent) of this float number.
-//pub fn ldexp<T: RealField>(x: T, exp: T) -> T {
+//pub fn ldexp<T: RealNumber>(x: T, exp: T) -> T {
 //    // TODO: is there a better approach?
 //    x * (exp).exp2()
 //}
@@ -477,7 +477,7 @@ pub fn modf<T: Number>(x: T, i: T) -> T {
 /// * [`floor`](fn.floor.html)
 /// * [`fract`](fn.fract.html)
 /// * [`trunc`](fn.trunc.html)
-pub fn round<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
+pub fn round<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.round())
 }
 
@@ -507,9 +507,9 @@ pub fn sign<T: Number, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
 ///
 /// This is useful in cases where you would want a threshold function with a smooth transition.
 /// This is equivalent to: `let result = clamp((x - edge0) / (edge1 - edge0), 0, 1); return t * t * (3 - 2 * t);` Results are undefined if `edge0 >= edge1`.
-pub fn smoothstep<T: Number>(edge0: T, edge1: T, x: T) -> T {
-    let _3: T = FromPrimitive::from_f64(3.0).unwrap();
-    let _2: T = FromPrimitive::from_f64(2.0).unwrap();
+pub fn smoothstep<T: RealNumber>(edge0: T, edge1: T, x: T) -> T {
+    let _3 = T::from_subset(&3.0f64);
+    let _2 = T::from_subset(&2.0f64);
     let t = na::clamp((x - edge0) / (edge1 - edge0), T::zero(), T::one());
     t * t * (_3 - t * _2)
 }
@@ -549,7 +549,7 @@ pub fn step_vec<T: Number, const D: usize>(edge: &TVec<T, D>, x: &TVec<T, D>) ->
 /// * [`floor`](fn.floor.html)
 /// * [`fract`](fn.fract.html)
 /// * [`round`](fn.round.html)
-pub fn trunc<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
+pub fn trunc<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.trunc())
 }
 

nalgebra-glm/src/constructors.rs

@@ -2,7 +2,8 @@ use crate::aliases::{
     Qua, TMat, TMat2, TMat2x3, TMat2x4, TMat3, TMat3x2, TMat3x4, TMat4, TMat4x2, TMat4x3, TVec1,
     TVec2, TVec3, TVec4,
 };
-use na::{RealField, Scalar};
+use crate::RealNumber;
+use na::Scalar;
 
 /// Creates a new 1D vector.
 ///
@@ -178,6 +179,6 @@ pub fn mat4<T: Scalar>(m11: T, m12: T, m13: T, m14: T,
 }
 
 /// Creates a new quaternion.
-pub fn quat<T: RealField>(x: T, y: T, z: T, w: T) -> Qua<T> {
+pub fn quat<T: RealNumber>(x: T, y: T, z: T, w: T) -> Qua<T> {
     Qua::new(w, x, y, z)
 }

nalgebra-glm/src/exponential.rs

@@ -1,12 +1,12 @@
 use crate::aliases::TVec;
-use na::RealField;
+use crate::RealNumber;
 
 /// Component-wise exponential.
 ///
 /// # See also:
 ///
 /// * [`exp2`](fn.exp2.html)
-pub fn exp<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
+pub fn exp<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.exp())
 }
 
@@ -15,7 +15,7 @@ pub fn exp<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
 /// # See also:
 ///
 /// * [`exp`](fn.exp.html)
-pub fn exp2<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
+pub fn exp2<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.exp2())
 }
 
@@ -24,7 +24,7 @@ pub fn exp2<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
 /// # See also:
 ///
 /// * [`sqrt`](fn.sqrt.html)
-pub fn inversesqrt<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
+pub fn inversesqrt<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| T::one() / x.sqrt())
 }
 
@@ -33,7 +33,7 @@ pub fn inversesqrt<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
 /// # See also:
 ///
 /// * [`log2`](fn.log2.html)
-pub fn log<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
+pub fn log<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.ln())
 }
 
@@ -42,12 +42,12 @@ pub fn log<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
 /// # See also:
 ///
 /// * [`log`](fn.log.html)
-pub fn log2<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
+pub fn log2<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.log2())
 }
 
 /// Component-wise power.
-pub fn pow<T: RealField, const D: usize>(base: &TVec<T, D>, exponent: &TVec<T, D>) -> TVec<T, D> {
+pub fn pow<T: RealNumber, const D: usize>(base: &TVec<T, D>, exponent: &TVec<T, D>) -> TVec<T, D> {
     base.zip_map(exponent, |b, e| b.powf(e))
 }
 
@@ -59,6 +59,6 @@ pub fn pow<T: RealField, const D: usize>(base: &TVec<T, D>, exponent: &TVec<T, D
 /// * [`exp2`](fn.exp2.html)
 /// * [`inversesqrt`](fn.inversesqrt.html)
 /// * [`pow`](fn.pow.html)
-pub fn sqrt<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
+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_clip_space.rs

@@ -1,51 +1,51 @@
 use crate::aliases::TMat4;
-use na::RealField;
+use crate::RealNumber;
 
-//pub fn frustum<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
+//pub fn frustum<T: RealNumber>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 
-//pub fn frustum_lh<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
+//pub fn frustum_lh<T: RealNumber>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_lr_no<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
+//pub fn frustum_lr_no<T: RealNumber>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_lh_zo<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
+//pub fn frustum_lh_zo<T: RealNumber>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_no<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
+//pub fn frustum_no<T: RealNumber>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_rh<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
+//pub fn frustum_rh<T: RealNumber>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_rh_no<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
+//pub fn frustum_rh_no<T: RealNumber>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_rh_zo<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
+//pub fn frustum_rh_zo<T: RealNumber>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_zo<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
+//pub fn frustum_zo<T: RealNumber>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 
-//pub fn infinite_perspective<T: RealField>(fovy: T, aspect: T, near: T) -> TMat4<T> {
+//pub fn infinite_perspective<T: RealNumber>(fovy: T, aspect: T, near: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn infinite_perspective_lh<T: RealField>(fovy: T, aspect: T, near: T) -> TMat4<T> {
+//pub fn infinite_perspective_lh<T: RealNumber>(fovy: T, aspect: T, near: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn infinite_ortho<T: RealField>(left: T, right: T, bottom: T, top: T) -> TMat4<T> {
+//pub fn infinite_ortho<T: RealNumber>(left: T, right: T, bottom: T, top: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 
@@ -60,7 +60,7 @@ use na::RealField;
 /// * `znear` - Distance from the viewer to the near clipping plane
 /// * `zfar` - Distance from the viewer to the far clipping plane
 ///
-pub fn ortho<T: RealField>(left: T, right: T, bottom: T, top: T, znear: T, zfar: T) -> TMat4<T> {
+pub fn ortho<T: RealNumber>(left: T, right: T, bottom: T, top: T, znear: T, zfar: T) -> TMat4<T> {
     ortho_rh_no(left, right, bottom, top, znear, zfar)
 }
 
@@ -75,7 +75,14 @@ pub fn ortho<T: RealField>(left: T, right: T, bottom: T, top: T, znear: T, zfar:
 /// * `znear` - Distance from the viewer to the near clipping plane
 /// * `zfar` - Distance from the viewer to the far clipping plane
 ///
-pub fn ortho_lh<T: RealField>(left: T, right: T, bottom: T, top: T, znear: T, zfar: T) -> TMat4<T> {
+pub fn ortho_lh<T: RealNumber>(
+    left: T,
+    right: T,
+    bottom: T,
+    top: T,
+    znear: T,
+    zfar: T,
+) -> TMat4<T> {
     ortho_lh_no(left, right, bottom, top, znear, zfar)
 }
 
@@ -90,7 +97,7 @@ pub fn ortho_lh<T: RealField>(left: T, right: T, bottom: T, top: T, znear: T, zf
 /// * `znear` - Distance from the viewer to the near clipping plane
 /// * `zfar` - Distance from the viewer to the far clipping plane
 ///
-pub fn ortho_lh_no<T: RealField>(
+pub fn ortho_lh_no<T: RealNumber>(
     left: T,
     right: T,
     bottom: T,
@@ -122,7 +129,7 @@ pub fn ortho_lh_no<T: RealField>(
 /// * `znear` - Distance from the viewer to the near clipping plane
 /// * `zfar` - Distance from the viewer to the far clipping plane
 ///
-pub fn ortho_lh_zo<T: RealField>(
+pub fn ortho_lh_zo<T: RealNumber>(
     left: T,
     right: T,
     bottom: T,
@@ -155,7 +162,14 @@ pub fn ortho_lh_zo<T: RealField>(
 /// * `znear` - Distance from the viewer to the near clipping plane
 /// * `zfar` - Distance from the viewer to the far clipping plane
 ///
-pub fn ortho_no<T: RealField>(left: T, right: T, bottom: T, top: T, znear: T, zfar: T) -> TMat4<T> {
+pub fn ortho_no<T: RealNumber>(
+    left: T,
+    right: T,
+    bottom: T,
+    top: T,
+    znear: T,
+    zfar: T,
+) -> TMat4<T> {
     ortho_rh_no(left, right, bottom, top, znear, zfar)
 }
 
@@ -170,7 +184,14 @@ pub fn ortho_no<T: RealField>(left: T, right: T, bottom: T, top: T, znear: T, zf
 /// * `znear` - Distance from the viewer to the near clipping plane
 /// * `zfar` - Distance from the viewer to the far clipping plane
 ///
-pub fn ortho_rh<T: RealField>(left: T, right: T, bottom: T, top: T, znear: T, zfar: T) -> TMat4<T> {
+pub fn ortho_rh<T: RealNumber>(
+    left: T,
+    right: T,
+    bottom: T,
+    top: T,
+    znear: T,
+    zfar: T,
+) -> TMat4<T> {
     ortho_rh_no(left, right, bottom, top, znear, zfar)
 }
 
@@ -185,7 +206,7 @@ pub fn ortho_rh<T: RealField>(left: T, right: T, bottom: T, top: T, znear: T, zf
 /// * `znear` - Distance from the viewer to the near clipping plane
 /// * `zfar` - Distance from the viewer to the far clipping plane
 ///
-pub fn ortho_rh_no<T: RealField>(
+pub fn ortho_rh_no<T: RealNumber>(
     left: T,
     right: T,
     bottom: T,
@@ -217,7 +238,7 @@ pub fn ortho_rh_no<T: RealField>(
 /// * `znear` - Distance from the viewer to the near clipping plane
 /// * `zfar` - Distance from the viewer to the far clipping plane
 ///
-pub fn ortho_rh_zo<T: RealField>(
+pub fn ortho_rh_zo<T: RealNumber>(
     left: T,
     right: T,
     bottom: T,
@@ -250,7 +271,14 @@ pub fn ortho_rh_zo<T: RealField>(
 /// * `znear` - Distance from the viewer to the near clipping plane
 /// * `zfar` - Distance from the viewer to the far clipping plane
 ///
-pub fn ortho_zo<T: RealField>(left: T, right: T, bottom: T, top: T, znear: T, zfar: T) -> TMat4<T> {
+pub fn ortho_zo<T: RealNumber>(
+    left: T,
+    right: T,
+    bottom: T,
+    top: T,
+    znear: T,
+    zfar: T,
+) -> TMat4<T> {
     ortho_rh_zo(left, right, bottom, top, znear, zfar)
 }
 
@@ -264,7 +292,7 @@ pub fn ortho_zo<T: RealField>(left: T, right: T, bottom: T, top: T, znear: T, zf
 /// * `near` - Distance from the viewer to the near clipping plane
 /// * `far` - Distance from the viewer to the far clipping plane
 ///
-pub fn perspective_fov<T: RealField>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_fov<T: RealNumber>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
     perspective_fov_rh_no(fov, width, height, near, far)
 }
 
@@ -278,7 +306,7 @@ pub fn perspective_fov<T: RealField>(fov: T, width: T, height: T, near: T, far:
 /// * `near` - Distance from the viewer to the near clipping plane
 /// * `far` - Distance from the viewer to the far clipping plane
 ///
-pub fn perspective_fov_lh<T: RealField>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_fov_lh<T: RealNumber>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
     perspective_fov_lh_no(fov, width, height, near, far)
 }
 
@@ -292,7 +320,7 @@ pub fn perspective_fov_lh<T: RealField>(fov: T, width: T, height: T, near: T, fa
 /// * `near` - Distance from the viewer to the near clipping plane
 /// * `far` - Distance from the viewer to the far clipping plane
 ///
-pub fn perspective_fov_lh_no<T: RealField>(
+pub fn perspective_fov_lh_no<T: RealNumber>(
     fov: T,
     width: T,
     height: T,
@@ -328,7 +356,7 @@ pub fn perspective_fov_lh_no<T: RealField>(
 /// * `near` - Distance from the viewer to the near clipping plane
 /// * `far` - Distance from the viewer to the far clipping plane
 ///
-pub fn perspective_fov_lh_zo<T: RealField>(
+pub fn perspective_fov_lh_zo<T: RealNumber>(
     fov: T,
     width: T,
     height: T,
@@ -364,7 +392,7 @@ pub fn perspective_fov_lh_zo<T: RealField>(
 /// * `near` - Distance from the viewer to the near clipping plane
 /// * `far` - Distance from the viewer to the far clipping plane
 ///
-pub fn perspective_fov_no<T: RealField>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_fov_no<T: RealNumber>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
     perspective_fov_rh_no(fov, width, height, near, far)
 }
 
@@ -378,7 +406,7 @@ pub fn perspective_fov_no<T: RealField>(fov: T, width: T, height: T, near: T, fa
 /// * `near` - Distance from the viewer to the near clipping plane
 /// * `far` - Distance from the viewer to the far clipping plane
 ///
-pub fn perspective_fov_rh<T: RealField>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_fov_rh<T: RealNumber>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
     perspective_fov_rh_no(fov, width, height, near, far)
 }
 
@@ -392,7 +420,7 @@ pub fn perspective_fov_rh<T: RealField>(fov: T, width: T, height: T, near: T, fa
 /// * `near` - Distance from the viewer to the near clipping plane
 /// * `far` - Distance from the viewer to the far clipping plane
 ///
-pub fn perspective_fov_rh_no<T: RealField>(
+pub fn perspective_fov_rh_no<T: RealNumber>(
     fov: T,
     width: T,
     height: T,
@@ -428,7 +456,7 @@ pub fn perspective_fov_rh_no<T: RealField>(
 /// * `near` - Distance from the viewer to the near clipping plane
 /// * `far` - Distance from the viewer to the far clipping plane
 ///
-pub fn perspective_fov_rh_zo<T: RealField>(
+pub fn perspective_fov_rh_zo<T: RealNumber>(
     fov: T,
     width: T,
     height: T,
@@ -464,7 +492,7 @@ pub fn perspective_fov_rh_zo<T: RealField>(
 /// * `near` - Distance from the viewer to the near clipping plane
 /// * `far` - Distance from the viewer to the far clipping plane
 ///
-pub fn perspective_fov_zo<T: RealField>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_fov_zo<T: RealNumber>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
     perspective_fov_rh_zo(fov, width, height, near, far)
 }
 
@@ -479,7 +507,7 @@ pub fn perspective_fov_zo<T: RealField>(fov: T, width: T, height: T, near: T, fa
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective<T: RealNumber>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     // TODO: Breaking change - revert back to proper glm conventions?
     //
     //       Prior to changes to support configuring the behaviour of this function it was simply
@@ -508,7 +536,7 @@ pub fn perspective<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_lh<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_lh<T: RealNumber>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     perspective_lh_no(aspect, fovy, near, far)
 }
 
@@ -523,7 +551,7 @@ pub fn perspective_lh<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_lh_no<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_lh_no<T: RealNumber>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     assert!(
         !relative_eq!(far - near, T::zero()),
         "The near-plane and far-plane must not be superimposed."
@@ -559,7 +587,7 @@ pub fn perspective_lh_no<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> T
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_lh_zo<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_lh_zo<T: RealNumber>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     assert!(
         !relative_eq!(far - near, T::zero()),
         "The near-plane and far-plane must not be superimposed."
@@ -595,7 +623,7 @@ pub fn perspective_lh_zo<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> T
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_no<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_no<T: RealNumber>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     perspective_rh_no(aspect, fovy, near, far)
 }
 
@@ -610,7 +638,7 @@ pub fn perspective_no<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_rh<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_rh<T: RealNumber>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     perspective_rh_no(aspect, fovy, near, far)
 }
 
@@ -625,7 +653,7 @@ pub fn perspective_rh<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_rh_no<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_rh_no<T: RealNumber>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     assert!(
         !relative_eq!(far - near, T::zero()),
         "The near-plane and far-plane must not be superimposed."
@@ -662,7 +690,7 @@ pub fn perspective_rh_no<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> T
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_rh_zo<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_rh_zo<T: RealNumber>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     assert!(
         !relative_eq!(far - near, T::zero()),
         "The near-plane and far-plane must not be superimposed."
@@ -699,7 +727,7 @@ pub fn perspective_rh_zo<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> T
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_zo<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
+pub fn perspective_zo<T: RealNumber>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     perspective_rh_zo(aspect, fovy, near, far)
 }
 
@@ -713,7 +741,7 @@ pub fn perspective_zo<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn infinite_perspective_rh_no<T: RealField>(aspect: T, fovy: T, near: T) -> TMat4<T> {
+pub fn infinite_perspective_rh_no<T: RealNumber>(aspect: T, fovy: T, near: T) -> TMat4<T> {
     let f = T::one() / (fovy * na::convert(0.5)).tan();
     let mut mat = TMat4::zeros();
 
@@ -738,7 +766,7 @@ pub fn infinite_perspective_rh_no<T: RealField>(aspect: T, fovy: T, near: T) ->
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
 ///
 // https://discourse.nphysics.org/t/reversed-z-and-infinite-zfar-in-projections/341/2
-pub fn infinite_perspective_rh_zo<T: RealField>(aspect: T, fovy: T, near: T) -> TMat4<T> {
+pub fn infinite_perspective_rh_zo<T: RealNumber>(aspect: T, fovy: T, near: T) -> TMat4<T> {
     let f = T::one() / (fovy * na::convert(0.5)).tan();
     let mut mat = TMat4::zeros();
 
@@ -763,7 +791,7 @@ pub fn infinite_perspective_rh_zo<T: RealField>(aspect: T, fovy: T, near: T) ->
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
 // NOTE: The variants `_no` of reversed perspective are not useful.
-pub fn reversed_perspective_rh_zo<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
+pub fn reversed_perspective_rh_zo<T: RealNumber>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     let one = T::one();
     let two = crate::convert(2.0);
     let mut mat = TMat4::zeros();
@@ -791,7 +819,7 @@ pub fn reversed_perspective_rh_zo<T: RealField>(aspect: T, fovy: T, near: T, far
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
 // Credit: https://discourse.nphysics.org/t/reversed-z-and-infinite-zfar-in-projections/341/2
 // NOTE: The variants `_no` of reversed perspective are not useful.
-pub fn reversed_infinite_perspective_rh_zo<T: RealField>(aspect: T, fovy: T, near: T) -> TMat4<T> {
+pub fn reversed_infinite_perspective_rh_zo<T: RealNumber>(aspect: T, fovy: T, near: T) -> TMat4<T> {
     let f = T::one() / (fovy * na::convert(0.5)).tan();
     let mut mat = TMat4::zeros();
 
@@ -803,10 +831,10 @@ pub fn reversed_infinite_perspective_rh_zo<T: RealField>(aspect: T, fovy: T, nea
     mat
 }
 
-//pub fn tweaked_infinite_perspective<T: RealField>(fovy: T, aspect: T, near: T) -> TMat4<T> {
+//pub fn tweaked_infinite_perspective<T: RealNumber>(fovy: T, aspect: T, near: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn tweaked_infinite_perspective_ep<T: RealField>(fovy: T, aspect: T, near: T, ep: T) -> TMat4<T> {
+//pub fn tweaked_infinite_perspective_ep<T: RealNumber>(fovy: T, aspect: T, near: T, ep: T) -> TMat4<T> {
 //    unimplemented!()
 //}

nalgebra-glm/src/ext/matrix_projection.rs

@@ -1,6 +1,7 @@
-use na::{self, RealField};
+use na;
 
 use crate::aliases::{TMat4, TVec2, TVec3, TVec4};
+use crate::RealNumber;
 
 /// Define a picking region.
 ///
@@ -9,7 +10,7 @@ use crate::aliases::{TMat4, TVec2, TVec3, TVec4};
 /// * `center` - Specify the center of a picking region in window coordinates.
 /// * `delta` - Specify the width and height, respectively, of the picking region in window coordinates.
 /// * `viewport` - Rendering viewport.
-pub fn pick_matrix<T: RealField>(
+pub fn pick_matrix<T: RealNumber>(
     center: &TVec2<T>,
     delta: &TVec2<T>,
     viewport: &TVec4<T>,
@@ -45,7 +46,7 @@ pub fn pick_matrix<T: RealField>(
 /// * [`unproject`](fn.unproject.html)
 /// * [`unproject_no`](fn.unproject_no.html)
 /// * [`unproject_zo`](fn.unproject_zo.html)
-pub fn project<T: RealField>(
+pub fn project<T: RealNumber>(
     obj: &TVec3<T>,
     model: &TMat4<T>,
     proj: &TMat4<T>,
@@ -72,7 +73,7 @@ pub fn project<T: RealField>(
 /// * [`unproject`](fn.unproject.html)
 /// * [`unproject_no`](fn.unproject_no.html)
 /// * [`unproject_zo`](fn.unproject_zo.html)
-pub fn project_no<T: RealField>(
+pub fn project_no<T: RealNumber>(
     obj: &TVec3<T>,
     model: &TMat4<T>,
     proj: &TMat4<T>,
@@ -100,7 +101,7 @@ pub fn project_no<T: RealField>(
 /// * [`unproject`](fn.unproject.html)
 /// * [`unproject_no`](fn.unproject_no.html)
 /// * [`unproject_zo`](fn.unproject_zo.html)
-pub fn project_zo<T: RealField>(
+pub fn project_zo<T: RealNumber>(
     obj: &TVec3<T>,
     model: &TMat4<T>,
     proj: &TMat4<T>,
@@ -133,7 +134,7 @@ pub fn project_zo<T: RealField>(
 /// * [`project_zo`](fn.project_zo.html)
 /// * [`unproject_no`](fn.unproject_no.html)
 /// * [`unproject_zo`](fn.unproject_zo.html)
-pub fn unproject<T: RealField>(
+pub fn unproject<T: RealNumber>(
     win: &TVec3<T>,
     model: &TMat4<T>,
     proj: &TMat4<T>,
@@ -160,7 +161,7 @@ pub fn unproject<T: RealField>(
 /// * [`project_zo`](fn.project_zo.html)
 /// * [`unproject`](fn.unproject.html)
 /// * [`unproject_zo`](fn.unproject_zo.html)
-pub fn unproject_no<T: RealField>(
+pub fn unproject_no<T: RealNumber>(
     win: &TVec3<T>,
     model: &TMat4<T>,
     proj: &TMat4<T>,
@@ -197,7 +198,7 @@ pub fn unproject_no<T: RealField>(
 /// * [`project_zo`](fn.project_zo.html)
 /// * [`unproject`](fn.unproject.html)
 /// * [`unproject_no`](fn.unproject_no.html)
-pub fn unproject_zo<T: RealField>(
+pub fn unproject_zo<T: RealNumber>(
     win: &TVec3<T>,
     model: &TMat4<T>,
     proj: &TMat4<T>,

nalgebra-glm/src/ext/matrix_transform.rs

@@ -1,7 +1,7 @@
-use na::{Point3, RealField, Rotation3, Unit};
+use na::{Point3, Rotation3, Unit};
 
 use crate::aliases::{TMat, TMat4, TVec, TVec3};
-use crate::traits::Number;
+use crate::traits::{Number, RealNumber};
 
 /// The identity matrix.
 pub fn identity<T: Number, const D: usize>() -> TMat<T, D, D> {
@@ -20,7 +20,7 @@ pub fn identity<T: Number, const D: usize>() -> TMat<T, D, D> {
 ///
 /// * [`look_at_lh`](fn.look_at_lh.html)
 /// * [`look_at_rh`](fn.look_at_rh.html)
-pub fn look_at<T: RealField>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
+pub fn look_at<T: RealNumber>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
     look_at_rh(eye, center, up)
 }
 
@@ -36,7 +36,7 @@ pub fn look_at<T: RealField>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>) -
 ///
 /// * [`look_at`](fn.look_at.html)
 /// * [`look_at_rh`](fn.look_at_rh.html)
-pub fn look_at_lh<T: RealField>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
+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)
 }
 
@@ -52,7 +52,7 @@ pub fn look_at_lh<T: RealField>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>
 ///
 /// * [`look_at`](fn.look_at.html)
 /// * [`look_at_lh`](fn.look_at_lh.html)
-pub fn look_at_rh<T: RealField>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
+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)
 }
 
@@ -71,7 +71,7 @@ pub fn look_at_rh<T: RealField>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>
 /// * [`rotate_z`](fn.rotate_z.html)
 /// * [`scale`](fn.scale.html)
 /// * [`translate`](fn.translate.html)
-pub fn rotate<T: RealField>(m: &TMat4<T>, angle: T, axis: &TVec3<T>) -> TMat4<T> {
+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()
 }
 
@@ -89,7 +89,7 @@ pub fn rotate<T: RealField>(m: &TMat4<T>, angle: T, axis: &TVec3<T>) -> TMat4<T>
 /// * [`rotate_z`](fn.rotate_z.html)
 /// * [`scale`](fn.scale.html)
 /// * [`translate`](fn.translate.html)
-pub fn rotate_x<T: RealField>(m: &TMat4<T>, angle: T) -> TMat4<T> {
+pub fn rotate_x<T: RealNumber>(m: &TMat4<T>, angle: T) -> TMat4<T> {
     rotate(m, angle, &TVec::x())
 }
 
@@ -107,7 +107,7 @@ pub fn rotate_x<T: RealField>(m: &TMat4<T>, angle: T) -> TMat4<T> {
 /// * [`rotate_z`](fn.rotate_z.html)
 /// * [`scale`](fn.scale.html)
 /// * [`translate`](fn.translate.html)
-pub fn rotate_y<T: RealField>(m: &TMat4<T>, angle: T) -> TMat4<T> {
+pub fn rotate_y<T: RealNumber>(m: &TMat4<T>, angle: T) -> TMat4<T> {
     rotate(m, angle, &TVec::y())
 }
 
@@ -125,7 +125,7 @@ pub fn rotate_y<T: RealField>(m: &TMat4<T>, angle: T) -> TMat4<T> {
 /// * [`rotate_y`](fn.rotate_y.html)
 /// * [`scale`](fn.scale.html)
 /// * [`translate`](fn.translate.html)
-pub fn rotate_z<T: RealField>(m: &TMat4<T>, angle: T) -> TMat4<T> {
+pub fn rotate_z<T: RealNumber>(m: &TMat4<T>, angle: T) -> TMat4<T> {
     rotate(m, angle, &TVec::z())
 }
 

nalgebra-glm/src/ext/quaternion_common.rs

@@ -1,36 +1,37 @@
-use na::{self, RealField, Unit};
+use na::{self, Unit};
 
 use crate::aliases::Qua;
+use crate::RealNumber;
 
 /// The conjugate of `q`.
-pub fn quat_conjugate<T: RealField>(q: &Qua<T>) -> Qua<T> {
+pub fn quat_conjugate<T: RealNumber>(q: &Qua<T>) -> Qua<T> {
     q.conjugate()
 }
 
 /// The inverse of `q`.
-pub fn quat_inverse<T: RealField>(q: &Qua<T>) -> Qua<T> {
+pub fn quat_inverse<T: RealNumber>(q: &Qua<T>) -> Qua<T> {
     q.try_inverse().unwrap_or_else(na::zero)
 }
 
-//pub fn quat_isinf<T: RealField>(x: &Qua<T>) -> TVec<bool, U4> {
+//pub fn quat_isinf<T: RealNumber>(x: &Qua<T>) -> TVec<bool, U4> {
 //    x.coords.map(|e| e.is_inf())
 //}
 
-//pub fn quat_isnan<T: RealField>(x: &Qua<T>) -> TVec<bool, U4> {
+//pub fn quat_isnan<T: RealNumber>(x: &Qua<T>) -> TVec<bool, U4> {
 //    x.coords.map(|e| e.is_nan())
 //}
 
 /// Interpolate linearly between `x` and `y`.
-pub fn quat_lerp<T: RealField>(x: &Qua<T>, y: &Qua<T>, a: T) -> Qua<T> {
+pub fn quat_lerp<T: RealNumber>(x: &Qua<T>, y: &Qua<T>, a: T) -> Qua<T> {
     x.lerp(y, a)
 }
 
-//pub fn quat_mix<T: RealField>(x: &Qua<T>, y: &Qua<T>, a: T) -> Qua<T> {
+//pub fn quat_mix<T: RealNumber>(x: &Qua<T>, y: &Qua<T>, a: T) -> Qua<T> {
 //    x * (T::one() - a) + y * a
 //}
 
 /// Interpolate spherically between `x` and `y`.
-pub fn quat_slerp<T: RealField>(x: &Qua<T>, y: &Qua<T>, a: T) -> Qua<T> {
+pub fn quat_slerp<T: RealNumber>(x: &Qua<T>, y: &Qua<T>, a: T) -> Qua<T> {
     Unit::new_normalize(*x)
         .slerp(&Unit::new_normalize(*y), a)
         .into_inner()

nalgebra-glm/src/ext/quaternion_geometric.rs

@@ -1,28 +1,28 @@
-use na::RealField;
+use crate::RealNumber;
 
 use crate::aliases::Qua;
 
 /// Multiplies two quaternions.
-pub fn quat_cross<T: RealField>(q1: &Qua<T>, q2: &Qua<T>) -> Qua<T> {
+pub fn quat_cross<T: RealNumber>(q1: &Qua<T>, q2: &Qua<T>) -> Qua<T> {
     q1 * q2
 }
 
 /// The scalar product of two quaternions.
-pub fn quat_dot<T: RealField>(x: &Qua<T>, y: &Qua<T>) -> T {
+pub fn quat_dot<T: RealNumber>(x: &Qua<T>, y: &Qua<T>) -> T {
     x.dot(y)
 }
 
 /// The magnitude of the quaternion `q`.
-pub fn quat_length<T: RealField>(q: &Qua<T>) -> T {
+pub fn quat_length<T: RealNumber>(q: &Qua<T>) -> T {
     q.norm()
 }
 
 /// The magnitude of the quaternion `q`.
-pub fn quat_magnitude<T: RealField>(q: &Qua<T>) -> T {
+pub fn quat_magnitude<T: RealNumber>(q: &Qua<T>) -> T {
     q.norm()
 }
 
 /// Normalizes the quaternion `q`.
-pub fn quat_normalize<T: RealField>(q: &Qua<T>) -> Qua<T> {
+pub fn quat_normalize<T: RealNumber>(q: &Qua<T>) -> Qua<T> {
     q.normalize()
 }

nalgebra-glm/src/ext/quaternion_relational.rs

@@ -1,23 +1,22 @@
-use na::RealField;
-
 use crate::aliases::{Qua, TVec};
+use crate::RealNumber;
 
 /// Component-wise equality comparison between two quaternions.
-pub fn quat_equal<T: RealField>(x: &Qua<T>, y: &Qua<T>) -> TVec<bool, 4> {
+pub fn quat_equal<T: RealNumber>(x: &Qua<T>, y: &Qua<T>) -> TVec<bool, 4> {
     crate::equal(&x.coords, &y.coords)
 }
 
 /// Component-wise approximate equality comparison between two quaternions.
-pub fn quat_equal_eps<T: RealField>(x: &Qua<T>, y: &Qua<T>, epsilon: T) -> TVec<bool, 4> {
+pub fn quat_equal_eps<T: RealNumber>(x: &Qua<T>, y: &Qua<T>, epsilon: T) -> TVec<bool, 4> {
     crate::equal_eps(&x.coords, &y.coords, epsilon)
 }
 
 /// Component-wise non-equality comparison between two quaternions.
-pub fn quat_not_equal<T: RealField>(x: &Qua<T>, y: &Qua<T>) -> TVec<bool, 4> {
+pub fn quat_not_equal<T: RealNumber>(x: &Qua<T>, y: &Qua<T>) -> TVec<bool, 4> {
     crate::not_equal(&x.coords, &y.coords)
 }
 
 /// Component-wise approximate non-equality comparison between two quaternions.
-pub fn quat_not_equal_eps<T: RealField>(x: &Qua<T>, y: &Qua<T>, epsilon: T) -> TVec<bool, 4> {
+pub fn quat_not_equal_eps<T: RealNumber>(x: &Qua<T>, y: &Qua<T>, epsilon: T) -> TVec<bool, 4> {
     crate::not_equal_eps(&x.coords, &y.coords, epsilon)
 }

nalgebra-glm/src/ext/quaternion_transform.rs

@@ -1,27 +1,28 @@
-use na::{RealField, Unit, UnitQuaternion};
+use na::{Unit, UnitQuaternion};
 
 use crate::aliases::{Qua, TVec3};
+use crate::RealNumber;
 
 /// Computes the quaternion exponential.
-pub fn quat_exp<T: RealField>(q: &Qua<T>) -> Qua<T> {
+pub fn quat_exp<T: RealNumber>(q: &Qua<T>) -> Qua<T> {
     q.exp()
 }
 
 /// Computes the quaternion logarithm.
-pub fn quat_log<T: RealField>(q: &Qua<T>) -> Qua<T> {
+pub fn quat_log<T: RealNumber>(q: &Qua<T>) -> Qua<T> {
     q.ln()
 }
 
 /// Raises the quaternion `q` to the power `y`.
-pub fn quat_pow<T: RealField>(q: &Qua<T>, y: T) -> Qua<T> {
+pub fn quat_pow<T: RealNumber>(q: &Qua<T>, y: T) -> Qua<T> {
     q.powf(y)
 }
 
 /// Builds a quaternion from an axis and an angle, and right-multiply it to the quaternion `q`.
-pub fn quat_rotate<T: RealField>(q: &Qua<T>, angle: T, axis: &TVec3<T>) -> Qua<T> {
+pub fn quat_rotate<T: RealNumber>(q: &Qua<T>, angle: T, axis: &TVec3<T>) -> Qua<T> {
     q * UnitQuaternion::from_axis_angle(&Unit::new_normalize(*axis), angle).into_inner()
 }
 
-//pub fn quat_sqrt<T: RealField>(q: &Qua<T>) -> Qua<T> {
+//pub fn quat_sqrt<T: RealNumber>(q: &Qua<T>) -> Qua<T> {
 //    unimplemented!()
 //}

nalgebra-glm/src/ext/quaternion_trigonometric.rs

@@ -1,19 +1,20 @@
-use na::{RealField, Unit, UnitQuaternion};
+use na::{Unit, UnitQuaternion};
 
 use crate::aliases::{Qua, TVec3};
+use crate::RealNumber;
 
 /// The rotation angle of this quaternion assumed to be normalized.
-pub fn quat_angle<T: RealField>(x: &Qua<T>) -> T {
+pub fn quat_angle<T: RealNumber>(x: &Qua<T>) -> T {
     UnitQuaternion::from_quaternion(*x).angle()
 }
 
 /// Creates a quaternion from an axis and an angle.
-pub fn quat_angle_axis<T: RealField>(angle: T, axis: &TVec3<T>) -> Qua<T> {
+pub fn quat_angle_axis<T: RealNumber>(angle: T, axis: &TVec3<T>) -> Qua<T> {
     UnitQuaternion::from_axis_angle(&Unit::new_normalize(*axis), angle).into_inner()
 }
 
 /// The rotation axis of a quaternion assumed to be normalized.
-pub fn quat_axis<T: RealField>(x: &Qua<T>) -> TVec3<T> {
+pub fn quat_axis<T: RealNumber>(x: &Qua<T>) -> TVec3<T> {
     if let Some(a) = UnitQuaternion::from_quaternion(*x).axis() {
         a.into_inner()
     } else {

nalgebra-glm/src/ext/scalar_constants.rs

@@ -1,5 +1,5 @@
+use crate::RealNumber;
 use approx::AbsDiffEq;
-use na::RealField;
 
 /// Default epsilon value used for approximate comparison.
 pub fn epsilon<T: AbsDiffEq<Epsilon = T>>() -> T {
@@ -22,6 +22,6 @@ pub fn epsilon<T: AbsDiffEq<Epsilon = T>>() -> T {
 /// * [`two_over_pi`](fn.two_over_pi.html)
 /// * [`two_over_root_pi`](fn.two_over_root_pi.html)
 /// * [`two_pi`](fn.two_pi.html)
-pub fn pi<T: RealField>() -> T {
+pub fn pi<T: RealNumber>() -> T {
     T::pi()
 }

nalgebra-glm/src/geometric.rs

@@ -1,4 +1,4 @@
-use na::RealField;
+use crate::RealNumber;
 
 use crate::aliases::{TVec, TVec3};
 use crate::traits::Number;
@@ -13,7 +13,7 @@ pub fn cross<T: Number>(x: &TVec3<T>, y: &TVec3<T>) -> TVec3<T> {
 /// # See also:
 ///
 /// * [`distance2`](fn.distance2.html)
-pub fn distance<T: RealField, const D: usize>(p0: &TVec<T, D>, p1: &TVec<T, D>) -> T {
+pub fn distance<T: RealNumber, const D: usize>(p0: &TVec<T, D>, p1: &TVec<T, D>) -> T {
     (p1 - p0).norm()
 }
 
@@ -44,7 +44,7 @@ pub fn faceforward<T: Number, const D: usize>(
 /// * [`length2`](fn.length2.html)
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude2`](fn.magnitude2.html)
-pub fn length<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
+pub fn length<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm()
 }
 
@@ -57,12 +57,12 @@ pub fn length<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
 /// * [`length`](fn.length.html)
 /// * [`magnitude2`](fn.magnitude2.html)
 /// * [`nalgebra::norm`](../nalgebra/fn.norm.html)
-pub fn magnitude<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
+pub fn magnitude<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm()
 }
 
 /// Normalizes a vector.
-pub fn normalize<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
+pub fn normalize<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.normalize()
 }
 
@@ -73,7 +73,7 @@ pub fn reflect_vec<T: Number, const D: usize>(i: &TVec<T, D>, n: &TVec<T, D>) ->
 }
 
 /// For the incident vector `i` and surface normal `n`, and the ratio of indices of refraction `eta`, return the refraction vector.
-pub fn refract_vec<T: RealField, const D: usize>(
+pub fn refract_vec<T: RealNumber, const D: usize>(
     i: &TVec<T, D>,
     n: &TVec<T, D>,
     eta: T,

nalgebra-glm/src/gtc/constants.rs

@@ -1,14 +1,15 @@
-use na::{self, RealField};
+use crate::RealNumber;
+use na;
 
 /// The Euler constant.
 ///
 /// This is a shorthand alias for [`euler`](fn.euler.html).
-pub fn e<T: RealField>() -> T {
+pub fn e<T: RealNumber>() -> T {
     T::e()
 }
 
 /// The Euler constant.
-pub fn euler<T: RealField>() -> T {
+pub fn euler<T: RealNumber>() -> T {
     T::e()
 }
 
@@ -28,12 +29,12 @@ pub fn euler<T: RealField>() -> T {
 /// * [`two_over_pi`](fn.two_over_pi.html)
 /// * [`two_over_root_pi`](fn.two_over_root_pi.html)
 /// * [`two_pi`](fn.two_pi.html)
-pub fn four_over_pi<T: RealField>() -> T {
+pub fn four_over_pi<T: RealNumber>() -> T {
     na::convert::<_, T>(4.0) / T::pi()
 }
 
 /// Returns the golden ratio.
-pub fn golden_ratio<T: RealField>() -> T {
+pub fn golden_ratio<T: RealNumber>() -> T {
     (T::one() + root_five()) / na::convert(2.0)
 }
 
@@ -53,7 +54,7 @@ pub fn golden_ratio<T: RealField>() -> T {
 /// * [`two_over_pi`](fn.two_over_pi.html)
 /// * [`two_over_root_pi`](fn.two_over_root_pi.html)
 /// * [`two_pi`](fn.two_pi.html)
-pub fn half_pi<T: RealField>() -> T {
+pub fn half_pi<T: RealNumber>() -> T {
     T::frac_pi_2()
 }
 
@@ -63,7 +64,7 @@ pub fn half_pi<T: RealField>() -> T {
 ///
 /// * [`ln_ten`](fn.ln_ten.html)
 /// * [`ln_two`](fn.ln_two.html)
-pub fn ln_ln_two<T: RealField>() -> T {
+pub fn ln_ln_two<T: RealNumber>() -> T {
     T::ln_2().ln()
 }
 
@@ -73,7 +74,7 @@ pub fn ln_ln_two<T: RealField>() -> T {
 ///
 /// * [`ln_ln_two`](fn.ln_ln_two.html)
 /// * [`ln_two`](fn.ln_two.html)
-pub fn ln_ten<T: RealField>() -> T {
+pub fn ln_ten<T: RealNumber>() -> T {
     T::ln_10()
 }
 
@@ -83,7 +84,7 @@ pub fn ln_ten<T: RealField>() -> T {
 ///
 /// * [`ln_ln_two`](fn.ln_ln_two.html)
 /// * [`ln_ten`](fn.ln_ten.html)
-pub fn ln_two<T: RealField>() -> T {
+pub fn ln_two<T: RealNumber>() -> T {
     T::ln_2()
 }
 
@@ -106,12 +107,12 @@ pub use na::one;
 /// * [`two_over_pi`](fn.two_over_pi.html)
 /// * [`two_over_root_pi`](fn.two_over_root_pi.html)
 /// * [`two_pi`](fn.two_pi.html)
-pub fn one_over_pi<T: RealField>() -> T {
+pub fn one_over_pi<T: RealNumber>() -> T {
     T::frac_1_pi()
 }
 
 /// Returns `1 / sqrt(2)`.
-pub fn one_over_root_two<T: RealField>() -> T {
+pub fn one_over_root_two<T: RealNumber>() -> T {
     T::one() / root_two()
 }
 
@@ -131,7 +132,7 @@ pub fn one_over_root_two<T: RealField>() -> T {
 /// * [`two_over_pi`](fn.two_over_pi.html)
 /// * [`two_over_root_pi`](fn.two_over_root_pi.html)
 /// * [`two_pi`](fn.two_pi.html)
-pub fn one_over_two_pi<T: RealField>() -> T {
+pub fn one_over_two_pi<T: RealNumber>() -> T {
     T::frac_1_pi() * na::convert(0.5)
 }
 
@@ -151,7 +152,7 @@ pub fn one_over_two_pi<T: RealField>() -> T {
 /// * [`two_over_pi`](fn.two_over_pi.html)
 /// * [`two_over_root_pi`](fn.two_over_root_pi.html)
 /// * [`two_pi`](fn.two_pi.html)
-pub fn quarter_pi<T: RealField>() -> T {
+pub fn quarter_pi<T: RealNumber>() -> T {
     T::frac_pi_4()
 }
 
@@ -161,7 +162,7 @@ pub fn quarter_pi<T: RealField>() -> T {
 ///
 /// * [`root_three`](fn.root_three.html)
 /// * [`root_two`](fn.root_two.html)
-pub fn root_five<T: RealField>() -> T {
+pub fn root_five<T: RealNumber>() -> T {
     na::convert::<_, T>(5.0).sqrt()
 }
 
@@ -181,12 +182,12 @@ pub fn root_five<T: RealField>() -> T {
 /// * [`two_over_pi`](fn.two_over_pi.html)
 /// * [`two_over_root_pi`](fn.two_over_root_pi.html)
 /// * [`two_pi`](fn.two_pi.html)
-pub fn root_half_pi<T: RealField>() -> T {
+pub fn root_half_pi<T: RealNumber>() -> T {
     (T::pi() / na::convert(2.0)).sqrt()
 }
 
 /// Returns `sqrt(ln(4))`.
-pub fn root_ln_four<T: RealField>() -> T {
+pub fn root_ln_four<T: RealNumber>() -> T {
     na::convert::<_, T>(4.0).ln().sqrt()
 }
 
@@ -206,7 +207,7 @@ pub fn root_ln_four<T: RealField>() -> T {
 /// * [`two_over_pi`](fn.two_over_pi.html)
 /// * [`two_over_root_pi`](fn.two_over_root_pi.html)
 /// * [`two_pi`](fn.two_pi.html)
-pub fn root_pi<T: RealField>() -> T {
+pub fn root_pi<T: RealNumber>() -> T {
     T::pi().sqrt()
 }
 
@@ -216,7 +217,7 @@ pub fn root_pi<T: RealField>() -> T {
 ///
 /// * [`root_five`](fn.root_five.html)
 /// * [`root_two`](fn.root_two.html)
-pub fn root_three<T: RealField>() -> T {
+pub fn root_three<T: RealNumber>() -> T {
     na::convert::<_, T>(3.0).sqrt()
 }
 
@@ -226,8 +227,8 @@ pub fn root_three<T: RealField>() -> T {
 ///
 /// * [`root_five`](fn.root_five.html)
 /// * [`root_three`](fn.root_three.html)
-pub fn root_two<T: RealField>() -> T {
-    // TODO: there should be a crate::sqrt_2() on the RealField trait.
+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()
 }
 
@@ -247,7 +248,7 @@ pub fn root_two<T: RealField>() -> T {
 /// * [`two_over_pi`](fn.two_over_pi.html)
 /// * [`two_over_root_pi`](fn.two_over_root_pi.html)
 /// * [`two_pi`](fn.two_pi.html)
-pub fn root_two_pi<T: RealField>() -> T {
+pub fn root_two_pi<T: RealNumber>() -> T {
     T::two_pi().sqrt()
 }
 
@@ -256,7 +257,7 @@ pub fn root_two_pi<T: RealField>() -> T {
 /// # See also:
 ///
 /// * [`two_thirds`](fn.two_thirds.html)
-pub fn third<T: RealField>() -> T {
+pub fn third<T: RealNumber>() -> T {
     na::convert(1.0 / 3.0)
 }
 
@@ -276,7 +277,7 @@ pub fn third<T: RealField>() -> T {
 /// * [`two_over_pi`](fn.two_over_pi.html)
 /// * [`two_over_root_pi`](fn.two_over_root_pi.html)
 /// * [`two_pi`](fn.two_pi.html)
-pub fn three_over_two_pi<T: RealField>() -> T {
+pub fn three_over_two_pi<T: RealNumber>() -> T {
     na::convert::<_, T>(3.0) / T::two_pi()
 }
 
@@ -295,7 +296,7 @@ pub fn three_over_two_pi<T: RealField>() -> T {
 /// * [`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)
-pub fn two_over_pi<T: RealField>() -> T {
+pub fn two_over_pi<T: RealNumber>() -> T {
     T::frac_2_pi()
 }
 
@@ -315,7 +316,7 @@ pub fn two_over_pi<T: RealField>() -> T {
 /// * [`three_over_two_pi`](fn.three_over_two_pi.html)
 /// * [`two_over_pi`](fn.two_over_pi.html)
 /// * [`two_pi`](fn.two_pi.html)
-pub fn two_over_root_pi<T: RealField>() -> T {
+pub fn two_over_root_pi<T: RealNumber>() -> T {
     T::frac_2_sqrt_pi()
 }
 
@@ -335,7 +336,7 @@ pub fn two_over_root_pi<T: RealField>() -> T {
 /// * [`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)
-pub fn two_pi<T: RealField>() -> T {
+pub fn two_pi<T: RealNumber>() -> T {
     T::two_pi()
 }
 
@@ -344,7 +345,7 @@ pub fn two_pi<T: RealField>() -> T {
 /// # See also:
 ///
 /// * [`third`](fn.third.html)
-pub fn two_thirds<T: RealField>() -> T {
+pub fn two_thirds<T: RealNumber>() -> T {
     na::convert(2.0 / 3.0)
 }
 

nalgebra-glm/src/gtc/matrix_inverse.rs

@@ -1,15 +1,15 @@
-use na::RealField;
+use crate::RealNumber;
 
 use crate::aliases::TMat;
 
 /// Fast matrix inverse for affine matrix.
-pub fn affine_inverse<T: RealField, const D: usize>(m: TMat<T, D, D>) -> TMat<T, D, D> {
+pub fn affine_inverse<T: RealNumber, const D: usize>(m: TMat<T, D, D>) -> TMat<T, D, D> {
     // TODO: this should be optimized.
     m.try_inverse().unwrap_or_else(TMat::<_, D, D>::zeros)
 }
 
 /// Compute the transpose of the inverse of a matrix.
-pub fn inverse_transpose<T: RealField, const D: usize>(m: TMat<T, D, D>) -> TMat<T, D, D> {
+pub fn inverse_transpose<T: RealNumber, const D: usize>(m: TMat<T, D, D>) -> TMat<T, D, D> {
     m.try_inverse()
         .unwrap_or_else(TMat::<_, D, D>::zeros)
         .transpose()

nalgebra-glm/src/gtc/packing.rs

@@ -1,4 +1,4 @@
-use na::{DefaultAllocator, RealField, Scalar, U3, U4};
+use na::{DefaultAllocator, RealNumber, Scalar, U3, U4};
 
 use crate::aliases::*;
 
@@ -53,7 +53,7 @@ pub fn packRGBM<T: Scalar>(rgb: &TVec3<T>) -> TVec4<T> {
     unimplemented!()
 }
 
-pub fn packSnorm<I: Scalar, T: RealField, const D: usize>(v: TVec<T, D>) -> TVec<I, D>
+pub fn packSnorm<I: Scalar, T: RealNumber, const D: usize>(v: TVec<T, D>) -> TVec<I, D>
 where
     DefaultAllocator: Alloc<T, D> + Alloc<I, D>,
 {
@@ -104,7 +104,7 @@ pub fn packUint4x8(v: &U8Vec4) -> i32 {
     unimplemented!()
 }
 
-pub fn packUnorm<UI: Scalar, T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<UI, D>
+pub fn packUnorm<UI: Scalar, T: RealNumber, const D: usize>(v: &TVec<T, D>) -> TVec<UI, D>
 where
     DefaultAllocator: Alloc<T, D> + Alloc<UI, D>,
 {
@@ -199,7 +199,7 @@ pub fn unpackRGBM<T: Scalar>(rgbm: &TVec4<T>) -> TVec3<T> {
     unimplemented!()
 }
 
-pub fn unpackSnorm<I: Scalar, T: RealField, const D: usize>(v: &TVec<I, D>) -> TVec<T, D>
+pub fn unpackSnorm<I: Scalar, T: RealNumber, const D: usize>(v: &TVec<I, D>) -> TVec<T, D>
 where
     DefaultAllocator: Alloc<T, D> + Alloc<I, D>,
 {
@@ -250,7 +250,7 @@ pub fn unpackUint4x8(p: i32) -> U8Vec4 {
     unimplemented!()
 }
 
-pub fn unpackUnorm<UI: Scalar, T: RealField, const D: usize>(v: &TVec<UI, D>) -> TVec<T, D>
+pub fn unpackUnorm<UI: Scalar, T: RealNumber, const D: usize>(v: &TVec<UI, D>) -> TVec<T, D>
 where
     DefaultAllocator: Alloc<T, D> + Alloc<UI, D>,
 {

nalgebra-glm/src/gtc/quaternion.rs

@@ -1,36 +1,37 @@
-use na::{RealField, UnitQuaternion};
+use na::UnitQuaternion;
 
 use crate::aliases::{Qua, TMat4, TVec, TVec3};
+use crate::RealNumber;
 
 /// Euler angles of the quaternion `q` as (pitch, yaw, roll).
-pub fn quat_euler_angles<T: RealField>(x: &Qua<T>) -> TVec3<T> {
+pub fn quat_euler_angles<T: RealNumber>(x: &Qua<T>) -> TVec3<T> {
     let q = UnitQuaternion::new_unchecked(*x);
     let a = q.euler_angles();
     TVec3::new(a.2, a.1, a.0)
 }
 
 /// Component-wise `>` comparison between two quaternions.
-pub fn quat_greater_than<T: RealField>(x: &Qua<T>, y: &Qua<T>) -> TVec<bool, 4> {
+pub fn quat_greater_than<T: RealNumber>(x: &Qua<T>, y: &Qua<T>) -> TVec<bool, 4> {
     crate::greater_than(&x.coords, &y.coords)
 }
 
 /// Component-wise `>=` comparison between two quaternions.
-pub fn quat_greater_than_equal<T: RealField>(x: &Qua<T>, y: &Qua<T>) -> TVec<bool, 4> {
+pub fn quat_greater_than_equal<T: RealNumber>(x: &Qua<T>, y: &Qua<T>) -> TVec<bool, 4> {
     crate::greater_than_equal(&x.coords, &y.coords)
 }
 
 /// Component-wise `<` comparison between two quaternions.
-pub fn quat_less_than<T: RealField>(x: &Qua<T>, y: &Qua<T>) -> TVec<bool, 4> {
+pub fn quat_less_than<T: RealNumber>(x: &Qua<T>, y: &Qua<T>) -> TVec<bool, 4> {
     crate::less_than(&x.coords, &y.coords)
 }
 
 /// Component-wise `<=` comparison between two quaternions.
-pub fn quat_less_than_equal<T: RealField>(x: &Qua<T>, y: &Qua<T>) -> TVec<bool, 4> {
+pub fn quat_less_than_equal<T: RealNumber>(x: &Qua<T>, y: &Qua<T>) -> TVec<bool, 4> {
     crate::less_than_equal(&x.coords, &y.coords)
 }
 
 /// Convert a quaternion to a rotation matrix in homogeneous coordinates.
-pub fn quat_cast<T: RealField>(x: &Qua<T>) -> TMat4<T> {
+pub fn quat_cast<T: RealNumber>(x: &Qua<T>) -> TMat4<T> {
     crate::quat_to_mat4(x)
 }
 
@@ -41,34 +42,34 @@ pub fn quat_cast<T: RealField>(x: &Qua<T>) -> TMat4<T> {
 /// * `direction` - Direction vector point at where to look
 /// * `up` - Object up vector
 ///
-pub fn quat_look_at<T: RealField>(direction: &TVec3<T>, up: &TVec3<T>) -> Qua<T> {
+pub fn quat_look_at<T: RealNumber>(direction: &TVec3<T>, up: &TVec3<T>) -> Qua<T> {
     quat_look_at_rh(direction, up)
 }
 
 /// Computes a left-handed look-at quaternion (equivalent to a left-handed look-at matrix).
-pub fn quat_look_at_lh<T: RealField>(direction: &TVec3<T>, up: &TVec3<T>) -> Qua<T> {
+pub fn quat_look_at_lh<T: RealNumber>(direction: &TVec3<T>, up: &TVec3<T>) -> Qua<T> {
     UnitQuaternion::look_at_lh(direction, up).into_inner()
 }
 
 /// Computes a right-handed look-at quaternion (equivalent to a right-handed look-at matrix).
-pub fn quat_look_at_rh<T: RealField>(direction: &TVec3<T>, up: &TVec3<T>) -> Qua<T> {
+pub fn quat_look_at_rh<T: RealNumber>(direction: &TVec3<T>, up: &TVec3<T>) -> Qua<T> {
     UnitQuaternion::look_at_rh(direction, up).into_inner()
 }
 
 /// The "roll" Euler angle of the quaternion `x` assumed to be normalized.
-pub fn quat_roll<T: RealField>(x: &Qua<T>) -> T {
+pub fn quat_roll<T: RealNumber>(x: &Qua<T>) -> T {
     // TODO: optimize this.
     quat_euler_angles(x).z
 }
 
 /// The "yaw" Euler angle of the quaternion `x` assumed to be normalized.
-pub fn quat_yaw<T: RealField>(x: &Qua<T>) -> T {
+pub fn quat_yaw<T: RealNumber>(x: &Qua<T>) -> T {
     // TODO: optimize this.
     quat_euler_angles(x).y
 }
 
 /// The "pitch" Euler angle of the quaternion `x` assumed to be normalized.
-pub fn quat_pitch<T: RealField>(x: &Qua<T>) -> T {
+pub fn quat_pitch<T: RealNumber>(x: &Qua<T>) -> T {
     // TODO: optimize this.
     quat_euler_angles(x).x
 }

nalgebra-glm/src/gtc/round.rs

@@ -1,4 +1,4 @@
-use na::{DefaultAllocator, RealField, Scalar, U3};
+use na::{DefaultAllocator, RealNumber, Scalar, U3};
 
 use crate::aliases::TVec;
 use crate::traits::{Alloc, Dimension, Number};

nalgebra-glm/src/gtc/type_ptr.rs

@@ -1,10 +1,10 @@
-use na::{Quaternion, RealField, Scalar};
+use na::{Quaternion, Scalar};
 
 use crate::aliases::{
     Qua, TMat, TMat2, TMat2x3, TMat2x4, TMat3, TMat3x2, TMat3x4, TMat4, TMat4x2, TMat4x3, TVec1,
     TVec2, TVec3, TVec4,
 };
-use crate::traits::Number;
+use crate::traits::{Number, RealNumber};
 
 /// Creates a 2x2 matrix from a slice arranged in column-major order.
 pub fn make_mat2<T: Scalar>(ptr: &[T]) -> TMat2<T> {
@@ -76,12 +76,7 @@ pub fn mat2_to_mat3<T: Number>(m: &TMat2<T>) -> TMat3<T> {
 
 /// Converts a 3x3 matrix to a 2x2 matrix.
 pub fn mat3_to_mat2<T: Scalar>(m: &TMat3<T>) -> TMat2<T> {
-    TMat2::new(
-        m.m11.inlined_clone(),
-        m.m12.inlined_clone(),
-        m.m21.inlined_clone(),
-        m.m22.inlined_clone(),
-    )
+    TMat2::new(m.m11.clone(), m.m12.clone(), m.m21.clone(), m.m22.clone())
 }
 
 /// Converts a 3x3 matrix to a 4x4 matrix.
@@ -97,15 +92,15 @@ pub fn mat3_to_mat4<T: Number>(m: &TMat3<T>) -> TMat4<T> {
 /// Converts a 4x4 matrix to a 3x3 matrix.
 pub fn mat4_to_mat3<T: Scalar>(m: &TMat4<T>) -> TMat3<T> {
     TMat3::new(
-        m.m11.inlined_clone(),
-        m.m12.inlined_clone(),
-        m.m13.inlined_clone(),
-        m.m21.inlined_clone(),
-        m.m22.inlined_clone(),
-        m.m23.inlined_clone(),
-        m.m31.inlined_clone(),
-        m.m32.inlined_clone(),
-        m.m33.inlined_clone(),
+        m.m11.clone(),
+        m.m12.clone(),
+        m.m13.clone(),
+        m.m21.clone(),
+        m.m22.clone(),
+        m.m23.clone(),
+        m.m31.clone(),
+        m.m32.clone(),
+        m.m33.clone(),
     )
 }
 
@@ -121,16 +116,11 @@ pub fn mat2_to_mat4<T: Number>(m: &TMat2<T>) -> TMat4<T> {
 
 /// Converts a 4x4 matrix to a 2x2 matrix.
 pub fn mat4_to_mat2<T: Scalar>(m: &TMat4<T>) -> TMat2<T> {
-    TMat2::new(
-        m.m11.inlined_clone(),
-        m.m12.inlined_clone(),
-        m.m21.inlined_clone(),
-        m.m22.inlined_clone(),
-    )
+    TMat2::new(m.m11.clone(), m.m12.clone(), m.m21.clone(), m.m22.clone())
 }
 
 /// Creates a quaternion from a slice arranged as `[x, y, z, w]`.
-pub fn make_quat<T: RealField>(ptr: &[T]) -> Qua<T> {
+pub fn make_quat<T: RealNumber>(ptr: &[T]) -> Qua<T> {
     Quaternion::from(TVec4::from_column_slice(ptr))
 }
 
@@ -156,7 +146,7 @@ pub fn make_vec1<T: Scalar>(v: &TVec1<T>) -> TVec1<T> {
 /// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
 /// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
 pub fn vec2_to_vec1<T: Scalar>(v: &TVec2<T>) -> TVec1<T> {
-    TVec1::new(v.x.inlined_clone())
+    TVec1::new(v.x.clone())
 }
 
 /// Creates a 1D vector from another vector.
@@ -170,7 +160,7 @@ pub fn vec2_to_vec1<T: Scalar>(v: &TVec2<T>) -> TVec1<T> {
 /// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
 /// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
 pub fn vec3_to_vec1<T: Scalar>(v: &TVec3<T>) -> TVec1<T> {
-    TVec1::new(v.x.inlined_clone())
+    TVec1::new(v.x.clone())
 }
 
 /// Creates a 1D vector from another vector.
@@ -184,7 +174,7 @@ pub fn vec3_to_vec1<T: Scalar>(v: &TVec3<T>) -> TVec1<T> {
 /// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
 /// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
 pub fn vec4_to_vec1<T: Scalar>(v: &TVec4<T>) -> TVec1<T> {
-    TVec1::new(v.x.inlined_clone())
+    TVec1::new(v.x.clone())
 }
 
 /// Creates a 2D vector from another vector.
@@ -200,7 +190,7 @@ pub fn vec4_to_vec1<T: Scalar>(v: &TVec4<T>) -> TVec1<T> {
 /// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
 /// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
 pub fn vec1_to_vec2<T: Number>(v: &TVec1<T>) -> TVec2<T> {
-    TVec2::new(v.x.inlined_clone(), T::zero())
+    TVec2::new(v.x.clone(), T::zero())
 }
 
 /// Creates a 2D vector from another vector.
@@ -229,7 +219,7 @@ pub fn vec2_to_vec2<T: Scalar>(v: &TVec2<T>) -> TVec2<T> {
 /// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
 /// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
 pub fn vec3_to_vec2<T: Scalar>(v: &TVec3<T>) -> TVec2<T> {
-    TVec2::new(v.x.inlined_clone(), v.y.inlined_clone())
+    TVec2::new(v.x.clone(), v.y.clone())
 }
 
 /// Creates a 2D vector from another vector.
@@ -243,7 +233,7 @@ pub fn vec3_to_vec2<T: Scalar>(v: &TVec3<T>) -> TVec2<T> {
 /// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
 /// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
 pub fn vec4_to_vec2<T: Scalar>(v: &TVec4<T>) -> TVec2<T> {
-    TVec2::new(v.x.inlined_clone(), v.y.inlined_clone())
+    TVec2::new(v.x.clone(), v.y.clone())
 }
 
 /// Creates a 2D vector from a slice.
@@ -269,7 +259,7 @@ pub fn make_vec2<T: Scalar>(ptr: &[T]) -> TVec2<T> {
 /// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
 /// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
 pub fn vec1_to_vec3<T: Number>(v: &TVec1<T>) -> TVec3<T> {
-    TVec3::new(v.x.inlined_clone(), T::zero(), T::zero())
+    TVec3::new(v.x.clone(), T::zero(), T::zero())
 }
 
 /// Creates a 3D vector from another vector.
@@ -285,7 +275,7 @@ pub fn vec1_to_vec3<T: Number>(v: &TVec1<T>) -> TVec3<T> {
 /// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
 /// * [`vec3_to_vec4`](fn.vec3_to_vec4.html)
 pub fn vec2_to_vec3<T: Number>(v: &TVec2<T>) -> TVec3<T> {
-    TVec3::new(v.x.inlined_clone(), v.y.inlined_clone(), T::zero())
+    TVec3::new(v.x.clone(), v.y.clone(), T::zero())
 }
 
 /// Creates a 3D vector from another vector.
@@ -313,11 +303,7 @@ pub fn vec3_to_vec3<T: Scalar>(v: &TVec3<T>) -> TVec3<T> {
 /// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
 /// * [`vec3_to_vec4`](fn.vec3_to_vec4.html)
 pub fn vec4_to_vec3<T: Scalar>(v: &TVec4<T>) -> TVec3<T> {
-    TVec3::new(
-        v.x.inlined_clone(),
-        v.y.inlined_clone(),
-        v.z.inlined_clone(),
-    )
+    TVec3::new(v.x.clone(), v.y.clone(), v.z.clone())
 }
 
 /// Creates a 3D vector from another vector.

nalgebra-glm/src/gtx/euler_angles.rs

@@ -1,163 +1,163 @@
-use na::{RealField, U3, U4};
+use na::{RealNumber, U3, U4};
 
 use crate::aliases::{TMat, TVec};
 
-pub fn derivedEulerAngleX<T: RealField>(angleX: T, angularVelocityX: T) -> TMat4<T> {
+pub fn derivedEulerAngleX<T: RealNumber>(angleX: T, angularVelocityX: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn derivedEulerAngleY<T: RealField>(angleY: T, angularVelocityY: T) -> TMat4<T> {
+pub fn derivedEulerAngleY<T: RealNumber>(angleY: T, angularVelocityY: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn derivedEulerAngleZ<T: RealField>(angleZ: T, angularVelocityZ: T) -> TMat4<T> {
+pub fn derivedEulerAngleZ<T: RealNumber>(angleZ: T, angularVelocityZ: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleX<T: RealField>(angleX: T) -> TMat4<T> {
+pub fn eulerAngleX<T: RealNumber>(angleX: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleXY<T: RealField>(angleX: T, angleY: T) -> TMat4<T> {
+pub fn eulerAngleXY<T: RealNumber>(angleX: T, angleY: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleXYX<T: RealField>(t1: T, t2: T, t3: T) -> TMat4<T> {
+pub fn eulerAngleXYX<T: RealNumber>(t1: T, t2: T, t3: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleXYZ<T: RealField>(t1: T, t2: T, t3: T) -> TMat4<T> {
+pub fn eulerAngleXYZ<T: RealNumber>(t1: T, t2: T, t3: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleXZ<T: RealField>(angleX: T, angleZ: T) -> TMat4<T> {
+pub fn eulerAngleXZ<T: RealNumber>(angleX: T, angleZ: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleXZX<T: RealField>(t1: T, t2: T, t3: T) -> TMat4<T> {
+pub fn eulerAngleXZX<T: RealNumber>(t1: T, t2: T, t3: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleXZY<T: RealField>(t1: T, t2: T, t3: T) -> TMat4<T> {
+pub fn eulerAngleXZY<T: RealNumber>(t1: T, t2: T, t3: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleY<T: RealField>(angleY: T) -> TMat4<T> {
+pub fn eulerAngleY<T: RealNumber>(angleY: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleYX<T: RealField>(angleY: T, angleX: T) -> TMat4<T> {
+pub fn eulerAngleYX<T: RealNumber>(angleY: T, angleX: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleYXY<T: RealField>(t1: T, t2: T, t3: T) -> TMat4<T> {
+pub fn eulerAngleYXY<T: RealNumber>(t1: T, t2: T, t3: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleYXZ<T: RealField>(yaw: T, pitch: T, roll: T) -> TMat4<T> {
+pub fn eulerAngleYXZ<T: RealNumber>(yaw: T, pitch: T, roll: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleYZ<T: RealField>(angleY: T, angleZ: T) -> TMat4<T> {
+pub fn eulerAngleYZ<T: RealNumber>(angleY: T, angleZ: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleYZX<T: RealField>(t1: T, t2: T, t3: T) -> TMat4<T> {
+pub fn eulerAngleYZX<T: RealNumber>(t1: T, t2: T, t3: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleYZY<T: RealField>(t1: T, t2: T, t3: T) -> TMat4<T> {
+pub fn eulerAngleYZY<T: RealNumber>(t1: T, t2: T, t3: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleZ<T: RealField>(angleZ: T) -> TMat4<T> {
+pub fn eulerAngleZ<T: RealNumber>(angleZ: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleZX<T: RealField>(angle: T, angleX: T) -> TMat4<T> {
+pub fn eulerAngleZX<T: RealNumber>(angle: T, angleX: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleZXY<T: RealField>(t1: T, t2: T, t3: T) -> TMat4<T> {
+pub fn eulerAngleZXY<T: RealNumber>(t1: T, t2: T, t3: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleZXZ<T: RealField>(t1: T, t2: T, t3: T) -> TMat4<T> {
+pub fn eulerAngleZXZ<T: RealNumber>(t1: T, t2: T, t3: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleZY<T: RealField>(angleZ: T, angleY: T) -> TMat4<T> {
+pub fn eulerAngleZY<T: RealNumber>(angleZ: T, angleY: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleZYX<T: RealField>(t1: T, t2: T, t3: T) -> TMat4<T> {
+pub fn eulerAngleZYX<T: RealNumber>(t1: T, t2: T, t3: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn eulerAngleZYZ<T: RealField>(t1: T, t2: T, t3: T) -> TMat4<T> {
+pub fn eulerAngleZYZ<T: RealNumber>(t1: T, t2: T, t3: T) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn extractEulerAngleXYX<T: RealField>(M: &TMat4<T>) -> (T, T, T) {
+pub fn extractEulerAngleXYX<T: RealNumber>(M: &TMat4<T>) -> (T, T, T) {
     unimplemented!()
 }
 
-pub fn extractEulerAngleXYZ<T: RealField>(M: &TMat4<T>) -> (T, T, T) {
+pub fn extractEulerAngleXYZ<T: RealNumber>(M: &TMat4<T>) -> (T, T, T) {
     unimplemented!()
 }
 
-pub fn extractEulerAngleXZX<T: RealField>(M: &TMat4<T>) -> (T, T, T) {
+pub fn extractEulerAngleXZX<T: RealNumber>(M: &TMat4<T>) -> (T, T, T) {
     unimplemented!()
 }
 
-pub fn extractEulerAngleXZY<T: RealField>(M: &TMat4<T>) -> (T, T, T) {
+pub fn extractEulerAngleXZY<T: RealNumber>(M: &TMat4<T>) -> (T, T, T) {
     unimplemented!()
 }
 
-pub fn extractEulerAngleYXY<T: RealField>(M: &TMat4<T>) -> (T, T, T) {
+pub fn extractEulerAngleYXY<T: RealNumber>(M: &TMat4<T>) -> (T, T, T) {
     unimplemented!()
 }
 
-pub fn extractEulerAngleYXZ<T: RealField>(M: &TMat4<T>) -> (T, T, T) {
+pub fn extractEulerAngleYXZ<T: RealNumber>(M: &TMat4<T>) -> (T, T, T) {
     unimplemented!()
 }
 
-pub fn extractEulerAngleYZX<T: RealField>(M: &TMat4<T>) -> (T, T, T) {
+pub fn extractEulerAngleYZX<T: RealNumber>(M: &TMat4<T>) -> (T, T, T) {
     unimplemented!()
 }
 
-pub fn extractEulerAngleYZY<T: RealField>(M: &TMat4<T>) -> (T, T, T) {
+pub fn extractEulerAngleYZY<T: RealNumber>(M: &TMat4<T>) -> (T, T, T) {
     unimplemented!()
 }
 
-pub fn extractEulerAngleZXY<T: RealField>(M: &TMat4<T>) -> (T, T, T) {
+pub fn extractEulerAngleZXY<T: RealNumber>(M: &TMat4<T>) -> (T, T, T) {
     unimplemented!()
 }
 
-pub fn extractEulerAngleZXZ<T: RealField>(M: &TMat4<T>) -> (T, T, T) {
+pub fn extractEulerAngleZXZ<T: RealNumber>(M: &TMat4<T>) -> (T, T, T) {
     unimplemented!()
 }
 
-pub fn extractEulerAngleZYX<T: RealField>(M: &TMat4<T>) -> (T, T, T) {
+pub fn extractEulerAngleZYX<T: RealNumber>(M: &TMat4<T>) -> (T, T, T) {
     unimplemented!()
 }
 
-pub fn extractEulerAngleZYZ<T: RealField>(M: &TMat4<T>) -> (T, T, T) {
+pub fn extractEulerAngleZYZ<T: RealNumber>(M: &TMat4<T>) -> (T, T, T) {
     unimplemented!()
 }
 
-pub fn orientate2<T: RealField>(angle: T) -> TMat3x3<T> {
+pub fn orientate2<T: RealNumber>(angle: T) -> TMat3x3<T> {
     unimplemented!()
 }
 
-pub fn orientate3<T: RealField>(angles: TVec3<T>) -> TMat3x3<T> {
+pub fn orientate3<T: RealNumber>(angles: TVec3<T>) -> TMat3x3<T> {
     unimplemented!()
 }
 
-pub fn orientate4<T: RealField>(angles: TVec3<T>) -> TMat4<T> {
+pub fn orientate4<T: RealNumber>(angles: TVec3<T>) -> TMat4<T> {
     unimplemented!()
 }
 
-pub fn yawPitchRoll<T: RealField>(yaw: T, pitch: T, roll: T) -> TMat4<T> {
+pub fn yawPitchRoll<T: RealNumber>(yaw: T, pitch: T, roll: T) -> TMat4<T> {
     unimplemented!()
 }

nalgebra-glm/src/gtx/matrix_cross_product.rs

@@ -1,13 +1,12 @@
-use na::RealField;
-
 use crate::aliases::{TMat3, TMat4, TVec3};
+use crate::RealNumber;
 
 /// Builds a 3x3 matrix `m` such that for any `v`: `m * v == cross(x, v)`.
 ///
 /// # See also:
 ///
 /// * [`matrix_cross`](fn.matrix_cross.html)
-pub fn matrix_cross3<T: RealField>(x: &TVec3<T>) -> TMat3<T> {
+pub fn matrix_cross3<T: RealNumber>(x: &TVec3<T>) -> TMat3<T> {
     x.cross_matrix()
 }
 
@@ -16,6 +15,6 @@ pub fn matrix_cross3<T: RealField>(x: &TVec3<T>) -> TMat3<T> {
 /// # See also:
 ///
 /// * [`matrix_cross3`](fn.matrix_cross3.html)
-pub fn matrix_cross<T: RealField>(x: &TVec3<T>) -> TMat4<T> {
+pub fn matrix_cross<T: RealNumber>(x: &TVec3<T>) -> TMat4<T> {
     crate::mat3_to_mat4(&x.cross_matrix())
 }

nalgebra-glm/src/gtx/norm.rs

@@ -1,13 +1,12 @@
-use na::RealField;
-
 use crate::aliases::TVec;
+use crate::RealNumber;
 
 /// The squared distance between two points.
 ///
 /// # See also:
 ///
 /// * [`distance`](fn.distance.html)
-pub fn distance2<T: RealField, const D: usize>(p0: &TVec<T, D>, p1: &TVec<T, D>) -> T {
+pub fn distance2<T: RealNumber, const D: usize>(p0: &TVec<T, D>, p1: &TVec<T, D>) -> T {
     (p1 - p0).norm_squared()
 }
 
@@ -18,7 +17,7 @@ pub fn distance2<T: RealField, const D: usize>(p0: &TVec<T, D>, p1: &TVec<T, D>)
 /// * [`l1_norm`](fn.l1_norm.html)
 /// * [`l2_distance`](fn.l2_distance.html)
 /// * [`l2_norm`](fn.l2_norm.html)
-pub fn l1_distance<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
+pub fn l1_distance<T: RealNumber, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
     l1_norm(&(y - x))
 }
 
@@ -32,7 +31,7 @@ pub fn l1_distance<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>)
 /// * [`l1_distance`](fn.l1_distance.html)
 /// * [`l2_distance`](fn.l2_distance.html)
 /// * [`l2_norm`](fn.l2_norm.html)
-pub fn l1_norm<T: RealField, const D: usize>(v: &TVec<T, D>) -> T {
+pub fn l1_norm<T: RealNumber, const D: usize>(v: &TVec<T, D>) -> T {
     crate::comp_add(&v.abs())
 }
 
@@ -50,7 +49,7 @@ pub fn l1_norm<T: RealField, const D: usize>(v: &TVec<T, D>) -> T {
 /// * [`length2`](fn.length2.html)
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude2`](fn.magnitude2.html)
-pub fn l2_distance<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
+pub fn l2_distance<T: RealNumber, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
     l2_norm(&(y - x))
 }
 
@@ -70,7 +69,7 @@ pub fn l2_distance<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>)
 /// * [`length2`](fn.length2.html)
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude2`](fn.magnitude2.html)
-pub fn l2_norm<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
+pub fn l2_norm<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm()
 }
 
@@ -85,7 +84,7 @@ pub fn l2_norm<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
 /// * [`length`](fn.length.html)
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude2`](fn.magnitude2.html)
-pub fn length2<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
+pub fn length2<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm_squared()
 }
 
@@ -100,14 +99,14 @@ pub fn length2<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
 /// * [`length2`](fn.length2.html)
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`nalgebra::norm_squared`](../nalgebra/fn.norm_squared.html)
-pub fn magnitude2<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
+pub fn magnitude2<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm_squared()
 }
 
-//pub fn lxNorm<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, unsigned int Depth) -> T {
+//pub fn lxNorm<T: RealNumber, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, unsigned int Depth) -> T {
 //    unimplemented!()
 //}
 //
-//pub fn lxNorm<T: RealField, const D: usize>(x: &TVec<T, D>, unsigned int Depth) -> T  {
+//pub fn lxNorm<T: RealNumber, const D: usize>(x: &TVec<T, D>, unsigned int Depth) -> T  {
 //    unimplemented!()
 //}

nalgebra-glm/src/gtx/normal.rs

@@ -1,10 +1,10 @@
-use na::RealField;
+use crate::RealNumber;
 
 use crate::aliases::TVec3;
 
 /// The normal vector of the given triangle.
 ///
 /// The normal is computed as the normalized vector `cross(p2 - p1, p3 - p1)`.
-pub fn triangle_normal<T: RealField>(p1: &TVec3<T>, p2: &TVec3<T>, p3: &TVec3<T>) -> TVec3<T> {
+pub fn triangle_normal<T: RealNumber>(p1: &TVec3<T>, p2: &TVec3<T>, p3: &TVec3<T>) -> TVec3<T> {
     (p2 - p1).cross(&(p3 - p1)).normalize()
 }

nalgebra-glm/src/gtx/normalize_dot.rs

@@ -1,4 +1,4 @@
-use na::RealField;
+use crate::RealNumber;
 
 use crate::aliases::TVec;
 
@@ -9,7 +9,7 @@ use crate::aliases::TVec;
 /// # See also:
 ///
 /// * [`normalize_dot`](fn.normalize_dot.html`)
-pub fn fast_normalize_dot<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
+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())
 }
@@ -19,7 +19,7 @@ pub fn fast_normalize_dot<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec
 /// # See also:
 ///
 /// * [`fast_normalize_dot`](fn.fast_normalize_dot.html`)
-pub fn normalize_dot<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
+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/quaternion.rs

@@ -1,97 +1,98 @@
-use na::{RealField, Rotation3, Unit, UnitQuaternion};
+use na::{Rotation3, Unit, UnitQuaternion};
 
 use crate::aliases::{Qua, TMat3, TMat4, TVec3, TVec4};
+use crate::RealNumber;
 
 /// Rotate the vector `v` by the quaternion `q` assumed to be normalized.
-pub fn quat_cross_vec<T: RealField>(q: &Qua<T>, v: &TVec3<T>) -> TVec3<T> {
+pub fn quat_cross_vec<T: RealNumber>(q: &Qua<T>, v: &TVec3<T>) -> TVec3<T> {
     UnitQuaternion::new_unchecked(*q) * v
 }
 
 /// Rotate the vector `v` by the inverse of the quaternion `q` assumed to be normalized.
-pub fn quat_inv_cross_vec<T: RealField>(v: &TVec3<T>, q: &Qua<T>) -> TVec3<T> {
+pub fn quat_inv_cross_vec<T: RealNumber>(v: &TVec3<T>, q: &Qua<T>) -> TVec3<T> {
     UnitQuaternion::new_unchecked(*q).inverse() * v
 }
 
 /// The quaternion `w` component.
-pub fn quat_extract_real_component<T: RealField>(q: &Qua<T>) -> T {
+pub fn quat_extract_real_component<T: RealNumber>(q: &Qua<T>) -> T {
     q.w
 }
 
 /// Normalized linear interpolation between two quaternions.
-pub fn quat_fast_mix<T: RealField>(x: &Qua<T>, y: &Qua<T>, a: T) -> Qua<T> {
+pub fn quat_fast_mix<T: RealNumber>(x: &Qua<T>, y: &Qua<T>, a: T) -> Qua<T> {
     Unit::new_unchecked(*x)
         .nlerp(&Unit::new_unchecked(*y), a)
         .into_inner()
 }
 
-//pub fn quat_intermediate<T: RealField>(prev: &Qua<T>, curr: &Qua<T>, next: &Qua<T>) -> Qua<T> {
+//pub fn quat_intermediate<T: RealNumber>(prev: &Qua<T>, curr: &Qua<T>, next: &Qua<T>) -> Qua<T> {
 //    unimplemented!()
 //}
 
 /// The squared magnitude of a quaternion `q`.
-pub fn quat_length2<T: RealField>(q: &Qua<T>) -> T {
+pub fn quat_length2<T: RealNumber>(q: &Qua<T>) -> T {
     q.norm_squared()
 }
 
 /// The squared magnitude of a quaternion `q`.
-pub fn quat_magnitude2<T: RealField>(q: &Qua<T>) -> T {
+pub fn quat_magnitude2<T: RealNumber>(q: &Qua<T>) -> T {
     q.norm_squared()
 }
 
 /// The quaternion representing the identity rotation.
-pub fn quat_identity<T: RealField>() -> Qua<T> {
+pub fn quat_identity<T: RealNumber>() -> Qua<T> {
     UnitQuaternion::identity().into_inner()
 }
 
 /// Rotates a vector by a quaternion assumed to be normalized.
-pub fn quat_rotate_vec3<T: RealField>(q: &Qua<T>, v: &TVec3<T>) -> TVec3<T> {
+pub fn quat_rotate_vec3<T: RealNumber>(q: &Qua<T>, v: &TVec3<T>) -> TVec3<T> {
     UnitQuaternion::new_unchecked(*q) * v
 }
 
 /// Rotates a vector in homogeneous coordinates by a quaternion assumed to be normalized.
-pub fn quat_rotate_vec<T: RealField>(q: &Qua<T>, v: &TVec4<T>) -> TVec4<T> {
+pub fn quat_rotate_vec<T: RealNumber>(q: &Qua<T>, v: &TVec4<T>) -> TVec4<T> {
     let rotated = Unit::new_unchecked(*q) * v.fixed_rows::<3>(0);
     TVec4::new(rotated.x, rotated.y, rotated.z, v.w)
 }
 
 /// The rotation required to align `orig` to `dest`.
-pub fn quat_rotation<T: RealField>(orig: &TVec3<T>, dest: &TVec3<T>) -> Qua<T> {
+pub fn quat_rotation<T: RealNumber>(orig: &TVec3<T>, dest: &TVec3<T>) -> Qua<T> {
     UnitQuaternion::rotation_between(orig, dest)
         .unwrap_or_else(UnitQuaternion::identity)
         .into_inner()
 }
 
 /// The spherical linear interpolation between two quaternions.
-pub fn quat_short_mix<T: RealField>(x: &Qua<T>, y: &Qua<T>, a: T) -> Qua<T> {
+pub fn quat_short_mix<T: RealNumber>(x: &Qua<T>, y: &Qua<T>, a: T) -> Qua<T> {
     Unit::new_normalize(*x)
         .slerp(&Unit::new_normalize(*y), a)
         .into_inner()
 }
 
-//pub fn quat_squad<T: RealField>(q1: &Qua<T>, q2: &Qua<T>, s1: &Qua<T>, s2: &Qua<T>, h: T) -> Qua<T> {
+//pub fn quat_squad<T: RealNumber>(q1: &Qua<T>, q2: &Qua<T>, s1: &Qua<T>, s2: &Qua<T>, h: T) -> Qua<T> {
 //    unimplemented!()
 //}
 
 /// Converts a quaternion to a rotation matrix.
-pub fn quat_to_mat3<T: RealField>(x: &Qua<T>) -> TMat3<T> {
+pub fn quat_to_mat3<T: RealNumber>(x: &Qua<T>) -> TMat3<T> {
     UnitQuaternion::new_unchecked(*x)
         .to_rotation_matrix()
         .into_inner()
 }
 
 /// Converts a quaternion to a rotation matrix in homogenous coordinates.
-pub fn quat_to_mat4<T: RealField>(x: &Qua<T>) -> TMat4<T> {
+pub fn quat_to_mat4<T: RealNumber>(x: &Qua<T>) -> TMat4<T> {
     UnitQuaternion::new_unchecked(*x).to_homogeneous()
 }
 
 /// Converts a rotation matrix to a quaternion.
-pub fn mat3_to_quat<T: RealField>(x: &TMat3<T>) -> Qua<T> {
+pub fn mat3_to_quat<T: RealNumber>(x: &TMat3<T>) -> Qua<T> {
     let r = Rotation3::from_matrix_unchecked(*x);
     UnitQuaternion::from_rotation_matrix(&r).into_inner()
 }
 
 /// Converts a rotation matrix in homogeneous coordinates to a quaternion.
-pub fn to_quat<T: RealField>(x: &TMat4<T>) -> Qua<T> {
+pub fn to_quat<T: RealNumber>(x: &TMat4<T>) -> Qua<T> {
     let rot = x.fixed_slice::<3, 3>(0, 0).into_owned();
     mat3_to_quat(&rot)
 }

nalgebra-glm/src/gtx/rotate_normalized_axis.rs

@@ -1,6 +1,7 @@
-use na::{RealField, Rotation3, Unit, UnitQuaternion};
+use na::{Rotation3, Unit, UnitQuaternion};
 
 use crate::aliases::{Qua, TMat4, TVec3};
+use crate::RealNumber;
 
 /// Builds a rotation 4 * 4 matrix created from a normalized axis and an angle.
 ///
@@ -9,7 +10,7 @@ use crate::aliases::{Qua, TMat4, TVec3};
 /// * `m` - Input matrix multiplied by this rotation matrix.
 /// * `angle` - Rotation angle expressed in radians.
 /// * `axis` - Rotation axis, must be normalized.
-pub fn rotate_normalized_axis<T: RealField>(m: &TMat4<T>, angle: T, axis: &TVec3<T>) -> TMat4<T> {
+pub fn rotate_normalized_axis<T: RealNumber>(m: &TMat4<T>, angle: T, axis: &TVec3<T>) -> TMat4<T> {
     m * Rotation3::from_axis_angle(&Unit::new_unchecked(*axis), angle).to_homogeneous()
 }
 
@@ -20,6 +21,6 @@ pub fn rotate_normalized_axis<T: RealField>(m: &TMat4<T>, angle: T, axis: &TVec3
 /// * `q` - Source orientation.
 /// * `angle` - Angle expressed in radians.
 /// * `axis` - Normalized axis of the rotation, must be normalized.
-pub fn quat_rotate_normalized_axis<T: RealField>(q: &Qua<T>, angle: T, axis: &TVec3<T>) -> Qua<T> {
+pub fn quat_rotate_normalized_axis<T: RealNumber>(q: &Qua<T>, angle: T, axis: &TVec3<T>) -> Qua<T> {
     q * UnitQuaternion::from_axis_angle(&Unit::new_unchecked(*axis), angle).into_inner()
 }

nalgebra-glm/src/gtx/rotate_vector.rs

@@ -1,9 +1,10 @@
-use na::{RealField, Rotation3, Unit, UnitComplex};
+use na::{Rotation3, Unit, UnitComplex};
 
 use crate::aliases::{TMat4, TVec2, TVec3, TVec4};
+use crate::RealNumber;
 
 /// Build the rotation matrix needed to align `normal` and `up`.
-pub fn orientation<T: RealField>(normal: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
+pub fn orientation<T: RealNumber>(normal: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
     if let Some(r) = Rotation3::rotation_between(normal, up) {
         r.to_homogeneous()
     } else {
@@ -12,52 +13,52 @@ pub fn orientation<T: RealField>(normal: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
 }
 
 /// Rotate a two dimensional vector.
-pub fn rotate_vec2<T: RealField>(v: &TVec2<T>, angle: T) -> TVec2<T> {
+pub fn rotate_vec2<T: RealNumber>(v: &TVec2<T>, angle: T) -> TVec2<T> {
     UnitComplex::new(angle) * v
 }
 
 /// Rotate a three dimensional vector around an axis.
-pub fn rotate_vec3<T: RealField>(v: &TVec3<T>, angle: T, normal: &TVec3<T>) -> TVec3<T> {
+pub fn rotate_vec3<T: RealNumber>(v: &TVec3<T>, angle: T, normal: &TVec3<T>) -> TVec3<T> {
     Rotation3::from_axis_angle(&Unit::new_normalize(*normal), angle) * v
 }
 
 /// Rotate a thee dimensional vector in homogeneous coordinates around an axis.
-pub fn rotate_vec4<T: RealField>(v: &TVec4<T>, angle: T, normal: &TVec3<T>) -> TVec4<T> {
+pub fn rotate_vec4<T: RealNumber>(v: &TVec4<T>, angle: T, normal: &TVec3<T>) -> TVec4<T> {
     Rotation3::from_axis_angle(&Unit::new_normalize(*normal), angle).to_homogeneous() * v
 }
 
 /// Rotate a three dimensional vector around the `X` axis.
-pub fn rotate_x_vec3<T: RealField>(v: &TVec3<T>, angle: T) -> TVec3<T> {
+pub fn rotate_x_vec3<T: RealNumber>(v: &TVec3<T>, angle: T) -> TVec3<T> {
     Rotation3::from_axis_angle(&TVec3::x_axis(), angle) * v
 }
 
 /// Rotate a three dimensional vector in homogeneous coordinates around the `X` axis.
-pub fn rotate_x_vec4<T: RealField>(v: &TVec4<T>, angle: T) -> TVec4<T> {
+pub fn rotate_x_vec4<T: RealNumber>(v: &TVec4<T>, angle: T) -> TVec4<T> {
     Rotation3::from_axis_angle(&TVec3::x_axis(), angle).to_homogeneous() * v
 }
 
 /// Rotate a three dimensional vector around the `Y` axis.
-pub fn rotate_y_vec3<T: RealField>(v: &TVec3<T>, angle: T) -> TVec3<T> {
+pub fn rotate_y_vec3<T: RealNumber>(v: &TVec3<T>, angle: T) -> TVec3<T> {
     Rotation3::from_axis_angle(&TVec3::y_axis(), angle) * v
 }
 
 /// Rotate a three dimensional vector in homogeneous coordinates around the `Y` axis.
-pub fn rotate_y_vec4<T: RealField>(v: &TVec4<T>, angle: T) -> TVec4<T> {
+pub fn rotate_y_vec4<T: RealNumber>(v: &TVec4<T>, angle: T) -> TVec4<T> {
     Rotation3::from_axis_angle(&TVec3::y_axis(), angle).to_homogeneous() * v
 }
 
 /// Rotate a three dimensional vector around the `Z` axis.
-pub fn rotate_z_vec3<T: RealField>(v: &TVec3<T>, angle: T) -> TVec3<T> {
+pub fn rotate_z_vec3<T: RealNumber>(v: &TVec3<T>, angle: T) -> TVec3<T> {
     Rotation3::from_axis_angle(&TVec3::z_axis(), angle) * v
 }
 
 /// Rotate a three dimensional vector in homogeneous coordinates around the `Z` axis.
-pub fn rotate_z_vec4<T: RealField>(v: &TVec4<T>, angle: T) -> TVec4<T> {
+pub fn rotate_z_vec4<T: RealNumber>(v: &TVec4<T>, angle: T) -> TVec4<T> {
     Rotation3::from_axis_angle(&TVec3::z_axis(), angle).to_homogeneous() * v
 }
 
 /// Computes a spherical linear interpolation between the vectors `x` and `y` assumed to be normalized.
-pub fn slerp<T: RealField>(x: &TVec3<T>, y: &TVec3<T>, a: T) -> TVec3<T> {
+pub fn slerp<T: RealNumber>(x: &TVec3<T>, y: &TVec3<T>, a: T) -> TVec3<T> {
     Unit::new_unchecked(*x)
         .slerp(&Unit::new_unchecked(*y), a)
         .into_inner()

nalgebra-glm/src/gtx/transform.rs

@@ -1,7 +1,7 @@
-use na::{RealField, Rotation2, Rotation3, Unit};
+use na::{Rotation2, Rotation3, Unit};
 
 use crate::aliases::{TMat3, TMat4, TVec2, TVec3};
-use crate::traits::Number;
+use crate::traits::{Number, RealNumber};
 
 /// A rotation 4 * 4 matrix created from an axis of 3 scalars and an angle expressed in radians.
 ///
@@ -12,7 +12,7 @@ use crate::traits::Number;
 /// * [`rotation2d`](fn.rotation2d.html)
 /// * [`scaling2d`](fn.scaling2d.html)
 /// * [`translation2d`](fn.translation2d.html)
-pub fn rotation<T: RealField>(angle: T, v: &TVec3<T>) -> TMat4<T> {
+pub fn rotation<T: RealNumber>(angle: T, v: &TVec3<T>) -> TMat4<T> {
     Rotation3::from_axis_angle(&Unit::new_normalize(*v), angle).to_homogeneous()
 }
 
@@ -51,7 +51,7 @@ pub fn translation<T: Number>(v: &TVec3<T>) -> TMat4<T> {
 /// * [`translation`](fn.translation.html)
 /// * [`scaling2d`](fn.scaling2d.html)
 /// * [`translation2d`](fn.translation2d.html)
-pub fn rotation2d<T: RealField>(angle: T) -> TMat3<T> {
+pub fn rotation2d<T: RealNumber>(angle: T) -> TMat3<T> {
     Rotation2::new(angle).to_homogeneous()
 }
 

nalgebra-glm/src/gtx/transform2.rs

@@ -1,5 +1,6 @@
 use crate::aliases::{TMat3, TMat4, TVec2, TVec3};
 use crate::traits::Number;
+use crate::RealNumber;
 
 /// Build planar projection matrix along normal axis and right-multiply it to `m`.
 pub fn proj2d<T: Number>(m: &TMat3<T>, normal: &TVec2<T>) -> TMat3<T> {
@@ -26,24 +27,24 @@ pub fn proj<T: Number>(m: &TMat4<T>, normal: &TVec3<T>) -> TMat4<T> {
 }
 
 /// Builds a reflection matrix and right-multiply it to `m`.
-pub fn reflect2d<T: Number>(m: &TMat3<T>, normal: &TVec2<T>) -> TMat3<T> {
+pub fn reflect2d<T: RealNumber>(m: &TMat3<T>, normal: &TVec2<T>) -> TMat3<T> {
     let mut res = TMat3::identity();
 
     {
         let mut part = res.fixed_slice_mut::<2, 2>(0, 0);
-        part -= (normal * T::from_f64(2.0).unwrap()) * normal.transpose();
+        part -= (normal * T::from_subset(&2.0)) * normal.transpose();
     }
 
     m * res
 }
 
 /// Builds a reflection matrix, and right-multiply it to `m`.
-pub fn reflect<T: Number>(m: &TMat4<T>, normal: &TVec3<T>) -> TMat4<T> {
+pub fn reflect<T: RealNumber>(m: &TMat4<T>, normal: &TVec3<T>) -> TMat4<T> {
     let mut res = TMat4::identity();
 
     {
         let mut part = res.fixed_slice_mut::<3, 3>(0, 0);
-        part -= (normal * T::from_f64(2.0).unwrap()) * normal.transpose();
+        part -= (normal * T::from_subset(&2.0)) * normal.transpose();
     }
 
     m * res

nalgebra-glm/src/gtx/transform2d.rs

@@ -1,7 +1,7 @@
-use na::{RealField, UnitComplex};
+use na::UnitComplex;
 
 use crate::aliases::{TMat3, TVec2};
-use crate::traits::Number;
+use crate::traits::{Number, RealNumber};
 
 /// Builds a 2D rotation matrix from an angle and right-multiply it to `m`.
 ///
@@ -12,7 +12,7 @@ use crate::traits::Number;
 /// * [`scaling2d`](fn.scaling2d.html)
 /// * [`translate2d`](fn.translate2d.html)
 /// * [`translation2d`](fn.translation2d.html)
-pub fn rotate2d<T: RealField>(m: &TMat3<T>, angle: T) -> TMat3<T> {
+pub fn rotate2d<T: RealNumber>(m: &TMat3<T>, angle: T) -> TMat3<T> {
     m * UnitComplex::new(angle).to_homogeneous()
 }
 

nalgebra-glm/src/gtx/vector_angle.rs

@@ -1,16 +1,16 @@
-use na::RealField;
+use crate::RealNumber;
 
 use crate::aliases::TVec;
 
 /// The angle between two vectors.
-pub fn angle<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
+pub fn angle<T: RealNumber, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
     x.angle(y)
 }
 
-//pub fn oriented_angle<T: RealField>(x: &TVec2<T>, y: &TVec2<T>) -> T {
+//pub fn oriented_angle<T: RealNumber>(x: &TVec2<T>, y: &TVec2<T>) -> T {
 //    unimplemented!()
 //}
 //
-//pub fn oriented_angle_ref<T: RealField>(x: &TVec3<T>, y: &TVec3<T>, refv: &TVec3<T>) -> T {
+//pub fn oriented_angle_ref<T: RealNumber>(x: &TVec3<T>, y: &TVec3<T>, refv: &TVec3<T>) -> T {
 //    unimplemented!()
 //}

nalgebra-glm/src/gtx/vector_query.rs

@@ -1,4 +1,4 @@
-use na::RealField;
+use crate::RealNumber;
 
 use crate::aliases::{TVec, TVec2, TVec3};
 use crate::traits::Number;
@@ -40,7 +40,7 @@ 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: RealField, const D: usize>(v: &TVec<T, D>, epsilon: T) -> bool {
+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)
 }
 

nalgebra-glm/src/integer.rs

@@ -1,4 +1,4 @@
-use na::{DefaultAllocator, RealField, Scalar, U3};
+use na::{DefaultAllocator, RealNumber, Scalar, U3};
 
 use crate::aliases::TVec;
 use crate::traits::{Alloc, Dimension, Number};

nalgebra-glm/src/lib.rs

@@ -110,6 +110,16 @@
    and keep in mind it is possible to convert, e.g., an `Isometry3` to a `Mat4` and vice-versa (see the [conversions section](#conversions)).
 */
 
+#![deny(
+    nonstandard_style,
+    unused,
+    missing_docs,
+    rust_2018_idioms,
+    rust_2018_compatibility,
+    future_incompatible,
+    missing_copy_implementations,
+    missing_debug_implementations
+)]
 #![doc(html_favicon_url = "https://nalgebra.org/img/favicon.ico")]
 #![cfg_attr(not(feature = "std"), no_std)]
 
@@ -119,7 +129,7 @@ extern crate approx;
 extern crate nalgebra as na;
 
 pub use crate::aliases::*;
-pub use crate::traits::Number;
+pub use crate::traits::{Number, RealNumber};
 pub use common::{
     abs, ceil, clamp, clamp_scalar, clamp_vec, float_bits_to_int, float_bits_to_int_vec,
     float_bits_to_uint, float_bits_to_uint_vec, floor, fract, int_bits_to_float,
@@ -191,7 +201,7 @@ pub use gtx::{
 pub use na::{
     convert, convert_ref, convert_ref_unchecked, convert_unchecked, try_convert, try_convert_ref,
 };
-pub use na::{DefaultAllocator, RealField, Scalar, U1, U2, U3, U4};
+pub use na::{DefaultAllocator, Scalar, U1, U2, U3, U4};
 
 mod aliases;
 mod common;

nalgebra-glm/src/matrix.rs

@@ -1,10 +1,10 @@
-use na::{Const, DimMin, RealField, Scalar};
+use na::{Const, DimMin, Scalar};
 
 use crate::aliases::{TMat, TVec};
-use crate::traits::Number;
+use crate::traits::{Number, RealNumber};
 
 /// The determinant of the matrix `m`.
-pub fn determinant<T: RealField, const D: usize>(m: &TMat<T, D, D>) -> T
+pub fn determinant<T: RealNumber, const D: usize>(m: &TMat<T, D, D>) -> T
 where
     Const<D>: DimMin<Const<D>, Output = Const<D>>,
 {
@@ -12,7 +12,7 @@ where
 }
 
 /// The inverse of the matrix `m`.
-pub fn inverse<T: RealField, const D: usize>(m: &TMat<T, D, D>) -> TMat<T, D, D> {
+pub fn inverse<T: RealNumber, const D: usize>(m: &TMat<T, D, D>) -> TMat<T, D, D> {
     m.clone()
         .try_inverse()
         .unwrap_or_else(TMat::<T, D, D>::zeros)

nalgebra-glm/src/traits.rs

@@ -1,8 +1,8 @@
 use approx::AbsDiffEq;
-use num::{Bounded, FromPrimitive, Signed};
+use num::{Bounded, Signed};
 
 use na::Scalar;
-use simba::scalar::{ClosedAdd, ClosedMul, ClosedSub};
+use simba::scalar::{ClosedAdd, ClosedMul, ClosedSub, RealField};
 use std::cmp::PartialOrd;
 
 /// A number that can either be an integer or a float.
@@ -15,7 +15,6 @@ pub trait Number:
     + ClosedMul
     + AbsDiffEq<Epsilon = Self>
     + Signed
-    + FromPrimitive
     + Bounded
 {
 }
@@ -29,8 +28,12 @@ impl<
             + ClosedMul
             + AbsDiffEq<Epsilon = Self>
             + Signed
-            + FromPrimitive
             + Bounded,
     > Number for T
 {
 }
+
+/// A number that can be any float type.
+pub trait RealNumber: Number + RealField {}
+
+impl<T: Number + RealField> RealNumber for T {}

nalgebra-glm/src/trigonometric.rs

@@ -1,78 +1,79 @@
-use na::{self, RealField};
+use na;
 
 use crate::aliases::TVec;
+use crate::RealNumber;
 
 /// Component-wise arc-cosinus.
-pub fn acos<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
+pub fn acos<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|e| e.acos())
 }
 
 /// Component-wise hyperbolic arc-cosinus.
-pub fn acosh<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
+pub fn acosh<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|e| e.acosh())
 }
 
 /// Component-wise arc-sinus.
-pub fn asin<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
+pub fn asin<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|e| e.asin())
 }
 
 /// Component-wise hyperbolic arc-sinus.
-pub fn asinh<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
+pub fn asinh<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|e| e.asinh())
 }
 
 /// Component-wise arc-tangent of `y / x`.
-pub fn atan2<T: RealField, const D: usize>(y: &TVec<T, D>, x: &TVec<T, D>) -> TVec<T, D> {
+pub fn atan2<T: RealNumber, const D: usize>(y: &TVec<T, D>, x: &TVec<T, D>) -> TVec<T, D> {
     y.zip_map(x, |y, x| y.atan2(x))
 }
 
 /// Component-wise arc-tangent.
-pub fn atan<T: RealField, const D: usize>(y_over_x: &TVec<T, D>) -> TVec<T, D> {
+pub fn atan<T: RealNumber, const D: usize>(y_over_x: &TVec<T, D>) -> TVec<T, D> {
     y_over_x.map(|e| e.atan())
 }
 
 /// Component-wise hyperbolic arc-tangent.
-pub fn atanh<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
+pub fn atanh<T: RealNumber, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|e| e.atanh())
 }
 
 /// Component-wise cosinus.
-pub fn cos<T: RealField, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
+pub fn cos<T: RealNumber, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
     angle.map(|e| e.cos())
 }
 
 /// Component-wise hyperbolic cosinus.
-pub fn cosh<T: RealField, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
+pub fn cosh<T: RealNumber, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
     angle.map(|e| e.cosh())
 }
 
 /// Component-wise conversion from radians to degrees.
-pub fn degrees<T: RealField, const D: usize>(radians: &TVec<T, D>) -> TVec<T, D> {
+pub fn degrees<T: RealNumber, const D: usize>(radians: &TVec<T, D>) -> TVec<T, D> {
     radians.map(|e| e * na::convert(180.0) / T::pi())
 }
 
 /// Component-wise conversion fro degrees to radians.
-pub fn radians<T: RealField, const D: usize>(degrees: &TVec<T, D>) -> TVec<T, D> {
+pub fn radians<T: RealNumber, const D: usize>(degrees: &TVec<T, D>) -> TVec<T, D> {
     degrees.map(|e| e * T::pi() / na::convert(180.0))
 }
 
 /// Component-wise sinus.
-pub fn sin<T: RealField, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
+pub fn sin<T: RealNumber, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
     angle.map(|e| e.sin())
 }
 
 /// Component-wise hyperbolic sinus.
-pub fn sinh<T: RealField, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
+pub fn sinh<T: RealNumber, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
     angle.map(|e| e.sinh())
 }
 
 /// Component-wise tangent.
-pub fn tan<T: RealField, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
+pub fn tan<T: RealNumber, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
     angle.map(|e| e.tan())
 }
 
 /// Component-wise hyperbolic tangent.
-pub fn tanh<T: RealField, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
+pub fn tanh<T: RealNumber, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
     angle.map(|e| e.tanh())
 }

nalgebra-lapack/Cargo.toml

@@ -29,7 +29,7 @@ accelerate = ["lapack-src/accelerate"]
 intel-mkl  = ["lapack-src/intel-mkl"]
 
 [dependencies]
-nalgebra      = { version = "0.28", path = ".." }
+nalgebra      = { version = "0.29", path = ".." }
 num-traits    = "0.2"
 num-complex   = { version = "0.4", default-features = false }
 simba         = "0.5"
@@ -39,7 +39,7 @@ lapack-src    = { version = "0.8", default-features = false }
 # clippy = "*"
 
 [dev-dependencies]
-nalgebra   = { version = "0.28", features = [ "arbitrary", "rand" ], path = ".." }
+nalgebra   = { version = "0.29", features = [ "arbitrary", "rand" ], path = ".." }
 proptest   = { version = "1", default-features = false, features = ["std"] }
 quickcheck = "1"
 approx     = "0.5"

nalgebra-lapack/src/eigen.rs

@@ -9,7 +9,6 @@ use simba::scalar::RealField;
 use crate::ComplexHelper;
 use na::allocator::Allocator;
 use na::dimension::{Const, Dim};
-use na::storage::Storage;
 use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
@@ -73,14 +72,15 @@ where
         let ljob = if left_eigenvectors { b'V' } else { b'T' };
         let rjob = if eigenvectors { b'V' } else { b'T' };
 
-        let (nrows, ncols) = m.data.shape();
+        let (nrows, ncols) = m.shape_generic();
         let n = nrows.value();
 
         let lda = n as i32;
 
-        let mut wr = unsafe { Matrix::new_uninitialized_generic(nrows, Const::<1>).assume_init() };
+        // TODO: avoid the initialization?
+        let mut wr = Matrix::zeros_generic(nrows, Const::<1>);
         // TODO: Tap into the workspace.
-        let mut wi = unsafe { Matrix::new_uninitialized_generic(nrows, Const::<1>).assume_init() };
+        let mut wi = Matrix::zeros_generic(nrows, Const::<1>);
 
         let mut info = 0;
         let mut placeholder1 = [T::zero()];
@@ -103,14 +103,13 @@ where
 
         lapack_check!(info);
 
-        let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
+        let mut work = vec![T::zero(); lwork as usize];
 
         match (left_eigenvectors, eigenvectors) {
             (true, true) => {
-                let mut vl =
-                    unsafe { Matrix::new_uninitialized_generic(nrows, ncols).assume_init() };
-                let mut vr =
-                    unsafe { Matrix::new_uninitialized_generic(nrows, ncols).assume_init() };
+                // TODO: avoid the initializations?
+                let mut vl = Matrix::zeros_generic(nrows, ncols);
+                let mut vr = Matrix::zeros_generic(nrows, ncols);
 
                 T::xgeev(
                     ljob,
@@ -139,8 +138,8 @@ where
                 }
             }
             (true, false) => {
-                let mut vl =
-                    unsafe { Matrix::new_uninitialized_generic(nrows, ncols).assume_init() };
+                // TODO: avoid the initialization?
+                let mut vl = Matrix::zeros_generic(nrows, ncols);
 
                 T::xgeev(
                     ljob,
@@ -169,8 +168,8 @@ where
                 }
             }
             (false, true) => {
-                let mut vr =
-                    unsafe { Matrix::new_uninitialized_generic(nrows, ncols).assume_init() };
+                // TODO: avoid the initialization?
+                let mut vr = Matrix::zeros_generic(nrows, ncols);
 
                 T::xgeev(
                     ljob,
@@ -242,13 +241,14 @@ where
             "Unable to compute the eigenvalue decomposition of a non-square matrix."
         );
 
-        let nrows = m.data.shape().0;
+        let nrows = m.shape_generic().0;
         let n = nrows.value();
 
         let lda = n as i32;
 
-        let mut wr = unsafe { Matrix::new_uninitialized_generic(nrows, Const::<1>).assume_init() };
-        let mut wi = unsafe { Matrix::new_uninitialized_generic(nrows, Const::<1>).assume_init() };
+        // TODO: avoid the initialization?
+        let mut wr = Matrix::zeros_generic(nrows, Const::<1>);
+        let mut wi = Matrix::zeros_generic(nrows, Const::<1>);
 
         let mut info = 0;
         let mut placeholder1 = [T::zero()];
@@ -271,7 +271,7 @@ where
 
         lapack_panic!(info);
 
-        let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
+        let mut work = vec![T::zero(); lwork as usize];
 
         T::xgeev(
             b'T',
@@ -291,7 +291,7 @@ where
         );
         lapack_panic!(info);
 
-        let mut res = unsafe { Matrix::new_uninitialized_generic(nrows, Const::<1>).assume_init() };
+        let mut res = Matrix::zeros_generic(nrows, Const::<1>);
 
         for i in 0..res.len() {
             res[i] = Complex::new(wr[i], wi[i]);

nalgebra-lapack/src/hessenberg.rs

@@ -4,7 +4,6 @@ use num_complex::Complex;
 use crate::ComplexHelper;
 use na::allocator::Allocator;
 use na::dimension::{Const, DimDiff, DimSub, U1};
-use na::storage::Storage;
 use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
@@ -48,7 +47,7 @@ where
 {
     /// Computes the hessenberg decomposition of the matrix `m`.
     pub fn new(mut m: OMatrix<T, D, D>) -> Self {
-        let nrows = m.data.shape().0;
+        let nrows = m.shape_generic().0;
         let n = nrows.value() as i32;
 
         assert!(
@@ -60,14 +59,12 @@ where
             "Unable to compute the hessenberg decomposition of an empty matrix."
         );
 
-        let mut tau = unsafe {
-            Matrix::new_uninitialized_generic(nrows.sub(Const::<1>), Const::<1>).assume_init()
-        };
+        let mut tau = Matrix::zeros_generic(nrows.sub(Const::<1>), Const::<1>);
 
         let mut info = 0;
         let lwork =
             T::xgehrd_work_size(n, 1, n, m.as_mut_slice(), n, tau.as_mut_slice(), &mut info);
-        let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
+        let mut work = vec![T::zero(); lwork as usize];
 
         lapack_panic!(info);
 
@@ -84,7 +81,7 @@ where
         );
         lapack_panic!(info);
 
-        Self { h: m, tau: tau }
+        Self { h: m, tau }
     }
 
     /// Computes the hessenberg matrix of this decomposition.

nalgebra-lapack/src/lib.rs

@@ -139,10 +139,3 @@ impl ComplexHelper for Complex<f64> {
         self.re
     }
 }
-
-unsafe fn uninitialized_vec<T: Copy>(n: usize) -> Vec<T> {
-    let mut res = Vec::new();
-    res.reserve_exact(n);
-    res.set_len(n);
-    res
-}

nalgebra-lapack/src/lu.rs

@@ -61,7 +61,7 @@ where
 {
     /// Computes the LU decomposition with partial (row) pivoting of `matrix`.
     pub fn new(mut m: OMatrix<T, R, C>) -> Self {
-        let (nrows, ncols) = m.data.shape();
+        let (nrows, ncols) = m.shape_generic();
         let min_nrows_ncols = nrows.min(ncols);
         let nrows = nrows.value() as i32;
         let ncols = ncols.value() as i32;
@@ -87,7 +87,7 @@ where
     #[inline]
     #[must_use]
     pub fn l(&self) -> OMatrix<T, R, DimMinimum<R, C>> {
-        let (nrows, ncols) = self.lu.data.shape();
+        let (nrows, ncols) = self.lu.shape_generic();
         let mut res = self.lu.columns_generic(0, nrows.min(ncols)).into_owned();
 
         res.fill_upper_triangle(Zero::zero(), 1);
@@ -100,7 +100,7 @@ where
     #[inline]
     #[must_use]
     pub fn u(&self) -> OMatrix<T, DimMinimum<R, C>, C> {
-        let (nrows, ncols) = self.lu.data.shape();
+        let (nrows, ncols) = self.lu.shape_generic();
         let mut res = self.lu.rows_generic(0, nrows.min(ncols)).into_owned();
 
         res.fill_lower_triangle(Zero::zero(), 1);
@@ -115,7 +115,7 @@ where
     #[inline]
     #[must_use]
     pub fn p(&self) -> OMatrix<T, R, R> {
-        let (dim, _) = self.lu.data.shape();
+        let (dim, _) = self.lu.shape_generic();
         let mut id = Matrix::identity_generic(dim, dim);
         self.permute(&mut id);
 
@@ -290,7 +290,7 @@ where
         );
         lapack_check!(info);
 
-        let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
+        let mut work = vec![T::zero(); lwork as usize];
 
         T::xgetri(
             dim,

nalgebra-lapack/src/qr.rs

@@ -7,7 +7,6 @@ use num_complex::Complex;
 use crate::ComplexHelper;
 use na::allocator::Allocator;
 use na::dimension::{Const, Dim, DimMin, DimMinimum};
-use na::storage::Storage;
 use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
@@ -54,15 +53,13 @@ where
 {
     /// Computes the QR decomposition of the matrix `m`.
     pub fn new(mut m: OMatrix<T, R, C>) -> Self {
-        let (nrows, ncols) = m.data.shape();
+        let (nrows, ncols) = m.shape_generic();
 
         let mut info = 0;
-        let mut tau = unsafe {
-            Matrix::new_uninitialized_generic(nrows.min(ncols), Const::<1>).assume_init()
-        };
+        let mut tau = Matrix::zeros_generic(nrows.min(ncols), Const::<1>);
 
         if nrows.value() == 0 || ncols.value() == 0 {
-            return Self { qr: m, tau: tau };
+            return Self { qr: m, tau };
         }
 
         let lwork = T::xgeqrf_work_size(
@@ -74,7 +71,7 @@ where
             &mut info,
         );
 
-        let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
+        let mut work = vec![T::zero(); lwork as usize];
 
         T::xgeqrf(
             nrows.value() as i32,
@@ -87,14 +84,14 @@ where
             &mut info,
         );
 
-        Self { qr: m, tau: tau }
+        Self { qr: m, tau }
     }
 
     /// Retrieves the upper trapezoidal submatrix `R` of this decomposition.
     #[inline]
     #[must_use]
     pub fn r(&self) -> OMatrix<T, DimMinimum<R, C>, C> {
-        let (nrows, ncols) = self.qr.data.shape();
+        let (nrows, ncols) = self.qr.shape_generic();
         self.qr.rows_generic(0, nrows.min(ncols)).upper_triangle()
     }
 }
@@ -120,7 +117,7 @@ where
     #[inline]
     #[must_use]
     pub fn q(&self) -> OMatrix<T, R, DimMinimum<R, C>> {
-        let (nrows, ncols) = self.qr.data.shape();
+        let (nrows, ncols) = self.qr.shape_generic();
         let min_nrows_ncols = nrows.min(ncols);
 
         if min_nrows_ncols.value() == 0 {

nalgebra-lapack/src/schur.rs

@@ -9,7 +9,6 @@ use simba::scalar::RealField;
 use crate::ComplexHelper;
 use na::allocator::Allocator;
 use na::dimension::{Const, Dim};
-use na::storage::Storage;
 use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
@@ -71,16 +70,16 @@ where
             "Unable to compute the eigenvalue decomposition of a non-square matrix."
         );
 
-        let (nrows, ncols) = m.data.shape();
+        let (nrows, ncols) = m.shape_generic();
         let n = nrows.value();
 
         let lda = n as i32;
 
         let mut info = 0;
 
-        let mut wr = unsafe { Matrix::new_uninitialized_generic(nrows, Const::<1>).assume_init() };
-        let mut wi = unsafe { Matrix::new_uninitialized_generic(nrows, Const::<1>).assume_init() };
-        let mut q = unsafe { Matrix::new_uninitialized_generic(nrows, ncols).assume_init() };
+        let mut wr = Matrix::zeros_generic(nrows, Const::<1>);
+        let mut wi = Matrix::zeros_generic(nrows, Const::<1>);
+        let mut q = Matrix::zeros_generic(nrows, ncols);
         // Placeholders:
         let mut bwork = [0i32];
         let mut unused = 0;
@@ -101,7 +100,7 @@ where
         );
         lapack_check!(info);
 
-        let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
+        let mut work = vec![T::zero(); lwork as usize];
 
         T::xgees(
             b'V',
@@ -125,7 +124,7 @@ where
             re: wr,
             im: wi,
             t: m,
-            q: q,
+            q,
         })
     }
 
@@ -153,9 +152,7 @@ where
     where
         DefaultAllocator: Allocator<Complex<T>, D>,
     {
-        let mut out = unsafe {
-            OVector::new_uninitialized_generic(self.t.data.shape().0, Const::<1>).assume_init()
-        };
+        let mut out = Matrix::zeros_generic(self.t.shape_generic().0, Const::<1>);
 
         for i in 0..out.len() {
             out[i] = Complex::new(self.re[i], self.im[i])

nalgebra-lapack/src/svd.rs

@@ -6,7 +6,6 @@ use std::cmp;
 
 use na::allocator::Allocator;
 use na::dimension::{Const, Dim, DimMin, DimMinimum, U1};
-use na::storage::Storage;
 use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
@@ -89,7 +88,7 @@ macro_rules! svd_impl(
                                         Allocator<$t, DimMinimum<R, C>> {
 
             fn compute(mut m: OMatrix<$t, R, C>) -> Option<SVD<$t, R, C>> {
-                let (nrows, ncols) = m.data.shape();
+                let (nrows, ncols) = m.shape_generic();
 
                 if nrows.value() == 0 || ncols.value() == 0 {
                     return None;
@@ -99,9 +98,9 @@ macro_rules! svd_impl(
 
                 let lda = nrows.value() as i32;
 
-                let mut u  = unsafe { Matrix::new_uninitialized_generic(nrows, nrows).assume_init() };
-                let mut s  = unsafe { Matrix::new_uninitialized_generic(nrows.min(ncols), Const::<1>).assume_init() };
-                let mut vt = unsafe { Matrix::new_uninitialized_generic(ncols, ncols).assume_init() };
+                let mut u  = Matrix::zeros_generic(nrows, nrows);
+                let mut s  = Matrix::zeros_generic(nrows.min(ncols), Const::<1>);
+                let mut vt = Matrix::zeros_generic(ncols, ncols);
 
                 let ldu  = nrows.value();
                 let ldvt = ncols.value();
@@ -109,7 +108,7 @@ macro_rules! svd_impl(
                 let mut work  = [ 0.0 ];
                 let mut lwork = -1 as i32;
                 let mut info  = 0;
-                let mut iwork = unsafe { crate::uninitialized_vec(8 * cmp::min(nrows.value(), ncols.value())) };
+                let mut iwork = vec![0; 8 * cmp::min(nrows.value(), ncols.value())];
 
                 unsafe {
                     $lapack_func(job, nrows.value() as i32, ncols.value() as i32, m.as_mut_slice(),
@@ -119,7 +118,7 @@ macro_rules! svd_impl(
                 lapack_check!(info);
 
                 lwork = work[0] as i32;
-                let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
+                let mut work = vec![0.0; lwork as usize];
 
                 unsafe {
                 $lapack_func(job, nrows.value() as i32, ncols.value() as i32, m.as_mut_slice(),
@@ -151,8 +150,8 @@ macro_rules! svd_impl(
             /// been manually changed by the user.
             #[inline]
             pub fn recompose(self) -> OMatrix<$t, R, C> {
-                let nrows           = self.u.data.shape().0;
-                let ncols           = self.vt.data.shape().1;
+                let nrows           = self.u.shape_generic().0;
+                let ncols           = self.vt.shape_generic().1;
                 let min_nrows_ncols = nrows.min(ncols);
 
                 let mut res: OMatrix<_, R, C> = Matrix::zeros_generic(nrows, ncols);
@@ -177,8 +176,8 @@ macro_rules! svd_impl(
             #[inline]
             #[must_use]
             pub fn pseudo_inverse(&self, epsilon: $t) -> OMatrix<$t, C, R> {
-                let nrows           = self.u.data.shape().0;
-                let ncols           = self.vt.data.shape().1;
+                let nrows           = self.u.shape_generic().0;
+                let ncols           = self.vt.shape_generic().1;
                 let min_nrows_ncols = nrows.min(ncols);
 
                 let mut res: OMatrix<_, C, R> = Matrix::zeros_generic(ncols, nrows);
@@ -241,7 +240,7 @@ macro_rules! svd_complex_impl(
                             Allocator<Complex<$t>, R, R>         +
                             Allocator<Complex<$t>, C, C>         +
                             Allocator<$t, DimMinimum<R, C>> {
-            let (nrows, ncols) = m.data.shape();
+            let (nrows, ncols) = m.shape_generic();
 
             if nrows.value() == 0 || ncols.value() == 0 {
                 return None;
@@ -254,9 +253,9 @@ macro_rules! svd_complex_impl(
             let min_nrows_ncols = nrows.min(ncols);
 
 
-            let mut u  = unsafe { Matrix::new_uninitialized_generic(nrows, nrows) };
-            let mut s  = unsafe { Matrix::new_uninitialized_generic(min_nrows_ncols, U1) };
-            let mut vt = unsafe { Matrix::new_uninitialized_generic(ncols, ncols) };
+            let mut u  = Matrix::zeros_generic(nrows, nrows);
+            let mut s  = Matrix::zeros_generic(min_nrows_ncols, U1);
+            let mut vt = Matrix::zeros_generic(ncols, ncols);
 
             let ldu  = nrows.value();
             let ldvt = ncols.value();

nalgebra-lapack/src/symmetric_eigen.rs

@@ -9,7 +9,6 @@ use simba::scalar::RealField;
 use crate::ComplexHelper;
 use na::allocator::Allocator;
 use na::dimension::{Const, Dim};
-use na::storage::Storage;
 use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
@@ -89,19 +88,18 @@ where
 
         let jobz = if eigenvectors { b'V' } else { b'T' };
 
-        let nrows = m.data.shape().0;
+        let nrows = m.shape_generic().0;
         let n = nrows.value();
 
         let lda = n as i32;
 
-        let mut values =
-            unsafe { Matrix::new_uninitialized_generic(nrows, Const::<1>).assume_init() };
+        let mut values = Matrix::zeros_generic(nrows, Const::<1>);
         let mut info = 0;
 
         let lwork = T::xsyev_work_size(jobz, b'L', n as i32, m.as_mut_slice(), lda, &mut info);
         lapack_check!(info);
 
-        let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
+        let mut work = vec![T::zero(); lwork as usize];
 
         T::xsyev(
             jobz,

nalgebra-macros/Cargo.toml

@@ -21,5 +21,5 @@ quote = "1.0"
 proc-macro2 = "1.0"
 
 [dev-dependencies]
-nalgebra = { version = "0.28.0", path = ".." }
+nalgebra = { version = "0.29.0", path = ".." }
 trybuild = "1.0.42"

nalgebra-macros/src/lib.rs

@@ -3,7 +3,18 @@
 //! This crate is not intended for direct consumption. Instead, the macros are re-exported by
 //! `nalgebra` if the `macros` feature is enabled (enabled by default).
 
-extern crate proc_macro;
+#![deny(
+    nonstandard_style,
+    unused,
+    missing_docs,
+    rust_2018_idioms,
+    rust_2018_compatibility,
+    future_incompatible,
+    missing_copy_implementations,
+    missing_debug_implementations,
+    clippy::all,
+    clippy::pedantic
+)]
 
 use proc_macro::TokenStream;
 use quote::{quote, ToTokens, TokenStreamExt};
@@ -60,7 +71,7 @@ impl Matrix {
 type MatrixRowSyntax = Punctuated<Expr, Token![,]>;
 
 impl Parse for Matrix {
-    fn parse(input: ParseStream) -> Result<Self> {
+    fn parse(input: ParseStream<'_>) -> Result<Self> {
         let mut rows = Vec::new();
         let mut ncols = None;
 
@@ -205,7 +216,7 @@ impl Vector {
 }
 
 impl Parse for Vector {
-    fn parse(input: ParseStream) -> Result<Self> {
+    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 {

nalgebra-sparse/Cargo.toml

@@ -20,7 +20,7 @@ compare = [ "matrixcompare-core" ]
 slow-tests = []
 
 [dependencies]
-nalgebra = { version="0.28", path = "../" }
+nalgebra = { version="0.29", path = "../" }
 num-traits = { version = "0.2", default-features = false }
 proptest = { version = "1.0", optional = true }
 matrixcompare-core = { version = "0.1.0", optional = true }
@@ -28,7 +28,7 @@ matrixcompare-core = { version = "0.1.0", optional = true }
 [dev-dependencies]
 itertools = "0.10"
 matrixcompare = { version = "0.3.0", features = [ "proptest-support" ] }
-nalgebra = { version="0.28", path = "../", features = ["compare"] }
+nalgebra = { version="0.29", path = "../", features = ["compare"] }
 
 [package.metadata.docs.rs]
 # Enable certain features when building docs for docs.rs

nalgebra-sparse/src/convert/impl_std_ops.rs

@@ -2,7 +2,7 @@ use crate::convert::serial::*;
 use crate::coo::CooMatrix;
 use crate::csc::CscMatrix;
 use crate::csr::CsrMatrix;
-use nalgebra::storage::Storage;
+use nalgebra::storage::RawStorage;
 use nalgebra::{ClosedAdd, DMatrix, Dim, Matrix, Scalar};
 use num_traits::Zero;
 
@@ -11,7 +11,7 @@ where
     T: Scalar + Zero,
     R: Dim,
     C: Dim,
-    S: Storage<T, R, C>,
+    S: RawStorage<T, R, C>,
 {
     fn from(matrix: &'a Matrix<T, R, C, S>) -> Self {
         convert_dense_coo(matrix)
@@ -50,7 +50,7 @@ where
     T: Scalar + Zero,
     R: Dim,
     C: Dim,
-    S: Storage<T, R, C>,
+    S: RawStorage<T, R, C>,
 {
     fn from(matrix: &'a Matrix<T, R, C, S>) -> Self {
         convert_dense_csr(matrix)
@@ -89,7 +89,7 @@ where
     T: Scalar + Zero,
     R: Dim,
     C: Dim,
-    S: Storage<T, R, C>,
+    S: RawStorage<T, R, C>,
 {
     fn from(matrix: &'a Matrix<T, R, C, S>) -> Self {
         convert_dense_csc(matrix)

nalgebra-sparse/src/convert/serial.rs

@@ -7,7 +7,7 @@ use std::ops::Add;
 
 use num_traits::Zero;
 
-use nalgebra::storage::Storage;
+use nalgebra::storage::RawStorage;
 use nalgebra::{ClosedAdd, DMatrix, Dim, Matrix, Scalar};
 
 use crate::coo::CooMatrix;
@@ -21,7 +21,7 @@ where
     T: Scalar + Zero,
     R: Dim,
     C: Dim,
-    S: Storage<T, R, C>,
+    S: RawStorage<T, R, C>,
 {
     let mut coo = CooMatrix::new(dense.nrows(), dense.ncols());
 
@@ -30,7 +30,7 @@ where
             // We use the fact that matrix iteration is guaranteed to be column-major
             let i = index % dense.nrows();
             let j = index / dense.nrows();
-            coo.push(i, j, v.inlined_clone());
+            coo.push(i, j, v.clone());
         }
     }
 
@@ -44,7 +44,7 @@ where
 {
     let mut output = DMatrix::repeat(coo.nrows(), coo.ncols(), T::zero());
     for (i, j, v) in coo.triplet_iter() {
-        output[(i, j)] += v.inlined_clone();
+        output[(i, j)] += v.clone();
     }
     output
 }
@@ -71,7 +71,7 @@ where
 pub fn convert_csr_coo<T: Scalar>(csr: &CsrMatrix<T>) -> CooMatrix<T> {
     let mut result = CooMatrix::new(csr.nrows(), csr.ncols());
     for (i, j, v) in csr.triplet_iter() {
-        result.push(i, j, v.inlined_clone());
+        result.push(i, j, v.clone());
     }
     result
 }
@@ -84,7 +84,7 @@ where
     let mut output = DMatrix::zeros(csr.nrows(), csr.ncols());
 
     for (i, j, v) in csr.triplet_iter() {
-        output[(i, j)] += v.inlined_clone();
+        output[(i, j)] += v.clone();
     }
 
     output
@@ -96,7 +96,7 @@ where
     T: Scalar + Zero,
     R: Dim,
     C: Dim,
-    S: Storage<T, R, C>,
+    S: RawStorage<T, R, C>,
 {
     let mut row_offsets = Vec::with_capacity(dense.nrows() + 1);
     let mut col_idx = Vec::new();
@@ -111,7 +111,7 @@ where
             let v = dense.index((i, j));
             if v != &T::zero() {
                 col_idx.push(j);
-                values.push(v.inlined_clone());
+                values.push(v.clone());
             }
         }
         row_offsets.push(col_idx.len());
@@ -148,7 +148,7 @@ where
 {
     let mut coo = CooMatrix::new(csc.nrows(), csc.ncols());
     for (i, j, v) in csc.triplet_iter() {
-        coo.push(i, j, v.inlined_clone());
+        coo.push(i, j, v.clone());
     }
     coo
 }
@@ -161,7 +161,7 @@ where
     let mut output = DMatrix::zeros(csc.nrows(), csc.ncols());
 
     for (i, j, v) in csc.triplet_iter() {
-        output[(i, j)] += v.inlined_clone();
+        output[(i, j)] += v.clone();
     }
 
     output
@@ -173,7 +173,7 @@ where
     T: Scalar + Zero,
     R: Dim,
     C: Dim,
-    S: Storage<T, R, C>,
+    S: RawStorage<T, R, C>,
 {
     let mut col_offsets = Vec::with_capacity(dense.ncols() + 1);
     let mut row_idx = Vec::new();
@@ -185,7 +185,7 @@ where
             let v = dense.index((i, j));
             if v != &T::zero() {
                 row_idx.push(i);
-                values.push(v.inlined_clone());
+                values.push(v.clone());
             }
         }
         col_offsets.push(row_idx.len());

nalgebra-sparse/src/coo.rs

@@ -57,7 +57,7 @@ impl<T: na::Scalar> CooMatrix<T> {
     /// Panics if any part of the dense matrix is out of bounds of the sparse matrix
     /// when inserted at `(r, c)`.
     #[inline]
-    pub fn push_matrix<R: na::Dim, C: na::Dim, S: nalgebra::storage::Storage<T, R, C>>(
+    pub fn push_matrix<R: na::Dim, C: na::Dim, S: nalgebra::storage::RawStorage<T, R, C>>(
         &mut self,
         r: usize,
         c: usize,

nalgebra-sparse/src/cs.rs

@@ -116,7 +116,7 @@ impl<T> CsMatrix<T> {
     /// Returns an entry for the given major/minor indices, or `None` if the indices are out
     /// of bounds.
     #[must_use]
-    pub fn get_entry(&self, major_index: usize, minor_index: usize) -> Option<SparseEntry<T>> {
+    pub fn get_entry(&self, major_index: usize, minor_index: usize) -> Option<SparseEntry<'_, T>> {
         let row_range = self.get_index_range(major_index)?;
         let (_, minor_indices, values) = self.cs_data();
         let minor_indices = &minor_indices[row_range.clone()];
@@ -135,7 +135,7 @@ impl<T> CsMatrix<T> {
         &mut self,
         major_index: usize,
         minor_index: usize,
-    ) -> Option<SparseEntryMut<T>> {
+    ) -> Option<SparseEntryMut<'_, T>> {
         let row_range = self.get_index_range(major_index)?;
         let minor_dim = self.pattern().minor_dim();
         let (_, minor_indices, values) = self.cs_data_mut();
@@ -145,7 +145,7 @@ impl<T> CsMatrix<T> {
     }
 
     #[must_use]
-    pub fn get_lane(&self, index: usize) -> Option<CsLane<T>> {
+    pub fn get_lane(&self, index: usize) -> Option<CsLane<'_, T>> {
         let range = self.get_index_range(index)?;
         let (_, minor_indices, values) = self.cs_data();
         Some(CsLane {
@@ -157,7 +157,7 @@ impl<T> CsMatrix<T> {
 
     #[inline]
     #[must_use]
-    pub fn get_lane_mut(&mut self, index: usize) -> Option<CsLaneMut<T>> {
+    pub fn get_lane_mut(&mut self, index: usize) -> Option<CsLaneMut<'_, T>> {
         let range = self.get_index_range(index)?;
         let minor_dim = self.pattern().minor_dim();
         let (_, minor_indices, values) = self.cs_data_mut();
@@ -169,12 +169,12 @@ impl<T> CsMatrix<T> {
     }
 
     #[inline]
-    pub fn lane_iter(&self) -> CsLaneIter<T> {
+    pub fn lane_iter(&self) -> CsLaneIter<'_, T> {
         CsLaneIter::new(self.pattern(), self.values())
     }
 
     #[inline]
-    pub fn lane_iter_mut(&mut self) -> CsLaneIterMut<T> {
+    pub fn lane_iter_mut(&mut self) -> CsLaneIterMut<'_, T> {
         CsLaneIterMut::new(&self.sparsity_pattern, &mut self.values)
     }
 
@@ -406,7 +406,7 @@ macro_rules! impl_cs_lane_common_methods {
 
             #[inline]
             #[must_use]
-            pub fn get_entry(&self, global_col_index: usize) -> Option<SparseEntry<T>> {
+            pub fn get_entry(&self, global_col_index: usize) -> Option<SparseEntry<'_, T>> {
                 get_entry_from_slices(
                     self.minor_dim,
                     self.minor_indices,
@@ -431,7 +431,7 @@ impl<'a, T> CsLaneMut<'a, T> {
     }
 
     #[must_use]
-    pub fn get_entry_mut(&mut self, global_minor_index: usize) -> Option<SparseEntryMut<T>> {
+    pub fn get_entry_mut(&mut self, global_minor_index: usize) -> Option<SparseEntryMut<'_, T>> {
         get_mut_entry_from_slices(
             self.minor_dim,
             self.minor_indices,
@@ -522,7 +522,7 @@ where
             let entry_offset = target_offsets[source_minor_idx] + *target_lane_count;
             target_indices[entry_offset] = source_major_idx;
             unsafe {
-                target_values.set(entry_offset, val.inlined_clone());
+                target_values.set(entry_offset, val.clone());
             }
             *target_lane_count += 1;
         }

nalgebra-sparse/src/csc.rs

@@ -260,7 +260,7 @@ impl<T> CscMatrix<T> {
     /// let triplets: Vec<_> = csc.triplet_iter().map(|(i, j, v)| (i, j, *v)).collect();
     /// assert_eq!(triplets, vec![(0, 0, 1), (2, 0, 3), (1, 1, 2), (0, 2, 4)]);
     /// ```
-    pub fn triplet_iter(&self) -> CscTripletIter<T> {
+    pub fn triplet_iter(&self) -> CscTripletIter<'_, T> {
         CscTripletIter {
             pattern_iter: self.pattern().entries(),
             values_iter: self.values().iter(),
@@ -290,7 +290,7 @@ impl<T> CscMatrix<T> {
     /// let triplets: Vec<_> = csc.triplet_iter().map(|(i, j, v)| (i, j, *v)).collect();
     /// assert_eq!(triplets, vec![(0, 0, 1), (2, 0, 0), (1, 1, 2), (0, 2, 4)]);
     /// ```
-    pub fn triplet_iter_mut(&mut self) -> CscTripletIterMut<T> {
+    pub fn triplet_iter_mut(&mut self) -> CscTripletIterMut<'_, T> {
         let (pattern, values) = self.cs.pattern_and_values_mut();
         CscTripletIterMut {
             pattern_iter: pattern.entries(),
@@ -305,7 +305,7 @@ impl<T> CscMatrix<T> {
     /// Panics if column index is out of bounds.
     #[inline]
     #[must_use]
-    pub fn col(&self, index: usize) -> CscCol<T> {
+    pub fn col(&self, index: usize) -> CscCol<'_, T> {
         self.get_col(index).expect("Row index must be in bounds")
     }
 
@@ -315,7 +315,7 @@ impl<T> CscMatrix<T> {
     /// ------
     /// Panics if column index is out of bounds.
     #[inline]
-    pub fn col_mut(&mut self, index: usize) -> CscColMut<T> {
+    pub fn col_mut(&mut self, index: usize) -> CscColMut<'_, T> {
         self.get_col_mut(index)
             .expect("Row index must be in bounds")
     }
@@ -323,26 +323,26 @@ impl<T> CscMatrix<T> {
     /// Return the column at the given column index, or `None` if out of bounds.
     #[inline]
     #[must_use]
-    pub fn get_col(&self, index: usize) -> Option<CscCol<T>> {
+    pub fn get_col(&self, index: usize) -> Option<CscCol<'_, T>> {
         self.cs.get_lane(index).map(|lane| CscCol { lane })
     }
 
     /// Mutable column access for the given column index, or `None` if out of bounds.
     #[inline]
     #[must_use]
-    pub fn get_col_mut(&mut self, index: usize) -> Option<CscColMut<T>> {
+    pub fn get_col_mut(&mut self, index: usize) -> Option<CscColMut<'_, T>> {
         self.cs.get_lane_mut(index).map(|lane| CscColMut { lane })
     }
 
     /// An iterator over columns in the matrix.
-    pub fn col_iter(&self) -> CscColIter<T> {
+    pub fn col_iter(&self) -> CscColIter<'_, T> {
         CscColIter {
             lane_iter: CsLaneIter::new(self.pattern(), self.values()),
         }
     }
 
     /// A mutable iterator over columns in the matrix.
-    pub fn col_iter_mut(&mut self) -> CscColIterMut<T> {
+    pub fn col_iter_mut(&mut self) -> CscColIterMut<'_, T> {
         let (pattern, values) = self.cs.pattern_and_values_mut();
         CscColIterMut {
             lane_iter: CsLaneIterMut::new(pattern, values),
@@ -408,7 +408,7 @@ impl<T> CscMatrix<T> {
     /// Each call to this function incurs the cost of a binary search among the explicitly
     /// stored row entries for the given column.
     #[must_use]
-    pub fn get_entry(&self, row_index: usize, col_index: usize) -> Option<SparseEntry<T>> {
+    pub fn get_entry(&self, row_index: usize, col_index: usize) -> Option<SparseEntry<'_, T>> {
         self.cs.get_entry(col_index, row_index)
     }
 
@@ -421,7 +421,7 @@ impl<T> CscMatrix<T> {
         &mut self,
         row_index: usize,
         col_index: usize,
-    ) -> Option<SparseEntryMut<T>> {
+    ) -> Option<SparseEntryMut<'_, T>> {
         self.cs.get_entry_mut(col_index, row_index)
     }
 
@@ -434,7 +434,7 @@ impl<T> CscMatrix<T> {
     /// ------
     /// Panics if `row_index` or `col_index` is out of bounds.
     #[must_use]
-    pub fn index_entry(&self, row_index: usize, col_index: usize) -> SparseEntry<T> {
+    pub fn index_entry(&self, row_index: usize, col_index: usize) -> SparseEntry<'_, T> {
         self.get_entry(row_index, col_index)
             .expect("Out of bounds matrix indices encountered")
     }
@@ -447,7 +447,7 @@ impl<T> CscMatrix<T> {
     /// Panics
     /// ------
     /// Panics if `row_index` or `col_index` is out of bounds.
-    pub fn index_entry_mut(&mut self, row_index: usize, col_index: usize) -> SparseEntryMut<T> {
+    pub fn index_entry_mut(&mut self, row_index: usize, col_index: usize) -> SparseEntryMut<'_, T> {
         self.get_entry_mut(row_index, col_index)
             .expect("Out of bounds matrix indices encountered")
     }
@@ -666,7 +666,7 @@ macro_rules! impl_csc_col_common_methods {
             /// Each call to this function incurs the cost of a binary search among the explicitly
             /// stored row entries.
             #[must_use]
-            pub fn get_entry(&self, global_row_index: usize) -> Option<SparseEntry<T>> {
+            pub fn get_entry(&self, global_row_index: usize) -> Option<SparseEntry<'_, T>> {
                 self.lane.get_entry(global_row_index)
             }
         }
@@ -693,7 +693,7 @@ impl<'a, T> CscColMut<'a, T> {
 
     /// Returns a mutable entry for the given global row index.
     #[must_use]
-    pub fn get_entry_mut(&mut self, global_row_index: usize) -> Option<SparseEntryMut<T>> {
+    pub fn get_entry_mut(&mut self, global_row_index: usize) -> Option<SparseEntryMut<'_, T>> {
         self.lane.get_entry_mut(global_row_index)
     }
 }

nalgebra-sparse/src/csr.rs

@@ -262,7 +262,7 @@ impl<T> CsrMatrix<T> {
     /// let triplets: Vec<_> = csr.triplet_iter().map(|(i, j, v)| (i, j, *v)).collect();
     /// assert_eq!(triplets, vec![(0, 0, 1), (0, 2, 2), (1, 1, 3), (2, 0, 4)]);
     /// ```
-    pub fn triplet_iter(&self) -> CsrTripletIter<T> {
+    pub fn triplet_iter(&self) -> CsrTripletIter<'_, T> {
         CsrTripletIter {
             pattern_iter: self.pattern().entries(),
             values_iter: self.values().iter(),
@@ -292,7 +292,7 @@ impl<T> CsrMatrix<T> {
     /// let triplets: Vec<_> = csr.triplet_iter().map(|(i, j, v)| (i, j, *v)).collect();
     /// assert_eq!(triplets, vec![(0, 0, 1), (0, 2, 2), (1, 1, 3), (2, 0, 0)]);
     /// ```
-    pub fn triplet_iter_mut(&mut self) -> CsrTripletIterMut<T> {
+    pub fn triplet_iter_mut(&mut self) -> CsrTripletIterMut<'_, T> {
         let (pattern, values) = self.cs.pattern_and_values_mut();
         CsrTripletIterMut {
             pattern_iter: pattern.entries(),
@@ -307,7 +307,7 @@ impl<T> CsrMatrix<T> {
     /// Panics if row index is out of bounds.
     #[inline]
     #[must_use]
-    pub fn row(&self, index: usize) -> CsrRow<T> {
+    pub fn row(&self, index: usize) -> CsrRow<'_, T> {
         self.get_row(index).expect("Row index must be in bounds")
     }
 
@@ -317,7 +317,7 @@ impl<T> CsrMatrix<T> {
     /// ------
     /// Panics if row index is out of bounds.
     #[inline]
-    pub fn row_mut(&mut self, index: usize) -> CsrRowMut<T> {
+    pub fn row_mut(&mut self, index: usize) -> CsrRowMut<'_, T> {
         self.get_row_mut(index)
             .expect("Row index must be in bounds")
     }
@@ -325,26 +325,26 @@ impl<T> CsrMatrix<T> {
     /// Return the row at the given row index, or `None` if out of bounds.
     #[inline]
     #[must_use]
-    pub fn get_row(&self, index: usize) -> Option<CsrRow<T>> {
+    pub fn get_row(&self, index: usize) -> Option<CsrRow<'_, T>> {
         self.cs.get_lane(index).map(|lane| CsrRow { lane })
     }
 
     /// Mutable row access for the given row index, or `None` if out of bounds.
     #[inline]
     #[must_use]
-    pub fn get_row_mut(&mut self, index: usize) -> Option<CsrRowMut<T>> {
+    pub fn get_row_mut(&mut self, index: usize) -> Option<CsrRowMut<'_, T>> {
         self.cs.get_lane_mut(index).map(|lane| CsrRowMut { lane })
     }
 
     /// An iterator over rows in the matrix.
-    pub fn row_iter(&self) -> CsrRowIter<T> {
+    pub fn row_iter(&self) -> CsrRowIter<'_, T> {
         CsrRowIter {
             lane_iter: CsLaneIter::new(self.pattern(), self.values()),
         }
     }
 
     /// A mutable iterator over rows in the matrix.
-    pub fn row_iter_mut(&mut self) -> CsrRowIterMut<T> {
+    pub fn row_iter_mut(&mut self) -> CsrRowIterMut<'_, T> {
         let (pattern, values) = self.cs.pattern_and_values_mut();
         CsrRowIterMut {
             lane_iter: CsLaneIterMut::new(pattern, values),
@@ -410,7 +410,7 @@ impl<T> CsrMatrix<T> {
     /// Each call to this function incurs the cost of a binary search among the explicitly
     /// stored column entries for the given row.
     #[must_use]
-    pub fn get_entry(&self, row_index: usize, col_index: usize) -> Option<SparseEntry<T>> {
+    pub fn get_entry(&self, row_index: usize, col_index: usize) -> Option<SparseEntry<'_, T>> {
         self.cs.get_entry(row_index, col_index)
     }
 
@@ -423,7 +423,7 @@ impl<T> CsrMatrix<T> {
         &mut self,
         row_index: usize,
         col_index: usize,
-    ) -> Option<SparseEntryMut<T>> {
+    ) -> Option<SparseEntryMut<'_, T>> {
         self.cs.get_entry_mut(row_index, col_index)
     }
 
@@ -436,7 +436,7 @@ impl<T> CsrMatrix<T> {
     /// ------
     /// Panics if `row_index` or `col_index` is out of bounds.
     #[must_use]
-    pub fn index_entry(&self, row_index: usize, col_index: usize) -> SparseEntry<T> {
+    pub fn index_entry(&self, row_index: usize, col_index: usize) -> SparseEntry<'_, T> {
         self.get_entry(row_index, col_index)
             .expect("Out of bounds matrix indices encountered")
     }
@@ -449,7 +449,7 @@ impl<T> CsrMatrix<T> {
     /// Panics
     /// ------
     /// Panics if `row_index` or `col_index` is out of bounds.
-    pub fn index_entry_mut(&mut self, row_index: usize, col_index: usize) -> SparseEntryMut<T> {
+    pub fn index_entry_mut(&mut self, row_index: usize, col_index: usize) -> SparseEntryMut<'_, T> {
         self.get_entry_mut(row_index, col_index)
             .expect("Out of bounds matrix indices encountered")
     }
@@ -667,7 +667,7 @@ macro_rules! impl_csr_row_common_methods {
             /// stored column entries.
             #[inline]
             #[must_use]
-            pub fn get_entry(&self, global_col_index: usize) -> Option<SparseEntry<T>> {
+            pub fn get_entry(&self, global_col_index: usize) -> Option<SparseEntry<'_, T>> {
                 self.lane.get_entry(global_col_index)
             }
         }
@@ -697,7 +697,7 @@ impl<'a, T> CsrRowMut<'a, T> {
     /// Returns a mutable entry for the given global column index.
     #[inline]
     #[must_use]
-    pub fn get_entry_mut(&mut self, global_col_index: usize) -> Option<SparseEntryMut<T>> {
+    pub fn get_entry_mut(&mut self, global_col_index: usize) -> Option<SparseEntryMut<'_, T>> {
         self.lane.get_entry_mut(global_col_index)
     }
 }

nalgebra-sparse/src/factorization/cholesky.rs

@@ -3,7 +3,7 @@ use crate::ops::serial::spsolve_csc_lower_triangular;
 use crate::ops::Op;
 use crate::pattern::SparsityPattern;
 use core::{iter, mem};
-use nalgebra::{DMatrix, DMatrixSlice, DMatrixSliceMut, RealField, Scalar};
+use nalgebra::{DMatrix, DMatrixSlice, DMatrixSliceMut, RealField};
 use std::fmt::{Display, Formatter};
 
 /// A symbolic sparse Cholesky factorization of a CSC matrix.
@@ -72,7 +72,7 @@ pub struct CscCholesky<T> {
     work_c: Vec<usize>,
 }
 
-#[derive(Debug, PartialEq, Eq, Clone)]
+#[derive(Debug, PartialEq, Eq, Copy, Clone)]
 #[non_exhaustive]
 /// Possible errors produced by the Cholesky factorization.
 pub enum CholeskyError {
@@ -209,15 +209,16 @@ impl<T: RealField> CscCholesky<T> {
                     let irow = *self.m_pattern.minor_indices().get_unchecked(p);
 
                     if irow >= k {
-                        *self.work_x.get_unchecked_mut(irow) = *values.get_unchecked(p);
+                        *self.work_x.get_unchecked_mut(irow) = values.get_unchecked(p).clone();
                     }
                 }
 
                 for &j in self.u_pattern.lane(k) {
-                    let factor = -*self
+                    let factor = -self
                         .l_factor
                         .values()
-                        .get_unchecked(*self.work_c.get_unchecked(j));
+                        .get_unchecked(*self.work_c.get_unchecked(j))
+                        .clone();
                     *self.work_c.get_unchecked_mut(j) += 1;
 
                     if j < k {
@@ -225,27 +226,27 @@ impl<T: RealField> CscCholesky<T> {
                         let col_j_entries = col_j.row_indices().iter().zip(col_j.values());
                         for (&z, val) in col_j_entries {
                             if z >= k {
-                                *self.work_x.get_unchecked_mut(z) += val.inlined_clone() * factor;
+                                *self.work_x.get_unchecked_mut(z) += val.clone() * factor.clone();
                             }
                         }
                     }
                 }
 
-                let diag = *self.work_x.get_unchecked(k);
+                let diag = self.work_x.get_unchecked(k).clone();
 
                 if diag > T::zero() {
                     let denom = diag.sqrt();
 
                     {
                         let (offsets, _, values) = self.l_factor.csc_data_mut();
-                        *values.get_unchecked_mut(*offsets.get_unchecked(k)) = denom;
+                        *values.get_unchecked_mut(*offsets.get_unchecked(k)) = denom.clone();
                     }
 
                     let mut col_k = self.l_factor.col_mut(k);
                     let (col_k_rows, col_k_values) = col_k.rows_and_values_mut();
                     let col_k_entries = col_k_rows.iter().zip(col_k_values);
                     for (&p, val) in col_k_entries {
-                        *val = *self.work_x.get_unchecked(p) / denom;
+                        *val = self.work_x.get_unchecked(p).clone() / denom.clone();
                         *self.work_x.get_unchecked_mut(p) = T::zero();
                     }
                 } else {

nalgebra-sparse/src/lib.rs

@@ -131,12 +131,15 @@
 //!     assert_matrix_eq!(y, y_expected, comp = abs, tol = 1e-9);
 //! }
 //! ```
-#![deny(non_camel_case_types)]
-#![deny(unused_parens)]
-#![deny(non_upper_case_globals)]
-#![deny(unused_qualifications)]
-#![deny(unused_results)]
-#![deny(missing_docs)]
+#![deny(
+    nonstandard_style,
+    unused,
+    missing_docs,
+    rust_2018_idioms,
+    rust_2018_compatibility,
+    future_incompatible,
+    missing_copy_implementations
+)]
 
 pub extern crate nalgebra as na;
 pub mod convert;
@@ -190,7 +193,7 @@ impl SparseFormatError {
 
 /// The type of format error described by a [SparseFormatError](struct.SparseFormatError.html).
 #[non_exhaustive]
-#[derive(Debug, Clone, PartialEq, Eq)]
+#[derive(Debug, Copy, Clone, PartialEq, Eq)]
 pub enum SparseFormatErrorKind {
     /// Indicates that the index data associated with the format contains at least one index
     /// out of bounds.
@@ -208,7 +211,7 @@ pub enum SparseFormatErrorKind {
 }
 
 impl fmt::Display for SparseFormatError {
-    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
         write!(f, "{}", self.error)
     }
 }

nalgebra-sparse/src/matrixcompare.rs

@@ -28,7 +28,7 @@ macro_rules! impl_matrix_for_csr_csc {
                 self.ncols()
             }
 
-            fn access(&self) -> Access<T> {
+            fn access(&self) -> Access<'_, T> {
                 Access::Sparse(self)
             }
         }
@@ -59,7 +59,7 @@ impl<T: Clone> matrixcompare_core::Matrix<T> for CooMatrix<T> {
         self.ncols()
     }
 
-    fn access(&self) -> Access<T> {
+    fn access(&self) -> Access<'_, T> {
         Access::Sparse(self)
     }
 }

nalgebra-sparse/src/ops/impl_std_ops.rs

@@ -7,7 +7,7 @@ use crate::ops::serial::{
 };
 use crate::ops::Op;
 use nalgebra::allocator::Allocator;
-use nalgebra::base::storage::Storage;
+use nalgebra::base::storage::RawStorage;
 use nalgebra::constraint::{DimEq, ShapeConstraint};
 use nalgebra::{
     ClosedAdd, ClosedDiv, ClosedMul, ClosedSub, DefaultAllocator, Dim, Dynamic, Matrix, OMatrix,
@@ -141,7 +141,7 @@ macro_rules! impl_scalar_mul {
         impl_mul!(<'a, T>(a: &'a $matrix_type<T>, b: &'a T) -> $matrix_type<T> {
             let values: Vec<_> = a.values()
                 .iter()
-                .map(|v_i| v_i.inlined_clone() * b.inlined_clone())
+                .map(|v_i| v_i.clone() * b.clone())
                 .collect();
             $matrix_type::try_from_pattern_and_values(a.pattern().clone(), values).unwrap()
         });
@@ -151,7 +151,7 @@ macro_rules! impl_scalar_mul {
         impl_mul!(<'a, T>(a: $matrix_type<T>, b: &'a T) -> $matrix_type<T> {
             let mut a = a;
             for value in a.values_mut() {
-                *value = b.inlined_clone() * value.inlined_clone();
+                *value = b.clone() * value.clone();
             }
             a
         });
@@ -168,7 +168,7 @@ macro_rules! impl_scalar_mul {
         {
             fn mul_assign(&mut self, scalar: T) {
                 for val in self.values_mut() {
-                    *val *= scalar.inlined_clone();
+                    *val *= scalar.clone();
                 }
             }
         }
@@ -179,7 +179,7 @@ macro_rules! impl_scalar_mul {
         {
             fn mul_assign(&mut self, scalar: &'a T) {
                 for val in self.values_mut() {
-                    *val *= scalar.inlined_clone();
+                    *val *= scalar.clone();
                 }
             }
         }
@@ -199,7 +199,7 @@ macro_rules! impl_neg {
 
             fn neg(mut self) -> Self::Output {
                 for v_i in self.values_mut() {
-                    *v_i = -v_i.inlined_clone();
+                    *v_i = -v_i.clone();
                 }
                 self
             }
@@ -233,25 +233,25 @@ macro_rules! impl_div {
             matrix
         });
         impl_bin_op!(Div, div, <'a, T: ClosedDiv>(matrix: $matrix_type<T>, scalar: &T) -> $matrix_type<T> {
-            matrix / scalar.inlined_clone()
+            matrix / scalar.clone()
         });
         impl_bin_op!(Div, div, <'a, T: ClosedDiv>(matrix: &'a $matrix_type<T>, scalar: T) -> $matrix_type<T> {
             let new_values = matrix.values()
                 .iter()
-                .map(|v_i| v_i.inlined_clone() / scalar.inlined_clone())
+                .map(|v_i| v_i.clone() / scalar.clone())
                 .collect();
             $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> {
-            matrix / scalar.inlined_clone()
+            matrix / scalar.clone()
         });
 
         impl<T> DivAssign<T> for $matrix_type<T>
             where T : Scalar + ClosedAdd + ClosedMul + ClosedDiv + Zero + One
         {
             fn div_assign(&mut self, scalar: T) {
-                self.values_mut().iter_mut().for_each(|v_i| *v_i /= scalar.inlined_clone());
+                self.values_mut().iter_mut().for_each(|v_i| *v_i /= scalar.clone());
             }
         }
 
@@ -259,7 +259,7 @@ macro_rules! impl_div {
             where T : Scalar + ClosedAdd + ClosedMul + ClosedDiv + Zero + One
         {
             fn div_assign(&mut self, scalar: &'a T) {
-                *self /= scalar.inlined_clone();
+                *self /= scalar.clone();
             }
         }
     }
@@ -272,7 +272,7 @@ macro_rules! impl_spmm_cs_dense {
     ($matrix_type_name:ident, $spmm_fn:ident) => {
         // Implement ref-ref
         impl_spmm_cs_dense!(&'a $matrix_type_name<T>, &'a Matrix<T, R, C, S>, $spmm_fn, |lhs, rhs| {
-            let (_, ncols) = rhs.data.shape();
+            let (_, ncols) = rhs.shape_generic();
             let nrows = Dynamic::new(lhs.nrows());
             let mut result = OMatrix::<T, Dynamic, C>::zeros_generic(nrows, ncols);
             $spmm_fn(T::zero(), &mut result, T::one(), Op::NoOp(lhs), Op::NoOp(rhs));
@@ -301,14 +301,14 @@ macro_rules! impl_spmm_cs_dense {
             T: Scalar + ClosedMul + ClosedAdd + ClosedSub + ClosedDiv + Neg + Zero + One,
             R: Dim,
             C: Dim,
-            S: Storage<T, R, C>,
+            S: RawStorage<T, R, C>,
             DefaultAllocator: Allocator<T, Dynamic, C>,
             // TODO: Is it possible to simplify these bounds?
             ShapeConstraint:
                 // Bounds so that we can turn OMatrix<T, Dynamic, C> into a DMatrixSliceMut
-                  DimEq<U1, <<DefaultAllocator as Allocator<T, Dynamic, C>>::Buffer as Storage<T, Dynamic, C>>::RStride>
+                  DimEq<U1, <<DefaultAllocator as Allocator<T, Dynamic, C>>::Buffer as RawStorage<T, Dynamic, C>>::RStride>
                 + DimEq<C, Dynamic>
-                + DimEq<Dynamic, <<DefaultAllocator as Allocator<T, Dynamic, C>>::Buffer as Storage<T, Dynamic, C>>::CStride>
+                + DimEq<Dynamic, <<DefaultAllocator as Allocator<T, Dynamic, C>>::Buffer as RawStorage<T, Dynamic, C>>::CStride>
                 // Bounds so that we can turn &Matrix<T, R, C, S> into a DMatrixSlice
                 + DimEq<U1, S::RStride>
                 + DimEq<R, Dynamic>

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

@@ -34,13 +34,13 @@ where
         let a_lane_i = a.get_lane(i).unwrap();
         let mut c_lane_i = c.get_lane_mut(i).unwrap();
         for c_ij in c_lane_i.values_mut() {
-            *c_ij = beta.inlined_clone() * c_ij.inlined_clone();
+            *c_ij = beta.clone() * c_ij.clone();
         }
 
         for (&k, a_ik) in a_lane_i.minor_indices().iter().zip(a_lane_i.values()) {
             let b_lane_k = b.get_lane(k).unwrap();
             let (mut c_lane_i_cols, mut c_lane_i_values) = c_lane_i.indices_and_values_mut();
-            let alpha_aik = alpha.inlined_clone() * a_ik.inlined_clone();
+            let alpha_aik = alpha.clone() * a_ik.clone();
             for (j, b_kj) in b_lane_k.minor_indices().iter().zip(b_lane_k.values()) {
                 // Determine the location in C to append the value
                 let (c_local_idx, _) = c_lane_i_cols
@@ -49,7 +49,7 @@ where
                     .find(|(_, c_col)| *c_col == j)
                     .ok_or_else(spmm_cs_unexpected_entry)?;
 
-                c_lane_i_values[c_local_idx] += alpha_aik.inlined_clone() * b_kj.inlined_clone();
+                c_lane_i_values[c_local_idx] += alpha_aik.clone() * b_kj.clone();
                 c_lane_i_cols = &c_lane_i_cols[c_local_idx..];
                 c_lane_i_values = &mut c_lane_i_values[c_local_idx..];
             }
@@ -81,7 +81,7 @@ where
             for (mut c_lane_i, a_lane_i) in c.lane_iter_mut().zip(a.lane_iter()) {
                 if beta != T::one() {
                     for c_ij in c_lane_i.values_mut() {
-                        *c_ij *= beta.inlined_clone();
+                        *c_ij *= beta.clone();
                     }
                 }
 
@@ -97,7 +97,7 @@ where
                         .enumerate()
                         .find(|(_, c_col)| *c_col == a_col)
                         .ok_or_else(spadd_cs_unexpected_entry)?;
-                    c_vals[c_idx] += alpha.inlined_clone() * a_val.inlined_clone();
+                    c_vals[c_idx] += alpha.clone() * a_val.clone();
                     c_minors = &c_minors[c_idx..];
                     c_vals = &mut c_vals[c_idx..];
                 }
@@ -106,14 +106,14 @@ where
         Op::Transpose(a) => {
             if beta != T::one() {
                 for c_ij in c.values_mut() {
-                    *c_ij *= beta.inlined_clone();
+                    *c_ij *= beta.clone();
                 }
             }
 
             for (i, a_lane_i) in a.lane_iter().enumerate() {
                 for (&j, a_val) in a_lane_i.minor_indices().iter().zip(a_lane_i.values()) {
-                    let a_val = a_val.inlined_clone();
-                    let alpha = alpha.inlined_clone();
+                    let a_val = a_val.clone();
+                    let alpha = alpha.clone();
                     match c.get_entry_mut(j, i).unwrap() {
                         SparseEntryMut::NonZero(c_ji) => *c_ji += alpha * a_val,
                         SparseEntryMut::Zero => return Err(spadd_cs_unexpected_entry()),
@@ -131,10 +131,10 @@ where
 /// the transposed operation must be specified for the CSC matrix.
 pub fn spmm_cs_dense<T>(
     beta: T,
-    mut c: DMatrixSliceMut<T>,
+    mut c: DMatrixSliceMut<'_, T>,
     alpha: T,
     a: Op<&CsMatrix<T>>,
-    b: Op<DMatrixSlice<T>>,
+    b: Op<DMatrixSlice<'_, T>>,
 ) where
     T: Scalar + ClosedAdd + ClosedMul + Zero + One,
 {
@@ -149,10 +149,9 @@ pub fn spmm_cs_dense<T>(
                             Op::NoOp(ref b) => b.index((k, j)),
                             Op::Transpose(ref b) => b.index((j, k)),
                         };
-                        dot_ij += a_ik.inlined_clone() * b_contrib.inlined_clone();
+                        dot_ij += a_ik.clone() * b_contrib.clone();
                     }
-                    *c_ij = beta.inlined_clone() * c_ij.inlined_clone()
-                        + alpha.inlined_clone() * dot_ij;
+                    *c_ij = beta.clone() * c_ij.clone() + alpha.clone() * dot_ij;
                 }
             }
         }
@@ -163,19 +162,19 @@ pub fn spmm_cs_dense<T>(
             for k in 0..a.pattern().major_dim() {
                 let a_row_k = a.get_lane(k).unwrap();
                 for (&i, a_ki) in a_row_k.minor_indices().iter().zip(a_row_k.values()) {
-                    let gamma_ki = alpha.inlined_clone() * a_ki.inlined_clone();
+                    let gamma_ki = alpha.clone() * a_ki.clone();
                     let mut c_row_i = c.row_mut(i);
                     match b {
                         Op::NoOp(ref b) => {
                             let b_row_k = b.row(k);
                             for (c_ij, b_kj) in c_row_i.iter_mut().zip(b_row_k.iter()) {
-                                *c_ij += gamma_ki.inlined_clone() * b_kj.inlined_clone();
+                                *c_ij += gamma_ki.clone() * b_kj.clone();
                             }
                         }
                         Op::Transpose(ref b) => {
                             let b_col_k = b.column(k);
                             for (c_ij, b_jk) in c_row_i.iter_mut().zip(b_col_k.iter()) {
-                                *c_ij += gamma_ki.inlined_clone() * b_jk.inlined_clone();
+                                *c_ij += gamma_ki.clone() * b_jk.clone();
                             }
                         }
                     }

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

@@ -27,10 +27,10 @@ pub fn spmm_csc_dense<'a, T>(
 
 fn spmm_csc_dense_<T>(
     beta: T,
-    c: DMatrixSliceMut<T>,
+    c: DMatrixSliceMut<'_, T>,
     alpha: T,
     a: Op<&CscMatrix<T>>,
-    b: Op<DMatrixSlice<T>>,
+    b: Op<DMatrixSlice<'_, T>>,
 ) where
     T: Scalar + ClosedAdd + ClosedMul + Zero + One,
 {
@@ -147,7 +147,7 @@ pub fn spsolve_csc_lower_triangular<'a, T: RealField>(
 
 fn spsolve_csc_lower_triangular_no_transpose<T: RealField>(
     l: &CscMatrix<T>,
-    b: DMatrixSliceMut<T>,
+    b: DMatrixSliceMut<'_, T>,
 ) -> Result<(), OperationError> {
     let mut x = b;
 
@@ -165,13 +165,13 @@ fn spsolve_csc_lower_triangular_no_transpose<T: RealField>(
             // a severe penalty)
             let diag_csc_index = l_col_k.row_indices().iter().position(|&i| i == k);
             if let Some(diag_csc_index) = diag_csc_index {
-                let l_kk = l_col_k.values()[diag_csc_index];
+                let l_kk = l_col_k.values()[diag_csc_index].clone();
 
                 if l_kk != T::zero() {
                     // Update entry associated with diagonal
                     x_col_j[k] /= l_kk;
                     // Copy value after updating (so we don't run into the borrow checker)
-                    let x_kj = x_col_j[k];
+                    let x_kj = x_col_j[k].clone();
 
                     let row_indices = &l_col_k.row_indices()[(diag_csc_index + 1)..];
                     let l_values = &l_col_k.values()[(diag_csc_index + 1)..];
@@ -179,7 +179,7 @@ fn spsolve_csc_lower_triangular_no_transpose<T: RealField>(
                     // Note: The remaining entries are below the diagonal
                     for (&i, l_ik) in row_indices.iter().zip(l_values) {
                         let x_ij = &mut x_col_j[i];
-                        *x_ij -= l_ik.inlined_clone() * x_kj;
+                        *x_ij -= l_ik.clone() * x_kj.clone();
                     }
 
                     x_col_j[k] = x_kj;
@@ -205,7 +205,7 @@ fn spsolve_encountered_zero_diagonal() -> Result<(), OperationError> {
 
 fn spsolve_csc_lower_triangular_transpose<T: RealField>(
     l: &CscMatrix<T>,
-    b: DMatrixSliceMut<T>,
+    b: DMatrixSliceMut<'_, T>,
 ) -> Result<(), OperationError> {
     let mut x = b;
 
@@ -223,22 +223,22 @@ fn spsolve_csc_lower_triangular_transpose<T: RealField>(
             // TODO: Can use exponential search here to quickly skip entries
             let diag_csc_index = l_col_i.row_indices().iter().position(|&k| i == k);
             if let Some(diag_csc_index) = diag_csc_index {
-                let l_ii = l_col_i.values()[diag_csc_index];
+                let l_ii = l_col_i.values()[diag_csc_index].clone();
 
                 if l_ii != T::zero() {
                     // // Update entry associated with diagonal
                     // x_col_j[k] /= a_kk;
 
                     // Copy value after updating (so we don't run into the borrow checker)
-                    let mut x_ii = x_col_j[i];
+                    let mut x_ii = x_col_j[i].clone();
 
                     let row_indices = &l_col_i.row_indices()[(diag_csc_index + 1)..];
                     let a_values = &l_col_i.values()[(diag_csc_index + 1)..];
 
                     // Note: The remaining entries are below the diagonal
-                    for (&k, &l_ki) in row_indices.iter().zip(a_values) {
-                        let x_kj = x_col_j[k];
-                        x_ii -= l_ki * x_kj;
+                    for (k, l_ki) in row_indices.iter().zip(a_values) {
+                        let x_kj = x_col_j[*k].clone();
+                        x_ii -= l_ki.clone() * x_kj;
                     }
 
                     x_col_j[i] = x_ii / l_ii;

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

@@ -22,10 +22,10 @@ pub fn spmm_csr_dense<'a, T>(
 
 fn spmm_csr_dense_<T>(
     beta: T,
-    c: DMatrixSliceMut<T>,
+    c: DMatrixSliceMut<'_, T>,
     alpha: T,
     a: Op<&CsrMatrix<T>>,
-    b: Op<DMatrixSlice<T>>,
+    b: Op<DMatrixSlice<'_, T>>,
 ) where
     T: Scalar + ClosedAdd + ClosedMul + Zero + One,
 {

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

@@ -8,7 +8,6 @@
 //! some operations which will be able to dynamically adapt the output pattern to fit the
 //! result, but these have yet to be implemented.
 
-#[macro_use]
 macro_rules! assert_compatible_spmm_dims {
     ($c:expr, $a:expr, $b:expr) => {{
         use crate::ops::Op::{NoOp, Transpose};
@@ -37,7 +36,6 @@ macro_rules! assert_compatible_spmm_dims {
     }};
 }
 
-#[macro_use]
 macro_rules! assert_compatible_spadd_dims {
     ($c:expr, $a:expr) => {
         use crate::ops::Op;
@@ -74,7 +72,7 @@ pub struct OperationError {
 
 /// The different kinds of operation errors that may occur.
 #[non_exhaustive]
-#[derive(Clone, Debug)]
+#[derive(Copy, Clone, Debug)]
 pub enum OperationErrorKind {
     /// Indicates that one or more sparsity patterns involved in the operation violate the
     /// expectations of the routine.

nalgebra-sparse/src/pattern.rs

@@ -205,7 +205,7 @@ impl SparsityPattern {
     /// ```
     ///
     #[must_use]
-    pub fn entries(&self) -> SparsityPatternIter {
+    pub fn entries(&self) -> SparsityPatternIter<'_> {
         SparsityPatternIter::from_pattern(self)
     }
 
@@ -260,7 +260,7 @@ impl SparsityPattern {
 
 /// Error type for `SparsityPattern` format errors.
 #[non_exhaustive]
-#[derive(Debug, PartialEq, Eq)]
+#[derive(Copy, Clone, Debug, PartialEq, Eq)]
 pub enum SparsityPatternFormatError {
     /// Indicates an invalid number of offsets.
     ///

rustfmt.toml

@@ -0,0 +1,3 @@
+edition = "2018"
+use_try_shorthand = true
+use_field_init_shorthand = true

src/base/alias.rs

@@ -5,6 +5,8 @@ use crate::base::storage::Owned;
 #[cfg(any(feature = "std", feature = "alloc"))]
 use crate::base::vec_storage::VecStorage;
 use crate::base::{ArrayStorage, Const, Matrix, Unit};
+use crate::storage::OwnedUninit;
+use std::mem::MaybeUninit;
 
 /*
  *
@@ -19,6 +21,9 @@ use crate::base::{ArrayStorage, Const, Matrix, Unit};
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 pub type OMatrix<T, R, C> = Matrix<T, R, C, Owned<T, R, C>>;
 
+/// An owned matrix with uninitialized data.
+pub type UninitMatrix<T, R, C> = Matrix<MaybeUninit<T>, R, C, OwnedUninit<T, R, C>>;
+
 /// An owned matrix column-major matrix with `R` rows and `C` columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
@@ -278,6 +283,9 @@ pub type OVector<T, D> = Matrix<T, D, U1, Owned<T, D, U1>>;
 /// A statically sized D-dimensional column vector.
 pub type SVector<T, const D: usize> = Matrix<T, Const<D>, U1, ArrayStorage<T, D, 1>>; // Owned<T, Const<D>, U1>>;
 
+/// An owned matrix with uninitialized data.
+pub type UninitVector<T, D> = Matrix<MaybeUninit<T>, D, U1, OwnedUninit<T, D, U1>>;
+
 /// An owned matrix column-major matrix with `R` rows and `C` columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**

src/base/allocator.rs

@@ -1,12 +1,14 @@
 //! Abstract definition of a matrix data storage allocator.
 
 use std::any::Any;
-use std::mem;
 
 use crate::base::constraint::{SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
 use crate::base::dimension::{Dim, U1};
-use crate::base::storage::ContiguousStorageMut;
 use crate::base::{DefaultAllocator, Scalar};
+use crate::storage::{IsContiguous, RawStorageMut};
+use crate::StorageMut;
+use std::fmt::Debug;
+use std::mem::MaybeUninit;
 
 /// A matrix allocator of a memory buffer that may contain `R::to_usize() * C::to_usize()`
 /// elements of type `T`.
@@ -17,12 +19,21 @@ use crate::base::{DefaultAllocator, Scalar};
 ///
 /// Every allocator must be both static and dynamic. Though not all implementations may share the
 /// same `Buffer` type.
-pub trait Allocator<T: Scalar, R: Dim, C: Dim = U1>: Any + Sized {
+pub trait Allocator<T, R: Dim, C: Dim = U1>: Any + Sized {
     /// The type of buffer this allocator can instanciate.
-    type Buffer: ContiguousStorageMut<T, R, C> + Clone;
+    type Buffer: StorageMut<T, R, C> + IsContiguous + Clone + Debug;
+    /// The type of buffer with uninitialized components this allocator can instanciate.
+    type BufferUninit: RawStorageMut<MaybeUninit<T>, R, C> + IsContiguous;
 
     /// Allocates a buffer with the given number of rows and columns without initializing its content.
-    unsafe fn allocate_uninitialized(nrows: R, ncols: C) -> mem::MaybeUninit<Self::Buffer>;
+    fn allocate_uninit(nrows: R, ncols: C) -> Self::BufferUninit;
+
+    /// 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;
 
     /// Allocates a buffer initialized with the content of the given iterator.
     fn allocate_from_iterator<I: IntoIterator<Item = T>>(
@@ -32,8 +43,8 @@ pub trait Allocator<T: Scalar, R: Dim, C: Dim = U1>: Any + Sized {
     ) -> Self::Buffer;
 }
 
-/// A matrix reallocator. Changes the size of the memory buffer that initially contains (RFrom ×
-/// CFrom) elements to a smaller or larger size (RTo, CTo).
+/// 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>
 {
@@ -41,15 +52,15 @@ pub trait Reallocator<T: Scalar, RFrom: Dim, CFrom: Dim, RTo: Dim, CTo: Dim>:
     /// `buf`. Data stored by `buf` are linearly copied to the output:
     ///
     /// # Safety
-    /// * The copy is performed as if both were just arrays (without a matrix structure).
-    /// * If `buf` is larger than the output size, then extra elements of `buf` are truncated.
-    /// * If `buf` is smaller than the output size, then extra elements of the output are left
-    /// uninitialized.
+    /// The following invariants must be respected by the implementors of this method:
+    /// * The copy is performed as if both were just arrays (without taking into account the matrix structure).
+    /// * If the underlying buffer is being shrunk, the removed elements must **not** be dropped
+    ///   by this method. Dropping them is the responsibility of the caller.
     unsafe fn reallocate_copy(
         nrows: RTo,
         ncols: CTo,
         buf: <Self as Allocator<T, RFrom, CFrom>>::Buffer,
-    ) -> <Self as Allocator<T, RTo, CTo>>::Buffer;
+    ) -> <Self as Allocator<T, RTo, CTo>>::BufferUninit;
 }
 
 /// The number of rows of the result of a componentwise operation on two matrices.
@@ -67,7 +78,6 @@ where
     R2: Dim,
     C1: Dim,
     C2: Dim,
-    T: Scalar,
     ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
 {
 }
@@ -78,7 +88,6 @@ where
     R2: Dim,
     C1: Dim,
     C2: Dim,
-    T: Scalar,
     DefaultAllocator: Allocator<T, R1, C1> + Allocator<T, SameShapeR<R1, R2>, SameShapeC<C1, C2>>,
     ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
 {
@@ -91,7 +100,6 @@ pub trait SameShapeVectorAllocator<T, R1, R2>:
 where
     R1: Dim,
     R2: Dim,
-    T: Scalar,
     ShapeConstraint: SameNumberOfRows<R1, R2>,
 {
 }
@@ -100,7 +108,6 @@ impl<T, R1, R2> SameShapeVectorAllocator<T, R1, R2> for DefaultAllocator
 where
     R1: Dim,
     R2: Dim,
-    T: Scalar,
     DefaultAllocator: Allocator<T, R1, U1> + Allocator<T, SameShapeR<R1, R2>>,
     ShapeConstraint: SameNumberOfRows<R1, R2>,
 {

src/base/array_storage.rs

@@ -12,8 +12,6 @@ use serde::ser::SerializeSeq;
 use serde::{Deserialize, Deserializer, Serialize, Serializer};
 #[cfg(feature = "serde-serialize-no-std")]
 use std::marker::PhantomData;
-#[cfg(feature = "serde-serialize-no-std")]
-use std::mem;
 
 #[cfg(feature = "abomonation-serialize")]
 use abomonation::Abomonation;
@@ -21,21 +19,37 @@ use abomonation::Abomonation;
 use crate::base::allocator::Allocator;
 use crate::base::default_allocator::DefaultAllocator;
 use crate::base::dimension::{Const, ToTypenum};
-use crate::base::storage::{
-    ContiguousStorage, ContiguousStorageMut, Owned, ReshapableStorage, Storage, StorageMut,
-};
+use crate::base::storage::{IsContiguous, Owned, RawStorage, RawStorageMut, ReshapableStorage};
 use crate::base::Scalar;
+use crate::Storage;
+use std::mem;
 
 /*
  *
- * Static Storage.
+ * Static RawStorage.
  *
  */
 /// A array-based statically sized matrix data storage.
-#[repr(C)]
+#[repr(transparent)]
 #[derive(Copy, Clone, PartialEq, Eq, Hash)]
 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> {
+    /// Converts this array storage to a slice.
+    #[inline]
+    pub fn as_slice(&self) -> &[T] {
+        // SAFETY: this is OK because ArrayStorage is contiguous.
+        unsafe { self.as_slice_unchecked() }
+    }
+
+    /// Converts this array storage to a mutable slice.
+    #[inline]
+    pub fn as_mut_slice(&mut self) -> &mut [T] {
+        // SAFETY: this is OK because ArrayStorage is contiguous.
+        unsafe { self.as_mut_slice_unchecked() }
+    }
+}
+
 // TODO: remove this once the stdlib implements Default for arrays.
 impl<T: Default, const R: usize, const C: usize> Default for ArrayStorage<T, R, C>
 where
@@ -49,16 +63,13 @@ where
 
 impl<T: Debug, const R: usize, const C: usize> Debug for ArrayStorage<T, R, C> {
     #[inline]
-    fn fmt(&self, fmt: &mut Formatter) -> fmt::Result {
+    fn fmt(&self, fmt: &mut Formatter<'_>) -> fmt::Result {
         self.0.fmt(fmt)
     }
 }
 
-unsafe impl<T, const R: usize, const C: usize> Storage<T, Const<R>, Const<C>>
+unsafe impl<T, const R: usize, const C: usize> RawStorage<T, Const<R>, Const<C>>
     for ArrayStorage<T, R, C>
-where
-    T: Scalar,
-    DefaultAllocator: Allocator<T, Const<R>, Const<C>, Buffer = Self>,
 {
     type RStride = Const<1>;
     type CStride = Const<R>;
@@ -83,6 +94,17 @@ where
         true
     }
 
+    #[inline]
+    unsafe fn as_slice_unchecked(&self) -> &[T] {
+        std::slice::from_raw_parts(self.ptr(), R * 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>,
+{
     #[inline]
     fn into_owned(self) -> Owned<T, Const<R>, Const<C>>
     where
@@ -96,21 +118,12 @@ where
     where
         DefaultAllocator: Allocator<T, Const<R>, Const<C>>,
     {
-        let it = self.as_slice().iter().cloned();
-        DefaultAllocator::allocate_from_iterator(self.shape().0, self.shape().1, it)
-    }
-
-    #[inline]
-    unsafe fn as_slice_unchecked(&self) -> &[T] {
-        std::slice::from_raw_parts(self.ptr(), R * C)
+        self.clone()
     }
 }
 
-unsafe impl<T, const R: usize, const C: usize> StorageMut<T, Const<R>, Const<C>>
+unsafe impl<T, const R: usize, const C: usize> RawStorageMut<T, Const<R>, Const<C>>
     for ArrayStorage<T, R, C>
-where
-    T: Scalar,
-    DefaultAllocator: Allocator<T, Const<R>, Const<C>, Buffer = Self>,
 {
     #[inline]
     fn ptr_mut(&mut self) -> *mut T {
@@ -123,21 +136,7 @@ where
     }
 }
 
-unsafe impl<T, const R: usize, const C: usize> ContiguousStorage<T, Const<R>, Const<C>>
-    for ArrayStorage<T, R, C>
-where
-    T: Scalar,
-    DefaultAllocator: Allocator<T, Const<R>, Const<C>, Buffer = Self>,
-{
-}
-
-unsafe impl<T, const R: usize, const C: usize> ContiguousStorageMut<T, Const<R>, Const<C>>
-    for ArrayStorage<T, R, C>
-where
-    T: Scalar,
-    DefaultAllocator: Allocator<T, Const<R>, Const<C>, Buffer = Self>,
-{
-}
+unsafe impl<T, const R: usize, const C: usize> IsContiguous for ArrayStorage<T, R, C> {}
 
 impl<T, const R1: usize, const C1: usize, const R2: usize, const C2: usize>
     ReshapableStorage<T, Const<R1>, Const<C1>, Const<R2>, Const<C2>> for ArrayStorage<T, R1, C1>
@@ -160,8 +159,8 @@ where
 
     fn reshape_generic(self, _: Const<R2>, _: Const<C2>) -> Self::Output {
         unsafe {
-            let data: [[T; R2]; C2] = std::mem::transmute_copy(&self.0);
-            std::mem::forget(self.0);
+            let data: [[T; R2]; C2] = mem::transmute_copy(&self.0);
+            mem::forget(self.0);
             ArrayStorage(data)
         }
     }
@@ -231,7 +230,7 @@ where
 {
     type Value = ArrayStorage<T, R, C>;
 
-    fn expecting(&self, formatter: &mut Formatter) -> fmt::Result {
+    fn expecting(&self, formatter: &mut Formatter<'_>) -> fmt::Result {
         formatter.write_str("a matrix array")
     }
 
@@ -240,19 +239,28 @@ where
     where
         V: SeqAccess<'a>,
     {
-        let mut out: Self::Value = unsafe { mem::MaybeUninit::uninit().assume_init() };
+        let mut out: ArrayStorage<core::mem::MaybeUninit<T>, R, C> =
+            DefaultAllocator::allocate_uninit(Const::<R>, Const::<C>);
         let mut curr = 0;
 
         while let Some(value) = visitor.next_element()? {
             *out.as_mut_slice()
                 .get_mut(curr)
-                .ok_or_else(|| V::Error::invalid_length(curr, &self))? = value;
+                .ok_or_else(|| V::Error::invalid_length(curr, &self))? =
+                core::mem::MaybeUninit::new(value);
             curr += 1;
         }
 
         if curr == R * C {
-            Ok(out)
+            // Safety: all the elements have been initialized.
+            unsafe { Ok(<DefaultAllocator as Allocator<T, Const<R>, Const<C>>>::assume_init(out)) }
         } else {
+            for i in 0..curr {
+                // Safety:
+                // - We couldn’t initialize the whole storage. Drop the ones we initialized.
+                unsafe { std::ptr::drop_in_place(out.as_mut_slice()[i].as_mut_ptr()) };
+            }
+
             Err(V::Error::invalid_length(curr, &self))
         }
     }

src/base/blas.rs

@@ -1,23 +1,21 @@
-use crate::SimdComplexField;
-#[cfg(feature = "std")]
-use matrixmultiply;
+use crate::{RawStorage, SimdComplexField};
 use num::{One, Zero};
 use simba::scalar::{ClosedAdd, ClosedMul};
-#[cfg(feature = "std")]
-use std::mem;
 
 use crate::base::allocator::Allocator;
+use crate::base::blas_uninit::{axcpy_uninit, gemm_uninit, gemv_uninit};
 use crate::base::constraint::{
     AreMultipliable, DimEq, SameNumberOfColumns, SameNumberOfRows, ShapeConstraint,
 };
 use crate::base::dimension::{Const, Dim, Dynamic, U1, U2, U3, U4};
 use crate::base::storage::{Storage, StorageMut};
+use crate::base::uninit::Init;
 use crate::base::{
     DVectorSlice, DefaultAllocator, Matrix, Scalar, SquareMatrix, Vector, VectorSlice,
 };
 
 /// # Dot/scalar product
-impl<T, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S>
+impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S>
 where
     T: Scalar + Zero + ClosedAdd + ClosedMul,
 {
@@ -28,7 +26,7 @@ where
         conjugate: impl Fn(T) -> T,
     ) -> T
     where
-        SB: Storage<T, R2, C2>,
+        SB: RawStorage<T, R2, C2>,
         ShapeConstraint: DimEq<R, R2> + DimEq<C, C2>,
     {
         assert!(
@@ -49,36 +47,36 @@ where
         // because the `for` loop below won't be very efficient on those.
         if (R::is::<U2>() || R2::is::<U2>()) && (C::is::<U1>() || C2::is::<U1>()) {
             unsafe {
-                let a = conjugate(self.get_unchecked((0, 0)).inlined_clone())
-                    * rhs.get_unchecked((0, 0)).inlined_clone();
-                let b = conjugate(self.get_unchecked((1, 0)).inlined_clone())
-                    * rhs.get_unchecked((1, 0)).inlined_clone();
+                let a = conjugate(self.get_unchecked((0, 0)).clone())
+                    * rhs.get_unchecked((0, 0)).clone();
+                let b = conjugate(self.get_unchecked((1, 0)).clone())
+                    * rhs.get_unchecked((1, 0)).clone();
 
                 return a + b;
             }
         }
         if (R::is::<U3>() || R2::is::<U3>()) && (C::is::<U1>() || C2::is::<U1>()) {
             unsafe {
-                let a = conjugate(self.get_unchecked((0, 0)).inlined_clone())
-                    * rhs.get_unchecked((0, 0)).inlined_clone();
-                let b = conjugate(self.get_unchecked((1, 0)).inlined_clone())
-                    * rhs.get_unchecked((1, 0)).inlined_clone();
-                let c = conjugate(self.get_unchecked((2, 0)).inlined_clone())
-                    * rhs.get_unchecked((2, 0)).inlined_clone();
+                let a = conjugate(self.get_unchecked((0, 0)).clone())
+                    * rhs.get_unchecked((0, 0)).clone();
+                let b = conjugate(self.get_unchecked((1, 0)).clone())
+                    * rhs.get_unchecked((1, 0)).clone();
+                let c = conjugate(self.get_unchecked((2, 0)).clone())
+                    * rhs.get_unchecked((2, 0)).clone();
 
                 return a + b + c;
             }
         }
         if (R::is::<U4>() || R2::is::<U4>()) && (C::is::<U1>() || C2::is::<U1>()) {
             unsafe {
-                let mut a = conjugate(self.get_unchecked((0, 0)).inlined_clone())
-                    * rhs.get_unchecked((0, 0)).inlined_clone();
-                let mut b = conjugate(self.get_unchecked((1, 0)).inlined_clone())
-                    * rhs.get_unchecked((1, 0)).inlined_clone();
-                let c = conjugate(self.get_unchecked((2, 0)).inlined_clone())
-                    * rhs.get_unchecked((2, 0)).inlined_clone();
-                let d = conjugate(self.get_unchecked((3, 0)).inlined_clone())
-                    * rhs.get_unchecked((3, 0)).inlined_clone();
+                let mut a = conjugate(self.get_unchecked((0, 0)).clone())
+                    * rhs.get_unchecked((0, 0)).clone();
+                let mut b = conjugate(self.get_unchecked((1, 0)).clone())
+                    * rhs.get_unchecked((1, 0)).clone();
+                let c = conjugate(self.get_unchecked((2, 0)).clone())
+                    * rhs.get_unchecked((2, 0)).clone();
+                let d = conjugate(self.get_unchecked((3, 0)).clone())
+                    * rhs.get_unchecked((3, 0)).clone();
 
                 a += c;
                 b += d;
@@ -119,36 +117,36 @@ where
 
             while self.nrows() - i >= 8 {
                 acc0 += unsafe {
-                    conjugate(self.get_unchecked((i, j)).inlined_clone())
-                        * rhs.get_unchecked((i, j)).inlined_clone()
+                    conjugate(self.get_unchecked((i, j)).clone())
+                        * rhs.get_unchecked((i, j)).clone()
                 };
                 acc1 += unsafe {
-                    conjugate(self.get_unchecked((i + 1, j)).inlined_clone())
-                        * rhs.get_unchecked((i + 1, j)).inlined_clone()
+                    conjugate(self.get_unchecked((i + 1, j)).clone())
+                        * rhs.get_unchecked((i + 1, j)).clone()
                 };
                 acc2 += unsafe {
-                    conjugate(self.get_unchecked((i + 2, j)).inlined_clone())
-                        * rhs.get_unchecked((i + 2, j)).inlined_clone()
+                    conjugate(self.get_unchecked((i + 2, j)).clone())
+                        * rhs.get_unchecked((i + 2, j)).clone()
                 };
                 acc3 += unsafe {
-                    conjugate(self.get_unchecked((i + 3, j)).inlined_clone())
-                        * rhs.get_unchecked((i + 3, j)).inlined_clone()
+                    conjugate(self.get_unchecked((i + 3, j)).clone())
+                        * rhs.get_unchecked((i + 3, j)).clone()
                 };
                 acc4 += unsafe {
-                    conjugate(self.get_unchecked((i + 4, j)).inlined_clone())
-                        * rhs.get_unchecked((i + 4, j)).inlined_clone()
+                    conjugate(self.get_unchecked((i + 4, j)).clone())
+                        * rhs.get_unchecked((i + 4, j)).clone()
                 };
                 acc5 += unsafe {
-                    conjugate(self.get_unchecked((i + 5, j)).inlined_clone())
-                        * rhs.get_unchecked((i + 5, j)).inlined_clone()
+                    conjugate(self.get_unchecked((i + 5, j)).clone())
+                        * rhs.get_unchecked((i + 5, j)).clone()
                 };
                 acc6 += unsafe {
-                    conjugate(self.get_unchecked((i + 6, j)).inlined_clone())
-                        * rhs.get_unchecked((i + 6, j)).inlined_clone()
+                    conjugate(self.get_unchecked((i + 6, j)).clone())
+                        * rhs.get_unchecked((i + 6, j)).clone()
                 };
                 acc7 += unsafe {
-                    conjugate(self.get_unchecked((i + 7, j)).inlined_clone())
-                        * rhs.get_unchecked((i + 7, j)).inlined_clone()
+                    conjugate(self.get_unchecked((i + 7, j)).clone())
+                        * rhs.get_unchecked((i + 7, j)).clone()
                 };
                 i += 8;
             }
@@ -160,8 +158,8 @@ where
 
             for k in i..self.nrows() {
                 res += unsafe {
-                    conjugate(self.get_unchecked((k, j)).inlined_clone())
-                        * rhs.get_unchecked((k, j)).inlined_clone()
+                    conjugate(self.get_unchecked((k, j)).clone())
+                        * rhs.get_unchecked((k, j)).clone()
                 }
             }
         }
@@ -196,7 +194,7 @@ where
     #[must_use]
     pub fn dot<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> T
     where
-        SB: Storage<T, R2, C2>,
+        SB: RawStorage<T, R2, C2>,
         ShapeConstraint: DimEq<R, R2> + DimEq<C, C2>,
     {
         self.dotx(rhs, |e| e)
@@ -226,7 +224,7 @@ where
     pub fn dotc<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> T
     where
         T: SimdComplexField,
-        SB: Storage<T, R2, C2>,
+        SB: RawStorage<T, R2, C2>,
         ShapeConstraint: DimEq<R, R2> + DimEq<C, C2>,
     {
         self.dotx(rhs, T::simd_conjugate)
@@ -253,7 +251,7 @@ where
     #[must_use]
     pub fn tr_dot<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> T
     where
-        SB: Storage<T, R2, C2>,
+        SB: RawStorage<T, R2, C2>,
         ShapeConstraint: DimEq<C, R2> + DimEq<R, C2>,
     {
         let (nrows, ncols) = self.shape();
@@ -268,8 +266,7 @@ where
         for j in 0..self.nrows() {
             for i in 0..self.ncols() {
                 res += unsafe {
-                    self.get_unchecked((j, i)).inlined_clone()
-                        * rhs.get_unchecked((i, j)).inlined_clone()
+                    self.get_unchecked((j, i)).clone() * rhs.get_unchecked((i, j)).clone()
                 }
             }
         }
@@ -278,43 +275,6 @@ where
     }
 }
 
-#[allow(clippy::too_many_arguments)]
-fn array_axcpy<T>(
-    y: &mut [T],
-    a: T,
-    x: &[T],
-    c: T,
-    beta: T,
-    stride1: usize,
-    stride2: usize,
-    len: usize,
-) where
-    T: Scalar + Zero + ClosedAdd + ClosedMul,
-{
-    for i in 0..len {
-        unsafe {
-            let y = y.get_unchecked_mut(i * stride1);
-            *y = a.inlined_clone()
-                * x.get_unchecked(i * stride2).inlined_clone()
-                * c.inlined_clone()
-                + beta.inlined_clone() * y.inlined_clone();
-        }
-    }
-}
-
-fn array_axc<T>(y: &mut [T], a: T, x: &[T], c: T, stride1: usize, stride2: usize, len: usize)
-where
-    T: Scalar + Zero + ClosedAdd + ClosedMul,
-{
-    for i in 0..len {
-        unsafe {
-            *y.get_unchecked_mut(i * stride1) = a.inlined_clone()
-                * x.get_unchecked(i * stride2).inlined_clone()
-                * c.inlined_clone();
-        }
-    }
-}
-
 /// # BLAS functions
 impl<T, D: Dim, S> Vector<T, D, S>
 where
@@ -341,23 +301,7 @@ where
         SB: Storage<T, D2>,
         ShapeConstraint: DimEq<D, D2>,
     {
-        assert_eq!(self.nrows(), x.nrows(), "Axcpy: mismatched vector shapes.");
-
-        let rstride1 = self.strides().0;
-        let rstride2 = x.strides().0;
-
-        unsafe {
-            // SAFETY: the conversion to slices is OK because we access the
-            //         elements taking the strides into account.
-            let y = self.data.as_mut_slice_unchecked();
-            let x = x.data.as_slice_unchecked();
-
-            if !b.is_zero() {
-                array_axcpy(y, a, x, c, b, rstride1, rstride2, x.len());
-            } else {
-                array_axc(y, a, x, c, rstride1, rstride2, x.len());
-            }
-        }
+        unsafe { axcpy_uninit(Init, self, a, x, c, b) };
     }
 
     /// Computes `self = a * x + b * self`.
@@ -413,38 +357,8 @@ where
         SC: Storage<T, D3>,
         ShapeConstraint: DimEq<D, R2> + AreMultipliable<R2, C2, D3, U1>,
     {
-        let dim1 = self.nrows();
-        let (nrows2, ncols2) = a.shape();
-        let dim3 = x.nrows();
-
-        assert!(
-            ncols2 == dim3 && dim1 == nrows2,
-            "Gemv: dimensions mismatch."
-        );
-
-        if ncols2 == 0 {
-            // NOTE: we can't just always multiply by beta
-            // because we documented the guaranty that `self` is
-            // never read if `beta` is zero.
-            if beta.is_zero() {
-                self.fill(T::zero());
-            } else {
-                *self *= beta;
-            }
-            return;
-        }
-
-        // TODO: avoid bound checks.
-        let col2 = a.column(0);
-        let val = unsafe { x.vget_unchecked(0).inlined_clone() };
-        self.axcpy(alpha.inlined_clone(), &col2, val, beta);
-
-        for j in 1..ncols2 {
-            let col2 = a.column(j);
-            let val = unsafe { x.vget_unchecked(j).inlined_clone() };
-
-            self.axcpy(alpha.inlined_clone(), &col2, val, T::one());
-        }
+        // Safety: this is safe because we are passing Status == Init.
+        unsafe { gemv_uninit(Init, self, alpha, a, x, beta) }
     }
 
     #[inline(always)]
@@ -455,8 +369,8 @@ where
         x: &Vector<T, D3, SC>,
         beta: T,
         dot: impl Fn(
-            &DVectorSlice<T, SB::RStride, SB::CStride>,
-            &DVectorSlice<T, SC::RStride, SC::CStride>,
+            &DVectorSlice<'_, T, SB::RStride, SB::CStride>,
+            &DVectorSlice<'_, T, SC::RStride, SC::CStride>,
         ) -> T,
     ) where
         T: One,
@@ -483,9 +397,9 @@ where
 
         // TODO: avoid bound checks.
         let col2 = a.column(0);
-        let val = unsafe { x.vget_unchecked(0).inlined_clone() };
-        self.axpy(alpha.inlined_clone() * val, &col2, beta);
-        self[0] += alpha.inlined_clone() * dot(&a.slice_range(1.., 0), &x.rows_range(1..));
+        let val = unsafe { x.vget_unchecked(0).clone() };
+        self.axpy(alpha.clone() * val, &col2, beta);
+        self[0] += alpha.clone() * dot(&a.slice_range(1.., 0), &x.rows_range(1..));
 
         for j in 1..dim2 {
             let col2 = a.column(j);
@@ -493,36 +407,17 @@ where
 
             let val;
             unsafe {
-                val = x.vget_unchecked(j).inlined_clone();
-                *self.vget_unchecked_mut(j) += alpha.inlined_clone() * dot;
+                val = x.vget_unchecked(j).clone();
+                *self.vget_unchecked_mut(j) += alpha.clone() * dot;
             }
             self.rows_range_mut(j + 1..).axpy(
-                alpha.inlined_clone() * val,
+                alpha.clone() * val,
                 &col2.rows_range(j + 1..),
                 T::one(),
             );
         }
     }
 
-    /// Computes `self = alpha * a * x + beta * self`, where `a` is a **symmetric** matrix, `x` a
-    /// vector, and `alpha, beta` two scalars. DEPRECATED: use `sygemv` instead.
-    #[inline]
-    #[deprecated(note = "This is renamed `sygemv` to match the original BLAS terminology.")]
-    pub fn gemv_symm<D2: Dim, D3: Dim, SB, SC>(
-        &mut self,
-        alpha: T,
-        a: &SquareMatrix<T, D2, SB>,
-        x: &Vector<T, D3, SC>,
-        beta: T,
-    ) where
-        T: One,
-        SB: Storage<T, D2, D2>,
-        SC: Storage<T, D3>,
-        ShapeConstraint: DimEq<D, D2> + AreMultipliable<D2, D2, D3, U1>,
-    {
-        self.sygemv(alpha, a, x, beta)
-    }
-
     /// Computes `self = alpha * a * x + beta * self`, where `a` is a **symmetric** matrix, `x` a
     /// vector, and `alpha, beta` two scalars.
     ///
@@ -619,7 +514,7 @@ where
         a: &Matrix<T, R2, C2, SB>,
         x: &Vector<T, D3, SC>,
         beta: T,
-        dot: impl Fn(&VectorSlice<T, R2, SB::RStride, SB::CStride>, &Vector<T, D3, SC>) -> T,
+        dot: impl Fn(&VectorSlice<'_, T, R2, SB::RStride, SB::CStride>, &Vector<T, D3, SC>) -> T,
     ) where
         T: One,
         SB: Storage<T, R2, C2>,
@@ -642,13 +537,12 @@ where
         if beta.is_zero() {
             for j in 0..ncols2 {
                 let val = unsafe { self.vget_unchecked_mut(j) };
-                *val = alpha.inlined_clone() * dot(&a.column(j), x)
+                *val = alpha.clone() * dot(&a.column(j), x)
             }
         } else {
             for j in 0..ncols2 {
                 let val = unsafe { self.vget_unchecked_mut(j) };
-                *val = alpha.inlined_clone() * dot(&a.column(j), x)
-                    + beta.inlined_clone() * val.inlined_clone();
+                *val = alpha.clone() * dot(&a.column(j), x) + beta.clone() * val.clone();
             }
         }
     }
@@ -752,9 +646,9 @@ where
 
         for j in 0..ncols1 {
             // TODO: avoid bound checks.
-            let val = unsafe { conjugate(y.vget_unchecked(j).inlined_clone()) };
+            let val = unsafe { conjugate(y.vget_unchecked(j).clone()) };
             self.column_mut(j)
-                .axpy(alpha.inlined_clone() * val, x, beta.inlined_clone());
+                .axpy(alpha.clone() * val, x, beta.clone());
         }
     }
 
@@ -859,122 +753,9 @@ where
             + SameNumberOfColumns<C1, C3>
             + AreMultipliable<R2, C2, R3, C3>,
     {
-        let ncols1 = self.ncols();
-
-        #[cfg(feature = "std")]
-        {
-            // We assume large matrices will be Dynamic but small matrices static.
-            // We could use matrixmultiply for large statically-sized matrices but the performance
-            // threshold to activate it would be different from SMALL_DIM because our code optimizes
-            // better for statically-sized matrices.
-            if R1::is::<Dynamic>()
-                || C1::is::<Dynamic>()
-                || R2::is::<Dynamic>()
-                || C2::is::<Dynamic>()
-                || R3::is::<Dynamic>()
-                || C3::is::<Dynamic>()
-            {
-                // matrixmultiply can be used only if the std feature is available.
-                let nrows1 = self.nrows();
-                let (nrows2, ncols2) = a.shape();
-                let (nrows3, ncols3) = b.shape();
-
-                // Threshold determined empirically.
-                const SMALL_DIM: usize = 5;
-
-                if nrows1 > SMALL_DIM
-                    && ncols1 > SMALL_DIM
-                    && nrows2 > SMALL_DIM
-                    && ncols2 > SMALL_DIM
-                {
-                    assert_eq!(
-                        ncols2, nrows3,
-                        "gemm: dimensions mismatch for multiplication."
-                    );
-                    assert_eq!(
-                        (nrows1, ncols1),
-                        (nrows2, ncols3),
-                        "gemm: dimensions mismatch for addition."
-                    );
-
-                    // NOTE: this case should never happen because we enter this
-                    // codepath only when ncols2 > SMALL_DIM. Though we keep this
-                    // here just in case if in the future we change the conditions to
-                    // enter this codepath.
-                    if ncols2 == 0 {
-                        // NOTE: we can't just always multiply by beta
-                        // because we documented the guaranty that `self` is
-                        // never read if `beta` is zero.
-                        if beta.is_zero() {
-                            self.fill(T::zero());
-                        } else {
-                            *self *= beta;
-                        }
-                        return;
-                    }
-
-                    if T::is::<f32>() {
-                        let (rsa, csa) = a.strides();
-                        let (rsb, csb) = b.strides();
-                        let (rsc, csc) = self.strides();
-
-                        unsafe {
-                            matrixmultiply::sgemm(
-                                nrows2,
-                                ncols2,
-                                ncols3,
-                                mem::transmute_copy(&alpha),
-                                a.data.ptr() as *const f32,
-                                rsa as isize,
-                                csa as isize,
-                                b.data.ptr() as *const f32,
-                                rsb as isize,
-                                csb as isize,
-                                mem::transmute_copy(&beta),
-                                self.data.ptr_mut() as *mut f32,
-                                rsc as isize,
-                                csc as isize,
-                            );
-                        }
-                        return;
-                    } else if T::is::<f64>() {
-                        let (rsa, csa) = a.strides();
-                        let (rsb, csb) = b.strides();
-                        let (rsc, csc) = self.strides();
-
-                        unsafe {
-                            matrixmultiply::dgemm(
-                                nrows2,
-                                ncols2,
-                                ncols3,
-                                mem::transmute_copy(&alpha),
-                                a.data.ptr() as *const f64,
-                                rsa as isize,
-                                csa as isize,
-                                b.data.ptr() as *const f64,
-                                rsb as isize,
-                                csb as isize,
-                                mem::transmute_copy(&beta),
-                                self.data.ptr_mut() as *mut f64,
-                                rsc as isize,
-                                csc as isize,
-                            );
-                        }
-                        return;
-                    }
-                }
-            }
-        }
-
-        for j1 in 0..ncols1 {
-            // TODO: avoid bound checks.
-            self.column_mut(j1).gemv(
-                alpha.inlined_clone(),
-                a,
-                &b.column(j1),
-                beta.inlined_clone(),
-            );
-        }
+        // SAFETY: this is valid because our matrices are initialized and
+        // we are using status = Init.
+        unsafe { gemm_uninit(Init, self, alpha, a, b, beta) }
     }
 
     /// Computes `self = alpha * a.transpose() * b + beta * self`, where `a, b, self` are matrices.
@@ -1030,12 +811,8 @@ where
 
         for j1 in 0..ncols1 {
             // TODO: avoid bound checks.
-            self.column_mut(j1).gemv_tr(
-                alpha.inlined_clone(),
-                a,
-                &b.column(j1),
-                beta.inlined_clone(),
-            );
+            self.column_mut(j1)
+                .gemv_tr(alpha.clone(), a, &b.column(j1), beta.clone());
         }
     }
 
@@ -1092,7 +869,8 @@ where
 
         for j1 in 0..ncols1 {
             // TODO: avoid bound checks.
-            self.column_mut(j1).gemv_ad(alpha, a, &b.column(j1), beta);
+            self.column_mut(j1)
+                .gemv_ad(alpha.clone(), a, &b.column(j1), beta.clone());
         }
     }
 }
@@ -1126,13 +904,13 @@ where
         assert!(dim1 == dim2 && dim1 == dim3, "ger: dimensions mismatch.");
 
         for j in 0..dim1 {
-            let val = unsafe { conjugate(y.vget_unchecked(j).inlined_clone()) };
+            let val = unsafe { conjugate(y.vget_unchecked(j).clone()) };
             let subdim = Dynamic::new(dim1 - j);
             // TODO: avoid bound checks.
             self.generic_slice_mut((j, j), (subdim, Const::<1>)).axpy(
-                alpha.inlined_clone() * val,
+                alpha.clone() * val,
                 &x.rows_range(j..),
-                beta.inlined_clone(),
+                beta.clone(),
             );
         }
     }
@@ -1293,11 +1071,11 @@ where
         ShapeConstraint: DimEq<D1, D2> + DimEq<D1, R3> + DimEq<D2, R3> + DimEq<C3, D4>,
     {
         work.gemv(T::one(), lhs, &mid.column(0), T::zero());
-        self.ger(alpha.inlined_clone(), work, &lhs.column(0), beta);
+        self.ger(alpha.clone(), work, &lhs.column(0), beta);
 
         for j in 1..mid.ncols() {
             work.gemv(T::one(), lhs, &mid.column(j), T::zero());
-            self.ger(alpha.inlined_clone(), work, &lhs.column(j), T::one());
+            self.ger(alpha.clone(), work, &lhs.column(j), T::one());
         }
     }
 
@@ -1337,9 +1115,8 @@ where
         ShapeConstraint: DimEq<D1, D1> + DimEq<D1, R3> + DimEq<C3, D4>,
         DefaultAllocator: Allocator<T, D1>,
     {
-        let mut work = unsafe {
-            crate::unimplemented_or_uninitialized_generic!(self.data.shape().0, Const::<1>)
-        };
+        // 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>);
         self.quadform_tr_with_workspace(&mut work, alpha, lhs, mid, beta)
     }
 
@@ -1388,12 +1165,12 @@ where
     {
         work.gemv(T::one(), mid, &rhs.column(0), T::zero());
         self.column_mut(0)
-            .gemv_tr(alpha.inlined_clone(), rhs, work, beta.inlined_clone());
+            .gemv_tr(alpha.clone(), rhs, work, beta.clone());
 
         for j in 1..rhs.ncols() {
             work.gemv(T::one(), mid, &rhs.column(j), T::zero());
             self.column_mut(j)
-                .gemv_tr(alpha.inlined_clone(), rhs, work, beta.inlined_clone());
+                .gemv_tr(alpha.clone(), rhs, work, beta.clone());
         }
     }
 
@@ -1432,9 +1209,8 @@ where
         ShapeConstraint: DimEq<D2, R3> + DimEq<D1, C3> + AreMultipliable<C3, R3, D2, U1>,
         DefaultAllocator: Allocator<T, D2>,
     {
-        let mut work = unsafe {
-            crate::unimplemented_or_uninitialized_generic!(mid.data.shape().0, Const::<1>)
-        };
+        // 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>);
         self.quadform_with_workspace(&mut work, alpha, mid, rhs, beta)
     }
 }

src/base/blas_uninit.rs

@@ -0,0 +1,321 @@
+/*
+ * This file implements some BLAS operations in such a way that they work
+ * even if the first argument (the output parameter) is an uninitialized matrix.
+ *
+ * Because doing this makes the code harder to read, we only implemented the operations that we
+ * know would benefit from this performance-wise, namely, GEMM (which we use for our matrix
+ * multiplication code). If we identify other operations like that in the future, we could add
+ * them here.
+ */
+
+#[cfg(feature = "std")]
+use matrixmultiply;
+use num::{One, Zero};
+use simba::scalar::{ClosedAdd, ClosedMul};
+#[cfg(feature = "std")]
+use std::mem;
+
+use crate::base::constraint::{
+    AreMultipliable, DimEq, SameNumberOfColumns, SameNumberOfRows, ShapeConstraint,
+};
+use crate::base::dimension::{Dim, Dynamic, 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
+// `Status::assume_init_mut` is sound.
+#[allow(clippy::too_many_arguments)]
+unsafe fn array_axcpy<Status, T>(
+    _: Status,
+    y: &mut [Status::Value],
+    a: T,
+    x: &[T],
+    c: T,
+    beta: T,
+    stride1: usize,
+    stride2: usize,
+    len: usize,
+) where
+    Status: InitStatus<T>,
+    T: Scalar + Zero + ClosedAdd + ClosedMul,
+{
+    for i in 0..len {
+        let y = Status::assume_init_mut(y.get_unchecked_mut(i * stride1));
+        *y =
+            a.clone() * x.get_unchecked(i * stride2).clone() * c.clone() + beta.clone() * y.clone();
+    }
+}
+
+fn array_axc<Status, T>(
+    _: Status,
+    y: &mut [Status::Value],
+    a: T,
+    x: &[T],
+    c: T,
+    stride1: usize,
+    stride2: usize,
+    len: usize,
+) where
+    Status: InitStatus<T>,
+    T: Scalar + Zero + ClosedAdd + ClosedMul,
+{
+    for i in 0..len {
+        unsafe {
+            Status::init(
+                y.get_unchecked_mut(i * stride1),
+                a.clone() * x.get_unchecked(i * stride2).clone() * c.clone(),
+            );
+        }
+    }
+}
+
+/// Computes `y = a * x * c + b * y`.
+///
+/// If `b` is zero, `y` is never read from and may be uninitialized.
+///
+/// # Safety
+/// This is UB if b != 0 and any component of `y` is uninitialized.
+#[inline(always)]
+#[allow(clippy::many_single_char_names)]
+pub unsafe fn axcpy_uninit<Status, T, D1: Dim, D2: Dim, SA, SB>(
+    status: Status,
+    y: &mut Vector<Status::Value, D1, SA>,
+    a: T,
+    x: &Vector<T, D2, SB>,
+    c: T,
+    b: T,
+) where
+    T: Scalar + Zero + ClosedAdd + ClosedMul,
+    SA: RawStorageMut<Status::Value, D1>,
+    SB: RawStorage<T, D2>,
+    ShapeConstraint: DimEq<D1, D2>,
+    Status: InitStatus<T>,
+{
+    assert_eq!(y.nrows(), x.nrows(), "Axcpy: mismatched vector shapes.");
+
+    let rstride1 = y.strides().0;
+    let rstride2 = x.strides().0;
+
+    // SAFETY: the conversion to slices is OK because we access the
+    //         elements taking the strides into account.
+    let y = y.data.as_mut_slice_unchecked();
+    let x = x.data.as_slice_unchecked();
+
+    if !b.is_zero() {
+        array_axcpy(status, y, a, x, c, b, rstride1, rstride2, x.len());
+    } else {
+        array_axc(status, y, a, x, c, rstride1, rstride2, x.len());
+    }
+}
+
+/// Computes `y = alpha * a * x + beta * y`, where `a` is a matrix, `x` a vector, and
+/// `alpha, beta` two scalars.
+///
+/// If `beta` is zero, `y` is never read from and may be uninitialized.
+///
+/// # Safety
+/// This is UB if beta != 0 and any component of `y` is uninitialized.
+#[inline(always)]
+pub unsafe fn gemv_uninit<Status, T, D1: Dim, R2: Dim, C2: Dim, D3: Dim, SA, SB, SC>(
+    status: Status,
+    y: &mut Vector<Status::Value, D1, SA>,
+    alpha: T,
+    a: &Matrix<T, R2, C2, SB>,
+    x: &Vector<T, D3, SC>,
+    beta: T,
+) where
+    Status: InitStatus<T>,
+    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    SA: RawStorageMut<Status::Value, D1>,
+    SB: RawStorage<T, R2, C2>,
+    SC: RawStorage<T, D3>,
+    ShapeConstraint: DimEq<D1, R2> + AreMultipliable<R2, C2, D3, U1>,
+{
+    let dim1 = y.nrows();
+    let (nrows2, ncols2) = a.shape();
+    let dim3 = x.nrows();
+
+    assert!(
+        ncols2 == dim3 && dim1 == nrows2,
+        "Gemv: dimensions mismatch."
+    );
+
+    if ncols2 == 0 {
+        if beta.is_zero() {
+            y.apply(|e| Status::init(e, T::zero()));
+        } else {
+            // SAFETY: this is UB if y is uninitialized.
+            y.apply(|e| *Status::assume_init_mut(e) *= beta.clone());
+        }
+        return;
+    }
+
+    // TODO: avoid bound checks.
+    let col2 = a.column(0);
+    let val = x.vget_unchecked(0).clone();
+
+    // SAFETY: this is the call that makes this method unsafe: it is UB if Status = Uninit and beta != 0.
+    axcpy_uninit(status, y, alpha.clone(), &col2, val, beta);
+
+    for j in 1..ncols2 {
+        let col2 = a.column(j);
+        let val = x.vget_unchecked(j).clone();
+
+        // SAFETY: safe because y was initialized above.
+        axcpy_uninit(status, y, alpha.clone(), &col2, val, T::one());
+    }
+}
+
+/// Computes `y = alpha * a * b + beta * y`, where `a, b, y` are matrices.
+/// `alpha` and `beta` are scalar.
+///
+/// If `beta` is zero, `y` is never read from and may be uninitialized.
+///
+/// # Safety
+/// This is UB if beta != 0 and any component of `y` is uninitialized.
+#[inline(always)]
+pub unsafe fn gemm_uninit<
+    Status,
+    T,
+    R1: Dim,
+    C1: Dim,
+    R2: Dim,
+    C2: Dim,
+    R3: Dim,
+    C3: Dim,
+    SA,
+    SB,
+    SC,
+>(
+    status: Status,
+    y: &mut Matrix<Status::Value, R1, C1, SA>,
+    alpha: T,
+    a: &Matrix<T, R2, C2, SB>,
+    b: &Matrix<T, R3, C3, SC>,
+    beta: T,
+) where
+    Status: InitStatus<T>,
+    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    SA: RawStorageMut<Status::Value, R1, C1>,
+    SB: RawStorage<T, R2, C2>,
+    SC: RawStorage<T, R3, C3>,
+    ShapeConstraint:
+        SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C3> + AreMultipliable<R2, C2, R3, C3>,
+{
+    let ncols1 = y.ncols();
+
+    #[cfg(feature = "std")]
+    {
+        // We assume large matrices will be Dynamic but small matrices static.
+        // We could use matrixmultiply for large statically-sized matrices but the performance
+        // threshold to activate it would be different from SMALL_DIM because our code optimizes
+        // better for statically-sized matrices.
+        if R1::is::<Dynamic>()
+            || C1::is::<Dynamic>()
+            || R2::is::<Dynamic>()
+            || C2::is::<Dynamic>()
+            || R3::is::<Dynamic>()
+            || C3::is::<Dynamic>()
+        {
+            // matrixmultiply can be used only if the std feature is available.
+            let nrows1 = y.nrows();
+            let (nrows2, ncols2) = a.shape();
+            let (nrows3, ncols3) = b.shape();
+
+            // Threshold determined empirically.
+            const SMALL_DIM: usize = 5;
+
+            if nrows1 > SMALL_DIM && ncols1 > SMALL_DIM && nrows2 > SMALL_DIM && ncols2 > SMALL_DIM
+            {
+                assert_eq!(
+                    ncols2, nrows3,
+                    "gemm: dimensions mismatch for multiplication."
+                );
+                assert_eq!(
+                    (nrows1, ncols1),
+                    (nrows2, ncols3),
+                    "gemm: dimensions mismatch for addition."
+                );
+
+                // NOTE: this case should never happen because we enter this
+                // codepath only when ncols2 > SMALL_DIM. Though we keep this
+                // here just in case if in the future we change the conditions to
+                // enter this codepath.
+                if ncols2 == 0 {
+                    // NOTE: we can't just always multiply by beta
+                    // because we documented the guaranty that `self` is
+                    // never read if `beta` is zero.
+                    if beta.is_zero() {
+                        y.apply(|e| Status::init(e, T::zero()));
+                    } else {
+                        // SAFETY: this is UB if Status = Uninit
+                        y.apply(|e| *Status::assume_init_mut(e) *= beta.clone());
+                    }
+                    return;
+                }
+
+                if TypeId::of::<T>() == TypeId::of::<f32>() {
+                    let (rsa, csa) = a.strides();
+                    let (rsb, csb) = b.strides();
+                    let (rsc, csc) = y.strides();
+
+                    matrixmultiply::sgemm(
+                        nrows2,
+                        ncols2,
+                        ncols3,
+                        mem::transmute_copy(&alpha),
+                        a.data.ptr() as *const f32,
+                        rsa as isize,
+                        csa as isize,
+                        b.data.ptr() as *const f32,
+                        rsb as isize,
+                        csb as isize,
+                        mem::transmute_copy(&beta),
+                        y.data.ptr_mut() as *mut f32,
+                        rsc as isize,
+                        csc as isize,
+                    );
+                    return;
+                } else if TypeId::of::<T>() == TypeId::of::<f64>() {
+                    let (rsa, csa) = a.strides();
+                    let (rsb, csb) = b.strides();
+                    let (rsc, csc) = y.strides();
+
+                    matrixmultiply::dgemm(
+                        nrows2,
+                        ncols2,
+                        ncols3,
+                        mem::transmute_copy(&alpha),
+                        a.data.ptr() as *const f64,
+                        rsa as isize,
+                        csa as isize,
+                        b.data.ptr() as *const f64,
+                        rsb as isize,
+                        csb as isize,
+                        mem::transmute_copy(&beta),
+                        y.data.ptr_mut() as *mut f64,
+                        rsc as isize,
+                        csc as isize,
+                    );
+                    return;
+                }
+            }
+        }
+    }
+
+    for j1 in 0..ncols1 {
+        // TODO: avoid bound checks.
+        // SAFETY: this is UB if Status = Uninit && beta != 0
+        gemv_uninit(
+            status,
+            &mut y.column_mut(j1),
+            alpha.clone(),
+            a,
+            &b.column(j1),
+            beta.clone(),
+        );
+    }
+}

src/base/cg.rs

@@ -45,7 +45,7 @@ where
     {
         let mut res = Self::identity();
         for i in 0..scaling.len() {
-            res[(i, i)] = scaling[i].inlined_clone();
+            res[(i, i)] = scaling[i].clone();
         }
 
         res
@@ -79,19 +79,19 @@ impl<T: RealField> Matrix3<T> {
 
     /// Creates a new homogeneous matrix that applies a scaling factor for each dimension with respect to point.
     ///
-    /// Can be used to implement "zoom_to" functionality.
+    /// Can be used to implement `zoom_to` functionality.
     #[inline]
     pub fn new_nonuniform_scaling_wrt_point(scaling: &Vector2<T>, pt: &Point2<T>) -> Self {
         let zero = T::zero();
         let one = T::one();
         Matrix3::new(
-            scaling.x,
-            zero,
-            pt.x - pt.x * scaling.x,
-            zero,
-            scaling.y,
-            pt.y - pt.y * scaling.y,
-            zero,
+            scaling.x.clone(),
+            zero.clone(),
+            pt.x.clone() - pt.x.clone() * scaling.x.clone(),
+            zero.clone(),
+            scaling.y.clone(),
+            pt.y.clone() - pt.y.clone() * scaling.y.clone(),
+            zero.clone(),
             zero,
             one,
         )
@@ -119,26 +119,26 @@ impl<T: RealField> Matrix4<T> {
 
     /// Creates a new homogeneous matrix that applies a scaling factor for each dimension with respect to point.
     ///
-    /// Can be used to implement "zoom_to" functionality.
+    /// Can be used to implement `zoom_to` functionality.
     #[inline]
     pub fn new_nonuniform_scaling_wrt_point(scaling: &Vector3<T>, pt: &Point3<T>) -> Self {
         let zero = T::zero();
         let one = T::one();
         Matrix4::new(
-            scaling.x,
-            zero,
-            zero,
-            pt.x - pt.x * scaling.x,
-            zero,
-            scaling.y,
-            zero,
-            pt.y - pt.y * scaling.y,
-            zero,
-            zero,
-            scaling.z,
-            pt.z - pt.z * scaling.z,
-            zero,
-            zero,
+            scaling.x.clone(),
+            zero.clone(),
+            zero.clone(),
+            pt.x.clone() - pt.x.clone() * scaling.x.clone(),
+            zero.clone(),
+            scaling.y.clone(),
+            zero.clone(),
+            pt.y.clone() - pt.y.clone() * scaling.y.clone(),
+            zero.clone(),
+            zero.clone(),
+            scaling.z.clone(),
+            pt.z.clone() - pt.z.clone() * scaling.z.clone(),
+            zero.clone(),
+            zero.clone(),
             zero,
             one,
         )
@@ -187,7 +187,7 @@ impl<T: RealField> Matrix4<T> {
         IsometryMatrix3::face_towards(eye, target, up).to_homogeneous()
     }
 
-    /// Deprecated: Use [Matrix4::face_towards] instead.
+    /// Deprecated: Use [`Matrix4::face_towards`] instead.
     #[deprecated(note = "renamed to `face_towards`")]
     pub fn new_observer_frame(eye: &Point3<T>, target: &Point3<T>, up: &Vector3<T>) -> Self {
         Matrix4::face_towards(eye, target, up)
@@ -336,7 +336,7 @@ impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D
     {
         for i in 0..scaling.len() {
             let mut to_scale = self.fixed_rows_mut::<1>(i);
-            to_scale *= scaling[i].inlined_clone();
+            to_scale *= scaling[i].clone();
         }
     }
 
@@ -352,7 +352,7 @@ impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D
     {
         for i in 0..scaling.len() {
             let mut to_scale = self.fixed_columns_mut::<1>(i);
-            to_scale *= scaling[i].inlined_clone();
+            to_scale *= scaling[i].clone();
         }
     }
 
@@ -366,7 +366,7 @@ impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D
     {
         for i in 0..D::dim() {
             for j in 0..D::dim() - 1 {
-                let add = shift[j].inlined_clone() * self[(D::dim() - 1, i)].inlined_clone();
+                let add = shift[j].clone() * self[(D::dim() - 1, i)].clone();
                 self[(j, i)] += add;
             }
         }
@@ -440,7 +440,7 @@ impl<T: RealField, S: Storage<T, Const<3>, Const<3>>> SquareMatrix<T, Const<3>,
         let transform = self.fixed_slice::<2, 2>(0, 0);
         let translation = self.fixed_slice::<2, 1>(0, 2);
         let normalizer = self.fixed_slice::<1, 2>(2, 0);
-        let n = normalizer.tr_dot(&pt.coords) + unsafe { *self.get_unchecked((2, 2)) };
+        let n = normalizer.tr_dot(&pt.coords) + unsafe { self.get_unchecked((2, 2)).clone() };
 
         if !n.is_zero() {
             (transform * pt + translation) / n
@@ -457,7 +457,7 @@ impl<T: RealField, S: Storage<T, Const<4>, Const<4>>> SquareMatrix<T, Const<4>,
         let transform = self.fixed_slice::<3, 3>(0, 0);
         let translation = self.fixed_slice::<3, 1>(0, 3);
         let normalizer = self.fixed_slice::<1, 3>(3, 0);
-        let n = normalizer.tr_dot(&pt.coords) + unsafe { *self.get_unchecked((3, 3)) };
+        let n = normalizer.tr_dot(&pt.coords) + unsafe { self.get_unchecked((3, 3)).clone() };
 
         if !n.is_zero() {
             (transform * pt + translation) / n

src/base/componentwise.rs

@@ -64,7 +64,7 @@ macro_rules! component_binop_impl(
             for j in 0 .. res.ncols() {
                 for i in 0 .. res.nrows() {
                     unsafe {
-                        res.get_unchecked_mut((i, j)).$op_assign(rhs.get_unchecked((i, j)).inlined_clone());
+                        res.get_unchecked_mut((i, j)).$op_assign(rhs.get_unchecked((i, j)).clone());
                     }
                 }
             }
@@ -91,7 +91,7 @@ macro_rules! component_binop_impl(
                 for j in 0 .. self.ncols() {
                     for i in 0 .. self.nrows() {
                         unsafe {
-                            let res = alpha.inlined_clone() * a.get_unchecked((i, j)).inlined_clone().$op(b.get_unchecked((i, j)).inlined_clone());
+                            let res = alpha.clone() * a.get_unchecked((i, j)).clone().$op(b.get_unchecked((i, j)).clone());
                             *self.get_unchecked_mut((i, j)) = res;
                         }
                     }
@@ -101,8 +101,8 @@ macro_rules! component_binop_impl(
                 for j in 0 .. self.ncols() {
                     for i in 0 .. self.nrows() {
                         unsafe {
-                            let res = alpha.inlined_clone() * a.get_unchecked((i, j)).inlined_clone().$op(b.get_unchecked((i, j)).inlined_clone());
-                            *self.get_unchecked_mut((i, j)) = beta.inlined_clone() * self.get_unchecked((i, j)).inlined_clone() + res;
+                            let res = alpha.clone() * a.get_unchecked((i, j)).clone().$op(b.get_unchecked((i, j)).clone());
+                            *self.get_unchecked_mut((i, j)) = beta.clone() * self.get_unchecked((i, j)).clone() + res;
                         }
                     }
                 }
@@ -124,7 +124,7 @@ macro_rules! component_binop_impl(
             for j in 0 .. self.ncols() {
                 for i in 0 .. self.nrows() {
                     unsafe {
-                        self.get_unchecked_mut((i, j)).$op_assign(rhs.get_unchecked((i, j)).inlined_clone());
+                        self.get_unchecked_mut((i, j)).$op_assign(rhs.get_unchecked((i, j)).clone());
                     }
                 }
             }
@@ -347,7 +347,7 @@ impl<T: Scalar, R1: Dim, C1: Dim, SA: Storage<T, R1, C1>> Matrix<T, R1, C1, SA>
         SA: StorageMut<T, R1, C1>,
     {
         for e in self.iter_mut() {
-            *e += rhs.inlined_clone()
+            *e += rhs.clone()
         }
     }
 }

src/base/constraint.rs

@@ -3,6 +3,7 @@
 use crate::base::dimension::{Dim, DimName, Dynamic};
 
 /// A type used in `where` clauses for enforcing constraints.
+#[derive(Copy, Clone, Debug)]
 pub struct ShapeConstraint;
 
 /// Constraints `C1` and `R2` to be equivalent.

src/base/construction.rs

@@ -14,33 +14,32 @@ use rand::{
 };
 
 use std::iter;
-use std::mem;
 use typenum::{self, Cmp, Greater};
 
 use simba::scalar::{ClosedAdd, ClosedMul};
 
 use crate::base::allocator::Allocator;
 use crate::base::dimension::{Dim, DimName, Dynamic, ToTypenum};
-use crate::base::storage::Storage;
+use crate::base::storage::RawStorage;
 use crate::base::{
     ArrayStorage, Const, DefaultAllocator, Matrix, OMatrix, OVector, Scalar, Unit, Vector,
 };
+use crate::UninitMatrix;
+use std::mem::MaybeUninit;
 
-/// When "no_unsound_assume_init" is enabled, expands to `unimplemented!()` instead of `new_uninitialized_generic().assume_init()`.
-/// Intended as a placeholder, each callsite should be refactored to use uninitialized memory soundly
-#[macro_export]
-macro_rules! unimplemented_or_uninitialized_generic {
-    ($nrows:expr, $ncols:expr) => {{
-        #[cfg(feature="no_unsound_assume_init")] {
-            // Some of the call sites need the number of rows and columns from this to infer a type, so
-            // uninitialized memory is used to infer the type, as `T: Zero` isn't available at all callsites.
-            // This may technically still be UB even though the assume_init is dead code, but all callsites should be fixed before #556 is closed.
-            let typeinference_helper = crate::base::Matrix::new_uninitialized_generic($nrows, $ncols);
-            unimplemented!();
-            typeinference_helper.assume_init()
+impl<T: Scalar, R: Dim, C: Dim> UninitMatrix<T, R, C>
+where
+    DefaultAllocator: Allocator<T, R, C>,
+{
+    /// Builds a matrix with uninitialized elements of type `MaybeUninit<T>`.
+    #[inline(always)]
+    pub fn uninit(nrows: R, ncols: C) -> Self {
+        // SAFETY: this is OK because the dimension automatically match the storage
+        //         because we are building an owned storage.
+        unsafe {
+            Self::from_data_statically_unchecked(DefaultAllocator::allocate_uninit(nrows, ncols))
         }
-        #[cfg(not(feature="no_unsound_assume_init"))] { crate::base::Matrix::new_uninitialized_generic($nrows, $ncols).assume_init() }
-    }}
+    }
 }
 
 /// # Generic constructors
@@ -53,16 +52,6 @@ impl<T: Scalar, R: Dim, C: Dim> OMatrix<T, R, C>
 where
     DefaultAllocator: Allocator<T, R, C>,
 {
-    /// Creates a new uninitialized matrix.
-    ///
-    /// # Safety
-    /// If the matrix has a compile-time dimension, this panics
-    /// if `nrows != R::to_usize()` or `ncols != C::to_usize()`.
-    #[inline]
-    pub unsafe fn new_uninitialized_generic(nrows: R, ncols: C) -> mem::MaybeUninit<Self> {
-        Self::from_uninitialized_data(DefaultAllocator::allocate_uninitialized(nrows, ncols))
-    }
-
     /// Creates a matrix with all its elements set to `elem`.
     #[inline]
     pub fn from_element_generic(nrows: R, ncols: C, elem: T) -> Self {
@@ -109,16 +98,19 @@ where
             "Matrix init. error: the slice did not contain the right number of elements."
         );
 
-        let mut res = unsafe { crate::unimplemented_or_uninitialized_generic!(nrows, ncols) };
+        let mut res = Matrix::uninit(nrows, ncols);
         let mut iter = slice.iter();
 
-        for i in 0..nrows.value() {
-            for j in 0..ncols.value() {
-                unsafe { *res.get_unchecked_mut((i, j)) = iter.next().unwrap().inlined_clone() }
+        unsafe {
+            for i in 0..nrows.value() {
+                for j in 0..ncols.value() {
+                    *res.get_unchecked_mut((i, j)) = MaybeUninit::new(iter.next().unwrap().clone())
+                }
             }
-        }
 
-        res
+            // SAFETY: the result has been fully initialized above.
+            res.assume_init()
+        }
     }
 
     /// Creates a matrix with its elements filled with the components provided by a slice. The
@@ -135,15 +127,18 @@ where
     where
         F: FnMut(usize, usize) -> T,
     {
-        let mut res: Self = unsafe { crate::unimplemented_or_uninitialized_generic!(nrows, ncols) };
+        let mut res = Matrix::uninit(nrows, ncols);
 
-        for j in 0..ncols.value() {
-            for i in 0..nrows.value() {
-                unsafe { *res.get_unchecked_mut((i, j)) = f(i, j) }
+        unsafe {
+            for j in 0..ncols.value() {
+                for i in 0..nrows.value() {
+                    *res.get_unchecked_mut((i, j)) = MaybeUninit::new(f(i, j));
+                }
             }
-        }
 
-        res
+            // SAFETY: the result has been fully initialized above.
+            res.assume_init()
+        }
     }
 
     /// Creates a new identity matrix.
@@ -170,7 +165,7 @@ where
         let mut res = Self::zeros_generic(nrows, ncols);
 
         for i in 0..crate::min(nrows.value(), ncols.value()) {
-            unsafe { *res.get_unchecked_mut((i, i)) = elt.inlined_clone() }
+            unsafe { *res.get_unchecked_mut((i, i)) = elt.clone() }
         }
 
         res
@@ -192,7 +187,7 @@ where
         );
 
         for (i, elt) in elts.iter().enumerate() {
-            unsafe { *res.get_unchecked_mut((i, i)) = elt.inlined_clone() }
+            unsafe { *res.get_unchecked_mut((i, i)) = elt.clone() }
         }
 
         res
@@ -217,7 +212,7 @@ where
     #[inline]
     pub fn from_rows<SB>(rows: &[Matrix<T, Const<1>, C, SB>]) -> Self
     where
-        SB: Storage<T, Const<1>, C>,
+        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());
@@ -236,7 +231,7 @@ where
 
         // TODO: optimize that.
         Self::from_fn_generic(R::from_usize(nrows), C::from_usize(ncols), |i, j| {
-            rows[i][(0, j)].inlined_clone()
+            rows[i][(0, j)].clone()
         })
     }
 
@@ -259,7 +254,7 @@ where
     #[inline]
     pub fn from_columns<SB>(columns: &[Vector<T, R, SB>]) -> Self
     where
-        SB: Storage<T, R>,
+        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());
@@ -278,7 +273,7 @@ where
 
         // TODO: optimize that.
         Self::from_fn_generic(R::from_usize(nrows), C::from_usize(ncols), |i, j| {
-            columns[j][i].inlined_clone()
+            columns[j][i].clone()
         })
     }
 
@@ -353,16 +348,16 @@ where
     ///         dm[(2, 0)] == 0.0 && dm[(2, 1)] == 0.0 && dm[(2, 2)] == 3.0);
     /// ```
     #[inline]
-    pub fn from_diagonal<SB: Storage<T, D>>(diag: &Vector<T, D, SB>) -> Self
+    pub fn from_diagonal<SB: RawStorage<T, D>>(diag: &Vector<T, D, SB>) -> Self
     where
         T: Zero,
     {
-        let (dim, _) = diag.data.shape();
+        let (dim, _) = diag.shape_generic();
         let mut res = Self::zeros_generic(dim, dim);
 
         for i in 0..diag.len() {
             unsafe {
-                *res.get_unchecked_mut((i, i)) = diag.vget_unchecked(i).inlined_clone();
+                *res.get_unchecked_mut((i, i)) = diag.vget_unchecked(i).clone();
             }
         }
 
@@ -377,12 +372,6 @@ where
  */
 macro_rules! impl_constructors(
     ($($Dims: ty),*; $(=> $DimIdent: ident: $DimBound: ident),*; $($gargs: expr),*; $($args: ident),*) => {
-        /// Creates a new uninitialized matrix or vector.
-        #[inline]
-        pub unsafe fn new_uninitialized($($args: usize),*) -> mem::MaybeUninit<Self> {
-            Self::new_uninitialized_generic($($gargs),*)
-        }
-
         /// Creates a matrix or vector with all its elements set to `elem`.
         ///
         /// # Example
@@ -888,19 +877,19 @@ macro_rules! transpose_array(
         [$([$a]),*]
     };
     [$($a: ident),*; $($b: ident),*;] => {
-        [$([$a, $b]),*];
+        [$([$a, $b]),*]
     };
     [$($a: ident),*; $($b: ident),*; $($c: ident),*;] => {
-        [$([$a, $b, $c]),*];
+        [$([$a, $b, $c]),*]
     };
     [$($a: ident),*; $($b: ident),*; $($c: ident),*; $($d: ident),*;] => {
-        [$([$a, $b, $c, $d]),*];
+        [$([$a, $b, $c, $d]),*]
     };
     [$($a: ident),*; $($b: ident),*; $($c: ident),*; $($d: ident),*; $($e: ident),*;] => {
-        [$([$a, $b, $c, $d, $e]),*];
+        [$([$a, $b, $c, $d, $e]),*]
     };
     [$($a: ident),*; $($b: ident),*; $($c: ident),*; $($d: ident),*; $($e: ident),*; $($f: ident),*;] => {
-        [$([$a, $b, $c, $d, $e, $f]),*];
+        [$([$a, $b, $c, $d, $e, $f]),*]
     };
 );
 

src/base/conversion.rs

@@ -14,7 +14,7 @@ use crate::base::dimension::{
     Const, Dim, DimName, U1, U10, U11, U12, U13, U14, U15, U16, U2, U3, U4, U5, U6, U7, U8, U9,
 };
 use crate::base::iter::{MatrixIter, MatrixIterMut};
-use crate::base::storage::{ContiguousStorage, ContiguousStorageMut, Storage, StorageMut};
+use crate::base::storage::{IsContiguous, RawStorage, RawStorageMut};
 use crate::base::{
     ArrayStorage, DVectorSlice, DVectorSliceMut, DefaultAllocator, Matrix, MatrixSlice,
     MatrixSliceMut, OMatrix, Scalar,
@@ -24,6 +24,7 @@ use crate::base::{DVector, VecStorage};
 use crate::base::{SliceStorage, SliceStorageMut};
 use crate::constraint::DimEq;
 use crate::{IsNotStaticOne, RowSVector, SMatrix, SVector};
+use std::mem::MaybeUninit;
 
 // TODO: too bad this won't work for slice conversions.
 impl<T1, T2, R1, C1, R2, C2> SubsetOf<OMatrix<T2, R2, C2>> for OMatrix<T1, R1, C1>
@@ -43,18 +44,20 @@ where
         let (nrows, ncols) = self.shape();
         let nrows2 = R2::from_usize(nrows);
         let ncols2 = C2::from_usize(ncols);
+        let mut res = Matrix::uninit(nrows2, ncols2);
 
-        let mut res: OMatrix<T2, R2, C2> =
-            unsafe { crate::unimplemented_or_uninitialized_generic!(nrows2, ncols2) };
         for i in 0..nrows {
             for j in 0..ncols {
+                // Safety: all indices are in range.
                 unsafe {
-                    *res.get_unchecked_mut((i, j)) = T2::from_subset(self.get_unchecked((i, j)))
+                    *res.get_unchecked_mut((i, j)) =
+                        MaybeUninit::new(T2::from_subset(self.get_unchecked((i, j))));
                 }
             }
         }
 
-        res
+        // Safety: res is now fully initialized.
+        unsafe { res.assume_init() }
     }
 
     #[inline]
@@ -67,21 +70,25 @@ where
         let (nrows2, ncols2) = m.shape();
         let nrows = R1::from_usize(nrows2);
         let ncols = C1::from_usize(ncols2);
+        let mut res = Matrix::uninit(nrows, ncols);
 
-        let mut res: Self = unsafe { crate::unimplemented_or_uninitialized_generic!(nrows, ncols) };
         for i in 0..nrows2 {
             for j in 0..ncols2 {
+                // Safety: all indices are in range.
                 unsafe {
-                    *res.get_unchecked_mut((i, j)) = m.get_unchecked((i, j)).to_subset_unchecked()
+                    *res.get_unchecked_mut((i, j)) =
+                        MaybeUninit::new(m.get_unchecked((i, j)).to_subset_unchecked())
                 }
             }
         }
 
-        res
+        unsafe { res.assume_init() }
     }
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> IntoIterator for &'a Matrix<T, R, C, S> {
+impl<'a, T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> IntoIterator
+    for &'a Matrix<T, R, C, S>
+{
     type Item = &'a T;
     type IntoIter = MatrixIter<'a, T, R, C, S>;
 
@@ -91,7 +98,7 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> IntoIterator for &'a Ma
     }
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> IntoIterator
+impl<'a, T: Scalar, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> IntoIterator
     for &'a mut Matrix<T, R, C, S>
 {
     type Item = &'a mut T;
@@ -142,9 +149,10 @@ macro_rules! impl_from_into_asref_1D(
     ($(($NRows: ident, $NCols: ident) => $SZ: expr);* $(;)*) => {$(
         impl<T, S> AsRef<[T; $SZ]> for Matrix<T, $NRows, $NCols, S>
         where T: Scalar,
-              S: ContiguousStorage<T, $NRows, $NCols> {
+              S: RawStorage<T, $NRows, $NCols> + IsContiguous {
             #[inline]
             fn as_ref(&self) -> &[T; $SZ] {
+                // Safety: this is OK thanks to the IsContiguous trait.
                 unsafe {
                     &*(self.data.ptr() as *const [T; $SZ])
                 }
@@ -153,9 +161,10 @@ macro_rules! impl_from_into_asref_1D(
 
         impl<T, S> AsMut<[T; $SZ]> for Matrix<T, $NRows, $NCols, S>
         where T: Scalar,
-              S: ContiguousStorageMut<T, $NRows, $NCols> {
+              S: RawStorageMut<T, $NRows, $NCols> + IsContiguous {
             #[inline]
             fn as_mut(&mut self) -> &mut [T; $SZ] {
+                // Safety: this is OK thanks to the IsContiguous trait.
                 unsafe {
                     &mut *(self.data.ptr_mut() as *mut [T; $SZ])
                 }
@@ -201,9 +210,10 @@ macro_rules! impl_from_into_asref_borrow_2D(
         $Ref:ident.$ref:ident(), $Mut:ident.$mut:ident()
     ) => {
         impl<T: Scalar, S> $Ref<[[T; $SZRows]; $SZCols]> for Matrix<T, $NRows, $NCols, S>
-        where S: ContiguousStorage<T, $NRows, $NCols> {
+        where S: RawStorage<T, $NRows, $NCols> + IsContiguous {
             #[inline]
             fn $ref(&self) -> &[[T; $SZRows]; $SZCols] {
+                // Safety: OK thanks to the IsContiguous trait.
                 unsafe {
                     &*(self.data.ptr() as *const [[T; $SZRows]; $SZCols])
                 }
@@ -211,9 +221,10 @@ macro_rules! impl_from_into_asref_borrow_2D(
         }
 
         impl<T: Scalar, S> $Mut<[[T; $SZRows]; $SZCols]> for Matrix<T, $NRows, $NCols, S>
-        where S: ContiguousStorageMut<T, $NRows, $NCols> {
+        where S: RawStorageMut<T, $NRows, $NCols> + IsContiguous {
             #[inline]
             fn $mut(&mut self) -> &mut [[T; $SZRows]; $SZCols] {
+                // Safety: OK thanks to the IsContiguous trait.
                 unsafe {
                     &mut *(self.data.ptr_mut() as *mut [[T; $SZRows]; $SZCols])
                 }
@@ -333,14 +344,14 @@ where
     CSlice: Dim,
     RStride: Dim,
     CStride: Dim,
-    S: Storage<T, R, C>,
+    S: RawStorage<T, R, C>,
     ShapeConstraint: DimEq<R, RSlice>
         + DimEq<C, CSlice>
         + DimEq<RStride, S::RStride>
         + DimEq<CStride, S::CStride>,
 {
     fn from(m: &'a Matrix<T, R, C, S>) -> Self {
-        let (row, col) = m.data.shape();
+        let (row, col) = m.shape_generic();
         let row_slice = RSlice::from_usize(row.value());
         let col_slice = CSlice::from_usize(col.value());
 
@@ -370,14 +381,14 @@ where
     CSlice: Dim,
     RStride: Dim,
     CStride: Dim,
-    S: Storage<T, R, C>,
+    S: RawStorage<T, R, C>,
     ShapeConstraint: DimEq<R, RSlice>
         + DimEq<C, CSlice>
         + DimEq<RStride, S::RStride>
         + DimEq<CStride, S::CStride>,
 {
     fn from(m: &'a mut Matrix<T, R, C, S>) -> Self {
-        let (row, col) = m.data.shape();
+        let (row, col) = m.shape_generic();
         let row_slice = RSlice::from_usize(row.value());
         let col_slice = CSlice::from_usize(col.value());
 
@@ -407,14 +418,14 @@ where
     CSlice: Dim,
     RStride: Dim,
     CStride: Dim,
-    S: StorageMut<T, R, C>,
+    S: RawStorageMut<T, R, C>,
     ShapeConstraint: DimEq<R, RSlice>
         + DimEq<C, CSlice>
         + DimEq<RStride, S::RStride>
         + DimEq<CStride, S::CStride>,
 {
     fn from(m: &'a mut Matrix<T, R, C, S>) -> Self {
-        let (row, col) = m.data.shape();
+        let (row, col) = m.shape_generic();
         let row_slice = RSlice::from_usize(row.value());
         let col_slice = CSlice::from_usize(col.value());
 
@@ -442,7 +453,7 @@ impl<'a, T: Scalar> From<Vec<T>> for DVector<T> {
     }
 }
 
-impl<'a, T: Scalar + Copy, R: Dim, C: Dim, S: ContiguousStorage<T, R, C>>
+impl<'a, T: Scalar + Copy, R: Dim, C: Dim, S: RawStorage<T, R, C> + IsContiguous>
     From<&'a Matrix<T, R, C, S>> for &'a [T]
 {
     #[inline]
@@ -451,7 +462,7 @@ impl<'a, T: Scalar + Copy, R: Dim, C: Dim, S: ContiguousStorage<T, R, C>>
     }
 }
 
-impl<'a, T: Scalar + Copy, R: Dim, C: Dim, S: ContiguousStorageMut<T, R, C>>
+impl<'a, T: Scalar + Copy, R: Dim, C: Dim, S: RawStorageMut<T, R, C> + IsContiguous>
     From<&'a mut Matrix<T, R, C, S>> for &'a mut [T]
 {
     #[inline]
@@ -495,14 +506,10 @@ where
 {
     #[inline]
     fn from(arr: [OMatrix<T::Element, R, C>; 2]) -> Self {
-        let (nrows, ncols) = arr[0].data.shape();
+        let (nrows, ncols) = arr[0].shape_generic();
 
         Self::from_fn_generic(nrows, ncols, |i, j| {
-            [
-                arr[0][(i, j)].inlined_clone(),
-                arr[1][(i, j)].inlined_clone(),
-            ]
-            .into()
+            [arr[0][(i, j)].clone(), arr[1][(i, j)].clone()].into()
         })
     }
 }
@@ -516,14 +523,14 @@ where
 {
     #[inline]
     fn from(arr: [OMatrix<T::Element, R, C>; 4]) -> Self {
-        let (nrows, ncols) = arr[0].data.shape();
+        let (nrows, ncols) = arr[0].shape_generic();
 
         Self::from_fn_generic(nrows, ncols, |i, j| {
             [
-                arr[0][(i, j)].inlined_clone(),
-                arr[1][(i, j)].inlined_clone(),
-                arr[2][(i, j)].inlined_clone(),
-                arr[3][(i, j)].inlined_clone(),
+                arr[0][(i, j)].clone(),
+                arr[1][(i, j)].clone(),
+                arr[2][(i, j)].clone(),
+                arr[3][(i, j)].clone(),
             ]
             .into()
         })
@@ -539,18 +546,18 @@ where
 {
     #[inline]
     fn from(arr: [OMatrix<T::Element, R, C>; 8]) -> Self {
-        let (nrows, ncols) = arr[0].data.shape();
+        let (nrows, ncols) = arr[0].shape_generic();
 
         Self::from_fn_generic(nrows, ncols, |i, j| {
             [
-                arr[0][(i, j)].inlined_clone(),
-                arr[1][(i, j)].inlined_clone(),
-                arr[2][(i, j)].inlined_clone(),
-                arr[3][(i, j)].inlined_clone(),
-                arr[4][(i, j)].inlined_clone(),
-                arr[5][(i, j)].inlined_clone(),
-                arr[6][(i, j)].inlined_clone(),
-                arr[7][(i, j)].inlined_clone(),
+                arr[0][(i, j)].clone(),
+                arr[1][(i, j)].clone(),
+                arr[2][(i, j)].clone(),
+                arr[3][(i, j)].clone(),
+                arr[4][(i, j)].clone(),
+                arr[5][(i, j)].clone(),
+                arr[6][(i, j)].clone(),
+                arr[7][(i, j)].clone(),
             ]
             .into()
         })
@@ -565,26 +572,26 @@ where
     DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
 {
     fn from(arr: [OMatrix<T::Element, R, C>; 16]) -> Self {
-        let (nrows, ncols) = arr[0].data.shape();
+        let (nrows, ncols) = arr[0].shape_generic();
 
         Self::from_fn_generic(nrows, ncols, |i, j| {
             [
-                arr[0][(i, j)].inlined_clone(),
-                arr[1][(i, j)].inlined_clone(),
-                arr[2][(i, j)].inlined_clone(),
-                arr[3][(i, j)].inlined_clone(),
-                arr[4][(i, j)].inlined_clone(),
-                arr[5][(i, j)].inlined_clone(),
-                arr[6][(i, j)].inlined_clone(),
-                arr[7][(i, j)].inlined_clone(),
-                arr[8][(i, j)].inlined_clone(),
-                arr[9][(i, j)].inlined_clone(),
-                arr[10][(i, j)].inlined_clone(),
-                arr[11][(i, j)].inlined_clone(),
-                arr[12][(i, j)].inlined_clone(),
-                arr[13][(i, j)].inlined_clone(),
-                arr[14][(i, j)].inlined_clone(),
-                arr[15][(i, j)].inlined_clone(),
+                arr[0][(i, j)].clone(),
+                arr[1][(i, j)].clone(),
+                arr[2][(i, j)].clone(),
+                arr[3][(i, j)].clone(),
+                arr[4][(i, j)].clone(),
+                arr[5][(i, j)].clone(),
+                arr[6][(i, j)].clone(),
+                arr[7][(i, j)].clone(),
+                arr[8][(i, j)].clone(),
+                arr[9][(i, j)].clone(),
+                arr[10][(i, j)].clone(),
+                arr[11][(i, j)].clone(),
+                arr[12][(i, j)].clone(),
+                arr[13][(i, j)].clone(),
+                arr[14][(i, j)].clone(),
+                arr[15][(i, j)].clone(),
             ]
             .into()
         })

src/base/coordinates.rs

@@ -7,7 +7,7 @@
 use std::ops::{Deref, DerefMut};
 
 use crate::base::dimension::{U1, U2, U3, U4, U5, U6};
-use crate::base::storage::{ContiguousStorage, ContiguousStorageMut};
+use crate::base::storage::{IsContiguous, RawStorage, RawStorageMut};
 use crate::base::{Matrix, Scalar};
 
 /*
@@ -32,19 +32,21 @@ macro_rules! coords_impl(
 macro_rules! deref_impl(
     ($R: ty, $C: ty; $Target: ident) => {
         impl<T: Scalar, S> Deref for Matrix<T, $R, $C, S>
-            where S: ContiguousStorage<T, $R, $C> {
+            where S: RawStorage<T, $R, $C> + IsContiguous {
             type Target = $Target<T>;
 
             #[inline]
             fn deref(&self) -> &Self::Target {
+                // Safety: this is OK because of the IsContiguous trait.
                 unsafe { &*(self.data.ptr() as *const Self::Target) }
             }
         }
 
         impl<T: Scalar, S> DerefMut for Matrix<T, $R, $C, S>
-            where S: ContiguousStorageMut<T, $R, $C> {
+            where S: RawStorageMut<T, $R, $C> + IsContiguous {
             #[inline]
             fn deref_mut(&mut self) -> &mut Self::Target {
+                // Safety: this is OK because of the IsContiguous trait.
                 unsafe { &mut *(self.data.ptr_mut() as *mut Self::Target) }
             }
         }

src/base/default_allocator.rs

@@ -4,7 +4,6 @@
 //! heap-allocated buffers for matrices with at least one dimension unknown at compile-time.
 
 use std::cmp;
-use std::mem;
 use std::ptr;
 
 #[cfg(all(feature = "alloc", not(feature = "std")))]
@@ -16,10 +15,11 @@ use crate::base::array_storage::ArrayStorage;
 #[cfg(any(feature = "alloc", feature = "std"))]
 use crate::base::dimension::Dynamic;
 use crate::base::dimension::{Dim, DimName};
-use crate::base::storage::{ContiguousStorageMut, Storage, StorageMut};
+use crate::base::storage::{RawStorage, RawStorageMut};
 #[cfg(any(feature = "std", feature = "alloc"))]
 use crate::base::vec_storage::VecStorage;
 use crate::base::Scalar;
+use std::mem::{ManuallyDrop, MaybeUninit};
 
 /*
  *
@@ -28,6 +28,7 @@ use crate::base::Scalar;
  */
 /// An allocator based on `GenericArray` and `VecStorage` for statically-sized and dynamically-sized
 /// matrices respectively.
+#[derive(Copy, Clone, Debug)]
 pub struct DefaultAllocator;
 
 // Static - Static
@@ -35,10 +36,23 @@ 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>;
 
-    #[inline]
-    unsafe fn allocate_uninitialized(_: Const<R>, _: Const<C>) -> mem::MaybeUninit<Self::Buffer> {
-        mem::MaybeUninit::<Self::Buffer>::uninit()
+    #[inline(always)]
+    fn allocate_uninit(_: 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> {
+        // Safety:
+        // * The caller guarantees that all elements of the array are initialized
+        // * `MaybeUninit<T>` and T are guaranteed to have the same layout
+        // * `MaybeUninit` does not drop, so there are no double-frees
+        // And thus the conversion is safe
+        ArrayStorage((&uninit as *const _ as *const [_; C]).read())
     }
 
     #[inline]
@@ -47,14 +61,13 @@ impl<T: Scalar, const R: usize, const C: usize> Allocator<T, Const<R>, Const<C>>
         ncols: Const<C>,
         iter: I,
     ) -> Self::Buffer {
-        #[cfg(feature = "no_unsound_assume_init")]
-        let mut res: Self::Buffer = unimplemented!();
-        #[cfg(not(feature = "no_unsound_assume_init"))]
-        let mut res = unsafe { Self::allocate_uninitialized(nrows, ncols).assume_init() };
+        let mut res = Self::allocate_uninit(nrows, ncols);
         let mut count = 0;
 
-        for (res, e) in res.as_mut_slice().iter_mut().zip(iter.into_iter()) {
-            *res = e;
+        // Safety: conversion to a slice is OK because the Buffer is known to be contiguous.
+        let res_slice = unsafe { res.as_mut_slice_unchecked() };
+        for (res, e) in res_slice.iter_mut().zip(iter.into_iter()) {
+            *res = MaybeUninit::new(e);
             count += 1;
         }
 
@@ -63,7 +76,9 @@ impl<T: Scalar, const R: usize, const C: usize> Allocator<T, Const<R>, Const<C>>
             "Matrix init. from iterator: iterator not long enough."
         );
 
-        res
+        // 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) }
     }
 }
 
@@ -72,15 +87,32 @@ impl<T: Scalar, const R: usize, const C: usize> Allocator<T, Const<R>, Const<C>>
 #[cfg(any(feature = "std", feature = "alloc"))]
 impl<T: Scalar, C: Dim> Allocator<T, Dynamic, C> for DefaultAllocator {
     type Buffer = VecStorage<T, Dynamic, C>;
+    type BufferUninit = VecStorage<MaybeUninit<T>, Dynamic, C>;
 
     #[inline]
-    unsafe fn allocate_uninitialized(nrows: Dynamic, ncols: C) -> mem::MaybeUninit<Self::Buffer> {
-        let mut res = Vec::new();
+    fn allocate_uninit(nrows: Dynamic, ncols: C) -> VecStorage<MaybeUninit<T>, Dynamic, C> {
+        let mut data = Vec::new();
         let length = nrows.value() * ncols.value();
-        res.reserve_exact(length);
-        res.set_len(length);
+        data.reserve_exact(length);
+        data.resize_with(length, MaybeUninit::uninit);
+        VecStorage::new(nrows, ncols, data)
+    }
 
-        mem::MaybeUninit::new(VecStorage::new(nrows, ncols, res))
+    #[inline]
+    unsafe fn assume_init(
+        uninit: VecStorage<MaybeUninit<T>, Dynamic, C>,
+    ) -> VecStorage<T, Dynamic, C> {
+        // Avoids a double-drop.
+        let (nrows, ncols) = uninit.shape();
+        let vec: Vec<_> = uninit.into();
+        let mut md = ManuallyDrop::new(vec);
+
+        // Safety:
+        // - MaybeUninit<T> has the same alignment and layout as T.
+        // - The length and capacity come from a valid vector.
+        let new_data = Vec::from_raw_parts(md.as_mut_ptr() as *mut _, md.len(), md.capacity());
+
+        VecStorage::new(nrows, ncols, new_data)
     }
 
     #[inline]
@@ -102,15 +134,33 @@ impl<T: Scalar, C: Dim> Allocator<T, Dynamic, C> for DefaultAllocator {
 #[cfg(any(feature = "std", feature = "alloc"))]
 impl<T: Scalar, R: DimName> Allocator<T, R, Dynamic> for DefaultAllocator {
     type Buffer = VecStorage<T, R, Dynamic>;
+    type BufferUninit = VecStorage<MaybeUninit<T>, R, Dynamic>;
 
     #[inline]
-    unsafe fn allocate_uninitialized(nrows: R, ncols: Dynamic) -> mem::MaybeUninit<Self::Buffer> {
-        let mut res = Vec::new();
+    fn allocate_uninit(nrows: R, ncols: Dynamic) -> VecStorage<MaybeUninit<T>, R, Dynamic> {
+        let mut data = Vec::new();
         let length = nrows.value() * ncols.value();
-        res.reserve_exact(length);
-        res.set_len(length);
+        data.reserve_exact(length);
+        data.resize_with(length, MaybeUninit::uninit);
 
-        mem::MaybeUninit::new(VecStorage::new(nrows, ncols, res))
+        VecStorage::new(nrows, ncols, data)
+    }
+
+    #[inline]
+    unsafe fn assume_init(
+        uninit: VecStorage<MaybeUninit<T>, R, Dynamic>,
+    ) -> VecStorage<T, R, Dynamic> {
+        // Avoids a double-drop.
+        let (nrows, ncols) = uninit.shape();
+        let vec: Vec<_> = uninit.into();
+        let mut md = ManuallyDrop::new(vec);
+
+        // Safety:
+        // - MaybeUninit<T> has the same alignment and layout as T.
+        // - The length and capacity come from a valid vector.
+        let new_data = Vec::from_raw_parts(md.as_mut_ptr() as *mut _, md.len(), md.capacity());
+
+        VecStorage::new(nrows, ncols, new_data)
     }
 
     #[inline]
@@ -145,20 +195,21 @@ where
     unsafe fn reallocate_copy(
         rto: Const<RTO>,
         cto: Const<CTO>,
-        buf: <Self as Allocator<T, RFrom, CFrom>>::Buffer,
-    ) -> ArrayStorage<T, RTO, CTO> {
-        #[cfg(feature = "no_unsound_assume_init")]
-        let mut res: ArrayStorage<T, RTO, CTO> = unimplemented!();
-        #[cfg(not(feature = "no_unsound_assume_init"))]
-        let mut res =
-            <Self as Allocator<T, Const<RTO>, Const<CTO>>>::allocate_uninitialized(rto, cto)
-                .assume_init();
+        mut buf: <Self as Allocator<T, RFrom, CFrom>>::Buffer,
+    ) -> ArrayStorage<MaybeUninit<T>, RTO, CTO> {
+        let mut res = <Self as Allocator<T, Const<RTO>, Const<CTO>>>::allocate_uninit(rto, cto);
 
         let (rfrom, cfrom) = buf.shape();
 
         let len_from = rfrom.value() * cfrom.value();
         let len_to = rto.value() * cto.value();
-        ptr::copy_nonoverlapping(buf.ptr(), res.ptr_mut(), cmp::min(len_from, len_to));
+        let len_copied = cmp::min(len_from, len_to);
+        ptr::copy_nonoverlapping(buf.ptr(), res.ptr_mut() as *mut T, len_copied);
+
+        // 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);
 
         res
     }
@@ -175,19 +226,21 @@ where
     unsafe fn reallocate_copy(
         rto: Dynamic,
         cto: CTo,
-        buf: ArrayStorage<T, RFROM, CFROM>,
-    ) -> VecStorage<T, Dynamic, CTo> {
-        #[cfg(feature = "no_unsound_assume_init")]
-        let mut res: VecStorage<T, Dynamic, CTo> = unimplemented!();
-        #[cfg(not(feature = "no_unsound_assume_init"))]
-        let mut res =
-            <Self as Allocator<T, Dynamic, CTo>>::allocate_uninitialized(rto, cto).assume_init();
+        mut buf: ArrayStorage<T, RFROM, CFROM>,
+    ) -> VecStorage<MaybeUninit<T>, Dynamic, CTo> {
+        let mut res = <Self as Allocator<T, Dynamic, CTo>>::allocate_uninit(rto, cto);
 
         let (rfrom, cfrom) = buf.shape();
 
         let len_from = rfrom.value() * cfrom.value();
         let len_to = rto.value() * cto.value();
-        ptr::copy_nonoverlapping(buf.ptr(), res.ptr_mut(), cmp::min(len_from, len_to));
+        let len_copied = cmp::min(len_from, len_to);
+        ptr::copy_nonoverlapping(buf.ptr(), res.ptr_mut() as *mut T, len_copied);
+
+        // 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);
 
         res
     }
@@ -204,19 +257,21 @@ where
     unsafe fn reallocate_copy(
         rto: RTo,
         cto: Dynamic,
-        buf: ArrayStorage<T, RFROM, CFROM>,
-    ) -> VecStorage<T, RTo, Dynamic> {
-        #[cfg(feature = "no_unsound_assume_init")]
-        let mut res: VecStorage<T, RTo, Dynamic> = unimplemented!();
-        #[cfg(not(feature = "no_unsound_assume_init"))]
-        let mut res =
-            <Self as Allocator<T, RTo, Dynamic>>::allocate_uninitialized(rto, cto).assume_init();
+        mut buf: ArrayStorage<T, RFROM, CFROM>,
+    ) -> VecStorage<MaybeUninit<T>, RTo, Dynamic> {
+        let mut res = <Self as Allocator<T, RTo, Dynamic>>::allocate_uninit(rto, cto);
 
         let (rfrom, cfrom) = buf.shape();
 
         let len_from = rfrom.value() * cfrom.value();
         let len_to = rto.value() * cto.value();
-        ptr::copy_nonoverlapping(buf.ptr(), res.ptr_mut(), cmp::min(len_from, len_to));
+        let len_copied = cmp::min(len_from, len_to);
+        ptr::copy_nonoverlapping(buf.ptr(), res.ptr_mut() as *mut T, len_copied);
+
+        // 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);
 
         res
     }
@@ -232,7 +287,7 @@ impl<T: Scalar, CFrom: Dim, CTo: Dim> Reallocator<T, Dynamic, CFrom, Dynamic, CT
         rto: Dynamic,
         cto: CTo,
         buf: VecStorage<T, Dynamic, CFrom>,
-    ) -> VecStorage<T, Dynamic, CTo> {
+    ) -> VecStorage<MaybeUninit<T>, Dynamic, CTo> {
         let new_buf = buf.resize(rto.value() * cto.value());
         VecStorage::new(rto, cto, new_buf)
     }
@@ -247,7 +302,7 @@ impl<T: Scalar, CFrom: Dim, RTo: DimName> Reallocator<T, Dynamic, CFrom, RTo, Dy
         rto: RTo,
         cto: Dynamic,
         buf: VecStorage<T, Dynamic, CFrom>,
-    ) -> VecStorage<T, RTo, Dynamic> {
+    ) -> VecStorage<MaybeUninit<T>, RTo, Dynamic> {
         let new_buf = buf.resize(rto.value() * cto.value());
         VecStorage::new(rto, cto, new_buf)
     }
@@ -262,7 +317,7 @@ impl<T: Scalar, RFrom: DimName, CTo: Dim> Reallocator<T, RFrom, Dynamic, Dynamic
         rto: Dynamic,
         cto: CTo,
         buf: VecStorage<T, RFrom, Dynamic>,
-    ) -> VecStorage<T, Dynamic, CTo> {
+    ) -> VecStorage<MaybeUninit<T>, Dynamic, CTo> {
         let new_buf = buf.resize(rto.value() * cto.value());
         VecStorage::new(rto, cto, new_buf)
     }
@@ -277,7 +332,7 @@ impl<T: Scalar, RFrom: DimName, RTo: DimName> Reallocator<T, RFrom, Dynamic, RTo
         rto: RTo,
         cto: Dynamic,
         buf: VecStorage<T, RFrom, Dynamic>,
-    ) -> VecStorage<T, RTo, Dynamic> {
+    ) -> VecStorage<MaybeUninit<T>, RTo, Dynamic> {
         let new_buf = buf.resize(rto.value() * cto.value());
         VecStorage::new(rto, cto, new_buf)
     }

src/base/edition.rs

@@ -2,8 +2,6 @@ use num::{One, Zero};
 use std::cmp;
 #[cfg(any(feature = "std", feature = "alloc"))]
 use std::iter::ExactSizeIterator;
-#[cfg(any(feature = "std", feature = "alloc"))]
-use std::mem;
 use std::ptr;
 
 use crate::base::allocator::{Allocator, Reallocator};
@@ -11,8 +9,10 @@ use crate::base::constraint::{DimEq, SameNumberOfColumns, SameNumberOfRows, Shap
 #[cfg(any(feature = "std", feature = "alloc"))]
 use crate::base::dimension::Dynamic;
 use crate::base::dimension::{Const, Dim, DimAdd, DimDiff, DimMin, DimMinimum, DimSub, DimSum, U1};
-use crate::base::storage::{ContiguousStorageMut, ReshapableStorage, Storage, StorageMut};
+use crate::base::storage::{RawStorage, RawStorageMut, ReshapableStorage};
 use crate::base::{DefaultAllocator, Matrix, OMatrix, RowVector, Scalar, Vector};
+use crate::{Storage, UninitMatrix};
+use std::mem::MaybeUninit;
 
 /// # Rows and columns extraction
 impl<T: Scalar + Zero, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
@@ -52,10 +52,8 @@ impl<T: Scalar + Zero, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Allocator<T, Dynamic, C>,
     {
         let irows = irows.into_iter();
-        let ncols = self.data.shape().1;
-        let mut res = unsafe {
-            crate::unimplemented_or_uninitialized_generic!(Dynamic::new(irows.len()), ncols)
-        };
+        let ncols = self.shape_generic().1;
+        let mut res = Matrix::uninit(Dynamic::new(irows.len()), ncols);
 
         // First, check that all the indices from irows are valid.
         // This will allow us to use unchecked access in the inner loop.
@@ -69,14 +67,16 @@ impl<T: Scalar + Zero, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
             let src = self.column(j);
 
             for (destination, source) in irows.clone().enumerate() {
+                // Safety: all indices are in range.
                 unsafe {
                     *res.vget_unchecked_mut(destination) =
-                        src.vget_unchecked(*source).inlined_clone()
+                        MaybeUninit::new(src.vget_unchecked(*source).clone());
                 }
             }
         }
 
-        res
+        // Safety: res is now fully initialized.
+        unsafe { res.assume_init() }
     }
 
     /// Creates a new matrix by extracting the given set of columns from `self`.
@@ -89,27 +89,30 @@ impl<T: Scalar + Zero, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Allocator<T, R, Dynamic>,
     {
         let icols = icols.into_iter();
-        let nrows = self.data.shape().0;
-        let mut res = unsafe {
-            crate::unimplemented_or_uninitialized_generic!(nrows, Dynamic::new(icols.len()))
-        };
+        let nrows = self.shape_generic().0;
+        let mut res = Matrix::uninit(nrows, Dynamic::new(icols.len()));
 
         for (destination, source) in icols.enumerate() {
-            res.column_mut(destination).copy_from(&self.column(*source))
+            // NOTE: this is basically a copy_frow but wrapping the values insnide of MaybeUninit.
+            res.column_mut(destination)
+                .zip_apply(&self.column(*source), |out, e| {
+                    *out = MaybeUninit::new(e.clone())
+                });
         }
 
-        res
+        // Safety: res is now fully initialized.
+        unsafe { res.assume_init() }
     }
 }
 
 /// # Set rows, columns, and diagonal
-impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> Matrix<T, R, C, S> {
     /// Fills the diagonal of this matrix with the content of the given vector.
     #[inline]
     pub fn set_diagonal<R2: Dim, S2>(&mut self, diag: &Vector<T, R2, S2>)
     where
         R: DimMin<C>,
-        S2: Storage<T, R2>,
+        S2: RawStorage<T, R2>,
         ShapeConstraint: DimEq<DimMinimum<R, C>, R2>,
     {
         let (nrows, ncols) = self.shape();
@@ -117,7 +120,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
         assert_eq!(diag.len(), min_nrows_ncols, "Mismatched dimensions.");
 
         for i in 0..min_nrows_ncols {
-            unsafe { *self.get_unchecked_mut((i, i)) = diag.vget_unchecked(i).inlined_clone() }
+            unsafe { *self.get_unchecked_mut((i, i)) = diag.vget_unchecked(i).clone() }
         }
     }
 
@@ -140,7 +143,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
     #[inline]
     pub fn set_row<C2: Dim, S2>(&mut self, i: usize, row: &RowVector<T, C2, S2>)
     where
-        S2: Storage<T, U1, C2>,
+        S2: RawStorage<T, U1, C2>,
         ShapeConstraint: SameNumberOfColumns<C, C2>,
     {
         self.row_mut(i).copy_from(row);
@@ -150,7 +153,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
     #[inline]
     pub fn set_column<R2: Dim, S2>(&mut self, i: usize, column: &Vector<T, R2, S2>)
     where
-        S2: Storage<T, R2, U1>,
+        S2: RawStorage<T, R2, U1>,
         ShapeConstraint: SameNumberOfRows<R, R2>,
     {
         self.column_mut(i).copy_from(column);
@@ -158,12 +161,23 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
 }
 
 /// # In-place filling
-impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
+impl<T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> Matrix<T, R, C, S> {
+    /// Sets all the elements of this matrix to the value returned by the closure.
+    #[inline]
+    pub fn fill_with(&mut self, val: impl Fn() -> T) {
+        for e in self.iter_mut() {
+            *e = val()
+        }
+    }
+
     /// Sets all the elements of this matrix to `val`.
     #[inline]
-    pub fn fill(&mut self, val: T) {
+    pub fn fill(&mut self, val: T)
+    where
+        T: Scalar,
+    {
         for e in self.iter_mut() {
-            *e = val.inlined_clone()
+            *e = val.clone()
         }
     }
 
@@ -171,7 +185,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
     #[inline]
     pub fn fill_with_identity(&mut self)
     where
-        T: Zero + One,
+        T: Scalar + Zero + One,
     {
         self.fill(T::zero());
         self.fill_diagonal(T::one());
@@ -179,30 +193,39 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
 
     /// Sets all the diagonal elements of this matrix to `val`.
     #[inline]
-    pub fn fill_diagonal(&mut self, val: T) {
+    pub fn fill_diagonal(&mut self, val: T)
+    where
+        T: Scalar,
+    {
         let (nrows, ncols) = self.shape();
         let n = cmp::min(nrows, ncols);
 
         for i in 0..n {
-            unsafe { *self.get_unchecked_mut((i, i)) = val.inlined_clone() }
+            unsafe { *self.get_unchecked_mut((i, i)) = val.clone() }
         }
     }
 
     /// Sets all the elements of the selected row to `val`.
     #[inline]
-    pub fn fill_row(&mut self, i: usize, val: T) {
+    pub fn fill_row(&mut self, i: usize, val: T)
+    where
+        T: Scalar,
+    {
         assert!(i < self.nrows(), "Row index out of bounds.");
         for j in 0..self.ncols() {
-            unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
+            unsafe { *self.get_unchecked_mut((i, j)) = val.clone() }
         }
     }
 
     /// Sets all the elements of the selected column to `val`.
     #[inline]
-    pub fn fill_column(&mut self, j: usize, val: T) {
+    pub fn fill_column(&mut self, j: usize, val: T)
+    where
+        T: Scalar,
+    {
         assert!(j < self.ncols(), "Row index out of bounds.");
         for i in 0..self.nrows() {
-            unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
+            unsafe { *self.get_unchecked_mut((i, j)) = val.clone() }
         }
     }
 
@@ -214,10 +237,13 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
     /// * If `shift > 1`, then the diagonal and the first `shift - 1` subdiagonals are left
     /// untouched.
     #[inline]
-    pub fn fill_lower_triangle(&mut self, val: T, shift: usize) {
+    pub fn fill_lower_triangle(&mut self, val: T, shift: usize)
+    where
+        T: Scalar,
+    {
         for j in 0..self.ncols() {
             for i in (j + shift)..self.nrows() {
-                unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
+                unsafe { *self.get_unchecked_mut((i, j)) = val.clone() }
             }
         }
     }
@@ -230,18 +256,21 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
     /// * If `shift > 1`, then the diagonal and the first `shift - 1` superdiagonals are left
     /// untouched.
     #[inline]
-    pub fn fill_upper_triangle(&mut self, val: T, shift: usize) {
+    pub fn fill_upper_triangle(&mut self, val: T, shift: usize)
+    where
+        T: Scalar,
+    {
         for j in shift..self.ncols() {
             // TODO: is there a more efficient way to avoid the min ?
             // (necessary for rectangular matrices)
             for i in 0..cmp::min(j + 1 - shift, self.nrows()) {
-                unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
+                unsafe { *self.get_unchecked_mut((i, j)) = val.clone() }
             }
         }
     }
 }
 
-impl<T: Scalar, D: Dim, S: StorageMut<T, D, D>> Matrix<T, D, D, S> {
+impl<T: Scalar, D: Dim, S: RawStorageMut<T, D, D>> Matrix<T, D, D, S> {
     /// Copies the upper-triangle of this matrix to its lower-triangular part.
     ///
     /// This makes the matrix symmetric. Panics if the matrix is not square.
@@ -252,7 +281,7 @@ impl<T: Scalar, D: Dim, S: StorageMut<T, D, D>> Matrix<T, D, D, S> {
         for j in 0..dim {
             for i in j + 1..dim {
                 unsafe {
-                    *self.get_unchecked_mut((i, j)) = self.get_unchecked((j, i)).inlined_clone();
+                    *self.get_unchecked_mut((i, j)) = self.get_unchecked((j, i)).clone();
                 }
             }
         }
@@ -267,7 +296,7 @@ impl<T: Scalar, D: Dim, S: StorageMut<T, D, D>> Matrix<T, D, D, S> {
         for j in 1..self.ncols() {
             for i in 0..j {
                 unsafe {
-                    *self.get_unchecked_mut((i, j)) = self.get_unchecked((j, i)).inlined_clone();
+                    *self.get_unchecked_mut((i, j)) = self.get_unchecked((j, i)).clone();
                 }
             }
         }
@@ -275,7 +304,7 @@ impl<T: Scalar, D: Dim, S: StorageMut<T, D, D>> Matrix<T, D, D, S> {
 }
 
 /// # In-place swapping
-impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> Matrix<T, R, C, S> {
     /// Swaps two rows in-place.
     #[inline]
     pub fn swap_rows(&mut self, irow1: usize, irow2: usize) {
@@ -335,29 +364,46 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Reallocator<T, R, C, R, Dynamic>,
     {
         let mut m = self.into_owned();
-        let (nrows, ncols) = m.data.shape();
+        let (nrows, ncols) = m.shape_generic();
         let mut offset: usize = 0;
         let mut target: usize = 0;
         while offset + target < ncols.value() {
             if indices.contains(&(target + offset)) {
+                // Safety: the resulting pointer is within range.
+                let col_ptr = unsafe { m.data.ptr_mut().add((target + offset) * nrows.value()) };
+                // Drop every element in the column we are about to overwrite.
+                // We use the a similar technique as in `Vec::truncate`.
+                let s = ptr::slice_from_raw_parts_mut(col_ptr, nrows.value());
+                // Safety: we drop the column in-place, which is OK because we will overwrite these
+                //         entries later in the loop, or discard them with the `reallocate_copy`
+                //         afterwards.
+                unsafe { ptr::drop_in_place(s) };
+
                 offset += 1;
             } else {
                 unsafe {
                     let ptr_source = m.data.ptr().add((target + offset) * nrows.value());
                     let ptr_target = m.data.ptr_mut().add(target * nrows.value());
 
+                    // Copy the data, overwriting what we dropped.
                     ptr::copy(ptr_source, ptr_target, nrows.value());
                     target += 1;
                 }
             }
         }
 
+        // Safety: The new size is smaller than the old size, so
+        //         DefaultAllocator::reallocate_copy will initialize
+        //         every element of the new matrix which can then
+        //         be assumed to be initialized.
         unsafe {
-            Matrix::from_data(DefaultAllocator::reallocate_copy(
+            let new_data = DefaultAllocator::reallocate_copy(
                 nrows,
                 ncols.sub(Dynamic::from_usize(offset)),
                 m.data,
-            ))
+            );
+
+            Matrix::from_data(new_data).assume_init()
         }
     }
 
@@ -369,29 +415,44 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Reallocator<T, R, C, Dynamic, C>,
     {
         let mut m = self.into_owned();
-        let (nrows, ncols) = m.data.shape();
+        let (nrows, ncols) = m.shape_generic();
         let mut offset: usize = 0;
         let mut target: usize = 0;
         while offset + target < nrows.value() * ncols.value() {
             if indices.contains(&((target + offset) % nrows.value())) {
+                // Safety: the resulting pointer is within range.
+                unsafe {
+                    let elt_ptr = m.data.ptr_mut().add(target + offset);
+                    // Safety: we drop the component in-place, which is OK because we will overwrite these
+                    //         entries later in the loop, or discard them with the `reallocate_copy`
+                    //         afterwards.
+                    ptr::drop_in_place(elt_ptr)
+                };
                 offset += 1;
             } else {
                 unsafe {
                     let ptr_source = m.data.ptr().add(target + offset);
                     let ptr_target = m.data.ptr_mut().add(target);
 
+                    // Copy the data, overwriting what we dropped in the previous iterations.
                     ptr::copy(ptr_source, ptr_target, 1);
                     target += 1;
                 }
             }
         }
 
+        // Safety: The new size is smaller than the old size, so
+        //         DefaultAllocator::reallocate_copy will initialize
+        //         every element of the new matrix which can then
+        //         be assumed to be initialized.
         unsafe {
-            Matrix::from_data(DefaultAllocator::reallocate_copy(
+            let new_data = DefaultAllocator::reallocate_copy(
                 nrows.sub(Dynamic::from_usize(offset / ncols.value())),
                 ncols,
                 m.data,
-            ))
+            );
+
+            Matrix::from_data(new_data).assume_init()
         }
     }
 
@@ -432,13 +493,14 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Reallocator<T, R, C, R, DimDiff<C, D>>,
     {
         let mut m = self.into_owned();
-        let (nrows, ncols) = m.data.shape();
+        let (nrows, ncols) = m.shape_generic();
         assert!(
             i + nremove.value() <= ncols.value(),
             "Column index out of range."
         );
 
-        if nremove.value() != 0 && i + nremove.value() < ncols.value() {
+        let need_column_shifts = nremove.value() != 0 && i + nremove.value() < ncols.value();
+        if need_column_shifts {
             // The first `deleted_i * nrows` are left untouched.
             let copied_value_start = i + nremove.value();
 
@@ -446,20 +508,35 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
                 let ptr_in = m.data.ptr().add(copied_value_start * nrows.value());
                 let ptr_out = m.data.ptr_mut().add(i * nrows.value());
 
+                // Drop all the elements of the columns we are about to overwrite.
+                // We use the a similar technique as in `Vec::truncate`.
+                let s = ptr::slice_from_raw_parts_mut(ptr_out, nremove.value() * nrows.value());
+                // Safety: we drop the column in-place, which is OK because we will overwrite these
+                //         entries with `ptr::copy` afterward.
+                ptr::drop_in_place(s);
+
                 ptr::copy(
                     ptr_in,
                     ptr_out,
                     (ncols.value() - copied_value_start) * nrows.value(),
                 );
             }
+        } else {
+            // All the columns to remove are at the end of the buffer. Drop them.
+            unsafe {
+                let ptr = m.data.ptr_mut().add(i * nrows.value());
+                let s = ptr::slice_from_raw_parts_mut(ptr, nremove.value() * nrows.value());
+                ptr::drop_in_place(s)
+            };
         }
 
+        // Safety: The new size is smaller than the old size, so
+        //         DefaultAllocator::reallocate_copy will initialize
+        //         every element of the new matrix which can then
+        //         be assumed to be initialized.
         unsafe {
-            Matrix::from_data(DefaultAllocator::reallocate_copy(
-                nrows,
-                ncols.sub(nremove),
-                m.data,
-            ))
+            let new_data = DefaultAllocator::reallocate_copy(nrows, ncols.sub(nremove), m.data);
+            Matrix::from_data(new_data).assume_init()
         }
     }
 
@@ -511,7 +588,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Reallocator<T, R, C, DimDiff<R, D>, C>,
     {
         let mut m = self.into_owned();
-        let (nrows, ncols) = m.data.shape();
+        let (nrows, ncols) = m.shape_generic();
         assert!(
             i + nremove.value() <= nrows.value(),
             "Row index out of range."
@@ -520,7 +597,7 @@ 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.data.as_mut_slice(),
+                    &mut m.as_mut_slice(),
                     nrows.value(),
                     ncols.value(),
                     i,
@@ -529,12 +606,13 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
             }
         }
 
+        // Safety: The new size is smaller than the old size, so
+        //         DefaultAllocator::reallocate_copy will initialize
+        //         every element of the new matrix which can then
+        //         be assumed to be initialized.
         unsafe {
-            Matrix::from_data(DefaultAllocator::reallocate_copy(
-                nrows.sub(nremove),
-                ncols,
-                m.data,
-            ))
+            let new_data = DefaultAllocator::reallocate_copy(nrows.sub(nremove), ncols, m.data);
+            Matrix::from_data(new_data).assume_init()
         }
     }
 }
@@ -568,8 +646,13 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Reallocator<T, R, C, R, DimSum<C, Const<D>>>,
     {
         let mut res = unsafe { self.insert_columns_generic_uninitialized(i, Const::<D>) };
-        res.fixed_columns_mut::<D>(i).fill(val);
-        res
+        res.fixed_columns_mut::<D>(i)
+            .fill_with(|| MaybeUninit::new(val.clone()));
+
+        // Safety: the result is now fully initialized. The added columns have
+        //         been initialized by the `fill_with` above, and the rest have
+        //         been initialized by `insert_columns_generic_uninitialized`.
+        unsafe { res.assume_init() }
     }
 
     /// Inserts `n` columns filled with `val` starting at the `i-th` position.
@@ -581,27 +664,33 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Reallocator<T, R, C, R, Dynamic>,
     {
         let mut res = unsafe { self.insert_columns_generic_uninitialized(i, Dynamic::new(n)) };
-        res.columns_mut(i, n).fill(val);
-        res
+        res.columns_mut(i, n)
+            .fill_with(|| MaybeUninit::new(val.clone()));
+
+        // Safety: the result is now fully initialized. The added columns have
+        //         been initialized by the `fill_with` above, and the rest have
+        //         been initialized by `insert_columns_generic_uninitialized`.
+        unsafe { res.assume_init() }
     }
 
     /// Inserts `ninsert.value()` columns starting at the `i-th` place of this matrix.
     ///
     /// # Safety
-    /// The added column values are not initialized.
+    /// The output matrix has all its elements initialized except for the the components of the
+    /// added columns.
     #[inline]
     pub unsafe fn insert_columns_generic_uninitialized<D>(
         self,
         i: usize,
         ninsert: D,
-    ) -> OMatrix<T, R, DimSum<C, D>>
+    ) -> UninitMatrix<T, R, DimSum<C, D>>
     where
         D: Dim,
         C: DimAdd<D>,
         DefaultAllocator: Reallocator<T, R, C, R, DimSum<C, D>>,
     {
         let m = self.into_owned();
-        let (nrows, ncols) = m.data.shape();
+        let (nrows, ncols) = m.shape_generic();
         let mut res = Matrix::from_data(DefaultAllocator::reallocate_copy(
             nrows,
             ncols.add(ninsert),
@@ -650,8 +739,13 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Reallocator<T, R, C, DimSum<R, Const<D>>, C>,
     {
         let mut res = unsafe { self.insert_rows_generic_uninitialized(i, Const::<D>) };
-        res.fixed_rows_mut::<D>(i).fill(val);
-        res
+        res.fixed_rows_mut::<D>(i)
+            .fill_with(|| MaybeUninit::new(val.clone()));
+
+        // Safety: the result is now fully initialized. The added rows have
+        //         been initialized by the `fill_with` above, and the rest have
+        //         been initialized by `insert_rows_generic_uninitialized`.
+        unsafe { res.assume_init() }
     }
 
     /// Inserts `n` rows filled with `val` starting at the `i-th` position.
@@ -663,8 +757,13 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Reallocator<T, R, C, Dynamic, C>,
     {
         let mut res = unsafe { self.insert_rows_generic_uninitialized(i, Dynamic::new(n)) };
-        res.rows_mut(i, n).fill(val);
-        res
+        res.rows_mut(i, n)
+            .fill_with(|| MaybeUninit::new(val.clone()));
+
+        // Safety: the result is now fully initialized. The added rows have
+        //         been initialized by the `fill_with` above, and the rest have
+        //         been initialized by `insert_rows_generic_uninitialized`.
+        unsafe { res.assume_init() }
     }
 
     /// Inserts `ninsert.value()` rows at the `i-th` place of this matrix.
@@ -678,14 +777,14 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         self,
         i: usize,
         ninsert: D,
-    ) -> OMatrix<T, DimSum<R, D>, C>
+    ) -> UninitMatrix<T, DimSum<R, D>, C>
     where
         D: Dim,
         R: DimAdd<D>,
         DefaultAllocator: Reallocator<T, R, C, DimSum<R, D>, C>,
     {
         let m = self.into_owned();
-        let (nrows, ncols) = m.data.shape();
+        let (nrows, ncols) = m.shape_generic();
         let mut res = Matrix::from_data(DefaultAllocator::reallocate_copy(
             nrows.add(ninsert),
             ncols,
@@ -696,7 +795,7 @@ 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.data.as_mut_slice(),
+                &mut res.as_mut_slice(),
                 nrows.value(),
                 ncols.value(),
                 i,
@@ -731,7 +830,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     where
         DefaultAllocator: Reallocator<T, R, C, Dynamic, C>,
     {
-        let ncols = self.data.shape().1;
+        let ncols = self.shape_generic().1;
         self.resize_generic(Dynamic::new(new_nrows), ncols, val)
     }
 
@@ -744,7 +843,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     where
         DefaultAllocator: Reallocator<T, R, C, R, Dynamic>,
     {
-        let nrows = self.data.shape().0;
+        let nrows = self.shape_generic().0;
         self.resize_generic(nrows, Dynamic::new(new_ncols), val)
     }
 
@@ -777,16 +876,32 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Reallocator<T, R, C, R2, C2>,
     {
         let (nrows, ncols) = self.shape();
-        let mut data = self.data.into_owned();
+        let mut data = self.into_owned();
 
         if new_nrows.value() == nrows {
-            let res = unsafe { DefaultAllocator::reallocate_copy(new_nrows, new_ncols, data) };
-            let mut res = Matrix::from_data(res);
-            if new_ncols.value() > ncols {
-                res.columns_range_mut(ncols..).fill(val);
+            if new_ncols.value() < ncols {
+                unsafe {
+                    let num_cols_to_delete = ncols - new_ncols.value();
+                    let col_ptr = data.data.ptr_mut().add(new_ncols.value() * nrows);
+                    let s = ptr::slice_from_raw_parts_mut(col_ptr, num_cols_to_delete * nrows);
+                    // Safety: drop the elements of the deleted columns.
+                    //         these are the elements that will be truncated
+                    //         by the `reallocate_copy` afterward.
+                    ptr::drop_in_place(s)
+                };
             }
 
-            res
+            let res = unsafe { DefaultAllocator::reallocate_copy(new_nrows, new_ncols, data.data) };
+            let mut res = Matrix::from_data(res);
+
+            if new_ncols.value() > ncols {
+                res.columns_range_mut(ncols..)
+                    .fill_with(|| MaybeUninit::new(val.clone()));
+            }
+
+            // Safety: the result is now fully initialized by `reallocate_copy` and
+            //         `fill_with` (if the output has more columns than the input).
+            unsafe { res.assume_init() }
         } else {
             let mut res;
 
@@ -800,14 +915,14 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
                         nrows - new_nrows.value(),
                     );
                     res = Matrix::from_data(DefaultAllocator::reallocate_copy(
-                        new_nrows, new_ncols, data,
+                        new_nrows, new_ncols, data.data,
                     ));
                 } else {
                     res = Matrix::from_data(DefaultAllocator::reallocate_copy(
-                        new_nrows, new_ncols, data,
+                        new_nrows, new_ncols, data.data,
                     ));
                     extend_rows(
-                        &mut res.data.as_mut_slice(),
+                        &mut res.as_mut_slice(),
                         nrows,
                         new_ncols.value(),
                         nrows,
@@ -817,15 +932,18 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
             }
 
             if new_ncols.value() > ncols {
-                res.columns_range_mut(ncols..).fill(val.inlined_clone());
+                res.columns_range_mut(ncols..)
+                    .fill_with(|| MaybeUninit::new(val.clone()));
             }
 
             if new_nrows.value() > nrows {
                 res.slice_range_mut(nrows.., ..cmp::min(ncols, new_ncols.value()))
-                    .fill(val);
+                    .fill_with(|| MaybeUninit::new(val.clone()));
             }
 
-            res
+            // Safety: the result is now fully initialized by `reallocate_copy` and
+            //         `fill_with` (whenever applicable).
+            unsafe { res.assume_init() }
         }
     }
 
@@ -910,12 +1028,8 @@ impl<T: Scalar> OMatrix<T, Dynamic, Dynamic> {
     where
         DefaultAllocator: Reallocator<T, Dynamic, Dynamic, Dynamic, Dynamic>,
     {
-        let placeholder = unsafe {
-            crate::unimplemented_or_uninitialized_generic!(Dynamic::new(0), Dynamic::new(0))
-        };
-        let old = mem::replace(self, placeholder);
-        let new = old.resize(new_nrows, new_ncols, val);
-        let _ = mem::replace(self, new);
+        // TODO: avoid the clone.
+        *self = self.clone().resize(new_nrows, new_ncols, val);
     }
 }
 
@@ -935,12 +1049,8 @@ where
     where
         DefaultAllocator: Reallocator<T, Dynamic, C, Dynamic, C>,
     {
-        let placeholder = unsafe {
-            crate::unimplemented_or_uninitialized_generic!(Dynamic::new(0), self.data.shape().1)
-        };
-        let old = mem::replace(self, placeholder);
-        let new = old.resize_vertically(new_nrows, val);
-        let _ = mem::replace(self, new);
+        // TODO: avoid the clone.
+        *self = self.clone().resize_vertically(new_nrows, val);
     }
 }
 
@@ -960,15 +1070,15 @@ where
     where
         DefaultAllocator: Reallocator<T, R, Dynamic, R, Dynamic>,
     {
-        let placeholder = unsafe {
-            crate::unimplemented_or_uninitialized_generic!(self.data.shape().0, Dynamic::new(0))
-        };
-        let old = mem::replace(self, placeholder);
-        let new = old.resize_horizontally(new_ncols, val);
-        let _ = mem::replace(self, new);
+        // TODO: avoid the clone.
+        *self = self.clone().resize_horizontally(new_ncols, val);
     }
 }
 
+// Move the elements of `data` in such a way that the matrix with
+// the rows `[i, i + nremove[` deleted is represented in a contigous
+// way in `data` after this method completes.
+// Every deleted element are manually dropped by this method.
 unsafe fn compress_rows<T: Scalar>(
     data: &mut [T],
     nrows: usize,
@@ -978,16 +1088,28 @@ unsafe fn compress_rows<T: Scalar>(
 ) {
     let new_nrows = nrows - nremove;
 
-    if new_nrows == 0 || ncols == 0 {
-        return; // Nothing to do as the output matrix is empty.
+    if nremove == 0 {
+        return; // Nothing to remove or drop.
     }
 
+    if new_nrows == 0 || ncols == 0 {
+        // The output matrix is empty, drop everything.
+        ptr::drop_in_place(data.as_mut());
+        return;
+    }
+
+    // Safety: because `nremove != 0`, the pointers given to `ptr::copy`
+    //         won’t alias.
     let ptr_in = data.as_ptr();
     let ptr_out = data.as_mut_ptr();
 
     let mut curr_i = i;
 
     for k in 0..ncols - 1 {
+        // Safety: we drop the row elements in-place because we will overwrite these
+        //         entries later with the `ptr::copy`.
+        let s = ptr::slice_from_raw_parts_mut(ptr_out.add(curr_i), nremove);
+        ptr::drop_in_place(s);
         ptr::copy(
             ptr_in.add(curr_i + (k + 1) * nremove),
             ptr_out.add(curr_i),
@@ -997,7 +1119,13 @@ unsafe fn compress_rows<T: Scalar>(
         curr_i += new_nrows;
     }
 
-    // Deal with the last column from which less values have to be copied.
+    /*
+     * Deal with the last column from which less values have to be copied.
+     */
+    // Safety: we drop the row elements in-place because we will overwrite these
+    //         entries later with the `ptr::copy`.
+    let s = ptr::slice_from_raw_parts_mut(ptr_out.add(curr_i), nremove);
+    ptr::drop_in_place(s);
     let remaining_len = nrows - i - nremove;
     ptr::copy(
         ptr_in.add(nrows * ncols - remaining_len),
@@ -1006,15 +1134,9 @@ unsafe fn compress_rows<T: Scalar>(
     );
 }
 
-// Moves entries of a matrix buffer to make place for `ninsert` emty rows starting at the `i-th` row index.
+// Moves entries of a matrix buffer to make place for `ninsert` empty rows starting at the `i-th` row index.
 // The `data` buffer is assumed to contained at least `(nrows + ninsert) * ncols` elements.
-unsafe fn extend_rows<T: Scalar>(
-    data: &mut [T],
-    nrows: usize,
-    ncols: usize,
-    i: usize,
-    ninsert: usize,
-) {
+unsafe fn extend_rows<T>(data: &mut [T], nrows: usize, ncols: usize, i: usize, ninsert: usize) {
     let new_nrows = nrows + ninsert;
 
     if new_nrows == 0 || ncols == 0 {
@@ -1119,7 +1241,7 @@ where
     R: Dim,
     S: Extend<Vector<T, RV, SV>>,
     RV: Dim,
-    SV: Storage<T, RV>,
+    SV: RawStorage<T, RV>,
     ShapeConstraint: SameNumberOfRows<R, RV>,
 {
     /// Extends the number of columns of a `Matrix` with `Vector`s

src/base/indexing.rs

@@ -1,6 +1,6 @@
 //! Indexing
 
-use crate::base::storage::{Storage, StorageMut};
+use crate::base::storage::{RawStorage, RawStorageMut};
 use crate::base::{
     Const, Dim, DimDiff, DimName, DimSub, Dynamic, Matrix, MatrixSlice, MatrixSliceMut, Scalar, U1,
 };
@@ -310,7 +310,7 @@ fn dimrange_rangetoinclusive_usize() {
 }
 
 /// A helper trait used for indexing operations.
-pub trait MatrixIndex<'a, T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>>: Sized {
+pub trait MatrixIndex<'a, T, R: Dim, C: Dim, S: RawStorage<T, R, C>>: Sized {
     /// The output type returned by methods.
     type Output: 'a;
 
@@ -345,7 +345,7 @@ pub trait MatrixIndex<'a, T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>>: Sized
 }
 
 /// A helper trait used for indexing operations.
-pub trait MatrixIndexMut<'a, T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>>:
+pub trait MatrixIndexMut<'a, T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>>:
     MatrixIndex<'a, T, R, C, S>
 {
     /// The output type returned by methods.
@@ -476,7 +476,7 @@ pub trait MatrixIndexMut<'a, T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>>:
 ///                         4, 7,
 ///                         5, 8)));
 /// ```
-impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
+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, or
     /// `None` if the index is out of bounds.
     #[inline]
@@ -494,7 +494,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn get_mut<'a, I>(&'a mut self, index: I) -> Option<I::OutputMut>
     where
-        S: StorageMut<T, R, C>,
+        S: RawStorageMut<T, R, C>,
         I: MatrixIndexMut<'a, T, R, C, S>,
     {
         index.get_mut(self)
@@ -516,7 +516,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     #[inline]
     pub fn index_mut<'a, I>(&'a mut self, index: I) -> I::OutputMut
     where
-        S: StorageMut<T, R, C>,
+        S: RawStorageMut<T, R, C>,
         I: MatrixIndexMut<'a, T, R, C, S>,
     {
         index.index_mut(self)
@@ -539,7 +539,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub unsafe fn get_unchecked_mut<'a, I>(&'a mut self, index: I) -> I::OutputMut
     where
-        S: StorageMut<T, R, C>,
+        S: RawStorageMut<T, R, C>,
         I: MatrixIndexMut<'a, T, R, C, S>,
     {
         index.get_unchecked_mut(self)
@@ -553,7 +553,7 @@ where
     T: Scalar,
     R: Dim,
     C: Dim,
-    S: Storage<T, R, C>,
+    S: RawStorage<T, R, C>,
 {
     type Output = &'a T;
 
@@ -575,7 +575,7 @@ where
     T: Scalar,
     R: Dim,
     C: Dim,
-    S: StorageMut<T, R, C>,
+    S: RawStorageMut<T, R, C>,
 {
     type OutputMut = &'a mut T;
 
@@ -583,7 +583,7 @@ where
     #[inline(always)]
     unsafe fn get_unchecked_mut(self, matrix: &'a mut Matrix<T, R, C, S>) -> Self::OutputMut
     where
-        S: StorageMut<T, R, C>,
+        S: RawStorageMut<T, R, C>,
     {
         matrix.data.get_unchecked_linear_mut(self)
     }
@@ -591,12 +591,11 @@ where
 
 // EXTRACT A SINGLE ELEMENT BY 2D COORDINATES
 
-impl<'a, T, R, C, S> MatrixIndex<'a, T, R, C, S> for (usize, usize)
+impl<'a, T: 'a, R, C, S> MatrixIndex<'a, T, R, C, S> for (usize, usize)
 where
-    T: Scalar,
     R: Dim,
     C: Dim,
-    S: Storage<T, R, C>,
+    S: RawStorage<T, R, C>,
 {
     type Output = &'a T;
 
@@ -604,7 +603,7 @@ where
     #[inline(always)]
     fn contained_by(&self, matrix: &Matrix<T, R, C, S>) -> bool {
         let (rows, cols) = self;
-        let (nrows, ncols) = matrix.data.shape();
+        let (nrows, ncols) = matrix.shape_generic();
         DimRange::contained_by(rows, nrows) && DimRange::contained_by(cols, ncols)
     }
 
@@ -616,12 +615,11 @@ where
     }
 }
 
-impl<'a, T, R, C, S> MatrixIndexMut<'a, T, R, C, S> for (usize, usize)
+impl<'a, T: 'a, R, C, S> MatrixIndexMut<'a, T, R, C, S> for (usize, usize)
 where
-    T: Scalar,
     R: Dim,
     C: Dim,
-    S: StorageMut<T, R, C>,
+    S: RawStorageMut<T, R, C>,
 {
     type OutputMut = &'a mut T;
 
@@ -629,7 +627,7 @@ where
     #[inline(always)]
     unsafe fn get_unchecked_mut(self, matrix: &'a mut Matrix<T, R, C, S>) -> Self::OutputMut
     where
-        S: StorageMut<T, R, C>,
+        S: RawStorageMut<T, R, C>,
     {
         let (row, col) = self;
         matrix.data.get_unchecked_mut(row, col)
@@ -660,7 +658,7 @@ macro_rules! impl_index_pair {
             T: Scalar,
             $R: Dim,
             $C: Dim,
-            S: Storage<T, R, C>,
+            S: RawStorage<T, R, C>,
             $( $RConstraintType: $RConstraintBound $(<$( $RConstraintBoundParams $( = $REqBound )*),*>)* ,)*
             $( $CConstraintType: $CConstraintBound $(<$( $CConstraintBoundParams $( = $CEqBound )*),*>)* ),*
         {
@@ -670,7 +668,7 @@ macro_rules! impl_index_pair {
             #[inline(always)]
             fn contained_by(&self, matrix: &Matrix<T, $R, $C, S>) -> bool {
                 let (rows, cols) = self;
-                let (nrows, ncols) = matrix.data.shape();
+                let (nrows, ncols) = matrix.shape_generic();
                 DimRange::contained_by(rows, nrows) && DimRange::contained_by(cols, ncols)
             }
 
@@ -680,7 +678,7 @@ macro_rules! impl_index_pair {
                 use crate::base::SliceStorage;
 
                 let (rows, cols) = self;
-                let (nrows, ncols) = matrix.data.shape();
+                let (nrows, ncols) = matrix.shape_generic();
 
                 let data =
                     SliceStorage::new_unchecked(&matrix.data,
@@ -696,7 +694,7 @@ macro_rules! impl_index_pair {
             T: Scalar,
             $R: Dim,
             $C: Dim,
-            S: StorageMut<T, R, C>,
+            S: RawStorageMut<T, R, C>,
             $( $RConstraintType: $RConstraintBound $(<$( $RConstraintBoundParams $( = $REqBound )*),*>)* ,)*
             $( $CConstraintType: $CConstraintBound $(<$( $CConstraintBoundParams $( = $CEqBound )*),*>)* ),*
         {
@@ -708,7 +706,7 @@ macro_rules! impl_index_pair {
                 use crate::base::SliceStorageMut;
 
                 let (rows, cols) = self;
-                let (nrows, ncols) = matrix.data.shape();
+                let (nrows, ncols) = matrix.shape_generic();
 
                 let data =
                     SliceStorageMut::new_unchecked(&mut matrix.data,

src/base/interpolation.rs

@@ -26,7 +26,7 @@ impl<T: Scalar + Zero + One + ClosedAdd + ClosedSub + ClosedMul, D: Dim, S: Stor
         DefaultAllocator: Allocator<T, D>,
     {
         let mut res = self.clone_owned();
-        res.axpy(t.inlined_clone(), rhs, T::one() - t);
+        res.axpy(t.clone(), rhs, T::one() - t);
         res
     }
 
@@ -109,14 +109,14 @@ impl<T: RealField, D: Dim, S: Storage<T, D>> Unit<Vector<T, D, S>> {
             return Some(Unit::new_unchecked(self.clone_owned()));
         }
 
-        let hang = c_hang.acos();
-        let s_hang = (T::one() - c_hang * c_hang).sqrt();
+        let hang = c_hang.clone().acos();
+        let s_hang = (T::one() - c_hang.clone() * c_hang).sqrt();
 
         // TODO: what if s_hang is 0.0 ? The result is not well-defined.
         if relative_eq!(s_hang, T::zero(), epsilon = epsilon) {
             None
         } else {
-            let ta = ((T::one() - t) * hang).sin() / s_hang;
+            let ta = ((T::one() - t.clone()) * hang.clone()).sin() / s_hang.clone();
             let tb = (t * hang).sin() / s_hang;
             let mut res = self.scale(ta);
             res.axpy(tb, &**rhs, T::one());

src/base/iter.rs

@@ -5,13 +5,14 @@ use std::marker::PhantomData;
 use std::mem;
 
 use crate::base::dimension::{Dim, U1};
-use crate::base::storage::{Storage, StorageMut};
+use crate::base::storage::{RawStorage, RawStorageMut};
 use crate::base::{Matrix, MatrixSlice, MatrixSliceMut, Scalar};
 
 macro_rules! iterator {
     (struct $Name:ident for $Storage:ident.$ptr: ident -> $Ptr:ty, $Ref:ty, $SRef: ty) => {
         /// An iterator through a dense matrix with arbitrary strides matrix.
-        pub struct $Name<'a, T: Scalar, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> {
+        #[derive(Debug)]
+        pub struct $Name<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> {
             ptr: $Ptr,
             inner_ptr: $Ptr,
             inner_end: $Ptr,
@@ -22,7 +23,7 @@ macro_rules! iterator {
 
         // 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: Scalar, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> $Name<'a, T, R, C, S> {
+        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) -> $Name<'a, T, R, C, S> {
                 let shape = storage.shape();
@@ -59,9 +60,7 @@ macro_rules! iterator {
             }
         }
 
-        impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> Iterator
-            for $Name<'a, T, R, C, S>
-        {
+        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]
@@ -116,7 +115,7 @@ macro_rules! iterator {
             }
         }
 
-        impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> DoubleEndedIterator
+        impl<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> DoubleEndedIterator
             for $Name<'a, T, R, C, S>
         {
             #[inline]
@@ -156,7 +155,7 @@ macro_rules! iterator {
             }
         }
 
-        impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> ExactSizeIterator
+        impl<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> ExactSizeIterator
             for $Name<'a, T, R, C, S>
         {
             #[inline]
@@ -165,35 +164,35 @@ macro_rules! iterator {
             }
         }
 
-        impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> FusedIterator
+        impl<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> FusedIterator
             for $Name<'a, T, R, C, S>
         {
         }
     };
 }
 
-iterator!(struct MatrixIter for Storage.ptr -> *const T, &'a T, &'a S);
-iterator!(struct MatrixIterMut for StorageMut.ptr_mut -> *mut T, &'a mut T, &'a mut S);
+iterator!(struct MatrixIter for RawStorage.ptr -> *const T, &'a T, &'a S);
+iterator!(struct MatrixIterMut for RawStorageMut.ptr_mut -> *mut T, &'a mut T, &'a mut S);
 
 /*
  *
  * Row iterators.
  *
  */
-#[derive(Clone)]
+#[derive(Clone, Debug)]
 /// An iterator through the rows of a matrix.
-pub struct RowIter<'a, T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> {
+pub struct RowIter<'a, T, R: Dim, C: Dim, S: RawStorage<T, R, C>> {
     mat: &'a Matrix<T, R, C, S>,
     curr: usize,
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> RowIter<'a, T, R, C, S> {
+impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> RowIter<'a, T, R, C, S> {
     pub(crate) fn new(mat: &'a Matrix<T, R, C, S>) -> Self {
         RowIter { mat, curr: 0 }
     }
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> Iterator for RowIter<'a, T, R, C, S> {
+impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> Iterator for RowIter<'a, T, R, C, S> {
     type Item = MatrixSlice<'a, T, U1, C, S::RStride, S::CStride>;
 
     #[inline]
@@ -221,7 +220,7 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> Iterator for RowIt
     }
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> ExactSizeIterator
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> ExactSizeIterator
     for RowIter<'a, T, R, C, S>
 {
     #[inline]
@@ -231,13 +230,14 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> ExactSizeIterator
 }
 
 /// An iterator through the mutable rows of a matrix.
-pub struct RowIterMut<'a, T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> {
+#[derive(Debug)]
+pub struct RowIterMut<'a, T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> {
     mat: *mut Matrix<T, R, C, S>,
     curr: usize,
     phantom: PhantomData<&'a mut Matrix<T, R, C, S>>,
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> RowIterMut<'a, T, R, C, S> {
+impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> RowIterMut<'a, T, R, C, S> {
     pub(crate) fn new(mat: &'a mut Matrix<T, R, C, S>) -> Self {
         RowIterMut {
             mat,
@@ -251,7 +251,7 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> RowIterMut<'a,
     }
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> Iterator
+impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> Iterator
     for RowIterMut<'a, T, R, C, S>
 {
     type Item = MatrixSliceMut<'a, T, U1, C, S::RStride, S::CStride>;
@@ -278,7 +278,7 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> Iterator
     }
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> ExactSizeIterator
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> ExactSizeIterator
     for RowIterMut<'a, T, R, C, S>
 {
     #[inline]
@@ -292,22 +292,20 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> ExactSizeIterat
  * Column iterators.
  *
  */
-#[derive(Clone)]
+#[derive(Clone, Debug)]
 /// An iterator through the columns of a matrix.
-pub struct ColumnIter<'a, T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> {
+pub struct ColumnIter<'a, T, R: Dim, C: Dim, S: RawStorage<T, R, C>> {
     mat: &'a Matrix<T, R, C, S>,
     curr: usize,
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> ColumnIter<'a, T, R, C, S> {
+impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> ColumnIter<'a, T, R, C, S> {
     pub(crate) fn new(mat: &'a Matrix<T, R, C, S>) -> Self {
         ColumnIter { mat, curr: 0 }
     }
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> Iterator
-    for ColumnIter<'a, T, R, C, S>
-{
+impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> Iterator for ColumnIter<'a, T, R, C, S> {
     type Item = MatrixSlice<'a, T, R, U1, S::RStride, S::CStride>;
 
     #[inline]
@@ -335,7 +333,7 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> Iterator
     }
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> ExactSizeIterator
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> ExactSizeIterator
     for ColumnIter<'a, T, R, C, S>
 {
     #[inline]
@@ -345,13 +343,14 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> ExactSizeIterator
 }
 
 /// An iterator through the mutable columns of a matrix.
-pub struct ColumnIterMut<'a, T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> {
+#[derive(Debug)]
+pub struct ColumnIterMut<'a, T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> {
     mat: *mut Matrix<T, R, C, S>,
     curr: usize,
     phantom: PhantomData<&'a mut Matrix<T, R, C, S>>,
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> ColumnIterMut<'a, T, R, C, S> {
+impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> ColumnIterMut<'a, T, R, C, S> {
     pub(crate) fn new(mat: &'a mut Matrix<T, R, C, S>) -> Self {
         ColumnIterMut {
             mat,
@@ -365,7 +364,7 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> ColumnIterMut<'
     }
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> Iterator
+impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> Iterator
     for ColumnIterMut<'a, T, R, C, S>
 {
     type Item = MatrixSliceMut<'a, T, R, U1, S::RStride, S::CStride>;
@@ -392,7 +391,7 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> Iterator
     }
 }
 
-impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> ExactSizeIterator
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> ExactSizeIterator
     for ColumnIterMut<'a, T, R, C, S>
 {
     #[inline]

src/base/matrix_simba.rs

@@ -44,7 +44,6 @@ where
     fn replace(&mut self, i: usize, val: Self::Element) {
         self.zip_apply(&val, |mut a, b| {
             a.replace(i, b);
-            a
         })
     }
 
@@ -52,7 +51,6 @@ where
     unsafe fn replace_unchecked(&mut self, i: usize, val: Self::Element) {
         self.zip_apply(&val, |mut a, b| {
             a.replace_unchecked(i, b);
-            a
         })
     }
 

src/base/matrix_slice.rs

@@ -6,29 +6,29 @@ use crate::base::allocator::Allocator;
 use crate::base::default_allocator::DefaultAllocator;
 use crate::base::dimension::{Const, Dim, DimName, Dynamic, IsNotStaticOne, U1};
 use crate::base::iter::MatrixIter;
-use crate::base::storage::{ContiguousStorage, ContiguousStorageMut, Owned, Storage, StorageMut};
+use crate::base::storage::{IsContiguous, Owned, RawStorage, RawStorageMut, Storage};
 use crate::base::{Matrix, Scalar};
 
 macro_rules! slice_storage_impl(
     ($doc: expr; $Storage: ident as $SRef: ty; $T: ident.$get_addr: ident ($Ptr: ty as $Ref: ty)) => {
         #[doc = $doc]
         #[derive(Debug)]
-        pub struct $T<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> {
+        pub struct $T<'a, T, R: Dim, C: Dim, RStride: Dim, CStride: Dim> {
             ptr:       $Ptr,
             shape:     (R, C),
             strides:   (RStride, CStride),
             _phantoms: PhantomData<$Ref>,
         }
 
-        unsafe impl<'a, T: Scalar + Send, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Send
+        unsafe impl<'a, T: Send, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Send
             for $T<'a, T, R, C, RStride, CStride>
         {}
 
-        unsafe impl<'a, T: Scalar + Sync, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Sync
+        unsafe impl<'a, T: Sync, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Sync
             for $T<'a, T, R, C, RStride, CStride>
         {}
 
-        impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> $T<'a, T, R, C, RStride, CStride> {
+        impl<'a, T, R: Dim, C: Dim, RStride: Dim, CStride: Dim> $T<'a, T, R, C, RStride, CStride> {
             /// Create a new matrix slice without bound checking and from a raw pointer.
             #[inline]
             pub unsafe fn from_raw_parts(ptr:     $Ptr,
@@ -48,7 +48,7 @@ macro_rules! slice_storage_impl(
         }
 
         // Dynamic is arbitrary. It's just to be able to call the constructors with `Slice::`
-        impl<'a, T: Scalar, R: Dim, C: Dim> $T<'a, T, R, C, Dynamic, Dynamic> {
+        impl<'a, T, R: Dim, C: Dim> $T<'a, T, R, C, Dynamic, Dynamic> {
             /// Create a new matrix slice without bound checking.
             #[inline]
             pub unsafe fn new_unchecked<RStor, CStor, S>(storage: $SRef, start: (usize, usize), shape: (R, C))
@@ -78,10 +78,10 @@ macro_rules! slice_storage_impl(
             }
         }
 
-        impl <'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
+        impl <'a, T, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
             $T<'a, T, R, C, RStride, CStride>
         where
-            Self: ContiguousStorage<T, R, C>
+            Self: RawStorage<T, R, C> + IsContiguous
         {
             /// Extracts the original slice from this storage
             pub fn into_slice(self) -> &'a [T] {
@@ -99,11 +99,11 @@ macro_rules! slice_storage_impl(
 
 slice_storage_impl!("A matrix data storage for a matrix slice. Only contains an internal reference \
                      to another matrix data storage.";
-    Storage as &'a S; SliceStorage.get_address_unchecked(*const T as &'a T));
+    RawStorage as &'a S; SliceStorage.get_address_unchecked(*const T as &'a T));
 
 slice_storage_impl!("A mutable matrix data storage for mutable matrix slice. Only contains an \
                      internal mutable reference to another matrix data storage.";
-    StorageMut as &'a mut S; SliceStorageMut.get_address_unchecked_mut(*mut T as &'a mut T)
+    RawStorageMut as &'a mut S; SliceStorageMut.get_address_unchecked_mut(*mut T as &'a mut T)
 );
 
 impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Copy
@@ -128,7 +128,7 @@ impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Clone
 impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
     SliceStorageMut<'a, T, R, C, RStride, CStride>
 where
-    Self: ContiguousStorageMut<T, R, C>,
+    Self: RawStorageMut<T, R, C> + IsContiguous,
 {
     /// Extracts the original slice from this storage
     pub fn into_slice_mut(self) -> &'a mut [T] {
@@ -144,7 +144,7 @@ where
 
 macro_rules! storage_impl(
     ($($T: ident),* $(,)*) => {$(
-        unsafe impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Storage<T, R, C>
+        unsafe impl<'a, T, R: Dim, C: Dim, RStride: Dim, CStride: Dim> RawStorage<T, R, C>
             for $T<'a, T, R, C, RStride, CStride> {
 
             type RStride = RStride;
@@ -181,6 +181,21 @@ macro_rules! storage_impl(
                 }
             }
 
+            #[inline]
+            unsafe fn as_slice_unchecked(&self) -> &[T] {
+                let (nrows, ncols) = self.shape();
+                if nrows.value() != 0 && ncols.value() != 0 {
+                    let sz = self.linear_index(nrows.value() - 1, ncols.value() - 1);
+                    slice::from_raw_parts(self.ptr, sz + 1)
+                }
+                else {
+                    slice::from_raw_parts(self.ptr, 0)
+                }
+            }
+        }
+
+        unsafe impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Storage<T, R, C>
+            for $T<'a, T, R, C, RStride, CStride> {
             #[inline]
             fn into_owned(self) -> Owned<T, R, C>
                 where DefaultAllocator: Allocator<T, R, C> {
@@ -194,25 +209,13 @@ macro_rules! storage_impl(
                 let it = MatrixIter::new(self).cloned();
                 DefaultAllocator::allocate_from_iterator(nrows, ncols, it)
             }
-
-            #[inline]
-            unsafe fn as_slice_unchecked(&self) -> &[T] {
-                let (nrows, ncols) = self.shape();
-                if nrows.value() != 0 && ncols.value() != 0 {
-                    let sz = self.linear_index(nrows.value() - 1, ncols.value() - 1);
-                    slice::from_raw_parts(self.ptr, sz + 1)
-                }
-                else {
-                    slice::from_raw_parts(self.ptr, 0)
-                }
-            }
         }
     )*}
 );
 
 storage_impl!(SliceStorage, SliceStorageMut);
 
-unsafe impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> StorageMut<T, R, C>
+unsafe impl<'a, T, R: Dim, C: Dim, RStride: Dim, CStride: Dim> RawStorageMut<T, R, C>
     for SliceStorageMut<'a, T, R, C, RStride, CStride>
 {
     #[inline]
@@ -232,33 +235,22 @@ unsafe impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> StorageMu
     }
 }
 
-unsafe impl<'a, T: Scalar, R: Dim, CStride: Dim> ContiguousStorage<T, R, U1>
-    for SliceStorage<'a, T, R, U1, U1, CStride>
-{
-}
-unsafe impl<'a, T: Scalar, R: Dim, CStride: Dim> ContiguousStorage<T, R, U1>
-    for SliceStorageMut<'a, T, R, U1, U1, CStride>
-{
-}
-unsafe impl<'a, T: Scalar, R: Dim, CStride: Dim> ContiguousStorageMut<T, R, U1>
+unsafe impl<'a, T, R: Dim, CStride: Dim> IsContiguous for SliceStorage<'a, T, R, U1, U1, CStride> {}
+unsafe impl<'a, T, R: Dim, CStride: Dim> IsContiguous
     for SliceStorageMut<'a, T, R, U1, U1, CStride>
 {
 }
 
-unsafe impl<'a, T: Scalar, R: DimName, C: Dim + IsNotStaticOne> ContiguousStorage<T, R, C>
+unsafe impl<'a, T, R: DimName, C: Dim + IsNotStaticOne> IsContiguous
     for SliceStorage<'a, T, R, C, U1, R>
 {
 }
-unsafe impl<'a, T: Scalar, R: DimName, C: Dim + IsNotStaticOne> ContiguousStorage<T, R, C>
-    for SliceStorageMut<'a, T, R, C, U1, R>
-{
-}
-unsafe impl<'a, T: Scalar, R: DimName, C: Dim + IsNotStaticOne> ContiguousStorageMut<T, R, C>
+unsafe impl<'a, T, R: DimName, C: Dim + IsNotStaticOne> IsContiguous
     for SliceStorageMut<'a, T, R, C, U1, R>
 {
 }
 
-impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
+impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     #[inline]
     fn assert_slice_index(
         &self,
@@ -315,20 +307,20 @@ macro_rules! matrix_slice_impl(
          */
         /// Returns a slice containing the i-th row of this matrix.
         #[inline]
-        pub fn $row($me: $Me, i: usize) -> $MatrixSlice<T, U1, C, S::RStride, S::CStride> {
+        pub fn $row($me: $Me, i: usize) -> $MatrixSlice<'_, T, U1, C, S::RStride, S::CStride> {
             $me.$fixed_rows::<1>(i)
         }
 
         /// Returns a slice containing the `n` first elements of the i-th row of this matrix.
         #[inline]
-        pub fn $row_part($me: $Me, i: usize, n: usize) -> $MatrixSlice<T, U1, Dynamic, S::RStride, S::CStride> {
+        pub fn $row_part($me: $Me, i: usize, n: usize) -> $MatrixSlice<'_, T, U1, Dynamic, S::RStride, S::CStride> {
             $me.$generic_slice((i, 0), (Const::<1>, Dynamic::new(n)))
         }
 
         /// Extracts from this matrix a set of consecutive rows.
         #[inline]
         pub fn $rows($me: $Me, first_row: usize, nrows: usize)
-            -> $MatrixSlice<T, Dynamic, C, S::RStride, S::CStride> {
+            -> $MatrixSlice<'_, T, Dynamic, C, S::RStride, S::CStride> {
 
             $me.$rows_generic(first_row, Dynamic::new(nrows))
         }
@@ -336,7 +328,7 @@ macro_rules! matrix_slice_impl(
         /// Extracts from this matrix a set of consecutive rows regularly skipping `step` rows.
         #[inline]
         pub fn $rows_with_step($me: $Me, first_row: usize, nrows: usize, step: usize)
-            -> $MatrixSlice<T, Dynamic, C, Dynamic, S::CStride> {
+            -> $MatrixSlice<'_, T, Dynamic, C, Dynamic, S::CStride> {
 
             $me.$rows_generic_with_step(first_row, Dynamic::new(nrows), step)
         }
@@ -344,7 +336,7 @@ macro_rules! matrix_slice_impl(
         /// Extracts a compile-time number of consecutive rows from this matrix.
         #[inline]
         pub fn $fixed_rows<const RSLICE: usize>($me: $Me, first_row: usize)
-            -> $MatrixSlice<T, Const<RSLICE>, C, S::RStride, S::CStride> {
+            -> $MatrixSlice<'_, T, Const<RSLICE>, C, S::RStride, S::CStride> {
 
             $me.$rows_generic(first_row, Const::<RSLICE>)
         }
@@ -353,7 +345,7 @@ macro_rules! matrix_slice_impl(
         /// rows.
         #[inline]
         pub fn $fixed_rows_with_step<const RSLICE: usize>($me: $Me, first_row: usize, step: usize)
-            -> $MatrixSlice<T, Const<RSLICE>, C, Dynamic, S::CStride> {
+            -> $MatrixSlice<'_, T, Const<RSLICE>, C, Dynamic, S::CStride> {
 
             $me.$rows_generic_with_step(first_row, Const::<RSLICE>, step)
         }
@@ -362,9 +354,9 @@ macro_rules! matrix_slice_impl(
         /// argument may or may not be values known at compile-time.
         #[inline]
         pub fn $rows_generic<RSlice: Dim>($me: $Me, row_start: usize, nrows: RSlice)
-            -> $MatrixSlice<T, RSlice, C, S::RStride, S::CStride> {
+            -> $MatrixSlice<'_, T, RSlice, C, S::RStride, S::CStride> {
 
-            let my_shape   = $me.data.shape();
+            let my_shape   = $me.shape_generic();
             $me.assert_slice_index((row_start, 0), (nrows.value(), my_shape.1.value()), (0, 0));
 
             let shape = (nrows, my_shape.1);
@@ -379,10 +371,10 @@ macro_rules! matrix_slice_impl(
         /// argument may or may not be values known at compile-time.
         #[inline]
         pub fn $rows_generic_with_step<RSlice>($me: $Me, row_start: usize, nrows: RSlice, step: usize)
-            -> $MatrixSlice<T, RSlice, C, Dynamic, S::CStride>
+            -> $MatrixSlice<'_, T, RSlice, C, Dynamic, S::CStride>
             where RSlice: Dim {
 
-            let my_shape   = $me.data.shape();
+            let my_shape   = $me.shape_generic();
             let my_strides = $me.data.strides();
             $me.assert_slice_index((row_start, 0), (nrows.value(), my_shape.1.value()), (step, 0));
 
@@ -402,20 +394,20 @@ macro_rules! matrix_slice_impl(
          */
         /// Returns a slice containing the i-th column of this matrix.
         #[inline]
-        pub fn $column($me: $Me, i: usize) -> $MatrixSlice<T, R, U1, S::RStride, S::CStride> {
+        pub fn $column($me: $Me, i: usize) -> $MatrixSlice<'_, T, R, U1, S::RStride, S::CStride> {
             $me.$fixed_columns::<1>(i)
         }
 
         /// Returns a slice containing the `n` first elements of the i-th column of this matrix.
         #[inline]
-        pub fn $column_part($me: $Me, i: usize, n: usize) -> $MatrixSlice<T, Dynamic, U1, S::RStride, S::CStride> {
+        pub fn $column_part($me: $Me, i: usize, n: usize) -> $MatrixSlice<'_, T, Dynamic, U1, S::RStride, S::CStride> {
             $me.$generic_slice((0, i), (Dynamic::new(n), Const::<1>))
         }
 
         /// Extracts from this matrix a set of consecutive columns.
         #[inline]
         pub fn $columns($me: $Me, first_col: usize, ncols: usize)
-            -> $MatrixSlice<T, R, Dynamic, S::RStride, S::CStride> {
+            -> $MatrixSlice<'_, T, R, Dynamic, S::RStride, S::CStride> {
 
             $me.$columns_generic(first_col, Dynamic::new(ncols))
         }
@@ -424,7 +416,7 @@ macro_rules! matrix_slice_impl(
         /// columns.
         #[inline]
         pub fn $columns_with_step($me: $Me, first_col: usize, ncols: usize, step: usize)
-            -> $MatrixSlice<T, R, Dynamic, S::RStride, Dynamic> {
+            -> $MatrixSlice<'_, T, R, Dynamic, S::RStride, Dynamic> {
 
             $me.$columns_generic_with_step(first_col, Dynamic::new(ncols), step)
         }
@@ -432,7 +424,7 @@ macro_rules! matrix_slice_impl(
         /// Extracts a compile-time number of consecutive columns from this matrix.
         #[inline]
         pub fn $fixed_columns<const CSLICE: usize>($me: $Me, first_col: usize)
-            -> $MatrixSlice<T, R, Const<CSLICE>, S::RStride, S::CStride> {
+            -> $MatrixSlice<'_, T, R, Const<CSLICE>, S::RStride, S::CStride> {
 
             $me.$columns_generic(first_col, Const::<CSLICE>)
         }
@@ -441,7 +433,7 @@ macro_rules! matrix_slice_impl(
         /// `step` columns.
         #[inline]
         pub fn $fixed_columns_with_step<const CSLICE: usize>($me: $Me, first_col: usize, step: usize)
-            -> $MatrixSlice<T, R, Const<CSLICE>, S::RStride, Dynamic> {
+            -> $MatrixSlice<'_, T, R, Const<CSLICE>, S::RStride, Dynamic> {
 
             $me.$columns_generic_with_step(first_col, Const::<CSLICE>, step)
         }
@@ -450,9 +442,9 @@ macro_rules! matrix_slice_impl(
         /// known at compile-time.
         #[inline]
         pub fn $columns_generic<CSlice: Dim>($me: $Me, first_col: usize, ncols: CSlice)
-            -> $MatrixSlice<T, R, CSlice, S::RStride, S::CStride> {
+            -> $MatrixSlice<'_, T, R, CSlice, S::RStride, S::CStride> {
 
-            let my_shape = $me.data.shape();
+            let my_shape = $me.shape_generic();
             $me.assert_slice_index((0, first_col), (my_shape.0.value(), ncols.value()), (0, 0));
             let shape = (my_shape.0, ncols);
 
@@ -467,9 +459,9 @@ macro_rules! matrix_slice_impl(
         /// or may not be values known at compile-time.
         #[inline]
         pub fn $columns_generic_with_step<CSlice: Dim>($me: $Me, first_col: usize, ncols: CSlice, step: usize)
-            -> $MatrixSlice<T, R, CSlice, S::RStride, Dynamic> {
+            -> $MatrixSlice<'_, T, R, CSlice, S::RStride, Dynamic> {
 
-            let my_shape   = $me.data.shape();
+            let my_shape   = $me.shape_generic();
             let my_strides = $me.data.strides();
 
             $me.assert_slice_index((0, first_col), (my_shape.0.value(), ncols.value()), (0, step));
@@ -492,7 +484,7 @@ macro_rules! matrix_slice_impl(
         /// consecutive elements.
         #[inline]
         pub fn $slice($me: $Me, start: (usize, usize), shape: (usize, usize))
-            -> $MatrixSlice<T, Dynamic, Dynamic, S::RStride, S::CStride> {
+            -> $MatrixSlice<'_, T, Dynamic, Dynamic, S::RStride, S::CStride> {
 
             $me.assert_slice_index(start, shape, (0, 0));
             let shape = (Dynamic::new(shape.0), Dynamic::new(shape.1));
@@ -510,7 +502,7 @@ macro_rules! matrix_slice_impl(
         /// original matrix.
         #[inline]
         pub fn $slice_with_steps($me: $Me, start: (usize, usize), shape: (usize, usize), steps: (usize, usize))
-            -> $MatrixSlice<T, Dynamic, Dynamic, Dynamic, Dynamic> {
+            -> $MatrixSlice<'_, T, Dynamic, Dynamic, Dynamic, Dynamic> {
             let shape = (Dynamic::new(shape.0), Dynamic::new(shape.1));
 
             $me.$generic_slice_with_steps(start, shape, steps)
@@ -520,7 +512,7 @@ macro_rules! matrix_slice_impl(
         /// CSlice::dim())` consecutive components.
         #[inline]
         pub fn $fixed_slice<const RSLICE: usize, const CSLICE: usize>($me: $Me, irow: usize, icol: usize)
-            -> $MatrixSlice<T, Const<RSLICE>, Const<CSLICE>, S::RStride, S::CStride> {
+            -> $MatrixSlice<'_, T, Const<RSLICE>, Const<CSLICE>, S::RStride, S::CStride> {
 
             $me.assert_slice_index((irow, icol), (RSLICE, CSLICE), (0, 0));
             let shape = (Const::<RSLICE>, Const::<CSLICE>);
@@ -537,7 +529,7 @@ macro_rules! matrix_slice_impl(
         /// the original matrix.
         #[inline]
         pub fn $fixed_slice_with_steps<const RSLICE: usize, const CSLICE: usize>($me: $Me, start: (usize, usize), steps: (usize, usize))
-            -> $MatrixSlice<T, Const<RSLICE>, Const<CSLICE>, Dynamic, Dynamic> {
+            -> $MatrixSlice<'_, T, Const<RSLICE>, Const<CSLICE>, Dynamic, Dynamic> {
             let shape = (Const::<RSLICE>, Const::<CSLICE>);
             $me.$generic_slice_with_steps(start, shape, steps)
         }
@@ -545,7 +537,7 @@ macro_rules! matrix_slice_impl(
         /// Creates a slice that may or may not have a fixed size and stride.
         #[inline]
         pub fn $generic_slice<RSlice, CSlice>($me: $Me, start: (usize, usize), shape: (RSlice, CSlice))
-            -> $MatrixSlice<T, RSlice, CSlice, S::RStride, S::CStride>
+            -> $MatrixSlice<'_, T, RSlice, CSlice, S::RStride, S::CStride>
             where RSlice: Dim,
                   CSlice: Dim {
 
@@ -563,7 +555,7 @@ macro_rules! matrix_slice_impl(
                                                          start: (usize, usize),
                                                          shape: (RSlice, CSlice),
                                                          steps: (usize, usize))
-            -> $MatrixSlice<T, RSlice, CSlice, Dynamic, Dynamic>
+            -> $MatrixSlice<'_, T, RSlice, CSlice, Dynamic, Dynamic>
             where RSlice: Dim,
                   CSlice: Dim {
 
@@ -584,15 +576,15 @@ macro_rules! matrix_slice_impl(
          * Splitting.
          *
          */
-        /// Splits this NxM matrix into two parts delimited by two ranges.
+        /// Splits this `NxM` matrix into two parts delimited by two ranges.
         ///
         /// Panics if the ranges overlap or if the first range is empty.
         #[inline]
         pub fn $rows_range_pair<Range1: SliceRange<R>, Range2: SliceRange<R>>($me: $Me, r1: Range1, r2: Range2)
-            -> ($MatrixSlice<T, Range1::Size, C, S::RStride, S::CStride>,
-                $MatrixSlice<T, Range2::Size, C, S::RStride, S::CStride>) {
+            -> ($MatrixSlice<'_, T, Range1::Size, C, S::RStride, S::CStride>,
+                $MatrixSlice<'_, T, Range2::Size, C, S::RStride, S::CStride>) {
 
-            let (nrows, ncols) = $me.data.shape();
+            let (nrows, ncols) = $me.shape_generic();
             let strides        = $me.data.strides();
 
             let start1 = r1.begin(nrows);
@@ -620,15 +612,15 @@ macro_rules! matrix_slice_impl(
             }
         }
 
-        /// Splits this NxM matrix into two parts delimited by two ranges.
+        /// Splits this `NxM` matrix into two parts delimited by two ranges.
         ///
         /// Panics if the ranges overlap or if the first range is empty.
         #[inline]
         pub fn $columns_range_pair<Range1: SliceRange<C>, Range2: SliceRange<C>>($me: $Me, r1: Range1, r2: Range2)
-            -> ($MatrixSlice<T, R, Range1::Size, S::RStride, S::CStride>,
-                $MatrixSlice<T, R, Range2::Size, S::RStride, S::CStride>) {
+            -> ($MatrixSlice<'_, T, R, Range1::Size, S::RStride, S::CStride>,
+                $MatrixSlice<'_, T, R, Range2::Size, S::RStride, S::CStride>) {
 
-            let (nrows, ncols) = $me.data.shape();
+            let (nrows, ncols) = $me.shape_generic();
             let strides        = $me.data.strides();
 
             let start1 = r1.begin(ncols);
@@ -666,9 +658,9 @@ pub type MatrixSliceMut<'a, T, R, C, RStride = U1, CStride = R> =
     Matrix<T, R, C, SliceStorageMut<'a, T, R, C, RStride, CStride>>;
 
 /// # Slicing based on index and length
-impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
+impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     matrix_slice_impl!(
-     self: &Self, MatrixSlice, SliceStorage, Storage.get_address_unchecked(), &self.data;
+     self: &Self, MatrixSlice, SliceStorage, RawStorage.get_address_unchecked(), &self.data;
      row,
      row_part,
      rows,
@@ -696,9 +688,9 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
 }
 
 /// # Mutable slicing based on index and length
-impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
+impl<T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> Matrix<T, R, C, S> {
     matrix_slice_impl!(
-     self: &mut Self, MatrixSliceMut, SliceStorageMut, StorageMut.get_address_unchecked_mut(), &mut self.data;
+     self: &mut Self, MatrixSliceMut, SliceStorageMut, RawStorageMut.get_address_unchecked_mut(), &mut self.data;
      row_mut,
      row_part_mut,
      rows_mut,
@@ -861,7 +853,7 @@ impl<D: Dim> SliceRange<D> for RangeInclusive<usize> {
 
 // TODO: see how much of this overlaps with the general indexing
 // methods from indexing.rs.
-impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
+impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     /// Slices a sub-matrix containing the rows indexed by the range `rows` and the columns indexed
     /// by the range `cols`.
     #[inline]
@@ -870,12 +862,12 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         &self,
         rows: RowRange,
         cols: ColRange,
-    ) -> MatrixSlice<T, RowRange::Size, ColRange::Size, S::RStride, S::CStride>
+    ) -> MatrixSlice<'_, T, RowRange::Size, ColRange::Size, S::RStride, S::CStride>
     where
         RowRange: SliceRange<R>,
         ColRange: SliceRange<C>,
     {
-        let (nrows, ncols) = self.data.shape();
+        let (nrows, ncols) = self.shape_generic();
         self.generic_slice(
             (rows.begin(nrows), cols.begin(ncols)),
             (rows.size(nrows), cols.size(ncols)),
@@ -888,7 +880,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     pub fn rows_range<RowRange: SliceRange<R>>(
         &self,
         rows: RowRange,
-    ) -> MatrixSlice<T, RowRange::Size, C, S::RStride, S::CStride> {
+    ) -> MatrixSlice<'_, T, RowRange::Size, C, S::RStride, S::CStride> {
         self.slice_range(rows, ..)
     }
 
@@ -898,26 +890,26 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     pub fn columns_range<ColRange: SliceRange<C>>(
         &self,
         cols: ColRange,
-    ) -> MatrixSlice<T, R, ColRange::Size, S::RStride, S::CStride> {
+    ) -> MatrixSlice<'_, T, R, ColRange::Size, S::RStride, S::CStride> {
         self.slice_range(.., cols)
     }
 }
 
 // TODO: see how much of this overlaps with the general indexing
 // methods from indexing.rs.
-impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
+impl<T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> Matrix<T, R, C, S> {
     /// Slices a mutable sub-matrix containing the rows indexed by the range `rows` and the columns
     /// indexed by the range `cols`.
     pub fn slice_range_mut<RowRange, ColRange>(
         &mut self,
         rows: RowRange,
         cols: ColRange,
-    ) -> MatrixSliceMut<T, RowRange::Size, ColRange::Size, S::RStride, S::CStride>
+    ) -> MatrixSliceMut<'_, T, RowRange::Size, ColRange::Size, S::RStride, S::CStride>
     where
         RowRange: SliceRange<R>,
         ColRange: SliceRange<C>,
     {
-        let (nrows, ncols) = self.data.shape();
+        let (nrows, ncols) = self.shape_generic();
         self.generic_slice_mut(
             (rows.begin(nrows), cols.begin(ncols)),
             (rows.size(nrows), cols.size(ncols)),
@@ -929,7 +921,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
     pub fn rows_range_mut<RowRange: SliceRange<R>>(
         &mut self,
         rows: RowRange,
-    ) -> MatrixSliceMut<T, RowRange::Size, C, S::RStride, S::CStride> {
+    ) -> MatrixSliceMut<'_, T, RowRange::Size, C, S::RStride, S::CStride> {
         self.slice_range_mut(rows, ..)
     }
 
@@ -938,7 +930,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
     pub fn columns_range_mut<ColRange: SliceRange<C>>(
         &mut self,
         cols: ColRange,
-    ) -> MatrixSliceMut<T, R, ColRange::Size, S::RStride, S::CStride> {
+    ) -> MatrixSliceMut<'_, T, R, ColRange::Size, S::RStride, S::CStride> {
         self.slice_range_mut(.., cols)
     }
 }
@@ -946,7 +938,6 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
 impl<'a, T, R, C, RStride, CStride> From<MatrixSliceMut<'a, T, R, C, RStride, CStride>>
     for MatrixSlice<'a, T, R, C, RStride, CStride>
 where
-    T: Scalar,
     R: Dim,
     C: Dim,
     RStride: Dim,

src/base/min_max.rs

@@ -1,10 +1,10 @@
-use crate::storage::Storage;
+use crate::storage::RawStorage;
 use crate::{ComplexField, Dim, Matrix, Scalar, SimdComplexField, SimdPartialOrd, Vector};
 use num::{Signed, Zero};
 use simba::simd::SimdSigned;
 
 /// # Find the min and max components
-impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     /// Returns the absolute value of the component with the largest absolute value.
     /// # Example
     /// ```
@@ -40,8 +40,8 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         T: SimdComplexField,
     {
         self.fold_with(
-            |e| e.unwrap_or(&T::zero()).simd_norm1(),
-            |a, b| a.simd_max(b.simd_norm1()),
+            |e| e.unwrap_or(&T::zero()).clone().simd_norm1(),
+            |a, b| a.simd_max(b.clone().simd_norm1()),
         )
     }
 
@@ -60,8 +60,8 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         T: SimdPartialOrd + Zero,
     {
         self.fold_with(
-            |e| e.map(|e| e.inlined_clone()).unwrap_or_else(T::zero),
-            |a, b| a.simd_max(b.inlined_clone()),
+            |e| e.map(|e| e.clone()).unwrap_or_else(T::zero),
+            |a, b| a.simd_max(b.clone()),
         )
     }
 
@@ -101,10 +101,10 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     {
         self.fold_with(
             |e| {
-                e.map(|e| e.simd_norm1())
+                e.map(|e| e.clone().simd_norm1())
                     .unwrap_or_else(T::SimdRealField::zero)
             },
-            |a, b| a.simd_min(b.simd_norm1()),
+            |a, b| a.simd_min(b.clone().simd_norm1()),
         )
     }
 
@@ -123,8 +123,8 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         T: SimdPartialOrd + Zero,
     {
         self.fold_with(
-            |e| e.map(|e| e.inlined_clone()).unwrap_or_else(T::zero),
-            |a, b| a.simd_min(b.inlined_clone()),
+            |e| e.map(|e| e.clone()).unwrap_or_else(T::zero),
+            |a, b| a.simd_min(b.clone()),
         )
     }
 
@@ -149,12 +149,12 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     {
         assert!(!self.is_empty(), "The input matrix must not be empty.");
 
-        let mut the_max = unsafe { self.get_unchecked((0, 0)).norm1() };
+        let mut the_max = unsafe { self.get_unchecked((0, 0)).clone().norm1() };
         let mut the_ij = (0, 0);
 
         for j in 0..self.ncols() {
             for i in 0..self.nrows() {
-                let val = unsafe { self.get_unchecked((i, j)).norm1() };
+                let val = unsafe { self.get_unchecked((i, j)).clone().norm1() };
 
                 if val > the_max {
                     the_max = val;
@@ -167,7 +167,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     }
 }
 
-impl<T: Scalar + PartialOrd + Signed, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
+impl<T: Scalar + PartialOrd + Signed, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     /// Computes the index of the matrix component with the largest absolute value.
     ///
     /// # Examples:
@@ -203,7 +203,7 @@ impl<T: Scalar + PartialOrd + Signed, R: Dim, C: Dim, S: Storage<T, R, C>> Matri
 
 // TODO: find a way to avoid code duplication just for complex number support.
 /// # Find the min and max components (vector-specific methods)
-impl<T: Scalar, D: Dim, S: Storage<T, D>> Vector<T, D, S> {
+impl<T: Scalar, D: Dim, S: RawStorage<T, D>> Vector<T, D, S> {
     /// Computes the index of the vector component with the largest complex or real absolute value.
     ///
     /// # Examples:
@@ -224,11 +224,11 @@ impl<T: Scalar, D: Dim, S: Storage<T, D>> Vector<T, D, S> {
     {
         assert!(!self.is_empty(), "The input vector must not be empty.");
 
-        let mut the_max = unsafe { self.vget_unchecked(0).norm1() };
+        let mut the_max = unsafe { self.vget_unchecked(0).clone().norm1() };
         let mut the_i = 0;
 
         for i in 1..self.nrows() {
-            let val = unsafe { self.vget_unchecked(i).norm1() };
+            let val = unsafe { self.vget_unchecked(i).clone().norm1() };
 
             if val > the_max {
                 the_max = val;
@@ -268,7 +268,7 @@ impl<T: Scalar, D: Dim, S: Storage<T, D>> Vector<T, D, S> {
             }
         }
 
-        (the_i, the_max.inlined_clone())
+        (the_i, the_max.clone())
     }
 
     /// Computes the index of the vector component with the largest value.
@@ -350,7 +350,7 @@ impl<T: Scalar, D: Dim, S: Storage<T, D>> Vector<T, D, S> {
             }
         }
 
-        (the_i, the_min.inlined_clone())
+        (the_i, the_min.clone())
     }
 
     /// Computes the index of the vector component with the smallest value.

src/base/mod.rs

@@ -33,10 +33,13 @@ mod unit;
 #[cfg(any(feature = "std", feature = "alloc"))]
 mod vec_storage;
 
+mod blas_uninit;
 #[doc(hidden)]
 pub mod helper;
 mod interpolation;
 mod min_max;
+/// Mechanisms for working with values that may not be initialized.
+pub mod uninit;
 
 pub use self::matrix::*;
 pub use self::norm::*;
@@ -50,5 +53,6 @@ pub use self::alias::*;
 pub use self::alias_slice::*;
 pub use self::array_storage::*;
 pub use self::matrix_slice::*;
+pub use self::storage::*;
 #[cfg(any(feature = "std", feature = "alloc"))]
 pub use self::vec_storage::*;

src/base/norm.rs

@@ -40,10 +40,13 @@ pub trait Norm<T: SimdComplexField> {
 }
 
 /// Euclidean norm.
+#[derive(Copy, Clone, Debug)]
 pub struct EuclideanNorm;
 /// Lp norm.
+#[derive(Copy, Clone, Debug)]
 pub struct LpNorm(pub i32);
 /// L-infinite norm aka. Chebytchev norm aka. uniform norm aka. suppremum norm.
+#[derive(Copy, Clone, Debug)]
 pub struct UniformNorm;
 
 impl<T: SimdComplexField> Norm<T> for EuclideanNorm {
@@ -325,7 +328,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
     {
         let n = self.norm();
-        let le = n.simd_le(min_norm);
+        let le = n.clone().simd_le(min_norm);
         let val = self.unscale(n);
         SimdOption::new(val, le)
     }
@@ -374,7 +377,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
     {
         let n = self.norm();
-        let scaled = self.scale(max / n);
+        let scaled = self.scale(max.clone() / n.clone());
         let use_scaled = n.simd_gt(max);
         scaled.select(use_scaled, self.clone_owned())
     }
@@ -410,7 +413,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
         T: SimdComplexField,
     {
         let n = self.norm();
-        self.unscale_mut(n);
+        self.unscale_mut(n.clone());
 
         n
     }
@@ -430,8 +433,13 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
         DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
     {
         let n = self.norm();
-        let le = n.simd_le(min_norm);
-        self.apply(|e| e.simd_unscale(n).select(le, e));
+        let le = n.clone().simd_le(min_norm);
+        self.apply(|e| {
+            *e = e
+                .clone()
+                .simd_unscale(n.clone())
+                .select(le.clone(), e.clone())
+        });
         SimdOption::new(n, le)
     }
 
@@ -448,7 +456,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
         if n <= min_norm {
             None
         } else {
-            self.unscale_mut(n);
+            self.unscale_mut(n.clone());
             Some(n)
         }
     }
@@ -505,13 +513,8 @@ where
     /// The i-the canonical basis element.
     #[inline]
     fn canonical_basis_element(i: usize) -> Self {
-        assert!(i < D::dim(), "Index out of bound.");
-
         let mut res = Self::zero();
-        unsafe {
-            *res.data.get_unchecked_linear_mut(i) = T::one();
-        }
-
+        res[i] = T::one();
         res
     }
 
@@ -574,7 +577,7 @@ where
                         && f(&Self::canonical_basis_element(1));
                 } else if vs.len() == 1 {
                     let v = &vs[0];
-                    let res = Self::from_column_slice(&[-v[1], v[0]]);
+                    let res = Self::from_column_slice(&[-v[1].clone(), v[0].clone()]);
 
                     let _ = f(&res.normalize());
                 }
@@ -590,10 +593,10 @@ where
                     let v = &vs[0];
                     let mut a;
 
-                    if v[0].norm1() > v[1].norm1() {
-                        a = Self::from_column_slice(&[v[2], T::zero(), -v[0]]);
+                    if v[0].clone().norm1() > v[1].clone().norm1() {
+                        a = Self::from_column_slice(&[v[2].clone(), T::zero(), -v[0].clone()]);
                     } else {
-                        a = Self::from_column_slice(&[T::zero(), -v[2], v[1]]);
+                        a = Self::from_column_slice(&[T::zero(), -v[2].clone(), v[1].clone()]);
                     };
 
                     let _ = a.normalize_mut();

src/base/ops.rs

@@ -7,20 +7,25 @@ use std::ops::{
 use simba::scalar::{ClosedAdd, ClosedDiv, ClosedMul, ClosedNeg, ClosedSub};
 
 use crate::base::allocator::{Allocator, SameShapeAllocator, SameShapeC, SameShapeR};
+use crate::base::blas_uninit::gemm_uninit;
 use crate::base::constraint::{
     AreMultipliable, DimEq, SameNumberOfColumns, SameNumberOfRows, ShapeConstraint,
 };
 use crate::base::dimension::{Dim, DimMul, DimName, DimProd, Dynamic};
-use crate::base::storage::{ContiguousStorageMut, Storage, StorageMut};
+use crate::base::storage::{Storage, StorageMut};
+use crate::base::uninit::Uninit;
 use crate::base::{DefaultAllocator, Matrix, MatrixSum, OMatrix, Scalar, VectorSlice};
-use crate::SimdComplexField;
+use crate::storage::IsContiguous;
+use crate::uninit::{Init, InitStatus};
+use crate::{RawStorage, RawStorageMut, SimdComplexField};
+use std::mem::MaybeUninit;
 
 /*
  *
  * Indexing.
  *
  */
-impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Index<usize> for Matrix<T, R, C, S> {
+impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Index<usize> for Matrix<T, R, C, S> {
     type Output = T;
 
     #[inline]
@@ -30,11 +35,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Index<usize> for Matrix<T,
     }
 }
 
-impl<T, R: Dim, C: Dim, S> Index<(usize, usize)> for Matrix<T, R, C, S>
-where
-    T: Scalar,
-    S: Storage<T, R, C>,
-{
+impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Index<(usize, usize)> for Matrix<T, R, C, S> {
     type Output = T;
 
     #[inline]
@@ -50,7 +51,7 @@ where
 }
 
 // Mutable versions.
-impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> IndexMut<usize> for Matrix<T, R, C, S> {
+impl<T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> IndexMut<usize> for Matrix<T, R, C, S> {
     #[inline]
     fn index_mut(&mut self, i: usize) -> &mut T {
         let ij = self.vector_to_matrix_index(i);
@@ -58,11 +59,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> IndexMut<usize> for Matr
     }
 }
 
-impl<T, R: Dim, C: Dim, S> IndexMut<(usize, usize)> for Matrix<T, R, C, S>
-where
-    T: Scalar,
-    S: StorageMut<T, R, C>,
-{
+impl<T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> IndexMut<(usize, usize)> for Matrix<T, R, C, S> {
     #[inline]
     fn index_mut(&mut self, ij: (usize, usize)) -> &mut T {
         let shape = self.shape();
@@ -119,7 +116,7 @@ where
     #[inline]
     pub fn neg_mut(&mut self) {
         for e in self.iter_mut() {
-            *e = -e.inlined_clone()
+            *e = -e.clone()
         }
     }
 }
@@ -134,7 +131,7 @@ macro_rules! componentwise_binop_impl(
     ($Trait: ident, $method: ident, $bound: ident;
      $TraitAssign: ident, $method_assign: ident, $method_assign_statically_unchecked: ident,
      $method_assign_statically_unchecked_rhs: ident;
-     $method_to: ident, $method_to_statically_unchecked: ident) => {
+     $method_to: ident, $method_to_statically_unchecked_uninit: ident) => {
 
         impl<T, R1: Dim, C1: Dim, SA: Storage<T, R1, C1>> Matrix<T, R1, C1, SA>
             where T: Scalar + $bound {
@@ -147,12 +144,14 @@ macro_rules! componentwise_binop_impl(
              *
              */
             #[inline]
-            fn $method_to_statically_unchecked<R2: Dim, C2: Dim, SB,
-                                               R3: Dim, C3: Dim, SC>(&self,
+            fn $method_to_statically_unchecked_uninit<Status, R2: Dim, C2: Dim, SB,
+                                                       R3: Dim, C3: Dim, SC>(&self,
+                                                                     status: Status,
                                                                      rhs: &Matrix<T, R2, C2, SB>,
-                                                                     out: &mut Matrix<T, R3, C3, SC>)
-                where SB: Storage<T, R2, C2>,
-                      SC: StorageMut<T, R3, C3> {
+                                                                     out: &mut Matrix<Status::Value, R3, C3, SC>)
+                where Status: InitStatus<T>,
+                      SB: RawStorage<T, R2, C2>,
+                      SC: RawStorageMut<Status::Value, R3, C3> {
                 assert_eq!(self.shape(), rhs.shape(), "Matrix addition/subtraction dimensions mismatch.");
                 assert_eq!(self.shape(), out.shape(), "Matrix addition/subtraction output dimensions mismatch.");
 
@@ -164,13 +163,13 @@ macro_rules! componentwise_binop_impl(
                         let arr2 = rhs.data.as_slice_unchecked();
                         let out  = out.data.as_mut_slice_unchecked();
                         for i in 0 .. arr1.len() {
-                            *out.get_unchecked_mut(i) = arr1.get_unchecked(i).inlined_clone().$method(arr2.get_unchecked(i).inlined_clone());
+                            Status::init(out.get_unchecked_mut(i), arr1.get_unchecked(i).clone().$method(arr2.get_unchecked(i).clone()));
                         }
                     } else {
                         for j in 0 .. self.ncols() {
                             for i in 0 .. self.nrows() {
-                                let val = self.get_unchecked((i, j)).inlined_clone().$method(rhs.get_unchecked((i, j)).inlined_clone());
-                                *out.get_unchecked_mut((i, j)) = val;
+                                let val = self.get_unchecked((i, j)).clone().$method(rhs.get_unchecked((i, j)).clone());
+                                Status::init(out.get_unchecked_mut((i, j)), val);
                             }
                         }
                     }
@@ -194,12 +193,12 @@ macro_rules! componentwise_binop_impl(
                         let arr2 = rhs.data.as_slice_unchecked();
 
                         for i in 0 .. arr2.len() {
-                            arr1.get_unchecked_mut(i).$method_assign(arr2.get_unchecked(i).inlined_clone());
+                            arr1.get_unchecked_mut(i).$method_assign(arr2.get_unchecked(i).clone());
                         }
                     } else {
                         for j in 0 .. rhs.ncols() {
                             for i in 0 .. rhs.nrows() {
-                                self.get_unchecked_mut((i, j)).$method_assign(rhs.get_unchecked((i, j)).inlined_clone())
+                                self.get_unchecked_mut((i, j)).$method_assign(rhs.get_unchecked((i, j)).clone())
                             }
                         }
                     }
@@ -222,14 +221,14 @@ macro_rules! componentwise_binop_impl(
                         let arr2 = rhs.data.as_mut_slice_unchecked();
 
                         for i in 0 .. arr1.len() {
-                            let res = arr1.get_unchecked(i).inlined_clone().$method(arr2.get_unchecked(i).inlined_clone());
+                            let res = arr1.get_unchecked(i).clone().$method(arr2.get_unchecked(i).clone());
                             *arr2.get_unchecked_mut(i) = res;
                         }
                     } else {
                         for j in 0 .. self.ncols() {
                             for i in 0 .. self.nrows() {
                                 let r = rhs.get_unchecked_mut((i, j));
-                                *r = self.get_unchecked((i, j)).inlined_clone().$method(r.inlined_clone())
+                                *r = self.get_unchecked((i, j)).clone().$method(r.clone())
                             }
                         }
                     }
@@ -254,7 +253,7 @@ macro_rules! componentwise_binop_impl(
                       SC: StorageMut<T, R3, C3>,
                       ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> +
                                        SameNumberOfRows<R1, R3> + SameNumberOfColumns<C1, C3> {
-                self.$method_to_statically_unchecked(rhs, out)
+                self.$method_to_statically_unchecked_uninit(Init, rhs, out)
             }
         }
 
@@ -320,15 +319,13 @@ macro_rules! componentwise_binop_impl(
 
             #[inline]
             fn $method(self, rhs: &'b Matrix<T, R2, C2, SB>) -> Self::Output {
-                let mut res = unsafe {
-                    let (nrows, ncols) = self.shape();
-                    let nrows: SameShapeR<R1, R2> = Dim::from_usize(nrows);
-                    let ncols: SameShapeC<C1, C2> = Dim::from_usize(ncols);
-                    crate::unimplemented_or_uninitialized_generic!(nrows, ncols)
-                };
-
-                self.$method_to_statically_unchecked(rhs, &mut res);
-                res
+                let (nrows, ncols) = self.shape();
+                let nrows: SameShapeR<R1, R2> = Dim::from_usize(nrows);
+                let ncols: SameShapeC<C1, C2> = Dim::from_usize(ncols);
+                let mut res = Matrix::uninit(nrows, ncols);
+                self.$method_to_statically_unchecked_uninit(Uninit, rhs, &mut res);
+                // SAFETY: the output has been initialized above.
+                unsafe { res.assume_init() }
             }
         }
 
@@ -362,10 +359,10 @@ macro_rules! componentwise_binop_impl(
 
 componentwise_binop_impl!(Add, add, ClosedAdd;
                           AddAssign, add_assign, add_assign_statically_unchecked, add_assign_statically_unchecked_mut;
-                          add_to, add_to_statically_unchecked);
+                          add_to, add_to_statically_unchecked_uninit);
 componentwise_binop_impl!(Sub, sub, ClosedSub;
                           SubAssign, sub_assign, sub_assign_statically_unchecked, sub_assign_statically_unchecked_mut;
-                          sub_to, sub_to_statically_unchecked);
+                          sub_to, sub_to_statically_unchecked_uninit);
 
 impl<T, R: DimName, C: DimName> iter::Sum for OMatrix<T, R, C>
 where
@@ -475,7 +472,7 @@ macro_rules! componentwise_scalarop_impl(
 
                 // for left in res.iter_mut() {
                 for left in res.as_mut_slice().iter_mut() {
-                    *left = left.inlined_clone().$method(rhs.inlined_clone())
+                    *left = left.clone().$method(rhs.clone())
                 }
 
                 res
@@ -501,7 +498,7 @@ macro_rules! componentwise_scalarop_impl(
             fn $method_assign(&mut self, rhs: T) {
                 for j in 0 .. self.ncols() {
                     for i in 0 .. self.nrows() {
-                        unsafe { self.get_unchecked_mut((i, j)).$method_assign(rhs.inlined_clone()) };
+                        unsafe { self.get_unchecked_mut((i, j)).$method_assign(rhs.clone()) };
                     }
                 }
             }
@@ -564,11 +561,12 @@ where
 
     #[inline]
     fn mul(self, rhs: &'b Matrix<T, R2, C2, SB>) -> Self::Output {
-        let mut res = unsafe {
-            crate::unimplemented_or_uninitialized_generic!(self.data.shape().0, rhs.data.shape().1)
-        };
-        self.mul_to(rhs, &mut res);
-        res
+        let mut res = Matrix::uninit(self.shape_generic().0, rhs.shape_generic().1);
+        unsafe {
+            // SAFETY: this is OK because status = Uninit && bevy == 0
+            gemm_uninit(Uninit, &mut res, T::one(), self, rhs, T::zero());
+            res.assume_init()
+        }
     }
 }
 
@@ -633,7 +631,7 @@ where
     R2: Dim,
     T: Scalar + Zero + One + ClosedAdd + ClosedMul,
     SB: Storage<T, R2, C1>,
-    SA: ContiguousStorageMut<T, R1, C1> + Clone,
+    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>,
 {
@@ -650,7 +648,7 @@ where
     R2: Dim,
     T: Scalar + Zero + One + ClosedAdd + ClosedMul,
     SB: Storage<T, R2, C1>,
-    SA: ContiguousStorageMut<T, R1, C1> + Clone,
+    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>,
@@ -676,12 +674,10 @@ where
         DefaultAllocator: Allocator<T, C1, C2>,
         ShapeConstraint: SameNumberOfRows<R1, R2>,
     {
-        let mut res = unsafe {
-            crate::unimplemented_or_uninitialized_generic!(self.data.shape().1, rhs.data.shape().1)
-        };
-
-        self.tr_mul_to(rhs, &mut res);
-        res
+        let mut res = Matrix::uninit(self.shape_generic().1, rhs.shape_generic().1);
+        self.xx_mul_to_uninit(Uninit, rhs, &mut res, |a, b| a.dot(b));
+        // SAFETY: this is OK because the result is now initialized.
+        unsafe { res.assume_init() }
     }
 
     /// Equivalent to `self.adjoint() * rhs`.
@@ -694,26 +690,26 @@ where
         DefaultAllocator: Allocator<T, C1, C2>,
         ShapeConstraint: SameNumberOfRows<R1, R2>,
     {
-        let mut res = unsafe {
-            crate::unimplemented_or_uninitialized_generic!(self.data.shape().1, rhs.data.shape().1)
-        };
-
-        self.ad_mul_to(rhs, &mut res);
-        res
+        let mut res = Matrix::uninit(self.shape_generic().1, rhs.shape_generic().1);
+        self.xx_mul_to_uninit(Uninit, rhs, &mut res, |a, b| a.dotc(b));
+        // SAFETY: this is OK because the result is now initialized.
+        unsafe { res.assume_init() }
     }
 
     #[inline(always)]
-    fn xx_mul_to<R2: Dim, C2: Dim, SB, R3: Dim, C3: Dim, SC>(
+    fn xx_mul_to_uninit<Status, R2: Dim, C2: Dim, SB, R3: Dim, C3: Dim, SC>(
         &self,
+        status: Status,
         rhs: &Matrix<T, R2, C2, SB>,
-        out: &mut Matrix<T, R3, C3, SC>,
+        out: &mut Matrix<Status::Value, R3, C3, SC>,
         dot: impl Fn(
-            &VectorSlice<T, R1, SA::RStride, SA::CStride>,
-            &VectorSlice<T, R2, SB::RStride, SB::CStride>,
+            &VectorSlice<'_, T, R1, SA::RStride, SA::CStride>,
+            &VectorSlice<'_, T, R2, SB::RStride, SB::CStride>,
         ) -> T,
     ) where
-        SB: Storage<T, R2, C2>,
-        SC: StorageMut<T, R3, C3>,
+        Status: InitStatus<T>,
+        SB: RawStorage<T, R2, C2>,
+        SC: RawStorageMut<Status::Value, R3, C3>,
         ShapeConstraint: SameNumberOfRows<R1, R2> + DimEq<C1, R3> + DimEq<C2, C3>,
     {
         let (nrows1, ncols1) = self.shape();
@@ -742,7 +738,8 @@ where
         for i in 0..ncols1 {
             for j in 0..ncols2 {
                 let dot = dot(&self.column(i), &rhs.column(j));
-                unsafe { *out.get_unchecked_mut((i, j)) = dot };
+                let elt = unsafe { out.get_unchecked_mut((i, j)) };
+                Status::init(elt, dot);
             }
         }
     }
@@ -759,7 +756,7 @@ where
         SC: StorageMut<T, R3, C3>,
         ShapeConstraint: SameNumberOfRows<R1, R2> + DimEq<C1, R3> + DimEq<C2, C3>,
     {
-        self.xx_mul_to(rhs, out, |a, b| a.dot(b))
+        self.xx_mul_to_uninit(Init, rhs, out, |a, b| a.dot(b))
     }
 
     /// Equivalent to `self.adjoint() * rhs` but stores the result into `out` to avoid
@@ -775,7 +772,7 @@ where
         SC: StorageMut<T, R3, C3>,
         ShapeConstraint: SameNumberOfRows<R1, R2> + DimEq<C1, R3> + DimEq<C2, C3>,
     {
-        self.xx_mul_to(rhs, out, |a, b| a.dotc(b))
+        self.xx_mul_to_uninit(Init, rhs, out, |a, b| a.dotc(b))
     }
 
     /// Equivalent to `self * rhs` but stores the result into `out` to avoid allocations.
@@ -808,34 +805,31 @@ where
         SB: Storage<T, R2, C2>,
         DefaultAllocator: Allocator<T, DimProd<R1, R2>, DimProd<C1, C2>>,
     {
-        let (nrows1, ncols1) = self.data.shape();
-        let (nrows2, ncols2) = rhs.data.shape();
+        let (nrows1, ncols1) = self.shape_generic();
+        let (nrows2, ncols2) = rhs.shape_generic();
 
-        let mut res = unsafe {
-            crate::unimplemented_or_uninitialized_generic!(nrows1.mul(nrows2), ncols1.mul(ncols2))
-        };
-
-        {
-            let mut data_res = res.data.ptr_mut();
+        let mut res = Matrix::uninit(nrows1.mul(nrows2), ncols1.mul(ncols2));
+        let mut data_res = res.data.ptr_mut();
 
+        unsafe {
             for j1 in 0..ncols1.value() {
                 for j2 in 0..ncols2.value() {
                     for i1 in 0..nrows1.value() {
-                        unsafe {
-                            let coeff = self.get_unchecked((i1, j1)).inlined_clone();
+                        let coeff = self.get_unchecked((i1, j1)).clone();
 
-                            for i2 in 0..nrows2.value() {
-                                *data_res = coeff.inlined_clone()
-                                    * rhs.get_unchecked((i2, j2)).inlined_clone();
-                                data_res = data_res.offset(1);
-                            }
+                        for i2 in 0..nrows2.value() {
+                            *data_res = MaybeUninit::new(
+                                coeff.clone() * rhs.get_unchecked((i2, j2)).clone(),
+                            );
+                            data_res = data_res.offset(1);
                         }
                     }
                 }
             }
-        }
 
-        res
+            // SAFETY: the result matrix has been initialized by the loop above.
+            res.assume_init()
+        }
     }
 }
 

src/base/properties.rs

@@ -8,8 +8,9 @@ use crate::base::allocator::Allocator;
 use crate::base::dimension::{Dim, DimMin};
 use crate::base::storage::Storage;
 use crate::base::{DefaultAllocator, Matrix, Scalar, SquareMatrix};
+use crate::RawStorage;
 
-impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     /// The total number of elements of this matrix.
     ///
     /// # Examples:
@@ -59,7 +60,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     pub fn is_identity(&self, eps: T::Epsilon) -> bool
     where
         T: Zero + One + RelativeEq,
-        T::Epsilon: Copy,
+        T::Epsilon: Clone,
     {
         let (nrows, ncols) = self.shape();
         let d;
@@ -69,7 +70,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
 
             for i in d..nrows {
                 for j in 0..ncols {
-                    if !relative_eq!(self[(i, j)], T::zero(), epsilon = eps) {
+                    if !relative_eq!(self[(i, j)], T::zero(), epsilon = eps.clone()) {
                         return false;
                     }
                 }
@@ -80,7 +81,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
 
             for i in 0..nrows {
                 for j in d..ncols {
-                    if !relative_eq!(self[(i, j)], T::zero(), epsilon = eps) {
+                    if !relative_eq!(self[(i, j)], T::zero(), epsilon = eps.clone()) {
                         return false;
                     }
                 }
@@ -91,8 +92,8 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         for i in 1..d {
             for j in 0..i {
                 // TODO: use unsafe indexing.
-                if !relative_eq!(self[(i, j)], T::zero(), epsilon = eps)
-                    || !relative_eq!(self[(j, i)], T::zero(), epsilon = eps)
+                if !relative_eq!(self[(i, j)], T::zero(), epsilon = eps.clone())
+                    || !relative_eq!(self[(j, i)], T::zero(), epsilon = eps.clone())
                 {
                     return false;
                 }
@@ -101,7 +102,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
 
         // Diagonal elements of the sub-square matrix.
         for i in 0..d {
-            if !relative_eq!(self[(i, i)], T::one(), epsilon = eps) {
+            if !relative_eq!(self[(i, i)], T::one(), epsilon = eps.clone()) {
                 return false;
             }
         }
@@ -121,7 +122,7 @@ impl<T: ComplexField, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     where
         T: Zero + One + ClosedAdd + ClosedMul + RelativeEq,
         S: Storage<T, R, C>,
-        T::Epsilon: Copy,
+        T::Epsilon: Clone,
         DefaultAllocator: Allocator<T, R, C> + Allocator<T, C, C>,
     {
         (self.ad_mul(self)).is_identity(eps)

src/base/scalar.rs

@@ -1,29 +1,8 @@
-use std::any::Any;
-use std::any::TypeId;
 use std::fmt::Debug;
 
 /// The basic scalar type for all structures of `nalgebra`.
 ///
 /// This does not make any assumption on the algebraic properties of `Self`.
-pub trait Scalar: Clone + PartialEq + Debug + Any {
-    #[inline]
-    /// Tests if `Self` the same as the type `T`
-    ///
-    /// Typically used to test of `Self` is a f32 or a f64 with `T::is::<f32>()`.
-    fn is<T: Scalar>() -> bool {
-        TypeId::of::<Self>() == TypeId::of::<T>()
-    }
+pub trait Scalar: 'static + Clone + PartialEq + Debug {}
 
-    #[inline(always)]
-    /// Performance hack: Clone doesn't get inlined for Copy types in debug mode, so make it inline anyway.
-    fn inlined_clone(&self) -> Self {
-        self.clone()
-    }
-}
-
-impl<T: Copy + PartialEq + Debug + Any> Scalar for T {
-    #[inline(always)]
-    fn inlined_clone(&self) -> T {
-        *self
-    }
-}
+impl<T: 'static + Clone + PartialEq + Debug> Scalar for T {}

src/base/statistics.rs

@@ -1,34 +1,36 @@
 use crate::allocator::Allocator;
-use crate::storage::Storage;
+use crate::storage::RawStorage;
 use crate::{Const, DefaultAllocator, Dim, Matrix, OVector, RowOVector, Scalar, VectorSlice, U1};
 use num::Zero;
 use simba::scalar::{ClosedAdd, Field, SupersetOf};
+use std::mem::MaybeUninit;
 
 /// # Folding on columns and rows
-impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     /// Returns a row vector where each element is the result of the application of `f` on the
     /// corresponding column of the original matrix.
     #[inline]
     #[must_use]
     pub fn compress_rows(
         &self,
-        f: impl Fn(VectorSlice<T, R, S::RStride, S::CStride>) -> T,
+        f: impl Fn(VectorSlice<'_, T, R, S::RStride, S::CStride>) -> T,
     ) -> RowOVector<T, C>
     where
         DefaultAllocator: Allocator<T, U1, C>,
     {
-        let ncols = self.data.shape().1;
-        let mut res: RowOVector<T, C> =
-            unsafe { crate::unimplemented_or_uninitialized_generic!(Const::<1>, ncols) };
+        let ncols = self.shape_generic().1;
+        let mut res = Matrix::uninit(Const::<1>, ncols);
 
         for i in 0..ncols.value() {
             // TODO: avoid bound checking of column.
+            // Safety: all indices are in range.
             unsafe {
-                *res.get_unchecked_mut((0, i)) = f(self.column(i));
+                *res.get_unchecked_mut((0, i)) = MaybeUninit::new(f(self.column(i)));
             }
         }
 
-        res
+        // Safety: res is now fully initialized.
+        unsafe { res.assume_init() }
     }
 
     /// Returns a column vector where each element is the result of the application of `f` on the
@@ -39,23 +41,24 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     #[must_use]
     pub fn compress_rows_tr(
         &self,
-        f: impl Fn(VectorSlice<T, R, S::RStride, S::CStride>) -> T,
+        f: impl Fn(VectorSlice<'_, T, R, S::RStride, S::CStride>) -> T,
     ) -> OVector<T, C>
     where
         DefaultAllocator: Allocator<T, C>,
     {
-        let ncols = self.data.shape().1;
-        let mut res: OVector<T, C> =
-            unsafe { crate::unimplemented_or_uninitialized_generic!(ncols, Const::<1>) };
+        let ncols = self.shape_generic().1;
+        let mut res = Matrix::uninit(ncols, Const::<1>);
 
         for i in 0..ncols.value() {
             // TODO: avoid bound checking of column.
+            // Safety: all indices are in range.
             unsafe {
-                *res.vget_unchecked_mut(i) = f(self.column(i));
+                *res.vget_unchecked_mut(i) = MaybeUninit::new(f(self.column(i)));
             }
         }
 
-        res
+        // Safety: res is now fully initialized.
+        unsafe { res.assume_init() }
     }
 
     /// Returns a column vector resulting from the folding of `f` on each column of this matrix.
@@ -64,7 +67,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     pub fn compress_columns(
         &self,
         init: OVector<T, R>,
-        f: impl Fn(&mut OVector<T, R>, VectorSlice<T, R, S::RStride, S::CStride>),
+        f: impl Fn(&mut OVector<T, R>, VectorSlice<'_, T, R, S::RStride, S::CStride>),
     ) -> OVector<T, R>
     where
         DefaultAllocator: Allocator<T, R>,
@@ -80,7 +83,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
 }
 
 /// # Common statistics operations
-impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
     /*
      *
      * Sum computation.
@@ -108,7 +111,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
 
     /// The sum of all the rows of this matrix.
     ///
-    /// Use `.row_variance_tr` if you need the result in a column vector instead.
+    /// Use `.row_sum_tr` if you need the result in a column vector instead.
     ///
     /// # Example
     ///
@@ -180,7 +183,7 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         T: ClosedAdd + Zero,
         DefaultAllocator: Allocator<T, R>,
     {
-        let nrows = self.data.shape().0;
+        let nrows = self.shape_generic().0;
         self.compress_columns(OVector::zeros_generic(nrows, Const::<1>), |out, col| {
             *out += col;
         })
@@ -213,11 +216,11 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
             T::zero()
         } else {
             let val = self.iter().cloned().fold((T::zero(), T::zero()), |a, b| {
-                (a.0 + b.inlined_clone() * b.inlined_clone(), a.1 + b)
+                (a.0 + b.clone() * b.clone(), a.1 + b)
             });
             let denom = T::one() / crate::convert::<_, T>(self.len() as f64);
-            let vd = val.1 * denom.inlined_clone();
-            val.0 * denom - vd.inlined_clone() * vd
+            let vd = val.1 * denom.clone();
+            val.0 * denom - vd.clone() * vd
         }
     }
 
@@ -283,18 +286,17 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         T: Field + SupersetOf<f64>,
         DefaultAllocator: Allocator<T, R>,
     {
-        let (nrows, ncols) = self.data.shape();
+        let (nrows, ncols) = self.shape_generic();
 
         let mut mean = self.column_mean();
-        mean.apply(|e| -(e.inlined_clone() * e));
+        mean.apply(|e| *e = -(e.clone() * e.clone()));
 
         let denom = T::one() / crate::convert::<_, T>(ncols.value() as f64);
         self.compress_columns(mean, |out, col| {
             for i in 0..nrows.value() {
                 unsafe {
                     let val = col.vget_unchecked(i);
-                    *out.vget_unchecked_mut(i) +=
-                        denom.inlined_clone() * val.inlined_clone() * val.inlined_clone()
+                    *out.vget_unchecked_mut(i) += denom.clone() * val.clone() * val.clone()
                 }
             }
         })
@@ -391,10 +393,10 @@ impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
         T: Field + SupersetOf<f64>,
         DefaultAllocator: Allocator<T, R>,
     {
-        let (nrows, ncols) = self.data.shape();
+        let (nrows, ncols) = self.shape_generic();
         let denom = T::one() / crate::convert::<_, T>(ncols.value() as f64);
         self.compress_columns(OVector::zeros_generic(nrows, Const::<1>), |out, col| {
-            out.axpy(denom.inlined_clone(), &col, T::one())
+            out.axpy(denom.clone(), &col, T::one())
         })
     }
 }

src/base/storage.rs

@@ -1,6 +1,5 @@
 //! Abstract definition of a matrix data storage.
 
-use std::fmt::Debug;
 use std::ptr;
 
 use crate::base::allocator::{Allocator, SameShapeC, SameShapeR};
@@ -19,24 +18,30 @@ pub type SameShapeStorage<T, R1, C1, R2, C2> =
 /// The owned data storage that can be allocated from `S`.
 pub type Owned<T, R, C = U1> = <DefaultAllocator as Allocator<T, R, C>>::Buffer;
 
+/// The owned data storage that can be allocated from `S`.
+pub type OwnedUninit<T, R, C = U1> = <DefaultAllocator as Allocator<T, R, C>>::BufferUninit;
+
 /// The row-stride of the owned data storage for a buffer of dimension `(R, C)`.
 pub type RStride<T, R, C = U1> =
-    <<DefaultAllocator as Allocator<T, R, C>>::Buffer as Storage<T, R, C>>::RStride;
+    <<DefaultAllocator as Allocator<T, R, C>>::Buffer as RawStorage<T, R, C>>::RStride;
 
 /// The column-stride of the owned data storage for a buffer of dimension `(R, C)`.
 pub type CStride<T, R, C = U1> =
-    <<DefaultAllocator as Allocator<T, R, C>>::Buffer as Storage<T, R, C>>::CStride;
+    <<DefaultAllocator as Allocator<T, R, C>>::Buffer as RawStorage<T, R, C>>::CStride;
 
 /// The trait shared by all matrix data storage.
 ///
 /// TODO: doc
+/// In generic code, it is recommended use the `Storage` trait bound instead. The `RawStorage`
+/// trait bound is generally used by code that needs to work with storages that contains
+/// `MaybeUninit<T>` elements.
 ///
 /// Note that `Self` must always have a number of elements compatible with the matrix length (given
 /// by `R` and `C` if they are known at compile-time). For example, implementors of this trait
 /// should **not** allow the user to modify the size of the underlying buffer with safe methods
 /// (for example the `VecStorage::data_mut` method is unsafe because the user could change the
 /// vector's size so that it no longer contains enough elements: this will lead to UB.
-pub unsafe trait Storage<T: Scalar, R: Dim, C: Dim = U1>: Debug + Sized {
+pub unsafe trait RawStorage<T, R: Dim, C: Dim = U1>: Sized {
     /// The static stride of this storage's rows.
     type RStride: Dim;
 
@@ -121,7 +126,10 @@ pub unsafe trait Storage<T: Scalar, R: Dim, C: Dim = U1>: Debug + Sized {
     ///
     /// Call the safe alternative `matrix.as_slice()` instead.
     unsafe fn as_slice_unchecked(&self) -> &[T];
+}
 
+/// Trait shared by all matrix data storage that don’t contain any uninitialized elements.
+pub unsafe trait Storage<T, R: Dim, C: Dim = U1>: RawStorage<T, R, C> {
     /// Builds a matrix data storage that does not contain any reference.
     fn into_owned(self) -> Owned<T, R, C>
     where
@@ -135,10 +143,14 @@ pub unsafe trait Storage<T: Scalar, R: Dim, C: Dim = U1>: Debug + Sized {
 
 /// Trait implemented by matrix data storage that can provide a mutable access to its elements.
 ///
+/// In generic code, it is recommended use the `StorageMut` trait bound instead. The
+/// `RawStorageMut` trait bound is generally used by code that needs to work with storages that
+/// contains `MaybeUninit<T>` elements.
+///
 /// Note that a mutable access does not mean that the matrix owns its data. For example, a mutable
 /// matrix slice can provide mutable access to its elements even if it does not own its data (it
 /// contains only an internal reference to them).
-pub unsafe trait StorageMut<T: Scalar, R: Dim, C: Dim = U1>: Storage<T, R, C> {
+pub unsafe trait RawStorageMut<T, R: Dim, C: Dim = U1>: RawStorage<T, R, C> {
     /// The matrix mutable data pointer.
     fn ptr_mut(&mut self) -> *mut T;
 
@@ -213,40 +225,29 @@ pub unsafe trait StorageMut<T: Scalar, R: Dim, C: Dim = U1>: Storage<T, R, C> {
     unsafe fn as_mut_slice_unchecked(&mut self) -> &mut [T];
 }
 
-/// A matrix storage that is stored contiguously in memory.
-///
-/// The storage requirement means that for any value of `i` in `[0, nrows * ncols - 1]`, the value
-/// `.get_unchecked_linear` returns one of the matrix component. This trait is unsafe because
-/// failing to comply to this may cause Undefined Behaviors.
-pub unsafe trait ContiguousStorage<T: Scalar, R: Dim, C: Dim = U1>:
-    Storage<T, R, C>
+/// Trait shared by all mutable matrix data storage that don’t contain any uninitialized elements.
+pub unsafe trait StorageMut<T, R: Dim, C: Dim = U1>:
+    Storage<T, R, C> + RawStorageMut<T, R, C>
 {
-    /// Converts this data storage to a contiguous slice.
-    fn as_slice(&self) -> &[T] {
-        // SAFETY: this is safe because this trait guarantees the fact
-        //         that the data is stored contiguously.
-        unsafe { self.as_slice_unchecked() }
-    }
 }
 
-/// A mutable matrix storage that is stored contiguously in memory.
+unsafe impl<S, T, R, C> StorageMut<T, R, C> for S
+where
+    R: Dim,
+    C: Dim,
+    S: Storage<T, R, C> + RawStorageMut<T, R, C>,
+{
+}
+
+/// Marker trait indicating that a storage is stored contiguously in memory.
 ///
 /// The storage requirement means that for any value of `i` in `[0, nrows * ncols - 1]`, the value
 /// `.get_unchecked_linear` returns one of the matrix component. This trait is unsafe because
 /// failing to comply to this may cause Undefined Behaviors.
-pub unsafe trait ContiguousStorageMut<T: Scalar, R: Dim, C: Dim = U1>:
-    ContiguousStorage<T, R, C> + StorageMut<T, R, C>
-{
-    /// Converts this data storage to a contiguous mutable slice.
-    fn as_mut_slice(&mut self) -> &mut [T] {
-        // SAFETY: this is safe because this trait guarantees the fact
-        //         that the data is stored contiguously.
-        unsafe { self.as_mut_slice_unchecked() }
-    }
-}
+pub unsafe trait IsContiguous {}
 
 /// A matrix storage that can be reshaped in-place.
-pub trait ReshapableStorage<T, R1, C1, R2, C2>: Storage<T, R1, C1>
+pub trait ReshapableStorage<T, R1, C1, R2, C2>: RawStorage<T, R1, C1>
 where
     T: Scalar,
     R1: Dim,
@@ -255,7 +256,7 @@ where
     C2: Dim,
 {
     /// The reshaped storage type.
-    type Output: Storage<T, R2, C2>;
+    type Output: RawStorage<T, R2, C2>;
 
     /// Reshapes the storage into the output storage type.
     fn reshape_generic(self, nrows: R2, ncols: C2) -> Self::Output;

src/base/swizzle.rs

@@ -1,5 +1,5 @@
 use crate::base::{DimName, Scalar, ToTypenum, Vector, Vector2, Vector3};
-use crate::storage::Storage;
+use crate::storage::RawStorage;
 use typenum::{self, Cmp, Greater};
 
 macro_rules! impl_swizzle {
@@ -11,7 +11,7 @@ macro_rules! impl_swizzle {
                 #[must_use]
                 pub fn $name(&self) -> $Result<T>
                 where D::Typenum: Cmp<typenum::$BaseDim, Output=Greater> {
-                    $Result::new($(self[$i].inlined_clone()),*)
+                    $Result::new($(self[$i].clone()),*)
                 }
             )*
         )*
@@ -19,7 +19,7 @@ macro_rules! impl_swizzle {
 }
 
 /// # Swizzling
-impl<T: Scalar, D, S: Storage<T, D>> Vector<T, D, S>
+impl<T: Scalar, D, S: RawStorage<T, D>> Vector<T, D, S>
 where
     D: DimName + ToTypenum,
 {

src/base/uninit.rs

@@ -0,0 +1,76 @@
+use std::mem::MaybeUninit;
+
+/// This trait is used to write code that may work on matrices that may or may not
+/// be initialized.
+///
+/// This trait is used to describe how a value must be accessed to initialize it or
+/// to retrieve a reference or mutable reference. Typically, a function accepting
+/// both initialized and uninitialized inputs should have a `Status: InitStatus<T>`
+/// type parameter. Then the methods of the `Status` can be used to access the element.
+///
+/// # Safety
+/// This trait must not be implemented outside of this crate.
+pub unsafe trait InitStatus<T>: Copy {
+    /// The type of the values with the initialization status described by `Self`.
+    type Value;
+
+    /// Initialize the given element.
+    fn init(out: &mut Self::Value, t: T);
+
+    /// Retrieve a reference to the element, assuming that it is initialized.
+    ///
+    /// # Safety
+    /// This is unsound if the referenced value isn’t initialized.
+    unsafe fn assume_init_ref(t: &Self::Value) -> &T;
+
+    /// Retrieve a mutable reference to the element, assuming that it is initialized.
+    ///
+    /// # Safety
+    /// This is unsound if the referenced value isn’t initialized.
+    unsafe fn assume_init_mut(t: &mut Self::Value) -> &mut T;
+}
+
+#[derive(Copy, Clone, Debug, PartialEq, Eq)]
+/// A type implementing `InitStatus` indicating that the value is completely initialized.
+pub struct Init;
+#[derive(Copy, Clone, Debug, PartialEq, Eq)]
+/// A type implementing `InitStatus` indicating that the value is completely unitialized.
+pub struct Uninit;
+
+unsafe impl<T> InitStatus<T> for Init {
+    type Value = T;
+
+    #[inline(always)]
+    fn init(out: &mut T, t: T) {
+        *out = t;
+    }
+
+    #[inline(always)]
+    unsafe fn assume_init_ref(t: &T) -> &T {
+        t
+    }
+
+    #[inline(always)]
+    unsafe fn assume_init_mut(t: &mut T) -> &mut T {
+        t
+    }
+}
+
+unsafe impl<T> InitStatus<T> for Uninit {
+    type Value = MaybeUninit<T>;
+
+    #[inline(always)]
+    fn init(out: &mut MaybeUninit<T>, t: T) {
+        *out = MaybeUninit::new(t);
+    }
+
+    #[inline(always)]
+    unsafe fn assume_init_ref(t: &MaybeUninit<T>) -> &T {
+        std::mem::transmute(t.as_ptr()) // TODO: use t.assume_init_ref()
+    }
+
+    #[inline(always)]
+    unsafe fn assume_init_mut(t: &mut MaybeUninit<T>) -> &mut T {
+        std::mem::transmute(t.as_mut_ptr()) // TODO: use t.assume_init_mut()
+    }
+}