Rename generic parameter N -> T

Cargo.toml

@@ -36,7 +36,7 @@ no_unsound_assume_init = [ ]
 # Conversion
 convert-mint = [ "mint" ]
 convert-glam = [ "glam" ]
-convert-glam-unchecked = [ "convert-glam" ] # Unable edgy conversions like Mat4 -> Isometry3
+convert-glam-unchecked = [ "convert-glam" ] # Enable edgy conversions like Mat4 -> Isometry3
 convert-bytemuck = [ "bytemuck" ]
 
 # Serialization

benches/core/matrix.rs

@@ -1,4 +1,4 @@
-use na::{DMatrix, DVector, Matrix2, Matrix3, Matrix4, MatrixN, Vector2, Vector3, Vector4, U10};
+use na::{DMatrix, DVector, Matrix2, Matrix3, Matrix4, OMatrix, Vector2, Vector3, Vector4, U10};
 use rand::Rng;
 use rand_isaac::IsaacRng;
 use std::ops::{Add, Div, Mul, Sub};
@@ -116,8 +116,8 @@ fn mat10_mul_mat10(bench: &mut criterion::Criterion) {
 }
 
 fn mat10_mul_mat10_static(bench: &mut criterion::Criterion) {
-    let a = MatrixN::<f64, U10>::new_random();
-    let b = MatrixN::<f64, U10>::new_random();
+    let a = OMatrix::<f64, U10>::new_random();
+    let b = OMatrix::<f64, U10>::new_random();
 
     bench.bench_function("mat10_mul_mat10_static", move |bh| bh.iter(|| &a * &b));
 }

benches/core/vector.rs

@@ -1,4 +1,4 @@
-use na::{DVector, Vector2, Vector3, Vector4, VectorN};
+use na::{DVector, OVector, Vector2, Vector3, Vector4};
 use rand::Rng;
 use rand_isaac::IsaacRng;
 use std::ops::{Add, Div, Mul, Sub};
@@ -45,8 +45,8 @@ bench_unop!(vec2_normalize, Vector2<f32>, normalize);
 bench_unop!(vec3_normalize, Vector3<f32>, normalize);
 bench_unop!(vec4_normalize, Vector4<f32>, normalize);
 
-bench_binop_ref!(vec10000_dot_f64, VectorN<f64, U10000>, VectorN<f64, U10000>, dot);
-bench_binop_ref!(vec10000_dot_f32, VectorN<f32, U10000>, VectorN<f32, U10000>, dot);
+bench_binop_ref!(vec10000_dot_f64, OVector<f64, U10000>, OVector<f64, U10000>, dot);
+bench_binop_ref!(vec10000_dot_f32, OVector<f32, U10000>, OVector<f32, U10000>, dot);
 
 fn vec10000_axpy_f64(bh: &mut criterion::Criterion) {
     use rand::SeedableRng;
@@ -93,11 +93,11 @@ fn vec10000_axpy_f64_slice(bh: &mut criterion::Criterion) {
 fn vec10000_axpy_f64_static(bh: &mut criterion::Criterion) {
     use rand::SeedableRng;
     let mut rng = IsaacRng::seed_from_u64(0);
-    let mut a = VectorN::<f64, U10000>::new_random();
-    let b = VectorN::<f64, U10000>::new_random();
+    let mut a = OVector::<f64, U10000>::new_random();
+    let b = OVector::<f64, U10000>::new_random();
     let n = rng.gen::<f64>();
 
-    // NOTE: for some reasons, it is much faster if the arument are boxed (Box::new(VectorN...)).
+    // NOTE: for some reasons, it is much faster if the arument are boxed (Box::new(OVector...)).
     bh.bench_function("vec10000_axpy_f64_static", move |bh| {
         bh.iter(|| a.axpy(n, &b, 1.0))
     });

examples/dimensional_genericity.rs

@@ -2,26 +2,26 @@ extern crate nalgebra as na;
 
 use na::allocator::Allocator;
 use na::dimension::Dim;
-use na::{DefaultAllocator, RealField, Unit, Vector2, Vector3, VectorN};
+use na::{DefaultAllocator, OVector, RealField, Unit, Vector2, Vector3};
 
 /// Reflects a vector wrt. the hyperplane with normal `plane_normal`.
-fn reflect_wrt_hyperplane_with_dimensional_genericity<N: RealField, D: Dim>(
-    plane_normal: &Unit<VectorN<N, D>>,
-    vector: &VectorN<N, D>,
-) -> VectorN<N, D>
+fn reflect_wrt_hyperplane_with_dimensional_genericity<T: RealField, D: Dim>(
+    plane_normal: &Unit<OVector<T, D>>,
+    vector: &OVector<T, D>,
+) -> OVector<T, D>
 where
-    N: RealField,
+    T: RealField,
     D: Dim,
-    DefaultAllocator: Allocator<N, D>,
+    DefaultAllocator: Allocator<T, D>,
 {
     let n = plane_normal.as_ref(); // Get the underlying V.
     vector - n * (n.dot(vector) * na::convert(2.0))
 }
 
 /// Reflects a 2D vector wrt. the 2D line with normal `plane_normal`.
-fn reflect_wrt_hyperplane2<N>(plane_normal: &Unit<Vector2<N>>, vector: &Vector2<N>) -> Vector2<N>
+fn reflect_wrt_hyperplane2<T>(plane_normal: &Unit<Vector2<T>>, vector: &Vector2<T>) -> Vector2<T>
 where
-    N: RealField,
+    T: RealField,
 {
     let n = plane_normal.as_ref(); // Get the underlying Vector2
     vector - n * (n.dot(vector) * na::convert(2.0))
@@ -29,9 +29,9 @@ where
 
 /// Reflects a 3D vector wrt. the 3D plane with normal `plane_normal`.
 /// /!\ This is an exact replicate of `reflect_wrt_hyperplane2, but for 3D.
-fn reflect_wrt_hyperplane3<N>(plane_normal: &Unit<Vector3<N>>, vector: &Vector3<N>) -> Vector3<N>
+fn reflect_wrt_hyperplane3<T>(plane_normal: &Unit<Vector3<T>>, vector: &Vector3<T>) -> Vector3<T>
 where
-    N: RealField,
+    T: RealField,
 {
     let n = plane_normal.as_ref(); // Get the underlying Vector3
     vector - n * (n.dot(vector) * na::convert(2.0))

examples/matrixcompare.rs

@@ -2,20 +2,20 @@ extern crate nalgebra as na;
 
 use matrixcompare::comparators::{AbsoluteElementwiseComparator, ExactElementwiseComparator};
 use matrixcompare::compare_matrices;
-use na::{MatrixMN, U3, U4};
+use na::{OMatrix, U3, U4};
 
 fn compare_integers_fail() {
     println!("Comparing two integer matrices.");
 
     #[rustfmt::skip]
-    let a = MatrixMN::<_, U3, U4>::from_row_slice(&[
+    let a = OMatrix::<_, U3, U4>::from_row_slice(&[
         0, 1,  2,  3,
         4, 5,  6,  7,
         8, 9, -2, 11
     ]);
 
     #[rustfmt::skip]
-    let b = MatrixMN::<_, U3, U4>::from_row_slice(&[
+    let b = OMatrix::<_, U3, U4>::from_row_slice(&[
         0, 1,  2,  3,
         4, 5,  6,  7,
         8, 9, 10, 11
@@ -29,14 +29,14 @@ fn compare_integers_fail() {
 fn compare_different_size() {
     println!("Comparing matrices of different size.");
     #[rustfmt::skip]
-    let a = MatrixMN::<_, U3, U3>::from_row_slice(&[
+    let a = OMatrix::<_, U3, U3>::from_row_slice(&[
         0, 1,  2,
         4, 5,  6,
         8, 9, 10,
     ]);
 
     #[rustfmt::skip]
-    let b = MatrixMN::<_, U3, U4>::from_row_slice(&[
+    let b = OMatrix::<_, U3, U4>::from_row_slice(&[
         0, 1,  2,  3,
         4, 5,  6,  7,
         8, 9, 10, 11
@@ -51,14 +51,14 @@ fn compare_f64_abs_tol_fail() {
     println!("Comparing two f64 matrices.");
 
     #[rustfmt::skip]
-    let a = MatrixMN::<f64, U3, U3>::from_row_slice(&[
+    let a = OMatrix::<f64, U3, U3>::from_row_slice(&[
         0.0, 1.0,  2.0 + 1e-10,
         4.0, 5.0,  6.0,
         8.0, 9.0, 10.0,
     ]);
 
     #[rustfmt::skip]
-    let b = MatrixMN::<_, U3, U3>::from_row_slice(&[
+    let b = OMatrix::<_, U3, U3>::from_row_slice(&[
         0.0, 1.0,  2.0,
         4.0, 5.0,  6.0,
         8.0, 9.0, 10.0

examples/scalar_genericity.rs

@@ -3,15 +3,15 @@ extern crate nalgebra as na;
 use na::{Scalar, Vector3};
 use simba::scalar::RealField;
 
-fn print_vector<N: Scalar>(m: &Vector3<N>) {
+fn print_vector<T: Scalar>(m: &Vector3<T>) {
     println!("{:?}", m)
 }
 
-fn print_norm<N: RealField>(v: &Vector3<N>) {
+fn print_norm<T: RealField>(v: &Vector3<T>) {
     // NOTE: alternatively, nalgebra already defines `v.norm()`.
     let norm = v.dot(v).sqrt();
 
-    // The RealField bound implies that N is Display so we can
+    // The RealField bound implies that T is Display so we can
     // use "{}" instead of "{:?}" for the format string.
     println!("{}", norm)
 }

nalgebra-glm/src/aliases.rs

@@ -1,9 +1,9 @@
 use na::{
     Matrix2, Matrix2x3, Matrix2x4, Matrix3, Matrix3x2, Matrix3x4, Matrix4, Matrix4x2, Matrix4x3,
-    MatrixMN, Quaternion, VectorN, U1, U2, U3, U4,
+    Quaternion, SMatrix, SVector,
 };
 
-/// A matrix with components of type `N`. It has `R` rows, and `C` columns.
+/// A matrix with components of type `T`. It has `R` rows, and `C` columns.
 ///
 /// In this library, vectors, represented as [`TVec`](type.TVec.html) and
 /// friends, are also matrices. Operations that operate on a matrix will
@@ -24,8 +24,8 @@ use na::{
 /// * [`TMat4x3`](type.TMat4x3.html)
 /// * [`TMat4x4`](type.TMat4x4.html)
 /// * [`TVec`](type.TVec.html)
-pub type TMat<N, R, C> = MatrixMN<N, R, C>;
-/// A column vector with components of type `N`. It has `D` rows (and one column).
+pub type TMat<T, const R: usize, const C: usize> = SMatrix<T, R, C>;
+/// A column vector with components of type `T`. It has `D` rows (and one column).
 ///
 /// In this library, vectors are represented as a single column matrix, so
 /// operations on [`TMat`](type.TMat.html) are also valid on vectors.
@@ -37,11 +37,11 @@ pub type TMat<N, R, C> = MatrixMN<N, R, C>;
 /// * [`TVec2`](type.TVec2.html)
 /// * [`TVec3`](type.TVec3.html)
 /// * [`TVec4`](type.TVec4.html)
-pub type TVec<N, R> = VectorN<N, R>;
-/// A quaternion with components of type `N`.
-pub type Qua<N> = Quaternion<N>;
+pub type TVec<T, const R: usize> = SVector<T, R>;
+/// A quaternion with components of type `T`.
+pub type Qua<T> = Quaternion<T>;
 
-/// A 1D vector with components of type `N`.
+/// A 1D vector with components of type `T`.
 ///
 /// # See also:
 ///
@@ -69,8 +69,8 @@ pub type Qua<N> = Quaternion<N>;
 /// * [`U64Vec1`](type.U64Vec1.html)
 /// * [`U8Vec1`](type.U8Vec1.html)
 /// * [`Vec1`](type.Vec1.html)
-pub type TVec1<N> = TVec<N, U1>;
-/// A 2D vector with components of type `N`.
+pub type TVec1<T> = TVec<T, 1>;
+/// A 2D vector with components of type `T`.
 ///
 /// # See also:
 ///
@@ -99,8 +99,8 @@ pub type TVec1<N> = TVec<N, U1>;
 /// * [`U64Vec2`](type.U64Vec2.html)
 /// * [`U8Vec2`](type.U8Vec2.html)
 /// * [`Vec2`](type.Vec2.html)
-pub type TVec2<N> = TVec<N, U2>;
-/// A 3D vector with components of type `N`.
+pub type TVec2<T> = TVec<T, 2>;
+/// A 3D vector with components of type `T`.
 ///
 /// # See also:
 ///
@@ -129,8 +129,8 @@ pub type TVec2<N> = TVec<N, U2>;
 /// * [`U64Vec3`](type.U64Vec3.html)
 /// * [`U8Vec3`](type.U8Vec3.html)
 /// * [`Vec3`](type.Vec3.html)
-pub type TVec3<N> = TVec<N, U3>;
-/// A 4D vector with components of type `N`.
+pub type TVec3<T> = TVec<T, 3>;
+/// A 4D vector with components of type `T`.
 ///
 /// # See also:
 ///
@@ -158,7 +158,7 @@ pub type TVec3<N> = TVec<N, U3>;
 /// * [`U64Vec4`](type.U64Vec4.html)
 /// * [`U8Vec4`](type.U8Vec4.html)
 /// * [`Vec4`](type.Vec4.html)
-pub type TVec4<N> = TVec<N, U4>;
+pub type TVec4<T> = TVec<T, 4>;
 /// A 1D vector with boolean components.
 pub type BVec1 = TVec1<bool>;
 /// A 2D vector with boolean components.
@@ -268,31 +268,31 @@ pub type I8Vec3 = TVec3<i8>;
 /// A 4D vector with `i8` components.
 pub type I8Vec4 = TVec4<i8>;
 
-/// A 2x2 matrix with components of type `N`.
-pub type TMat2<N> = Matrix2<N>;
-/// A 2x2 matrix with components of type `N`.
-pub type TMat2x2<N> = Matrix2<N>;
-/// A 2x3 matrix with components of type `N`.
-pub type TMat2x3<N> = Matrix2x3<N>;
-/// A 2x4 matrix with components of type `N`.
-pub type TMat2x4<N> = Matrix2x4<N>;
-/// A 3x3 matrix with components of type `N`.
-pub type TMat3<N> = Matrix3<N>;
-/// A 3x2 matrix with components of type `N`.
-pub type TMat3x2<N> = Matrix3x2<N>;
-/// A 3x3 matrix with components of type `N`.
-pub type TMat3x3<N> = Matrix3<N>;
-/// A 3x4 matrix with components of type `N`.
-pub type TMat3x4<N> = Matrix3x4<N>;
-/// A 4x4 matrix with components of type `N`.
-pub type TMat4<N> = Matrix4<N>;
-/// A 4x2 matrix with components of type `N`.
-pub type TMat4x2<N> = Matrix4x2<N>;
-/// A 4x3 matrix with components of type `N`.
-pub type TMat4x3<N> = Matrix4x3<N>;
-/// A 4x4 matrix with components of type `N`.
-pub type TMat4x4<N> = Matrix4<N>;
-/// A 2x2 matrix with components of type `N`.
+/// A 2x2 matrix with components of type `T`.
+pub type TMat2<T> = Matrix2<T>;
+/// A 2x2 matrix with components of type `T`.
+pub type TMat2x2<T> = Matrix2<T>;
+/// A 2x3 matrix with components of type `T`.
+pub type TMat2x3<T> = Matrix2x3<T>;
+/// A 2x4 matrix with components of type `T`.
+pub type TMat2x4<T> = Matrix2x4<T>;
+/// A 3x3 matrix with components of type `T`.
+pub type TMat3<T> = Matrix3<T>;
+/// A 3x2 matrix with components of type `T`.
+pub type TMat3x2<T> = Matrix3x2<T>;
+/// A 3x3 matrix with components of type `T`.
+pub type TMat3x3<T> = Matrix3<T>;
+/// A 3x4 matrix with components of type `T`.
+pub type TMat3x4<T> = Matrix3x4<T>;
+/// A 4x4 matrix with components of type `T`.
+pub type TMat4<T> = Matrix4<T>;
+/// A 4x2 matrix with components of type `T`.
+pub type TMat4x2<T> = Matrix4x2<T>;
+/// A 4x3 matrix with components of type `T`.
+pub type TMat4x3<T> = Matrix4x3<T>;
+/// A 4x4 matrix with components of type `T`.
+pub type TMat4x4<T> = Matrix4<T>;
+/// A 2x2 matrix with components of type `T`.
 pub type DMat2 = Matrix2<f64>;
 /// A 2x2 matrix with `f64` components.
 pub type DMat2x2 = Matrix2<f64>;

nalgebra-glm/src/common.rs

@@ -1,9 +1,9 @@
 use core::mem;
-use na::{self, DefaultAllocator, RealField};
+use na::{self, RealField};
 use num::FromPrimitive;
 
 use crate::aliases::{TMat, TVec};
-use crate::traits::{Alloc, Dimension, Number};
+use crate::traits::Number;
 
 /// For each matrix or vector component `x` if `x >= 0`; otherwise, it returns `-x`.
 ///
@@ -21,10 +21,7 @@ use crate::traits::{Alloc, Dimension, Number};
 /// # See also:
 ///
 /// * [`sign`](fn.sign.html)
-pub fn abs<N: Number, R: Dimension, C: Dimension>(x: &TMat<N, R, C>) -> TMat<N, R, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn abs<T: Number, const R: usize, const C: usize>(x: &TMat<T, R, C>) -> TMat<T, R, C> {
     x.abs()
 }
 
@@ -45,10 +42,7 @@ where
 /// * [`fract`](fn.fract.html)
 /// * [`round`](fn.round.html)
 /// * [`trunc`](fn.trunc.html)
-pub fn ceil<N: RealField, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn ceil<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.ceil())
 }
 
@@ -73,7 +67,7 @@ where
 ///
 /// * [`clamp`](fn.clamp.html)
 /// * [`clamp_vec`](fn.clamp_vec.html)
-pub fn clamp_scalar<N: Number>(x: N, min_val: N, max_val: N) -> N {
+pub fn clamp_scalar<T: Number>(x: T, min_val: T, max_val: T) -> T {
     na::clamp(x, min_val, max_val)
 }
 
@@ -97,10 +91,7 @@ pub fn clamp_scalar<N: Number>(x: N, min_val: N, max_val: N) -> N {
 ///
 /// * [`clamp_scalar`](fn.clamp_scalar.html)
 /// * [`clamp_vec`](fn.clamp_vec.html)
-pub fn clamp<N: Number, D: Dimension>(x: &TVec<N, D>, min_val: N, max_val: N) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn clamp<T: Number, const D: usize>(x: &TVec<T, D>, min_val: T, max_val: T) -> TVec<T, D> {
     x.map(|x| na::clamp(x, min_val, max_val))
 }
 
@@ -131,14 +122,11 @@ where
 ///
 /// * [`clamp_scalar`](fn.clamp_scalar.html)
 /// * [`clamp`](fn.clamp.html)
-pub fn clamp_vec<N: Number, D: Dimension>(
-    x: &TVec<N, D>,
-    min_val: &TVec<N, D>,
-    max_val: &TVec<N, D>,
-) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn clamp_vec<T: Number, const D: usize>(
+    x: &TVec<T, D>,
+    min_val: &TVec<T, D>,
+    max_val: &TVec<T, D>,
+) -> TVec<T, D> {
     x.zip_zip_map(min_val, max_val, |a, min, max| na::clamp(a, min, max))
 }
 
@@ -172,10 +160,7 @@ pub fn float_bits_to_int(v: f32) -> i32 {
 /// * [`int_bits_to_float_vec`](fn.int_bits_to_float_vec.html)
 /// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
 /// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
-pub fn float_bits_to_int_vec<D: Dimension>(v: &TVec<f32, D>) -> TVec<i32, D>
-where
-    DefaultAllocator: Alloc<f32, D>,
-{
+pub fn float_bits_to_int_vec<const D: usize>(v: &TVec<f32, D>) -> TVec<i32, D> {
     v.map(float_bits_to_int)
 }
 
@@ -209,10 +194,7 @@ pub fn float_bits_to_uint(v: f32) -> u32 {
 /// * [`int_bits_to_float_vec`](fn.int_bits_to_float_vec.html)
 /// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
 /// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
-pub fn float_bits_to_uint_vec<D: Dimension>(v: &TVec<f32, D>) -> TVec<u32, D>
-where
-    DefaultAllocator: Alloc<f32, D>,
-{
+pub fn float_bits_to_uint_vec<const D: usize>(v: &TVec<f32, D>) -> TVec<u32, D> {
     v.map(float_bits_to_uint)
 }
 
@@ -232,15 +214,12 @@ where
 /// * [`fract`](fn.fract.html)
 /// * [`round`](fn.round.html)
 /// * [`trunc`](fn.trunc.html)
-pub fn floor<N: RealField, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn floor<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.floor())
 }
 
 //// TODO: should be implemented for TVec/TMat?
-//pub fn fma<N: Number>(a: N, b: N, c: N) -> N {
+//pub fn fma<T: Number>(a: T, b: T, c: T) -> T {
 //    // TODO: use an actual FMA
 //    a * b + c
 //}
@@ -261,16 +240,13 @@ where
 /// * [`floor`](fn.floor.html)
 /// * [`round`](fn.round.html)
 /// * [`trunc`](fn.trunc.html)
-pub fn fract<N: RealField, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn fract<T: RealField, 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<N: RealField>(x: N, exp: N) -> (N, N) {
+//pub fn frexp<T: RealField>(x: T, exp: T) -> (T, T) {
 //    // TODO: is there a better approach?
 //    let e = x.log2().ceil();
 //    (x * (-e).exp2(), e)
@@ -306,27 +282,22 @@ pub fn int_bits_to_float(v: i32) -> f32 {
 /// * [`int_bits_to_float`](fn.int_bits_to_float.html)
 /// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
 /// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
-pub fn int_bits_to_float_vec<D: Dimension>(v: &TVec<i32, D>) -> TVec<f32, D>
-where
-    DefaultAllocator: Alloc<f32, D>,
-{
+pub fn int_bits_to_float_vec<const D: usize>(v: &TVec<i32, D>) -> TVec<f32, D> {
     v.map(int_bits_to_float)
 }
 
-//pub fn isinf<N: Scalar, D: Dimension>(x: &TVec<N, D>) -> TVec<bool, D>
-//    where DefaultAllocator: Alloc<N, D> {
+//pub fn isinf<T: Scalar, const D: usize>(x: &TVec<T, D>) -> TVec<bool, D> {
 //        unimplemented!()
 //
 //}
 //
-//pub fn isnan<N: Scalar, D: Dimension>(x: &TVec<N, D>) -> TVec<bool, D>
-//    where DefaultAllocator: Alloc<N, D> {
+//pub fn isnan<T: Scalar, const D: usize>(x: &TVec<T, D>) -> TVec<bool, D> {
 //        unimplemented!()
 //
 //}
 
 ///// Returns the (significant, exponent) of this float number.
-//pub fn ldexp<N: RealField>(x: N, exp: N) -> N {
+//pub fn ldexp<T: RealField>(x: T, exp: T) -> T {
 //    // TODO: is there a better approach?
 //    x * (exp).exp2()
 //}
@@ -346,8 +317,8 @@ where
 ///
 /// * [`mix`](fn.mix.html)
 /// * [`mix_vec`](fn.mix_vec.html)
-pub fn mix_scalar<N: Number>(x: N, y: N, a: N) -> N {
-    x * (N::one() - a) + y * a
+pub fn mix_scalar<T: Number>(x: T, y: T, a: T) -> T {
+    x * (T::one() - a) + y * a
 }
 
 /// Returns `x * (1.0 - a) + y * a`, i.e., the linear blend of the vectors x and y using the scalar value a.
@@ -367,11 +338,8 @@ pub fn mix_scalar<N: Number>(x: N, y: N, a: N) -> N {
 ///
 /// * [`mix_scalar`](fn.mix_scalar.html)
 /// * [`mix_vec`](fn.mix_vec.html)
-pub fn mix<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>, a: N) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
-    x * (N::one() - a) + y * a
+pub fn mix<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, a: T) -> TVec<T, D> {
+    x * (T::one() - a) + y * a
 }
 
 /// Returns `x * (1.0 - a) + y * a`, i.e., the component-wise linear blend of `x` and `y` using the components of
@@ -393,15 +361,12 @@ where
 ///
 /// * [`mix_scalar`](fn.mix_scalar.html)
 /// * [`mix`](fn.mix.html)
-pub fn mix_vec<N: Number, D: Dimension>(
-    x: &TVec<N, D>,
-    y: &TVec<N, D>,
-    a: &TVec<N, D>,
-) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
-    x.component_mul(&(TVec::<N, D>::repeat(N::one()) - a)) + y.component_mul(&a)
+pub fn mix_vec<T: Number, const D: usize>(
+    x: &TVec<T, D>,
+    y: &TVec<T, D>,
+    a: &TVec<T, D>,
+) -> TVec<T, D> {
+    x.component_mul(&(TVec::<T, D>::repeat(T::one()) - a)) + y.component_mul(&a)
 }
 
 /// Returns `x * (1.0 - a) + y * a`, i.e., the linear blend of the scalars x and y using the scalar value a.
@@ -420,7 +385,7 @@ where
 ///
 /// * [`lerp`](fn.lerp.html)
 /// * [`lerp_vec`](fn.lerp_vec.html)
-pub fn lerp_scalar<N: Number>(x: N, y: N, a: N) -> N {
+pub fn lerp_scalar<T: Number>(x: T, y: T, a: T) -> T {
     mix_scalar(x, y, a)
 }
 
@@ -442,10 +407,7 @@ pub fn lerp_scalar<N: Number>(x: N, y: N, a: N) -> N {
 ///
 /// * [`lerp_scalar`](fn.lerp_scalar.html)
 /// * [`lerp_vec`](fn.lerp_vec.html)
-pub fn lerp<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>, a: N) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn lerp<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, a: T) -> TVec<T, D> {
     mix(x, y, a)
 }
 
@@ -469,14 +431,11 @@ where
 ///
 /// * [`lerp_scalar`](fn.lerp_scalar.html)
 /// * [`lerp`](fn.lerp.html)
-pub fn lerp_vec<N: Number, D: Dimension>(
-    x: &TVec<N, D>,
-    y: &TVec<N, D>,
-    a: &TVec<N, D>,
-) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn lerp_vec<T: Number, const D: usize>(
+    x: &TVec<T, D>,
+    y: &TVec<T, D>,
+    a: &TVec<T, D>,
+) -> TVec<T, D> {
     mix_vec(x, y, a)
 }
 
@@ -487,10 +446,7 @@ where
 /// # See also:
 ///
 /// * [`modf`](fn.modf.html)
-pub fn modf_vec<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn modf_vec<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<T, D> {
     x.zip_map(y, |x, y| x % y)
 }
 
@@ -499,7 +455,7 @@ where
 /// # See also:
 ///
 /// * [`modf_vec`](fn.modf_vec.html)
-pub fn modf<N: Number>(x: N, i: N) -> N {
+pub fn modf<T: Number>(x: T, i: T) -> T {
     x % i
 }
 
@@ -521,15 +477,11 @@ pub fn modf<N: Number>(x: N, i: N) -> N {
 /// * [`floor`](fn.floor.html)
 /// * [`fract`](fn.fract.html)
 /// * [`trunc`](fn.trunc.html)
-pub fn round<N: RealField, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn round<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.round())
 }
 
-//pub fn roundEven<N: Scalar, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-//    where DefaultAllocator: Alloc<N, D> {
+//pub fn roundEven<T: Scalar, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
 //        unimplemented!()
 //}
 
@@ -547,46 +499,37 @@ where
 ///
 /// * [`abs`](fn.abs.html)
 ///
-pub fn sign<N: Number, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
-    x.map(|x| if x.is_zero() { N::zero() } else { x.signum() })
+pub fn sign<T: Number, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
+    x.map(|x| if x.is_zero() { T::zero() } else { x.signum() })
 }
 
 /// Returns 0.0 if `x <= edge0` and `1.0 if x >= edge1` and performs smooth Hermite interpolation between 0 and 1 when `edge0 < x < edge1`.
 ///
 /// 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<N: Number>(edge0: N, edge1: N, x: N) -> N {
-    let _3: N = FromPrimitive::from_f64(3.0).unwrap();
-    let _2: N = FromPrimitive::from_f64(2.0).unwrap();
-    let t = na::clamp((x - edge0) / (edge1 - edge0), N::zero(), N::one());
+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();
+    let t = na::clamp((x - edge0) / (edge1 - edge0), T::zero(), T::one());
     t * t * (_3 - t * _2)
 }
 
 /// Returns 0.0 if `x < edge`, otherwise it returns 1.0.
-pub fn step_scalar<N: Number>(edge: N, x: N) -> N {
+pub fn step_scalar<T: Number>(edge: T, x: T) -> T {
     if edge > x {
-        N::zero()
+        T::zero()
     } else {
-        N::one()
+        T::one()
     }
 }
 
 /// Returns 0.0 if `x[i] < edge`, otherwise it returns 1.0.
-pub fn step<N: Number, D: Dimension>(edge: N, x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn step<T: Number, const D: usize>(edge: T, x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| step_scalar(edge, x))
 }
 
 /// Returns 0.0 if `x[i] < edge[i]`, otherwise it returns 1.0.
-pub fn step_vec<N: Number, D: Dimension>(edge: &TVec<N, D>, x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn step_vec<T: Number, const D: usize>(edge: &TVec<T, D>, x: &TVec<T, D>) -> TVec<T, D> {
     edge.zip_map(x, step_scalar)
 }
 
@@ -606,10 +549,7 @@ where
 /// * [`floor`](fn.floor.html)
 /// * [`fract`](fn.fract.html)
 /// * [`round`](fn.round.html)
-pub fn trunc<N: RealField, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn trunc<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|x| x.trunc())
 }
 
@@ -643,9 +583,6 @@ pub fn uint_bits_to_float_scalar(v: u32) -> f32 {
 /// * [`int_bits_to_float`](fn.int_bits_to_float.html)
 /// * [`int_bits_to_float_vec`](fn.int_bits_to_float_vec.html)
 /// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
-pub fn uint_bits_to_float<D: Dimension>(v: &TVec<u32, D>) -> TVec<f32, D>
-where
-    DefaultAllocator: Alloc<f32, D>,
-{
+pub fn uint_bits_to_float<const D: usize>(v: &TVec<u32, D>) -> TVec<f32, D> {
     v.map(uint_bits_to_float_scalar)
 }

nalgebra-glm/src/constructors.rs

@@ -2,7 +2,7 @@ use crate::aliases::{
     Qua, TMat, TMat2, TMat2x3, TMat2x4, TMat3, TMat3x2, TMat3x4, TMat4, TMat4x2, TMat4x3, TVec1,
     TVec2, TVec3, TVec4,
 };
-use na::{RealField, Scalar, U2, U3, U4};
+use na::{RealField, Scalar};
 
 /// Creates a new 1D vector.
 ///
@@ -14,30 +14,30 @@ use na::{RealField, Scalar, U2, U3, U4};
 /// # use nalgebra_glm as glm;
 /// let v = glm::vec1(true);
 /// ```
-pub fn vec1<N: Scalar>(x: N) -> TVec1<N> {
+pub fn vec1<T: Scalar>(x: T) -> TVec1<T> {
     TVec1::new(x)
 }
 
 /// Creates a new 2D vector.
-pub fn vec2<N: Scalar>(x: N, y: N) -> TVec2<N> {
+pub fn vec2<T: Scalar>(x: T, y: T) -> TVec2<T> {
     TVec2::new(x, y)
 }
 
 /// Creates a new 3D vector.
-pub fn vec3<N: Scalar>(x: N, y: N, z: N) -> TVec3<N> {
+pub fn vec3<T: Scalar>(x: T, y: T, z: T) -> TVec3<T> {
     TVec3::new(x, y, z)
 }
 
 /// Creates a new 4D vector.
-pub fn vec4<N: Scalar>(x: N, y: N, z: N, w: N) -> TVec4<N> {
+pub fn vec4<T: Scalar>(x: T, y: T, z: T, w: T) -> TVec4<T> {
     TVec4::new(x, y, z, w)
 }
 
 /// Create a new 2x2 matrix.
 #[rustfmt::skip]
-pub fn mat2<N: Scalar>(m11: N, m12: N,
-                       m21: N, m22: N) -> TMat2<N> {
-    TMat::<N, U2, U2>::new(
+pub fn mat2<T: Scalar>(m11: T, m12: T,
+                       m21: T, m22: T) -> TMat2<T> {
+    TMat::<T, 2, 2>::new(
         m11, m12,
         m21, m22,
     )
@@ -45,9 +45,9 @@ pub fn mat2<N: Scalar>(m11: N, m12: N,
 
 /// Create a new 2x2 matrix.
 #[rustfmt::skip]
-pub fn mat2x2<N: Scalar>(m11: N, m12: N,
-                         m21: N, m22: N) -> TMat2<N> {
-    TMat::<N, U2, U2>::new(
+pub fn mat2x2<T: Scalar>(m11: T, m12: T,
+                         m21: T, m22: T) -> TMat2<T> {
+    TMat::<T, 2, 2>::new(
         m11, m12,
         m21, m22,
     )
@@ -55,9 +55,9 @@ pub fn mat2x2<N: Scalar>(m11: N, m12: N,
 
 /// Create a new 2x3 matrix.
 #[rustfmt::skip]
-pub fn mat2x3<N: Scalar>(m11: N, m12: N, m13: N,
-                         m21: N, m22: N, m23: N) -> TMat2x3<N> {
-    TMat::<N, U2, U3>::new(
+pub fn mat2x3<T: Scalar>(m11: T, m12: T, m13: T,
+                         m21: T, m22: T, m23: T) -> TMat2x3<T> {
+    TMat::<T, 2, 3>::new(
         m11, m12, m13,
         m21, m22, m23,
     )
@@ -65,9 +65,9 @@ pub fn mat2x3<N: Scalar>(m11: N, m12: N, m13: N,
 
 /// Create a new 2x4 matrix.
 #[rustfmt::skip]
-pub fn mat2x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N,
-                         m21: N, m22: N, m23: N, m24: N) -> TMat2x4<N> {
-    TMat::<N, U2, U4>::new(
+pub fn mat2x4<T: Scalar>(m11: T, m12: T, m13: T, m14: T,
+                         m21: T, m22: T, m23: T, m24: T) -> TMat2x4<T> {
+    TMat::<T, 2, 4>::new(
         m11, m12, m13, m14,
         m21, m22, m23, m24,
     )
@@ -75,10 +75,10 @@ pub fn mat2x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N,
 
 /// Create a new 3x3 matrix.
 #[rustfmt::skip]
-pub fn mat3<N: Scalar>(m11: N, m12: N, m13: N,
-                       m21: N, m22: N, m23: N,
-                       m31: N, m32: N, m33: N) -> TMat3<N> {
-    TMat::<N, U3, U3>::new(
+pub fn mat3<T: Scalar>(m11: T, m12: T, m13: T,
+                       m21: T, m22: T, m23: T,
+                       m31: T, m32: T, m33: T) -> TMat3<T> {
+    TMat::<T, 3, 3>::new(
         m11, m12, m13,
         m21, m22, m23,
         m31, m32, m33,
@@ -87,10 +87,10 @@ pub fn mat3<N: Scalar>(m11: N, m12: N, m13: N,
 
 /// Create a new 3x2 matrix.
 #[rustfmt::skip]
-pub fn mat3x2<N: Scalar>(m11: N, m12: N,
-                         m21: N, m22: N,
-                         m31: N, m32: N) -> TMat3x2<N> {
-    TMat::<N, U3, U2>::new(
+pub fn mat3x2<T: Scalar>(m11: T, m12: T,
+                         m21: T, m22: T,
+                         m31: T, m32: T) -> TMat3x2<T> {
+    TMat::<T, 3, 2>::new(
         m11, m12,
         m21, m22,
         m31, m32,
@@ -99,10 +99,10 @@ pub fn mat3x2<N: Scalar>(m11: N, m12: N,
 
 /// Create a new 3x3 matrix.
 #[rustfmt::skip]
-pub fn mat3x3<N: Scalar>(m11: N, m12: N, m13: N,
-                         m21: N, m22: N, m23: N,
-                         m31: N, m32: N, m33: N) -> TMat3<N> {
-    TMat::<N, U3, U3>::new(
+pub fn mat3x3<T: Scalar>(m11: T, m12: T, m13: T,
+                         m21: T, m22: T, m23: T,
+                         m31: T, m32: T, m33: T) -> TMat3<T> {
+    TMat::<T, 3, 3>::new(
         m11, m12, m13,
         m31, m32, m33,
         m21, m22, m23,
@@ -111,10 +111,10 @@ pub fn mat3x3<N: Scalar>(m11: N, m12: N, m13: N,
 
 /// Create a new 3x4 matrix.
 #[rustfmt::skip]
-pub fn mat3x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N,
-                         m21: N, m22: N, m23: N, m24: N,
-                         m31: N, m32: N, m33: N, m34: N) -> TMat3x4<N> {
-    TMat::<N, U3, U4>::new(
+pub fn mat3x4<T: Scalar>(m11: T, m12: T, m13: T, m14: T,
+                         m21: T, m22: T, m23: T, m24: T,
+                         m31: T, m32: T, m33: T, m34: T) -> TMat3x4<T> {
+    TMat::<T, 3, 4>::new(
         m11, m12, m13, m14,
         m21, m22, m23, m24,
         m31, m32, m33, m34,
@@ -123,11 +123,11 @@ pub fn mat3x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N,
 
 /// Create a new 4x2 matrix.
 #[rustfmt::skip]
-pub fn mat4x2<N: Scalar>(m11: N, m12: N,
-                         m21: N, m22: N,
-                         m31: N, m32: N,
-                         m41: N, m42: N) -> TMat4x2<N> {
-    TMat::<N, U4, U2>::new(
+pub fn mat4x2<T: Scalar>(m11: T, m12: T,
+                         m21: T, m22: T,
+                         m31: T, m32: T,
+                         m41: T, m42: T) -> TMat4x2<T> {
+    TMat::<T, 4, 2>::new(
         m11, m12,
         m21, m22,
         m31, m32,
@@ -137,11 +137,11 @@ pub fn mat4x2<N: Scalar>(m11: N, m12: N,
 
 /// Create a new 4x3 matrix.
 #[rustfmt::skip]
-pub fn mat4x3<N: Scalar>(m11: N, m12: N, m13: N,
-                         m21: N, m22: N, m23: N,
-                         m31: N, m32: N, m33: N,
-                         m41: N, m42: N, m43: N) -> TMat4x3<N> {
-    TMat::<N, U4, U3>::new(
+pub fn mat4x3<T: Scalar>(m11: T, m12: T, m13: T,
+                         m21: T, m22: T, m23: T,
+                         m31: T, m32: T, m33: T,
+                         m41: T, m42: T, m43: T) -> TMat4x3<T> {
+    TMat::<T, 4, 3>::new(
         m11, m12, m13,
         m21, m22, m23,
         m31, m32, m33,
@@ -151,11 +151,11 @@ pub fn mat4x3<N: Scalar>(m11: N, m12: N, m13: N,
 
 /// Create a new 4x4 matrix.
 #[rustfmt::skip]
-pub fn mat4x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N,
-                         m21: N, m22: N, m23: N, m24: N,
-                         m31: N, m32: N, m33: N, m34: N,
-                         m41: N, m42: N, m43: N, m44: N) -> TMat4<N> {
-    TMat::<N, U4, U4>::new(
+pub fn mat4x4<T: Scalar>(m11: T, m12: T, m13: T, m14: T,
+                         m21: T, m22: T, m23: T, m24: T,
+                         m31: T, m32: T, m33: T, m34: T,
+                         m41: T, m42: T, m43: T, m44: T) -> TMat4<T> {
+    TMat::<T, 4, 4>::new(
         m11, m12, m13, m14,
         m21, m22, m23, m24,
         m31, m32, m33, m34,
@@ -165,11 +165,11 @@ pub fn mat4x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N,
 
 /// Create a new 4x4 matrix.
 #[rustfmt::skip]
-pub fn mat4<N: Scalar>(m11: N, m12: N, m13: N, m14: N,
-                       m21: N, m22: N, m23: N, m24: N,
-                       m31: N, m32: N, m33: N, m34: N,
-                       m41: N, m42: N, m43: N, m44: N) -> TMat4<N> {
-    TMat::<N, U4, U4>::new(
+pub fn mat4<T: Scalar>(m11: T, m12: T, m13: T, m14: T,
+                       m21: T, m22: T, m23: T, m24: T,
+                       m31: T, m32: T, m33: T, m34: T,
+                       m41: T, m42: T, m43: T, m44: T) -> TMat4<T> {
+    TMat::<T, 4, 4>::new(
         m11, m12, m13, m14,
         m21, m22, m23, m24,
         m31, m32, m33, m34,
@@ -178,6 +178,6 @@ pub fn mat4<N: Scalar>(m11: N, m12: N, m13: N, m14: N,
 }
 
 /// Creates a new quaternion.
-pub fn quat<N: RealField>(x: N, y: N, z: N, w: N) -> Qua<N> {
+pub fn quat<T: RealField>(x: T, y: T, z: T, w: T) -> Qua<T> {
     Qua::new(w, x, y, z)
 }

nalgebra-glm/src/exponential.rs

@@ -1,16 +1,12 @@
 use crate::aliases::TVec;
-use crate::traits::{Alloc, Dimension};
-use na::{DefaultAllocator, RealField};
+use na::RealField;
 
 /// Component-wise exponential.
 ///
 /// # See also:
 ///
 /// * [`exp2`](fn.exp2.html)
-pub fn exp<N: RealField, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn exp<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.exp())
 }
 
@@ -19,10 +15,7 @@ where
 /// # See also:
 ///
 /// * [`exp`](fn.exp.html)
-pub fn exp2<N: RealField, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn exp2<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.exp2())
 }
 
@@ -31,11 +24,8 @@ where
 /// # See also:
 ///
 /// * [`sqrt`](fn.sqrt.html)
-pub fn inversesqrt<N: RealField, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
-    v.map(|x| N::one() / x.sqrt())
+pub fn inversesqrt<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
+    v.map(|x| T::one() / x.sqrt())
 }
 
 /// Component-wise logarithm.
@@ -43,10 +33,7 @@ where
 /// # See also:
 ///
 /// * [`log2`](fn.log2.html)
-pub fn log<N: RealField, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn log<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.ln())
 }
 
@@ -55,18 +42,12 @@ where
 /// # See also:
 ///
 /// * [`log`](fn.log.html)
-pub fn log2<N: RealField, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn log2<T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     v.map(|x| x.log2())
 }
 
 /// Component-wise power.
-pub fn pow<N: RealField, D: Dimension>(base: &TVec<N, D>, exponent: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn pow<T: RealField, const D: usize>(base: &TVec<T, D>, exponent: &TVec<T, D>) -> TVec<T, D> {
     base.zip_map(exponent, |b, e| b.powf(e))
 }
 
@@ -78,9 +59,6 @@ where
 /// * [`exp2`](fn.exp2.html)
 /// * [`inversesqrt`](fn.inversesqrt.html)
 /// * [`pow`](fn.pow.html)
-pub fn sqrt<N: RealField, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn sqrt<T: RealField, 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;
 
-//pub fn frustum<N: RealField>(left: N, right: N, bottom: N, top: N, near: N, far: N) -> TMat4<N> {
+//pub fn frustum<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 
-//pub fn frustum_lh<N: RealField>(left: N, right: N, bottom: N, top: N, near: N, far: N) -> TMat4<N> {
+//pub fn frustum_lh<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_lr_no<N: RealField>(left: N, right: N, bottom: N, top: N, near: N, far: N) -> TMat4<N> {
+//pub fn frustum_lr_no<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_lh_zo<N: RealField>(left: N, right: N, bottom: N, top: N, near: N, far: N) -> TMat4<N> {
+//pub fn frustum_lh_zo<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_no<N: RealField>(left: N, right: N, bottom: N, top: N, near: N, far: N) -> TMat4<N> {
+//pub fn frustum_no<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_rh<N: RealField>(left: N, right: N, bottom: N, top: N, near: N, far: N) -> TMat4<N> {
+//pub fn frustum_rh<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_rh_no<N: RealField>(left: N, right: N, bottom: N, top: N, near: N, far: N) -> TMat4<N> {
+//pub fn frustum_rh_no<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_rh_zo<N: RealField>(left: N, right: N, bottom: N, top: N, near: N, far: N) -> TMat4<N> {
+//pub fn frustum_rh_zo<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn frustum_zo<N: RealField>(left: N, right: N, bottom: N, top: N, near: N, far: N) -> TMat4<N> {
+//pub fn frustum_zo<T: RealField>(left: T, right: T, bottom: T, top: T, near: T, far: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 
-//pub fn infinite_perspective<N: RealField>(fovy: N, aspect: N, near: N) -> TMat4<N> {
+//pub fn infinite_perspective<T: RealField>(fovy: T, aspect: T, near: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn infinite_perspective_lh<N: RealField>(fovy: N, aspect: N, near: N) -> TMat4<N> {
+//pub fn infinite_perspective_lh<T: RealField>(fovy: T, aspect: T, near: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn infinite_ortho<N: RealField>(left: N, right: N, bottom: N, top: N) -> TMat4<N> {
+//pub fn infinite_ortho<T: RealField>(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<N: RealField>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+pub fn ortho<T: RealField>(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 +75,7 @@ pub fn ortho<N: RealField>(left: N, right: N, bottom: N, top: N, znear: N, 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<N: RealField>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+pub fn ortho_lh<T: RealField>(left: T, right: T, bottom: T, top: T, znear: T, zfar: T) -> TMat4<T> {
     ortho_lh_no(left, right, bottom, top, znear, zfar)
 }
 
@@ -90,16 +90,16 @@ pub fn ortho_lh<N: RealField>(left: N, right: N, bottom: N, top: N, znear: N, 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<N: RealField>(
-    left: N,
-    right: N,
-    bottom: N,
-    top: N,
-    znear: N,
-    zfar: N,
-) -> TMat4<N> {
-    let two: N = crate::convert(2.0);
-    let mut mat: TMat4<N> = TMat4::<N>::identity();
+pub fn ortho_lh_no<T: RealField>(
+    left: T,
+    right: T,
+    bottom: T,
+    top: T,
+    znear: T,
+    zfar: T,
+) -> TMat4<T> {
+    let two: T = crate::convert(2.0);
+    let mut mat: TMat4<T> = TMat4::<T>::identity();
 
     mat[(0, 0)] = two / (right - left);
     mat[(0, 3)] = -(right + left) / (right - left);
@@ -122,17 +122,17 @@ pub fn ortho_lh_no<N: 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<N: RealField>(
-    left: N,
-    right: N,
-    bottom: N,
-    top: N,
-    znear: N,
-    zfar: N,
-) -> TMat4<N> {
-    let one: N = N::one();
-    let two: N = crate::convert(2.0);
-    let mut mat: TMat4<N> = TMat4::<N>::identity();
+pub fn ortho_lh_zo<T: RealField>(
+    left: T,
+    right: T,
+    bottom: T,
+    top: T,
+    znear: T,
+    zfar: T,
+) -> TMat4<T> {
+    let one: T = T::one();
+    let two: T = crate::convert(2.0);
+    let mut mat: TMat4<T> = TMat4::<T>::identity();
 
     mat[(0, 0)] = two / (right - left);
     mat[(0, 3)] = -(right + left) / (right - left);
@@ -155,7 +155,7 @@ pub fn ortho_lh_zo<N: 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<N: RealField>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+pub fn ortho_no<T: RealField>(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 +170,7 @@ pub fn ortho_no<N: RealField>(left: N, right: N, bottom: N, top: N, znear: N, 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<N: RealField>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+pub fn ortho_rh<T: RealField>(left: T, right: T, bottom: T, top: T, znear: T, zfar: T) -> TMat4<T> {
     ortho_rh_no(left, right, bottom, top, znear, zfar)
 }
 
@@ -185,16 +185,16 @@ pub fn ortho_rh<N: RealField>(left: N, right: N, bottom: N, top: N, znear: N, 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<N: RealField>(
-    left: N,
-    right: N,
-    bottom: N,
-    top: N,
-    znear: N,
-    zfar: N,
-) -> TMat4<N> {
-    let two: N = crate::convert(2.0);
-    let mut mat: TMat4<N> = TMat4::<N>::identity();
+pub fn ortho_rh_no<T: RealField>(
+    left: T,
+    right: T,
+    bottom: T,
+    top: T,
+    znear: T,
+    zfar: T,
+) -> TMat4<T> {
+    let two: T = crate::convert(2.0);
+    let mut mat: TMat4<T> = TMat4::<T>::identity();
 
     mat[(0, 0)] = two / (right - left);
     mat[(0, 3)] = -(right + left) / (right - left);
@@ -217,17 +217,17 @@ pub fn ortho_rh_no<N: 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<N: RealField>(
-    left: N,
-    right: N,
-    bottom: N,
-    top: N,
-    znear: N,
-    zfar: N,
-) -> TMat4<N> {
-    let one: N = N::one();
-    let two: N = crate::convert(2.0);
-    let mut mat: TMat4<N> = TMat4::<N>::identity();
+pub fn ortho_rh_zo<T: RealField>(
+    left: T,
+    right: T,
+    bottom: T,
+    top: T,
+    znear: T,
+    zfar: T,
+) -> TMat4<T> {
+    let one: T = T::one();
+    let two: T = crate::convert(2.0);
+    let mut mat: TMat4<T> = TMat4::<T>::identity();
 
     mat[(0, 0)] = two / (right - left);
     mat[(0, 3)] = -(right + left) / (right - left);
@@ -250,7 +250,7 @@ pub fn ortho_rh_zo<N: 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<N: RealField>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+pub fn ortho_zo<T: RealField>(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 +264,7 @@ pub fn ortho_zo<N: RealField>(left: N, right: N, bottom: N, top: N, znear: N, 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<N: RealField>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_fov<T: RealField>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
     perspective_fov_rh_no(fov, width, height, near, far)
 }
 
@@ -278,7 +278,7 @@ pub fn perspective_fov<N: RealField>(fov: N, width: N, height: N, near: N, 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<N: RealField>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_fov_lh<T: RealField>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
     perspective_fov_lh_no(fov, width, height, near, far)
 }
 
@@ -292,16 +292,16 @@ pub fn perspective_fov_lh<N: RealField>(fov: N, width: N, height: N, near: N, 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<N: RealField>(
-    fov: N,
-    width: N,
-    height: N,
-    near: N,
-    far: N,
-) -> TMat4<N> {
-    assert!(width > N::zero(), "The width must be greater than zero");
-    assert!(height > N::zero(), "The height must be greater than zero.");
-    assert!(fov > N::zero(), "The fov must be greater than zero");
+pub fn perspective_fov_lh_no<T: RealField>(
+    fov: T,
+    width: T,
+    height: T,
+    near: T,
+    far: T,
+) -> TMat4<T> {
+    assert!(width > T::zero(), "The width must be greater than zero");
+    assert!(height > T::zero(), "The height must be greater than zero.");
+    assert!(fov > T::zero(), "The fov must be greater than zero");
 
     let mut mat = TMat4::zeros();
 
@@ -313,7 +313,7 @@ pub fn perspective_fov_lh_no<N: RealField>(
     mat[(1, 1)] = h;
     mat[(2, 2)] = (far + near) / (far - near);
     mat[(2, 3)] = -(far * near * crate::convert(2.0)) / (far - near);
-    mat[(3, 2)] = N::one();
+    mat[(3, 2)] = T::one();
 
     mat
 }
@@ -328,16 +328,16 @@ pub fn perspective_fov_lh_no<N: 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<N: RealField>(
-    fov: N,
-    width: N,
-    height: N,
-    near: N,
-    far: N,
-) -> TMat4<N> {
-    assert!(width > N::zero(), "The width must be greater than zero");
-    assert!(height > N::zero(), "The height must be greater than zero.");
-    assert!(fov > N::zero(), "The fov must be greater than zero");
+pub fn perspective_fov_lh_zo<T: RealField>(
+    fov: T,
+    width: T,
+    height: T,
+    near: T,
+    far: T,
+) -> TMat4<T> {
+    assert!(width > T::zero(), "The width must be greater than zero");
+    assert!(height > T::zero(), "The height must be greater than zero.");
+    assert!(fov > T::zero(), "The fov must be greater than zero");
 
     let mut mat = TMat4::zeros();
 
@@ -349,7 +349,7 @@ pub fn perspective_fov_lh_zo<N: RealField>(
     mat[(1, 1)] = h;
     mat[(2, 2)] = far / (far - near);
     mat[(2, 3)] = -(far * near) / (far - near);
-    mat[(3, 2)] = N::one();
+    mat[(3, 2)] = T::one();
 
     mat
 }
@@ -364,7 +364,7 @@ pub fn perspective_fov_lh_zo<N: 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<N: RealField>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_fov_no<T: RealField>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
     perspective_fov_rh_no(fov, width, height, near, far)
 }
 
@@ -378,7 +378,7 @@ pub fn perspective_fov_no<N: RealField>(fov: N, width: N, height: N, near: N, 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<N: RealField>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_fov_rh<T: RealField>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
     perspective_fov_rh_no(fov, width, height, near, far)
 }
 
@@ -392,16 +392,16 @@ pub fn perspective_fov_rh<N: RealField>(fov: N, width: N, height: N, near: N, 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<N: RealField>(
-    fov: N,
-    width: N,
-    height: N,
-    near: N,
-    far: N,
-) -> TMat4<N> {
-    assert!(width > N::zero(), "The width must be greater than zero");
-    assert!(height > N::zero(), "The height must be greater than zero.");
-    assert!(fov > N::zero(), "The fov must be greater than zero");
+pub fn perspective_fov_rh_no<T: RealField>(
+    fov: T,
+    width: T,
+    height: T,
+    near: T,
+    far: T,
+) -> TMat4<T> {
+    assert!(width > T::zero(), "The width must be greater than zero");
+    assert!(height > T::zero(), "The height must be greater than zero.");
+    assert!(fov > T::zero(), "The fov must be greater than zero");
 
     let mut mat = TMat4::zeros();
 
@@ -413,7 +413,7 @@ pub fn perspective_fov_rh_no<N: RealField>(
     mat[(1, 1)] = h;
     mat[(2, 2)] = -(far + near) / (far - near);
     mat[(2, 3)] = -(far * near * crate::convert(2.0)) / (far - near);
-    mat[(3, 2)] = -N::one();
+    mat[(3, 2)] = -T::one();
 
     mat
 }
@@ -428,16 +428,16 @@ pub fn perspective_fov_rh_no<N: 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<N: RealField>(
-    fov: N,
-    width: N,
-    height: N,
-    near: N,
-    far: N,
-) -> TMat4<N> {
-    assert!(width > N::zero(), "The width must be greater than zero");
-    assert!(height > N::zero(), "The height must be greater than zero.");
-    assert!(fov > N::zero(), "The fov must be greater than zero");
+pub fn perspective_fov_rh_zo<T: RealField>(
+    fov: T,
+    width: T,
+    height: T,
+    near: T,
+    far: T,
+) -> TMat4<T> {
+    assert!(width > T::zero(), "The width must be greater than zero");
+    assert!(height > T::zero(), "The height must be greater than zero.");
+    assert!(fov > T::zero(), "The fov must be greater than zero");
 
     let mut mat = TMat4::zeros();
 
@@ -449,7 +449,7 @@ pub fn perspective_fov_rh_zo<N: RealField>(
     mat[(1, 1)] = h;
     mat[(2, 2)] = far / (near - far);
     mat[(2, 3)] = -(far * near) / (far - near);
-    mat[(3, 2)] = -N::one();
+    mat[(3, 2)] = -T::one();
 
     mat
 }
@@ -464,7 +464,7 @@ pub fn perspective_fov_rh_zo<N: 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<N: RealField>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_fov_zo<T: RealField>(fov: T, width: T, height: T, near: T, far: T) -> TMat4<T> {
     perspective_fov_rh_zo(fov, width, height, near, far)
 }
 
@@ -479,7 +479,7 @@ pub fn perspective_fov_zo<N: RealField>(fov: N, width: N, height: N, near: N, fa
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective<T: RealField>(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 +508,7 @@ pub fn perspective<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_lh<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_lh<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     perspective_lh_no(aspect, fovy, near, far)
 }
 
@@ -523,19 +523,19 @@ pub fn perspective_lh<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_lh_no<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_lh_no<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     assert!(
-        !relative_eq!(far - near, N::zero()),
+        !relative_eq!(far - near, T::zero()),
         "The near-plane and far-plane must not be superimposed."
     );
     assert!(
-        !relative_eq!(aspect, N::zero()),
+        !relative_eq!(aspect, T::zero()),
         "The aspect ratio must not be zero."
     );
 
-    let one = N::one();
-    let two: N = crate::convert(2.0);
-    let mut mat: TMat4<N> = TMat4::zeros();
+    let one = T::one();
+    let two: T = crate::convert(2.0);
+    let mut mat: TMat4<T> = TMat4::zeros();
 
     let tan_half_fovy = (fovy / two).tan();
 
@@ -559,19 +559,19 @@ pub fn perspective_lh_no<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> T
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_lh_zo<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_lh_zo<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     assert!(
-        !relative_eq!(far - near, N::zero()),
+        !relative_eq!(far - near, T::zero()),
         "The near-plane and far-plane must not be superimposed."
     );
     assert!(
-        !relative_eq!(aspect, N::zero()),
+        !relative_eq!(aspect, T::zero()),
         "The aspect ratio must not be zero."
     );
 
-    let one = N::one();
-    let two: N = crate::convert(2.0);
-    let mut mat: TMat4<N> = TMat4::zeros();
+    let one = T::one();
+    let two: T = crate::convert(2.0);
+    let mut mat: TMat4<T> = TMat4::zeros();
 
     let tan_half_fovy = (fovy / two).tan();
 
@@ -595,7 +595,7 @@ pub fn perspective_lh_zo<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> T
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_no<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_no<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     perspective_rh_no(aspect, fovy, near, far)
 }
 
@@ -610,7 +610,7 @@ pub fn perspective_no<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_rh<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_rh<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     perspective_rh_no(aspect, fovy, near, far)
 }
 
@@ -625,19 +625,19 @@ pub fn perspective_rh<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_rh_no<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_rh_no<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     assert!(
-        !relative_eq!(far - near, N::zero()),
+        !relative_eq!(far - near, T::zero()),
         "The near-plane and far-plane must not be superimposed."
     );
     assert!(
-        !relative_eq!(aspect, N::zero()),
+        !relative_eq!(aspect, T::zero()),
         "The aspect ratio must not be zero."
     );
 
-    let negone = -N::one();
-    let one = N::one();
-    let two: N = crate::convert(2.0);
+    let negone = -T::one();
+    let one = T::one();
+    let two: T = crate::convert(2.0);
     let mut mat = TMat4::zeros();
 
     let tan_half_fovy = (fovy / two).tan();
@@ -662,18 +662,18 @@ pub fn perspective_rh_no<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> T
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_rh_zo<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_rh_zo<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     assert!(
-        !relative_eq!(far - near, N::zero()),
+        !relative_eq!(far - near, T::zero()),
         "The near-plane and far-plane must not be superimposed."
     );
     assert!(
-        !relative_eq!(aspect, N::zero()),
+        !relative_eq!(aspect, T::zero()),
         "The aspect ratio must not be zero."
     );
 
-    let negone = -N::one();
-    let one = N::one();
+    let negone = -T::one();
+    let one = T::one();
     let two = crate::convert(2.0);
     let mut mat = TMat4::zeros();
 
@@ -699,7 +699,7 @@ pub fn perspective_rh_zo<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> T
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn perspective_zo<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+pub fn perspective_zo<T: RealField>(aspect: T, fovy: T, near: T, far: T) -> TMat4<T> {
     perspective_rh_zo(aspect, fovy, near, far)
 }
 
@@ -713,15 +713,15 @@ pub fn perspective_zo<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
-pub fn infinite_perspective_rh_no<N: RealField>(aspect: N, fovy: N, near: N) -> TMat4<N> {
-    let f = N::one() / (fovy * na::convert(0.5)).tan();
+pub fn infinite_perspective_rh_no<T: RealField>(aspect: T, fovy: T, near: T) -> TMat4<T> {
+    let f = T::one() / (fovy * na::convert(0.5)).tan();
     let mut mat = TMat4::zeros();
 
     mat[(0, 0)] = f / aspect;
     mat[(1, 1)] = f;
-    mat[(2, 2)] = -N::one();
+    mat[(2, 2)] = -T::one();
     mat[(2, 3)] = -near * na::convert(2.0);
-    mat[(3, 2)] = -N::one();
+    mat[(3, 2)] = -T::one();
 
     mat
 }
@@ -738,15 +738,15 @@ pub fn infinite_perspective_rh_no<N: RealField>(aspect: N, fovy: N, near: N) ->
 /// 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<N: RealField>(aspect: N, fovy: N, near: N) -> TMat4<N> {
-    let f = N::one() / (fovy * na::convert(0.5)).tan();
+pub fn infinite_perspective_rh_zo<T: RealField>(aspect: T, fovy: T, near: T) -> TMat4<T> {
+    let f = T::one() / (fovy * na::convert(0.5)).tan();
     let mut mat = TMat4::zeros();
 
     mat[(0, 0)] = f / aspect;
     mat[(1, 1)] = f;
-    mat[(2, 2)] = -N::one();
+    mat[(2, 2)] = -T::one();
     mat[(2, 3)] = -near;
-    mat[(3, 2)] = -N::one();
+    mat[(3, 2)] = -T::one();
 
     mat
 }
@@ -763,8 +763,8 @@ pub fn infinite_perspective_rh_zo<N: RealField>(aspect: N, fovy: N, near: N) ->
 /// # 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<N: RealField>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
-    let one = N::one();
+pub fn reversed_perspective_rh_zo<T: RealField>(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();
 
@@ -791,22 +791,22 @@ pub fn reversed_perspective_rh_zo<N: RealField>(aspect: N, fovy: N, near: N, 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<N: RealField>(aspect: N, fovy: N, near: N) -> TMat4<N> {
-    let f = N::one() / (fovy * na::convert(0.5)).tan();
+pub fn reversed_infinite_perspective_rh_zo<T: RealField>(aspect: T, fovy: T, near: T) -> TMat4<T> {
+    let f = T::one() / (fovy * na::convert(0.5)).tan();
     let mut mat = TMat4::zeros();
 
     mat[(0, 0)] = f / aspect;
     mat[(1, 1)] = f;
     mat[(2, 3)] = near;
-    mat[(3, 2)] = -N::one();
+    mat[(3, 2)] = -T::one();
 
     mat
 }
 
-//pub fn tweaked_infinite_perspective<N: RealField>(fovy: N, aspect: N, near: N) -> TMat4<N> {
+//pub fn tweaked_infinite_perspective<T: RealField>(fovy: T, aspect: T, near: T) -> TMat4<T> {
 //    unimplemented!()
 //}
 //
-//pub fn tweaked_infinite_perspective_ep<N: RealField>(fovy: N, aspect: N, near: N, ep: N) -> TMat4<N> {
+//pub fn tweaked_infinite_perspective_ep<T: RealField>(fovy: T, aspect: T, near: T, ep: T) -> TMat4<T> {
 //    unimplemented!()
 //}

nalgebra-glm/src/ext/matrix_projection.rs

@@ -1,4 +1,4 @@
-use na::{self, RealField, U3};
+use na::{self, RealField};
 
 use crate::aliases::{TMat4, TVec2, TVec3, TVec4};
 
@@ -9,22 +9,22 @@ 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<N: RealField>(
-    center: &TVec2<N>,
-    delta: &TVec2<N>,
-    viewport: &TVec4<N>,
-) -> TMat4<N> {
+pub fn pick_matrix<T: RealField>(
+    center: &TVec2<T>,
+    delta: &TVec2<T>,
+    viewport: &TVec4<T>,
+) -> TMat4<T> {
     let shift = TVec3::new(
         (viewport.z - (center.x - viewport.x) * na::convert(2.0)) / delta.x,
         (viewport.w - (center.y - viewport.y) * na::convert(2.0)) / delta.y,
-        N::zero(),
+        T::zero(),
     );
 
     let result = TMat4::new_translation(&shift);
     result.prepend_nonuniform_scaling(&TVec3::new(
         viewport.z / delta.x,
         viewport.w / delta.y,
-        N::one(),
+        T::one(),
     ))
 }
 
@@ -45,12 +45,12 @@ pub fn pick_matrix<N: RealField>(
 /// * [`unproject`](fn.unproject.html)
 /// * [`unproject_no`](fn.unproject_no.html)
 /// * [`unproject_zo`](fn.unproject_zo.html)
-pub fn project<N: RealField>(
-    obj: &TVec3<N>,
-    model: &TMat4<N>,
-    proj: &TMat4<N>,
-    viewport: TVec4<N>,
-) -> TVec3<N> {
+pub fn project<T: RealField>(
+    obj: &TVec3<T>,
+    model: &TMat4<T>,
+    proj: &TMat4<T>,
+    viewport: TVec4<T>,
+) -> TVec3<T> {
     project_no(obj, model, proj, viewport)
 }
 
@@ -72,12 +72,12 @@ pub fn project<N: RealField>(
 /// * [`unproject`](fn.unproject.html)
 /// * [`unproject_no`](fn.unproject_no.html)
 /// * [`unproject_zo`](fn.unproject_zo.html)
-pub fn project_no<N: RealField>(
-    obj: &TVec3<N>,
-    model: &TMat4<N>,
-    proj: &TMat4<N>,
-    viewport: TVec4<N>,
-) -> TVec3<N> {
+pub fn project_no<T: RealField>(
+    obj: &TVec3<T>,
+    model: &TMat4<T>,
+    proj: &TMat4<T>,
+    viewport: TVec4<T>,
+) -> TVec3<T> {
     let proj = project_zo(obj, model, proj, viewport);
     TVec3::new(proj.x, proj.y, proj.z * na::convert(0.5) + na::convert(0.5))
 }
@@ -100,18 +100,18 @@ pub fn project_no<N: RealField>(
 /// * [`unproject`](fn.unproject.html)
 /// * [`unproject_no`](fn.unproject_no.html)
 /// * [`unproject_zo`](fn.unproject_zo.html)
-pub fn project_zo<N: RealField>(
-    obj: &TVec3<N>,
-    model: &TMat4<N>,
-    proj: &TMat4<N>,
-    viewport: TVec4<N>,
-) -> TVec3<N> {
-    let normalized = proj * model * TVec4::new(obj.x, obj.y, obj.z, N::one());
-    let scale = N::one() / normalized.w;
+pub fn project_zo<T: RealField>(
+    obj: &TVec3<T>,
+    model: &TMat4<T>,
+    proj: &TMat4<T>,
+    viewport: TVec4<T>,
+) -> TVec3<T> {
+    let normalized = proj * model * TVec4::new(obj.x, obj.y, obj.z, T::one());
+    let scale = T::one() / normalized.w;
 
     TVec3::new(
-        viewport.x + (viewport.z * (normalized.x * scale + N::one()) * na::convert(0.5)),
-        viewport.y + (viewport.w * (normalized.y * scale + N::one()) * na::convert(0.5)),
+        viewport.x + (viewport.z * (normalized.x * scale + T::one()) * na::convert(0.5)),
+        viewport.y + (viewport.w * (normalized.y * scale + T::one()) * na::convert(0.5)),
         normalized.z * scale,
     )
 }
@@ -133,12 +133,12 @@ pub fn project_zo<N: RealField>(
 /// * [`project_zo`](fn.project_zo.html)
 /// * [`unproject_no`](fn.unproject_no.html)
 /// * [`unproject_zo`](fn.unproject_zo.html)
-pub fn unproject<N: RealField>(
-    win: &TVec3<N>,
-    model: &TMat4<N>,
-    proj: &TMat4<N>,
-    viewport: TVec4<N>,
-) -> TVec3<N> {
+pub fn unproject<T: RealField>(
+    win: &TVec3<T>,
+    model: &TMat4<T>,
+    proj: &TMat4<T>,
+    viewport: TVec4<T>,
+) -> TVec3<T> {
     unproject_no(win, model, proj, viewport)
 }
 
@@ -160,23 +160,23 @@ pub fn unproject<N: RealField>(
 /// * [`project_zo`](fn.project_zo.html)
 /// * [`unproject`](fn.unproject.html)
 /// * [`unproject_zo`](fn.unproject_zo.html)
-pub fn unproject_no<N: RealField>(
-    win: &TVec3<N>,
-    model: &TMat4<N>,
-    proj: &TMat4<N>,
-    viewport: TVec4<N>,
-) -> TVec3<N> {
-    let _2: N = na::convert(2.0);
+pub fn unproject_no<T: RealField>(
+    win: &TVec3<T>,
+    model: &TMat4<T>,
+    proj: &TMat4<T>,
+    viewport: TVec4<T>,
+) -> TVec3<T> {
+    let _2: T = na::convert(2.0);
     let transform = (proj * model).try_inverse().unwrap_or_else(TMat4::zeros);
     let pt = TVec4::new(
-        _2 * (win.x - viewport.x) / viewport.z - N::one(),
-        _2 * (win.y - viewport.y) / viewport.w - N::one(),
-        _2 * win.z - N::one(),
-        N::one(),
+        _2 * (win.x - viewport.x) / viewport.z - T::one(),
+        _2 * (win.y - viewport.y) / viewport.w - T::one(),
+        _2 * win.z - T::one(),
+        T::one(),
     );
 
     let result = transform * pt;
-    result.fixed_rows::<U3>(0) / result.w
+    result.fixed_rows::<3>(0) / result.w
 }
 
 /// Map the specified window coordinates (win.x, win.y, win.z) into object coordinates.
@@ -197,21 +197,21 @@ pub fn unproject_no<N: RealField>(
 /// * [`project_zo`](fn.project_zo.html)
 /// * [`unproject`](fn.unproject.html)
 /// * [`unproject_no`](fn.unproject_no.html)
-pub fn unproject_zo<N: RealField>(
-    win: &TVec3<N>,
-    model: &TMat4<N>,
-    proj: &TMat4<N>,
-    viewport: TVec4<N>,
-) -> TVec3<N> {
-    let _2: N = na::convert(2.0);
+pub fn unproject_zo<T: RealField>(
+    win: &TVec3<T>,
+    model: &TMat4<T>,
+    proj: &TMat4<T>,
+    viewport: TVec4<T>,
+) -> TVec3<T> {
+    let _2: T = na::convert(2.0);
     let transform = (proj * model).try_inverse().unwrap_or_else(TMat4::zeros);
     let pt = TVec4::new(
-        _2 * (win.x - viewport.x) / viewport.z - N::one(),
-        _2 * (win.y - viewport.y) / viewport.w - N::one(),
+        _2 * (win.x - viewport.x) / viewport.z - T::one(),
+        _2 * (win.y - viewport.y) / viewport.w - T::one(),
         win.z,
-        N::one(),
+        T::one(),
     );
 
     let result = transform * pt;
-    result.fixed_rows::<U3>(0) / result.w
+    result.fixed_rows::<3>(0) / result.w
 }

nalgebra-glm/src/ext/matrix_relationnal.rs

@@ -1,21 +1,16 @@
-use na::DefaultAllocator;
-
 use crate::aliases::{TMat, TVec};
-use crate::traits::{Alloc, Dimension, Number};
+use crate::traits::Number;
 
 /// Perform a component-wise equal-to comparison of two matrices.
 ///
 /// Return a boolean vector which components value is True if this expression is satisfied per column of the matrices.
-pub fn equal_columns<N: Number, R: Dimension, C: Dimension>(
-    x: &TMat<N, R, C>,
-    y: &TMat<N, R, C>,
-) -> TVec<bool, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn equal_columns<T: Number, const R: usize, const C: usize>(
+    x: &TMat<T, R, C>,
+    y: &TMat<T, R, C>,
+) -> TVec<bool, C> {
     let mut res = TVec::<_, C>::repeat(false);
 
-    for i in 0..C::dim() {
+    for i in 0..C {
         res[i] = x.column(i) == y.column(i)
     }
 
@@ -25,31 +20,25 @@ where
 /// Returns the component-wise comparison of `|x - y| < epsilon`.
 ///
 /// True if this expression is satisfied.
-pub fn equal_columns_eps<N: Number, R: Dimension, C: Dimension>(
-    x: &TMat<N, R, C>,
-    y: &TMat<N, R, C>,
-    epsilon: N,
-) -> TVec<bool, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn equal_columns_eps<T: Number, const R: usize, const C: usize>(
+    x: &TMat<T, R, C>,
+    y: &TMat<T, R, C>,
+    epsilon: T,
+) -> TVec<bool, C> {
     equal_columns_eps_vec(x, y, &TVec::<_, C>::repeat(epsilon))
 }
 
 /// Returns the component-wise comparison on each matrix column `|x - y| < epsilon`.
 ///
 /// True if this expression is satisfied.
-pub fn equal_columns_eps_vec<N: Number, R: Dimension, C: Dimension>(
-    x: &TMat<N, R, C>,
-    y: &TMat<N, R, C>,
-    epsilon: &TVec<N, C>,
-) -> TVec<bool, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn equal_columns_eps_vec<T: Number, const R: usize, const C: usize>(
+    x: &TMat<T, R, C>,
+    y: &TMat<T, R, C>,
+    epsilon: &TVec<T, C>,
+) -> TVec<bool, C> {
     let mut res = TVec::<_, C>::repeat(false);
 
-    for i in 0..C::dim() {
+    for i in 0..C {
         res[i] = (x.column(i) - y.column(i)).abs() < TVec::<_, R>::repeat(epsilon[i])
     }
 
@@ -59,16 +48,13 @@ where
 /// Perform a component-wise not-equal-to comparison of two matrices.
 ///
 /// Return a boolean vector which components value is True if this expression is satisfied per column of the matrices.
-pub fn not_equal_columns<N: Number, R: Dimension, C: Dimension>(
-    x: &TMat<N, R, C>,
-    y: &TMat<N, R, C>,
-) -> TVec<bool, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn not_equal_columns<T: Number, const R: usize, const C: usize>(
+    x: &TMat<T, R, C>,
+    y: &TMat<T, R, C>,
+) -> TVec<bool, C> {
     let mut res = TVec::<_, C>::repeat(false);
 
-    for i in 0..C::dim() {
+    for i in 0..C {
         res[i] = x.column(i) != y.column(i)
     }
 
@@ -78,31 +64,25 @@ where
 /// Returns the component-wise comparison of `|x - y| < epsilon`.
 ///
 /// True if this expression is not satisfied.
-pub fn not_equal_columns_eps<N: Number, R: Dimension, C: Dimension>(
-    x: &TMat<N, R, C>,
-    y: &TMat<N, R, C>,
-    epsilon: N,
-) -> TVec<bool, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn not_equal_columns_eps<T: Number, const R: usize, const C: usize>(
+    x: &TMat<T, R, C>,
+    y: &TMat<T, R, C>,
+    epsilon: T,
+) -> TVec<bool, C> {
     not_equal_columns_eps_vec(x, y, &TVec::<_, C>::repeat(epsilon))
 }
 
 /// Returns the component-wise comparison of `|x - y| >= epsilon`.
 ///
 /// True if this expression is not satisfied.
-pub fn not_equal_columns_eps_vec<N: Number, R: Dimension, C: Dimension>(
-    x: &TMat<N, R, C>,
-    y: &TMat<N, R, C>,
-    epsilon: &TVec<N, C>,
-) -> TVec<bool, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn not_equal_columns_eps_vec<T: Number, const R: usize, const C: usize>(
+    x: &TMat<T, R, C>,
+    y: &TMat<T, R, C>,
+    epsilon: &TVec<T, C>,
+) -> TVec<bool, C> {
     let mut res = TVec::<_, C>::repeat(false);
 
-    for i in 0..C::dim() {
+    for i in 0..C {
         res[i] = (x.column(i) - y.column(i)).abs() >= TVec::<_, R>::repeat(epsilon[i])
     }
 

nalgebra-glm/src/ext/matrix_transform.rs

@@ -1,14 +1,11 @@
-use na::{DefaultAllocator, Point3, RealField, Rotation3, Unit};
+use na::{Point3, RealField, Rotation3, Unit};
 
 use crate::aliases::{TMat, TMat4, TVec, TVec3};
-use crate::traits::{Alloc, Dimension, Number};
+use crate::traits::Number;
 
 /// The identity matrix.
-pub fn identity<N: Number, D: Dimension>() -> TMat<N, D, D>
-where
-    DefaultAllocator: Alloc<N, D, D>,
-{
-    TMat::<N, D, D>::identity()
+pub fn identity<T: Number, const D: usize>() -> TMat<T, D, D> {
+    TMat::<T, D, D>::identity()
 }
 
 /// Build a look at view matrix based on the right handedness.
@@ -23,7 +20,7 @@ where
 ///
 /// * [`look_at_lh`](fn.look_at_lh.html)
 /// * [`look_at_rh`](fn.look_at_rh.html)
-pub fn look_at<N: RealField>(eye: &TVec3<N>, center: &TVec3<N>, up: &TVec3<N>) -> TMat4<N> {
+pub fn look_at<T: RealField>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
     look_at_rh(eye, center, up)
 }
 
@@ -39,7 +36,7 @@ pub fn look_at<N: RealField>(eye: &TVec3<N>, center: &TVec3<N>, up: &TVec3<N>) -
 ///
 /// * [`look_at`](fn.look_at.html)
 /// * [`look_at_rh`](fn.look_at_rh.html)
-pub fn look_at_lh<N: RealField>(eye: &TVec3<N>, center: &TVec3<N>, up: &TVec3<N>) -> TMat4<N> {
+pub fn look_at_lh<T: RealField>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
     TMat::look_at_lh(&Point3::from(*eye), &Point3::from(*center), up)
 }
 
@@ -55,7 +52,7 @@ pub fn look_at_lh<N: RealField>(eye: &TVec3<N>, center: &TVec3<N>, up: &TVec3<N>
 ///
 /// * [`look_at`](fn.look_at.html)
 /// * [`look_at_lh`](fn.look_at_lh.html)
-pub fn look_at_rh<N: RealField>(eye: &TVec3<N>, center: &TVec3<N>, up: &TVec3<N>) -> TMat4<N> {
+pub fn look_at_rh<T: RealField>(eye: &TVec3<T>, center: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
     TMat::look_at_rh(&Point3::from(*eye), &Point3::from(*center), up)
 }
 
@@ -74,7 +71,7 @@ pub fn look_at_rh<N: RealField>(eye: &TVec3<N>, center: &TVec3<N>, up: &TVec3<N>
 /// * [`rotate_z`](fn.rotate_z.html)
 /// * [`scale`](fn.scale.html)
 /// * [`translate`](fn.translate.html)
-pub fn rotate<N: RealField>(m: &TMat4<N>, angle: N, axis: &TVec3<N>) -> TMat4<N> {
+pub fn rotate<T: RealField>(m: &TMat4<T>, angle: T, axis: &TVec3<T>) -> TMat4<T> {
     m * Rotation3::from_axis_angle(&Unit::new_normalize(*axis), angle).to_homogeneous()
 }
 
@@ -92,7 +89,7 @@ pub fn rotate<N: RealField>(m: &TMat4<N>, angle: N, axis: &TVec3<N>) -> TMat4<N>
 /// * [`rotate_z`](fn.rotate_z.html)
 /// * [`scale`](fn.scale.html)
 /// * [`translate`](fn.translate.html)
-pub fn rotate_x<N: RealField>(m: &TMat4<N>, angle: N) -> TMat4<N> {
+pub fn rotate_x<T: RealField>(m: &TMat4<T>, angle: T) -> TMat4<T> {
     rotate(m, angle, &TVec::x())
 }
 
@@ -110,7 +107,7 @@ pub fn rotate_x<N: RealField>(m: &TMat4<N>, angle: N) -> TMat4<N> {
 /// * [`rotate_z`](fn.rotate_z.html)
 /// * [`scale`](fn.scale.html)
 /// * [`translate`](fn.translate.html)
-pub fn rotate_y<N: RealField>(m: &TMat4<N>, angle: N) -> TMat4<N> {
+pub fn rotate_y<T: RealField>(m: &TMat4<T>, angle: T) -> TMat4<T> {
     rotate(m, angle, &TVec::y())
 }
 
@@ -128,7 +125,7 @@ pub fn rotate_y<N: RealField>(m: &TMat4<N>, angle: N) -> TMat4<N> {
 /// * [`rotate_y`](fn.rotate_y.html)
 /// * [`scale`](fn.scale.html)
 /// * [`translate`](fn.translate.html)
-pub fn rotate_z<N: RealField>(m: &TMat4<N>, angle: N) -> TMat4<N> {
+pub fn rotate_z<T: RealField>(m: &TMat4<T>, angle: T) -> TMat4<T> {
     rotate(m, angle, &TVec::z())
 }
 
@@ -146,7 +143,7 @@ pub fn rotate_z<N: RealField>(m: &TMat4<N>, angle: N) -> TMat4<N> {
 /// * [`rotate_y`](fn.rotate_y.html)
 /// * [`rotate_z`](fn.rotate_z.html)
 /// * [`translate`](fn.translate.html)
-pub fn scale<N: Number>(m: &TMat4<N>, v: &TVec3<N>) -> TMat4<N> {
+pub fn scale<T: Number>(m: &TMat4<T>, v: &TVec3<T>) -> TMat4<T> {
     m.prepend_nonuniform_scaling(v)
 }
 
@@ -164,6 +161,6 @@ pub fn scale<N: Number>(m: &TMat4<N>, v: &TVec3<N>) -> TMat4<N> {
 /// * [`rotate_y`](fn.rotate_y.html)
 /// * [`rotate_z`](fn.rotate_z.html)
 /// * [`scale`](fn.scale.html)
-pub fn translate<N: Number>(m: &TMat4<N>, v: &TVec3<N>) -> TMat4<N> {
+pub fn translate<T: Number>(m: &TMat4<T>, v: &TVec3<T>) -> TMat4<T> {
     m.prepend_translation(v)
 }

nalgebra-glm/src/ext/quaternion_common.rs

@@ -3,34 +3,34 @@ use na::{self, RealField, Unit};
 use crate::aliases::Qua;
 
 /// The conjugate of `q`.
-pub fn quat_conjugate<N: RealField>(q: &Qua<N>) -> Qua<N> {
+pub fn quat_conjugate<T: RealField>(q: &Qua<T>) -> Qua<T> {
     q.conjugate()
 }
 
 /// The inverse of `q`.
-pub fn quat_inverse<N: RealField>(q: &Qua<N>) -> Qua<N> {
+pub fn quat_inverse<T: RealField>(q: &Qua<T>) -> Qua<T> {
     q.try_inverse().unwrap_or_else(na::zero)
 }
 
-//pub fn quat_isinf<N: RealField>(x: &Qua<N>) -> TVec<bool, U4> {
+//pub fn quat_isinf<T: RealField>(x: &Qua<T>) -> TVec<bool, U4> {
 //    x.coords.map(|e| e.is_inf())
 //}
 
-//pub fn quat_isnan<N: RealField>(x: &Qua<N>) -> TVec<bool, U4> {
+//pub fn quat_isnan<T: RealField>(x: &Qua<T>) -> TVec<bool, U4> {
 //    x.coords.map(|e| e.is_nan())
 //}
 
 /// Interpolate linearly between `x` and `y`.
-pub fn quat_lerp<N: RealField>(x: &Qua<N>, y: &Qua<N>, a: N) -> Qua<N> {
+pub fn quat_lerp<T: RealField>(x: &Qua<T>, y: &Qua<T>, a: T) -> Qua<T> {
     x.lerp(y, a)
 }
 
-//pub fn quat_mix<N: RealField>(x: &Qua<N>, y: &Qua<N>, a: N) -> Qua<N> {
-//    x * (N::one() - a) + y * a
+//pub fn quat_mix<T: RealField>(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<N: RealField>(x: &Qua<N>, y: &Qua<N>, a: N) -> Qua<N> {
+pub fn quat_slerp<T: RealField>(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

@@ -3,26 +3,26 @@ use na::RealField;
 use crate::aliases::Qua;
 
 /// Multiplies two quaternions.
-pub fn quat_cross<N: RealField>(q1: &Qua<N>, q2: &Qua<N>) -> Qua<N> {
+pub fn quat_cross<T: RealField>(q1: &Qua<T>, q2: &Qua<T>) -> Qua<T> {
     q1 * q2
 }
 
 /// The scalar product of two quaternions.
-pub fn quat_dot<N: RealField>(x: &Qua<N>, y: &Qua<N>) -> N {
+pub fn quat_dot<T: RealField>(x: &Qua<T>, y: &Qua<T>) -> T {
     x.dot(y)
 }
 
 /// The magnitude of the quaternion `q`.
-pub fn quat_length<N: RealField>(q: &Qua<N>) -> N {
+pub fn quat_length<T: RealField>(q: &Qua<T>) -> T {
     q.norm()
 }
 
 /// The magnitude of the quaternion `q`.
-pub fn quat_magnitude<N: RealField>(q: &Qua<N>) -> N {
+pub fn quat_magnitude<T: RealField>(q: &Qua<T>) -> T {
     q.norm()
 }
 
 /// Normalizes the quaternion `q`.
-pub fn quat_normalize<N: RealField>(q: &Qua<N>) -> Qua<N> {
+pub fn quat_normalize<T: RealField>(q: &Qua<T>) -> Qua<T> {
     q.normalize()
 }

nalgebra-glm/src/ext/quaternion_relational.rs

@@ -1,23 +1,23 @@
-use na::{RealField, U4};
+use na::RealField;
 
 use crate::aliases::{Qua, TVec};
 
 /// Component-wise equality comparison between two quaternions.
-pub fn quat_equal<N: RealField>(x: &Qua<N>, y: &Qua<N>) -> TVec<bool, U4> {
+pub fn quat_equal<T: RealField>(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<N: RealField>(x: &Qua<N>, y: &Qua<N>, epsilon: N) -> TVec<bool, U4> {
+pub fn quat_equal_eps<T: RealField>(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<N: RealField>(x: &Qua<N>, y: &Qua<N>) -> TVec<bool, U4> {
+pub fn quat_not_equal<T: RealField>(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<N: RealField>(x: &Qua<N>, y: &Qua<N>, epsilon: N) -> TVec<bool, U4> {
+pub fn quat_not_equal_eps<T: RealField>(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

@@ -3,25 +3,25 @@ use na::{RealField, Unit, UnitQuaternion};
 use crate::aliases::{Qua, TVec3};
 
 /// Computes the quaternion exponential.
-pub fn quat_exp<N: RealField>(q: &Qua<N>) -> Qua<N> {
+pub fn quat_exp<T: RealField>(q: &Qua<T>) -> Qua<T> {
     q.exp()
 }
 
 /// Computes the quaternion logarithm.
-pub fn quat_log<N: RealField>(q: &Qua<N>) -> Qua<N> {
+pub fn quat_log<T: RealField>(q: &Qua<T>) -> Qua<T> {
     q.ln()
 }
 
 /// Raises the quaternion `q` to the power `y`.
-pub fn quat_pow<N: RealField>(q: &Qua<N>, y: N) -> Qua<N> {
+pub fn quat_pow<T: RealField>(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<N: RealField>(q: &Qua<N>, angle: N, axis: &TVec3<N>) -> Qua<N> {
+pub fn quat_rotate<T: RealField>(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<N: RealField>(q: &Qua<N>) -> Qua<N> {
+//pub fn quat_sqrt<T: RealField>(q: &Qua<T>) -> Qua<T> {
 //    unimplemented!()
 //}

nalgebra-glm/src/ext/quaternion_trigonometric.rs

@@ -3,17 +3,17 @@ use na::{RealField, Unit, UnitQuaternion};
 use crate::aliases::{Qua, TVec3};
 
 /// The rotation angle of this quaternion assumed to be normalized.
-pub fn quat_angle<N: RealField>(x: &Qua<N>) -> N {
+pub fn quat_angle<T: RealField>(x: &Qua<T>) -> T {
     UnitQuaternion::from_quaternion(*x).angle()
 }
 
 /// Creates a quaternion from an axis and an angle.
-pub fn quat_angle_axis<N: RealField>(angle: N, axis: &TVec3<N>) -> Qua<N> {
+pub fn quat_angle_axis<T: RealField>(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<N: RealField>(x: &Qua<N>) -> TVec3<N> {
+pub fn quat_axis<T: RealField>(x: &Qua<T>) -> TVec3<T> {
     if let Some(a) = UnitQuaternion::from_quaternion(*x).axis() {
         a.into_inner()
     } else {

nalgebra-glm/src/ext/scalar_common.rs

@@ -15,7 +15,7 @@ use crate::traits::Number;
 /// * [`max4_scalar`](fn.max4_scalar.html)
 /// * [`min3_scalar`](fn.min3_scalar.html)
 /// * [`min4_scalar`](fn.min4_scalar.html)
-pub fn max2_scalar<N: Number>(a: N, b: N) -> N {
+pub fn max2_scalar<T: Number>(a: T, b: T) -> T {
     if a >= b {
         a
     } else {
@@ -38,7 +38,7 @@ pub fn max2_scalar<N: Number>(a: N, b: N) -> N {
 /// * [`max4_scalar`](fn.max4_scalar.html)
 /// * [`min3_scalar`](fn.min3_scalar.html)
 /// * [`min4_scalar`](fn.min4_scalar.html)
-pub fn min2_scalar<N: Number>(a: N, b: N) -> N {
+pub fn min2_scalar<T: Number>(a: T, b: T) -> T {
     if a <= b {
         a
     } else {
@@ -61,7 +61,7 @@ pub fn min2_scalar<N: Number>(a: N, b: N) -> N {
 /// * [`max4_scalar`](fn.max4_scalar.html)
 /// * [`min3_scalar`](fn.min3_scalar.html)
 /// * [`min4_scalar`](fn.min4_scalar.html)
-pub fn max3_scalar<N: Number>(a: N, b: N, c: N) -> N {
+pub fn max3_scalar<T: Number>(a: T, b: T, c: T) -> T {
     max2_scalar(max2_scalar(a, b), c)
 }
 
@@ -80,7 +80,7 @@ pub fn max3_scalar<N: Number>(a: N, b: N, c: N) -> N {
 /// * [`max3_scalar`](fn.max3_scalar.html)
 /// * [`min3_scalar`](fn.min3_scalar.html)
 /// * [`min4_scalar`](fn.min4_scalar.html)
-pub fn max4_scalar<N: Number>(a: N, b: N, c: N, d: N) -> N {
+pub fn max4_scalar<T: Number>(a: T, b: T, c: T, d: T) -> T {
     max2_scalar(max2_scalar(a, b), max2_scalar(c, d))
 }
 
@@ -99,7 +99,7 @@ pub fn max4_scalar<N: Number>(a: N, b: N, c: N, d: N) -> N {
 /// * [`max3_scalar`](fn.max3_scalar.html)
 /// * [`max4_scalar`](fn.max4_scalar.html)
 /// * [`min4_scalar`](fn.min4_scalar.html)
-pub fn min3_scalar<N: Number>(a: N, b: N, c: N) -> N {
+pub fn min3_scalar<T: Number>(a: T, b: T, c: T) -> T {
     min2_scalar(min2_scalar(a, b), c)
 }
 
@@ -118,6 +118,6 @@ pub fn min3_scalar<N: Number>(a: N, b: N, c: N) -> N {
 /// * [`max3_scalar`](fn.max3_scalar.html)
 /// * [`max4_scalar`](fn.max4_scalar.html)
 /// * [`min3_scalar`](fn.min3_scalar.html)
-pub fn min4_scalar<N: Number>(a: N, b: N, c: N, d: N) -> N {
+pub fn min4_scalar<T: Number>(a: T, b: T, c: T, d: T) -> T {
     min2_scalar(min2_scalar(a, b), min2_scalar(c, d))
 }

nalgebra-glm/src/ext/scalar_constants.rs

@@ -2,8 +2,8 @@ use approx::AbsDiffEq;
 use na::RealField;
 
 /// Default epsilon value used for approximate comparison.
-pub fn epsilon<N: AbsDiffEq<Epsilon = N>>() -> N {
-    N::default_epsilon()
+pub fn epsilon<T: AbsDiffEq<Epsilon = T>>() -> T {
+    T::default_epsilon()
 }
 
 /// The value of PI.
@@ -22,6 +22,6 @@ pub fn epsilon<N: AbsDiffEq<Epsilon = N>>() -> N {
 /// * [`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<N: RealField>() -> N {
-    N::pi()
+pub fn pi<T: RealField>() -> T {
+    T::pi()
 }

nalgebra-glm/src/ext/vector_common.rs

@@ -1,7 +1,5 @@
-use na::{self, DefaultAllocator};
-
 use crate::aliases::TVec;
-use crate::traits::{Alloc, Dimension, Number};
+use crate::traits::Number;
 
 /// Component-wise maximum between a vector and a scalar.
 ///
@@ -16,10 +14,7 @@ use crate::traits::{Alloc, Dimension, Number};
 /// * [`min2`](fn.min2.html)
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
-pub fn max<N: Number, D: Dimension>(a: &TVec<N, D>, b: N) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn max<T: Number, const D: usize>(a: &TVec<T, D>, b: T) -> TVec<T, D> {
     a.map(|a| crate::max2_scalar(a, b))
 }
 
@@ -36,10 +31,7 @@ where
 /// * [`min2`](fn.min2.html)
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
-pub fn max2<N: Number, D: Dimension>(a: &TVec<N, D>, b: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn max2<T: Number, const D: usize>(a: &TVec<T, D>, b: &TVec<T, D>) -> TVec<T, D> {
     a.zip_map(b, |a, b| crate::max2_scalar(a, b))
 }
 
@@ -56,10 +48,11 @@ where
 /// * [`min2`](fn.min2.html)
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
-pub fn max3<N: Number, D: Dimension>(a: &TVec<N, D>, b: &TVec<N, D>, c: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn max3<T: Number, const D: usize>(
+    a: &TVec<T, D>,
+    b: &TVec<T, D>,
+    c: &TVec<T, D>,
+) -> TVec<T, D> {
     max2(&max2(a, b), c)
 }
 
@@ -76,15 +69,12 @@ where
 /// * [`min2`](fn.min2.html)
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
-pub fn max4<N: Number, D: Dimension>(
-    a: &TVec<N, D>,
-    b: &TVec<N, D>,
-    c: &TVec<N, D>,
-    d: &TVec<N, D>,
-) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn max4<T: Number, const D: usize>(
+    a: &TVec<T, D>,
+    b: &TVec<T, D>,
+    c: &TVec<T, D>,
+    d: &TVec<T, D>,
+) -> TVec<T, D> {
     max2(&max2(a, b), &max2(c, d))
 }
 
@@ -101,10 +91,7 @@ where
 /// * [`min2`](fn.min2.html)
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
-pub fn min<N: Number, D: Dimension>(x: &TVec<N, D>, y: N) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn min<T: Number, const D: usize>(x: &TVec<T, D>, y: T) -> TVec<T, D> {
     x.map(|x| crate::min2_scalar(x, y))
 }
 
@@ -121,10 +108,7 @@ where
 /// * [`min`](fn.min.html)
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
-pub fn min2<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn min2<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<T, D> {
     x.zip_map(y, |a, b| crate::min2_scalar(a, b))
 }
 
@@ -141,10 +125,11 @@ where
 /// * [`min`](fn.min.html)
 /// * [`min2`](fn.min2.html)
 /// * [`min4`](fn.min4.html)
-pub fn min3<N: Number, D: Dimension>(a: &TVec<N, D>, b: &TVec<N, D>, c: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn min3<T: Number, const D: usize>(
+    a: &TVec<T, D>,
+    b: &TVec<T, D>,
+    c: &TVec<T, D>,
+) -> TVec<T, D> {
     min2(&min2(a, b), c)
 }
 
@@ -161,14 +146,11 @@ where
 /// * [`min`](fn.min.html)
 /// * [`min2`](fn.min2.html)
 /// * [`min3`](fn.min3.html)
-pub fn min4<N: Number, D: Dimension>(
-    a: &TVec<N, D>,
-    b: &TVec<N, D>,
-    c: &TVec<N, D>,
-    d: &TVec<N, D>,
-) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn min4<T: Number, const D: usize>(
+    a: &TVec<T, D>,
+    b: &TVec<T, D>,
+    c: &TVec<T, D>,
+    d: &TVec<T, D>,
+) -> TVec<T, D> {
     min2(&min2(a, b), &min2(c, d))
 }

nalgebra-glm/src/ext/vector_relational.rs

@@ -1,7 +1,5 @@
-use na::DefaultAllocator;
-
 use crate::aliases::TVec;
-use crate::traits::{Alloc, Dimension, Number};
+use crate::traits::Number;
 
 /// Component-wise approximate equality of two vectors, using a scalar epsilon.
 ///
@@ -10,14 +8,11 @@ use crate::traits::{Alloc, Dimension, Number};
 /// * [`equal_eps_vec`](fn.equal_eps_vec.html)
 /// * [`not_equal_eps`](fn.not_equal_eps.html)
 /// * [`not_equal_eps_vec`](fn.not_equal_eps_vec.html)
-pub fn equal_eps<N: Number, D: Dimension>(
-    x: &TVec<N, D>,
-    y: &TVec<N, D>,
-    epsilon: N,
-) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn equal_eps<T: Number, const D: usize>(
+    x: &TVec<T, D>,
+    y: &TVec<T, D>,
+    epsilon: T,
+) -> TVec<bool, D> {
     x.zip_map(y, |x, y| abs_diff_eq!(x, y, epsilon = epsilon))
 }
 
@@ -28,14 +23,11 @@ where
 /// * [`equal_eps`](fn.equal_eps.html)
 /// * [`not_equal_eps`](fn.not_equal_eps.html)
 /// * [`not_equal_eps_vec`](fn.not_equal_eps_vec.html)
-pub fn equal_eps_vec<N: Number, D: Dimension>(
-    x: &TVec<N, D>,
-    y: &TVec<N, D>,
-    epsilon: &TVec<N, D>,
-) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn equal_eps_vec<T: Number, const D: usize>(
+    x: &TVec<T, D>,
+    y: &TVec<T, D>,
+    epsilon: &TVec<T, D>,
+) -> TVec<bool, D> {
     x.zip_zip_map(y, epsilon, |x, y, eps| abs_diff_eq!(x, y, epsilon = eps))
 }
 
@@ -46,14 +38,11 @@ where
 /// * [`equal_eps`](fn.equal_eps.html)
 /// * [`equal_eps_vec`](fn.equal_eps_vec.html)
 /// * [`not_equal_eps_vec`](fn.not_equal_eps_vec.html)
-pub fn not_equal_eps<N: Number, D: Dimension>(
-    x: &TVec<N, D>,
-    y: &TVec<N, D>,
-    epsilon: N,
-) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn not_equal_eps<T: Number, const D: usize>(
+    x: &TVec<T, D>,
+    y: &TVec<T, D>,
+    epsilon: T,
+) -> TVec<bool, D> {
     x.zip_map(y, |x, y| abs_diff_ne!(x, y, epsilon = epsilon))
 }
 
@@ -64,13 +53,10 @@ where
 /// * [`equal_eps`](fn.equal_eps.html)
 /// * [`equal_eps_vec`](fn.equal_eps_vec.html)
 /// * [`not_equal_eps`](fn.not_equal_eps.html)
-pub fn not_equal_eps_vec<N: Number, D: Dimension>(
-    x: &TVec<N, D>,
-    y: &TVec<N, D>,
-    epsilon: &TVec<N, D>,
-) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn not_equal_eps_vec<T: Number, const D: usize>(
+    x: &TVec<T, D>,
+    y: &TVec<T, D>,
+    epsilon: &TVec<T, D>,
+) -> TVec<bool, D> {
     x.zip_zip_map(y, epsilon, |x, y, eps| abs_diff_ne!(x, y, epsilon = eps))
 }

nalgebra-glm/src/geometric.rs

@@ -1,10 +1,10 @@
-use na::{DefaultAllocator, RealField};
+use na::RealField;
 
 use crate::aliases::{TVec, TVec3};
-use crate::traits::{Alloc, Dimension, Number};
+use crate::traits::Number;
 
 /// The cross product of two vectors.
-pub fn cross<N: Number>(x: &TVec3<N>, y: &TVec3<N>) -> TVec3<N> {
+pub fn cross<T: Number>(x: &TVec3<T>, y: &TVec3<T>) -> TVec3<T> {
     x.cross(y)
 }
 
@@ -13,31 +13,22 @@ pub fn cross<N: Number>(x: &TVec3<N>, y: &TVec3<N>) -> TVec3<N> {
 /// # See also:
 ///
 /// * [`distance2`](fn.distance2.html)
-pub fn distance<N: RealField, D: Dimension>(p0: &TVec<N, D>, p1: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn distance<T: RealField, const D: usize>(p0: &TVec<T, D>, p1: &TVec<T, D>) -> T {
     (p1 - p0).norm()
 }
 
 /// The dot product of two vectors.
-pub fn dot<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn dot<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
     x.dot(y)
 }
 
 /// If `dot(nref, i) < 0.0`, return `n`, otherwise, return `-n`.
-pub fn faceforward<N: Number, D: Dimension>(
-    n: &TVec<N, D>,
-    i: &TVec<N, D>,
-    nref: &TVec<N, D>,
-) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
-    if nref.dot(i) < N::zero() {
+pub fn faceforward<T: Number, const D: usize>(
+    n: &TVec<T, D>,
+    i: &TVec<T, D>,
+    nref: &TVec<T, D>,
+) -> TVec<T, D> {
+    if nref.dot(i) < T::zero() {
         n.clone()
     } else {
         -n.clone()
@@ -53,10 +44,7 @@ where
 /// * [`length2`](fn.length2.html)
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude2`](fn.magnitude2.html)
-pub fn length<N: RealField, D: Dimension>(x: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn length<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm()
 }
 
@@ -69,39 +57,31 @@ where
 /// * [`length`](fn.length.html)
 /// * [`magnitude2`](fn.magnitude2.html)
 /// * [`nalgebra::norm`](../nalgebra/fn.norm.html)
-pub fn magnitude<N: RealField, D: Dimension>(x: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn magnitude<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm()
 }
 
 /// Normalizes a vector.
-pub fn normalize<N: RealField, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn normalize<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.normalize()
 }
 
 /// For the incident vector `i` and surface orientation `n`, returns the reflection direction : `result = i - 2.0 * dot(n, i) * n`.
-pub fn reflect_vec<N: Number, D: Dimension>(i: &TVec<N, D>, n: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
-    let _2 = N::one() + N::one();
+pub fn reflect_vec<T: Number, const D: usize>(i: &TVec<T, D>, n: &TVec<T, D>) -> TVec<T, D> {
+    let _2 = T::one() + T::one();
     i - n * (n.dot(i) * _2)
 }
 
 /// 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<N: RealField, D: Dimension>(i: &TVec<N, D>, n: &TVec<N, D>, eta: N) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn refract_vec<T: RealField, const D: usize>(
+    i: &TVec<T, D>,
+    n: &TVec<T, D>,
+    eta: T,
+) -> TVec<T, D> {
     let ni = n.dot(i);
-    let k = N::one() - eta * eta * (N::one() - ni * ni);
+    let k = T::one() - eta * eta * (T::one() - ni * ni);
 
-    if k < N::zero() {
+    if k < T::zero() {
         TVec::<_, D>::zeros()
     } else {
         i * eta - n * (eta * dot(n, i) + k.sqrt())

nalgebra-glm/src/gtc/bitfield.rs

@@ -1,6 +1,5 @@
-use na::{Scalar, DefaultAllocator};
+use na::{DefaultAllocator, Scalar};
 
-use crate::traits::{Alloc, Dimension};
 use crate::aliases::*;
 
 pub fn bitfieldDeinterleave(x: u16) -> U8Vec2 {
@@ -19,8 +18,11 @@ pub fn bitfieldFillOne<IU>(Value: IU, FirstBit: i32, BitCount: i32) -> IU {
     unimplemented!()
 }
 
-pub fn bitfieldFillOne2<N: Scalar, D: Dimension>(Value: &TVec<N, D>, FirstBit: i32, BitCount: i32) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn bitfieldFillOne2<T: Scalar, const D: usize>(
+    Value: &TVec<T, D>,
+    FirstBit: i32,
+    BitCount: i32,
+) -> TVec<T, D> {
     unimplemented!()
 }
 
@@ -28,8 +30,11 @@ pub fn bitfieldFillZero<IU>(Value: IU, FirstBit: i32, BitCount: i32) -> IU {
     unimplemented!()
 }
 
-pub fn bitfieldFillZero2<N: Scalar, D: Dimension>(Value: &TVec<N, D>, FirstBit: i32, BitCount: i32) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn bitfieldFillZero2<T: Scalar, const D: usize>(
+    Value: &TVec<T, D>,
+    FirstBit: i32,
+    BitCount: i32,
+) -> TVec<T, D> {
     unimplemented!()
 }
 
@@ -113,8 +118,7 @@ pub fn bitfieldRotateLeft<IU>(In: IU, Shift: i32) -> IU {
     unimplemented!()
 }
 
-pub fn bitfieldRotateLeft2<N: Scalar, D: Dimension>(In: &TVec<N, D>, Shift: i32) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn bitfieldRotateLeft2<T: Scalar, const D: usize>(In: &TVec<T, D>, Shift: i32) -> TVec<T, D> {
     unimplemented!()
 }
 
@@ -122,8 +126,7 @@ pub fn bitfieldRotateRight<IU>(In: IU, Shift: i32) -> IU {
     unimplemented!()
 }
 
-pub fn bitfieldRotateRight2<N: Scalar, D: Dimension>(In: &TVec<N, D>, Shift: i32) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn bitfieldRotateRight2<T: Scalar, const D: usize>(In: &TVec<T, D>, Shift: i32) -> TVec<T, D> {
     unimplemented!()
 }
 
@@ -131,7 +134,6 @@ pub fn mask<IU>(Bits: IU) -> IU {
     unimplemented!()
 }
 
-pub fn mask2<N: Scalar, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn mask2<T: Scalar, const D: usize>(v: &TVec<T, D>) -> TVec<T, D> {
     unimplemented!()
 }

nalgebra-glm/src/gtc/constants.rs

@@ -3,13 +3,13 @@ use na::{self, RealField};
 /// The Euler constant.
 ///
 /// This is a shorthand alias for [`euler`](fn.euler.html).
-pub fn e<N: RealField>() -> N {
-    N::e()
+pub fn e<T: RealField>() -> T {
+    T::e()
 }
 
 /// The Euler constant.
-pub fn euler<N: RealField>() -> N {
-    N::e()
+pub fn euler<T: RealField>() -> T {
+    T::e()
 }
 
 /// Returns `4 / pi`.
@@ -28,13 +28,13 @@ pub fn euler<N: RealField>() -> N {
 /// * [`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<N: RealField>() -> N {
-    na::convert::<_, N>(4.0) / N::pi()
+pub fn four_over_pi<T: RealField>() -> T {
+    na::convert::<_, T>(4.0) / T::pi()
 }
 
 /// Returns the golden ratio.
-pub fn golden_ratio<N: RealField>() -> N {
-    (N::one() + root_five()) / na::convert(2.0)
+pub fn golden_ratio<T: RealField>() -> T {
+    (T::one() + root_five()) / na::convert(2.0)
 }
 
 /// Returns `pi / 2`.
@@ -53,8 +53,8 @@ pub fn golden_ratio<N: RealField>() -> N {
 /// * [`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<N: RealField>() -> N {
-    N::frac_pi_2()
+pub fn half_pi<T: RealField>() -> T {
+    T::frac_pi_2()
 }
 
 /// Returns `ln(ln(2))`.
@@ -63,8 +63,8 @@ pub fn half_pi<N: RealField>() -> N {
 ///
 /// * [`ln_ten`](fn.ln_ten.html)
 /// * [`ln_two`](fn.ln_two.html)
-pub fn ln_ln_two<N: RealField>() -> N {
-    N::ln_2().ln()
+pub fn ln_ln_two<T: RealField>() -> T {
+    T::ln_2().ln()
 }
 
 /// Returns `ln(10)`.
@@ -73,8 +73,8 @@ pub fn ln_ln_two<N: RealField>() -> N {
 ///
 /// * [`ln_ln_two`](fn.ln_ln_two.html)
 /// * [`ln_two`](fn.ln_two.html)
-pub fn ln_ten<N: RealField>() -> N {
-    N::ln_10()
+pub fn ln_ten<T: RealField>() -> T {
+    T::ln_10()
 }
 
 /// Returns `ln(2)`.
@@ -83,8 +83,8 @@ pub fn ln_ten<N: RealField>() -> N {
 ///
 /// * [`ln_ln_two`](fn.ln_ln_two.html)
 /// * [`ln_ten`](fn.ln_ten.html)
-pub fn ln_two<N: RealField>() -> N {
-    N::ln_2()
+pub fn ln_two<T: RealField>() -> T {
+    T::ln_2()
 }
 
 /// Returns `1`.
@@ -106,13 +106,13 @@ 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<N: RealField>() -> N {
-    N::frac_1_pi()
+pub fn one_over_pi<T: RealField>() -> T {
+    T::frac_1_pi()
 }
 
 /// Returns `1 / sqrt(2)`.
-pub fn one_over_root_two<N: RealField>() -> N {
-    N::one() / root_two()
+pub fn one_over_root_two<T: RealField>() -> T {
+    T::one() / root_two()
 }
 
 /// Returns `1 / (2pi)`.
@@ -131,8 +131,8 @@ pub fn one_over_root_two<N: RealField>() -> N {
 /// * [`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<N: RealField>() -> N {
-    N::frac_1_pi() * na::convert(0.5)
+pub fn one_over_two_pi<T: RealField>() -> T {
+    T::frac_1_pi() * na::convert(0.5)
 }
 
 /// Returns `pi / 4`.
@@ -151,8 +151,8 @@ pub fn one_over_two_pi<N: RealField>() -> N {
 /// * [`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<N: RealField>() -> N {
-    N::frac_pi_4()
+pub fn quarter_pi<T: RealField>() -> T {
+    T::frac_pi_4()
 }
 
 /// Returns `sqrt(5)`.
@@ -161,8 +161,8 @@ pub fn quarter_pi<N: RealField>() -> N {
 ///
 /// * [`root_three`](fn.root_three.html)
 /// * [`root_two`](fn.root_two.html)
-pub fn root_five<N: RealField>() -> N {
-    na::convert::<_, N>(5.0).sqrt()
+pub fn root_five<T: RealField>() -> T {
+    na::convert::<_, T>(5.0).sqrt()
 }
 
 /// Returns `sqrt(pi / 2)`.
@@ -181,13 +181,13 @@ pub fn root_five<N: RealField>() -> N {
 /// * [`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<N: RealField>() -> N {
-    (N::pi() / na::convert(2.0)).sqrt()
+pub fn root_half_pi<T: RealField>() -> T {
+    (T::pi() / na::convert(2.0)).sqrt()
 }
 
 /// Returns `sqrt(ln(4))`.
-pub fn root_ln_four<N: RealField>() -> N {
-    na::convert::<_, N>(4.0).ln().sqrt()
+pub fn root_ln_four<T: RealField>() -> T {
+    na::convert::<_, T>(4.0).ln().sqrt()
 }
 
 /// Returns the square root of pi.
@@ -206,8 +206,8 @@ pub fn root_ln_four<N: RealField>() -> N {
 /// * [`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<N: RealField>() -> N {
-    N::pi().sqrt()
+pub fn root_pi<T: RealField>() -> T {
+    T::pi().sqrt()
 }
 
 /// Returns the square root of 3.
@@ -216,8 +216,8 @@ pub fn root_pi<N: RealField>() -> N {
 ///
 /// * [`root_five`](fn.root_five.html)
 /// * [`root_two`](fn.root_two.html)
-pub fn root_three<N: RealField>() -> N {
-    na::convert::<_, N>(3.0).sqrt()
+pub fn root_three<T: RealField>() -> T {
+    na::convert::<_, T>(3.0).sqrt()
 }
 
 /// Returns the square root of 2.
@@ -226,9 +226,9 @@ pub fn root_three<N: RealField>() -> N {
 ///
 /// * [`root_five`](fn.root_five.html)
 /// * [`root_three`](fn.root_three.html)
-pub fn root_two<N: RealField>() -> N {
+pub fn root_two<T: RealField>() -> T {
     // TODO: there should be a crate::sqrt_2() on the RealField trait.
-    na::convert::<_, N>(2.0).sqrt()
+    na::convert::<_, T>(2.0).sqrt()
 }
 
 /// Returns the square root of 2pi.
@@ -247,8 +247,8 @@ pub fn root_two<N: RealField>() -> N {
 /// * [`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<N: RealField>() -> N {
-    N::two_pi().sqrt()
+pub fn root_two_pi<T: RealField>() -> T {
+    T::two_pi().sqrt()
 }
 
 /// Returns `1 / 3`.
@@ -256,7 +256,7 @@ pub fn root_two_pi<N: RealField>() -> N {
 /// # See also:
 ///
 /// * [`two_thirds`](fn.two_thirds.html)
-pub fn third<N: RealField>() -> N {
+pub fn third<T: RealField>() -> T {
     na::convert(1.0 / 3.0)
 }
 
@@ -276,8 +276,8 @@ pub fn third<N: RealField>() -> N {
 /// * [`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<N: RealField>() -> N {
-    na::convert::<_, N>(3.0) / N::two_pi()
+pub fn three_over_two_pi<T: RealField>() -> T {
+    na::convert::<_, T>(3.0) / T::two_pi()
 }
 
 /// Returns `2 / pi`.
@@ -295,8 +295,8 @@ pub fn three_over_two_pi<N: RealField>() -> N {
 /// * [`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<N: RealField>() -> N {
-    N::frac_2_pi()
+pub fn two_over_pi<T: RealField>() -> T {
+    T::frac_2_pi()
 }
 
 /// Returns `2 / sqrt(pi)`.
@@ -315,8 +315,8 @@ pub fn two_over_pi<N: RealField>() -> N {
 /// * [`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<N: RealField>() -> N {
-    N::frac_2_sqrt_pi()
+pub fn two_over_root_pi<T: RealField>() -> T {
+    T::frac_2_sqrt_pi()
 }
 
 /// Returns `2pi`.
@@ -335,8 +335,8 @@ pub fn two_over_root_pi<N: RealField>() -> N {
 /// * [`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<N: RealField>() -> N {
-    N::two_pi()
+pub fn two_pi<T: RealField>() -> T {
+    T::two_pi()
 }
 
 /// Returns `2 / 3`.
@@ -344,7 +344,7 @@ pub fn two_pi<N: RealField>() -> N {
 /// # See also:
 ///
 /// * [`third`](fn.third.html)
-pub fn two_thirds<N: RealField>() -> N {
+pub fn two_thirds<T: RealField>() -> T {
     na::convert(2.0 / 3.0)
 }
 

nalgebra-glm/src/gtc/epsilon.rs

@@ -8,24 +8,24 @@ use crate::traits::{Alloc, Number, Dimension};
 use crate::aliases::TVec;
 
 /// Component-wise approximate equality beween two vectors.
-pub fn epsilon_equal<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>, epsilon: N) -> TVec<bool, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn epsilon_equal<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, epsilon: T) -> TVec<bool, D>
+    where DefaultAllocator: Alloc<T, D> {
     x.zip_map(y, |x, y| abs_diff_eq!(x, y, epsilon = epsilon))
 }
 
 /// Component-wise approximate equality beween two scalars.
-pub fn epsilon_equal2<N: AbsDiffEq<Epsilon = N>>(x: N, y: N, epsilon: N) -> bool {
+pub fn epsilon_equal2<T: AbsDiffEq<Epsilon = T>>(x: T, y: T, epsilon: T) -> bool {
     abs_diff_eq!(x, y, epsilon = epsilon)
 }
 
 /// Component-wise approximate non-equality beween two vectors.
-pub fn epsilon_not_equal<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>, epsilon: N) -> TVec<bool, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn epsilon_not_equal<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, epsilon: T) -> TVec<bool, D>
+    where DefaultAllocator: Alloc<T, D> {
     x.zip_map(y, |x, y| abs_diff_ne!(x, y, epsilon = epsilon))
 }
 
 /// Component-wise approximate non-equality beween two scalars.
-pub fn epsilon_not_equal2<N: AbsDiffEq<Epsilon = N>>(x: N, y: N, epsilon: N) -> bool {
+pub fn epsilon_not_equal2<T: AbsDiffEq<Epsilon = T>>(x: T, y: T, epsilon: T) -> bool {
     abs_diff_ne!(x, y, epsilon = epsilon)
 }
 */

nalgebra-glm/src/gtc/integer.rs

@@ -1,10 +1,9 @@
-//use na::{Scalar, DefaultAllocator};
+//use na::Scalar;
+//
 //
-//use crate::traits::{Alloc, Dimension};
 //use crate::aliases::TVec;
 
-//pub fn iround<N: Scalar, D: Dimension>(x: &TVec<N, D>) -> TVec<i32, D>
-//    where DefaultAllocator: Alloc<N, D> {
+//pub fn iround<T: Scalar, const D: usize>(x: &TVec<T, D>) -> TVec<i32, D> {
 //    x.map(|x| x.round())
 //}
 //
@@ -12,7 +11,6 @@
 //    unimplemented!()
 //}
 //
-//pub fn uround<N: Scalar, D: Dimension>(x: &TVec<N, D>) -> TVec<u32, D>
-//    where DefaultAllocator: Alloc<N, D> {
+//pub fn uround<T: Scalar, const D: usize>(x: &TVec<T, D>) -> TVec<u32, D>  {
 //    unimplemented!()
 //}

nalgebra-glm/src/gtc/matrix_access.rs

@@ -1,7 +1,6 @@
-use na::{DefaultAllocator, Scalar};
+use na::Scalar;
 
 use crate::aliases::{TMat, TVec};
-use crate::traits::{Alloc, Dimension};
 
 /// The `index`-th column of the matrix `m`.
 ///
@@ -10,10 +9,10 @@ use crate::traits::{Alloc, Dimension};
 /// * [`row`](fn.row.html)
 /// * [`set_column`](fn.set_column.html)
 /// * [`set_row`](fn.set_row.html)
-pub fn column<N: Scalar, R: Dimension, C: Dimension>(m: &TMat<N, R, C>, index: usize) -> TVec<N, R>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn column<T: Scalar, const R: usize, const C: usize>(
+    m: &TMat<T, R, C>,
+    index: usize,
+) -> TVec<T, R> {
     m.column(index).into_owned()
 }
 
@@ -24,14 +23,11 @@ where
 /// * [`column`](fn.column.html)
 /// * [`row`](fn.row.html)
 /// * [`set_row`](fn.set_row.html)
-pub fn set_column<N: Scalar, R: Dimension, C: Dimension>(
-    m: &TMat<N, R, C>,
+pub fn set_column<T: Scalar, const R: usize, const C: usize>(
+    m: &TMat<T, R, C>,
     index: usize,
-    x: &TVec<N, R>,
-) -> TMat<N, R, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+    x: &TVec<T, R>,
+) -> TMat<T, R, C> {
     let mut res = m.clone();
     res.set_column(index, x);
     res
@@ -44,10 +40,10 @@ where
 /// * [`column`](fn.column.html)
 /// * [`set_column`](fn.set_column.html)
 /// * [`set_row`](fn.set_row.html)
-pub fn row<N: Scalar, R: Dimension, C: Dimension>(m: &TMat<N, R, C>, index: usize) -> TVec<N, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn row<T: Scalar, const R: usize, const C: usize>(
+    m: &TMat<T, R, C>,
+    index: usize,
+) -> TVec<T, C> {
     m.row(index).into_owned().transpose()
 }
 
@@ -58,14 +54,11 @@ where
 /// * [`column`](fn.column.html)
 /// * [`row`](fn.row.html)
 /// * [`set_column`](fn.set_column.html)
-pub fn set_row<N: Scalar, R: Dimension, C: Dimension>(
-    m: &TMat<N, R, C>,
+pub fn set_row<T: Scalar, const R: usize, const C: usize>(
+    m: &TMat<T, R, C>,
     index: usize,
-    x: &TVec<N, C>,
-) -> TMat<N, R, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+    x: &TVec<T, C>,
+) -> TMat<T, R, C> {
     let mut res = m.clone();
     res.set_row(index, &x.transpose());
     res

nalgebra-glm/src/gtc/matrix_inverse.rs

@@ -1,22 +1,15 @@
-use na::{DefaultAllocator, RealField};
+use na::RealField;
 
 use crate::aliases::TMat;
-use crate::traits::{Alloc, Dimension};
 
 /// Fast matrix inverse for affine matrix.
-pub fn affine_inverse<N: RealField, D: Dimension>(m: TMat<N, D, D>) -> TMat<N, D, D>
-where
-    DefaultAllocator: Alloc<N, D, D>,
-{
+pub fn affine_inverse<T: RealField, 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<N: RealField, D: Dimension>(m: TMat<N, D, D>) -> TMat<N, D, D>
-where
-    DefaultAllocator: Alloc<N, D, D>,
-{
+pub fn inverse_transpose<T: RealField, 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

@@ -1,9 +1,7 @@
-use na::{Scalar, RealField, DefaultAllocator, U3, U4};
+use na::{DefaultAllocator, RealField, Scalar, U3, U4};
 
-use crate::traits::{Alloc, Dimension};
 use crate::aliases::*;
 
-
 pub fn packF2x11_1x10(v: &Vec3) -> i32 {
     unimplemented!()
 }
@@ -12,8 +10,10 @@ pub fn packF3x9_E1x5(v: &Vec3) -> i32 {
     unimplemented!()
 }
 
-pub fn packHalf<D: Dimension>(v: &TVec<f32, D>) -> TVec<u16, D>
-    where DefaultAllocator: Alloc<u16, D> {
+pub fn packHalf<const D: usize>(v: &TVec<f32, D>) -> TVec<u16, D>
+where
+    DefaultAllocator: Alloc<u16, D>,
+{
     unimplemented!()
 }
 
@@ -49,12 +49,14 @@ pub fn packInt4x8(v: &I8Vec4) -> i32 {
     unimplemented!()
 }
 
-pub fn packRGBM<N: Scalar>(rgb: &TVec3<N>) -> TVec4<N> {
+pub fn packRGBM<T: Scalar>(rgb: &TVec3<T>) -> TVec4<T> {
     unimplemented!()
 }
 
-pub fn packSnorm<I: Scalar, N: RealField, D: Dimension>(v: TVec<N, D>) -> TVec<I, D>
-    where DefaultAllocator: Alloc<N, D> + Alloc<I, D> {
+pub fn packSnorm<I: Scalar, T: RealField, const D: usize>(v: TVec<T, D>) -> TVec<I, D>
+where
+    DefaultAllocator: Alloc<T, D> + Alloc<I, D>,
+{
     unimplemented!()
 }
 
@@ -102,8 +104,10 @@ pub fn packUint4x8(v: &U8Vec4) -> i32 {
     unimplemented!()
 }
 
-pub fn packUnorm<UI: Scalar, N: RealField, D: Dimension>(v: &TVec<N, D>) -> TVec<UI, D>
-    where DefaultAllocator: Alloc<N, D> + Alloc<UI, D> {
+pub fn packUnorm<UI: Scalar, T: RealField, const D: usize>(v: &TVec<T, D>) -> TVec<UI, D>
+where
+    DefaultAllocator: Alloc<T, D> + Alloc<UI, D>,
+{
     unimplemented!()
 }
 
@@ -155,8 +159,7 @@ pub fn unpackF3x9_E1x5(p: i32) -> Vec3 {
     unimplemented!()
 }
 
-pub fn unpackHalf<N: Scalar, D: Dimension>(p: TVec<i16, D>) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn unpackHalf<T: Scalar, const D: usize>(p: TVec<i16, D>) -> TVec<T, D> {
     unimplemented!()
 }
 
@@ -192,12 +195,14 @@ pub fn unpackInt4x8(p: i32) -> I8Vec4 {
     unimplemented!()
 }
 
-pub fn unpackRGBM<N: Scalar>(rgbm: &TVec4<N>) -> TVec3<N> {
+pub fn unpackRGBM<T: Scalar>(rgbm: &TVec4<T>) -> TVec3<T> {
     unimplemented!()
 }
 
-pub fn unpackSnorm<I: Scalar, N: RealField, D: Dimension>(v: &TVec<I, D>) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> + Alloc<I, D> {
+pub fn unpackSnorm<I: Scalar, T: RealField, const D: usize>(v: &TVec<I, D>) -> TVec<T, D>
+where
+    DefaultAllocator: Alloc<T, D> + Alloc<I, D>,
+{
     unimplemented!()
 }
 
@@ -245,8 +250,10 @@ pub fn unpackUint4x8(p: i32) -> U8Vec4 {
     unimplemented!()
 }
 
-pub fn unpackUnorm<UI: Scalar, N: RealField, D: Dimension>(v: &TVec<UI, D>) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> + Alloc<UI, D> {
+pub fn unpackUnorm<UI: Scalar, T: RealField, const D: usize>(v: &TVec<UI, D>) -> TVec<T, D>
+where
+    DefaultAllocator: Alloc<T, D> + Alloc<UI, D>,
+{
     unimplemented!()
 }
 

nalgebra-glm/src/gtc/quaternion.rs

@@ -1,36 +1,36 @@
-use na::{RealField, UnitQuaternion, U4};
+use na::{RealField, UnitQuaternion};
 
 use crate::aliases::{Qua, TMat4, TVec, TVec3};
 
 /// Euler angles of the quaternion `q` as (pitch, yaw, roll).
-pub fn quat_euler_angles<N: RealField>(x: &Qua<N>) -> TVec3<N> {
+pub fn quat_euler_angles<T: RealField>(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<N: RealField>(x: &Qua<N>, y: &Qua<N>) -> TVec<bool, U4> {
+pub fn quat_greater_than<T: RealField>(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<N: RealField>(x: &Qua<N>, y: &Qua<N>) -> TVec<bool, U4> {
+pub fn quat_greater_than_equal<T: RealField>(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<N: RealField>(x: &Qua<N>, y: &Qua<N>) -> TVec<bool, U4> {
+pub fn quat_less_than<T: RealField>(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<N: RealField>(x: &Qua<N>, y: &Qua<N>) -> TVec<bool, U4> {
+pub fn quat_less_than_equal<T: RealField>(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<N: RealField>(x: &Qua<N>) -> TMat4<N> {
+pub fn quat_cast<T: RealField>(x: &Qua<T>) -> TMat4<T> {
     crate::quat_to_mat4(x)
 }
 
@@ -41,34 +41,34 @@ pub fn quat_cast<N: RealField>(x: &Qua<N>) -> TMat4<N> {
 /// * `direction` - Direction vector point at where to look
 /// * `up` - Object up vector
 ///
-pub fn quat_look_at<N: RealField>(direction: &TVec3<N>, up: &TVec3<N>) -> Qua<N> {
+pub fn quat_look_at<T: RealField>(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<N: RealField>(direction: &TVec3<N>, up: &TVec3<N>) -> Qua<N> {
+pub fn quat_look_at_lh<T: RealField>(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<N: RealField>(direction: &TVec3<N>, up: &TVec3<N>) -> Qua<N> {
+pub fn quat_look_at_rh<T: RealField>(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<N: RealField>(x: &Qua<N>) -> N {
+pub fn quat_roll<T: RealField>(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<N: RealField>(x: &Qua<N>) -> N {
+pub fn quat_yaw<T: RealField>(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<N: RealField>(x: &Qua<N>) -> N {
+pub fn quat_pitch<T: RealField>(x: &Qua<T>) -> T {
     // TODO: optimize this.
     quat_euler_angles(x).x
 }

nalgebra-glm/src/gtc/round.rs

@@ -1,15 +1,16 @@
-use na::{Scalar, RealField, U3, DefaultAllocator};
+use na::{DefaultAllocator, RealField, Scalar, U3};
 
-use crate::traits::{Number, Alloc, Dimension};
 use crate::aliases::TVec;
-
+use crate::traits::{Alloc, Dimension, Number};
 
 pub fn ceilMultiple<T>(v: T, Multiple: T) -> T {
     unimplemented!()
 }
 
-pub fn ceilMultiple2<N: Scalar, D: Dimension>(v: &TVec<N, D>, Multiple: &TVec<N, D>) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn ceilMultiple2<T: Scalar, const D: usize>(v: &TVec<T, D>, Multiple: &TVec<T, D>) -> TVec<T, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
@@ -17,8 +18,10 @@ pub fn ceilPowerOfTwo<IU>(v: IU) -> IU {
     unimplemented!()
 }
 
-pub fn ceilPowerOfTwo2<N: Scalar, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn ceilPowerOfTwo2<T: Scalar, const D: usize>(v: &TVec<T, D>) -> TVec<T, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
@@ -26,8 +29,13 @@ pub fn floorMultiple<T>(v: T, Multiple: T) -> T {
     unimplemented!()
 }
 
-pub fn floorMultiple2<N: Scalar, D: Dimension>(v: &TVec<N, D>, Multiple: &TVec<N, D>) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn floorMultiple2<T: Scalar, const D: usize>(
+    v: &TVec<T, D>,
+    Multiple: &TVec<T, D>,
+) -> TVec<T, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
@@ -35,8 +43,10 @@ pub fn floorPowerOfTwo<IU>(v: IU) -> IU {
     unimplemented!()
 }
 
-pub fn floorPowerOfTwo2<N: Scalar, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn floorPowerOfTwo2<T: Scalar, const D: usize>(v: &TVec<T, D>) -> TVec<T, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
@@ -44,13 +54,20 @@ pub fn isMultiple<IU>(v: IU, Multiple: IU) -> bool {
     unimplemented!()
 }
 
-pub fn isMultiple2<N: Scalar, D: Dimension>(v: &TVec<N, D>,Multiple: N) -> TVec<bool, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn isMultiple2<T: Scalar, const D: usize>(v: &TVec<T, D>, Multiple: T) -> TVec<bool, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
-pub fn isMultiple3<N: Scalar, D: Dimension>(v: &TVec<N, D>, Multiple: &TVec<N, D>) -> TVec<bool, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn isMultiple3<T: Scalar, const D: usize>(
+    v: &TVec<T, D>,
+    Multiple: &TVec<T, D>,
+) -> TVec<bool, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
@@ -58,8 +75,10 @@ pub fn isPowerOfTwo2<IU>(v: IU) -> bool {
     unimplemented!()
 }
 
-pub fn isPowerOfTwo<N: Scalar, D: Dimension>(v: &TVec<N, D>) -> TVec<bool, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn isPowerOfTwo<T: Scalar, const D: usize>(v: &TVec<T, D>) -> TVec<bool, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
@@ -67,8 +86,13 @@ pub fn roundMultiple<T>(v: T, Multiple: T) -> T {
     unimplemented!()
 }
 
-pub fn roundMultiple2<N: Scalar, D: Dimension>(v: &TVec<N, D>, Multiple: &TVec<N, D>) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn roundMultiple2<T: Scalar, const D: usize>(
+    v: &TVec<T, D>,
+    Multiple: &TVec<T, D>,
+) -> TVec<T, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
@@ -76,7 +100,9 @@ pub fn roundPowerOfTwo<IU>(v: IU) -> IU {
     unimplemented!()
 }
 
-pub fn roundPowerOfTwo2<N: Scalar, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn roundPowerOfTwo2<T: Scalar, const D: usize>(v: &TVec<T, D>) -> TVec<T, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }

nalgebra-glm/src/gtc/type_ptr.rs

@@ -1,81 +1,81 @@
-use na::{DefaultAllocator, Quaternion, RealField, Scalar};
+use na::{Quaternion, RealField, Scalar};
 
 use crate::aliases::{
     Qua, TMat, TMat2, TMat2x3, TMat2x4, TMat3, TMat3x2, TMat3x4, TMat4, TMat4x2, TMat4x3, TVec1,
     TVec2, TVec3, TVec4,
 };
-use crate::traits::{Alloc, Dimension, Number};
+use crate::traits::Number;
 
 /// Creates a 2x2 matrix from a slice arranged in column-major order.
-pub fn make_mat2<N: Scalar>(ptr: &[N]) -> TMat2<N> {
+pub fn make_mat2<T: Scalar>(ptr: &[T]) -> TMat2<T> {
     TMat2::from_column_slice(ptr)
 }
 
 /// Creates a 2x2 matrix from a slice arranged in column-major order.
-pub fn make_mat2x2<N: Scalar>(ptr: &[N]) -> TMat2<N> {
+pub fn make_mat2x2<T: Scalar>(ptr: &[T]) -> TMat2<T> {
     TMat2::from_column_slice(ptr)
 }
 
 /// Creates a 2x3 matrix from a slice arranged in column-major order.
-pub fn make_mat2x3<N: Scalar>(ptr: &[N]) -> TMat2x3<N> {
+pub fn make_mat2x3<T: Scalar>(ptr: &[T]) -> TMat2x3<T> {
     TMat2x3::from_column_slice(ptr)
 }
 
 /// Creates a 2x4 matrix from a slice arranged in column-major order.
-pub fn make_mat2x4<N: Scalar>(ptr: &[N]) -> TMat2x4<N> {
+pub fn make_mat2x4<T: Scalar>(ptr: &[T]) -> TMat2x4<T> {
     TMat2x4::from_column_slice(ptr)
 }
 
 /// Creates a 3 matrix from a slice arranged in column-major order.
-pub fn make_mat3<N: Scalar>(ptr: &[N]) -> TMat3<N> {
+pub fn make_mat3<T: Scalar>(ptr: &[T]) -> TMat3<T> {
     TMat3::from_column_slice(ptr)
 }
 
 /// Creates a 3x2 matrix from a slice arranged in column-major order.
-pub fn make_mat3x2<N: Scalar>(ptr: &[N]) -> TMat3x2<N> {
+pub fn make_mat3x2<T: Scalar>(ptr: &[T]) -> TMat3x2<T> {
     TMat3x2::from_column_slice(ptr)
 }
 
 /// Creates a 3x3 matrix from a slice arranged in column-major order.
-pub fn make_mat3x3<N: Scalar>(ptr: &[N]) -> TMat3<N> {
+pub fn make_mat3x3<T: Scalar>(ptr: &[T]) -> TMat3<T> {
     TMat3::from_column_slice(ptr)
 }
 
 /// Creates a 3x4 matrix from a slice arranged in column-major order.
-pub fn make_mat3x4<N: Scalar>(ptr: &[N]) -> TMat3x4<N> {
+pub fn make_mat3x4<T: Scalar>(ptr: &[T]) -> TMat3x4<T> {
     TMat3x4::from_column_slice(ptr)
 }
 
 /// Creates a 4x4 matrix from a slice arranged in column-major order.
-pub fn make_mat4<N: Scalar>(ptr: &[N]) -> TMat4<N> {
+pub fn make_mat4<T: Scalar>(ptr: &[T]) -> TMat4<T> {
     TMat4::from_column_slice(ptr)
 }
 
 /// Creates a 4x2 matrix from a slice arranged in column-major order.
-pub fn make_mat4x2<N: Scalar>(ptr: &[N]) -> TMat4x2<N> {
+pub fn make_mat4x2<T: Scalar>(ptr: &[T]) -> TMat4x2<T> {
     TMat4x2::from_column_slice(ptr)
 }
 
 /// Creates a 4x3 matrix from a slice arranged in column-major order.
-pub fn make_mat4x3<N: Scalar>(ptr: &[N]) -> TMat4x3<N> {
+pub fn make_mat4x3<T: Scalar>(ptr: &[T]) -> TMat4x3<T> {
     TMat4x3::from_column_slice(ptr)
 }
 
 /// Creates a 4x4 matrix from a slice arranged in column-major order.
-pub fn make_mat4x4<N: Scalar>(ptr: &[N]) -> TMat4<N> {
+pub fn make_mat4x4<T: Scalar>(ptr: &[T]) -> TMat4<T> {
     TMat4::from_column_slice(ptr)
 }
 
 /// Converts a 2x2 matrix to a 3x3 matrix.
-pub fn mat2_to_mat3<N: Number>(m: &TMat2<N>) -> TMat3<N> {
-    let _0 = N::zero();
-    let _1 = N::one();
+pub fn mat2_to_mat3<T: Number>(m: &TMat2<T>) -> TMat3<T> {
+    let _0 = T::zero();
+    let _1 = T::one();
 
     TMat3::new(m.m11, m.m12, _0, m.m21, m.m22, _0, _0, _0, _1)
 }
 
 /// Converts a 3x3 matrix to a 2x2 matrix.
-pub fn mat3_to_mat2<N: Scalar>(m: &TMat3<N>) -> TMat2<N> {
+pub fn mat3_to_mat2<T: Scalar>(m: &TMat3<T>) -> TMat2<T> {
     TMat2::new(
         m.m11.inlined_clone(),
         m.m12.inlined_clone(),
@@ -85,9 +85,9 @@ pub fn mat3_to_mat2<N: Scalar>(m: &TMat3<N>) -> TMat2<N> {
 }
 
 /// Converts a 3x3 matrix to a 4x4 matrix.
-pub fn mat3_to_mat4<N: Number>(m: &TMat3<N>) -> TMat4<N> {
-    let _0 = N::zero();
-    let _1 = N::one();
+pub fn mat3_to_mat4<T: Number>(m: &TMat3<T>) -> TMat4<T> {
+    let _0 = T::zero();
+    let _1 = T::one();
 
     TMat4::new(
         m.m11, m.m12, m.m13, _0, m.m21, m.m22, m.m23, _0, m.m31, m.m32, m.m33, _0, _0, _0, _0, _1,
@@ -95,7 +95,7 @@ pub fn mat3_to_mat4<N: Number>(m: &TMat3<N>) -> TMat4<N> {
 }
 
 /// Converts a 4x4 matrix to a 3x3 matrix.
-pub fn mat4_to_mat3<N: Scalar>(m: &TMat4<N>) -> TMat3<N> {
+pub fn mat4_to_mat3<T: Scalar>(m: &TMat4<T>) -> TMat3<T> {
     TMat3::new(
         m.m11.inlined_clone(),
         m.m12.inlined_clone(),
@@ -110,9 +110,9 @@ pub fn mat4_to_mat3<N: Scalar>(m: &TMat4<N>) -> TMat3<N> {
 }
 
 /// Converts a 2x2 matrix to a 4x4 matrix.
-pub fn mat2_to_mat4<N: Number>(m: &TMat2<N>) -> TMat4<N> {
-    let _0 = N::zero();
-    let _1 = N::one();
+pub fn mat2_to_mat4<T: Number>(m: &TMat2<T>) -> TMat4<T> {
+    let _0 = T::zero();
+    let _1 = T::one();
 
     TMat4::new(
         m.m11, m.m12, _0, _0, m.m21, m.m22, _0, _0, _0, _0, _1, _0, _0, _0, _0, _1,
@@ -120,7 +120,7 @@ pub fn mat2_to_mat4<N: Number>(m: &TMat2<N>) -> TMat4<N> {
 }
 
 /// Converts a 4x4 matrix to a 2x2 matrix.
-pub fn mat4_to_mat2<N: Scalar>(m: &TMat4<N>) -> TMat2<N> {
+pub fn mat4_to_mat2<T: Scalar>(m: &TMat4<T>) -> TMat2<T> {
     TMat2::new(
         m.m11.inlined_clone(),
         m.m12.inlined_clone(),
@@ -130,7 +130,7 @@ pub fn mat4_to_mat2<N: Scalar>(m: &TMat4<N>) -> TMat2<N> {
 }
 
 /// Creates a quaternion from a slice arranged as `[x, y, z, w]`.
-pub fn make_quat<N: RealField>(ptr: &[N]) -> Qua<N> {
+pub fn make_quat<T: RealField>(ptr: &[T]) -> Qua<T> {
     Quaternion::from(TVec4::from_column_slice(ptr))
 }
 
@@ -141,7 +141,7 @@ pub fn make_quat<N: RealField>(ptr: &[N]) -> Qua<N> {
 /// * [`make_vec2`](fn.make_vec2.html)
 /// * [`make_vec3`](fn.make_vec3.html)
 /// * [`make_vec4`](fn.make_vec4.html)
-pub fn make_vec1<N: Scalar>(v: &TVec1<N>) -> TVec1<N> {
+pub fn make_vec1<T: Scalar>(v: &TVec1<T>) -> TVec1<T> {
     v.clone()
 }
 
@@ -155,7 +155,7 @@ pub fn make_vec1<N: Scalar>(v: &TVec1<N>) -> TVec1<N> {
 /// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
 /// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
 /// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
-pub fn vec2_to_vec1<N: Scalar>(v: &TVec2<N>) -> TVec1<N> {
+pub fn vec2_to_vec1<T: Scalar>(v: &TVec2<T>) -> TVec1<T> {
     TVec1::new(v.x.inlined_clone())
 }
 
@@ -169,7 +169,7 @@ pub fn vec2_to_vec1<N: Scalar>(v: &TVec2<N>) -> TVec1<N> {
 /// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
 /// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
 /// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
-pub fn vec3_to_vec1<N: Scalar>(v: &TVec3<N>) -> TVec1<N> {
+pub fn vec3_to_vec1<T: Scalar>(v: &TVec3<T>) -> TVec1<T> {
     TVec1::new(v.x.inlined_clone())
 }
 
@@ -183,7 +183,7 @@ pub fn vec3_to_vec1<N: Scalar>(v: &TVec3<N>) -> TVec1<N> {
 /// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
 /// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
 /// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
-pub fn vec4_to_vec1<N: Scalar>(v: &TVec4<N>) -> TVec1<N> {
+pub fn vec4_to_vec1<T: Scalar>(v: &TVec4<T>) -> TVec1<T> {
     TVec1::new(v.x.inlined_clone())
 }
 
@@ -199,8 +199,8 @@ pub fn vec4_to_vec1<N: Scalar>(v: &TVec4<N>) -> TVec1<N> {
 /// * [`vec2_to_vec2`](fn.vec2_to_vec2.html)
 /// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
 /// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
-pub fn vec1_to_vec2<N: Number>(v: &TVec1<N>) -> TVec2<N> {
-    TVec2::new(v.x.inlined_clone(), N::zero())
+pub fn vec1_to_vec2<T: Number>(v: &TVec1<T>) -> TVec2<T> {
+    TVec2::new(v.x.inlined_clone(), T::zero())
 }
 
 /// Creates a 2D vector from another vector.
@@ -214,7 +214,7 @@ pub fn vec1_to_vec2<N: Number>(v: &TVec1<N>) -> TVec2<N> {
 /// * [`vec2_to_vec2`](fn.vec2_to_vec2.html)
 /// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
 /// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
-pub fn vec2_to_vec2<N: Scalar>(v: &TVec2<N>) -> TVec2<N> {
+pub fn vec2_to_vec2<T: Scalar>(v: &TVec2<T>) -> TVec2<T> {
     v.clone()
 }
 
@@ -228,7 +228,7 @@ pub fn vec2_to_vec2<N: Scalar>(v: &TVec2<N>) -> TVec2<N> {
 /// * [`vec2_to_vec2`](fn.vec2_to_vec2.html)
 /// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
 /// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
-pub fn vec3_to_vec2<N: Scalar>(v: &TVec3<N>) -> TVec2<N> {
+pub fn vec3_to_vec2<T: Scalar>(v: &TVec3<T>) -> TVec2<T> {
     TVec2::new(v.x.inlined_clone(), v.y.inlined_clone())
 }
 
@@ -242,7 +242,7 @@ pub fn vec3_to_vec2<N: Scalar>(v: &TVec3<N>) -> TVec2<N> {
 /// * [`vec2_to_vec2`](fn.vec2_to_vec2.html)
 /// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
 /// * [`vec2_to_vec4`](fn.vec2_to_vec4.html)
-pub fn vec4_to_vec2<N: Scalar>(v: &TVec4<N>) -> TVec2<N> {
+pub fn vec4_to_vec2<T: Scalar>(v: &TVec4<T>) -> TVec2<T> {
     TVec2::new(v.x.inlined_clone(), v.y.inlined_clone())
 }
 
@@ -253,7 +253,7 @@ pub fn vec4_to_vec2<N: Scalar>(v: &TVec4<N>) -> TVec2<N> {
 /// * [`make_vec1`](fn.make_vec1.html)
 /// * [`make_vec3`](fn.make_vec3.html)
 /// * [`make_vec4`](fn.make_vec4.html)
-pub fn make_vec2<N: Scalar>(ptr: &[N]) -> TVec2<N> {
+pub fn make_vec2<T: Scalar>(ptr: &[T]) -> TVec2<T> {
     TVec2::from_column_slice(ptr)
 }
 
@@ -268,8 +268,8 @@ pub fn make_vec2<N: Scalar>(ptr: &[N]) -> TVec2<N> {
 /// * [`vec4_to_vec3`](fn.vec4_to_vec3.html)
 /// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
 /// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
-pub fn vec1_to_vec3<N: Number>(v: &TVec1<N>) -> TVec3<N> {
-    TVec3::new(v.x.inlined_clone(), N::zero(), N::zero())
+pub fn vec1_to_vec3<T: Number>(v: &TVec1<T>) -> TVec3<T> {
+    TVec3::new(v.x.inlined_clone(), T::zero(), T::zero())
 }
 
 /// Creates a 3D vector from another vector.
@@ -284,8 +284,8 @@ pub fn vec1_to_vec3<N: Number>(v: &TVec1<N>) -> TVec3<N> {
 /// * [`vec3_to_vec1`](fn.vec3_to_vec1.html)
 /// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
 /// * [`vec3_to_vec4`](fn.vec3_to_vec4.html)
-pub fn vec2_to_vec3<N: Number>(v: &TVec2<N>) -> TVec3<N> {
-    TVec3::new(v.x.inlined_clone(), v.y.inlined_clone(), N::zero())
+pub fn vec2_to_vec3<T: Number>(v: &TVec2<T>) -> TVec3<T> {
+    TVec3::new(v.x.inlined_clone(), v.y.inlined_clone(), T::zero())
 }
 
 /// Creates a 3D vector from another vector.
@@ -298,7 +298,7 @@ pub fn vec2_to_vec3<N: Number>(v: &TVec2<N>) -> TVec3<N> {
 /// * [`vec3_to_vec1`](fn.vec3_to_vec1.html)
 /// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
 /// * [`vec3_to_vec4`](fn.vec3_to_vec4.html)
-pub fn vec3_to_vec3<N: Scalar>(v: &TVec3<N>) -> TVec3<N> {
+pub fn vec3_to_vec3<T: Scalar>(v: &TVec3<T>) -> TVec3<T> {
     v.clone()
 }
 
@@ -312,7 +312,7 @@ pub fn vec3_to_vec3<N: Scalar>(v: &TVec3<N>) -> TVec3<N> {
 /// * [`vec3_to_vec1`](fn.vec3_to_vec1.html)
 /// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
 /// * [`vec3_to_vec4`](fn.vec3_to_vec4.html)
-pub fn vec4_to_vec3<N: Scalar>(v: &TVec4<N>) -> TVec3<N> {
+pub fn vec4_to_vec3<T: Scalar>(v: &TVec4<T>) -> TVec3<T> {
     TVec3::new(
         v.x.inlined_clone(),
         v.y.inlined_clone(),
@@ -327,7 +327,7 @@ pub fn vec4_to_vec3<N: Scalar>(v: &TVec4<N>) -> TVec3<N> {
 /// * [`make_vec1`](fn.make_vec1.html)
 /// * [`make_vec2`](fn.make_vec2.html)
 /// * [`make_vec4`](fn.make_vec4.html)
-pub fn make_vec3<N: Scalar>(ptr: &[N]) -> TVec3<N> {
+pub fn make_vec3<T: Scalar>(ptr: &[T]) -> TVec3<T> {
     TVec3::from_column_slice(ptr)
 }
 
@@ -343,8 +343,8 @@ pub fn make_vec3<N: Scalar>(ptr: &[N]) -> TVec3<N> {
 /// * [`vec1_to_vec2`](fn.vec1_to_vec2.html)
 /// * [`vec1_to_vec3`](fn.vec1_to_vec3.html)
 /// * [`vec1_to_vec4`](fn.vec1_to_vec4.html)
-pub fn vec1_to_vec4<N: Number>(v: &TVec1<N>) -> TVec4<N> {
-    TVec4::new(v.x, N::zero(), N::zero(), N::zero())
+pub fn vec1_to_vec4<T: Number>(v: &TVec1<T>) -> TVec4<T> {
+    TVec4::new(v.x, T::zero(), T::zero(), T::zero())
 }
 
 /// Creates a 4D vector from another vector.
@@ -359,8 +359,8 @@ pub fn vec1_to_vec4<N: Number>(v: &TVec1<N>) -> TVec4<N> {
 /// * [`vec2_to_vec1`](fn.vec2_to_vec1.html)
 /// * [`vec2_to_vec2`](fn.vec2_to_vec2.html)
 /// * [`vec2_to_vec3`](fn.vec2_to_vec3.html)
-pub fn vec2_to_vec4<N: Number>(v: &TVec2<N>) -> TVec4<N> {
-    TVec4::new(v.x, v.y, N::zero(), N::zero())
+pub fn vec2_to_vec4<T: Number>(v: &TVec2<T>) -> TVec4<T> {
+    TVec4::new(v.x, v.y, T::zero(), T::zero())
 }
 
 /// Creates a 4D vector from another vector.
@@ -375,8 +375,8 @@ pub fn vec2_to_vec4<N: Number>(v: &TVec2<N>) -> TVec4<N> {
 /// * [`vec3_to_vec1`](fn.vec3_to_vec1.html)
 /// * [`vec3_to_vec2`](fn.vec3_to_vec2.html)
 /// * [`vec3_to_vec3`](fn.vec3_to_vec3.html)
-pub fn vec3_to_vec4<N: Number>(v: &TVec3<N>) -> TVec4<N> {
-    TVec4::new(v.x, v.y, v.z, N::zero())
+pub fn vec3_to_vec4<T: Number>(v: &TVec3<T>) -> TVec4<T> {
+    TVec4::new(v.x, v.y, v.z, T::zero())
 }
 
 /// Creates a 4D vector from another vector.
@@ -389,7 +389,7 @@ pub fn vec3_to_vec4<N: Number>(v: &TVec3<N>) -> TVec4<N> {
 /// * [`vec4_to_vec1`](fn.vec4_to_vec1.html)
 /// * [`vec4_to_vec2`](fn.vec4_to_vec2.html)
 /// * [`vec4_to_vec3`](fn.vec4_to_vec3.html)
-pub fn vec4_to_vec4<N: Scalar>(v: &TVec4<N>) -> TVec4<N> {
+pub fn vec4_to_vec4<T: Scalar>(v: &TVec4<T>) -> TVec4<T> {
     v.clone()
 }
 
@@ -400,22 +400,16 @@ pub fn vec4_to_vec4<N: Scalar>(v: &TVec4<N>) -> TVec4<N> {
 /// * [`make_vec1`](fn.make_vec1.html)
 /// * [`make_vec2`](fn.make_vec2.html)
 /// * [`make_vec3`](fn.make_vec3.html)
-pub fn make_vec4<N: Scalar>(ptr: &[N]) -> TVec4<N> {
+pub fn make_vec4<T: Scalar>(ptr: &[T]) -> TVec4<T> {
     TVec4::from_column_slice(ptr)
 }
 
 /// Converts a matrix or vector to a slice arranged in column-major order.
-pub fn value_ptr<N: Scalar, R: Dimension, C: Dimension>(x: &TMat<N, R, C>) -> &[N]
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn value_ptr<T: Scalar, const R: usize, const C: usize>(x: &TMat<T, R, C>) -> &[T] {
     x.as_slice()
 }
 
 /// Converts a matrix or vector to a mutable slice arranged in column-major order.
-pub fn value_ptr_mut<N: Scalar, R: Dimension, C: Dimension>(x: &mut TMat<N, R, C>) -> &mut [N]
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn value_ptr_mut<T: Scalar, const R: usize, const C: usize>(x: &mut TMat<T, R, C>) -> &mut [T] {
     x.as_mut_slice()
 }

nalgebra-glm/src/gtc/ulp.rs

@@ -2,12 +2,11 @@ use na::{Scalar, U2};
 
 use crate::aliases::TVec;
 
-
 pub fn float_distance<T>(x: T, y: T) -> u64 {
     unimplemented!()
 }
 
-pub fn float_distance2<N: Scalar>(x: &TVec2<N>, y: &TVec2<N>) -> TVec<u64, U2> {
+pub fn float_distance2<T: Scalar>(x: &TVec2<T>, y: &TVec2<T>) -> TVec<u64, U2> {
     unimplemented!()
 }
 

nalgebra-glm/src/gtx/component_wise.rs

@@ -1,7 +1,5 @@
-use na::{self, DefaultAllocator};
-
 use crate::aliases::TMat;
-use crate::traits::{Alloc, Dimension, Number};
+use crate::traits::Number;
 
 /// The sum of every component of the given matrix or vector.
 ///
@@ -21,11 +19,8 @@ use crate::traits::{Alloc, Dimension, Number};
 /// * [`comp_max`](fn.comp_max.html)
 /// * [`comp_min`](fn.comp_min.html)
 /// * [`comp_mul`](fn.comp_mul.html)
-pub fn comp_add<N: Number, R: Dimension, C: Dimension>(m: &TMat<N, R, C>) -> N
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
-    m.iter().fold(N::zero(), |x, y| x + *y)
+pub fn comp_add<T: Number, const R: usize, const C: usize>(m: &TMat<T, R, C>) -> T {
+    m.iter().fold(T::zero(), |x, y| x + *y)
 }
 
 /// The maximum of every component of the given matrix or vector.
@@ -50,12 +45,9 @@ where
 /// * [`max2`](fn.max2.html)
 /// * [`max3`](fn.max3.html)
 /// * [`max4`](fn.max4.html)
-pub fn comp_max<N: Number, R: Dimension, C: Dimension>(m: &TMat<N, R, C>) -> N
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn comp_max<T: Number, const R: usize, const C: usize>(m: &TMat<T, R, C>) -> T {
     m.iter()
-        .fold(N::min_value(), |x, y| crate::max2_scalar(x, *y))
+        .fold(T::min_value(), |x, y| crate::max2_scalar(x, *y))
 }
 
 /// The minimum of every component of the given matrix or vector.
@@ -80,12 +72,9 @@ where
 /// * [`min2`](fn.min2.html)
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
-pub fn comp_min<N: Number, R: Dimension, C: Dimension>(m: &TMat<N, R, C>) -> N
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn comp_min<T: Number, const R: usize, const C: usize>(m: &TMat<T, R, C>) -> T {
     m.iter()
-        .fold(N::max_value(), |x, y| crate::min2_scalar(x, *y))
+        .fold(T::max_value(), |x, y| crate::min2_scalar(x, *y))
 }
 
 /// The product of every component of the given matrix or vector.
@@ -106,11 +95,8 @@ where
 /// * [`comp_add`](fn.comp_add.html)
 /// * [`comp_max`](fn.comp_max.html)
 /// * [`comp_min`](fn.comp_min.html)
-pub fn comp_mul<N: Number, R: Dimension, C: Dimension>(m: &TMat<N, R, C>) -> N
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
-    m.iter().fold(N::one(), |x, y| x * *y)
+pub fn comp_mul<T: Number, const R: usize, const C: usize>(m: &TMat<T, R, C>) -> T {
+    m.iter().fold(T::one(), |x, y| x * *y)
 }
 
 //pub fn vec< L, floatType, Q > compNormalize (vec< L, T, Q > const &v)

nalgebra-glm/src/gtx/euler_angles.rs

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

nalgebra-glm/src/gtx/exterior_product.rs

@@ -2,6 +2,6 @@ use crate::aliases::TVec2;
 use crate::traits::Number;
 
 /// The 2D perpendicular product between two vectors.
-pub fn cross2d<N: Number>(v: &TVec2<N>, u: &TVec2<N>) -> N {
+pub fn cross2d<T: Number>(v: &TVec2<T>, u: &TVec2<T>) -> T {
     v.perp(u)
 }

nalgebra-glm/src/gtx/handed_coordinate_space.rs

@@ -6,8 +6,8 @@ use crate::traits::Number;
 /// # See also:
 ///
 /// * [`right_handed`](fn.right_handed.html)
-pub fn left_handed<N: Number>(a: &TVec3<N>, b: &TVec3<N>, c: &TVec3<N>) -> bool {
-    a.cross(b).dot(c) < N::zero()
+pub fn left_handed<T: Number>(a: &TVec3<T>, b: &TVec3<T>, c: &TVec3<T>) -> bool {
+    a.cross(b).dot(c) < T::zero()
 }
 
 /// Returns `true` if `{a, b, c}` forms a right-handed trihedron.
@@ -15,6 +15,6 @@ pub fn left_handed<N: Number>(a: &TVec3<N>, b: &TVec3<N>, c: &TVec3<N>) -> bool
 /// # See also:
 ///
 /// * [`left_handed`](fn.left_handed.html)
-pub fn right_handed<N: Number>(a: &TVec3<N>, b: &TVec3<N>, c: &TVec3<N>) -> bool {
-    a.cross(b).dot(c) > N::zero()
+pub fn right_handed<T: Number>(a: &TVec3<T>, b: &TVec3<T>, c: &TVec3<T>) -> bool {
+    a.cross(b).dot(c) > T::zero()
 }

nalgebra-glm/src/gtx/matrix_cross_product.rs

@@ -7,7 +7,7 @@ use crate::aliases::{TMat3, TMat4, TVec3};
 /// # See also:
 ///
 /// * [`matrix_cross`](fn.matrix_cross.html)
-pub fn matrix_cross3<N: RealField>(x: &TVec3<N>) -> TMat3<N> {
+pub fn matrix_cross3<T: RealField>(x: &TVec3<T>) -> TMat3<T> {
     x.cross_matrix()
 }
 
@@ -16,6 +16,6 @@ pub fn matrix_cross3<N: RealField>(x: &TVec3<N>) -> TMat3<N> {
 /// # See also:
 ///
 /// * [`matrix_cross3`](fn.matrix_cross3.html)
-pub fn matrix_cross<N: RealField>(x: &TVec3<N>) -> TMat4<N> {
+pub fn matrix_cross<T: RealField>(x: &TVec3<T>) -> TMat4<T> {
     crate::mat3_to_mat4(&x.cross_matrix())
 }

nalgebra-glm/src/gtx/matrix_operation.rs

@@ -15,7 +15,7 @@ use crate::traits::Number;
 /// * [`diagonal4x2`](fn.diagonal4x2.html)
 /// * [`diagonal4x3`](fn.diagonal4x3.html)
 /// * [`diagonal4x4`](fn.diagonal4x4.html)
-pub fn diagonal2x2<N: Number>(v: &TVec2<N>) -> TMat2<N> {
+pub fn diagonal2x2<T: Number>(v: &TVec2<T>) -> TMat2<T> {
     TMat2::from_diagonal(v)
 }
 
@@ -31,7 +31,7 @@ pub fn diagonal2x2<N: Number>(v: &TVec2<N>) -> TMat2<N> {
 /// * [`diagonal4x2`](fn.diagonal4x2.html)
 /// * [`diagonal4x3`](fn.diagonal4x3.html)
 /// * [`diagonal4x4`](fn.diagonal4x4.html)
-pub fn diagonal2x3<N: Number>(v: &TVec2<N>) -> TMat2x3<N> {
+pub fn diagonal2x3<T: Number>(v: &TVec2<T>) -> TMat2x3<T> {
     TMat2x3::from_partial_diagonal(v.as_slice())
 }
 
@@ -47,7 +47,7 @@ pub fn diagonal2x3<N: Number>(v: &TVec2<N>) -> TMat2x3<N> {
 /// * [`diagonal4x2`](fn.diagonal4x2.html)
 /// * [`diagonal4x3`](fn.diagonal4x3.html)
 /// * [`diagonal4x4`](fn.diagonal4x4.html)
-pub fn diagonal2x4<N: Number>(v: &TVec2<N>) -> TMat2x4<N> {
+pub fn diagonal2x4<T: Number>(v: &TVec2<T>) -> TMat2x4<T> {
     TMat2x4::from_partial_diagonal(v.as_slice())
 }
 
@@ -63,7 +63,7 @@ pub fn diagonal2x4<N: Number>(v: &TVec2<N>) -> TMat2x4<N> {
 /// * [`diagonal4x2`](fn.diagonal4x2.html)
 /// * [`diagonal4x3`](fn.diagonal4x3.html)
 /// * [`diagonal4x4`](fn.diagonal4x4.html)
-pub fn diagonal3x2<N: Number>(v: &TVec2<N>) -> TMat3x2<N> {
+pub fn diagonal3x2<T: Number>(v: &TVec2<T>) -> TMat3x2<T> {
     TMat3x2::from_partial_diagonal(v.as_slice())
 }
 
@@ -79,7 +79,7 @@ pub fn diagonal3x2<N: Number>(v: &TVec2<N>) -> TMat3x2<N> {
 /// * [`diagonal4x2`](fn.diagonal4x2.html)
 /// * [`diagonal4x3`](fn.diagonal4x3.html)
 /// * [`diagonal4x4`](fn.diagonal4x4.html)
-pub fn diagonal3x3<N: Number>(v: &TVec3<N>) -> TMat3<N> {
+pub fn diagonal3x3<T: Number>(v: &TVec3<T>) -> TMat3<T> {
     TMat3::from_diagonal(v)
 }
 
@@ -95,7 +95,7 @@ pub fn diagonal3x3<N: Number>(v: &TVec3<N>) -> TMat3<N> {
 /// * [`diagonal4x2`](fn.diagonal4x2.html)
 /// * [`diagonal4x3`](fn.diagonal4x3.html)
 /// * [`diagonal4x4`](fn.diagonal4x4.html)
-pub fn diagonal3x4<N: Number>(v: &TVec3<N>) -> TMat3x4<N> {
+pub fn diagonal3x4<T: Number>(v: &TVec3<T>) -> TMat3x4<T> {
     TMat3x4::from_partial_diagonal(v.as_slice())
 }
 
@@ -111,7 +111,7 @@ pub fn diagonal3x4<N: Number>(v: &TVec3<N>) -> TMat3x4<N> {
 /// * [`diagonal3x4`](fn.diagonal3x4.html)
 /// * [`diagonal4x3`](fn.diagonal4x3.html)
 /// * [`diagonal4x4`](fn.diagonal4x4.html)
-pub fn diagonal4x2<N: Number>(v: &TVec2<N>) -> TMat4x2<N> {
+pub fn diagonal4x2<T: Number>(v: &TVec2<T>) -> TMat4x2<T> {
     TMat4x2::from_partial_diagonal(v.as_slice())
 }
 
@@ -127,7 +127,7 @@ pub fn diagonal4x2<N: Number>(v: &TVec2<N>) -> TMat4x2<N> {
 /// * [`diagonal3x4`](fn.diagonal3x4.html)
 /// * [`diagonal4x2`](fn.diagonal4x2.html)
 /// * [`diagonal4x4`](fn.diagonal4x4.html)
-pub fn diagonal4x3<N: Number>(v: &TVec3<N>) -> TMat4x3<N> {
+pub fn diagonal4x3<T: Number>(v: &TVec3<T>) -> TMat4x3<T> {
     TMat4x3::from_partial_diagonal(v.as_slice())
 }
 
@@ -143,6 +143,6 @@ pub fn diagonal4x3<N: Number>(v: &TVec3<N>) -> TMat4x3<N> {
 /// * [`diagonal3x4`](fn.diagonal3x4.html)
 /// * [`diagonal4x2`](fn.diagonal4x2.html)
 /// * [`diagonal4x3`](fn.diagonal4x3.html)
-pub fn diagonal4x4<N: Number>(v: &TVec4<N>) -> TMat4<N> {
+pub fn diagonal4x4<T: Number>(v: &TVec4<T>) -> TMat4<T> {
     TMat4::from_diagonal(v)
 }

nalgebra-glm/src/gtx/norm.rs

@@ -1,17 +1,13 @@
-use na::{DefaultAllocator, RealField};
+use na::RealField;
 
 use crate::aliases::TVec;
-use crate::traits::{Alloc, Dimension};
 
 /// The squared distance between two points.
 ///
 /// # See also:
 ///
 /// * [`distance`](fn.distance.html)
-pub fn distance2<N: RealField, D: Dimension>(p0: &TVec<N, D>, p1: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn distance2<T: RealField, const D: usize>(p0: &TVec<T, D>, p1: &TVec<T, D>) -> T {
     (p1 - p0).norm_squared()
 }
 
@@ -22,10 +18,7 @@ where
 /// * [`l1_norm`](fn.l1_norm.html)
 /// * [`l2_distance`](fn.l2_distance.html)
 /// * [`l2_norm`](fn.l2_norm.html)
-pub fn l1_distance<N: RealField, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn l1_distance<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
     l1_norm(&(y - x))
 }
 
@@ -39,10 +32,7 @@ where
 /// * [`l1_distance`](fn.l1_distance.html)
 /// * [`l2_distance`](fn.l2_distance.html)
 /// * [`l2_norm`](fn.l2_norm.html)
-pub fn l1_norm<N: RealField, D: Dimension>(v: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn l1_norm<T: RealField, const D: usize>(v: &TVec<T, D>) -> T {
     crate::comp_add(&v.abs())
 }
 
@@ -60,10 +50,7 @@ where
 /// * [`length2`](fn.length2.html)
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude2`](fn.magnitude2.html)
-pub fn l2_distance<N: RealField, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn l2_distance<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
     l2_norm(&(y - x))
 }
 
@@ -83,10 +70,7 @@ where
 /// * [`length2`](fn.length2.html)
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude2`](fn.magnitude2.html)
-pub fn l2_norm<N: RealField, D: Dimension>(x: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn l2_norm<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm()
 }
 
@@ -101,10 +85,7 @@ where
 /// * [`length`](fn.length.html)
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude2`](fn.magnitude2.html)
-pub fn length2<N: RealField, D: Dimension>(x: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn length2<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm_squared()
 }
 
@@ -119,19 +100,14 @@ where
 /// * [`length2`](fn.length2.html)
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`nalgebra::norm_squared`](../nalgebra/fn.norm_squared.html)
-pub fn magnitude2<N: RealField, D: Dimension>(x: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn magnitude2<T: RealField, const D: usize>(x: &TVec<T, D>) -> T {
     x.norm_squared()
 }
 
-//pub fn lxNorm<N: RealField, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>, unsigned int Depth) -> N
-//    where DefaultAllocator: Alloc<N, D> {
+//pub fn lxNorm<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, unsigned int Depth) -> T {
 //    unimplemented!()
 //}
 //
-//pub fn lxNorm<N: RealField, D: Dimension>(x: &TVec<N, D>, unsigned int Depth) -> N
-//    where DefaultAllocator: Alloc<N, D> {
+//pub fn lxNorm<T: RealField, const D: usize>(x: &TVec<T, D>, unsigned int Depth) -> T  {
 //    unimplemented!()
 //}

nalgebra-glm/src/gtx/normal.rs

@@ -5,6 +5,6 @@ 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<N: RealField>(p1: &TVec3<N>, p2: &TVec3<N>, p3: &TVec3<N>) -> TVec3<N> {
+pub fn triangle_normal<T: RealField>(p1: &TVec3<T>, p2: &TVec3<T>, p3: &TVec3<T>) -> TVec3<T> {
     (p2 - p1).cross(&(p3 - p1)).normalize()
 }

nalgebra-glm/src/gtx/normalize_dot.rs

@@ -1,7 +1,6 @@
-use na::{DefaultAllocator, RealField};
+use na::RealField;
 
 use crate::aliases::TVec;
-use crate::traits::{Alloc, Dimension};
 
 /// The dot product of the normalized version of `x` and `y`.
 ///
@@ -10,10 +9,7 @@ use crate::traits::{Alloc, Dimension};
 /// # See also:
 ///
 /// * [`normalize_dot`](fn.normalize_dot.html`)
-pub fn fast_normalize_dot<N: RealField, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn fast_normalize_dot<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
     // XXX: improve those.
     x.normalize().dot(&y.normalize())
 }
@@ -23,10 +19,7 @@ where
 /// # See also:
 ///
 /// * [`fast_normalize_dot`](fn.fast_normalize_dot.html`)
-pub fn normalize_dot<N: RealField, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn normalize_dot<T: RealField, 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 +1,97 @@
-use na::{RealField, Rotation3, Unit, UnitQuaternion, U3};
+use na::{RealField, Rotation3, Unit, UnitQuaternion};
 
 use crate::aliases::{Qua, TMat3, TMat4, TVec3, TVec4};
 
 /// Rotate the vector `v` by the quaternion `q` assumed to be normalized.
-pub fn quat_cross_vec<N: RealField>(q: &Qua<N>, v: &TVec3<N>) -> TVec3<N> {
+pub fn quat_cross_vec<T: RealField>(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<N: RealField>(v: &TVec3<N>, q: &Qua<N>) -> TVec3<N> {
+pub fn quat_inv_cross_vec<T: RealField>(v: &TVec3<T>, q: &Qua<T>) -> TVec3<T> {
     UnitQuaternion::new_unchecked(*q).inverse() * v
 }
 
 /// The quaternion `w` component.
-pub fn quat_extract_real_component<N: RealField>(q: &Qua<N>) -> N {
+pub fn quat_extract_real_component<T: RealField>(q: &Qua<T>) -> T {
     q.w
 }
 
 /// Normalized linear interpolation between two quaternions.
-pub fn quat_fast_mix<N: RealField>(x: &Qua<N>, y: &Qua<N>, a: N) -> Qua<N> {
+pub fn quat_fast_mix<T: RealField>(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<N: RealField>(prev: &Qua<N>, curr: &Qua<N>, next: &Qua<N>) -> Qua<N> {
+//pub fn quat_intermediate<T: RealField>(prev: &Qua<T>, curr: &Qua<T>, next: &Qua<T>) -> Qua<T> {
 //    unimplemented!()
 //}
 
 /// The squared magnitude of a quaternion `q`.
-pub fn quat_length2<N: RealField>(q: &Qua<N>) -> N {
+pub fn quat_length2<T: RealField>(q: &Qua<T>) -> T {
     q.norm_squared()
 }
 
 /// The squared magnitude of a quaternion `q`.
-pub fn quat_magnitude2<N: RealField>(q: &Qua<N>) -> N {
+pub fn quat_magnitude2<T: RealField>(q: &Qua<T>) -> T {
     q.norm_squared()
 }
 
 /// The quaternion representing the identity rotation.
-pub fn quat_identity<N: RealField>() -> Qua<N> {
+pub fn quat_identity<T: RealField>() -> Qua<T> {
     UnitQuaternion::identity().into_inner()
 }
 
 /// Rotates a vector by a quaternion assumed to be normalized.
-pub fn quat_rotate_vec3<N: RealField>(q: &Qua<N>, v: &TVec3<N>) -> TVec3<N> {
+pub fn quat_rotate_vec3<T: RealField>(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<N: RealField>(q: &Qua<N>, v: &TVec4<N>) -> TVec4<N> {
-    let rotated = Unit::new_unchecked(*q) * v.fixed_rows::<U3>(0);
+pub fn quat_rotate_vec<T: RealField>(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<N: RealField>(orig: &TVec3<N>, dest: &TVec3<N>) -> Qua<N> {
+pub fn quat_rotation<T: RealField>(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<N: RealField>(x: &Qua<N>, y: &Qua<N>, a: N) -> Qua<N> {
+pub fn quat_short_mix<T: RealField>(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<N: RealField>(q1: &Qua<N>, q2: &Qua<N>, s1: &Qua<N>, s2: &Qua<N>, h: N) -> Qua<N> {
+//pub fn quat_squad<T: RealField>(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<N: RealField>(x: &Qua<N>) -> TMat3<N> {
+pub fn quat_to_mat3<T: RealField>(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<N: RealField>(x: &Qua<N>) -> TMat4<N> {
+pub fn quat_to_mat4<T: RealField>(x: &Qua<T>) -> TMat4<T> {
     UnitQuaternion::new_unchecked(*x).to_homogeneous()
 }
 
 /// Converts a rotation matrix to a quaternion.
-pub fn mat3_to_quat<N: RealField>(x: &TMat3<N>) -> Qua<N> {
+pub fn mat3_to_quat<T: RealField>(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<N: RealField>(x: &TMat4<N>) -> Qua<N> {
-    let rot = x.fixed_slice::<U3, U3>(0, 0).into_owned();
+pub fn to_quat<T: RealField>(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

@@ -9,7 +9,7 @@ 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<N: RealField>(m: &TMat4<N>, angle: N, axis: &TVec3<N>) -> TMat4<N> {
+pub fn rotate_normalized_axis<T: RealField>(m: &TMat4<T>, angle: T, axis: &TVec3<T>) -> TMat4<T> {
     m * Rotation3::from_axis_angle(&Unit::new_unchecked(*axis), angle).to_homogeneous()
 }
 
@@ -20,6 +20,6 @@ pub fn rotate_normalized_axis<N: RealField>(m: &TMat4<N>, angle: N, 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<N: RealField>(q: &Qua<N>, angle: N, axis: &TVec3<N>) -> Qua<N> {
+pub fn quat_rotate_normalized_axis<T: RealField>(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

@@ -3,7 +3,7 @@ use na::{RealField, Rotation3, Unit, UnitComplex};
 use crate::aliases::{TMat4, TVec2, TVec3, TVec4};
 
 /// Build the rotation matrix needed to align `normal` and `up`.
-pub fn orientation<N: RealField>(normal: &TVec3<N>, up: &TVec3<N>) -> TMat4<N> {
+pub fn orientation<T: RealField>(normal: &TVec3<T>, up: &TVec3<T>) -> TMat4<T> {
     if let Some(r) = Rotation3::rotation_between(normal, up) {
         r.to_homogeneous()
     } else {
@@ -12,52 +12,52 @@ pub fn orientation<N: RealField>(normal: &TVec3<N>, up: &TVec3<N>) -> TMat4<N> {
 }
 
 /// Rotate a two dimensional vector.
-pub fn rotate_vec2<N: RealField>(v: &TVec2<N>, angle: N) -> TVec2<N> {
+pub fn rotate_vec2<T: RealField>(v: &TVec2<T>, angle: T) -> TVec2<T> {
     UnitComplex::new(angle) * v
 }
 
 /// Rotate a three dimensional vector around an axis.
-pub fn rotate_vec3<N: RealField>(v: &TVec3<N>, angle: N, normal: &TVec3<N>) -> TVec3<N> {
+pub fn rotate_vec3<T: RealField>(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<N: RealField>(v: &TVec4<N>, angle: N, normal: &TVec3<N>) -> TVec4<N> {
+pub fn rotate_vec4<T: RealField>(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<N: RealField>(v: &TVec3<N>, angle: N) -> TVec3<N> {
+pub fn rotate_x_vec3<T: RealField>(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<N: RealField>(v: &TVec4<N>, angle: N) -> TVec4<N> {
+pub fn rotate_x_vec4<T: RealField>(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<N: RealField>(v: &TVec3<N>, angle: N) -> TVec3<N> {
+pub fn rotate_y_vec3<T: RealField>(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<N: RealField>(v: &TVec4<N>, angle: N) -> TVec4<N> {
+pub fn rotate_y_vec4<T: RealField>(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<N: RealField>(v: &TVec3<N>, angle: N) -> TVec3<N> {
+pub fn rotate_z_vec3<T: RealField>(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<N: RealField>(v: &TVec4<N>, angle: N) -> TVec4<N> {
+pub fn rotate_z_vec4<T: RealField>(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<N: RealField>(x: &TVec3<N>, y: &TVec3<N>, a: N) -> TVec3<N> {
+pub fn slerp<T: RealField>(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

@@ -12,7 +12,7 @@ use crate::traits::Number;
 /// * [`rotation2d`](fn.rotation2d.html)
 /// * [`scaling2d`](fn.scaling2d.html)
 /// * [`translation2d`](fn.translation2d.html)
-pub fn rotation<N: RealField>(angle: N, v: &TVec3<N>) -> TMat4<N> {
+pub fn rotation<T: RealField>(angle: T, v: &TVec3<T>) -> TMat4<T> {
     Rotation3::from_axis_angle(&Unit::new_normalize(*v), angle).to_homogeneous()
 }
 
@@ -25,7 +25,7 @@ pub fn rotation<N: RealField>(angle: N, v: &TVec3<N>) -> TMat4<N> {
 /// * [`rotation2d`](fn.rotation2d.html)
 /// * [`scaling2d`](fn.scaling2d.html)
 /// * [`translation2d`](fn.translation2d.html)
-pub fn scaling<N: Number>(v: &TVec3<N>) -> TMat4<N> {
+pub fn scaling<T: Number>(v: &TVec3<T>) -> TMat4<T> {
     TMat4::new_nonuniform_scaling(v)
 }
 
@@ -38,7 +38,7 @@ pub fn scaling<N: Number>(v: &TVec3<N>) -> TMat4<N> {
 /// * [`rotation2d`](fn.rotation2d.html)
 /// * [`scaling2d`](fn.scaling2d.html)
 /// * [`translation2d`](fn.translation2d.html)
-pub fn translation<N: Number>(v: &TVec3<N>) -> TMat4<N> {
+pub fn translation<T: Number>(v: &TVec3<T>) -> TMat4<T> {
     TMat4::new_translation(v)
 }
 
@@ -51,7 +51,7 @@ pub fn translation<N: Number>(v: &TVec3<N>) -> TMat4<N> {
 /// * [`translation`](fn.translation.html)
 /// * [`scaling2d`](fn.scaling2d.html)
 /// * [`translation2d`](fn.translation2d.html)
-pub fn rotation2d<N: RealField>(angle: N) -> TMat3<N> {
+pub fn rotation2d<T: RealField>(angle: T) -> TMat3<T> {
     Rotation2::new(angle).to_homogeneous()
 }
 
@@ -64,7 +64,7 @@ pub fn rotation2d<N: RealField>(angle: N) -> TMat3<N> {
 /// * [`translation`](fn.translation.html)
 /// * [`rotation2d`](fn.rotation2d.html)
 /// * [`translation2d`](fn.translation2d.html)
-pub fn scaling2d<N: Number>(v: &TVec2<N>) -> TMat3<N> {
+pub fn scaling2d<T: Number>(v: &TVec2<T>) -> TMat3<T> {
     TMat3::new_nonuniform_scaling(v)
 }
 
@@ -77,6 +77,6 @@ pub fn scaling2d<N: Number>(v: &TVec2<N>) -> TMat3<N> {
 /// * [`translation`](fn.translation.html)
 /// * [`rotation2d`](fn.rotation2d.html)
 /// * [`scaling2d`](fn.scaling2d.html)
-pub fn translation2d<N: Number>(v: &TVec2<N>) -> TMat3<N> {
+pub fn translation2d<T: Number>(v: &TVec2<T>) -> TMat3<T> {
     TMat3::new_translation(v)
 }

nalgebra-glm/src/gtx/transform2.rs

@@ -1,14 +1,12 @@
-use na::{U2, U3};
-
 use crate::aliases::{TMat3, TMat4, TVec2, TVec3};
 use crate::traits::Number;
 
 /// Build planar projection matrix along normal axis and right-multiply it to `m`.
-pub fn proj2d<N: Number>(m: &TMat3<N>, normal: &TVec2<N>) -> TMat3<N> {
+pub fn proj2d<T: Number>(m: &TMat3<T>, normal: &TVec2<T>) -> TMat3<T> {
     let mut res = TMat3::identity();
 
     {
-        let mut part = res.fixed_slice_mut::<U2, U2>(0, 0);
+        let mut part = res.fixed_slice_mut::<2, 2>(0, 0);
         part -= normal * normal.transpose();
     }
 
@@ -16,11 +14,11 @@ pub fn proj2d<N: Number>(m: &TMat3<N>, normal: &TVec2<N>) -> TMat3<N> {
 }
 
 /// Build planar projection matrix along normal axis, and right-multiply it to `m`.
-pub fn proj<N: Number>(m: &TMat4<N>, normal: &TVec3<N>) -> TMat4<N> {
+pub fn proj<T: Number>(m: &TMat4<T>, normal: &TVec3<T>) -> TMat4<T> {
     let mut res = TMat4::identity();
 
     {
-        let mut part = res.fixed_slice_mut::<U3, U3>(0, 0);
+        let mut part = res.fixed_slice_mut::<3, 3>(0, 0);
         part -= normal * normal.transpose();
     }
 
@@ -28,33 +26,33 @@ pub fn proj<N: Number>(m: &TMat4<N>, normal: &TVec3<N>) -> TMat4<N> {
 }
 
 /// Builds a reflection matrix and right-multiply it to `m`.
-pub fn reflect2d<N: Number>(m: &TMat3<N>, normal: &TVec2<N>) -> TMat3<N> {
+pub fn reflect2d<T: Number>(m: &TMat3<T>, normal: &TVec2<T>) -> TMat3<T> {
     let mut res = TMat3::identity();
 
     {
-        let mut part = res.fixed_slice_mut::<U2, U2>(0, 0);
-        part -= (normal * N::from_f64(2.0).unwrap()) * normal.transpose();
+        let mut part = res.fixed_slice_mut::<2, 2>(0, 0);
+        part -= (normal * T::from_f64(2.0).unwrap()) * normal.transpose();
     }
 
     m * res
 }
 
 /// Builds a reflection matrix, and right-multiply it to `m`.
-pub fn reflect<N: Number>(m: &TMat4<N>, normal: &TVec3<N>) -> TMat4<N> {
+pub fn reflect<T: Number>(m: &TMat4<T>, normal: &TVec3<T>) -> TMat4<T> {
     let mut res = TMat4::identity();
 
     {
-        let mut part = res.fixed_slice_mut::<U3, U3>(0, 0);
-        part -= (normal * N::from_f64(2.0).unwrap()) * normal.transpose();
+        let mut part = res.fixed_slice_mut::<3, 3>(0, 0);
+        part -= (normal * T::from_f64(2.0).unwrap()) * normal.transpose();
     }
 
     m * res
 }
 
 /// Builds a scale-bias matrix.
-pub fn scale_bias_matrix<N: Number>(scale: N, bias: N) -> TMat4<N> {
-    let _0 = N::zero();
-    let _1 = N::one();
+pub fn scale_bias_matrix<T: Number>(scale: T, bias: T) -> TMat4<T> {
+    let _0 = T::zero();
+    let _1 = T::one();
 
     TMat4::new(
         scale, _0, _0, bias, _0, scale, _0, bias, _0, _0, scale, bias, _0, _0, _0, _1,
@@ -62,50 +60,50 @@ pub fn scale_bias_matrix<N: Number>(scale: N, bias: N) -> TMat4<N> {
 }
 
 /// Builds a scale-bias matrix, and right-multiply it to `m`.
-pub fn scale_bias<N: Number>(m: &TMat4<N>, scale: N, bias: N) -> TMat4<N> {
+pub fn scale_bias<T: Number>(m: &TMat4<T>, scale: T, bias: T) -> TMat4<T> {
     m * scale_bias_matrix(scale, bias)
 }
 
 /// Transforms a matrix with a shearing on X axis.
-pub fn shear2d_x<N: Number>(m: &TMat3<N>, y: N) -> TMat3<N> {
-    let _0 = N::zero();
-    let _1 = N::one();
+pub fn shear2d_x<T: Number>(m: &TMat3<T>, y: T) -> TMat3<T> {
+    let _0 = T::zero();
+    let _1 = T::one();
 
     let shear = TMat3::new(_1, y, _0, _0, _1, _0, _0, _0, _1);
     m * shear
 }
 
 /// Transforms a matrix with a shearing on Y axis.
-pub fn shear_x<N: Number>(m: &TMat4<N>, y: N, z: N) -> TMat4<N> {
-    let _0 = N::zero();
-    let _1 = N::one();
+pub fn shear_x<T: Number>(m: &TMat4<T>, y: T, z: T) -> TMat4<T> {
+    let _0 = T::zero();
+    let _1 = T::one();
     let shear = TMat4::new(_1, _0, _0, _0, y, _1, _0, _0, z, _0, _1, _0, _0, _0, _0, _1);
 
     m * shear
 }
 
 /// Transforms a matrix with a shearing on Y axis.
-pub fn shear2d_y<N: Number>(m: &TMat3<N>, x: N) -> TMat3<N> {
-    let _0 = N::zero();
-    let _1 = N::one();
+pub fn shear2d_y<T: Number>(m: &TMat3<T>, x: T) -> TMat3<T> {
+    let _0 = T::zero();
+    let _1 = T::one();
 
     let shear = TMat3::new(_1, _0, _0, x, _1, _0, _0, _0, _1);
     m * shear
 }
 
 /// Transforms a matrix with a shearing on Y axis.
-pub fn shear_y<N: Number>(m: &TMat4<N>, x: N, z: N) -> TMat4<N> {
-    let _0 = N::zero();
-    let _1 = N::one();
+pub fn shear_y<T: Number>(m: &TMat4<T>, x: T, z: T) -> TMat4<T> {
+    let _0 = T::zero();
+    let _1 = T::one();
     let shear = TMat4::new(_1, x, _0, _0, _0, _1, _0, _0, _0, z, _1, _0, _0, _0, _0, _1);
 
     m * shear
 }
 
 /// Transforms a matrix with a shearing on Z axis.
-pub fn shear_z<N: Number>(m: &TMat4<N>, x: N, y: N) -> TMat4<N> {
-    let _0 = N::zero();
-    let _1 = N::one();
+pub fn shear_z<T: Number>(m: &TMat4<T>, x: T, y: T) -> TMat4<T> {
+    let _0 = T::zero();
+    let _1 = T::one();
     let shear = TMat4::new(_1, _0, x, _0, _0, _1, y, _0, _0, _0, _1, _0, _0, _0, _0, _1);
 
     m * shear

nalgebra-glm/src/gtx/transform2d.rs

@@ -12,7 +12,7 @@ use crate::traits::Number;
 /// * [`scaling2d`](fn.scaling2d.html)
 /// * [`translate2d`](fn.translate2d.html)
 /// * [`translation2d`](fn.translation2d.html)
-pub fn rotate2d<N: RealField>(m: &TMat3<N>, angle: N) -> TMat3<N> {
+pub fn rotate2d<T: RealField>(m: &TMat3<T>, angle: T) -> TMat3<T> {
     m * UnitComplex::new(angle).to_homogeneous()
 }
 
@@ -25,7 +25,7 @@ pub fn rotate2d<N: RealField>(m: &TMat3<N>, angle: N) -> TMat3<N> {
 /// * [`scaling2d`](fn.scaling2d.html)
 /// * [`translate2d`](fn.translate2d.html)
 /// * [`translation2d`](fn.translation2d.html)
-pub fn scale2d<N: Number>(m: &TMat3<N>, v: &TVec2<N>) -> TMat3<N> {
+pub fn scale2d<T: Number>(m: &TMat3<T>, v: &TVec2<T>) -> TMat3<T> {
     m.prepend_nonuniform_scaling(v)
 }
 
@@ -38,6 +38,6 @@ pub fn scale2d<N: Number>(m: &TMat3<N>, v: &TVec2<N>) -> TMat3<N> {
 /// * [`scale2d`](fn.scale2d.html)
 /// * [`scaling2d`](fn.scaling2d.html)
 /// * [`translation2d`](fn.translation2d.html)
-pub fn translate2d<N: Number>(m: &TMat3<N>, v: &TVec2<N>) -> TMat3<N> {
+pub fn translate2d<T: Number>(m: &TMat3<T>, v: &TVec2<T>) -> TMat3<T> {
     m.prepend_translation(v)
 }

nalgebra-glm/src/gtx/vector_angle.rs

@@ -1,20 +1,16 @@
-use na::{DefaultAllocator, RealField};
+use na::RealField;
 
 use crate::aliases::TVec;
-use crate::traits::{Alloc, Dimension};
 
 /// The angle between two vectors.
-pub fn angle<N: RealField, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn angle<T: RealField, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> T {
     x.angle(y)
 }
 
-//pub fn oriented_angle<N: RealField>(x: &TVec2<N>, y: &TVec2<N>) -> N {
+//pub fn oriented_angle<T: RealField>(x: &TVec2<T>, y: &TVec2<T>) -> T {
 //    unimplemented!()
 //}
 //
-//pub fn oriented_angle_ref<N: RealField>(x: &TVec3<N>, y: &TVec3<N>, refv: &TVec3<N>) -> N {
+//pub fn oriented_angle_ref<T: RealField>(x: &TVec3<T>, y: &TVec3<T>, refv: &TVec3<T>) -> T {
 //    unimplemented!()
 //}

nalgebra-glm/src/gtx/vector_query.rs

@@ -1,14 +1,14 @@
-use na::{DefaultAllocator, RealField};
+use na::RealField;
 
 use crate::aliases::{TVec, TVec2, TVec3};
-use crate::traits::{Alloc, Dimension, Number};
+use crate::traits::Number;
 
 /// Returns `true` if two vectors are collinear (up to an epsilon).
 ///
 /// # See also:
 ///
 /// * [`are_collinear2d`](fn.are_collinear2d.html)
-pub fn are_collinear<N: Number>(v0: &TVec3<N>, v1: &TVec3<N>, epsilon: N) -> bool {
+pub fn are_collinear<T: Number>(v0: &TVec3<T>, v1: &TVec3<T>, epsilon: T) -> bool {
     is_null(&v0.cross(v1), epsilon)
 }
 
@@ -17,43 +17,34 @@ pub fn are_collinear<N: Number>(v0: &TVec3<N>, v1: &TVec3<N>, epsilon: N) -> boo
 /// # See also:
 ///
 /// * [`are_collinear`](fn.are_collinear.html)
-pub fn are_collinear2d<N: Number>(v0: &TVec2<N>, v1: &TVec2<N>, epsilon: N) -> bool {
-    abs_diff_eq!(v0.perp(v1), N::zero(), epsilon = epsilon)
+pub fn are_collinear2d<T: Number>(v0: &TVec2<T>, v1: &TVec2<T>, epsilon: T) -> bool {
+    abs_diff_eq!(v0.perp(v1), T::zero(), epsilon = epsilon)
 }
 
 /// Returns `true` if two vectors are orthogonal (up to an epsilon).
-pub fn are_orthogonal<N: Number, D: Dimension>(v0: &TVec<N, D>, v1: &TVec<N, D>, epsilon: N) -> bool
-where
-    DefaultAllocator: Alloc<N, D>,
-{
-    abs_diff_eq!(v0.dot(v1), N::zero(), epsilon = epsilon)
+pub fn are_orthogonal<T: Number, const D: usize>(
+    v0: &TVec<T, D>,
+    v1: &TVec<T, D>,
+    epsilon: T,
+) -> bool {
+    abs_diff_eq!(v0.dot(v1), T::zero(), epsilon = epsilon)
 }
 
-//pub fn are_orthonormal<N: Number, D: Dimension>(v0: &TVec<N, D>, v1: &TVec<N, D>, epsilon: N) -> bool
-//    where DefaultAllocator: Alloc<N, D> {
+//pub fn are_orthonormal<T: Number, const D: usize>(v0: &TVec<T, D>, v1: &TVec<T, D>, epsilon: T) -> bool {
 //    unimplemented!()
 //}
 
 /// Returns `true` if all the components of `v` are zero (up to an epsilon).
-pub fn is_comp_null<N: Number, D: Dimension>(v: &TVec<N, D>, epsilon: N) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
-    v.map(|x| abs_diff_eq!(x, N::zero(), epsilon = epsilon))
+pub fn is_comp_null<T: Number, const D: usize>(v: &TVec<T, D>, epsilon: T) -> TVec<bool, D> {
+    v.map(|x| abs_diff_eq!(x, T::zero(), epsilon = epsilon))
 }
 
 /// Returns `true` if `v` has a magnitude of 1 (up to an epsilon).
-pub fn is_normalized<N: RealField, D: Dimension>(v: &TVec<N, D>, epsilon: N) -> bool
-where
-    DefaultAllocator: Alloc<N, D>,
-{
-    abs_diff_eq!(v.norm_squared(), N::one(), epsilon = epsilon * epsilon)
+pub fn is_normalized<T: RealField, const D: usize>(v: &TVec<T, D>, epsilon: T) -> bool {
+    abs_diff_eq!(v.norm_squared(), T::one(), epsilon = epsilon * epsilon)
 }
 
 /// Returns `true` if `v` is zero (up to an epsilon).
-pub fn is_null<N: Number, D: Dimension>(v: &TVec<N, D>, epsilon: N) -> bool
-where
-    DefaultAllocator: Alloc<N, D>,
-{
-    abs_diff_eq!(*v, TVec::<N, D>::zeros(), epsilon = epsilon)
+pub fn is_null<T: Number, const D: usize>(v: &TVec<T, D>, epsilon: T) -> bool {
+    abs_diff_eq!(*v, TVec::<T, D>::zeros(), epsilon = epsilon)
 }

nalgebra-glm/src/integer.rs

@@ -1,29 +1,46 @@
-use na::{Scalar, RealField, U3, DefaultAllocator};
+use na::{DefaultAllocator, RealField, Scalar, U3};
 
-use crate::traits::{Number, Alloc, Dimension};
 use crate::aliases::TVec;
+use crate::traits::{Alloc, Dimension, Number};
 
 pub fn bitCount<T>(v: T) -> i32 {
     unimplemented!()
 }
 
-pub fn bitCount2<N: Scalar, D: Dimension>(v: &TVec<N, D>) -> TVec<i32, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn bitCount2<T: Scalar, const D: usize>(v: &TVec<T, D>) -> TVec<i32, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
-pub fn bitfieldExtract<N: Scalar, D: Dimension>(Value: &TVec<N, D>, Offset: i32, Bits: i32) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn bitfieldExtract<T: Scalar, const D: usize>(
+    Value: &TVec<T, D>,
+    Offset: i32,
+    Bits: i32,
+) -> TVec<T, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
-pub fn bitfieldInsert<N: Scalar, D: Dimension>(Base: &TVec<N, D>, Insert: &TVec<N, D>, Offset: i32, Bits: i32) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn bitfieldInsert<T: Scalar, const D: usize>(
+    Base: &TVec<T, D>,
+    Insert: &TVec<T, D>,
+    Offset: i32,
+    Bits: i32,
+) -> TVec<T, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
-pub fn bitfieldReverse<N: Scalar, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn bitfieldReverse<T: Scalar, const D: usize>(v: &TVec<T, D>) -> TVec<T, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
@@ -31,8 +48,10 @@ pub fn findLSB<IU>(x: IU) -> u32 {
     unimplemented!()
 }
 
-pub fn findLSB2<N: Scalar, D: Dimension>(v: &TVec<N, D>) -> TVec<i32, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn findLSB2<T: Scalar, const D: usize>(v: &TVec<T, D>) -> TVec<i32, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
@@ -40,27 +59,53 @@ pub fn findMSB<IU>(x: IU) -> i32 {
     unimplemented!()
 }
 
-pub fn findMSB2<N: Scalar, D: Dimension>(v: &TVec<N, D>) -> TVec<i32, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn findMSB2<T: Scalar, const D: usize>(v: &TVec<T, D>) -> TVec<i32, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
-pub fn imulExtended<N: Scalar, D: Dimension>(x: &TVec<i32, D>, y: &TVec<i32, D>, msb: &TVec<i32, D>, lsb: &TVec<i32, D>)
-    where DefaultAllocator: Alloc<N, D> {
+pub fn imulExtended<T: Scalar, const D: usize>(
+    x: &TVec<i32, D>,
+    y: &TVec<i32, D>,
+    msb: &TVec<i32, D>,
+    lsb: &TVec<i32, D>,
+) where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
-pub fn uaddCarry<N: Scalar, D: Dimension>(x: &TVec<u32, D>, y: &TVec<u32, D>, carry: &TVec<u32, D>) -> TVec<u32, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn uaddCarry<T: Scalar, const D: usize>(
+    x: &TVec<u32, D>,
+    y: &TVec<u32, D>,
+    carry: &TVec<u32, D>,
+) -> TVec<u32, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }
 
-pub fn umulExtended<N: Scalar, D: Dimension>(x: &TVec<u32, D>, y: &TVec<u32, D>, msb: &TVec<u32, D>, lsb: &TVec<u32, D>)
-    where DefaultAllocator: Alloc<N, D> {
-unimplemented!()
-}
-
-pub fn usubBorrow<N: Scalar, D: Dimension>(x: &TVec<u32, D>, y: &TVec<u32, D>, borrow: &TVec<u32, D>) -> TVec<u32, D>
-    where DefaultAllocator: Alloc<N, D> {
+pub fn umulExtended<T: Scalar, const D: usize>(
+    x: &TVec<u32, D>,
+    y: &TVec<u32, D>,
+    msb: &TVec<u32, D>,
+    lsb: &TVec<u32, D>,
+) where
+    DefaultAllocator: Alloc<T, D>,
+{
+    unimplemented!()
+}
+
+pub fn usubBorrow<T: Scalar, const D: usize>(
+    x: &TVec<u32, D>,
+    y: &TVec<u32, D>,
+    borrow: &TVec<u32, D>,
+) -> TVec<u32, D>
+where
+    DefaultAllocator: Alloc<T, D>,
+{
     unimplemented!()
 }

nalgebra-glm/src/lib.rs

@@ -54,7 +54,7 @@
    ### Vector and matrix construction
    Vectors, matrices, and quaternions can be constructed using several approaches:
    * Using functions with the same name as their type in lower-case. For example [`glm::vec3(x, y, z)`](fn.vec3.html) will create a 3D vector.
-   * Using the `::new` constructor. For example [`Vec3::new(x, y, z)`](../nalgebra/base/type.MatrixMN.html#method.new-27) will create a 3D vector.
+   * Using the `::new` constructor. For example [`Vec3::new(x, y, z)`](../nalgebra/base/type.OMatrix.html#method.new-27) will create a 3D vector.
    * Using the functions prefixed by `make_` to build a vector a matrix from a slice. For example [`glm::make_vec3(&[x, y, z])`](fn.make_vec3.html) will create a 3D vector.
    Keep in mind that constructing a matrix using this type of functions require its components to be arranged in column-major order on the slice.
    * Using a geometric construction function. For example [`glm::rotation(angle, axis)`](fn.rotation.html) will build a 4x4 homogeneous rotation matrix from an angle (in radians) and an axis.
@@ -119,7 +119,7 @@ extern crate approx;
 extern crate nalgebra as na;
 
 pub use crate::aliases::*;
-pub use crate::traits::{Alloc, Dimension, Number};
+pub use crate::traits::Number;
 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,

nalgebra-glm/src/matrix.rs

@@ -1,52 +1,40 @@
-use na::{DefaultAllocator, RealField, Scalar};
+use na::{Const, DimMin, RealField, Scalar};
 
 use crate::aliases::{TMat, TVec};
-use crate::traits::{Alloc, Dimension, Number};
+use crate::traits::Number;
 
 /// The determinant of the matrix `m`.
-pub fn determinant<N: RealField, D: Dimension>(m: &TMat<N, D, D>) -> N
+pub fn determinant<T: RealField, const D: usize>(m: &TMat<T, D, D>) -> T
 where
-    DefaultAllocator: Alloc<N, D, D>,
+    Const<D>: DimMin<Const<D>, Output = Const<D>>,
 {
     m.determinant()
 }
 
 /// The inverse of the matrix `m`.
-pub fn inverse<N: RealField, D: Dimension>(m: &TMat<N, D, D>) -> TMat<N, D, D>
-where
-    DefaultAllocator: Alloc<N, D, D>,
-{
+pub fn inverse<T: RealField, const D: usize>(m: &TMat<T, D, D>) -> TMat<T, D, D> {
     m.clone()
         .try_inverse()
-        .unwrap_or_else(TMat::<N, D, D>::zeros)
+        .unwrap_or_else(TMat::<T, D, D>::zeros)
 }
 
 /// Component-wise multiplication of two matrices.
-pub fn matrix_comp_mult<N: Number, R: Dimension, C: Dimension>(
-    x: &TMat<N, R, C>,
-    y: &TMat<N, R, C>,
-) -> TMat<N, R, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn matrix_comp_mult<T: Number, const R: usize, const C: usize>(
+    x: &TMat<T, R, C>,
+    y: &TMat<T, R, C>,
+) -> TMat<T, R, C> {
     x.component_mul(y)
 }
 
 /// Treats the first parameter `c` as a column vector and the second parameter `r` as a row vector and does a linear algebraic matrix multiply `c * r`.
-pub fn outer_product<N: Number, R: Dimension, C: Dimension>(
-    c: &TVec<N, R>,
-    r: &TVec<N, C>,
-) -> TMat<N, R, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn outer_product<T: Number, const R: usize, const C: usize>(
+    c: &TVec<T, R>,
+    r: &TVec<T, C>,
+) -> TMat<T, R, C> {
     c * r.transpose()
 }
 
 /// The transpose of the matrix `m`.
-pub fn transpose<N: Scalar, R: Dimension, C: Dimension>(x: &TMat<N, R, C>) -> TMat<N, C, R>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+pub fn transpose<T: Scalar, const R: usize, const C: usize>(x: &TMat<T, R, C>) -> TMat<T, C, R> {
     x.transpose()
 }

nalgebra-glm/src/packing.rs

@@ -1,52 +1,51 @@
 use na::Scalar;
 
-use crate::aliases::{Vec2, Vec4, UVec2};
+use crate::aliases::{UVec2, Vec2, Vec4};
 
-
-pub fn packDouble2x32<N: Scalar>(v: &UVec2) -> f64 {
+pub fn packDouble2x32<T: Scalar>(v: &UVec2) -> f64 {
     unimplemented!()
 }
 
-pub fn packHalf2x16<N: Scalar>(v: &Vec2) -> u32 {
+pub fn packHalf2x16<T: Scalar>(v: &Vec2) -> u32 {
     unimplemented!()
 }
 
-pub fn packSnorm2x16<N: Scalar>(v: &Vec2) -> u32 {
+pub fn packSnorm2x16<T: Scalar>(v: &Vec2) -> u32 {
     unimplemented!()
 }
 
-pub fn packSnorm4x8<N: Scalar>(v: &Vec4) -> u32 {
+pub fn packSnorm4x8<T: Scalar>(v: &Vec4) -> u32 {
     unimplemented!()
 }
 
-pub fn packUnorm2x16<N: Scalar>(v: &Vec2) -> u32 {
+pub fn packUnorm2x16<T: Scalar>(v: &Vec2) -> u32 {
     unimplemented!()
 }
 
-pub fn packUnorm4x8<N: Scalar>(v: &Vec4) -> u32 {
+pub fn packUnorm4x8<T: Scalar>(v: &Vec4) -> u32 {
     unimplemented!()
 }
 
-pub fn unpackDouble2x32<N: Scalar>(v: f64) -> UVec2 {
+pub fn unpackDouble2x32<T: Scalar>(v: f64) -> UVec2 {
     unimplemented!()
 }
 
-pub fn unpackHalf2x16<N: Scalar>(v: u32) -> Vec2 {
+pub fn unpackHalf2x16<T: Scalar>(v: u32) -> Vec2 {
     unimplemented!()
 }
 
-pub fn unpackSnorm2x16<N: Scalar>(p: u32) -> Vec2 {
+pub fn unpackSnorm2x16<T: Scalar>(p: u32) -> Vec2 {
     unimplemented!()
 }
 
-pub fn unpackSnorm4x8<N: Scalar>(p: u32) -> Vec4 {
+pub fn unpackSnorm4x8<T: Scalar>(p: u32) -> Vec4 {
     unimplemented!()
 }
 
-pub fn unpackUnorm2x16<N: Scalar>(p: u32) -> Vec2 {
+pub fn unpackUnorm2x16<T: Scalar>(p: u32) -> Vec2 {
     unimplemented!()
 }
 
-pub fn unpackUnorm4x8<N: Scalar>(p: u32) -> Vec4 {
+pub fn unpackUnorm4x8<T: Scalar>(p: u32) -> Vec4 {
     unimplemented!()
 }

nalgebra-glm/src/traits.rs

@@ -1,15 +1,10 @@
 use approx::AbsDiffEq;
 use num::{Bounded, FromPrimitive, Signed};
 
-use na::allocator::Allocator;
-use na::{DimMin, DimName, Scalar, U1};
+use na::Scalar;
 use simba::scalar::{ClosedAdd, ClosedMul, ClosedSub};
 use std::cmp::PartialOrd;
 
-/// A type-level number representing a vector, matrix row, or matrix column, dimension.
-pub trait Dimension: DimName + DimMin<Self, Output = Self> {}
-impl<D: DimName + DimMin<D, Output = Self>> Dimension for D {}
-
 /// A number that can either be an integer or a float.
 pub trait Number:
     Scalar
@@ -39,64 +34,3 @@ impl<
     > Number for T
 {
 }
-
-#[doc(hidden)]
-pub trait Alloc<N: Scalar, R: Dimension, C: Dimension = U1>:
-    Allocator<N, R>
-    + Allocator<N, C>
-    + Allocator<N, U1, R>
-    + Allocator<N, U1, C>
-    + Allocator<N, R, C>
-    + Allocator<N, C, R>
-    + Allocator<N, R, R>
-    + Allocator<N, C, C>
-    + Allocator<bool, R>
-    + Allocator<bool, C>
-    + Allocator<f32, R>
-    + Allocator<f32, C>
-    + Allocator<u32, R>
-    + Allocator<u32, C>
-    + Allocator<i32, R>
-    + Allocator<i32, C>
-    + Allocator<f64, R>
-    + Allocator<f64, C>
-    + Allocator<u64, R>
-    + Allocator<u64, C>
-    + Allocator<i64, R>
-    + Allocator<i64, C>
-    + Allocator<i16, R>
-    + Allocator<i16, C>
-    + Allocator<(usize, usize), R>
-    + Allocator<(usize, usize), C>
-{
-}
-
-impl<N: Scalar, R: Dimension, C: Dimension, T> Alloc<N, R, C> for T where
-    T: Allocator<N, R>
-        + Allocator<N, C>
-        + Allocator<N, U1, R>
-        + Allocator<N, U1, C>
-        + Allocator<N, R, C>
-        + Allocator<N, C, R>
-        + Allocator<N, R, R>
-        + Allocator<N, C, C>
-        + Allocator<bool, R>
-        + Allocator<bool, C>
-        + Allocator<f32, R>
-        + Allocator<f32, C>
-        + Allocator<u32, R>
-        + Allocator<u32, C>
-        + Allocator<i32, R>
-        + Allocator<i32, C>
-        + Allocator<f64, R>
-        + Allocator<f64, C>
-        + Allocator<u64, R>
-        + Allocator<u64, C>
-        + Allocator<i64, R>
-        + Allocator<i64, C>
-        + Allocator<i16, R>
-        + Allocator<i16, C>
-        + Allocator<(usize, usize), R>
-        + Allocator<(usize, usize), C>
-{
-}

nalgebra-glm/src/trigonometric.rs

@@ -1,124 +1,78 @@
-use na::{self, DefaultAllocator, RealField};
+use na::{self, RealField};
 
 use crate::aliases::TVec;
-use crate::traits::{Alloc, Dimension};
 
 /// Component-wise arc-cosinus.
-pub fn acos<N: RealField, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn acos<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|e| e.acos())
 }
 
 /// Component-wise hyperbolic arc-cosinus.
-pub fn acosh<N: RealField, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn acosh<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|e| e.acosh())
 }
 
 /// Component-wise arc-sinus.
-pub fn asin<N: RealField, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn asin<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|e| e.asin())
 }
 
 /// Component-wise hyperbolic arc-sinus.
-pub fn asinh<N: RealField, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn asinh<T: RealField, 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<N: RealField, D: Dimension>(y: &TVec<N, D>, x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn atan2<T: RealField, 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<N: RealField, D: Dimension>(y_over_x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn atan<T: RealField, 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<N: RealField, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn atanh<T: RealField, const D: usize>(x: &TVec<T, D>) -> TVec<T, D> {
     x.map(|e| e.atanh())
 }
 
 /// Component-wise cosinus.
-pub fn cos<N: RealField, D: Dimension>(angle: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn cos<T: RealField, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
     angle.map(|e| e.cos())
 }
 
 /// Component-wise hyperbolic cosinus.
-pub fn cosh<N: RealField, D: Dimension>(angle: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn cosh<T: RealField, 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<N: RealField, D: Dimension>(radians: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
-    radians.map(|e| e * na::convert(180.0) / N::pi())
+pub fn degrees<T: RealField, 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<N: RealField, D: Dimension>(degrees: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
-    degrees.map(|e| e * N::pi() / na::convert(180.0))
+pub fn radians<T: RealField, 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<N: RealField, D: Dimension>(angle: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn sin<T: RealField, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
     angle.map(|e| e.sin())
 }
 
 /// Component-wise hyperbolic sinus.
-pub fn sinh<N: RealField, D: Dimension>(angle: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn sinh<T: RealField, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
     angle.map(|e| e.sinh())
 }
 
 /// Component-wise tangent.
-pub fn tan<N: RealField, D: Dimension>(angle: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn tan<T: RealField, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
     angle.map(|e| e.tan())
 }
 
 /// Component-wise hyperbolic tangent.
-pub fn tanh<N: RealField, D: Dimension>(angle: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn tanh<T: RealField, const D: usize>(angle: &TVec<T, D>) -> TVec<T, D> {
     angle.map(|e| e.tanh())
 }

nalgebra-glm/src/vector_relational.rs

@@ -1,7 +1,5 @@
-use na::DefaultAllocator;
-
 use crate::aliases::TVec;
-use crate::traits::{Alloc, Dimension, Number};
+use crate::traits::Number;
 
 /// Checks that all the vector components are `true`.
 ///
@@ -20,10 +18,7 @@ use crate::traits::{Alloc, Dimension, Number};
 ///
 /// * [`any`](fn.any.html)
 /// * [`not`](fn.not.html)
-pub fn all<D: Dimension>(v: &TVec<bool, D>) -> bool
-where
-    DefaultAllocator: Alloc<bool, D>,
-{
+pub fn all<const D: usize>(v: &TVec<bool, D>) -> bool {
     v.iter().all(|x| *x)
 }
 
@@ -47,10 +42,7 @@ where
 ///
 /// * [`all`](fn.all.html)
 /// * [`not`](fn.not.html)
-pub fn any<D: Dimension>(v: &TVec<bool, D>) -> bool
-where
-    DefaultAllocator: Alloc<bool, D>,
-{
+pub fn any<const D: usize>(v: &TVec<bool, D>) -> bool {
     v.iter().any(|x| *x)
 }
 
@@ -73,10 +65,7 @@ where
 /// * [`less_than_equal`](fn.less_than_equal.html)
 /// * [`not`](fn.not.html)
 /// * [`not_equal`](fn.not_equal.html)
-pub fn equal<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn equal<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<bool, D> {
     x.zip_map(y, |x, y| x == y)
 }
 
@@ -99,10 +88,7 @@ where
 /// * [`less_than_equal`](fn.less_than_equal.html)
 /// * [`not`](fn.not.html)
 /// * [`not_equal`](fn.not_equal.html)
-pub fn greater_than<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn greater_than<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<bool, D> {
     x.zip_map(y, |x, y| x > y)
 }
 
@@ -125,10 +111,10 @@ where
 /// * [`less_than_equal`](fn.less_than_equal.html)
 /// * [`not`](fn.not.html)
 /// * [`not_equal`](fn.not_equal.html)
-pub fn greater_than_equal<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn greater_than_equal<T: Number, const D: usize>(
+    x: &TVec<T, D>,
+    y: &TVec<T, D>,
+) -> TVec<bool, D> {
     x.zip_map(y, |x, y| x >= y)
 }
 
@@ -151,10 +137,7 @@ where
 /// * [`less_than_equal`](fn.less_than_equal.html)
 /// * [`not`](fn.not.html)
 /// * [`not_equal`](fn.not_equal.html)
-pub fn less_than<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn less_than<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<bool, D> {
     x.zip_map(y, |x, y| x < y)
 }
 
@@ -177,10 +160,7 @@ where
 /// * [`less_than`](fn.less_than.html)
 /// * [`not`](fn.not.html)
 /// * [`not_equal`](fn.not_equal.html)
-pub fn less_than_equal<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn less_than_equal<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<bool, D> {
     x.zip_map(y, |x, y| x <= y)
 }
 
@@ -204,10 +184,7 @@ where
 /// * [`less_than`](fn.less_than.html)
 /// * [`less_than_equal`](fn.less_than_equal.html)
 /// * [`not_equal`](fn.not_equal.html)
-pub fn not<D: Dimension>(v: &TVec<bool, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<bool, D>,
-{
+pub fn not<const D: usize>(v: &TVec<bool, D>) -> TVec<bool, D> {
     v.map(|x| !x)
 }
 
@@ -230,9 +207,6 @@ where
 /// * [`less_than`](fn.less_than.html)
 /// * [`less_than_equal`](fn.less_than_equal.html)
 /// * [`not`](fn.not.html)
-pub fn not_equal<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+pub fn not_equal<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>) -> TVec<bool, D> {
     x.zip_map(y, |x, y| x != y)
 }

nalgebra-lapack/src/cholesky.rs

@@ -7,7 +7,7 @@ use num_complex::Complex;
 use na::allocator::Allocator;
 use na::dimension::Dim;
 use na::storage::Storage;
-use na::{DefaultAllocator, Matrix, MatrixMN, MatrixN, Scalar};
+use na::{DefaultAllocator, Matrix, OMatrix, Scalar};
 
 use lapack;
 
@@ -15,39 +15,39 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<N, D>,
-         MatrixN<N, D>: Serialize"))
+    serde(bound(serialize = "DefaultAllocator: Allocator<T, D>,
+         OMatrix<T, D, D>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(deserialize = "DefaultAllocator: Allocator<N, D>,
-         MatrixN<N, D>: Deserialize<'de>"))
+    serde(bound(deserialize = "DefaultAllocator: Allocator<T, D>,
+         OMatrix<T, D, D>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
-pub struct Cholesky<N: Scalar, D: Dim>
+pub struct Cholesky<T: Scalar, D: Dim>
 where
-    DefaultAllocator: Allocator<N, D, D>,
+    DefaultAllocator: Allocator<T, D, D>,
 {
-    l: MatrixN<N, D>,
+    l: OMatrix<T, D, D>,
 }
 
-impl<N: Scalar + Copy, D: Dim> Copy for Cholesky<N, D>
+impl<T: Scalar + Copy, D: Dim> Copy for Cholesky<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D>,
-    MatrixN<N, D>: Copy,
+    DefaultAllocator: Allocator<T, D, D>,
+    OMatrix<T, D, D>: Copy,
 {
 }
 
-impl<N: CholeskyScalar + Zero, D: Dim> Cholesky<N, D>
+impl<T: CholeskyScalar + Zero, D: Dim> Cholesky<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D>,
+    DefaultAllocator: Allocator<T, D, D>,
 {
     /// Computes the cholesky decomposition of the given symmetric-definite-positive square
     /// matrix.
     ///
     /// Only the lower-triangular part of the input matrix is considered.
     #[inline]
-    pub fn new(mut m: MatrixN<N, D>) -> Option<Self> {
+    pub fn new(mut m: OMatrix<T, D, D>) -> Option<Self> {
         // TODO: check symmetry as well?
         assert!(
             m.is_square(),
@@ -58,14 +58,14 @@ where
         let dim = m.nrows() as i32;
         let mut info = 0;
 
-        N::xpotrf(uplo, dim, m.as_mut_slice(), dim, &mut info);
+        T::xpotrf(uplo, dim, m.as_mut_slice(), dim, &mut info);
         lapack_check!(info);
 
         Some(Self { l: m })
     }
 
     /// Retrieves the lower-triangular factor of the cholesky decomposition.
-    pub fn unpack(mut self) -> MatrixN<N, D> {
+    pub fn unpack(mut self) -> OMatrix<T, D, D> {
         self.l.fill_upper_triangle(Zero::zero(), 1);
         self.l
     }
@@ -75,12 +75,12 @@ where
     ///
     /// This is an allocation-less version of `self.l()`. The values of the strict upper-triangular
     /// part are garbage and should be ignored by further computations.
-    pub fn unpack_dirty(self) -> MatrixN<N, D> {
+    pub fn unpack_dirty(self) -> OMatrix<T, D, D> {
         self.l
     }
 
     /// Retrieves the lower-triangular factor of the cholesky decomposition.
-    pub fn l(&self) -> MatrixN<N, D> {
+    pub fn l(&self) -> OMatrix<T, D, D> {
         let mut res = self.l.clone();
         res.fill_upper_triangle(Zero::zero(), 1);
         res
@@ -91,7 +91,7 @@ where
     ///
     /// This is an allocation-less version of `self.l()`. The values of the strict upper-triangular
     /// part are garbage and should be ignored by further computations.
-    pub fn l_dirty(&self) -> &MatrixN<N, D> {
+    pub fn l_dirty(&self) -> &OMatrix<T, D, D> {
         &self.l
     }
 
@@ -99,11 +99,11 @@ where
     /// unknown to be determined.
     pub fn solve<R2: Dim, C2: Dim, S2>(
         &self,
-        b: &Matrix<N, R2, C2, S2>,
-    ) -> Option<MatrixMN<N, R2, C2>>
+        b: &Matrix<T, R2, C2, S2>,
+    ) -> Option<OMatrix<T, R2, C2>>
     where
-        S2: Storage<N, R2, C2>,
-        DefaultAllocator: Allocator<N, R2, C2>,
+        S2: Storage<T, R2, C2>,
+        DefaultAllocator: Allocator<T, R2, C2>,
     {
         let mut res = b.clone_owned();
         if self.solve_mut(&mut res) {
@@ -115,9 +115,9 @@ where
 
     /// Solves in-place the symmetric-definite-positive linear system `self * x = b`, where `x` is
     /// the unknown to be determined.
-    pub fn solve_mut<R2: Dim, C2: Dim>(&self, b: &mut MatrixMN<N, R2, C2>) -> bool
+    pub fn solve_mut<R2: Dim, C2: Dim>(&self, b: &mut OMatrix<T, R2, C2>) -> bool
     where
-        DefaultAllocator: Allocator<N, R2, C2>,
+        DefaultAllocator: Allocator<T, R2, C2>,
     {
         let dim = self.l.nrows();
 
@@ -131,7 +131,7 @@ where
         let ldb = dim as i32;
         let mut info = 0;
 
-        N::xpotrs(
+        T::xpotrs(
             b'L',
             dim as i32,
             nrhs,
@@ -145,11 +145,11 @@ where
     }
 
     /// Computes the inverse of the decomposed matrix.
-    pub fn inverse(mut self) -> Option<MatrixN<N, D>> {
+    pub fn inverse(mut self) -> Option<OMatrix<T, D, D>> {
         let dim = self.l.nrows();
         let mut info = 0;
 
-        N::xpotri(
+        T::xpotri(
             b'L',
             dim as i32,
             self.l.as_mut_slice(),

nalgebra-lapack/src/eigen.rs

@@ -10,7 +10,7 @@ use crate::ComplexHelper;
 use na::allocator::Allocator;
 use na::dimension::{Dim, U1};
 use na::storage::Storage;
-use na::{DefaultAllocator, Matrix, MatrixN, Scalar, VectorN};
+use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
 
@@ -19,59 +19,59 @@ use lapack;
 #[cfg_attr(
     feature = "serde-serialize",
     serde(
-        bound(serialize = "DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
-         VectorN<N, D>: Serialize,
-         MatrixN<N, D>: Serialize")
+        bound(serialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+         OVector<T, D>: Serialize,
+         OMatrix<T, D, D>: Serialize")
     )
 )]
 #[cfg_attr(
     feature = "serde-serialize",
     serde(
-        bound(deserialize = "DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
-         VectorN<N, D>: Serialize,
-         MatrixN<N, D>: Deserialize<'de>")
+        bound(deserialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+         OVector<T, D>: Serialize,
+         OMatrix<T, D, D>: Deserialize<'de>")
     )
 )]
 #[derive(Clone, Debug)]
-pub struct Eigen<N: Scalar, D: Dim>
+pub struct Eigen<T: Scalar, D: Dim>
 where
-    DefaultAllocator: Allocator<N, D> + Allocator<N, D, D>,
+    DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
 {
     /// The eigenvalues of the decomposed matrix.
-    pub eigenvalues: VectorN<N, D>,
+    pub eigenvalues: OVector<T, D>,
     /// The (right) eigenvectors of the decomposed matrix.
-    pub eigenvectors: Option<MatrixN<N, D>>,
+    pub eigenvectors: Option<OMatrix<T, D, D>>,
     /// The left eigenvectors of the decomposed matrix.
-    pub left_eigenvectors: Option<MatrixN<N, D>>,
+    pub left_eigenvectors: Option<OMatrix<T, D, D>>,
 }
 
-impl<N: Scalar + Copy, D: Dim> Copy for Eigen<N, D>
+impl<T: Scalar + Copy, D: Dim> Copy for Eigen<T, D>
 where
-    DefaultAllocator: Allocator<N, D> + Allocator<N, D, D>,
-    VectorN<N, D>: Copy,
-    MatrixN<N, D>: Copy,
+    DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
+    OVector<T, D>: Copy,
+    OMatrix<T, D, D>: Copy,
 {
 }
 
-impl<N: EigenScalar + RealField, D: Dim> Eigen<N, D>
+impl<T: EigenScalar + RealField, D: Dim> Eigen<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
+    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
 {
     /// Computes the eigenvalues and eigenvectors of the square matrix `m`.
     ///
     /// If `eigenvectors` is `false` then, the eigenvectors are not computed explicitly.
     pub fn new(
-        mut m: MatrixN<N, D>,
+        mut m: OMatrix<T, D, D>,
         left_eigenvectors: bool,
         eigenvectors: bool,
-    ) -> Option<Eigen<N, D>> {
+    ) -> Option<Eigen<T, D>> {
         assert!(
             m.is_square(),
             "Unable to compute the eigenvalue decomposition of a non-square matrix."
         );
 
-        let ljob = if left_eigenvectors { b'V' } else { b'N' };
-        let rjob = if eigenvectors { b'V' } else { b'N' };
+        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 n = nrows.value();
@@ -83,10 +83,10 @@ where
         let mut wi = unsafe { Matrix::new_uninitialized_generic(nrows, U1).assume_init() };
 
         let mut info = 0;
-        let mut placeholder1 = [N::zero()];
-        let mut placeholder2 = [N::zero()];
+        let mut placeholder1 = [T::zero()];
+        let mut placeholder2 = [T::zero()];
 
-        let lwork = N::xgeev_work_size(
+        let lwork = T::xgeev_work_size(
             ljob,
             rjob,
             n as i32,
@@ -112,7 +112,7 @@ where
                 let mut vr =
                     unsafe { Matrix::new_uninitialized_generic(nrows, ncols).assume_init() };
 
-                N::xgeev(
+                T::xgeev(
                     ljob,
                     rjob,
                     n as i32,
@@ -142,7 +142,7 @@ where
                 let mut vl =
                     unsafe { Matrix::new_uninitialized_generic(nrows, ncols).assume_init() };
 
-                N::xgeev(
+                T::xgeev(
                     ljob,
                     rjob,
                     n as i32,
@@ -172,7 +172,7 @@ where
                 let mut vr =
                     unsafe { Matrix::new_uninitialized_generic(nrows, ncols).assume_init() };
 
-                N::xgeev(
+                T::xgeev(
                     ljob,
                     rjob,
                     n as i32,
@@ -199,7 +199,7 @@ where
                 }
             }
             (false, false) => {
-                N::xgeev(
+                T::xgeev(
                     ljob,
                     rjob,
                     n as i32,
@@ -233,9 +233,9 @@ where
     /// The complex eigenvalues of the given matrix.
     ///
     /// Panics if the eigenvalue computation does not converge.
-    pub fn complex_eigenvalues(mut m: MatrixN<N, D>) -> VectorN<Complex<N>, D>
+    pub fn complex_eigenvalues(mut m: OMatrix<T, D, D>) -> OVector<Complex<T>, D>
     where
-        DefaultAllocator: Allocator<Complex<N>, D>,
+        DefaultAllocator: Allocator<Complex<T>, D>,
     {
         assert!(
             m.is_square(),
@@ -251,12 +251,12 @@ where
         let mut wi = unsafe { Matrix::new_uninitialized_generic(nrows, U1).assume_init() };
 
         let mut info = 0;
-        let mut placeholder1 = [N::zero()];
-        let mut placeholder2 = [N::zero()];
+        let mut placeholder1 = [T::zero()];
+        let mut placeholder2 = [T::zero()];
 
-        let lwork = N::xgeev_work_size(
-            b'N',
-            b'N',
+        let lwork = T::xgeev_work_size(
+            b'T',
+            b'T',
             n as i32,
             m.as_mut_slice(),
             lda,
@@ -273,9 +273,9 @@ where
 
         let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
 
-        N::xgeev(
-            b'N',
-            b'N',
+        T::xgeev(
+            b'T',
+            b'T',
             n as i32,
             m.as_mut_slice(),
             lda,
@@ -302,8 +302,8 @@ where
 
     /// The determinant of the decomposed matrix.
     #[inline]
-    pub fn determinant(&self) -> N {
-        let mut det = N::one();
+    pub fn determinant(&self) -> T {
+        let mut det = T::one();
         for e in self.eigenvalues.iter() {
             det *= *e;
         }

nalgebra-lapack/src/hessenberg.rs

@@ -5,7 +5,7 @@ use crate::ComplexHelper;
 use na::allocator::Allocator;
 use na::dimension::{DimDiff, DimSub, U1};
 use na::storage::Storage;
-use na::{DefaultAllocator, Matrix, MatrixN, Scalar, VectorN};
+use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
 
@@ -13,41 +13,41 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<N, D, D> +
-                           Allocator<N, DimDiff<D, U1>>,
-         MatrixN<N, D>: Serialize,
-         VectorN<N, DimDiff<D, U1>>: Serialize"))
+    serde(bound(serialize = "DefaultAllocator: Allocator<T, D, D> +
+                           Allocator<T, DimDiff<D, U1>>,
+         OMatrix<T, D, D>: Serialize,
+         OVector<T, DimDiff<D, U1>>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(deserialize = "DefaultAllocator: Allocator<N, D, D> +
-                           Allocator<N, DimDiff<D, U1>>,
-         MatrixN<N, D>: Deserialize<'de>,
-         VectorN<N, DimDiff<D, U1>>: Deserialize<'de>"))
+    serde(bound(deserialize = "DefaultAllocator: Allocator<T, D, D> +
+                           Allocator<T, DimDiff<D, U1>>,
+         OMatrix<T, D, D>: Deserialize<'de>,
+         OVector<T, DimDiff<D, U1>>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
-pub struct Hessenberg<N: Scalar, D: DimSub<U1>>
+pub struct Hessenberg<T: Scalar, D: DimSub<U1>>
 where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
+    DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
 {
-    h: MatrixN<N, D>,
-    tau: VectorN<N, DimDiff<D, U1>>,
+    h: OMatrix<T, D, D>,
+    tau: OVector<T, DimDiff<D, U1>>,
 }
 
-impl<N: Scalar + Copy, D: DimSub<U1>> Copy for Hessenberg<N, D>
+impl<T: Scalar + Copy, D: DimSub<U1>> Copy for Hessenberg<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
-    MatrixN<N, D>: Copy,
-    VectorN<N, DimDiff<D, U1>>: Copy,
+    DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
+    OMatrix<T, D, D>: Copy,
+    OVector<T, DimDiff<D, U1>>: Copy,
 {
 }
 
-impl<N: HessenbergScalar + Zero, D: DimSub<U1>> Hessenberg<N, D>
+impl<T: HessenbergScalar + Zero, D: DimSub<U1>> Hessenberg<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
+    DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
 {
     /// Computes the hessenberg decomposition of the matrix `m`.
-    pub fn new(mut m: MatrixN<N, D>) -> Self {
+    pub fn new(mut m: OMatrix<T, D, D>) -> Self {
         let nrows = m.data.shape().0;
         let n = nrows.value() as i32;
 
@@ -64,12 +64,12 @@ where
 
         let mut info = 0;
         let lwork =
-            N::xgehrd_work_size(n, 1, n, m.as_mut_slice(), n, tau.as_mut_slice(), &mut info);
+            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) };
 
         lapack_panic!(info);
 
-        N::xgehrd(
+        T::xgehrd(
             n,
             1,
             n,
@@ -87,36 +87,36 @@ where
 
     /// Computes the hessenberg matrix of this decomposition.
     #[inline]
-    pub fn h(&self) -> MatrixN<N, D> {
+    pub fn h(&self) -> OMatrix<T, D, D> {
         let mut h = self.h.clone_owned();
-        h.fill_lower_triangle(N::zero(), 2);
+        h.fill_lower_triangle(T::zero(), 2);
 
         h
     }
 }
 
-impl<N: HessenbergReal + Zero, D: DimSub<U1>> Hessenberg<N, D>
+impl<T: HessenbergReal + Zero, D: DimSub<U1>> Hessenberg<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
+    DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
 {
     /// Computes the matrices `(Q, H)` of this decomposition.
     #[inline]
-    pub fn unpack(self) -> (MatrixN<N, D>, MatrixN<N, D>) {
+    pub fn unpack(self) -> (OMatrix<T, D, D>, OMatrix<T, D, D>) {
         (self.q(), self.h())
     }
 
     /// Computes the unitary matrix `Q` of this decomposition.
     #[inline]
-    pub fn q(&self) -> MatrixN<N, D> {
+    pub fn q(&self) -> OMatrix<T, D, D> {
         let n = self.h.nrows() as i32;
         let mut q = self.h.clone_owned();
         let mut info = 0;
 
         let lwork =
-            N::xorghr_work_size(n, 1, n, q.as_mut_slice(), n, self.tau.as_slice(), &mut info);
-        let mut work = vec![N::zero(); lwork as usize];
+            T::xorghr_work_size(n, 1, n, q.as_mut_slice(), n, self.tau.as_slice(), &mut info);
+        let mut work = vec![T::zero(); lwork as usize];
 
-        N::xorghr(
+        T::xorghr(
             n,
             1,
             n,

nalgebra-lapack/src/lu.rs

@@ -5,7 +5,7 @@ use crate::ComplexHelper;
 use na::allocator::Allocator;
 use na::dimension::{Dim, DimMin, DimMinimum, U1};
 use na::storage::Storage;
-use na::{DefaultAllocator, Matrix, MatrixMN, MatrixN, Scalar, VectorN};
+use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
 
@@ -20,57 +20,57 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<N, R, C> +
+    serde(bound(serialize = "DefaultAllocator: Allocator<T, R, C> +
                            Allocator<i32, DimMinimum<R, C>>,
-         MatrixMN<N, R, C>: Serialize,
+         OMatrix<T, R, C>: Serialize,
          PermutationSequence<DimMinimum<R, C>>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(deserialize = "DefaultAllocator: Allocator<N, R, C> +
+    serde(bound(deserialize = "DefaultAllocator: Allocator<T, R, C> +
                            Allocator<i32, DimMinimum<R, C>>,
-         MatrixMN<N, R, C>: Deserialize<'de>,
+         OMatrix<T, R, C>: Deserialize<'de>,
          PermutationSequence<DimMinimum<R, C>>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
-pub struct LU<N: Scalar, R: DimMin<C>, C: Dim>
+pub struct LU<T: Scalar, R: DimMin<C>, C: Dim>
 where
-    DefaultAllocator: Allocator<i32, DimMinimum<R, C>> + Allocator<N, R, C>,
+    DefaultAllocator: Allocator<i32, DimMinimum<R, C>> + Allocator<T, R, C>,
 {
-    lu: MatrixMN<N, R, C>,
-    p: VectorN<i32, DimMinimum<R, C>>,
+    lu: OMatrix<T, R, C>,
+    p: OVector<i32, DimMinimum<R, C>>,
 }
 
-impl<N: Scalar + Copy, R: DimMin<C>, C: Dim> Copy for LU<N, R, C>
+impl<T: Scalar + Copy, R: DimMin<C>, C: Dim> Copy for LU<T, R, C>
 where
-    DefaultAllocator: Allocator<N, R, C> + Allocator<i32, DimMinimum<R, C>>,
-    MatrixMN<N, R, C>: Copy,
-    VectorN<i32, DimMinimum<R, C>>: Copy,
+    DefaultAllocator: Allocator<T, R, C> + Allocator<i32, DimMinimum<R, C>>,
+    OMatrix<T, R, C>: Copy,
+    OVector<i32, DimMinimum<R, C>>: Copy,
 {
 }
 
-impl<N: LUScalar, R: Dim, C: Dim> LU<N, R, C>
+impl<T: LUScalar, R: Dim, C: Dim> LU<T, R, C>
 where
-    N: Zero + One,
+    T: Zero + One,
     R: DimMin<C>,
-    DefaultAllocator: Allocator<N, R, C>
-        + Allocator<N, R, R>
-        + Allocator<N, R, DimMinimum<R, C>>
-        + Allocator<N, DimMinimum<R, C>, C>
+    DefaultAllocator: Allocator<T, R, C>
+        + Allocator<T, R, R>
+        + Allocator<T, R, DimMinimum<R, C>>
+        + Allocator<T, DimMinimum<R, C>, C>
         + Allocator<i32, DimMinimum<R, C>>,
 {
     /// Computes the LU decomposition with partial (row) pivoting of `matrix`.
-    pub fn new(mut m: MatrixMN<N, R, C>) -> Self {
+    pub fn new(mut m: OMatrix<T, R, C>) -> Self {
         let (nrows, ncols) = m.data.shape();
         let min_nrows_ncols = nrows.min(ncols);
         let nrows = nrows.value() as i32;
         let ncols = ncols.value() as i32;
 
-        let mut ipiv: VectorN<i32, _> = Matrix::zeros_generic(min_nrows_ncols, U1);
+        let mut ipiv: OVector<i32, _> = Matrix::zeros_generic(min_nrows_ncols, U1);
 
         let mut info = 0;
 
-        N::xgetrf(
+        T::xgetrf(
             nrows,
             ncols,
             m.as_mut_slice(),
@@ -85,7 +85,7 @@ where
 
     /// Gets the lower-triangular matrix part of the decomposition.
     #[inline]
-    pub fn l(&self) -> MatrixMN<N, R, DimMinimum<R, C>> {
+    pub fn l(&self) -> OMatrix<T, R, DimMinimum<R, C>> {
         let (nrows, ncols) = self.lu.data.shape();
         let mut res = self.lu.columns_generic(0, nrows.min(ncols)).into_owned();
 
@@ -97,7 +97,7 @@ where
 
     /// Gets the upper-triangular matrix part of the decomposition.
     #[inline]
-    pub fn u(&self) -> MatrixMN<N, DimMinimum<R, C>, C> {
+    pub fn u(&self) -> OMatrix<T, DimMinimum<R, C>, C> {
         let (nrows, ncols) = self.lu.data.shape();
         let mut res = self.lu.rows_generic(0, nrows.min(ncols)).into_owned();
 
@@ -111,7 +111,7 @@ where
     /// Computing the permutation matrix explicitly is costly and usually not necessary.
     /// To permute rows of a matrix or vector, use the method `self.permute(...)` instead.
     #[inline]
-    pub fn p(&self) -> MatrixN<N, R> {
+    pub fn p(&self) -> OMatrix<T, R> {
         let (dim, _) = self.lu.data.shape();
         let mut id = Matrix::identity_generic(dim, dim);
         self.permute(&mut id);
@@ -124,19 +124,19 @@ where
 
     /// Gets the LAPACK permutation indices.
     #[inline]
-    pub fn permutation_indices(&self) -> &VectorN<i32, DimMinimum<R, C>> {
+    pub fn permutation_indices(&self) -> &OVector<i32, DimMinimum<R, C>> {
         &self.p
     }
 
     /// Applies the permutation matrix to a given matrix or vector in-place.
     #[inline]
-    pub fn permute<C2: Dim>(&self, rhs: &mut MatrixMN<N, R, C2>)
+    pub fn permute<C2: Dim>(&self, rhs: &mut OMatrix<T, R, C2>)
     where
-        DefaultAllocator: Allocator<N, R, C2>,
+        DefaultAllocator: Allocator<T, R, C2>,
     {
         let (nrows, ncols) = rhs.shape();
 
-        N::xlaswp(
+        T::xlaswp(
             ncols as i32,
             rhs.as_mut_slice(),
             nrows as i32,
@@ -147,9 +147,9 @@ where
         );
     }
 
-    fn generic_solve_mut<R2: Dim, C2: Dim>(&self, trans: u8, b: &mut MatrixMN<N, R2, C2>) -> bool
+    fn generic_solve_mut<R2: Dim, C2: Dim>(&self, trans: u8, b: &mut OMatrix<T, R2, C2>) -> bool
     where
-        DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2>,
+        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
     {
         let dim = self.lu.nrows();
 
@@ -167,7 +167,7 @@ where
         let ldb = dim as i32;
         let mut info = 0;
 
-        N::xgetrs(
+        T::xgetrs(
             trans,
             dim as i32,
             nrhs,
@@ -184,14 +184,14 @@ where
     /// Solves the linear system `self * x = b`, where `x` is the unknown to be determined.
     pub fn solve<R2: Dim, C2: Dim, S2>(
         &self,
-        b: &Matrix<N, R2, C2, S2>,
-    ) -> Option<MatrixMN<N, R2, C2>>
+        b: &Matrix<T, R2, C2, S2>,
+    ) -> Option<OMatrix<T, R2, C2>>
     where
-        S2: Storage<N, R2, C2>,
-        DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2>,
+        S2: Storage<T, R2, C2>,
+        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
     {
         let mut res = b.clone_owned();
-        if self.generic_solve_mut(b'N', &mut res) {
+        if self.generic_solve_mut(b'T', &mut res) {
             Some(res)
         } else {
             None
@@ -202,11 +202,11 @@ where
     /// determined.
     pub fn solve_transpose<R2: Dim, C2: Dim, S2>(
         &self,
-        b: &Matrix<N, R2, C2, S2>,
-    ) -> Option<MatrixMN<N, R2, C2>>
+        b: &Matrix<T, R2, C2, S2>,
+    ) -> Option<OMatrix<T, R2, C2>>
     where
-        S2: Storage<N, R2, C2>,
-        DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2>,
+        S2: Storage<T, R2, C2>,
+        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
     {
         let mut res = b.clone_owned();
         if self.generic_solve_mut(b'T', &mut res) {
@@ -220,11 +220,11 @@ where
     /// be determined.
     pub fn solve_conjugate_transpose<R2: Dim, C2: Dim, S2>(
         &self,
-        b: &Matrix<N, R2, C2, S2>,
-    ) -> Option<MatrixMN<N, R2, C2>>
+        b: &Matrix<T, R2, C2, S2>,
+    ) -> Option<OMatrix<T, R2, C2>>
     where
-        S2: Storage<N, R2, C2>,
-        DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2>,
+        S2: Storage<T, R2, C2>,
+        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
     {
         let mut res = b.clone_owned();
         if self.generic_solve_mut(b'T', &mut res) {
@@ -237,20 +237,20 @@ where
     /// Solves in-place the linear system `self * x = b`, where `x` is the unknown to be determined.
     ///
     /// Returns `false` if no solution was found (the decomposed matrix is singular).
-    pub fn solve_mut<R2: Dim, C2: Dim>(&self, b: &mut MatrixMN<N, R2, C2>) -> bool
+    pub fn solve_mut<R2: Dim, C2: Dim>(&self, b: &mut OMatrix<T, R2, C2>) -> bool
     where
-        DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2>,
+        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
     {
-        self.generic_solve_mut(b'N', b)
+        self.generic_solve_mut(b'T', b)
     }
 
     /// Solves in-place the linear system `self.transpose() * x = b`, where `x` is the unknown to be
     /// determined.
     ///
     /// Returns `false` if no solution was found (the decomposed matrix is singular).
-    pub fn solve_transpose_mut<R2: Dim, C2: Dim>(&self, b: &mut MatrixMN<N, R2, C2>) -> bool
+    pub fn solve_transpose_mut<R2: Dim, C2: Dim>(&self, b: &mut OMatrix<T, R2, C2>) -> bool
     where
-        DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2>,
+        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
     {
         self.generic_solve_mut(b'T', b)
     }
@@ -259,25 +259,25 @@ where
     /// be determined.
     ///
     /// Returns `false` if no solution was found (the decomposed matrix is singular).
-    pub fn solve_adjoint_mut<R2: Dim, C2: Dim>(&self, b: &mut MatrixMN<N, R2, C2>) -> bool
+    pub fn solve_adjoint_mut<R2: Dim, C2: Dim>(&self, b: &mut OMatrix<T, R2, C2>) -> bool
     where
-        DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2>,
+        DefaultAllocator: Allocator<T, R2, C2> + Allocator<i32, R2>,
     {
         self.generic_solve_mut(b'T', b)
     }
 }
 
-impl<N: LUScalar, D: Dim> LU<N, D, D>
+impl<T: LUScalar, D: Dim> LU<T, D, D>
 where
-    N: Zero + One,
+    T: Zero + One,
     D: DimMin<D, Output = D>,
-    DefaultAllocator: Allocator<N, D, D> + Allocator<i32, D>,
+    DefaultAllocator: Allocator<T, D, D> + Allocator<i32, D>,
 {
     /// Computes the inverse of the decomposed matrix.
-    pub fn inverse(mut self) -> Option<MatrixN<N, D>> {
+    pub fn inverse(mut self) -> Option<OMatrix<T, D, D>> {
         let dim = self.lu.nrows() as i32;
         let mut info = 0;
-        let lwork = N::xgetri_work_size(
+        let lwork = T::xgetri_work_size(
             dim,
             self.lu.as_mut_slice(),
             dim,
@@ -288,7 +288,7 @@ where
 
         let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
 
-        N::xgetri(
+        T::xgetri(
             dim,
             self.lu.as_mut_slice(),
             dim,

nalgebra-lapack/src/qr.rs

@@ -8,7 +8,7 @@ use crate::ComplexHelper;
 use na::allocator::Allocator;
 use na::dimension::{Dim, DimMin, DimMinimum, U1};
 use na::storage::Storage;
-use na::{DefaultAllocator, Matrix, MatrixMN, Scalar, VectorN};
+use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
 
@@ -16,44 +16,44 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<N, R, C> +
-                           Allocator<N, DimMinimum<R, C>>,
-         MatrixMN<N, R, C>: Serialize,
-         VectorN<N, DimMinimum<R, C>>: Serialize"))
+    serde(bound(serialize = "DefaultAllocator: Allocator<T, R, C> +
+                           Allocator<T, DimMinimum<R, C>>,
+         OMatrix<T, R, C>: Serialize,
+         OVector<T, DimMinimum<R, C>>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(deserialize = "DefaultAllocator: Allocator<N, R, C> +
-                           Allocator<N, DimMinimum<R, C>>,
-         MatrixMN<N, R, C>: Deserialize<'de>,
-         VectorN<N, DimMinimum<R, C>>: Deserialize<'de>"))
+    serde(bound(deserialize = "DefaultAllocator: Allocator<T, R, C> +
+                           Allocator<T, DimMinimum<R, C>>,
+         OMatrix<T, R, C>: Deserialize<'de>,
+         OVector<T, DimMinimum<R, C>>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
-pub struct QR<N: Scalar, R: DimMin<C>, C: Dim>
+pub struct QR<T: Scalar, R: DimMin<C>, C: Dim>
 where
-    DefaultAllocator: Allocator<N, R, C> + Allocator<N, DimMinimum<R, C>>,
+    DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>>,
 {
-    qr: MatrixMN<N, R, C>,
-    tau: VectorN<N, DimMinimum<R, C>>,
+    qr: OMatrix<T, R, C>,
+    tau: OVector<T, DimMinimum<R, C>>,
 }
 
-impl<N: Scalar + Copy, R: DimMin<C>, C: Dim> Copy for QR<N, R, C>
+impl<T: Scalar + Copy, R: DimMin<C>, C: Dim> Copy for QR<T, R, C>
 where
-    DefaultAllocator: Allocator<N, R, C> + Allocator<N, DimMinimum<R, C>>,
-    MatrixMN<N, R, C>: Copy,
-    VectorN<N, DimMinimum<R, C>>: Copy,
+    DefaultAllocator: Allocator<T, R, C> + Allocator<T, DimMinimum<R, C>>,
+    OMatrix<T, R, C>: Copy,
+    OVector<T, DimMinimum<R, C>>: Copy,
 {
 }
 
-impl<N: QRScalar + Zero, R: DimMin<C>, C: Dim> QR<N, R, C>
+impl<T: QRScalar + Zero, R: DimMin<C>, C: Dim> QR<T, R, C>
 where
-    DefaultAllocator: Allocator<N, R, C>
-        + Allocator<N, R, DimMinimum<R, C>>
-        + Allocator<N, DimMinimum<R, C>, C>
-        + Allocator<N, DimMinimum<R, C>>,
+    DefaultAllocator: Allocator<T, R, C>
+        + Allocator<T, R, DimMinimum<R, C>>
+        + Allocator<T, DimMinimum<R, C>, C>
+        + Allocator<T, DimMinimum<R, C>>,
 {
     /// Computes the QR decomposition of the matrix `m`.
-    pub fn new(mut m: MatrixMN<N, R, C>) -> Self {
+    pub fn new(mut m: OMatrix<T, R, C>) -> Self {
         let (nrows, ncols) = m.data.shape();
 
         let mut info = 0;
@@ -64,7 +64,7 @@ where
             return Self { qr: m, tau: tau };
         }
 
-        let lwork = N::xgeqrf_work_size(
+        let lwork = T::xgeqrf_work_size(
             nrows.value() as i32,
             ncols.value() as i32,
             m.as_mut_slice(),
@@ -75,7 +75,7 @@ where
 
         let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
 
-        N::xgeqrf(
+        T::xgeqrf(
             nrows.value() as i32,
             ncols.value() as i32,
             m.as_mut_slice(),
@@ -91,37 +91,37 @@ where
 
     /// Retrieves the upper trapezoidal submatrix `R` of this decomposition.
     #[inline]
-    pub fn r(&self) -> MatrixMN<N, DimMinimum<R, C>, C> {
+    pub fn r(&self) -> OMatrix<T, DimMinimum<R, C>, C> {
         let (nrows, ncols) = self.qr.data.shape();
         self.qr.rows_generic(0, nrows.min(ncols)).upper_triangle()
     }
 }
 
-impl<N: QRReal + Zero, R: DimMin<C>, C: Dim> QR<N, R, C>
+impl<T: QRReal + Zero, R: DimMin<C>, C: Dim> QR<T, R, C>
 where
-    DefaultAllocator: Allocator<N, R, C>
-        + Allocator<N, R, DimMinimum<R, C>>
-        + Allocator<N, DimMinimum<R, C>, C>
-        + Allocator<N, DimMinimum<R, C>>,
+    DefaultAllocator: Allocator<T, R, C>
+        + Allocator<T, R, DimMinimum<R, C>>
+        + Allocator<T, DimMinimum<R, C>, C>
+        + Allocator<T, DimMinimum<R, C>>,
 {
     /// Retrieves the matrices `(Q, R)` of this decompositions.
     pub fn unpack(
         self,
     ) -> (
-        MatrixMN<N, R, DimMinimum<R, C>>,
-        MatrixMN<N, DimMinimum<R, C>, C>,
+        OMatrix<T, R, DimMinimum<R, C>>,
+        OMatrix<T, DimMinimum<R, C>, C>,
     ) {
         (self.q(), self.r())
     }
 
     /// Computes the orthogonal matrix `Q` of this decomposition.
     #[inline]
-    pub fn q(&self) -> MatrixMN<N, R, DimMinimum<R, C>> {
+    pub fn q(&self) -> OMatrix<T, R, DimMinimum<R, C>> {
         let (nrows, ncols) = self.qr.data.shape();
         let min_nrows_ncols = nrows.min(ncols);
 
         if min_nrows_ncols.value() == 0 {
-            return MatrixMN::from_element_generic(nrows, min_nrows_ncols, N::zero());
+            return OMatrix::from_element_generic(nrows, min_nrows_ncols, T::zero());
         }
 
         let mut q = self
@@ -132,7 +132,7 @@ where
         let mut info = 0;
         let nrows = nrows.value() as i32;
 
-        let lwork = N::xorgqr_work_size(
+        let lwork = T::xorgqr_work_size(
             nrows,
             min_nrows_ncols.value() as i32,
             self.tau.len() as i32,
@@ -142,9 +142,9 @@ where
             &mut info,
         );
 
-        let mut work = vec![N::zero(); lwork as usize];
+        let mut work = vec![T::zero(); lwork as usize];
 
-        N::xorgqr(
+        T::xorgqr(
             nrows,
             min_nrows_ncols.value() as i32,
             self.tau.len() as i32,

nalgebra-lapack/src/schur.rs

@@ -10,7 +10,7 @@ use crate::ComplexHelper;
 use na::allocator::Allocator;
 use na::dimension::{Dim, U1};
 use na::storage::Storage;
-use na::{DefaultAllocator, Matrix, MatrixN, Scalar, VectorN};
+use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
 
@@ -19,53 +19,53 @@ use lapack;
 #[cfg_attr(
     feature = "serde-serialize",
     serde(
-        bound(serialize = "DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
-         VectorN<N, D>: Serialize,
-         MatrixN<N, D>: Serialize")
+        bound(serialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+         OVector<T, D>: Serialize,
+         OMatrix<T, D, D>: Serialize")
     )
 )]
 #[cfg_attr(
     feature = "serde-serialize",
     serde(
-        bound(deserialize = "DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
-         VectorN<N, D>: Serialize,
-         MatrixN<N, D>: Deserialize<'de>")
+        bound(deserialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+         OVector<T, D>: Serialize,
+         OMatrix<T, D, D>: Deserialize<'de>")
     )
 )]
 #[derive(Clone, Debug)]
-pub struct Schur<N: Scalar, D: Dim>
+pub struct Schur<T: Scalar, D: Dim>
 where
-    DefaultAllocator: Allocator<N, D> + Allocator<N, D, D>,
+    DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
 {
-    re: VectorN<N, D>,
-    im: VectorN<N, D>,
-    t: MatrixN<N, D>,
-    q: MatrixN<N, D>,
+    re: OVector<T, D>,
+    im: OVector<T, D>,
+    t: OMatrix<T, D, D>,
+    q: OMatrix<T, D, D>,
 }
 
-impl<N: Scalar + Copy, D: Dim> Copy for Schur<N, D>
+impl<T: Scalar + Copy, D: Dim> Copy for Schur<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
-    MatrixN<N, D>: Copy,
-    VectorN<N, D>: Copy,
+    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    OMatrix<T, D, D>: Copy,
+    OVector<T, D>: Copy,
 {
 }
 
-impl<N: SchurScalar + RealField, D: Dim> Schur<N, D>
+impl<T: SchurScalar + RealField, D: Dim> Schur<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
+    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
 {
     /// Computes the eigenvalues and real Schur form of the matrix `m`.
     ///
     /// Panics if the method did not converge.
-    pub fn new(m: MatrixN<N, D>) -> Self {
+    pub fn new(m: OMatrix<T, D, D>) -> Self {
         Self::try_new(m).expect("Schur decomposition: convergence failed.")
     }
 
     /// Computes the eigenvalues and real Schur form of the matrix `m`.
     ///
     /// Returns `None` if the method did not converge.
-    pub fn try_new(mut m: MatrixN<N, D>) -> Option<Self> {
+    pub fn try_new(mut m: OMatrix<T, D, D>) -> Option<Self> {
         assert!(
             m.is_square(),
             "Unable to compute the eigenvalue decomposition of a non-square matrix."
@@ -85,9 +85,9 @@ where
         let mut bwork = [0i32];
         let mut unused = 0;
 
-        let lwork = N::xgees_work_size(
+        let lwork = T::xgees_work_size(
             b'V',
-            b'N',
+            b'T',
             n as i32,
             m.as_mut_slice(),
             lda,
@@ -103,9 +103,9 @@ where
 
         let mut work = unsafe { crate::uninitialized_vec(lwork as usize) };
 
-        N::xgees(
+        T::xgees(
             b'V',
-            b'N',
+            b'T',
             n as i32,
             m.as_mut_slice(),
             lda,
@@ -131,14 +131,14 @@ where
 
     /// Retrieves the unitary matrix `Q` and the upper-quasitriangular matrix `T` such that the
     /// decomposed matrix equals `Q * T * Q.transpose()`.
-    pub fn unpack(self) -> (MatrixN<N, D>, MatrixN<N, D>) {
+    pub fn unpack(self) -> (OMatrix<T, D, D>, OMatrix<T, D, D>) {
         (self.q, self.t)
     }
 
     /// Computes the real eigenvalues of the decomposed matrix.
     ///
     /// Return `None` if some eigenvalues are complex.
-    pub fn eigenvalues(&self) -> Option<VectorN<N, D>> {
+    pub fn eigenvalues(&self) -> Option<OVector<T, D>> {
         if self.im.iter().all(|e| e.is_zero()) {
             Some(self.re.clone())
         } else {
@@ -147,12 +147,12 @@ where
     }
 
     /// Computes the complex eigenvalues of the decomposed matrix.
-    pub fn complex_eigenvalues(&self) -> VectorN<Complex<N>, D>
+    pub fn complex_eigenvalues(&self) -> OVector<Complex<T>, D>
     where
-        DefaultAllocator: Allocator<Complex<N>, D>,
+        DefaultAllocator: Allocator<Complex<T>, D>,
     {
         let mut out =
-            unsafe { VectorN::new_uninitialized_generic(self.t.data.shape().0, U1).assume_init() };
+            unsafe { OVector::new_uninitialized_generic(self.t.data.shape().0, U1).assume_init() };
 
         for i in 0..out.len() {
             out[i] = Complex::new(self.re[i], self.im[i])

nalgebra-lapack/src/svd.rs

@@ -7,7 +7,7 @@ use std::cmp;
 use na::allocator::Allocator;
 use na::dimension::{Dim, DimMin, DimMinimum, U1};
 use na::storage::Storage;
-use na::{DefaultAllocator, Matrix, MatrixMN, MatrixN, Scalar, VectorN};
+use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
 
@@ -15,41 +15,41 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<N, DimMinimum<R, C>> +
-                           Allocator<N, R, R> +
-                           Allocator<N, C, C>,
-         MatrixN<N, R>: Serialize,
-         MatrixN<N, C>: Serialize,
-         VectorN<N, DimMinimum<R, C>>: Serialize"))
+    serde(bound(serialize = "DefaultAllocator: Allocator<T, DimMinimum<R, C>> +
+                           Allocator<T, R, R> +
+                           Allocator<T, C, C>,
+         OMatrix<T, R>: Serialize,
+         OMatrix<T, C>: Serialize,
+         OVector<T, DimMinimum<R, C>>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<N, DimMinimum<R, C>> +
-                           Allocator<N, R, R> +
-                           Allocator<N, C, C>,
-         MatrixN<N, R>: Deserialize<'de>,
-         MatrixN<N, C>: Deserialize<'de>,
-         VectorN<N, DimMinimum<R, C>>: Deserialize<'de>"))
+    serde(bound(serialize = "DefaultAllocator: Allocator<T, DimMinimum<R, C>> +
+                           Allocator<T, R, R> +
+                           Allocator<T, C, C>,
+         OMatrix<T, R>: Deserialize<'de>,
+         OMatrix<T, C>: Deserialize<'de>,
+         OVector<T, DimMinimum<R, C>>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
-pub struct SVD<N: Scalar, R: DimMin<C>, C: Dim>
+pub struct SVD<T: Scalar, R: DimMin<C>, C: Dim>
 where
-    DefaultAllocator: Allocator<N, R, R> + Allocator<N, DimMinimum<R, C>> + Allocator<N, C, C>,
+    DefaultAllocator: Allocator<T, R, R> + Allocator<T, DimMinimum<R, C>> + Allocator<T, C, C>,
 {
     /// The left-singular vectors `U` of this SVD.
-    pub u: MatrixN<N, R>, // TODO: should be MatrixMN<N, R, DimMinimum<R, C>>
+    pub u: OMatrix<T, R>, // TODO: should be OMatrix<T, R, DimMinimum<R, C>>
     /// The right-singular vectors `V^t` of this SVD.
-    pub vt: MatrixN<N, C>, // TODO: should be MatrixMN<N, DimMinimum<R, C>, C>
+    pub vt: OMatrix<T, C>, // TODO: should be OMatrix<T, DimMinimum<R, C>, C>
     /// The singular values of this SVD.
-    pub singular_values: VectorN<N, DimMinimum<R, C>>,
+    pub singular_values: OVector<T, DimMinimum<R, C>>,
 }
 
-impl<N: Scalar + Copy, R: DimMin<C>, C: Dim> Copy for SVD<N, R, C>
+impl<T: Scalar + Copy, R: DimMin<C>, C: Dim> Copy for SVD<T, R, C>
 where
-    DefaultAllocator: Allocator<N, C, C> + Allocator<N, R, R> + Allocator<N, DimMinimum<R, C>>,
-    MatrixMN<N, R, R>: Copy,
-    MatrixMN<N, C, C>: Copy,
-    VectorN<N, DimMinimum<R, C>>: Copy,
+    DefaultAllocator: Allocator<T, C, C> + Allocator<T, R, R> + Allocator<T, DimMinimum<R, C>>,
+    OMatrix<T, R, R>: Copy,
+    OMatrix<T, C, C>: Copy,
+    OVector<T, DimMinimum<R, C>>: Copy,
 {
 }
 
@@ -63,19 +63,19 @@ where
         + Allocator<Self, C, C>,
 {
     /// Computes the SVD decomposition of `m`.
-    fn compute(m: MatrixMN<Self, R, C>) -> Option<SVD<Self, R, C>>;
+    fn compute(m: OMatrix<Self, R, C>) -> Option<SVD<Self, R, C>>;
 }
 
-impl<N: SVDScalar<R, C>, R: DimMin<C>, C: Dim> SVD<N, R, C>
+impl<T: SVDScalar<R, C>, R: DimMin<C>, C: Dim> SVD<T, R, C>
 where
-    DefaultAllocator: Allocator<N, R, R>
-        + Allocator<N, R, C>
-        + Allocator<N, DimMinimum<R, C>>
-        + Allocator<N, C, C>,
+    DefaultAllocator: Allocator<T, R, R>
+        + Allocator<T, R, C>
+        + Allocator<T, DimMinimum<R, C>>
+        + Allocator<T, C, C>,
 {
     /// Computes the Singular Value Decomposition of `matrix`.
-    pub fn new(m: MatrixMN<N, R, C>) -> Option<Self> {
-        N::compute(m)
+    pub fn new(m: OMatrix<T, R, C>) -> Option<Self> {
+        T::compute(m)
     }
 }
 
@@ -88,7 +88,7 @@ macro_rules! svd_impl(
                                         Allocator<$t, C, C> +
                                         Allocator<$t, DimMinimum<R, C>> {
 
-            fn compute(mut m: MatrixMN<$t, R, C>) -> Option<SVD<$t, R, C>> {
+            fn compute(mut m: OMatrix<$t, R, C>) -> Option<SVD<$t, R, C>> {
                 let (nrows, ncols) = m.data.shape();
 
                 if nrows.value() == 0 || ncols.value() == 0 {
@@ -150,12 +150,12 @@ macro_rules! svd_impl(
             /// Useful if some components (e.g. some singular values) of this decomposition have
             /// been manually changed by the user.
             #[inline]
-            pub fn recompose(self) -> MatrixMN<$t, R, C> {
+            pub fn recompose(self) -> OMatrix<$t, R, C> {
                 let nrows           = self.u.data.shape().0;
                 let ncols           = self.vt.data.shape().1;
                 let min_nrows_ncols = nrows.min(ncols);
 
-                let mut res: MatrixMN<_, R, C> = Matrix::zeros_generic(nrows, ncols);
+                let mut res: OMatrix<_, R, C> = Matrix::zeros_generic(nrows, ncols);
 
                 {
                     let mut sres = res.generic_slice_mut((0, 0), (min_nrows_ncols, ncols));
@@ -175,12 +175,12 @@ macro_rules! svd_impl(
             ///
             /// All singular value below epsilon will be set to zero instead of being inverted.
             #[inline]
-            pub fn pseudo_inverse(&self, epsilon: $t) -> MatrixMN<$t, C, R> {
+            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 min_nrows_ncols = nrows.min(ncols);
 
-                let mut res: MatrixMN<_, C, R> = Matrix::zeros_generic(ncols, nrows);
+                let mut res: OMatrix<_, C, R> = Matrix::zeros_generic(ncols, nrows);
 
                 {
                     let mut sres = res.generic_slice_mut((0, 0), (min_nrows_ncols, nrows));
@@ -230,9 +230,9 @@ macro_rules! svd_complex_impl(
     ($name: ident, $t: ty, $lapack_func: path) => (
         impl SVDScalar for Complex<$t> {
             fn compute<R: Dim, C: Dim, S>(mut m: Matrix<$t, R, C, S>) -> Option<SVD<$t, R, C, S::Alloc>>
-            Option<(MatrixN<Complex<$t>, R, S::Alloc>,
-                    VectorN<$t, DimMinimum<R, C>, S::Alloc>,
-                    MatrixN<Complex<$t>, C, S::Alloc>)>
+            Option<(OMatrix<Complex<$t>, R, S::Alloc>,
+                    OVector<$t, DimMinimum<R, C>, S::Alloc>,
+                    OMatrix<Complex<$t>, C, S::Alloc>)>
             where R: DimMin<C>,
                   S: ContiguousStorage<Complex<$t>, R, C>,
                   S::Alloc: OwnedAllocator<Complex<$t>, R, C, S> +

nalgebra-lapack/src/symmetric_eigen.rs

@@ -10,7 +10,7 @@ use crate::ComplexHelper;
 use na::allocator::Allocator;
 use na::dimension::{Dim, U1};
 use na::storage::Storage;
-use na::{DefaultAllocator, Matrix, MatrixN, Scalar, VectorN};
+use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
 
 use lapack;
 
@@ -18,47 +18,47 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<N, D, D> +
-                           Allocator<N, D>,
-         VectorN<N, D>: Serialize,
-         MatrixN<N, D>: Serialize"))
+    serde(bound(serialize = "DefaultAllocator: Allocator<T, D, D> +
+                           Allocator<T, D>,
+         OVector<T, D>: Serialize,
+         OMatrix<T, D, D>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(deserialize = "DefaultAllocator: Allocator<N, D, D> +
-                           Allocator<N, D>,
-         VectorN<N, D>: Deserialize<'de>,
-         MatrixN<N, D>: Deserialize<'de>"))
+    serde(bound(deserialize = "DefaultAllocator: Allocator<T, D, D> +
+                           Allocator<T, D>,
+         OVector<T, D>: Deserialize<'de>,
+         OMatrix<T, D, D>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
-pub struct SymmetricEigen<N: Scalar, D: Dim>
+pub struct SymmetricEigen<T: Scalar, D: Dim>
 where
-    DefaultAllocator: Allocator<N, D> + Allocator<N, D, D>,
+    DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
 {
     /// The eigenvectors of the decomposed matrix.
-    pub eigenvectors: MatrixN<N, D>,
+    pub eigenvectors: OMatrix<T, D, D>,
 
     /// The unsorted eigenvalues of the decomposed matrix.
-    pub eigenvalues: VectorN<N, D>,
+    pub eigenvalues: OVector<T, D>,
 }
 
-impl<N: Scalar + Copy, D: Dim> Copy for SymmetricEigen<N, D>
+impl<T: Scalar + Copy, D: Dim> Copy for SymmetricEigen<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
-    MatrixN<N, D>: Copy,
-    VectorN<N, D>: Copy,
+    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    OMatrix<T, D, D>: Copy,
+    OVector<T, D>: Copy,
 {
 }
 
-impl<N: SymmetricEigenScalar + RealField, D: Dim> SymmetricEigen<N, D>
+impl<T: SymmetricEigenScalar + RealField, D: Dim> SymmetricEigen<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
+    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
 {
     /// Computes the eigenvalues and eigenvectors of the symmetric matrix `m`.
     ///
     /// Only the lower-triangular part of `m` is read. If `eigenvectors` is `false` then, the
     /// eigenvectors are not computed explicitly. Panics if the method did not converge.
-    pub fn new(m: MatrixN<N, D>) -> Self {
+    pub fn new(m: OMatrix<T, D, D>) -> Self {
         let (vals, vecs) =
             Self::do_decompose(m, true).expect("SymmetricEigen: convergence failure.");
         Self {
@@ -71,7 +71,7 @@ where
     ///
     /// Only the lower-triangular part of `m` is read. If `eigenvectors` is `false` then, the
     /// eigenvectors are not computed explicitly. Returns `None` if the method did not converge.
-    pub fn try_new(m: MatrixN<N, D>) -> Option<Self> {
+    pub fn try_new(m: OMatrix<T, D, D>) -> Option<Self> {
         Self::do_decompose(m, true).map(|(vals, vecs)| SymmetricEigen {
             eigenvalues: vals,
             eigenvectors: vecs.unwrap(),
@@ -79,15 +79,15 @@ where
     }
 
     fn do_decompose(
-        mut m: MatrixN<N, D>,
+        mut m: OMatrix<T, D, D>,
         eigenvectors: bool,
-    ) -> Option<(VectorN<N, D>, Option<MatrixN<N, D>>)> {
+    ) -> Option<(OVector<T, D>, Option<OMatrix<T, D, D>>)> {
         assert!(
             m.is_square(),
             "Unable to compute the eigenvalue decomposition of a non-square matrix."
         );
 
-        let jobz = if eigenvectors { b'V' } else { b'N' };
+        let jobz = if eigenvectors { b'V' } else { b'T' };
 
         let nrows = m.data.shape().0;
         let n = nrows.value();
@@ -97,12 +97,12 @@ where
         let mut values = unsafe { Matrix::new_uninitialized_generic(nrows, U1).assume_init() };
         let mut info = 0;
 
-        let lwork = N::xsyev_work_size(jobz, b'L', n as i32, m.as_mut_slice(), lda, &mut info);
+        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) };
 
-        N::xsyev(
+        T::xsyev(
             jobz,
             b'L',
             n as i32,
@@ -122,7 +122,7 @@ where
     /// Computes only the eigenvalues of the input matrix.
     ///
     /// Panics if the method does not converge.
-    pub fn eigenvalues(m: MatrixN<N, D>) -> VectorN<N, D> {
+    pub fn eigenvalues(m: OMatrix<T, D, D>) -> OVector<T, D> {
         Self::do_decompose(m, false)
             .expect("SymmetricEigen eigenvalues: convergence failure.")
             .0
@@ -131,14 +131,14 @@ where
     /// Computes only the eigenvalues of the input matrix.
     ///
     /// Returns `None` if the method does not converge.
-    pub fn try_eigenvalues(m: MatrixN<N, D>) -> Option<VectorN<N, D>> {
+    pub fn try_eigenvalues(m: OMatrix<T, D, D>) -> Option<OVector<T, D>> {
         Self::do_decompose(m, false).map(|res| res.0)
     }
 
     /// The determinant of the decomposed matrix.
     #[inline]
-    pub fn determinant(&self) -> N {
-        let mut det = N::one();
+    pub fn determinant(&self) -> T {
+        let mut det = T::one();
         for e in self.eigenvalues.iter() {
             det *= *e;
         }
@@ -149,7 +149,7 @@ where
     /// Rebuild the original matrix.
     ///
     /// This is useful if some of the eigenvalues have been manually modified.
-    pub fn recompose(&self) -> MatrixN<N, D> {
+    pub fn recompose(&self) -> OMatrix<T, D, D> {
         let mut u_t = self.eigenvectors.clone();
         for i in 0..self.eigenvalues.len() {
             let val = self.eigenvalues[i];

nalgebra-sparse/src/ops/impl_std_ops.rs

@@ -10,7 +10,7 @@ use nalgebra::allocator::Allocator;
 use nalgebra::base::storage::Storage;
 use nalgebra::constraint::{DimEq, ShapeConstraint};
 use nalgebra::{
-    ClosedAdd, ClosedDiv, ClosedMul, ClosedSub, DefaultAllocator, Dim, Dynamic, Matrix, MatrixMN,
+    ClosedAdd, ClosedDiv, ClosedMul, ClosedSub, DefaultAllocator, Dim, Dynamic, Matrix, OMatrix,
     Scalar, U1,
 };
 use num_traits::{One, Zero};
@@ -274,7 +274,7 @@ macro_rules! impl_spmm_cs_dense {
         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 nrows = Dynamic::new(lhs.nrows());
-            let mut result = MatrixMN::<T, Dynamic, C>::zeros_generic(nrows, ncols);
+            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));
             result
         });
@@ -305,7 +305,7 @@ macro_rules! impl_spmm_cs_dense {
             DefaultAllocator: Allocator<T, Dynamic, C>,
             // TODO: Is it possible to simplify these bounds?
             ShapeConstraint:
-                // Bounds so that we can turn MatrixMN<T, Dynamic, C> into a DMatrixSliceMut
+                // 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<C, Dynamic>
                 + DimEq<Dynamic, <<DefaultAllocator as Allocator<T, Dynamic, C>>::Buffer as Storage<T, Dynamic, C>>::CStride>
@@ -316,7 +316,7 @@ macro_rules! impl_spmm_cs_dense {
         {
             // We need the column dimension to be generic, so that if RHS is a vector, then
             // we also get a vector (and not a matrix)
-            type Output = MatrixMN<T, Dynamic, C>;
+            type Output = OMatrix<T, Dynamic, C>;
 
             fn mul(self, rhs: $dense_matrix_type) -> Self::Output {
                 let $lhs = self;

src/base/alias.rs

@@ -13,247 +13,248 @@ use crate::base::{Const, Matrix, Unit};
  *
  *
  */
-/// A statically sized column-major matrix with `R` rows and `C` columns.
+
+/// 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.**
-#[deprecated(note = "This matrix name contains a typo. Use MatrixMN instead.")]
-pub type MatrixNM<N, R, C> = Matrix<N, R, C, Owned<N, R, C>>;
+pub type OMatrix<T, R, C> = Matrix<T, R, C, Owned<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.**
+#[deprecated(
+    note = "use SMatrix for a statically-sized matrix using integer dimensions, or OMatrix for an owned matrix using types as dimensions."
+)]
+pub type MatrixMN<T, R, C> = Matrix<T, R, C, Owned<T, R, C>>;
 
 /// A statically sized 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.**
-pub type MatrixMN<N, R, C> = Matrix<N, R, C, Owned<N, R, C>>;
-pub type CMatrixMN<N, const R: usize, const C: usize> =
-    Matrix<N, Const<R>, Const<C>, Owned<N, Const<R>, Const<C>>>;
-
-/// A statically sized column-major square matrix with `D` rows and columns.
-///
-/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixN<N, D> = Matrix<N, D, D, Owned<N, D, D>>;
-pub type CMatrixN<N, const D: usize> = Matrix<N, Const<D>, Const<D>, Owned<N, Const<D>, Const<D>>>;
+pub type SMatrix<T, const R: usize, const C: usize> =
+    Matrix<T, Const<R>, Const<C>, Owned<T, Const<R>, Const<C>>>;
 
 /// A dynamically sized column-major matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type DMatrix<N> = Matrix<N, Dynamic, Dynamic, Owned<N, Dynamic, Dynamic>>;
+pub type DMatrix<T> = Matrix<T, Dynamic, Dynamic, Owned<T, Dynamic, Dynamic>>;
 
 /// A heap-allocated, column-major, matrix with a dynamic number of rows and 1 columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type MatrixXx1<N> = Matrix<N, Dynamic, U1, Owned<N, Dynamic, U1>>;
+pub type MatrixXx1<T> = Matrix<T, Dynamic, U1, Owned<T, Dynamic, U1>>;
 /// A heap-allocated, column-major, matrix with a dynamic number of rows and 2 columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type MatrixXx2<N> = Matrix<N, Dynamic, U2, Owned<N, Dynamic, U2>>;
+pub type MatrixXx2<T> = Matrix<T, Dynamic, U2, Owned<T, Dynamic, U2>>;
 /// A heap-allocated, column-major, matrix with a dynamic number of rows and 3 columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type MatrixXx3<N> = Matrix<N, Dynamic, U3, Owned<N, Dynamic, U3>>;
+pub type MatrixXx3<T> = Matrix<T, Dynamic, U3, Owned<T, Dynamic, U3>>;
 /// A heap-allocated, column-major, matrix with a dynamic number of rows and 4 columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type MatrixXx4<N> = Matrix<N, Dynamic, U4, Owned<N, Dynamic, U4>>;
+pub type MatrixXx4<T> = Matrix<T, Dynamic, U4, Owned<T, Dynamic, U4>>;
 /// A heap-allocated, column-major, matrix with a dynamic number of rows and 5 columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type MatrixXx5<N> = Matrix<N, Dynamic, U5, Owned<N, Dynamic, U5>>;
+pub type MatrixXx5<T> = Matrix<T, Dynamic, U5, Owned<T, Dynamic, U5>>;
 /// A heap-allocated, column-major, matrix with a dynamic number of rows and 6 columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type MatrixXx6<N> = Matrix<N, Dynamic, U6, Owned<N, Dynamic, U6>>;
+pub type MatrixXx6<T> = Matrix<T, Dynamic, U6, Owned<T, Dynamic, U6>>;
 
 /// A heap-allocated, row-major, matrix with 1 rows and a dynamic number of columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type Matrix1xX<N> = Matrix<N, U1, Dynamic, Owned<N, U1, Dynamic>>;
+pub type Matrix1xX<T> = Matrix<T, U1, Dynamic, Owned<T, U1, Dynamic>>;
 /// A heap-allocated, row-major, matrix with 2 rows and a dynamic number of columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type Matrix2xX<N> = Matrix<N, U2, Dynamic, Owned<N, U2, Dynamic>>;
+pub type Matrix2xX<T> = Matrix<T, U2, Dynamic, Owned<T, U2, Dynamic>>;
 /// A heap-allocated, row-major, matrix with 3 rows and a dynamic number of columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type Matrix3xX<N> = Matrix<N, U3, Dynamic, Owned<N, U3, Dynamic>>;
+pub type Matrix3xX<T> = Matrix<T, U3, Dynamic, Owned<T, U3, Dynamic>>;
 /// A heap-allocated, row-major, matrix with 4 rows and a dynamic number of columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type Matrix4xX<N> = Matrix<N, U4, Dynamic, Owned<N, U4, Dynamic>>;
+pub type Matrix4xX<T> = Matrix<T, U4, Dynamic, Owned<T, U4, Dynamic>>;
 /// A heap-allocated, row-major, matrix with 5 rows and a dynamic number of columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type Matrix5xX<N> = Matrix<N, U5, Dynamic, Owned<N, U5, Dynamic>>;
+pub type Matrix5xX<T> = Matrix<T, U5, Dynamic, Owned<T, U5, Dynamic>>;
 /// A heap-allocated, row-major, matrix with 6 rows and a dynamic number of columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type Matrix6xX<N> = Matrix<N, U6, Dynamic, Owned<N, U6, Dynamic>>;
+pub type Matrix6xX<T> = Matrix<T, U6, Dynamic, Owned<T, U6, Dynamic>>;
 
 /// A stack-allocated, column-major, 1x1 square matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix1<N> = Matrix<N, U1, U1, Owned<N, U1, U1>>;
+pub type Matrix1<T> = Matrix<T, U1, U1, Owned<T, U1, U1>>;
 /// A stack-allocated, column-major, 2x2 square matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix2<N> = Matrix<N, U2, U2, Owned<N, U2, U2>>;
+pub type Matrix2<T> = Matrix<T, U2, U2, Owned<T, U2, U2>>;
 /// A stack-allocated, column-major, 3x3 square matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix3<N> = Matrix<N, U3, U3, Owned<N, U3, U3>>;
+pub type Matrix3<T> = Matrix<T, U3, U3, Owned<T, U3, U3>>;
 /// A stack-allocated, column-major, 4x4 square matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix4<N> = Matrix<N, U4, U4, Owned<N, U4, U4>>;
+pub type Matrix4<T> = Matrix<T, U4, U4, Owned<T, U4, U4>>;
 /// A stack-allocated, column-major, 5x5 square matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix5<N> = Matrix<N, U5, U5, Owned<N, U5, U5>>;
+pub type Matrix5<T> = Matrix<T, U5, U5, Owned<T, U5, U5>>;
 /// A stack-allocated, column-major, 6x6 square matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix6<N> = Matrix<N, U6, U6, Owned<N, U6, U6>>;
+pub type Matrix6<T> = Matrix<T, U6, U6, Owned<T, U6, U6>>;
 
 /// A stack-allocated, column-major, 1x2 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix1x2<N> = Matrix<N, U1, U2, Owned<N, U1, U2>>;
+pub type Matrix1x2<T> = Matrix<T, U1, U2, Owned<T, U1, U2>>;
 /// A stack-allocated, column-major, 1x3 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix1x3<N> = Matrix<N, U1, U3, Owned<N, U1, U3>>;
+pub type Matrix1x3<T> = Matrix<T, U1, U3, Owned<T, U1, U3>>;
 /// A stack-allocated, column-major, 1x4 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix1x4<N> = Matrix<N, U1, U4, Owned<N, U1, U4>>;
+pub type Matrix1x4<T> = Matrix<T, U1, U4, Owned<T, U1, U4>>;
 /// A stack-allocated, column-major, 1x5 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix1x5<N> = Matrix<N, U1, U5, Owned<N, U1, U5>>;
+pub type Matrix1x5<T> = Matrix<T, U1, U5, Owned<T, U1, U5>>;
 /// A stack-allocated, column-major, 1x6 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix1x6<N> = Matrix<N, U1, U6, Owned<N, U1, U6>>;
+pub type Matrix1x6<T> = Matrix<T, U1, U6, Owned<T, U1, U6>>;
 
 /// A stack-allocated, column-major, 2x3 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix2x3<N> = Matrix<N, U2, U3, Owned<N, U2, U3>>;
+pub type Matrix2x3<T> = Matrix<T, U2, U3, Owned<T, U2, U3>>;
 /// A stack-allocated, column-major, 2x4 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix2x4<N> = Matrix<N, U2, U4, Owned<N, U2, U4>>;
+pub type Matrix2x4<T> = Matrix<T, U2, U4, Owned<T, U2, U4>>;
 /// A stack-allocated, column-major, 2x5 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix2x5<N> = Matrix<N, U2, U5, Owned<N, U2, U5>>;
+pub type Matrix2x5<T> = Matrix<T, U2, U5, Owned<T, U2, U5>>;
 /// A stack-allocated, column-major, 2x6 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix2x6<N> = Matrix<N, U2, U6, Owned<N, U2, U6>>;
+pub type Matrix2x6<T> = Matrix<T, U2, U6, Owned<T, U2, U6>>;
 
 /// A stack-allocated, column-major, 3x4 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix3x4<N> = Matrix<N, U3, U4, Owned<N, U3, U4>>;
+pub type Matrix3x4<T> = Matrix<T, U3, U4, Owned<T, U3, U4>>;
 /// A stack-allocated, column-major, 3x5 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix3x5<N> = Matrix<N, U3, U5, Owned<N, U3, U5>>;
+pub type Matrix3x5<T> = Matrix<T, U3, U5, Owned<T, U3, U5>>;
 /// A stack-allocated, column-major, 3x6 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix3x6<N> = Matrix<N, U3, U6, Owned<N, U3, U6>>;
+pub type Matrix3x6<T> = Matrix<T, U3, U6, Owned<T, U3, U6>>;
 
 /// A stack-allocated, column-major, 4x5 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix4x5<N> = Matrix<N, U4, U5, Owned<N, U4, U5>>;
+pub type Matrix4x5<T> = Matrix<T, U4, U5, Owned<T, U4, U5>>;
 /// A stack-allocated, column-major, 4x6 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix4x6<N> = Matrix<N, U4, U6, Owned<N, U4, U6>>;
+pub type Matrix4x6<T> = Matrix<T, U4, U6, Owned<T, U4, U6>>;
 
 /// A stack-allocated, column-major, 5x6 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix5x6<N> = Matrix<N, U5, U6, Owned<N, U5, U6>>;
+pub type Matrix5x6<T> = Matrix<T, U5, U6, Owned<T, U5, U6>>;
 
 /// A stack-allocated, column-major, 2x1 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix2x1<N> = Matrix<N, U2, U1, Owned<N, U2, U1>>;
+pub type Matrix2x1<T> = Matrix<T, U2, U1, Owned<T, U2, U1>>;
 /// A stack-allocated, column-major, 3x1 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix3x1<N> = Matrix<N, U3, U1, Owned<N, U3, U1>>;
+pub type Matrix3x1<T> = Matrix<T, U3, U1, Owned<T, U3, U1>>;
 /// A stack-allocated, column-major, 4x1 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix4x1<N> = Matrix<N, U4, U1, Owned<N, U4, U1>>;
+pub type Matrix4x1<T> = Matrix<T, U4, U1, Owned<T, U4, U1>>;
 /// A stack-allocated, column-major, 5x1 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix5x1<N> = Matrix<N, U5, U1, Owned<N, U5, U1>>;
+pub type Matrix5x1<T> = Matrix<T, U5, U1, Owned<T, U5, U1>>;
 /// A stack-allocated, column-major, 6x1 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix6x1<N> = Matrix<N, U6, U1, Owned<N, U6, U1>>;
+pub type Matrix6x1<T> = Matrix<T, U6, U1, Owned<T, U6, U1>>;
 
 /// A stack-allocated, column-major, 3x2 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix3x2<N> = Matrix<N, U3, U2, Owned<N, U3, U2>>;
+pub type Matrix3x2<T> = Matrix<T, U3, U2, Owned<T, U3, U2>>;
 /// A stack-allocated, column-major, 4x2 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix4x2<N> = Matrix<N, U4, U2, Owned<N, U4, U2>>;
+pub type Matrix4x2<T> = Matrix<T, U4, U2, Owned<T, U4, U2>>;
 /// A stack-allocated, column-major, 5x2 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix5x2<N> = Matrix<N, U5, U2, Owned<N, U5, U2>>;
+pub type Matrix5x2<T> = Matrix<T, U5, U2, Owned<T, U5, U2>>;
 /// A stack-allocated, column-major, 6x2 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix6x2<N> = Matrix<N, U6, U2, Owned<N, U6, U2>>;
+pub type Matrix6x2<T> = Matrix<T, U6, U2, Owned<T, U6, U2>>;
 
 /// A stack-allocated, column-major, 4x3 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix4x3<N> = Matrix<N, U4, U3, Owned<N, U4, U3>>;
+pub type Matrix4x3<T> = Matrix<T, U4, U3, Owned<T, U4, U3>>;
 /// A stack-allocated, column-major, 5x3 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix5x3<N> = Matrix<N, U5, U3, Owned<N, U5, U3>>;
+pub type Matrix5x3<T> = Matrix<T, U5, U3, Owned<T, U5, U3>>;
 /// A stack-allocated, column-major, 6x3 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix6x3<N> = Matrix<N, U6, U3, Owned<N, U6, U3>>;
+pub type Matrix6x3<T> = Matrix<T, U6, U3, Owned<T, U6, U3>>;
 
 /// A stack-allocated, column-major, 5x4 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix5x4<N> = Matrix<N, U5, U4, Owned<N, U5, U4>>;
+pub type Matrix5x4<T> = Matrix<T, U5, U4, Owned<T, U5, U4>>;
 /// A stack-allocated, column-major, 6x4 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix6x4<N> = Matrix<N, U6, U4, Owned<N, U6, U4>>;
+pub type Matrix6x4<T> = Matrix<T, U6, U4, Owned<T, U6, U4>>;
 
 /// A stack-allocated, column-major, 6x5 matrix.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type Matrix6x5<N> = Matrix<N, U6, U5, Owned<N, U6, U5>>;
+pub type Matrix6x5<T> = Matrix<T, U6, U5, Owned<T, U6, U5>>;
 
 /*
  *
@@ -264,24 +265,33 @@ pub type Matrix6x5<N> = Matrix<N, U6, U5, Owned<N, U6, U5>>;
  */
 /// A dynamically sized column vector.
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type DVector<N> = Matrix<N, Dynamic, U1, VecStorage<N, Dynamic, U1>>;
+pub type DVector<T> = Matrix<T, Dynamic, U1, VecStorage<T, Dynamic, U1>>;
 
+/// An owned D-dimensional column vector.
+pub type OVector<T, D> = Matrix<T, D, U1, Owned<T, D, U1>>;
 /// A statically sized D-dimensional column vector.
-pub type VectorN<N, D> = Matrix<N, D, U1, Owned<N, D, U1>>;
-pub type CVectorN<N, const D: usize> = Matrix<N, Const<D>, U1, Owned<N, Const<D>, U1>>;
+pub type SVector<T, const D: usize> = Matrix<T, Const<D>, U1, Owned<T, Const<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.**
+#[deprecated(
+    note = "use SVector for a statically-sized matrix using integer dimensions, or OVector for an owned matrix using types as dimensions."
+)]
+pub type VectorN<T, D> = Matrix<T, D, U1, Owned<T, D, U1>>;
 
 /// A stack-allocated, 1-dimensional column vector.
-pub type Vector1<N> = Matrix<N, U1, U1, Owned<N, U1, U1>>;
+pub type Vector1<T> = Matrix<T, U1, U1, Owned<T, U1, U1>>;
 /// A stack-allocated, 2-dimensional column vector.
-pub type Vector2<N> = Matrix<N, U2, U1, Owned<N, U2, U1>>;
+pub type Vector2<T> = Matrix<T, U2, U1, Owned<T, U2, U1>>;
 /// A stack-allocated, 3-dimensional column vector.
-pub type Vector3<N> = Matrix<N, U3, U1, Owned<N, U3, U1>>;
+pub type Vector3<T> = Matrix<T, U3, U1, Owned<T, U3, U1>>;
 /// A stack-allocated, 4-dimensional column vector.
-pub type Vector4<N> = Matrix<N, U4, U1, Owned<N, U4, U1>>;
+pub type Vector4<T> = Matrix<T, U4, U1, Owned<T, U4, U1>>;
 /// A stack-allocated, 5-dimensional column vector.
-pub type Vector5<N> = Matrix<N, U5, U1, Owned<N, U5, U1>>;
+pub type Vector5<T> = Matrix<T, U5, U1, Owned<T, U5, U1>>;
 /// A stack-allocated, 6-dimensional column vector.
-pub type Vector6<N> = Matrix<N, U6, U1, Owned<N, U6, U1>>;
+pub type Vector6<T> = Matrix<T, U6, U1, Owned<T, U6, U1>>;
 
 /*
  *
@@ -292,23 +302,26 @@ pub type Vector6<N> = Matrix<N, U6, U1, Owned<N, U6, U1>>;
  */
 /// A dynamically sized row vector.
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type RowDVector<N> = Matrix<N, U1, Dynamic, VecStorage<N, U1, Dynamic>>;
+pub type RowDVector<T> = Matrix<T, U1, Dynamic, VecStorage<T, U1, Dynamic>>;
+
+/// An owned D-dimensional row vector.
+pub type RowOVector<T, D> = Matrix<T, U1, D, Owned<T, U1, D>>;
 
 /// A statically sized D-dimensional row vector.
-pub type RowVectorN<N, D> = Matrix<N, U1, D, Owned<N, U1, D>>;
+pub type RowSVector<T, const D: usize> = Matrix<T, U1, Const<D>, Owned<T, U1, Const<D>>>;
 
 /// A stack-allocated, 1-dimensional row vector.
-pub type RowVector1<N> = Matrix<N, U1, U1, Owned<N, U1, U1>>;
+pub type RowVector1<T> = Matrix<T, U1, U1, Owned<T, U1, U1>>;
 /// A stack-allocated, 2-dimensional row vector.
-pub type RowVector2<N> = Matrix<N, U1, U2, Owned<N, U1, U2>>;
+pub type RowVector2<T> = Matrix<T, U1, U2, Owned<T, U1, U2>>;
 /// A stack-allocated, 3-dimensional row vector.
-pub type RowVector3<N> = Matrix<N, U1, U3, Owned<N, U1, U3>>;
+pub type RowVector3<T> = Matrix<T, U1, U3, Owned<T, U1, U3>>;
 /// A stack-allocated, 4-dimensional row vector.
-pub type RowVector4<N> = Matrix<N, U1, U4, Owned<N, U1, U4>>;
+pub type RowVector4<T> = Matrix<T, U1, U4, Owned<T, U1, U4>>;
 /// A stack-allocated, 5-dimensional row vector.
-pub type RowVector5<N> = Matrix<N, U1, U5, Owned<N, U1, U5>>;
+pub type RowVector5<T> = Matrix<T, U1, U5, Owned<T, U1, U5>>;
 /// A stack-allocated, 6-dimensional row vector.
-pub type RowVector6<N> = Matrix<N, U1, U6, Owned<N, U1, U6>>;
+pub type RowVector6<T> = Matrix<T, U1, U6, Owned<T, U1, U6>>;
 
 /*
  *
@@ -318,14 +331,14 @@ pub type RowVector6<N> = Matrix<N, U1, U6, Owned<N, U1, U6>>;
  *
  */
 /// A stack-allocated, 1-dimensional unit vector.
-pub type UnitVector1<N> = Unit<Matrix<N, U1, U1, Owned<N, U1, U1>>>;
+pub type UnitVector1<T> = Unit<Matrix<T, U1, U1, Owned<T, U1, U1>>>;
 /// A stack-allocated, 2-dimensional unit vector.
-pub type UnitVector2<N> = Unit<Matrix<N, U2, U1, Owned<N, U2, U1>>>;
+pub type UnitVector2<T> = Unit<Matrix<T, U2, U1, Owned<T, U2, U1>>>;
 /// A stack-allocated, 3-dimensional unit vector.
-pub type UnitVector3<N> = Unit<Matrix<N, U3, U1, Owned<N, U3, U1>>>;
+pub type UnitVector3<T> = Unit<Matrix<T, U3, U1, Owned<T, U3, U1>>>;
 /// A stack-allocated, 4-dimensional unit vector.
-pub type UnitVector4<N> = Unit<Matrix<N, U4, U1, Owned<N, U4, U1>>>;
+pub type UnitVector4<T> = Unit<Matrix<T, U4, U1, Owned<T, U4, U1>>>;
 /// A stack-allocated, 5-dimensional unit vector.
-pub type UnitVector5<N> = Unit<Matrix<N, U5, U1, Owned<N, U5, U1>>>;
+pub type UnitVector5<T> = Unit<Matrix<T, U5, U1, Owned<T, U5, U1>>>;
 /// A stack-allocated, 6-dimensional unit vector.
-pub type UnitVector6<N> = Unit<Matrix<N, U6, U1, Owned<N, U6, U1>>>;
+pub type UnitVector6<T> = Unit<Matrix<T, U6, U1, Owned<T, U6, U1>>>;

src/base/alias_slice.rs

@@ -1,6 +1,6 @@
 use crate::base::dimension::{Dynamic, U1, U2, U3, U4, U5, U6};
 use crate::base::matrix_slice::{SliceStorage, SliceStorageMut};
-use crate::base::Matrix;
+use crate::base::{Const, Matrix};
 
 /*
  *
@@ -9,287 +9,290 @@ use crate::base::Matrix;
  *
  *
  */
-/// A column-major matrix slice with `R` rows and `C` columns.
+// NOTE: we can't provide defaults for the strides because it's not supported yet by min_const_generics.
+/// A column-major matrix slice with dimensions known at compile-time.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMN<'a, N, R, C, RStride = U1, CStride = R> =
-    Matrix<N, R, C, SliceStorage<'a, N, R, C, RStride, CStride>>;
-
-/// A column-major matrix slice with `D` rows and columns.
-///
-/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceN<'a, N, D, RStride = U1, CStride = D> =
-    Matrix<N, D, D, SliceStorage<'a, N, D, D, RStride, CStride>>;
+pub type SMatrixSlice<'a, T, const R: usize, const C: usize> =
+    Matrix<T, Const<R>, Const<C>, SliceStorage<'a, T, Const<R>, Const<C>, Const<1>, Const<R>>>;
 
 /// A column-major matrix slice dynamic numbers of rows and columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type DMatrixSlice<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, Dynamic, SliceStorage<'a, N, Dynamic, Dynamic, RStride, CStride>>;
+pub type DMatrixSlice<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, Dynamic, SliceStorage<'a, T, Dynamic, Dynamic, RStride, CStride>>;
 
 /// A column-major 1x1 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice1<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U1, SliceStorage<'a, N, U1, U1, RStride, CStride>>;
+pub type MatrixSlice1<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U1, SliceStorage<'a, T, U1, U1, RStride, CStride>>;
 /// A column-major 2x2 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice2<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U2, SliceStorage<'a, N, U2, U2, RStride, CStride>>;
+pub type MatrixSlice2<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U2, SliceStorage<'a, T, U2, U2, RStride, CStride>>;
 /// A column-major 3x3 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice3<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U3, SliceStorage<'a, N, U3, U3, RStride, CStride>>;
+pub type MatrixSlice3<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U3, SliceStorage<'a, T, U3, U3, RStride, CStride>>;
 /// A column-major 4x4 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice4<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U4, SliceStorage<'a, N, U4, U4, RStride, CStride>>;
+pub type MatrixSlice4<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U4, SliceStorage<'a, T, U4, U4, RStride, CStride>>;
 /// A column-major 5x5 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice5<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U5, SliceStorage<'a, N, U5, U5, RStride, CStride>>;
+pub type MatrixSlice5<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U5, SliceStorage<'a, T, U5, U5, RStride, CStride>>;
 /// A column-major 6x6 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice6<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U6, SliceStorage<'a, N, U6, U6, RStride, CStride>>;
+pub type MatrixSlice6<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U6, SliceStorage<'a, T, U6, U6, RStride, CStride>>;
 
 /// A column-major 1x2 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice1x2<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U2, SliceStorage<'a, N, U1, U2, RStride, CStride>>;
+pub type MatrixSlice1x2<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U2, SliceStorage<'a, T, U1, U2, RStride, CStride>>;
 /// A column-major 1x3 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice1x3<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U3, SliceStorage<'a, N, U1, U3, RStride, CStride>>;
+pub type MatrixSlice1x3<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U3, SliceStorage<'a, T, U1, U3, RStride, CStride>>;
 /// A column-major 1x4 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice1x4<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U4, SliceStorage<'a, N, U1, U4, RStride, CStride>>;
+pub type MatrixSlice1x4<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U4, SliceStorage<'a, T, U1, U4, RStride, CStride>>;
 /// A column-major 1x5 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice1x5<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U5, SliceStorage<'a, N, U1, U5, RStride, CStride>>;
+pub type MatrixSlice1x5<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U5, SliceStorage<'a, T, U1, U5, RStride, CStride>>;
 /// A column-major 1x6 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice1x6<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U6, SliceStorage<'a, N, U1, U6, RStride, CStride>>;
+pub type MatrixSlice1x6<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U6, SliceStorage<'a, T, U1, U6, RStride, CStride>>;
 
 /// A column-major 2x1 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice2x1<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U1, SliceStorage<'a, N, U2, U1, RStride, CStride>>;
+pub type MatrixSlice2x1<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U1, SliceStorage<'a, T, U2, U1, RStride, CStride>>;
 /// A column-major 2x3 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice2x3<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U3, SliceStorage<'a, N, U2, U3, RStride, CStride>>;
+pub type MatrixSlice2x3<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U3, SliceStorage<'a, T, U2, U3, RStride, CStride>>;
 /// A column-major 2x4 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice2x4<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U4, SliceStorage<'a, N, U2, U4, RStride, CStride>>;
+pub type MatrixSlice2x4<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U4, SliceStorage<'a, T, U2, U4, RStride, CStride>>;
 /// A column-major 2x5 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice2x5<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U5, SliceStorage<'a, N, U2, U5, RStride, CStride>>;
+pub type MatrixSlice2x5<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U5, SliceStorage<'a, T, U2, U5, RStride, CStride>>;
 /// A column-major 2x6 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice2x6<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U6, SliceStorage<'a, N, U2, U6, RStride, CStride>>;
+pub type MatrixSlice2x6<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U6, SliceStorage<'a, T, U2, U6, RStride, CStride>>;
 
 /// A column-major 3x1 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice3x1<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U1, SliceStorage<'a, N, U3, U1, RStride, CStride>>;
+pub type MatrixSlice3x1<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U1, SliceStorage<'a, T, U3, U1, RStride, CStride>>;
 /// A column-major 3x2 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice3x2<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U2, SliceStorage<'a, N, U3, U2, RStride, CStride>>;
+pub type MatrixSlice3x2<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U2, SliceStorage<'a, T, U3, U2, RStride, CStride>>;
 /// A column-major 3x4 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice3x4<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U4, SliceStorage<'a, N, U3, U4, RStride, CStride>>;
+pub type MatrixSlice3x4<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U4, SliceStorage<'a, T, U3, U4, RStride, CStride>>;
 /// A column-major 3x5 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice3x5<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U5, SliceStorage<'a, N, U3, U5, RStride, CStride>>;
+pub type MatrixSlice3x5<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U5, SliceStorage<'a, T, U3, U5, RStride, CStride>>;
 /// A column-major 3x6 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice3x6<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U6, SliceStorage<'a, N, U3, U6, RStride, CStride>>;
+pub type MatrixSlice3x6<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U6, SliceStorage<'a, T, U3, U6, RStride, CStride>>;
 
 /// A column-major 4x1 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice4x1<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U1, SliceStorage<'a, N, U4, U1, RStride, CStride>>;
+pub type MatrixSlice4x1<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U1, SliceStorage<'a, T, U4, U1, RStride, CStride>>;
 /// A column-major 4x2 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice4x2<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U2, SliceStorage<'a, N, U4, U2, RStride, CStride>>;
+pub type MatrixSlice4x2<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U2, SliceStorage<'a, T, U4, U2, RStride, CStride>>;
 /// A column-major 4x3 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice4x3<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U3, SliceStorage<'a, N, U4, U3, RStride, CStride>>;
+pub type MatrixSlice4x3<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U3, SliceStorage<'a, T, U4, U3, RStride, CStride>>;
 /// A column-major 4x5 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice4x5<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U5, SliceStorage<'a, N, U4, U5, RStride, CStride>>;
+pub type MatrixSlice4x5<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U5, SliceStorage<'a, T, U4, U5, RStride, CStride>>;
 /// A column-major 4x6 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice4x6<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U6, SliceStorage<'a, N, U4, U6, RStride, CStride>>;
+pub type MatrixSlice4x6<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U6, SliceStorage<'a, T, U4, U6, RStride, CStride>>;
 
 /// A column-major 5x1 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice5x1<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U1, SliceStorage<'a, N, U5, U1, RStride, CStride>>;
+pub type MatrixSlice5x1<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U1, SliceStorage<'a, T, U5, U1, RStride, CStride>>;
 /// A column-major 5x2 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice5x2<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U2, SliceStorage<'a, N, U5, U2, RStride, CStride>>;
+pub type MatrixSlice5x2<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U2, SliceStorage<'a, T, U5, U2, RStride, CStride>>;
 /// A column-major 5x3 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice5x3<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U3, SliceStorage<'a, N, U5, U3, RStride, CStride>>;
+pub type MatrixSlice5x3<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U3, SliceStorage<'a, T, U5, U3, RStride, CStride>>;
 /// A column-major 5x4 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice5x4<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U4, SliceStorage<'a, N, U5, U4, RStride, CStride>>;
+pub type MatrixSlice5x4<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U4, SliceStorage<'a, T, U5, U4, RStride, CStride>>;
 /// A column-major 5x6 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice5x6<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U6, SliceStorage<'a, N, U5, U6, RStride, CStride>>;
+pub type MatrixSlice5x6<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U6, SliceStorage<'a, T, U5, U6, RStride, CStride>>;
 
 /// A column-major 6x1 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice6x1<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U1, SliceStorage<'a, N, U6, U1, RStride, CStride>>;
+pub type MatrixSlice6x1<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U1, SliceStorage<'a, T, U6, U1, RStride, CStride>>;
 /// A column-major 6x2 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice6x2<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U2, SliceStorage<'a, N, U6, U2, RStride, CStride>>;
+pub type MatrixSlice6x2<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U2, SliceStorage<'a, T, U6, U2, RStride, CStride>>;
 /// A column-major 6x3 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice6x3<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U3, SliceStorage<'a, N, U6, U3, RStride, CStride>>;
+pub type MatrixSlice6x3<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U3, SliceStorage<'a, T, U6, U3, RStride, CStride>>;
 /// A column-major 6x4 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice6x4<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U4, SliceStorage<'a, N, U6, U4, RStride, CStride>>;
+pub type MatrixSlice6x4<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U4, SliceStorage<'a, T, U6, U4, RStride, CStride>>;
 /// A column-major 6x5 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSlice6x5<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U5, SliceStorage<'a, N, U6, U5, RStride, CStride>>;
+pub type MatrixSlice6x5<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U5, SliceStorage<'a, T, U6, U5, RStride, CStride>>;
 
 /// A column-major matrix slice with 1 row and a number of columns chosen at runtime.
-pub type MatrixSlice1xX<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, Dynamic, SliceStorage<'a, N, U1, Dynamic, RStride, CStride>>;
+pub type MatrixSlice1xX<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, Dynamic, SliceStorage<'a, T, U1, Dynamic, RStride, CStride>>;
 /// A column-major matrix slice with 2 rows and a number of columns chosen at runtime.
-pub type MatrixSlice2xX<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, Dynamic, SliceStorage<'a, N, U2, Dynamic, RStride, CStride>>;
+pub type MatrixSlice2xX<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, Dynamic, SliceStorage<'a, T, U2, Dynamic, RStride, CStride>>;
 /// A column-major matrix slice with 3 rows and a number of columns chosen at runtime.
-pub type MatrixSlice3xX<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, Dynamic, SliceStorage<'a, N, U3, Dynamic, RStride, CStride>>;
+pub type MatrixSlice3xX<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, Dynamic, SliceStorage<'a, T, U3, Dynamic, RStride, CStride>>;
 /// A column-major matrix slice with 4 rows and a number of columns chosen at runtime.
-pub type MatrixSlice4xX<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, Dynamic, SliceStorage<'a, N, U4, Dynamic, RStride, CStride>>;
+pub type MatrixSlice4xX<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, Dynamic, SliceStorage<'a, T, U4, Dynamic, RStride, CStride>>;
 /// A column-major matrix slice with 5 rows and a number of columns chosen at runtime.
-pub type MatrixSlice5xX<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, Dynamic, SliceStorage<'a, N, U5, Dynamic, RStride, CStride>>;
+pub type MatrixSlice5xX<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, Dynamic, SliceStorage<'a, T, U5, Dynamic, RStride, CStride>>;
 /// A column-major matrix slice with 6 rows and a number of columns chosen at runtime.
-pub type MatrixSlice6xX<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, Dynamic, SliceStorage<'a, N, U6, Dynamic, RStride, CStride>>;
+pub type MatrixSlice6xX<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, Dynamic, SliceStorage<'a, T, U6, Dynamic, RStride, CStride>>;
 
 /// A column-major matrix slice with a number of rows chosen at runtime and 1 column.
-pub type MatrixSliceXx1<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U1, SliceStorage<'a, N, Dynamic, U1, RStride, CStride>>;
+pub type MatrixSliceXx1<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U1, SliceStorage<'a, T, Dynamic, U1, RStride, CStride>>;
 /// A column-major matrix slice with a number of rows chosen at runtime and 2 columns.
-pub type MatrixSliceXx2<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U2, SliceStorage<'a, N, Dynamic, U2, RStride, CStride>>;
+pub type MatrixSliceXx2<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U2, SliceStorage<'a, T, Dynamic, U2, RStride, CStride>>;
 /// A column-major matrix slice with a number of rows chosen at runtime and 3 columns.
-pub type MatrixSliceXx3<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U3, SliceStorage<'a, N, Dynamic, U3, RStride, CStride>>;
+pub type MatrixSliceXx3<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U3, SliceStorage<'a, T, Dynamic, U3, RStride, CStride>>;
 /// A column-major matrix slice with a number of rows chosen at runtime and 4 columns.
-pub type MatrixSliceXx4<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U4, SliceStorage<'a, N, Dynamic, U4, RStride, CStride>>;
+pub type MatrixSliceXx4<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U4, SliceStorage<'a, T, Dynamic, U4, RStride, CStride>>;
 /// A column-major matrix slice with a number of rows chosen at runtime and 5 columns.
-pub type MatrixSliceXx5<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U5, SliceStorage<'a, N, Dynamic, U5, RStride, CStride>>;
+pub type MatrixSliceXx5<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U5, SliceStorage<'a, T, Dynamic, U5, RStride, CStride>>;
 /// A column-major matrix slice with a number of rows chosen at runtime and 6 columns.
-pub type MatrixSliceXx6<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U6, SliceStorage<'a, N, Dynamic, U6, RStride, CStride>>;
+pub type MatrixSliceXx6<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U6, SliceStorage<'a, T, Dynamic, U6, RStride, CStride>>;
 
-/// A column vector slice with `D` rows.
-pub type VectorSliceN<'a, N, D, RStride = U1, CStride = D> =
-    Matrix<N, D, U1, SliceStorage<'a, N, D, U1, RStride, CStride>>;
+/// A column vector slice with dimensions known at compile-time.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
+pub type VectorSlice<'a, T, D, RStride = U1, CStride = D> =
+    Matrix<T, D, U1, SliceStorage<'a, T, D, U1, RStride, CStride>>;
+
+/// A column vector slice with dimensions known at compile-time.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
+pub type SVectorSlice<'a, T, const D: usize> =
+    Matrix<T, Const<D>, Const<1>, SliceStorage<'a, T, Const<D>, Const<1>, Const<1>, Const<D>>>;
 
 /// A column vector slice dynamic numbers of rows and columns.
-pub type DVectorSlice<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U1, SliceStorage<'a, N, Dynamic, U1, RStride, CStride>>;
+pub type DVectorSlice<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U1, SliceStorage<'a, T, Dynamic, U1, RStride, CStride>>;
 
 /// A 1D column vector slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type VectorSlice1<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U1, SliceStorage<'a, N, U1, U1, RStride, CStride>>;
+pub type VectorSlice1<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U1, SliceStorage<'a, T, U1, U1, RStride, CStride>>;
 /// A 2D column vector slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type VectorSlice2<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U1, SliceStorage<'a, N, U2, U1, RStride, CStride>>;
+pub type VectorSlice2<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U1, SliceStorage<'a, T, U2, U1, RStride, CStride>>;
 /// A 3D column vector slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type VectorSlice3<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U1, SliceStorage<'a, N, U3, U1, RStride, CStride>>;
+pub type VectorSlice3<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U1, SliceStorage<'a, T, U3, U1, RStride, CStride>>;
 /// A 4D column vector slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type VectorSlice4<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U1, SliceStorage<'a, N, U4, U1, RStride, CStride>>;
+pub type VectorSlice4<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U1, SliceStorage<'a, T, U4, U1, RStride, CStride>>;
 /// A 5D column vector slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type VectorSlice5<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U1, SliceStorage<'a, N, U5, U1, RStride, CStride>>;
+pub type VectorSlice5<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U1, SliceStorage<'a, T, U5, U1, RStride, CStride>>;
 /// A 6D column vector slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type VectorSlice6<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U1, SliceStorage<'a, N, U6, U1, RStride, CStride>>;
+pub type VectorSlice6<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U1, SliceStorage<'a, T, U6, U1, RStride, CStride>>;
 
 /*
  *
@@ -301,281 +304,297 @@ pub type VectorSlice6<'a, N, RStride = U1, CStride = U6> =
 /// A column-major matrix slice 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.**
-pub type MatrixSliceMutMN<'a, N, R, C, RStride = U1, CStride = R> =
-    Matrix<N, R, C, SliceStorageMut<'a, N, R, C, RStride, CStride>>;
+pub type MatrixSliceMutMN<'a, T, R, C, RStride = U1, CStride = R> =
+    Matrix<T, R, C, SliceStorageMut<'a, T, R, C, RStride, CStride>>;
 
 /// A column-major matrix slice with `D` rows and columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMutN<'a, N, D, RStride = U1, CStride = D> =
-    Matrix<N, D, D, SliceStorageMut<'a, N, D, D, RStride, CStride>>;
+pub type MatrixSliceMutN<'a, T, D, RStride = U1, CStride = D> =
+    Matrix<T, D, D, SliceStorageMut<'a, T, D, D, RStride, CStride>>;
+
+/// A column-major matrix slice with dimensions known at compile-time.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
+pub type SMatrixSliceMut<'a, T, const R: usize, const C: usize> =
+    Matrix<T, Const<R>, Const<C>, SliceStorageMut<'a, T, Const<R>, Const<C>, Const<1>, Const<R>>>;
 
 /// A column-major matrix slice dynamic numbers of rows and columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type DMatrixSliceMut<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, Dynamic, SliceStorageMut<'a, N, Dynamic, Dynamic, RStride, CStride>>;
+pub type DMatrixSliceMut<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, Dynamic, SliceStorageMut<'a, T, Dynamic, Dynamic, RStride, CStride>>;
 
 /// A column-major 1x1 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut1<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U1, SliceStorageMut<'a, N, U1, U1, RStride, CStride>>;
+pub type MatrixSliceMut1<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U1, SliceStorageMut<'a, T, U1, U1, RStride, CStride>>;
 /// A column-major 2x2 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut2<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U2, SliceStorageMut<'a, N, U2, U2, RStride, CStride>>;
+pub type MatrixSliceMut2<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U2, SliceStorageMut<'a, T, U2, U2, RStride, CStride>>;
 /// A column-major 3x3 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut3<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U3, SliceStorageMut<'a, N, U3, U3, RStride, CStride>>;
+pub type MatrixSliceMut3<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U3, SliceStorageMut<'a, T, U3, U3, RStride, CStride>>;
 /// A column-major 4x4 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut4<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U4, SliceStorageMut<'a, N, U4, U4, RStride, CStride>>;
+pub type MatrixSliceMut4<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U4, SliceStorageMut<'a, T, U4, U4, RStride, CStride>>;
 /// A column-major 5x5 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut5<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U5, SliceStorageMut<'a, N, U5, U5, RStride, CStride>>;
+pub type MatrixSliceMut5<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U5, SliceStorageMut<'a, T, U5, U5, RStride, CStride>>;
 /// A column-major 6x6 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut6<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U6, SliceStorageMut<'a, N, U6, U6, RStride, CStride>>;
+pub type MatrixSliceMut6<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U6, SliceStorageMut<'a, T, U6, U6, RStride, CStride>>;
 
 /// A column-major 1x2 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut1x2<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U2, SliceStorageMut<'a, N, U1, U2, RStride, CStride>>;
+pub type MatrixSliceMut1x2<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U2, SliceStorageMut<'a, T, U1, U2, RStride, CStride>>;
 /// A column-major 1x3 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut1x3<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U3, SliceStorageMut<'a, N, U1, U3, RStride, CStride>>;
+pub type MatrixSliceMut1x3<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U3, SliceStorageMut<'a, T, U1, U3, RStride, CStride>>;
 /// A column-major 1x4 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut1x4<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U4, SliceStorageMut<'a, N, U1, U4, RStride, CStride>>;
+pub type MatrixSliceMut1x4<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U4, SliceStorageMut<'a, T, U1, U4, RStride, CStride>>;
 /// A column-major 1x5 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut1x5<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U5, SliceStorageMut<'a, N, U1, U5, RStride, CStride>>;
+pub type MatrixSliceMut1x5<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U5, SliceStorageMut<'a, T, U1, U5, RStride, CStride>>;
 /// A column-major 1x6 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut1x6<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U6, SliceStorageMut<'a, N, U1, U6, RStride, CStride>>;
+pub type MatrixSliceMut1x6<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U6, SliceStorageMut<'a, T, U1, U6, RStride, CStride>>;
 
 /// A column-major 2x1 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut2x1<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U1, SliceStorageMut<'a, N, U2, U1, RStride, CStride>>;
+pub type MatrixSliceMut2x1<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U1, SliceStorageMut<'a, T, U2, U1, RStride, CStride>>;
 /// A column-major 2x3 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut2x3<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U3, SliceStorageMut<'a, N, U2, U3, RStride, CStride>>;
+pub type MatrixSliceMut2x3<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U3, SliceStorageMut<'a, T, U2, U3, RStride, CStride>>;
 /// A column-major 2x4 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut2x4<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U4, SliceStorageMut<'a, N, U2, U4, RStride, CStride>>;
+pub type MatrixSliceMut2x4<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U4, SliceStorageMut<'a, T, U2, U4, RStride, CStride>>;
 /// A column-major 2x5 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut2x5<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U5, SliceStorageMut<'a, N, U2, U5, RStride, CStride>>;
+pub type MatrixSliceMut2x5<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U5, SliceStorageMut<'a, T, U2, U5, RStride, CStride>>;
 /// A column-major 2x6 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut2x6<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U6, SliceStorageMut<'a, N, U2, U6, RStride, CStride>>;
+pub type MatrixSliceMut2x6<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U6, SliceStorageMut<'a, T, U2, U6, RStride, CStride>>;
 
 /// A column-major 3x1 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut3x1<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U1, SliceStorageMut<'a, N, U3, U1, RStride, CStride>>;
+pub type MatrixSliceMut3x1<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U1, SliceStorageMut<'a, T, U3, U1, RStride, CStride>>;
 /// A column-major 3x2 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut3x2<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U2, SliceStorageMut<'a, N, U3, U2, RStride, CStride>>;
+pub type MatrixSliceMut3x2<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U2, SliceStorageMut<'a, T, U3, U2, RStride, CStride>>;
 /// A column-major 3x4 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut3x4<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U4, SliceStorageMut<'a, N, U3, U4, RStride, CStride>>;
+pub type MatrixSliceMut3x4<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U4, SliceStorageMut<'a, T, U3, U4, RStride, CStride>>;
 /// A column-major 3x5 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut3x5<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U5, SliceStorageMut<'a, N, U3, U5, RStride, CStride>>;
+pub type MatrixSliceMut3x5<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U5, SliceStorageMut<'a, T, U3, U5, RStride, CStride>>;
 /// A column-major 3x6 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut3x6<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U6, SliceStorageMut<'a, N, U3, U6, RStride, CStride>>;
+pub type MatrixSliceMut3x6<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U6, SliceStorageMut<'a, T, U3, U6, RStride, CStride>>;
 
 /// A column-major 4x1 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut4x1<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U1, SliceStorageMut<'a, N, U4, U1, RStride, CStride>>;
+pub type MatrixSliceMut4x1<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U1, SliceStorageMut<'a, T, U4, U1, RStride, CStride>>;
 /// A column-major 4x2 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut4x2<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U2, SliceStorageMut<'a, N, U4, U2, RStride, CStride>>;
+pub type MatrixSliceMut4x2<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U2, SliceStorageMut<'a, T, U4, U2, RStride, CStride>>;
 /// A column-major 4x3 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut4x3<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U3, SliceStorageMut<'a, N, U4, U3, RStride, CStride>>;
+pub type MatrixSliceMut4x3<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U3, SliceStorageMut<'a, T, U4, U3, RStride, CStride>>;
 /// A column-major 4x5 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut4x5<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U5, SliceStorageMut<'a, N, U4, U5, RStride, CStride>>;
+pub type MatrixSliceMut4x5<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U5, SliceStorageMut<'a, T, U4, U5, RStride, CStride>>;
 /// A column-major 4x6 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut4x6<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U6, SliceStorageMut<'a, N, U4, U6, RStride, CStride>>;
+pub type MatrixSliceMut4x6<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U6, SliceStorageMut<'a, T, U4, U6, RStride, CStride>>;
 
 /// A column-major 5x1 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut5x1<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U1, SliceStorageMut<'a, N, U5, U1, RStride, CStride>>;
+pub type MatrixSliceMut5x1<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U1, SliceStorageMut<'a, T, U5, U1, RStride, CStride>>;
 /// A column-major 5x2 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut5x2<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U2, SliceStorageMut<'a, N, U5, U2, RStride, CStride>>;
+pub type MatrixSliceMut5x2<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U2, SliceStorageMut<'a, T, U5, U2, RStride, CStride>>;
 /// A column-major 5x3 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut5x3<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U3, SliceStorageMut<'a, N, U5, U3, RStride, CStride>>;
+pub type MatrixSliceMut5x3<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U3, SliceStorageMut<'a, T, U5, U3, RStride, CStride>>;
 /// A column-major 5x4 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut5x4<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U4, SliceStorageMut<'a, N, U5, U4, RStride, CStride>>;
+pub type MatrixSliceMut5x4<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U4, SliceStorageMut<'a, T, U5, U4, RStride, CStride>>;
 /// A column-major 5x6 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut5x6<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U6, SliceStorageMut<'a, N, U5, U6, RStride, CStride>>;
+pub type MatrixSliceMut5x6<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U6, SliceStorageMut<'a, T, U5, U6, RStride, CStride>>;
 
 /// A column-major 6x1 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut6x1<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U1, SliceStorageMut<'a, N, U6, U1, RStride, CStride>>;
+pub type MatrixSliceMut6x1<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U1, SliceStorageMut<'a, T, U6, U1, RStride, CStride>>;
 /// A column-major 6x2 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut6x2<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U2, SliceStorageMut<'a, N, U6, U2, RStride, CStride>>;
+pub type MatrixSliceMut6x2<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U2, SliceStorageMut<'a, T, U6, U2, RStride, CStride>>;
 /// A column-major 6x3 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut6x3<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U3, SliceStorageMut<'a, N, U6, U3, RStride, CStride>>;
+pub type MatrixSliceMut6x3<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U3, SliceStorageMut<'a, T, U6, U3, RStride, CStride>>;
 /// A column-major 6x4 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut6x4<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U4, SliceStorageMut<'a, N, U6, U4, RStride, CStride>>;
+pub type MatrixSliceMut6x4<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U4, SliceStorageMut<'a, T, U6, U4, RStride, CStride>>;
 /// A column-major 6x5 matrix slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type MatrixSliceMut6x5<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U5, SliceStorageMut<'a, N, U6, U5, RStride, CStride>>;
+pub type MatrixSliceMut6x5<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U5, SliceStorageMut<'a, T, U6, U5, RStride, CStride>>;
 
 /// A column-major matrix slice with 1 row and a number of columns chosen at runtime.
-pub type MatrixSliceMut1xX<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, Dynamic, SliceStorageMut<'a, N, U1, Dynamic, RStride, CStride>>;
+pub type MatrixSliceMut1xX<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, Dynamic, SliceStorageMut<'a, T, U1, Dynamic, RStride, CStride>>;
 /// A column-major matrix slice with 2 rows and a number of columns chosen at runtime.
-pub type MatrixSliceMut2xX<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, Dynamic, SliceStorageMut<'a, N, U2, Dynamic, RStride, CStride>>;
+pub type MatrixSliceMut2xX<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, Dynamic, SliceStorageMut<'a, T, U2, Dynamic, RStride, CStride>>;
 /// A column-major matrix slice with 3 rows and a number of columns chosen at runtime.
-pub type MatrixSliceMut3xX<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, Dynamic, SliceStorageMut<'a, N, U3, Dynamic, RStride, CStride>>;
+pub type MatrixSliceMut3xX<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, Dynamic, SliceStorageMut<'a, T, U3, Dynamic, RStride, CStride>>;
 /// A column-major matrix slice with 4 rows and a number of columns chosen at runtime.
-pub type MatrixSliceMut4xX<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, Dynamic, SliceStorageMut<'a, N, U4, Dynamic, RStride, CStride>>;
+pub type MatrixSliceMut4xX<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, Dynamic, SliceStorageMut<'a, T, U4, Dynamic, RStride, CStride>>;
 /// A column-major matrix slice with 5 rows and a number of columns chosen at runtime.
-pub type MatrixSliceMut5xX<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, Dynamic, SliceStorageMut<'a, N, U5, Dynamic, RStride, CStride>>;
+pub type MatrixSliceMut5xX<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, Dynamic, SliceStorageMut<'a, T, U5, Dynamic, RStride, CStride>>;
 /// A column-major matrix slice with 6 rows and a number of columns chosen at runtime.
-pub type MatrixSliceMut6xX<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, Dynamic, SliceStorageMut<'a, N, U6, Dynamic, RStride, CStride>>;
+pub type MatrixSliceMut6xX<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, Dynamic, SliceStorageMut<'a, T, U6, Dynamic, RStride, CStride>>;
 
 /// A column-major matrix slice with a number of rows chosen at runtime and 1 column.
-pub type MatrixSliceMutXx1<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U1, SliceStorageMut<'a, N, Dynamic, U1, RStride, CStride>>;
+pub type MatrixSliceMutXx1<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U1, SliceStorageMut<'a, T, Dynamic, U1, RStride, CStride>>;
 /// A column-major matrix slice with a number of rows chosen at runtime and 2 columns.
-pub type MatrixSliceMutXx2<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U2, SliceStorageMut<'a, N, Dynamic, U2, RStride, CStride>>;
+pub type MatrixSliceMutXx2<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U2, SliceStorageMut<'a, T, Dynamic, U2, RStride, CStride>>;
 /// A column-major matrix slice with a number of rows chosen at runtime and 3 columns.
-pub type MatrixSliceMutXx3<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U3, SliceStorageMut<'a, N, Dynamic, U3, RStride, CStride>>;
+pub type MatrixSliceMutXx3<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U3, SliceStorageMut<'a, T, Dynamic, U3, RStride, CStride>>;
 /// A column-major matrix slice with a number of rows chosen at runtime and 4 columns.
-pub type MatrixSliceMutXx4<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U4, SliceStorageMut<'a, N, Dynamic, U4, RStride, CStride>>;
+pub type MatrixSliceMutXx4<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U4, SliceStorageMut<'a, T, Dynamic, U4, RStride, CStride>>;
 /// A column-major matrix slice with a number of rows chosen at runtime and 5 columns.
-pub type MatrixSliceMutXx5<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U5, SliceStorageMut<'a, N, Dynamic, U5, RStride, CStride>>;
+pub type MatrixSliceMutXx5<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U5, SliceStorageMut<'a, T, Dynamic, U5, RStride, CStride>>;
 /// A column-major matrix slice with a number of rows chosen at runtime and 6 columns.
-pub type MatrixSliceMutXx6<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U6, SliceStorageMut<'a, N, Dynamic, U6, RStride, CStride>>;
+pub type MatrixSliceMutXx6<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U6, SliceStorageMut<'a, T, Dynamic, U6, RStride, CStride>>;
 
-/// A column vector slice with `D` rows.
-pub type VectorSliceMutN<'a, N, D, RStride = U1, CStride = D> =
-    Matrix<N, D, U1, SliceStorageMut<'a, N, D, U1, RStride, CStride>>;
+/// A column vector slice with dimensions known at compile-time.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
+pub type VectorSliceMut<'a, T, D, RStride = U1, CStride = D> =
+    Matrix<T, D, U1, SliceStorageMut<'a, T, D, U1, RStride, CStride>>;
+
+/// A column vector slice with dimensions known at compile-time.
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
+pub type SVectorSliceMut<'a, T, const D: usize> =
+    Matrix<T, Const<D>, Const<1>, SliceStorageMut<'a, T, Const<D>, Const<1>, Const<1>, Const<D>>>;
 
 /// A column vector slice dynamic numbers of rows and columns.
-pub type DVectorSliceMut<'a, N, RStride = U1, CStride = Dynamic> =
-    Matrix<N, Dynamic, U1, SliceStorageMut<'a, N, Dynamic, U1, RStride, CStride>>;
+///
+/// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
+pub type DVectorSliceMut<'a, T, RStride = U1, CStride = Dynamic> =
+    Matrix<T, Dynamic, U1, SliceStorageMut<'a, T, Dynamic, U1, RStride, CStride>>;
 
 /// A 1D column vector slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type VectorSliceMut1<'a, N, RStride = U1, CStride = U1> =
-    Matrix<N, U1, U1, SliceStorageMut<'a, N, U1, U1, RStride, CStride>>;
+pub type VectorSliceMut1<'a, T, RStride = U1, CStride = U1> =
+    Matrix<T, U1, U1, SliceStorageMut<'a, T, U1, U1, RStride, CStride>>;
 /// A 2D column vector slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type VectorSliceMut2<'a, N, RStride = U1, CStride = U2> =
-    Matrix<N, U2, U1, SliceStorageMut<'a, N, U2, U1, RStride, CStride>>;
+pub type VectorSliceMut2<'a, T, RStride = U1, CStride = U2> =
+    Matrix<T, U2, U1, SliceStorageMut<'a, T, U2, U1, RStride, CStride>>;
 /// A 3D column vector slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type VectorSliceMut3<'a, N, RStride = U1, CStride = U3> =
-    Matrix<N, U3, U1, SliceStorageMut<'a, N, U3, U1, RStride, CStride>>;
+pub type VectorSliceMut3<'a, T, RStride = U1, CStride = U3> =
+    Matrix<T, U3, U1, SliceStorageMut<'a, T, U3, U1, RStride, CStride>>;
 /// A 4D column vector slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type VectorSliceMut4<'a, N, RStride = U1, CStride = U4> =
-    Matrix<N, U4, U1, SliceStorageMut<'a, N, U4, U1, RStride, CStride>>;
+pub type VectorSliceMut4<'a, T, RStride = U1, CStride = U4> =
+    Matrix<T, U4, U1, SliceStorageMut<'a, T, U4, U1, RStride, CStride>>;
 /// A 5D column vector slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type VectorSliceMut5<'a, N, RStride = U1, CStride = U5> =
-    Matrix<N, U5, U1, SliceStorageMut<'a, N, U5, U1, RStride, CStride>>;
+pub type VectorSliceMut5<'a, T, RStride = U1, CStride = U5> =
+    Matrix<T, U5, U1, SliceStorageMut<'a, T, U5, U1, RStride, CStride>>;
 /// A 6D column vector slice.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
-pub type VectorSliceMut6<'a, N, RStride = U1, CStride = U6> =
-    Matrix<N, U6, U1, SliceStorageMut<'a, N, U6, U1, RStride, CStride>>;
+pub type VectorSliceMut6<'a, T, RStride = U1, CStride = U6> =
+    Matrix<T, U6, U1, SliceStorageMut<'a, T, U6, U1, RStride, CStride>>;

src/base/allocator.rs

@@ -9,7 +9,7 @@ use crate::base::storage::ContiguousStorageMut;
 use crate::base::{DefaultAllocator, Scalar};
 
 /// A matrix allocator of a memory buffer that may contain `R::to_usize() * C::to_usize()`
-/// elements of type `N`.
+/// elements of type `T`.
 ///
 /// An allocator is said to be:
 ///   − static:  if `R` and `C` both implement `DimName`.
@@ -17,25 +17,35 @@ 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<N: Scalar, R: Dim, C: Dim = U1>: Any + Sized {
+pub trait Allocator<T: Scalar, R: Dim, C: Dim = U1>: Any + Sized {
     /// The type of buffer this allocator can instanciate.
-    type Buffer: ContiguousStorageMut<N, R, C> + Clone;
+    type Buffer: ContiguousStorageMut<T, R, C> + Clone;
 
     /// 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>;
 
     /// Allocates a buffer initialized with the content of the given iterator.
-    fn allocate_from_iterator<I: IntoIterator<Item = N>>(
+    fn allocate_from_iterator<I: IntoIterator<Item = T>>(
         nrows: R,
         ncols: C,
         iter: I,
     ) -> Self::Buffer;
+
+    unsafe fn allocate_more<R2: Dim, C2: Dim>(
+        nrows: R2,
+        ncols: C2,
+    ) -> mem::MaybeUninit<<Self as Allocator<T, R2, C2>>::Buffer>
+    where
+        Self: Allocator<T, R2, C2>,
+    {
+        <Self as Allocator<T, R2, C2>>::allocate_uninitialized(nrows, ncols)
+    }
 }
 
 /// 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<N: Scalar, RFrom: Dim, CFrom: Dim, RTo: Dim, CTo: Dim>:
-    Allocator<N, RFrom, CFrom> + Allocator<N, RTo, CTo>
+pub trait Reallocator<T: Scalar, RFrom: Dim, CFrom: Dim, RTo: Dim, CTo: Dim>:
+    Allocator<T, RFrom, CFrom> + Allocator<T, RTo, CTo>
 {
     /// Reallocates a buffer of shape `(RTo, CTo)`, possibly reusing a previously allocated buffer
     /// `buf`. Data stored by `buf` are linearly copied to the output:
@@ -47,8 +57,8 @@ pub trait Reallocator<N: Scalar, RFrom: Dim, CFrom: Dim, RTo: Dim, CTo: Dim>:
     unsafe fn reallocate_copy(
         nrows: RTo,
         ncols: CTo,
-        buf: <Self as Allocator<N, RFrom, CFrom>>::Buffer,
-    ) -> <Self as Allocator<N, RTo, CTo>>::Buffer;
+        buf: <Self as Allocator<T, RFrom, CFrom>>::Buffer,
+    ) -> <Self as Allocator<T, RTo, CTo>>::Buffer;
 }
 
 /// The number of rows of the result of a componentwise operation on two matrices.
@@ -59,48 +69,48 @@ pub type SameShapeC<C1, C2> = <ShapeConstraint as SameNumberOfColumns<C1, C2>>::
 
 // TODO: Bad name.
 /// Restricts the given number of rows and columns to be respectively the same.
-pub trait SameShapeAllocator<N, R1, C1, R2, C2>:
-    Allocator<N, R1, C1> + Allocator<N, SameShapeR<R1, R2>, SameShapeC<C1, C2>>
+pub trait SameShapeAllocator<T, R1, C1, R2, C2>:
+    Allocator<T, R1, C1> + Allocator<T, SameShapeR<R1, R2>, SameShapeC<C1, C2>>
 where
     R1: Dim,
     R2: Dim,
     C1: Dim,
     C2: Dim,
-    N: Scalar,
+    T: Scalar,
     ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
 {
 }
 
-impl<N, R1, R2, C1, C2> SameShapeAllocator<N, R1, C1, R2, C2> for DefaultAllocator
+impl<T, R1, R2, C1, C2> SameShapeAllocator<T, R1, C1, R2, C2> for DefaultAllocator
 where
     R1: Dim,
     R2: Dim,
     C1: Dim,
     C2: Dim,
-    N: Scalar,
-    DefaultAllocator: Allocator<N, R1, C1> + Allocator<N, SameShapeR<R1, R2>, SameShapeC<C1, C2>>,
+    T: Scalar,
+    DefaultAllocator: Allocator<T, R1, C1> + Allocator<T, SameShapeR<R1, R2>, SameShapeC<C1, C2>>,
     ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
 {
 }
 
 // XXX: Bad name.
 /// Restricts the given number of rows to be equal.
-pub trait SameShapeVectorAllocator<N, R1, R2>:
-    Allocator<N, R1> + Allocator<N, SameShapeR<R1, R2>> + SameShapeAllocator<N, R1, U1, R2, U1>
+pub trait SameShapeVectorAllocator<T, R1, R2>:
+    Allocator<T, R1> + Allocator<T, SameShapeR<R1, R2>> + SameShapeAllocator<T, R1, U1, R2, U1>
 where
     R1: Dim,
     R2: Dim,
-    N: Scalar,
+    T: Scalar,
     ShapeConstraint: SameNumberOfRows<R1, R2>,
 {
 }
 
-impl<N, R1, R2> SameShapeVectorAllocator<N, R1, R2> for DefaultAllocator
+impl<T, R1, R2> SameShapeVectorAllocator<T, R1, R2> for DefaultAllocator
 where
     R1: Dim,
     R2: Dim,
-    N: Scalar,
-    DefaultAllocator: Allocator<N, R1, U1> + Allocator<N, SameShapeR<R1, R2>>,
+    T: Scalar,
+    DefaultAllocator: Allocator<T, R1, U1> + Allocator<T, SameShapeR<R1, R2>>,
     ShapeConstraint: SameNumberOfRows<R1, R2>,
 {
 }

src/base/array_storage.rs

@@ -34,42 +34,38 @@ use crate::base::Scalar;
 /// A array-based statically sized matrix data storage.
 #[repr(C)]
 #[derive(Copy, Clone, PartialEq, Eq, Hash)]
-pub struct ArrayStorage<N, const R: usize, const C: usize> {
-    data: [[N; R]; C],
-}
+pub struct ArrayStorage<T, const R: usize, const C: usize>(pub [[T; R]; C]);
 
 // TODO: remove this once the stdlib implements Default for arrays.
-impl<N: Default, const R: usize, const C: usize> Default for ArrayStorage<N, R, C>
+impl<T: Default, const R: usize, const C: usize> Default for ArrayStorage<T, R, C>
 where
-    [[N; R]; C]: Default,
+    [[T; R]; C]: Default,
 {
     #[inline]
     fn default() -> Self {
-        Self {
-            data: Default::default(),
-        }
+        Self(Default::default())
     }
 }
 
-impl<N: Debug, const R: usize, const C: usize> Debug for ArrayStorage<N, R, C> {
+impl<T: Debug, const R: usize, const C: usize> Debug for ArrayStorage<T, R, C> {
     #[inline]
     fn fmt(&self, fmt: &mut Formatter) -> fmt::Result {
-        self.data.fmt(fmt)
+        self.0.fmt(fmt)
     }
 }
 
-unsafe impl<N, const R: usize, const C: usize> Storage<N, Const<R>, Const<C>>
-    for ArrayStorage<N, R, C>
+unsafe impl<T, const R: usize, const C: usize> Storage<T, Const<R>, Const<C>>
+    for ArrayStorage<T, R, C>
 where
-    N: Scalar,
-    DefaultAllocator: Allocator<N, Const<R>, Const<C>, Buffer = Self>,
+    T: Scalar,
+    DefaultAllocator: Allocator<T, Const<R>, Const<C>, Buffer = Self>,
 {
     type RStride = Const<1>;
     type CStride = Const<R>;
 
     #[inline]
-    fn ptr(&self) -> *const N {
-        self.data.as_ptr() as *const N
+    fn ptr(&self) -> *const T {
+        self.0.as_ptr() as *const T
     }
 
     #[inline]
@@ -88,65 +84,65 @@ where
     }
 
     #[inline]
-    fn into_owned(self) -> Owned<N, Const<R>, Const<C>>
+    fn into_owned(self) -> Owned<T, Const<R>, Const<C>>
     where
-        DefaultAllocator: Allocator<N, Const<R>, Const<C>>,
+        DefaultAllocator: Allocator<T, Const<R>, Const<C>>,
     {
         self
     }
 
     #[inline]
-    fn clone_owned(&self) -> Owned<N, Const<R>, Const<C>>
+    fn clone_owned(&self) -> Owned<T, Const<R>, Const<C>>
     where
-        DefaultAllocator: Allocator<N, Const<R>, Const<C>>,
+        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]
-    fn as_slice(&self) -> &[N] {
+    fn as_slice(&self) -> &[T] {
         unsafe { std::slice::from_raw_parts(self.ptr(), R * C) }
     }
 }
 
-unsafe impl<N, const R: usize, const C: usize> StorageMut<N, Const<R>, Const<C>>
-    for ArrayStorage<N, R, C>
+unsafe impl<T, const R: usize, const C: usize> StorageMut<T, Const<R>, Const<C>>
+    for ArrayStorage<T, R, C>
 where
-    N: Scalar,
-    DefaultAllocator: Allocator<N, Const<R>, Const<C>, Buffer = Self>,
+    T: Scalar,
+    DefaultAllocator: Allocator<T, Const<R>, Const<C>, Buffer = Self>,
 {
     #[inline]
-    fn ptr_mut(&mut self) -> *mut N {
-        self.data.as_mut_ptr() as *mut N
+    fn ptr_mut(&mut self) -> *mut T {
+        self.0.as_mut_ptr() as *mut T
     }
 
     #[inline]
-    fn as_mut_slice(&mut self) -> &mut [N] {
+    fn as_mut_slice(&mut self) -> &mut [T] {
         unsafe { std::slice::from_raw_parts_mut(self.ptr_mut(), R * C) }
     }
 }
 
-unsafe impl<N, const R: usize, const C: usize> ContiguousStorage<N, Const<R>, Const<C>>
-    for ArrayStorage<N, R, C>
+unsafe impl<T, const R: usize, const C: usize> ContiguousStorage<T, Const<R>, Const<C>>
+    for ArrayStorage<T, R, C>
 where
-    N: Scalar,
-    DefaultAllocator: Allocator<N, Const<R>, Const<C>, Buffer = Self>,
+    T: Scalar,
+    DefaultAllocator: Allocator<T, Const<R>, Const<C>, Buffer = Self>,
 {
 }
 
-unsafe impl<N, const R: usize, const C: usize> ContiguousStorageMut<N, Const<R>, Const<C>>
-    for ArrayStorage<N, R, C>
+unsafe impl<T, const R: usize, const C: usize> ContiguousStorageMut<T, Const<R>, Const<C>>
+    for ArrayStorage<T, R, C>
 where
-    N: Scalar,
-    DefaultAllocator: Allocator<N, Const<R>, Const<C>, Buffer = Self>,
+    T: Scalar,
+    DefaultAllocator: Allocator<T, Const<R>, Const<C>, Buffer = Self>,
 {
 }
 
-impl<N, const R1: usize, const C1: usize, const R2: usize, const C2: usize>
-    ReshapableStorage<N, Const<R1>, Const<C1>, Const<R2>, Const<C2>> for ArrayStorage<N, R1, C1>
+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>
 where
-    N: Scalar,
+    T: Scalar,
     Const<R1>: ToTypenum,
     Const<C1>: ToTypenum,
     Const<R2>: ToTypenum,
@@ -160,13 +156,13 @@ where
         >,
     >,
 {
-    type Output = ArrayStorage<N, R2, C2>;
+    type Output = ArrayStorage<T, R2, C2>;
 
     fn reshape_generic(self, _: Const<R2>, _: Const<C2>) -> Self::Output {
         unsafe {
-            let data: [[N; R2]; C2] = std::mem::transmute_copy(&self.data);
-            std::mem::forget(self.data);
-            ArrayStorage { data }
+            let data: [[T; R2]; C2] = std::mem::transmute_copy(&self.0);
+            std::mem::forget(self.0);
+            ArrayStorage(data)
         }
     }
 }
@@ -178,9 +174,9 @@ where
  */
 // XXX: open an issue for serde so that it allows the serialization/deserialization of all arrays?
 #[cfg(feature = "serde-serialize")]
-impl<N, const R: usize, const C: usize> Serialize for ArrayStorage<N, R, C>
+impl<T, const R: usize, const C: usize> Serialize for ArrayStorage<T, R, C>
 where
-    N: Scalar + Serialize,
+    T: Scalar + Serialize,
 {
     fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
     where
@@ -197,9 +193,9 @@ where
 }
 
 #[cfg(feature = "serde-serialize")]
-impl<'a, N, const R: usize, const C: usize> Deserialize<'a> for ArrayStorage<N, R, C>
+impl<'a, T, const R: usize, const C: usize> Deserialize<'a> for ArrayStorage<T, R, C>
 where
-    N: Scalar + Deserialize<'a>,
+    T: Scalar + Deserialize<'a>,
 {
     fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
     where
@@ -211,14 +207,14 @@ where
 
 #[cfg(feature = "serde-serialize")]
 /// A visitor that produces a matrix array.
-struct ArrayStorageVisitor<N, const R: usize, const C: usize> {
-    marker: PhantomData<N>,
+struct ArrayStorageVisitor<T, const R: usize, const C: usize> {
+    marker: PhantomData<T>,
 }
 
 #[cfg(feature = "serde-serialize")]
-impl<N, const R: usize, const C: usize> ArrayStorageVisitor<N, R, C>
+impl<T, const R: usize, const C: usize> ArrayStorageVisitor<T, R, C>
 where
-    N: Scalar,
+    T: Scalar,
 {
     /// Construct a new sequence visitor.
     pub fn new() -> Self {
@@ -229,18 +225,18 @@ where
 }
 
 #[cfg(feature = "serde-serialize")]
-impl<'a, N, const R: usize, const C: usize> Visitor<'a> for ArrayStorageVisitor<N, R, C>
+impl<'a, T, const R: usize, const C: usize> Visitor<'a> for ArrayStorageVisitor<T, R, C>
 where
-    N: Scalar + Deserialize<'a>,
+    T: Scalar + Deserialize<'a>,
 {
-    type Value = ArrayStorage<N, R, C>;
+    type Value = ArrayStorage<T, R, C>;
 
     fn expecting(&self, formatter: &mut Formatter) -> fmt::Result {
         formatter.write_str("a matrix array")
     }
 
     #[inline]
-    fn visit_seq<V>(self, mut visitor: V) -> Result<ArrayStorage<N, R, C>, V::Error>
+    fn visit_seq<V>(self, mut visitor: V) -> Result<ArrayStorage<T, R, C>, V::Error>
     where
         V: SeqAccess<'a>,
     {
@@ -263,29 +259,21 @@ where
 }
 
 #[cfg(feature = "bytemuck")]
-unsafe impl<N: Scalar + bytemuck::Zeroable, R: DimName, C: DimName> bytemuck::Zeroable
-    for ArrayStorage<N, R, C>
-where
-    R::Value: Mul<C::Value>,
-    Prod<R::Value, C::Value>: ArrayLength<N>,
-    Self: Copy,
+unsafe impl<T: Scalar + Copy + bytemuck::Zeroable, const R: usize, const C: usize>
+    bytemuck::Zeroable for ArrayStorage<T, R, C>
 {
 }
 
 #[cfg(feature = "bytemuck")]
-unsafe impl<N: Scalar + bytemuck::Pod, R: DimName, C: DimName> bytemuck::Pod
-    for ArrayStorage<N, R, C>
-where
-    R::Value: Mul<C::Value>,
-    Prod<R::Value, C::Value>: ArrayLength<N>,
-    Self: Copy,
+unsafe impl<T: Scalar + Copy + bytemuck::Pod, const R: usize, const C: usize> bytemuck::Pod
+    for ArrayStorage<T, R, C>
 {
 }
 
 #[cfg(feature = "abomonation-serialize")]
-impl<N, const R: usize, const C: usize> Abomonation for ArrayStorage<N, R, C>
+impl<T, const R: usize, const C: usize> Abomonation for ArrayStorage<T, R, C>
 where
-    N: Scalar + Abomonation,
+    T: Scalar + Abomonation,
 {
     unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
         for element in self.as_slice() {

src/base/blas.rs

@@ -13,22 +13,22 @@ use crate::base::constraint::{
 use crate::base::dimension::{Const, Dim, Dynamic, U1, U2, U3, U4};
 use crate::base::storage::{Storage, StorageMut};
 use crate::base::{
-    DVectorSlice, DefaultAllocator, Matrix, Scalar, SquareMatrix, Vector, VectorSliceN,
+    DVectorSlice, DefaultAllocator, Matrix, Scalar, SquareMatrix, Vector, VectorSlice,
 };
 
 /// # Dot/scalar product
-impl<N, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S>
+impl<T, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S>
 where
-    N: Scalar + Zero + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + ClosedAdd + ClosedMul,
 {
     #[inline(always)]
     fn dotx<R2: Dim, C2: Dim, SB>(
         &self,
-        rhs: &Matrix<N, R2, C2, SB>,
-        conjugate: impl Fn(N) -> N,
-    ) -> N
+        rhs: &Matrix<T, R2, C2, SB>,
+        conjugate: impl Fn(T) -> T,
+    ) -> T
     where
-        SB: Storage<N, R2, C2>,
+        SB: Storage<T, R2, C2>,
         ShapeConstraint: DimEq<R, R2> + DimEq<C, C2>,
     {
         assert!(
@@ -92,7 +92,7 @@ where
         //
         // And this comment from bluss:
         // https://users.rust-lang.org/t/how-to-zip-two-slices-efficiently/2048/12
-        let mut res = N::zero();
+        let mut res = T::zero();
 
         // We have to define them outside of the loop (and not inside at first assignment)
         // otherwise vectorization won't kick in for some reason.
@@ -108,14 +108,14 @@ where
         for j in 0..self.ncols() {
             let mut i = 0;
 
-            acc0 = N::zero();
-            acc1 = N::zero();
-            acc2 = N::zero();
-            acc3 = N::zero();
-            acc4 = N::zero();
-            acc5 = N::zero();
-            acc6 = N::zero();
-            acc7 = N::zero();
+            acc0 = T::zero();
+            acc1 = T::zero();
+            acc2 = T::zero();
+            acc3 = T::zero();
+            acc4 = T::zero();
+            acc5 = T::zero();
+            acc6 = T::zero();
+            acc7 = T::zero();
 
             while self.nrows() - i >= 8 {
                 acc0 += unsafe {
@@ -193,9 +193,9 @@ where
     /// ```
     ///
     #[inline]
-    pub fn dot<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<N, R2, C2, SB>) -> N
+    pub fn dot<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> T
     where
-        SB: Storage<N, R2, C2>,
+        SB: Storage<T, R2, C2>,
         ShapeConstraint: DimEq<R, R2> + DimEq<C, C2>,
     {
         self.dotx(rhs, |e| e)
@@ -221,13 +221,13 @@ where
     /// assert_ne!(vec1.dotc(&vec2), vec1.dot(&vec2));
     /// ```
     #[inline]
-    pub fn dotc<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<N, R2, C2, SB>) -> N
+    pub fn dotc<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> T
     where
-        N: SimdComplexField,
-        SB: Storage<N, R2, C2>,
+        T: SimdComplexField,
+        SB: Storage<T, R2, C2>,
         ShapeConstraint: DimEq<R, R2> + DimEq<C, C2>,
     {
-        self.dotx(rhs, N::simd_conjugate)
+        self.dotx(rhs, T::simd_conjugate)
     }
 
     /// The dot product between the transpose of `self` and `rhs`.
@@ -248,9 +248,9 @@ where
     /// assert_eq!(mat1.tr_dot(&mat2), 9.1);
     /// ```
     #[inline]
-    pub fn tr_dot<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<N, R2, C2, SB>) -> N
+    pub fn tr_dot<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> T
     where
-        SB: Storage<N, R2, C2>,
+        SB: Storage<T, R2, C2>,
         ShapeConstraint: DimEq<C, R2> + DimEq<R, C2>,
     {
         let (nrows, ncols) = self.shape();
@@ -260,7 +260,7 @@ where
             "Transposed dot product dimension mismatch."
         );
 
-        let mut res = N::zero();
+        let mut res = T::zero();
 
         for j in 0..self.nrows() {
             for i in 0..self.ncols() {
@@ -275,17 +275,17 @@ where
     }
 }
 
-fn array_axcpy<N>(
-    y: &mut [N],
-    a: N,
-    x: &[N],
-    c: N,
-    beta: N,
+fn array_axcpy<T>(
+    y: &mut [T],
+    a: T,
+    x: &[T],
+    c: T,
+    beta: T,
     stride1: usize,
     stride2: usize,
     len: usize,
 ) where
-    N: Scalar + Zero + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + ClosedAdd + ClosedMul,
 {
     for i in 0..len {
         unsafe {
@@ -298,9 +298,9 @@ fn array_axcpy<N>(
     }
 }
 
-fn array_axc<N>(y: &mut [N], a: N, x: &[N], c: N, stride1: usize, stride2: usize, len: usize)
+fn array_axc<T>(y: &mut [T], a: T, x: &[T], c: T, stride1: usize, stride2: usize, len: usize)
 where
-    N: Scalar + Zero + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + ClosedAdd + ClosedMul,
 {
     for i in 0..len {
         unsafe {
@@ -312,10 +312,10 @@ where
 }
 
 /// # BLAS functions
-impl<N, D: Dim, S> Vector<N, D, S>
+impl<T, D: Dim, S> Vector<T, D, S>
 where
-    N: Scalar + Zero + ClosedAdd + ClosedMul,
-    S: StorageMut<N, D>,
+    T: Scalar + Zero + ClosedAdd + ClosedMul,
+    S: StorageMut<T, D>,
 {
     /// Computes `self = a * x * c + b * self`.
     ///
@@ -331,9 +331,9 @@ where
     /// assert_eq!(vec1, Vector3::new(6.0, 12.0, 18.0));
     /// ```
     #[inline]
-    pub fn axcpy<D2: Dim, SB>(&mut self, a: N, x: &Vector<N, D2, SB>, c: N, b: N)
+    pub fn axcpy<D2: Dim, SB>(&mut self, a: T, x: &Vector<T, D2, SB>, c: T, b: T)
     where
-        SB: Storage<N, D2>,
+        SB: Storage<T, D2>,
         ShapeConstraint: DimEq<D, D2>,
     {
         assert_eq!(self.nrows(), x.nrows(), "Axcpy: mismatched vector shapes.");
@@ -365,14 +365,14 @@ where
     /// assert_eq!(vec1, Vector3::new(6.0, 12.0, 18.0));
     /// ```
     #[inline]
-    pub fn axpy<D2: Dim, SB>(&mut self, a: N, x: &Vector<N, D2, SB>, b: N)
+    pub fn axpy<D2: Dim, SB>(&mut self, a: T, x: &Vector<T, D2, SB>, b: T)
     where
-        N: One,
-        SB: Storage<N, D2>,
+        T: One,
+        SB: Storage<T, D2>,
         ShapeConstraint: DimEq<D, D2>,
     {
         assert_eq!(self.nrows(), x.nrows(), "Axpy: mismatched vector shapes.");
-        self.axcpy(a, x, N::one(), b)
+        self.axcpy(a, x, T::one(), b)
     }
 
     /// Computes `self = alpha * a * x + beta * self`, where `a` is a matrix, `x` a vector, and
@@ -394,14 +394,14 @@ where
     #[inline]
     pub fn gemv<R2: Dim, C2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        a: &Matrix<N, R2, C2, SB>,
-        x: &Vector<N, D3, SC>,
-        beta: N,
+        alpha: T,
+        a: &Matrix<T, R2, C2, SB>,
+        x: &Vector<T, D3, SC>,
+        beta: T,
     ) where
-        N: One,
-        SB: Storage<N, R2, C2>,
-        SC: Storage<N, D3>,
+        T: One,
+        SB: Storage<T, R2, C2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<D, R2> + AreMultipliable<R2, C2, D3, U1>,
     {
         let dim1 = self.nrows();
@@ -418,7 +418,7 @@ where
             // because we documented the guaranty that `self` is
             // never read if `beta` is zero.
             if beta.is_zero() {
-                self.fill(N::zero());
+                self.fill(T::zero());
             } else {
                 *self *= beta;
             }
@@ -434,25 +434,25 @@ where
             let col2 = a.column(j);
             let val = unsafe { x.vget_unchecked(j).inlined_clone() };
 
-            self.axcpy(alpha.inlined_clone(), &col2, val, N::one());
+            self.axcpy(alpha.inlined_clone(), &col2, val, T::one());
         }
     }
 
     #[inline(always)]
     fn xxgemv<D2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        a: &SquareMatrix<N, D2, SB>,
-        x: &Vector<N, D3, SC>,
-        beta: N,
+        alpha: T,
+        a: &SquareMatrix<T, D2, SB>,
+        x: &Vector<T, D3, SC>,
+        beta: T,
         dot: impl Fn(
-            &DVectorSlice<N, SB::RStride, SB::CStride>,
-            &DVectorSlice<N, SC::RStride, SC::CStride>,
-        ) -> N,
+            &DVectorSlice<T, SB::RStride, SB::CStride>,
+            &DVectorSlice<T, SC::RStride, SC::CStride>,
+        ) -> T,
     ) where
-        N: One,
-        SB: Storage<N, D2, D2>,
-        SC: Storage<N, D3>,
+        T: One,
+        SB: Storage<T, D2, D2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<D, D2> + AreMultipliable<D2, D2, D3, U1>,
     {
         let dim1 = self.nrows();
@@ -490,7 +490,7 @@ where
             self.rows_range_mut(j + 1..).axpy(
                 alpha.inlined_clone() * val,
                 &col2.rows_range(j + 1..),
-                N::one(),
+                T::one(),
             );
         }
     }
@@ -501,14 +501,14 @@ where
     #[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: N,
-        a: &SquareMatrix<N, D2, SB>,
-        x: &Vector<N, D3, SC>,
-        beta: N,
+        alpha: T,
+        a: &SquareMatrix<T, D2, SB>,
+        x: &Vector<T, D3, SC>,
+        beta: T,
     ) where
-        N: One,
-        SB: Storage<N, D2, D2>,
-        SC: Storage<N, D3>,
+        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)
@@ -545,14 +545,14 @@ where
     #[inline]
     pub fn sygemv<D2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        a: &SquareMatrix<N, D2, SB>,
-        x: &Vector<N, D3, SC>,
-        beta: N,
+        alpha: T,
+        a: &SquareMatrix<T, D2, SB>,
+        x: &Vector<T, D3, SC>,
+        beta: T,
     ) where
-        N: One,
-        SB: Storage<N, D2, D2>,
-        SC: Storage<N, D3>,
+        T: One,
+        SB: Storage<T, D2, D2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<D, D2> + AreMultipliable<D2, D2, D3, U1>,
     {
         self.xxgemv(alpha, a, x, beta, |a, b| a.dot(b))
@@ -590,14 +590,14 @@ where
     #[inline]
     pub fn hegemv<D2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        a: &SquareMatrix<N, D2, SB>,
-        x: &Vector<N, D3, SC>,
-        beta: N,
+        alpha: T,
+        a: &SquareMatrix<T, D2, SB>,
+        x: &Vector<T, D3, SC>,
+        beta: T,
     ) where
-        N: SimdComplexField,
-        SB: Storage<N, D2, D2>,
-        SC: Storage<N, D3>,
+        T: SimdComplexField,
+        SB: Storage<T, D2, D2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<D, D2> + AreMultipliable<D2, D2, D3, U1>,
     {
         self.xxgemv(alpha, a, x, beta, |a, b| a.dotc(b))
@@ -606,15 +606,15 @@ where
     #[inline(always)]
     fn gemv_xx<R2: Dim, C2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        a: &Matrix<N, R2, C2, SB>,
-        x: &Vector<N, D3, SC>,
-        beta: N,
-        dot: impl Fn(&VectorSliceN<N, R2, SB::RStride, SB::CStride>, &Vector<N, D3, SC>) -> N,
+        alpha: T,
+        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,
     ) where
-        N: One,
-        SB: Storage<N, R2, C2>,
-        SC: Storage<N, D3>,
+        T: One,
+        SB: Storage<T, R2, C2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<D, C2> + AreMultipliable<C2, R2, D3, U1>,
     {
         let dim1 = self.nrows();
@@ -665,14 +665,14 @@ where
     #[inline]
     pub fn gemv_tr<R2: Dim, C2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        a: &Matrix<N, R2, C2, SB>,
-        x: &Vector<N, D3, SC>,
-        beta: N,
+        alpha: T,
+        a: &Matrix<T, R2, C2, SB>,
+        x: &Vector<T, D3, SC>,
+        beta: T,
     ) where
-        N: One,
-        SB: Storage<N, R2, C2>,
-        SC: Storage<N, D3>,
+        T: One,
+        SB: Storage<T, R2, C2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<D, C2> + AreMultipliable<C2, R2, D3, U1>,
     {
         self.gemv_xx(alpha, a, x, beta, |a, b| a.dot(b))
@@ -700,36 +700,36 @@ where
     #[inline]
     pub fn gemv_ad<R2: Dim, C2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        a: &Matrix<N, R2, C2, SB>,
-        x: &Vector<N, D3, SC>,
-        beta: N,
+        alpha: T,
+        a: &Matrix<T, R2, C2, SB>,
+        x: &Vector<T, D3, SC>,
+        beta: T,
     ) where
-        N: SimdComplexField,
-        SB: Storage<N, R2, C2>,
-        SC: Storage<N, D3>,
+        T: SimdComplexField,
+        SB: Storage<T, R2, C2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<D, C2> + AreMultipliable<C2, R2, D3, U1>,
     {
         self.gemv_xx(alpha, a, x, beta, |a, b| a.dotc(b))
     }
 }
 
-impl<N, R1: Dim, C1: Dim, S: StorageMut<N, R1, C1>> Matrix<N, R1, C1, S>
+impl<T, R1: Dim, C1: Dim, S: StorageMut<T, R1, C1>> Matrix<T, R1, C1, S>
 where
-    N: Scalar + Zero + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + ClosedAdd + ClosedMul,
 {
     #[inline(always)]
     fn gerx<D2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        x: &Vector<N, D2, SB>,
-        y: &Vector<N, D3, SC>,
-        beta: N,
-        conjugate: impl Fn(N) -> N,
+        alpha: T,
+        x: &Vector<T, D2, SB>,
+        y: &Vector<T, D3, SC>,
+        beta: T,
+        conjugate: impl Fn(T) -> T,
     ) where
-        N: One,
-        SB: Storage<N, D2>,
-        SC: Storage<N, D3>,
+        T: One,
+        SB: Storage<T, D2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<R1, D2> + DimEq<C1, D3>,
     {
         let (nrows1, ncols1) = self.shape();
@@ -768,14 +768,14 @@ where
     #[inline]
     pub fn ger<D2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        x: &Vector<N, D2, SB>,
-        y: &Vector<N, D3, SC>,
-        beta: N,
+        alpha: T,
+        x: &Vector<T, D2, SB>,
+        y: &Vector<T, D3, SC>,
+        beta: T,
     ) where
-        N: One,
-        SB: Storage<N, D2>,
-        SC: Storage<N, D3>,
+        T: One,
+        SB: Storage<T, D2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<R1, D2> + DimEq<C1, D3>,
     {
         self.gerx(alpha, x, y, beta, |e| e)
@@ -801,14 +801,14 @@ where
     #[inline]
     pub fn gerc<D2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        x: &Vector<N, D2, SB>,
-        y: &Vector<N, D3, SC>,
-        beta: N,
+        alpha: T,
+        x: &Vector<T, D2, SB>,
+        y: &Vector<T, D3, SC>,
+        beta: T,
     ) where
-        N: SimdComplexField,
-        SB: Storage<N, D2>,
-        SC: Storage<N, D3>,
+        T: SimdComplexField,
+        SB: Storage<T, D2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<R1, D2> + DimEq<C1, D3>,
     {
         self.gerx(alpha, x, y, beta, SimdComplexField::simd_conjugate)
@@ -838,14 +838,14 @@ where
     #[inline]
     pub fn gemm<R2: Dim, C2: Dim, R3: Dim, C3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        a: &Matrix<N, R2, C2, SB>,
-        b: &Matrix<N, R3, C3, SC>,
-        beta: N,
+        alpha: T,
+        a: &Matrix<T, R2, C2, SB>,
+        b: &Matrix<T, R3, C3, SC>,
+        beta: T,
     ) where
-        N: One,
-        SB: Storage<N, R2, C2>,
-        SC: Storage<N, R3, C3>,
+        T: One,
+        SB: Storage<T, R2, C2>,
+        SC: Storage<T, R3, C3>,
         ShapeConstraint: SameNumberOfRows<R1, R2>
             + SameNumberOfColumns<C1, C3>
             + AreMultipliable<R2, C2, R3, C3>,
@@ -897,14 +897,14 @@ where
                         // because we documented the guaranty that `self` is
                         // never read if `beta` is zero.
                         if beta.is_zero() {
-                            self.fill(N::zero());
+                            self.fill(T::zero());
                         } else {
                             *self *= beta;
                         }
                         return;
                     }
 
-                    if N::is::<f32>() {
+                    if T::is::<f32>() {
                         let (rsa, csa) = a.strides();
                         let (rsb, csb) = b.strides();
                         let (rsc, csc) = self.strides();
@@ -928,7 +928,7 @@ where
                             );
                         }
                         return;
-                    } else if N::is::<f64>() {
+                    } else if T::is::<f64>() {
                         let (rsa, csa) = a.strides();
                         let (rsb, csb) = b.strides();
                         let (rsc, csc) = self.strides();
@@ -993,14 +993,14 @@ where
     #[inline]
     pub fn gemm_tr<R2: Dim, C2: Dim, R3: Dim, C3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        a: &Matrix<N, R2, C2, SB>,
-        b: &Matrix<N, R3, C3, SC>,
-        beta: N,
+        alpha: T,
+        a: &Matrix<T, R2, C2, SB>,
+        b: &Matrix<T, R3, C3, SC>,
+        beta: T,
     ) where
-        N: One,
-        SB: Storage<N, R2, C2>,
-        SC: Storage<N, R3, C3>,
+        T: One,
+        SB: Storage<T, R2, C2>,
+        SC: Storage<T, R3, C3>,
         ShapeConstraint: SameNumberOfRows<R1, C2>
             + SameNumberOfColumns<C1, C3>
             + AreMultipliable<C2, R2, R3, C3>,
@@ -1055,14 +1055,14 @@ where
     #[inline]
     pub fn gemm_ad<R2: Dim, C2: Dim, R3: Dim, C3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        a: &Matrix<N, R2, C2, SB>,
-        b: &Matrix<N, R3, C3, SC>,
-        beta: N,
+        alpha: T,
+        a: &Matrix<T, R2, C2, SB>,
+        b: &Matrix<T, R3, C3, SC>,
+        beta: T,
     ) where
-        N: SimdComplexField,
-        SB: Storage<N, R2, C2>,
-        SC: Storage<N, R3, C3>,
+        T: SimdComplexField,
+        SB: Storage<T, R2, C2>,
+        SC: Storage<T, R3, C3>,
         ShapeConstraint: SameNumberOfRows<R1, C2>
             + SameNumberOfColumns<C1, C3>
             + AreMultipliable<C2, R2, R3, C3>,
@@ -1088,22 +1088,22 @@ where
     }
 }
 
-impl<N, R1: Dim, C1: Dim, S: StorageMut<N, R1, C1>> Matrix<N, R1, C1, S>
+impl<T, R1: Dim, C1: Dim, S: StorageMut<T, R1, C1>> Matrix<T, R1, C1, S>
 where
-    N: Scalar + Zero + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + ClosedAdd + ClosedMul,
 {
     #[inline(always)]
     fn xxgerx<D2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        x: &Vector<N, D2, SB>,
-        y: &Vector<N, D3, SC>,
-        beta: N,
-        conjugate: impl Fn(N) -> N,
+        alpha: T,
+        x: &Vector<T, D2, SB>,
+        y: &Vector<T, D3, SC>,
+        beta: T,
+        conjugate: impl Fn(T) -> T,
     ) where
-        N: One,
-        SB: Storage<N, D2>,
-        SC: Storage<N, D3>,
+        T: One,
+        SB: Storage<T, D2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<R1, D2> + DimEq<C1, D3>,
     {
         let dim1 = self.nrows();
@@ -1151,14 +1151,14 @@ where
     #[deprecated(note = "This is renamed `syger` to match the original BLAS terminology.")]
     pub fn ger_symm<D2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        x: &Vector<N, D2, SB>,
-        y: &Vector<N, D3, SC>,
-        beta: N,
+        alpha: T,
+        x: &Vector<T, D2, SB>,
+        y: &Vector<T, D3, SC>,
+        beta: T,
     ) where
-        N: One,
-        SB: Storage<N, D2>,
-        SC: Storage<N, D3>,
+        T: One,
+        SB: Storage<T, D2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<R1, D2> + DimEq<C1, D3>,
     {
         self.syger(alpha, x, y, beta)
@@ -1187,14 +1187,14 @@ where
     #[inline]
     pub fn syger<D2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        x: &Vector<N, D2, SB>,
-        y: &Vector<N, D3, SC>,
-        beta: N,
+        alpha: T,
+        x: &Vector<T, D2, SB>,
+        y: &Vector<T, D3, SC>,
+        beta: T,
     ) where
-        N: One,
-        SB: Storage<N, D2>,
-        SC: Storage<N, D3>,
+        T: One,
+        SB: Storage<T, D2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<R1, D2> + DimEq<C1, D3>,
     {
         self.xxgerx(alpha, x, y, beta, |e| e)
@@ -1222,23 +1222,23 @@ where
     #[inline]
     pub fn hegerc<D2: Dim, D3: Dim, SB, SC>(
         &mut self,
-        alpha: N,
-        x: &Vector<N, D2, SB>,
-        y: &Vector<N, D3, SC>,
-        beta: N,
+        alpha: T,
+        x: &Vector<T, D2, SB>,
+        y: &Vector<T, D3, SC>,
+        beta: T,
     ) where
-        N: SimdComplexField,
-        SB: Storage<N, D2>,
-        SC: Storage<N, D3>,
+        T: SimdComplexField,
+        SB: Storage<T, D2>,
+        SC: Storage<T, D3>,
         ShapeConstraint: DimEq<R1, D2> + DimEq<C1, D3>,
     {
         self.xxgerx(alpha, x, y, beta, SimdComplexField::simd_conjugate)
     }
 }
 
-impl<N, D1: Dim, S: StorageMut<N, D1, D1>> SquareMatrix<N, D1, S>
+impl<T, D1: Dim, S: StorageMut<T, D1, D1>> SquareMatrix<T, D1, S>
 where
-    N: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
 {
     /// Computes the quadratic form `self = alpha * lhs * mid * lhs.transpose() + beta * self`.
     ///
@@ -1268,27 +1268,27 @@ where
     /// assert_relative_eq!(mat, expected);
     pub fn quadform_tr_with_workspace<D2, S2, R3, C3, S3, D4, S4>(
         &mut self,
-        work: &mut Vector<N, D2, S2>,
-        alpha: N,
-        lhs: &Matrix<N, R3, C3, S3>,
-        mid: &SquareMatrix<N, D4, S4>,
-        beta: N,
+        work: &mut Vector<T, D2, S2>,
+        alpha: T,
+        lhs: &Matrix<T, R3, C3, S3>,
+        mid: &SquareMatrix<T, D4, S4>,
+        beta: T,
     ) where
         D2: Dim,
         R3: Dim,
         C3: Dim,
         D4: Dim,
-        S2: StorageMut<N, D2>,
-        S3: Storage<N, R3, C3>,
-        S4: Storage<N, D4, D4>,
+        S2: StorageMut<T, D2>,
+        S3: Storage<T, R3, C3>,
+        S4: Storage<T, D4, D4>,
         ShapeConstraint: DimEq<D1, D2> + DimEq<D1, R3> + DimEq<D2, R3> + DimEq<C3, D4>,
     {
-        work.gemv(N::one(), lhs, &mid.column(0), N::zero());
+        work.gemv(T::one(), lhs, &mid.column(0), T::zero());
         self.ger(alpha.inlined_clone(), work, &lhs.column(0), beta);
 
         for j in 1..mid.ncols() {
-            work.gemv(N::one(), lhs, &mid.column(j), N::zero());
-            self.ger(alpha.inlined_clone(), work, &lhs.column(j), N::one());
+            work.gemv(T::one(), lhs, &mid.column(j), T::zero());
+            self.ger(alpha.inlined_clone(), work, &lhs.column(j), T::one());
         }
     }
 
@@ -1315,21 +1315,22 @@ where
     /// assert_relative_eq!(mat, expected);
     pub fn quadform_tr<R3, C3, S3, D4, S4>(
         &mut self,
-        alpha: N,
-        lhs: &Matrix<N, R3, C3, S3>,
-        mid: &SquareMatrix<N, D4, S4>,
-        beta: N,
+        alpha: T,
+        lhs: &Matrix<T, R3, C3, S3>,
+        mid: &SquareMatrix<T, D4, S4>,
+        beta: T,
     ) where
         R3: Dim,
         C3: Dim,
         D4: Dim,
-        S3: Storage<N, R3, C3>,
-        S4: Storage<N, D4, D4>,
+        S3: Storage<T, R3, C3>,
+        S4: Storage<T, D4, D4>,
         ShapeConstraint: DimEq<D1, D1> + DimEq<D1, R3> + DimEq<C3, D4>,
-        DefaultAllocator: Allocator<N, D1>,
+        DefaultAllocator: Allocator<T, D1>,
     {
-        let mut work =
-            unsafe { crate::unimplemented_or_uninitialized_generic!(self.data.shape().0, Const::<1>) };
+        let mut work = unsafe {
+            crate::unimplemented_or_uninitialized_generic!(self.data.shape().0, Const::<1>)
+        };
         self.quadform_tr_with_workspace(&mut work, alpha, lhs, mid, beta)
     }
 
@@ -1360,28 +1361,28 @@ where
     /// assert_relative_eq!(mat, expected);
     pub fn quadform_with_workspace<D2, S2, D3, S3, R4, C4, S4>(
         &mut self,
-        work: &mut Vector<N, D2, S2>,
-        alpha: N,
-        mid: &SquareMatrix<N, D3, S3>,
-        rhs: &Matrix<N, R4, C4, S4>,
-        beta: N,
+        work: &mut Vector<T, D2, S2>,
+        alpha: T,
+        mid: &SquareMatrix<T, D3, S3>,
+        rhs: &Matrix<T, R4, C4, S4>,
+        beta: T,
     ) where
         D2: Dim,
         D3: Dim,
         R4: Dim,
         C4: Dim,
-        S2: StorageMut<N, D2>,
-        S3: Storage<N, D3, D3>,
-        S4: Storage<N, R4, C4>,
+        S2: StorageMut<T, D2>,
+        S3: Storage<T, D3, D3>,
+        S4: Storage<T, R4, C4>,
         ShapeConstraint:
             DimEq<D3, R4> + DimEq<D1, C4> + DimEq<D2, D3> + AreMultipliable<C4, R4, D2, U1>,
     {
-        work.gemv(N::one(), mid, &rhs.column(0), N::zero());
+        work.gemv(T::one(), mid, &rhs.column(0), T::zero());
         self.column_mut(0)
             .gemv_tr(alpha.inlined_clone(), &rhs, work, beta.inlined_clone());
 
         for j in 1..rhs.ncols() {
-            work.gemv(N::one(), mid, &rhs.column(j), N::zero());
+            work.gemv(T::one(), mid, &rhs.column(j), T::zero());
             self.column_mut(j)
                 .gemv_tr(alpha.inlined_clone(), &rhs, work, beta.inlined_clone());
         }
@@ -1409,21 +1410,22 @@ where
     /// assert_relative_eq!(mat, expected);
     pub fn quadform<D2, S2, R3, C3, S3>(
         &mut self,
-        alpha: N,
-        mid: &SquareMatrix<N, D2, S2>,
-        rhs: &Matrix<N, R3, C3, S3>,
-        beta: N,
+        alpha: T,
+        mid: &SquareMatrix<T, D2, S2>,
+        rhs: &Matrix<T, R3, C3, S3>,
+        beta: T,
     ) where
         D2: Dim,
         R3: Dim,
         C3: Dim,
-        S2: Storage<N, D2, D2>,
-        S3: Storage<N, R3, C3>,
+        S2: Storage<T, D2, D2>,
+        S3: Storage<T, R3, C3>,
         ShapeConstraint: DimEq<D2, R3> + DimEq<D1, C3> + AreMultipliable<C3, R3, D2, U1>,
-        DefaultAllocator: Allocator<N, D2>,
+        DefaultAllocator: Allocator<T, D2>,
     {
-        let mut work =
-            unsafe { crate::unimplemented_or_uninitialized_generic!(mid.data.shape().0, Const::<1>) };
+        let mut work = unsafe {
+            crate::unimplemented_or_uninitialized_generic!(mid.data.shape().0, Const::<1>)
+        };
         self.quadform_with_workspace(&mut work, alpha, mid, rhs, beta)
     }
 }

src/base/cg.rs

@@ -11,8 +11,8 @@ use crate::base::allocator::Allocator;
 use crate::base::dimension::{DimName, DimNameDiff, DimNameSub, U1};
 use crate::base::storage::{Storage, StorageMut};
 use crate::base::{
-    Const, DefaultAllocator, Matrix3, Matrix4, MatrixN, Scalar, SquareMatrix, Unit, Vector,
-    Vector2, Vector3, VectorN,
+    Const, DefaultAllocator, Matrix3, Matrix4, OMatrix, OVector, Scalar, SquareMatrix, Unit,
+    Vector, Vector2, Vector3,
 };
 use crate::geometry::{
     Isometry, IsometryMatrix3, Orthographic3, Perspective3, Point, Point2, Point3, Rotation2,
@@ -22,26 +22,26 @@ use crate::geometry::{
 use simba::scalar::{ClosedAdd, ClosedMul, RealField};
 
 /// # Translation and scaling in any dimension
-impl<N, D: DimName> MatrixN<N, D>
+impl<T, D: DimName> OMatrix<T, D, D>
 where
-    N: Scalar + Zero + One,
-    DefaultAllocator: Allocator<N, D, D>,
+    T: Scalar + Zero + One,
+    DefaultAllocator: Allocator<T, D, D>,
 {
     /// Creates a new homogeneous matrix that applies the same scaling factor on each dimension.
     #[inline]
-    pub fn new_scaling(scaling: N) -> Self {
+    pub fn new_scaling(scaling: T) -> Self {
         let mut res = Self::from_diagonal_element(scaling);
-        res[(D::dim() - 1, D::dim() - 1)] = N::one();
+        res[(D::dim() - 1, D::dim() - 1)] = T::one();
 
         res
     }
 
     /// Creates a new homogeneous matrix that applies a distinct scaling factor for each dimension.
     #[inline]
-    pub fn new_nonuniform_scaling<SB>(scaling: &Vector<N, DimNameDiff<D, U1>, SB>) -> Self
+    pub fn new_nonuniform_scaling<SB>(scaling: &Vector<T, DimNameDiff<D, U1>, SB>) -> Self
     where
         D: DimNameSub<U1>,
-        SB: Storage<N, DimNameDiff<D, U1>>,
+        SB: Storage<T, DimNameDiff<D, U1>>,
     {
         let mut res = Self::identity();
         for i in 0..scaling.len() {
@@ -53,24 +53,27 @@ where
 
     /// Creates a new homogeneous matrix that applies a pure translation.
     #[inline]
-    pub fn new_translation<SB>(translation: &Vector<N, DimNameDiff<D, U1>, SB>) -> Self
+    pub fn new_translation<SB>(translation: &Vector<T, DimNameDiff<D, U1>, SB>) -> Self
     where
         D: DimNameSub<U1>,
-        SB: Storage<N, DimNameDiff<D, U1>>,
+        SB: Storage<T, DimNameDiff<D, U1>>,
     {
         let mut res = Self::identity();
-        res.fixed_slice_mut::<DimNameDiff<D, U1>, U1>(0, D::dim() - 1)
-            .copy_from(translation);
+        res.generic_slice_mut(
+            (0, D::dim() - 1),
+            (DimNameDiff::<D, U1>::name(), Const::<1>),
+        )
+        .copy_from(translation);
 
         res
     }
 }
 
 /// # 2D transformations as a Matrix3
-impl<N: RealField> Matrix3<N> {
+impl<T: RealField> Matrix3<T> {
     /// Builds a 2 dimensional homogeneous rotation matrix from an angle in radian.
     #[inline]
-    pub fn new_rotation(angle: N) -> Self {
+    pub fn new_rotation(angle: T) -> Self {
         Rotation2::new(angle).to_homogeneous()
     }
 
@@ -78,9 +81,9 @@ impl<N: RealField> Matrix3<N> {
     ///
     /// Can be used to implement "zoom_to" functionality.
     #[inline]
-    pub fn new_nonuniform_scaling_wrt_point(scaling: &Vector2<N>, pt: &Point2<N>) -> Self {
-        let zero = N::zero();
-        let one = N::one();
+    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,
@@ -96,12 +99,12 @@ impl<N: RealField> Matrix3<N> {
 }
 
 /// # 3D transformations as a Matrix4
-impl<N: RealField> Matrix4<N> {
+impl<T: RealField> Matrix4<T> {
     /// Builds a 3D homogeneous rotation matrix from an axis and an angle (multiplied together).
     ///
     /// Returns the identity matrix if the given argument is zero.
     #[inline]
-    pub fn new_rotation(axisangle: Vector3<N>) -> Self {
+    pub fn new_rotation(axisangle: Vector3<T>) -> Self {
         Rotation3::new(axisangle).to_homogeneous()
     }
 
@@ -109,7 +112,7 @@ impl<N: RealField> Matrix4<N> {
     ///
     /// Returns the identity matrix if the given argument is zero.
     #[inline]
-    pub fn new_rotation_wrt_point(axisangle: Vector3<N>, pt: Point3<N>) -> Self {
+    pub fn new_rotation_wrt_point(axisangle: Vector3<T>, pt: Point3<T>) -> Self {
         let rot = Rotation3::from_scaled_axis(axisangle);
         Isometry::rotation_wrt_point(rot, pt).to_homogeneous()
     }
@@ -118,9 +121,9 @@ impl<N: RealField> Matrix4<N> {
     ///
     /// Can be used to implement "zoom_to" functionality.
     #[inline]
-    pub fn new_nonuniform_scaling_wrt_point(scaling: &Vector3<N>, pt: &Point3<N>) -> Self {
-        let zero = N::zero();
-        let one = N::one();
+    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,
@@ -146,31 +149,31 @@ impl<N: RealField> Matrix4<N> {
     /// Returns the identity matrix if the given argument is zero.
     /// This is identical to `Self::new_rotation`.
     #[inline]
-    pub fn from_scaled_axis(axisangle: Vector3<N>) -> Self {
+    pub fn from_scaled_axis(axisangle: Vector3<T>) -> Self {
         Rotation3::from_scaled_axis(axisangle).to_homogeneous()
     }
 
     /// Creates a new rotation from Euler angles.
     ///
     /// The primitive rotations are applied in order: 1 roll − 2 pitch − 3 yaw.
-    pub fn from_euler_angles(roll: N, pitch: N, yaw: N) -> Self {
+    pub fn from_euler_angles(roll: T, pitch: T, yaw: T) -> Self {
         Rotation3::from_euler_angles(roll, pitch, yaw).to_homogeneous()
     }
 
     /// Builds a 3D homogeneous rotation matrix from an axis and a rotation angle.
-    pub fn from_axis_angle(axis: &Unit<Vector3<N>>, angle: N) -> Self {
+    pub fn from_axis_angle(axis: &Unit<Vector3<T>>, angle: T) -> Self {
         Rotation3::from_axis_angle(axis, angle).to_homogeneous()
     }
 
     /// Creates a new homogeneous matrix for an orthographic projection.
     #[inline]
-    pub fn new_orthographic(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> Self {
+    pub fn new_orthographic(left: T, right: T, bottom: T, top: T, znear: T, zfar: T) -> Self {
         Orthographic3::new(left, right, bottom, top, znear, zfar).into_inner()
     }
 
     /// Creates a new homogeneous matrix for a perspective projection.
     #[inline]
-    pub fn new_perspective(aspect: N, fovy: N, znear: N, zfar: N) -> Self {
+    pub fn new_perspective(aspect: T, fovy: T, znear: T, zfar: T) -> Self {
         Perspective3::new(aspect, fovy, znear, zfar).into_inner()
     }
 
@@ -180,40 +183,40 @@ impl<N: RealField> Matrix4<N> {
     /// It maps the view direction `target - eye` to the positive `z` axis and the origin to the
     /// `eye`.
     #[inline]
-    pub fn face_towards(eye: &Point3<N>, target: &Point3<N>, up: &Vector3<N>) -> Self {
+    pub fn face_towards(eye: &Point3<T>, target: &Point3<T>, up: &Vector3<T>) -> Self {
         IsometryMatrix3::face_towards(eye, target, up).to_homogeneous()
     }
 
     /// Deprecated: Use [Matrix4::face_towards] instead.
     #[deprecated(note = "renamed to `face_towards`")]
-    pub fn new_observer_frame(eye: &Point3<N>, target: &Point3<N>, up: &Vector3<N>) -> Self {
+    pub fn new_observer_frame(eye: &Point3<T>, target: &Point3<T>, up: &Vector3<T>) -> Self {
         Matrix4::face_towards(eye, target, up)
     }
 
     /// Builds a right-handed look-at view matrix.
     #[inline]
-    pub fn look_at_rh(eye: &Point3<N>, target: &Point3<N>, up: &Vector3<N>) -> Self {
+    pub fn look_at_rh(eye: &Point3<T>, target: &Point3<T>, up: &Vector3<T>) -> Self {
         IsometryMatrix3::look_at_rh(eye, target, up).to_homogeneous()
     }
 
     /// Builds a left-handed look-at view matrix.
     #[inline]
-    pub fn look_at_lh(eye: &Point3<N>, target: &Point3<N>, up: &Vector3<N>) -> Self {
+    pub fn look_at_lh(eye: &Point3<T>, target: &Point3<T>, up: &Vector3<T>) -> Self {
         IsometryMatrix3::look_at_lh(eye, target, up).to_homogeneous()
     }
 }
 
 /// # Append/prepend translation and scaling
-impl<N: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<N, D, D>>
-    SquareMatrix<N, D, S>
+impl<T: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<T, D, D>>
+    SquareMatrix<T, D, S>
 {
     /// Computes the transformation equal to `self` followed by an uniform scaling factor.
     #[inline]
     #[must_use = "Did you mean to use append_scaling_mut()?"]
-    pub fn append_scaling(&self, scaling: N) -> MatrixN<N, D>
+    pub fn append_scaling(&self, scaling: T) -> OMatrix<T, D, D>
     where
         D: DimNameSub<U1>,
-        DefaultAllocator: Allocator<N, D, D>,
+        DefaultAllocator: Allocator<T, D, D>,
     {
         let mut res = self.clone_owned();
         res.append_scaling_mut(scaling);
@@ -223,10 +226,10 @@ impl<N: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<N, D
     /// Computes the transformation equal to an uniform scaling factor followed by `self`.
     #[inline]
     #[must_use = "Did you mean to use prepend_scaling_mut()?"]
-    pub fn prepend_scaling(&self, scaling: N) -> MatrixN<N, D>
+    pub fn prepend_scaling(&self, scaling: T) -> OMatrix<T, D, D>
     where
         D: DimNameSub<U1>,
-        DefaultAllocator: Allocator<N, D, D>,
+        DefaultAllocator: Allocator<T, D, D>,
     {
         let mut res = self.clone_owned();
         res.prepend_scaling_mut(scaling);
@@ -238,12 +241,12 @@ impl<N: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<N, D
     #[must_use = "Did you mean to use append_nonuniform_scaling_mut()?"]
     pub fn append_nonuniform_scaling<SB>(
         &self,
-        scaling: &Vector<N, DimNameDiff<D, U1>, SB>,
-    ) -> MatrixN<N, D>
+        scaling: &Vector<T, DimNameDiff<D, U1>, SB>,
+    ) -> OMatrix<T, D, D>
     where
         D: DimNameSub<U1>,
-        SB: Storage<N, DimNameDiff<D, U1>>,
-        DefaultAllocator: Allocator<N, D, D>,
+        SB: Storage<T, DimNameDiff<D, U1>>,
+        DefaultAllocator: Allocator<T, D, D>,
     {
         let mut res = self.clone_owned();
         res.append_nonuniform_scaling_mut(scaling);
@@ -255,12 +258,12 @@ impl<N: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<N, D
     #[must_use = "Did you mean to use prepend_nonuniform_scaling_mut()?"]
     pub fn prepend_nonuniform_scaling<SB>(
         &self,
-        scaling: &Vector<N, DimNameDiff<D, U1>, SB>,
-    ) -> MatrixN<N, D>
+        scaling: &Vector<T, DimNameDiff<D, U1>, SB>,
+    ) -> OMatrix<T, D, D>
     where
         D: DimNameSub<U1>,
-        SB: Storage<N, DimNameDiff<D, U1>>,
-        DefaultAllocator: Allocator<N, D, D>,
+        SB: Storage<T, DimNameDiff<D, U1>>,
+        DefaultAllocator: Allocator<T, D, D>,
     {
         let mut res = self.clone_owned();
         res.prepend_nonuniform_scaling_mut(scaling);
@@ -270,11 +273,14 @@ impl<N: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<N, D
     /// Computes the transformation equal to `self` followed by a translation.
     #[inline]
     #[must_use = "Did you mean to use append_translation_mut()?"]
-    pub fn append_translation<SB>(&self, shift: &Vector<N, DimNameDiff<D, U1>, SB>) -> MatrixN<N, D>
+    pub fn append_translation<SB>(
+        &self,
+        shift: &Vector<T, DimNameDiff<D, U1>, SB>,
+    ) -> OMatrix<T, D, D>
     where
         D: DimNameSub<U1>,
-        SB: Storage<N, DimNameDiff<D, U1>>,
-        DefaultAllocator: Allocator<N, D, D>,
+        SB: Storage<T, DimNameDiff<D, U1>>,
+        DefaultAllocator: Allocator<T, D, D>,
     {
         let mut res = self.clone_owned();
         res.append_translation_mut(shift);
@@ -286,12 +292,12 @@ impl<N: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<N, D
     #[must_use = "Did you mean to use prepend_translation_mut()?"]
     pub fn prepend_translation<SB>(
         &self,
-        shift: &Vector<N, DimNameDiff<D, U1>, SB>,
-    ) -> MatrixN<N, D>
+        shift: &Vector<T, DimNameDiff<D, U1>, SB>,
+    ) -> OMatrix<T, D, D>
     where
         D: DimNameSub<U1>,
-        SB: Storage<N, DimNameDiff<D, U1>>,
-        DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimNameDiff<D, U1>>,
+        SB: Storage<T, DimNameDiff<D, U1>>,
+        DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimNameDiff<D, U1>>,
     {
         let mut res = self.clone_owned();
         res.prepend_translation_mut(shift);
@@ -300,36 +306,36 @@ impl<N: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<N, D
 
     /// Computes in-place the transformation equal to `self` followed by an uniform scaling factor.
     #[inline]
-    pub fn append_scaling_mut(&mut self, scaling: N)
+    pub fn append_scaling_mut(&mut self, scaling: T)
     where
-        S: StorageMut<N, D, D>,
+        S: StorageMut<T, D, D>,
         D: DimNameSub<U1>,
     {
-        let mut to_scale = self.fixed_rows_mut::<DimNameDiff<D, U1>>(0);
+        let mut to_scale = self.rows_generic_mut(0, DimNameDiff::<D, U1>::name());
         to_scale *= scaling;
     }
 
     /// Computes in-place the transformation equal to an uniform scaling factor followed by `self`.
     #[inline]
-    pub fn prepend_scaling_mut(&mut self, scaling: N)
+    pub fn prepend_scaling_mut(&mut self, scaling: T)
     where
-        S: StorageMut<N, D, D>,
+        S: StorageMut<T, D, D>,
         D: DimNameSub<U1>,
     {
-        let mut to_scale = self.fixed_columns_mut::<DimNameDiff<D, U1>>(0);
+        let mut to_scale = self.columns_generic_mut(0, DimNameDiff::<D, U1>::name());
         to_scale *= scaling;
     }
 
     /// Computes in-place the transformation equal to `self` followed by a non-uniform scaling factor.
     #[inline]
-    pub fn append_nonuniform_scaling_mut<SB>(&mut self, scaling: &Vector<N, DimNameDiff<D, U1>, SB>)
+    pub fn append_nonuniform_scaling_mut<SB>(&mut self, scaling: &Vector<T, DimNameDiff<D, U1>, SB>)
     where
-        S: StorageMut<N, D, D>,
+        S: StorageMut<T, D, D>,
         D: DimNameSub<U1>,
-        SB: Storage<N, DimNameDiff<D, U1>>,
+        SB: Storage<T, DimNameDiff<D, U1>>,
     {
         for i in 0..scaling.len() {
-            let mut to_scale = self.fixed_rows_mut::<U1>(i);
+            let mut to_scale = self.fixed_rows_mut::<1>(i);
             to_scale *= scaling[i].inlined_clone();
         }
     }
@@ -338,25 +344,25 @@ impl<N: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<N, D
     #[inline]
     pub fn prepend_nonuniform_scaling_mut<SB>(
         &mut self,
-        scaling: &Vector<N, DimNameDiff<D, U1>, SB>,
+        scaling: &Vector<T, DimNameDiff<D, U1>, SB>,
     ) where
-        S: StorageMut<N, D, D>,
+        S: StorageMut<T, D, D>,
         D: DimNameSub<U1>,
-        SB: Storage<N, DimNameDiff<D, U1>>,
+        SB: Storage<T, DimNameDiff<D, U1>>,
     {
         for i in 0..scaling.len() {
-            let mut to_scale = self.fixed_columns_mut::<U1>(i);
+            let mut to_scale = self.fixed_columns_mut::<1>(i);
             to_scale *= scaling[i].inlined_clone();
         }
     }
 
     /// Computes the transformation equal to `self` followed by a translation.
     #[inline]
-    pub fn append_translation_mut<SB>(&mut self, shift: &Vector<N, DimNameDiff<D, U1>, SB>)
+    pub fn append_translation_mut<SB>(&mut self, shift: &Vector<T, DimNameDiff<D, U1>, SB>)
     where
-        S: StorageMut<N, D, D>,
+        S: StorageMut<T, D, D>,
         D: DimNameSub<U1>,
-        SB: Storage<N, DimNameDiff<D, U1>>,
+        SB: Storage<T, DimNameDiff<D, U1>>,
     {
         for i in 0..D::dim() {
             for j in 0..D::dim() - 1 {
@@ -368,41 +374,55 @@ impl<N: Scalar + Zero + One + ClosedMul + ClosedAdd, D: DimName, S: Storage<N, D
 
     /// Computes the transformation equal to a translation followed by `self`.
     #[inline]
-    pub fn prepend_translation_mut<SB>(&mut self, shift: &Vector<N, DimNameDiff<D, U1>, SB>)
+    pub fn prepend_translation_mut<SB>(&mut self, shift: &Vector<T, DimNameDiff<D, U1>, SB>)
     where
         D: DimNameSub<U1>,
-        S: StorageMut<N, D, D>,
-        SB: Storage<N, DimNameDiff<D, U1>>,
-        DefaultAllocator: Allocator<N, DimNameDiff<D, U1>>,
+        S: StorageMut<T, D, D>,
+        SB: Storage<T, DimNameDiff<D, U1>>,
+        DefaultAllocator: Allocator<T, DimNameDiff<D, U1>>,
     {
         let scale = self
-            .fixed_slice::<U1, DimNameDiff<D, U1>>(D::dim() - 1, 0)
+            .generic_slice(
+                (D::dim() - 1, 0),
+                (Const::<1>, DimNameDiff::<D, U1>::name()),
+            )
             .tr_dot(&shift);
-        let post_translation =
-            self.fixed_slice::<DimNameDiff<D, U1>, DimNameDiff<D, U1>>(0, 0) * shift;
+        let post_translation = self.generic_slice(
+            (0, 0),
+            (DimNameDiff::<D, U1>::name(), DimNameDiff::<D, U1>::name()),
+        ) * shift;
 
         self[(D::dim() - 1, D::dim() - 1)] += scale;
 
-        let mut translation = self.fixed_slice_mut::<DimNameDiff<D, U1>, U1>(0, D::dim() - 1);
+        let mut translation = self.generic_slice_mut(
+            (0, D::dim() - 1),
+            (DimNameDiff::<D, U1>::name(), Const::<1>),
+        );
         translation += post_translation;
     }
 }
 
 /// # Transformation of vectors and points
-impl<N: RealField, D: DimNameSub<U1>, S: Storage<N, D, D>> SquareMatrix<N, D, S>
+impl<T: RealField, D: DimNameSub<U1>, S: Storage<T, D, D>> SquareMatrix<T, D, S>
 where
-    DefaultAllocator: Allocator<N, D, D>
-        + Allocator<N, DimNameDiff<D, U1>>
-        + Allocator<N, DimNameDiff<D, U1>, DimNameDiff<D, U1>>,
+    DefaultAllocator: Allocator<T, D, D>
+        + Allocator<T, DimNameDiff<D, U1>>
+        + Allocator<T, DimNameDiff<D, U1>, DimNameDiff<D, U1>>,
 {
     /// Transforms the given vector, assuming the matrix `self` uses homogeneous coordinates.
     #[inline]
     pub fn transform_vector(
         &self,
-        v: &VectorN<N, DimNameDiff<D, U1>>,
-    ) -> VectorN<N, DimNameDiff<D, U1>> {
-        let transform = self.fixed_slice::<DimNameDiff<D, U1>, DimNameDiff<D, U1>>(0, 0);
-        let normalizer = self.fixed_slice::<U1, DimNameDiff<D, U1>>(D::dim() - 1, 0);
+        v: &OVector<T, DimNameDiff<D, U1>>,
+    ) -> OVector<T, DimNameDiff<D, U1>> {
+        let transform = self.generic_slice(
+            (0, 0),
+            (DimNameDiff::<D, U1>::name(), DimNameDiff::<D, U1>::name()),
+        );
+        let normalizer = self.generic_slice(
+            (D::dim() - 1, 0),
+            (Const::<1>, DimNameDiff::<D, U1>::name()),
+        );
         let n = normalizer.tr_dot(&v);
 
         if !n.is_zero() {
@@ -413,13 +433,13 @@ where
     }
 }
 
-impl<N: RealField, S: Storage<N, Const<3>, Const<3>>> SquareMatrix<N, Const<3>, S> {
+impl<T: RealField, S: Storage<T, Const<3>, Const<3>>> SquareMatrix<T, Const<3>, S> {
     /// Transforms the given point, assuming the matrix `self` uses homogeneous coordinates.
     #[inline]
-    pub fn transform_point(&self, pt: &Point<N, 2>) -> Point<N, 2> {
-        let transform = self.fixed_slice::<Const<2>, Const<2>>(0, 0);
-        let translation = self.fixed_slice::<Const<2>, U1>(0, 2);
-        let normalizer = self.fixed_slice::<U1, Const<2>>(2, 0);
+    pub fn transform_point(&self, pt: &Point<T, 2>) -> Point<T, 2> {
+        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)) };
 
         if !n.is_zero() {
@@ -430,13 +450,13 @@ impl<N: RealField, S: Storage<N, Const<3>, Const<3>>> SquareMatrix<N, Const<3>,
     }
 }
 
-impl<N: RealField, S: Storage<N, Const<4>, Const<4>>> SquareMatrix<N, Const<4>, S> {
+impl<T: RealField, S: Storage<T, Const<4>, Const<4>>> SquareMatrix<T, Const<4>, S> {
     /// Transforms the given point, assuming the matrix `self` uses homogeneous coordinates.
     #[inline]
-    pub fn transform_point(&self, pt: &Point<N, 3>) -> Point<N, 3> {
-        let transform = self.fixed_slice::<Const<3>, Const<3>>(0, 0);
-        let translation = self.fixed_slice::<Const<3>, U1>(0, 3);
-        let normalizer = self.fixed_slice::<U1, Const<3>>(3, 0);
+    pub fn transform_point(&self, pt: &Point<T, 3>) -> Point<T, 3> {
+        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)) };
 
         if !n.is_zero() {

src/base/componentwise.rs

@@ -10,13 +10,13 @@ use crate::base::allocator::{Allocator, SameShapeAllocator};
 use crate::base::constraint::{SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
 use crate::base::dimension::Dim;
 use crate::base::storage::{Storage, StorageMut};
-use crate::base::{DefaultAllocator, Matrix, MatrixMN, MatrixSum, Scalar};
+use crate::base::{DefaultAllocator, Matrix, MatrixSum, OMatrix, Scalar};
 use crate::ClosedAdd;
 
 /// The type of the result of a matrix component-wise operation.
-pub type MatrixComponentOp<N, R1, C1, R2, C2> = MatrixSum<N, R1, C1, R2, C2>;
+pub type MatrixComponentOp<T, R1, C1, R2, C2> = MatrixSum<T, R1, C1, R2, C2>;
 
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     /// Computes the component-wise absolute value.
     ///
     /// # Example
@@ -28,10 +28,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(a.abs(), Matrix2::new(0.0, 1.0, 2.0, 3.0))
     /// ```
     #[inline]
-    pub fn abs(&self) -> MatrixMN<N, R, C>
+    pub fn abs(&self) -> OMatrix<T, R, C>
     where
-        N: Signed,
-        DefaultAllocator: Allocator<N, R, C>,
+        T: Signed,
+        DefaultAllocator: Allocator<T, R, C>,
     {
         let mut res = self.clone_owned();
 
@@ -49,11 +49,11 @@ macro_rules! component_binop_impl(
     ($($binop: ident, $binop_mut: ident, $binop_assign: ident, $cmpy: ident, $Trait: ident . $op: ident . $op_assign: ident, $desc:expr, $desc_cmpy:expr, $desc_mut:expr);* $(;)*) => {$(
         #[doc = $desc]
         #[inline]
-        pub fn $binop<R2, C2, SB>(&self, rhs: &Matrix<N, R2, C2, SB>) -> MatrixComponentOp<N, R1, C1, R2, C2>
-            where N: $Trait,
+        pub fn $binop<R2, C2, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> MatrixComponentOp<T, R1, C1, R2, C2>
+            where T: $Trait,
                   R2: Dim, C2: Dim,
-                  SB: Storage<N, R2, C2>,
-                  DefaultAllocator: SameShapeAllocator<N, R1, C1, R2, C2>,
+                  SB: Storage<T, R2, C2>,
+                  DefaultAllocator: SameShapeAllocator<T, R1, C1, R2, C2>,
                   ShapeConstraint:  SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
 
             assert_eq!(self.shape(), rhs.shape(), "Componentwise mul/div: mismatched matrix dimensions.");
@@ -73,13 +73,13 @@ macro_rules! component_binop_impl(
         // componentwise binop plus Y.
         #[doc = $desc_cmpy]
         #[inline]
-        pub fn $cmpy<R2, C2, SB, R3, C3, SC>(&mut self, alpha: N, a: &Matrix<N, R2, C2, SB>, b: &Matrix<N, R3, C3, SC>, beta: N)
-            where N: $Trait + Zero + Mul<N, Output = N> + Add<N, Output = N>,
+        pub fn $cmpy<R2, C2, SB, R3, C3, SC>(&mut self, alpha: T, a: &Matrix<T, R2, C2, SB>, b: &Matrix<T, R3, C3, SC>, beta: T)
+            where T: $Trait + Zero + Mul<T, Output = T> + Add<T, Output = T>,
                   R2: Dim, C2: Dim,
                   R3: Dim, C3: Dim,
-                  SA: StorageMut<N, R1, C1>,
-                  SB: Storage<N, R2, C2>,
-                  SC: Storage<N, R3, C3>,
+                  SA: StorageMut<T, R1, C1>,
+                  SB: Storage<T, R2, C2>,
+                  SC: Storage<T, R3, C3>,
                   ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> +
                                    SameNumberOfRows<R1, R3> + SameNumberOfColumns<C1, C3> {
             assert_eq!(self.shape(), a.shape(), "Componentwise mul/div: mismatched matrix dimensions.");
@@ -109,12 +109,12 @@ macro_rules! component_binop_impl(
 
         #[doc = $desc_mut]
         #[inline]
-        pub fn $binop_assign<R2, C2, SB>(&mut self, rhs: &Matrix<N, R2, C2, SB>)
-            where N: $Trait,
+        pub fn $binop_assign<R2, C2, SB>(&mut self, rhs: &Matrix<T, R2, C2, SB>)
+            where T: $Trait,
                   R2: Dim,
                   C2: Dim,
-                  SA: StorageMut<N, R1, C1>,
-                  SB: Storage<N, R2, C2>,
+                  SA: StorageMut<T, R1, C1>,
+                  SB: Storage<T, R2, C2>,
                   ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
 
             assert_eq!(self.shape(), rhs.shape(), "Componentwise mul/div: mismatched matrix dimensions.");
@@ -131,12 +131,12 @@ macro_rules! component_binop_impl(
         #[doc = $desc_mut]
         #[inline]
         #[deprecated(note = "This is renamed using the `_assign` suffix instead of the `_mut` suffix.")]
-        pub fn $binop_mut<R2, C2, SB>(&mut self, rhs: &Matrix<N, R2, C2, SB>)
-            where N: $Trait,
+        pub fn $binop_mut<R2, C2, SB>(&mut self, rhs: &Matrix<T, R2, C2, SB>)
+            where T: $Trait,
                   R2: Dim,
                   C2: Dim,
-                  SA: StorageMut<N, R1, C1>,
-                  SB: Storage<N, R2, C2>,
+                  SA: StorageMut<T, R1, C1>,
+                  SB: Storage<T, R2, C2>,
                   ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
             self.$binop_assign(rhs)
         }
@@ -144,7 +144,7 @@ macro_rules! component_binop_impl(
 );
 
 /// # Componentwise operations
-impl<N: Scalar, R1: Dim, C1: Dim, SA: Storage<N, R1, C1>> Matrix<N, R1, C1, SA> {
+impl<T: Scalar, R1: Dim, C1: Dim, SA: Storage<T, R1, C1>> Matrix<T, R1, C1, SA> {
     component_binop_impl!(
         component_mul, component_mul_mut, component_mul_assign, cmpy, ClosedMul.mul.mul_assign,
         r"
@@ -241,30 +241,30 @@ impl<N: Scalar, R1: Dim, C1: Dim, SA: Storage<N, R1, C1>> Matrix<N, R1, C1, SA>
 
     /// Computes the infimum (aka. componentwise min) of two matrices/vectors.
     #[inline]
-    pub fn inf(&self, other: &Self) -> MatrixMN<N, R1, C1>
+    pub fn inf(&self, other: &Self) -> OMatrix<T, R1, C1>
     where
-        N: SimdPartialOrd,
-        DefaultAllocator: Allocator<N, R1, C1>,
+        T: SimdPartialOrd,
+        DefaultAllocator: Allocator<T, R1, C1>,
     {
         self.zip_map(other, |a, b| a.simd_min(b))
     }
 
     /// Computes the supremum (aka. componentwise max) of two matrices/vectors.
     #[inline]
-    pub fn sup(&self, other: &Self) -> MatrixMN<N, R1, C1>
+    pub fn sup(&self, other: &Self) -> OMatrix<T, R1, C1>
     where
-        N: SimdPartialOrd,
-        DefaultAllocator: Allocator<N, R1, C1>,
+        T: SimdPartialOrd,
+        DefaultAllocator: Allocator<T, R1, C1>,
     {
         self.zip_map(other, |a, b| a.simd_max(b))
     }
 
     /// Computes the (infimum, supremum) of two matrices/vectors.
     #[inline]
-    pub fn inf_sup(&self, other: &Self) -> (MatrixMN<N, R1, C1>, MatrixMN<N, R1, C1>)
+    pub fn inf_sup(&self, other: &Self) -> (OMatrix<T, R1, C1>, OMatrix<T, R1, C1>)
     where
-        N: SimdPartialOrd,
-        DefaultAllocator: Allocator<N, R1, C1>,
+        T: SimdPartialOrd,
+        DefaultAllocator: Allocator<T, R1, C1>,
     {
         // TODO: can this be optimized?
         (self.inf(other), self.sup(other))
@@ -273,10 +273,10 @@ impl<N: Scalar, R1: Dim, C1: Dim, SA: Storage<N, R1, C1>> Matrix<N, R1, C1, SA>
     /// Adds a scalar to `self`.
     #[inline]
     #[must_use = "Did you mean to use add_scalar_mut()?"]
-    pub fn add_scalar(&self, rhs: N) -> MatrixMN<N, R1, C1>
+    pub fn add_scalar(&self, rhs: T) -> OMatrix<T, R1, C1>
     where
-        N: ClosedAdd,
-        DefaultAllocator: Allocator<N, R1, C1>,
+        T: ClosedAdd,
+        DefaultAllocator: Allocator<T, R1, C1>,
     {
         let mut res = self.clone_owned();
         res.add_scalar_mut(rhs);
@@ -285,10 +285,10 @@ impl<N: Scalar, R1: Dim, C1: Dim, SA: Storage<N, R1, C1>> Matrix<N, R1, C1, SA>
 
     /// Adds a scalar to `self` in-place.
     #[inline]
-    pub fn add_scalar_mut(&mut self, rhs: N)
+    pub fn add_scalar_mut(&mut self, rhs: T)
     where
-        N: ClosedAdd,
-        SA: StorageMut<N, R1, C1>,
+        T: ClosedAdd,
+        SA: StorageMut<T, R1, C1>,
     {
         for e in self.iter_mut() {
             *e += rhs.inlined_clone()

src/base/construction.rs

@@ -22,9 +22,7 @@ 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::{
-    Const, DefaultAllocator, Matrix, MatrixMN, MatrixN, Scalar, Unit, Vector, VectorN,
-};
+use crate::base::{Const, DefaultAllocator, Matrix, OMatrix, OVector, Scalar, Unit, Vector};
 
 /// 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
@@ -33,7 +31,7 @@ macro_rules! unimplemented_or_uninitialized_generic {
     ($nrows:expr, $ncols:expr) => {{
         #[cfg(feature="no_unsound_assume_init")] {
             // Some of the call sites need the number of rows and columns from this to infer a type, so
-            // uninitialized memory is used to infer the type, as `N: Zero` isn't available at all callsites.
+            // uninitialized memory is used to infer the type, as `T: Zero` isn't available at all callsites.
             // This may technically still be UB even though the assume_init is dead code, but all callsites should be fixed before #556 is closed.
             let typeinference_helper = crate::base::Matrix::new_uninitialized_generic($nrows, $ncols);
             unimplemented!();
@@ -49,9 +47,9 @@ macro_rules! unimplemented_or_uninitialized_generic {
 /// the dimension as inputs.
 ///
 /// These functions should only be used when working on dimension-generic code.
-impl<N: Scalar, R: Dim, C: Dim> MatrixMN<N, R, C>
+impl<T: Scalar, R: Dim, C: Dim> OMatrix<T, R, C>
 where
-    DefaultAllocator: Allocator<N, R, C>,
+    DefaultAllocator: Allocator<T, R, C>,
 {
     /// Creates a new uninitialized matrix. If the matrix has a compile-time dimension, this panics
     /// if `nrows != R::to_usize()` or `ncols != C::to_usize()`.
@@ -62,7 +60,7 @@ where
 
     /// Creates a matrix with all its elements set to `elem`.
     #[inline]
-    pub fn from_element_generic(nrows: R, ncols: C, elem: N) -> Self {
+    pub fn from_element_generic(nrows: R, ncols: C, elem: T) -> Self {
         let len = nrows.value() * ncols.value();
         Self::from_iterator_generic(nrows, ncols, iter::repeat(elem).take(len))
     }
@@ -71,7 +69,7 @@ where
     ///
     /// Same as `from_element_generic`.
     #[inline]
-    pub fn repeat_generic(nrows: R, ncols: C, elem: N) -> Self {
+    pub fn repeat_generic(nrows: R, ncols: C, elem: T) -> Self {
         let len = nrows.value() * ncols.value();
         Self::from_iterator_generic(nrows, ncols, iter::repeat(elem).take(len))
     }
@@ -80,16 +78,16 @@ where
     #[inline]
     pub fn zeros_generic(nrows: R, ncols: C) -> Self
     where
-        N: Zero,
+        T: Zero,
     {
-        Self::from_element_generic(nrows, ncols, N::zero())
+        Self::from_element_generic(nrows, ncols, T::zero())
     }
 
     /// Creates a matrix with all its elements filled by an iterator.
     #[inline]
     pub fn from_iterator_generic<I>(nrows: R, ncols: C, iter: I) -> Self
     where
-        I: IntoIterator<Item = N>,
+        I: IntoIterator<Item = T>,
     {
         Self::from_data(DefaultAllocator::allocate_from_iterator(nrows, ncols, iter))
     }
@@ -100,7 +98,7 @@ where
     /// The order of elements in the slice must follow the usual mathematic writing, i.e.,
     /// row-by-row.
     #[inline]
-    pub fn from_row_slice_generic(nrows: R, ncols: C, slice: &[N]) -> Self {
+    pub fn from_row_slice_generic(nrows: R, ncols: C, slice: &[T]) -> Self {
         assert!(
             slice.len() == nrows.value() * ncols.value(),
             "Matrix init. error: the slice did not contain the right number of elements."
@@ -121,7 +119,7 @@ where
     /// Creates a matrix with its elements filled with the components provided by a slice. The
     /// components must have the same layout as the matrix data storage (i.e. column-major).
     #[inline]
-    pub fn from_column_slice_generic(nrows: R, ncols: C, slice: &[N]) -> Self {
+    pub fn from_column_slice_generic(nrows: R, ncols: C, slice: &[T]) -> Self {
         Self::from_iterator_generic(nrows, ncols, slice.iter().cloned())
     }
 
@@ -130,7 +128,7 @@ where
     #[inline]
     pub fn from_fn_generic<F>(nrows: R, ncols: C, mut f: F) -> Self
     where
-        F: FnMut(usize, usize) -> N,
+        F: FnMut(usize, usize) -> T,
     {
         let mut res: Self = unsafe { crate::unimplemented_or_uninitialized_generic!(nrows, ncols) };
 
@@ -150,9 +148,9 @@ where
     #[inline]
     pub fn identity_generic(nrows: R, ncols: C) -> Self
     where
-        N: Zero + One,
+        T: Zero + One,
     {
-        Self::from_diagonal_element_generic(nrows, ncols, N::one())
+        Self::from_diagonal_element_generic(nrows, ncols, T::one())
     }
 
     /// Creates a new matrix with its diagonal filled with copies of `elt`.
@@ -160,9 +158,9 @@ where
     /// If the matrix is not square, the largest square submatrix starting at index `(0, 0)` is set
     /// to the identity matrix. All other entries are set to zero.
     #[inline]
-    pub fn from_diagonal_element_generic(nrows: R, ncols: C, elt: N) -> Self
+    pub fn from_diagonal_element_generic(nrows: R, ncols: C, elt: T) -> Self
     where
-        N: Zero + One,
+        T: Zero + One,
     {
         let mut res = Self::zeros_generic(nrows, ncols);
 
@@ -178,9 +176,9 @@ where
     ///
     /// Panics if `elts.len()` is larger than the minimum among `nrows` and `ncols`.
     #[inline]
-    pub fn from_partial_diagonal_generic(nrows: R, ncols: C, elts: &[N]) -> Self
+    pub fn from_partial_diagonal_generic(nrows: R, ncols: C, elts: &[T]) -> Self
     where
-        N: Zero,
+        T: Zero,
     {
         let mut res = Self::zeros_generic(nrows, ncols);
         assert!(
@@ -212,9 +210,9 @@ where
     ///         m.m31 == 7.0 && m.m32 == 8.0 && m.m33 == 9.0);
     /// ```
     #[inline]
-    pub fn from_rows<SB>(rows: &[Matrix<N, Const<1>, C, SB>]) -> Self
+    pub fn from_rows<SB>(rows: &[Matrix<T, Const<1>, C, SB>]) -> Self
     where
-        SB: Storage<N, Const<1>, C>,
+        SB: Storage<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());
@@ -254,9 +252,9 @@ where
     ///         m.m31 == 3.0 && m.m32 == 6.0 && m.m33 == 9.0);
     /// ```
     #[inline]
-    pub fn from_columns<SB>(columns: &[Vector<N, R, SB>]) -> Self
+    pub fn from_columns<SB>(columns: &[Vector<T, R, SB>]) -> Self
     where
-        SB: Storage<N, R>,
+        SB: Storage<T, R>,
     {
         assert!(!columns.is_empty(), "At least one column must be given.");
         let ncols = C::try_to_usize().unwrap_or_else(|| columns.len());
@@ -284,7 +282,7 @@ where
     #[cfg(feature = "rand")]
     pub fn new_random_generic(nrows: R, ncols: C) -> Self
     where
-        Standard: Distribution<N>,
+        Standard: Distribution<T>,
     {
         let mut rng = rand::thread_rng();
         Self::from_fn_generic(nrows, ncols, |_, _| rng.gen())
@@ -293,7 +291,7 @@ where
     /// Creates a matrix filled with random values from the given distribution.
     #[inline]
     #[cfg(feature = "rand-no-std")]
-    pub fn from_distribution_generic<Distr: Distribution<N> + ?Sized, G: Rng + ?Sized>(
+    pub fn from_distribution_generic<Distr: Distribution<T> + ?Sized, G: Rng + ?Sized>(
         nrows: R,
         ncols: C,
         distribution: &Distr,
@@ -321,15 +319,15 @@ where
     /// ```
     #[inline]
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn from_vec_generic(nrows: R, ncols: C, data: Vec<N>) -> Self {
+    pub fn from_vec_generic(nrows: R, ncols: C, data: Vec<T>) -> Self {
         Self::from_iterator_generic(nrows, ncols, data)
     }
 }
 
-impl<N, D: Dim> MatrixN<N, D>
+impl<T, D: Dim> OMatrix<T, D, D>
 where
-    N: Scalar,
-    DefaultAllocator: Allocator<N, D, D>,
+    T: Scalar,
+    DefaultAllocator: Allocator<T, D, D>,
 {
     /// Creates a square matrix with its diagonal set to `diag` and all other entries set to 0.
     ///
@@ -350,9 +348,9 @@ where
     ///         dm[(2, 0)] == 0.0 && dm[(2, 1)] == 0.0 && dm[(2, 2)] == 3.0);
     /// ```
     #[inline]
-    pub fn from_diagonal<SB: Storage<N, D>>(diag: &Vector<N, D, SB>) -> Self
+    pub fn from_diagonal<SB: Storage<T, D>>(diag: &Vector<T, D, SB>) -> Self
     where
-        N: Zero,
+        T: Zero,
     {
         let (dim, _) = diag.data.shape();
         let mut res = Self::zeros_generic(dim, dim);
@@ -401,7 +399,7 @@ macro_rules! impl_constructors(
         ///         dm[(1, 0)] == 2.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 2.0);
         /// ```
         #[inline]
-        pub fn from_element($($args: usize,)* elem: N) -> Self {
+        pub fn from_element($($args: usize,)* elem: T) -> Self {
             Self::from_element_generic($($gargs, )* elem)
         }
 
@@ -428,7 +426,7 @@ macro_rules! impl_constructors(
         ///         dm[(1, 0)] == 2.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 2.0);
         /// ```
         #[inline]
-        pub fn repeat($($args: usize,)* elem: N) -> Self {
+        pub fn repeat($($args: usize,)* elem: T) -> Self {
             Self::repeat_generic($($gargs, )* elem)
         }
 
@@ -454,7 +452,7 @@ macro_rules! impl_constructors(
         /// ```
         #[inline]
         pub fn zeros($($args: usize),*) -> Self
-            where N: Zero {
+            where T: Zero {
             Self::zeros_generic($($gargs),*)
         }
 
@@ -483,7 +481,7 @@ macro_rules! impl_constructors(
         /// ```
         #[inline]
         pub fn from_iterator<I>($($args: usize,)* iter: I) -> Self
-            where I: IntoIterator<Item = N> {
+            where I: IntoIterator<Item = T> {
             Self::from_iterator_generic($($gargs, )* iter)
         }
 
@@ -511,7 +509,7 @@ macro_rules! impl_constructors(
         /// ```
         #[inline]
         pub fn from_fn<F>($($args: usize,)* f: F) -> Self
-            where F: FnMut(usize, usize) -> N {
+            where F: FnMut(usize, usize) -> T {
             Self::from_fn_generic($($gargs, )* f)
         }
 
@@ -535,7 +533,7 @@ macro_rules! impl_constructors(
         /// ```
         #[inline]
         pub fn identity($($args: usize,)*) -> Self
-            where N: Zero + One {
+            where T: Zero + One {
             Self::identity_generic($($gargs),* )
         }
 
@@ -557,8 +555,8 @@ macro_rules! impl_constructors(
         ///         dm[(1, 0)] == 0.0 && dm[(1, 1)] == 5.0 && dm[(1, 2)] == 0.0);
         /// ```
         #[inline]
-        pub fn from_diagonal_element($($args: usize,)* elt: N) -> Self
-            where N: Zero + One {
+        pub fn from_diagonal_element($($args: usize,)* elt: T) -> Self
+            where T: Zero + One {
             Self::from_diagonal_element_generic($($gargs, )* elt)
         }
 
@@ -584,15 +582,15 @@ macro_rules! impl_constructors(
         ///         dm[(2, 0)] == 0.0 && dm[(2, 1)] == 0.0 && dm[(2, 2)] == 0.0);
         /// ```
         #[inline]
-        pub fn from_partial_diagonal($($args: usize,)* elts: &[N]) -> Self
-            where N: Zero {
+        pub fn from_partial_diagonal($($args: usize,)* elts: &[T]) -> Self
+            where T: Zero {
             Self::from_partial_diagonal_generic($($gargs, )* elts)
         }
 
         /// Creates a matrix or vector filled with random values from the given distribution.
         #[inline]
         #[cfg(feature = "rand-no-std")]
-        pub fn from_distribution<Distr: Distribution<N> + ?Sized, G: Rng + ?Sized>(
+        pub fn from_distribution<Distr: Distribution<T> + ?Sized, G: Rng + ?Sized>(
             $($args: usize,)*
             distribution: &Distr,
             rng: &mut G,
@@ -604,28 +602,28 @@ macro_rules! impl_constructors(
         #[inline]
         #[cfg(feature = "rand")]
         pub fn new_random($($args: usize),*) -> Self
-            where Standard: Distribution<N> {
+            where Standard: Distribution<T> {
             Self::new_random_generic($($gargs),*)
         }
     }
 );
 
 /// # Constructors of statically-sized vectors or statically-sized matrices
-impl<N: Scalar, R: DimName, C: DimName> MatrixMN<N, R, C>
+impl<T: Scalar, R: DimName, C: DimName> OMatrix<T, R, C>
 where
-    DefaultAllocator: Allocator<N, R, C>,
+    DefaultAllocator: Allocator<T, R, C>,
 {
-    // TODO: this is not very pretty. We could find a better call syntax.
-    impl_constructors!(R, C;                         // Arguments for Matrix<N, ..., S>
-    => R: DimName, => C: DimName; // Type parameters for impl<N, ..., S>
+    // TODO: this is not very pretty. We could find a better call syntax.
+    impl_constructors!(R, C;                         // Arguments for Matrix<T, ..., S>
+    => R: DimName, => C: DimName; // Type parameters for impl<T, ..., S>
     R::name(), C::name();         // Arguments for `_generic` constructors.
     ); // Arguments for non-generic constructors.
 }
 
 /// # Constructors of matrices with a dynamic number of columns
-impl<N: Scalar, R: DimName> MatrixMN<N, R, Dynamic>
+impl<T: Scalar, R: DimName> OMatrix<T, R, Dynamic>
 where
-    DefaultAllocator: Allocator<N, R, Dynamic>,
+    DefaultAllocator: Allocator<T, R, Dynamic>,
 {
     impl_constructors!(R, Dynamic;
                    => R: DimName;
@@ -634,9 +632,9 @@ where
 }
 
 /// # Constructors of dynamic vectors and matrices with a dynamic number of rows
-impl<N: Scalar, C: DimName> MatrixMN<N, Dynamic, C>
+impl<T: Scalar, C: DimName> OMatrix<T, Dynamic, C>
 where
-    DefaultAllocator: Allocator<N, Dynamic, C>,
+    DefaultAllocator: Allocator<T, Dynamic, C>,
 {
     impl_constructors!(Dynamic, C;
                    => C: DimName;
@@ -645,9 +643,9 @@ where
 }
 
 /// # Constructors of fully dynamic matrices
-impl<N: Scalar> MatrixMN<N, Dynamic, Dynamic>
+impl<T: Scalar> OMatrix<T, Dynamic, Dynamic>
 where
-    DefaultAllocator: Allocator<N, Dynamic, Dynamic>,
+    DefaultAllocator: Allocator<T, Dynamic, Dynamic>,
 {
     impl_constructors!(Dynamic, Dynamic;
                    ;
@@ -663,8 +661,8 @@ where
  */
 macro_rules! impl_constructors_from_data(
     ($data: ident; $($Dims: ty),*; $(=> $DimIdent: ident: $DimBound: ident),*; $($gargs: expr),*; $($args: ident),*) => {
-        impl<N: Scalar, $($DimIdent: $DimBound, )*> MatrixMN<N $(, $Dims)*>
-        where DefaultAllocator: Allocator<N $(, $Dims)*> {
+        impl<T: Scalar, $($DimIdent: $DimBound, )*> OMatrix<T $(, $Dims)*>
+        where DefaultAllocator: Allocator<T $(, $Dims)*> {
             /// Creates a matrix with its elements filled with the components provided by a slice
             /// in row-major order.
             ///
@@ -691,7 +689,7 @@ macro_rules! impl_constructors_from_data(
             ///         dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
             /// ```
             #[inline]
-            pub fn from_row_slice($($args: usize,)* $data: &[N]) -> Self {
+            pub fn from_row_slice($($args: usize,)* $data: &[T]) -> Self {
                 Self::from_row_slice_generic($($gargs, )* $data)
             }
 
@@ -718,7 +716,7 @@ macro_rules! impl_constructors_from_data(
             ///         dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
             /// ```
             #[inline]
-            pub fn from_column_slice($($args: usize,)* $data: &[N]) -> Self {
+            pub fn from_column_slice($($args: usize,)* $data: &[T]) -> Self {
                 Self::from_column_slice_generic($($gargs, )* $data)
             }
 
@@ -744,7 +742,7 @@ macro_rules! impl_constructors_from_data(
             /// ```
             #[inline]
             #[cfg(any(feature = "std", feature = "alloc"))]
-            pub fn from_vec($($args: usize,)* $data: Vec<N>) -> Self {
+            pub fn from_vec($($args: usize,)* $data: Vec<T>) -> Self {
                 Self::from_vec_generic($($gargs, )* $data)
             }
         }
@@ -752,8 +750,8 @@ macro_rules! impl_constructors_from_data(
 );
 
 // TODO: this is not very pretty. We could find a better call syntax.
-impl_constructors_from_data!(data; R, C;                  // Arguments for Matrix<N, ..., S>
-=> R: DimName, => C: DimName; // Type parameters for impl<N, ..., S>
+impl_constructors_from_data!(data; R, C;                  // Arguments for Matrix<T, ..., S>
+=> R: DimName, => C: DimName; // Type parameters for impl<T, ..., S>
 R::name(), C::name();         // Arguments for `_generic` constructors.
 ); // Arguments for non-generic constructors.
 
@@ -777,14 +775,14 @@ impl_constructors_from_data!(data; Dynamic, Dynamic;
  * Zero, One, Rand traits.
  *
  */
-impl<N, R: DimName, C: DimName> Zero for MatrixMN<N, R, C>
+impl<T, R: DimName, C: DimName> Zero for OMatrix<T, R, C>
 where
-    N: Scalar + Zero + ClosedAdd,
-    DefaultAllocator: Allocator<N, R, C>,
+    T: Scalar + Zero + ClosedAdd,
+    DefaultAllocator: Allocator<T, R, C>,
 {
     #[inline]
     fn zero() -> Self {
-        Self::from_element(N::zero())
+        Self::from_element(T::zero())
     }
 
     #[inline]
@@ -793,10 +791,10 @@ where
     }
 }
 
-impl<N, D: DimName> One for MatrixN<N, D>
+impl<T, D: DimName> One for OMatrix<T, D, D>
 where
-    N: Scalar + Zero + One + ClosedMul + ClosedAdd,
-    DefaultAllocator: Allocator<N, D, D>,
+    T: Scalar + Zero + One + ClosedMul + ClosedAdd,
+    DefaultAllocator: Allocator<T, D, D>,
 {
     #[inline]
     fn one() -> Self {
@@ -804,45 +802,45 @@ where
     }
 }
 
-impl<N, R: DimName, C: DimName> Bounded for MatrixMN<N, R, C>
+impl<T, R: DimName, C: DimName> Bounded for OMatrix<T, R, C>
 where
-    N: Scalar + Bounded,
-    DefaultAllocator: Allocator<N, R, C>,
+    T: Scalar + Bounded,
+    DefaultAllocator: Allocator<T, R, C>,
 {
     #[inline]
     fn max_value() -> Self {
-        Self::from_element(N::max_value())
+        Self::from_element(T::max_value())
     }
 
     #[inline]
     fn min_value() -> Self {
-        Self::from_element(N::min_value())
+        Self::from_element(T::min_value())
     }
 }
 
 #[cfg(feature = "rand-no-std")]
-impl<N: Scalar, R: Dim, C: Dim> Distribution<MatrixMN<N, R, C>> for Standard
+impl<T: Scalar, R: Dim, C: Dim> Distribution<OMatrix<T, R, C>> for Standard
 where
-    DefaultAllocator: Allocator<N, R, C>,
-    Standard: Distribution<N>,
+    DefaultAllocator: Allocator<T, R, C>,
+    Standard: Distribution<T>,
 {
     #[inline]
-    fn sample<'a, G: Rng + ?Sized>(&self, rng: &'a mut G) -> MatrixMN<N, R, C> {
+    fn sample<'a, G: Rng + ?Sized>(&self, rng: &'a mut G) -> OMatrix<T, R, C> {
         let nrows = R::try_to_usize().unwrap_or_else(|| rng.gen_range(0..10));
         let ncols = C::try_to_usize().unwrap_or_else(|| rng.gen_range(0..10));
 
-        MatrixMN::from_fn_generic(R::from_usize(nrows), C::from_usize(ncols), |_, _| rng.gen())
+        OMatrix::from_fn_generic(R::from_usize(nrows), C::from_usize(ncols), |_, _| rng.gen())
     }
 }
 
 #[cfg(feature = "arbitrary")]
-impl<N, R, C> Arbitrary for MatrixMN<N, R, C>
+impl<T, R, C> Arbitrary for OMatrix<T, R, C>
 where
     R: Dim,
     C: Dim,
-    N: Scalar + Arbitrary + Send,
-    DefaultAllocator: Allocator<N, R, C>,
-    Owned<N, R, C>: Clone + Send,
+    T: Scalar + Arbitrary + Send,
+    DefaultAllocator: Allocator<T, R, C>,
+    Owned<T, R, C>: Clone + Send,
 {
     #[inline]
     fn arbitrary(g: &mut Gen) -> Self {
@@ -850,22 +848,22 @@ where
         let ncols = C::try_to_usize().unwrap_or(usize::arbitrary(g) % 10);
 
         Self::from_fn_generic(R::from_usize(nrows), C::from_usize(ncols), |_, _| {
-            N::arbitrary(g)
+            T::arbitrary(g)
         })
     }
 }
 
 // TODO(specialization): faster impls possible for D≤4 (see rand_distr::{UnitCircle, UnitSphere})
 #[cfg(feature = "rand")]
-impl<N: crate::RealField, D: DimName> Distribution<Unit<VectorN<N, D>>> for Standard
+impl<T: crate::RealField, D: DimName> Distribution<Unit<OVector<T, D>>> for Standard
 where
-    DefaultAllocator: Allocator<N, D>,
-    rand_distr::StandardNormal: Distribution<N>,
+    DefaultAllocator: Allocator<T, D>,
+    rand_distr::StandardNormal: Distribution<T>,
 {
     /// Generate a uniformly distributed random unit vector.
     #[inline]
-    fn sample<'a, G: Rng + ?Sized>(&self, rng: &'a mut G) -> Unit<VectorN<N, D>> {
-        Unit::new_normalize(VectorN::from_distribution_generic(
+    fn sample<'a, G: Rng + ?Sized>(&self, rng: &'a mut G) -> Unit<OVector<T, D>> {
+        Unit::new_normalize(OVector::from_distribution_generic(
             D::name(),
             Const::<1>,
             &rand_distr::StandardNormal,
@@ -881,12 +879,12 @@ where
  */
 macro_rules! componentwise_constructors_impl(
     ($($R: expr, $C: expr, $($args: ident:($irow: expr,$icol: expr)),*);* $(;)*) => {$(
-        impl<N> MatrixMN<N, Const<$R>, Const<$C>>
-            where N: Scalar,
-                  DefaultAllocator: Allocator<N, Const<$R>, Const<$C>> {
+        impl<T> OMatrix<T, Const<$R>, Const<$C>>
+            where T: Scalar,
+                  DefaultAllocator: Allocator<T, Const<$R>, Const<$C>> {
             /// Initializes this matrix from its components.
             #[inline]
-            pub fn new($($args: N),*) -> Self {
+            pub fn new($($args: T),*) -> Self {
                 unsafe {
                     #[cfg(feature="no_unsound_assume_init")]
                     let mut res: Self = unimplemented!();
@@ -1051,24 +1049,24 @@ componentwise_constructors_impl!(
  * Axis constructors.
  *
  */
-impl<N, R: DimName> VectorN<N, R>
+impl<T, R: DimName> OVector<T, R>
 where
     R: ToTypenum,
-    N: Scalar + Zero + One,
-    DefaultAllocator: Allocator<N, R>,
+    T: Scalar + Zero + One,
+    DefaultAllocator: Allocator<T, R>,
 {
     /// The column vector with `val` as its i-th component.
     #[inline]
-    pub fn ith(i: usize, val: N) -> Self {
+    pub fn ith(i: usize, val: T) -> Self {
         let mut res = Self::zeros();
         res[i] = val;
         res
     }
 
-    /// The column unit vector with `N::one()` as its i-th component.
+    /// The column unit vector with `T::one()` as its i-th component.
     #[inline]
     pub fn ith_axis(i: usize) -> Unit<Self> {
-        Unit::new_unchecked(Self::ith(i, N::one()))
+        Unit::new_unchecked(Self::ith(i, T::one()))
     }
 
     /// The column vector with a 1 as its first component, and zero elsewhere.
@@ -1079,7 +1077,7 @@ where
     {
         let mut res = Self::zeros();
         unsafe {
-            *res.vget_unchecked_mut(0) = N::one();
+            *res.vget_unchecked_mut(0) = T::one();
         }
 
         res
@@ -1093,7 +1091,7 @@ where
     {
         let mut res = Self::zeros();
         unsafe {
-            *res.vget_unchecked_mut(1) = N::one();
+            *res.vget_unchecked_mut(1) = T::one();
         }
 
         res
@@ -1107,7 +1105,7 @@ where
     {
         let mut res = Self::zeros();
         unsafe {
-            *res.vget_unchecked_mut(2) = N::one();
+            *res.vget_unchecked_mut(2) = T::one();
         }
 
         res
@@ -1121,7 +1119,7 @@ where
     {
         let mut res = Self::zeros();
         unsafe {
-            *res.vget_unchecked_mut(3) = N::one();
+            *res.vget_unchecked_mut(3) = T::one();
         }
 
         res
@@ -1135,7 +1133,7 @@ where
     {
         let mut res = Self::zeros();
         unsafe {
-            *res.vget_unchecked_mut(4) = N::one();
+            *res.vget_unchecked_mut(4) = T::one();
         }
 
         res
@@ -1149,7 +1147,7 @@ where
     {
         let mut res = Self::zeros();
         unsafe {
-            *res.vget_unchecked_mut(5) = N::one();
+            *res.vget_unchecked_mut(5) = T::one();
         }
 
         res

src/base/construction_slice.rs

@@ -1,12 +1,12 @@
 use crate::base::dimension::{Const, Dim, DimName, Dynamic};
 use crate::base::matrix_slice::{SliceStorage, SliceStorageMut};
-use crate::base::{MatrixSliceMN, MatrixSliceMutMN, Scalar};
+use crate::base::{MatrixSlice, MatrixSliceMutMN, Scalar};
 
 use num_rational::Ratio;
 
 /// # Creating matrix slices from `&[T]`
-impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
-    MatrixSliceMN<'a, N, R, C, RStride, CStride>
+impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
+    MatrixSlice<'a, T, R, C, RStride, CStride>
 {
     /// Creates, without bound-checking, a matrix slice from an array and with dimensions and strides specified by generic types instances.
     ///
@@ -14,7 +14,7 @@ impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
     /// The generic types `R`, `C`, `RStride`, `CStride` can either be type-level integers or integers wrapped with `Dynamic::new()`.
     #[inline]
     pub unsafe fn from_slice_with_strides_generic_unchecked(
-        data: &'a [N],
+        data: &'a [T],
         start: usize,
         nrows: R,
         ncols: C,
@@ -35,7 +35,7 @@ impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
     /// The generic types `R`, `C`, `RStride`, `CStride` can either be type-level integers or integers wrapped with `Dynamic::new()`.
     #[inline]
     pub fn from_slice_with_strides_generic(
-        data: &'a [N],
+        data: &'a [T],
         nrows: R,
         ncols: C,
         rstride: RStride,
@@ -56,14 +56,14 @@ impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
     }
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim> MatrixSliceMN<'a, N, R, C> {
+impl<'a, T: Scalar, R: Dim, C: Dim> MatrixSlice<'a, T, R, C> {
     /// Creates, without bound-checking, a matrix slice from an array and with dimensions specified by generic types instances.
     ///
     /// This method is unsafe because the input data array is not checked to contain enough elements.
     /// The generic types `R` and `C` can either be type-level integers or integers wrapped with `Dynamic::new()`.
     #[inline]
     pub unsafe fn from_slice_generic_unchecked(
-        data: &'a [N],
+        data: &'a [T],
         start: usize,
         nrows: R,
         ncols: C,
@@ -78,41 +78,41 @@ impl<'a, N: Scalar, R: Dim, C: Dim> MatrixSliceMN<'a, N, R, C> {
     /// Panics if the input data array dose not contain enough elements.
     /// The generic types `R` and `C` can either be type-level integers or integers wrapped with `Dynamic::new()`.
     #[inline]
-    pub fn from_slice_generic(data: &'a [N], nrows: R, ncols: C) -> Self {
+    pub fn from_slice_generic(data: &'a [T], nrows: R, ncols: C) -> Self {
         Self::from_slice_with_strides_generic(data, nrows, ncols, Const::<1>, nrows)
     }
 }
 
 macro_rules! impl_constructors(
     ($($Dims: ty),*; $(=> $DimIdent: ident: $DimBound: ident),*; $($gargs: expr),*; $($args: ident),*) => {
-        impl<'a, N: Scalar, $($DimIdent: $DimBound),*> MatrixSliceMN<'a, N, $($Dims),*> {
+        impl<'a, T: Scalar, $($DimIdent: $DimBound),*> MatrixSlice<'a, T, $($Dims),*> {
             /// Creates a new matrix slice from the given data array.
             ///
             /// Panics if `data` does not contain enough elements.
             #[inline]
-            pub fn from_slice(data: &'a [N], $($args: usize),*) -> Self {
+            pub fn from_slice(data: &'a [T], $($args: usize),*) -> Self {
                 Self::from_slice_generic(data, $($gargs),*)
             }
 
             /// Creates, without bound checking, a new matrix slice from the given data array.
             #[inline]
-            pub unsafe fn from_slice_unchecked(data: &'a [N], start: usize, $($args: usize),*) -> Self {
+            pub unsafe fn from_slice_unchecked(data: &'a [T], start: usize, $($args: usize),*) -> Self {
                 Self::from_slice_generic_unchecked(data, start, $($gargs),*)
             }
         }
 
-        impl<'a, N: Scalar, $($DimIdent: $DimBound, )*> MatrixSliceMN<'a, N, $($Dims,)* Dynamic, Dynamic> {
+        impl<'a, T: Scalar, $($DimIdent: $DimBound, )*> MatrixSlice<'a, T, $($Dims,)* Dynamic, Dynamic> {
             /// Creates a new matrix slice with the specified strides from the given data array.
             ///
             /// Panics if `data` does not contain enough elements.
             #[inline]
-            pub fn from_slice_with_strides(data: &'a [N], $($args: usize,)* rstride: usize, cstride: usize) -> Self {
+            pub fn from_slice_with_strides(data: &'a [T], $($args: usize,)* rstride: usize, cstride: usize) -> Self {
                 Self::from_slice_with_strides_generic(data, $($gargs,)* Dynamic::new(rstride), Dynamic::new(cstride))
             }
 
             /// Creates, without bound checking, a new matrix slice with the specified strides from the given data array.
             #[inline]
-            pub unsafe fn from_slice_with_strides_unchecked(data: &'a [N], start: usize, $($args: usize,)* rstride: usize, cstride: usize) -> Self {
+            pub unsafe fn from_slice_with_strides_unchecked(data: &'a [T], start: usize, $($args: usize,)* rstride: usize, cstride: usize) -> Self {
                 Self::from_slice_with_strides_generic_unchecked(data, start, $($gargs,)* Dynamic::new(rstride), Dynamic::new(cstride))
             }
         }
@@ -120,8 +120,8 @@ macro_rules! impl_constructors(
 );
 
 // TODO: this is not very pretty. We could find a better call syntax.
-impl_constructors!(R, C;                         // Arguments for Matrix<N, ..., S>
-=> R: DimName, => C: DimName; // Type parameters for impl<N, ..., S>
+impl_constructors!(R, C;                         // Arguments for Matrix<T, ..., S>
+=> R: DimName, => C: DimName; // Type parameters for impl<T, ..., S>
 R::name(), C::name();         // Arguments for `_generic` constructors.
 ); // Arguments for non-generic constructors.
 
@@ -141,8 +141,8 @@ impl_constructors!(Dynamic, Dynamic;
                    nrows, ncols);
 
 /// # Creating mutable matrix slices from `&mut [T]`
-impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
-    MatrixSliceMutMN<'a, N, R, C, RStride, CStride>
+impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
+    MatrixSliceMutMN<'a, T, R, C, RStride, CStride>
 {
     /// Creates, without bound-checking, a mutable matrix slice from an array and with dimensions and strides specified by generic types instances.
     ///
@@ -150,7 +150,7 @@ impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
     /// The generic types `R`, `C`, `RStride`, `CStride` can either be type-level integers or integers wrapped with `Dynamic::new()`.
     #[inline]
     pub unsafe fn from_slice_with_strides_generic_unchecked(
-        data: &'a mut [N],
+        data: &'a mut [T],
         start: usize,
         nrows: R,
         ncols: C,
@@ -171,7 +171,7 @@ impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
     /// The generic types `R`, `C`, `RStride`, `CStride` can either be type-level integers or integers wrapped with `Dynamic::new()`.
     #[inline]
     pub fn from_slice_with_strides_generic(
-        data: &'a mut [N],
+        data: &'a mut [T],
         nrows: R,
         ncols: C,
         rstride: RStride,
@@ -214,14 +214,14 @@ impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
     }
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim> MatrixSliceMutMN<'a, N, R, C> {
+impl<'a, T: Scalar, R: Dim, C: Dim> MatrixSliceMutMN<'a, T, R, C> {
     /// Creates, without bound-checking, a mutable matrix slice from an array and with dimensions specified by generic types instances.
     ///
     /// This method is unsafe because the input data array is not checked to contain enough elements.
     /// The generic types `R` and `C` can either be type-level integers or integers wrapped with `Dynamic::new()`.
     #[inline]
     pub unsafe fn from_slice_generic_unchecked(
-        data: &'a mut [N],
+        data: &'a mut [T],
         start: usize,
         nrows: R,
         ncols: C,
@@ -236,42 +236,42 @@ impl<'a, N: Scalar, R: Dim, C: Dim> MatrixSliceMutMN<'a, N, R, C> {
     /// Panics if the input data array dose not contain enough elements.
     /// The generic types `R` and `C` can either be type-level integers or integers wrapped with `Dynamic::new()`.
     #[inline]
-    pub fn from_slice_generic(data: &'a mut [N], nrows: R, ncols: C) -> Self {
+    pub fn from_slice_generic(data: &'a mut [T], nrows: R, ncols: C) -> Self {
         Self::from_slice_with_strides_generic(data, nrows, ncols, Const::<1>, nrows)
     }
 }
 
 macro_rules! impl_constructors_mut(
     ($($Dims: ty),*; $(=> $DimIdent: ident: $DimBound: ident),*; $($gargs: expr),*; $($args: ident),*) => {
-        impl<'a, N: Scalar, $($DimIdent: $DimBound),*> MatrixSliceMutMN<'a, N, $($Dims),*> {
+        impl<'a, T: Scalar, $($DimIdent: $DimBound),*> MatrixSliceMutMN<'a, T, $($Dims),*> {
             /// Creates a new mutable matrix slice from the given data array.
             ///
             /// Panics if `data` does not contain enough elements.
             #[inline]
-            pub fn from_slice(data: &'a mut [N], $($args: usize),*) -> Self {
+            pub fn from_slice(data: &'a mut [T], $($args: usize),*) -> Self {
                 Self::from_slice_generic(data, $($gargs),*)
             }
 
             /// Creates, without bound checking, a new mutable matrix slice from the given data array.
             #[inline]
-            pub unsafe fn from_slice_unchecked(data: &'a mut [N], start: usize, $($args: usize),*) -> Self {
+            pub unsafe fn from_slice_unchecked(data: &'a mut [T], start: usize, $($args: usize),*) -> Self {
                 Self::from_slice_generic_unchecked(data, start, $($gargs),*)
             }
         }
 
-        impl<'a, N: Scalar, $($DimIdent: $DimBound, )*> MatrixSliceMutMN<'a, N, $($Dims,)* Dynamic, Dynamic> {
+        impl<'a, T: Scalar, $($DimIdent: $DimBound, )*> MatrixSliceMutMN<'a, T, $($Dims,)* Dynamic, Dynamic> {
             /// Creates a new mutable matrix slice with the specified strides from the given data array.
             ///
             /// Panics if `data` does not contain enough elements.
             #[inline]
-            pub fn from_slice_with_strides_mut(data: &'a mut [N], $($args: usize,)* rstride: usize, cstride: usize) -> Self {
+            pub fn from_slice_with_strides_mut(data: &'a mut [T], $($args: usize,)* rstride: usize, cstride: usize) -> Self {
                 Self::from_slice_with_strides_generic(
                     data, $($gargs,)* Dynamic::new(rstride), Dynamic::new(cstride))
             }
 
             /// Creates, without bound checking, a new mutable matrix slice with the specified strides from the given data array.
             #[inline]
-            pub unsafe fn from_slice_with_strides_unchecked(data: &'a mut [N], start: usize, $($args: usize,)* rstride: usize, cstride: usize) -> Self {
+            pub unsafe fn from_slice_with_strides_unchecked(data: &'a mut [T], start: usize, $($args: usize,)* rstride: usize, cstride: usize) -> Self {
                 Self::from_slice_with_strides_generic_unchecked(
                     data, start, $($gargs,)* Dynamic::new(rstride), Dynamic::new(cstride))
             }
@@ -280,8 +280,8 @@ macro_rules! impl_constructors_mut(
 );
 
 // TODO: this is not very pretty. We could find a better call syntax.
-impl_constructors_mut!(R, C;                         // Arguments for Matrix<N, ..., S>
-=> R: DimName, => C: DimName; // Type parameters for impl<N, ..., S>
+impl_constructors_mut!(R, C;                         // Arguments for Matrix<T, ..., S>
+=> R: DimName, => C: DimName; // Type parameters for impl<T, ..., S>
 R::name(), C::name();         // Arguments for `_generic` constructors.
 ); // Arguments for non-generic constructors.
 

src/base/conversion.rs

@@ -17,8 +17,8 @@ use crate::base::dimension::{
 use crate::base::iter::{MatrixIter, MatrixIterMut};
 use crate::base::storage::{ContiguousStorage, ContiguousStorageMut, Storage, StorageMut};
 use crate::base::{
-    ArrayStorage, DVectorSlice, DVectorSliceMut, DefaultAllocator, Matrix, MatrixMN, MatrixSlice,
-    MatrixSliceMut, Scalar,
+    ArrayStorage, DVectorSlice, DVectorSliceMut, DefaultAllocator, Matrix, MatrixSlice,
+    MatrixSliceMut, OMatrix, Scalar,
 };
 #[cfg(any(feature = "std", feature = "alloc"))]
 use crate::base::{DVector, VecStorage};
@@ -26,30 +26,30 @@ use crate::base::{SliceStorage, SliceStorageMut};
 use crate::constraint::DimEq;
 
 // TODO: too bad this won't work allo slice conversions.
-impl<N1, N2, R1, C1, R2, C2> SubsetOf<MatrixMN<N2, R2, C2>> for MatrixMN<N1, R1, C1>
+impl<T1, T2, R1, C1, R2, C2> SubsetOf<OMatrix<T2, R2, C2>> for OMatrix<T1, R1, C1>
 where
     R1: Dim,
     C1: Dim,
     R2: Dim,
     C2: Dim,
-    N1: Scalar,
-    N2: Scalar + SupersetOf<N1>,
+    T1: Scalar,
+    T2: Scalar + SupersetOf<T1>,
     DefaultAllocator:
-        Allocator<N2, R2, C2> + Allocator<N1, R1, C1> + SameShapeAllocator<N1, R1, C1, R2, C2>,
+        Allocator<T2, R2, C2> + Allocator<T1, R1, C1> + SameShapeAllocator<T1, R1, C1, R2, C2>,
     ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
 {
     #[inline]
-    fn to_superset(&self) -> MatrixMN<N2, R2, C2> {
+    fn to_superset(&self) -> OMatrix<T2, R2, C2> {
         let (nrows, ncols) = self.shape();
         let nrows2 = R2::from_usize(nrows);
         let ncols2 = C2::from_usize(ncols);
 
-        let mut res: MatrixMN<N2, R2, C2> =
+        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 {
                 unsafe {
-                    *res.get_unchecked_mut((i, j)) = N2::from_subset(self.get_unchecked((i, j)))
+                    *res.get_unchecked_mut((i, j)) = T2::from_subset(self.get_unchecked((i, j)))
                 }
             }
         }
@@ -58,12 +58,12 @@ where
     }
 
     #[inline]
-    fn is_in_subset(m: &MatrixMN<N2, R2, C2>) -> bool {
+    fn is_in_subset(m: &OMatrix<T2, R2, C2>) -> bool {
         m.iter().all(|e| e.is_in_subset())
     }
 
     #[inline]
-    fn from_superset_unchecked(m: &MatrixMN<N2, R2, C2>) -> Self {
+    fn from_superset_unchecked(m: &OMatrix<T2, R2, C2>) -> Self {
         let (nrows2, ncols2) = m.shape();
         let nrows = R1::from_usize(nrows2);
         let ncols = C1::from_usize(ncols2);
@@ -81,9 +81,9 @@ where
     }
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> IntoIterator for &'a Matrix<N, R, C, S> {
-    type Item = &'a N;
-    type IntoIter = MatrixIter<'a, N, R, C, S>;
+impl<'a, T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> IntoIterator for &'a Matrix<T, R, C, S> {
+    type Item = &'a T;
+    type IntoIter = MatrixIter<'a, T, R, C, S>;
 
     #[inline]
     fn into_iter(self) -> Self::IntoIter {
@@ -91,11 +91,11 @@ impl<'a, N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> IntoIterator for &'a Ma
     }
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> IntoIterator
-    for &'a mut Matrix<N, R, C, S>
+impl<'a, T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> IntoIterator
+    for &'a mut Matrix<T, R, C, S>
 {
-    type Item = &'a mut N;
-    type IntoIter = MatrixIterMut<'a, N, R, C, S>;
+    type Item = &'a mut T;
+    type IntoIter = MatrixIterMut<'a, T, R, C, S>;
 
     #[inline]
     fn into_iter(self) -> Self::IntoIter {
@@ -105,11 +105,11 @@ impl<'a, N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> IntoIterator
 
 macro_rules! impl_from_into_asref_1D(
     ($(($NRows: ident, $NCols: ident) => $SZ: expr);* $(;)*) => {$(
-        impl<N> From<[N; $SZ]> for MatrixMN<N, $NRows, $NCols>
-        where N: Scalar,
-              DefaultAllocator: Allocator<N, $NRows, $NCols> {
+        impl<T> From<[T; $SZ]> for OMatrix<T, $NRows, $NCols>
+        where T: Scalar,
+              DefaultAllocator: Allocator<T, $NRows, $NCols> {
             #[inline]
-            fn from(arr: [N; $SZ]) -> Self {
+            fn from(arr: [T; $SZ]) -> Self {
                 unsafe {
                     let mut res = Self::new_uninitialized();
                     ptr::copy_nonoverlapping(&arr[0], (*res.as_mut_ptr()).data.ptr_mut(), $SZ);
@@ -119,35 +119,35 @@ macro_rules! impl_from_into_asref_1D(
             }
         }
 
-        impl<N, S> Into<[N; $SZ]> for Matrix<N, $NRows, $NCols, S>
-        where N: Scalar,
-              S: ContiguousStorage<N, $NRows, $NCols> {
+        impl<T, S> Into<[T; $SZ]> for Matrix<T, $NRows, $NCols, S>
+        where T: Scalar,
+              S: ContiguousStorage<T, $NRows, $NCols> {
             #[inline]
-            fn into(self) -> [N; $SZ] {
-                let mut res = mem::MaybeUninit::<[N; $SZ]>::uninit();
+            fn into(self) -> [T; $SZ] {
+                let mut res = mem::MaybeUninit::<[T; $SZ]>::uninit();
 
-                unsafe { ptr::copy_nonoverlapping(self.data.ptr(), res.as_mut_ptr() as *mut N, $SZ) };
+                unsafe { ptr::copy_nonoverlapping(self.data.ptr(), res.as_mut_ptr() as *mut T, $SZ) };
 
                 unsafe { res.assume_init() }
             }
         }
 
-        impl<N, S> AsRef<[N; $SZ]> for Matrix<N, $NRows, $NCols, S>
-        where N: Scalar,
-              S: ContiguousStorage<N, $NRows, $NCols> {
+        impl<T, S> AsRef<[T; $SZ]> for Matrix<T, $NRows, $NCols, S>
+        where T: Scalar,
+              S: ContiguousStorage<T, $NRows, $NCols> {
             #[inline]
-            fn as_ref(&self) -> &[N; $SZ] {
+            fn as_ref(&self) -> &[T; $SZ] {
                 unsafe {
                     mem::transmute(self.data.ptr())
                 }
             }
         }
 
-        impl<N, S> AsMut<[N; $SZ]> for Matrix<N, $NRows, $NCols, S>
-        where N: Scalar,
-              S: ContiguousStorageMut<N, $NRows, $NCols> {
+        impl<T, S> AsMut<[T; $SZ]> for Matrix<T, $NRows, $NCols, S>
+        where T: Scalar,
+              S: ContiguousStorageMut<T, $NRows, $NCols> {
             #[inline]
-            fn as_mut(&mut self) -> &mut [N; $SZ] {
+            fn as_mut(&mut self) -> &mut [T; $SZ] {
                 unsafe {
                     mem::transmute(self.data.ptr_mut())
                 }
@@ -173,10 +173,10 @@ impl_from_into_asref_1D!(
 
 macro_rules! impl_from_into_asref_2D(
     ($(($NRows: ty, $NCols: ty) => ($SZRows: expr, $SZCols: expr));* $(;)*) => {$(
-        impl<N: Scalar> From<[[N; $SZRows]; $SZCols]> for MatrixMN<N, $NRows, $NCols>
-        where DefaultAllocator: Allocator<N, $NRows, $NCols> {
+        impl<T: Scalar> From<[[T; $SZRows]; $SZCols]> for OMatrix<T, $NRows, $NCols>
+        where DefaultAllocator: Allocator<T, $NRows, $NCols> {
             #[inline]
-            fn from(arr: [[N; $SZRows]; $SZCols]) -> Self {
+            fn from(arr: [[T; $SZRows]; $SZCols]) -> Self {
                 unsafe {
                     let mut res = Self::new_uninitialized();
                     ptr::copy_nonoverlapping(&arr[0][0], (*res.as_mut_ptr()).data.ptr_mut(), $SZRows * $SZCols);
@@ -186,32 +186,32 @@ macro_rules! impl_from_into_asref_2D(
             }
         }
 
-        impl<N: Scalar, S> Into<[[N; $SZRows]; $SZCols]> for Matrix<N, $NRows, $NCols, S>
-        where S: ContiguousStorage<N, $NRows, $NCols> {
+        impl<T: Scalar, S> Into<[[T; $SZRows]; $SZCols]> for Matrix<T, $NRows, $NCols, S>
+        where S: ContiguousStorage<T, $NRows, $NCols> {
             #[inline]
-            fn into(self) -> [[N; $SZRows]; $SZCols] {
-                let mut res = mem::MaybeUninit::<[[N; $SZRows]; $SZCols]>::uninit();
+            fn into(self) -> [[T; $SZRows]; $SZCols] {
+                let mut res = mem::MaybeUninit::<[[T; $SZRows]; $SZCols]>::uninit();
 
-                unsafe { ptr::copy_nonoverlapping(self.data.ptr(), res.as_mut_ptr() as *mut N, $SZRows * $SZCols) };
+                unsafe { ptr::copy_nonoverlapping(self.data.ptr(), res.as_mut_ptr() as *mut T, $SZRows * $SZCols) };
 
                 unsafe { res.assume_init() }
             }
         }
 
-        impl<N: Scalar, S> AsRef<[[N; $SZRows]; $SZCols]> for Matrix<N, $NRows, $NCols, S>
-        where S: ContiguousStorage<N, $NRows, $NCols> {
+        impl<T: Scalar, S> AsRef<[[T; $SZRows]; $SZCols]> for Matrix<T, $NRows, $NCols, S>
+        where S: ContiguousStorage<T, $NRows, $NCols> {
             #[inline]
-            fn as_ref(&self) -> &[[N; $SZRows]; $SZCols] {
+            fn as_ref(&self) -> &[[T; $SZRows]; $SZCols] {
                 unsafe {
                     mem::transmute(self.data.ptr())
                 }
             }
         }
 
-        impl<N: Scalar, S> AsMut<[[N; $SZRows]; $SZCols]> for Matrix<N, $NRows, $NCols, S>
-        where S: ContiguousStorageMut<N, $NRows, $NCols> {
+        impl<T: Scalar, S> AsMut<[[T; $SZRows]; $SZCols]> for Matrix<T, $NRows, $NCols, S>
+        where S: ContiguousStorageMut<T, $NRows, $NCols> {
             #[inline]
-            fn as_mut(&mut self) -> &mut [[N; $SZRows]; $SZCols] {
+            fn as_mut(&mut self) -> &mut [[T; $SZRows]; $SZCols] {
                 unsafe {
                     mem::transmute(self.data.ptr_mut())
                 }
@@ -229,106 +229,105 @@ impl_from_into_asref_2D!(
     (U6, U2) => (6, 2); (U6, U3) => (6, 3); (U6, U4) => (6, 4); (U6, U5) => (6, 5); (U6, U6) => (6, 6);
 );
 
-
-impl<'a, N, RStride, CStride, const R: usize, const C: usize>
-    From<MatrixSlice<'a, N, Const<R>, Const<C>, RStride, CStride>>
-    for Matrix<N, Const<R>, Const<C>, ArrayStorage<N, R, C>>
+impl<'a, T, RStride, CStride, const R: usize, const C: usize>
+    From<MatrixSlice<'a, T, Const<R>, Const<C>, RStride, CStride>>
+    for Matrix<T, Const<R>, Const<C>, ArrayStorage<T, R, C>>
 where
-    N: Scalar,
+    T: Scalar,
     RStride: Dim,
     CStride: Dim,
 {
-    fn from(matrix_slice: MatrixSlice<'a, N, Const<R>, Const<C>, RStride, CStride>) -> Self {
+    fn from(matrix_slice: MatrixSlice<'a, T, Const<R>, Const<C>, RStride, CStride>) -> Self {
         matrix_slice.into_owned()
     }
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<'a, N, C, RStride, CStride> From<MatrixSlice<'a, N, Dynamic, C, RStride, CStride>>
-    for Matrix<N, Dynamic, C, VecStorage<N, Dynamic, C>>
+impl<'a, T, C, RStride, CStride> From<MatrixSlice<'a, T, Dynamic, C, RStride, CStride>>
+    for Matrix<T, Dynamic, C, VecStorage<T, Dynamic, C>>
 where
-    N: Scalar,
+    T: Scalar,
     C: Dim,
     RStride: Dim,
     CStride: Dim,
 {
-    fn from(matrix_slice: MatrixSlice<'a, N, Dynamic, C, RStride, CStride>) -> Self {
+    fn from(matrix_slice: MatrixSlice<'a, T, Dynamic, C, RStride, CStride>) -> Self {
         matrix_slice.into_owned()
     }
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<'a, N, R, RStride, CStride> From<MatrixSlice<'a, N, R, Dynamic, RStride, CStride>>
-    for Matrix<N, R, Dynamic, VecStorage<N, R, Dynamic>>
+impl<'a, T, R, RStride, CStride> From<MatrixSlice<'a, T, R, Dynamic, RStride, CStride>>
+    for Matrix<T, R, Dynamic, VecStorage<T, R, Dynamic>>
 where
-    N: Scalar,
+    T: Scalar,
     R: DimName,
     RStride: Dim,
     CStride: Dim,
 {
-    fn from(matrix_slice: MatrixSlice<'a, N, R, Dynamic, RStride, CStride>) -> Self {
+    fn from(matrix_slice: MatrixSlice<'a, T, R, Dynamic, RStride, CStride>) -> Self {
         matrix_slice.into_owned()
     }
 }
 
-impl<'a, N, RStride, CStride, const R: usize, const C: usize>
-    From<MatrixSliceMut<'a, N, Const<R>, Const<C>, RStride, CStride>>
-    for Matrix<N, Const<R>, Const<C>, ArrayStorage<N, R, C>>
+impl<'a, T, RStride, CStride, const R: usize, const C: usize>
+    From<MatrixSliceMut<'a, T, Const<R>, Const<C>, RStride, CStride>>
+    for Matrix<T, Const<R>, Const<C>, ArrayStorage<T, R, C>>
 where
-    N: Scalar,
+    T: Scalar,
     RStride: Dim,
     CStride: Dim,
 {
-    fn from(matrix_slice: MatrixSliceMut<'a, N, Const<R>, Const<C>, RStride, CStride>) -> Self {
+    fn from(matrix_slice: MatrixSliceMut<'a, T, Const<R>, Const<C>, RStride, CStride>) -> Self {
         matrix_slice.into_owned()
     }
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<'a, N, C, RStride, CStride> From<MatrixSliceMut<'a, N, Dynamic, C, RStride, CStride>>
-    for Matrix<N, Dynamic, C, VecStorage<N, Dynamic, C>>
+impl<'a, T, C, RStride, CStride> From<MatrixSliceMut<'a, T, Dynamic, C, RStride, CStride>>
+    for Matrix<T, Dynamic, C, VecStorage<T, Dynamic, C>>
 where
-    N: Scalar,
+    T: Scalar,
     C: Dim,
     RStride: Dim,
     CStride: Dim,
 {
-    fn from(matrix_slice: MatrixSliceMut<'a, N, Dynamic, C, RStride, CStride>) -> Self {
+    fn from(matrix_slice: MatrixSliceMut<'a, T, Dynamic, C, RStride, CStride>) -> Self {
         matrix_slice.into_owned()
     }
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<'a, N, R, RStride, CStride> From<MatrixSliceMut<'a, N, R, Dynamic, RStride, CStride>>
-    for Matrix<N, R, Dynamic, VecStorage<N, R, Dynamic>>
+impl<'a, T, R, RStride, CStride> From<MatrixSliceMut<'a, T, R, Dynamic, RStride, CStride>>
+    for Matrix<T, R, Dynamic, VecStorage<T, R, Dynamic>>
 where
-    N: Scalar,
+    T: Scalar,
     R: DimName,
     RStride: Dim,
     CStride: Dim,
 {
-    fn from(matrix_slice: MatrixSliceMut<'a, N, R, Dynamic, RStride, CStride>) -> Self {
+    fn from(matrix_slice: MatrixSliceMut<'a, T, R, Dynamic, RStride, CStride>) -> Self {
         matrix_slice.into_owned()
     }
 }
 
-impl<'a, N, R, C, RSlice, CSlice, RStride, CStride, S> From<&'a Matrix<N, R, C, S>>
-    for MatrixSlice<'a, N, RSlice, CSlice, RStride, CStride>
+impl<'a, T, R, C, RSlice, CSlice, RStride, CStride, S> From<&'a Matrix<T, R, C, S>>
+    for MatrixSlice<'a, T, RSlice, CSlice, RStride, CStride>
 where
-    N: Scalar,
+    T: Scalar,
     R: Dim,
     C: Dim,
     RSlice: Dim,
     CSlice: Dim,
     RStride: Dim,
     CStride: Dim,
-    S: Storage<N, R, C>,
+    S: Storage<T, R, C>,
     ShapeConstraint: DimEq<R, RSlice>
         + DimEq<C, CSlice>
         + DimEq<RStride, S::RStride>
         + DimEq<CStride, S::CStride>,
 {
-    fn from(m: &'a Matrix<N, R, C, S>) -> Self {
+    fn from(m: &'a Matrix<T, R, C, S>) -> Self {
         let (row, col) = m.data.shape();
         let row_slice = RSlice::from_usize(row.value());
         let col_slice = CSlice::from_usize(col.value());
@@ -349,23 +348,23 @@ where
     }
 }
 
-impl<'a, N, R, C, RSlice, CSlice, RStride, CStride, S> From<&'a mut Matrix<N, R, C, S>>
-    for MatrixSlice<'a, N, RSlice, CSlice, RStride, CStride>
+impl<'a, T, R, C, RSlice, CSlice, RStride, CStride, S> From<&'a mut Matrix<T, R, C, S>>
+    for MatrixSlice<'a, T, RSlice, CSlice, RStride, CStride>
 where
-    N: Scalar,
+    T: Scalar,
     R: Dim,
     C: Dim,
     RSlice: Dim,
     CSlice: Dim,
     RStride: Dim,
     CStride: Dim,
-    S: Storage<N, R, C>,
+    S: Storage<T, R, C>,
     ShapeConstraint: DimEq<R, RSlice>
         + DimEq<C, CSlice>
         + DimEq<RStride, S::RStride>
         + DimEq<CStride, S::CStride>,
 {
-    fn from(m: &'a mut Matrix<N, R, C, S>) -> Self {
+    fn from(m: &'a mut Matrix<T, R, C, S>) -> Self {
         let (row, col) = m.data.shape();
         let row_slice = RSlice::from_usize(row.value());
         let col_slice = CSlice::from_usize(col.value());
@@ -386,23 +385,23 @@ where
     }
 }
 
-impl<'a, N, R, C, RSlice, CSlice, RStride, CStride, S> From<&'a mut Matrix<N, R, C, S>>
-    for MatrixSliceMut<'a, N, RSlice, CSlice, RStride, CStride>
+impl<'a, T, R, C, RSlice, CSlice, RStride, CStride, S> From<&'a mut Matrix<T, R, C, S>>
+    for MatrixSliceMut<'a, T, RSlice, CSlice, RStride, CStride>
 where
-    N: Scalar,
+    T: Scalar,
     R: Dim,
     C: Dim,
     RSlice: Dim,
     CSlice: Dim,
     RStride: Dim,
     CStride: Dim,
-    S: StorageMut<N, R, C>,
+    S: StorageMut<T, R, C>,
     ShapeConstraint: DimEq<R, RSlice>
         + DimEq<C, CSlice>
         + DimEq<RStride, S::RStride>
         + DimEq<CStride, S::CStride>,
 {
-    fn from(m: &'a mut Matrix<N, R, C, S>) -> Self {
+    fn from(m: &'a mut Matrix<T, R, C, S>) -> Self {
         let (row, col) = m.data.shape();
         let row_slice = RSlice::from_usize(row.value());
         let col_slice = CSlice::from_usize(col.value());
@@ -424,54 +423,54 @@ where
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<'a, N: Scalar> From<Vec<N>> for DVector<N> {
+impl<'a, T: Scalar> From<Vec<T>> for DVector<T> {
     #[inline]
-    fn from(vec: Vec<N>) -> Self {
+    fn from(vec: Vec<T>) -> Self {
         Self::from_vec(vec)
     }
 }
 
-impl<'a, N: Scalar + Copy, R: Dim, C: Dim, S: ContiguousStorage<N, R, C>> Into<&'a [N]>
-    for &'a Matrix<N, R, C, S>
+impl<'a, T: Scalar + Copy, R: Dim, C: Dim, S: ContiguousStorage<T, R, C>> Into<&'a [T]>
+    for &'a Matrix<T, R, C, S>
 {
     #[inline]
-    fn into(self) -> &'a [N] {
+    fn into(self) -> &'a [T] {
         self.as_slice()
     }
 }
 
-impl<'a, N: Scalar + Copy, R: Dim, C: Dim, S: ContiguousStorageMut<N, R, C>> Into<&'a mut [N]>
-    for &'a mut Matrix<N, R, C, S>
+impl<'a, T: Scalar + Copy, R: Dim, C: Dim, S: ContiguousStorageMut<T, R, C>> Into<&'a mut [T]>
+    for &'a mut Matrix<T, R, C, S>
 {
     #[inline]
-    fn into(self) -> &'a mut [N] {
+    fn into(self) -> &'a mut [T] {
         self.as_mut_slice()
     }
 }
 
-impl<'a, N: Scalar + Copy> From<&'a [N]> for DVectorSlice<'a, N> {
+impl<'a, T: Scalar + Copy> From<&'a [T]> for DVectorSlice<'a, T> {
     #[inline]
-    fn from(slice: &'a [N]) -> Self {
+    fn from(slice: &'a [T]) -> Self {
         Self::from_slice(slice, slice.len())
     }
 }
 
-impl<'a, N: Scalar + Copy> From<&'a mut [N]> for DVectorSliceMut<'a, N> {
+impl<'a, T: Scalar + Copy> From<&'a mut [T]> for DVectorSliceMut<'a, T> {
     #[inline]
-    fn from(slice: &'a mut [N]) -> Self {
+    fn from(slice: &'a mut [T]) -> Self {
         Self::from_slice(slice, slice.len())
     }
 }
 
-impl<N: Scalar + PrimitiveSimdValue, R: Dim, C: Dim> From<[MatrixMN<N::Element, R, C>; 2]>
-    for MatrixMN<N, R, C>
+impl<T: Scalar + PrimitiveSimdValue, R: Dim, C: Dim> From<[OMatrix<T::Element, R, C>; 2]>
+    for OMatrix<T, R, C>
 where
-    N: From<[<N as SimdValue>::Element; 2]>,
-    N::Element: Scalar + SimdValue,
-    DefaultAllocator: Allocator<N, R, C> + Allocator<N::Element, R, C>,
+    T: From<[<T as SimdValue>::Element; 2]>,
+    T::Element: Scalar + SimdValue,
+    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
 {
     #[inline]
-    fn from(arr: [MatrixMN<N::Element, R, C>; 2]) -> Self {
+    fn from(arr: [OMatrix<T::Element, R, C>; 2]) -> Self {
         let (nrows, ncols) = arr[0].data.shape();
 
         Self::from_fn_generic(nrows, ncols, |i, j| {
@@ -484,15 +483,15 @@ where
     }
 }
 
-impl<N: Scalar + PrimitiveSimdValue, R: Dim, C: Dim> From<[MatrixMN<N::Element, R, C>; 4]>
-    for MatrixMN<N, R, C>
+impl<T: Scalar + PrimitiveSimdValue, R: Dim, C: Dim> From<[OMatrix<T::Element, R, C>; 4]>
+    for OMatrix<T, R, C>
 where
-    N: From<[<N as SimdValue>::Element; 4]>,
-    N::Element: Scalar + SimdValue,
-    DefaultAllocator: Allocator<N, R, C> + Allocator<N::Element, R, C>,
+    T: From<[<T as SimdValue>::Element; 4]>,
+    T::Element: Scalar + SimdValue,
+    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
 {
     #[inline]
-    fn from(arr: [MatrixMN<N::Element, R, C>; 4]) -> Self {
+    fn from(arr: [OMatrix<T::Element, R, C>; 4]) -> Self {
         let (nrows, ncols) = arr[0].data.shape();
 
         Self::from_fn_generic(nrows, ncols, |i, j| {
@@ -507,15 +506,15 @@ where
     }
 }
 
-impl<N: Scalar + PrimitiveSimdValue, R: Dim, C: Dim> From<[MatrixMN<N::Element, R, C>; 8]>
-    for MatrixMN<N, R, C>
+impl<T: Scalar + PrimitiveSimdValue, R: Dim, C: Dim> From<[OMatrix<T::Element, R, C>; 8]>
+    for OMatrix<T, R, C>
 where
-    N: From<[<N as SimdValue>::Element; 8]>,
-    N::Element: Scalar + SimdValue,
-    DefaultAllocator: Allocator<N, R, C> + Allocator<N::Element, R, C>,
+    T: From<[<T as SimdValue>::Element; 8]>,
+    T::Element: Scalar + SimdValue,
+    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
 {
     #[inline]
-    fn from(arr: [MatrixMN<N::Element, R, C>; 8]) -> Self {
+    fn from(arr: [OMatrix<T::Element, R, C>; 8]) -> Self {
         let (nrows, ncols) = arr[0].data.shape();
 
         Self::from_fn_generic(nrows, ncols, |i, j| {
@@ -534,14 +533,14 @@ where
     }
 }
 
-impl<N: Scalar + PrimitiveSimdValue, R: Dim, C: Dim> From<[MatrixMN<N::Element, R, C>; 16]>
-    for MatrixMN<N, R, C>
+impl<T: Scalar + PrimitiveSimdValue, R: Dim, C: Dim> From<[OMatrix<T::Element, R, C>; 16]>
+    for OMatrix<T, R, C>
 where
-    N: From<[<N as SimdValue>::Element; 16]>,
-    N::Element: Scalar + SimdValue,
-    DefaultAllocator: Allocator<N, R, C> + Allocator<N::Element, R, C>,
+    T: From<[<T as SimdValue>::Element; 16]>,
+    T::Element: Scalar + SimdValue,
+    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
 {
-    fn from(arr: [MatrixMN<N::Element, R, C>; 16]) -> Self {
+    fn from(arr: [OMatrix<T::Element, R, C>; 16]) -> Self {
         let (nrows, ncols) = arr[0].data.shape();
 
         Self::from_fn_generic(nrows, ncols, |i, j| {

src/base/coordinates.rs

@@ -24,17 +24,17 @@ macro_rules! coords_impl(
         #[repr(C)]
         #[derive(Eq, PartialEq, Clone, Hash, Debug, Copy)]
         #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
-        pub struct $T<N: Scalar> {
-            $(pub $comps: N),*
+        pub struct $T<T: Scalar> {
+            $(pub $comps: T),*
         }
     }
 );
 
 macro_rules! deref_impl(
     ($R: ty, $C: ty; $Target: ident) => {
-        impl<N: Scalar, S> Deref for Matrix<N, $R, $C, S>
-            where S: ContiguousStorage<N, $R, $C> {
-            type Target = $Target<N>;
+        impl<T: Scalar, S> Deref for Matrix<T, $R, $C, S>
+            where S: ContiguousStorage<T, $R, $C> {
+            type Target = $Target<T>;
 
             #[inline]
             fn deref(&self) -> &Self::Target {
@@ -42,8 +42,8 @@ macro_rules! deref_impl(
             }
         }
 
-        impl<N: Scalar, S> DerefMut for Matrix<N, $R, $C, S>
-            where S: ContiguousStorageMut<N, $R, $C> {
+        impl<T: Scalar, S> DerefMut for Matrix<T, $R, $C, S>
+            where S: ContiguousStorageMut<T, $R, $C> {
             #[inline]
             fn deref_mut(&mut self) -> &mut Self::Target {
                 unsafe { mem::transmute(self.data.ptr_mut()) }

src/base/default_allocator.rs

@@ -31,10 +31,10 @@ use crate::base::Scalar;
 pub struct DefaultAllocator;
 
 // Static - Static
-impl<N: Scalar, const R: usize, const C: usize> Allocator<N, Const<R>, Const<C>>
+impl<T: Scalar, const R: usize, const C: usize> Allocator<T, Const<R>, Const<C>>
     for DefaultAllocator
 {
-    type Buffer = ArrayStorage<N, R, C>;
+    type Buffer = ArrayStorage<T, R, C>;
 
     #[inline]
     unsafe fn allocate_uninitialized(_: Const<R>, _: Const<C>) -> mem::MaybeUninit<Self::Buffer> {
@@ -42,7 +42,7 @@ impl<N: Scalar, const R: usize, const C: usize> Allocator<N, Const<R>, Const<C>>
     }
 
     #[inline]
-    fn allocate_from_iterator<I: IntoIterator<Item = N>>(
+    fn allocate_from_iterator<I: IntoIterator<Item = T>>(
         nrows: Const<R>,
         ncols: Const<C>,
         iter: I,
@@ -70,8 +70,8 @@ impl<N: Scalar, const R: usize, const C: usize> Allocator<N, Const<R>, Const<C>>
 // Dynamic - Static
 // Dynamic - Dynamic
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N: Scalar, C: Dim> Allocator<N, Dynamic, C> for DefaultAllocator {
-    type Buffer = VecStorage<N, Dynamic, C>;
+impl<T: Scalar, C: Dim> Allocator<T, Dynamic, C> for DefaultAllocator {
+    type Buffer = VecStorage<T, Dynamic, C>;
 
     #[inline]
     unsafe fn allocate_uninitialized(nrows: Dynamic, ncols: C) -> mem::MaybeUninit<Self::Buffer> {
@@ -84,13 +84,13 @@ impl<N: Scalar, C: Dim> Allocator<N, Dynamic, C> for DefaultAllocator {
     }
 
     #[inline]
-    fn allocate_from_iterator<I: IntoIterator<Item = N>>(
+    fn allocate_from_iterator<I: IntoIterator<Item = T>>(
         nrows: Dynamic,
         ncols: C,
         iter: I,
     ) -> Self::Buffer {
         let it = iter.into_iter();
-        let res: Vec<N> = it.collect();
+        let res: Vec<T> = it.collect();
         assert!(res.len() == nrows.value() * ncols.value(),
                 "Allocation from iterator error: the iterator did not yield the correct number of elements.");
 
@@ -100,8 +100,8 @@ impl<N: Scalar, C: Dim> Allocator<N, Dynamic, C> for DefaultAllocator {
 
 // Static - Dynamic
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N: Scalar, R: DimName> Allocator<N, R, Dynamic> for DefaultAllocator {
-    type Buffer = VecStorage<N, R, Dynamic>;
+impl<T: Scalar, R: DimName> Allocator<T, R, Dynamic> for DefaultAllocator {
+    type Buffer = VecStorage<T, R, Dynamic>;
 
     #[inline]
     unsafe fn allocate_uninitialized(nrows: R, ncols: Dynamic) -> mem::MaybeUninit<Self::Buffer> {
@@ -114,13 +114,13 @@ impl<N: Scalar, R: DimName> Allocator<N, R, Dynamic> for DefaultAllocator {
     }
 
     #[inline]
-    fn allocate_from_iterator<I: IntoIterator<Item = N>>(
+    fn allocate_from_iterator<I: IntoIterator<Item = T>>(
         nrows: R,
         ncols: Dynamic,
         iter: I,
     ) -> Self::Buffer {
         let it = iter.into_iter();
-        let res: Vec<N> = it.collect();
+        let res: Vec<T> = it.collect();
         assert!(res.len() == nrows.value() * ncols.value(),
                 "Allocation from iterator error: the iterator did not yield the correct number of elements.");
 
@@ -134,24 +134,24 @@ impl<N: Scalar, R: DimName> Allocator<N, R, Dynamic> for DefaultAllocator {
  *
  */
 // Anything -> Static × Static
-impl<N: Scalar, RFrom, CFrom, const RTO: usize, const CTO: usize>
-    Reallocator<N, RFrom, CFrom, Const<RTO>, Const<CTO>> for DefaultAllocator
+impl<T: Scalar, RFrom, CFrom, const RTO: usize, const CTO: usize>
+    Reallocator<T, RFrom, CFrom, Const<RTO>, Const<CTO>> for DefaultAllocator
 where
     RFrom: Dim,
     CFrom: Dim,
-    Self: Allocator<N, RFrom, CFrom>,
+    Self: Allocator<T, RFrom, CFrom>,
 {
     #[inline]
     unsafe fn reallocate_copy(
         rto: Const<RTO>,
         cto: Const<CTO>,
-        buf: <Self as Allocator<N, RFrom, CFrom>>::Buffer,
-    ) -> ArrayStorage<N, RTO, CTO> {
+        buf: <Self as Allocator<T, RFrom, CFrom>>::Buffer,
+    ) -> ArrayStorage<T, RTO, CTO> {
         #[cfg(feature = "no_unsound_assume_init")]
-        let mut res: ArrayStorage<N, RTO, CTO> = unimplemented!();
+        let mut res: ArrayStorage<T, RTO, CTO> = unimplemented!();
         #[cfg(not(feature = "no_unsound_assume_init"))]
         let mut res =
-            <Self as Allocator<N, Const<RTO>, Const<CTO>>>::allocate_uninitialized(rto, cto)
+            <Self as Allocator<T, Const<RTO>, Const<CTO>>>::allocate_uninitialized(rto, cto)
                 .assume_init();
 
         let (rfrom, cfrom) = buf.shape();
@@ -166,8 +166,8 @@ where
 
 // Static × Static -> Dynamic × Any
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N: Scalar, CTo, const RFROM: usize, const CFROM: usize>
-    Reallocator<N, Const<RFROM>, Const<CFROM>, Dynamic, CTo> for DefaultAllocator
+impl<T: Scalar, CTo, const RFROM: usize, const CFROM: usize>
+    Reallocator<T, Const<RFROM>, Const<CFROM>, Dynamic, CTo> for DefaultAllocator
 where
     CTo: Dim,
 {
@@ -175,13 +175,13 @@ where
     unsafe fn reallocate_copy(
         rto: Dynamic,
         cto: CTo,
-        buf: ArrayStorage<N, RFROM, CFROM>,
-    ) -> VecStorage<N, Dynamic, CTo> {
+        buf: ArrayStorage<T, RFROM, CFROM>,
+    ) -> VecStorage<T, Dynamic, CTo> {
         #[cfg(feature = "no_unsound_assume_init")]
-        let mut res: VecStorage<N, Dynamic, CTo> = unimplemented!();
+        let mut res: VecStorage<T, Dynamic, CTo> = unimplemented!();
         #[cfg(not(feature = "no_unsound_assume_init"))]
         let mut res =
-            <Self as Allocator<N, Dynamic, CTo>>::allocate_uninitialized(rto, cto).assume_init();
+            <Self as Allocator<T, Dynamic, CTo>>::allocate_uninitialized(rto, cto).assume_init();
 
         let (rfrom, cfrom) = buf.shape();
 
@@ -195,8 +195,8 @@ where
 
 // Static × Static -> Static × Dynamic
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N: Scalar, RTo, const RFROM: usize, const CFROM: usize>
-    Reallocator<N, Const<RFROM>, Const<CFROM>, RTo, Dynamic> for DefaultAllocator
+impl<T: Scalar, RTo, const RFROM: usize, const CFROM: usize>
+    Reallocator<T, Const<RFROM>, Const<CFROM>, RTo, Dynamic> for DefaultAllocator
 where
     RTo: DimName,
 {
@@ -204,13 +204,13 @@ where
     unsafe fn reallocate_copy(
         rto: RTo,
         cto: Dynamic,
-        buf: ArrayStorage<N, RFROM, CFROM>,
-    ) -> VecStorage<N, RTo, Dynamic> {
+        buf: ArrayStorage<T, RFROM, CFROM>,
+    ) -> VecStorage<T, RTo, Dynamic> {
         #[cfg(feature = "no_unsound_assume_init")]
-        let mut res: VecStorage<N, RTo, Dynamic> = unimplemented!();
+        let mut res: VecStorage<T, RTo, Dynamic> = unimplemented!();
         #[cfg(not(feature = "no_unsound_assume_init"))]
         let mut res =
-            <Self as Allocator<N, RTo, Dynamic>>::allocate_uninitialized(rto, cto).assume_init();
+            <Self as Allocator<T, RTo, Dynamic>>::allocate_uninitialized(rto, cto).assume_init();
 
         let (rfrom, cfrom) = buf.shape();
 
@@ -224,60 +224,60 @@ where
 
 // All conversion from a dynamic buffer to a dynamic buffer.
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N: Scalar, CFrom: Dim, CTo: Dim> Reallocator<N, Dynamic, CFrom, Dynamic, CTo>
+impl<T: Scalar, CFrom: Dim, CTo: Dim> Reallocator<T, Dynamic, CFrom, Dynamic, CTo>
     for DefaultAllocator
 {
     #[inline]
     unsafe fn reallocate_copy(
         rto: Dynamic,
         cto: CTo,
-        buf: VecStorage<N, Dynamic, CFrom>,
-    ) -> VecStorage<N, Dynamic, CTo> {
+        buf: VecStorage<T, Dynamic, CFrom>,
+    ) -> VecStorage<T, Dynamic, CTo> {
         let new_buf = buf.resize(rto.value() * cto.value());
         VecStorage::new(rto, cto, new_buf)
     }
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N: Scalar, CFrom: Dim, RTo: DimName> Reallocator<N, Dynamic, CFrom, RTo, Dynamic>
+impl<T: Scalar, CFrom: Dim, RTo: DimName> Reallocator<T, Dynamic, CFrom, RTo, Dynamic>
     for DefaultAllocator
 {
     #[inline]
     unsafe fn reallocate_copy(
         rto: RTo,
         cto: Dynamic,
-        buf: VecStorage<N, Dynamic, CFrom>,
-    ) -> VecStorage<N, RTo, Dynamic> {
+        buf: VecStorage<T, Dynamic, CFrom>,
+    ) -> VecStorage<T, RTo, Dynamic> {
         let new_buf = buf.resize(rto.value() * cto.value());
         VecStorage::new(rto, cto, new_buf)
     }
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N: Scalar, RFrom: DimName, CTo: Dim> Reallocator<N, RFrom, Dynamic, Dynamic, CTo>
+impl<T: Scalar, RFrom: DimName, CTo: Dim> Reallocator<T, RFrom, Dynamic, Dynamic, CTo>
     for DefaultAllocator
 {
     #[inline]
     unsafe fn reallocate_copy(
         rto: Dynamic,
         cto: CTo,
-        buf: VecStorage<N, RFrom, Dynamic>,
-    ) -> VecStorage<N, Dynamic, CTo> {
+        buf: VecStorage<T, RFrom, Dynamic>,
+    ) -> VecStorage<T, Dynamic, CTo> {
         let new_buf = buf.resize(rto.value() * cto.value());
         VecStorage::new(rto, cto, new_buf)
     }
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N: Scalar, RFrom: DimName, RTo: DimName> Reallocator<N, RFrom, Dynamic, RTo, Dynamic>
+impl<T: Scalar, RFrom: DimName, RTo: DimName> Reallocator<T, RFrom, Dynamic, RTo, Dynamic>
     for DefaultAllocator
 {
     #[inline]
     unsafe fn reallocate_copy(
         rto: RTo,
         cto: Dynamic,
-        buf: VecStorage<N, RFrom, Dynamic>,
-    ) -> VecStorage<N, RTo, Dynamic> {
+        buf: VecStorage<T, RFrom, Dynamic>,
+    ) -> VecStorage<T, RTo, Dynamic> {
         let new_buf = buf.resize(rto.value() * cto.value());
         VecStorage::new(rto, cto, new_buf)
     }

src/base/edition.rs

@@ -10,47 +10,45 @@ use crate::base::allocator::{Allocator, Reallocator};
 use crate::base::constraint::{DimEq, SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
 #[cfg(any(feature = "std", feature = "alloc"))]
 use crate::base::dimension::Dynamic;
-use crate::base::dimension::{
-    Dim, DimAdd, DimDiff, DimMin, DimMinimum, DimName, DimSub, DimSum, U1,
-};
+use crate::base::dimension::{Const, Dim, DimAdd, DimDiff, DimMin, DimMinimum, DimSub, DimSum, U1};
 use crate::base::storage::{ReshapableStorage, Storage, StorageMut};
 #[cfg(any(feature = "std", feature = "alloc"))]
 use crate::base::DMatrix;
-use crate::base::{DefaultAllocator, Matrix, MatrixMN, RowVector, Scalar, Vector};
+use crate::base::{DefaultAllocator, Matrix, OMatrix, RowVector, SMatrix, Scalar, Vector};
 
 /// # Rows and columns extraction
-impl<N: Scalar + Zero, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar + Zero, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     /// Extracts the upper triangular part of this matrix (including the diagonal).
     #[inline]
-    pub fn upper_triangle(&self) -> MatrixMN<N, R, C>
+    pub fn upper_triangle(&self) -> OMatrix<T, R, C>
     where
-        DefaultAllocator: Allocator<N, R, C>,
+        DefaultAllocator: Allocator<T, R, C>,
     {
         let mut res = self.clone_owned();
-        res.fill_lower_triangle(N::zero(), 1);
+        res.fill_lower_triangle(T::zero(), 1);
 
         res
     }
 
     /// Extracts the lower triangular part of this matrix (including the diagonal).
     #[inline]
-    pub fn lower_triangle(&self) -> MatrixMN<N, R, C>
+    pub fn lower_triangle(&self) -> OMatrix<T, R, C>
     where
-        DefaultAllocator: Allocator<N, R, C>,
+        DefaultAllocator: Allocator<T, R, C>,
     {
         let mut res = self.clone_owned();
-        res.fill_upper_triangle(N::zero(), 1);
+        res.fill_upper_triangle(T::zero(), 1);
 
         res
     }
 
     /// Creates a new matrix by extracting the given set of rows from `self`.
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn select_rows<'a, I>(&self, irows: I) -> MatrixMN<N, Dynamic, C>
+    pub fn select_rows<'a, I>(&self, irows: I) -> OMatrix<T, Dynamic, C>
     where
         I: IntoIterator<Item = &'a usize>,
         I::IntoIter: ExactSizeIterator + Clone,
-        DefaultAllocator: Allocator<N, Dynamic, C>,
+        DefaultAllocator: Allocator<T, Dynamic, C>,
     {
         let irows = irows.into_iter();
         let ncols = self.data.shape().1;
@@ -82,11 +80,11 @@ impl<N: Scalar + Zero, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
     /// Creates a new matrix by extracting the given set of columns from `self`.
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn select_columns<'a, I>(&self, icols: I) -> MatrixMN<N, R, Dynamic>
+    pub fn select_columns<'a, I>(&self, icols: I) -> OMatrix<T, R, Dynamic>
     where
         I: IntoIterator<Item = &'a usize>,
         I::IntoIter: ExactSizeIterator,
-        DefaultAllocator: Allocator<N, R, Dynamic>,
+        DefaultAllocator: Allocator<T, R, Dynamic>,
     {
         let icols = icols.into_iter();
         let nrows = self.data.shape().0;
@@ -103,13 +101,13 @@ impl<N: Scalar + Zero, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 }
 
 /// # Set rows, columns, and diagonal
-impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<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<N, R2, S2>)
+    pub fn set_diagonal<R2: Dim, S2>(&mut self, diag: &Vector<T, R2, S2>)
     where
         R: DimMin<C>,
-        S2: Storage<N, R2>,
+        S2: Storage<T, R2>,
         ShapeConstraint: DimEq<DimMinimum<R, C>, R2>,
     {
         let (nrows, ncols) = self.shape();
@@ -127,7 +125,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     /// minimum of the number of rows and columns of `self`, and starting with the
     /// diagonal element at index (0, 0).
     #[inline]
-    pub fn set_partial_diagonal(&mut self, diag: impl Iterator<Item = N>) {
+    pub fn set_partial_diagonal(&mut self, diag: impl Iterator<Item = T>) {
         let (nrows, ncols) = self.shape();
         let min_nrows_ncols = cmp::min(nrows, ncols);
 
@@ -138,9 +136,9 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
 
     /// Fills the selected row of this matrix with the content of the given vector.
     #[inline]
-    pub fn set_row<C2: Dim, S2>(&mut self, i: usize, row: &RowVector<N, C2, S2>)
+    pub fn set_row<C2: Dim, S2>(&mut self, i: usize, row: &RowVector<T, C2, S2>)
     where
-        S2: Storage<N, U1, C2>,
+        S2: Storage<T, U1, C2>,
         ShapeConstraint: SameNumberOfColumns<C, C2>,
     {
         self.row_mut(i).copy_from(row);
@@ -148,9 +146,9 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
 
     /// Fills the selected column of this matrix with the content of the given vector.
     #[inline]
-    pub fn set_column<R2: Dim, S2>(&mut self, i: usize, column: &Vector<N, R2, S2>)
+    pub fn set_column<R2: Dim, S2>(&mut self, i: usize, column: &Vector<T, R2, S2>)
     where
-        S2: Storage<N, R2, U1>,
+        S2: Storage<T, R2, U1>,
         ShapeConstraint: SameNumberOfRows<R, R2>,
     {
         self.column_mut(i).copy_from(column);
@@ -158,10 +156,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
 }
 
 /// # In-place filling
-impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
     /// Sets all the elements of this matrix to `val`.
     #[inline]
-    pub fn fill(&mut self, val: N) {
+    pub fn fill(&mut self, val: T) {
         for e in self.iter_mut() {
             *e = val.inlined_clone()
         }
@@ -171,15 +169,15 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     #[inline]
     pub fn fill_with_identity(&mut self)
     where
-        N: Zero + One,
+        T: Zero + One,
     {
-        self.fill(N::zero());
-        self.fill_diagonal(N::one());
+        self.fill(T::zero());
+        self.fill_diagonal(T::one());
     }
 
     /// Sets all the diagonal elements of this matrix to `val`.
     #[inline]
-    pub fn fill_diagonal(&mut self, val: N) {
+    pub fn fill_diagonal(&mut self, val: T) {
         let (nrows, ncols) = self.shape();
         let n = cmp::min(nrows, ncols);
 
@@ -190,7 +188,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
 
     /// Sets all the elements of the selected row to `val`.
     #[inline]
-    pub fn fill_row(&mut self, i: usize, val: N) {
+    pub fn fill_row(&mut self, i: usize, val: T) {
         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() }
@@ -199,7 +197,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
 
     /// Sets all the elements of the selected column to `val`.
     #[inline]
-    pub fn fill_column(&mut self, j: usize, val: N) {
+    pub fn fill_column(&mut self, j: usize, val: T) {
         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() }
@@ -214,7 +212,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, 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: N, shift: usize) {
+    pub fn fill_lower_triangle(&mut self, val: T, shift: usize) {
         for j in 0..self.ncols() {
             for i in (j + shift)..self.nrows() {
                 unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
@@ -230,7 +228,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, 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: N, shift: usize) {
+    pub fn fill_upper_triangle(&mut self, val: T, shift: usize) {
         for j in shift..self.ncols() {
             // TODO: is there a more efficient way to avoid the min ?
             // (necessary for rectangular matrices)
@@ -241,7 +239,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     }
 }
 
-impl<N: Scalar, D: Dim, S: StorageMut<N, D, D>> Matrix<N, D, D, S> {
+impl<T: Scalar, D: Dim, S: StorageMut<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.
@@ -275,7 +273,7 @@ impl<N: Scalar, D: Dim, S: StorageMut<N, D, D>> Matrix<N, D, D, S> {
 }
 
 /// # In-place swapping
-impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
     /// Swaps two rows in-place.
     #[inline]
     pub fn swap_rows(&mut self, irow1: usize, irow2: usize) {
@@ -311,7 +309,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
  *
  */
 /// # Rows and columns removal
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     /*
      *
      * Column removal.
@@ -319,20 +317,20 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
      */
     /// Removes the `i`-th column from this matrix.
     #[inline]
-    pub fn remove_column(self, i: usize) -> MatrixMN<N, R, DimDiff<C, U1>>
+    pub fn remove_column(self, i: usize) -> OMatrix<T, R, DimDiff<C, U1>>
     where
         C: DimSub<U1>,
-        DefaultAllocator: Reallocator<N, R, C, R, DimDiff<C, U1>>,
+        DefaultAllocator: Reallocator<T, R, C, R, DimDiff<C, U1>>,
     {
-        self.remove_fixed_columns::<U1>(i)
+        self.remove_fixed_columns::<1>(i)
     }
 
     /// Removes all columns in `indices`   
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn remove_columns_at(self, indices: &[usize]) -> MatrixMN<N, R, Dynamic>
+    pub fn remove_columns_at(self, indices: &[usize]) -> OMatrix<T, R, Dynamic>
     where
         C: DimSub<Dynamic, Output = Dynamic>,
-        DefaultAllocator: Reallocator<N, R, C, R, Dynamic>,
+        DefaultAllocator: Reallocator<T, R, C, R, Dynamic>,
     {
         let mut m = self.into_owned();
         let (nrows, ncols) = m.data.shape();
@@ -363,10 +361,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
     /// Removes all rows in `indices`   
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn remove_rows_at(self, indices: &[usize]) -> MatrixMN<N, Dynamic, C>
+    pub fn remove_rows_at(self, indices: &[usize]) -> OMatrix<T, Dynamic, C>
     where
         R: DimSub<Dynamic, Output = Dynamic>,
-        DefaultAllocator: Reallocator<N, R, C, Dynamic, C>,
+        DefaultAllocator: Reallocator<T, R, C, Dynamic, C>,
     {
         let mut m = self.into_owned();
         let (nrows, ncols) = m.data.shape();
@@ -398,22 +396,24 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// Removes `D::dim()` consecutive columns from this matrix, starting with the `i`-th
     /// (included).
     #[inline]
-    pub fn remove_fixed_columns<D>(self, i: usize) -> MatrixMN<N, R, DimDiff<C, D>>
+    pub fn remove_fixed_columns<const D: usize>(
+        self,
+        i: usize,
+    ) -> OMatrix<T, R, DimDiff<C, Const<D>>>
     where
-        D: DimName,
-        C: DimSub<D>,
-        DefaultAllocator: Reallocator<N, R, C, R, DimDiff<C, D>>,
+        C: DimSub<Const<D>>,
+        DefaultAllocator: Reallocator<T, R, C, R, DimDiff<C, Const<D>>>,
     {
-        self.remove_columns_generic(i, D::name())
+        self.remove_columns_generic(i, Const::<D>)
     }
 
     /// Removes `n` consecutive columns from this matrix, starting with the `i`-th (included).
     #[inline]
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn remove_columns(self, i: usize, n: usize) -> MatrixMN<N, R, Dynamic>
+    pub fn remove_columns(self, i: usize, n: usize) -> OMatrix<T, R, Dynamic>
     where
         C: DimSub<Dynamic, Output = Dynamic>,
-        DefaultAllocator: Reallocator<N, R, C, R, Dynamic>,
+        DefaultAllocator: Reallocator<T, R, C, R, Dynamic>,
     {
         self.remove_columns_generic(i, Dynamic::new(n))
     }
@@ -423,11 +423,11 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// This is the generic implementation of `.remove_columns(...)` and
     /// `.remove_fixed_columns(...)` which have nicer API interfaces.
     #[inline]
-    pub fn remove_columns_generic<D>(self, i: usize, nremove: D) -> MatrixMN<N, R, DimDiff<C, D>>
+    pub fn remove_columns_generic<D>(self, i: usize, nremove: D) -> OMatrix<T, R, DimDiff<C, D>>
     where
         D: Dim,
         C: DimSub<D>,
-        DefaultAllocator: Reallocator<N, R, C, R, DimDiff<C, D>>,
+        DefaultAllocator: Reallocator<T, R, C, R, DimDiff<C, D>>,
     {
         let mut m = self.into_owned();
         let (nrows, ncols) = m.data.shape();
@@ -468,32 +468,31 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
      */
     /// Removes the `i`-th row from this matrix.
     #[inline]
-    pub fn remove_row(self, i: usize) -> MatrixMN<N, DimDiff<R, U1>, C>
+    pub fn remove_row(self, i: usize) -> OMatrix<T, DimDiff<R, U1>, C>
     where
         R: DimSub<U1>,
-        DefaultAllocator: Reallocator<N, R, C, DimDiff<R, U1>, C>,
+        DefaultAllocator: Reallocator<T, R, C, DimDiff<R, U1>, C>,
     {
-        self.remove_fixed_rows::<U1>(i)
+        self.remove_fixed_rows::<1>(i)
     }
 
     /// Removes `D::dim()` consecutive rows from this matrix, starting with the `i`-th (included).
     #[inline]
-    pub fn remove_fixed_rows<D>(self, i: usize) -> MatrixMN<N, DimDiff<R, D>, C>
+    pub fn remove_fixed_rows<const D: usize>(self, i: usize) -> OMatrix<T, DimDiff<R, Const<D>>, C>
     where
-        D: DimName,
-        R: DimSub<D>,
-        DefaultAllocator: Reallocator<N, R, C, DimDiff<R, D>, C>,
+        R: DimSub<Const<D>>,
+        DefaultAllocator: Reallocator<T, R, C, DimDiff<R, Const<D>>, C>,
     {
-        self.remove_rows_generic(i, D::name())
+        self.remove_rows_generic(i, Const::<D>)
     }
 
     /// Removes `n` consecutive rows from this matrix, starting with the `i`-th (included).
     #[inline]
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn remove_rows(self, i: usize, n: usize) -> MatrixMN<N, Dynamic, C>
+    pub fn remove_rows(self, i: usize, n: usize) -> OMatrix<T, Dynamic, C>
     where
         R: DimSub<Dynamic, Output = Dynamic>,
-        DefaultAllocator: Reallocator<N, R, C, Dynamic, C>,
+        DefaultAllocator: Reallocator<T, R, C, Dynamic, C>,
     {
         self.remove_rows_generic(i, Dynamic::new(n))
     }
@@ -503,11 +502,11 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// This is the generic implementation of `.remove_rows(...)` and `.remove_fixed_rows(...)`
     /// which have nicer API interfaces.
     #[inline]
-    pub fn remove_rows_generic<D>(self, i: usize, nremove: D) -> MatrixMN<N, DimDiff<R, D>, C>
+    pub fn remove_rows_generic<D>(self, i: usize, nremove: D) -> OMatrix<T, DimDiff<R, D>, C>
     where
         D: Dim,
         R: DimSub<D>,
-        DefaultAllocator: Reallocator<N, R, C, DimDiff<R, D>, C>,
+        DefaultAllocator: Reallocator<T, R, C, DimDiff<R, D>, C>,
     {
         let mut m = self.into_owned();
         let (nrows, ncols) = m.data.shape();
@@ -539,7 +538,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 }
 
 /// # Rows and columns insertion
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     /*
      *
      * Columns insertion.
@@ -547,23 +546,26 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
      */
     /// Inserts a column filled with `val` at the `i-th` position.
     #[inline]
-    pub fn insert_column(self, i: usize, val: N) -> MatrixMN<N, R, DimSum<C, U1>>
+    pub fn insert_column(self, i: usize, val: T) -> OMatrix<T, R, DimSum<C, U1>>
     where
         C: DimAdd<U1>,
-        DefaultAllocator: Reallocator<N, R, C, R, DimSum<C, U1>>,
+        DefaultAllocator: Reallocator<T, R, C, R, DimSum<C, U1>>,
     {
-        self.insert_fixed_columns::<U1>(i, val)
+        self.insert_fixed_columns::<1>(i, val)
     }
 
-    /// Inserts `D::dim()` columns filled with `val` starting at the `i-th` position.
+    /// Inserts `D` columns filled with `val` starting at the `i-th` position.
     #[inline]
-    pub fn insert_fixed_columns<D>(self, i: usize, val: N) -> MatrixMN<N, R, DimSum<C, D>>
+    pub fn insert_fixed_columns<const D: usize>(
+        self,
+        i: usize,
+        val: T,
+    ) -> OMatrix<T, R, DimSum<C, Const<D>>>
     where
-        D: DimName,
-        C: DimAdd<D>,
-        DefaultAllocator: Reallocator<N, R, C, R, DimSum<C, D>>,
+        C: DimAdd<Const<D>>,
+        DefaultAllocator: Reallocator<T, R, C, R, DimSum<C, Const<D>>>,
     {
-        let mut res = unsafe { self.insert_columns_generic_uninitialized(i, D::name()) };
+        let mut res = unsafe { self.insert_columns_generic_uninitialized(i, Const::<D>) };
         res.fixed_columns_mut::<D>(i).fill(val);
         res
     }
@@ -571,10 +573,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// Inserts `n` columns filled with `val` starting at the `i-th` position.
     #[inline]
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn insert_columns(self, i: usize, n: usize, val: N) -> MatrixMN<N, R, Dynamic>
+    pub fn insert_columns(self, i: usize, n: usize, val: T) -> OMatrix<T, R, Dynamic>
     where
         C: DimAdd<Dynamic, Output = Dynamic>,
-        DefaultAllocator: Reallocator<N, R, C, R, Dynamic>,
+        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);
@@ -589,11 +591,11 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         self,
         i: usize,
         ninsert: D,
-    ) -> MatrixMN<N, R, DimSum<C, D>>
+    ) -> OMatrix<T, R, DimSum<C, D>>
     where
         D: Dim,
         C: DimAdd<D>,
-        DefaultAllocator: Reallocator<N, R, C, R, DimSum<C, D>>,
+        DefaultAllocator: Reallocator<T, R, C, R, DimSum<C, D>>,
     {
         let m = self.into_owned();
         let (nrows, ncols) = m.data.shape();
@@ -625,23 +627,26 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
      */
     /// Inserts a row filled with `val` at the `i-th` position.
     #[inline]
-    pub fn insert_row(self, i: usize, val: N) -> MatrixMN<N, DimSum<R, U1>, C>
+    pub fn insert_row(self, i: usize, val: T) -> OMatrix<T, DimSum<R, U1>, C>
     where
         R: DimAdd<U1>,
-        DefaultAllocator: Reallocator<N, R, C, DimSum<R, U1>, C>,
+        DefaultAllocator: Reallocator<T, R, C, DimSum<R, U1>, C>,
     {
-        self.insert_fixed_rows::<U1>(i, val)
+        self.insert_fixed_rows::<1>(i, val)
     }
 
     /// Inserts `D::dim()` rows filled with `val` starting at the `i-th` position.
     #[inline]
-    pub fn insert_fixed_rows<D>(self, i: usize, val: N) -> MatrixMN<N, DimSum<R, D>, C>
+    pub fn insert_fixed_rows<const D: usize>(
+        self,
+        i: usize,
+        val: T,
+    ) -> OMatrix<T, DimSum<R, Const<D>>, C>
     where
-        D: DimName,
-        R: DimAdd<D>,
-        DefaultAllocator: Reallocator<N, R, C, DimSum<R, D>, C>,
+        R: DimAdd<Const<D>>,
+        DefaultAllocator: Reallocator<T, R, C, DimSum<R, Const<D>>, C>,
     {
-        let mut res = unsafe { self.insert_rows_generic_uninitialized(i, D::name()) };
+        let mut res = unsafe { self.insert_rows_generic_uninitialized(i, Const::<D>) };
         res.fixed_rows_mut::<D>(i).fill(val);
         res
     }
@@ -649,10 +654,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// Inserts `n` rows filled with `val` starting at the `i-th` position.
     #[inline]
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn insert_rows(self, i: usize, n: usize, val: N) -> MatrixMN<N, Dynamic, C>
+    pub fn insert_rows(self, i: usize, n: usize, val: T) -> OMatrix<T, Dynamic, C>
     where
         R: DimAdd<Dynamic, Output = Dynamic>,
-        DefaultAllocator: Reallocator<N, R, C, Dynamic, C>,
+        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);
@@ -669,11 +674,11 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         self,
         i: usize,
         ninsert: D,
-    ) -> MatrixMN<N, DimSum<R, D>, C>
+    ) -> OMatrix<T, DimSum<R, D>, C>
     where
         D: Dim,
         R: DimAdd<D>,
-        DefaultAllocator: Reallocator<N, R, C, DimSum<R, D>, C>,
+        DefaultAllocator: Reallocator<T, R, C, DimSum<R, D>, C>,
     {
         let m = self.into_owned();
         let (nrows, ncols) = m.data.shape();
@@ -700,15 +705,15 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 }
 
 /// # Resizing and reshaping
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     /// Resizes this matrix so that it contains `new_nrows` rows and `new_ncols` columns.
     ///
     /// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
     /// rows and/or columns than `self`, then the extra rows or columns are filled with `val`.
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn resize(self, new_nrows: usize, new_ncols: usize, val: N) -> DMatrix<N>
+    pub fn resize(self, new_nrows: usize, new_ncols: usize, val: T) -> DMatrix<T>
     where
-        DefaultAllocator: Reallocator<N, R, C, Dynamic, Dynamic>,
+        DefaultAllocator: Reallocator<T, R, C, Dynamic, Dynamic>,
     {
         self.resize_generic(Dynamic::new(new_nrows), Dynamic::new(new_ncols), val)
     }
@@ -718,9 +723,9 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
     /// rows than `self`, then the extra rows are filled with `val`.
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn resize_vertically(self, new_nrows: usize, val: N) -> MatrixMN<N, Dynamic, C>
+    pub fn resize_vertically(self, new_nrows: usize, val: T) -> OMatrix<T, Dynamic, C>
     where
-        DefaultAllocator: Reallocator<N, R, C, Dynamic, C>,
+        DefaultAllocator: Reallocator<T, R, C, Dynamic, C>,
     {
         let ncols = self.data.shape().1;
         self.resize_generic(Dynamic::new(new_nrows), ncols, val)
@@ -731,9 +736,9 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
     /// columns than `self`, then the extra columns are filled with `val`.
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn resize_horizontally(self, new_ncols: usize, val: N) -> MatrixMN<N, R, Dynamic>
+    pub fn resize_horizontally(self, new_ncols: usize, val: T) -> OMatrix<T, R, Dynamic>
     where
-        DefaultAllocator: Reallocator<N, R, C, R, Dynamic>,
+        DefaultAllocator: Reallocator<T, R, C, R, Dynamic>,
     {
         let nrows = self.data.shape().0;
         self.resize_generic(nrows, Dynamic::new(new_ncols), val)
@@ -743,11 +748,11 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     ///
     /// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
     /// rows and/or columns than `self`, then the extra rows or columns are filled with `val`.
-    pub fn fixed_resize<R2: DimName, C2: DimName>(self, val: N) -> MatrixMN<N, R2, C2>
+    pub fn fixed_resize<const R2: usize, const C2: usize>(self, val: T) -> SMatrix<T, R2, C2>
     where
-        DefaultAllocator: Reallocator<N, R, C, R2, C2>,
+        DefaultAllocator: Reallocator<T, R, C, Const<R2>, Const<C2>>,
     {
-        self.resize_generic(R2::name(), C2::name(), val)
+        self.resize_generic(Const::<R2>, Const::<C2>, val)
     }
 
     /// Resizes `self` such that it has dimensions `new_nrows × new_ncols`.
@@ -759,10 +764,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         self,
         new_nrows: R2,
         new_ncols: C2,
-        val: N,
-    ) -> MatrixMN<N, R2, C2>
+        val: T,
+    ) -> OMatrix<T, R2, C2>
     where
-        DefaultAllocator: Reallocator<N, R, C, R2, C2>,
+        DefaultAllocator: Reallocator<T, R, C, R2, C2>,
     {
         let (nrows, ncols) = self.shape();
         let mut data = self.data.into_owned();
@@ -874,11 +879,11 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         self,
         new_nrows: R2,
         new_ncols: C2,
-    ) -> Matrix<N, R2, C2, S::Output>
+    ) -> Matrix<T, R2, C2, S::Output>
     where
         R2: Dim,
         C2: Dim,
-        S: ReshapableStorage<N, R, C, R2, C2>,
+        S: ReshapableStorage<T, R, C, R2, C2>,
     {
         let data = self.data.reshape_generic(new_nrows, new_ncols);
         Matrix::from_data(data)
@@ -887,16 +892,16 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
 /// # In-place resizing
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N: Scalar> DMatrix<N> {
+impl<T: Scalar> DMatrix<T> {
     /// Resizes this matrix in-place.
     ///
     /// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
     /// rows and/or columns than `self`, then the extra rows or columns are filled with `val`.
     ///
     /// Defined only for owned fully-dynamic matrices, i.e., `DMatrix`.
-    pub fn resize_mut(&mut self, new_nrows: usize, new_ncols: usize, val: N)
+    pub fn resize_mut(&mut self, new_nrows: usize, new_ncols: usize, val: T)
     where
-        DefaultAllocator: Reallocator<N, Dynamic, Dynamic, Dynamic, Dynamic>,
+        DefaultAllocator: Reallocator<T, Dynamic, Dynamic, Dynamic, Dynamic>,
     {
         let placeholder = unsafe {
             crate::unimplemented_or_uninitialized_generic!(Dynamic::new(0), Dynamic::new(0))
@@ -908,9 +913,9 @@ impl<N: Scalar> DMatrix<N> {
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N: Scalar, C: Dim> MatrixMN<N, Dynamic, C>
+impl<T: Scalar, C: Dim> OMatrix<T, Dynamic, C>
 where
-    DefaultAllocator: Allocator<N, Dynamic, C>,
+    DefaultAllocator: Allocator<T, Dynamic, C>,
 {
     /// Changes the number of rows of this matrix in-place.
     ///
@@ -919,9 +924,9 @@ where
     ///
     /// Defined only for owned matrices with a dynamic number of rows (for example, `DVector`).
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn resize_vertically_mut(&mut self, new_nrows: usize, val: N)
+    pub fn resize_vertically_mut(&mut self, new_nrows: usize, val: T)
     where
-        DefaultAllocator: Reallocator<N, Dynamic, C, Dynamic, C>,
+        DefaultAllocator: Reallocator<T, Dynamic, C, Dynamic, C>,
     {
         let placeholder = unsafe {
             crate::unimplemented_or_uninitialized_generic!(Dynamic::new(0), self.data.shape().1)
@@ -933,9 +938,9 @@ where
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N: Scalar, R: Dim> MatrixMN<N, R, Dynamic>
+impl<T: Scalar, R: Dim> OMatrix<T, R, Dynamic>
 where
-    DefaultAllocator: Allocator<N, R, Dynamic>,
+    DefaultAllocator: Allocator<T, R, Dynamic>,
 {
     /// Changes the number of column of this matrix in-place.
     ///
@@ -944,9 +949,9 @@ where
     ///
     /// Defined only for owned matrices with a dynamic number of columns (for example, `DVector`).
     #[cfg(any(feature = "std", feature = "alloc"))]
-    pub fn resize_horizontally_mut(&mut self, new_ncols: usize, val: N)
+    pub fn resize_horizontally_mut(&mut self, new_ncols: usize, val: T)
     where
-        DefaultAllocator: Reallocator<N, R, Dynamic, R, Dynamic>,
+        DefaultAllocator: Reallocator<T, R, Dynamic, R, Dynamic>,
     {
         let placeholder = unsafe {
             crate::unimplemented_or_uninitialized_generic!(self.data.shape().0, Dynamic::new(0))
@@ -957,8 +962,8 @@ where
     }
 }
 
-unsafe fn compress_rows<N: Scalar>(
-    data: &mut [N],
+unsafe fn compress_rows<T: Scalar>(
+    data: &mut [T],
     nrows: usize,
     ncols: usize,
     i: usize,
@@ -996,8 +1001,8 @@ unsafe fn compress_rows<N: Scalar>(
 
 // Moves entries of a matrix buffer to make place for `ninsert` emty 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<N: Scalar>(
-    data: &mut [N],
+unsafe fn extend_rows<T: Scalar>(
+    data: &mut [T],
     nrows: usize,
     ncols: usize,
     i: usize,
@@ -1032,18 +1037,18 @@ unsafe fn extend_rows<N: Scalar>(
 /// Extend the number of columns of the `Matrix` with elements from
 /// a given iterator.
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N, R, S> Extend<N> for Matrix<N, R, Dynamic, S>
+impl<T, R, S> Extend<T> for Matrix<T, R, Dynamic, S>
 where
-    N: Scalar,
+    T: Scalar,
     R: Dim,
-    S: Extend<N>,
+    S: Extend<T>,
 {
     /// Extend the number of columns of the `Matrix` with elements
     /// from the given iterator.
     ///
     /// # Example
     /// ```
-    /// # use nalgebra::{DMatrix, Dynamic, Matrix, MatrixMN, Matrix3};
+    /// # use nalgebra::{DMatrix, Dynamic, Matrix, OMatrix, Matrix3};
     ///
     /// let data = vec![0, 1, 2,      // column 1
     ///                 3, 4, 5];     // column 2
@@ -1063,7 +1068,7 @@ where
     /// `Matrix`.
     ///
     /// ```should_panic
-    /// # use nalgebra::{DMatrix, Dynamic, MatrixMN};
+    /// # use nalgebra::{DMatrix, Dynamic, OMatrix};
     /// let data = vec![0, 1, 2,  // column 1
     ///                 3, 4, 5]; // column 2
     ///
@@ -1072,7 +1077,7 @@ where
     /// // The following panics because the vec length is not a multiple of 3.
     /// matrix.extend(vec![6, 7, 8, 9]);
     /// ```
-    fn extend<I: IntoIterator<Item = N>>(&mut self, iter: I) {
+    fn extend<I: IntoIterator<Item = T>>(&mut self, iter: I) {
         self.data.extend(iter);
     }
 }
@@ -1080,10 +1085,10 @@ where
 /// Extend the number of rows of the `Vector` with elements from
 /// a given iterator.
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N, S> Extend<N> for Matrix<N, Dynamic, U1, S>
+impl<T, S> Extend<T> for Matrix<T, Dynamic, U1, S>
 where
-    N: Scalar,
-    S: Extend<N>,
+    T: Scalar,
+    S: Extend<T>,
 {
     /// Extend the number of rows of a `Vector` with elements
     /// from the given iterator.
@@ -1095,19 +1100,19 @@ where
     /// vector.extend(vec![3, 4, 5]);
     /// assert!(vector.eq(&DVector::from_vec(vec![0, 1, 2, 3, 4, 5])));
     /// ```
-    fn extend<I: IntoIterator<Item = N>>(&mut self, iter: I) {
+    fn extend<I: IntoIterator<Item = T>>(&mut self, iter: I) {
         self.data.extend(iter);
     }
 }
 
 #[cfg(any(feature = "std", feature = "alloc"))]
-impl<N, R, S, RV, SV> Extend<Vector<N, RV, SV>> for Matrix<N, R, Dynamic, S>
+impl<T, R, S, RV, SV> Extend<Vector<T, RV, SV>> for Matrix<T, R, Dynamic, S>
 where
-    N: Scalar,
+    T: Scalar,
     R: Dim,
-    S: Extend<Vector<N, RV, SV>>,
+    S: Extend<Vector<T, RV, SV>>,
     RV: Dim,
-    SV: Storage<N, RV>,
+    SV: Storage<T, RV>,
     ShapeConstraint: SameNumberOfRows<R, RV>,
 {
     /// Extends the number of columns of a `Matrix` with `Vector`s
@@ -1159,7 +1164,7 @@ where
     /// matrix.extend(
     ///   vec![Vector4::new(6, 7, 8, 9)]); // too few dimensions!
     /// ```
-    fn extend<I: IntoIterator<Item = Vector<N, RV, SV>>>(&mut self, iter: I) {
+    fn extend<I: IntoIterator<Item = Vector<T, RV, SV>>>(&mut self, iter: I) {
         self.data.extend(iter);
     }
 }

src/base/indexing.rs

@@ -7,7 +7,7 @@ use crate::base::{
 
 use std::ops;
 
-// N.B.: Not a public trait!
+// T.B.: Not a public trait!
 trait DimRange<D: Dim> {
     /// The number of elements indexed by this range.
     type Length: Dim;
@@ -315,19 +315,19 @@ fn dimrange_rangetoinclusive_usize() {
 }
 
 /// A helper trait used for indexing operations.
-pub trait MatrixIndex<'a, N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>>: Sized {
+pub trait MatrixIndex<'a, T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>>: Sized {
     /// The output type returned by methods.
     type Output: 'a;
 
     /// Produces true if the given matrix is contained by this index.
     #[doc(hidden)]
-    fn contained_by(&self, matrix: &Matrix<N, R, C, S>) -> bool;
+    fn contained_by(&self, matrix: &Matrix<T, R, C, S>) -> bool;
 
     /// Produces a shared view of the data at this location if in bounds,
     /// or `None`, otherwise.
     #[doc(hidden)]
     #[inline(always)]
-    fn get(self, matrix: &'a Matrix<N, R, C, S>) -> Option<Self::Output> {
+    fn get(self, matrix: &'a Matrix<T, R, C, S>) -> Option<Self::Output> {
         if self.contained_by(matrix) {
             Some(unsafe { self.get_unchecked(matrix) })
         } else {
@@ -338,20 +338,20 @@ pub trait MatrixIndex<'a, N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>>: Sized
     /// Produces a shared view of the data at this location if in bounds
     /// without any bounds checking.
     #[doc(hidden)]
-    unsafe fn get_unchecked(self, matrix: &'a Matrix<N, R, C, S>) -> Self::Output;
+    unsafe fn get_unchecked(self, matrix: &'a Matrix<T, R, C, S>) -> Self::Output;
 
     /// Produces a shared view to the data at this location, or panics
     /// if out of bounds.
     #[doc(hidden)]
     #[inline(always)]
-    fn index(self, matrix: &'a Matrix<N, R, C, S>) -> Self::Output {
+    fn index(self, matrix: &'a Matrix<T, R, C, S>) -> Self::Output {
         self.get(matrix).expect("Index out of bounds.")
     }
 }
 
 /// A helper trait used for indexing operations.
-pub trait MatrixIndexMut<'a, N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>>:
-    MatrixIndex<'a, N, R, C, S>
+pub trait MatrixIndexMut<'a, T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>>:
+    MatrixIndex<'a, T, R, C, S>
 {
     /// The output type returned by methods.
     type OutputMut: 'a;
@@ -359,13 +359,13 @@ pub trait MatrixIndexMut<'a, N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>>:
     /// Produces a mutable view of the data at this location, without
     /// performing any bounds checking.
     #[doc(hidden)]
-    unsafe fn get_unchecked_mut(self, matrix: &'a mut Matrix<N, R, C, S>) -> Self::OutputMut;
+    unsafe fn get_unchecked_mut(self, matrix: &'a mut Matrix<T, R, C, S>) -> Self::OutputMut;
 
     /// Produces a mutable view of the data at this location, if in
     /// bounds.
     #[doc(hidden)]
     #[inline(always)]
-    fn get_mut(self, matrix: &'a mut Matrix<N, R, C, S>) -> Option<Self::OutputMut> {
+    fn get_mut(self, matrix: &'a mut Matrix<T, R, C, S>) -> Option<Self::OutputMut> {
         if self.contained_by(matrix) {
             Some(unsafe { self.get_unchecked_mut(matrix) })
         } else {
@@ -377,7 +377,7 @@ pub trait MatrixIndexMut<'a, N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>>:
     /// if out of bounds.
     #[doc(hidden)]
     #[inline(always)]
-    fn index_mut(self, matrix: &'a mut Matrix<N, R, C, S>) -> Self::OutputMut {
+    fn index_mut(self, matrix: &'a mut Matrix<T, R, C, S>) -> Self::OutputMut {
         self.get_mut(matrix).expect("Index out of bounds.")
     }
 }
@@ -481,13 +481,13 @@ pub trait MatrixIndexMut<'a, N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>>:
 ///                         4, 7,
 ///                         5, 8)));
 /// ```
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<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]
     pub fn get<'a, I>(&'a self, index: I) -> Option<I::Output>
     where
-        I: MatrixIndex<'a, N, R, C, S>,
+        I: MatrixIndex<'a, T, R, C, S>,
     {
         index.get(self)
     }
@@ -497,8 +497,8 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     #[inline]
     pub fn get_mut<'a, I>(&'a mut self, index: I) -> Option<I::OutputMut>
     where
-        S: StorageMut<N, R, C>,
-        I: MatrixIndexMut<'a, N, R, C, S>,
+        S: StorageMut<T, R, C>,
+        I: MatrixIndexMut<'a, T, R, C, S>,
     {
         index.get_mut(self)
     }
@@ -508,7 +508,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     #[inline]
     pub fn index<'a, I>(&'a self, index: I) -> I::Output
     where
-        I: MatrixIndex<'a, N, R, C, S>,
+        I: MatrixIndex<'a, T, R, C, S>,
     {
         index.index(self)
     }
@@ -518,8 +518,8 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     #[inline]
     pub fn index_mut<'a, I>(&'a mut self, index: I) -> I::OutputMut
     where
-        S: StorageMut<N, R, C>,
-        I: MatrixIndexMut<'a, N, R, C, S>,
+        S: StorageMut<T, R, C>,
+        I: MatrixIndexMut<'a, T, R, C, S>,
     {
         index.index_mut(self)
     }
@@ -529,7 +529,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     #[inline]
     pub unsafe fn get_unchecked<'a, I>(&'a self, index: I) -> I::Output
     where
-        I: MatrixIndex<'a, N, R, C, S>,
+        I: MatrixIndex<'a, T, R, C, S>,
     {
         index.get_unchecked(self)
     }
@@ -539,8 +539,8 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     #[inline]
     pub unsafe fn get_unchecked_mut<'a, I>(&'a mut self, index: I) -> I::OutputMut
     where
-        S: StorageMut<N, R, C>,
-        I: MatrixIndexMut<'a, N, R, C, S>,
+        S: StorageMut<T, R, C>,
+        I: MatrixIndexMut<'a, T, R, C, S>,
     {
         index.get_unchecked_mut(self)
     }
@@ -548,42 +548,42 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
 // EXTRACT A SINGLE ELEMENT BY 1D LINEAR ADDRESS
 
-impl<'a, N, R, C, S> MatrixIndex<'a, N, R, C, S> for usize
+impl<'a, T, R, C, S> MatrixIndex<'a, T, R, C, S> for usize
 where
-    N: Scalar,
+    T: Scalar,
     R: Dim,
     C: Dim,
-    S: Storage<N, R, C>,
+    S: Storage<T, R, C>,
 {
-    type Output = &'a N;
+    type Output = &'a T;
 
     #[doc(hidden)]
     #[inline(always)]
-    fn contained_by(&self, matrix: &Matrix<N, R, C, S>) -> bool {
+    fn contained_by(&self, matrix: &Matrix<T, R, C, S>) -> bool {
         *self < matrix.len()
     }
 
     #[doc(hidden)]
     #[inline(always)]
-    unsafe fn get_unchecked(self, matrix: &'a Matrix<N, R, C, S>) -> Self::Output {
+    unsafe fn get_unchecked(self, matrix: &'a Matrix<T, R, C, S>) -> Self::Output {
         matrix.data.get_unchecked_linear(self)
     }
 }
 
-impl<'a, N, R, C, S> MatrixIndexMut<'a, N, R, C, S> for usize
+impl<'a, T, R, C, S> MatrixIndexMut<'a, T, R, C, S> for usize
 where
-    N: Scalar,
+    T: Scalar,
     R: Dim,
     C: Dim,
-    S: StorageMut<N, R, C>,
+    S: StorageMut<T, R, C>,
 {
-    type OutputMut = &'a mut N;
+    type OutputMut = &'a mut T;
 
     #[doc(hidden)]
     #[inline(always)]
-    unsafe fn get_unchecked_mut(self, matrix: &'a mut Matrix<N, R, C, S>) -> Self::OutputMut
+    unsafe fn get_unchecked_mut(self, matrix: &'a mut Matrix<T, R, C, S>) -> Self::OutputMut
     where
-        S: StorageMut<N, R, C>,
+        S: StorageMut<T, R, C>,
     {
         matrix.data.get_unchecked_linear_mut(self)
     }
@@ -591,18 +591,18 @@ where
 
 // EXTRACT A SINGLE ELEMENT BY 2D COORDINATES
 
-impl<'a, N, R, C, S> MatrixIndex<'a, N, R, C, S> for (usize, usize)
+impl<'a, T, R, C, S> MatrixIndex<'a, T, R, C, S> for (usize, usize)
 where
-    N: Scalar,
+    T: Scalar,
     R: Dim,
     C: Dim,
-    S: Storage<N, R, C>,
+    S: Storage<T, R, C>,
 {
-    type Output = &'a N;
+    type Output = &'a T;
 
     #[doc(hidden)]
     #[inline(always)]
-    fn contained_by(&self, matrix: &Matrix<N, R, C, S>) -> bool {
+    fn contained_by(&self, matrix: &Matrix<T, R, C, S>) -> bool {
         let (rows, cols) = self;
         let (nrows, ncols) = matrix.data.shape();
         DimRange::contained_by(rows, nrows) && DimRange::contained_by(cols, ncols)
@@ -610,26 +610,26 @@ where
 
     #[doc(hidden)]
     #[inline(always)]
-    unsafe fn get_unchecked(self, matrix: &'a Matrix<N, R, C, S>) -> Self::Output {
+    unsafe fn get_unchecked(self, matrix: &'a Matrix<T, R, C, S>) -> Self::Output {
         let (row, col) = self;
         matrix.data.get_unchecked(row, col)
     }
 }
 
-impl<'a, N, R, C, S> MatrixIndexMut<'a, N, R, C, S> for (usize, usize)
+impl<'a, T, R, C, S> MatrixIndexMut<'a, T, R, C, S> for (usize, usize)
 where
-    N: Scalar,
+    T: Scalar,
     R: Dim,
     C: Dim,
-    S: StorageMut<N, R, C>,
+    S: StorageMut<T, R, C>,
 {
-    type OutputMut = &'a mut N;
+    type OutputMut = &'a mut T;
 
     #[doc(hidden)]
     #[inline(always)]
-    unsafe fn get_unchecked_mut(self, matrix: &'a mut Matrix<N, R, C, S>) -> Self::OutputMut
+    unsafe fn get_unchecked_mut(self, matrix: &'a mut Matrix<T, R, C, S>) -> Self::OutputMut
     where
-        S: StorageMut<N, R, C>,
+        S: StorageMut<T, R, C>,
     {
         let (row, col) = self;
         matrix.data.get_unchecked_mut(row, col)
@@ -655,20 +655,20 @@ macro_rules! impl_index_pair {
         $(where $CConstraintType: ty: $CConstraintBound: ident $(<$($CConstraintBoundParams: ty $( = $CEqBound: ty )*),*>)* )*]
     ) =>
     {
-        impl<'a, N, $R, $C, S, $($RTyP : $RTyPB,)* $($CTyP : $CTyPB),*> MatrixIndex<'a, N, $R, $C, S> for ($RIdx, $CIdx)
+        impl<'a, T, $R, $C, S, $($RTyP : $RTyPB,)* $($CTyP : $CTyPB),*> MatrixIndex<'a, T, $R, $C, S> for ($RIdx, $CIdx)
         where
-            N: Scalar,
+            T: Scalar,
             $R: Dim,
             $C: Dim,
-            S: Storage<N, R, C>,
+            S: Storage<T, R, C>,
             $( $RConstraintType: $RConstraintBound $(<$( $RConstraintBoundParams $( = $REqBound )*),*>)* ,)*
             $( $CConstraintType: $CConstraintBound $(<$( $CConstraintBoundParams $( = $CEqBound )*),*>)* ),*
         {
-            type Output = MatrixSlice<'a, N, $ROut, $COut, S::RStride, S::CStride>;
+            type Output = MatrixSlice<'a, T, $ROut, $COut, S::RStride, S::CStride>;
 
             #[doc(hidden)]
             #[inline(always)]
-            fn contained_by(&self, matrix: &Matrix<N, $R, $C, S>) -> bool {
+            fn contained_by(&self, matrix: &Matrix<T, $R, $C, S>) -> bool {
                 let (rows, cols) = self;
                 let (nrows, ncols) = matrix.data.shape();
                 DimRange::contained_by(rows, nrows) && DimRange::contained_by(cols, ncols)
@@ -676,7 +676,7 @@ macro_rules! impl_index_pair {
 
             #[doc(hidden)]
             #[inline(always)]
-            unsafe fn get_unchecked(self, matrix: &'a Matrix<N, $R, $C, S>) -> Self::Output {
+            unsafe fn get_unchecked(self, matrix: &'a Matrix<T, $R, $C, S>) -> Self::Output {
                 use crate::base::SliceStorage;
 
                 let (rows, cols) = self;
@@ -691,20 +691,20 @@ macro_rules! impl_index_pair {
             }
         }
 
-        impl<'a, N, $R, $C, S, $($RTyP : $RTyPB,)* $($CTyP : $CTyPB),*> MatrixIndexMut<'a, N, $R, $C, S> for ($RIdx, $CIdx)
+        impl<'a, T, $R, $C, S, $($RTyP : $RTyPB,)* $($CTyP : $CTyPB),*> MatrixIndexMut<'a, T, $R, $C, S> for ($RIdx, $CIdx)
         where
-            N: Scalar,
+            T: Scalar,
             $R: Dim,
             $C: Dim,
-            S: StorageMut<N, R, C>,
+            S: StorageMut<T, R, C>,
             $( $RConstraintType: $RConstraintBound $(<$( $RConstraintBoundParams $( = $REqBound )*),*>)* ,)*
             $( $CConstraintType: $CConstraintBound $(<$( $CConstraintBoundParams $( = $CEqBound )*),*>)* ),*
         {
-            type OutputMut = MatrixSliceMut<'a, N, $ROut, $COut, S::RStride, S::CStride>;
+            type OutputMut = MatrixSliceMut<'a, T, $ROut, $COut, S::RStride, S::CStride>;
 
             #[doc(hidden)]
             #[inline(always)]
-            unsafe fn get_unchecked_mut(self, matrix: &'a mut Matrix<N, $R, $C, S>) -> Self::OutputMut {
+            unsafe fn get_unchecked_mut(self, matrix: &'a mut Matrix<T, $R, $C, S>) -> Self::OutputMut {
                 use crate::base::SliceStorageMut;
 
                 let (rows, cols) = self;

src/base/interpolation.rs

@@ -1,12 +1,12 @@
 use crate::storage::Storage;
 use crate::{
-    Allocator, DefaultAllocator, Dim, One, RealField, Scalar, Unit, Vector, VectorN, Zero,
+    Allocator, DefaultAllocator, Dim, OVector, One, RealField, Scalar, Unit, Vector, Zero,
 };
 use simba::scalar::{ClosedAdd, ClosedMul, ClosedSub};
 
 /// # Interpolation
-impl<N: Scalar + Zero + One + ClosedAdd + ClosedSub + ClosedMul, D: Dim, S: Storage<N, D>>
-    Vector<N, D, S>
+impl<T: Scalar + Zero + One + ClosedAdd + ClosedSub + ClosedMul, D: Dim, S: Storage<T, D>>
+    Vector<T, D, S>
 {
     /// Returns `self * (1.0 - t) + rhs * t`, i.e., the linear blend of the vectors x and y using the scalar value a.
     ///
@@ -20,12 +20,12 @@ impl<N: Scalar + Zero + One + ClosedAdd + ClosedSub + ClosedMul, D: Dim, S: Stor
     /// let y = Vector3::new(10.0, 20.0, 30.0);
     /// assert_eq!(x.lerp(&y, 0.1), Vector3::new(1.9, 3.8, 5.7));
     /// ```
-    pub fn lerp<S2: Storage<N, D>>(&self, rhs: &Vector<N, D, S2>, t: N) -> VectorN<N, D>
+    pub fn lerp<S2: Storage<T, D>>(&self, rhs: &Vector<T, D, S2>, t: T) -> OVector<T, D>
     where
-        DefaultAllocator: Allocator<N, D>,
+        DefaultAllocator: Allocator<T, D>,
     {
         let mut res = self.clone_owned();
-        res.axpy(t.inlined_clone(), rhs, N::one() - t);
+        res.axpy(t.inlined_clone(), rhs, T::one() - t);
         res
     }
 
@@ -45,10 +45,10 @@ impl<N: Scalar + Zero + One + ClosedAdd + ClosedSub + ClosedMul, D: Dim, S: Stor
     ///
     /// assert_eq!(v, v2.normalize());
     /// ```
-    pub fn slerp<S2: Storage<N, D>>(&self, rhs: &Vector<N, D, S2>, t: N) -> VectorN<N, D>
+    pub fn slerp<S2: Storage<T, D>>(&self, rhs: &Vector<T, D, S2>, t: T) -> OVector<T, D>
     where
-        N: RealField,
-        DefaultAllocator: Allocator<N, D>,
+        T: RealField,
+        DefaultAllocator: Allocator<T, D>,
     {
         let me = Unit::new_normalize(self.clone_owned());
         let rhs = Unit::new_normalize(rhs.clone_owned());
@@ -57,7 +57,7 @@ impl<N: Scalar + Zero + One + ClosedAdd + ClosedSub + ClosedMul, D: Dim, S: Stor
 }
 
 /// # Interpolation between two unit vectors
-impl<N: RealField, D: Dim, S: Storage<N, D>> Unit<Vector<N, D, S>> {
+impl<T: RealField, D: Dim, S: Storage<T, D>> Unit<Vector<T, D, S>> {
     /// Computes the spherical linear interpolation between two unit vectors.
     ///
     /// # Examples:
@@ -72,16 +72,16 @@ impl<N: RealField, D: Dim, S: Storage<N, D>> Unit<Vector<N, D, S>> {
     ///
     /// assert_eq!(v, v2);
     /// ```
-    pub fn slerp<S2: Storage<N, D>>(
+    pub fn slerp<S2: Storage<T, D>>(
         &self,
-        rhs: &Unit<Vector<N, D, S2>>,
-        t: N,
-    ) -> Unit<VectorN<N, D>>
+        rhs: &Unit<Vector<T, D, S2>>,
+        t: T,
+    ) -> Unit<OVector<T, D>>
     where
-        DefaultAllocator: Allocator<N, D>,
+        DefaultAllocator: Allocator<T, D>,
     {
         // TODO: the result is wrong when self and rhs are collinear with opposite direction.
-        self.try_slerp(rhs, t, N::default_epsilon())
+        self.try_slerp(rhs, t, T::default_epsilon())
             .unwrap_or_else(|| Unit::new_unchecked(self.clone_owned()))
     }
 
@@ -89,33 +89,33 @@ impl<N: RealField, D: Dim, S: Storage<N, D>> Unit<Vector<N, D, S>> {
     ///
     /// Returns `None` if the two vectors are almost collinear and with opposite direction
     /// (in this case, there is an infinity of possible results).
-    pub fn try_slerp<S2: Storage<N, D>>(
+    pub fn try_slerp<S2: Storage<T, D>>(
         &self,
-        rhs: &Unit<Vector<N, D, S2>>,
-        t: N,
-        epsilon: N,
-    ) -> Option<Unit<VectorN<N, D>>>
+        rhs: &Unit<Vector<T, D, S2>>,
+        t: T,
+        epsilon: T,
+    ) -> Option<Unit<OVector<T, D>>>
     where
-        DefaultAllocator: Allocator<N, D>,
+        DefaultAllocator: Allocator<T, D>,
     {
         let c_hang = self.dot(rhs);
 
         // self == other
-        if c_hang >= N::one() {
+        if c_hang >= T::one() {
             return Some(Unit::new_unchecked(self.clone_owned()));
         }
 
         let hang = c_hang.acos();
-        let s_hang = (N::one() - c_hang * c_hang).sqrt();
+        let s_hang = (T::one() - c_hang * c_hang).sqrt();
 
         // TODO: what if s_hang is 0.0 ? The result is not well-defined.
-        if relative_eq!(s_hang, N::zero(), epsilon = epsilon) {
+        if relative_eq!(s_hang, T::zero(), epsilon = epsilon) {
             None
         } else {
-            let ta = ((N::one() - t) * hang).sin() / s_hang;
+            let ta = ((T::one() - t) * hang).sin() / s_hang;
             let tb = (t * hang).sin() / s_hang;
             let mut res = self.scale(ta);
-            res.axpy(tb, &**rhs, N::one());
+            res.axpy(tb, &**rhs, T::one());
 
             Some(Unit::new_unchecked(res))
         }

src/base/iter.rs

@@ -11,7 +11,7 @@ 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, N: Scalar, R: Dim, C: Dim, S: 'a + $Storage<N, R, C>> {
+        pub struct $Name<'a, T: Scalar, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> {
             ptr: $Ptr,
             inner_ptr: $Ptr,
             inner_end: $Ptr,
@@ -22,9 +22,9 @@ 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, N: Scalar, R: Dim, C: Dim, S: 'a + $Storage<N, R, C>> $Name<'a, N, R, C, S> {
+        impl<'a, T: Scalar, 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, N, R, C, S> {
+            pub fn new(storage: $SRef) -> $Name<'a, T, R, C, S> {
                 let shape = storage.shape();
                 let strides = storage.strides();
                 let inner_offset = shape.0.value() * strides.0.value();
@@ -59,8 +59,8 @@ macro_rules! iterator {
             }
         }
 
-        impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + $Storage<N, R, C>> Iterator
-            for $Name<'a, N, R, C, S>
+        impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> Iterator
+            for $Name<'a, T, R, C, S>
         {
             type Item = $Ref;
 
@@ -112,8 +112,8 @@ macro_rules! iterator {
             }
         }
 
-        impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + $Storage<N, R, C>> DoubleEndedIterator
-            for $Name<'a, N, R, C, S>
+        impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> DoubleEndedIterator
+            for $Name<'a, T, R, C, S>
         {
             #[inline]
             fn next_back(&mut self) -> Option<$Ref> {
@@ -152,8 +152,8 @@ macro_rules! iterator {
             }
         }
 
-        impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + $Storage<N, R, C>> ExactSizeIterator
-            for $Name<'a, N, R, C, S>
+        impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> ExactSizeIterator
+            for $Name<'a, T, R, C, S>
         {
             #[inline]
             fn len(&self) -> usize {
@@ -161,15 +161,15 @@ macro_rules! iterator {
             }
         }
 
-        impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + $Storage<N, R, C>> FusedIterator
-            for $Name<'a, N, R, C, S>
+        impl<'a, T: Scalar, 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 N, &'a N, &'a S);
-iterator!(struct MatrixIterMut for StorageMut.ptr_mut -> *mut N, &'a mut N, &'a mut 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);
 
 /*
  *
@@ -178,19 +178,19 @@ iterator!(struct MatrixIterMut for StorageMut.ptr_mut -> *mut N, &'a mut N, &'a
  */
 #[derive(Clone)]
 /// An iterator through the rows of a matrix.
-pub struct RowIter<'a, N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> {
-    mat: &'a Matrix<N, R, C, S>,
+pub struct RowIter<'a, T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> {
+    mat: &'a Matrix<T, R, C, S>,
     curr: usize,
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + Storage<N, R, C>> RowIter<'a, N, R, C, S> {
-    pub(crate) fn new(mat: &'a Matrix<N, R, C, S>) -> Self {
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<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, N: Scalar, R: Dim, C: Dim, S: 'a + Storage<N, R, C>> Iterator for RowIter<'a, N, R, C, S> {
-    type Item = MatrixSlice<'a, N, U1, C, S::RStride, S::CStride>;
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> Iterator for RowIter<'a, T, R, C, S> {
+    type Item = MatrixSlice<'a, T, U1, C, S::RStride, S::CStride>;
 
     #[inline]
     fn next(&mut self) -> Option<Self::Item> {
@@ -217,8 +217,8 @@ impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + Storage<N, R, C>> Iterator for RowIt
     }
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + Storage<N, R, C>> ExactSizeIterator
-    for RowIter<'a, N, R, C, S>
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> ExactSizeIterator
+    for RowIter<'a, T, R, C, S>
 {
     #[inline]
     fn len(&self) -> usize {
@@ -227,14 +227,14 @@ impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + Storage<N, R, C>> ExactSizeIterator
 }
 
 /// An iterator through the mutable rows of a matrix.
-pub struct RowIterMut<'a, N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> {
-    mat: *mut Matrix<N, R, C, S>,
+pub struct RowIterMut<'a, T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> {
+    mat: *mut Matrix<T, R, C, S>,
     curr: usize,
-    phantom: PhantomData<&'a mut Matrix<N, R, C, S>>,
+    phantom: PhantomData<&'a mut Matrix<T, R, C, S>>,
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> RowIterMut<'a, N, R, C, S> {
-    pub(crate) fn new(mat: &'a mut Matrix<N, R, C, S>) -> Self {
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> RowIterMut<'a, T, R, C, S> {
+    pub(crate) fn new(mat: &'a mut Matrix<T, R, C, S>) -> Self {
         RowIterMut {
             mat,
             curr: 0,
@@ -247,10 +247,10 @@ impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> RowIterMut<'a,
     }
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> Iterator
-    for RowIterMut<'a, N, R, C, S>
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> Iterator
+    for RowIterMut<'a, T, R, C, S>
 {
-    type Item = MatrixSliceMut<'a, N, U1, C, S::RStride, S::CStride>;
+    type Item = MatrixSliceMut<'a, T, U1, C, S::RStride, S::CStride>;
 
     #[inline]
     fn next(&mut self) -> Option<Self::Item> {
@@ -274,8 +274,8 @@ impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> Iterator
     }
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> ExactSizeIterator
-    for RowIterMut<'a, N, R, C, S>
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> ExactSizeIterator
+    for RowIterMut<'a, T, R, C, S>
 {
     #[inline]
     fn len(&self) -> usize {
@@ -290,21 +290,21 @@ impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> ExactSizeIterat
  */
 #[derive(Clone)]
 /// An iterator through the columns of a matrix.
-pub struct ColumnIter<'a, N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> {
-    mat: &'a Matrix<N, R, C, S>,
+pub struct ColumnIter<'a, T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> {
+    mat: &'a Matrix<T, R, C, S>,
     curr: usize,
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + Storage<N, R, C>> ColumnIter<'a, N, R, C, S> {
-    pub(crate) fn new(mat: &'a Matrix<N, R, C, S>) -> Self {
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<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, N: Scalar, R: Dim, C: Dim, S: 'a + Storage<N, R, C>> Iterator
-    for ColumnIter<'a, N, R, C, S>
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> Iterator
+    for ColumnIter<'a, T, R, C, S>
 {
-    type Item = MatrixSlice<'a, N, R, U1, S::RStride, S::CStride>;
+    type Item = MatrixSlice<'a, T, R, U1, S::RStride, S::CStride>;
 
     #[inline]
     fn next(&mut self) -> Option<Self::Item> {
@@ -331,8 +331,8 @@ impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + Storage<N, R, C>> Iterator
     }
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + Storage<N, R, C>> ExactSizeIterator
-    for ColumnIter<'a, N, R, C, S>
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + Storage<T, R, C>> ExactSizeIterator
+    for ColumnIter<'a, T, R, C, S>
 {
     #[inline]
     fn len(&self) -> usize {
@@ -341,14 +341,14 @@ impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + Storage<N, R, C>> ExactSizeIterator
 }
 
 /// An iterator through the mutable columns of a matrix.
-pub struct ColumnIterMut<'a, N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> {
-    mat: *mut Matrix<N, R, C, S>,
+pub struct ColumnIterMut<'a, T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> {
+    mat: *mut Matrix<T, R, C, S>,
     curr: usize,
-    phantom: PhantomData<&'a mut Matrix<N, R, C, S>>,
+    phantom: PhantomData<&'a mut Matrix<T, R, C, S>>,
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> ColumnIterMut<'a, N, R, C, S> {
-    pub(crate) fn new(mat: &'a mut Matrix<N, R, C, S>) -> Self {
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> ColumnIterMut<'a, T, R, C, S> {
+    pub(crate) fn new(mat: &'a mut Matrix<T, R, C, S>) -> Self {
         ColumnIterMut {
             mat,
             curr: 0,
@@ -361,10 +361,10 @@ impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> ColumnIterMut<'
     }
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> Iterator
-    for ColumnIterMut<'a, N, R, C, S>
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> Iterator
+    for ColumnIterMut<'a, T, R, C, S>
 {
-    type Item = MatrixSliceMut<'a, N, R, U1, S::RStride, S::CStride>;
+    type Item = MatrixSliceMut<'a, T, R, U1, S::RStride, S::CStride>;
 
     #[inline]
     fn next(&mut self) -> Option<Self::Item> {
@@ -388,8 +388,8 @@ impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> Iterator
     }
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> ExactSizeIterator
-    for ColumnIterMut<'a, N, R, C, S>
+impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<T, R, C>> ExactSizeIterator
+    for ColumnIterMut<'a, T, R, C, S>
 {
     #[inline]
     fn len(&self) -> usize {

src/base/matrix_simba.rs

@@ -2,32 +2,32 @@ use simba::simd::SimdValue;
 
 use crate::base::allocator::Allocator;
 use crate::base::dimension::Dim;
-use crate::base::{DefaultAllocator, MatrixMN, Scalar};
+use crate::base::{DefaultAllocator, OMatrix, Scalar};
 
 /*
  *
  * Simd structures.
  *
  */
-impl<N, R, C> SimdValue for MatrixMN<N, R, C>
+impl<T, R, C> SimdValue for OMatrix<T, R, C>
 where
-    N: Scalar + SimdValue,
+    T: Scalar + SimdValue,
     R: Dim,
     C: Dim,
-    N::Element: Scalar,
-    DefaultAllocator: Allocator<N, R, C> + Allocator<N::Element, R, C>,
+    T::Element: Scalar,
+    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
 {
-    type Element = MatrixMN<N::Element, R, C>;
-    type SimdBool = N::SimdBool;
+    type Element = OMatrix<T::Element, R, C>;
+    type SimdBool = T::SimdBool;
 
     #[inline]
     fn lanes() -> usize {
-        N::lanes()
+        T::lanes()
     }
 
     #[inline]
     fn splat(val: Self::Element) -> Self {
-        val.map(N::splat)
+        val.map(T::splat)
     }
 
     #[inline]

src/base/matrix_slice.rs

@@ -13,22 +13,22 @@ 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, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> {
+        pub struct $T<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> {
             ptr:       $Ptr,
             shape:     (R, C),
             strides:   (RStride, CStride),
             _phantoms: PhantomData<$Ref>,
         }
 
-        unsafe impl<'a, N: Scalar + Send, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Send
-            for $T<'a, N, R, C, RStride, CStride>
+        unsafe impl<'a, T: Scalar + Send, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Send
+            for $T<'a, T, R, C, RStride, CStride>
         {}
 
-        unsafe impl<'a, N: Scalar + Sync, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Sync
-            for $T<'a, N, R, C, RStride, CStride>
+        unsafe impl<'a, T: Scalar + Sync, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Sync
+            for $T<'a, T, R, C, RStride, CStride>
         {}
 
-        impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> $T<'a, N, R, C, RStride, CStride> {
+        impl<'a, T: Scalar, 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,
@@ -48,14 +48,14 @@ macro_rules! slice_storage_impl(
         }
 
         // Dynamic is arbitrary. It's just to be able to call the constructors with `Slice::`
-        impl<'a, N: Scalar, R: Dim, C: Dim> $T<'a, N, R, C, Dynamic, Dynamic> {
+        impl<'a, T: Scalar, 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))
-                -> $T<'a, N, R, C, S::RStride, S::CStride>
+                -> $T<'a, T, R, C, S::RStride, S::CStride>
                 where RStor: Dim,
                       CStor: Dim,
-                      S:     $Storage<N, RStor, CStor> {
+                      S:     $Storage<T, RStor, CStor> {
 
                 let strides = storage.strides();
                 $T::new_with_strides_unchecked(storage, start, shape, strides)
@@ -67,10 +67,10 @@ macro_rules! slice_storage_impl(
                                                                                         start:   (usize, usize),
                                                                                         shape:   (R, C),
                                                                                         strides: (RStride, CStride))
-                -> $T<'a, N, R, C, RStride, CStride>
+                -> $T<'a, T, R, C, RStride, CStride>
                 where RStor: Dim,
                       CStor: Dim,
-                      S: $Storage<N, RStor, CStor>,
+                      S: $Storage<T, RStor, CStor>,
                       RStride: Dim,
                       CStride: Dim {
 
@@ -82,20 +82,20 @@ 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 N as &'a N));
+    Storage 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 N as &'a mut N)
+    StorageMut as &'a mut S; SliceStorageMut.get_address_unchecked_mut(*mut T as &'a mut T)
 );
 
-impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Copy
-    for SliceStorage<'a, N, R, C, RStride, CStride>
+impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Copy
+    for SliceStorage<'a, T, R, C, RStride, CStride>
 {
 }
 
-impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Clone
-    for SliceStorage<'a, N, R, C, RStride, CStride>
+impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Clone
+    for SliceStorage<'a, T, R, C, RStride, CStride>
 {
     #[inline]
     fn clone(&self) -> Self {
@@ -110,14 +110,14 @@ impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Clone
 
 macro_rules! storage_impl(
     ($($T: ident),* $(,)*) => {$(
-        unsafe impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Storage<N, R, C>
-            for $T<'a, N, R, C, RStride, CStride> {
+        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> {
 
             type RStride = RStride;
             type CStride = CStride;
 
             #[inline]
-            fn ptr(&self) -> *const N {
+            fn ptr(&self) -> *const T {
                 self.ptr
             }
 
@@ -148,21 +148,21 @@ macro_rules! storage_impl(
             }
 
             #[inline]
-            fn into_owned(self) -> Owned<N, R, C>
-                where DefaultAllocator: Allocator<N, R, C> {
+            fn into_owned(self) -> Owned<T, R, C>
+                where DefaultAllocator: Allocator<T, R, C> {
                 self.clone_owned()
             }
 
             #[inline]
-            fn clone_owned(&self) -> Owned<N, R, C>
-                where DefaultAllocator: Allocator<N, R, C> {
+            fn clone_owned(&self) -> Owned<T, R, C>
+                where DefaultAllocator: Allocator<T, R, C> {
                 let (nrows, ncols) = self.shape();
                 let it = MatrixIter::new(self).cloned();
                 DefaultAllocator::allocate_from_iterator(nrows, ncols, it)
             }
 
             #[inline]
-            fn as_slice(&self) -> &[N] {
+            fn as_slice(&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);
@@ -178,16 +178,16 @@ macro_rules! storage_impl(
 
 storage_impl!(SliceStorage, SliceStorageMut);
 
-unsafe impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> StorageMut<N, R, C>
-    for SliceStorageMut<'a, N, R, C, RStride, CStride>
+unsafe impl<'a, T: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> StorageMut<T, R, C>
+    for SliceStorageMut<'a, T, R, C, RStride, CStride>
 {
     #[inline]
-    fn ptr_mut(&mut self) -> *mut N {
+    fn ptr_mut(&mut self) -> *mut T {
         self.ptr
     }
 
     #[inline]
-    fn as_mut_slice(&mut self) -> &mut [N] {
+    fn as_mut_slice(&mut self) -> &mut [T] {
         let (nrows, ncols) = self.shape();
         if nrows.value() != 0 && ncols.value() != 0 {
             let sz = self.linear_index(nrows.value() - 1, ncols.value() - 1);
@@ -198,33 +198,33 @@ unsafe impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> StorageMu
     }
 }
 
-unsafe impl<'a, N: Scalar, R: Dim, CStride: Dim> ContiguousStorage<N, R, U1>
-    for SliceStorage<'a, N, R, U1, U1, CStride>
+unsafe impl<'a, T: Scalar, R: Dim, CStride: Dim> ContiguousStorage<T, R, U1>
+    for SliceStorage<'a, T, R, U1, U1, CStride>
 {
 }
-unsafe impl<'a, N: Scalar, R: Dim, CStride: Dim> ContiguousStorage<N, R, U1>
-    for SliceStorageMut<'a, N, 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, N: Scalar, R: Dim, CStride: Dim> ContiguousStorageMut<N, R, U1>
-    for SliceStorageMut<'a, N, R, U1, U1, CStride>
+unsafe impl<'a, T: Scalar, R: Dim, CStride: Dim> ContiguousStorageMut<T, R, U1>
+    for SliceStorageMut<'a, T, R, U1, U1, CStride>
 {
 }
 
-unsafe impl<'a, N: Scalar, R: DimName, C: Dim + IsNotStaticOne> ContiguousStorage<N, R, C>
-    for SliceStorage<'a, N, R, C, U1, R>
+unsafe impl<'a, T: Scalar, R: DimName, C: Dim + IsNotStaticOne> ContiguousStorage<T, R, C>
+    for SliceStorage<'a, T, R, C, U1, R>
 {
 }
-unsafe impl<'a, N: Scalar, R: DimName, C: Dim + IsNotStaticOne> ContiguousStorage<N, R, C>
-    for SliceStorageMut<'a, N, 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, N: Scalar, R: DimName, C: Dim + IsNotStaticOne> ContiguousStorageMut<N, R, C>
-    for SliceStorageMut<'a, N, R, C, U1, R>
+unsafe impl<'a, T: Scalar, R: DimName, C: Dim + IsNotStaticOne> ContiguousStorageMut<T, R, C>
+    for SliceStorageMut<'a, T, R, C, U1, R>
 {
 }
 
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     #[inline]
     fn assert_slice_index(
         &self,
@@ -281,20 +281,20 @@ 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<N, U1, C, S::RStride, S::CStride> {
-            $me.$fixed_rows::<U1>(i)
+        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<N, 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<N, Dynamic, C, S::RStride, S::CStride> {
+            -> $MatrixSlice<T, Dynamic, C, S::RStride, S::CStride> {
 
             $me.$rows_generic(first_row, Dynamic::new(nrows))
         }
@@ -302,33 +302,33 @@ 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<N, Dynamic, C, Dynamic, S::CStride> {
+            -> $MatrixSlice<T, Dynamic, C, Dynamic, S::CStride> {
 
             $me.$rows_generic_with_step(first_row, Dynamic::new(nrows), step)
         }
 
         /// Extracts a compile-time number of consecutive rows from this matrix.
         #[inline]
-        pub fn $fixed_rows<RSlice: DimName>($me: $Me, first_row: usize)
-            -> $MatrixSlice<N, RSlice, C, S::RStride, S::CStride> {
+        pub fn $fixed_rows<const RSLICE: usize>($me: $Me, first_row: usize)
+            -> $MatrixSlice<T, Const<RSLICE>, C, S::RStride, S::CStride> {
 
-            $me.$rows_generic(first_row, RSlice::name())
+            $me.$rows_generic(first_row, Const::<RSLICE>)
         }
 
         /// Extracts from this matrix a compile-time number of rows regularly skipping `step`
         /// rows.
         #[inline]
-        pub fn $fixed_rows_with_step<RSlice: DimName>($me: $Me, first_row: usize, step: usize)
-            -> $MatrixSlice<N, RSlice, C, Dynamic, S::CStride> {
+        pub fn $fixed_rows_with_step<const RSLICE: usize>($me: $Me, first_row: usize, step: usize)
+            -> $MatrixSlice<T, Const<RSLICE>, C, Dynamic, S::CStride> {
 
-            $me.$rows_generic_with_step(first_row, RSlice::name(), step)
+            $me.$rows_generic_with_step(first_row, Const::<RSLICE>, step)
         }
 
         /// Extracts from this matrix `nrows` rows regularly skipping `step` rows. Both
         /// 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<N, RSlice, C, S::RStride, S::CStride> {
+            -> $MatrixSlice<T, RSlice, C, S::RStride, S::CStride> {
 
             let my_shape   = $me.data.shape();
             $me.assert_slice_index((row_start, 0), (nrows.value(), my_shape.1.value()), (0, 0));
@@ -345,7 +345,7 @@ 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<N, RSlice, C, Dynamic, S::CStride>
+            -> $MatrixSlice<T, RSlice, C, Dynamic, S::CStride>
             where RSlice: Dim {
 
             let my_shape   = $me.data.shape();
@@ -368,20 +368,20 @@ 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<N, R, U1, S::RStride, S::CStride> {
-            $me.$fixed_columns::<U1>(i)
+        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<N, 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<N, R, Dynamic, S::RStride, S::CStride> {
+            -> $MatrixSlice<T, R, Dynamic, S::RStride, S::CStride> {
 
             $me.$columns_generic(first_col, Dynamic::new(ncols))
         }
@@ -390,33 +390,33 @@ macro_rules! matrix_slice_impl(
         /// columns.
         #[inline]
         pub fn $columns_with_step($me: $Me, first_col: usize, ncols: usize, step: usize)
-            -> $MatrixSlice<N, R, Dynamic, S::RStride, Dynamic> {
+            -> $MatrixSlice<T, R, Dynamic, S::RStride, Dynamic> {
 
             $me.$columns_generic_with_step(first_col, Dynamic::new(ncols), step)
         }
 
         /// Extracts a compile-time number of consecutive columns from this matrix.
         #[inline]
-        pub fn $fixed_columns<CSlice: DimName>($me: $Me, first_col: usize)
-            -> $MatrixSlice<N, R, CSlice, S::RStride, S::CStride> {
+        pub fn $fixed_columns<const CSLICE: usize>($me: $Me, first_col: usize)
+            -> $MatrixSlice<T, R, Const<CSLICE>, S::RStride, S::CStride> {
 
-            $me.$columns_generic(first_col, CSlice::name())
+            $me.$columns_generic(first_col, Const::<CSLICE>)
         }
 
         /// Extracts from this matrix a compile-time number of columns regularly skipping
         /// `step` columns.
         #[inline]
-        pub fn $fixed_columns_with_step<CSlice: DimName>($me: $Me, first_col: usize, step: usize)
-            -> $MatrixSlice<N, R, CSlice, S::RStride, Dynamic> {
+        pub fn $fixed_columns_with_step<const CSLICE: usize>($me: $Me, first_col: usize, step: usize)
+            -> $MatrixSlice<T, R, Const<CSLICE>, S::RStride, Dynamic> {
 
-            $me.$columns_generic_with_step(first_col, CSlice::name(), step)
+            $me.$columns_generic_with_step(first_col, Const::<CSLICE>, step)
         }
 
         /// Extracts from this matrix `ncols` columns. The number of columns may or may not be
         /// known at compile-time.
         #[inline]
         pub fn $columns_generic<CSlice: Dim>($me: $Me, first_col: usize, ncols: CSlice)
-            -> $MatrixSlice<N, R, CSlice, S::RStride, S::CStride> {
+            -> $MatrixSlice<T, R, CSlice, S::RStride, S::CStride> {
 
             let my_shape = $me.data.shape();
             $me.assert_slice_index((0, first_col), (my_shape.0.value(), ncols.value()), (0, 0));
@@ -433,7 +433,7 @@ 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<N, R, CSlice, S::RStride, Dynamic> {
+            -> $MatrixSlice<T, R, CSlice, S::RStride, Dynamic> {
 
             let my_shape   = $me.data.shape();
             let my_strides = $me.data.strides();
@@ -458,7 +458,7 @@ macro_rules! matrix_slice_impl(
         /// consecutive elements.
         #[inline]
         pub fn $slice($me: $Me, start: (usize, usize), shape: (usize, usize))
-            -> $MatrixSlice<N, 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));
@@ -476,7 +476,7 @@ 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<N, 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)
@@ -485,13 +485,11 @@ macro_rules! matrix_slice_impl(
         /// Slices this matrix starting at its component `(irow, icol)` and with `(R::dim(),
         /// CSlice::dim())` consecutive components.
         #[inline]
-        pub fn $fixed_slice<RSlice, CSlice>($me: $Me, irow: usize, icol: usize)
-            -> $MatrixSlice<N, RSlice, CSlice, S::RStride, S::CStride>
-            where RSlice: DimName,
-                  CSlice: DimName {
+        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> {
 
-            $me.assert_slice_index((irow, icol), (RSlice::dim(), CSlice::dim()), (0, 0));
-            let shape = (RSlice::name(), CSlice::name());
+            $me.assert_slice_index((irow, icol), (RSLICE, CSLICE), (0, 0));
+            let shape = (Const::<RSLICE>, Const::<CSLICE>);
 
             unsafe {
                 let data = $SliceStorage::new_unchecked($data, (irow, icol), shape);
@@ -500,22 +498,20 @@ macro_rules! matrix_slice_impl(
         }
 
         /// Slices this matrix starting at its component `(start.0, start.1)` and with
-        /// `(R::dim(), CSlice::dim())` components. Each row (resp. column) of the sliced
+        /// `(RSLICE, CSLICE)` components. Each row (resp. column) of the sliced
         /// matrix is separated by `steps.0` (resp. `steps.1`) ignored rows (resp. columns) of
         /// the original matrix.
         #[inline]
-        pub fn $fixed_slice_with_steps<RSlice, CSlice>($me: $Me, start: (usize, usize), steps: (usize, usize))
-            -> $MatrixSlice<N, RSlice, CSlice, Dynamic, Dynamic>
-            where RSlice: DimName,
-                  CSlice: DimName {
-            let shape = (RSlice::name(), CSlice::name());
+        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> {
+            let shape = (Const::<RSLICE>, Const::<CSLICE>);
             $me.$generic_slice_with_steps(start, shape, steps)
         }
 
         /// 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<N, RSlice, CSlice, S::RStride, S::CStride>
+            -> $MatrixSlice<T, RSlice, CSlice, S::RStride, S::CStride>
             where RSlice: Dim,
                   CSlice: Dim {
 
@@ -533,7 +529,7 @@ macro_rules! matrix_slice_impl(
                                                          start: (usize, usize),
                                                          shape: (RSlice, CSlice),
                                                          steps: (usize, usize))
-            -> $MatrixSlice<N, RSlice, CSlice, Dynamic, Dynamic>
+            -> $MatrixSlice<T, RSlice, CSlice, Dynamic, Dynamic>
             where RSlice: Dim,
                   CSlice: Dim {
 
@@ -559,8 +555,8 @@ macro_rules! matrix_slice_impl(
         /// 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<N, Range1::Size, C, S::RStride, S::CStride>,
-                $MatrixSlice<N, Range2::Size, C, S::RStride, S::CStride>) {
+            -> ($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 strides        = $me.data.strides();
@@ -595,8 +591,8 @@ macro_rules! matrix_slice_impl(
         /// 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<N, R, Range1::Size, S::RStride, S::CStride>,
-                $MatrixSlice<N, R, Range2::Size, S::RStride, S::CStride>) {
+            -> ($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 strides        = $me.data.strides();
@@ -629,14 +625,14 @@ macro_rules! matrix_slice_impl(
 );
 
 /// A matrix slice.
-pub type MatrixSlice<'a, N, R, C, RStride, CStride> =
-    Matrix<N, R, C, SliceStorage<'a, N, R, C, RStride, CStride>>;
+pub type MatrixSlice<'a, T, R, C, RStride = U1, CStride = R> =
+    Matrix<T, R, C, SliceStorage<'a, T, R, C, RStride, CStride>>;
 /// A mutable matrix slice.
-pub type MatrixSliceMut<'a, N, R, C, RStride, CStride> =
-    Matrix<N, R, C, SliceStorageMut<'a, N, R, C, RStride, CStride>>;
+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<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     matrix_slice_impl!(
      self: &Self, MatrixSlice, SliceStorage, Storage.get_address_unchecked(), &self.data;
      row,
@@ -666,7 +662,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 }
 
 /// # Mutable slicing based on index and length
-impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
     matrix_slice_impl!(
      self: &mut Self, MatrixSliceMut, SliceStorageMut, StorageMut.get_address_unchecked_mut(), &mut self.data;
      row_mut,
@@ -812,7 +808,7 @@ impl<D: Dim> SliceRange<D> for RangeFull {
 
 // TODO: see how much of this overlaps with the general indexing
 // methods from indexing.rs.
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<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]
@@ -820,7 +816,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         &self,
         rows: RowRange,
         cols: ColRange,
-    ) -> MatrixSlice<N, 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>,
@@ -837,7 +833,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     pub fn rows_range<RowRange: SliceRange<R>>(
         &self,
         rows: RowRange,
-    ) -> MatrixSlice<N, RowRange::Size, C, S::RStride, S::CStride> {
+    ) -> MatrixSlice<T, RowRange::Size, C, S::RStride, S::CStride> {
         self.slice_range(rows, ..)
     }
 
@@ -846,21 +842,21 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     pub fn columns_range<ColRange: SliceRange<C>>(
         &self,
         cols: ColRange,
-    ) -> MatrixSlice<N, 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<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<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<N, 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>,
@@ -877,7 +873,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     pub fn rows_range_mut<RowRange: SliceRange<R>>(
         &mut self,
         rows: RowRange,
-    ) -> MatrixSliceMut<N, RowRange::Size, C, S::RStride, S::CStride> {
+    ) -> MatrixSliceMut<T, RowRange::Size, C, S::RStride, S::CStride> {
         self.slice_range_mut(rows, ..)
     }
 
@@ -886,21 +882,21 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     pub fn columns_range_mut<ColRange: SliceRange<C>>(
         &mut self,
         cols: ColRange,
-    ) -> MatrixSliceMut<N, R, ColRange::Size, S::RStride, S::CStride> {
+    ) -> MatrixSliceMut<T, R, ColRange::Size, S::RStride, S::CStride> {
         self.slice_range_mut(.., cols)
     }
 }
 
-impl<'a, N, R, C, RStride, CStride> From<MatrixSliceMut<'a, N, R, C, RStride, CStride>>
-    for MatrixSlice<'a, N, R, C, RStride, CStride>
+impl<'a, T, R, C, RStride, CStride> From<MatrixSliceMut<'a, T, R, C, RStride, CStride>>
+    for MatrixSlice<'a, T, R, C, RStride, CStride>
 where
-    N: Scalar,
+    T: Scalar,
     R: Dim,
     C: Dim,
     RStride: Dim,
     CStride: Dim,
 {
-    fn from(slice_mut: MatrixSliceMut<'a, N, R, C, RStride, CStride>) -> Self {
+    fn from(slice_mut: MatrixSliceMut<'a, T, R, C, RStride, CStride>) -> Self {
         let data = SliceStorage {
             ptr: slice_mut.data.ptr,
             shape: slice_mut.data.shape,

src/base/min_max.rs

@@ -4,7 +4,7 @@ use num::{Signed, Zero};
 use simba::simd::SimdSigned;
 
 /// # Find the min and max components
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     /// Returns the absolute value of the component with the largest absolute value.
     /// # Example
     /// ```
@@ -13,12 +13,12 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(Vector3::new(-1.0, -2.0, -3.0).amax(), 3.0);
     /// ```
     #[inline]
-    pub fn amax(&self) -> N
+    pub fn amax(&self) -> T
     where
-        N: Zero + SimdSigned + SimdPartialOrd,
+        T: Zero + SimdSigned + SimdPartialOrd,
     {
         self.fold_with(
-            |e| e.unwrap_or(&N::zero()).simd_abs(),
+            |e| e.unwrap_or(&T::zero()).simd_abs(),
             |a, b| a.simd_max(b.simd_abs()),
         )
     }
@@ -33,12 +33,12 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     ///     Complex::new(1.0, 3.0)).camax(), 5.0);
     /// ```
     #[inline]
-    pub fn camax(&self) -> N::SimdRealField
+    pub fn camax(&self) -> T::SimdRealField
     where
-        N: SimdComplexField,
+        T: SimdComplexField,
     {
         self.fold_with(
-            |e| e.unwrap_or(&N::zero()).simd_norm1(),
+            |e| e.unwrap_or(&T::zero()).simd_norm1(),
             |a, b| a.simd_max(b.simd_norm1()),
         )
     }
@@ -52,12 +52,12 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(Vector3::new(5u32, 2, 3).max(), 5);
     /// ```
     #[inline]
-    pub fn max(&self) -> N
+    pub fn max(&self) -> T
     where
-        N: SimdPartialOrd + Zero,
+        T: SimdPartialOrd + Zero,
     {
         self.fold_with(
-            |e| e.map(|e| e.inlined_clone()).unwrap_or_else(N::zero),
+            |e| e.map(|e| e.inlined_clone()).unwrap_or_else(T::zero),
             |a, b| a.simd_max(b.inlined_clone()),
         )
     }
@@ -70,12 +70,12 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(Vector3::new(10.0, 2.0, 30.0).amin(), 2.0);
     /// ```
     #[inline]
-    pub fn amin(&self) -> N
+    pub fn amin(&self) -> T
     where
-        N: Zero + SimdPartialOrd + SimdSigned,
+        T: Zero + SimdPartialOrd + SimdSigned,
     {
         self.fold_with(
-            |e| e.map(|e| e.simd_abs()).unwrap_or_else(N::zero),
+            |e| e.map(|e| e.simd_abs()).unwrap_or_else(T::zero),
             |a, b| a.simd_min(b.simd_abs()),
         )
     }
@@ -90,14 +90,14 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     ///     Complex::new(1.0, 3.0)).camin(), 3.0);
     /// ```
     #[inline]
-    pub fn camin(&self) -> N::SimdRealField
+    pub fn camin(&self) -> T::SimdRealField
     where
-        N: SimdComplexField,
+        T: SimdComplexField,
     {
         self.fold_with(
             |e| {
                 e.map(|e| e.simd_norm1())
-                    .unwrap_or_else(N::SimdRealField::zero)
+                    .unwrap_or_else(T::SimdRealField::zero)
             },
             |a, b| a.simd_min(b.simd_norm1()),
         )
@@ -112,12 +112,12 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(Vector3::new(5u32, 2, 3).min(), 2);
     /// ```
     #[inline]
-    pub fn min(&self) -> N
+    pub fn min(&self) -> T
     where
-        N: SimdPartialOrd + Zero,
+        T: SimdPartialOrd + Zero,
     {
         self.fold_with(
-            |e| e.map(|e| e.inlined_clone()).unwrap_or_else(N::zero),
+            |e| e.map(|e| e.inlined_clone()).unwrap_or_else(T::zero),
             |a, b| a.simd_min(b.inlined_clone()),
         )
     }
@@ -138,7 +138,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     #[inline]
     pub fn icamax_full(&self) -> (usize, usize)
     where
-        N: ComplexField,
+        T: ComplexField,
     {
         assert!(!self.is_empty(), "The input matrix must not be empty.");
 
@@ -160,7 +160,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     }
 }
 
-impl<N: Scalar + PartialOrd + Signed, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar + PartialOrd + Signed, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     /// Computes the index of the matrix component with the largest absolute value.
     ///
     /// # Examples:
@@ -195,7 +195,7 @@ impl<N: Scalar + PartialOrd + Signed, R: Dim, C: Dim, S: Storage<N, 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<N: Scalar, D: Dim, S: Storage<N, D>> Vector<N, D, S> {
+impl<T: Scalar, D: Dim, S: Storage<T, D>> Vector<T, D, S> {
     /// Computes the index of the vector component with the largest complex or real absolute value.
     ///
     /// # Examples:
@@ -211,7 +211,7 @@ impl<N: Scalar, D: Dim, S: Storage<N, D>> Vector<N, D, S> {
     #[inline]
     pub fn icamax(&self) -> usize
     where
-        N: ComplexField,
+        T: ComplexField,
     {
         assert!(!self.is_empty(), "The input vector must not be empty.");
 
@@ -240,9 +240,9 @@ impl<N: Scalar, D: Dim, S: Storage<N, D>> Vector<N, D, S> {
     /// assert_eq!(vec.argmax(), (2, 13));
     /// ```
     #[inline]
-    pub fn argmax(&self) -> (usize, N)
+    pub fn argmax(&self) -> (usize, T)
     where
-        N: PartialOrd,
+        T: PartialOrd,
     {
         assert!(!self.is_empty(), "The input vector must not be empty.");
 
@@ -273,7 +273,7 @@ impl<N: Scalar, D: Dim, S: Storage<N, D>> Vector<N, D, S> {
     #[inline]
     pub fn imax(&self) -> usize
     where
-        N: PartialOrd,
+        T: PartialOrd,
     {
         self.argmax().0
     }
@@ -290,7 +290,7 @@ impl<N: Scalar, D: Dim, S: Storage<N, D>> Vector<N, D, S> {
     #[inline]
     pub fn iamax(&self) -> usize
     where
-        N: PartialOrd + Signed,
+        T: PartialOrd + Signed,
     {
         assert!(!self.is_empty(), "The input vector must not be empty.");
 
@@ -319,9 +319,9 @@ impl<N: Scalar, D: Dim, S: Storage<N, D>> Vector<N, D, S> {
     /// assert_eq!(vec.argmin(), (1, -15));
     /// ```
     #[inline]
-    pub fn argmin(&self) -> (usize, N)
+    pub fn argmin(&self) -> (usize, T)
     where
-        N: PartialOrd,
+        T: PartialOrd,
     {
         assert!(!self.is_empty(), "The input vector must not be empty.");
 
@@ -352,7 +352,7 @@ impl<N: Scalar, D: Dim, S: Storage<N, D>> Vector<N, D, S> {
     #[inline]
     pub fn imin(&self) -> usize
     where
-        N: PartialOrd,
+        T: PartialOrd,
     {
         self.argmin().0
     }
@@ -369,7 +369,7 @@ impl<N: Scalar, D: Dim, S: Storage<N, D>> Vector<N, D, S> {
     #[inline]
     pub fn iamin(&self) -> usize
     where
-        N: PartialOrd + Signed,
+        T: PartialOrd + Signed,
     {
         assert!(!self.is_empty(), "The input vector must not be empty.");
 

src/base/norm.rs

@@ -5,7 +5,7 @@ use num::Zero;
 use std::ops::Neg;
 
 use crate::allocator::Allocator;
-use crate::base::{DefaultAllocator, Dim, DimName, Matrix, MatrixMN, Normed, VectorN};
+use crate::base::{DefaultAllocator, Dim, DimName, Matrix, Normed, OMatrix, OVector};
 use crate::constraint::{SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
 use crate::storage::{Storage, StorageMut};
 use crate::{ComplexField, Scalar, SimdComplexField, Unit};
@@ -16,26 +16,26 @@ use simba::simd::{SimdOption, SimdPartialOrd, SimdValue};
 /// A trait for abstract matrix norms.
 ///
 /// This may be moved to the alga crate in the future.
-pub trait Norm<N: SimdComplexField> {
+pub trait Norm<T: SimdComplexField> {
     /// Apply this norm to the given matrix.
-    fn norm<R, C, S>(&self, m: &Matrix<N, R, C, S>) -> N::SimdRealField
+    fn norm<R, C, S>(&self, m: &Matrix<T, R, C, S>) -> T::SimdRealField
     where
         R: Dim,
         C: Dim,
-        S: Storage<N, R, C>;
+        S: Storage<T, R, C>;
     /// Use the metric induced by this norm to compute the metric distance between the two given matrices.
     fn metric_distance<R1, C1, S1, R2, C2, S2>(
         &self,
-        m1: &Matrix<N, R1, C1, S1>,
-        m2: &Matrix<N, R2, C2, S2>,
-    ) -> N::SimdRealField
+        m1: &Matrix<T, R1, C1, S1>,
+        m2: &Matrix<T, R2, C2, S2>,
+    ) -> T::SimdRealField
     where
         R1: Dim,
         C1: Dim,
-        S1: Storage<N, R1, C1>,
+        S1: Storage<T, R1, C1>,
         R2: Dim,
         C2: Dim,
-        S2: Storage<N, R2, C2>,
+        S2: Storage<T, R2, C2>,
         ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>;
 }
 
@@ -46,13 +46,13 @@ pub struct LpNorm(pub i32);
 /// L-infinite norm aka. Chebytchev norm aka. uniform norm aka. suppremum norm.
 pub struct UniformNorm;
 
-impl<N: SimdComplexField> Norm<N> for EuclideanNorm {
+impl<T: SimdComplexField> Norm<T> for EuclideanNorm {
     #[inline]
-    fn norm<R, C, S>(&self, m: &Matrix<N, R, C, S>) -> N::SimdRealField
+    fn norm<R, C, S>(&self, m: &Matrix<T, R, C, S>) -> T::SimdRealField
     where
         R: Dim,
         C: Dim,
-        S: Storage<N, R, C>,
+        S: Storage<T, R, C>,
     {
         m.norm_squared().simd_sqrt()
     }
@@ -60,19 +60,19 @@ impl<N: SimdComplexField> Norm<N> for EuclideanNorm {
     #[inline]
     fn metric_distance<R1, C1, S1, R2, C2, S2>(
         &self,
-        m1: &Matrix<N, R1, C1, S1>,
-        m2: &Matrix<N, R2, C2, S2>,
-    ) -> N::SimdRealField
+        m1: &Matrix<T, R1, C1, S1>,
+        m2: &Matrix<T, R2, C2, S2>,
+    ) -> T::SimdRealField
     where
         R1: Dim,
         C1: Dim,
-        S1: Storage<N, R1, C1>,
+        S1: Storage<T, R1, C1>,
         R2: Dim,
         C2: Dim,
-        S2: Storage<N, R2, C2>,
+        S2: Storage<T, R2, C2>,
         ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
     {
-        m1.zip_fold(m2, N::SimdRealField::zero(), |acc, a, b| {
+        m1.zip_fold(m2, T::SimdRealField::zero(), |acc, a, b| {
             let diff = a - b;
             acc + diff.simd_modulus_squared()
         })
@@ -80,15 +80,15 @@ impl<N: SimdComplexField> Norm<N> for EuclideanNorm {
     }
 }
 
-impl<N: SimdComplexField> Norm<N> for LpNorm {
+impl<T: SimdComplexField> Norm<T> for LpNorm {
     #[inline]
-    fn norm<R, C, S>(&self, m: &Matrix<N, R, C, S>) -> N::SimdRealField
+    fn norm<R, C, S>(&self, m: &Matrix<T, R, C, S>) -> T::SimdRealField
     where
         R: Dim,
         C: Dim,
-        S: Storage<N, R, C>,
+        S: Storage<T, R, C>,
     {
-        m.fold(N::SimdRealField::zero(), |a, b| {
+        m.fold(T::SimdRealField::zero(), |a, b| {
             a + b.simd_modulus().simd_powi(self.0)
         })
         .simd_powf(crate::convert(1.0 / (self.0 as f64)))
@@ -97,19 +97,19 @@ impl<N: SimdComplexField> Norm<N> for LpNorm {
     #[inline]
     fn metric_distance<R1, C1, S1, R2, C2, S2>(
         &self,
-        m1: &Matrix<N, R1, C1, S1>,
-        m2: &Matrix<N, R2, C2, S2>,
-    ) -> N::SimdRealField
+        m1: &Matrix<T, R1, C1, S1>,
+        m2: &Matrix<T, R2, C2, S2>,
+    ) -> T::SimdRealField
     where
         R1: Dim,
         C1: Dim,
-        S1: Storage<N, R1, C1>,
+        S1: Storage<T, R1, C1>,
         R2: Dim,
         C2: Dim,
-        S2: Storage<N, R2, C2>,
+        S2: Storage<T, R2, C2>,
         ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
     {
-        m1.zip_fold(m2, N::SimdRealField::zero(), |acc, a, b| {
+        m1.zip_fold(m2, T::SimdRealField::zero(), |acc, a, b| {
             let diff = a - b;
             acc + diff.simd_modulus().simd_powi(self.0)
         })
@@ -117,17 +117,17 @@ impl<N: SimdComplexField> Norm<N> for LpNorm {
     }
 }
 
-impl<N: SimdComplexField> Norm<N> for UniformNorm {
+impl<T: SimdComplexField> Norm<T> for UniformNorm {
     #[inline]
-    fn norm<R, C, S>(&self, m: &Matrix<N, R, C, S>) -> N::SimdRealField
+    fn norm<R, C, S>(&self, m: &Matrix<T, R, C, S>) -> T::SimdRealField
     where
         R: Dim,
         C: Dim,
-        S: Storage<N, R, C>,
+        S: Storage<T, R, C>,
     {
         // NOTE: we don't use `m.amax()` here because for the complex
         // numbers this will return the max norm1 instead of the modulus.
-        m.fold(N::SimdRealField::zero(), |acc, a| {
+        m.fold(T::SimdRealField::zero(), |acc, a| {
             acc.simd_max(a.simd_modulus())
         })
     }
@@ -135,19 +135,19 @@ impl<N: SimdComplexField> Norm<N> for UniformNorm {
     #[inline]
     fn metric_distance<R1, C1, S1, R2, C2, S2>(
         &self,
-        m1: &Matrix<N, R1, C1, S1>,
-        m2: &Matrix<N, R2, C2, S2>,
-    ) -> N::SimdRealField
+        m1: &Matrix<T, R1, C1, S1>,
+        m2: &Matrix<T, R2, C2, S2>,
+    ) -> T::SimdRealField
     where
         R1: Dim,
         C1: Dim,
-        S1: Storage<N, R1, C1>,
+        S1: Storage<T, R1, C1>,
         R2: Dim,
         C2: Dim,
-        S2: Storage<N, R2, C2>,
+        S2: Storage<T, R2, C2>,
         ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
     {
-        m1.zip_fold(m2, N::SimdRealField::zero(), |acc, a, b| {
+        m1.zip_fold(m2, T::SimdRealField::zero(), |acc, a, b| {
             let val = (a - b).simd_modulus();
             acc.simd_max(val)
         })
@@ -155,14 +155,14 @@ impl<N: SimdComplexField> Norm<N> for UniformNorm {
 }
 
 /// # Magnitude and norms
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     /// The squared L2 norm of this vector.
     #[inline]
-    pub fn norm_squared(&self) -> N::SimdRealField
+    pub fn norm_squared(&self) -> T::SimdRealField
     where
-        N: SimdComplexField,
+        T: SimdComplexField,
     {
-        let mut res = N::SimdRealField::zero();
+        let mut res = T::SimdRealField::zero();
 
         for i in 0..self.ncols() {
             let col = self.column(i);
@@ -176,9 +176,9 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     ///
     /// Use `.apply_norm` to apply a custom norm.
     #[inline]
-    pub fn norm(&self) -> N::SimdRealField
+    pub fn norm(&self) -> T::SimdRealField
     where
-        N: SimdComplexField,
+        T: SimdComplexField,
     {
         self.norm_squared().simd_sqrt()
     }
@@ -187,12 +187,12 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     ///
     /// Use `.apply_metric_distance` to apply a custom norm.
     #[inline]
-    pub fn metric_distance<R2, C2, S2>(&self, rhs: &Matrix<N, R2, C2, S2>) -> N::SimdRealField
+    pub fn metric_distance<R2, C2, S2>(&self, rhs: &Matrix<T, R2, C2, S2>) -> T::SimdRealField
     where
-        N: SimdComplexField,
+        T: SimdComplexField,
         R2: Dim,
         C2: Dim,
-        S2: Storage<N, R2, C2>,
+        S2: Storage<T, R2, C2>,
         ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
     {
         self.apply_metric_distance(rhs, &EuclideanNorm)
@@ -211,9 +211,9 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(v.apply_norm(&EuclideanNorm), v.norm());
     /// ```
     #[inline]
-    pub fn apply_norm(&self, norm: &impl Norm<N>) -> N::SimdRealField
+    pub fn apply_norm(&self, norm: &impl Norm<T>) -> T::SimdRealField
     where
-        N: SimdComplexField,
+        T: SimdComplexField,
     {
         norm.norm(self)
     }
@@ -235,14 +235,14 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     #[inline]
     pub fn apply_metric_distance<R2, C2, S2>(
         &self,
-        rhs: &Matrix<N, R2, C2, S2>,
-        norm: &impl Norm<N>,
-    ) -> N::SimdRealField
+        rhs: &Matrix<T, R2, C2, S2>,
+        norm: &impl Norm<T>,
+    ) -> T::SimdRealField
     where
-        N: SimdComplexField,
+        T: SimdComplexField,
         R2: Dim,
         C2: Dim,
-        S2: Storage<N, R2, C2>,
+        S2: Storage<T, R2, C2>,
         ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
     {
         norm.metric_distance(self, rhs)
@@ -254,9 +254,9 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     ///
     /// This function is simply implemented as a call to `norm()`
     #[inline]
-    pub fn magnitude(&self) -> N::SimdRealField
+    pub fn magnitude(&self) -> T::SimdRealField
     where
-        N: SimdComplexField,
+        T: SimdComplexField,
     {
         self.norm()
     }
@@ -267,19 +267,19 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     ///
     /// This function is simply implemented as a call to `norm_squared()`
     #[inline]
-    pub fn magnitude_squared(&self) -> N::SimdRealField
+    pub fn magnitude_squared(&self) -> T::SimdRealField
     where
-        N: SimdComplexField,
+        T: SimdComplexField,
     {
         self.norm_squared()
     }
 
     /// Sets the magnitude of this vector.
     #[inline]
-    pub fn set_magnitude(&mut self, magnitude: N::SimdRealField)
+    pub fn set_magnitude(&mut self, magnitude: T::SimdRealField)
     where
-        N: SimdComplexField,
-        S: StorageMut<N, R, C>,
+        T: SimdComplexField,
+        S: StorageMut<T, R, C>,
     {
         let n = self.norm();
         self.scale_mut(magnitude / n)
@@ -288,19 +288,19 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// Returns a normalized version of this matrix.
     #[inline]
     #[must_use = "Did you mean to use normalize_mut()?"]
-    pub fn normalize(&self) -> MatrixMN<N, R, C>
+    pub fn normalize(&self) -> OMatrix<T, R, C>
     where
-        N: SimdComplexField,
-        DefaultAllocator: Allocator<N, R, C>,
+        T: SimdComplexField,
+        DefaultAllocator: Allocator<T, R, C>,
     {
         self.unscale(self.norm())
     }
 
     /// The Lp norm of this matrix.
     #[inline]
-    pub fn lp_norm(&self, p: i32) -> N::SimdRealField
+    pub fn lp_norm(&self, p: i32) -> T::SimdRealField
     where
-        N: SimdComplexField,
+        T: SimdComplexField,
     {
         self.apply_norm(&LpNorm(p))
     }
@@ -310,11 +310,11 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// The components of this matrix can be SIMD types.
     #[inline]
     #[must_use = "Did you mean to use simd_try_normalize_mut()?"]
-    pub fn simd_try_normalize(&self, min_norm: N::SimdRealField) -> SimdOption<MatrixMN<N, R, C>>
+    pub fn simd_try_normalize(&self, min_norm: T::SimdRealField) -> SimdOption<OMatrix<T, R, C>>
     where
-        N: SimdComplexField,
-        N::Element: Scalar,
-        DefaultAllocator: Allocator<N, R, C> + Allocator<N::Element, R, C>,
+        T: SimdComplexField,
+        T::Element: Scalar,
+        DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
     {
         let n = self.norm();
         let le = n.simd_le(min_norm);
@@ -327,10 +327,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// If `self.magnitude()` is smaller than `min_magnitude`, it will be left unchanged.
     /// Otherwise this is equivalent to: `*self = self.normalize() * magnitude.
     #[inline]
-    pub fn try_set_magnitude(&mut self, magnitude: N::RealField, min_magnitude: N::RealField)
+    pub fn try_set_magnitude(&mut self, magnitude: T::RealField, min_magnitude: T::RealField)
     where
-        N: ComplexField,
-        S: StorageMut<N, R, C>,
+        T: ComplexField,
+        S: StorageMut<T, R, C>,
     {
         let n = self.norm();
 
@@ -341,10 +341,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
     /// Returns a new vector with the same magnitude as `self` clamped between `0.0` and `max`.
     #[inline]
-    pub fn cap_magnitude(&self, max: N::RealField) -> MatrixMN<N, R, C>
+    pub fn cap_magnitude(&self, max: T::RealField) -> OMatrix<T, R, C>
     where
-        N: ComplexField,
-        DefaultAllocator: Allocator<N, R, C>,
+        T: ComplexField,
+        DefaultAllocator: Allocator<T, R, C>,
     {
         let n = self.norm();
 
@@ -357,11 +357,11 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
     /// Returns a new vector with the same magnitude as `self` clamped between `0.0` and `max`.
     #[inline]
-    pub fn simd_cap_magnitude(&self, max: N::SimdRealField) -> MatrixMN<N, R, C>
+    pub fn simd_cap_magnitude(&self, max: T::SimdRealField) -> OMatrix<T, R, C>
     where
-        N: SimdComplexField,
-        N::Element: Scalar,
-        DefaultAllocator: Allocator<N, R, C> + Allocator<N::Element, R, C>,
+        T: SimdComplexField,
+        T::Element: Scalar,
+        DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
     {
         let n = self.norm();
         let scaled = self.scale(max / n);
@@ -374,10 +374,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// The components of this matrix cannot be SIMD types (see `simd_try_normalize`) instead.
     #[inline]
     #[must_use = "Did you mean to use try_normalize_mut()?"]
-    pub fn try_normalize(&self, min_norm: N::RealField) -> Option<MatrixMN<N, R, C>>
+    pub fn try_normalize(&self, min_norm: T::RealField) -> Option<OMatrix<T, R, C>>
     where
-        N: ComplexField,
-        DefaultAllocator: Allocator<N, R, C>,
+        T: ComplexField,
+        DefaultAllocator: Allocator<T, R, C>,
     {
         let n = self.norm();
 
@@ -390,14 +390,14 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 }
 
 /// # In-place normalization
-impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> Matrix<T, R, C, S> {
     /// Normalizes this matrix in-place and returns its norm.
     ///
     /// The components of the matrix cannot be SIMD types (see `simd_try_normalize_mut` instead).
     #[inline]
-    pub fn normalize_mut(&mut self) -> N::SimdRealField
+    pub fn normalize_mut(&mut self) -> T::SimdRealField
     where
-        N: SimdComplexField,
+        T: SimdComplexField,
     {
         let n = self.norm();
         self.unscale_mut(n);
@@ -412,12 +412,12 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     #[must_use = "Did you mean to use simd_try_normalize_mut()?"]
     pub fn simd_try_normalize_mut(
         &mut self,
-        min_norm: N::SimdRealField,
-    ) -> SimdOption<N::SimdRealField>
+        min_norm: T::SimdRealField,
+    ) -> SimdOption<T::SimdRealField>
     where
-        N: SimdComplexField,
-        N::Element: Scalar,
-        DefaultAllocator: Allocator<N, R, C> + Allocator<N::Element, R, C>,
+        T: SimdComplexField,
+        T::Element: Scalar,
+        DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
     {
         let n = self.norm();
         let le = n.simd_le(min_norm);
@@ -429,9 +429,9 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     ///
     /// If the normalization succeeded, returns the old norm of this matrix.
     #[inline]
-    pub fn try_normalize_mut(&mut self, min_norm: N::RealField) -> Option<N::RealField>
+    pub fn try_normalize_mut(&mut self, min_norm: T::RealField) -> Option<T::RealField>
     where
-        N: ComplexField,
+        T: ComplexField,
     {
         let n = self.norm();
 
@@ -444,19 +444,19 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     }
 }
 
-impl<N: SimdComplexField, R: Dim, C: Dim> Normed for MatrixMN<N, R, C>
+impl<T: SimdComplexField, R: Dim, C: Dim> Normed for OMatrix<T, R, C>
 where
-    DefaultAllocator: Allocator<N, R, C>,
+    DefaultAllocator: Allocator<T, R, C>,
 {
-    type Norm = N::SimdRealField;
+    type Norm = T::SimdRealField;
 
     #[inline]
-    fn norm(&self) -> N::SimdRealField {
+    fn norm(&self) -> T::SimdRealField {
         self.norm()
     }
 
     #[inline]
-    fn norm_squared(&self) -> N::SimdRealField {
+    fn norm_squared(&self) -> T::SimdRealField {
         self.norm_squared()
     }
 
@@ -471,11 +471,11 @@ where
     }
 }
 
-impl<N: Scalar + ClosedNeg, R: Dim, C: Dim> Neg for Unit<MatrixMN<N, R, C>>
+impl<T: Scalar + ClosedNeg, R: Dim, C: Dim> Neg for Unit<OMatrix<T, R, C>>
 where
-    DefaultAllocator: Allocator<N, R, C>,
+    DefaultAllocator: Allocator<T, R, C>,
 {
-    type Output = Unit<MatrixMN<N, R, C>>;
+    type Output = Unit<OMatrix<T, R, C>>;
 
     #[inline]
     fn neg(self) -> Self::Output {
@@ -488,9 +488,9 @@ where
 //   − use `x()` instead of `::canonical_basis_element`
 //   − use `::new(x, y, z)` instead of `::from_slice`
 /// # Basis and orthogonalization
-impl<N: ComplexField, D: DimName> VectorN<N, D>
+impl<T: ComplexField, D: DimName> OVector<T, D>
 where
-    DefaultAllocator: Allocator<N, D>,
+    DefaultAllocator: Allocator<T, D>,
 {
     /// The i-the canonical basis element.
     #[inline]
@@ -499,7 +499,7 @@ where
 
         let mut res = Self::zero();
         unsafe {
-            *res.data.get_unchecked_linear_mut(i) = N::one();
+            *res.data.get_unchecked_linear_mut(i) = T::one();
         }
 
         res
@@ -521,7 +521,7 @@ where
                 }
             }
 
-            if vs[i].try_normalize_mut(N::RealField::zero()).is_some() {
+            if vs[i].try_normalize_mut(T::RealField::zero()).is_some() {
                 // TODO: this will be efficient on dynamically-allocated vectors but for
                 // statically-allocated ones, `.clone_from` would be better.
                 vs.swap(nbasis_elements, i);
@@ -581,9 +581,9 @@ where
                     let mut a;
 
                     if v[0].norm1() > v[1].norm1() {
-                        a = Self::from_column_slice(&[v[2], N::zero(), -v[0]]);
+                        a = Self::from_column_slice(&[v[2], T::zero(), -v[0]]);
                     } else {
-                        a = Self::from_column_slice(&[N::zero(), -v[2], v[1]]);
+                        a = Self::from_column_slice(&[T::zero(), -v[2], v[1]]);
                     };
 
                     let _ = a.normalize_mut();
@@ -612,7 +612,7 @@ where
                             elt -= v * elt.dot(v)
                         }
 
-                        if let Some(subsp_elt) = elt.try_normalize(N::RealField::zero()) {
+                        if let Some(subsp_elt) = elt.try_normalize(T::RealField::zero()) {
                             if !f(&subsp_elt) {
                                 return;
                             };

src/base/ops.rs

@@ -12,7 +12,7 @@ use crate::base::constraint::{
 };
 use crate::base::dimension::{Dim, DimMul, DimName, DimProd, Dynamic};
 use crate::base::storage::{ContiguousStorageMut, Storage, StorageMut};
-use crate::base::{DefaultAllocator, Matrix, MatrixMN, MatrixN, MatrixSum, Scalar, VectorSliceN};
+use crate::base::{DefaultAllocator, Matrix, MatrixSum, OMatrix, Scalar, VectorSlice};
 use crate::SimdComplexField;
 
 /*
@@ -20,8 +20,8 @@ use crate::SimdComplexField;
  * Indexing.
  *
  */
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Index<usize> for Matrix<N, R, C, S> {
-    type Output = N;
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Index<usize> for Matrix<T, R, C, S> {
+    type Output = T;
 
     #[inline]
     fn index(&self, i: usize) -> &Self::Output {
@@ -30,12 +30,12 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Index<usize> for Matrix<N,
     }
 }
 
-impl<N, R: Dim, C: Dim, S> Index<(usize, usize)> for Matrix<N, R, C, S>
+impl<T, R: Dim, C: Dim, S> Index<(usize, usize)> for Matrix<T, R, C, S>
 where
-    N: Scalar,
-    S: Storage<N, R, C>,
+    T: Scalar,
+    S: Storage<T, R, C>,
 {
-    type Output = N;
+    type Output = T;
 
     #[inline]
     fn index(&self, ij: (usize, usize)) -> &Self::Output {
@@ -50,21 +50,21 @@ where
 }
 
 // Mutable versions.
-impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> IndexMut<usize> for Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: StorageMut<T, R, C>> IndexMut<usize> for Matrix<T, R, C, S> {
     #[inline]
-    fn index_mut(&mut self, i: usize) -> &mut N {
+    fn index_mut(&mut self, i: usize) -> &mut T {
         let ij = self.vector_to_matrix_index(i);
         &mut self[ij]
     }
 }
 
-impl<N, R: Dim, C: Dim, S> IndexMut<(usize, usize)> for Matrix<N, R, C, S>
+impl<T, R: Dim, C: Dim, S> IndexMut<(usize, usize)> for Matrix<T, R, C, S>
 where
-    N: Scalar,
-    S: StorageMut<N, R, C>,
+    T: Scalar,
+    S: StorageMut<T, R, C>,
 {
     #[inline]
-    fn index_mut(&mut self, ij: (usize, usize)) -> &mut N {
+    fn index_mut(&mut self, ij: (usize, usize)) -> &mut T {
         let shape = self.shape();
         assert!(
             ij.0 < shape.0 && ij.1 < shape.1,
@@ -80,13 +80,13 @@ where
  * Neg
  *
  */
-impl<N, R: Dim, C: Dim, S> Neg for Matrix<N, R, C, S>
+impl<T, R: Dim, C: Dim, S> Neg for Matrix<T, R, C, S>
 where
-    N: Scalar + ClosedNeg,
-    S: Storage<N, R, C>,
-    DefaultAllocator: Allocator<N, R, C>,
+    T: Scalar + ClosedNeg,
+    S: Storage<T, R, C>,
+    DefaultAllocator: Allocator<T, R, C>,
 {
-    type Output = MatrixMN<N, R, C>;
+    type Output = OMatrix<T, R, C>;
 
     #[inline]
     fn neg(self) -> Self::Output {
@@ -96,13 +96,13 @@ where
     }
 }
 
-impl<'a, N, R: Dim, C: Dim, S> Neg for &'a Matrix<N, R, C, S>
+impl<'a, T, R: Dim, C: Dim, S> Neg for &'a Matrix<T, R, C, S>
 where
-    N: Scalar + ClosedNeg,
-    S: Storage<N, R, C>,
-    DefaultAllocator: Allocator<N, R, C>,
+    T: Scalar + ClosedNeg,
+    S: Storage<T, R, C>,
+    DefaultAllocator: Allocator<T, R, C>,
 {
-    type Output = MatrixMN<N, R, C>;
+    type Output = OMatrix<T, R, C>;
 
     #[inline]
     fn neg(self) -> Self::Output {
@@ -110,10 +110,10 @@ where
     }
 }
 
-impl<N, R: Dim, C: Dim, S> Matrix<N, R, C, S>
+impl<T, R: Dim, C: Dim, S> Matrix<T, R, C, S>
 where
-    N: Scalar + ClosedNeg,
-    S: StorageMut<N, R, C>,
+    T: Scalar + ClosedNeg,
+    S: StorageMut<T, R, C>,
 {
     /// Negates `self` in-place.
     #[inline]
@@ -136,8 +136,8 @@ macro_rules! componentwise_binop_impl(
      $method_assign_statically_unchecked_rhs: ident;
      $method_to: ident, $method_to_statically_unchecked: ident) => {
 
-        impl<N, R1: Dim, C1: Dim, SA: Storage<N, R1, C1>> Matrix<N, R1, C1, SA>
-            where N: Scalar + $bound {
+        impl<T, R1: Dim, C1: Dim, SA: Storage<T, R1, C1>> Matrix<T, R1, C1, SA>
+            where T: Scalar + $bound {
 
             /*
              *
@@ -149,10 +149,10 @@ macro_rules! componentwise_binop_impl(
             #[inline]
             fn $method_to_statically_unchecked<R2: Dim, C2: Dim, SB,
                                                R3: Dim, C3: Dim, SC>(&self,
-                                                                     rhs: &Matrix<N, R2, C2, SB>,
-                                                                     out: &mut Matrix<N, R3, C3, SC>)
-                where SB: Storage<N, R2, C2>,
-                      SC: StorageMut<N, R3, C3> {
+                                                                     rhs: &Matrix<T, R2, C2, SB>,
+                                                                     out: &mut Matrix<T, R3, C3, SC>)
+                where SB: Storage<T, R2, C2>,
+                      SC: StorageMut<T, 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.");
 
@@ -182,11 +182,11 @@ macro_rules! componentwise_binop_impl(
 
 
             #[inline]
-            fn $method_assign_statically_unchecked<R2, C2, SB>(&mut self, rhs: &Matrix<N, R2, C2, SB>)
+            fn $method_assign_statically_unchecked<R2, C2, SB>(&mut self, rhs: &Matrix<T, R2, C2, SB>)
                 where R2: Dim,
                       C2: Dim,
-                      SA: StorageMut<N, R1, C1>,
-                      SB: Storage<N, R2, C2> {
+                      SA: StorageMut<T, R1, C1>,
+                      SB: Storage<T, R2, C2> {
                 assert_eq!(self.shape(), rhs.shape(), "Matrix addition/subtraction dimensions mismatch.");
 
                 // This is the most common case and should be deduced at compile-time.
@@ -213,10 +213,10 @@ macro_rules! componentwise_binop_impl(
 
 
             #[inline]
-            fn $method_assign_statically_unchecked_rhs<R2, C2, SB>(&self, rhs: &mut Matrix<N, R2, C2, SB>)
+            fn $method_assign_statically_unchecked_rhs<R2, C2, SB>(&self, rhs: &mut Matrix<T, R2, C2, SB>)
                 where R2: Dim,
                       C2: Dim,
-                      SB: StorageMut<N, R2, C2> {
+                      SB: StorageMut<T, R2, C2> {
                 assert_eq!(self.shape(), rhs.shape(), "Matrix addition/subtraction dimensions mismatch.");
 
                 // This is the most common case and should be deduced at compile-time.
@@ -255,27 +255,27 @@ macro_rules! componentwise_binop_impl(
             #[inline]
             pub fn $method_to<R2: Dim, C2: Dim, SB,
                               R3: Dim, C3: Dim, SC>(&self,
-                                                    rhs: &Matrix<N, R2, C2, SB>,
-                                                    out: &mut Matrix<N, R3, C3, SC>)
-                where SB: Storage<N, R2, C2>,
-                      SC: StorageMut<N, R3, C3>,
+                                                    rhs: &Matrix<T, R2, C2, SB>,
+                                                    out: &mut Matrix<T, R3, C3, SC>)
+                where SB: Storage<T, R2, C2>,
+                      SC: StorageMut<T, R3, C3>,
                       ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> +
                                        SameNumberOfRows<R1, R3> + SameNumberOfColumns<C1, C3> {
                 self.$method_to_statically_unchecked(rhs, out)
             }
         }
 
-        impl<'b, N, R1, C1, R2, C2, SA, SB> $Trait<&'b Matrix<N, R2, C2, SB>> for Matrix<N, R1, C1, SA>
+        impl<'b, T, R1, C1, R2, C2, SA, SB> $Trait<&'b Matrix<T, R2, C2, SB>> for Matrix<T, R1, C1, SA>
             where R1: Dim, C1: Dim, R2: Dim, C2: Dim,
-                  N: Scalar + $bound,
-                  SA: Storage<N, R1, C1>,
-                  SB: Storage<N, R2, C2>,
-                  DefaultAllocator: SameShapeAllocator<N, R1, C1, R2, C2>,
+                  T: Scalar + $bound,
+                  SA: Storage<T, R1, C1>,
+                  SB: Storage<T, R2, C2>,
+                  DefaultAllocator: SameShapeAllocator<T, R1, C1, R2, C2>,
                   ShapeConstraint:  SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
-            type Output = MatrixSum<N, R1, C1, R2, C2>;
+            type Output = MatrixSum<T, R1, C1, R2, C2>;
 
             #[inline]
-            fn $method(self, rhs: &'b Matrix<N, R2, C2, SB>) -> Self::Output {
+            fn $method(self, rhs: &'b Matrix<T, R2, C2, SB>) -> Self::Output {
                 assert_eq!(self.shape(), rhs.shape(), "Matrix addition/subtraction dimensions mismatch.");
                 let mut res = self.into_owned_sum::<R2, C2>();
                 res.$method_assign_statically_unchecked(rhs);
@@ -283,17 +283,17 @@ macro_rules! componentwise_binop_impl(
             }
         }
 
-        impl<'a, N, R1, C1, R2, C2, SA, SB> $Trait<Matrix<N, R2, C2, SB>> for &'a Matrix<N, R1, C1, SA>
+        impl<'a, T, R1, C1, R2, C2, SA, SB> $Trait<Matrix<T, R2, C2, SB>> for &'a Matrix<T, R1, C1, SA>
             where R1: Dim, C1: Dim, R2: Dim, C2: Dim,
-                  N: Scalar + $bound,
-                  SA: Storage<N, R1, C1>,
-                  SB: Storage<N, R2, C2>,
-                  DefaultAllocator: SameShapeAllocator<N, R2, C2, R1, C1>,
+                  T: Scalar + $bound,
+                  SA: Storage<T, R1, C1>,
+                  SB: Storage<T, R2, C2>,
+                  DefaultAllocator: SameShapeAllocator<T, R2, C2, R1, C1>,
                   ShapeConstraint:  SameNumberOfRows<R2, R1> + SameNumberOfColumns<C2, C1> {
-            type Output = MatrixSum<N, R2, C2, R1, C1>;
+            type Output = MatrixSum<T, R2, C2, R1, C1>;
 
             #[inline]
-            fn $method(self, rhs: Matrix<N, R2, C2, SB>) -> Self::Output {
+            fn $method(self, rhs: Matrix<T, R2, C2, SB>) -> Self::Output {
                 let mut rhs = rhs.into_owned_sum::<R1, C1>();
                 assert_eq!(self.shape(), rhs.shape(), "Matrix addition/subtraction dimensions mismatch.");
                 self.$method_assign_statically_unchecked_rhs(&mut rhs);
@@ -301,32 +301,32 @@ macro_rules! componentwise_binop_impl(
             }
         }
 
-        impl<N, R1, C1, R2, C2, SA, SB> $Trait<Matrix<N, R2, C2, SB>> for Matrix<N, R1, C1, SA>
+        impl<T, R1, C1, R2, C2, SA, SB> $Trait<Matrix<T, R2, C2, SB>> for Matrix<T, R1, C1, SA>
             where R1: Dim, C1: Dim, R2: Dim, C2: Dim,
-                  N: Scalar + $bound,
-                  SA: Storage<N, R1, C1>,
-                  SB: Storage<N, R2, C2>,
-                  DefaultAllocator: SameShapeAllocator<N, R1, C1, R2, C2>,
+                  T: Scalar + $bound,
+                  SA: Storage<T, R1, C1>,
+                  SB: Storage<T, R2, C2>,
+                  DefaultAllocator: SameShapeAllocator<T, R1, C1, R2, C2>,
                   ShapeConstraint:  SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
-            type Output = MatrixSum<N, R1, C1, R2, C2>;
+            type Output = MatrixSum<T, R1, C1, R2, C2>;
 
             #[inline]
-            fn $method(self, rhs: Matrix<N, R2, C2, SB>) -> Self::Output {
+            fn $method(self, rhs: Matrix<T, R2, C2, SB>) -> Self::Output {
                 self.$method(&rhs)
             }
         }
 
-        impl<'a, 'b, N, R1, C1, R2, C2, SA, SB> $Trait<&'b Matrix<N, R2, C2, SB>> for &'a Matrix<N, R1, C1, SA>
+        impl<'a, 'b, T, R1, C1, R2, C2, SA, SB> $Trait<&'b Matrix<T, R2, C2, SB>> for &'a Matrix<T, R1, C1, SA>
             where R1: Dim, C1: Dim, R2: Dim, C2: Dim,
-                  N: Scalar + $bound,
-                  SA: Storage<N, R1, C1>,
-                  SB: Storage<N, R2, C2>,
-                  DefaultAllocator: SameShapeAllocator<N, R1, C1, R2, C2>,
+                  T: Scalar + $bound,
+                  SA: Storage<T, R1, C1>,
+                  SB: Storage<T, R2, C2>,
+                  DefaultAllocator: SameShapeAllocator<T, R1, C1, R2, C2>,
                   ShapeConstraint:  SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
-            type Output = MatrixSum<N, R1, C1, R2, C2>;
+            type Output = MatrixSum<T, R1, C1, R2, C2>;
 
             #[inline]
-            fn $method(self, rhs: &'b Matrix<N, R2, C2, SB>) -> Self::Output {
+            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);
@@ -339,28 +339,28 @@ macro_rules! componentwise_binop_impl(
             }
         }
 
-        impl<'b, N, R1, C1, R2, C2, SA, SB> $TraitAssign<&'b Matrix<N, R2, C2, SB>> for Matrix<N, R1, C1, SA>
+        impl<'b, T, R1, C1, R2, C2, SA, SB> $TraitAssign<&'b Matrix<T, R2, C2, SB>> for Matrix<T, R1, C1, SA>
             where R1: Dim, C1: Dim, R2: Dim, C2: Dim,
-                  N: Scalar + $bound,
-                  SA: StorageMut<N, R1, C1>,
-                  SB: Storage<N, R2, C2>,
+                  T: Scalar + $bound,
+                  SA: StorageMut<T, R1, C1>,
+                  SB: Storage<T, R2, C2>,
                   ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
 
             #[inline]
-            fn $method_assign(&mut self, rhs: &'b Matrix<N, R2, C2, SB>) {
+            fn $method_assign(&mut self, rhs: &'b Matrix<T, R2, C2, SB>) {
                 self.$method_assign_statically_unchecked(rhs)
             }
         }
 
-        impl<N, R1, C1, R2, C2, SA, SB> $TraitAssign<Matrix<N, R2, C2, SB>> for Matrix<N, R1, C1, SA>
+        impl<T, R1, C1, R2, C2, SA, SB> $TraitAssign<Matrix<T, R2, C2, SB>> for Matrix<T, R1, C1, SA>
             where R1: Dim, C1: Dim, R2: Dim, C2: Dim,
-                  N: Scalar + $bound,
-                  SA: StorageMut<N, R1, C1>,
-                  SB: Storage<N, R2, C2>,
+                  T: Scalar + $bound,
+                  SA: StorageMut<T, R1, C1>,
+                  SB: Storage<T, R2, C2>,
                   ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
 
             #[inline]
-            fn $method_assign(&mut self, rhs: Matrix<N, R2, C2, SB>) {
+            fn $method_assign(&mut self, rhs: Matrix<T, R2, C2, SB>) {
                 self.$method_assign(&rhs)
             }
         }
@@ -374,20 +374,20 @@ componentwise_binop_impl!(Sub, sub, ClosedSub;
                           SubAssign, sub_assign, sub_assign_statically_unchecked, sub_assign_statically_unchecked_mut;
                           sub_to, sub_to_statically_unchecked);
 
-impl<N, R: DimName, C: DimName> iter::Sum for MatrixMN<N, R, C>
+impl<T, R: DimName, C: DimName> iter::Sum for OMatrix<T, R, C>
 where
-    N: Scalar + ClosedAdd + Zero,
-    DefaultAllocator: Allocator<N, R, C>,
+    T: Scalar + ClosedAdd + Zero,
+    DefaultAllocator: Allocator<T, R, C>,
 {
-    fn sum<I: Iterator<Item = MatrixMN<N, R, C>>>(iter: I) -> MatrixMN<N, R, C> {
+    fn sum<I: Iterator<Item = OMatrix<T, R, C>>>(iter: I) -> OMatrix<T, R, C> {
         iter.fold(Matrix::zero(), |acc, x| acc + x)
     }
 }
 
-impl<N, C: Dim> iter::Sum for MatrixMN<N, Dynamic, C>
+impl<T, C: Dim> iter::Sum for OMatrix<T, Dynamic, C>
 where
-    N: Scalar + ClosedAdd + Zero,
-    DefaultAllocator: Allocator<N, Dynamic, C>,
+    T: Scalar + ClosedAdd + Zero,
+    DefaultAllocator: Allocator<T, Dynamic, C>,
 {
     /// # Example
     /// ```
@@ -405,7 +405,7 @@ where
     /// # use nalgebra::DMatrix;
     /// iter::empty::<DMatrix<f64>>().sum::<DMatrix<f64>>(); // panics!
     /// ```
-    fn sum<I: Iterator<Item = MatrixMN<N, Dynamic, C>>>(mut iter: I) -> MatrixMN<N, Dynamic, C> {
+    fn sum<I: Iterator<Item = OMatrix<T, Dynamic, C>>>(mut iter: I) -> OMatrix<T, Dynamic, C> {
         if let Some(first) = iter.next() {
             iter.fold(first, |acc, x| acc + x)
         } else {
@@ -414,20 +414,20 @@ where
     }
 }
 
-impl<'a, N, R: DimName, C: DimName> iter::Sum<&'a MatrixMN<N, R, C>> for MatrixMN<N, R, C>
+impl<'a, T, R: DimName, C: DimName> iter::Sum<&'a OMatrix<T, R, C>> for OMatrix<T, R, C>
 where
-    N: Scalar + ClosedAdd + Zero,
-    DefaultAllocator: Allocator<N, R, C>,
+    T: Scalar + ClosedAdd + Zero,
+    DefaultAllocator: Allocator<T, R, C>,
 {
-    fn sum<I: Iterator<Item = &'a MatrixMN<N, R, C>>>(iter: I) -> MatrixMN<N, R, C> {
+    fn sum<I: Iterator<Item = &'a OMatrix<T, R, C>>>(iter: I) -> OMatrix<T, R, C> {
         iter.fold(Matrix::zero(), |acc, x| acc + x)
     }
 }
 
-impl<'a, N, C: Dim> iter::Sum<&'a MatrixMN<N, Dynamic, C>> for MatrixMN<N, Dynamic, C>
+impl<'a, T, C: Dim> iter::Sum<&'a OMatrix<T, Dynamic, C>> for OMatrix<T, Dynamic, C>
 where
-    N: Scalar + ClosedAdd + Zero,
-    DefaultAllocator: Allocator<N, Dynamic, C>,
+    T: Scalar + ClosedAdd + Zero,
+    DefaultAllocator: Allocator<T, Dynamic, C>,
 {
     /// # Example
     /// ```
@@ -445,9 +445,7 @@ where
     /// # use nalgebra::DMatrix;
     /// iter::empty::<&DMatrix<f64>>().sum::<DMatrix<f64>>(); // panics!
     /// ```
-    fn sum<I: Iterator<Item = &'a MatrixMN<N, Dynamic, C>>>(
-        mut iter: I,
-    ) -> MatrixMN<N, Dynamic, C> {
+    fn sum<I: Iterator<Item = &'a OMatrix<T, Dynamic, C>>>(mut iter: I) -> OMatrix<T, Dynamic, C> {
         if let Some(first) = iter.next() {
             iter.fold(first.clone(), |acc, x| acc + x)
         } else {
@@ -467,14 +465,14 @@ where
 macro_rules! componentwise_scalarop_impl(
     ($Trait: ident, $method: ident, $bound: ident;
      $TraitAssign: ident, $method_assign: ident) => {
-        impl<N, R: Dim, C: Dim, S> $Trait<N> for Matrix<N, R, C, S>
-            where N: Scalar + $bound,
-                  S: Storage<N, R, C>,
-                  DefaultAllocator: Allocator<N, R, C> {
-            type Output = MatrixMN<N, R, C>;
+        impl<T, R: Dim, C: Dim, S> $Trait<T> for Matrix<T, R, C, S>
+            where T: Scalar + $bound,
+                  S: Storage<T, R, C>,
+                  DefaultAllocator: Allocator<T, R, C> {
+            type Output = OMatrix<T, R, C>;
 
             #[inline]
-            fn $method(self, rhs: N) -> Self::Output {
+            fn $method(self, rhs: T) -> Self::Output {
                 let mut res = self.into_owned();
 
                 // XXX: optimize our iterator!
@@ -491,23 +489,23 @@ macro_rules! componentwise_scalarop_impl(
             }
         }
 
-        impl<'a, N, R: Dim, C: Dim, S> $Trait<N> for &'a Matrix<N, R, C, S>
-            where N: Scalar + $bound,
-                  S: Storage<N, R, C>,
-                  DefaultAllocator: Allocator<N, R, C> {
-            type Output = MatrixMN<N, R, C>;
+        impl<'a, T, R: Dim, C: Dim, S> $Trait<T> for &'a Matrix<T, R, C, S>
+            where T: Scalar + $bound,
+                  S: Storage<T, R, C>,
+                  DefaultAllocator: Allocator<T, R, C> {
+            type Output = OMatrix<T, R, C>;
 
             #[inline]
-            fn $method(self, rhs: N) -> Self::Output {
+            fn $method(self, rhs: T) -> Self::Output {
                 self.clone_owned().$method(rhs)
             }
         }
 
-        impl<N, R: Dim, C: Dim, S> $TraitAssign<N> for Matrix<N, R, C, S>
-            where N: Scalar + $bound,
-                  S: StorageMut<N, R, C> {
+        impl<T, R: Dim, C: Dim, S> $TraitAssign<T> for Matrix<T, R, C, S>
+            where T: Scalar + $bound,
+                  S: StorageMut<T, R, C> {
             #[inline]
-            fn $method_assign(&mut self, rhs: N) {
+            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()) };
@@ -525,7 +523,7 @@ macro_rules! left_scalar_mul_impl(
     ($($T: ty),* $(,)*) => {$(
         impl<R: Dim, C: Dim, S: Storage<$T, R, C>> Mul<Matrix<$T, R, C, S>> for $T
             where DefaultAllocator: Allocator<$T, R, C> {
-            type Output = MatrixMN<$T, R, C>;
+            type Output = OMatrix<$T, R, C>;
 
             #[inline]
             fn mul(self, rhs: Matrix<$T, R, C, S>) -> Self::Output {
@@ -547,7 +545,7 @@ macro_rules! left_scalar_mul_impl(
 
         impl<'b, R: Dim, C: Dim, S: Storage<$T, R, C>> Mul<&'b Matrix<$T, R, C, S>> for $T
             where DefaultAllocator: Allocator<$T, R, C> {
-            type Output = MatrixMN<$T, R, C>;
+            type Output = OMatrix<$T, R, C>;
 
             #[inline]
             fn mul(self, rhs: &'b Matrix<$T, R, C, S>) -> Self::Output {
@@ -560,19 +558,19 @@ macro_rules! left_scalar_mul_impl(
 left_scalar_mul_impl!(u8, u16, u32, u64, usize, i8, i16, i32, i64, isize, f32, f64);
 
 // Matrix × Matrix
-impl<'a, 'b, N, R1: Dim, C1: Dim, R2: Dim, C2: Dim, SA, SB> Mul<&'b Matrix<N, R2, C2, SB>>
-    for &'a Matrix<N, R1, C1, SA>
+impl<'a, 'b, T, R1: Dim, C1: Dim, R2: Dim, C2: Dim, SA, SB> Mul<&'b Matrix<T, R2, C2, SB>>
+    for &'a Matrix<T, R1, C1, SA>
 where
-    N: Scalar + Zero + One + ClosedAdd + ClosedMul,
-    SA: Storage<N, R1, C1>,
-    SB: Storage<N, R2, C2>,
-    DefaultAllocator: Allocator<N, R1, C2>,
+    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    SA: Storage<T, R1, C1>,
+    SB: Storage<T, R2, C2>,
+    DefaultAllocator: Allocator<T, R1, C2>,
     ShapeConstraint: AreMultipliable<R1, C1, R2, C2>,
 {
-    type Output = MatrixMN<N, R1, C2>;
+    type Output = OMatrix<T, R1, C2>;
 
     #[inline]
-    fn mul(self, rhs: &'b Matrix<N, R2, C2, SB>) -> Self::Output {
+    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)
         };
@@ -581,53 +579,53 @@ where
     }
 }
 
-impl<'a, N, R1: Dim, C1: Dim, R2: Dim, C2: Dim, SA, SB> Mul<Matrix<N, R2, C2, SB>>
-    for &'a Matrix<N, R1, C1, SA>
+impl<'a, T, R1: Dim, C1: Dim, R2: Dim, C2: Dim, SA, SB> Mul<Matrix<T, R2, C2, SB>>
+    for &'a Matrix<T, R1, C1, SA>
 where
-    N: Scalar + Zero + One + ClosedAdd + ClosedMul,
-    SB: Storage<N, R2, C2>,
-    SA: Storage<N, R1, C1>,
-    DefaultAllocator: Allocator<N, R1, C2>,
+    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    SB: Storage<T, R2, C2>,
+    SA: Storage<T, R1, C1>,
+    DefaultAllocator: Allocator<T, R1, C2>,
     ShapeConstraint: AreMultipliable<R1, C1, R2, C2>,
 {
-    type Output = MatrixMN<N, R1, C2>;
+    type Output = OMatrix<T, R1, C2>;
 
     #[inline]
-    fn mul(self, rhs: Matrix<N, R2, C2, SB>) -> Self::Output {
+    fn mul(self, rhs: Matrix<T, R2, C2, SB>) -> Self::Output {
         self * &rhs
     }
 }
 
-impl<'b, N, R1: Dim, C1: Dim, R2: Dim, C2: Dim, SA, SB> Mul<&'b Matrix<N, R2, C2, SB>>
-    for Matrix<N, R1, C1, SA>
+impl<'b, T, R1: Dim, C1: Dim, R2: Dim, C2: Dim, SA, SB> Mul<&'b Matrix<T, R2, C2, SB>>
+    for Matrix<T, R1, C1, SA>
 where
-    N: Scalar + Zero + One + ClosedAdd + ClosedMul,
-    SB: Storage<N, R2, C2>,
-    SA: Storage<N, R1, C1>,
-    DefaultAllocator: Allocator<N, R1, C2>,
+    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    SB: Storage<T, R2, C2>,
+    SA: Storage<T, R1, C1>,
+    DefaultAllocator: Allocator<T, R1, C2>,
     ShapeConstraint: AreMultipliable<R1, C1, R2, C2>,
 {
-    type Output = MatrixMN<N, R1, C2>;
+    type Output = OMatrix<T, R1, C2>;
 
     #[inline]
-    fn mul(self, rhs: &'b Matrix<N, R2, C2, SB>) -> Self::Output {
+    fn mul(self, rhs: &'b Matrix<T, R2, C2, SB>) -> Self::Output {
         &self * rhs
     }
 }
 
-impl<N, R1: Dim, C1: Dim, R2: Dim, C2: Dim, SA, SB> Mul<Matrix<N, R2, C2, SB>>
-    for Matrix<N, R1, C1, SA>
+impl<T, R1: Dim, C1: Dim, R2: Dim, C2: Dim, SA, SB> Mul<Matrix<T, R2, C2, SB>>
+    for Matrix<T, R1, C1, SA>
 where
-    N: Scalar + Zero + One + ClosedAdd + ClosedMul,
-    SB: Storage<N, R2, C2>,
-    SA: Storage<N, R1, C1>,
-    DefaultAllocator: Allocator<N, R1, C2>,
+    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    SB: Storage<T, R2, C2>,
+    SA: Storage<T, R1, C1>,
+    DefaultAllocator: Allocator<T, R1, C2>,
     ShapeConstraint: AreMultipliable<R1, C1, R2, C2>,
 {
-    type Output = MatrixMN<N, R1, C2>;
+    type Output = OMatrix<T, R1, C2>;
 
     #[inline]
-    fn mul(self, rhs: Matrix<N, R2, C2, SB>) -> Self::Output {
+    fn mul(self, rhs: Matrix<T, R2, C2, SB>) -> Self::Output {
         &self * &rhs
     }
 }
@@ -635,53 +633,53 @@ where
 // TODO: this is too restrictive:
 //    − we can't use `a *= b` when `a` is a mutable slice.
 //    − we can't use `a *= b` when C2 is not equal to C1.
-impl<N, R1, C1, R2, SA, SB> MulAssign<Matrix<N, R2, C1, SB>> for Matrix<N, R1, C1, SA>
+impl<T, R1, C1, R2, SA, SB> MulAssign<Matrix<T, R2, C1, SB>> for Matrix<T, R1, C1, SA>
 where
     R1: Dim,
     C1: Dim,
     R2: Dim,
-    N: Scalar + Zero + One + ClosedAdd + ClosedMul,
-    SB: Storage<N, R2, C1>,
-    SA: ContiguousStorageMut<N, R1, C1> + Clone,
+    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    SB: Storage<T, R2, C1>,
+    SA: ContiguousStorageMut<T, R1, C1> + Clone,
     ShapeConstraint: AreMultipliable<R1, C1, R2, C1>,
-    DefaultAllocator: Allocator<N, R1, C1, Buffer = SA>,
+    DefaultAllocator: Allocator<T, R1, C1, Buffer = SA>,
 {
     #[inline]
-    fn mul_assign(&mut self, rhs: Matrix<N, R2, C1, SB>) {
+    fn mul_assign(&mut self, rhs: Matrix<T, R2, C1, SB>) {
         *self = &*self * rhs
     }
 }
 
-impl<'b, N, R1, C1, R2, SA, SB> MulAssign<&'b Matrix<N, R2, C1, SB>> for Matrix<N, R1, C1, SA>
+impl<'b, T, R1, C1, R2, SA, SB> MulAssign<&'b Matrix<T, R2, C1, SB>> for Matrix<T, R1, C1, SA>
 where
     R1: Dim,
     C1: Dim,
     R2: Dim,
-    N: Scalar + Zero + One + ClosedAdd + ClosedMul,
-    SB: Storage<N, R2, C1>,
-    SA: ContiguousStorageMut<N, R1, C1> + Clone,
+    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    SB: Storage<T, R2, C1>,
+    SA: ContiguousStorageMut<T, R1, C1> + Clone,
     ShapeConstraint: AreMultipliable<R1, C1, R2, C1>,
     // TODO: this is too restrictive. See comments for the non-ref version.
-    DefaultAllocator: Allocator<N, R1, C1, Buffer = SA>,
+    DefaultAllocator: Allocator<T, R1, C1, Buffer = SA>,
 {
     #[inline]
-    fn mul_assign(&mut self, rhs: &'b Matrix<N, R2, C1, SB>) {
+    fn mul_assign(&mut self, rhs: &'b Matrix<T, R2, C1, SB>) {
         *self = &*self * rhs
     }
 }
 
 /// # Special multiplications.
-impl<N, R1: Dim, C1: Dim, SA> Matrix<N, R1, C1, SA>
+impl<T, R1: Dim, C1: Dim, SA> Matrix<T, R1, C1, SA>
 where
-    N: Scalar + Zero + One + ClosedAdd + ClosedMul,
-    SA: Storage<N, R1, C1>,
+    T: Scalar + Zero + One + ClosedAdd + ClosedMul,
+    SA: Storage<T, R1, C1>,
 {
     /// Equivalent to `self.transpose() * rhs`.
     #[inline]
-    pub fn tr_mul<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<N, R2, C2, SB>) -> MatrixMN<N, C1, C2>
+    pub fn tr_mul<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> OMatrix<T, C1, C2>
     where
-        SB: Storage<N, R2, C2>,
-        DefaultAllocator: Allocator<N, C1, C2>,
+        SB: Storage<T, R2, C2>,
+        DefaultAllocator: Allocator<T, C1, C2>,
         ShapeConstraint: SameNumberOfRows<R1, R2>,
     {
         let mut res = unsafe {
@@ -694,11 +692,11 @@ where
 
     /// Equivalent to `self.adjoint() * rhs`.
     #[inline]
-    pub fn ad_mul<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<N, R2, C2, SB>) -> MatrixMN<N, C1, C2>
+    pub fn ad_mul<R2: Dim, C2: Dim, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> OMatrix<T, C1, C2>
     where
-        N: SimdComplexField,
-        SB: Storage<N, R2, C2>,
-        DefaultAllocator: Allocator<N, C1, C2>,
+        T: SimdComplexField,
+        SB: Storage<T, R2, C2>,
+        DefaultAllocator: Allocator<T, C1, C2>,
         ShapeConstraint: SameNumberOfRows<R1, R2>,
     {
         let mut res = unsafe {
@@ -712,15 +710,15 @@ where
     #[inline(always)]
     fn xx_mul_to<R2: Dim, C2: Dim, SB, R3: Dim, C3: Dim, SC>(
         &self,
-        rhs: &Matrix<N, R2, C2, SB>,
-        out: &mut Matrix<N, R3, C3, SC>,
+        rhs: &Matrix<T, R2, C2, SB>,
+        out: &mut Matrix<T, R3, C3, SC>,
         dot: impl Fn(
-            &VectorSliceN<N, R1, SA::RStride, SA::CStride>,
-            &VectorSliceN<N, R2, SB::RStride, SB::CStride>,
-        ) -> N,
+            &VectorSlice<T, R1, SA::RStride, SA::CStride>,
+            &VectorSlice<T, R2, SB::RStride, SB::CStride>,
+        ) -> T,
     ) where
-        SB: Storage<N, R2, C2>,
-        SC: StorageMut<N, R3, C3>,
+        SB: Storage<T, R2, C2>,
+        SC: StorageMut<T, R3, C3>,
         ShapeConstraint: SameNumberOfRows<R1, R2> + DimEq<C1, R3> + DimEq<C2, C3>,
     {
         let (nrows1, ncols1) = self.shape();
@@ -759,11 +757,11 @@ where
     #[inline]
     pub fn tr_mul_to<R2: Dim, C2: Dim, SB, R3: Dim, C3: Dim, SC>(
         &self,
-        rhs: &Matrix<N, R2, C2, SB>,
-        out: &mut Matrix<N, R3, C3, SC>,
+        rhs: &Matrix<T, R2, C2, SB>,
+        out: &mut Matrix<T, R3, C3, SC>,
     ) where
-        SB: Storage<N, R2, C2>,
-        SC: StorageMut<N, R3, C3>,
+        SB: Storage<T, R2, C2>,
+        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))
@@ -774,12 +772,12 @@ where
     #[inline]
     pub fn ad_mul_to<R2: Dim, C2: Dim, SB, R3: Dim, C3: Dim, SC>(
         &self,
-        rhs: &Matrix<N, R2, C2, SB>,
-        out: &mut Matrix<N, R3, C3, SC>,
+        rhs: &Matrix<T, R2, C2, SB>,
+        out: &mut Matrix<T, R3, C3, SC>,
     ) where
-        N: SimdComplexField,
-        SB: Storage<N, R2, C2>,
-        SC: StorageMut<N, R3, C3>,
+        T: SimdComplexField,
+        SB: Storage<T, R2, C2>,
+        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))
@@ -789,30 +787,30 @@ where
     #[inline]
     pub fn mul_to<R2: Dim, C2: Dim, SB, R3: Dim, C3: Dim, SC>(
         &self,
-        rhs: &Matrix<N, R2, C2, SB>,
-        out: &mut Matrix<N, R3, C3, SC>,
+        rhs: &Matrix<T, R2, C2, SB>,
+        out: &mut Matrix<T, R3, C3, SC>,
     ) where
-        SB: Storage<N, R2, C2>,
-        SC: StorageMut<N, R3, C3>,
+        SB: Storage<T, R2, C2>,
+        SC: StorageMut<T, R3, C3>,
         ShapeConstraint: SameNumberOfRows<R3, R1>
             + SameNumberOfColumns<C3, C2>
             + AreMultipliable<R1, C1, R2, C2>,
     {
-        out.gemm(N::one(), self, rhs, N::zero());
+        out.gemm(T::one(), self, rhs, T::zero());
     }
 
     /// The kronecker product of two matrices (aka. tensor product of the corresponding linear
     /// maps).
     pub fn kronecker<R2: Dim, C2: Dim, SB>(
         &self,
-        rhs: &Matrix<N, R2, C2, SB>,
-    ) -> MatrixMN<N, DimProd<R1, R2>, DimProd<C1, C2>>
+        rhs: &Matrix<T, R2, C2, SB>,
+    ) -> OMatrix<T, DimProd<R1, R2>, DimProd<C1, C2>>
     where
-        N: ClosedMul,
+        T: ClosedMul,
         R1: DimMul<R2>,
         C1: DimMul<C2>,
-        SB: Storage<N, R2, C2>,
-        DefaultAllocator: Allocator<N, DimProd<R1, R2>, DimProd<C1, C2>>,
+        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();
@@ -845,22 +843,22 @@ where
     }
 }
 
-impl<N, D: DimName> iter::Product for MatrixN<N, D>
+impl<T, D: DimName> iter::Product for OMatrix<T, D, D>
 where
-    N: Scalar + Zero + One + ClosedMul + ClosedAdd,
-    DefaultAllocator: Allocator<N, D, D>,
+    T: Scalar + Zero + One + ClosedMul + ClosedAdd,
+    DefaultAllocator: Allocator<T, D, D>,
 {
-    fn product<I: Iterator<Item = MatrixN<N, D>>>(iter: I) -> MatrixN<N, D> {
+    fn product<I: Iterator<Item = OMatrix<T, D, D>>>(iter: I) -> OMatrix<T, D, D> {
         iter.fold(Matrix::one(), |acc, x| acc * x)
     }
 }
 
-impl<'a, N, D: DimName> iter::Product<&'a MatrixN<N, D>> for MatrixN<N, D>
+impl<'a, T, D: DimName> iter::Product<&'a OMatrix<T, D, D>> for OMatrix<T, D, D>
 where
-    N: Scalar + Zero + One + ClosedMul + ClosedAdd,
-    DefaultAllocator: Allocator<N, D, D>,
+    T: Scalar + Zero + One + ClosedMul + ClosedAdd,
+    DefaultAllocator: Allocator<T, D, D>,
 {
-    fn product<I: Iterator<Item = &'a MatrixN<N, D>>>(iter: I) -> MatrixN<N, D> {
+    fn product<I: Iterator<Item = &'a OMatrix<T, D, D>>>(iter: I) -> OMatrix<T, D, D> {
         iter.fold(Matrix::one(), |acc, x| acc * x)
     }
 }

src/base/properties.rs

@@ -9,7 +9,7 @@ use crate::base::dimension::{Dim, DimMin};
 use crate::base::storage::Storage;
 use crate::base::{DefaultAllocator, Matrix, Scalar, SquareMatrix};
 
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     /// The total number of elements of this matrix.
     ///
     /// # Examples:
@@ -52,10 +52,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// If the matrix is diagonal, this checks that diagonal elements (i.e. at coordinates `(i, i)`
     /// for i from `0` to `min(R, C)`) are equal one; and that all other elements are zero.
     #[inline]
-    pub fn is_identity(&self, eps: N::Epsilon) -> bool
+    pub fn is_identity(&self, eps: T::Epsilon) -> bool
     where
-        N: Zero + One + RelativeEq,
-        N::Epsilon: Copy,
+        T: Zero + One + RelativeEq,
+        T::Epsilon: Copy,
     {
         let (nrows, ncols) = self.shape();
         let d;
@@ -65,7 +65,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
             for i in d..nrows {
                 for j in 0..ncols {
-                    if !relative_eq!(self[(i, j)], N::zero(), epsilon = eps) {
+                    if !relative_eq!(self[(i, j)], T::zero(), epsilon = eps) {
                         return false;
                     }
                 }
@@ -76,7 +76,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
             for i in 0..nrows {
                 for j in d..ncols {
-                    if !relative_eq!(self[(i, j)], N::zero(), epsilon = eps) {
+                    if !relative_eq!(self[(i, j)], T::zero(), epsilon = eps) {
                         return false;
                     }
                 }
@@ -87,8 +87,8 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         for i in 1..d {
             for j in 0..i {
                 // TODO: use unsafe indexing.
-                if !relative_eq!(self[(i, j)], N::zero(), epsilon = eps)
-                    || !relative_eq!(self[(j, i)], N::zero(), epsilon = eps)
+                if !relative_eq!(self[(i, j)], T::zero(), epsilon = eps)
+                    || !relative_eq!(self[(j, i)], T::zero(), epsilon = eps)
                 {
                     return false;
                 }
@@ -97,7 +97,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
         // Diagonal elements of the sub-square matrix.
         for i in 0..d {
-            if !relative_eq!(self[(i, i)], N::one(), epsilon = eps) {
+            if !relative_eq!(self[(i, i)], T::one(), epsilon = eps) {
                 return false;
             }
         }
@@ -106,35 +106,35 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     }
 }
 
-impl<N: ComplexField, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: ComplexField, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     /// Checks that `Mᵀ × M = Id`.
     ///
     /// In this definition `Id` is approximately equal to the identity matrix with a relative error
     /// equal to `eps`.
     #[inline]
-    pub fn is_orthogonal(&self, eps: N::Epsilon) -> bool
+    pub fn is_orthogonal(&self, eps: T::Epsilon) -> bool
     where
-        N: Zero + One + ClosedAdd + ClosedMul + RelativeEq,
-        S: Storage<N, R, C>,
-        N::Epsilon: Copy,
-        DefaultAllocator: Allocator<N, R, C> + Allocator<N, C, C>,
+        T: Zero + One + ClosedAdd + ClosedMul + RelativeEq,
+        S: Storage<T, R, C>,
+        T::Epsilon: Copy,
+        DefaultAllocator: Allocator<T, R, C> + Allocator<T, C, C>,
     {
         (self.ad_mul(self)).is_identity(eps)
     }
 }
 
-impl<N: RealField, D: Dim, S: Storage<N, D, D>> SquareMatrix<N, D, S>
+impl<T: RealField, D: Dim, S: Storage<T, D, D>> SquareMatrix<T, D, S>
 where
-    DefaultAllocator: Allocator<N, D, D>,
+    DefaultAllocator: Allocator<T, D, D>,
 {
     /// Checks that this matrix is orthogonal and has a determinant equal to 1.
     #[inline]
-    pub fn is_special_orthogonal(&self, eps: N) -> bool
+    pub fn is_special_orthogonal(&self, eps: T) -> bool
     where
         D: DimMin<D, Output = D>,
         DefaultAllocator: Allocator<(usize, usize), D>,
     {
-        self.is_square() && self.is_orthogonal(eps) && self.determinant() > N::zero()
+        self.is_square() && self.is_orthogonal(eps) && self.determinant() > T::zero()
     }
 
     /// Returns `true` if this matrix is invertible.

src/base/scalar.rs

@@ -9,7 +9,7 @@ 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 `N::is::<f32>()`.
+    /// 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>()
     }

src/base/statistics.rs

@@ -1,23 +1,23 @@
 use crate::allocator::Allocator;
 use crate::storage::Storage;
-use crate::{Const, DefaultAllocator, Dim, Matrix, RowVectorN, Scalar, VectorN, VectorSliceN, U1};
+use crate::{Const, DefaultAllocator, Dim, Matrix, OVector, RowOVector, Scalar, VectorSlice, U1};
 use num::Zero;
 use simba::scalar::{ClosedAdd, Field, SupersetOf};
 
 /// # Folding on columns and rows
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<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]
     pub fn compress_rows(
         &self,
-        f: impl Fn(VectorSliceN<N, R, S::RStride, S::CStride>) -> N,
-    ) -> RowVectorN<N, C>
+        f: impl Fn(VectorSlice<T, R, S::RStride, S::CStride>) -> T,
+    ) -> RowOVector<T, C>
     where
-        DefaultAllocator: Allocator<N, U1, C>,
+        DefaultAllocator: Allocator<T, U1, C>,
     {
         let ncols = self.data.shape().1;
-        let mut res: RowVectorN<N, C> =
+        let mut res: RowOVector<T, C> =
             unsafe { crate::unimplemented_or_uninitialized_generic!(Const::<1>, ncols) };
 
         for i in 0..ncols.value() {
@@ -37,13 +37,13 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     #[inline]
     pub fn compress_rows_tr(
         &self,
-        f: impl Fn(VectorSliceN<N, R, S::RStride, S::CStride>) -> N,
-    ) -> VectorN<N, C>
+        f: impl Fn(VectorSlice<T, R, S::RStride, S::CStride>) -> T,
+    ) -> OVector<T, C>
     where
-        DefaultAllocator: Allocator<N, C>,
+        DefaultAllocator: Allocator<T, C>,
     {
         let ncols = self.data.shape().1;
-        let mut res: VectorN<N, C> =
+        let mut res: OVector<T, C> =
             unsafe { crate::unimplemented_or_uninitialized_generic!(ncols, Const::<1>) };
 
         for i in 0..ncols.value() {
@@ -60,11 +60,11 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     #[inline]
     pub fn compress_columns(
         &self,
-        init: VectorN<N, R>,
-        f: impl Fn(&mut VectorN<N, R>, VectorSliceN<N, R, S::RStride, S::CStride>),
-    ) -> VectorN<N, R>
+        init: OVector<T, R>,
+        f: impl Fn(&mut OVector<T, R>, VectorSlice<T, R, S::RStride, S::CStride>),
+    ) -> OVector<T, R>
     where
-        DefaultAllocator: Allocator<N, R>,
+        DefaultAllocator: Allocator<T, R>,
     {
         let mut res = init;
 
@@ -77,7 +77,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 }
 
 /// # Common statistics operations
-impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
     /*
      *
      * Sum computation.
@@ -95,11 +95,11 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(m.sum(), 21.0);
     /// ```
     #[inline]
-    pub fn sum(&self) -> N
+    pub fn sum(&self) -> T
     where
-        N: ClosedAdd + Zero,
+        T: ClosedAdd + Zero,
     {
-        self.iter().cloned().fold(N::zero(), |a, b| a + b)
+        self.iter().cloned().fold(T::zero(), |a, b| a + b)
     }
 
     /// The sum of all the rows of this matrix.
@@ -120,10 +120,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(mint.row_sum(), RowVector2::new(9,12));
     /// ```
     #[inline]
-    pub fn row_sum(&self) -> RowVectorN<N, C>
+    pub fn row_sum(&self) -> RowOVector<T, C>
     where
-        N: ClosedAdd + Zero,
-        DefaultAllocator: Allocator<N, U1, C>,
+        T: ClosedAdd + Zero,
+        DefaultAllocator: Allocator<T, U1, C>,
     {
         self.compress_rows(|col| col.sum())
     }
@@ -144,10 +144,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(mint.row_sum_tr(), Vector2::new(9,12));
     /// ```
     #[inline]
-    pub fn row_sum_tr(&self) -> VectorN<N, C>
+    pub fn row_sum_tr(&self) -> OVector<T, C>
     where
-        N: ClosedAdd + Zero,
-        DefaultAllocator: Allocator<N, C>,
+        T: ClosedAdd + Zero,
+        DefaultAllocator: Allocator<T, C>,
     {
         self.compress_rows_tr(|col| col.sum())
     }
@@ -168,13 +168,13 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(mint.column_sum(), Vector3::new(3,7,11));
     /// ```
     #[inline]
-    pub fn column_sum(&self) -> VectorN<N, R>
+    pub fn column_sum(&self) -> OVector<T, R>
     where
-        N: ClosedAdd + Zero,
-        DefaultAllocator: Allocator<N, R>,
+        T: ClosedAdd + Zero,
+        DefaultAllocator: Allocator<T, R>,
     {
         let nrows = self.data.shape().0;
-        self.compress_columns(VectorN::zeros_generic(nrows, Const::<1>), |out, col| {
+        self.compress_columns(OVector::zeros_generic(nrows, Const::<1>), |out, col| {
             *out += col;
         })
     }
@@ -197,17 +197,17 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_relative_eq!(m.variance(), 35.0 / 12.0, epsilon = 1.0e-8);
     /// ```
     #[inline]
-    pub fn variance(&self) -> N
+    pub fn variance(&self) -> T
     where
-        N: Field + SupersetOf<f64>,
+        T: Field + SupersetOf<f64>,
     {
         if self.is_empty() {
-            N::zero()
+            T::zero()
         } else {
-            let val = self.iter().cloned().fold((N::zero(), N::zero()), |a, b| {
+            let val = self.iter().cloned().fold((T::zero(), T::zero()), |a, b| {
                 (a.0 + b.inlined_clone() * b.inlined_clone(), a.1 + b)
             });
-            let denom = N::one() / crate::convert::<_, N>(self.len() as f64);
+            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
         }
@@ -226,10 +226,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(m.row_variance(), RowVector3::new(2.25, 2.25, 2.25));
     /// ```
     #[inline]
-    pub fn row_variance(&self) -> RowVectorN<N, C>
+    pub fn row_variance(&self) -> RowOVector<T, C>
     where
-        N: Field + SupersetOf<f64>,
-        DefaultAllocator: Allocator<N, U1, C>,
+        T: Field + SupersetOf<f64>,
+        DefaultAllocator: Allocator<T, U1, C>,
     {
         self.compress_rows(|col| col.variance())
     }
@@ -246,10 +246,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(m.row_variance_tr(), Vector3::new(2.25, 2.25, 2.25));
     /// ```
     #[inline]
-    pub fn row_variance_tr(&self) -> VectorN<N, C>
+    pub fn row_variance_tr(&self) -> OVector<T, C>
     where
-        N: Field + SupersetOf<f64>,
-        DefaultAllocator: Allocator<N, C>,
+        T: Field + SupersetOf<f64>,
+        DefaultAllocator: Allocator<T, C>,
     {
         self.compress_rows_tr(|col| col.variance())
     }
@@ -267,17 +267,17 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_relative_eq!(m.column_variance(), Vector2::new(2.0 / 3.0, 2.0 / 3.0), epsilon = 1.0e-8);
     /// ```
     #[inline]
-    pub fn column_variance(&self) -> VectorN<N, R>
+    pub fn column_variance(&self) -> OVector<T, R>
     where
-        N: Field + SupersetOf<f64>,
-        DefaultAllocator: Allocator<N, R>,
+        T: Field + SupersetOf<f64>,
+        DefaultAllocator: Allocator<T, R>,
     {
         let (nrows, ncols) = self.data.shape();
 
         let mut mean = self.column_mean();
         mean.apply(|e| -(e.inlined_clone() * e));
 
-        let denom = N::one() / crate::convert::<_, N>(ncols.value() as f64);
+        let denom = T::one() / crate::convert::<_, T>(ncols.value() as f64);
         self.compress_columns(mean, |out, col| {
             for i in 0..nrows.value() {
                 unsafe {
@@ -306,12 +306,12 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(m.mean(), 3.5);
     /// ```
     #[inline]
-    pub fn mean(&self) -> N
+    pub fn mean(&self) -> T
     where
-        N: Field + SupersetOf<f64>,
+        T: Field + SupersetOf<f64>,
     {
         if self.is_empty() {
-            N::zero()
+            T::zero()
         } else {
             self.sum() / crate::convert(self.len() as f64)
         }
@@ -331,10 +331,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(m.row_mean(), RowVector3::new(2.5, 3.5, 4.5));
     /// ```
     #[inline]
-    pub fn row_mean(&self) -> RowVectorN<N, C>
+    pub fn row_mean(&self) -> RowOVector<T, C>
     where
-        N: Field + SupersetOf<f64>,
-        DefaultAllocator: Allocator<N, U1, C>,
+        T: Field + SupersetOf<f64>,
+        DefaultAllocator: Allocator<T, U1, C>,
     {
         self.compress_rows(|col| col.mean())
     }
@@ -351,10 +351,10 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(m.row_mean_tr(), Vector3::new(2.5, 3.5, 4.5));
     /// ```
     #[inline]
-    pub fn row_mean_tr(&self) -> VectorN<N, C>
+    pub fn row_mean_tr(&self) -> OVector<T, C>
     where
-        N: Field + SupersetOf<f64>,
-        DefaultAllocator: Allocator<N, C>,
+        T: Field + SupersetOf<f64>,
+        DefaultAllocator: Allocator<T, C>,
     {
         self.compress_rows_tr(|col| col.mean())
     }
@@ -371,15 +371,15 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// assert_eq!(m.column_mean(), Vector2::new(2.0, 5.0));
     /// ```
     #[inline]
-    pub fn column_mean(&self) -> VectorN<N, R>
+    pub fn column_mean(&self) -> OVector<T, R>
     where
-        N: Field + SupersetOf<f64>,
-        DefaultAllocator: Allocator<N, R>,
+        T: Field + SupersetOf<f64>,
+        DefaultAllocator: Allocator<T, R>,
     {
         let (nrows, ncols) = self.data.shape();
-        let denom = N::one() / crate::convert::<_, N>(ncols.value() as f64);
-        self.compress_columns(VectorN::zeros_generic(nrows, Const::<1>), |out, col| {
-            out.axpy(denom.inlined_clone(), &col, N::one())
+        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())
         })
     }
 }

src/base/storage.rs

@@ -12,20 +12,20 @@ use crate::base::Scalar;
  * Aliases for allocation results.
  */
 /// The data storage for the sum of two matrices with dimensions `(R1, C1)` and `(R2, C2)`.
-pub type SameShapeStorage<N, R1, C1, R2, C2> =
-    <DefaultAllocator as Allocator<N, SameShapeR<R1, R2>, SameShapeC<C1, C2>>>::Buffer;
+pub type SameShapeStorage<T, R1, C1, R2, C2> =
+    <DefaultAllocator as Allocator<T, SameShapeR<R1, R2>, SameShapeC<C1, C2>>>::Buffer;
 
 // TODO: better name than Owned ?
 /// The owned data storage that can be allocated from `S`.
-pub type Owned<N, R, C = U1> = <DefaultAllocator as Allocator<N, R, C>>::Buffer;
+pub type Owned<T, R, C = U1> = <DefaultAllocator as Allocator<T, R, C>>::Buffer;
 
 /// The row-stride of the owned data storage for a buffer of dimension `(R, C)`.
-pub type RStride<N, R, C = U1> =
-    <<DefaultAllocator as Allocator<N, R, C>>::Buffer as Storage<N, R, C>>::RStride;
+pub type RStride<T, R, C = U1> =
+    <<DefaultAllocator as Allocator<T, R, C>>::Buffer as Storage<T, R, C>>::RStride;
 
 /// The column-stride of the owned data storage for a buffer of dimension `(R, C)`.
-pub type CStride<N, R, C = U1> =
-    <<DefaultAllocator as Allocator<N, R, C>>::Buffer as Storage<N, R, C>>::CStride;
+pub type CStride<T, R, C = U1> =
+    <<DefaultAllocator as Allocator<T, R, C>>::Buffer as Storage<T, R, C>>::CStride;
 
 /// The trait shared by all matrix data storage.
 ///
@@ -36,7 +36,7 @@ pub type CStride<N, R, C = U1> =
 /// 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<N: Scalar, R: Dim, C: Dim = U1>: Debug + Sized {
+pub unsafe trait Storage<T: Scalar, R: Dim, C: Dim = U1>: Debug + Sized {
     /// The static stride of this storage's rows.
     type RStride: Dim;
 
@@ -44,7 +44,7 @@ pub unsafe trait Storage<N: Scalar, R: Dim, C: Dim = U1>: Debug + Sized {
     type CStride: Dim;
 
     /// The matrix data pointer.
-    fn ptr(&self) -> *const N;
+    fn ptr(&self) -> *const T;
 
     /// The dimension of the matrix at run-time. Arr length of zero indicates the additive identity
     /// element of any dimension. Must be equal to `Self::dimension()` if it is not `None`.
@@ -71,25 +71,25 @@ pub unsafe trait Storage<N: Scalar, R: Dim, C: Dim = U1>: Debug + Sized {
 
     /// Gets the address of the i-th matrix component without performing bound-checking.
     #[inline]
-    unsafe fn get_address_unchecked_linear(&self, i: usize) -> *const N {
+    unsafe fn get_address_unchecked_linear(&self, i: usize) -> *const T {
         self.ptr().wrapping_add(i)
     }
 
     /// Gets the address of the i-th matrix component without performing bound-checking.
     #[inline]
-    unsafe fn get_address_unchecked(&self, irow: usize, icol: usize) -> *const N {
+    unsafe fn get_address_unchecked(&self, irow: usize, icol: usize) -> *const T {
         self.get_address_unchecked_linear(self.linear_index(irow, icol))
     }
 
     /// Retrieves a reference to the i-th element without bound-checking.
     #[inline]
-    unsafe fn get_unchecked_linear(&self, i: usize) -> &N {
+    unsafe fn get_unchecked_linear(&self, i: usize) -> &T {
         &*self.get_address_unchecked_linear(i)
     }
 
     /// Retrieves a reference to the i-th element without bound-checking.
     #[inline]
-    unsafe fn get_unchecked(&self, irow: usize, icol: usize) -> &N {
+    unsafe fn get_unchecked(&self, irow: usize, icol: usize) -> &T {
         self.get_unchecked_linear(self.linear_index(irow, icol))
     }
 
@@ -99,17 +99,17 @@ pub unsafe trait Storage<N: Scalar, R: Dim, C: Dim = U1>: Debug + Sized {
     /// Retrieves the data buffer as a contiguous slice.
     ///
     /// The matrix components may not be stored in a contiguous way, depending on the strides.
-    fn as_slice(&self) -> &[N];
+    fn as_slice(&self) -> &[T];
 
     /// Builds a matrix data storage that does not contain any reference.
-    fn into_owned(self) -> Owned<N, R, C>
+    fn into_owned(self) -> Owned<T, R, C>
     where
-        DefaultAllocator: Allocator<N, R, C>;
+        DefaultAllocator: Allocator<T, R, C>;
 
     /// Clones this data storage to one that does not contain any reference.
-    fn clone_owned(&self) -> Owned<N, R, C>
+    fn clone_owned(&self) -> Owned<T, R, C>
     where
-        DefaultAllocator: Allocator<N, R, C>;
+        DefaultAllocator: Allocator<T, R, C>;
 }
 
 /// Trait implemented by matrix data storage that can provide a mutable access to its elements.
@@ -117,31 +117,31 @@ pub unsafe trait Storage<N: Scalar, R: Dim, C: Dim = U1>: Debug + Sized {
 /// 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<N: Scalar, R: Dim, C: Dim = U1>: Storage<N, R, C> {
+pub unsafe trait StorageMut<T: Scalar, R: Dim, C: Dim = U1>: Storage<T, R, C> {
     /// The matrix mutable data pointer.
-    fn ptr_mut(&mut self) -> *mut N;
+    fn ptr_mut(&mut self) -> *mut T;
 
     /// Gets the mutable address of the i-th matrix component without performing bound-checking.
     #[inline]
-    unsafe fn get_address_unchecked_linear_mut(&mut self, i: usize) -> *mut N {
+    unsafe fn get_address_unchecked_linear_mut(&mut self, i: usize) -> *mut T {
         self.ptr_mut().wrapping_add(i)
     }
 
     /// Gets the mutable address of the i-th matrix component without performing bound-checking.
     #[inline]
-    unsafe fn get_address_unchecked_mut(&mut self, irow: usize, icol: usize) -> *mut N {
+    unsafe fn get_address_unchecked_mut(&mut self, irow: usize, icol: usize) -> *mut T {
         let lid = self.linear_index(irow, icol);
         self.get_address_unchecked_linear_mut(lid)
     }
 
     /// Retrieves a mutable reference to the i-th element without bound-checking.
-    unsafe fn get_unchecked_linear_mut(&mut self, i: usize) -> &mut N {
+    unsafe fn get_unchecked_linear_mut(&mut self, i: usize) -> &mut T {
         &mut *self.get_address_unchecked_linear_mut(i)
     }
 
     /// Retrieves a mutable reference to the element at `(irow, icol)` without bound-checking.
     #[inline]
-    unsafe fn get_unchecked_mut(&mut self, irow: usize, icol: usize) -> &mut N {
+    unsafe fn get_unchecked_mut(&mut self, irow: usize, icol: usize) -> &mut T {
         &mut *self.get_address_unchecked_mut(irow, icol)
     }
 
@@ -166,7 +166,7 @@ pub unsafe trait StorageMut<N: Scalar, R: Dim, C: Dim = U1>: Storage<N, R, C> {
     /// Retrieves the mutable data buffer as a contiguous slice.
     ///
     /// Matrix components may not be contiguous, depending on its strides.
-    fn as_mut_slice(&mut self) -> &mut [N];
+    fn as_mut_slice(&mut self) -> &mut [T];
 }
 
 /// A matrix storage that is stored contiguously in memory.
@@ -174,8 +174,8 @@ pub unsafe trait StorageMut<N: Scalar, R: Dim, C: Dim = U1>: Storage<N, R, C> {
 /// 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<N: Scalar, R: Dim, C: Dim = U1>:
-    Storage<N, R, C>
+pub unsafe trait ContiguousStorage<T: Scalar, R: Dim, C: Dim = U1>:
+    Storage<T, R, C>
 {
 }
 
@@ -184,22 +184,22 @@ pub unsafe trait ContiguousStorage<N: Scalar, R: Dim, C: Dim = U1>:
 /// 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<N: Scalar, R: Dim, C: Dim = U1>:
-    ContiguousStorage<N, R, C> + StorageMut<N, R, C>
+pub unsafe trait ContiguousStorageMut<T: Scalar, R: Dim, C: Dim = U1>:
+    ContiguousStorage<T, R, C> + StorageMut<T, R, C>
 {
 }
 
 /// A matrix storage that can be reshaped in-place.
-pub trait ReshapableStorage<N, R1, C1, R2, C2>: Storage<N, R1, C1>
+pub trait ReshapableStorage<T, R1, C1, R2, C2>: Storage<T, R1, C1>
 where
-    N: Scalar,
+    T: Scalar,
     R1: Dim,
     C1: Dim,
     R2: Dim,
     C2: Dim,
 {
     /// The reshaped storage type.
-    type Output: Storage<N, R2, C2>;
+    type Output: Storage<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

@@ -8,7 +8,7 @@ macro_rules! impl_swizzle {
             $(
                 /// Builds a new vector from components of `self`.
                 #[inline]
-                pub fn $name(&self) -> $Result<N>
+                pub fn $name(&self) -> $Result<T>
                 where D::Typenum: Cmp<typenum::$BaseDim, Output=Greater> {
                     $Result::new($(self[$i].inlined_clone()),*)
                 }
@@ -18,7 +18,7 @@ macro_rules! impl_swizzle {
 }
 
 /// # Swizzling
-impl<N: Scalar, D, S: Storage<N, D>> Vector<N, D, S>
+impl<T: Scalar, D, S: Storage<T, D>> Vector<T, D, S>
 where
     D: DimName + ToTypenum,
 {

src/base/unit.rs

@@ -12,7 +12,7 @@ use abomonation::Abomonation;
 use crate::allocator::Allocator;
 use crate::base::DefaultAllocator;
 use crate::storage::Storage;
-use crate::{Dim, Matrix, MatrixMN, RealField, Scalar, SimdComplexField, SimdRealField};
+use crate::{Dim, Matrix, OMatrix, RealField, Scalar, SimdComplexField, SimdRealField};
 
 /// A wrapper that ensures the underlying algebraic entity has a unit norm.
 ///
@@ -71,12 +71,12 @@ impl<T: Abomonation> Abomonation for Unit<T> {
     }
 }
 
-impl<N, R, C, S> PartialEq for Unit<Matrix<N, R, C, S>>
+impl<T, R, C, S> PartialEq for Unit<Matrix<T, R, C, S>>
 where
-    N: Scalar + PartialEq,
+    T: Scalar + PartialEq,
     R: Dim,
     C: Dim,
-    S: Storage<N, R, C>,
+    S: Storage<T, R, C>,
 {
     #[inline]
     fn eq(&self, rhs: &Self) -> bool {
@@ -84,12 +84,12 @@ where
     }
 }
 
-impl<N, R, C, S> Eq for Unit<Matrix<N, R, C, S>>
+impl<T, R, C, S> Eq for Unit<Matrix<T, R, C, S>>
 where
-    N: Scalar + Eq,
+    T: Scalar + Eq,
     R: Dim,
     C: Dim,
-    S: Storage<N, R, C>,
+    S: Storage<T, R, C>,
 {
 }
 
@@ -298,32 +298,32 @@ impl<T> Deref for Unit<T> {
 // NOTE: we can't use a generic implementation for `Unit<T>` because
 // num_complex::Complex does not implement `From[Complex<...>...]` (and can't
 // because of the orphan rules).
-impl<N: Scalar + simba::simd::PrimitiveSimdValue, R: Dim, C: Dim>
-    From<[Unit<MatrixMN<N::Element, R, C>>; 2]> for Unit<MatrixMN<N, R, C>>
+impl<T: Scalar + simba::simd::PrimitiveSimdValue, R: Dim, C: Dim>
+    From<[Unit<OMatrix<T::Element, R, C>>; 2]> for Unit<OMatrix<T, R, C>>
 where
-    N: From<[<N as simba::simd::SimdValue>::Element; 2]>,
-    N::Element: Scalar,
-    DefaultAllocator: Allocator<N, R, C> + Allocator<N::Element, R, C>,
+    T: From<[<T as simba::simd::SimdValue>::Element; 2]>,
+    T::Element: Scalar,
+    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
 {
     #[inline]
-    fn from(arr: [Unit<MatrixMN<N::Element, R, C>>; 2]) -> Self {
-        Self::new_unchecked(MatrixMN::from([
+    fn from(arr: [Unit<OMatrix<T::Element, R, C>>; 2]) -> Self {
+        Self::new_unchecked(OMatrix::from([
             arr[0].clone().into_inner(),
             arr[1].clone().into_inner(),
         ]))
     }
 }
 
-impl<N: Scalar + simba::simd::PrimitiveSimdValue, R: Dim, C: Dim>
-    From<[Unit<MatrixMN<N::Element, R, C>>; 4]> for Unit<MatrixMN<N, R, C>>
+impl<T: Scalar + simba::simd::PrimitiveSimdValue, R: Dim, C: Dim>
+    From<[Unit<OMatrix<T::Element, R, C>>; 4]> for Unit<OMatrix<T, R, C>>
 where
-    N: From<[<N as simba::simd::SimdValue>::Element; 4]>,
-    N::Element: Scalar,
-    DefaultAllocator: Allocator<N, R, C> + Allocator<N::Element, R, C>,
+    T: From<[<T as simba::simd::SimdValue>::Element; 4]>,
+    T::Element: Scalar,
+    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
 {
     #[inline]
-    fn from(arr: [Unit<MatrixMN<N::Element, R, C>>; 4]) -> Self {
-        Self::new_unchecked(MatrixMN::from([
+    fn from(arr: [Unit<OMatrix<T::Element, R, C>>; 4]) -> Self {
+        Self::new_unchecked(OMatrix::from([
             arr[0].clone().into_inner(),
             arr[1].clone().into_inner(),
             arr[2].clone().into_inner(),
@@ -332,16 +332,16 @@ where
     }
 }
 
-impl<N: Scalar + simba::simd::PrimitiveSimdValue, R: Dim, C: Dim>
-    From<[Unit<MatrixMN<N::Element, R, C>>; 8]> for Unit<MatrixMN<N, R, C>>
+impl<T: Scalar + simba::simd::PrimitiveSimdValue, R: Dim, C: Dim>
+    From<[Unit<OMatrix<T::Element, R, C>>; 8]> for Unit<OMatrix<T, R, C>>
 where
-    N: From<[<N as simba::simd::SimdValue>::Element; 8]>,
-    N::Element: Scalar,
-    DefaultAllocator: Allocator<N, R, C> + Allocator<N::Element, R, C>,
+    T: From<[<T as simba::simd::SimdValue>::Element; 8]>,
+    T::Element: Scalar,
+    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
 {
     #[inline]
-    fn from(arr: [Unit<MatrixMN<N::Element, R, C>>; 8]) -> Self {
-        Self::new_unchecked(MatrixMN::from([
+    fn from(arr: [Unit<OMatrix<T::Element, R, C>>; 8]) -> Self {
+        Self::new_unchecked(OMatrix::from([
             arr[0].clone().into_inner(),
             arr[1].clone().into_inner(),
             arr[2].clone().into_inner(),
@@ -354,16 +354,16 @@ where
     }
 }
 
-impl<N: Scalar + simba::simd::PrimitiveSimdValue, R: Dim, C: Dim>
-    From<[Unit<MatrixMN<N::Element, R, C>>; 16]> for Unit<MatrixMN<N, R, C>>
+impl<T: Scalar + simba::simd::PrimitiveSimdValue, R: Dim, C: Dim>
+    From<[Unit<OMatrix<T::Element, R, C>>; 16]> for Unit<OMatrix<T, R, C>>
 where
-    N: From<[<N as simba::simd::SimdValue>::Element; 16]>,
-    N::Element: Scalar,
-    DefaultAllocator: Allocator<N, R, C> + Allocator<N::Element, R, C>,
+    T: From<[<T as simba::simd::SimdValue>::Element; 16]>,
+    T::Element: Scalar,
+    DefaultAllocator: Allocator<T, R, C> + Allocator<T::Element, R, C>,
 {
     #[inline]
-    fn from(arr: [Unit<MatrixMN<N::Element, R, C>>; 16]) -> Self {
-        Self::new_unchecked(MatrixMN::from([
+    fn from(arr: [Unit<OMatrix<T::Element, R, C>>; 16]) -> Self {
+        Self::new_unchecked(OMatrix::from([
             arr[0].clone().into_inner(),
             arr[1].clone().into_inner(),
             arr[2].clone().into_inner(),

src/base/vec_storage.rs

@@ -25,20 +25,20 @@ use abomonation::Abomonation;
 #[repr(C)]
 #[derive(Eq, Debug, Clone, PartialEq)]
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
-pub struct VecStorage<N, R: Dim, C: Dim> {
-    data: Vec<N>,
+pub struct VecStorage<T, R: Dim, C: Dim> {
+    data: Vec<T>,
     nrows: R,
     ncols: C,
 }
 
 #[deprecated(note = "renamed to `VecStorage`")]
 /// Renamed to [VecStorage].
-pub type MatrixVec<N, R, C> = VecStorage<N, R, C>;
+pub type MatrixVec<T, R, C> = VecStorage<T, R, C>;
 
-impl<N, R: Dim, C: Dim> VecStorage<N, R, C> {
+impl<T, R: Dim, C: Dim> VecStorage<T, R, C> {
     /// Creates a new dynamic matrix data storage from the given vector and shape.
     #[inline]
-    pub fn new(nrows: R, ncols: C, data: Vec<N>) -> Self {
+    pub fn new(nrows: R, ncols: C, data: Vec<T>) -> Self {
         assert!(
             nrows.value() * ncols.value() == data.len(),
             "Data storage buffer dimension mismatch."
@@ -48,7 +48,7 @@ impl<N, R: Dim, C: Dim> VecStorage<N, R, C> {
 
     /// The underlying data storage.
     #[inline]
-    pub fn as_vec(&self) -> &Vec<N> {
+    pub fn as_vec(&self) -> &Vec<T> {
         &self.data
     }
 
@@ -57,7 +57,7 @@ impl<N, R: Dim, C: Dim> VecStorage<N, R, C> {
     /// This is unsafe because this may cause UB if the size of the vector is changed
     /// by the user.
     #[inline]
-    pub unsafe fn as_vec_mut(&mut self) -> &mut Vec<N> {
+    pub unsafe fn as_vec_mut(&mut self) -> &mut Vec<T> {
         &mut self.data
     }
 
@@ -66,7 +66,7 @@ impl<N, R: Dim, C: Dim> VecStorage<N, R, C> {
     /// If `sz` is larger than the current size, additional elements are uninitialized.
     /// If `sz` is smaller than the current size, additional elements are truncated.
     #[inline]
-    pub unsafe fn resize(mut self, sz: usize) -> Vec<N> {
+    pub unsafe fn resize(mut self, sz: usize) -> Vec<T> {
         let len = self.len();
 
         if sz < len {
@@ -93,8 +93,8 @@ impl<N, R: Dim, C: Dim> VecStorage<N, R, C> {
     }
 }
 
-impl<N, R: Dim, C: Dim> Into<Vec<N>> for VecStorage<N, R, C> {
-    fn into(self) -> Vec<N> {
+impl<T, R: Dim, C: Dim> Into<Vec<T>> for VecStorage<T, R, C> {
+    fn into(self) -> Vec<T> {
         self.data
     }
 }
@@ -105,15 +105,15 @@ impl<N, R: Dim, C: Dim> Into<Vec<N>> for VecStorage<N, R, C> {
  * Dynamic − Dynamic
  *
  */
-unsafe impl<N: Scalar, C: Dim> Storage<N, Dynamic, C> for VecStorage<N, Dynamic, C>
+unsafe impl<T: Scalar, C: Dim> Storage<T, Dynamic, C> for VecStorage<T, Dynamic, C>
 where
-    DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>,
+    DefaultAllocator: Allocator<T, Dynamic, C, Buffer = Self>,
 {
     type RStride = U1;
     type CStride = Dynamic;
 
     #[inline]
-    fn ptr(&self) -> *const N {
+    fn ptr(&self) -> *const T {
         self.data.as_ptr()
     }
 
@@ -133,36 +133,36 @@ where
     }
 
     #[inline]
-    fn into_owned(self) -> Owned<N, Dynamic, C>
+    fn into_owned(self) -> Owned<T, Dynamic, C>
     where
-        DefaultAllocator: Allocator<N, Dynamic, C>,
+        DefaultAllocator: Allocator<T, Dynamic, C>,
     {
         self
     }
 
     #[inline]
-    fn clone_owned(&self) -> Owned<N, Dynamic, C>
+    fn clone_owned(&self) -> Owned<T, Dynamic, C>
     where
-        DefaultAllocator: Allocator<N, Dynamic, C>,
+        DefaultAllocator: Allocator<T, Dynamic, C>,
     {
         self.clone()
     }
 
     #[inline]
-    fn as_slice(&self) -> &[N] {
+    fn as_slice(&self) -> &[T] {
         &self.data
     }
 }
 
-unsafe impl<N: Scalar, R: DimName> Storage<N, R, Dynamic> for VecStorage<N, R, Dynamic>
+unsafe impl<T: Scalar, R: DimName> Storage<T, R, Dynamic> for VecStorage<T, R, Dynamic>
 where
-    DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>,
+    DefaultAllocator: Allocator<T, R, Dynamic, Buffer = Self>,
 {
     type RStride = U1;
     type CStride = R;
 
     #[inline]
-    fn ptr(&self) -> *const N {
+    fn ptr(&self) -> *const T {
         self.data.as_ptr()
     }
 
@@ -182,23 +182,23 @@ where
     }
 
     #[inline]
-    fn into_owned(self) -> Owned<N, R, Dynamic>
+    fn into_owned(self) -> Owned<T, R, Dynamic>
     where
-        DefaultAllocator: Allocator<N, R, Dynamic>,
+        DefaultAllocator: Allocator<T, R, Dynamic>,
     {
         self
     }
 
     #[inline]
-    fn clone_owned(&self) -> Owned<N, R, Dynamic>
+    fn clone_owned(&self) -> Owned<T, R, Dynamic>
     where
-        DefaultAllocator: Allocator<N, R, Dynamic>,
+        DefaultAllocator: Allocator<T, R, Dynamic>,
     {
         self.clone()
     }
 
     #[inline]
-    fn as_slice(&self) -> &[N] {
+    fn as_slice(&self) -> &[T] {
         &self.data
     }
 }
@@ -208,38 +208,38 @@ where
  * StorageMut, ContiguousStorage.
  *
  */
-unsafe impl<N: Scalar, C: Dim> StorageMut<N, Dynamic, C> for VecStorage<N, Dynamic, C>
+unsafe impl<T: Scalar, C: Dim> StorageMut<T, Dynamic, C> for VecStorage<T, Dynamic, C>
 where
-    DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>,
+    DefaultAllocator: Allocator<T, Dynamic, C, Buffer = Self>,
 {
     #[inline]
-    fn ptr_mut(&mut self) -> *mut N {
+    fn ptr_mut(&mut self) -> *mut T {
         self.data.as_mut_ptr()
     }
 
     #[inline]
-    fn as_mut_slice(&mut self) -> &mut [N] {
+    fn as_mut_slice(&mut self) -> &mut [T] {
         &mut self.data[..]
     }
 }
 
-unsafe impl<N: Scalar, C: Dim> ContiguousStorage<N, Dynamic, C> for VecStorage<N, Dynamic, C> where
-    DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>
+unsafe impl<T: Scalar, C: Dim> ContiguousStorage<T, Dynamic, C> for VecStorage<T, Dynamic, C> where
+    DefaultAllocator: Allocator<T, Dynamic, C, Buffer = Self>
 {
 }
 
-unsafe impl<N: Scalar, C: Dim> ContiguousStorageMut<N, Dynamic, C> for VecStorage<N, Dynamic, C> where
-    DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>
+unsafe impl<T: Scalar, C: Dim> ContiguousStorageMut<T, Dynamic, C> for VecStorage<T, Dynamic, C> where
+    DefaultAllocator: Allocator<T, Dynamic, C, Buffer = Self>
 {
 }
 
-impl<N, C1, C2> ReshapableStorage<N, Dynamic, C1, Dynamic, C2> for VecStorage<N, Dynamic, C1>
+impl<T, C1, C2> ReshapableStorage<T, Dynamic, C1, Dynamic, C2> for VecStorage<T, Dynamic, C1>
 where
-    N: Scalar,
+    T: Scalar,
     C1: Dim,
     C2: Dim,
 {
-    type Output = VecStorage<N, Dynamic, C2>;
+    type Output = VecStorage<T, Dynamic, C2>;
 
     fn reshape_generic(self, nrows: Dynamic, ncols: C2) -> Self::Output {
         assert_eq!(nrows.value() * ncols.value(), self.data.len());
@@ -251,13 +251,13 @@ where
     }
 }
 
-impl<N, C1, R2> ReshapableStorage<N, Dynamic, C1, R2, Dynamic> for VecStorage<N, Dynamic, C1>
+impl<T, C1, R2> ReshapableStorage<T, Dynamic, C1, R2, Dynamic> for VecStorage<T, Dynamic, C1>
 where
-    N: Scalar,
+    T: Scalar,
     C1: Dim,
     R2: DimName,
 {
-    type Output = VecStorage<N, R2, Dynamic>;
+    type Output = VecStorage<T, R2, Dynamic>;
 
     fn reshape_generic(self, nrows: R2, ncols: Dynamic) -> Self::Output {
         assert_eq!(nrows.value() * ncols.value(), self.data.len());
@@ -269,28 +269,28 @@ where
     }
 }
 
-unsafe impl<N: Scalar, R: DimName> StorageMut<N, R, Dynamic> for VecStorage<N, R, Dynamic>
+unsafe impl<T: Scalar, R: DimName> StorageMut<T, R, Dynamic> for VecStorage<T, R, Dynamic>
 where
-    DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>,
+    DefaultAllocator: Allocator<T, R, Dynamic, Buffer = Self>,
 {
     #[inline]
-    fn ptr_mut(&mut self) -> *mut N {
+    fn ptr_mut(&mut self) -> *mut T {
         self.data.as_mut_ptr()
     }
 
     #[inline]
-    fn as_mut_slice(&mut self) -> &mut [N] {
+    fn as_mut_slice(&mut self) -> &mut [T] {
         &mut self.data[..]
     }
 }
 
-impl<N, R1, C2> ReshapableStorage<N, R1, Dynamic, Dynamic, C2> for VecStorage<N, R1, Dynamic>
+impl<T, R1, C2> ReshapableStorage<T, R1, Dynamic, Dynamic, C2> for VecStorage<T, R1, Dynamic>
 where
-    N: Scalar,
+    T: Scalar,
     R1: DimName,
     C2: Dim,
 {
-    type Output = VecStorage<N, Dynamic, C2>;
+    type Output = VecStorage<T, Dynamic, C2>;
 
     fn reshape_generic(self, nrows: Dynamic, ncols: C2) -> Self::Output {
         assert_eq!(nrows.value() * ncols.value(), self.data.len());
@@ -302,13 +302,13 @@ where
     }
 }
 
-impl<N, R1, R2> ReshapableStorage<N, R1, Dynamic, R2, Dynamic> for VecStorage<N, R1, Dynamic>
+impl<T, R1, R2> ReshapableStorage<T, R1, Dynamic, R2, Dynamic> for VecStorage<T, R1, Dynamic>
 where
-    N: Scalar,
+    T: Scalar,
     R1: DimName,
     R2: DimName,
 {
-    type Output = VecStorage<N, R2, Dynamic>;
+    type Output = VecStorage<T, R2, Dynamic>;
 
     fn reshape_generic(self, nrows: R2, ncols: Dynamic) -> Self::Output {
         assert_eq!(nrows.value() * ncols.value(), self.data.len());
@@ -321,7 +321,7 @@ where
 }
 
 #[cfg(feature = "abomonation-serialize")]
-impl<N: Abomonation, R: Dim, C: Dim> Abomonation for VecStorage<N, R, C> {
+impl<T: Abomonation, R: Dim, C: Dim> Abomonation for VecStorage<T, R, C> {
     unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
         self.data.entomb(writer)
     }
@@ -335,17 +335,17 @@ impl<N: Abomonation, R: Dim, C: Dim> Abomonation for VecStorage<N, R, C> {
     }
 }
 
-unsafe impl<N: Scalar, R: DimName> ContiguousStorage<N, R, Dynamic> for VecStorage<N, R, Dynamic> where
-    DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>
+unsafe impl<T: Scalar, R: DimName> ContiguousStorage<T, R, Dynamic> for VecStorage<T, R, Dynamic> where
+    DefaultAllocator: Allocator<T, R, Dynamic, Buffer = Self>
 {
 }
 
-unsafe impl<N: Scalar, R: DimName> ContiguousStorageMut<N, R, Dynamic> for VecStorage<N, R, Dynamic> where
-    DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>
+unsafe impl<T: Scalar, R: DimName> ContiguousStorageMut<T, R, Dynamic> for VecStorage<T, R, Dynamic> where
+    DefaultAllocator: Allocator<T, R, Dynamic, Buffer = Self>
 {
 }
 
-impl<N, R: Dim> Extend<N> for VecStorage<N, R, Dynamic> {
+impl<T, R: Dim> Extend<T> for VecStorage<T, R, Dynamic> {
     /// Extends the number of columns of the `VecStorage` with elements
     /// from the given iterator.
     ///
@@ -353,7 +353,7 @@ impl<N, R: Dim> Extend<N> for VecStorage<N, R, Dynamic> {
     /// This function panics if the number of elements yielded by the
     /// given iterator is not a multiple of the number of rows of the
     /// `VecStorage`.
-    fn extend<I: IntoIterator<Item = N>>(&mut self, iter: I) {
+    fn extend<I: IntoIterator<Item = T>>(&mut self, iter: I) {
         self.data.extend(iter);
         self.ncols = Dynamic::new(self.data.len() / self.nrows.value());
         assert!(self.data.len() % self.nrows.value() == 0,
@@ -361,7 +361,7 @@ impl<N, R: Dim> Extend<N> for VecStorage<N, R, Dynamic> {
     }
 }
 
-impl<'a, N: 'a + Copy, R: Dim> Extend<&'a N> for VecStorage<N, R, Dynamic> {
+impl<'a, T: 'a + Copy, R: Dim> Extend<&'a T> for VecStorage<T, R, Dynamic> {
     /// Extends the number of columns of the `VecStorage` with elements
     /// from the given iterator.
     ///
@@ -369,17 +369,17 @@ impl<'a, N: 'a + Copy, R: Dim> Extend<&'a N> for VecStorage<N, R, Dynamic> {
     /// This function panics if the number of elements yielded by the
     /// given iterator is not a multiple of the number of rows of the
     /// `VecStorage`.
-    fn extend<I: IntoIterator<Item = &'a N>>(&mut self, iter: I) {
+    fn extend<I: IntoIterator<Item = &'a T>>(&mut self, iter: I) {
         self.extend(iter.into_iter().copied())
     }
 }
 
-impl<N, R, RV, SV> Extend<Vector<N, RV, SV>> for VecStorage<N, R, Dynamic>
+impl<T, R, RV, SV> Extend<Vector<T, RV, SV>> for VecStorage<T, R, Dynamic>
 where
-    N: Scalar,
+    T: Scalar,
     R: Dim,
     RV: Dim,
-    SV: Storage<N, RV>,
+    SV: Storage<T, RV>,
     ShapeConstraint: SameNumberOfRows<R, RV>,
 {
     /// Extends the number of columns of the `VecStorage` with vectors
@@ -389,7 +389,7 @@ where
     /// This function panics if the number of rows of each `Vector`
     /// yielded by the iterator is not equal to the number of rows
     /// of this `VecStorage`.
-    fn extend<I: IntoIterator<Item = Vector<N, RV, SV>>>(&mut self, iter: I) {
+    fn extend<I: IntoIterator<Item = Vector<T, RV, SV>>>(&mut self, iter: I) {
         let nrows = self.nrows.value();
         let iter = iter.into_iter();
         let (lower, _upper) = iter.size_hint();
@@ -402,10 +402,10 @@ where
     }
 }
 
-impl<N> Extend<N> for VecStorage<N, Dynamic, U1> {
+impl<T> Extend<T> for VecStorage<T, Dynamic, U1> {
     /// Extends the number of rows of the `VecStorage` with elements
     /// from the given iterator.
-    fn extend<I: IntoIterator<Item = N>>(&mut self, iter: I) {
+    fn extend<I: IntoIterator<Item = T>>(&mut self, iter: I) {
         self.data.extend(iter);
         self.nrows = Dynamic::new(self.data.len());
     }

src/debug/random_orthogonal.rs

@@ -4,38 +4,38 @@ use crate::base::storage::Owned;
 use quickcheck::{Arbitrary, Gen};
 
 use crate::base::allocator::Allocator;
-use crate::base::dimension::{Dim, Dynamic, U2};
+use crate::base::dimension::{Dim, Dynamic};
 use crate::base::Scalar;
-use crate::base::{DefaultAllocator, MatrixN};
+use crate::base::{DefaultAllocator, OMatrix};
 use crate::linalg::givens::GivensRotation;
 use simba::scalar::ComplexField;
 
 /// A random orthogonal matrix.
 #[derive(Clone, Debug)]
-pub struct RandomOrthogonal<N: Scalar, D: Dim = Dynamic>
+pub struct RandomOrthogonal<T: Scalar, D: Dim = Dynamic>
 where
-    DefaultAllocator: Allocator<N, D, D>,
+    DefaultAllocator: Allocator<T, D, D>,
 {
-    m: MatrixN<N, D>,
+    m: OMatrix<T, D, D>,
 }
 
-impl<N: ComplexField, D: Dim> RandomOrthogonal<N, D>
+impl<T: ComplexField, D: Dim> RandomOrthogonal<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D>,
+    DefaultAllocator: Allocator<T, D, D>,
 {
     /// Retrieve the generated matrix.
-    pub fn unwrap(self) -> MatrixN<N, D> {
+    pub fn unwrap(self) -> OMatrix<T, D, D> {
         self.m
     }
 
     /// Creates a new random orthogonal matrix from its dimension and a random reals generators.
-    pub fn new<Rand: FnMut() -> N>(dim: D, mut rand: Rand) -> Self {
-        let mut res = MatrixN::identity_generic(dim, dim);
+    pub fn new<Rand: FnMut() -> T>(dim: D, mut rand: Rand) -> Self {
+        let mut res = OMatrix::identity_generic(dim, dim);
 
         // Create an orthogonal matrix by composing random Givens rotations rotations.
         for i in 0..dim.value() - 1 {
             let rot = GivensRotation::new(rand(), rand()).0;
-            rot.rotate(&mut res.fixed_rows_mut::<U2>(i));
+            rot.rotate(&mut res.fixed_rows_mut::<2>(i));
         }
 
         RandomOrthogonal { m: res }
@@ -43,13 +43,13 @@ where
 }
 
 #[cfg(feature = "arbitrary")]
-impl<N: ComplexField + Arbitrary + Send, D: Dim> Arbitrary for RandomOrthogonal<N, D>
+impl<T: ComplexField + Arbitrary + Send, D: Dim> Arbitrary for RandomOrthogonal<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D>,
-    Owned<N, D, D>: Clone + Send,
+    DefaultAllocator: Allocator<T, D, D>,
+    Owned<T, D, D>: Clone + Send,
 {
     fn arbitrary(g: &mut Gen) -> Self {
         let dim = D::try_to_usize().unwrap_or(1 + usize::arbitrary(g) % 50);
-        Self::new(D::from_usize(dim), || N::arbitrary(g))
+        Self::new(D::from_usize(dim), || T::arbitrary(g))
     }
 }

src/debug/random_sdp.rs

@@ -6,38 +6,38 @@ use quickcheck::{Arbitrary, Gen};
 use crate::base::allocator::Allocator;
 use crate::base::dimension::{Dim, Dynamic};
 use crate::base::Scalar;
-use crate::base::{DefaultAllocator, MatrixN};
+use crate::base::{DefaultAllocator, OMatrix};
 use simba::scalar::ComplexField;
 
 use crate::debug::RandomOrthogonal;
 
 /// A random, well-conditioned, symmetric definite-positive matrix.
 #[derive(Clone, Debug)]
-pub struct RandomSDP<N: Scalar, D: Dim = Dynamic>
+pub struct RandomSDP<T: Scalar, D: Dim = Dynamic>
 where
-    DefaultAllocator: Allocator<N, D, D>,
+    DefaultAllocator: Allocator<T, D, D>,
 {
-    m: MatrixN<N, D>,
+    m: OMatrix<T, D, D>,
 }
 
-impl<N: ComplexField, D: Dim> RandomSDP<N, D>
+impl<T: ComplexField, D: Dim> RandomSDP<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D>,
+    DefaultAllocator: Allocator<T, D, D>,
 {
     /// Retrieve the generated matrix.
-    pub fn unwrap(self) -> MatrixN<N, D> {
+    pub fn unwrap(self) -> OMatrix<T, D, D> {
         self.m
     }
 
     /// Creates a new well conditioned symmetric definite-positive matrix from its dimension and a
     /// random reals generators.
-    pub fn new<Rand: FnMut() -> N>(dim: D, mut rand: Rand) -> Self {
+    pub fn new<Rand: FnMut() -> T>(dim: D, mut rand: Rand) -> Self {
         let mut m = RandomOrthogonal::new(dim, || rand()).unwrap();
         let mt = m.adjoint();
 
         for i in 0..dim.value() {
             let mut col = m.column_mut(i);
-            let eigenval = N::one() + N::from_real(rand().modulus());
+            let eigenval = T::one() + T::from_real(rand().modulus());
             col *= eigenval;
         }
 
@@ -46,13 +46,13 @@ where
 }
 
 #[cfg(feature = "arbitrary")]
-impl<N: ComplexField + Arbitrary + Send, D: Dim> Arbitrary for RandomSDP<N, D>
+impl<T: ComplexField + Arbitrary + Send, D: Dim> Arbitrary for RandomSDP<T, D>
 where
-    DefaultAllocator: Allocator<N, D, D>,
-    Owned<N, D, D>: Clone + Send,
+    DefaultAllocator: Allocator<T, D, D>,
+    Owned<T, D, D>: Clone + Send,
 {
     fn arbitrary(g: &mut Gen) -> Self {
         let dim = D::try_to_usize().unwrap_or(1 + usize::arbitrary(g) % 50);
-        Self::new(D::from_usize(dim), || N::arbitrary(g))
+        Self::new(D::from_usize(dim), || T::arbitrary(g))
     }
 }

src/geometry/abstract_rotation.rs

@@ -1,10 +1,10 @@
 use crate::geometry::{Rotation, UnitComplex, UnitQuaternion};
-use crate::{CVectorN, Const, Point, Scalar, SimdRealField, Unit, VectorN};
+use crate::{Const, OVector, Point, SVector, Scalar, SimdRealField, Unit};
 
 use simba::scalar::ClosedMul;
 
 /// Trait implemented by rotations that can be used inside of an `Isometry` or `Similarity`.
-pub trait AbstractRotation<N: Scalar, const D: usize>: PartialEq + ClosedMul + Clone {
+pub trait AbstractRotation<T: Scalar, const D: usize>: PartialEq + ClosedMul + Clone {
     /// The rotation identity.
     fn identity() -> Self;
     /// The rotation inverse.
@@ -12,33 +12,22 @@ pub trait AbstractRotation<N: Scalar, const D: usize>: PartialEq + ClosedMul + C
     /// Change `self` to its inverse.
     fn inverse_mut(&mut self);
     /// Apply the rotation to the given vector.
-    fn transform_vector(&self, v: &CVectorN<N, D>) -> CVectorN<N, D>;
-    // where
-    //     DefaultAllocator: Allocator<N, D>;
+    fn transform_vector(&self, v: &SVector<T, D>) -> SVector<T, D>;
     /// Apply the rotation to the given point.
-    fn transform_point(&self, p: &Point<N, D>) -> Point<N, D>;
-    // where
-    //     DefaultAllocator: Allocator<N, D>;
+    fn transform_point(&self, p: &Point<T, D>) -> Point<T, D>;
     /// Apply the inverse rotation to the given vector.
-    fn inverse_transform_vector(&self, v: &VectorN<N, Const<D>>) -> VectorN<N, Const<D>>;
-    // where
-    //     DefaultAllocator: Allocator<N, D>;
+    fn inverse_transform_vector(&self, v: &OVector<T, Const<D>>) -> OVector<T, Const<D>>;
     /// Apply the inverse rotation to the given unit vector.
-    fn inverse_transform_unit_vector(&self, v: &Unit<CVectorN<N, D>>) -> Unit<CVectorN<N, D>>
-// where
-    //     DefaultAllocator: Allocator<N, D>,
-    {
+    fn inverse_transform_unit_vector(&self, v: &Unit<SVector<T, D>>) -> Unit<SVector<T, D>> {
         Unit::new_unchecked(self.inverse_transform_vector(&**v))
     }
     /// Apply the inverse rotation to the given point.
-    fn inverse_transform_point(&self, p: &Point<N, D>) -> Point<N, D>;
-    // where
-    //     DefaultAllocator: Allocator<N, D>;
+    fn inverse_transform_point(&self, p: &Point<T, D>) -> Point<T, D>;
 }
 
-impl<N: SimdRealField, const D: usize> AbstractRotation<N, D> for Rotation<N, D>
+impl<T: SimdRealField, const D: usize> AbstractRotation<T, D> for Rotation<T, D>
 where
-    N::Element: SimdRealField,
+    T::Element: SimdRealField,
 {
     #[inline]
     fn identity() -> Self {
@@ -56,49 +45,34 @@ where
     }
 
     #[inline]
-    fn transform_vector(&self, v: &CVectorN<N, D>) -> CVectorN<N, D>
-// where
-    //     DefaultAllocator: Allocator<N, D>,
-    {
+    fn transform_vector(&self, v: &SVector<T, D>) -> SVector<T, D> {
         self * v
     }
 
     #[inline]
-    fn transform_point(&self, p: &Point<N, D>) -> Point<N, D>
-// where
-    //     DefaultAllocator: Allocator<N, D>,
-    {
+    fn transform_point(&self, p: &Point<T, D>) -> Point<T, D> {
         self * p
     }
 
     #[inline]
-    fn inverse_transform_vector(&self, v: &CVectorN<N, D>) -> CVectorN<N, D>
-// where
-    //     DefaultAllocator: Allocator<N, D>,
-    {
+    fn inverse_transform_vector(&self, v: &SVector<T, D>) -> SVector<T, D> {
         self.inverse_transform_vector(v)
     }
 
     #[inline]
-    fn inverse_transform_unit_vector(&self, v: &Unit<CVectorN<N, D>>) -> Unit<CVectorN<N, D>>
-// where
-    //     DefaultAllocator: Allocator<N, D>,
-    {
+    fn inverse_transform_unit_vector(&self, v: &Unit<SVector<T, D>>) -> Unit<SVector<T, D>> {
         self.inverse_transform_unit_vector(v)
     }
 
     #[inline]
-    fn inverse_transform_point(&self, p: &Point<N, D>) -> Point<N, D>
-// where
-    //     DefaultAllocator: Allocator<N, D>,
-    {
+    fn inverse_transform_point(&self, p: &Point<T, D>) -> Point<T, D> {
         self.inverse_transform_point(p)
     }
 }
 
-impl<N: SimdRealField> AbstractRotation<N, 3> for UnitQuaternion<N>
+impl<T: SimdRealField> AbstractRotation<T, 3> for UnitQuaternion<T>
 where
-    N::Element: SimdRealField,
+    T::Element: SimdRealField,
 {
     #[inline]
     fn identity() -> Self {
@@ -116,29 +90,29 @@ where
     }
 
     #[inline]
-    fn transform_vector(&self, v: &CVectorN<N, 3>) -> CVectorN<N, 3> {
+    fn transform_vector(&self, v: &SVector<T, 3>) -> SVector<T, 3> {
         self * v
     }
 
     #[inline]
-    fn transform_point(&self, p: &Point<N, 3>) -> Point<N, 3> {
+    fn transform_point(&self, p: &Point<T, 3>) -> Point<T, 3> {
         self * p
     }
 
     #[inline]
-    fn inverse_transform_vector(&self, v: &CVectorN<N, 3>) -> CVectorN<N, 3> {
+    fn inverse_transform_vector(&self, v: &SVector<T, 3>) -> SVector<T, 3> {
         self.inverse_transform_vector(v)
     }
 
     #[inline]
-    fn inverse_transform_point(&self, p: &Point<N, 3>) -> Point<N, 3> {
+    fn inverse_transform_point(&self, p: &Point<T, 3>) -> Point<T, 3> {
         self.inverse_transform_point(p)
     }
 }
 
-impl<N: SimdRealField> AbstractRotation<N, 2> for UnitComplex<N>
+impl<T: SimdRealField> AbstractRotation<T, 2> for UnitComplex<T>
 where
-    N::Element: SimdRealField,
+    T::Element: SimdRealField,
 {
     #[inline]
     fn identity() -> Self {
@@ -156,22 +130,22 @@ where
     }
 
     #[inline]
-    fn transform_vector(&self, v: &CVectorN<N, 2>) -> CVectorN<N, 2> {
+    fn transform_vector(&self, v: &SVector<T, 2>) -> SVector<T, 2> {
         self * v
     }
 
     #[inline]
-    fn transform_point(&self, p: &Point<N, 2>) -> Point<N, 2> {
+    fn transform_point(&self, p: &Point<T, 2>) -> Point<T, 2> {
         self * p
     }
 
     #[inline]
-    fn inverse_transform_vector(&self, v: &CVectorN<N, 2>) -> CVectorN<N, 2> {
+    fn inverse_transform_vector(&self, v: &SVector<T, 2>) -> SVector<T, 2> {
         self.inverse_transform_vector(v)
     }
 
     #[inline]
-    fn inverse_transform_point(&self, p: &Point<N, 2>) -> Point<N, 2> {
+    fn inverse_transform_point(&self, p: &Point<T, 2>) -> Point<T, 2> {
         self.inverse_transform_point(p)
     }
 }