Merge branch 'master' into as_ptr

CHANGELOG.md

@@ -7,7 +7,8 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 ## [0.17.0] - WIP
 
 ### Added
-  * Add swizzling up to dimension 3. For example, you can do `v.zxy()` as an equivalent to `Vector3::new(v.z, v.x, v.w)`.
+  * Add swizzling up to dimension 3 for vectors. For example, you can do `v.zxy()` as an equivalent to `Vector3::new(v.z, v.x, v.y)`.
+  * Add swizzling up to dimension 3 for points. For example, you can do `p.zxy()` as an equivalent to `Point3::new(p.z, p.x, p.y)`.
   * Add `.copy_from_slice` to copy matrix components from a slice in column-major order.
   * Add `.dot` to quaternions.
   * Add `.zip_zip_map` for iterating on three matrices simultaneously, and applying a closure to them.
@@ -25,6 +26,16 @@ This project adheres to [Semantic Versioning](http://semver.org/).
   * Add impl `From<Vector>` for `Translation`.
   * Add the `::from_vec` constructor to construct a matrix from a `Vec` (a `DMatrix` will reuse the original `Vec`
   as-is for its storage).
+  * Add `.to_homogeneous` to square matrices (and with dimensions higher than 1x1). This will increase their number of row
+  and columns by 1. The new column and row are filled with 0, except for the diagonal element which is set to 1.
+  * Implement `Extend<Vec>` for matrices with a dynamic storage. The provided `Vec` is assumed to represent a column-major
+  matrix with the same number of rows as the one being extended. This will effectively append new columns on the right of
+  the matrix being extended.
+  * Implement `Extend<Vec>` for vectors with a dynamic storage. This will concatenate the vector with the given `Vec`.
+  * Implement `Extend<Matrix<...>>` for matrices with dynamic storage. This will concatenate the columns of both matrices.
+  * Implement `Into<Vec>` for the `MatrixVec` storage.
+  * Implement `Hash` for all matrices.
+  * Add a `.len()` method to retrieve the size of a `MatrixVec`.
 
 ### Modified
   * The orthographic projection no longer require that `bottom < top`, that `left < right`, and that `znear < zfar`. The
@@ -32,6 +43,17 @@ This project adheres to [Semantic Versioning](http://semver.org/).
   * The `Point::from_coordinates` methods is deprecated. Use `Point::from` instead.
   * The `.transform_point` and `.transform_vector` methods are now inherent methods for matrices so that the user does not have to
   explicitly import the `Transform` trait from the alga crate.
+  * Renamed the matrix storage types: `MatrixArray` -> `ArrayStorage` and `MatrixVec` -> `VecStorage`.
+  * Renamed `.unwrap()` to `.into_inner()` for geometric types that wrap another type.
+    This is for the case of `Unit`, `Transform`, `Orthographic3`, `Perspective3`, `Rotation`.
+  * Deprecate several functions at the root of the crate (replaced by methods).
+
+### Removed
+    * Remove the `Deref` impl for `MatrixVec` as it could cause hard-to-understand compilation errors.
+
+### nalgebra-glm
+  * Add several alternative projection computations, e.g., `ortho_lh`, `ortho_lh_no`, `perspective_lh`, etc.
+  * Add features matching those of nalgebra, in particular: `serde-serialize`, `abmonation-serialize`, std` (enabled by default).
 
 ## [0.16.0]
 All dependencies have been updated to their latest versions.

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name    = "nalgebra"
-version = "0.16.10"
+version = "0.16.13"
 authors = [ "Sébastien Crozet <developer@crozet.re>" ]
 
 description = "Linear algebra library with transformations and statically-sized or dynamically-sized matrices."
@@ -23,26 +23,31 @@ stdweb          = [ "rand/stdweb" ]
 arbitrary       = [ "quickcheck" ]
 serde-serialize = [ "serde", "serde_derive", "num-complex/serde" ]
 abomonation-serialize = [ "abomonation" ]
+sparse = [ ]
 debug = [ ]
 alloc = [ ]
+io = [ "pest", "pest_derive" ]
 
 [dependencies]
 typenum        = "1.10"
-generic-array  = "0.11"
+generic-array  = "0.12"
-rand           = { version = "0.5", default-features = false }
+rand           = { version = "0.6", default-features = false }
 num-traits     = { version = "0.2", default-features = false }
 num-complex    = { version = "0.2", default-features = false }
 approx         = { version = "0.3", default-features = false }
-alga           = { version = "0.7", default-features = false }
+alga           = { version = "0.8", default-features = false }
-matrixmultiply = { version = "0.1", optional = true }
+matrixmultiply = { version = "0.2", optional = true }
 serde          = { version = "1.0", optional = true }
 serde_derive   = { version = "1.0", optional = true }
-abomonation    = { version = "0.5", optional = true }
+abomonation    = { version = "0.7", optional = true }
 mint           = { version = "0.5", optional = true }
-quickcheck     = { version = "0.6", optional = true }
+quickcheck     = { version = "0.8", optional = true }
+pest           = { version = "2.0", optional = true }
+pest_derive    = { version = "2.0", optional = true }
 
 [dev-dependencies]
 serde_json = "1.0"
+rand_xorshift = "0.1"
 
 [workspace]
 members = [ "nalgebra-lapack", "nalgebra-glm" ]

benches/common/macros.rs

@@ -4,7 +4,8 @@ macro_rules! bench_binop(
     ($name: ident, $t1: ty, $t2: ty, $binop: ident) => {
         #[bench]
         fn $name(bh: &mut Bencher) {
-            let mut rng = IsaacRng::new_unseeded();
+            use rand::SeedableRng;
+            let mut rng = IsaacRng::seed_from_u64(0);
             let a = rng.gen::<$t1>();
             let b = rng.gen::<$t2>();
 
@@ -19,7 +20,8 @@ macro_rules! bench_binop_ref(
     ($name: ident, $t1: ty, $t2: ty, $binop: ident) => {
         #[bench]
         fn $name(bh: &mut Bencher) {
-            let mut rng = IsaacRng::new_unseeded();
+            use rand::SeedableRng;
+            let mut rng = IsaacRng::seed_from_u64(0);
             let a = rng.gen::<$t1>();
             let b = rng.gen::<$t2>();
 
@@ -34,7 +36,8 @@ macro_rules! bench_binop_fn(
     ($name: ident, $t1: ty, $t2: ty, $binop: path) => {
         #[bench]
         fn $name(bh: &mut Bencher) {
-            let mut rng = IsaacRng::new_unseeded();
+            use rand::SeedableRng;
+            let mut rng = IsaacRng::seed_from_u64(0);
             let a = rng.gen::<$t1>();
             let b = rng.gen::<$t2>();
 
@@ -51,7 +54,8 @@ macro_rules! bench_unop_na(
         fn $name(bh: &mut Bencher) {
             const LEN: usize = 1 << 13;
 
-            let mut rng = IsaacRng::new_unseeded();
+            use rand::SeedableRng;
+            let mut rng = IsaacRng::seed_from_u64(0);
 
             let elems: Vec<$t> =  (0usize .. LEN).map(|_| rng.gen::<$t>()).collect();
             let mut i = 0;
@@ -73,7 +77,8 @@ macro_rules! bench_unop(
         fn $name(bh: &mut Bencher) {
             const LEN: usize = 1 << 13;
 
-            let mut rng = IsaacRng::new_unseeded();
+            use rand::SeedableRng;
+            let mut rng = IsaacRng::seed_from_u64(0);
 
             let mut elems: Vec<$t> =  (0usize .. LEN).map(|_| rng.gen::<$t>()).collect();
             let mut i = 0;
@@ -95,7 +100,8 @@ macro_rules! bench_construction(
         fn $name(bh: &mut Bencher) {
             const LEN: usize = 1 << 13;
 
-            let mut rng = IsaacRng::new_unseeded();
+            use rand::SeedableRng;
+            let mut rng = IsaacRng::seed_from_u64(0);
 
             $(let $args: Vec<$types> = (0usize .. LEN).map(|_| rng.gen::<$types>()).collect();)*
             let mut i = 0;

benches/core/vector.rs

@@ -50,7 +50,8 @@ bench_binop_ref!(vec10000_dot_f32, VectorN<f32, U10000>, VectorN<f32, U10000>, d
 
 #[bench]
 fn vec10000_axpy_f64(bh: &mut Bencher) {
-    let mut rng = IsaacRng::new_unseeded();
+    use rand::SeedableRng;
+    let mut rng = IsaacRng::seed_from_u64(0);
     let mut a = DVector::new_random(10000);
     let b = DVector::new_random(10000);
     let n = rng.gen::<f64>();
@@ -60,7 +61,8 @@ fn vec10000_axpy_f64(bh: &mut Bencher) {
 
 #[bench]
 fn vec10000_axpy_beta_f64(bh: &mut Bencher) {
-    let mut rng = IsaacRng::new_unseeded();
+    use rand::SeedableRng;
+    let mut rng = IsaacRng::seed_from_u64(0);
     let mut a = DVector::new_random(10000);
     let b = DVector::new_random(10000);
     let n = rng.gen::<f64>();
@@ -71,7 +73,8 @@ fn vec10000_axpy_beta_f64(bh: &mut Bencher) {
 
 #[bench]
 fn vec10000_axpy_f64_slice(bh: &mut Bencher) {
-    let mut rng = IsaacRng::new_unseeded();
+    use rand::SeedableRng;
+    let mut rng = IsaacRng::seed_from_u64(0);
     let mut a = DVector::new_random(10000);
     let b = DVector::new_random(10000);
     let n = rng.gen::<f64>();
@@ -86,7 +89,8 @@ fn vec10000_axpy_f64_slice(bh: &mut Bencher) {
 
 #[bench]
 fn vec10000_axpy_f64_static(bh: &mut Bencher) {
-    let mut rng = IsaacRng::new_unseeded();
+    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 n = rng.gen::<f64>();
@@ -97,7 +101,8 @@ fn vec10000_axpy_f64_static(bh: &mut Bencher) {
 
 #[bench]
 fn vec10000_axpy_f32(bh: &mut Bencher) {
-    let mut rng = IsaacRng::new_unseeded();
+    use rand::SeedableRng;
+    let mut rng = IsaacRng::seed_from_u64(0);
     let mut a = DVector::new_random(10000);
     let b = DVector::new_random(10000);
     let n = rng.gen::<f32>();
@@ -107,7 +112,8 @@ fn vec10000_axpy_f32(bh: &mut Bencher) {
 
 #[bench]
 fn vec10000_axpy_beta_f32(bh: &mut Bencher) {
-    let mut rng = IsaacRng::new_unseeded();
+    use rand::SeedableRng;
+    let mut rng = IsaacRng::seed_from_u64(0);
     let mut a = DVector::new_random(10000);
     let b = DVector::new_random(10000);
     let n = rng.gen::<f32>();

benches/lib.rs

@@ -14,6 +14,7 @@ mod geometry;
 mod linalg;
 
 fn reproductible_dmatrix(nrows: usize, ncols: usize) -> DMatrix<f64> {
-    let mut rng = IsaacRng::new_unseeded();
+    use rand::SeedableRng;
+    let mut rng = IsaacRng::seed_from_u64(0);
     DMatrix::<f64>::from_fn(nrows, ncols, |_, _| rng.gen())
 }

ci/build.sh

@@ -11,7 +11,7 @@ if [ -z "$NO_STD" ]; then
         cargo build --verbose -p nalgebra --features "serde-serialize";
         cargo build --verbose -p nalgebra --features "abomonation-serialize";
         cargo build --verbose -p nalgebra --features "debug";
-        cargo build --verbose -p nalgebra --features "debug arbitrary mint serde-serialize abomonation-serialize";
+        cargo build --verbose -p nalgebra --all-features
     else
         cargo build -p nalgebra-lapack;
     fi

examples/matrix_construction.rs

@@ -51,8 +51,8 @@ fn main() {
             // Components listed column-by-column.
             1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0,
         ]
-            .iter()
+        .iter()
-            .cloned(),
+        .cloned(),
     );
 
     assert_eq!(dm, dm1);

examples/transform_matrix4.rs

@@ -3,7 +3,6 @@ extern crate alga;
 extern crate approx;
 extern crate nalgebra as na;
 
-use alga::linear::Transformation;
 use na::{Matrix4, Point3, Vector3};
 
 fn main() {

examples/transform_vector_point3.rs

@@ -1,7 +1,6 @@
 extern crate alga;
 extern crate nalgebra as na;
 
-use alga::linear::Transformation;
 use na::{Matrix4, Point3, Vector3, Vector4};
 
 fn main() {

nalgebra-glm/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "nalgebra-glm"
-version = "0.2.0"
+version = "0.2.1"
 authors = ["sebcrozet <developer@crozet.re>"]
 
 description = "A computer-graphics oriented API for nalgebra, inspired by the C++ GLM library."
@@ -12,8 +12,16 @@ categories = [ "science" ]
 keywords = [ "linear", "algebra", "matrix", "vector", "math" ]
 license = "BSD-3-Clause"
 
+[features]
+default         = [ "std" ]
+std             = [ "nalgebra/std", "alga/std" ]
+stdweb          = [ "nalgebra/stdweb" ]
+arbitrary       = [ "nalgebra/arbitrary" ]
+serde-serialize = [ "nalgebra/serde-serialize" ]
+abomonation-serialize = [ "nalgebra/abomonation-serialize" ]
+
 [dependencies]
 num-traits = { version = "0.2", default-features = false }
 approx = { version = "0.3", default-features = false }
-alga = "0.7"
+alga = { version = "0.8", default-features = false }
-nalgebra = { path =  "..", version = "^0.16.4" }
+nalgebra = { path =  "..", version = "^0.16.13", default-features = false }

nalgebra-glm/src/ext/matrix_clip_space.rs

@@ -1,5 +1,5 @@
 use aliases::TMat4;
-use na::{Orthographic3, Perspective3, Real};
+use na::{Real};
 
 //pub fn frustum<N: Real>(left: N, right: N, bottom: N, top: N, near: N, far: N) -> TMat4<N> {
 //    unimplemented!()
@@ -53,119 +53,644 @@ use na::{Orthographic3, Perspective3, Real};
 //    unimplemented!()
 //}
 
-/// Creates a matrix for an orthographic parallel viewing volume, using the right handedness and OpenGL near and far clip planes definition.
+/// Creates a matrix for a right hand orthographic-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `left` - Coordinate for left bound of matrix
+/// * `right` - Coordinate for right bound of matrix
+/// * `bottom` - Coordinate for bottom bound of matrix
+/// * `top` - Coordinate for top bound of matrix
+/// * `znear` - Distance from the viewer to the near clipping plane
+/// * `zfar` - Distance from the viewer to the far clipping plane
+///
 pub fn ortho<N: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
-    Orthographic3::new(left, right, bottom, top, znear, zfar).unwrap()
+    ortho_rh_no(left, right, bottom, top, znear, zfar)
 }
 
-//pub fn ortho_lh<N: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+/// Creates a left hand matrix for a orthographic-view frustum with a depth range of -1 to 1
-//    unimplemented!()
+///
-//}
+/// # Parameters
-//
+///
-//pub fn ortho_lh_no<N: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+/// * `left` - Coordinate for left bound of matrix
-//    unimplemented!()
+/// * `right` - Coordinate for right bound of matrix
-//}
+/// * `bottom` - Coordinate for bottom bound of matrix
-//
+/// * `top` - Coordinate for top bound of matrix
-//pub fn ortho_lh_zo<N: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+/// * `znear` - Distance from the viewer to the near clipping plane
-//    unimplemented!()
+/// * `zfar` - Distance from the viewer to the far clipping plane
-//}
+///
-//
+pub fn ortho_lh<N: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
-//pub fn ortho_no<N: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+    ortho_lh_no(left, right, bottom, top, znear, zfar)
-//    unimplemented!()
+}
-//}
-//
-//pub fn ortho_rh<N: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn ortho_rh_no<N: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn ortho_rh_zo<N: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn ortho_zo<N: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
-//    unimplemented!()
-//}
 
-/// Creates a matrix for a perspective-view frustum based on the right handedness and OpenGL near and far clip planes definition.
+/// Creates a left hand matrix for a orthographic-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `left` - Coordinate for left bound of matrix
+/// * `right` - Coordinate for right bound of matrix
+/// * `bottom` - Coordinate for bottom bound of matrix
+/// * `top` - Coordinate for top bound of matrix
+/// * `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: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+    let two    : N =  ::convert(2.0);
+    let mut mat : TMat4<N> = TMat4::<N>::identity();
+
+    mat[(0, 0)] = two / (right - left);
+    mat[(0, 3)] = -(right + left) / (right - left);
+    mat[(1, 1)] = two / (top-bottom);
+    mat[(1, 3)] = -(top + bottom) / (top - bottom);
+    mat[(2, 2)] = two / (zfar - znear);
+    mat[(2, 3)] = -(zfar + znear) / (zfar - znear);
+
+    mat
+}
+
+/// Creates a matrix for a left hand orthographic-view frustum with a depth range of 0 to 1
+///
+/// # Parameters
+///
+/// * `left` - Coordinate for left bound of matrix
+/// * `right` - Coordinate for right bound of matrix
+/// * `bottom` - Coordinate for bottom bound of matrix
+/// * `top` - Coordinate for top bound of matrix
+/// * `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: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+    let one    : N = N::one();
+    let two    : N = ::convert(2.0);
+    let mut mat : TMat4<N> = TMat4::<N>::identity();
+
+    mat[(0, 0)] = two / (right - left);
+    mat[(0, 3)] = - (right + left) / (right - left);
+    mat[(1, 1)] = two / (top - bottom);
+    mat[(1, 3)] = - (top + bottom) / (top - bottom);
+    mat[(2, 2)] = one / (zfar - znear);
+    mat[(2, 3)] = - znear / (zfar  - znear);
+
+    mat
+}
+
+/// Creates a matrix for a right hand orthographic-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `left` - Coordinate for left bound of matrix
+/// * `right` - Coordinate for right bound of matrix
+/// * `bottom` - Coordinate for bottom bound of matrix
+/// * `top` - Coordinate for top bound of matrix
+/// * `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: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+    ortho_rh_no(left, right, bottom, top, znear, zfar)
+}
+
+/// Creates a matrix for a right hand orthographic-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `left` - Coordinate for left bound of matrix
+/// * `right` - Coordinate for right bound of matrix
+/// * `bottom` - Coordinate for bottom bound of matrix
+/// * `top` - Coordinate for top bound of matrix
+/// * `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: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+    ortho_rh_no(left, right, bottom, top, znear, zfar)
+}
+
+/// Creates a matrix for a right hand orthographic-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `left` - Coordinate for left bound of matrix
+/// * `right` - Coordinate for right bound of matrix
+/// * `bottom` - Coordinate for bottom bound of matrix
+/// * `top` - Coordinate for top bound of matrix
+/// * `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: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+    let two    : N =  ::convert(2.0);
+    let mut mat : TMat4<N> = TMat4::<N>::identity();
+
+    mat[(0, 0)] = two / (right - left);
+    mat[(0, 3)] = - (right + left) / (right - left);
+    mat[(1, 1)] = two/(top-bottom);
+    mat[(1, 3)] = - (top + bottom) / (top - bottom);
+    mat[(2, 2)] = - two / (zfar - znear);
+    mat[(2, 3)] = - (zfar + znear) / (zfar  - znear);
+
+    mat
+}
+
+/// Creates a right hand matrix for a orthographic-view frustum with a depth range of 0 to 1
+///
+/// # Parameters
+///
+/// * `left` - Coordinate for left bound of matrix
+/// * `right` - Coordinate for right bound of matrix
+/// * `bottom` - Coordinate for bottom bound of matrix
+/// * `top` - Coordinate for top bound of matrix
+/// * `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: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+    let one    : N = N::one();
+    let two    : N =  ::convert(2.0);
+    let mut mat : TMat4<N> = TMat4::<N>::identity();
+
+    mat[(0, 0)] = two / (right - left);
+    mat[(0, 3)] = - (right + left) / (right - left);
+    mat[(1, 1)] = two/(top-bottom);
+    mat[(1, 3)] = - (top + bottom) / (top - bottom);
+    mat[(2, 2)] = - one / (zfar - znear);
+    mat[(2, 3)] = - znear / (zfar  - znear);
+
+    mat
+}
+
+/// Creates a right hand matrix for a orthographic-view frustum with a depth range of 0 to 1
+///
+/// # Parameters
+///
+/// * `left` - Coordinate for left bound of matrix
+/// * `right` - Coordinate for right bound of matrix
+/// * `bottom` - Coordinate for bottom bound of matrix
+/// * `top` - Coordinate for top bound of matrix
+/// * `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: Real>(left: N, right: N, bottom: N, top: N, znear: N, zfar: N) -> TMat4<N> {
+    ortho_rh_zo(left, right, bottom, top, znear, zfar)
+}
+
+/// Creates a matrix for a right hand perspective-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `fov` - Field of view, in radians
+/// * `width` - Width of the viewport
+/// * `height` - Height of the viewport
+/// * `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: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
+    perspective_fov_rh_no(fov, width, height, near, far)
+}
+
+/// Creates a matrix for a left hand perspective-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `fov` - Field of view, in radians
+/// * `width` - Width of the viewport
+/// * `height` - Height of the viewport
+/// * `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: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
+    perspective_fov_lh_no(fov, width, height, near, far)
+}
+
+/// Creates a matrix for a left hand perspective-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `fov` - Field of view, in radians
+/// * `width` - Width of the viewport
+/// * `height` - Height of the viewport
+/// * `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: Real>(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"
+    );
+
+    let mut mat = TMat4::zeros();
+
+    let rad = fov;
+    let h = (rad * ::convert(0.5)).cos() / (rad * ::convert(0.5)).sin();
+    let w = h * height / width;
+
+    mat[(0, 0)] = w;
+    mat[(1, 1)] = h;
+    mat[(2, 2)] = (far + near) / (far - near);
+    mat[(2, 3)] = - (far * near * ::convert(2.0)) / (far - near);
+    mat[(3, 2)] = N::one();
+
+    mat
+}
+
+/// Creates a matrix for a left hand perspective-view frustum with a depth range of 0 to 1
+///
+/// # Parameters
+///
+/// * `fov` - Field of view, in radians
+/// * `width` - Width of the viewport
+/// * `height` - Height of the viewport
+/// * `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: Real>(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"
+    );
+
+    let mut mat = TMat4::zeros();
+
+    let rad = fov;
+    let h = (rad * ::convert(0.5)).cos() / (rad * ::convert(0.5)).sin();
+    let w = h * height / width;
+
+    mat[(0, 0)] = w;
+    mat[(1, 1)] = h;
+    mat[(2, 2)] = far / (far - near);
+    mat[(2, 3)] = -(far * near) / (far - near);
+    mat[(3, 2)] = N::one();
+
+    mat
+}
+
+/// Creates a matrix for a right hand perspective-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `fov` - Field of view, in radians
+/// * `width` - Width of the viewport
+/// * `height` - Height of the viewport
+/// * `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: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
+    perspective_fov_rh_no(fov, width, height, near, far)
+}
+
+/// Creates a matrix for a right hand perspective-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `fov` - Field of view, in radians
+/// * `width` - Width of the viewport
+/// * `height` - Height of the viewport
+/// * `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: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
+    perspective_fov_rh_no(fov, width, height, near, far)
+}
+
+/// Creates a matrix for a right hand perspective-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `fov` - Field of view, in radians
+/// * `width` - Width of the viewport
+/// * `height` - Height of the viewport
+/// * `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: Real>(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"
+    );
+
+    let mut mat = TMat4::zeros();
+
+    let rad = fov;
+    let h = (rad * ::convert(0.5)).cos() / (rad * ::convert(0.5)).sin();
+    let w = h * height / width;
+
+    mat[(0, 0)] = w;
+    mat[(1, 1)] = h;
+    mat[(2, 2)] = - (far + near) / (far - near);
+    mat[(2, 3)] = - (far * near * ::convert(2.0)) / (far - near);
+    mat[(3, 2)] = -N::one();
+
+    mat
+}
+
+/// Creates a matrix for a right hand perspective-view frustum with a depth range of 0 to 1
+///
+/// # Parameters
+///
+/// * `fov` - Field of view, in radians
+/// * `width` - Width of the viewport
+/// * `height` - Height of the viewport
+/// * `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: Real>(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"
+    );
+
+    let mut mat = TMat4::zeros();
+
+    let rad = fov;
+    let h = (rad * ::convert(0.5)).cos() / (rad * ::convert(0.5)).sin();
+    let w = h * height / width;
+
+    mat[(0, 0)] = w;
+    mat[(1, 1)] = h;
+    mat[(2, 2)] = far / (near - far);
+    mat[(2, 3)] = -(far * near) / (far - near);
+    mat[(3, 2)] = -N::one();
+
+    mat
+}
+
+/// Creates a matrix for a right hand perspective-view frustum with a depth range of 0 to 1
+///
+/// # Parameters
+///
+/// * `fov` - Field of view, in radians
+/// * `width` - Width of the viewport
+/// * `height` - Height of the viewport
+/// * `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: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
+    perspective_fov_rh_zo(fov, width, height, near, far)
+}
+
+/// Creates a matrix for a right hand perspective-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `fovy` - Field of view, in radians
+/// * `aspect` - Ratio of viewport width to height (width/height)
+/// * `near` - Distance from the viewer to the near clipping plane
+/// * `far` - Distance from the viewer to the far clipping plane
 ///
 /// # Important note
 /// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
 pub fn perspective<N: Real>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
-    Perspective3::new(aspect, fovy, near, far).unwrap()
+    // TODO: Breaking change - revert back to proper glm conventions?
+    //
+    //       Prior to changes to support configuring the behaviour of this function it was simply
+    //       a wrapper around Perspective3::new(). The argument order for that function is different
+    //       than the glm convention, but reordering the arguments would've caused pointlessly
+    //       un-optimal code to be generated so they were rearranged so the function would just call
+    //       straight through.
+    //
+    //       Now this call to Perspective3::new() is no longer made so the functions can have their
+    //       arguments reordered to the glm convention. Unfortunately this is a breaking change so
+    //       can't be cleanly integrated into the existing library version without breaking other
+    //       people's code. Reordering to glm isn't a huge deal but if it is done it will have to be
+    //       in a major API breaking update.
+    //
+    perspective_rh_no(aspect, fovy, near, far)
+}
+
+/// Creates a matrix for a left hand perspective-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `fovy` - Field of view, in radians
+/// * `aspect` - Ratio of viewport width to height (width/height)
+/// * `near` - Distance from the viewer to the near clipping plane
+/// * `far` - Distance from the viewer to the far clipping plane
+///
+/// # Important note
+/// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
+pub fn perspective_lh<N: Real>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+    perspective_lh_no(aspect, fovy, near, far)
+}
+
+/// Creates a matrix for a left hand perspective-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `fovy` - Field of view, in radians
+/// * `aspect` - Ratio of viewport width to height (width/height)
+/// * `near` - Distance from the viewer to the near clipping plane
+/// * `far` - Distance from the viewer to the far clipping plane
+///
+/// # Important note
+/// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
+pub fn perspective_lh_no<N: Real>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+    assert!(
+        !relative_eq!(far - near, N::zero()),
+        "The near-plane and far-plane must not be superimposed."
+    );
+    assert!(
+        !relative_eq!(aspect, N::zero()),
+        "The apsect ratio must not be zero."
+    );
+
+    let one = N::one();
+    let two: N = ::convert( 2.0);
+    let mut mat : TMat4<N> = TMat4::zeros();
+
+    let tan_half_fovy = (fovy / two).tan();
+
+    mat[(0, 0)] = one / (aspect * tan_half_fovy);
+    mat[(1, 1)] = one / tan_half_fovy;
+    mat[(2, 2)] = (far + near) / (far - near);
+    mat[(2, 3)] = -(two * far * near) / (far - near);
+    mat[(3, 2)] = one;
+
+    mat
+}
+
+/// Creates a matrix for a left hand perspective-view frustum with a depth range of 0 to 1
+///
+/// # Parameters
+///
+/// * `fovy` - Field of view, in radians
+/// * `aspect` - Ratio of viewport width to height (width/height)
+/// * `near` - Distance from the viewer to the near clipping plane
+/// * `far` - Distance from the viewer to the far clipping plane
+///
+/// # Important note
+/// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
+pub fn perspective_lh_zo<N: Real>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+    assert!(
+        !relative_eq!(far - near, N::zero()),
+        "The near-plane and far-plane must not be superimposed."
+    );
+    assert!(
+        !relative_eq!(aspect, N::zero()),
+        "The apsect ratio must not be zero."
+    );
+
+    let one = N::one();
+    let two: N = ::convert( 2.0);
+    let mut mat: TMat4<N> = TMat4::zeros();
+
+    let tan_half_fovy = (fovy / two).tan();
+
+    mat[(0, 0)] = one / (aspect * tan_half_fovy);
+    mat[(1, 1)] = one / tan_half_fovy;
+    mat[(2, 2)] = far / (far - near);
+    mat[(2, 3)] = -(far * near) / (far - near);
+    mat[(3, 2)] = one;
+
+    mat
+}
+
+/// Creates a matrix for a right hand perspective-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `fovy` - Field of view, in radians
+/// * `aspect` - Ratio of viewport width to height (width/height)
+/// * `near` - Distance from the viewer to the near clipping plane
+/// * `far` - Distance from the viewer to the far clipping plane
+///
+/// # Important note
+/// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
+pub fn perspective_no<N: Real>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+    perspective_rh_no(aspect, fovy, near, far)
+}
+
+/// Creates a matrix for a right hand perspective-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `fovy` - Field of view, in radians
+/// * `aspect` - Ratio of viewport width to height (width/height)
+/// * `near` - Distance from the viewer to the near clipping plane
+/// * `far` - Distance from the viewer to the far clipping plane
+///
+/// # Important note
+/// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
+pub fn perspective_rh<N: Real>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+    perspective_rh_no(aspect, fovy, near, far)
+}
+
+/// Creates a matrix for a right hand perspective-view frustum with a depth range of -1 to 1
+///
+/// # Parameters
+///
+/// * `fovy` - Field of view, in radians
+/// * `aspect` - Ratio of viewport width to height (width/height)
+/// * `near` - Distance from the viewer to the near clipping plane
+/// * `far` - Distance from the viewer to the far clipping plane
+///
+/// # Important note
+/// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
+pub fn perspective_rh_no<N: Real>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+    assert!(
+        !relative_eq!(far - near, N::zero()),
+        "The near-plane and far-plane must not be superimposed."
+    );
+    assert!(
+        !relative_eq!(aspect, N::zero()),
+        "The apsect ratio must not be zero."
+    );
+
+    let negone = -N::one();
+    let one =  N::one();
+    let two: N =   ::convert( 2.0);
+    let mut mat = TMat4::zeros();
+
+    let tan_half_fovy = (fovy / two).tan();
+
+    mat[(0, 0)] = one / (aspect * tan_half_fovy);
+    mat[(1, 1)] = one / tan_half_fovy;
+    mat[(2, 2)] = - (far + near) / (far - near);
+    mat[(2, 3)] = -(two * far * near) / (far - near);
+    mat[(3, 2)] = negone;
+
+    mat
+}
+
+/// Creates a matrix for a right hand perspective-view frustum with a depth range of 0 to 1
+///
+/// # Parameters
+///
+/// * `fovy` - Field of view, in radians
+/// * `aspect` - Ratio of viewport width to height (width/height)
+/// * `near` - Distance from the viewer to the near clipping plane
+/// * `far` - Distance from the viewer to the far clipping plane
+///
+/// # Important note
+/// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
+pub fn perspective_rh_zo<N: Real>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+    assert!(
+        !relative_eq!(far - near, N::zero()),
+        "The near-plane and far-plane must not be superimposed."
+    );
+    assert!(
+        !relative_eq!(aspect, N::zero()),
+        "The apsect ratio must not be zero."
+    );
+
+    let negone = -N::one();
+    let one =  N::one();
+    let two =   ::convert( 2.0);
+    let mut mat = TMat4::zeros();
+
+    let tan_half_fovy = (fovy / two).tan();
+
+    mat[(0, 0)] = one / (aspect * tan_half_fovy);
+    mat[(1, 1)] = one / tan_half_fovy;
+    mat[(2, 2)] = far / (near - far);
+    mat[(2, 3)] = -(far * near) / (far - near);
+    mat[(3, 2)] = negone;
+
+    mat
+}
+
+/// Creates a matrix for a right hand perspective-view frustum with a depth range of 0 to 1
+///
+/// # Parameters
+///
+/// * `fovy` - Field of view, in radians
+/// * `aspect` - Ratio of viewport width to height (width/height)
+/// * `near` - Distance from the viewer to the near clipping plane
+/// * `far` - Distance from the viewer to the far clipping plane
+///
+/// # Important note
+/// The `aspect` and `fovy` argument are interchanged compared to the original GLM API.
+pub fn perspective_zo<N: Real>(aspect: N, fovy: N, near: N, far: N) -> TMat4<N> {
+    perspective_rh_zo(aspect, fovy, near, far)
 }
 
-//pub fn perspective_fov<N: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_fov_lh<N: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_fov_lh_no<N: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_fov_lh_zo<N: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_fov_no<N: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_fov_rh<N: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_fov_rh_no<N: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_fov_rh_zo<N: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_fov_zo<N: Real>(fov: N, width: N, height: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_lh<N: Real>(fovy: N, aspect: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_lh_no<N: Real>(fovy: N, aspect: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_lh_zo<N: Real>(fovy: N, aspect: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_no<N: Real>(fovy: N, aspect: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_rh<N: Real>(fovy: N, aspect: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_rh_no<N: Real>(fovy: N, aspect: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_rh_zo<N: Real>(fovy: N, aspect: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
-//pub fn perspective_zo<N: Real>(fovy: N, aspect: N, near: N, far: N) -> TMat4<N> {
-//    unimplemented!()
-//}
-//
 //pub fn tweaked_infinite_perspective<N: Real>(fovy: N, aspect: N, near: N) -> TMat4<N> {
 //    unimplemented!()
 //}

nalgebra-glm/src/ext/matrix_projection.rs

@@ -24,7 +24,8 @@ pub fn pick_matrix<N: Real>(center: &TVec2<N>, delta: &TVec2<N>, viewport: &TVec
     ))
 }
 
-/// Map the specified object coordinates `(obj.x, obj.y, obj.z)` into window coordinates using OpenGL near and far clip planes definition.
+/// Map the specified object coordinates `(obj.x, obj.y, obj.z)` into window coordinates with a
+/// depth range of -1 to 1
 ///
 /// # Parameters:
 ///
@@ -114,7 +115,8 @@ pub fn project_zo<N: Real>(
     )
 }
 
-/// Map the specified window coordinates (win.x, win.y, win.z) into object coordinates using OpenGL near and far clip planes definition.
+/// Map the specified window coordinates (win.x, win.y, win.z) into object coordinates using a
+/// depth range of -1 to 1
 ///
 /// # Parameters:
 ///

nalgebra-glm/src/ext/mod.rs

@@ -1,6 +1,16 @@
 //! (Reexported) Additional features not specified by GLSL specification
 
-pub use self::matrix_clip_space::{ortho, perspective};
+pub use self::matrix_clip_space::{
+    ortho, ortho_lh, ortho_lh_no, ortho_lh_zo, ortho_no, ortho_rh, ortho_rh_no, ortho_rh_zo,
+    ortho_zo,
+
+    perspective, perspective_lh, perspective_lh_no, perspective_lh_zo, perspective_no,
+    perspective_rh, perspective_rh_no, perspective_rh_zo, perspective_zo,
+
+    perspective_fov, perspective_fov_lh,perspective_fov_lh_no, perspective_fov_lh_zo,
+    perspective_fov_no, perspective_fov_rh, perspective_fov_rh_no, perspective_fov_rh_zo,
+    perspective_fov_zo,
+};
 pub use self::matrix_projection::{
     pick_matrix, project, project_no, project_zo, unproject, unproject_no, unproject_zo,
 };

nalgebra-glm/src/ext/quaternion_common.rs

@@ -33,5 +33,5 @@ pub fn quat_lerp<N: Real>(x: &Qua<N>, y: &Qua<N>, a: N) -> Qua<N> {
 pub fn quat_slerp<N: Real>(x: &Qua<N>, y: &Qua<N>, a: N) -> Qua<N> {
     Unit::new_normalize(*x)
         .slerp(&Unit::new_normalize(*y), a)
-        .unwrap()
+        .into_inner()
 }

nalgebra-glm/src/ext/quaternion_transform.rs

@@ -19,7 +19,7 @@ pub fn quat_pow<N: Real>(q: &Qua<N>, y: N) -> Qua<N> {
 
 /// Builds a quaternion from an axis and an angle, and right-multiply it to the quaternion `q`.
 pub fn quat_rotate<N: Real>(q: &Qua<N>, angle: N, axis: &TVec3<N>) -> Qua<N> {
-    q * UnitQuaternion::from_axis_angle(&Unit::new_normalize(*axis), angle).unwrap()
+    q * UnitQuaternion::from_axis_angle(&Unit::new_normalize(*axis), angle).into_inner()
 }
 
 //pub fn quat_sqrt<N: Real>(q: &Qua<N>) -> Qua<N> {

nalgebra-glm/src/ext/quaternion_trigonometric.rs

@@ -9,13 +9,13 @@ pub fn quat_angle<N: Real>(x: &Qua<N>) -> N {
 
 /// Creates a quaternion from an axis and an angle.
 pub fn quat_angle_axis<N: Real>(angle: N, axis: &TVec3<N>) -> Qua<N> {
-    UnitQuaternion::from_axis_angle(&Unit::new_normalize(*axis), angle).unwrap()
+    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: Real>(x: &Qua<N>) -> TVec3<N> {
     if let Some(a) = UnitQuaternion::from_quaternion(*x).axis() {
-        a.unwrap()
+        a.into_inner()
     } else {
         TVec3::zeros()
     }

nalgebra-glm/src/gtc/quaternion.rs

@@ -5,7 +5,7 @@ use aliases::{Qua, TMat4, TVec, TVec3};
 /// Euler angles of the quaternion `q` as (pitch, yaw, roll).
 pub fn quat_euler_angles<N: Real>(x: &Qua<N>) -> TVec3<N> {
     let q = UnitQuaternion::new_unchecked(*x);
-    let a = q.to_euler_angles();
+    let a = q.euler_angles();
     TVec3::new(a.2, a.1, a.0)
 }
 
@@ -34,19 +34,25 @@ pub fn quat_cast<N: Real>(x: &Qua<N>) -> TMat4<N> {
     ::quat_to_mat4(x)
 }
 
-/// Computes a right-handed look-at quaternion (equivalent to a right-handed look-at matrix).
+/// Computes a right hand look-at quaternion
+///
+/// # Parameters
+///
+/// * `direction` - Direction vector point at where to look
+/// * `up` - Object up vector
+///
 pub fn quat_look_at<N: Real>(direction: &TVec3<N>, up: &TVec3<N>) -> Qua<N> {
     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: Real>(direction: &TVec3<N>, up: &TVec3<N>) -> Qua<N> {
-    UnitQuaternion::look_at_lh(direction, up).unwrap()
+    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: Real>(direction: &TVec3<N>, up: &TVec3<N>) -> Qua<N> {
-    UnitQuaternion::look_at_rh(direction, up).unwrap()
+    UnitQuaternion::look_at_rh(direction, up).into_inner()
 }
 
 /// The "roll" Euler angle of the quaternion `x` assumed to be normalized.

nalgebra-glm/src/gtx/quaternion.rs

@@ -21,7 +21,7 @@ pub fn quat_extract_real_component<N: Real>(q: &Qua<N>) -> N {
 pub fn quat_fast_mix<N: Real>(x: &Qua<N>, y: &Qua<N>, a: N) -> Qua<N> {
     Unit::new_unchecked(*x)
         .nlerp(&Unit::new_unchecked(*y), a)
-        .unwrap()
+        .into_inner()
 }
 
 //pub fn quat_intermediate<N: Real>(prev: &Qua<N>, curr: &Qua<N>, next: &Qua<N>) -> Qua<N> {
@@ -40,7 +40,7 @@ pub fn quat_magnitude2<N: Real>(q: &Qua<N>) -> N {
 
 /// The quaternion representing the identity rotation.
 pub fn quat_identity<N: Real>() -> Qua<N> {
-    UnitQuaternion::identity().unwrap()
+    UnitQuaternion::identity().into_inner()
 }
 
 /// Rotates a vector by a quaternion assumed to be normalized.
@@ -58,14 +58,14 @@ pub fn quat_rotate_vec<N: Real>(q: &Qua<N>, v: &TVec4<N>) -> TVec4<N> {
 pub fn quat_rotation<N: Real>(orig: &TVec3<N>, dest: &TVec3<N>) -> Qua<N> {
     UnitQuaternion::rotation_between(orig, dest)
         .unwrap_or_else(UnitQuaternion::identity)
-        .unwrap()
+        .into_inner()
 }
 
 /// The spherical linear interpolation between two quaternions.
 pub fn quat_short_mix<N: Real>(x: &Qua<N>, y: &Qua<N>, a: N) -> Qua<N> {
     Unit::new_normalize(*x)
         .slerp(&Unit::new_normalize(*y), a)
-        .unwrap()
+        .into_inner()
 }
 
 //pub fn quat_squad<N: Real>(q1: &Qua<N>, q2: &Qua<N>, s1: &Qua<N>, s2: &Qua<N>, h: N) -> Qua<N> {
@@ -76,7 +76,7 @@ pub fn quat_short_mix<N: Real>(x: &Qua<N>, y: &Qua<N>, a: N) -> Qua<N> {
 pub fn quat_to_mat3<N: Real>(x: &Qua<N>) -> TMat3<N> {
     UnitQuaternion::new_unchecked(*x)
         .to_rotation_matrix()
-        .unwrap()
+        .into_inner()
 }
 
 /// Converts a quaternion to a rotation matrix in homogenous coordinates.
@@ -87,7 +87,7 @@ pub fn quat_to_mat4<N: Real>(x: &Qua<N>) -> TMat4<N> {
 /// Converts a rotation matrix to a quaternion.
 pub fn mat3_to_quat<N: Real>(x: &TMat3<N>) -> Qua<N> {
     let r = Rotation3::from_matrix_unchecked(*x);
-    UnitQuaternion::from_rotation_matrix(&r).unwrap()
+    UnitQuaternion::from_rotation_matrix(&r).into_inner()
 }
 
 /// Converts a rotation matrix in homogeneous coordinates to a quaternion.

nalgebra-glm/src/gtx/rotate_normalized_axis.rs

@@ -21,5 +21,5 @@ pub fn rotate_normalized_axis<N: Real>(m: &TMat4<N>, angle: N, axis: &TVec3<N>)
 /// * `angle` - Angle expressed in radians.
 /// * `axis` - Normalized axis of the rotation, must be normalized.
 pub fn quat_rotate_normalized_axis<N: Real>(q: &Qua<N>, angle: N, axis: &TVec3<N>) -> Qua<N> {
-    q * UnitQuaternion::from_axis_angle(&Unit::new_unchecked(*axis), angle).unwrap()
+    q * UnitQuaternion::from_axis_angle(&Unit::new_unchecked(*axis), angle).into_inner()
 }

nalgebra-glm/src/gtx/rotate_vector.rs

@@ -60,5 +60,5 @@ pub fn rotate_z_vec4<N: Real>(v: &TVec4<N>, angle: N) -> TVec4<N> {
 pub fn slerp<N: Real>(x: &TVec3<N>, y: &TVec3<N>, a: N) -> TVec3<N> {
     Unit::new_unchecked(*x)
         .slerp(&Unit::new_unchecked(*y), a)
-        .unwrap()
+        .into_inner()
 }

nalgebra-glm/src/lib.rs

@@ -110,6 +110,9 @@
    and keep in mind it is possible to convert, e.g., an `Isometry3` to a `Mat4` and vice-versa (see the [conversions section](#conversions)).
 */
 
+#![doc(html_favicon_url = "http://nalgebra.org/img/favicon.ico")]
+#![cfg_attr(not(feature = "std"), no_std)]
+
 extern crate num_traits as num;
 #[macro_use]
 extern crate approx;
@@ -142,12 +145,17 @@ pub use ext::{
     epsilon, equal_columns, equal_columns_eps, equal_columns_eps_vec, equal_eps, equal_eps_vec,
     identity, look_at, look_at_lh, look_at_rh, max, max2, max3, max3_scalar, max4, max4_scalar,
     min, min2, min3, min3_scalar, min4, min4_scalar, not_equal_columns, not_equal_columns_eps,
-    not_equal_columns_eps_vec, not_equal_eps, not_equal_eps_vec, ortho, perspective, pi,
+    not_equal_columns_eps_vec, not_equal_eps, not_equal_eps_vec, ortho, perspective, perspective_fov,
-    pick_matrix, project, project_no, project_zo, quat_angle, quat_angle_axis, quat_axis,
+    perspective_fov_lh,perspective_fov_lh_no, perspective_fov_lh_zo, perspective_fov_no,
-    quat_conjugate, quat_cross, quat_dot, quat_equal, quat_equal_eps, quat_exp, quat_inverse,
+    perspective_fov_rh, perspective_fov_rh_no, perspective_fov_rh_zo, perspective_fov_zo,
-    quat_length, quat_lerp, quat_log, quat_magnitude, quat_normalize, quat_not_equal,
+    perspective_lh, perspective_lh_no, perspective_lh_zo, perspective_no, perspective_rh,
-    quat_not_equal_eps, quat_pow, quat_rotate, quat_slerp, rotate, rotate_x, rotate_y, rotate_z,
+    perspective_rh_no, perspective_rh_zo, perspective_zo, ortho_lh, ortho_lh_no, ortho_lh_zo,
-    scale, translate, unproject, unproject_no, unproject_zo,
+    ortho_no, ortho_rh, ortho_rh_no, ortho_rh_zo, ortho_zo, pi, pick_matrix, project, project_no,
+    project_zo, quat_angle, quat_angle_axis, quat_axis, quat_conjugate, quat_cross, quat_dot,
+    quat_equal, quat_equal_eps, quat_exp, quat_inverse, quat_length, quat_lerp, quat_log,
+    quat_magnitude, quat_normalize, quat_not_equal, quat_not_equal_eps, quat_pow, quat_rotate,
+    quat_slerp, rotate, rotate_x, rotate_y, rotate_z, scale, translate, unproject, unproject_no,
+    unproject_zo,
 };
 pub use gtc::{
     affine_inverse, column, e, euler, four_over_pi, golden_ratio, half_pi, inverse_transpose,

nalgebra-glm/tests/lib.rs

@@ -0,0 +1,55 @@
+extern crate nalgebra as na;
+extern crate nalgebra_glm as glm;
+
+use na::Perspective3;
+use na::Orthographic3;
+use glm::Mat4;
+use glm::Vec4;
+
+#[test]
+pub fn orthographic_glm_nalgebra_same()
+{
+    let na_mat : Mat4 = Orthographic3::new(-100.0f32,100.0f32, -50.0f32, 50.0f32, 0.1f32, 100.0f32).into_inner();
+    let gl_mat : Mat4 = glm::ortho(-100.0f32,100.0f32, -50.0f32, 50.0f32, 0.1f32, 100.0f32);
+
+    assert_eq!(na_mat, gl_mat);
+}
+
+#[test]
+pub fn perspective_glm_nalgebra_same()
+{
+    let na_mat : Mat4 = Perspective3::new(16.0f32/9.0f32, 3.14f32/2.0f32, 0.1f32, 100.0f32).into_inner();
+    let gl_mat : Mat4 = glm::perspective(16.0f32/9.0f32, 3.14f32/2.0f32, 0.1f32, 100.0f32);
+
+    assert_eq!(na_mat, gl_mat);
+}
+
+#[test]
+pub fn orthographic_glm_nalgebra_project_same()
+{
+    let point = Vec4::new(1.0,0.0,-20.0,1.0);
+
+    let na_mat : Mat4 = Orthographic3::new(-100.0f32,100.0f32, -50.0f32, 50.0f32, 0.1f32, 100.0f32).into_inner();
+    let gl_mat : Mat4 = glm::ortho(-100.0f32,100.0f32, -50.0f32, 50.0f32, 0.1f32, 100.0f32);
+
+    let na_pt = na_mat * point;
+    let gl_pt = gl_mat * point;
+
+    assert_eq!(na_mat, gl_mat);
+    assert_eq!(na_pt, gl_pt);
+}
+
+#[test]
+pub fn perspective_glm_nalgebra_project_same()
+{
+    let point = Vec4::new(1.0,0.0,-20.0,1.0);
+
+    let na_mat : Mat4 = Perspective3::new(16.0f32/9.0f32, 3.14f32/2.0f32, 0.1f32, 100.0f32).into_inner();
+    let gl_mat : Mat4 = glm::perspective(16.0f32/9.0f32, 3.14f32/2.0f32, 0.1f32, 100.0f32);
+
+    let na_pt = na_mat * point;
+    let gl_pt = gl_mat * point;
+
+    assert_eq!(na_mat, gl_mat);
+    assert_eq!(na_pt, gl_pt);
+}

nalgebra-lapack/Cargo.toml

@@ -25,7 +25,7 @@ intel-mkl  = ["lapack-src/intel-mkl"]
 nalgebra      = { version = "0.16", path = ".." }
 num-traits    = "0.2"
 num-complex   = { version = "0.2", default-features = false }
-alga          = { version = "0.7", default-features = false }
+alga          = { version = "0.8", default-features = false }
 serde         = { version = "1.0", optional = true }
 serde_derive  = { version = "1.0", optional = true }
 lapack        = { version = "0.16", default-features = false }
@@ -34,6 +34,6 @@ lapack-src    = { version = "0.2", default-features = false }
 
 [dev-dependencies]
 nalgebra   = { version = "0.16", path = "..", features = [ "arbitrary" ] }
-quickcheck = "0.6"
+quickcheck = "0.8"
 approx     = "0.3"
-rand       = "0.5"
+rand       = "0.6"

nalgebra-lapack/src/cholesky.rs

@@ -160,7 +160,7 @@ where DefaultAllocator: Allocator<N, D, D>
         // Copy lower triangle to upper triangle.
         for i in 0..dim {
             for j in i + 1..dim {
-                unsafe { *self.l.get_unchecked_mut(i, j) = *self.l.get_unchecked(j, i) };
+                unsafe { *self.l.get_unchecked_mut((i, j)) = *self.l.get_unchecked((j, i)) };
             }
         }
 

nalgebra-lapack/src/lib.rs

@@ -68,8 +68,10 @@
 #![deny(unused_qualifications)]
 #![deny(unused_results)]
 #![deny(missing_docs)]
-#![doc(html_favicon_url = "http://nalgebra.org/img/favicon.ico",
+#![doc(
-       html_root_url = "http://nalgebra.org/rustdoc")]
+    html_favicon_url = "http://nalgebra.org/img/favicon.ico",
+    html_root_url = "http://nalgebra.org/rustdoc"
+)]
 
 extern crate alga;
 extern crate lapack;

src/base/alias.rs

@@ -2,7 +2,7 @@
 use base::dimension::Dynamic;
 use base::dimension::{U1, U2, U3, U4, U5, U6};
 #[cfg(any(feature = "std", feature = "alloc"))]
-use base::matrix_vec::MatrixVec;
+use base::vec_storage::VecStorage;
 use base::storage::Owned;
 use base::Matrix;
 
@@ -119,7 +119,7 @@ pub type Matrix6x5<N> = MatrixMN<N, U6, U5>;
  */
 /// A dynamically sized column vector.
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type DVector<N> = Matrix<N, Dynamic, U1, MatrixVec<N, Dynamic, U1>>;
+pub type DVector<N> = Matrix<N, Dynamic, U1, VecStorage<N, Dynamic, U1>>;
 
 /// A statically sized D-dimensional column vector.
 pub type VectorN<N, D> = MatrixMN<N, D, U1>;
@@ -146,7 +146,7 @@ pub type Vector6<N> = VectorN<N, U6>;
  */
 /// A dynamically sized row vector.
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub type RowDVector<N> = Matrix<N, U1, Dynamic, MatrixVec<N, U1, Dynamic>>;
+pub type RowDVector<N> = Matrix<N, U1, Dynamic, VecStorage<N, U1, Dynamic>>;
 
 /// A statically sized D-dimensional row vector.
 pub type RowVectorN<N, D> = MatrixMN<N, U1, D>;

src/base/alias_slice.rs

@@ -175,24 +175,24 @@ pub type MatrixSliceXx6<'a, N, RStride = U1, CStride = Dynamic> =
     MatrixSliceMN<'a, N, Dynamic, U6, RStride, CStride>;
 
 /// A column vector slice with `D` rows.
-pub type VectorSliceN<'a, N, D, Stride = U1> =
+pub type VectorSliceN<'a, N, D, RStride = U1, CStride = D> =
-    Matrix<N, D, U1, SliceStorage<'a, N, D, U1, Stride, D>>;
+    Matrix<N, D, U1, SliceStorage<'a, N, D, U1, RStride, CStride>>;
 
 /// A column vector slice dynamic numbers of rows and columns.
-pub type DVectorSlice<'a, N, Stride = U1> = VectorSliceN<'a, N, Dynamic, Stride>;
+pub type DVectorSlice<'a, N, RStride = U1, CStride = Dynamic> = VectorSliceN<'a, N, Dynamic, RStride, CStride>;
 
 /// A 1D column vector slice.
-pub type VectorSlice1<'a, N, Stride = U1> = VectorSliceN<'a, N, U1, Stride>;
+pub type VectorSlice1<'a, N, RStride = U1, CStride = U1> = VectorSliceN<'a, N, U1, RStride, CStride>;
 /// A 2D column vector slice.
-pub type VectorSlice2<'a, N, Stride = U1> = VectorSliceN<'a, N, U2, Stride>;
+pub type VectorSlice2<'a, N, RStride = U1, CStride = U2> = VectorSliceN<'a, N, U2, RStride, CStride>;
 /// A 3D column vector slice.
-pub type VectorSlice3<'a, N, Stride = U1> = VectorSliceN<'a, N, U3, Stride>;
+pub type VectorSlice3<'a, N, RStride = U1, CStride = U3> = VectorSliceN<'a, N, U3, RStride, CStride>;
 /// A 4D column vector slice.
-pub type VectorSlice4<'a, N, Stride = U1> = VectorSliceN<'a, N, U4, Stride>;
+pub type VectorSlice4<'a, N, RStride = U1, CStride = U4> = VectorSliceN<'a, N, U4, RStride, CStride>;
 /// A 5D column vector slice.
-pub type VectorSlice5<'a, N, Stride = U1> = VectorSliceN<'a, N, U5, Stride>;
+pub type VectorSlice5<'a, N, RStride = U1, CStride = U5> = VectorSliceN<'a, N, U5, RStride, CStride>;
 /// A 6D column vector slice.
-pub type VectorSlice6<'a, N, Stride = U1> = VectorSliceN<'a, N, U6, Stride>;
+pub type VectorSlice6<'a, N, RStride = U1, CStride = U6> = VectorSliceN<'a, N, U6, RStride, CStride>;
 
 /*
  *
@@ -367,21 +367,21 @@ pub type MatrixSliceMutXx6<'a, N, RStride = U1, CStride = Dynamic> =
     MatrixSliceMutMN<'a, N, Dynamic, U6, RStride, CStride>;
 
 /// A mutable column vector slice with `D` rows.
-pub type VectorSliceMutN<'a, N, D, Stride = U1> =
+pub type VectorSliceMutN<'a, N, D, RStride = U1, CStride = D> =
-    Matrix<N, D, U1, SliceStorageMut<'a, N, D, U1, Stride, D>>;
+    Matrix<N, D, U1, SliceStorageMut<'a, N, D, U1, RStride, CStride>>;
 
 /// A mutable column vector slice dynamic numbers of rows and columns.
-pub type DVectorSliceMut<'a, N, Stride = U1> = VectorSliceMutN<'a, N, Dynamic, Stride>;
+pub type DVectorSliceMut<'a, N, RStride = U1, CStride = Dynamic> = VectorSliceMutN<'a, N, Dynamic, RStride, CStride>;
 
 /// A 1D mutable column vector slice.
-pub type VectorSliceMut1<'a, N, Stride = U1> = VectorSliceMutN<'a, N, U1, Stride>;
+pub type VectorSliceMut1<'a, N, RStride = U1, CStride = U1> = VectorSliceMutN<'a, N, U1, RStride, CStride>;
 /// A 2D mutable column vector slice.
-pub type VectorSliceMut2<'a, N, Stride = U1> = VectorSliceMutN<'a, N, U2, Stride>;
+pub type VectorSliceMut2<'a, N, RStride = U1, CStride = U2> = VectorSliceMutN<'a, N, U2, RStride, CStride>;
 /// A 3D mutable column vector slice.
-pub type VectorSliceMut3<'a, N, Stride = U1> = VectorSliceMutN<'a, N, U3, Stride>;
+pub type VectorSliceMut3<'a, N, RStride = U1, CStride = U3> = VectorSliceMutN<'a, N, U3, RStride, CStride>;
 /// A 4D mutable column vector slice.
-pub type VectorSliceMut4<'a, N, Stride = U1> = VectorSliceMutN<'a, N, U4, Stride>;
+pub type VectorSliceMut4<'a, N, RStride = U1, CStride = U4> = VectorSliceMutN<'a, N, U4, RStride, CStride>;
 /// A 5D mutable column vector slice.
-pub type VectorSliceMut5<'a, N, Stride = U1> = VectorSliceMutN<'a, N, U5, Stride>;
+pub type VectorSliceMut5<'a, N, RStride = U1, CStride = U5> = VectorSliceMutN<'a, N, U5, RStride, CStride>;
 /// A 6D mutable column vector slice.
-pub type VectorSliceMut6<'a, N, Stride = U1> = VectorSliceMutN<'a, N, U6, Stride>;
+pub type VectorSliceMut6<'a, N, RStride = U1, CStride = U6> = VectorSliceMutN<'a, N, U6, RStride, CStride>;

src/base/array_storage.rs

@@ -34,7 +34,7 @@ use base::Scalar;
  */
 /// A array-based statically sized matrix data storage.
 #[repr(C)]
-pub struct MatrixArray<N, R, C>
+pub struct ArrayStorage<N, R, C>
 where
     R: DimName,
     C: DimName,
@@ -44,7 +44,11 @@ where
     data: GenericArray<N, Prod<R::Value, C::Value>>,
 }
 
-impl<N, R, C> Hash for MatrixArray<N, R, C>
+#[deprecated(note="renamed to `ArrayStorage`")]
+/// Renamed to [ArrayStorage].
+pub type MatrixArray<N, R, C> = ArrayStorage<N, R, C>;
+
+impl<N, R, C> Hash for ArrayStorage<N, R, C>
 where
     N: Hash,
     R: DimName,
@@ -57,7 +61,7 @@ where
     }
 }
 
-impl<N, R, C> Deref for MatrixArray<N, R, C>
+impl<N, R, C> Deref for ArrayStorage<N, R, C>
 where
     R: DimName,
     C: DimName,
@@ -72,7 +76,7 @@ where
     }
 }
 
-impl<N, R, C> DerefMut for MatrixArray<N, R, C>
+impl<N, R, C> DerefMut for ArrayStorage<N, R, C>
 where
     R: DimName,
     C: DimName,
@@ -85,7 +89,7 @@ where
     }
 }
 
-impl<N, R, C> Debug for MatrixArray<N, R, C>
+impl<N, R, C> Debug for ArrayStorage<N, R, C>
 where
     N: Debug,
     R: DimName,
@@ -99,7 +103,7 @@ where
     }
 }
 
-impl<N, R, C> Copy for MatrixArray<N, R, C>
+impl<N, R, C> Copy for ArrayStorage<N, R, C>
 where
     N: Copy,
     R: DimName,
@@ -109,7 +113,7 @@ where
     GenericArray<N, Prod<R::Value, C::Value>>: Copy,
 {}
 
-impl<N, R, C> Clone for MatrixArray<N, R, C>
+impl<N, R, C> Clone for ArrayStorage<N, R, C>
 where
     N: Clone,
     R: DimName,
@@ -119,13 +123,13 @@ where
 {
     #[inline]
     fn clone(&self) -> Self {
-        MatrixArray {
+        ArrayStorage {
             data: self.data.clone(),
         }
     }
 }
 
-impl<N, R, C> Eq for MatrixArray<N, R, C>
+impl<N, R, C> Eq for ArrayStorage<N, R, C>
 where
     N: Eq,
     R: DimName,
@@ -134,7 +138,7 @@ where
     Prod<R::Value, C::Value>: ArrayLength<N>,
 {}
 
-impl<N, R, C> PartialEq for MatrixArray<N, R, C>
+impl<N, R, C> PartialEq for ArrayStorage<N, R, C>
 where
     N: PartialEq,
     R: DimName,
@@ -148,7 +152,7 @@ where
     }
 }
 
-unsafe impl<N, R, C> Storage<N, R, C> for MatrixArray<N, R, C>
+unsafe impl<N, R, C> Storage<N, R, C> for ArrayStorage<N, R, C>
 where
     N: Scalar,
     R: DimName,
@@ -200,7 +204,7 @@ where
     }
 }
 
-unsafe impl<N, R, C> StorageMut<N, R, C> for MatrixArray<N, R, C>
+unsafe impl<N, R, C> StorageMut<N, R, C> for ArrayStorage<N, R, C>
 where
     N: Scalar,
     R: DimName,
@@ -220,7 +224,7 @@ where
     }
 }
 
-unsafe impl<N, R, C> ContiguousStorage<N, R, C> for MatrixArray<N, R, C>
+unsafe impl<N, R, C> ContiguousStorage<N, R, C> for ArrayStorage<N, R, C>
 where
     N: Scalar,
     R: DimName,
@@ -230,7 +234,7 @@ where
     DefaultAllocator: Allocator<N, R, C, Buffer = Self>,
 {}
 
-unsafe impl<N, R, C> ContiguousStorageMut<N, R, C> for MatrixArray<N, R, C>
+unsafe impl<N, R, C> ContiguousStorageMut<N, R, C> for ArrayStorage<N, R, C>
 where
     N: Scalar,
     R: DimName,
@@ -247,7 +251,7 @@ where
  */
 // XXX: open an issue for GenericArray so that it implements serde traits?
 #[cfg(feature = "serde-serialize")]
-impl<N, R, C> Serialize for MatrixArray<N, R, C>
+impl<N, R, C> Serialize for ArrayStorage<N, R, C>
 where
     N: Scalar + Serialize,
     R: DimName,
@@ -268,7 +272,7 @@ where
 }
 
 #[cfg(feature = "serde-serialize")]
-impl<'a, N, R, C> Deserialize<'a> for MatrixArray<N, R, C>
+impl<'a, N, R, C> Deserialize<'a> for ArrayStorage<N, R, C>
 where
     N: Scalar + Deserialize<'a>,
     R: DimName,
@@ -278,18 +282,18 @@ where
 {
     fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
     where D: Deserializer<'a> {
-        deserializer.deserialize_seq(MatrixArrayVisitor::new())
+        deserializer.deserialize_seq(ArrayStorageVisitor::new())
     }
 }
 
 #[cfg(feature = "serde-serialize")]
 /// A visitor that produces a matrix array.
-struct MatrixArrayVisitor<N, R, C> {
+struct ArrayStorageVisitor<N, R, C> {
     marker: PhantomData<(N, R, C)>,
 }
 
 #[cfg(feature = "serde-serialize")]
-impl<N, R, C> MatrixArrayVisitor<N, R, C>
+impl<N, R, C> ArrayStorageVisitor<N, R, C>
 where
     N: Scalar,
     R: DimName,
@@ -299,14 +303,14 @@ where
 {
     /// Construct a new sequence visitor.
     pub fn new() -> Self {
-        MatrixArrayVisitor {
+        ArrayStorageVisitor {
             marker: PhantomData,
         }
     }
 }
 
 #[cfg(feature = "serde-serialize")]
-impl<'a, N, R, C> Visitor<'a> for MatrixArrayVisitor<N, R, C>
+impl<'a, N, R, C> Visitor<'a> for ArrayStorageVisitor<N, R, C>
 where
     N: Scalar + Deserialize<'a>,
     R: DimName,
@@ -314,20 +318,20 @@ where
     R::Value: Mul<C::Value>,
     Prod<R::Value, C::Value>: ArrayLength<N>,
 {
-    type Value = MatrixArray<N, R, C>;
+    type Value = ArrayStorage<N, 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<MatrixArray<N, R, C>, V::Error>
+    fn visit_seq<V>(self, mut visitor: V) -> Result<ArrayStorage<N, R, C>, V::Error>
     where V: SeqAccess<'a> {
         let mut out: Self::Value = unsafe { mem::uninitialized() };
         let mut curr = 0;
 
         while let Some(value) = try!(visitor.next_element()) {
-            out[curr] = value;
+            *out.get_mut(curr).ok_or_else(|| V::Error::invalid_length(curr, &self))? = value;
             curr += 1;
         }
 
@@ -340,7 +344,7 @@ where
 }
 
 #[cfg(feature = "abomonation-serialize")]
-impl<N, R, C> Abomonation for MatrixArray<N, R, C>
+impl<N, R, C> Abomonation for ArrayStorage<N, R, C>
 where
     R: DimName,
     C: DimName,

src/base/blas.rs

@@ -13,18 +13,18 @@ use base::dimension::{Dim, Dynamic, U1, U2, U3, U4};
 use base::storage::{Storage, StorageMut};
 use base::{DefaultAllocator, Matrix, Scalar, SquareMatrix, Vector};
 
-impl<N: Scalar + PartialOrd + Signed, D: Dim, S: Storage<N, D>> Vector<N, D, S> {
+impl<N: Scalar + PartialOrd, D: Dim, S: Storage<N, D>> Vector<N, D, S> {
-    /// Computes the index of the vector component with the largest value.
+    /// Computes the index and value of the vector component with the largest value.
     ///
     /// # Examples:
     ///
     /// ```
     /// # use nalgebra::Vector3;
     /// let vec = Vector3::new(11, -15, 13);
-    /// assert_eq!(vec.imax(), 2);
+    /// assert_eq!(vec.argmax(), (2, 13));
     /// ```
     #[inline]
-    pub fn imax(&self) -> usize {
+    pub fn argmax(&self) -> (usize, N) {
         assert!(!self.is_empty(), "The input vector must not be empty.");
 
         let mut the_max = unsafe { self.vget_unchecked(0) };
@@ -39,7 +39,21 @@ impl<N: Scalar + PartialOrd + Signed, D: Dim, S: Storage<N, D>> Vector<N, D, S>
             }
         }
 
-        the_i
+        (the_i, *the_max)
+    }
+
+    /// Computes the index of the vector component with the largest value.
+    ///
+    /// # Examples:
+    ///
+    /// ```
+    /// # use nalgebra::Vector3;
+    /// let vec = Vector3::new(11, -15, 13);
+    /// assert_eq!(vec.imax(), 2);
+    /// ```
+    #[inline]
+    pub fn imax(&self) -> usize {
+        self.argmax().0
     }
 
     /// Computes the index of the vector component with the largest absolute value.
@@ -52,7 +66,8 @@ impl<N: Scalar + PartialOrd + Signed, D: Dim, S: Storage<N, D>> Vector<N, D, S>
     /// assert_eq!(vec.iamax(), 1);
     /// ```
     #[inline]
-    pub fn iamax(&self) -> usize {
+    pub fn iamax(&self) -> usize
+        where N: Signed {
         assert!(!self.is_empty(), "The input vector must not be empty.");
 
         let mut the_max = unsafe { self.vget_unchecked(0).abs() };
@@ -70,6 +85,34 @@ impl<N: Scalar + PartialOrd + Signed, D: Dim, S: Storage<N, D>> Vector<N, D, S>
         the_i
     }
 
+    /// Computes the index and value of the vector component with the smallest value.
+    ///
+    /// # Examples:
+    ///
+    /// ```
+    /// # use nalgebra::Vector3;
+    /// let vec = Vector3::new(11, -15, 13);
+    /// assert_eq!(vec.argmin(), (1, -15));
+    /// ```
+    #[inline]
+    pub fn argmin(&self) -> (usize, N) {
+        assert!(!self.is_empty(), "The input vector must not be empty.");
+
+        let mut the_min = unsafe { self.vget_unchecked(0) };
+        let mut the_i = 0;
+
+        for i in 1..self.nrows() {
+            let val = unsafe { self.vget_unchecked(i) };
+
+            if val < the_min {
+                the_min = val;
+                the_i = i;
+            }
+        }
+
+        (the_i, *the_min)
+    }
+
     /// Computes the index of the vector component with the smallest value.
     ///
     /// # Examples:
@@ -81,21 +124,7 @@ impl<N: Scalar + PartialOrd + Signed, D: Dim, S: Storage<N, D>> Vector<N, D, S>
     /// ```
     #[inline]
     pub fn imin(&self) -> usize {
-        assert!(!self.is_empty(), "The input vector must not be empty.");
+        self.argmin().0
-
-        let mut the_max = unsafe { self.vget_unchecked(0) };
-        let mut the_i = 0;
-
-        for i in 1..self.nrows() {
-            let val = unsafe { self.vget_unchecked(i) };
-
-            if val < the_max {
-                the_max = val;
-                the_i = i;
-            }
-        }
-
-        the_i
     }
 
     /// Computes the index of the vector component with the smallest absolute value.
@@ -108,17 +137,18 @@ impl<N: Scalar + PartialOrd + Signed, D: Dim, S: Storage<N, D>> Vector<N, D, S>
     /// assert_eq!(vec.iamin(), 0);
     /// ```
     #[inline]
-    pub fn iamin(&self) -> usize {
+    pub fn iamin(&self) -> usize
+        where N: Signed {
         assert!(!self.is_empty(), "The input vector must not be empty.");
 
-        let mut the_max = unsafe { self.vget_unchecked(0).abs() };
+        let mut the_min = unsafe { self.vget_unchecked(0).abs() };
         let mut the_i = 0;
 
         for i in 1..self.nrows() {
             let val = unsafe { self.vget_unchecked(i).abs() };
 
-            if val < the_max {
+            if val < the_min {
-                the_max = val;
+                the_min = val;
                 the_i = i;
             }
         }
@@ -142,12 +172,12 @@ impl<N: Scalar + PartialOrd + Signed, R: Dim, C: Dim, S: Storage<N, R, C>> Matri
     pub fn iamax_full(&self) -> (usize, usize) {
         assert!(!self.is_empty(), "The input matrix must not be empty.");
 
-        let mut the_max = unsafe { self.get_unchecked(0, 0).abs() };
+        let mut the_max = unsafe { self.get_unchecked((0, 0)).abs() };
         let mut the_ij = (0, 0);
 
         for j in 0..self.ncols() {
             for i in 0..self.nrows() {
-                let val = unsafe { self.get_unchecked(i, j).abs() };
+                let val = unsafe { self.get_unchecked((i, j)).abs() };
 
                 if val > the_max {
                     the_max = val;
@@ -197,27 +227,27 @@ where N: Scalar + Zero + ClosedAdd + ClosedMul
         // because the `for` loop below won't be very efficient on those.
         if (R::is::<U2>() || R2::is::<U2>()) && (C::is::<U1>() || C2::is::<U1>()) {
             unsafe {
-                let a = *self.get_unchecked(0, 0) * *rhs.get_unchecked(0, 0);
+                let a = *self.get_unchecked((0, 0)) * *rhs.get_unchecked((0, 0));
-                let b = *self.get_unchecked(1, 0) * *rhs.get_unchecked(1, 0);
+                let b = *self.get_unchecked((1, 0)) * *rhs.get_unchecked((1, 0));
 
                 return a + b;
             }
         }
         if (R::is::<U3>() || R2::is::<U3>()) && (C::is::<U1>() || C2::is::<U1>()) {
             unsafe {
-                let a = *self.get_unchecked(0, 0) * *rhs.get_unchecked(0, 0);
+                let a = *self.get_unchecked((0, 0)) * *rhs.get_unchecked((0, 0));
-                let b = *self.get_unchecked(1, 0) * *rhs.get_unchecked(1, 0);
+                let b = *self.get_unchecked((1, 0)) * *rhs.get_unchecked((1, 0));
-                let c = *self.get_unchecked(2, 0) * *rhs.get_unchecked(2, 0);
+                let c = *self.get_unchecked((2, 0)) * *rhs.get_unchecked((2, 0));
 
                 return a + b + c;
             }
         }
         if (R::is::<U4>() || R2::is::<U4>()) && (C::is::<U1>() || C2::is::<U1>()) {
             unsafe {
-                let mut a = *self.get_unchecked(0, 0) * *rhs.get_unchecked(0, 0);
+                let mut a = *self.get_unchecked((0, 0)) * *rhs.get_unchecked((0, 0));
-                let mut b = *self.get_unchecked(1, 0) * *rhs.get_unchecked(1, 0);
+                let mut b = *self.get_unchecked((1, 0)) * *rhs.get_unchecked((1, 0));
-                let c = *self.get_unchecked(2, 0) * *rhs.get_unchecked(2, 0);
+                let c = *self.get_unchecked((2, 0)) * *rhs.get_unchecked((2, 0));
-                let d = *self.get_unchecked(3, 0) * *rhs.get_unchecked(3, 0);
+                let d = *self.get_unchecked((3, 0)) * *rhs.get_unchecked((3, 0));
 
                 a += c;
                 b += d;
@@ -257,14 +287,14 @@ where N: Scalar + Zero + ClosedAdd + ClosedMul
             acc7 = N::zero();
 
             while self.nrows() - i >= 8 {
-                acc0 += unsafe { *self.get_unchecked(i + 0, j) * *rhs.get_unchecked(i + 0, j) };
+                acc0 += unsafe { *self.get_unchecked((i + 0, j)) * *rhs.get_unchecked((i + 0, j)) };
-                acc1 += unsafe { *self.get_unchecked(i + 1, j) * *rhs.get_unchecked(i + 1, j) };
+                acc1 += unsafe { *self.get_unchecked((i + 1, j)) * *rhs.get_unchecked((i + 1, j)) };
-                acc2 += unsafe { *self.get_unchecked(i + 2, j) * *rhs.get_unchecked(i + 2, j) };
+                acc2 += unsafe { *self.get_unchecked((i + 2, j)) * *rhs.get_unchecked((i + 2, j)) };
-                acc3 += unsafe { *self.get_unchecked(i + 3, j) * *rhs.get_unchecked(i + 3, j) };
+                acc3 += unsafe { *self.get_unchecked((i + 3, j)) * *rhs.get_unchecked((i + 3, j)) };
-                acc4 += unsafe { *self.get_unchecked(i + 4, j) * *rhs.get_unchecked(i + 4, j) };
+                acc4 += unsafe { *self.get_unchecked((i + 4, j)) * *rhs.get_unchecked((i + 4, j)) };
-                acc5 += unsafe { *self.get_unchecked(i + 5, j) * *rhs.get_unchecked(i + 5, j) };
+                acc5 += unsafe { *self.get_unchecked((i + 5, j)) * *rhs.get_unchecked((i + 5, j)) };
-                acc6 += unsafe { *self.get_unchecked(i + 6, j) * *rhs.get_unchecked(i + 6, j) };
+                acc6 += unsafe { *self.get_unchecked((i + 6, j)) * *rhs.get_unchecked((i + 6, j)) };
-                acc7 += unsafe { *self.get_unchecked(i + 7, j) * *rhs.get_unchecked(i + 7, j) };
+                acc7 += unsafe { *self.get_unchecked((i + 7, j)) * *rhs.get_unchecked((i + 7, j)) };
                 i += 8;
             }
 
@@ -274,7 +304,7 @@ where N: Scalar + Zero + ClosedAdd + ClosedMul
             res += acc3 + acc7;
 
             for k in i..self.nrows() {
-                res += unsafe { *self.get_unchecked(k, j) * *rhs.get_unchecked(k, j) }
+                res += unsafe { *self.get_unchecked((k, j)) * *rhs.get_unchecked((k, j)) }
             }
         }
 
@@ -314,7 +344,7 @@ where N: Scalar + Zero + ClosedAdd + ClosedMul
 
         for j in 0..self.nrows() {
             for i in 0..self.ncols() {
-                res += unsafe { *self.get_unchecked(j, i) * *rhs.get_unchecked(i, j) }
+                res += unsafe { *self.get_unchecked((j, i)) * *rhs.get_unchecked((i, j)) }
             }
         }
 
@@ -627,7 +657,6 @@ where N: Scalar + Zero + ClosedAdd + ClosedMul
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Matrix2x3, Matrix3x4, Matrix2x4};
     /// let mut mat1 = Matrix2x4::identity();
     /// let mat2 = Matrix2x3::new(1.0, 2.0, 3.0,
@@ -760,7 +789,6 @@ where N: Scalar + Zero + ClosedAdd + ClosedMul
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Matrix3x2, Matrix3x4, Matrix2x4};
     /// let mut mat1 = Matrix2x4::identity();
     /// let mat2 = Matrix3x2::new(1.0, 4.0,
@@ -879,7 +907,6 @@ where N: Scalar + Zero + One + ClosedAdd + ClosedMul
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{DMatrix, DVector};
     /// // Note that all those would also work with statically-sized matrices.
     /// // We use DMatrix/DVector since that's the only case where pre-allocating the
@@ -934,7 +961,6 @@ where N: Scalar + Zero + One + ClosedAdd + ClosedMul
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Matrix2, Matrix3, Matrix2x3, Vector2};
     /// let mut mat = Matrix2::identity();
     /// let lhs = Matrix2x3::new(1.0, 2.0, 3.0,
@@ -971,7 +997,6 @@ where N: Scalar + Zero + One + ClosedAdd + ClosedMul
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{DMatrix, DVector};
     /// // Note that all those would also work with statically-sized matrices.
     /// // We use DMatrix/DVector since that's the only case where pre-allocating the
@@ -1026,7 +1051,6 @@ where N: Scalar + Zero + One + ClosedAdd + ClosedMul
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Matrix2, Matrix3x2, Matrix3};
     /// let mut mat = Matrix2::identity();
     /// let rhs = Matrix3x2::new(1.0, 2.0,

src/base/cg.rs

@@ -115,13 +115,13 @@ impl<N: Real> Matrix4<N> {
     /// 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 {
-        Orthographic3::new(left, right, bottom, top, znear, zfar).unwrap()
+        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 {
-        Perspective3::new(aspect, fovy, znear, zfar).unwrap()
+        Perspective3::new(aspect, fovy, znear, zfar).into_inner()
     }
 
     /// Creates an isometry that corresponds to the local frame of an observer standing at the
@@ -130,8 +130,14 @@ impl<N: Real> 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 {
+        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 {
-        IsometryMatrix3::new_observer_frame(eye, target, up).to_homogeneous()
+        Matrix4::face_towards(eye, target, up)
     }
 
     /// Builds a right-handed look-at view matrix.
@@ -348,7 +354,7 @@ where DefaultAllocator: Allocator<N, D, D>
         let translation = self.fixed_slice::<DimNameDiff<D, U1>, U1>(0, D::dim() - 1);
         let normalizer = self.fixed_slice::<U1, DimNameDiff<D, U1>>(D::dim() - 1, 0);
         let n = normalizer.tr_dot(&pt.coords)
-            + unsafe { *self.get_unchecked(D::dim() - 1, D::dim() - 1) };
+            + unsafe { *self.get_unchecked((D::dim() - 1, D::dim() - 1)) };
 
         if !n.is_zero() {
             return transform * (pt / n) + translation;

src/base/componentwise.rs

@@ -1,4 +1,4 @@
-// Non-conventional componentwise operators.
+// Non-conventional component-wise operators.
 
 use num::{Signed, Zero};
 use std::ops::{Add, Mul};
@@ -61,7 +61,7 @@ macro_rules! component_binop_impl(
                 for j in 0 .. res.ncols() {
                     for i in 0 .. res.nrows() {
                         unsafe {
-                            res.get_unchecked_mut(i, j).$op_assign(*rhs.get_unchecked(i, j));
+                            res.get_unchecked_mut((i, j)).$op_assign(*rhs.get_unchecked((i, j)));
                         }
                     }
                 }
@@ -89,8 +89,8 @@ macro_rules! component_binop_impl(
                     for j in 0 .. self.ncols() {
                         for i in 0 .. self.nrows() {
                             unsafe {
-                                let res = alpha * a.get_unchecked(i, j).$op(*b.get_unchecked(i, j));
+                                let res = alpha * a.get_unchecked((i, j)).$op(*b.get_unchecked((i, j)));
-                                *self.get_unchecked_mut(i, j) = res;
+                                *self.get_unchecked_mut((i, j)) = res;
                             }
                         }
                     }
@@ -99,8 +99,8 @@ macro_rules! component_binop_impl(
                     for j in 0 .. self.ncols() {
                         for i in 0 .. self.nrows() {
                             unsafe {
-                                let res = alpha * a.get_unchecked(i, j).$op(*b.get_unchecked(i, j));
+                                let res = alpha * a.get_unchecked((i, j)).$op(*b.get_unchecked((i, j)));
-                                *self.get_unchecked_mut(i, j) = beta * *self.get_unchecked(i, j) + res;
+                                *self.get_unchecked_mut((i, j)) = beta * *self.get_unchecked((i, j)) + res;
                             }
                         }
                     }
@@ -121,7 +121,7 @@ macro_rules! component_binop_impl(
                 for j in 0 .. self.ncols() {
                     for i in 0 .. self.nrows() {
                         unsafe {
-                            self.get_unchecked_mut(i, j).$op_assign(*rhs.get_unchecked(i, j));
+                            self.get_unchecked_mut((i, j)).$op_assign(*rhs.get_unchecked((i, j)));
                         }
                     }
                 }

src/base/construction.rs

@@ -82,7 +82,7 @@ where DefaultAllocator: Allocator<N, R, C>
 
         for i in 0..nrows.value() {
             for j in 0..ncols.value() {
-                unsafe { *res.get_unchecked_mut(i, j) = *iter.next().unwrap() }
+                unsafe { *res.get_unchecked_mut((i, j)) = *iter.next().unwrap() }
             }
         }
 
@@ -105,7 +105,7 @@ where DefaultAllocator: Allocator<N, R, C>
 
         for j in 0..ncols.value() {
             for i in 0..nrows.value() {
-                unsafe { *res.get_unchecked_mut(i, j) = f(i, j) }
+                unsafe { *res.get_unchecked_mut((i, j)) = f(i, j) }
             }
         }
 
@@ -132,7 +132,7 @@ where DefaultAllocator: Allocator<N, R, C>
         let mut res = Self::zeros_generic(nrows, ncols);
 
         for i in 0..::min(nrows.value(), ncols.value()) {
-            unsafe { *res.get_unchecked_mut(i, i) = elt }
+            unsafe { *res.get_unchecked_mut((i, i)) = elt }
         }
 
         res
@@ -152,7 +152,7 @@ where DefaultAllocator: Allocator<N, R, C>
         );
 
         for (i, elt) in elts.iter().enumerate() {
-            unsafe { *res.get_unchecked_mut(i, i) = *elt }
+            unsafe { *res.get_unchecked_mut((i, i)) = *elt }
         }
 
         res
@@ -270,7 +270,7 @@ where DefaultAllocator: Allocator<N, R, C>
     /// let vec_ptr = vec.as_ptr();
     ///
     /// let matrix = Matrix::from_vec_generic(Dynamic::new(vec.len()), U1, vec);
-    /// let matrix_storage_ptr = matrix.data.as_ptr();
+    /// let matrix_storage_ptr = matrix.data.as_vec().as_ptr();
     ///
     /// // `matrix` is backed by exactly the same `Vec` as it was constructed from.
     /// assert_eq!(matrix_storage_ptr, vec_ptr);
@@ -296,7 +296,7 @@ where
     ///
     /// let m = Matrix3::from_diagonal(&Vector3::new(1.0, 2.0, 3.0));
     /// // The two additional arguments represent the matrix dimensions.
-    /// let dm = DMatrix::from_diagonal(&DVector::from_row_slice(3, &[1.0, 2.0, 3.0]));
+    /// let dm = DMatrix::from_diagonal(&DVector::from_row_slice(&[1.0, 2.0, 3.0]));
     ///
     /// assert!(m.m11 == 1.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
     ///         m.m21 == 0.0 && m.m22 == 2.0 && m.m23 == 0.0 &&
@@ -313,7 +313,7 @@ where
 
         for i in 0..diag.len() {
             unsafe {
-                *res.get_unchecked_mut(i, i) = *diag.vget_unchecked(i);
+                *res.get_unchecked_mut((i, i)) = *diag.vget_unchecked(i);
             }
         }
 
@@ -444,63 +444,6 @@ macro_rules! impl_constructors(
                 Self::from_iterator_generic($($gargs, )* iter)
             }
 
-            /// Creates a matrix with its elements filled with the components provided by a slice
-            /// in row-major order.
-            ///
-            /// The order of elements in the slice must follow the usual mathematic writing, i.e.,
-            /// row-by-row.
-            ///
-            /// # Example
-            /// ```
-            /// # use nalgebra::{Matrix2x3, Vector3, DVector, DMatrix};
-            /// # use std::iter;
-            ///
-            /// let v = Vector3::from_row_slice(&[0, 1, 2]);
-            /// // The additional argument represents the vector dimension.
-            /// let dv = DVector::from_row_slice(3, &[0, 1, 2]);
-            /// let m = Matrix2x3::from_row_slice(&[0, 1, 2, 3, 4, 5]);
-            /// // The two additional arguments represent the matrix dimensions.
-            /// let dm = DMatrix::from_row_slice(2, 3, &[0, 1, 2, 3, 4, 5]);
-            ///
-            /// assert!(v.x == 0 && v.y == 1 && v.z == 2);
-            /// assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
-            /// assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
-            ///         m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
-            /// assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
-            ///         dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
-            /// ```
-            #[inline]
-            pub fn from_row_slice($($args: usize,)* slice: &[N]) -> Self {
-                Self::from_row_slice_generic($($gargs, )* slice)
-            }
-
-            /// Creates a matrix with its elements filled with the components provided by a slice
-            /// in column-major order.
-            ///
-            /// # Example
-            /// ```
-            /// # use nalgebra::{Matrix2x3, Vector3, DVector, DMatrix};
-            /// # use std::iter;
-            ///
-            /// let v = Vector3::from_column_slice(&[0, 1, 2]);
-            /// // The additional argument represents the vector dimension.
-            /// let dv = DVector::from_column_slice(3, &[0, 1, 2]);
-            /// let m = Matrix2x3::from_column_slice(&[0, 1, 2, 3, 4, 5]);
-            /// // The two additional arguments represent the matrix dimensions.
-            /// let dm = DMatrix::from_column_slice(2, 3, &[0, 1, 2, 3, 4, 5]);
-            ///
-            /// assert!(v.x == 0 && v.y == 1 && v.z == 2);
-            /// assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
-            /// assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
-            ///         m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
-            /// assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
-            ///         dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
-            /// ```
-            #[inline]
-            pub fn from_column_slice($($args: usize,)* slice: &[N]) -> Self {
-                Self::from_column_slice_generic($($gargs, )* slice)
-            }
-
             /// Creates a matrix or vector filled with the results of a function applied to each of its
             /// component coordinates.
             ///
@@ -612,32 +555,6 @@ macro_rules! impl_constructors(
             ) -> Self {
                 Self::from_distribution_generic($($gargs, )* distribution, rng)
             }
-
-            /// Creates a matrix backed by a given `Vec`.
-            ///
-            /// The output matrix is filled column-by-column.
-            ///
-            /// # Example
-            /// ```
-            /// # use nalgebra::{DMatrix, Matrix2x3};
-            ///
-            /// let m = Matrix2x3::from_vec(vec![0, 1, 2, 3, 4, 5]);
-            ///
-            /// assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
-            ///         m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
-            ///
-            ///
-            /// // The two additional arguments represent the matrix dimensions.
-            /// let dm = DMatrix::from_vec(2, 3, vec![0, 1, 2, 3, 4, 5]);
-            ///
-            /// assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
-            ///         dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
-            /// ```
-            #[inline]
-            #[cfg(feature = "std")]
-            pub fn from_vec($($args: usize,)* data: Vec<N>) -> Self {
-                Self::from_vec_generic($($gargs, )* data)
-            }
         }
 
         impl<N: Scalar, $($DimIdent: $DimBound, )*> MatrixMN<N $(, $Dims)*>
@@ -676,6 +593,125 @@ impl_constructors!(Dynamic, Dynamic;
                    Dynamic::new(nrows), Dynamic::new(ncols);
                    nrows, ncols);
 
+/*
+ *
+ * Constructors that don't necessarily require all dimensions
+ * to be specified whon one dimension is already known.
+ *
+ */
+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 $(, $Dims)*> {
+            /// Creates a matrix with its elements filled with the components provided by a slice
+            /// in row-major order.
+            ///
+            /// The order of elements in the slice must follow the usual mathematic writing, i.e.,
+            /// row-by-row.
+            ///
+            /// # Example
+            /// ```
+            /// # use nalgebra::{Matrix2x3, Vector3, DVector, DMatrix};
+            /// # use std::iter;
+            ///
+            /// let v = Vector3::from_row_slice(&[0, 1, 2]);
+            /// // The additional argument represents the vector dimension.
+            /// let dv = DVector::from_row_slice(&[0, 1, 2]);
+            /// let m = Matrix2x3::from_row_slice(&[0, 1, 2, 3, 4, 5]);
+            /// // The two additional arguments represent the matrix dimensions.
+            /// let dm = DMatrix::from_row_slice(2, 3, &[0, 1, 2, 3, 4, 5]);
+            ///
+            /// assert!(v.x == 0 && v.y == 1 && v.z == 2);
+            /// assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
+            /// assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
+            ///         m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
+            /// assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
+            ///         dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
+            /// ```
+            #[inline]
+            pub fn from_row_slice($($args: usize,)* $data: &[N]) -> Self {
+                Self::from_row_slice_generic($($gargs, )* $data)
+            }
+
+            /// Creates a matrix with its elements filled with the components provided by a slice
+            /// in column-major order.
+            ///
+            /// # Example
+            /// ```
+            /// # use nalgebra::{Matrix2x3, Vector3, DVector, DMatrix};
+            /// # use std::iter;
+            ///
+            /// let v = Vector3::from_column_slice(&[0, 1, 2]);
+            /// // The additional argument represents the vector dimension.
+            /// let dv = DVector::from_column_slice(&[0, 1, 2]);
+            /// let m = Matrix2x3::from_column_slice(&[0, 1, 2, 3, 4, 5]);
+            /// // The two additional arguments represent the matrix dimensions.
+            /// let dm = DMatrix::from_column_slice(2, 3, &[0, 1, 2, 3, 4, 5]);
+            ///
+            /// assert!(v.x == 0 && v.y == 1 && v.z == 2);
+            /// assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
+            /// assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
+            ///         m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
+            /// assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
+            ///         dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
+            /// ```
+            #[inline]
+            pub fn from_column_slice($($args: usize,)* $data: &[N]) -> Self {
+                Self::from_column_slice_generic($($gargs, )* $data)
+            }
+
+            /// Creates a matrix backed by a given `Vec`.
+            ///
+            /// The output matrix is filled column-by-column.
+            ///
+            /// # Example
+            /// ```
+            /// # use nalgebra::{DMatrix, Matrix2x3};
+            ///
+            /// let m = Matrix2x3::from_vec(vec![0, 1, 2, 3, 4, 5]);
+            ///
+            /// assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
+            ///         m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
+            ///
+            ///
+            /// // The two additional arguments represent the matrix dimensions.
+            /// let dm = DMatrix::from_vec(2, 3, vec![0, 1, 2, 3, 4, 5]);
+            ///
+            /// assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
+            ///         dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
+            /// ```
+            #[inline]
+            #[cfg(feature = "std")]
+            pub fn from_vec($($args: usize,)* $data: Vec<N>) -> Self {
+                Self::from_vec_generic($($gargs, )* $data)
+            }
+        }
+    }
+);
+
+// FIXME: this is not very pretty. We could find a better call syntax.
+impl_constructors_from_data!(data; R, C;                  // Arguments for Matrix<N, ..., S>
+                            => R: DimName, => C: DimName; // Type parameters for impl<N, ..., S>
+                            R::name(), C::name();         // Arguments for `_generic` constructors.
+                            ); // Arguments for non-generic constructors.
+
+impl_constructors_from_data!(data; R, Dynamic;
+                            => R: DimName;
+                            R::name(), Dynamic::new(data.len() / R::dim());
+                            );
+
+impl_constructors_from_data!(data; Dynamic, C;
+                            => C: DimName;
+                            Dynamic::new(data.len() / C::dim()), C::name();
+                            );
+
+impl_constructors_from_data!(data; Dynamic, Dynamic;
+                            ;
+                            Dynamic::new(nrows), Dynamic::new(ncols);
+                            nrows, ncols);
+
+
+
 /*
  *
  * Zero, One, Rand traits.
@@ -791,7 +827,7 @@ macro_rules! componentwise_constructors_impl(
             pub fn new($($args: N),*) -> Self {
                 unsafe {
                     let mut res = Self::new_uninitialized();
-                    $( *res.get_unchecked_mut($irow, $icol) = $args; )*
+                    $( *res.get_unchecked_mut(($irow, $icol)) = $args; )*
 
                     res
                 }

src/base/conversion.rs

@@ -12,13 +12,15 @@ use typenum::Prod;
 use base::allocator::{Allocator, SameShapeAllocator};
 use base::constraint::{SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
 use base::dimension::{
-    Dim, DimName, Dynamic, U1, U10, U11, U12, U13, U14, U15, U16, U2, U3, U4, U5, U6, U7, U8, U9,
+    Dim, DimName, U1, U10, U11, U12, U13, U14, U15, U16, U2, U3, U4, U5, U6, U7, U8, U9,
 };
+#[cfg(any(feature = "std", feature = "alloc"))]
+use base::dimension::Dynamic;
 use base::iter::{MatrixIter, MatrixIterMut};
 use base::storage::{ContiguousStorage, ContiguousStorageMut, Storage, StorageMut};
 #[cfg(any(feature = "std", feature = "alloc"))]
-use base::MatrixVec;
+use base::VecStorage;
-use base::{DefaultAllocator, Matrix, MatrixArray, MatrixMN, MatrixSlice, MatrixSliceMut, Scalar};
+use base::{DefaultAllocator, Matrix, ArrayStorage, MatrixMN, MatrixSlice, MatrixSliceMut, Scalar};
 
 // FIXME: 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>
@@ -42,7 +44,7 @@ where
         let mut res = unsafe { MatrixMN::<N2, R2, C2>::new_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)) }
+                unsafe { *res.get_unchecked_mut((i, j)) = N2::from_subset(self.get_unchecked((i, j))) }
             }
         }
 
@@ -63,7 +65,7 @@ where
         let mut res = Self::new_uninitialized_generic(nrows, ncols);
         for i in 0..nrows2 {
             for j in 0..ncols2 {
-                *res.get_unchecked_mut(i, j) = m.get_unchecked(i, j).to_subset_unchecked()
+                *res.get_unchecked_mut((i, j)) = m.get_unchecked((i, j)).to_subset_unchecked()
             }
         }
 
@@ -336,7 +338,7 @@ impl_from_into_mint_2D!(
 );
 
 impl<'a, N, R, C, RStride, CStride> From<MatrixSlice<'a, N, R, C, RStride, CStride>>
-    for Matrix<N, R, C, MatrixArray<N, R, C>>
+    for Matrix<N, R, C, ArrayStorage<N, R, C>>
 where
     N: Scalar,
     R: DimName,
@@ -353,7 +355,7 @@ where
 
 #[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, MatrixVec<N, Dynamic, C>>
+    for Matrix<N, Dynamic, C, VecStorage<N, Dynamic, C>>
 where
     N: Scalar,
     C: Dim,
@@ -367,7 +369,7 @@ where
 
 #[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, MatrixVec<N, R, Dynamic>>
+    for Matrix<N, R, Dynamic, VecStorage<N, R, Dynamic>>
 where
     N: Scalar,
     R: DimName,
@@ -380,7 +382,7 @@ where
 }
 
 impl<'a, N, R, C, RStride, CStride> From<MatrixSliceMut<'a, N, R, C, RStride, CStride>>
-    for Matrix<N, R, C, MatrixArray<N, R, C>>
+    for Matrix<N, R, C, ArrayStorage<N, R, C>>
 where
     N: Scalar,
     R: DimName,
@@ -397,7 +399,7 @@ where
 
 #[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, MatrixVec<N, Dynamic, C>>
+    for Matrix<N, Dynamic, C, VecStorage<N, Dynamic, C>>
 where
     N: Scalar,
     C: Dim,
@@ -411,7 +413,7 @@ where
 
 #[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, MatrixVec<N, R, Dynamic>>
+    for Matrix<N, R, Dynamic, VecStorage<N, R, Dynamic>>
 where
     N: Scalar,
     R: DimName,

src/base/default_allocator.rs

@@ -18,9 +18,9 @@ use base::allocator::{Allocator, Reallocator};
 #[cfg(any(feature = "alloc", feature = "std"))]
 use base::dimension::Dynamic;
 use base::dimension::{Dim, DimName};
-use base::matrix_array::MatrixArray;
+use base::array_storage::ArrayStorage;
 #[cfg(any(feature = "std", feature = "alloc"))]
-use base::matrix_vec::MatrixVec;
+use base::vec_storage::VecStorage;
 use base::storage::{Storage, StorageMut};
 use base::Scalar;
 
@@ -29,7 +29,7 @@ use base::Scalar;
  * Allocator.
  *
  */
-/// An allocator based on `GenericArray` and `MatrixVec` for statically-sized and dynamically-sized
+/// An allocator based on `GenericArray` and `VecStorage` for statically-sized and dynamically-sized
 /// matrices respectively.
 pub struct DefaultAllocator;
 
@@ -42,7 +42,7 @@ where
     R::Value: Mul<C::Value>,
     Prod<R::Value, C::Value>: ArrayLength<N>,
 {
-    type Buffer = MatrixArray<N, R, C>;
+    type Buffer = ArrayStorage<N, R, C>;
 
     #[inline]
     unsafe fn allocate_uninitialized(_: R, _: C) -> Self::Buffer {
@@ -77,7 +77,7 @@ where
 // Dynamic - Dynamic
 #[cfg(any(feature = "std", feature = "alloc"))]
 impl<N: Scalar, C: Dim> Allocator<N, Dynamic, C> for DefaultAllocator {
-    type Buffer = MatrixVec<N, Dynamic, C>;
+    type Buffer = VecStorage<N, Dynamic, C>;
 
     #[inline]
     unsafe fn allocate_uninitialized(nrows: Dynamic, ncols: C) -> Self::Buffer {
@@ -86,7 +86,7 @@ impl<N: Scalar, C: Dim> Allocator<N, Dynamic, C> for DefaultAllocator {
         res.reserve_exact(length);
         res.set_len(length);
 
-        MatrixVec::new(nrows, ncols, res)
+        VecStorage::new(nrows, ncols, res)
     }
 
     #[inline]
@@ -101,14 +101,14 @@ impl<N: Scalar, C: Dim> Allocator<N, Dynamic, C> for DefaultAllocator {
         assert!(res.len() == nrows.value() * ncols.value(),
                 "Allocation from iterator error: the iterator did not yield the correct number of elements.");
 
-        MatrixVec::new(nrows, ncols, res)
+        VecStorage::new(nrows, ncols, res)
     }
 }
 
 // Static - Dynamic
 #[cfg(any(feature = "std", feature = "alloc"))]
 impl<N: Scalar, R: DimName> Allocator<N, R, Dynamic> for DefaultAllocator {
-    type Buffer = MatrixVec<N, R, Dynamic>;
+    type Buffer = VecStorage<N, R, Dynamic>;
 
     #[inline]
     unsafe fn allocate_uninitialized(nrows: R, ncols: Dynamic) -> Self::Buffer {
@@ -117,7 +117,7 @@ impl<N: Scalar, R: DimName> Allocator<N, R, Dynamic> for DefaultAllocator {
         res.reserve_exact(length);
         res.set_len(length);
 
-        MatrixVec::new(nrows, ncols, res)
+        VecStorage::new(nrows, ncols, res)
     }
 
     #[inline]
@@ -132,7 +132,7 @@ impl<N: Scalar, R: DimName> Allocator<N, R, Dynamic> for DefaultAllocator {
         assert!(res.len() == nrows.value() * ncols.value(),
                 "Allocation from iterator error: the iterator did not yield the correct number of elements.");
 
-        MatrixVec::new(nrows, ncols, res)
+        VecStorage::new(nrows, ncols, res)
     }
 }
 
@@ -157,7 +157,7 @@ where
         rto: RTo,
         cto: CTo,
         buf: <Self as Allocator<N, RFrom, CFrom>>::Buffer,
-    ) -> MatrixArray<N, RTo, CTo>
+    ) -> ArrayStorage<N, RTo, CTo>
     {
         let mut res = <Self as Allocator<N, RTo, CTo>>::allocate_uninitialized(rto, cto);
 
@@ -185,8 +185,8 @@ where
     unsafe fn reallocate_copy(
         rto: Dynamic,
         cto: CTo,
-        buf: MatrixArray<N, RFrom, CFrom>,
+        buf: ArrayStorage<N, RFrom, CFrom>,
-    ) -> MatrixVec<N, Dynamic, CTo>
+    ) -> VecStorage<N, Dynamic, CTo>
     {
         let mut res = <Self as Allocator<N, Dynamic, CTo>>::allocate_uninitialized(rto, cto);
 
@@ -214,8 +214,8 @@ where
     unsafe fn reallocate_copy(
         rto: RTo,
         cto: Dynamic,
-        buf: MatrixArray<N, RFrom, CFrom>,
+        buf: ArrayStorage<N, RFrom, CFrom>,
-    ) -> MatrixVec<N, RTo, Dynamic>
+    ) -> VecStorage<N, RTo, Dynamic>
     {
         let mut res = <Self as Allocator<N, RTo, Dynamic>>::allocate_uninitialized(rto, cto);
 
@@ -238,11 +238,11 @@ impl<N: Scalar, CFrom: Dim, CTo: Dim> Reallocator<N, Dynamic, CFrom, Dynamic, CT
     unsafe fn reallocate_copy(
         rto: Dynamic,
         cto: CTo,
-        buf: MatrixVec<N, Dynamic, CFrom>,
+        buf: VecStorage<N, Dynamic, CFrom>,
-    ) -> MatrixVec<N, Dynamic, CTo>
+    ) -> VecStorage<N, Dynamic, CTo>
     {
         let new_buf = buf.resize(rto.value() * cto.value());
-        MatrixVec::new(rto, cto, new_buf)
+        VecStorage::new(rto, cto, new_buf)
     }
 }
 
@@ -254,11 +254,11 @@ impl<N: Scalar, CFrom: Dim, RTo: DimName> Reallocator<N, Dynamic, CFrom, RTo, Dy
     unsafe fn reallocate_copy(
         rto: RTo,
         cto: Dynamic,
-        buf: MatrixVec<N, Dynamic, CFrom>,
+        buf: VecStorage<N, Dynamic, CFrom>,
-    ) -> MatrixVec<N, RTo, Dynamic>
+    ) -> VecStorage<N, RTo, Dynamic>
     {
         let new_buf = buf.resize(rto.value() * cto.value());
-        MatrixVec::new(rto, cto, new_buf)
+        VecStorage::new(rto, cto, new_buf)
     }
 }
 
@@ -270,11 +270,11 @@ impl<N: Scalar, RFrom: DimName, CTo: Dim> Reallocator<N, RFrom, Dynamic, Dynamic
     unsafe fn reallocate_copy(
         rto: Dynamic,
         cto: CTo,
-        buf: MatrixVec<N, RFrom, Dynamic>,
+        buf: VecStorage<N, RFrom, Dynamic>,
-    ) -> MatrixVec<N, Dynamic, CTo>
+    ) -> VecStorage<N, Dynamic, CTo>
     {
         let new_buf = buf.resize(rto.value() * cto.value());
-        MatrixVec::new(rto, cto, new_buf)
+        VecStorage::new(rto, cto, new_buf)
     }
 }
 
@@ -286,10 +286,10 @@ impl<N: Scalar, RFrom: DimName, RTo: DimName> Reallocator<N, RFrom, Dynamic, RTo
     unsafe fn reallocate_copy(
         rto: RTo,
         cto: Dynamic,
-        buf: MatrixVec<N, RFrom, Dynamic>,
+        buf: VecStorage<N, RFrom, Dynamic>,
-    ) -> MatrixVec<N, RTo, Dynamic>
+    ) -> VecStorage<N, RTo, Dynamic>
     {
         let new_buf = buf.resize(rto.value() * cto.value());
-        MatrixVec::new(rto, cto, new_buf)
+        VecStorage::new(rto, cto, new_buf)
     }
 }

src/base/dimension.rs

@@ -181,7 +181,7 @@ dim_ops!(
     DimMul, DimNameMul, Mul, mul, Mul::mul, DimProd,    DimNameProd,    Prod;
     DimSub, DimNameSub, Sub, sub, Sub::sub, DimDiff,    DimNameDiff,    Diff;
     DimDiv, DimNameDiv, Div, div, Div::div, DimQuot,    DimNameQuot,    Quot;
-    DimMin, DimNameMin, Min, min, cmp::min, DimMinimum, DimNameNimimum, Minimum;
+    DimMin, DimNameMin, Min, min, cmp::min, DimMinimum, DimNameMinimum, Minimum;
     DimMax, DimNameMax, Max, max, cmp::max, DimMaximum, DimNameMaximum, Maximum;
 );
 
@@ -364,7 +364,8 @@ impl<
         G: Bit + Any + Debug + Copy + PartialEq + Send + Sync,
     > IsNotStaticOne
     for UInt<UInt<UInt<UInt<UInt<UInt<UInt<UInt<UTerm, B1>, A>, B>, C>, D>, E>, F>, G>
-{}
+{
+}
 
 impl<U: Unsigned + DimName, B: Bit + Any + Debug + Copy + PartialEq + Send + Sync> NamedDim
     for UInt<U, B>
@@ -405,4 +406,5 @@ impl<U: Unsigned + DimName, B: Bit + Any + Debug + Copy + PartialEq + Send + Syn
 
 impl<U: Unsigned + DimName, B: Bit + Any + Debug + Copy + PartialEq + Send + Sync> IsNotStaticOne
     for UInt<U, B>
-{}
+{
+}

src/base/edition.rs

@@ -1,12 +1,18 @@
 use num::{One, Zero};
 use std::cmp;
 use std::ptr;
+#[cfg(any(feature = "std", feature = "alloc"))]
+use std::iter::ExactSizeIterator;
+#[cfg(any(feature = "std", feature = "alloc"))]
+use std::mem;
 
 use base::allocator::{Allocator, Reallocator};
 use base::constraint::{DimEq, SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
 use base::dimension::{
-    Dim, DimAdd, DimDiff, DimMin, DimMinimum, DimName, DimSub, DimSum, Dynamic, U1,
+    Dim, DimAdd, DimDiff, DimMin, DimMinimum, DimName, DimSub, DimSum, U1,
 };
+#[cfg(any(feature = "std", feature = "alloc"))]
+use base::dimension::Dynamic;
 use base::storage::{Storage, StorageMut};
 #[cfg(any(feature = "std", feature = "alloc"))]
 use base::DMatrix;
@@ -23,7 +29,7 @@ impl<N: Scalar + Zero, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         res
     }
 
-    /// Extracts the upper triangular part of this matrix (including the diagonal).
+    /// Extracts the lower triangular part of this matrix (including the diagonal).
     #[inline]
     pub fn lower_triangle(&self) -> MatrixMN<N, R, C>
     where DefaultAllocator: Allocator<N, R, C> {
@@ -32,6 +38,54 @@ impl<N: Scalar + Zero, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
         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>
+        where I: IntoIterator<Item = &'a usize>,
+              I::IntoIter: ExactSizeIterator + Clone,
+              DefaultAllocator: Allocator<N, Dynamic, C> {
+        let irows = irows.into_iter();
+        let ncols = self.data.shape().1;
+        let mut res = unsafe { MatrixMN::new_uninitialized_generic(Dynamic::new(irows.len()), ncols) };
+
+        // First, check that all the indices from irows are valid.
+        // This will allow us to use unchecked access in the inner loop.
+        for i in irows.clone() {
+            assert!(*i < self.nrows(), "Row index out of bounds.")
+        }
+
+        for j in 0..ncols.value() {
+            // FIXME: use unchecked column indexing
+            let mut res = res.column_mut(j);
+            let mut src = self.column(j);
+
+            for (destination, source) in irows.clone().enumerate() {
+                unsafe {
+                    *res.vget_unchecked_mut(destination) = *src.vget_unchecked(*source)
+                }
+            }
+        }
+
+        res
+    }
+
+    /// 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>
+        where I: IntoIterator<Item = &'a usize>,
+              I::IntoIter: ExactSizeIterator,
+              DefaultAllocator: Allocator<N, R, Dynamic> {
+        let icols = icols.into_iter();
+        let nrows = self.data.shape().0;
+        let mut res = unsafe { MatrixMN::new_uninitialized_generic(nrows, Dynamic::new(icols.len())) };
+
+        for (destination, source) in icols.enumerate() {
+            res.column_mut(destination).copy_from(&self.column(*source))
+        }
+
+        res
+    }
 }
 
 impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
@@ -58,7 +112,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
         let n = cmp::min(nrows, ncols);
 
         for i in 0..n {
-            unsafe { *self.get_unchecked_mut(i, i) = val }
+            unsafe { *self.get_unchecked_mut((i, i)) = val }
         }
     }
 
@@ -67,7 +121,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     pub fn fill_row(&mut self, i: usize, val: N) {
         assert!(i < self.nrows(), "Row index out of bounds.");
         for j in 0..self.ncols() {
-            unsafe { *self.get_unchecked_mut(i, j) = val }
+            unsafe { *self.get_unchecked_mut((i, j)) = val }
         }
     }
 
@@ -76,7 +130,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     pub fn fill_column(&mut self, j: usize, val: N) {
         assert!(j < self.ncols(), "Row index out of bounds.");
         for i in 0..self.nrows() {
-            unsafe { *self.get_unchecked_mut(i, j) = val }
+            unsafe { *self.get_unchecked_mut((i, j)) = val }
         }
     }
 
@@ -93,7 +147,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
         assert_eq!(diag.len(), min_nrows_ncols, "Mismatched dimensions.");
 
         for i in 0..min_nrows_ncols {
-            unsafe { *self.get_unchecked_mut(i, i) = *diag.vget_unchecked(i) }
+            unsafe { *self.get_unchecked_mut((i, i)) = *diag.vget_unchecked(i) }
         }
     }
 
@@ -128,7 +182,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     pub fn fill_lower_triangle(&mut self, val: N, shift: usize) {
         for j in 0..self.ncols() {
             for i in (j + shift)..self.nrows() {
-                unsafe { *self.get_unchecked_mut(i, j) = val }
+                unsafe { *self.get_unchecked_mut((i, j)) = val }
             }
         }
     }
@@ -146,7 +200,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
             // FIXME: is there a more efficient way to avoid the min ?
             // (necessary for rectangular matrices)
             for i in 0..cmp::min(j + 1 - shift, self.nrows()) {
-                unsafe { *self.get_unchecked_mut(i, j) = val }
+                unsafe { *self.get_unchecked_mut((i, j)) = val }
             }
         }
     }
@@ -191,7 +245,7 @@ impl<N: Scalar, D: Dim, S: StorageMut<N, D, D>> Matrix<N, D, D, S> {
         for j in 0..dim {
             for i in j + 1..dim {
                 unsafe {
-                    *self.get_unchecked_mut(i, j) = *self.get_unchecked(j, i);
+                    *self.get_unchecked_mut((i, j)) = *self.get_unchecked((j, i));
                 }
             }
         }
@@ -206,7 +260,7 @@ impl<N: Scalar, D: Dim, S: StorageMut<N, D, D>> Matrix<N, D, D, S> {
         for j in 1..self.ncols() {
             for i in 0..j {
                 unsafe {
-                    *self.get_unchecked_mut(i, j) = *self.get_unchecked(j, i);
+                    *self.get_unchecked_mut((i, j)) = *self.get_unchecked((j, i));
                 }
             }
         }
@@ -248,6 +302,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
     /// 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>
     where
         C: DimSub<Dynamic, Output = Dynamic>,
@@ -330,6 +385,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
     /// 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>
     where
         R: DimSub<Dynamic, Output = Dynamic>,
@@ -407,6 +463,7 @@ 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>
     where
         C: DimAdd<Dynamic, Output = Dynamic>,
@@ -484,6 +541,7 @@ 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>
     where
         R: DimAdd<Dynamic, Output = Dynamic>,
@@ -549,6 +607,29 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         self.resize_generic(Dynamic::new(new_nrows), Dynamic::new(new_ncols), val)
     }
 
+    /// Resizes this matrix vertically, i.e., so that it contains `new_nrows` rows while keeping the same number of columns.
+    ///
+    /// 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>
+        where DefaultAllocator: Reallocator<N, R, C, Dynamic, C> {
+        let ncols = self.data.shape().1;
+        self.resize_generic(Dynamic::new(new_nrows), ncols, val)
+    }
+
+    /// Resizes this matrix horizontally, i.e., so that it contains `new_ncolumns` columns while keeping the same number of columns.
+    ///
+    /// 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>
+        where DefaultAllocator: Reallocator<N, R, C, R, Dynamic> {
+        let nrows = self.data.shape().0;
+        self.resize_generic(nrows, Dynamic::new(new_ncols), val)
+    }
+
+
     /// Resizes this matrix so that it contains `R2::value()` rows and `C2::value()` columns.
     ///
     /// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
@@ -626,6 +707,61 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     }
 }
 
+#[cfg(any(feature = "std", feature = "alloc"))]
+impl<N: Scalar> DMatrix<N> {
+    /// 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)
+        where DefaultAllocator: Reallocator<N, Dynamic, Dynamic, Dynamic, Dynamic> {
+        let placeholder = unsafe { Self::new_uninitialized(0, 0) };
+        let old = mem::replace(self, placeholder);
+        let new = old.resize(new_nrows, new_ncols, val);
+        let _ = mem::replace(self, new);
+    }
+}
+
+#[cfg(any(feature = "std", feature = "alloc"))]
+impl<N: Scalar, C: Dim> MatrixMN<N, Dynamic, C>
+    where DefaultAllocator: Allocator<N, Dynamic, C> {
+    /// Changes the number of rows of this matrix in-place.
+    ///
+    /// 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`.
+    ///
+    /// 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)
+        where DefaultAllocator: Reallocator<N, Dynamic, C, Dynamic, C> {
+        let placeholder = unsafe { Self::new_uninitialized_generic(Dynamic::new(0), self.data.shape().1) };
+        let old = mem::replace(self, placeholder);
+        let new = old.resize_vertically(new_nrows, val);
+        let _ = mem::replace(self, new);
+    }
+}
+
+#[cfg(any(feature = "std", feature = "alloc"))]
+impl<N: Scalar, R: Dim> MatrixMN<N, R, Dynamic>
+    where DefaultAllocator: Allocator<N, R, Dynamic> {
+    /// Changes the number of column of this matrix in-place.
+    ///
+    /// 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`.
+    ///
+    /// 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)
+        where DefaultAllocator: Reallocator<N, R, Dynamic, R, Dynamic> {
+        let placeholder = unsafe { Self::new_uninitialized_generic(self.data.shape().0, Dynamic::new(0)) };
+        let old = mem::replace(self, placeholder);
+        let new = old.resize_horizontally(new_ncols, val);
+        let _ = mem::replace(self, new);
+    }
+}
+
 unsafe fn compress_rows<N: Scalar>(
     data: &mut [N],
     nrows: usize,
@@ -706,6 +842,7 @@ 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>
 where
     N: Scalar,
@@ -753,6 +890,7 @@ 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>
 where
     N: Scalar,
@@ -764,15 +902,16 @@ where
     /// # Example
     /// ```
     /// # use nalgebra::DVector;
-    /// let mut vector = DVector::from_vec(3, vec![0, 1, 2]);
+    /// let mut vector = DVector::from_vec(vec![0, 1, 2]);
     /// vector.extend(vec![3, 4, 5]);
-    /// assert!(vector.eq(&DVector::from_vec(6, vec![0, 1, 2, 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) {
         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>
 where
     N: Scalar,

src/base/indexing.rs

@@ -0,0 +1,714 @@
+//! Indexing
+
+use base::{Dim, DimName, DimDiff, DimSub, Dynamic, Matrix, MatrixSlice, MatrixSliceMut, Scalar, U1};
+use base::storage::{Storage, StorageMut};
+
+use std::ops;
+
+// N.B.: Not a public trait!
+trait DimRange<D: Dim>
+{
+    /// The number of elements indexed by this range.
+    type Length: Dim;
+
+    /// The lower bound of the range, inclusive.
+    fn lower(&self, dimension: D) -> usize;
+
+    /// The number of elements included in the range.
+    fn length(&self, dimension: D) -> Self::Length;
+
+    /// Produces true if `Self` is contained within `dimension`.
+    fn contained_by(&self, dimension: D) -> bool;
+}
+
+impl<D: Dim> DimRange<D> for usize {
+    type Length = U1;
+
+    #[inline(always)]
+    fn lower(&self, _: D) -> usize {
+        *self
+    }
+
+    #[inline(always)]
+    fn length(&self, _: D) -> Self::Length {
+        U1
+    }
+
+    #[inline(always)]
+    fn contained_by(&self, dimension: D) -> bool {
+        *self < dimension.value()
+    }
+}
+
+#[test]
+fn dimrange_usize() {
+    use base::dimension::U0;
+    assert_eq!(DimRange::contained_by(&0, U0), false);
+    assert_eq!(DimRange::contained_by(&0, U1), true);
+}
+
+impl<D: Dim> DimRange<D> for ops::Range<usize> {
+    type Length = Dynamic;
+
+    #[inline(always)]
+    fn lower(&self, _: D) -> usize {
+        self.start
+    }
+
+    #[inline(always)]
+    fn length(&self, _: D) -> Self::Length {
+        Dynamic::new(self.end.saturating_sub(self.start))
+    }
+
+    #[inline(always)]
+    fn contained_by(&self, dimension: D) -> bool {
+        (self.start < dimension.value()) && (self.end <= dimension.value())
+    }
+}
+
+#[test]
+fn dimrange_range_usize() {
+    use std::usize::MAX;
+    use base::dimension::U0;
+    assert_eq!(DimRange::contained_by(&(0..0), U0), false);
+    assert_eq!(DimRange::contained_by(&(0..1), U0), false);
+    assert_eq!(DimRange::contained_by(&(0..1), U1), true);
+    assert_eq!(DimRange::contained_by(&((MAX - 1)..MAX), Dynamic::new(MAX)), true);
+    assert_eq!(DimRange::length(&((MAX - 1)..MAX), Dynamic::new(MAX)), Dynamic::new(1));
+    assert_eq!(DimRange::length(&(MAX..(MAX - 1)), Dynamic::new(MAX)), Dynamic::new(0));
+    assert_eq!(DimRange::length(&(MAX..MAX), Dynamic::new(MAX)), Dynamic::new(0));
+}
+
+impl<D: Dim> DimRange<D> for ops::RangeFrom<usize> {
+    type Length = Dynamic;
+
+    #[inline(always)]
+    fn lower(&self, _: D) -> usize {
+        self.start
+    }
+
+    #[inline(always)]
+    fn length(&self, dimension: D) -> Self::Length {
+        (self.start..dimension.value()).length(dimension)
+    }
+
+    #[inline(always)]
+    fn contained_by(&self, dimension: D) -> bool {
+        self.start < dimension.value()
+    }
+}
+
+#[test]
+fn dimrange_rangefrom_usize() {
+    use std::usize::MAX;
+    use base::dimension::U0;
+    assert_eq!(DimRange::contained_by(&(0..), U0), false);
+    assert_eq!(DimRange::contained_by(&(0..), U0), false);
+    assert_eq!(DimRange::contained_by(&(0..), U1), true);
+    assert_eq!(DimRange::contained_by(&((MAX - 1)..), Dynamic::new(MAX)), true);
+    assert_eq!(DimRange::length(&((MAX - 1)..), Dynamic::new(MAX)), Dynamic::new(1));
+    assert_eq!(DimRange::length(&(MAX..), Dynamic::new(MAX)), Dynamic::new(0));
+}
+
+impl<D: Dim, T: Dim> DimRange<D> for ops::RangeFrom<T>
+where D: DimSub<T>
+{
+    type Length = DimDiff<D, T>;
+
+    #[inline(always)]
+    fn lower(&self, _: D) -> usize {
+        self.start.value()
+    }
+
+    #[inline(always)]
+    fn length(&self, dimension: D) -> Self::Length {
+        dimension.sub(self.start)
+    }
+
+    #[inline(always)]
+    fn contained_by(&self, _: D) -> bool {
+        true
+    }
+}
+
+#[test]
+fn dimrange_rangefrom_dimname() {
+    use base::dimension::{U5, U4};
+    assert_eq!(DimRange::length(&(U1..), U5), U4);
+}
+
+impl<D: Dim> DimRange<D> for ops::RangeFull {
+    type Length = D;
+
+    #[inline(always)]
+    fn lower(&self, _: D) -> usize {
+        0
+    }
+
+    #[inline(always)]
+    fn length(&self, dimension: D) -> Self::Length {
+        dimension
+    }
+
+    #[inline(always)]
+    fn contained_by(&self, _: D) -> bool {
+        true
+    }
+}
+
+#[test]
+fn dimrange_rangefull() {
+    use base::dimension::U0;
+    assert_eq!(DimRange::contained_by(&(..), U0), true);
+    assert_eq!(DimRange::length(&(..), U1), U1);
+}
+
+impl<D: Dim> DimRange<D> for ops::RangeInclusive<usize> {
+    type Length = Dynamic;
+
+    #[inline(always)]
+    fn lower(&self, _: D) -> usize {
+        *self.start()
+    }
+
+    #[inline(always)]
+    fn length(&self, _: D) -> Self::Length {
+        Dynamic::new(
+            if self.end() < self.start() {
+                0
+            } else {
+                self.end().wrapping_sub(self.start().wrapping_sub(1))
+            })
+    }
+
+    #[inline(always)]
+    fn contained_by(&self, dimension: D) -> bool {
+        (*self.start() < dimension.value()) && (*self.end() < dimension.value())
+    }
+}
+
+#[test]
+fn dimrange_rangeinclusive_usize() {
+    use std::usize::MAX;
+    use base::dimension::U0;
+    assert_eq!(DimRange::contained_by(&(0..=0), U0), false);
+    assert_eq!(DimRange::contained_by(&(0..=0), U1), true);
+    assert_eq!(DimRange::contained_by(&(MAX..=MAX), Dynamic::new(MAX)), false);
+    assert_eq!(DimRange::contained_by(&((MAX-1)..=MAX), Dynamic::new(MAX)), false);
+    assert_eq!(DimRange::contained_by(&((MAX-1)..=(MAX-1)), Dynamic::new(MAX)), true);
+    assert_eq!(DimRange::length(&(0..=0), U1), Dynamic::new(1));
+    assert_eq!(DimRange::length(&((MAX - 1)..=MAX), Dynamic::new(MAX)), Dynamic::new(2));
+    assert_eq!(DimRange::length(&(MAX..=(MAX - 1)), Dynamic::new(MAX)), Dynamic::new(0));
+    assert_eq!(DimRange::length(&(MAX..=MAX), Dynamic::new(MAX)), Dynamic::new(1));
+}
+
+impl<D: Dim> DimRange<D> for ops::RangeTo<usize>
+{
+    type Length = Dynamic;
+
+    #[inline(always)]
+    fn lower(&self, _: D) -> usize {
+        0
+    }
+
+    #[inline(always)]
+    fn length(&self, _: D) -> Self::Length {
+        Dynamic::new(self.end)
+    }
+
+    #[inline(always)]
+    fn contained_by(&self, dimension: D) -> bool {
+        self.end <= dimension.value()
+    }
+}
+
+#[test]
+fn dimrange_rangeto_usize() {
+    use std::usize::MAX;
+    use base::dimension::U0;
+    assert_eq!(DimRange::contained_by(&(..0), U0), true);
+    assert_eq!(DimRange::contained_by(&(..1), U0), false);
+    assert_eq!(DimRange::contained_by(&(..0), U1), true);
+    assert_eq!(DimRange::contained_by(&(..(MAX - 1)), Dynamic::new(MAX)), true);
+    assert_eq!(DimRange::length(&(..(MAX - 1)), Dynamic::new(MAX)), Dynamic::new(MAX - 1));
+    assert_eq!(DimRange::length(&(..MAX), Dynamic::new(MAX)), Dynamic::new(MAX));
+}
+
+impl<D: Dim> DimRange<D> for ops::RangeToInclusive<usize>
+{
+    type Length = Dynamic;
+
+    #[inline(always)]
+    fn lower(&self, _: D) -> usize {
+        0
+    }
+
+    #[inline(always)]
+    fn length(&self, _: D) -> Self::Length {
+        Dynamic::new(self.end + 1)
+    }
+
+    #[inline(always)]
+    fn contained_by(&self, dimension: D) -> bool {
+        self.end < dimension.value()
+    }
+}
+
+#[test]
+fn dimrange_rangetoinclusive_usize() {
+    use std::usize::MAX;
+    use base::dimension::U0;
+    assert_eq!(DimRange::contained_by(&(..=0), U0), false);
+    assert_eq!(DimRange::contained_by(&(..=1), U0), false);
+    assert_eq!(DimRange::contained_by(&(..=0), U1), true);
+    assert_eq!(DimRange::contained_by(&(..=(MAX)), Dynamic::new(MAX)), false);
+    assert_eq!(DimRange::contained_by(&(..=(MAX - 1)), Dynamic::new(MAX)), true);
+    assert_eq!(DimRange::length(&(..=(MAX - 1)), Dynamic::new(MAX)), Dynamic::new(MAX));
+}
+
+/// A helper trait used for indexing operations.
+pub trait MatrixIndex<'a, N: Scalar, R: Dim, C: Dim, S: Storage<N, 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;
+
+    /// 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> {
+        if self.contained_by(matrix) {
+            Some(unsafe{self.get_unchecked(matrix)})
+        } else {
+            None
+        }
+    }
+
+    /// 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;
+
+    /// 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 {
+        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> {
+    /// The output type returned by methods.
+    type OutputMut : 'a;
+
+    /// 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;
+
+    /// 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> {
+        if self.contained_by(matrix) {
+            Some(unsafe{self.get_unchecked_mut(matrix)})
+        } else {
+            None
+        }
+    }
+
+    /// Produces a mutable view of the data at this location, or panics
+    /// if out of bounds.
+    #[doc(hidden)]
+    #[inline(always)]
+    fn index_mut(self, matrix: &'a mut Matrix<N, R, C, S>) -> Self::OutputMut {
+        self.get_mut(matrix).expect("Index out of bounds.")
+    }
+}
+
+/// # Indexing Operations
+/// ## Indices to Individual Elements
+/// ### Two-Dimensional Indices
+/// ```
+/// # use nalgebra::*;
+/// let matrix = Matrix2::new(0, 2,
+///                           1, 3);
+///
+/// assert_eq!(matrix.index((0, 0)), &0);
+/// assert_eq!(matrix.index((1, 0)), &1);
+/// assert_eq!(matrix.index((0, 1)), &2);
+/// assert_eq!(matrix.index((1, 1)), &3);
+/// ```
+///
+/// ### Linear Address Indexing
+/// ```
+/// # use nalgebra::*;
+/// let matrix = Matrix2::new(0, 2,
+///                           1, 3);
+///
+/// assert_eq!(matrix.get(0), Some(&0));
+/// assert_eq!(matrix.get(1), Some(&1));
+/// assert_eq!(matrix.get(2), Some(&2));
+/// assert_eq!(matrix.get(3), Some(&3));
+/// ```
+///
+/// ## Indices to Individual Rows and Columns
+/// ### Index to a Row
+/// ```
+/// # use nalgebra::*;
+/// let matrix = Matrix2::new(0, 2,
+///                           1, 3);
+///
+/// assert!(matrix.index((0, ..))
+///     .eq(&Matrix1x2::new(0, 2)));
+/// ```
+///
+/// ### Index to a Column
+/// ```
+/// # use nalgebra::*;
+/// let matrix = Matrix2::new(0, 2,
+///                           1, 3);
+///
+/// assert!(matrix.index((.., 0))
+///     .eq(&Matrix2x1::new(0,
+///                         1)));
+/// ```
+///
+/// ## Indices to Parts of Individual Rows and Columns
+/// ### Index to a Partial Row
+/// ```
+/// # use nalgebra::*;
+/// let matrix = Matrix3::new(0, 3, 6,
+///                           1, 4, 7,
+///                           2, 5, 8);
+///
+/// assert!(matrix.index((0, ..2))
+///     .eq(&Matrix1x2::new(0, 3)));
+/// ```
+///
+/// ### Index to a Partial Column
+/// ```
+/// # use nalgebra::*;
+/// let matrix = Matrix3::new(0, 3, 6,
+///                           1, 4, 7,
+///                           2, 5, 8);
+///
+/// assert!(matrix.index((..2, 0))
+///     .eq(&Matrix2x1::new(0,
+///                         1)));
+///
+/// assert!(matrix.index((U1.., 0))
+///     .eq(&Matrix2x1::new(1,
+///                         2)));
+/// ```
+/// ## Indices to Ranges of Rows and Columns
+/// ### Index to a Range of Rows
+/// ```
+/// # use nalgebra::*;
+/// let matrix = Matrix3::new(0, 3, 6,
+///                           1, 4, 7,
+///                           2, 5, 8);
+///
+/// assert!(matrix.index((1..3, ..))
+///     .eq(&Matrix2x3::new(1, 4, 7,
+///                         2, 5, 8)));
+/// ```
+/// ### Index to a Range of Columns
+/// ```
+/// # use nalgebra::*;
+/// let matrix = Matrix3::new(0, 3, 6,
+///                           1, 4, 7,
+///                           2, 5, 8);
+///
+/// assert!(matrix.index((.., 1..3))
+///     .eq(&Matrix3x2::new(3, 6,
+///                         4, 7,
+///                         5, 8)));
+/// ```
+impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, 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>
+    {
+        index.get(self)
+    }
+
+    /// Produces a mutable view of the data at the given index, or
+    /// `None` if the index is out of bounds.
+    #[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>
+    {
+        index.get_mut(self)
+    }
+
+    /// Produces a view of the data at the given index, or
+    /// panics if the index is out of bounds.
+    #[inline]
+    pub fn index<'a, I>(&'a self, index: I) -> I::Output
+    where
+        I: MatrixIndex<'a, N, R, C, S>
+    {
+        index.index(self)
+    }
+
+    /// Produces a mutable view of the data at the given index, or
+    /// panics if the index is out of bounds.
+    #[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>
+    {
+        index.index_mut(self)
+    }
+
+    /// Produces a view of the data at the given index, without doing
+    /// any bounds checking.
+    #[inline]
+    pub unsafe fn get_unchecked<'a, I>(&'a self, index: I) -> I::Output
+    where
+        I: MatrixIndex<'a, N, R, C, S>
+    {
+        index.get_unchecked(self)
+    }
+
+    /// Returns a mutable view of the data at the given index, without doing
+    /// any bounds checking.
+    #[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>
+    {
+        index.get_unchecked_mut(self)
+    }
+}
+
+// EXTRACT A SINGLE ELEMENT BY 1D LINEAR ADDRESS
+
+impl<'a, N, R, C, S> MatrixIndex<'a, N, R, C, S> for usize
+where
+    N: Scalar,
+    R: Dim,
+    C: Dim,
+    S: Storage<N, R, C>
+{
+    type Output = &'a N;
+
+    #[doc(hidden)]
+    #[inline(always)]
+    fn contained_by(&self, matrix: &Matrix<N, 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 {
+        matrix.data.get_unchecked_linear(self)
+    }
+}
+
+impl<'a, N, R, C, S> MatrixIndexMut<'a, N, R, C, S> for usize
+where
+    N: Scalar,
+    R: Dim,
+    C: Dim,
+    S: StorageMut<N, R, C>
+{
+    type OutputMut = &'a mut N;
+
+    #[doc(hidden)]
+    #[inline(always)]
+    unsafe fn get_unchecked_mut(self, matrix: &'a mut Matrix<N, R, C, S>) -> Self::OutputMut
+    where S: StorageMut<N, R, C>,
+    {
+        matrix.data.get_unchecked_linear_mut(self)
+    }
+}
+
+// EXTRACT A SINGLE ELEMENT BY 2D COORDINATES
+
+impl<'a, N, R, C, S> MatrixIndex<'a, N, R, C, S> for (usize, usize)
+where
+    N: Scalar,
+    R: Dim,
+    C: Dim,
+    S: Storage<N, R, C>
+{
+    type Output = &'a N;
+
+    #[doc(hidden)]
+    #[inline(always)]
+    fn contained_by(&self, matrix: &Matrix<N, R, C, S>) -> bool {
+        let (rows, cols) = self;
+        let (nrows, ncols) = matrix.data.shape();
+        DimRange::contained_by(rows, nrows) && DimRange::contained_by(cols, ncols)
+    }
+
+    #[doc(hidden)]
+    #[inline(always)]
+    unsafe fn get_unchecked(self, matrix: &'a Matrix<N, 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)
+where
+    N: Scalar,
+    R: Dim,
+    C: Dim,
+    S: StorageMut<N, R, C>
+{
+    type OutputMut = &'a mut N;
+
+    #[doc(hidden)]
+    #[inline(always)]
+    unsafe fn get_unchecked_mut(self, matrix: &'a mut Matrix<N, R, C, S>) -> Self::OutputMut
+    where S: StorageMut<N, R, C>,
+    {
+        let (row, col) = self;
+        matrix.data.get_unchecked_mut(row, col)
+    }
+}
+
+macro_rules! impl_index_pair {
+    (
+      $R: ident,
+      $C: ident,
+      [<$($RTyP: ident : $RTyPB: ty,)*> usize => $ROut: ty
+        $(where $RConstraintType: ty: $RConstraintBound: ident<$($RConstraintBoundParams: ty $( = $REqBound: ty )*),*>)*],
+      [<$($CTyP: ident : $CTyPB: ty,)*> usize => $COut: ty
+        $(where $CConstraintType: ty: $CConstraintBound: ident<$($CConstraintBoundParams: ty $( = $CEqBound: ty )*),*>)*]
+    ) => {};
+
+    (
+      $R: ident,
+      $C: ident,
+      [<$($RTyP: ident: $RTyPB: tt),*> $RIdx: ty => $ROut: ty
+        $(where $RConstraintType: ty: $RConstraintBound: ident $(<$($RConstraintBoundParams: ty $( = $REqBound: ty )*),*>)* )*],
+      [<$($CTyP: ident: $CTyPB: tt),*> $CIdx: ty => $COut: ty
+        $(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)
+        where
+            N: Scalar,
+            $R: Dim,
+            $C: Dim,
+            S: Storage<N, R, C>,
+            $( $RConstraintType: $RConstraintBound $(<$( $RConstraintBoundParams $( = $REqBound )*),*>)* ,)*
+            $( $CConstraintType: $CConstraintBound $(<$( $CConstraintBoundParams $( = $CEqBound )*),*>)* ),*
+        {
+            type Output = MatrixSlice<'a, N, $ROut, $COut, S::RStride, S::CStride>;
+
+            #[doc(hidden)]
+            #[inline(always)]
+            fn contained_by(&self, matrix: &Matrix<N, $R, $C, S>) -> bool {
+                let (rows, cols) = self;
+                let (nrows, ncols) = matrix.data.shape();
+                DimRange::contained_by(rows, nrows) && DimRange::contained_by(cols, ncols)
+            }
+
+            #[doc(hidden)]
+            #[inline(always)]
+            unsafe fn get_unchecked(self, matrix: &'a Matrix<N, $R, $C, S>) -> Self::Output {
+                use base::SliceStorage;
+
+                let (rows, cols) = self;
+                let (nrows, ncols) = matrix.data.shape();
+
+                let data =
+                    SliceStorage::new_unchecked(&matrix.data,
+                        (rows.lower(nrows),  cols.lower(ncols)),
+                        (rows.length(nrows), cols.length(ncols)));
+
+                Matrix::from_data_statically_unchecked(data)
+            }
+        }
+
+        impl<'a, N, $R, $C, S, $($RTyP : $RTyPB,)* $($CTyP : $CTyPB),*> MatrixIndexMut<'a, N, $R, $C, S> for ($RIdx, $CIdx)
+        where
+            N: Scalar,
+            $R: Dim,
+            $C: Dim,
+            S: StorageMut<N, R, C>,
+            $( $RConstraintType: $RConstraintBound $(<$( $RConstraintBoundParams $( = $REqBound )*),*>)* ,)*
+            $( $CConstraintType: $CConstraintBound $(<$( $CConstraintBoundParams $( = $CEqBound )*),*>)* ),*
+        {
+            type OutputMut = MatrixSliceMut<'a, N, $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 {
+                use base::SliceStorageMut;
+
+                let (rows, cols) = self;
+                let (nrows, ncols) = matrix.data.shape();
+
+                let data =
+                    SliceStorageMut::new_unchecked(&mut matrix.data,
+                        (rows.lower(nrows),  cols.lower(ncols)),
+                        (rows.length(nrows), cols.length(ncols)));
+
+                Matrix::from_data_statically_unchecked(data)
+            }
+        }
+    }
+}
+
+macro_rules! impl_index_pairs {
+    (index $R: ident with {} index $C: ident with {$($r: tt,)* }) => {};
+
+    (index $R: ident with {$lh : tt, $($lt : tt,)*}
+     index $C: ident with { $($r: tt,)* }) =>
+    {
+        $(
+            impl_index_pair!{$R, $C, $lh, $r}
+        )*
+        impl_index_pairs!{index $R with {$($lt,)*} index $C with {$($r,)*}}
+    }
+}
+
+impl_index_pairs!{
+    index R with {
+        [<> usize                         =>  U1],
+        [<> ops::Range<usize>             =>  Dynamic],
+        [<> ops::RangeFrom<usize>         =>  Dynamic],
+        [<> ops::RangeFull                =>  R],
+        [<> ops::RangeInclusive<usize>    =>  Dynamic],
+        [<> ops::RangeTo<usize>           =>  Dynamic],
+        [<> ops::RangeToInclusive<usize>  =>  Dynamic],
+
+        [<I: Dim> ops::RangeFrom<I>
+          =>  DimDiff<R, I>
+          where R: DimSub<I>],
+    }
+    index C with {
+        [<> usize                         =>  U1],
+        [<> ops::Range<usize>             =>  Dynamic],
+        [<> ops::RangeFrom<usize>         =>  Dynamic],
+        [<> ops::RangeFull                =>  C],
+        [<> ops::RangeInclusive<usize>    =>  Dynamic],
+        [<> ops::RangeTo<usize>           =>  Dynamic],
+        [<> ops::RangeToInclusive<usize>  =>  Dynamic],
+
+        [<J: DimName> ops::RangeFrom<J>
+          =>  DimDiff<C, J>
+          where C: DimSub<J>],
+    }
+}

src/base/iter.rs

@@ -3,9 +3,9 @@
 use std::marker::PhantomData;
 use std::mem;
 
-use base::dimension::Dim;
+use base::dimension::{Dim, U1};
 use base::storage::{Storage, StorageMut};
-use base::Scalar;
+use base::{Scalar, Matrix, MatrixSlice, MatrixSliceMut};
 
 macro_rules! iterator {
     (struct $Name:ident for $Storage:ident.$ptr: ident -> $Ptr:ty, $Ref:ty, $SRef: ty) => {
@@ -96,3 +96,226 @@ macro_rules! iterator {
 
 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);
+
+
+/*
+ *
+ * Row iterators.
+ *
+ */
+#[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>,
+    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 {
+        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>;
+
+    #[inline]
+    fn next(&mut self) -> Option<Self::Item> {
+        if self.curr < self.mat.nrows() {
+            let res = self.mat.row(self.curr);
+            self.curr += 1;
+            Some(res)
+        } else {
+            None
+        }
+    }
+
+    #[inline]
+    fn size_hint(&self) -> (usize, Option<usize>) {
+        (self.mat.nrows() - self.curr, Some(self.mat.nrows() - self.curr))
+    }
+
+    #[inline]
+    fn count(self) -> usize {
+        self.mat.nrows() - self.curr
+    }
+}
+
+impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + Storage<N, R, C>> ExactSizeIterator for RowIter<'a, N, R, C, S> {
+    #[inline]
+    fn len(&self) -> usize {
+        self.mat.nrows() - self.curr
+    }
+}
+
+
+/// 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>,
+    curr: usize,
+    phantom: PhantomData<&'a mut Matrix<N, 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 {
+        RowIterMut {
+            mat,
+            curr: 0,
+            phantom: PhantomData
+        }
+    }
+
+    fn nrows(&self) -> usize {
+        unsafe {
+            (*self.mat).nrows()
+        }
+    }
+}
+
+
+impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> Iterator for RowIterMut<'a, N, R, C, S> {
+    type Item = MatrixSliceMut<'a, N, U1, C, S::RStride, S::CStride>;
+
+    #[inline]
+    fn next(&mut self) -> Option<Self::Item> {
+        if self.curr < self.nrows() {
+            let res = unsafe { (*self.mat).row_mut(self.curr) };
+            self.curr += 1;
+            Some(res)
+        } else {
+            None
+        }
+    }
+
+    #[inline]
+    fn size_hint(&self) -> (usize, Option<usize>) {
+        (self.nrows() - self.curr, Some(self.nrows() - self.curr))
+    }
+
+    #[inline]
+    fn count(self) -> usize {
+        self.nrows() - self.curr
+    }
+}
+
+impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> ExactSizeIterator for RowIterMut<'a, N, R, C, S> {
+    #[inline]
+    fn len(&self) -> usize {
+        self.nrows() - self.curr
+    }
+}
+
+
+/*
+ *
+ * Column iterators.
+ *
+ */
+#[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>,
+    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 {
+        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> {
+    type Item = MatrixSlice<'a, N, R, U1, S::RStride, S::CStride>;
+
+    #[inline]
+    fn next(&mut self) -> Option<Self::Item> {
+        if self.curr < self.mat.ncols() {
+            let res = self.mat.column(self.curr);
+            self.curr += 1;
+            Some(res)
+        } else {
+            None
+        }
+    }
+
+    #[inline]
+    fn size_hint(&self) -> (usize, Option<usize>) {
+        (self.mat.ncols() - self.curr, Some(self.mat.ncols() - self.curr))
+    }
+
+    #[inline]
+    fn count(self) -> usize {
+        self.mat.ncols() - self.curr
+    }
+}
+
+impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + Storage<N, R, C>> ExactSizeIterator for ColumnIter<'a, N, R, C, S> {
+    #[inline]
+    fn len(&self) -> usize {
+        self.mat.ncols() - self.curr
+    }
+}
+
+
+/// 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>,
+    curr: usize,
+    phantom: PhantomData<&'a mut Matrix<N, 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 {
+        ColumnIterMut {
+            mat,
+            curr: 0,
+            phantom: PhantomData
+        }
+    }
+
+    fn ncols(&self) -> usize {
+        unsafe {
+            (*self.mat).ncols()
+        }
+    }
+}
+
+
+impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> Iterator for ColumnIterMut<'a, N, R, C, S> {
+    type Item = MatrixSliceMut<'a, N, R, U1, S::RStride, S::CStride>;
+
+    #[inline]
+    fn next(&mut self) -> Option<Self::Item> {
+        if self.curr < self.ncols() {
+            let res = unsafe { (*self.mat).column_mut(self.curr) };
+            self.curr += 1;
+            Some(res)
+        } else {
+            None
+        }
+    }
+
+    #[inline]
+    fn size_hint(&self) -> (usize, Option<usize>) {
+        (self.ncols() - self.curr, Some(self.ncols() - self.curr))
+    }
+
+    #[inline]
+    fn count(self) -> usize {
+        self.ncols() - self.curr
+    }
+}
+
+impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + StorageMut<N, R, C>> ExactSizeIterator for ColumnIterMut<'a, N, R, C, S> {
+    #[inline]
+    fn len(&self) -> usize {
+        self.ncols() - self.curr
+    }
+}
+

src/base/matrix.rs

@@ -7,6 +7,7 @@ use approx::{AbsDiffEq, RelativeEq, UlpsEq};
 use std::any::TypeId;
 use std::cmp::Ordering;
 use std::fmt;
+use std::hash::{Hash, Hasher};
 use std::marker::PhantomData;
 use std::mem;
 
@@ -20,8 +21,8 @@ use alga::general::{ClosedAdd, ClosedMul, ClosedSub, Real, Ring};
 
 use base::allocator::{Allocator, SameShapeAllocator, SameShapeC, SameShapeR};
 use base::constraint::{DimEq, SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
-use base::dimension::{Dim, DimAdd, DimSum, U1, U2, U3};
+use base::dimension::{Dim, DimAdd, DimSum, IsNotStaticOne, U1, U2, U3};
-use base::iter::{MatrixIter, MatrixIterMut};
+use base::iter::{MatrixIter, MatrixIterMut, RowIter, RowIterMut, ColumnIter, ColumnIterMut};
 use base::storage::{
     ContiguousStorage, ContiguousStorageMut, Owned, SameShapeStorage, Storage, StorageMut,
 };
@@ -72,7 +73,7 @@ pub type MatrixCross<N, R1, C1, R2, C2> =
 /// dynamically-sized column vector should be represented as a `Matrix<N, Dynamic, U1, S>` (given
 /// some concrete types for `N` and a compatible data storage type `S`).
 #[repr(C)]
-#[derive(Hash, Clone, Copy)]
+#[derive(Clone, Copy)]
 pub struct Matrix<N: Scalar, R: Dim, C: Dim, S> {
     /// The data storage that contains all the matrix components and informations about its number
     /// of rows and column (if needed).
@@ -246,6 +247,37 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         MatrixIter::new(&self.data)
     }
 
+    /// Iterate through the rows of this matrix.
+    ///
+    /// # Example
+    /// ```
+    /// # use nalgebra::Matrix2x3;
+    /// let mut a = Matrix2x3::new(1, 2, 3,
+    ///                            4, 5, 6);
+    /// for (i, row) in a.row_iter().enumerate() {
+    ///     assert_eq!(row, a.row(i))
+    /// }
+    /// ```
+    #[inline]
+    pub fn row_iter(&self) -> RowIter<N, R, C, S> {
+        RowIter::new(self)
+    }
+
+    /// Iterate through the columns of this matrix.
+    /// # Example
+    /// ```
+    /// # use nalgebra::Matrix2x3;
+    /// let mut a = Matrix2x3::new(1, 2, 3,
+    ///                            4, 5, 6);
+    /// for (i, column) in a.column_iter().enumerate() {
+    ///     assert_eq!(column, a.column(i))
+    /// }
+    /// ```
+    #[inline]
+    pub fn column_iter(&self) -> ColumnIter<N, R, C, S> {
+        ColumnIter::new(self)
+    }
+
     /// Computes the row and column coordinates of the i-th element of this matrix seen as a
     /// vector.
     #[inline]
@@ -263,17 +295,6 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         }
     }
 
-    /// Gets a reference to the element of this matrix at row `irow` and column `icol` without
-    /// bound-checking.
-    #[inline]
-    pub unsafe fn get_unchecked(&self, irow: usize, icol: usize) -> &N {
-        debug_assert!(
-            irow < self.nrows() && icol < self.ncols(),
-            "Matrix index out of bounds."
-        );
-        self.data.get_unchecked(irow, icol)
-    }
-
     /// Returns a pointer to the start of the matrix.
     ///
     /// If the matrix is not empty, this pointer is guaranteed to be aligned
@@ -383,7 +404,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         for j in 0..res.ncols() {
             for i in 0..res.nrows() {
                 unsafe {
-                    *res.get_unchecked_mut(i, j) = *self.get_unchecked(i, j);
+                    *res.get_unchecked_mut((i, j)) = *self.get_unchecked((i, j));
                 }
             }
         }
@@ -412,7 +433,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     }
 
     /// Returns a matrix containing the result of `f` applied to each of its entries. Unlike `map`,
-    /// `f` also gets passed the row and column index, i.e. `f(value, row, col)`.
+    /// `f` also gets passed the row and column index, i.e. `f(row, col, value)`.
     #[inline]
     pub fn map_with_location<N2: Scalar, F: FnMut(usize, usize, N) -> N2>(
         &self,
@@ -512,6 +533,57 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         res
     }
 
+    /// Folds a function `f` on each entry of `self`.
+    #[inline]
+    pub fn fold<Acc>(&self, init: Acc, mut f: impl FnMut(Acc, N) -> Acc) -> Acc {
+        let (nrows, ncols) = self.data.shape();
+
+        let mut res = init;
+
+        for j in 0..ncols.value() {
+            for i in 0..nrows.value() {
+                unsafe {
+                    let a = *self.data.get_unchecked(i, j);
+                    res = f(res, a)
+                }
+            }
+        }
+
+        res
+    }
+
+    /// Folds a function `f` on each pairs of entries from `self` and `rhs`.
+    #[inline]
+    pub fn zip_fold<N2, R2, C2, S2, Acc>(&self, rhs: &Matrix<N2, R2, C2, S2>, init: Acc, mut f: impl FnMut(Acc, N, N2) -> Acc) -> Acc
+        where
+            N2: Scalar,
+            R2: Dim,
+            C2: Dim,
+            S2: Storage<N2, R2, C2>,
+            ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>
+    {
+        let (nrows, ncols) = self.data.shape();
+
+        let mut res = init;
+
+        assert!(
+            (nrows.value(), ncols.value()) == rhs.shape(),
+            "Matrix simultaneous traversal error: dimension mismatch."
+        );
+
+        for j in 0..ncols.value() {
+            for i in 0..nrows.value() {
+                unsafe {
+                    let a = *self.data.get_unchecked(i, j);
+                    let b = *rhs.data.get_unchecked(i, j);
+                    res = f(res, a, b)
+                }
+            }
+        }
+
+        res
+    }
+
     /// Transposes `self` and store the result into `out`.
     #[inline]
     pub fn transpose_to<R2, C2, SB>(&self, out: &mut Matrix<N, R2, C2, SB>)
@@ -531,7 +603,7 @@ 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 0..ncols {
                 unsafe {
-                    *out.get_unchecked_mut(j, i) = *self.get_unchecked(i, j);
+                    *out.get_unchecked_mut((j, i)) = *self.get_unchecked((i, j));
                 }
             }
         }
@@ -568,14 +640,44 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
         self.data.ptr_mut()
     }
 
-    /// Gets a mutable reference to the i-th element of this matrix.
+    /// Mutably iterates through this matrix rows.
+    ///
+    /// # Example
+    /// ```
+    /// # use nalgebra::Matrix2x3;
+    /// let mut a = Matrix2x3::new(1, 2, 3,
+    ///                            4, 5, 6);
+    /// for (i, mut row) in a.row_iter_mut().enumerate() {
+    ///     row *= (i + 1) * 10;
+    /// }
+    ///
+    /// let expected = Matrix2x3::new(10, 20, 30,
+    ///                               80, 100, 120);
+    /// assert_eq!(a, expected);
+    /// ```
     #[inline]
-    pub unsafe fn get_unchecked_mut(&mut self, irow: usize, icol: usize) -> &mut N {
+    pub fn row_iter_mut(&mut self) -> RowIterMut<N, R, C, S> {
-        debug_assert!(
+        RowIterMut::new(self)
-            irow < self.nrows() && icol < self.ncols(),
+    }
-            "Matrix index out of bounds."
+
-        );
+    /// Mutably iterates through this matrix columns.
-        self.data.get_unchecked_mut(irow, icol)
+    ///
+    /// # Example
+    /// ```
+    /// # use nalgebra::Matrix2x3;
+    /// let mut a = Matrix2x3::new(1, 2, 3,
+    ///                            4, 5, 6);
+    /// for (i, mut col) in a.column_iter_mut().enumerate() {
+    ///     col *= (i + 1) * 10;
+    /// }
+    ///
+    /// let expected = Matrix2x3::new(10, 40, 90,
+    ///                               40, 100, 180);
+    /// assert_eq!(a, expected);
+    /// ```
+    #[inline]
+    pub fn column_iter_mut(&mut self) -> ColumnIterMut<N, R, C, S> {
+        ColumnIterMut::new(self)
     }
 
     /// Swaps two entries without bound-checking.
@@ -616,7 +718,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
         for j in 0..ncols {
             for i in 0..nrows {
                 unsafe {
-                    *self.get_unchecked_mut(i, j) = *slice.get_unchecked(i + j * nrows);
+                    *self.get_unchecked_mut((i, j)) = *slice.get_unchecked(i + j * nrows);
                 }
             }
         }
@@ -639,7 +741,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
         for j in 0..self.ncols() {
             for i in 0..self.nrows() {
                 unsafe {
-                    *self.get_unchecked_mut(i, j) = *other.get_unchecked(i, j);
+                    *self.get_unchecked_mut((i, j)) = *other.get_unchecked((i, j));
                 }
             }
         }
@@ -663,7 +765,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
         for j in 0..ncols {
             for i in 0..nrows {
                 unsafe {
-                    *self.get_unchecked_mut(i, j) = *other.get_unchecked(j, i);
+                    *self.get_unchecked_mut((i, j)) = *other.get_unchecked((j, i));
                 }
             }
         }
@@ -671,8 +773,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
 
     /// Replaces each component of `self` by the result of a closure `f` applied on it.
     #[inline]
-    pub fn apply<F: FnMut(N) -> N>(&mut self, mut f: F)
+    pub fn apply<F: FnMut(N) -> N>(&mut self, mut f: F) {
-    where DefaultAllocator: Allocator<N, R, C> {
         let (nrows, ncols) = self.shape();
 
         for j in 0..ncols {
@@ -684,6 +785,71 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
             }
         }
     }
+
+    /// Replaces each component of `self` by the result of a closure `f` applied on its components
+    /// joined with the components from `rhs`.
+    #[inline]
+    pub fn zip_apply<N2, R2, C2, S2>(&mut self, rhs: &Matrix<N2, R2, C2, S2>, mut f: impl FnMut(N, N2) -> N)
+        where N2: Scalar,
+              R2: Dim,
+              C2: Dim,
+              S2: Storage<N2, R2, C2>,
+              ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2> {
+        let (nrows, ncols) = self.shape();
+
+        assert!(
+            (nrows, ncols) == rhs.shape(),
+            "Matrix simultaneous traversal error: dimension mismatch."
+        );
+
+        for j in 0..ncols {
+            for i in 0..nrows {
+                unsafe {
+                    let e = self.data.get_unchecked_mut(i, j);
+                    let rhs = rhs.get_unchecked((i, j));
+                    *e = f(*e, *rhs)
+                }
+            }
+        }
+    }
+
+
+    /// Replaces each component of `self` by the result of a closure `f` applied on its components
+    /// joined with the components from `b` and `c`.
+    #[inline]
+    pub fn zip_zip_apply<N2, R2, C2, S2, N3, R3, C3, S3>(&mut self, b: &Matrix<N2, R2, C2, S2>, c: &Matrix<N3, R3, C3, S3>, mut f: impl FnMut(N, N2, N3) -> N)
+        where N2: Scalar,
+              R2: Dim,
+              C2: Dim,
+              S2: Storage<N2, R2, C2>,
+              N3: Scalar,
+              R3: Dim,
+              C3: Dim,
+              S3: Storage<N3, R3, C3>,
+              ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
+              ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2> {
+        let (nrows, ncols) = self.shape();
+
+        assert!(
+            (nrows, ncols) == b.shape(),
+            "Matrix simultaneous traversal error: dimension mismatch."
+        );
+        assert!(
+            (nrows, ncols) == c.shape(),
+            "Matrix simultaneous traversal error: dimension mismatch."
+        );
+
+        for j in 0..ncols {
+            for i in 0..nrows {
+                unsafe {
+                    let e = self.data.get_unchecked_mut(i, j);
+                    let b = b.get_unchecked((i, j));
+                    let c = c.get_unchecked((i, j));
+                    *e = f(*e, *b, *c)
+                }
+            }
+        }
+    }
 }
 
 impl<N: Scalar, D: Dim, S: Storage<N, D>> Vector<N, D, S> {
@@ -760,7 +926,7 @@ impl<N: Real, R: Dim, C: Dim, S: Storage<Complex<N>, R, C>> Matrix<Complex<N>, R
         for i in 0..nrows {
             for j in 0..ncols {
                 unsafe {
-                    *out.get_unchecked_mut(j, i) = self.get_unchecked(i, j).conj();
+                    *out.get_unchecked_mut((j, i)) = self.get_unchecked((i, j)).conj();
                 }
             }
         }
@@ -794,8 +960,8 @@ impl<N: Real, D: Dim, S: StorageMut<Complex<N>, D, D>> Matrix<Complex<N>, D, D,
         for i in 1..dim {
             for j in 0..i {
                 unsafe {
-                    let ref_ij = self.get_unchecked_mut(i, j) as *mut Complex<N>;
+                    let ref_ij = self.get_unchecked_mut((i, j)) as *mut Complex<N>;
-                    let ref_ji = self.get_unchecked_mut(j, i) as *mut Complex<N>;
+                    let ref_ji = self.get_unchecked_mut((j, i)) as *mut Complex<N>;
                     let conj_ij = (*ref_ij).conj();
                     let conj_ji = (*ref_ji).conj();
                     *ref_ij = conj_ji;
@@ -821,7 +987,7 @@ impl<N: Scalar, D: Dim, S: Storage<N, D, D>> SquareMatrix<N, D, S> {
 
         for i in 0..dim.value() {
             unsafe {
-                *res.vget_unchecked_mut(i) = *self.get_unchecked(i, i);
+                *res.vget_unchecked_mut(i) = *self.get_unchecked((i, i));
             }
         }
 
@@ -841,27 +1007,36 @@ impl<N: Scalar, D: Dim, S: Storage<N, D, D>> SquareMatrix<N, D, S> {
         let mut res = N::zero();
 
         for i in 0..dim.value() {
-            res += unsafe { *self.get_unchecked(i, i) };
+            res += unsafe { *self.get_unchecked((i, i)) };
         }
 
         res
     }
 }
 
+impl<N: Scalar + One + Zero, D: DimAdd<U1> + IsNotStaticOne, S: Storage<N, D, D>> Matrix<N, D, D, S> {
+
+    /// Yields the homogeneous matrix for this matrix, i.e., appending an additional dimension and
+    /// and setting the diagonal element to `1`.
+    #[inline]
+    pub fn to_homogeneous(&self) -> MatrixN<N, DimSum<D, U1>>
+    where DefaultAllocator: Allocator<N, DimSum<D, U1>, DimSum<D, U1>> {
+        assert!(self.is_square(), "Only square matrices can currently be transformed to homogeneous coordinates.");
+        let dim = DimSum::<D, U1>::from_usize(self.nrows() + 1);
+        let mut res = MatrixN::identity_generic(dim, dim); 
+        res.generic_slice_mut::<D, D>((0, 0), self.data.shape()).copy_from(&self);
+        res
+    }
+
+}
+
 impl<N: Scalar + Zero, D: DimAdd<U1>, S: Storage<N, D>> Vector<N, D, S> {
     /// Computes the coordinates in projective space of this vector, i.e., appends a `0` to its
     /// coordinates.
     #[inline]
     pub fn to_homogeneous(&self) -> VectorN<N, DimSum<D, U1>>
     where DefaultAllocator: Allocator<N, DimSum<D, U1>> {
-        let len = self.len();
+        self.push(N::zero())
-        let hnrows = DimSum::<D, U1>::from_usize(len + 1);
-        let mut res = unsafe { VectorN::<N, _>::new_uninitialized_generic(hnrows, U1) };
-        res.generic_slice_mut((0, 0), self.data.shape())
-            .copy_from(self);
-        res[(len, 0)] = N::zero();
-
-        res
     }
 
     /// Constructs a vector from coordinates in projective space, i.e., removes a `0` at the end of
@@ -881,6 +1056,22 @@ impl<N: Scalar + Zero, D: DimAdd<U1>, S: Storage<N, D>> Vector<N, D, S> {
     }
 }
 
+impl<N: Scalar + Zero, D: DimAdd<U1>, S: Storage<N, D>> Vector<N, D, S> {
+    /// Constructs a new vector of higher dimension by appending `element` to the end of `self`.
+    #[inline]
+    pub fn push(&self, element: N) -> VectorN<N, DimSum<D, U1>>
+    where DefaultAllocator: Allocator<N, DimSum<D, U1>> {
+        let len = self.len();
+        let hnrows = DimSum::<D, U1>::from_usize(len + 1);
+        let mut res = unsafe { VectorN::<N, _>::new_uninitialized_generic(hnrows, U1) };
+        res.generic_slice_mut((0, 0), self.data.shape())
+            .copy_from(self);
+        res[(len, 0)] = element;
+
+        res
+    }
+}
+
 impl<N, R: Dim, C: Dim, S> AbsDiffEq for Matrix<N, R, C, S>
 where
     N: Scalar + AbsDiffEq,
@@ -1141,8 +1332,8 @@ impl<N: Scalar + Ring, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         assert!(self.shape() == (2, 1), "2D perpendicular product ");
 
         unsafe {
-            *self.get_unchecked(0, 0) * *b.get_unchecked(1, 0)
+            *self.get_unchecked((0, 0)) * *b.get_unchecked((1, 0))
-                - *self.get_unchecked(1, 0) * *b.get_unchecked(0, 0)
+                - *self.get_unchecked((1, 0)) * *b.get_unchecked((0, 0))
         }
     }
 
@@ -1177,17 +1368,17 @@ impl<N: Scalar + Ring, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
                 let ncols = SameShapeC::<C, C2>::from_usize(1);
                 let mut res = Matrix::new_uninitialized_generic(nrows, ncols);
 
-                let ax = *self.get_unchecked(0, 0);
+                let ax = *self.get_unchecked((0, 0));
-                let ay = *self.get_unchecked(1, 0);
+                let ay = *self.get_unchecked((1, 0));
-                let az = *self.get_unchecked(2, 0);
+                let az = *self.get_unchecked((2, 0));
 
-                let bx = *b.get_unchecked(0, 0);
+                let bx = *b.get_unchecked((0, 0));
-                let by = *b.get_unchecked(1, 0);
+                let by = *b.get_unchecked((1, 0));
-                let bz = *b.get_unchecked(2, 0);
+                let bz = *b.get_unchecked((2, 0));
 
-                *res.get_unchecked_mut(0, 0) = ay * bz - az * by;
+                *res.get_unchecked_mut((0, 0)) = ay * bz - az * by;
-                *res.get_unchecked_mut(1, 0) = az * bx - ax * bz;
+                *res.get_unchecked_mut((1, 0)) = az * bx - ax * bz;
-                *res.get_unchecked_mut(2, 0) = ax * by - ay * bx;
+                *res.get_unchecked_mut((2, 0)) = ax * by - ay * bx;
 
                 res
             }
@@ -1198,17 +1389,17 @@ impl<N: Scalar + Ring, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
                 let ncols = SameShapeC::<C, C2>::from_usize(3);
                 let mut res = Matrix::new_uninitialized_generic(nrows, ncols);
 
-                let ax = *self.get_unchecked(0, 0);
+                let ax = *self.get_unchecked((0, 0));
-                let ay = *self.get_unchecked(0, 1);
+                let ay = *self.get_unchecked((0, 1));
-                let az = *self.get_unchecked(0, 2);
+                let az = *self.get_unchecked((0, 2));
 
-                let bx = *b.get_unchecked(0, 0);
+                let bx = *b.get_unchecked((0, 0));
-                let by = *b.get_unchecked(0, 1);
+                let by = *b.get_unchecked((0, 1));
-                let bz = *b.get_unchecked(0, 2);
+                let bz = *b.get_unchecked((0, 2));
 
-                *res.get_unchecked_mut(0, 0) = ay * bz - az * by;
+                *res.get_unchecked_mut((0, 0)) = ay * bz - az * by;
-                *res.get_unchecked_mut(0, 1) = az * bx - ax * bz;
+                *res.get_unchecked_mut((0, 1)) = az * bx - ax * bz;
-                *res.get_unchecked_mut(0, 2) = ax * by - ay * bx;
+                *res.get_unchecked_mut((0, 2)) = ax * by - ay * bx;
 
                 res
             }
@@ -1264,67 +1455,6 @@ impl<N: Real, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     }
 }
 
-impl<N: Real, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
-    /// The squared L2 norm of this vector.
-    #[inline]
-    pub fn norm_squared(&self) -> N {
-        let mut res = N::zero();
-
-        for i in 0..self.ncols() {
-            let col = self.column(i);
-            res += col.dot(&col)
-        }
-
-        res
-    }
-
-    /// The L2 norm of this matrix.
-    #[inline]
-    pub fn norm(&self) -> N {
-        self.norm_squared().sqrt()
-    }
-
-    /// A synonym for the norm of this matrix.
-    ///
-    /// Aka the length.
-    ///
-    /// This function is simply implemented as a call to `norm()`
-    #[inline]
-    pub fn magnitude(&self) -> N {
-        self.norm()
-    }
-
-    /// A synonym for the squared norm of this matrix.
-    ///
-    /// Aka the squared length.
-    ///
-    /// This function is simply implemented as a call to `norm_squared()`
-    #[inline]
-    pub fn magnitude_squared(&self) -> N {
-        self.norm_squared()
-    }
-
-    /// Returns a normalized version of this matrix.
-    #[inline]
-    pub fn normalize(&self) -> MatrixMN<N, R, C>
-    where DefaultAllocator: Allocator<N, R, C> {
-        self / self.norm()
-    }
-
-    /// Returns a normalized version of this matrix unless its norm as smaller or equal to `eps`.
-    #[inline]
-    pub fn try_normalize(&self, min_norm: N) -> Option<MatrixMN<N, R, C>>
-    where DefaultAllocator: Allocator<N, R, C> {
-        let n = self.norm();
-
-        if n <= min_norm {
-            None
-        } else {
-            Some(self / n)
-        }
-    }
-}
-
 impl<N: Scalar + Zero + One + ClosedAdd + ClosedSub + ClosedMul, D: Dim, S: Storage<N, D>>
     Vector<N, D, S>
 {
@@ -1399,32 +1529,6 @@ impl<N: Real, D: Dim, S: Storage<N, D>> Unit<Vector<N, D, S>> {
     }
 }
 
-impl<N: Real, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
-    /// Normalizes this matrix in-place and returns its norm.
-    #[inline]
-    pub fn normalize_mut(&mut self) -> N {
-        let n = self.norm();
-        *self /= n;
-
-        n
-    }
-
-    /// Normalizes this matrix in-place or does nothing if its norm is smaller or equal to `eps`.
-    ///
-    /// If the normalization succeeded, returns the old normal of this matrix.
-    #[inline]
-    pub fn try_normalize_mut(&mut self, min_norm: N) -> Option<N> {
-        let n = self.norm();
-
-        if n <= min_norm {
-            None
-        } else {
-            *self /= n;
-            Some(n)
-        }
-    }
-}
-
 impl<N, R: Dim, C: Dim, S> AbsDiffEq for Unit<Matrix<N, R, C, S>>
 where
     N: Scalar + AbsDiffEq,
@@ -1484,3 +1588,24 @@ where
         self.as_ref().ulps_eq(other.as_ref(), epsilon, max_ulps)
     }
 }
+
+impl<N, R, C, S> Hash for Matrix<N, R, C, S>
+where
+    N: Scalar + Hash,
+    R: Dim,
+    C: Dim,
+    S: Storage<N, R, C>,
+{
+    fn hash<H: Hasher>(&self, state: &mut H) {
+        let (nrows, ncols) = self.shape();
+        (nrows, ncols).hash(state);
+
+        for j in 0..ncols {
+            for i in 0..nrows {
+                unsafe {
+                     self.get_unchecked((i, j)).hash(state);
+                }
+            }
+        }
+    }
+}

src/base/matrix_alga.rs

@@ -6,7 +6,7 @@ use num::{One, Zero};
 use alga::general::{
     AbstractGroup, AbstractGroupAbelian, AbstractLoop, AbstractMagma, AbstractModule,
     AbstractMonoid, AbstractQuasigroup, AbstractSemigroup, Additive, ClosedAdd, ClosedMul,
-    ClosedNeg, Field, Identity, Inverse, JoinSemilattice, Lattice, MeetSemilattice, Module,
+    ClosedNeg, Field, Identity, TwoSidedInverse, JoinSemilattice, Lattice, MeetSemilattice, Module,
     Multiplicative, Real, RingCommutative,
 };
 use alga::linear::{
@@ -45,18 +45,18 @@ where
     }
 }
 
-impl<N, R: DimName, C: DimName> Inverse<Additive> for MatrixMN<N, R, C>
+impl<N, R: DimName, C: DimName> TwoSidedInverse<Additive> for MatrixMN<N, R, C>
 where
     N: Scalar + ClosedNeg,
     DefaultAllocator: Allocator<N, R, C>,
 {
     #[inline]
-    fn inverse(&self) -> MatrixMN<N, R, C> {
+    fn two_sided_inverse(&self) -> MatrixMN<N, R, C> {
         -self
     }
 
     #[inline]
-    fn inverse_mut(&mut self) {
+    fn two_sided_inverse_mut(&mut self) {
         *self = -self.clone()
     }
 }

src/base/matrix_slice.rs

@@ -4,9 +4,9 @@ use std::slice;
 
 use base::allocator::Allocator;
 use base::default_allocator::DefaultAllocator;
-use base::dimension::{Dim, DimName, Dynamic, U1};
+use base::dimension::{Dim, DimName, Dynamic, U1, IsNotStaticOne};
 use base::iter::MatrixIter;
-use base::storage::{Owned, Storage, StorageMut};
+use base::storage::{Owned, Storage, StorageMut, ContiguousStorage, ContiguousStorageMut};
 use base::{Matrix, Scalar};
 
 macro_rules! slice_storage_impl(
@@ -91,7 +91,8 @@ slice_storage_impl!("A mutable matrix data storage for mutable matrix slice. Onl
 
 impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim> Copy
     for SliceStorage<'a, N, 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>
@@ -146,8 +147,6 @@ macro_rules! storage_impl(
                 }
             }
 
-
-
             #[inline]
             fn into_owned(self) -> Owned<N, R, C>
                 where DefaultAllocator: Allocator<N, R, C> {
@@ -199,6 +198,14 @@ 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, N: Scalar, R: Dim, CStride: Dim> ContiguousStorage<N, R, U1> for SliceStorageMut<'a, N, 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, N: Scalar, R: DimName, C: Dim + IsNotStaticOne> ContiguousStorage<N, R, C> for SliceStorage<'a, N, 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, N: Scalar, R: DimName, C: Dim + IsNotStaticOne> ContiguousStorageMut<N, R, C> for SliceStorageMut<'a, N, R, C, U1, R> { }
+
 impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     #[inline]
     fn assert_slice_index(
@@ -859,3 +866,25 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
         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>
+    where
+        N: Scalar,
+        R: Dim,
+        C: Dim,
+        RStride: Dim,
+        CStride: Dim,
+{
+    fn from(slice_mut: MatrixSliceMut<'a, N, R, C, RStride, CStride>) -> Self {
+        let data = SliceStorage {
+            ptr:       slice_mut.data.ptr,
+            shape:     slice_mut.data.shape,
+            strides:   slice_mut.data.strides,
+            _phantoms: PhantomData,
+        };
+
+        unsafe { Matrix::from_data_statically_unchecked(data) }
+    }
+}

src/base/mod.rs

@@ -18,16 +18,19 @@ mod construction;
 mod construction_slice;
 mod conversion;
 mod edition;
+pub mod indexing;
 mod matrix;
 mod matrix_alga;
-mod matrix_array;
+mod array_storage;
 mod matrix_slice;
 #[cfg(any(feature = "std", feature = "alloc"))]
-mod matrix_vec;
+mod vec_storage;
 mod properties;
 mod scalar;
 mod swizzle;
 mod unit;
+mod statistics;
+mod norm;
 
 #[doc(hidden)]
 pub mod helper;
@@ -35,13 +38,14 @@ pub mod helper;
 pub use self::matrix::*;
 pub use self::scalar::*;
 pub use self::unit::*;
+pub use self::norm::*;
 
 pub use self::default_allocator::*;
 pub use self::dimension::*;
 
 pub use self::alias::*;
 pub use self::alias_slice::*;
-pub use self::matrix_array::*;
+pub use self::array_storage::*;
 pub use self::matrix_slice::*;
 #[cfg(any(feature = "std", feature = "alloc"))]
-pub use self::matrix_vec::*;
+pub use self::vec_storage::*;

src/base/norm.rs

@@ -0,0 +1,238 @@
+use num::Signed;
+use std::cmp::PartialOrd;
+
+use allocator::Allocator;
+use ::{Real, Scalar};
+use storage::{Storage, StorageMut};
+use base::{DefaultAllocator, Matrix, Dim, MatrixMN};
+use constraint::{SameNumberOfRows, SameNumberOfColumns, ShapeConstraint};
+
+
+// FIXME: this should be be a trait on alga?
+/// A trait for abstract matrix norms.
+///
+/// This may be moved to the alga crate in the future.
+pub trait Norm<N: Scalar> {
+    /// Apply this norm to the given matrix.
+    fn norm<R, C, S>(&self, m: &Matrix<N, R, C, S>) -> N
+        where R: Dim, C: Dim, S: Storage<N, 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
+        where R1: Dim, C1: Dim, S1: Storage<N, R1, C1>,
+              R2: Dim, C2: Dim, S2: Storage<N, R2, C2>,
+              ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>;
+}
+
+/// Euclidean norm.
+pub struct EuclideanNorm;
+/// Lp norm.
+pub struct LpNorm(pub i32);
+/// L-infinite norm aka. Chebytchev norm aka. uniform norm aka. suppremum norm.
+pub struct UniformNorm;
+
+impl<N: Real> Norm<N> for EuclideanNorm {
+    #[inline]
+    fn norm<R, C, S>(&self, m: &Matrix<N, R, C, S>) -> N
+        where R: Dim, C: Dim, S: Storage<N, R, C> {
+        m.norm_squared().sqrt()
+    }
+
+    #[inline]
+    fn metric_distance<R1, C1, S1, R2, C2, S2>(&self, m1: &Matrix<N, R1, C1, S1>, m2: &Matrix<N, R2, C2, S2>) -> N
+        where R1: Dim, C1: Dim, S1: Storage<N, R1, C1>,
+              R2: Dim, C2: Dim, S2: Storage<N, R2, C2>,
+              ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
+        m1.zip_fold(m2, N::zero(), |acc, a, b| {
+            let diff = a - b;
+            acc + diff * diff
+        }).sqrt()
+    }
+}
+
+impl<N: Real> Norm<N> for LpNorm {
+    #[inline]
+    fn norm<R, C, S>(&self, m: &Matrix<N, R, C, S>) -> N
+        where R: Dim, C: Dim, S: Storage<N, R, C> {
+        m.fold(N::zero(), |a, b| {
+            a + b.abs().powi(self.0)
+        }).powf(::convert(1.0 / (self.0 as f64)))
+    }
+
+    #[inline]
+    fn metric_distance<R1, C1, S1, R2, C2, S2>(&self, m1: &Matrix<N, R1, C1, S1>, m2: &Matrix<N, R2, C2, S2>) -> N
+        where R1: Dim, C1: Dim, S1: Storage<N, R1, C1>,
+              R2: Dim, C2: Dim, S2: Storage<N, R2, C2>,
+              ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
+        m1.zip_fold(m2, N::zero(), |acc, a, b| {
+            let diff = a - b;
+            acc + diff.abs().powi(self.0)
+        }).powf(::convert(1.0 / (self.0 as f64)))
+    }
+}
+
+impl<N: Scalar + PartialOrd + Signed> Norm<N> for UniformNorm {
+    #[inline]
+    fn norm<R, C, S>(&self, m: &Matrix<N, R, C, S>) -> N
+        where R: Dim, C: Dim, S: Storage<N, R, C> {
+        m.amax()
+    }
+
+    #[inline]
+    fn metric_distance<R1, C1, S1, R2, C2, S2>(&self, m1: &Matrix<N, R1, C1, S1>, m2: &Matrix<N, R2, C2, S2>) -> N
+        where R1: Dim, C1: Dim, S1: Storage<N, R1, C1>,
+              R2: Dim, C2: Dim, S2: Storage<N, R2, C2>,
+              ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
+        m1.zip_fold(m2, N::zero(), |acc, a, b| {
+            let val = (a - b).abs();
+            if val > acc {
+                val
+            } else {
+                acc
+            }
+        })
+    }
+}
+
+
+impl<N: Real, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+    /// The squared L2 norm of this vector.
+    #[inline]
+    pub fn norm_squared(&self) -> N {
+        let mut res = N::zero();
+
+        for i in 0..self.ncols() {
+            let col = self.column(i);
+            res += col.dot(&col)
+        }
+
+        res
+    }
+
+    /// The L2 norm of this matrix.
+    ///
+    /// Use `.apply_norm` to apply a custom norm.
+    #[inline]
+    pub fn norm(&self) -> N {
+        self.norm_squared().sqrt()
+    }
+
+    /// Compute the distance between `self` and `rhs` using the metric induced by the euclidean norm.
+    ///
+    /// 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
+        where R2: Dim, C2: Dim, S2: Storage<N, R2, C2>,
+              ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2> {
+        self.apply_metric_distance(rhs, &EuclideanNorm)
+    }
+
+    /// Uses the given `norm` to compute the norm of `self`.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use nalgebra::{Vector3, UniformNorm, LpNorm, EuclideanNorm};
+    ///
+    /// let v = Vector3::new(1.0, 2.0, 3.0);
+    /// assert_eq!(v.apply_norm(&UniformNorm), 3.0);
+    /// assert_eq!(v.apply_norm(&LpNorm(1)), 6.0);
+    /// assert_eq!(v.apply_norm(&EuclideanNorm), v.norm());
+    /// ```
+    #[inline]
+    pub fn apply_norm(&self, norm: &impl Norm<N>) -> N {
+        norm.norm(self)
+    }
+
+    /// Uses the metric induced by the given `norm` to compute the metric distance between `self` and `rhs`.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use nalgebra::{Vector3, UniformNorm, LpNorm, EuclideanNorm};
+    ///
+    /// let v1 = Vector3::new(1.0, 2.0, 3.0);
+    /// let v2 = Vector3::new(10.0, 20.0, 30.0);
+    ///
+    /// assert_eq!(v1.apply_metric_distance(&v2, &UniformNorm), 27.0);
+    /// assert_eq!(v1.apply_metric_distance(&v2, &LpNorm(1)), 27.0 + 18.0 + 9.0);
+    /// assert_eq!(v1.apply_metric_distance(&v2, &EuclideanNorm), (v1 - v2).norm());
+    /// ```
+    #[inline]
+    pub fn apply_metric_distance<R2, C2, S2>(&self, rhs: &Matrix<N, R2, C2, S2>, norm: &impl Norm<N>) -> N
+        where R2: Dim, C2: Dim, S2: Storage<N, R2, C2>,
+              ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2> {
+        norm.metric_distance(self,rhs)
+    }
+
+    /// The Lp norm of this matrix.
+    #[inline]
+    pub fn lp_norm(&self, p: i32) -> N {
+        self.apply_norm(&LpNorm(p))
+    }
+
+    /// A synonym for the norm of this matrix.
+    ///
+    /// Aka the length.
+    ///
+    /// This function is simply implemented as a call to `norm()`
+    #[inline]
+    pub fn magnitude(&self) -> N {
+        self.norm()
+    }
+
+    /// A synonym for the squared norm of this matrix.
+    ///
+    /// Aka the squared length.
+    ///
+    /// This function is simply implemented as a call to `norm_squared()`
+    #[inline]
+    pub fn magnitude_squared(&self) -> N {
+        self.norm_squared()
+    }
+
+    /// Returns a normalized version of this matrix.
+    #[inline]
+    pub fn normalize(&self) -> MatrixMN<N, R, C>
+        where DefaultAllocator: Allocator<N, R, C> {
+        self / self.norm()
+    }
+
+    /// Returns a normalized version of this matrix unless its norm as smaller or equal to `eps`.
+    #[inline]
+    pub fn try_normalize(&self, min_norm: N) -> Option<MatrixMN<N, R, C>>
+        where DefaultAllocator: Allocator<N, R, C> {
+        let n = self.norm();
+
+        if n <= min_norm {
+            None
+        } else {
+            Some(self / n)
+        }
+    }
+}
+
+impl<N: Real, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
+    /// Normalizes this matrix in-place and returns its norm.
+    #[inline]
+    pub fn normalize_mut(&mut self) -> N {
+        let n = self.norm();
+        *self /= n;
+
+        n
+    }
+
+    /// Normalizes this matrix in-place or does nothing if its norm is smaller or equal to `eps`.
+    ///
+    /// If the normalization succeeded, returns the old normal of this matrix.
+    #[inline]
+    pub fn try_normalize_mut(&mut self, min_norm: N) -> Option<N> {
+        let n = self.norm();
+
+        if n <= min_norm {
+            None
+        } else {
+            *self /= n;
+            Some(n)
+        }
+    }
+}

src/base/ops.rs

@@ -45,7 +45,7 @@ where
             "Matrix index out of bounds."
         );
 
-        unsafe { self.get_unchecked(ij.0, ij.1) }
+        unsafe { self.get_unchecked((ij.0, ij.1)) }
     }
 }
 
@@ -71,7 +71,7 @@ where
             "Matrix index out of bounds."
         );
 
-        unsafe { self.get_unchecked_mut(ij.0, ij.1) }
+        unsafe { self.get_unchecked_mut((ij.0, ij.1)) }
     }
 }
 
@@ -172,8 +172,8 @@ macro_rules! componentwise_binop_impl(
                     for j in 0 .. self.ncols() {
                         for i in 0 .. self.nrows() {
                             unsafe {
-                                let val = self.get_unchecked(i, j).$method(*rhs.get_unchecked(i, j));
+                                let val = self.get_unchecked((i, j)).$method(*rhs.get_unchecked((i, j)));
-                                *out.get_unchecked_mut(i, j) = val;
+                                *out.get_unchecked_mut((i, j)) = val;
                             }
                         }
                     }
@@ -204,7 +204,7 @@ macro_rules! componentwise_binop_impl(
                     for j in 0 .. rhs.ncols() {
                         for i in 0 .. rhs.nrows() {
                             unsafe {
-                                self.get_unchecked_mut(i, j).$method_assign(*rhs.get_unchecked(i, j))
+                                self.get_unchecked_mut((i, j)).$method_assign(*rhs.get_unchecked((i, j)))
                             }
                         }
                     }
@@ -235,8 +235,8 @@ macro_rules! componentwise_binop_impl(
                     for j in 0 .. self.ncols() {
                         for i in 0 .. self.nrows() {
                             unsafe {
-                                let r = rhs.get_unchecked_mut(i, j);
+                                let r = rhs.get_unchecked_mut((i, j));
-                                *r = self.get_unchecked(i, j).$method(*r)
+                                *r = self.get_unchecked((i, j)).$method(*r)
                             }
                         }
                     }
@@ -448,7 +448,7 @@ macro_rules! componentwise_scalarop_impl(
             fn $method_assign(&mut self, rhs: N) {
                 for j in 0 .. self.ncols() {
                     for i in 0 .. self.nrows() {
-                        unsafe { self.get_unchecked_mut(i, j).$method_assign(rhs) };
+                        unsafe { self.get_unchecked_mut((i, j)).$method_assign(rhs) };
                     }
                 }
             }
@@ -657,7 +657,7 @@ where
         for i in 0..ncols1 {
             for j in 0..ncols2 {
                 let dot = self.column(i).dot(&rhs.column(j));
-                unsafe { *out.get_unchecked_mut(i, j) = dot };
+                unsafe { *out.get_unchecked_mut((i, j)) = dot };
             }
         }
     }
@@ -704,10 +704,10 @@ where
                 for j2 in 0..ncols2.value() {
                     for i1 in 0..nrows1.value() {
                         unsafe {
-                            let coeff = *self.get_unchecked(i1, j1);
+                            let coeff = *self.get_unchecked((i1, j1));
 
                             for i2 in 0..nrows2.value() {
-                                *data_res = coeff * *rhs.get_unchecked(i2, j2);
+                                *data_res = coeff * *rhs.get_unchecked((i2, j2));
                                 data_res = data_res.offset(1);
                             }
                         }
@@ -761,7 +761,7 @@ where
 }
 
 impl<N: Scalar + PartialOrd + Signed, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
-    /// Returns the absolute value of the coefficient with the largest absolute value.
+    /// Returns the absolute value of the component with the largest absolute value.
     #[inline]
     pub fn amax(&self) -> N {
         let mut max = N::zero();
@@ -777,7 +777,7 @@ impl<N: Scalar + PartialOrd + Signed, R: Dim, C: Dim, S: Storage<N, R, C>> Matri
         max
     }
 
-    /// Returns the absolute value of the coefficient with the smallest absolute value.
+    /// Returns the absolute value of the component with the smallest absolute value.
     #[inline]
     pub fn amin(&self) -> N {
         let mut it = self.iter();
@@ -796,4 +796,42 @@ impl<N: Scalar + PartialOrd + Signed, R: Dim, C: Dim, S: Storage<N, R, C>> Matri
 
         min
     }
+
+    /// Returns the component with the largest value.
+    #[inline]
+    pub fn max(&self) -> N {
+        let mut it = self.iter();
+        let mut max = it
+            .next()
+            .expect("max: empty matrices not supported.");
+
+        for e in it {
+            let ae = e;
+
+            if ae > max {
+                max = ae;
+            }
+        }
+
+        *max
+    }
+
+    /// Returns the component with the smallest value.
+    #[inline]
+    pub fn min(&self) -> N {
+        let mut it = self.iter();
+        let mut min = it
+            .next()
+            .expect("min: empty matrices not supported.");
+
+        for e in it {
+            let ae = e;
+
+            if ae < min {
+                min = ae;
+            }
+        }
+
+        *min
+    }
 }

src/base/statistics.rs

@@ -0,0 +1,309 @@
+use ::{Real, Dim, Matrix, VectorN, RowVectorN, DefaultAllocator, U1, VectorSliceN};
+use storage::Storage;
+use allocator::Allocator;
+
+impl<N: Real, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, 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>
+        where DefaultAllocator: Allocator<N, U1, C> {
+
+        let ncols = self.data.shape().1;
+        let mut res = unsafe { RowVectorN::new_uninitialized_generic(U1, ncols) };
+
+        for i in 0..ncols.value() {
+            // FIXME: avoid bound checking of column.
+            unsafe { *res.get_unchecked_mut((0, i)) = f(self.column(i)); }
+        }
+
+        res
+    }
+
+    /// Returns a column vector where each element is the result of the application of `f` on the
+    /// corresponding column of the original matrix.
+    ///
+    /// This is the same as `self.compress_rows(f).transpose()`.
+    #[inline]
+    pub fn compress_rows_tr(&self, f: impl Fn(VectorSliceN<N, R, S::RStride, S::CStride>) -> N) -> VectorN<N, C>
+        where DefaultAllocator: Allocator<N, C> {
+
+        let ncols = self.data.shape().1;
+        let mut res = unsafe { VectorN::new_uninitialized_generic(ncols, U1) };
+
+        for i in 0..ncols.value() {
+            // FIXME: avoid bound checking of column.
+            unsafe { *res.vget_unchecked_mut(i) = f(self.column(i)); }
+        }
+
+        res
+    }
+
+    /// Returns a column vector resulting from the folding of `f` on each column of this matrix.
+    #[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>
+        where DefaultAllocator: Allocator<N, R> {
+        let mut res = init;
+
+        for i in 0..self.ncols() {
+            f(&mut res, self.column(i))
+        }
+
+        res
+    }
+}
+
+impl<N: Real, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
+    /*
+     *
+     * Sum computation.
+     *
+     */
+    /// The sum of all the elements of this matrix.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use nalgebra::Matrix2x3;
+    ///
+    /// let m = Matrix2x3::new(1.0, 2.0, 3.0,
+    ///                        4.0, 5.0, 6.0);
+    /// assert_eq!(m.sum(), 21.0);
+    /// ```
+    #[inline]
+    pub fn sum(&self) -> N {
+        self.iter().cloned().fold(N::zero(), |a, b| a + b)
+    }
+
+    /// The sum of all the rows of this matrix.
+    ///
+    /// Use `.row_variance_tr` if you need the result in a column vector instead.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use nalgebra::{Matrix2x3, RowVector3};
+    ///
+    /// let m = Matrix2x3::new(1.0, 2.0, 3.0,
+    ///                        4.0, 5.0, 6.0);
+    /// assert_eq!(m.row_sum(), RowVector3::new(5.0, 7.0, 9.0));
+    /// ```
+    #[inline]
+    pub fn row_sum(&self) -> RowVectorN<N, C>
+        where DefaultAllocator: Allocator<N, U1, C> {
+        self.compress_rows(|col| col.sum())
+    }
+
+    /// The sum of all the rows of this matrix. The result is transposed and returned as a column vector.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use nalgebra::{Matrix2x3, Vector3};
+    ///
+    /// let m = Matrix2x3::new(1.0, 2.0, 3.0,
+    ///                        4.0, 5.0, 6.0);
+    /// assert_eq!(m.row_sum_tr(), Vector3::new(5.0, 7.0, 9.0));
+    /// ```
+    #[inline]
+    pub fn row_sum_tr(&self) -> VectorN<N, C>
+        where DefaultAllocator: Allocator<N, C> {
+        self.compress_rows_tr(|col| col.sum())
+    }
+
+    /// The sum of all the columns of this matrix.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use nalgebra::{Matrix2x3, Vector2};
+    ///
+    /// let m = Matrix2x3::new(1.0, 2.0, 3.0,
+    ///                        4.0, 5.0, 6.0);
+    /// assert_eq!(m.column_sum(), Vector2::new(6.0, 15.0));
+    /// ```
+    #[inline]
+    pub fn column_sum(&self) -> VectorN<N, R>
+        where DefaultAllocator: Allocator<N, R> {
+        let nrows = self.data.shape().0;
+        self.compress_columns(VectorN::zeros_generic(nrows, U1), |out, col| {
+            out.axpy(N::one(), &col, N::one())
+        })
+    }
+
+    /*
+     *
+     * Variance computation.
+     *
+     */
+    /// The variance of all the elements of this matrix.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # #[macro_use] extern crate approx;
+    /// # use nalgebra::Matrix2x3;
+    ///
+    /// let m = Matrix2x3::new(1.0, 2.0, 3.0,
+    ///                        4.0, 5.0, 6.0);
+    /// assert_relative_eq!(m.variance(), 35.0 / 12.0, epsilon = 1.0e-8);
+    /// ```
+    #[inline]
+    pub fn variance(&self) -> N {
+        if self.len() == 0 {
+            N::zero()
+        } else {
+            let val = self.iter().cloned().fold((N::zero(), N::zero()), |a, b| (a.0 + b * b, a.1 + b));
+            let denom = N::one() / ::convert::<_, N>(self.len() as f64);
+            val.0 * denom - (val.1 * denom) * (val.1 * denom)
+        }
+    }
+
+    /// The variance of all the rows of this matrix.
+    ///
+    /// Use `.row_variance_tr` if you need the result in a column vector instead.
+    /// # Example
+    ///
+    /// ```
+    /// # use nalgebra::{Matrix2x3, RowVector3};
+    ///
+    /// let m = Matrix2x3::new(1.0, 2.0, 3.0,
+    ///                        4.0, 5.0, 6.0);
+    /// assert_eq!(m.row_variance(), RowVector3::new(2.25, 2.25, 2.25));
+    /// ```
+    #[inline]
+    pub fn row_variance(&self) -> RowVectorN<N, C>
+        where DefaultAllocator: Allocator<N, U1, C> {
+        self.compress_rows(|col| col.variance())
+    }
+
+    /// The variance of all the rows of this matrix. The result is transposed and returned as a column vector.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use nalgebra::{Matrix2x3, Vector3};
+    ///
+    /// let m = Matrix2x3::new(1.0, 2.0, 3.0,
+    ///                        4.0, 5.0, 6.0);
+    /// assert_eq!(m.row_variance_tr(), Vector3::new(2.25, 2.25, 2.25));
+    /// ```
+    #[inline]
+    pub fn row_variance_tr(&self) -> VectorN<N, C>
+        where DefaultAllocator: Allocator<N, C> {
+        self.compress_rows_tr(|col| col.variance())
+    }
+
+    /// The variance of all the columns of this matrix.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # #[macro_use] extern crate approx;
+    /// # use nalgebra::{Matrix2x3, Vector2};
+    ///
+    /// let m = Matrix2x3::new(1.0, 2.0, 3.0,
+    ///                        4.0, 5.0, 6.0);
+    /// 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>
+        where DefaultAllocator: Allocator<N, R> {
+        let (nrows, ncols) = self.data.shape();
+
+        let mut mean = self.column_mean();
+        mean.apply(|e| -(e * e));
+
+        let denom = N::one() / ::convert::<_, N>(ncols.value() as f64);
+        self.compress_columns(mean, |out, col| {
+            for i in 0..nrows.value() {
+                unsafe {
+                    let val = col.vget_unchecked(i);
+                    *out.vget_unchecked_mut(i) += denom * *val * *val
+                }
+            }
+        })
+    }
+
+    /*
+     *
+     * Mean computation.
+     *
+     */
+    /// The mean of all the elements of this matrix.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use nalgebra::Matrix2x3;
+    ///
+    /// let m = Matrix2x3::new(1.0, 2.0, 3.0,
+    ///                        4.0, 5.0, 6.0);
+    /// assert_eq!(m.mean(), 3.5);
+    /// ```
+    #[inline]
+    pub fn mean(&self) -> N {
+        if self.len() == 0 {
+            N::zero()
+        } else {
+            self.sum() / ::convert(self.len() as f64)
+        }
+    }
+
+    /// The mean of all the rows of this matrix.
+    ///
+    /// Use `.row_mean_tr` if you need the result in a column vector instead.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use nalgebra::{Matrix2x3, RowVector3};
+    ///
+    /// let m = Matrix2x3::new(1.0, 2.0, 3.0,
+    ///                        4.0, 5.0, 6.0);
+    /// assert_eq!(m.row_mean(), RowVector3::new(2.5, 3.5, 4.5));
+    /// ```
+    #[inline]
+    pub fn row_mean(&self) -> RowVectorN<N, C>
+        where DefaultAllocator: Allocator<N, U1, C> {
+        self.compress_rows(|col| col.mean())
+    }
+
+    /// The mean of all the rows of this matrix. The result is transposed and returned as a column vector.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use nalgebra::{Matrix2x3, Vector3};
+    ///
+    /// let m = Matrix2x3::new(1.0, 2.0, 3.0,
+    ///                        4.0, 5.0, 6.0);
+    /// assert_eq!(m.row_mean_tr(), Vector3::new(2.5, 3.5, 4.5));
+    /// ```
+    #[inline]
+    pub fn row_mean_tr(&self) -> VectorN<N, C>
+        where DefaultAllocator: Allocator<N, C> {
+        self.compress_rows_tr(|col| col.mean())
+    }
+
+    /// The mean of all the columns of this matrix.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use nalgebra::{Matrix2x3, Vector2};
+    ///
+    /// let m = Matrix2x3::new(1.0, 2.0, 3.0,
+    ///                        4.0, 5.0, 6.0);
+    /// assert_eq!(m.column_mean(), Vector2::new(2.0, 5.0));
+    /// ```
+    #[inline]
+    pub fn column_mean(&self) -> VectorN<N, R>
+        where DefaultAllocator: Allocator<N, R> {
+        let (nrows, ncols) = self.data.shape();
+        let denom = N::one() / ::convert::<_, N>(ncols.value() as f64);
+        self.compress_columns(VectorN::zeros_generic(nrows, U1), |out, col| {
+            out.axpy(denom, &col, N::one())
+        })
+    }
+}

src/base/storage.rs

@@ -34,7 +34,7 @@ pub type CStride<N, R, C = U1> =
 /// Note that `Self` must always have a number of elements compatible with the matrix length (given
 /// by `R` and `C` if they are known at compile-time). For example, implementors of this trait
 /// should **not** allow the user to modify the size of the underlying buffer with safe methods
-/// (for example the `MatrixVec::data_mut` method is unsafe because the user could change the
+/// (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 {
     /// The static stride of this storage's rows.

src/base/swizzle.rs

@@ -3,64 +3,60 @@ use storage::Storage;
 use typenum::{self, Cmp, Greater};
 
 macro_rules! impl_swizzle {
-    ($(where $BaseDim: ident: $name: ident() -> $Result: ident[$($i: expr),*]);*) => {
+    ($( where $BaseDim: ident: $( $name: ident() -> $Result: ident[$($i: expr),+] ),+ ;)* ) => {
         $(
-            impl<N: Scalar, D: DimName, S: Storage<N, D>> Vector<N, D, S> {
+            impl<N: Scalar, D: DimName, S: Storage<N, D>> Vector<N, D, S>
-                /// Builds a new vector from components of `self`.
+            where D::Value: Cmp<typenum::$BaseDim, Output=Greater>
-                #[inline]
+            {
-                pub fn $name(&self) -> $Result<N>
+                $(
-                    where D::Value: Cmp<typenum::$BaseDim, Output=Greater> {
+                    /// Builds a new vector from components of `self`.
-                    $Result::new($(self[$i]),*)
+                    #[inline]
-                }
+                    pub fn $name(&self) -> $Result<N> {
+                        $Result::new($(self[$i]),*)
+                    }
+                )*
             }
         )*
     }
 }
 
 impl_swizzle!(
-    where U0: xx() -> Vector2[0, 0];
+    where U0: xx()  -> Vector2[0, 0],
-    where U1: xy() -> Vector2[0, 1];
+              xxx() -> Vector3[0, 0, 0];
-    where U2: xz() -> Vector2[0, 2];
-    where U1: yx() -> Vector2[1, 0];
-    where U1: yy() -> Vector2[1, 1];
-    where U1: yz() -> Vector2[1, 2];
-    where U2: zx() -> Vector2[2, 0];
-    where U2: zy() -> Vector2[2, 1];
-    where U2: zz() -> Vector2[2, 2];
 
-    where U0: xxx() -> Vector3[0, 0, 0];
+    where U1: xy()  -> Vector2[0, 1],
-    where U1: xxy() -> Vector3[0, 0, 1];
+              yx()  -> Vector2[1, 0],
-    where U2: xxz() -> Vector3[0, 0, 2];
+              yy()  -> Vector2[1, 1],
+              xxy() -> Vector3[0, 0, 1],
+              xyx() -> Vector3[0, 1, 0],
+              xyy() -> Vector3[0, 1, 1],
+              yxx() -> Vector3[1, 0, 0],
+              yxy() -> Vector3[1, 0, 1],
+              yyx() -> Vector3[1, 1, 0],
+              yyy() -> Vector3[1, 1, 1];
 
-    where U1: xyx() -> Vector3[0, 1, 0];
+    where U2: xz()  -> Vector2[0, 2],
-    where U1: xyy() -> Vector3[0, 1, 1];
+              yz()  -> Vector2[1, 2],
-    where U2: xyz() -> Vector3[0, 1, 2];
+              zx()  -> Vector2[2, 0],
-
+              zy()  -> Vector2[2, 1],
-    where U2: xzx() -> Vector3[0, 2, 0];
+              zz()  -> Vector2[2, 2],
-    where U2: xzy() -> Vector3[0, 2, 1];
+              xxz() -> Vector3[0, 0, 2],
-    where U2: xzz() -> Vector3[0, 2, 2];
+              xyz() -> Vector3[0, 1, 2],
-
+              xzx() -> Vector3[0, 2, 0],
-    where U1: yxx() -> Vector3[1, 0, 0];
+              xzy() -> Vector3[0, 2, 1],
-    where U1: yxy() -> Vector3[1, 0, 1];
+              xzz() -> Vector3[0, 2, 2],
-    where U2: yxz() -> Vector3[1, 0, 2];
+              yxz() -> Vector3[1, 0, 2],
-
+              yyz() -> Vector3[1, 1, 2],
-    where U1: yyx() -> Vector3[1, 1, 0];
+              yzx() -> Vector3[1, 2, 0],
-    where U1: yyy() -> Vector3[1, 1, 1];
+              yzy() -> Vector3[1, 2, 1],
-    where U2: yyz() -> Vector3[1, 1, 2];
+              yzz() -> Vector3[1, 2, 2],
-
+              zxx() -> Vector3[2, 0, 0],
-    where U2: yzx() -> Vector3[1, 2, 0];
+              zxy() -> Vector3[2, 0, 1],
-    where U2: yzy() -> Vector3[1, 2, 1];
+              zxz() -> Vector3[2, 0, 2],
-    where U2: yzz() -> Vector3[1, 2, 2];
+              zyx() -> Vector3[2, 1, 0],
-
+              zyy() -> Vector3[2, 1, 1],
-    where U2: zxx() -> Vector3[2, 0, 0];
+              zyz() -> Vector3[2, 1, 2],
-    where U2: zxy() -> Vector3[2, 0, 1];
+              zzx() -> Vector3[2, 2, 0],
-    where U2: zxz() -> Vector3[2, 0, 2];
+              zzy() -> Vector3[2, 2, 1],
-
+              zzz() -> Vector3[2, 2, 2];
-    where U2: zyx() -> Vector3[2, 1, 0];
-    where U2: zyy() -> Vector3[2, 1, 1];
-    where U2: zyz() -> Vector3[2, 1, 2];
-
-    where U2: zzx() -> Vector3[2, 2, 0];
-    where U2: zzy() -> Vector3[2, 2, 1];
-    where U2: zzz() -> Vector3[2, 2, 2]
 );

src/base/unit.rs

@@ -15,7 +15,7 @@ use alga::linear::NormedSpace;
 
 /// A wrapper that ensures the underlying algebraic entity has a unit norm.
 ///
-/// Use `.as_ref()` or `.unwrap()` to obtain the underlying value by-reference or by-move.
+/// Use `.as_ref()` or `.into_inner()` to obtain the underlying value by-reference or by-move.
 #[repr(transparent)]
 #[derive(Eq, PartialEq, Clone, Hash, Debug, Copy)]
 pub struct Unit<T> {
@@ -113,6 +113,14 @@ impl<T> Unit<T> {
 
     /// Retrieves the underlying value.
     #[inline]
+    pub fn into_inner(self) -> T {
+        self.value
+    }
+
+    /// Retrieves the underlying value.
+    /// Deprecated: use [Unit::into_inner] instead.
+    #[deprecated(note="use `.into_inner()` instead")]
+    #[inline]
     pub fn unwrap(self) -> T {
         self.value
     }
@@ -143,7 +151,7 @@ where T::Field: RelativeEq
 {
     #[inline]
     fn to_superset(&self) -> T {
-        self.clone().unwrap()
+        self.clone().into_inner()
     }
 
     #[inline]

src/base/vec_storage.rs

@@ -1,6 +1,5 @@
 #[cfg(feature = "abomonation-serialize")]
 use std::io::{Result as IOResult, Write};
-use std::ops::Deref;
 
 #[cfg(all(feature = "alloc", not(feature = "std")))]
 use alloc::vec::Vec;
@@ -24,21 +23,25 @@ use abomonation::Abomonation;
 #[repr(C)]
 #[derive(Eq, Debug, Clone, PartialEq)]
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
-pub struct MatrixVec<N, R: Dim, C: Dim> {
+pub struct VecStorage<N, R: Dim, C: Dim> {
     data: Vec<N>,
     nrows: R,
     ncols: C,
 }
 
-impl<N, R: Dim, C: Dim> MatrixVec<N, R, C> {
+#[deprecated(note="renamed to `VecStorage`")]
+/// Renamed to [VecStorage].
+pub type MatrixVec<N, R, C> = VecStorage<N, R, C>;
+
+impl<N, R: Dim, C: Dim> VecStorage<N, 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>) -> MatrixVec<N, R, C> {
+    pub fn new(nrows: R, ncols: C, data: Vec<N>) -> VecStorage<N, R, C> {
         assert!(
             nrows.value() * ncols.value() == data.len(),
             "Data storage buffer dimension mismatch."
         );
-        MatrixVec {
+        VecStorage {
             data: data,
             nrows: nrows,
             ncols: ncols,
@@ -47,15 +50,16 @@ impl<N, R: Dim, C: Dim> MatrixVec<N, R, C> {
 
     /// The underlying data storage.
     #[inline]
-    pub fn data(&self) -> &Vec<N> {
+    pub fn as_vec(&self) -> &Vec<N> {
         &self.data
     }
 
     /// The underlying mutable data storage.
     ///
-    /// This is unsafe because this may cause UB if the vector is modified by the user.
+    /// This is unsafe because this may cause UB if the size of the vector is changed
+    /// by the user.
     #[inline]
-    pub unsafe fn data_mut(&mut self) -> &mut Vec<N> {
+    pub unsafe fn as_vec_mut(&mut self) -> &mut Vec<N> {
         &mut self.data
     }
 
@@ -77,14 +81,18 @@ impl<N, R: Dim, C: Dim> MatrixVec<N, R, C> {
 
         self.data
     }
+
+    /// The number of elements on the underlying vector.
+    #[inline]
+    pub fn len(&self) -> usize {
+        self.data.len()
+    }
 }
 
-impl<N, R: Dim, C: Dim> Deref for MatrixVec<N, R, C> {
+impl<N, R: Dim, C: Dim> Into<Vec<N>> for VecStorage<N, R, C>
-    type Target = Vec<N>;
+{
-
+    fn into(self) -> Vec<N> {
-    #[inline]
+        self.data
-    fn deref(&self) -> &Self::Target {
-        &self.data
     }
 }
 
@@ -94,7 +102,7 @@ impl<N, R: Dim, C: Dim> Deref for MatrixVec<N, R, C> {
  * Dynamic − Dynamic
  *
  */
-unsafe impl<N: Scalar, C: Dim> Storage<N, Dynamic, C> for MatrixVec<N, Dynamic, C>
+unsafe impl<N: Scalar, C: Dim> Storage<N, Dynamic, C> for VecStorage<N, Dynamic, C>
 where DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>
 {
     type RStride = U1;
@@ -134,11 +142,11 @@ where DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>
 
     #[inline]
     fn as_slice(&self) -> &[N] {
-        &self[..]
+        &self.data
     }
 }
 
-unsafe impl<N: Scalar, R: DimName> Storage<N, R, Dynamic> for MatrixVec<N, R, Dynamic>
+unsafe impl<N: Scalar, R: DimName> Storage<N, R, Dynamic> for VecStorage<N, R, Dynamic>
 where DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>
 {
     type RStride = U1;
@@ -178,7 +186,7 @@ where DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>
 
     #[inline]
     fn as_slice(&self) -> &[N] {
-        &self[..]
+        &self.data
     }
 }
 
@@ -187,7 +195,7 @@ where DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>
  * StorageMut, ContiguousStorage.
  *
  */
-unsafe impl<N: Scalar, C: Dim> StorageMut<N, Dynamic, C> for MatrixVec<N, Dynamic, C>
+unsafe impl<N: Scalar, C: Dim> StorageMut<N, Dynamic, C> for VecStorage<N, Dynamic, C>
 where DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>
 {
     #[inline]
@@ -201,13 +209,13 @@ where DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>
     }
 }
 
-unsafe impl<N: Scalar, C: Dim> ContiguousStorage<N, Dynamic, C> for MatrixVec<N, Dynamic, C> where DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>
+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<N: Scalar, C: Dim> ContiguousStorageMut<N, Dynamic, C> for MatrixVec<N, Dynamic, C> where DefaultAllocator: Allocator<N, 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<N: Scalar, R: DimName> StorageMut<N, R, Dynamic> for MatrixVec<N, R, Dynamic>
+unsafe impl<N: Scalar, R: DimName> StorageMut<N, R, Dynamic> for VecStorage<N, R, Dynamic>
 where DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>
 {
     #[inline]
@@ -222,7 +230,7 @@ where DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>
 }
 
 #[cfg(feature = "abomonation-serialize")]
-impl<N: Abomonation, R: Dim, C: Dim> Abomonation for MatrixVec<N, R, C> {
+impl<N: Abomonation, R: Dim, C: Dim> Abomonation for VecStorage<N, R, C> {
     unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
         self.data.entomb(writer)
     }
@@ -236,21 +244,21 @@ impl<N: Abomonation, R: Dim, C: Dim> Abomonation for MatrixVec<N, R, C> {
     }
 }
 
-unsafe impl<N: Scalar, R: DimName> ContiguousStorage<N, R, Dynamic> for MatrixVec<N, R, Dynamic> where DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>
+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<N: Scalar, R: DimName> ContiguousStorageMut<N, R, Dynamic> for MatrixVec<N, R, Dynamic> where DefaultAllocator: Allocator<N, 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>
 {}
 
-impl<N, R: Dim> Extend<N> for MatrixVec<N, R, Dynamic>
+impl<N, R: Dim> Extend<N> for VecStorage<N, R, Dynamic>
 {
-    /// Extends the number of columns of the `MatrixVec` with elements
+    /// Extends the number of columns of the `VecStorage` with elements
     /// from the given iterator.
     ///
     /// # Panics
     /// This function panics if the number of elements yielded by the
     /// given iterator is not a multiple of the number of rows of the
-    /// `MatrixVec`.
+    /// `VecStorage`.
     fn extend<I: IntoIterator<Item=N>>(&mut self, iter: I)
     {
         self.data.extend(iter);
@@ -260,7 +268,7 @@ impl<N, R: Dim> Extend<N> for MatrixVec<N, R, Dynamic>
     }
 }
 
-impl<N, R, RV, SV> Extend<Vector<N, RV, SV>> for MatrixVec<N, R, Dynamic>
+impl<N, R, RV, SV> Extend<Vector<N, RV, SV>> for VecStorage<N, R, Dynamic>
 where
     N: Scalar,
     R: Dim,
@@ -268,13 +276,13 @@ where
     SV: Storage<N, RV>,
     ShapeConstraint: SameNumberOfRows<R, RV>,
 {
-    /// Extends the number of columns of the `MatrixVec` with vectors
+    /// Extends the number of columns of the `VecStorage` with vectors
     /// from the given iterator.
     ///
     /// # Panics
     /// 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 `MatrixVec`.
+    /// of this `VecStorage`.
     fn extend<I: IntoIterator<Item=Vector<N, RV, SV>>>(&mut self, iter: I)
     {
         let nrows = self.nrows.value();
@@ -289,9 +297,9 @@ where
     }
 }
 
-impl<N> Extend<N> for MatrixVec<N, Dynamic, U1>
+impl<N> Extend<N> for VecStorage<N, Dynamic, U1>
 {
-    /// Extends the number of rows of the `MatrixVec` with elements
+    /// Extends the number of rows of the `VecStorage` with elements
     /// from the given iterator.
     fn extend<I: IntoIterator<Item=N>>(&mut self, iter: I)
     {

src/debug/random_orthogonal.rs

@@ -48,6 +48,7 @@ where
     Owned<N, D, D>: Clone + Send,
 {
     fn arbitrary<G: Gen>(g: &mut G) -> Self {
+        use rand::Rng;
         let dim = D::try_to_usize().unwrap_or(g.gen_range(1, 50));
         Self::new(D::from_usize(dim), || N::arbitrary(g))
     }

src/debug/random_sdp.rs

@@ -49,6 +49,7 @@ where
     Owned<N, D, D>: Clone + Send,
 {
     fn arbitrary<G: Gen>(g: &mut G) -> Self {
+        use rand::Rng;
         let dim = D::try_to_usize().unwrap_or(g.gen_range(1, 50));
         Self::new(D::from_usize(dim), || N::arbitrary(g))
     }

src/geometry/isometry.rs

@@ -113,7 +113,6 @@ where DefaultAllocator: Allocator<N, D>
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Isometry3, Translation3, UnitQuaternion, Vector3, Point3};
     /// let tra = Translation3::new(0.0, 0.0, 3.0);
@@ -167,7 +166,7 @@ where DefaultAllocator: Allocator<N, D>
     /// ```
     #[inline]
     pub fn inverse_mut(&mut self) {
-        self.rotation.inverse_mut();
+        self.rotation.two_sided_inverse_mut();
         self.translation.inverse_mut();
         self.translation.vector = self.rotation.transform_vector(&self.translation.vector);
     }
@@ -197,7 +196,6 @@ where DefaultAllocator: Allocator<N, D>
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Isometry2, Translation2, UnitComplex, Vector2};
     /// let mut iso = Isometry2::new(Vector2::new(1.0, 2.0), f32::consts::PI / 6.0);
@@ -220,7 +218,6 @@ where DefaultAllocator: Allocator<N, D>
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Isometry2, Translation2, UnitComplex, Vector2, Point2};
     /// let mut iso = Isometry2::new(Vector2::new(1.0, 2.0), f32::consts::FRAC_PI_2);
@@ -272,7 +269,6 @@ where DefaultAllocator: Allocator<N, D>
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Isometry2, Vector2, Matrix3};
     /// let iso = Isometry2::new(Vector2::new(10.0, 20.0), f32::consts::FRAC_PI_6);

src/geometry/isometry_alga.rs

@@ -1,6 +1,6 @@
 use alga::general::{
     AbstractGroup, AbstractLoop, AbstractMagma, AbstractMonoid, AbstractQuasigroup,
-    AbstractSemigroup, Id, Identity, Inverse, Multiplicative, Real,
+    AbstractSemigroup, Id, Identity, TwoSidedInverse, Multiplicative, Real,
 };
 use alga::linear::Isometry as AlgaIsometry;
 use alga::linear::{
@@ -30,18 +30,18 @@ where
     }
 }
 
-impl<N: Real, D: DimName, R> Inverse<Multiplicative> for Isometry<N, D, R>
+impl<N: Real, D: DimName, R> TwoSidedInverse<Multiplicative> for Isometry<N, D, R>
 where
     R: Rotation<Point<N, D>>,
     DefaultAllocator: Allocator<N, D>,
 {
     #[inline]
-    fn inverse(&self) -> Self {
+    fn two_sided_inverse(&self) -> Self {
         self.inverse()
     }
 
     #[inline]
-    fn inverse_mut(&mut self) {
+    fn two_sided_inverse_mut(&mut self) {
         self.inverse_mut()
     }
 }

src/geometry/isometry_construction.rs

@@ -16,7 +16,7 @@ use base::{DefaultAllocator, Vector2, Vector3};
 
 use geometry::{
     Isometry, Point, Point3, Rotation, Rotation2, Rotation3, Translation, UnitComplex,
-    UnitQuaternion,
+    UnitQuaternion, Translation2, Translation3
 };
 
 impl<N: Real, D: DimName, R: AlgaRotation<Point<N, D>>> Isometry<N, D, R>
@@ -49,7 +49,6 @@ where DefaultAllocator: Allocator<N, D>
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Isometry2, Point2, UnitComplex};
     /// let rot = UnitComplex::new(f32::consts::PI);
@@ -130,6 +129,18 @@ impl<N: Real> Isometry<N, U2, Rotation2<N>> {
             Rotation::<N, U2>::new(angle),
         )
     }
+
+    /// Creates a new isometry from the given translation coordinates.
+    #[inline]
+    pub fn translation(x: N, y: N) -> Self {
+        Self::new(Vector2::new(x, y), N::zero())
+    }
+
+    /// Creates a new isometry from the given rotation angle.
+    #[inline]
+    pub fn rotation(angle: N) -> Self {
+        Self::new(Vector2::zeros(), angle)
+    }
 }
 
 impl<N: Real> Isometry<N, U2, UnitComplex<N>> {
@@ -153,6 +164,18 @@ impl<N: Real> Isometry<N, U2, UnitComplex<N>> {
             UnitComplex::from_angle(angle),
         )
     }
+
+    /// Creates a new isometry from the given translation coordinates.
+    #[inline]
+    pub fn translation(x: N, y: N) -> Self {
+        Self::from_parts(Translation2::new(x, y), UnitComplex::identity())
+    }
+
+    /// Creates a new isometry from the given rotation angle.
+    #[inline]
+    pub fn rotation(angle: N) -> Self {
+        Self::new(Vector2::zeros(), angle)
+    }
 }
 
 // 3D rotation.
@@ -165,7 +188,6 @@ macro_rules! isometry_construction_impl(
             ///
             /// ```
             /// # #[macro_use] extern crate approx;
-            /// # extern crate nalgebra;
             /// # use std::f32;
             /// # use nalgebra::{Isometry3, IsometryMatrix3, Point3, Vector3};
             /// let axisangle = Vector3::y() * f32::consts::FRAC_PI_2;
@@ -191,6 +213,18 @@ macro_rules! isometry_construction_impl(
                     $RotId::<$($RotParams),*>::from_scaled_axis(axisangle))
             }
 
+            /// Creates a new isometry from the given translation coordinates.
+            #[inline]
+            pub fn translation(x: N, y: N, z: N) -> Self {
+                Self::from_parts(Translation3::new(x, y, z), $RotId::identity())
+            }
+
+            /// Creates a new isometry from the given rotation angle.
+            #[inline]
+            pub fn rotation(axisangle: Vector3<N>) -> Self {
+                Self::new(Vector3::zeros(), axisangle)
+            }
+
             /// Creates an isometry that corresponds to the local frame of an observer standing at the
             /// point `eye` and looking toward `target`.
             ///
@@ -206,7 +240,6 @@ macro_rules! isometry_construction_impl(
             ///
             /// ```
             /// # #[macro_use] extern crate approx;
-            /// # extern crate nalgebra;
             /// # use std::f32;
             /// # use nalgebra::{Isometry3, IsometryMatrix3, Point3, Vector3};
             /// let eye = Point3::new(1.0, 2.0, 3.0);
@@ -214,23 +247,32 @@ macro_rules! isometry_construction_impl(
             /// let up = Vector3::y();
             ///
             /// // Isometry with its rotation part represented as a UnitQuaternion
-            /// let iso = Isometry3::new_observer_frame(&eye, &target, &up);
+            /// let iso = Isometry3::face_towards(&eye, &target, &up);
             /// assert_eq!(iso * Point3::origin(), eye);
             /// assert_relative_eq!(iso * Vector3::z(), Vector3::x());
             ///
             /// // Isometry with its rotation part represented as Rotation3 (a 3x3 rotation matrix).
-            /// let iso = IsometryMatrix3::new_observer_frame(&eye, &target, &up);
+            /// let iso = IsometryMatrix3::face_towards(&eye, &target, &up);
             /// assert_eq!(iso * Point3::origin(), eye);
             /// assert_relative_eq!(iso * Vector3::z(), Vector3::x());
             /// ```
             #[inline]
-            pub fn new_observer_frame(eye:    &Point3<N>,
+            pub fn face_towards(eye:    &Point3<N>,
                                       target: &Point3<N>,
                                       up:     &Vector3<N>)
                                       -> Self {
                 Self::from_parts(
                     Translation::from(eye.coords.clone()),
-                    $RotId::new_observer_frame(&(target - eye), up))
+                    $RotId::face_towards(&(target - eye), up))
+            }
+
+            /// Deprecated: Use [Isometry::face_towards] instead.
+            #[deprecated(note="renamed to `face_towards`")]
+            pub fn new_observer_frame(eye:    &Point3<N>,
+                                      target: &Point3<N>,
+                                      up:     &Vector3<N>)
+                                      -> Self {
+                Self::face_towards(eye, target, up)
             }
 
             /// Builds a right-handed look-at view matrix.
@@ -249,7 +291,6 @@ macro_rules! isometry_construction_impl(
             ///
             /// ```
             /// # #[macro_use] extern crate approx;
-            /// # extern crate nalgebra;
             /// # use std::f32;
             /// # use nalgebra::{Isometry3, IsometryMatrix3, Point3, Vector3};
             /// let eye = Point3::new(1.0, 2.0, 3.0);
@@ -293,7 +334,6 @@ macro_rules! isometry_construction_impl(
             ///
             /// ```
             /// # #[macro_use] extern crate approx;
-            /// # extern crate nalgebra;
             /// # use std::f32;
             /// # use nalgebra::{Isometry3, IsometryMatrix3, Point3, Vector3};
             /// let eye = Point3::new(1.0, 2.0, 3.0);

src/geometry/isometry_ops.rs

@@ -200,8 +200,8 @@ isometry_binop_assign_impl_all!(
     DivAssign, div_assign;
     self: Isometry<N, D, R>, rhs: R;
     // FIXME: don't invert explicitly?
-    [val] => *self *= rhs.inverse();
+    [val] => *self *= rhs.two_sided_inverse();
-    [ref] => *self *= rhs.inverse();
+    [ref] => *self *= rhs.two_sided_inverse();
 );
 
 // Isometry × R

src/geometry/mod.rs

@@ -37,6 +37,7 @@ mod translation_alga;
 mod translation_alias;
 mod translation_construction;
 mod translation_conversion;
+mod translation_coordinates;
 mod translation_ops;
 
 mod isometry;
@@ -53,6 +54,8 @@ mod similarity_construction;
 mod similarity_conversion;
 mod similarity_ops;
 
+mod swizzle;
+
 mod transform;
 mod transform_alga;
 mod transform_alias;

src/geometry/orthographic.rs

@@ -69,7 +69,6 @@ impl<N: Real> Orthographic3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Orthographic3, Point3};
     /// let proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// // Check this projection actually transforms the view cuboid into the double-unit cube.
@@ -170,7 +169,6 @@ impl<N: Real> Orthographic3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Orthographic3, Point3, Matrix4};
     /// let proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// let inv = proj.inverse();
@@ -271,7 +269,6 @@ impl<N: Real> Orthographic3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Orthographic3, Point3, Matrix4};
     /// let proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// let expected = Matrix4::new(
@@ -280,9 +277,17 @@ impl<N: Real> Orthographic3<N> {
     ///     0.0,       0.0,       -2.0 / 999.9, -1000.1 / 999.9,
     ///     0.0,       0.0,        0.0,         1.0
     /// );
-    /// assert_eq!(proj.unwrap(), expected);
+    /// assert_eq!(proj.into_inner(), expected);
     /// ```
     #[inline]
+    pub fn into_inner(self) -> Matrix4<N> {
+        self.matrix
+    }
+
+    /// Retrieves the underlying homogeneous matrix.
+    /// Deprecated: Use [Orthographic3::into_inner] instead.
+    #[deprecated(note="use `.into_inner()` instead")]
+    #[inline]
     pub fn unwrap(self) -> Matrix4<N> {
         self.matrix
     }
@@ -291,7 +296,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// assert_relative_eq!(proj.left(), 1.0, epsilon = 1.0e-6);
@@ -308,7 +312,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// assert_relative_eq!(proj.right(), 10.0, epsilon = 1.0e-6);
@@ -325,7 +328,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// assert_relative_eq!(proj.bottom(), 2.0, epsilon = 1.0e-6);
@@ -342,7 +344,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// assert_relative_eq!(proj.top(), 20.0, epsilon = 1.0e-6);
@@ -359,7 +360,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// assert_relative_eq!(proj.znear(), 0.1, epsilon = 1.0e-6);
@@ -376,7 +376,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// assert_relative_eq!(proj.zfar(), 1000.0, epsilon = 1.0e-6);
@@ -395,7 +394,6 @@ impl<N: Real> Orthographic3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Orthographic3, Point3};
     /// let proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     ///
@@ -431,7 +429,6 @@ impl<N: Real> Orthographic3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Orthographic3, Point3};
     /// let proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     ///
@@ -470,7 +467,6 @@ impl<N: Real> Orthographic3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Orthographic3, Vector3};
     /// let proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     ///
@@ -496,7 +492,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let mut proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// proj.set_left(2.0);
@@ -516,7 +511,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let mut proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// proj.set_right(15.0);
@@ -536,7 +530,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let mut proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// proj.set_bottom(8.0);
@@ -556,7 +549,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let mut proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// proj.set_top(15.0);
@@ -576,7 +568,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let mut proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// proj.set_znear(8.0);
@@ -596,7 +587,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let mut proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// proj.set_zfar(15.0);
@@ -616,7 +606,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let mut proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// proj.set_left_and_right(7.0, 70.0);
@@ -642,7 +631,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let mut proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// proj.set_bottom_and_top(7.0, 70.0);
@@ -668,7 +656,6 @@ impl<N: Real> Orthographic3<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Orthographic3;
     /// let mut proj = Orthographic3::new(1.0, 10.0, 2.0, 20.0, 0.1, 1000.0);
     /// proj.set_znear_and_zfar(50.0, 5000.0);
@@ -725,6 +712,6 @@ where Matrix4<N>: Send
 impl<N: Real> From<Orthographic3<N>> for Matrix4<N> {
     #[inline]
     fn from(orth: Orthographic3<N>) -> Self {
-        orth.unwrap()
+        orth.into_inner()
     }
 }

src/geometry/perspective.rs

@@ -141,6 +141,14 @@ impl<N: Real> Perspective3<N> {
 
     /// Retrieves the underlying homogeneous matrix.
     #[inline]
+    pub fn into_inner(self) -> Matrix4<N> {
+        self.matrix
+    }
+
+    /// Retrieves the underlying homogeneous matrix.
+    /// Deprecated: Use [Perspective3::into_inner] instead.
+    #[deprecated(note="use `.into_inner()` instead")]
+    #[inline]
     pub fn unwrap(self) -> Matrix4<N> {
         self.matrix
     }
@@ -279,6 +287,6 @@ impl<N: Real + Arbitrary> Arbitrary for Perspective3<N> {
 impl<N: Real> From<Perspective3<N>> for Matrix4<N> {
     #[inline]
     fn from(orth: Perspective3<N>) -> Self {
-        orth.unwrap()
+        orth.into_inner()
     }
 }

src/geometry/quaternion.rs

@@ -114,7 +114,6 @@ impl<N: Real> Quaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Quaternion;
     /// let q = Quaternion::new(1.0, 2.0, 3.0, 4.0);
     /// let q_normalized = q.normalize();
@@ -150,7 +149,6 @@ impl<N: Real> Quaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Quaternion;
     /// let q = Quaternion::new(1.0, 2.0, 3.0, 4.0);
     /// let inv_q = q.try_inverse();
@@ -240,7 +238,6 @@ impl<N: Real> Quaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Quaternion;
     /// let q = Quaternion::new(1.0, 2.0, 3.0, 4.0);
     /// assert_relative_eq!(q.norm(), 5.47722557, epsilon = 1.0e-6);
@@ -258,7 +255,6 @@ impl<N: Real> Quaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Quaternion;
     /// let q = Quaternion::new(1.0, 2.0, 3.0, 4.0);
     /// assert_relative_eq!(q.magnitude(), 5.47722557, epsilon = 1.0e-6);
@@ -345,7 +341,6 @@ impl<N: Real> Quaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Quaternion;
     /// let q = Quaternion::new(2.0, 5.0, 0.0, 0.0);
     /// assert_relative_eq!(q.ln(), Quaternion::new(1.683647, 1.190289, 0.0, 0.0), epsilon = 1.0e-6)
@@ -364,7 +359,6 @@ impl<N: Real> Quaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Quaternion;
     /// let q = Quaternion::new(1.683647, 1.190289, 0.0, 0.0);
     /// assert_relative_eq!(q.exp(), Quaternion::new(2.0, 5.0, 0.0, 0.0), epsilon = 1.0e-5)
@@ -380,7 +374,6 @@ impl<N: Real> Quaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Quaternion;
     /// let q = Quaternion::new(1.683647, 1.190289, 0.0, 0.0);
     /// assert_relative_eq!(q.exp_eps(1.0e-6), Quaternion::new(2.0, 5.0, 0.0, 0.0), epsilon = 1.0e-5);
@@ -410,7 +403,6 @@ impl<N: Real> Quaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Quaternion;
     /// let q = Quaternion::new(1.0, 2.0, 3.0, 4.0);
     /// assert_relative_eq!(q.powf(1.5), Quaternion::new( -6.2576659, 4.1549037, 6.2323556, 8.3098075), epsilon = 1.0e-6);
@@ -476,7 +468,6 @@ impl<N: Real> Quaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Quaternion;
     /// let mut q = Quaternion::new(1.0, 2.0, 3.0, 4.0);
     ///
@@ -506,7 +497,6 @@ impl<N: Real> Quaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Quaternion;
     /// let mut q = Quaternion::new(1.0, 2.0, 3.0, 4.0);
     /// q.normalize_mut();
@@ -672,7 +662,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{UnitQuaternion, Vector3};
     /// let rot1 = UnitQuaternion::from_axis_angle(&Vector3::y_axis(), 1.0);
     /// let rot2 = UnitQuaternion::from_axis_angle(&Vector3::x_axis(), 0.1);
@@ -691,7 +680,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{UnitQuaternion, Vector3};
     /// let rot1 = UnitQuaternion::from_axis_angle(&Vector3::y_axis(), 1.0);
     /// let rot2 = UnitQuaternion::from_axis_angle(&Vector3::x_axis(), 0.1);
@@ -747,7 +735,7 @@ impl<N: Real> UnitQuaternion<N> {
         Unit::new_unchecked(Quaternion::from(
             Unit::new_unchecked(self.coords)
                 .slerp(&Unit::new_unchecked(other.coords), t)
-                .unwrap(),
+                .into_inner(),
         ))
     }
 
@@ -771,7 +759,7 @@ impl<N: Real> UnitQuaternion<N> {
     {
         Unit::new_unchecked(self.coords)
             .try_slerp(&Unit::new_unchecked(other.coords), t, epsilon)
-            .map(|q| Unit::new_unchecked(Quaternion::from(q.unwrap())))
+            .map(|q| Unit::new_unchecked(Quaternion::from(q.into_inner())))
     }
 
     /// Compute the conjugate of this unit quaternion in-place.
@@ -785,7 +773,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{UnitQuaternion, Vector3, Unit};
     /// let axisangle = Vector3::new(0.1, 0.2, 0.3);
     /// let mut rot = UnitQuaternion::new(axisangle);
@@ -828,7 +815,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{UnitQuaternion, Vector3, Unit};
     /// let axisangle = Vector3::new(0.1, 0.2, 0.3);
     /// let rot = UnitQuaternion::new(axisangle);
@@ -837,7 +823,7 @@ impl<N: Real> UnitQuaternion<N> {
     #[inline]
     pub fn scaled_axis(&self) -> Vector3<N> {
         if let Some(axis) = self.axis() {
-            axis.unwrap() * self.angle()
+            axis.into_inner() * self.angle()
         } else {
             Vector3::zero()
         }
@@ -885,7 +871,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Vector3, UnitQuaternion};
     /// let axisangle = Vector3::new(0.1, 0.2, 0.3);
     /// let q = UnitQuaternion::new(axisangle);
@@ -894,7 +879,7 @@ impl<N: Real> UnitQuaternion<N> {
     #[inline]
     pub fn ln(&self) -> Quaternion<N> {
         if let Some(v) = self.axis() {
-            Quaternion::from_parts(N::zero(), v.unwrap() * self.angle())
+            Quaternion::from_parts(N::zero(), v.into_inner() * self.angle())
         } else {
             Quaternion::zero()
         }
@@ -908,7 +893,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{UnitQuaternion, Vector3, Unit};
     /// let axis = Unit::new_normalize(Vector3::new(1.0, 2.0, 3.0));
     /// let angle = 1.2;
@@ -932,7 +916,6 @@ impl<N: Real> UnitQuaternion<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitQuaternion, Vector3, Matrix3};
     /// let q = UnitQuaternion::from_axis_angle(&Vector3::z_axis(), f32::consts::FRAC_PI_6);
@@ -990,7 +973,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::UnitQuaternion;
     /// let rot = UnitQuaternion::from_euler_angles(0.1, 0.2, 0.3);
     /// let euler = rot.euler_angles();
@@ -1009,7 +991,6 @@ impl<N: Real> UnitQuaternion<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitQuaternion, Vector3, Matrix4};
     /// let rot = UnitQuaternion::from_axis_angle(&Vector3::z_axis(), f32::consts::FRAC_PI_6);
@@ -1029,7 +1010,7 @@ impl<N: Real> UnitQuaternion<N> {
 impl<N: Real + fmt::Display> fmt::Display for UnitQuaternion<N> {
     fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
         if let Some(axis) = self.axis() {
-            let axis = axis.unwrap();
+            let axis = axis.into_inner();
             write!(
                 f,
                 "UnitQuaternion angle: {} − axis: ({}, {}, {})",

src/geometry/quaternion_alga.rs

@@ -2,7 +2,7 @@ use num::Zero;
 
 use alga::general::{
     AbstractGroup, AbstractGroupAbelian, AbstractLoop, AbstractMagma, AbstractModule,
-    AbstractMonoid, AbstractQuasigroup, AbstractSemigroup, Additive, Id, Identity, Inverse, Module,
+    AbstractMonoid, AbstractQuasigroup, AbstractSemigroup, Additive, Id, Identity, TwoSidedInverse, Module,
     Multiplicative, Real,
 };
 use alga::linear::{
@@ -42,9 +42,9 @@ impl<N: Real> AbstractMagma<Additive> for Quaternion<N> {
     }
 }
 
-impl<N: Real> Inverse<Additive> for Quaternion<N> {
+impl<N: Real> TwoSidedInverse<Additive> for Quaternion<N> {
     #[inline]
-    fn inverse(&self) -> Self {
+    fn two_sided_inverse(&self) -> Self {
         -self
     }
 }
@@ -173,14 +173,14 @@ impl<N: Real> AbstractMagma<Multiplicative> for UnitQuaternion<N> {
     }
 }
 
-impl<N: Real> Inverse<Multiplicative> for UnitQuaternion<N> {
+impl<N: Real> TwoSidedInverse<Multiplicative> for UnitQuaternion<N> {
     #[inline]
-    fn inverse(&self) -> Self {
+    fn two_sided_inverse(&self) -> Self {
         self.inverse()
     }
 
     #[inline]
-    fn inverse_mut(&mut self) {
+    fn two_sided_inverse_mut(&mut self) {
         self.inverse_mut()
     }
 }

src/geometry/quaternion_construction.rs

@@ -76,7 +76,7 @@ impl<N: Real> Quaternion<N> {
     where SB: Storage<N, U3> {
         let rot = UnitQuaternion::<N>::from_axis_angle(&axis, theta * ::convert(2.0f64));
 
-        rot.unwrap() * scale
+        rot.into_inner() * scale
     }
 
     /// The quaternion multiplicative identity.
@@ -166,7 +166,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitQuaternion, Point3, Vector3};
     /// let axis = Vector3::y_axis();
@@ -208,7 +207,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::UnitQuaternion;
     /// let rot = UnitQuaternion::from_euler_angles(0.1, 0.2, 0.3);
     /// let euler = rot.euler_angles();
@@ -237,7 +235,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Rotation3, UnitQuaternion, Vector3};
     /// let axis = Vector3::y_axis();
     /// let angle = 0.1;
@@ -302,7 +299,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Vector3, UnitQuaternion};
     /// let a = Vector3::new(1.0, 2.0, 3.0);
     /// let b = Vector3::new(3.0, 1.0, 2.0);
@@ -325,7 +321,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Vector3, UnitQuaternion};
     /// let a = Vector3::new(1.0, 2.0, 3.0);
     /// let b = Vector3::new(3.0, 1.0, 2.0);
@@ -361,7 +356,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Unit, Vector3, UnitQuaternion};
     /// let a = Unit::new_normalize(Vector3::new(1.0, 2.0, 3.0));
     /// let b = Unit::new_normalize(Vector3::new(3.0, 1.0, 2.0));
@@ -387,7 +381,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Unit, Vector3, UnitQuaternion};
     /// let a = Unit::new_normalize(Vector3::new(1.0, 2.0, 3.0));
     /// let b = Unit::new_normalize(Vector3::new(3.0, 1.0, 2.0));
@@ -446,22 +439,31 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitQuaternion, Vector3};
     /// let dir = Vector3::new(1.0, 2.0, 3.0);
     /// let up = Vector3::y();
     ///
-    /// let q = UnitQuaternion::new_observer_frame(&dir, &up);
+    /// let q = UnitQuaternion::face_towards(&dir, &up);
     /// assert_relative_eq!(q * Vector3::z(), dir.normalize());
     /// ```
     #[inline]
-    pub fn new_observer_frame<SB, SC>(dir: &Vector<N, U3, SB>, up: &Vector<N, U3, SC>) -> Self
+    pub fn face_towards<SB, SC>(dir: &Vector<N, U3, SB>, up: &Vector<N, U3, SC>) -> Self
     where
         SB: Storage<N, U3>,
         SC: Storage<N, U3>,
     {
-        Self::from_rotation_matrix(&Rotation::<N, U3>::new_observer_frame(dir, up))
+        Self::from_rotation_matrix(&Rotation::<N, U3>::face_towards(dir, up))
+    }
+
+    /// Deprecated: Use [UnitQuaternion::face_towards] instead.
+    #[deprecated(note="renamed to `face_towards`")]
+    pub fn new_observer_frames<SB, SC>(dir: &Vector<N, U3, SB>, up: &Vector<N, U3, SC>) -> Self
+    where
+        SB: Storage<N, U3>,
+        SC: Storage<N, U3>,
+    {
+        Self::face_towards(dir, up)
     }
 
     /// Builds a right-handed look-at view matrix without translation.
@@ -478,7 +480,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitQuaternion, Vector3};
     /// let dir = Vector3::new(1.0, 2.0, 3.0);
@@ -493,7 +494,7 @@ impl<N: Real> UnitQuaternion<N> {
         SB: Storage<N, U3>,
         SC: Storage<N, U3>,
     {
-        Self::new_observer_frame(&-dir, up).inverse()
+        Self::face_towards(&-dir, up).inverse()
     }
 
     /// Builds a left-handed look-at view matrix without translation.
@@ -510,7 +511,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitQuaternion, Vector3};
     /// let dir = Vector3::new(1.0, 2.0, 3.0);
@@ -525,7 +525,7 @@ impl<N: Real> UnitQuaternion<N> {
         SB: Storage<N, U3>,
         SC: Storage<N, U3>,
     {
-        Self::new_observer_frame(dir, up).inverse()
+        Self::face_towards(dir, up).inverse()
     }
 
     /// Creates a new unit quaternion rotation from a rotation axis scaled by the rotation angle.
@@ -535,7 +535,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitQuaternion, Point3, Vector3};
     /// let axisangle = Vector3::y() * f32::consts::FRAC_PI_2;
@@ -565,7 +564,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitQuaternion, Point3, Vector3};
     /// let axisangle = Vector3::y() * f32::consts::FRAC_PI_2;
@@ -596,7 +594,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitQuaternion, Point3, Vector3};
     /// let axisangle = Vector3::y() * f32::consts::FRAC_PI_2;
@@ -625,7 +622,6 @@ impl<N: Real> UnitQuaternion<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitQuaternion, Point3, Vector3};
     /// let axisangle = Vector3::y() * f32::consts::FRAC_PI_2;
@@ -693,15 +689,16 @@ where
 
 #[cfg(test)]
 mod tests {
+    extern crate rand_xorshift;
     use super::*;
-    use rand::{self, SeedableRng};
+    use rand::SeedableRng;
 
     #[test]
     fn random_unit_quats_are_unit() {
-        let mut rng = rand::prng::XorShiftRng::from_seed([0xAB; 16]);
+        let mut rng = rand_xorshift::XorShiftRng::from_seed([0xAB; 16]);
         for _ in 0..1000 {
             let x = rng.gen::<UnitQuaternion<f32>>();
-            assert!(relative_eq!(x.unwrap().norm(), 1.0))
+            assert!(relative_eq!(x.into_inner().norm(), 1.0))
         }
     }
 }

src/geometry/quaternion_conversion.rs

@@ -228,7 +228,7 @@ impl<N: Real> From<UnitQuaternion<N>> for Matrix4<N> {
 impl<N: Real> From<UnitQuaternion<N>> for Matrix3<N> {
     #[inline]
     fn from(q: UnitQuaternion<N>) -> Matrix3<N> {
-        q.to_rotation_matrix().unwrap()
+        q.to_rotation_matrix().into_inner()
     }
 }
 

src/geometry/quaternion_ops.rs

@@ -469,7 +469,7 @@ quaternion_op_impl!(
     (U4, U1), (U3, U1) for SB: Storage<N, U3> ;
     self: &'a UnitQuaternion<N>, rhs: Unit<Vector<N, U3, SB>>,
     Output = Unit<Vector3<N>> => U3, U4;
-    Unit::new_unchecked(self * rhs.unwrap());
+    Unit::new_unchecked(self * rhs.into_inner());
     'a);
 
 quaternion_op_impl!(
@@ -485,7 +485,7 @@ quaternion_op_impl!(
     (U4, U1), (U3, U1) for SB: Storage<N, U3> ;
     self: UnitQuaternion<N>, rhs: Unit<Vector<N, U3, SB>>,
     Output = Unit<Vector3<N>> => U3, U4;
-    Unit::new_unchecked(self * rhs.unwrap());
+    Unit::new_unchecked(self * rhs.into_inner());
     );
 
 macro_rules! scalar_op_impl(

src/geometry/reflection.rs

@@ -20,7 +20,7 @@ impl<N: Real, D: Dim, S: Storage<N, D>> Reflection<N, D, S> {
     /// represents a plane that passes through the origin.
     pub fn new(axis: Unit<Vector<N, D, S>>, bias: N) -> Reflection<N, D, S> {
         Reflection {
-            axis: axis.unwrap(),
+            axis: axis.into_inner(),
             bias: bias,
         }
     }

src/geometry/rotation.rs

@@ -154,7 +154,7 @@ where DefaultAllocator: Allocator<N, D, D>
     /// # use nalgebra::{Rotation2, Rotation3, Vector3, Matrix2, Matrix3};
     /// # use std::f32;
     /// let rot = Rotation3::from_axis_angle(&Vector3::z_axis(), f32::consts::FRAC_PI_6);
-    /// let mat = rot.unwrap();
+    /// let mat = rot.into_inner();
     /// let expected = Matrix3::new(0.8660254, -0.5,      0.0,
     ///                             0.5,       0.8660254, 0.0,
     ///                             0.0,       0.0,       1.0);
@@ -162,12 +162,20 @@ where DefaultAllocator: Allocator<N, D, D>
     ///
     ///
     /// let rot = Rotation2::new(f32::consts::FRAC_PI_6);
-    /// let mat = rot.unwrap();
+    /// let mat = rot.into_inner();
     /// let expected = Matrix2::new(0.8660254, -0.5,
     ///                             0.5,       0.8660254);
     /// assert_eq!(mat, expected);
     /// ```
     #[inline]
+    pub fn into_inner(self) -> MatrixN<N, D> {
+        self.matrix
+    }
+
+    /// Unwraps the underlying matrix.
+    /// Deprecated: Use [Rotation::into_inner] instead.
+    #[deprecated(note="use `.into_inner()` instead")]
+    #[inline]
     pub fn unwrap(self) -> MatrixN<N, D> {
         self.matrix
     }
@@ -201,6 +209,9 @@ where DefaultAllocator: Allocator<N, D, D>
         D: DimNameAdd<U1>,
         DefaultAllocator: Allocator<N, DimNameSum<D, U1>, DimNameSum<D, U1>>,
     {
+        // We could use `MatrixN::to_homogeneous()` here, but that would imply
+        // adding the additional traits `DimAdd` and `IsNotStaticOne`. Maybe
+        // these things will get nicer once specialization lands in Rust.
         let mut res = MatrixN::<N, DimNameSum<D, U1>>::identity();
         res.fixed_slice_mut::<D, D>(0, 0).copy_from(&self.matrix);
 
@@ -246,7 +257,6 @@ where DefaultAllocator: Allocator<N, D, D>
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Rotation2, Rotation3, Vector3};
     /// let rot = Rotation3::new(Vector3::new(1.0, 2.0, 3.0));
     /// let tr_rot = rot.transpose();
@@ -270,7 +280,6 @@ where DefaultAllocator: Allocator<N, D, D>
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Rotation2, Rotation3, Vector3};
     /// let rot = Rotation3::new(Vector3::new(1.0, 2.0, 3.0));
     /// let inv = rot.inverse();
@@ -294,7 +303,6 @@ where DefaultAllocator: Allocator<N, D, D>
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Rotation2, Rotation3, Vector3};
     /// let rot = Rotation3::new(Vector3::new(1.0, 2.0, 3.0));
     /// let mut tr_rot = Rotation3::new(Vector3::new(1.0, 2.0, 3.0));
@@ -322,7 +330,6 @@ where DefaultAllocator: Allocator<N, D, D>
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Rotation2, Rotation3, Vector3};
     /// let rot = Rotation3::new(Vector3::new(1.0, 2.0, 3.0));
     /// let mut inv = Rotation3::new(Vector3::new(1.0, 2.0, 3.0));

src/geometry/rotation_alga.rs

@@ -1,6 +1,6 @@
 use alga::general::{
     AbstractGroup, AbstractLoop, AbstractMagma, AbstractMonoid, AbstractQuasigroup,
-    AbstractSemigroup, Id, Identity, Inverse, Multiplicative, Real,
+    AbstractSemigroup, Id, Identity, TwoSidedInverse, Multiplicative, Real,
 };
 use alga::linear::{
     self, AffineTransformation, DirectIsometry, Isometry, OrthogonalTransformation,
@@ -27,16 +27,16 @@ where DefaultAllocator: Allocator<N, D, D>
     }
 }
 
-impl<N: Real, D: DimName> Inverse<Multiplicative> for Rotation<N, D>
+impl<N: Real, D: DimName> TwoSidedInverse<Multiplicative> for Rotation<N, D>
 where DefaultAllocator: Allocator<N, D, D>
 {
     #[inline]
-    fn inverse(&self) -> Self {
+    fn two_sided_inverse(&self) -> Self {
         self.transpose()
     }
 
     #[inline]
-    fn inverse_mut(&mut self) {
+    fn two_sided_inverse_mut(&mut self) {
         self.transpose_mut()
     }
 }

src/geometry/rotation_conversion.rs

@@ -227,7 +227,7 @@ impl<N: Real> From<Rotation2<N>> for Matrix3<N> {
 impl<N: Real> From<Rotation2<N>> for Matrix2<N> {
     #[inline]
     fn from(q: Rotation2<N>) -> Matrix2<N> {
-        q.unwrap()
+        q.into_inner()
     }
 }
 
@@ -241,6 +241,6 @@ impl<N: Real> From<Rotation3<N>> for Matrix4<N> {
 impl<N: Real> From<Rotation3<N>> for Matrix3<N> {
     #[inline]
     fn from(q: Rotation3<N>) -> Matrix3<N> {
-        q.unwrap()
+        q.into_inner()
     }
 }

src/geometry/rotation_ops.rs

@@ -46,9 +46,9 @@ md_impl_all!(
     Mul, mul;
     (D, D), (D, D) for D: DimName;
     self: Rotation<N, D>, right: Rotation<N, D>, Output = Rotation<N, D>;
-    [val val] => Rotation::from_matrix_unchecked(self.unwrap() * right.unwrap());
+    [val val] => Rotation::from_matrix_unchecked(self.into_inner() * right.into_inner());
-    [ref val] => Rotation::from_matrix_unchecked(self.matrix() * right.unwrap());
+    [ref val] => Rotation::from_matrix_unchecked(self.matrix() * right.into_inner());
-    [val ref] => Rotation::from_matrix_unchecked(self.unwrap() * right.matrix());
+    [val ref] => Rotation::from_matrix_unchecked(self.into_inner() * right.matrix());
     [ref ref] => Rotation::from_matrix_unchecked(self.matrix() * right.matrix());
 );
 
@@ -71,9 +71,9 @@ md_impl_all!(
     where DefaultAllocator: Allocator<N, D1, C2>
     where ShapeConstraint: AreMultipliable<D1, D1, R2, C2>;
     self: Rotation<N, D1>, right: Matrix<N, R2, C2, SB>, Output = MatrixMN<N, D1, C2>;
-    [val val] => self.unwrap() * right;
+    [val val] => self.into_inner() * right;
     [ref val] => self.matrix() * right;
-    [val ref] => self.unwrap() * right;
+    [val ref] => self.into_inner() * right;
     [ref ref] => self.matrix() * right;
 );
 
@@ -84,8 +84,8 @@ md_impl_all!(
     where DefaultAllocator: Allocator<N, R1, D2>
     where ShapeConstraint:  AreMultipliable<R1, C1, D2, D2>;
     self: Matrix<N, R1, C1, SA>, right: Rotation<N, D2>, Output = MatrixMN<N, R1, D2>;
-    [val val] => self * right.unwrap();
+    [val val] => self * right.into_inner();
-    [ref val] => self * right.unwrap();
+    [ref val] => self * right.into_inner();
     [val ref] => self * right.matrix();
     [ref ref] => self * right.matrix();
 );
@@ -112,9 +112,9 @@ md_impl_all!(
     where DefaultAllocator: Allocator<N, D>
     where ShapeConstraint:  AreMultipliable<D, D, D, U1>;
     self: Rotation<N, D>, right: Point<N, D>, Output = Point<N, D>;
-    [val val] => self.unwrap() * right;
+    [val val] => self.into_inner() * right;
     [ref val] => self.matrix() * right;
-    [val ref] => self.unwrap() * right;
+    [val ref] => self.into_inner() * right;
     [ref ref] => self.matrix() * right;
 );
 
@@ -125,9 +125,9 @@ md_impl_all!(
     where DefaultAllocator: Allocator<N, D>
     where ShapeConstraint:  AreMultipliable<D, D, D, U1>;
     self: Rotation<N, D>, right: Unit<Vector<N, D, S>>, Output = Unit<VectorN<N, D>>;
-    [val val] => Unit::new_unchecked(self.unwrap() * right.unwrap());
+    [val val] => Unit::new_unchecked(self.into_inner() * right.into_inner());
-    [ref val] => Unit::new_unchecked(self.matrix() * right.unwrap());
+    [ref val] => Unit::new_unchecked(self.matrix() * right.into_inner());
-    [val ref] => Unit::new_unchecked(self.unwrap() * right.as_ref());
+    [val ref] => Unit::new_unchecked(self.into_inner() * right.as_ref());
     [ref ref] => Unit::new_unchecked(self.matrix() * right.as_ref());
 );
 
@@ -138,7 +138,7 @@ md_assign_impl_all!(
     MulAssign, mul_assign;
     (D, D), (D, D) for D: DimName;
     self: Rotation<N, D>, right: Rotation<N, D>;
-    [val] => self.matrix_mut_unchecked().mul_assign(right.unwrap());
+    [val] => self.matrix_mut_unchecked().mul_assign(right.into_inner());
     [ref] => self.matrix_mut_unchecked().mul_assign(right.matrix());
 );
 
@@ -146,7 +146,7 @@ md_assign_impl_all!(
     DivAssign, div_assign;
     (D, D), (D, D) for D: DimName;
     self: Rotation<N, D>, right: Rotation<N, D>;
-    [val] => self.matrix_mut_unchecked().mul_assign(right.inverse().unwrap());
+    [val] => self.matrix_mut_unchecked().mul_assign(right.inverse().into_inner());
     [ref] => self.matrix_mut_unchecked().mul_assign(right.inverse().matrix());
 );
 
@@ -160,7 +160,7 @@ md_assign_impl_all!(
     MulAssign, mul_assign;
     (R1, C1), (C1, C1) for R1: DimName, C1: DimName;
     self: MatrixMN<N, R1, C1>, right: Rotation<N, C1>;
-    [val] => self.mul_assign(right.unwrap());
+    [val] => self.mul_assign(right.into_inner());
     [ref] => self.mul_assign(right.matrix());
 );
 
@@ -168,6 +168,6 @@ md_assign_impl_all!(
     DivAssign, div_assign;
     (R1, C1), (C1, C1) for R1: DimName, C1: DimName;
     self: MatrixMN<N, R1, C1>, right: Rotation<N, C1>;
-    [val] => self.mul_assign(right.inverse().unwrap());
+    [val] => self.mul_assign(right.inverse().into_inner());
     [ref] => self.mul_assign(right.inverse().matrix());
 );

src/geometry/rotation_specialization.rs

@@ -27,7 +27,6 @@ impl<N: Real> Rotation2<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Rotation2, Point2};
     /// let rot = Rotation2::new(f32::consts::FRAC_PI_2);
@@ -56,7 +55,6 @@ impl<N: Real> Rotation2<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Vector2, Rotation2};
     /// let a = Vector2::new(1.0, 2.0);
     /// let b = Vector2::new(2.0, 1.0);
@@ -79,7 +77,6 @@ impl<N: Real> Rotation2<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Vector2, Rotation2};
     /// let a = Vector2::new(1.0, 2.0);
     /// let b = Vector2::new(2.0, 1.0);
@@ -107,9 +104,10 @@ impl<N: Real> Rotation2<N> {
     ///
     /// # Example
     /// ```
+    /// # #[macro_use] extern crate approx;
     /// # use nalgebra::Rotation2;
     /// let rot = Rotation2::new(1.78);
-    /// assert_eq!(rot.angle(), 1.78);
+    /// assert_relative_eq!(rot.angle(), 1.78);
     /// ```
     #[inline]
     pub fn angle(&self) -> N {
@@ -121,7 +119,6 @@ impl<N: Real> Rotation2<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Rotation2;
     /// let rot1 = Rotation2::new(0.1);
     /// let rot2 = Rotation2::new(1.7);
@@ -139,7 +136,6 @@ impl<N: Real> Rotation2<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Rotation2;
     /// let rot1 = Rotation2::new(0.1);
     /// let rot2 = Rotation2::new(1.7);
@@ -158,10 +154,11 @@ impl<N: Real> Rotation2<N> {
     ///
     /// # Example
     /// ```
+    /// # #[macro_use] extern crate approx;
     /// # use nalgebra::Rotation2;
     /// let rot = Rotation2::new(0.78);
     /// let pow = rot.powf(2.0);
-    /// assert_eq!(pow.angle(), 2.0 * 0.78);
+    /// assert_relative_eq!(pow.angle(), 2.0 * 0.78);
     /// ```
     #[inline]
     pub fn powf(&self, n: N) -> Rotation2<N> {
@@ -213,7 +210,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Rotation3, Point3, Vector3};
     /// let axisangle = Vector3::y() * f32::consts::FRAC_PI_2;
@@ -241,7 +237,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Rotation3, Point3, Vector3};
     /// let axisangle = Vector3::y() * f32::consts::FRAC_PI_2;
@@ -265,7 +260,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Rotation3, Point3, Vector3};
     /// let axis = Vector3::y_axis();
@@ -318,7 +312,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Rotation3;
     /// let rot = Rotation3::from_euler_angles(0.1, 0.2, 0.3);
     /// let euler = rot.euler_angles();
@@ -359,7 +352,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::Rotation3;
     /// let rot = Rotation3::from_euler_angles(0.1, 0.2, 0.3);
     /// let euler = rot.euler_angles();
@@ -370,12 +362,12 @@ impl<N: Real> Rotation3<N> {
     pub fn euler_angles(&self) -> (N, N, N) {
         // Implementation informed by "Computing Euler angles from a rotation matrix", by Gregory G. Slabaugh
         //  http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.371.6578
-        if self[(2, 0)].abs() != N::one() {
+        if self[(2, 0)].abs() < N::one() {
             let yaw = -self[(2, 0)].asin();
             let roll = (self[(2, 1)] / yaw.cos()).atan2(self[(2, 2)] / yaw.cos());
             let pitch = (self[(1, 0)] / yaw.cos()).atan2(self[(0, 0)] / yaw.cos());
             (roll, yaw, pitch)
-        } else if self[(2, 0)] == -N::one() {
+        } else if self[(2, 0)] <= -N::one() {
             (self[(0, 1)].atan2(self[(0, 2)]), N::frac_pi_2(), N::zero())
         } else {
             (
@@ -399,17 +391,16 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Rotation3, Vector3};
     /// let dir = Vector3::new(1.0, 2.0, 3.0);
     /// let up = Vector3::y();
     ///
-    /// let rot = Rotation3::new_observer_frame(&dir, &up);
+    /// let rot = Rotation3::face_towards(&dir, &up);
     /// assert_relative_eq!(rot * Vector3::z(), dir.normalize());
     /// ```
     #[inline]
-    pub fn new_observer_frame<SB, SC>(dir: &Vector<N, U3, SB>, up: &Vector<N, U3, SC>) -> Self
+    pub fn face_towards<SB, SC>(dir: &Vector<N, U3, SB>, up: &Vector<N, U3, SC>) -> Self
     where
         SB: Storage<N, U3>,
         SC: Storage<N, U3>,
@@ -423,6 +414,16 @@ impl<N: Real> Rotation3<N> {
         ))
     }
 
+    /// Deprecated: Use [Rotation3::face_towards] instead.
+    #[deprecated(note="renamed to `face_towards`")]
+    pub fn new_observer_frames<SB, SC>(dir: &Vector<N, U3, SB>, up: &Vector<N, U3, SC>) -> Self
+    where
+        SB: Storage<N, U3>,
+        SC: Storage<N, U3>,
+    {
+        Self::face_towards(dir, up)
+    }
+
     /// Builds a right-handed look-at view matrix without translation.
     ///
     /// It maps the view direction `dir` to the **negative** `z` axis.
@@ -437,7 +438,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Rotation3, Vector3};
     /// let dir = Vector3::new(1.0, 2.0, 3.0);
@@ -452,7 +452,7 @@ impl<N: Real> Rotation3<N> {
         SB: Storage<N, U3>,
         SC: Storage<N, U3>,
     {
-        Self::new_observer_frame(&dir.neg(), up).inverse()
+        Self::face_towards(&dir.neg(), up).inverse()
     }
 
     /// Builds a left-handed look-at view matrix without translation.
@@ -469,7 +469,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Rotation3, Vector3};
     /// let dir = Vector3::new(1.0, 2.0, 3.0);
@@ -484,7 +483,7 @@ impl<N: Real> Rotation3<N> {
         SB: Storage<N, U3>,
         SC: Storage<N, U3>,
     {
-        Self::new_observer_frame(dir, up).inverse()
+        Self::face_towards(dir, up).inverse()
     }
 
     /// The rotation matrix required to align `a` and `b` but with its angle.
@@ -494,7 +493,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Vector3, Rotation3};
     /// let a = Vector3::new(1.0, 2.0, 3.0);
     /// let b = Vector3::new(3.0, 1.0, 2.0);
@@ -517,7 +515,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Vector3, Rotation3};
     /// let a = Vector3::new(1.0, 2.0, 3.0);
     /// let b = Vector3::new(3.0, 1.0, 2.0);
@@ -562,7 +559,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Unit, Rotation3, Vector3};
     /// let axis = Unit::new_normalize(Vector3::new(1.0, 2.0, 3.0));
     /// let rot = Rotation3::from_axis_angle(&axis, 1.78);
@@ -580,7 +576,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Rotation3, Vector3, Unit};
     /// let axis = Unit::new_normalize(Vector3::new(1.0, 2.0, 3.0));
     /// let angle = 1.2;
@@ -607,7 +602,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Rotation3, Vector3, Unit};
     /// let axisangle = Vector3::new(0.1, 0.2, 0.3);
     /// let rot = Rotation3::new(axisangle);
@@ -616,7 +610,7 @@ impl<N: Real> Rotation3<N> {
     #[inline]
     pub fn scaled_axis(&self) -> Vector3<N> {
         if let Some(axis) = self.axis() {
-            axis.unwrap() * self.angle()
+            axis.into_inner() * self.angle()
         } else {
             Vector::zero()
         }
@@ -629,7 +623,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Rotation3, Vector3, Unit};
     /// let axis = Unit::new_normalize(Vector3::new(1.0, 2.0, 3.0));
     /// let angle = 1.2;
@@ -656,7 +649,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Rotation3, Vector3};
     /// let rot1 = Rotation3::from_axis_angle(&Vector3::y_axis(), 1.0);
     /// let rot2 = Rotation3::from_axis_angle(&Vector3::x_axis(), 0.1);
@@ -674,7 +666,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Rotation3, Vector3};
     /// let rot1 = Rotation3::from_axis_angle(&Vector3::y_axis(), 1.0);
     /// let rot2 = Rotation3::from_axis_angle(&Vector3::x_axis(), 0.1);
@@ -692,7 +683,6 @@ impl<N: Real> Rotation3<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Rotation3, Vector3, Unit};
     /// let axis = Unit::new_normalize(Vector3::new(1.0, 2.0, 3.0));
     /// let angle = 1.2;

src/geometry/similarity_alga.rs

@@ -1,6 +1,6 @@
 use alga::general::{
     AbstractGroup, AbstractLoop, AbstractMagma, AbstractMonoid, AbstractQuasigroup,
-    AbstractSemigroup, Identity, Inverse, Multiplicative, Real,
+    AbstractSemigroup, Identity, TwoSidedInverse, Multiplicative, Real,
 };
 use alga::linear::Similarity as AlgaSimilarity;
 use alga::linear::{AffineTransformation, ProjectiveTransformation, Rotation, Transformation};
@@ -27,18 +27,18 @@ where
     }
 }
 
-impl<N: Real, D: DimName, R> Inverse<Multiplicative> for Similarity<N, D, R>
+impl<N: Real, D: DimName, R> TwoSidedInverse<Multiplicative> for Similarity<N, D, R>
 where
     R: Rotation<Point<N, D>>,
     DefaultAllocator: Allocator<N, D>,
 {
     #[inline]
-    fn inverse(&self) -> Self {
+    fn two_sided_inverse(&self) -> Self {
         self.inverse()
     }
 
     #[inline]
-    fn inverse_mut(&mut self) {
+    fn two_sided_inverse_mut(&mut self) {
         self.inverse_mut()
     }
 }

src/geometry/similarity_construction.rs

@@ -86,7 +86,6 @@ where
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Similarity2, Point2, UnitComplex};
     /// let rot = UnitComplex::new(f32::consts::FRAC_PI_2);
@@ -135,7 +134,6 @@ impl<N: Real> Similarity<N, U2, Rotation2<N>> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{SimilarityMatrix2, Vector2, Point2};
     /// let sim = SimilarityMatrix2::new(Vector2::new(1.0, 2.0), f32::consts::FRAC_PI_2, 3.0);
@@ -159,7 +157,6 @@ impl<N: Real> Similarity<N, U2, UnitComplex<N>> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{Similarity2, Vector2, Point2};
     /// let sim = Similarity2::new(Vector2::new(1.0, 2.0), f32::consts::FRAC_PI_2, 3.0);
@@ -187,7 +184,6 @@ macro_rules! similarity_construction_impl(
             ///
             /// ```
             /// # #[macro_use] extern crate approx;
-            /// # extern crate nalgebra;
             /// # use std::f32;
             /// # use nalgebra::{Similarity3, SimilarityMatrix3, Point3, Vector3};
             /// let axisangle = Vector3::y() * f32::consts::FRAC_PI_2;
@@ -227,7 +223,6 @@ macro_rules! similarity_construction_impl(
             ///
             /// ```
             /// # #[macro_use] extern crate approx;
-            /// # extern crate nalgebra;
             /// # use std::f32;
             /// # use nalgebra::{Similarity3, SimilarityMatrix3, Point3, Vector3};
             /// let eye = Point3::new(1.0, 2.0, 3.0);
@@ -235,22 +230,32 @@ macro_rules! similarity_construction_impl(
             /// let up = Vector3::y();
             ///
             /// // Similarity with its rotation part represented as a UnitQuaternion
-            /// let sim = Similarity3::new_observer_frame(&eye, &target, &up, 3.0);
+            /// let sim = Similarity3::face_towards(&eye, &target, &up, 3.0);
             /// assert_eq!(sim * Point3::origin(), eye);
             /// assert_relative_eq!(sim * Vector3::z(), Vector3::x() * 3.0, epsilon = 1.0e-6);
             ///
             /// // Similarity with its rotation part represented as Rotation3 (a 3x3 rotation matrix).
-            /// let sim = SimilarityMatrix3::new_observer_frame(&eye, &target, &up, 3.0);
+            /// let sim = SimilarityMatrix3::face_towards(&eye, &target, &up, 3.0);
             /// assert_eq!(sim * Point3::origin(), eye);
             /// assert_relative_eq!(sim * Vector3::z(), Vector3::x() * 3.0, epsilon = 1.0e-6);
             /// ```
             #[inline]
-            pub fn new_observer_frame(eye:    &Point3<N>,
+            pub fn face_towards(eye:    &Point3<N>,
                                       target: &Point3<N>,
                                       up:     &Vector3<N>,
                                       scaling: N)
                                       -> Self {
-                Self::from_isometry(Isometry::<_, U3, $Rot>::new_observer_frame(eye, target, up), scaling)
+                Self::from_isometry(Isometry::<_, U3, $Rot>::face_towards(eye, target, up), scaling)
+            }
+
+            /// Deprecated: Use [SimilarityMatrix3::face_towards] instead.
+            #[deprecated(note="renamed to `face_towards`")]
+            pub fn new_observer_frames(eye:    &Point3<N>,
+                                      target: &Point3<N>,
+                                      up:     &Vector3<N>,
+                                      scaling: N)
+                                      -> Self {
+                Self::face_towards(eye, target, up, scaling)
             }
 
             /// Builds a right-handed look-at view matrix including scaling factor.
@@ -268,7 +273,6 @@ macro_rules! similarity_construction_impl(
             ///
             /// ```
             /// # #[macro_use] extern crate approx;
-            /// # extern crate nalgebra;
             /// # use std::f32;
             /// # use nalgebra::{Similarity3, SimilarityMatrix3, Point3, Vector3};
             /// let eye = Point3::new(1.0, 2.0, 3.0);
@@ -307,7 +311,6 @@ macro_rules! similarity_construction_impl(
             ///
             /// ```
             /// # #[macro_use] extern crate approx;
-            /// # extern crate nalgebra;
             /// # use std::f32;
             /// # use nalgebra::{Similarity3, SimilarityMatrix3, Point3, Vector3};
             /// let eye = Point3::new(1.0, 2.0, 3.0);

src/geometry/similarity_ops.rs

@@ -222,8 +222,8 @@ similarity_binop_assign_impl_all!(
     DivAssign, div_assign;
     self: Similarity<N, D, R>, rhs: R;
     // FIXME: don't invert explicitly?
-    [val] => *self *= rhs.inverse();
+    [val] => *self *= rhs.two_sided_inverse();
-    [ref] => *self *= rhs.inverse();
+    [ref] => *self *= rhs.two_sided_inverse();
 );
 
 // Similarity × R

src/geometry/swizzle.rs

@@ -0,0 +1,65 @@
+use base::allocator::Allocator;
+use base::{DefaultAllocator, DimName, Scalar};
+use geometry::{Point, Point2, Point3};
+use typenum::{self, Cmp, Greater};
+
+macro_rules! impl_swizzle {
+    ($( where $BaseDim: ident: $( $name: ident() -> $Result: ident[$($i: expr),+] ),+ ;)* ) => {
+        $(
+            impl<N: Scalar, D: DimName> Point<N, D>
+            where
+                DefaultAllocator: Allocator<N, D>,
+                D::Value: Cmp<typenum::$BaseDim, Output=Greater>
+            {
+                $(
+                    /// Builds a new point from components of `self`.
+                    #[inline]
+                    pub fn $name(&self) -> $Result<N> {
+                        $Result::new($(self[$i]),*)
+                    }
+                )*
+            }
+        )*
+    }
+}
+
+impl_swizzle!(
+    where U0: xx()  -> Point2[0, 0],
+              xxx() -> Point3[0, 0, 0];
+
+    where U1: xy()  -> Point2[0, 1],
+              yx()  -> Point2[1, 0],
+              yy()  -> Point2[1, 1],
+              xxy() -> Point3[0, 0, 1],
+              xyx() -> Point3[0, 1, 0],
+              xyy() -> Point3[0, 1, 1],
+              yxx() -> Point3[1, 0, 0],
+              yxy() -> Point3[1, 0, 1],
+              yyx() -> Point3[1, 1, 0],
+              yyy() -> Point3[1, 1, 1];
+
+    where U2: xz()  -> Point2[0, 2],
+              yz()  -> Point2[1, 2],
+              zx()  -> Point2[2, 0],
+              zy()  -> Point2[2, 1],
+              zz()  -> Point2[2, 2],
+              xxz() -> Point3[0, 0, 2],
+              xyz() -> Point3[0, 1, 2],
+              xzx() -> Point3[0, 2, 0],
+              xzy() -> Point3[0, 2, 1],
+              xzz() -> Point3[0, 2, 2],
+              yxz() -> Point3[1, 0, 2],
+              yyz() -> Point3[1, 1, 2],
+              yzx() -> Point3[1, 2, 0],
+              yzy() -> Point3[1, 2, 1],
+              yzz() -> Point3[1, 2, 2],
+              zxx() -> Point3[2, 0, 0],
+              zxy() -> Point3[2, 0, 1],
+              zxz() -> Point3[2, 0, 2],
+              zyx() -> Point3[2, 1, 0],
+              zyy() -> Point3[2, 1, 1],
+              zyz() -> Point3[2, 1, 2],
+              zzx() -> Point3[2, 2, 0],
+              zzy() -> Point3[2, 2, 1],
+              zzz() -> Point3[2, 2, 2];
+);

src/geometry/transform.rs

@@ -248,9 +248,17 @@ where DefaultAllocator: Allocator<N, DimNameSum<D, U1>, DimNameSum<D, U1>>
     ///                      3.0, 4.0, 0.0,
     ///                      0.0, 0.0, 1.0);
     /// let t = Transform2::from_matrix_unchecked(m);
-    /// assert_eq!(t.unwrap(), m);
+    /// assert_eq!(t.into_inner(), m);
     /// ```
     #[inline]
+    pub fn into_inner(self) -> MatrixN<N, DimNameSum<D, U1>> {
+        self.matrix
+    }
+
+    /// Retrieves the underlying matrix.
+    /// Deprecated: Use [Transform::into_inner] instead.
+    #[deprecated(note="use `.into_inner()` instead")]
+    #[inline]
     pub fn unwrap(self) -> MatrixN<N, DimNameSum<D, U1>> {
         self.matrix
     }
@@ -329,7 +337,7 @@ where DefaultAllocator: Allocator<N, DimNameSum<D, U1>, DimNameSum<D, U1>>
     ///                      3.0, 4.0, 0.0,
     ///                      0.0, 0.0, 1.0);
     /// let t = Transform2::from_matrix_unchecked(m);
-    /// assert_eq!(t.unwrap(), m);
+    /// assert_eq!(t.into_inner(), m);
     /// ```
     #[inline]
     pub fn to_homogeneous(&self) -> MatrixN<N, DimNameSum<D, U1>> {
@@ -342,7 +350,6 @@ where DefaultAllocator: Allocator<N, DimNameSum<D, U1>, DimNameSum<D, U1>>
     /// # Examples
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Matrix3, Transform2};
     ///
     /// let m = Matrix3::new(2.0, 2.0, -0.3,
@@ -375,7 +382,6 @@ where DefaultAllocator: Allocator<N, DimNameSum<D, U1>, DimNameSum<D, U1>>
     /// # Examples
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Matrix3, Projective2};
     ///
     /// let m = Matrix3::new(2.0, 2.0, -0.3,
@@ -399,7 +405,6 @@ where DefaultAllocator: Allocator<N, DimNameSum<D, U1>, DimNameSum<D, U1>>
     /// # Examples
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Matrix3, Transform2};
     ///
     /// let m = Matrix3::new(2.0, 2.0, -0.3,
@@ -429,7 +434,6 @@ where DefaultAllocator: Allocator<N, DimNameSum<D, U1>, DimNameSum<D, U1>>
     /// # Examples
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Matrix3, Projective2};
     ///
     /// let m = Matrix3::new(2.0, 2.0, -0.3,

src/geometry/transform_alga.rs

@@ -1,6 +1,6 @@
 use alga::general::{
     AbstractGroup, AbstractLoop, AbstractMagma, AbstractMonoid, AbstractQuasigroup,
-    AbstractSemigroup, Identity, Inverse, Multiplicative, Real,
+    AbstractSemigroup, Identity, TwoSidedInverse, Multiplicative, Real,
 };
 use alga::linear::{ProjectiveTransformation, Transformation};
 
@@ -26,18 +26,18 @@ where
     }
 }
 
-impl<N: Real, D: DimNameAdd<U1>, C> Inverse<Multiplicative> for Transform<N, D, C>
+impl<N: Real, D: DimNameAdd<U1>, C> TwoSidedInverse<Multiplicative> for Transform<N, D, C>
 where
     C: SubTCategoryOf<TProjective>,
     DefaultAllocator: Allocator<N, DimNameSum<D, U1>, DimNameSum<D, U1>>,
 {
     #[inline]
-    fn inverse(&self) -> Self {
+    fn two_sided_inverse(&self) -> Self {
         self.clone().inverse()
     }
 
     #[inline]
-    fn inverse_mut(&mut self) {
+    fn two_sided_inverse_mut(&mut self) {
         self.inverse_mut()
     }
 }
@@ -116,12 +116,12 @@ where
 {
     #[inline]
     fn inverse_transform_point(&self, pt: &Point<N, D>) -> Point<N, D> {
-        self.inverse() * pt
+        self.two_sided_inverse() * pt
     }
 
     #[inline]
     fn inverse_transform_vector(&self, v: &VectorN<N, D>) -> VectorN<N, D> {
-        self.inverse() * v
+        self.two_sided_inverse() * v
     }
 }
 

src/geometry/transform_ops.rs

@@ -143,7 +143,7 @@ md_impl_all!(
 
         if C::has_normalizer() {
             let normalizer = self.matrix().fixed_slice::<U1, D>(D::dim(), 0);
-            let n = normalizer.tr_dot(&rhs.coords) + unsafe { *self.matrix().get_unchecked(D::dim(), D::dim()) };
+            let n = normalizer.tr_dot(&rhs.coords) + unsafe { *self.matrix().get_unchecked((D::dim(), D::dim())) };
 
             if !n.is_zero() {
                 return (transform * rhs + translation) / n;
@@ -159,9 +159,9 @@ md_impl_all!(
     Mul, mul where N: Real;
     (DimNameSum<D, U1>, DimNameSum<D, U1>), (DimNameSum<D, U1>, DimNameSum<D, U1>) for D: DimNameAdd<U1>, CA: TCategoryMul<CB>, CB: TCategory;
     self: Transform<N, D, CA>, rhs: Transform<N, D, CB>, Output = Transform<N, D, CA::Representative>;
-    [val val] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.unwrap());
+    [val val] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.into_inner());
-    [ref val] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.unwrap());
+    [ref val] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.into_inner());
-    [val ref] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.matrix());
+    [val ref] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.matrix());
     [ref ref] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.matrix());
 );
 
@@ -170,9 +170,9 @@ md_impl_all!(
     Mul, mul where N: Real;
     (DimNameSum<D, U1>, DimNameSum<D, U1>), (D, D) for D: DimNameAdd<U1>, C: TCategoryMul<TAffine>;
     self: Transform<N, D, C>, rhs: Rotation<N, D>, Output = Transform<N, D, C::Representative>;
-    [val val] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.to_homogeneous());
+    [val val] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.to_homogeneous());
     [ref val] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.to_homogeneous());
-    [val ref] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.to_homogeneous());
+    [val ref] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.to_homogeneous());
     [ref ref] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.to_homogeneous());
 );
 
@@ -181,8 +181,8 @@ md_impl_all!(
     Mul, mul where N: Real;
     (D, D), (DimNameSum<D, U1>, DimNameSum<D, U1>) for D: DimNameAdd<U1>, C: TCategoryMul<TAffine>;
     self: Rotation<N, D>, rhs: Transform<N, D, C>, Output = Transform<N, D, C::Representative>;
-    [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+    [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
-    [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+    [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
     [val ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
     [ref ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
 );
@@ -192,9 +192,9 @@ md_impl_all!(
     Mul, mul where N: Real;
     (U4, U4), (U4, U1) for C: TCategoryMul<TAffine>;
     self: Transform<N, U3, C>, rhs: UnitQuaternion<N>, Output = Transform<N, U3, C::Representative>;
-    [val val] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.to_homogeneous());
+    [val val] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.to_homogeneous());
     [ref val] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.to_homogeneous());
-    [val ref] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.to_homogeneous());
+    [val ref] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.to_homogeneous());
     [ref ref] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.to_homogeneous());
 );
 
@@ -203,8 +203,8 @@ md_impl_all!(
     Mul, mul where N: Real;
     (U4, U1), (U4, U4) for C: TCategoryMul<TAffine>;
     self: UnitQuaternion<N>, rhs: Transform<N, U3, C>, Output = Transform<N, U3, C::Representative>;
-    [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+    [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
-    [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+    [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
     [val ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
     [ref ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
 );
@@ -215,9 +215,9 @@ md_impl_all!(
     (DimNameSum<D, U1>, DimNameSum<D, U1>), (D, U1)
     for D: DimNameAdd<U1>, C: TCategoryMul<TAffine>, R: SubsetOf<MatrixN<N, DimNameSum<D, U1>> >;
     self: Transform<N, D, C>, rhs: Isometry<N, D, R>, Output = Transform<N, D, C::Representative>;
-    [val val] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.to_homogeneous());
+    [val val] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.to_homogeneous());
     [ref val] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.to_homogeneous());
-    [val ref] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.to_homogeneous());
+    [val ref] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.to_homogeneous());
     [ref ref] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.to_homogeneous());
 );
 
@@ -227,8 +227,8 @@ md_impl_all!(
     (D, U1), (DimNameSum<D, U1>, DimNameSum<D, U1>)
     for D: DimNameAdd<U1>, C: TCategoryMul<TAffine>, R: SubsetOf<MatrixN<N, DimNameSum<D, U1>> >;
     self: Isometry<N, D, R>, rhs: Transform<N, D, C>, Output = Transform<N, D, C::Representative>;
-    [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+    [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
-    [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+    [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
     [val ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
     [ref ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
 );
@@ -239,9 +239,9 @@ md_impl_all!(
     (DimNameSum<D, U1>, DimNameSum<D, U1>), (D, U1)
     for D: DimNameAdd<U1>, C: TCategoryMul<TAffine>, R: SubsetOf<MatrixN<N, DimNameSum<D, U1>> >;
     self: Transform<N, D, C>, rhs: Similarity<N, D, R>, Output = Transform<N, D, C::Representative>;
-    [val val] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.to_homogeneous());
+    [val val] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.to_homogeneous());
     [ref val] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.to_homogeneous());
-    [val ref] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.to_homogeneous());
+    [val ref] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.to_homogeneous());
     [ref ref] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.to_homogeneous());
 );
 
@@ -251,8 +251,8 @@ md_impl_all!(
     (D, U1), (DimNameSum<D, U1>, DimNameSum<D, U1>)
     for D: DimNameAdd<U1>, C: TCategoryMul<TAffine>, R: SubsetOf<MatrixN<N, DimNameSum<D, U1>> >;
     self: Similarity<N, D, R>, rhs: Transform<N, D, C>, Output = Transform<N, D, C::Representative>;
-    [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+    [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
-    [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+    [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
     [val ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
     [ref ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
 );
@@ -270,9 +270,9 @@ md_impl_all!(
     Mul, mul where N: Real;
     (DimNameSum<D, U1>, DimNameSum<D, U1>), (D, U1) for D: DimNameAdd<U1>, C: TCategoryMul<TAffine>;
     self: Transform<N, D, C>, rhs: Translation<N, D>, Output = Transform<N, D, C::Representative>;
-    [val val] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.to_homogeneous());
+    [val val] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.to_homogeneous());
     [ref val] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.to_homogeneous());
-    [val ref] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.to_homogeneous());
+    [val ref] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.to_homogeneous());
     [ref ref] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.to_homogeneous());
 );
 
@@ -282,8 +282,8 @@ md_impl_all!(
     (D, U1), (DimNameSum<D, U1>, DimNameSum<D, U1>)
     for D: DimNameAdd<U1>, C: TCategoryMul<TAffine>;
     self: Translation<N, D>, rhs: Transform<N, D, C>, Output = Transform<N, D, C::Representative>;
-    [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+    [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
-    [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+    [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
     [val ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
     [ref ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
 );
@@ -350,9 +350,9 @@ md_impl_all!(
 //          for D: DimNameAdd<U1>, C: TCategoryMul<TAffine>, R: SubsetOf<MatrixN<N, DimNameSum<D, U1>> >
 //          where SB::Alloc: Allocator<N, DimNameSum<D, U1>, DimNameSum<D, U1> >;
 //          self: Transform<N, D, C>, rhs: Isometry<N, D, R>, Output = Transform<N, D, C::Representative>;
-//          [val val] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.inverse().to_homogeneous());
+//          [val val] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.inverse().to_homogeneous());
 //          [ref val] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.inverse().to_homogeneous());
-//          [val ref] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.inverse().to_homogeneous());
+//          [val ref] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.inverse().to_homogeneous());
 //          [ref ref] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.inverse().to_homogeneous());
 //      );
 
@@ -363,8 +363,8 @@ md_impl_all!(
 //          for D: DimNameAdd<U1>, C: TCategoryMul<TAffine>, R: SubsetOf<MatrixN<N, DimNameSum<D, U1>> >
 //          where SA::Alloc: Allocator<N, DimNameSum<D, U1>, DimNameSum<D, U1> >;
 //          self: Isometry<N, D, R>, rhs: Transform<N, D, C>, Output = Transform<N, D, C::Representative>;
-//          [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+//          [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
-//          [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+//          [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
 //          [val ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
 //          [ref ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
 //      );
@@ -377,9 +377,9 @@ md_impl_all!(
 //          where SB::Alloc: Allocator<N, D, D >
 //          where SB::Alloc: Allocator<N, DimNameSum<D, U1>, DimNameSum<D, U1> >;
 //          self: Transform<N, D, C>, rhs: Similarity<N, D, R>, Output = Transform<N, D, C::Representative>;
-//          [val val] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.to_homogeneous());
+//          [val val] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.to_homogeneous());
 //          [ref val] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.to_homogeneous());
-//          [val ref] => Self::Output::from_matrix_unchecked(self.unwrap() * rhs.to_homogeneous());
+//          [val ref] => Self::Output::from_matrix_unchecked(self.into_inner() * rhs.to_homogeneous());
 //          [ref ref] => Self::Output::from_matrix_unchecked(self.matrix() * rhs.to_homogeneous());
 //      );
 
@@ -391,8 +391,8 @@ md_impl_all!(
 //          where SA::Alloc: Allocator<N, D, D >
 //          where SA::Alloc: Allocator<N, DimNameSum<D, U1>, DimNameSum<D, U1> >;
 //          self: Similarity<N, D, R>, rhs: Transform<N, D, C>, Output = Transform<N, D, C::Representative>;
-//          [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+//          [val val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
-//          [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.unwrap());
+//          [ref val] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.into_inner());
 //          [val ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
 //          [ref ref] => Self::Output::from_matrix_unchecked(self.to_homogeneous() * rhs.matrix());
 //      );
@@ -425,7 +425,7 @@ md_assign_impl_all!(
     MulAssign, mul_assign where N: Real;
     (DimNameSum<D, U1>, DimNameSum<D, U1>), (DimNameSum<D, U1>, DimNameSum<D, U1>) for D: DimNameAdd<U1>, CA: TCategory, CB: SubTCategoryOf<CA>;
     self: Transform<N, D, CA>, rhs: Transform<N, D, CB>;
-    [val] => *self.matrix_mut_unchecked() *= rhs.unwrap();
+    [val] => *self.matrix_mut_unchecked() *= rhs.into_inner();
     [ref] => *self.matrix_mut_unchecked() *= rhs.matrix();
 );
 

src/geometry/translation_alga.rs

@@ -1,6 +1,6 @@
 use alga::general::{
     AbstractGroup, AbstractLoop, AbstractMagma, AbstractMonoid, AbstractQuasigroup,
-    AbstractSemigroup, Id, Identity, Inverse, Multiplicative, Real,
+    AbstractSemigroup, Id, Identity, TwoSidedInverse, Multiplicative, Real,
 };
 use alga::linear::Translation as AlgaTranslation;
 use alga::linear::{
@@ -28,16 +28,16 @@ where DefaultAllocator: Allocator<N, D>
     }
 }
 
-impl<N: Real, D: DimName> Inverse<Multiplicative> for Translation<N, D>
+impl<N: Real, D: DimName> TwoSidedInverse<Multiplicative> for Translation<N, D>
 where DefaultAllocator: Allocator<N, D>
 {
     #[inline]
-    fn inverse(&self) -> Self {
+    fn two_sided_inverse(&self) -> Self {
         self.inverse()
     }
 
     #[inline]
-    fn inverse_mut(&mut self) {
+    fn two_sided_inverse_mut(&mut self) {
         self.inverse_mut()
     }
 }

src/geometry/translation_coordinates.rs

@@ -0,0 +1,44 @@
+use std::mem;
+use std::ops::{Deref, DerefMut};
+
+use base::allocator::Allocator;
+use base::coordinates::{X, XY, XYZ, XYZW, XYZWA, XYZWAB};
+use base::dimension::{U1, U2, U3, U4, U5, U6};
+use base::{DefaultAllocator, Scalar};
+
+use geometry::Translation;
+
+/*
+ *
+ * Give coordinates to Translation{1 .. 6}
+ *
+ */
+
+macro_rules! deref_impl(
+    ($D: ty, $Target: ident $(, $comps: ident)*) => {
+        impl<N: Scalar> Deref for Translation<N, $D>
+            where DefaultAllocator: Allocator<N, $D> {
+            type Target = $Target<N>;
+
+            #[inline]
+            fn deref(&self) -> &Self::Target {
+                unsafe { mem::transmute(self) }
+            }
+        }
+
+        impl<N: Scalar> DerefMut for Translation<N, $D>
+            where DefaultAllocator: Allocator<N, $D> {
+            #[inline]
+            fn deref_mut(&mut self) -> &mut Self::Target {
+                unsafe { mem::transmute(self) }
+            }
+        }
+    }
+);
+
+deref_impl!(U1, X, x);
+deref_impl!(U2, XY, x, y);
+deref_impl!(U3, XYZ, x, y, z);
+deref_impl!(U4, XYZW, x, y, z, w);
+deref_impl!(U5, XYZWA, x, y, z, w, a);
+deref_impl!(U6, XYZWAB, x, y, z, w, a, b);

src/geometry/unit_complex.rs

@@ -85,7 +85,6 @@ impl<N: Real> UnitComplex<N> {
     /// # Example
     /// ```
     /// # extern crate num_complex;
-    /// # extern crate nalgebra;
     /// # use num_complex::Complex;
     /// # use nalgebra::UnitComplex;
     /// let angle = 1.78f32;
@@ -117,7 +116,6 @@ impl<N: Real> UnitComplex<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::UnitComplex;
     /// let rot = UnitComplex::new(1.2);
     /// let inv = rot.inverse();
@@ -134,7 +132,6 @@ impl<N: Real> UnitComplex<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::UnitComplex;
     /// let rot1 = UnitComplex::new(0.1);
     /// let rot2 = UnitComplex::new(1.7);
@@ -153,7 +150,6 @@ impl<N: Real> UnitComplex<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::UnitComplex;
     /// let rot1 = UnitComplex::new(0.1);
     /// let rot2 = UnitComplex::new(1.7);
@@ -172,7 +168,6 @@ impl<N: Real> UnitComplex<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::UnitComplex;
     /// let angle = 1.7;
     /// let rot = UnitComplex::new(angle);
@@ -192,7 +187,6 @@ impl<N: Real> UnitComplex<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::UnitComplex;
     /// let angle = 1.7;
     /// let mut rot = UnitComplex::new(angle);
@@ -212,10 +206,11 @@ impl<N: Real> UnitComplex<N> {
     ///
     /// # Example
     /// ```
+    /// # #[macro_use] extern crate approx;
     /// # use nalgebra::UnitComplex;
     /// let rot = UnitComplex::new(0.78);
     /// let pow = rot.powf(2.0);
-    /// assert_eq!(pow.angle(), 2.0 * 0.78);
+    /// assert_relative_eq!(pow.angle(), 2.0 * 0.78);
     /// ```
     #[inline]
     pub fn powf(&self, n: N) -> Self {
@@ -320,6 +315,6 @@ impl<N: Real> From<UnitComplex<N>> for Matrix3<N> {
 impl<N: Real> From<UnitComplex<N>> for Matrix2<N> {
     #[inline]
     fn from(q: UnitComplex<N>) -> Matrix2<N> {
-        q.to_rotation_matrix().unwrap()
+        q.to_rotation_matrix().into_inner()
     }
 }

src/geometry/unit_complex_alga.rs

@@ -1,6 +1,6 @@
 use alga::general::{
     AbstractGroup, AbstractLoop, AbstractMagma, AbstractMonoid, AbstractQuasigroup,
-    AbstractSemigroup, Id, Identity, Inverse, Multiplicative, Real,
+    AbstractSemigroup, Id, Identity, TwoSidedInverse, Multiplicative, Real,
 };
 use alga::linear::{
     AffineTransformation, DirectIsometry, Isometry, OrthogonalTransformation,
@@ -31,14 +31,14 @@ impl<N: Real> AbstractMagma<Multiplicative> for UnitComplex<N> {
     }
 }
 
-impl<N: Real> Inverse<Multiplicative> for UnitComplex<N> {
+impl<N: Real> TwoSidedInverse<Multiplicative> for UnitComplex<N> {
     #[inline]
-    fn inverse(&self) -> Self {
+    fn two_sided_inverse(&self) -> Self {
         self.inverse()
     }
 
     #[inline]
-    fn inverse_mut(&mut self) {
+    fn two_sided_inverse_mut(&mut self) {
         self.inverse_mut()
     }
 }

src/geometry/unit_complex_construction.rs

@@ -7,10 +7,9 @@ use rand::distributions::{Distribution, OpenClosed01, Standard};
 use rand::Rng;
 
 use alga::general::Real;
-use base::allocator::Allocator;
 use base::dimension::{U1, U2};
 use base::storage::Storage;
-use base::{DefaultAllocator, Unit, Vector};
+use base::{Unit, Vector};
 use geometry::{Rotation2, UnitComplex};
 
 impl<N: Real> UnitComplex<N> {
@@ -36,7 +35,6 @@ impl<N: Real> UnitComplex<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitComplex, Point2};
     /// let rot = UnitComplex::new(f32::consts::FRAC_PI_2);
@@ -57,7 +55,6 @@ impl<N: Real> UnitComplex<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitComplex, Point2};
     /// let rot = UnitComplex::from_angle(f32::consts::FRAC_PI_2);
@@ -79,7 +76,6 @@ impl<N: Real> UnitComplex<N> {
     ///
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use std::f32;
     /// # use nalgebra::{UnitComplex, Vector2, Point2};
     /// let angle = f32::consts::FRAC_PI_2;
@@ -139,7 +135,6 @@ impl<N: Real> UnitComplex<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Vector2, UnitComplex};
     /// let a = Vector2::new(1.0, 2.0);
     /// let b = Vector2::new(2.0, 1.0);
@@ -162,7 +157,6 @@ impl<N: Real> UnitComplex<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Vector2, UnitComplex};
     /// let a = Vector2::new(1.0, 2.0);
     /// let b = Vector2::new(2.0, 1.0);
@@ -198,7 +192,6 @@ impl<N: Real> UnitComplex<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Unit, Vector2, UnitComplex};
     /// let a = Unit::new_normalize(Vector2::new(1.0, 2.0));
     /// let b = Unit::new_normalize(Vector2::new(2.0, 1.0));
@@ -224,7 +217,6 @@ impl<N: Real> UnitComplex<N> {
     /// # Example
     /// ```
     /// # #[macro_use] extern crate approx;
-    /// # extern crate nalgebra;
     /// # use nalgebra::{Unit, Vector2, UnitComplex};
     /// let a = Unit::new_normalize(Vector2::new(1.0, 2.0));
     /// let b = Unit::new_normalize(Vector2::new(2.0, 1.0));

src/geometry/unit_complex_ops.rs

@@ -50,7 +50,7 @@ impl<N: Real> Mul<UnitComplex<N>> for UnitComplex<N> {
 
     #[inline]
     fn mul(self, rhs: UnitComplex<N>) -> UnitComplex<N> {
-        Unit::new_unchecked(self.unwrap() * rhs.unwrap())
+        Unit::new_unchecked(self.into_inner() * rhs.into_inner())
     }
 }
 
@@ -59,7 +59,7 @@ impl<'a, N: Real> Mul<UnitComplex<N>> for &'a UnitComplex<N> {
 
     #[inline]
     fn mul(self, rhs: UnitComplex<N>) -> UnitComplex<N> {
-        Unit::new_unchecked(self.complex() * rhs.unwrap())
+        Unit::new_unchecked(self.complex() * rhs.into_inner())
     }
 }
 
@@ -68,7 +68,7 @@ impl<'b, N: Real> Mul<&'b UnitComplex<N>> for UnitComplex<N> {
 
     #[inline]
     fn mul(self, rhs: &'b UnitComplex<N>) -> UnitComplex<N> {
-        Unit::new_unchecked(self.unwrap() * rhs.complex())
+        Unit::new_unchecked(self.into_inner() * rhs.complex())
     }
 }
 
@@ -87,7 +87,7 @@ impl<N: Real> Div<UnitComplex<N>> for UnitComplex<N> {
 
     #[inline]
     fn div(self, rhs: UnitComplex<N>) -> UnitComplex<N> {
-        Unit::new_unchecked(self.unwrap() * rhs.conjugate().unwrap())
+        Unit::new_unchecked(self.into_inner() * rhs.conjugate().into_inner())
     }
 }
 
@@ -96,7 +96,7 @@ impl<'a, N: Real> Div<UnitComplex<N>> for &'a UnitComplex<N> {
 
     #[inline]
     fn div(self, rhs: UnitComplex<N>) -> UnitComplex<N> {
-        Unit::new_unchecked(self.complex() * rhs.conjugate().unwrap())
+        Unit::new_unchecked(self.complex() * rhs.conjugate().into_inner())
     }
 }
 
@@ -105,7 +105,7 @@ impl<'b, N: Real> Div<&'b UnitComplex<N>> for UnitComplex<N> {
 
     #[inline]
     fn div(self, rhs: &'b UnitComplex<N>) -> UnitComplex<N> {
-        Unit::new_unchecked(self.unwrap() * rhs.conjugate().unwrap())
+        Unit::new_unchecked(self.into_inner() * rhs.conjugate().into_inner())
     }
 }
 
@@ -114,7 +114,7 @@ impl<'a, 'b, N: Real> Div<&'b UnitComplex<N>> for &'a UnitComplex<N> {
 
     #[inline]
     fn div(self, rhs: &'b UnitComplex<N>) -> UnitComplex<N> {
-        Unit::new_unchecked(self.complex() * rhs.conjugate().unwrap())
+        Unit::new_unchecked(self.complex() * rhs.conjugate().into_inner())
     }
 }
 
@@ -425,11 +425,11 @@ impl<N: Real> UnitComplex<N> {
 
         for j in 0..rhs.ncols() {
             unsafe {
-                let a = *rhs.get_unchecked(0, j);
+                let a = *rhs.get_unchecked((0, j));
-                let b = *rhs.get_unchecked(1, j);
+                let b = *rhs.get_unchecked((1, j));
 
-                *rhs.get_unchecked_mut(0, j) = r * a - i * b;
+                *rhs.get_unchecked_mut((0, j)) = r * a - i * b;
-                *rhs.get_unchecked_mut(1, j) = i * a + r * b;
+                *rhs.get_unchecked_mut((1, j)) = i * a + r * b;
             }
         }
     }
@@ -452,11 +452,11 @@ impl<N: Real> UnitComplex<N> {
         // FIXME: can we optimize that to iterate on one column at a time ?
         for j in 0..lhs.nrows() {
             unsafe {
-                let a = *lhs.get_unchecked(j, 0);
+                let a = *lhs.get_unchecked((j, 0));
-                let b = *lhs.get_unchecked(j, 1);
+                let b = *lhs.get_unchecked((j, 1));
 
-                *lhs.get_unchecked_mut(j, 0) = r * a + i * b;
+                *lhs.get_unchecked_mut((j, 0)) = r * a + i * b;
-                *lhs.get_unchecked_mut(j, 1) = -i * a + r * b;
+                *lhs.get_unchecked_mut((j, 1)) = -i * a + r * b;
             }
         }
     }

src/io/matrix_market.pest

@@ -0,0 +1,16 @@
+WHITESPACE = _{ " " }
+
+Comments = _{ "%" ~ (!NEWLINE ~ ANY)* }
+Header = { "%%" ~ (!NEWLINE ~ ANY)* }
+Shape = { Dimension ~ Dimension ~ Dimension }
+Document = {
+    SOI ~
+    NEWLINE* ~
+    Header ~
+    (NEWLINE ~ Comments)* ~
+    (NEWLINE ~ Shape) ~
+    (NEWLINE ~ Entry?)*
+}
+Dimension = @{ ASCII_DIGIT+ }
+Value = @{ ("+" | "-")? ~ NUMBER+ ~ ("." ~ NUMBER+)? ~ ("e" ~ ("+" | "-")? ~ NUMBER+)? }
+Entry = { Dimension ~ Dimension ~ Value }

src/io/matrix_market.rs

@@ -0,0 +1,53 @@
+use std::fs;
+use std::path::Path;
+
+use pest::Parser;
+use sparse::CsMatrix;
+use Real;
+
+#[derive(Parser)]
+#[grammar = "io/matrix_market.pest"]
+struct MatrixMarketParser;
+
+// FIXME: return an Error instead of an Option.
+/// Parses a Matrix Market file at the given path, and returns the corresponding sparse matrix.
+pub fn cs_matrix_from_matrix_market<N: Real, P: AsRef<Path>>(path: P) -> Option<CsMatrix<N>> {
+    let file = fs::read_to_string(path).ok()?;
+    cs_matrix_from_matrix_market_str(&file)
+}
+
+// FIXME: return an Error instead of an Option.
+/// Parses a Matrix Market file described by the given string, and returns the corresponding sparse matrix.
+pub fn cs_matrix_from_matrix_market_str<N: Real>(data: &str) -> Option<CsMatrix<N>> {
+    let file = MatrixMarketParser::parse(Rule::Document, data)
+        .unwrap()
+        .next()?;
+    let mut shape = (0, 0, 0);
+    let mut rows: Vec<usize> = Vec::new();
+    let mut cols: Vec<usize> = Vec::new();
+    let mut data: Vec<N> = Vec::new();
+
+    for line in file.into_inner() {
+        match line.as_rule() {
+            Rule::Header => {}
+            Rule::Shape => {
+                let mut inner = line.into_inner();
+                shape.0 = inner.next()?.as_str().parse::<usize>().ok()?;
+                shape.1 = inner.next()?.as_str().parse::<usize>().ok()?;
+                shape.2 = inner.next()?.as_str().parse::<usize>().ok()?;
+            }
+            Rule::Entry => {
+                let mut inner = line.into_inner();
+                // NOTE: indices are 1-based.
+                rows.push(inner.next()?.as_str().parse::<usize>().ok()? - 1);
+                cols.push(inner.next()?.as_str().parse::<usize>().ok()? - 1);
+                data.push(::convert(inner.next()?.as_str().parse::<f64>().ok()?));
+            }
+            _ => return None, // FIXME: return an Err instead.
+        }
+    }
+
+    Some(CsMatrix::from_triplet(
+        shape.0, shape.1, &rows, &cols, &data,
+    ))
+}

src/io/mod.rs

@@ -0,0 +1,5 @@
+//! Parsers for various matrix formats.
+
+pub use self::matrix_market::{cs_matrix_from_matrix_market, cs_matrix_from_matrix_market_str};
+
+mod matrix_market;

src/lib.rs

@@ -81,10 +81,12 @@ an optimized set of tools for computer graphics and physics. Those features incl
 #![deny(non_upper_case_globals)]
 #![deny(unused_qualifications)]
 #![deny(unused_results)]
-#![deny(missing_docs)]
+#![warn(missing_docs)] // FIXME: deny this
 #![warn(incoherent_fundamental_impls)]
-#![doc(html_favicon_url = "http://nalgebra.org/img/favicon.ico",
+#![doc(
-       html_root_url = "http://nalgebra.org/rustdoc")]
+    html_favicon_url = "http://nalgebra.org/img/favicon.ico",
+    html_root_url = "http://nalgebra.org/rustdoc"
+)]
 #![cfg_attr(not(feature = "std"), no_std)]
 #![cfg_attr(all(feature = "alloc", not(feature = "std")), feature(alloc))]
 
@@ -121,11 +123,21 @@ extern crate alloc;
 #[cfg(not(feature = "std"))]
 extern crate core as std;
 
+#[cfg(feature = "io")]
+extern crate pest;
+#[macro_use]
+#[cfg(feature = "io")]
+extern crate pest_derive;
+
 pub mod base;
 #[cfg(feature = "debug")]
 pub mod debug;
 pub mod geometry;
+#[cfg(feature = "io")]
+pub mod io;
 pub mod linalg;
+#[cfg(feature = "sparse")]
+pub mod sparse;
 
 #[cfg(feature = "std")]
 #[deprecated(
@@ -135,11 +147,13 @@ pub use base as core;
 pub use base::*;
 pub use geometry::*;
 pub use linalg::*;
+#[cfg(feature = "sparse")]
+pub use sparse::*;
 
 use std::cmp::{self, Ordering, PartialOrd};
 
 use alga::general::{
-    Additive, AdditiveGroup, Identity, Inverse, JoinSemilattice, Lattice, MeetSemilattice,
+    Additive, AdditiveGroup, Identity, TwoSidedInverse, JoinSemilattice, Lattice, MeetSemilattice,
     Multiplicative, SupersetOf,
 };
 use alga::linear::SquareMatrix as AlgaSquareMatrix;
@@ -189,6 +203,12 @@ pub fn zero<T: Identity<Additive>>() -> T {
 ///
 /// * [`one`](fn.one.html)
 /// * [`zero`](fn.zero.html)
+///
+/// # Deprecated
+/// Use [Point::origin] instead.
+///
+/// Or, use [EuclideanSpace::origin](https://docs.rs/alga/0.7.2/alga/linear/trait.EuclideanSpace.html#tymethod.origin).
+#[deprecated(note = "use `Point::origin` instead")]
 #[inline]
 pub fn origin<P: EuclideanSpace>() -> P {
     P::origin()
@@ -275,6 +295,9 @@ pub fn min<T: Ord>(a: T, b: T) -> T {
 }
 
 /// The absolute value of `a`.
+///
+/// Deprecated: Use [Matrix::abs] or [Real::abs] instead.
+#[deprecated(note = "use `Matrix::abs` or `Real::abs` instead")]
 #[inline]
 pub fn abs<T: Signed>(a: &T) -> T {
     a.abs()
@@ -404,8 +427,8 @@ pub fn try_inverse<M: AlgaSquareMatrix>(m: &M) -> Option<M> {
 ///
 /// * [`try_inverse`](fn.try_inverse.html)
 #[inline]
-pub fn inverse<M: Inverse<Multiplicative>>(m: &M) -> M {
+pub fn inverse<M: TwoSidedInverse<Multiplicative>>(m: &M) -> M {
-    m.inverse()
+    m.two_sided_inverse()
 }
 
 /*
@@ -413,12 +436,26 @@ pub fn inverse<M: Inverse<Multiplicative>>(m: &M) -> M {
  */
 
 /// Computes the dot product of two vectors.
+///
+/// ## Deprecated
+/// Use these methods instead:
+///   - [Matrix::dot]
+///   - [Quaternion::dot]
+///
+/// Or, use [FiniteDimVectorSpace::dot](https://docs.rs/alga/0.7.2/alga/linear/trait.FiniteDimVectorSpace.html#tymethod.dot).
+#[deprecated(note = "use `Matrix::dot` or `Quaternion::dot` instead")]
 #[inline]
 pub fn dot<V: FiniteDimVectorSpace>(a: &V, b: &V) -> V::Field {
     a.dot(b)
 }
 
 /// Computes the smallest angle between two vectors.
+///
+/// ## Deprecated
+/// Use [Matrix::angle] instead.
+///
+/// Or, use [InnerSpace::angle](https://docs.rs/alga/0.7.2/alga/linear/trait.InnerSpace.html#method.angle).
+#[deprecated(note = "use `Matrix::angle` instead")]
 #[inline]
 pub fn angle<V: InnerSpace>(a: &V, b: &V) -> V::Real {
     a.angle(b)
@@ -435,6 +472,14 @@ pub fn angle<V: InnerSpace>(a: &V, b: &V) -> V::Real {
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude_squared`](fn.magnitude_squared.html)
 /// * [`norm_squared`](fn.norm_squared.html)
+///
+/// # Deprecated
+/// Use these methods instead:
+/// * [Matrix::norm]
+/// * [Quaternion::norm]
+///
+/// Or, use [NormedSpace::norm](https://docs.rs/alga/0.7.2/alga/linear/trait.NormedSpace.html#tymethod.norm).
+#[deprecated(note = "use `Matrix::norm` or `Quaternion::norm` instead")]
 #[inline]
 pub fn norm<V: NormedSpace>(v: &V) -> V::Field {
     v.norm()
@@ -447,6 +492,14 @@ pub fn norm<V: NormedSpace>(v: &V) -> V::Field {
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude_squared`](fn.magnitude_squared.html)
 /// * [`norm`](fn.norm.html)
+///
+/// # Deprecated
+/// Use these methods instead:
+/// * [Matrix::norm_squared]
+/// * [Quaternion::norm_squared]
+///
+/// Or, use [NormedSpace::norm_squared](https://docs.rs/alga/0.7.2/alga/linear/trait.NormedSpace.html#tymethod.norm_squared).
+#[deprecated(note = "use `Matrix::norm_squared` or `Quaternion::norm_squared` instead")]
 #[inline]
 pub fn norm_squared<V: NormedSpace>(v: &V) -> V::Field {
     v.norm_squared()
@@ -459,6 +512,14 @@ pub fn norm_squared<V: NormedSpace>(v: &V) -> V::Field {
 /// * [`magnitude_squared`](fn.magnitude_squared.html)
 /// * [`norm`](fn.norm.html)
 /// * [`norm_squared`](fn.norm_squared.html)
+///
+/// # Deprecated
+/// Use these methods instead:
+/// * [Matrix::magnitude]
+/// * [Quaternion::magnitude]
+///
+/// Or, use [NormedSpace::norm](https://docs.rs/alga/0.7.2/alga/linear/trait.NormedSpace.html#tymethod.norm).
+#[deprecated(note = "use `Matrix::magnitude` or `Quaternion::magnitude` instead")]
 #[inline]
 pub fn magnitude<V: NormedSpace>(v: &V) -> V::Field {
     v.norm()
@@ -472,18 +533,42 @@ pub fn magnitude<V: NormedSpace>(v: &V) -> V::Field {
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`norm`](fn.norm.html)
 /// * [`norm_squared`](fn.norm_squared.html)
+///
+/// # Deprecated
+/// Use these methods instead:
+/// * [Matrix::magnitude_squared]
+/// * [Quaternion::magnitude_squared]
+///
+/// Or, use [NormedSpace::norm_squared](https://docs.rs/alga/0.7.2/alga/linear/trait.NormedSpace.html#tymethod.norm_squared).
+#[deprecated(note = "use `Matrix::magnitude_squared` or `Quaternion::magnitude_squared` instead")]
 #[inline]
 pub fn magnitude_squared<V: NormedSpace>(v: &V) -> V::Field {
     v.norm_squared()
 }
 
 /// Computes the normalized version of the vector `v`.
+///
+/// # Deprecated
+/// Use these methods instead:
+/// * [Matrix::normalize]
+/// * [Quaternion::normalize]
+///
+/// Or, use [NormedSpace::normalize](https://docs.rs/alga/0.7.2/alga/linear/trait.NormedSpace.html#tymethod.normalize).
+#[deprecated(note = "use `Matrix::normalize` or `Quaternion::normalize` instead")]
 #[inline]
 pub fn normalize<V: NormedSpace>(v: &V) -> V {
     v.normalize()
 }
 
 /// Computes the normalized version of the vector `v` or returns `None` if its norm is smaller than `min_norm`.
+///
+/// # Deprecated
+/// Use these methods instead:
+/// * [Matrix::try_normalize]
+/// * [Quaternion::try_normalize]
+///
+/// Or, use [NormedSpace::try_normalize](https://docs.rs/alga/0.7.2/alga/linear/trait.NormedSpace.html#tymethod.try_normalize).
+#[deprecated(note = "use `Matrix::try_normalize` or `Quaternion::try_normalize` instead")]
 #[inline]
 pub fn try_normalize<V: NormedSpace>(v: &V, min_norm: V::Field) -> Option<V> {
     v.try_normalize(min_norm)

src/linalg/cholesky.rs

@@ -52,7 +52,7 @@ where DefaultAllocator: Allocator<N, D, D>
 
         for j in 0..n {
             for k in 0..j {
-                let factor = unsafe { -*matrix.get_unchecked(j, k) };
+                let factor = unsafe { -*matrix.get_unchecked((j, k)) };
 
                 let (mut col_j, col_k) = matrix.columns_range_pair_mut(j, k);
                 let mut col_j = col_j.rows_range_mut(j..);
@@ -61,11 +61,11 @@ where DefaultAllocator: Allocator<N, D, D>
                 col_j.axpy(factor, &col_k, N::one());
             }
 
-            let diag = unsafe { *matrix.get_unchecked(j, j) };
+            let diag = unsafe { *matrix.get_unchecked((j, j)) };
             if diag > N::zero() {
                 let denom = diag.sqrt();
                 unsafe {
-                    *matrix.get_unchecked_mut(j, j) = denom;
+                    *matrix.get_unchecked_mut((j, j)) = denom;
                 }
 
                 let mut col = matrix.slice_range_mut(j + 1.., j);

src/linalg/determinant.rs

@@ -23,27 +23,27 @@ impl<N: Real, D: DimMin<D, Output = D>, S: Storage<N, D, D>> SquareMatrix<N, D,
         unsafe {
             match dim {
                 0 => N::one(),
-                1 => *self.get_unchecked(0, 0),
+                1 => *self.get_unchecked((0, 0)),
                 2 => {
-                    let m11 = *self.get_unchecked(0, 0);
+                    let m11 = *self.get_unchecked((0, 0));
-                    let m12 = *self.get_unchecked(0, 1);
+                    let m12 = *self.get_unchecked((0, 1));
-                    let m21 = *self.get_unchecked(1, 0);
+                    let m21 = *self.get_unchecked((1, 0));
-                    let m22 = *self.get_unchecked(1, 1);
+                    let m22 = *self.get_unchecked((1, 1));
 
                     m11 * m22 - m21 * m12
                 }
                 3 => {
-                    let m11 = *self.get_unchecked(0, 0);
+                    let m11 = *self.get_unchecked((0, 0));
-                    let m12 = *self.get_unchecked(0, 1);
+                    let m12 = *self.get_unchecked((0, 1));
-                    let m13 = *self.get_unchecked(0, 2);
+                    let m13 = *self.get_unchecked((0, 2));
 
-                    let m21 = *self.get_unchecked(1, 0);
+                    let m21 = *self.get_unchecked((1, 0));
-                    let m22 = *self.get_unchecked(1, 1);
+                    let m22 = *self.get_unchecked((1, 1));
-                    let m23 = *self.get_unchecked(1, 2);
+                    let m23 = *self.get_unchecked((1, 2));
 
-                    let m31 = *self.get_unchecked(2, 0);
+                    let m31 = *self.get_unchecked((2, 0));
-                    let m32 = *self.get_unchecked(2, 1);
+                    let m32 = *self.get_unchecked((2, 1));
-                    let m33 = *self.get_unchecked(2, 2);
+                    let m33 = *self.get_unchecked((2, 2));
 
                     let minor_m12_m23 = m22 * m33 - m32 * m23;
                     let minor_m11_m23 = m21 * m33 - m31 * m23;

src/linalg/full_piv_lu.rs

@@ -251,7 +251,7 @@ where DefaultAllocator: Allocator<N, D, D> + Allocator<(usize, usize), D>
         let mut res = self.lu[(dim - 1, dim - 1)];
         if !res.is_zero() {
             for i in 0..dim - 1 {
-                res *= unsafe { *self.lu.get_unchecked(i, i) };
+                res *= unsafe { *self.lu.get_unchecked((i, i)) };
             }
 
             res * self.p.determinant() * self.q.determinant()

src/linalg/inverse.rs

@@ -35,46 +35,46 @@ impl<N: Real, D: Dim, S: StorageMut<N, D, D>> SquareMatrix<N, D, S> {
             match dim {
                 0 => true,
                 1 => {
-                    let determinant = self.get_unchecked(0, 0).clone();
+                    let determinant = self.get_unchecked((0, 0)).clone();
                     if determinant == N::zero() {
                         false
                     } else {
-                        *self.get_unchecked_mut(0, 0) = N::one() / determinant;
+                        *self.get_unchecked_mut((0, 0)) = N::one() / determinant;
                         true
                     }
                 }
                 2 => {
-                    let m11 = *self.get_unchecked(0, 0);
+                    let m11 = *self.get_unchecked((0, 0));
-                    let m12 = *self.get_unchecked(0, 1);
+                    let m12 = *self.get_unchecked((0, 1));
-                    let m21 = *self.get_unchecked(1, 0);
+                    let m21 = *self.get_unchecked((1, 0));
-                    let m22 = *self.get_unchecked(1, 1);
+                    let m22 = *self.get_unchecked((1, 1));
 
                     let determinant = m11 * m22 - m21 * m12;
 
                     if determinant == N::zero() {
                         false
                     } else {
-                        *self.get_unchecked_mut(0, 0) = m22 / determinant;
+                        *self.get_unchecked_mut((0, 0)) = m22 / determinant;
-                        *self.get_unchecked_mut(0, 1) = -m12 / determinant;
+                        *self.get_unchecked_mut((0, 1)) = -m12 / determinant;
 
-                        *self.get_unchecked_mut(1, 0) = -m21 / determinant;
+                        *self.get_unchecked_mut((1, 0)) = -m21 / determinant;
-                        *self.get_unchecked_mut(1, 1) = m11 / determinant;
+                        *self.get_unchecked_mut((1, 1)) = m11 / determinant;
 
                         true
                     }
                 }
                 3 => {
-                    let m11 = *self.get_unchecked(0, 0);
+                    let m11 = *self.get_unchecked((0, 0));
-                    let m12 = *self.get_unchecked(0, 1);
+                    let m12 = *self.get_unchecked((0, 1));
-                    let m13 = *self.get_unchecked(0, 2);
+                    let m13 = *self.get_unchecked((0, 2));
 
-                    let m21 = *self.get_unchecked(1, 0);
+                    let m21 = *self.get_unchecked((1, 0));
-                    let m22 = *self.get_unchecked(1, 1);
+                    let m22 = *self.get_unchecked((1, 1));
-                    let m23 = *self.get_unchecked(1, 2);
+                    let m23 = *self.get_unchecked((1, 2));
 
-                    let m31 = *self.get_unchecked(2, 0);
+                    let m31 = *self.get_unchecked((2, 0));
-                    let m32 = *self.get_unchecked(2, 1);
+                    let m32 = *self.get_unchecked((2, 1));
-                    let m33 = *self.get_unchecked(2, 2);
+                    let m33 = *self.get_unchecked((2, 2));
 
                     let minor_m12_m23 = m22 * m33 - m32 * m23;
                     let minor_m11_m23 = m21 * m33 - m31 * m23;
@@ -86,17 +86,17 @@ impl<N: Real, D: Dim, S: StorageMut<N, D, D>> SquareMatrix<N, D, S> {
                     if determinant == N::zero() {
                         false
                     } else {
-                        *self.get_unchecked_mut(0, 0) = minor_m12_m23 / determinant;
+                        *self.get_unchecked_mut((0, 0)) = minor_m12_m23 / determinant;
-                        *self.get_unchecked_mut(0, 1) = (m13 * m32 - m33 * m12) / determinant;
+                        *self.get_unchecked_mut((0, 1)) = (m13 * m32 - m33 * m12) / determinant;
-                        *self.get_unchecked_mut(0, 2) = (m12 * m23 - m22 * m13) / determinant;
+                        *self.get_unchecked_mut((0, 2)) = (m12 * m23 - m22 * m13) / determinant;
 
-                        *self.get_unchecked_mut(1, 0) = -minor_m11_m23 / determinant;
+                        *self.get_unchecked_mut((1, 0)) = -minor_m11_m23 / determinant;
-                        *self.get_unchecked_mut(1, 1) = (m11 * m33 - m31 * m13) / determinant;
+                        *self.get_unchecked_mut((1, 1)) = (m11 * m33 - m31 * m13) / determinant;
-                        *self.get_unchecked_mut(1, 2) = (m13 * m21 - m23 * m11) / determinant;
+                        *self.get_unchecked_mut((1, 2)) = (m13 * m21 - m23 * m11) / determinant;
 
-                        *self.get_unchecked_mut(2, 0) = minor_m11_m22 / determinant;
+                        *self.get_unchecked_mut((2, 0)) = minor_m11_m22 / determinant;
-                        *self.get_unchecked_mut(2, 1) = (m12 * m31 - m32 * m11) / determinant;
+                        *self.get_unchecked_mut((2, 1)) = (m12 * m31 - m32 * m11) / determinant;
-                        *self.get_unchecked_mut(2, 2) = (m11 * m22 - m21 * m12) / determinant;
+                        *self.get_unchecked_mut((2, 2)) = (m11 * m22 - m21 * m12) / determinant;
 
                         true
                     }

src/linalg/lu.rs

@@ -290,7 +290,7 @@ where DefaultAllocator: Allocator<N, D, D> + Allocator<(usize, usize), D>
 
         let mut res = N::one();
         for i in 0..dim {
-            res *= unsafe { *self.lu.get_unchecked(i, i) };
+            res *= unsafe { *self.lu.get_unchecked((i, i)) };
         }
 
         res * self.p.determinant()

src/linalg/schur.rs

@@ -412,7 +412,7 @@ where
             rot.rotate_rows(&mut m);
 
             if compute_q {
-                let c = rot.unwrap();
+                let c = rot.into_inner();
                 // XXX: we have to build the matrix manually because
                 // rot.to_rotation_matrix().unwrap() causes an ICE.
                 q = Some(MatrixN::from_column_slice_generic(

src/linalg/solve.rs

@@ -79,7 +79,7 @@ impl<N: Real, D: Dim, S: Storage<N, D, D>> SquareMatrix<N, D, S> {
             let coeff;
 
             unsafe {
-                let diag = *self.get_unchecked(i, i);
+                let diag = *self.get_unchecked((i, i));
 
                 if diag.is_zero() {
                     return false;
@@ -161,7 +161,7 @@ impl<N: Real, D: Dim, S: Storage<N, D, D>> SquareMatrix<N, D, S> {
             let coeff;
 
             unsafe {
-                let diag = *self.get_unchecked(i, i);
+                let diag = *self.get_unchecked((i, i));
 
                 if diag.is_zero() {
                     return false;
@@ -258,7 +258,7 @@ impl<N: Real, D: Dim, S: Storage<N, D, D>> SquareMatrix<N, D, S> {
             unsafe {
                 let b_i = b.vget_unchecked_mut(i);
 
-                let diag = *self.get_unchecked(i, i);
+                let diag = *self.get_unchecked((i, i));
 
                 if diag.is_zero() {
                     return false;
@@ -304,7 +304,7 @@ impl<N: Real, D: Dim, S: Storage<N, D, D>> SquareMatrix<N, D, S> {
 
             unsafe {
                 let b_i = b.vget_unchecked_mut(i);
-                let diag = *self.get_unchecked(i, i);
+                let diag = *self.get_unchecked((i, i));
 
                 if diag.is_zero() {
                     return false;

src/linalg/svd.rs

@@ -484,90 +484,94 @@ where
 
     /// Rebuild the original matrix.
     ///
-    /// This is useful if some of the singular values have been manually modified.  Panics if the
+    /// This is useful if some of the singular values have been manually modified.
-    /// right- and left- singular vectors have not been computed at construction-time.
+    /// Returns `Err` if the right- and left- singular vectors have not been
-    pub fn recompose(self) -> MatrixMN<N, R, C> {
+    /// computed at construction-time.
-        let mut u = self.u.expect("SVD recomposition: U has not been computed.");
+    pub fn recompose(self) -> Result<MatrixMN<N, R, C>, &'static str> {
-        let v_t = self
+        match (self.u, self.v_t) {
-            .v_t
+            (Some(mut u), Some(v_t)) => {
-            .expect("SVD recomposition: V^t has not been computed.");
+                for i in 0..self.singular_values.len() {
-
+                    let val = self.singular_values[i];
-        for i in 0..self.singular_values.len() {
+                    u.column_mut(i).mul_assign(val);
-            let val = self.singular_values[i];
+                }
-            u.column_mut(i).mul_assign(val);
+                Ok(u * v_t)
+            }
+            (None, None) => Err("SVD recomposition: U and V^t have not been computed."),
+            (None, _) => Err("SVD recomposition: U has not been computed."),
+            (_, None) => Err("SVD recomposition: V^t has not been computed.")
         }
-
-        u * v_t
     }
 
     /// Computes the pseudo-inverse of the decomposed matrix.
     ///
     /// Any singular value smaller than `eps` is assumed to be zero.
-    /// Panics if the right- and left- singular vectors have not been computed at
+    /// Returns `Err` if the right- and left- singular vectors have not
-    /// construction-time.
+    /// been computed at construction-time.
-    pub fn pseudo_inverse(mut self, eps: N) -> MatrixMN<N, C, R>
+    pub fn pseudo_inverse(mut self, eps: N) -> Result<MatrixMN<N, C, R>, &'static str>
-    where DefaultAllocator: Allocator<N, C, R> {
+    where
-        assert!(
+        DefaultAllocator: Allocator<N, C, R>,
-            eps >= N::zero(),
+    {
-            "SVD pseudo inverse: the epsilon must be non-negative."
+        if eps < N::zero() {
-        );
+            Err("SVD pseudo inverse: the epsilon must be non-negative.")
-        for i in 0..self.singular_values.len() {
-            let val = self.singular_values[i];
-
-            if val > eps {
-                self.singular_values[i] = N::one() / val;
-            } else {
-                self.singular_values[i] = N::zero();
-            }
         }
+        else {
+            for i in 0..self.singular_values.len() {
+                let val = self.singular_values[i];
 
-        self.recompose().transpose()
+                if val > eps {
+                    self.singular_values[i] = N::one() / val;
+                } else {
+                    self.singular_values[i] = N::zero();
+                }
+            }
+
+            self.recompose().map(|m| m.transpose())
+        }
     }
 
     /// Solves the system `self * x = b` where `self` is the decomposed matrix and `x` the unknown.
     ///
     /// Any singular value smaller than `eps` is assumed to be zero.
-    /// Returns `None` if the singular vectors `U` and `V` have not been computed.
+    /// Returns `Err` if the singular vectors `U` and `V` have not been computed.
     // FIXME: make this more generic wrt the storage types and the dimensions for `b`.
     pub fn solve<R2: Dim, C2: Dim, S2>(
         &self,
         b: &Matrix<N, R2, C2, S2>,
         eps: N,
-    ) -> MatrixMN<N, C, C2>
+    ) -> Result<MatrixMN<N, C, C2>, &'static str>
     where
         S2: Storage<N, R2, C2>,
         DefaultAllocator: Allocator<N, C, C2> + Allocator<N, DimMinimum<R, C>, C2>,
         ShapeConstraint: SameNumberOfRows<R, R2>,
     {
-        assert!(
+        if eps < N::zero() {
-            eps >= N::zero(),
+            Err("SVD solve: the epsilon must be non-negative.")
-            "SVD solve: the epsilon must be non-negative."
+        }
-        );
+        else {
-        let u = self
+            match (&self.u, &self.v_t) {
-            .u
+                (Some(u), Some(v_t)) => {
-            .as_ref()
+                    let mut ut_b = u.tr_mul(b);
-            .expect("SVD solve: U has not been computed.");
-        let v_t = self
-            .v_t
-            .as_ref()
-            .expect("SVD solve: V^t has not been computed.");
 
-        let mut ut_b = u.tr_mul(b);
+                    for j in 0..ut_b.ncols() {
+                        let mut col = ut_b.column_mut(j);
 
-        for j in 0..ut_b.ncols() {
+                        for i in 0..self.singular_values.len() {
-            let mut col = ut_b.column_mut(j);
+                            let val = self.singular_values[i];
+                            if val > eps {
+                                col[i] /= val;
+                            } else {
+                                col[i] = N::zero();
+                            }
+                        }
+                    }
 
-            for i in 0..self.singular_values.len() {
+                    Ok(v_t.tr_mul(&ut_b))
-                let val = self.singular_values[i];
-                if val > eps {
-                    col[i] /= val;
-                } else {
-                    col[i] = N::zero();
                 }
+                (None, None) => Err("SVD solve: U and V^t have not been computed."),
+                (None, _) => Err("SVD solve: U has not been computed."),
+                (_, None) => Err("SVD solve: V^t has not been computed.")
             }
         }
-
-        v_t.tr_mul(&ut_b)
     }
 }
 
@@ -624,8 +628,10 @@ where
     /// Computes the pseudo-inverse of this matrix.
     ///
     /// All singular values below `eps` are considered equal to 0.
-    pub fn pseudo_inverse(self, eps: N) -> MatrixMN<N, C, R>
+    pub fn pseudo_inverse(self, eps: N) -> Result<MatrixMN<N, C, R>, &'static str>
-    where DefaultAllocator: Allocator<N, C, R> {
+    where
+        DefaultAllocator: Allocator<N, C, R>,
+    {
         SVD::new(self.clone_owned(), true, true).pseudo_inverse(eps)
     }
 }

src/sparse/cs_matrix.rs

@@ -0,0 +1,517 @@
+use alga::general::ClosedAdd;
+use num::Zero;
+use std::iter;
+use std::marker::PhantomData;
+use std::ops::Range;
+use std::slice;
+
+use allocator::Allocator;
+use sparse::cs_utils;
+use {
+    DefaultAllocator, Dim, Dynamic, Scalar, Vector, VectorN, U1
+};
+
+pub struct ColumnEntries<'a, N> {
+    curr: usize,
+    i: &'a [usize],
+    v: &'a [N],
+}
+
+impl<'a, N> ColumnEntries<'a, N> {
+    #[inline]
+    pub fn new(i: &'a [usize], v: &'a [N]) -> Self {
+        assert_eq!(i.len(), v.len());
+        ColumnEntries { curr: 0, i, v }
+    }
+}
+
+impl<'a, N: Copy> Iterator for ColumnEntries<'a, N> {
+    type Item = (usize, N);
+
+    #[inline]
+    fn next(&mut self) -> Option<(usize, N)> {
+        if self.curr >= self.i.len() {
+            None
+        } else {
+            let res = Some((unsafe { *self.i.get_unchecked(self.curr) }, unsafe {
+                *self.v.get_unchecked(self.curr)
+            }));
+            self.curr += 1;
+            res
+        }
+    }
+}
+
+// FIXME: this structure exists for now only because impl trait
+// cannot be used for trait method return types.
+/// Trait for iterable compressed-column matrix storage.
+pub trait CsStorageIter<'a, N, R, C = U1> {
+    /// Iterator through all the rows of a specific columns.
+    ///
+    /// The elements are given as a tuple (row_index, value).
+    type ColumnEntries: Iterator<Item = (usize, N)>;
+    /// Iterator through the row indices of a specific column.
+    type ColumnRowIndices: Iterator<Item = usize>;
+
+    /// Iterates through all the row indices of the j-th column.
+    fn column_row_indices(&'a self, j: usize) -> Self::ColumnRowIndices;
+    #[inline(always)]
+    /// Iterates through all the entries of the j-th column.
+    fn column_entries(&'a self, j: usize) -> Self::ColumnEntries;
+}
+
+/// Trait for mutably iterable compressed-column sparse matrix storage.
+pub trait CsStorageIterMut<'a, N: 'a, R, C = U1> {
+    /// Mutable iterator through all the values of the sparse matrix.
+    type ValuesMut: Iterator<Item = &'a mut N>;
+    /// Mutable iterator through all the rows of a specific columns.
+    ///
+    /// The elements are given as a tuple (row_index, value).
+    type ColumnEntriesMut: Iterator<Item = (usize, &'a mut N)>;
+
+    /// A mutable iterator through the values buffer of the sparse matrix.
+    fn values_mut(&'a mut self) -> Self::ValuesMut;
+    /// Iterates mutably through all the entries of the j-th column.
+    fn column_entries_mut(&'a mut self, j: usize) -> Self::ColumnEntriesMut;
+}
+
+/// Trait for compressed column sparse matrix storage.
+pub trait CsStorage<N, R, C = U1>: for<'a> CsStorageIter<'a, N, R, C> {
+    /// The shape of the stored matrix.
+    fn shape(&self) -> (R, C);
+    /// Retrieve the i-th row index of the underlying row index buffer.
+    ///
+    /// No bound-checking is performed.
+    unsafe fn row_index_unchecked(&self, i: usize) -> usize;
+    /// The i-th value on the contiguous value buffer of this storage.
+    ///
+    /// No bound-checking is performed.
+    unsafe fn get_value_unchecked(&self, i: usize) -> &N;
+    /// The i-th value on the contiguous value buffer of this storage.
+    fn get_value(&self, i: usize) -> &N;
+    /// Retrieve the i-th row index of the underlying row index buffer.
+    fn row_index(&self, i: usize) -> usize;
+    /// The value indices for the `i`-th column.
+    fn column_range(&self, i: usize) -> Range<usize>;
+    /// The size of the value buffer (i.e. the entries known as possibly being non-zero).
+    fn len(&self) -> usize;
+}
+
+/// Trait for compressed column sparse matrix mutable storage.
+pub trait CsStorageMut<N, R, C = U1>:
+    CsStorage<N, R, C> + for<'a> CsStorageIterMut<'a, N, R, C>
+{
+}
+
+/// A storage of column-compressed sparse matrix based on a Vec.
+#[derive(Clone, Debug, PartialEq)]
+pub struct CsVecStorage<N: Scalar, R: Dim, C: Dim>
+where DefaultAllocator: Allocator<usize, C>
+{
+    pub(crate) shape: (R, C),
+    pub(crate) p: VectorN<usize, C>,
+    pub(crate) i: Vec<usize>,
+    pub(crate) vals: Vec<N>,
+}
+
+impl<N: Scalar, R: Dim, C: Dim> CsVecStorage<N, R, C>
+where DefaultAllocator: Allocator<usize, C>
+{
+    /// The value buffer of this storage.
+    pub fn values(&self) -> &[N] {
+        &self.vals
+    }
+
+    /// The column shifts buffer.
+    pub fn p(&self) -> &[usize] {
+        self.p.as_slice()
+    }
+
+    /// The row index buffers.
+    pub fn i(&self) -> &[usize] {
+        &self.i
+    }
+}
+
+impl<N: Scalar, R: Dim, C: Dim> CsVecStorage<N, R, C> where DefaultAllocator: Allocator<usize, C> {}
+
+impl<'a, N: Scalar, R: Dim, C: Dim> CsStorageIter<'a, N, R, C> for CsVecStorage<N, R, C>
+where DefaultAllocator: Allocator<usize, C>
+{
+    type ColumnEntries = ColumnEntries<'a, N>;
+    type ColumnRowIndices = iter::Cloned<slice::Iter<'a, usize>>;
+
+    #[inline]
+    fn column_entries(&'a self, j: usize) -> Self::ColumnEntries {
+        let rng = self.column_range(j);
+        ColumnEntries::new(&self.i[rng.clone()], &self.vals[rng])
+    }
+
+    #[inline]
+    fn column_row_indices(&'a self, j: usize) -> Self::ColumnRowIndices {
+        let rng = self.column_range(j);
+        self.i[rng.clone()].iter().cloned()
+    }
+}
+
+impl<N: Scalar, R: Dim, C: Dim> CsStorage<N, R, C> for CsVecStorage<N, R, C>
+where DefaultAllocator: Allocator<usize, C>
+{
+    #[inline]
+    fn shape(&self) -> (R, C) {
+        self.shape
+    }
+
+    #[inline]
+    fn len(&self) -> usize {
+        self.vals.len()
+    }
+
+    #[inline]
+    fn row_index(&self, i: usize) -> usize {
+        self.i[i]
+    }
+
+    #[inline]
+    unsafe fn row_index_unchecked(&self, i: usize) -> usize {
+        *self.i.get_unchecked(i)
+    }
+
+    #[inline]
+    unsafe fn get_value_unchecked(&self, i: usize) -> &N {
+        self.vals.get_unchecked(i)
+    }
+
+    #[inline]
+    fn get_value(&self, i: usize) -> &N {
+        &self.vals[i]
+    }
+
+    #[inline]
+    fn column_range(&self, j: usize) -> Range<usize> {
+        let end = if j + 1 == self.p.len() {
+            self.len()
+        } else {
+            self.p[j + 1]
+        };
+
+        self.p[j]..end
+    }
+}
+
+impl<'a, N: Scalar, R: Dim, C: Dim> CsStorageIterMut<'a, N, R, C> for CsVecStorage<N, R, C>
+where DefaultAllocator: Allocator<usize, C>
+{
+    type ValuesMut = slice::IterMut<'a, N>;
+    type ColumnEntriesMut = iter::Zip<iter::Cloned<slice::Iter<'a, usize>>, slice::IterMut<'a, N>>;
+
+    #[inline]
+    fn values_mut(&'a mut self) -> Self::ValuesMut {
+        self.vals.iter_mut()
+    }
+
+    #[inline]
+    fn column_entries_mut(&'a mut self, j: usize) -> Self::ColumnEntriesMut {
+        let rng = self.column_range(j);
+        self.i[rng.clone()]
+            .iter()
+            .cloned()
+            .zip(self.vals[rng].iter_mut())
+    }
+}
+
+impl<N: Scalar, R: Dim, C: Dim> CsStorageMut<N, R, C> for CsVecStorage<N, R, C> where DefaultAllocator: Allocator<usize, C>
+{}
+
+/*
+pub struct CsSliceStorage<'a, N: Scalar, R: Dim, C: DimAdd<U1>> {
+    shape: (R, C),
+    p: VectorSlice<usize, DimSum<C, U1>>,
+    i: VectorSlice<usize, Dynamic>,
+    vals: VectorSlice<N, Dynamic>,
+}*/
+
+/// A compressed sparse column matrix.
+#[derive(Clone, Debug, PartialEq)]
+pub struct CsMatrix<
+    N: Scalar,
+    R: Dim = Dynamic,
+    C: Dim = Dynamic,
+    S: CsStorage<N, R, C> = CsVecStorage<N, R, C>,
+> {
+    pub(crate) data: S,
+    _phantoms: PhantomData<(N, R, C)>,
+}
+
+/// A column compressed sparse vector.
+pub type CsVector<N, R = Dynamic, S = CsVecStorage<N, R, U1>> = CsMatrix<N, R, U1, S>;
+
+impl<N: Scalar, R: Dim, C: Dim> CsMatrix<N, R, C>
+where DefaultAllocator: Allocator<usize, C>
+{
+    /// Creates a new compressed sparse column matrix with the specified dimension and
+    /// `nvals` possible non-zero values.
+    pub fn new_uninitialized_generic(nrows: R, ncols: C, nvals: usize) -> Self {
+        let mut i = Vec::with_capacity(nvals);
+        unsafe {
+            i.set_len(nvals);
+        }
+        i.shrink_to_fit();
+
+        let mut vals = Vec::with_capacity(nvals);
+        unsafe {
+            vals.set_len(nvals);
+        }
+        vals.shrink_to_fit();
+
+        CsMatrix {
+            data: CsVecStorage {
+                shape: (nrows, ncols),
+                p: VectorN::zeros_generic(ncols, U1),
+                i,
+                vals,
+            },
+            _phantoms: PhantomData,
+        }
+    }
+
+    /*
+    pub(crate) fn from_parts_generic(
+        nrows: R,
+        ncols: C,
+        p: VectorN<usize, C>,
+        i: Vec<usize>,
+        vals: Vec<N>,
+    ) -> Self
+    where
+        N: Zero + ClosedAdd,
+        DefaultAllocator: Allocator<N, R>,
+    {
+        assert_eq!(ncols.value(), p.len(), "Invalid inptr size.");
+        assert_eq!(i.len(), vals.len(), "Invalid value size.");
+
+        // Check p.
+        for ptr in &p {
+            assert!(*ptr < i.len(), "Invalid inptr value.");
+        }
+
+        for ptr in p.as_slice().windows(2) {
+            assert!(ptr[0] <= ptr[1], "Invalid inptr ordering.");
+        }
+
+        // Check i.
+        for i in &i {
+            assert!(*i < nrows.value(), "Invalid row ptr value.")
+        }
+
+        let mut res = CsMatrix {
+            data: CsVecStorage {
+                shape: (nrows, ncols),
+                p,
+                i,
+                vals,
+            },
+            _phantoms: PhantomData,
+        };
+
+        // Sort and remove duplicates.
+        res.sort();
+        res.dedup();
+
+        res
+    }*/
+}
+
+/*
+impl<N: Scalar + Zero + ClosedAdd> CsMatrix<N> {
+    pub(crate) fn from_parts(
+        nrows: usize,
+        ncols: usize,
+        p: Vec<usize>,
+        i: Vec<usize>,
+        vals: Vec<N>,
+    ) -> Self
+    {
+        let nrows = Dynamic::new(nrows);
+        let ncols = Dynamic::new(ncols);
+        let p = DVector::from_data(VecStorage::new(ncols, U1, p));
+        Self::from_parts_generic(nrows, ncols, p, i, vals)
+    }
+}
+*/
+
+impl<N: Scalar, R: Dim, C: Dim, S: CsStorage<N, R, C>> CsMatrix<N, R, C, S> {
+    pub(crate) fn from_data(data: S) -> Self {
+        CsMatrix {
+            data,
+            _phantoms: PhantomData,
+        }
+    }
+
+    /// The size of the data buffer.
+    pub fn len(&self) -> usize {
+        self.data.len()
+    }
+
+    /// The number of rows of this matrix.
+    pub fn nrows(&self) -> usize {
+        self.data.shape().0.value()
+    }
+
+    /// The number of rows of this matrix.
+    pub fn ncols(&self) -> usize {
+        self.data.shape().1.value()
+    }
+
+    /// The shape of this matrix.
+    pub fn shape(&self) -> (usize, usize) {
+        let (nrows, ncols) = self.data.shape();
+        (nrows.value(), ncols.value())
+    }
+
+    /// Whether this matrix is square or not.
+    pub fn is_square(&self) -> bool {
+        let (nrows, ncols) = self.data.shape();
+        nrows.value() == ncols.value()
+    }
+
+    /// Should always return `true`.
+    ///
+    /// This method is generally used for debugging and should typically not be called in user code.
+    /// This checks that the row inner indices of this matrix are sorted. It takes `O(n)` time,
+    /// where n` is `self.len()`.
+    /// All operations of CSC matrices on nalgebra assume, and will return, sorted indices.
+    /// If at any time this `is_sorted` method returns `false`, then, something went wrong
+    /// and an issue should be open on the nalgebra repository with details on how to reproduce
+    /// this.
+    pub fn is_sorted(&self) -> bool {
+        for j in 0..self.ncols() {
+            let mut curr = None;
+            for idx in self.data.column_row_indices(j) {
+                if let Some(curr) = curr {
+                    if idx <= curr {
+                        return false;
+                    }
+                }
+
+                curr = Some(idx);
+            }
+        }
+
+        true
+    }
+
+    /// Computes the transpose of this sparse matrix.
+    pub fn transpose(&self) -> CsMatrix<N, C, R>
+    where DefaultAllocator: Allocator<usize, R> {
+        let (nrows, ncols) = self.data.shape();
+
+        let nvals = self.len();
+        let mut res = CsMatrix::new_uninitialized_generic(ncols, nrows, nvals);
+        let mut workspace = Vector::zeros_generic(nrows, U1);
+
+        // Compute p.
+        for i in 0..nvals {
+            let row_id = self.data.row_index(i);
+            workspace[row_id] += 1;
+        }
+
+        let _ = cs_utils::cumsum(&mut workspace, &mut res.data.p);
+
+        // Fill the result.
+        for j in 0..ncols.value() {
+            for (row_id, value) in self.data.column_entries(j) {
+                let shift = workspace[row_id];
+
+                res.data.vals[shift] = value;
+                res.data.i[shift] = j;
+                workspace[row_id] += 1;
+            }
+        }
+
+        res
+    }
+}
+
+impl<N: Scalar, R: Dim, C: Dim, S: CsStorageMut<N, R, C>> CsMatrix<N, R, C, S> {
+    /// Iterator through all the mutable values of this sparse matrix.
+    #[inline]
+    pub fn values_mut(&mut self) -> impl Iterator<Item = &mut N> {
+        self.data.values_mut()
+    }
+}
+
+impl<N: Scalar, R: Dim, C: Dim> CsMatrix<N, R, C>
+where DefaultAllocator: Allocator<usize, C>
+{
+    pub(crate) fn sort(&mut self)
+    where DefaultAllocator: Allocator<N, R> {
+        // Size = R
+        let nrows = self.data.shape().0;
+        let mut workspace = unsafe { VectorN::new_uninitialized_generic(nrows, U1) };
+        self.sort_with_workspace(workspace.as_mut_slice());
+    }
+
+    pub(crate) fn sort_with_workspace(&mut self, workspace: &mut [N]) {
+        assert!(
+            workspace.len() >= self.nrows(),
+            "Workspace must be able to hold at least self.nrows() elements."
+        );
+
+        for j in 0..self.ncols() {
+            // Scatter the row in the workspace.
+            for (irow, val) in self.data.column_entries(j) {
+                workspace[irow] = val;
+            }
+
+            // Sort the index vector.
+            let range = self.data.column_range(j);
+            self.data.i[range.clone()].sort();
+
+            // Permute the values too.
+            for (i, irow) in range.clone().zip(self.data.i[range].iter().cloned()) {
+                self.data.vals[i] = workspace[irow];
+            }
+        }
+    }
+
+    // Remove dupliate entries on a sorted CsMatrix.
+    pub(crate) fn dedup(&mut self)
+    where N: Zero + ClosedAdd {
+        let mut curr_i = 0;
+
+        for j in 0..self.ncols() {
+            let range = self.data.column_range(j);
+            self.data.p[j] = curr_i;
+
+            if range.start != range.end {
+                let mut value = N::zero();
+                let mut irow = self.data.i[range.start];
+
+                for idx in range {
+                    let curr_irow = self.data.i[idx];
+
+                    if curr_irow == irow {
+                        value += self.data.vals[idx];
+                    } else {
+                        self.data.i[curr_i] = irow;
+                        self.data.vals[curr_i] = value;
+                        value = self.data.vals[idx];
+                        irow = curr_irow;
+                        curr_i += 1;
+                    }
+                }
+
+                // Handle the last entry.
+                self.data.i[curr_i] = irow;
+                self.data.vals[curr_i] = value;
+                curr_i += 1;
+            }
+        }
+
+        self.data.i.truncate(curr_i);
+        self.data.i.shrink_to_fit();
+        self.data.vals.truncate(curr_i);
+        self.data.vals.shrink_to_fit();
+    }
+}

src/sparse/cs_matrix_cholesky.rs

@@ -0,0 +1,408 @@
+use std::iter;
+use std::mem;
+
+use allocator::Allocator;
+use sparse::{CsMatrix, CsStorage, CsStorageIter, CsStorageIterMut, CsVecStorage};
+use {DefaultAllocator, Dim, Real, VectorN, U1};
+
+/// The cholesky decomposition of a column compressed sparse matrix.
+pub struct CsCholesky<N: Real, D: Dim>
+where DefaultAllocator: Allocator<usize, D> + Allocator<N, D>
+{
+    // Non-zero pattern of the original matrix upper-triangular part.
+    // Unlike the original matrix, the `original_p` array does contain the last sentinel value
+    // equal to `original_i.len()` at the end.
+    original_p: Vec<usize>,
+    original_i: Vec<usize>,
+    // Decomposition result.
+    l: CsMatrix<N, D, D>,
+    // Used only for the pattern.
+    // FIXME: store only the nonzero pattern instead.
+    u: CsMatrix<N, D, D>,
+    ok: bool,
+    // Workspaces.
+    work_x: VectorN<N, D>,
+    work_c: VectorN<usize, D>,
+}
+
+impl<N: Real, D: Dim> CsCholesky<N, D>
+where DefaultAllocator: Allocator<usize, D> + Allocator<N, D>
+{
+    /// Computes the cholesky decomposition of the sparse matrix `m`.
+    pub fn new(m: &CsMatrix<N, D, D>) -> Self {
+        let mut me = Self::new_symbolic(m);
+        let _ = me.decompose_left_looking(&m.data.vals);
+        me
+    }
+    /// Perform symbolic analysis for the given matrix.
+    ///
+    /// This does not access the numerical values of `m`.
+    pub fn new_symbolic(m: &CsMatrix<N, D, D>) -> Self {
+        assert!(
+            m.is_square(),
+            "The matrix `m` must be square to compute its elimination tree."
+        );
+
+        let (l, u) = Self::nonzero_pattern(m);
+
+        // Workspaces.
+        let work_x = unsafe { VectorN::new_uninitialized_generic(m.data.shape().0, U1) };
+        let work_c = unsafe { VectorN::new_uninitialized_generic(m.data.shape().1, U1) };
+        let mut original_p = m.data.p.as_slice().to_vec();
+        original_p.push(m.data.i.len());
+
+        CsCholesky {
+            original_p,
+            original_i: m.data.i.clone(),
+            l,
+            u,
+            ok: false,
+            work_x,
+            work_c,
+        }
+    }
+
+    /// The lower-triangular matrix of the cholesky decomposition.
+    pub fn l(&self) -> Option<&CsMatrix<N, D, D>> {
+        if self.ok {
+            Some(&self.l)
+        } else {
+            None
+        }
+    }
+
+    /// Extracts the lower-triangular matrix of the cholesky decomposition.
+    pub fn unwrap_l(self) -> Option<CsMatrix<N, D, D>> {
+        if self.ok {
+            Some(self.l)
+        } else {
+            None
+        }
+    }
+
+    /// Perform a numerical left-looking cholesky decomposition of a matrix with the same structure as the
+    /// one used to initialize `self`, but with different non-zero values provided by `values`.
+    pub fn decompose_left_looking(&mut self, values: &[N]) -> bool {
+        assert!(
+            values.len() >= self.original_i.len(),
+            "The set of values is too small."
+        );
+
+        let n = self.l.nrows();
+
+        // Reset `work_c` to the column pointers of `l`.
+        self.work_c.copy_from(&self.l.data.p);
+
+        unsafe {
+            for k in 0..n {
+                // Scatter the k-th column of the original matrix with the values provided.
+                let range_k =
+                    *self.original_p.get_unchecked(k)..*self.original_p.get_unchecked(k + 1);
+
+                *self.work_x.vget_unchecked_mut(k) = N::zero();
+                for p in range_k.clone() {
+                    let irow = *self.original_i.get_unchecked(p);
+
+                    if irow >= k {
+                        *self.work_x.vget_unchecked_mut(irow) = *values.get_unchecked(p);
+                    }
+                }
+
+                for j in self.u.data.column_row_indices(k) {
+                    let factor = -*self
+                        .l
+                        .data
+                        .vals
+                        .get_unchecked(*self.work_c.vget_unchecked(j));
+                    *self.work_c.vget_unchecked_mut(j) += 1;
+
+                    if j < k {
+                        for (z, val) in self.l.data.column_entries(j) {
+                            if z >= k {
+                                *self.work_x.vget_unchecked_mut(z) += val * factor;
+                            }
+                        }
+                    }
+                }
+
+                let diag = *self.work_x.vget_unchecked(k);
+
+                if diag > N::zero() {
+                    let denom = diag.sqrt();
+                    *self
+                        .l
+                        .data
+                        .vals
+                        .get_unchecked_mut(*self.l.data.p.vget_unchecked(k)) = denom;
+
+                    for (p, val) in self.l.data.column_entries_mut(k) {
+                        *val = *self.work_x.vget_unchecked(p) / denom;
+                        *self.work_x.vget_unchecked_mut(p) = N::zero();
+                    }
+                } else {
+                    self.ok = false;
+                    return false;
+                }
+            }
+        }
+
+        self.ok = true;
+        true
+    }
+
+    /// Perform a numerical up-looking cholesky decomposition of a matrix with the same structure as the
+    /// one used to initialize `self`, but with different non-zero values provided by `values`.
+    pub fn decompose_up_looking(&mut self, values: &[N]) -> bool {
+        assert!(
+            values.len() >= self.original_i.len(),
+            "The set of values is too small."
+        );
+
+        // Reset `work_c` to the column pointers of `l`.
+        self.work_c.copy_from(&self.l.data.p);
+
+        // Perform the decomposition.
+        for k in 0..self.l.nrows() {
+            unsafe {
+                // Scatter the k-th column of the original matrix with the values provided.
+                let column_range =
+                    *self.original_p.get_unchecked(k)..*self.original_p.get_unchecked(k + 1);
+
+                *self.work_x.vget_unchecked_mut(k) = N::zero();
+                for p in column_range.clone() {
+                    let irow = *self.original_i.get_unchecked(p);
+
+                    if irow <= k {
+                        *self.work_x.vget_unchecked_mut(irow) = *values.get_unchecked(p);
+                    }
+                }
+
+                let mut diag = *self.work_x.vget_unchecked(k);
+                *self.work_x.vget_unchecked_mut(k) = N::zero();
+
+                // Triangular solve.
+                for irow in self.u.data.column_row_indices(k) {
+                    if irow >= k {
+                        continue;
+                    }
+
+                    let lki = *self.work_x.vget_unchecked(irow)
+                        / *self
+                            .l
+                            .data
+                            .vals
+                            .get_unchecked(*self.l.data.p.vget_unchecked(irow));
+                    *self.work_x.vget_unchecked_mut(irow) = N::zero();
+
+                    for p in
+                        *self.l.data.p.vget_unchecked(irow) + 1..*self.work_c.vget_unchecked(irow)
+                    {
+                        *self
+                            .work_x
+                            .vget_unchecked_mut(*self.l.data.i.get_unchecked(p)) -=
+                            *self.l.data.vals.get_unchecked(p) * lki;
+                    }
+
+                    diag -= lki * lki;
+                    let p = *self.work_c.vget_unchecked(irow);
+                    *self.work_c.vget_unchecked_mut(irow) += 1;
+                    *self.l.data.i.get_unchecked_mut(p) = k;
+                    *self.l.data.vals.get_unchecked_mut(p) = lki;
+                }
+
+                if diag <= N::zero() {
+                    self.ok = false;
+                    return false;
+                }
+
+                // Deal with the diagonal element.
+                let p = *self.work_c.vget_unchecked(k);
+                *self.work_c.vget_unchecked_mut(k) += 1;
+                *self.l.data.i.get_unchecked_mut(p) = k;
+                *self.l.data.vals.get_unchecked_mut(p) = diag.sqrt();
+            }
+        }
+
+        self.ok = true;
+        true
+    }
+
+    fn elimination_tree<S: CsStorage<N, D, D>>(m: &CsMatrix<N, D, D, S>) -> Vec<usize> {
+        let nrows = m.nrows();
+        let mut forest: Vec<_> = iter::repeat(usize::max_value()).take(nrows).collect();
+        let mut ancestor: Vec<_> = iter::repeat(usize::max_value()).take(nrows).collect();
+
+        for k in 0..nrows {
+            for irow in m.data.column_row_indices(k) {
+                let mut i = irow;
+
+                while i < k {
+                    let i_ancestor = ancestor[i];
+                    ancestor[i] = k;
+
+                    if i_ancestor == usize::max_value() {
+                        forest[i] = k;
+                        break;
+                    }
+
+                    i = i_ancestor;
+                }
+            }
+        }
+
+        forest
+    }
+
+    fn reach<S: CsStorage<N, D, D>>(
+        m: &CsMatrix<N, D, D, S>,
+        j: usize,
+        max_j: usize,
+        tree: &[usize],
+        marks: &mut Vec<bool>,
+        out: &mut Vec<usize>,
+    )
+    {
+        marks.clear();
+        marks.resize(tree.len(), false);
+
+        // FIXME: avoid all those allocations.
+        let mut tmp = Vec::new();
+        let mut res = Vec::new();
+
+        for irow in m.data.column_row_indices(j) {
+            let mut curr = irow;
+            while curr != usize::max_value() && curr <= max_j && !marks[curr] {
+                marks[curr] = true;
+                tmp.push(curr);
+                curr = tree[curr];
+            }
+
+            tmp.append(&mut res);
+            mem::swap(&mut tmp, &mut res);
+        }
+
+        out.append(&mut res);
+    }
+
+    fn nonzero_pattern<S: CsStorage<N, D, D>>(
+        m: &CsMatrix<N, D, D, S>,
+    ) -> (CsMatrix<N, D, D>, CsMatrix<N, D, D>) {
+        let etree = Self::elimination_tree(m);
+        let (nrows, ncols) = m.data.shape();
+        let mut rows = Vec::with_capacity(m.len());
+        let mut cols = unsafe { VectorN::new_uninitialized_generic(m.data.shape().0, U1) };
+        let mut marks = Vec::new();
+
+        // NOTE: the following will actually compute the non-zero pattern of
+        // the transpose of l.
+        for i in 0..nrows.value() {
+            cols[i] = rows.len();
+            Self::reach(m, i, i, &etree, &mut marks, &mut rows);
+        }
+
+        let mut vals = Vec::with_capacity(rows.len());
+        unsafe {
+            vals.set_len(rows.len());
+        }
+        vals.shrink_to_fit();
+
+        let data = CsVecStorage {
+            shape: (nrows, ncols),
+            p: cols,
+            i: rows,
+            vals,
+        };
+
+        let u = CsMatrix::from_data(data);
+        // XXX: avoid this transpose.
+        let l = u.transpose();
+
+        (l, u)
+    }
+
+    /*
+     *
+     * NOTE: All the following methods are untested and currently unused.
+     *
+     *
+    fn column_counts<S: CsStorage<N, D, D>>(
+        m: &CsMatrix<N, D, D, S>,
+        tree: &[usize],
+    ) -> Vec<usize> {
+        let len = m.data.shape().0.value();
+        let mut counts: Vec<_> = iter::repeat(0).take(len).collect();
+        let mut reach = Vec::new();
+        let mut marks = Vec::new();
+    
+        for i in 0..len {
+            Self::reach(m, i, i, tree, &mut marks, &mut reach);
+    
+            for j in reach.drain(..) {
+                counts[j] += 1;
+            }
+        }
+    
+        counts
+    }
+    
+    fn tree_postorder(tree: &[usize]) -> Vec<usize> {
+        // FIXME: avoid all those allocations?
+        let mut first_child: Vec<_> = iter::repeat(usize::max_value()).take(tree.len()).collect();
+        let mut other_children: Vec<_> =
+            iter::repeat(usize::max_value()).take(tree.len()).collect();
+    
+        // Build the children list from the parent list.
+        // The set of children of the node `i` is given by the linked list
+        // starting at `first_child[i]`. The nodes of this list are then:
+        // { first_child[i], other_children[first_child[i]], other_children[other_children[first_child[i]], ... }
+        for (i, parent) in tree.iter().enumerate() {
+            if *parent != usize::max_value() {
+                let brother = first_child[*parent];
+                first_child[*parent] = i;
+                other_children[i] = brother;
+            }
+        }
+    
+        let mut stack = Vec::with_capacity(tree.len());
+        let mut postorder = Vec::with_capacity(tree.len());
+    
+        for (i, node) in tree.iter().enumerate() {
+            if *node == usize::max_value() {
+                Self::dfs(
+                    i,
+                    &mut first_child,
+                    &other_children,
+                    &mut stack,
+                    &mut postorder,
+                )
+            }
+        }
+    
+        postorder
+    }
+    
+    fn dfs(
+        i: usize,
+        first_child: &mut [usize],
+        other_children: &[usize],
+        stack: &mut Vec<usize>,
+        result: &mut Vec<usize>,
+    ) {
+        stack.clear();
+        stack.push(i);
+    
+        while let Some(n) = stack.pop() {
+            let child = first_child[n];
+    
+            if child == usize::max_value() {
+                // No children left.
+                result.push(n);
+            } else {
+                stack.push(n);
+                stack.push(child);
+                first_child[n] = other_children[child];
+            }
+        }
+    }
+    */
+}

src/sparse/cs_matrix_conversion.rs

@@ -0,0 +1,114 @@
+use alga::general::ClosedAdd;
+use num::Zero;
+
+use allocator::Allocator;
+use sparse::cs_utils;
+use sparse::{CsMatrix, CsStorage};
+use storage::Storage;
+use {DefaultAllocator, Dim, Dynamic, Matrix, MatrixMN, Scalar};
+
+impl<'a, N: Scalar + Zero + ClosedAdd> CsMatrix<N> {
+    /// Creates a column-compressed sparse matrix from a sparse matrix in triplet form.
+    pub fn from_triplet(
+        nrows: usize,
+        ncols: usize,
+        irows: &[usize],
+        icols: &[usize],
+        vals: &[N],
+    ) -> Self
+    {
+        Self::from_triplet_generic(Dynamic::new(nrows), Dynamic::new(ncols), irows, icols, vals)
+    }
+}
+
+impl<'a, N: Scalar + Zero + ClosedAdd, R: Dim, C: Dim> CsMatrix<N, R, C>
+where DefaultAllocator: Allocator<usize, C> + Allocator<N, R>
+{
+    /// Creates a column-compressed sparse matrix from a sparse matrix in triplet form.
+    pub fn from_triplet_generic(
+        nrows: R,
+        ncols: C,
+        irows: &[usize],
+        icols: &[usize],
+        vals: &[N],
+    ) -> Self
+    {
+        assert!(vals.len() == irows.len());
+        assert!(vals.len() == icols.len());
+
+        let mut res = CsMatrix::new_uninitialized_generic(nrows, ncols, vals.len());
+        let mut workspace = res.data.p.clone();
+
+        // Column count.
+        for j in icols.iter().cloned() {
+            workspace[j] += 1;
+        }
+
+        let _ = cs_utils::cumsum(&mut workspace, &mut res.data.p);
+
+        // Fill i and vals.
+        for ((i, j), val) in irows
+            .iter()
+            .cloned()
+            .zip(icols.iter().cloned())
+            .zip(vals.iter().cloned())
+        {
+            let offset = workspace[j];
+            res.data.i[offset] = i;
+            res.data.vals[offset] = val;
+            workspace[j] = offset + 1;
+        }
+
+        // Sort the result.
+        res.sort();
+        res.dedup();
+        res
+    }
+}
+
+impl<'a, N: Scalar + Zero, R: Dim, C: Dim, S> From<CsMatrix<N, R, C, S>> for MatrixMN<N, R, C>
+where
+    S: CsStorage<N, R, C>,
+    DefaultAllocator: Allocator<N, R, C>,
+{
+    fn from(m: CsMatrix<N, R, C, S>) -> Self {
+        let (nrows, ncols) = m.data.shape();
+        let mut res = MatrixMN::zeros_generic(nrows, ncols);
+
+        for j in 0..ncols.value() {
+            for (i, val) in m.data.column_entries(j) {
+                res[(i, j)] = val;
+            }
+        }
+
+        res
+    }
+}
+
+impl<'a, N: Scalar + Zero, R: Dim, C: Dim, S> From<Matrix<N, R, C, S>> for CsMatrix<N, R, C>
+where
+    S: Storage<N, R, C>,
+    DefaultAllocator: Allocator<N, R, C> + Allocator<usize, C>,
+{
+    fn from(m: Matrix<N, R, C, S>) -> Self {
+        let (nrows, ncols) = m.data.shape();
+        let len = m.iter().filter(|e| !e.is_zero()).count();
+        let mut res = CsMatrix::new_uninitialized_generic(nrows, ncols, len);
+        let mut nz = 0;
+
+        for j in 0..ncols.value() {
+            let column = m.column(j);
+            res.data.p[j] = nz;
+
+            for i in 0..nrows.value() {
+                if !column[i].is_zero() {
+                    res.data.i[nz] = i;
+                    res.data.vals[nz] = column[i];
+                    nz += 1;
+                }
+            }
+        }
+
+        res
+    }
+}

src/sparse/cs_matrix_ops.rs

@@ -0,0 +1,304 @@
+use alga::general::{ClosedAdd, ClosedMul};
+use num::{One, Zero};
+use std::ops::{Add, Mul};
+
+use allocator::Allocator;
+use constraint::{AreMultipliable, DimEq, ShapeConstraint};
+use sparse::{CsMatrix, CsStorage, CsStorageMut, CsVector};
+use storage::StorageMut;
+use {DefaultAllocator, Dim, Scalar, Vector, VectorN, U1};
+
+impl<N: Scalar, R: Dim, C: Dim, S: CsStorage<N, R, C>> CsMatrix<N, R, C, S> {
+    fn scatter<R2: Dim, C2: Dim>(
+        &self,
+        j: usize,
+        beta: N,
+        timestamps: &mut [usize],
+        timestamp: usize,
+        workspace: &mut [N],
+        mut nz: usize,
+        res: &mut CsMatrix<N, R2, C2>,
+    ) -> usize
+    where
+        N: ClosedAdd + ClosedMul,
+        DefaultAllocator: Allocator<usize, C2>,
+    {
+        for (i, val) in self.data.column_entries(j) {
+            if timestamps[i] < timestamp {
+                timestamps[i] = timestamp;
+                res.data.i[nz] = i;
+                nz += 1;
+                workspace[i] = val * beta;
+            } else {
+                workspace[i] += val * beta;
+            }
+        }
+
+        nz
+    }
+}
+
+/*
+impl<N: Scalar, R, S> CsVector<N, R, S> {
+    pub fn axpy(&mut self, alpha: N, x: CsVector<N, R, S>, beta: N) {
+        // First, compute the number of non-zero entries.
+        let mut nnzero = 0;
+
+        // Allocate a size large enough.
+        self.data.set_column_len(0, nnzero);
+
+        // Fill with the axpy.
+        let mut i = self.len();
+        let mut j = x.len();
+        let mut k = nnzero - 1;
+        let mut rid1 = self.data.row_index(0, i - 1);
+        let mut rid2 = x.data.row_index(0, j - 1);
+
+        while k > 0 {
+            if rid1 == rid2 {
+                self.data.set_row_index(0, k, rid1);
+                self[k] = alpha * x[j] + beta * self[k];
+                i -= 1;
+                j -= 1;
+            } else if rid1 < rid2 {
+                self.data.set_row_index(0, k, rid1);
+                self[k] = beta * self[i];
+                i -= 1;
+            } else {
+                self.data.set_row_index(0, k, rid2);
+                self[k] = alpha * x[j];
+                j -= 1;
+            }
+
+            k -= 1;
+        }
+    }
+}
+*/
+
+impl<N: Scalar + Zero + ClosedAdd + ClosedMul, D: Dim, S: StorageMut<N, D>> Vector<N, D, S> {
+    /// Perform a sparse axpy operation: `self = alpha * x + beta * self` operation.
+    pub fn axpy_cs<D2: Dim, S2>(&mut self, alpha: N, x: &CsVector<N, D2, S2>, beta: N)
+    where
+        S2: CsStorage<N, D2>,
+        ShapeConstraint: DimEq<D, D2>,
+    {
+        if beta.is_zero() {
+            for i in 0..x.len() {
+                unsafe {
+                    let k = x.data.row_index_unchecked(i);
+                    let y = self.vget_unchecked_mut(k);
+                    *y = alpha * *x.data.get_value_unchecked(i);
+                }
+            }
+        } else {
+            // Needed to be sure even components not present on `x` are multiplied.
+            *self *= beta;
+
+            for i in 0..x.len() {
+                unsafe {
+                    let k = x.data.row_index_unchecked(i);
+                    let y = self.vget_unchecked_mut(k);
+                    *y += alpha * *x.data.get_value_unchecked(i);
+                }
+            }
+        }
+    }
+
+    /*
+    pub fn gemv_sparse<R2: Dim, C2: Dim, S2>(&mut self, alpha: N, a: &CsMatrix<N, R2, C2, S2>, x: &DVector<N>, beta: N)
+        where
+            S2: CsStorage<N, R2, C2> {
+        let col2 = a.column(0);
+        let val = unsafe { *x.vget_unchecked(0) };
+        self.axpy_sparse(alpha * val, &col2, beta);
+    
+        for j in 1..ncols2 {
+            let col2 = a.column(j);
+            let val = unsafe { *x.vget_unchecked(j) };
+    
+            self.axpy_sparse(alpha * val, &col2, N::one());
+        }
+    }
+    */
+}
+
+impl<'a, 'b, N, R1, R2, C1, C2, S1, S2> Mul<&'b CsMatrix<N, R2, C2, S2>>
+    for &'a CsMatrix<N, R1, C1, S1>
+where
+    N: Scalar + ClosedAdd + ClosedMul + Zero,
+    R1: Dim,
+    C1: Dim,
+    R2: Dim,
+    C2: Dim,
+    S1: CsStorage<N, R1, C1>,
+    S2: CsStorage<N, R2, C2>,
+    ShapeConstraint: AreMultipliable<R1, C1, R2, C2>,
+    DefaultAllocator: Allocator<usize, C2> + Allocator<usize, R1> + Allocator<N, R1>,
+{
+    type Output = CsMatrix<N, R1, C2>;
+
+    fn mul(self, rhs: &'b CsMatrix<N, R2, C2, S2>) -> CsMatrix<N, R1, C2> {
+        let (nrows1, ncols1) = self.data.shape();
+        let (nrows2, ncols2) = rhs.data.shape();
+        assert_eq!(
+            ncols1.value(),
+            nrows2.value(),
+            "Mismatched dimensions for matrix multiplication."
+        );
+
+        let mut res = CsMatrix::new_uninitialized_generic(nrows1, ncols2, self.len() + rhs.len());
+        let mut workspace = VectorN::<N, R1>::zeros_generic(nrows1, U1);
+        let mut nz = 0;
+
+        for j in 0..ncols2.value() {
+            res.data.p[j] = nz;
+            let new_size_bound = nz + nrows1.value();
+            res.data.i.resize(new_size_bound, 0);
+            res.data.vals.resize(new_size_bound, N::zero());
+
+            for (i, beta) in rhs.data.column_entries(j) {
+                for (k, val) in self.data.column_entries(i) {
+                    workspace[k] += val * beta;
+                }
+            }
+
+            for (i, val) in workspace.as_mut_slice().iter_mut().enumerate() {
+                if !val.is_zero() {
+                    res.data.i[nz] = i;
+                    res.data.vals[nz] = *val;
+                    *val = N::zero();
+                    nz += 1;
+                }
+            }
+        }
+
+        // NOTE: the following has a lower complexity, but is slower in many cases, likely because
+        // of branching inside of the inner loop.
+        //
+        // let mut res = CsMatrix::new_uninitialized_generic(nrows1, ncols2, self.len() + rhs.len());
+        // let mut timestamps = VectorN::zeros_generic(nrows1, U1);
+        // let mut workspace = unsafe { VectorN::new_uninitialized_generic(nrows1, U1) };
+        // let mut nz = 0;
+        //
+        // for j in 0..ncols2.value() {
+        //     res.data.p[j] = nz;
+        //     let new_size_bound = nz + nrows1.value();
+        //     res.data.i.resize(new_size_bound, 0);
+        //     res.data.vals.resize(new_size_bound, N::zero());
+        //
+        //     for (i, val) in rhs.data.column_entries(j) {
+        //         nz = self.scatter(
+        //             i,
+        //             val,
+        //             timestamps.as_mut_slice(),
+        //             j + 1,
+        //             workspace.as_mut_slice(),
+        //             nz,
+        //             &mut res,
+        //         );
+        //     }
+        //
+        //     // Keep the output sorted.
+        //     let range = res.data.p[j]..nz;
+        //     res.data.i[range.clone()].sort();
+        //
+        //     for p in range {
+        //         res.data.vals[p] = workspace[res.data.i[p]]
+        //     }
+        // }
+
+        res.data.i.truncate(nz);
+        res.data.i.shrink_to_fit();
+        res.data.vals.truncate(nz);
+        res.data.vals.shrink_to_fit();
+        res
+    }
+}
+
+impl<'a, 'b, N, R1, R2, C1, C2, S1, S2> Add<&'b CsMatrix<N, R2, C2, S2>>
+    for &'a CsMatrix<N, R1, C1, S1>
+where
+    N: Scalar + ClosedAdd + ClosedMul + One,
+    R1: Dim,
+    C1: Dim,
+    R2: Dim,
+    C2: Dim,
+    S1: CsStorage<N, R1, C1>,
+    S2: CsStorage<N, R2, C2>,
+    ShapeConstraint: DimEq<R1, R2> + DimEq<C1, C2>,
+    DefaultAllocator: Allocator<usize, C2> + Allocator<usize, R1> + Allocator<N, R1>,
+{
+    type Output = CsMatrix<N, R1, C2>;
+
+    fn add(self, rhs: &'b CsMatrix<N, R2, C2, S2>) -> CsMatrix<N, R1, C2> {
+        let (nrows1, ncols1) = self.data.shape();
+        let (nrows2, ncols2) = rhs.data.shape();
+        assert_eq!(
+            (nrows1.value(), ncols1.value()),
+            (nrows2.value(), ncols2.value()),
+            "Mismatched dimensions for matrix sum."
+        );
+
+        let mut res = CsMatrix::new_uninitialized_generic(nrows1, ncols2, self.len() + rhs.len());
+        let mut timestamps = VectorN::zeros_generic(nrows1, U1);
+        let mut workspace = unsafe { VectorN::new_uninitialized_generic(nrows1, U1) };
+        let mut nz = 0;
+
+        for j in 0..ncols2.value() {
+            res.data.p[j] = nz;
+
+            nz = self.scatter(
+                j,
+                N::one(),
+                timestamps.as_mut_slice(),
+                j + 1,
+                workspace.as_mut_slice(),
+                nz,
+                &mut res,
+            );
+
+            nz = rhs.scatter(
+                j,
+                N::one(),
+                timestamps.as_mut_slice(),
+                j + 1,
+                workspace.as_mut_slice(),
+                nz,
+                &mut res,
+            );
+
+            // Keep the output sorted.
+            let range = res.data.p[j]..nz;
+            res.data.i[range.clone()].sort();
+
+            for p in range {
+                res.data.vals[p] = workspace[res.data.i[p]]
+            }
+        }
+
+        res.data.i.truncate(nz);
+        res.data.i.shrink_to_fit();
+        res.data.vals.truncate(nz);
+        res.data.vals.shrink_to_fit();
+        res
+    }
+}
+
+impl<'a, 'b, N, R, C, S> Mul<N> for CsMatrix<N, R, C, S>
+where
+    N: Scalar + ClosedAdd + ClosedMul + Zero,
+    R: Dim,
+    C: Dim,
+    S: CsStorageMut<N, R, C>,
+{
+    type Output = Self;
+
+    fn mul(mut self, rhs: N) -> Self {
+        for e in self.values_mut() {
+            *e *= rhs
+        }
+
+        self
+    }
+}

src/sparse/cs_matrix_solve.rs

@@ -0,0 +1,283 @@
+use allocator::Allocator;
+use constraint::{SameNumberOfRows, ShapeConstraint};
+use sparse::{CsMatrix, CsStorage, CsVector};
+use storage::{Storage, StorageMut};
+use {DefaultAllocator, Dim, Matrix, MatrixMN, Real, VectorN, U1};
+
+impl<N: Real, D: Dim, S: CsStorage<N, D, D>> CsMatrix<N, D, D, S> {
+    /// Solve a lower-triangular system with a dense right-hand-side.
+    pub fn solve_lower_triangular<R2: Dim, C2: Dim, S2>(
+        &self,
+        b: &Matrix<N, R2, C2, S2>,
+    ) -> Option<MatrixMN<N, R2, C2>>
+    where
+        S2: Storage<N, R2, C2>,
+        DefaultAllocator: Allocator<N, R2, C2>,
+        ShapeConstraint: SameNumberOfRows<D, R2>,
+    {
+        let mut b = b.clone_owned();
+        if self.solve_lower_triangular_mut(&mut b) {
+            Some(b)
+        } else {
+            None
+        }
+    }
+
+    /// Solve a lower-triangular system with `self` transposed and a dense right-hand-side.
+    pub fn tr_solve_lower_triangular<R2: Dim, C2: Dim, S2>(
+        &self,
+        b: &Matrix<N, R2, C2, S2>,
+    ) -> Option<MatrixMN<N, R2, C2>>
+    where
+        S2: Storage<N, R2, C2>,
+        DefaultAllocator: Allocator<N, R2, C2>,
+        ShapeConstraint: SameNumberOfRows<D, R2>,
+    {
+        let mut b = b.clone_owned();
+        if self.tr_solve_lower_triangular_mut(&mut b) {
+            Some(b)
+        } else {
+            None
+        }
+    }
+
+    /// Solve in-place a lower-triangular system with a dense right-hand-side.
+    pub fn solve_lower_triangular_mut<R2: Dim, C2: Dim, S2>(
+        &self,
+        b: &mut Matrix<N, R2, C2, S2>,
+    ) -> bool
+    where
+        S2: StorageMut<N, R2, C2>,
+        ShapeConstraint: SameNumberOfRows<D, R2>,
+    {
+        let (nrows, ncols) = self.data.shape();
+        assert_eq!(nrows.value(), ncols.value(), "The matrix must be square.");
+        assert_eq!(nrows.value(), b.len(), "Mismatched matrix dimensions.");
+
+        for j2 in 0..b.ncols() {
+            let mut b = b.column_mut(j2);
+
+            for j in 0..ncols.value() {
+                let mut column = self.data.column_entries(j);
+                let mut diag_found = false;
+
+                while let Some((i, val)) = column.next() {
+                    if i == j {
+                        if val.is_zero() {
+                            return false;
+                        }
+
+                        b[j] /= val;
+                        diag_found = true;
+                        break;
+                    }
+                }
+
+                if !diag_found {
+                    return false;
+                }
+
+                for (i, val) in column {
+                    b[i] -= b[j] * val;
+                }
+            }
+        }
+
+        true
+    }
+
+    /// Solve a lower-triangular system with `self` transposed and a dense right-hand-side.
+    pub fn tr_solve_lower_triangular_mut<R2: Dim, C2: Dim, S2>(
+        &self,
+        b: &mut Matrix<N, R2, C2, S2>,
+    ) -> bool
+    where
+        S2: StorageMut<N, R2, C2>,
+        ShapeConstraint: SameNumberOfRows<D, R2>,
+    {
+        let (nrows, ncols) = self.data.shape();
+        assert_eq!(nrows.value(), ncols.value(), "The matrix must be square.");
+        assert_eq!(nrows.value(), b.len(), "Mismatched matrix dimensions.");
+
+        for j2 in 0..b.ncols() {
+            let mut b = b.column_mut(j2);
+
+            for j in (0..ncols.value()).rev() {
+                let mut column = self.data.column_entries(j);
+                let mut diag = None;
+
+                while let Some((i, val)) = column.next() {
+                    if i == j {
+                        if val.is_zero() {
+                            return false;
+                        }
+
+                        diag = Some(val);
+                        break;
+                    }
+                }
+
+                if let Some(diag) = diag {
+                    for (i, val) in column {
+                        b[j] -= val * b[i];
+                    }
+
+                    b[j] /= diag;
+                } else {
+                    return false;
+                }
+            }
+        }
+
+        true
+    }
+
+    /// Solve a lower-triangular system with a sparse right-hand-side.
+    pub fn solve_lower_triangular_cs<D2: Dim, S2>(
+        &self,
+        b: &CsVector<N, D2, S2>,
+    ) -> Option<CsVector<N, D2>>
+    where
+        S2: CsStorage<N, D2>,
+        DefaultAllocator: Allocator<bool, D> + Allocator<N, D2> + Allocator<usize, D2>,
+        ShapeConstraint: SameNumberOfRows<D, D2>,
+    {
+        let mut reach = Vec::new();
+        // We don't compute a postordered reach here because it will be sorted after anyway.
+        self.lower_triangular_reach(b, &mut reach);
+        // We sort the reach so the result matrix has sorted indices.
+        reach.sort();
+        let mut workspace = unsafe { VectorN::new_uninitialized_generic(b.data.shape().0, U1) };
+
+        for i in reach.iter().cloned() {
+            workspace[i] = N::zero();
+        }
+
+        for (i, val) in b.data.column_entries(0) {
+            workspace[i] = val;
+        }
+
+        for j in reach.iter().cloned() {
+            let mut column = self.data.column_entries(j);
+            let mut diag_found = false;
+
+            while let Some((i, val)) = column.next() {
+                if i == j {
+                    if val.is_zero() {
+                        break;
+                    }
+
+                    workspace[j] /= val;
+                    diag_found = true;
+                    break;
+                }
+            }
+
+            if !diag_found {
+                return None;
+            }
+
+            for (i, val) in column {
+                workspace[i] -= workspace[j] * val;
+            }
+        }
+
+        // Copy the result into a sparse vector.
+        let mut result = CsVector::new_uninitialized_generic(b.data.shape().0, U1, reach.len());
+
+        for (i, val) in reach.iter().zip(result.data.vals.iter_mut()) {
+            *val = workspace[*i];
+        }
+
+        result.data.i = reach;
+        Some(result)
+    }
+
+    /*
+    // Computes the reachable, post-ordered, nodes from `b`.
+    fn lower_triangular_reach_postordered<D2: Dim, S2>(
+        &self,
+        b: &CsVector<N, D2, S2>,
+        xi: &mut Vec<usize>,
+    ) where
+        S2: CsStorage<N, D2>,
+        DefaultAllocator: Allocator<bool, D>,
+    {
+        let mut visited = VectorN::repeat_generic(self.data.shape().1, U1, false);
+        let mut stack = Vec::new();
+
+        for i in b.data.column_range(0) {
+            let row_index = b.data.row_index(i);
+
+            if !visited[row_index] {
+                let rng = self.data.column_range(row_index);
+                stack.push((row_index, rng));
+                self.lower_triangular_dfs(visited.as_mut_slice(), &mut stack, xi);
+            }
+        }
+    }
+
+    fn lower_triangular_dfs(
+        &self,
+        visited: &mut [bool],
+        stack: &mut Vec<(usize, Range<usize>)>,
+        xi: &mut Vec<usize>,
+    )
+    {
+        'recursion: while let Some((j, rng)) = stack.pop() {
+            visited[j] = true;
+
+            for i in rng.clone() {
+                let row_id = self.data.row_index(i);
+                if row_id > j && !visited[row_id] {
+                    stack.push((j, (i + 1)..rng.end));
+                    stack.push((row_id, self.data.column_range(row_id)));
+                    continue 'recursion;
+                }
+            }
+
+            xi.push(j)
+        }
+    }
+    */
+
+    // Computes the nodes reachable from `b` in an arbitrary order.
+    fn lower_triangular_reach<D2: Dim, S2>(&self, b: &CsVector<N, D2, S2>, xi: &mut Vec<usize>)
+    where
+        S2: CsStorage<N, D2>,
+        DefaultAllocator: Allocator<bool, D>,
+    {
+        let mut visited = VectorN::repeat_generic(self.data.shape().1, U1, false);
+        let mut stack = Vec::new();
+
+        for irow in b.data.column_row_indices(0) {
+            self.lower_triangular_bfs(irow, visited.as_mut_slice(), &mut stack, xi);
+        }
+    }
+
+    fn lower_triangular_bfs(
+        &self,
+        start: usize,
+        visited: &mut [bool],
+        stack: &mut Vec<usize>,
+        xi: &mut Vec<usize>,
+    )
+    {
+        if !visited[start] {
+            stack.clear();
+            stack.push(start);
+            xi.push(start);
+            visited[start] = true;
+
+            while let Some(j) = stack.pop() {
+                for irow in self.data.column_row_indices(j) {
+                    if irow > j && !visited[irow] {
+                        stack.push(irow);
+                        xi.push(irow);
+                        visited[irow] = true;
+                    }
+                }
+            }
+        }
+    }
+}

src/sparse/cs_utils.rs

@@ -0,0 +1,16 @@
+use allocator::Allocator;
+use {DefaultAllocator, Dim, VectorN};
+
+pub fn cumsum<D: Dim>(a: &mut VectorN<usize, D>, b: &mut VectorN<usize, D>) -> usize
+where DefaultAllocator: Allocator<usize, D> {
+    assert!(a.len() == b.len());
+    let mut sum = 0;
+
+    for i in 0..a.len() {
+        b[i] = sum;
+        sum += a[i];
+        a[i] = b[i];
+    }
+
+    sum
+}