Add rustfmt.toml and run it.

benches/core/matrix.rs

@@ -1,7 +1,7 @@
+use na::{DMatrix, DVector, Matrix2, Matrix3, Matrix4, MatrixN, Vector2, Vector3, Vector4, U10};
 use rand::{IsaacRng, Rng};
-use test::{self, Bencher};
-use na::{DMatrix, DVector, Matrix2, Matrix3, Matrix4, MatrixN, U10, Vector2, Vector3, Vector4};
 use std::ops::{Add, Div, Mul, Sub};
+use test::{self, Bencher};
 
 #[path = "../common/macros.rs"]
 mod macros;
@@ -189,18 +189,10 @@ fn mat_mul_mat(bench: &mut Bencher) {
 
 #[bench]
 fn mat100_from_fn(bench: &mut Bencher) {
-    bench.iter(|| {
-        DMatrix::from_fn(100, 100, |a, b| {
-            a + b
-        })
-    })
+    bench.iter(|| DMatrix::from_fn(100, 100, |a, b| a + b))
 }
 
 #[bench]
 fn mat500_from_fn(bench: &mut Bencher) {
-    bench.iter(|| {
-        DMatrix::from_fn(500, 500, |a, b| {
-            a + b
-        })
-    })
+    bench.iter(|| DMatrix::from_fn(500, 500, |a, b| a + b))
 }

benches/core/vector.rs

@@ -1,8 +1,8 @@
+use na::{DVector, Vector2, Vector3, Vector4, VectorN};
 use rand::{IsaacRng, Rng};
+use std::ops::{Add, Div, Mul, Sub};
 use test::{self, Bencher};
 use typenum::U10000;
-use na::{DVector, Vector2, Vector3, Vector4, VectorN};
-use std::ops::{Add, Div, Mul, Sub};
 
 #[path = "../common/macros.rs"]
 mod macros;

benches/geometry/quaternion.rs

@@ -1,7 +1,7 @@
-use rand::{IsaacRng, Rng};
-use test::{self, Bencher};
 use na::{Quaternion, UnitQuaternion, Vector3};
+use rand::{IsaacRng, Rng};
 use std::ops::{Add, Div, Mul, Sub};
+use test::{self, Bencher};
 
 #[path = "../common/macros.rs"]
 mod macros;

benches/lib.rs

@@ -6,12 +6,12 @@ extern crate rand;
 extern crate test;
 extern crate typenum;
 
-use rand::{IsaacRng, Rng};
 use na::DMatrix;
+use rand::{IsaacRng, Rng};
 
 mod core;
-mod linalg;
 mod geometry;
+mod linalg;
 
 fn reproductible_dmatrix(nrows: usize, ncols: usize) -> DMatrix<f64> {
     let mut rng = IsaacRng::new_unseeded();

benches/linalg/bidiagonal.rs

@@ -1,5 +1,5 @@
-use test::{self, Bencher};
 use na::{Bidiagonal, DMatrix, Matrix4};
+use test::{self, Bencher};
 
 #[path = "../common/macros.rs"]
 mod macros;

benches/linalg/cholesky.rs

@@ -1,5 +1,5 @@
-use test::{self, Bencher};
 use na::{Cholesky, DMatrix, DVector};
+use test::{self, Bencher};
 
 #[bench]
 fn cholesky_100x100(bh: &mut Bencher) {

benches/linalg/full_piv_lu.rs

@@ -1,5 +1,5 @@
-use test::{self, Bencher};
 use na::{DMatrix, DVector, FullPivLU};
+use test::{self, Bencher};
 
 // Without unpack.
 #[bench]

benches/linalg/hessenberg.rs

@@ -1,5 +1,5 @@
-use test::{self, Bencher};
 use na::{DMatrix, Hessenberg, Matrix4};
+use test::{self, Bencher};
 
 #[path = "../common/macros.rs"]
 mod macros;

benches/linalg/lu.rs

@@ -1,5 +1,5 @@
-use test::{self, Bencher};
 use na::{DMatrix, DVector, LU};
+use test::{self, Bencher};
 
 // Without unpack.
 #[bench]

benches/linalg/mod.rs

@@ -1,11 +1,11 @@
-mod solve;
-mod cholesky;
-mod qr;
-mod hessenberg;
 mod bidiagonal;
-mod lu;
+mod cholesky;
 mod full_piv_lu;
-mod svd;
+mod hessenberg;
+mod lu;
+mod qr;
 mod schur;
+mod solve;
+mod svd;
 mod symmetric_eigen;
 // mod eigen;

benches/linalg/qr.rs

@@ -1,5 +1,5 @@
-use test::{self, Bencher};
 use na::{DMatrix, DVector, Matrix4, QR};
+use test::{self, Bencher};
 
 #[path = "../common/macros.rs"]
 mod macros;

benches/linalg/schur.rs

@@ -1,5 +1,5 @@
-use test::{self, Bencher};
 use na::{Matrix4, RealSchur};
+use test::{self, Bencher};
 
 #[bench]
 fn schur_decompose_4x4(bh: &mut Bencher) {

benches/linalg/solve.rs

@@ -1,5 +1,5 @@
-use test::Bencher;
 use na::{DMatrix, DVector};
+use test::Bencher;
 
 #[bench]
 fn solve_l_triangular_100x100(bh: &mut Bencher) {

benches/linalg/svd.rs

@@ -1,5 +1,5 @@
-use test::{self, Bencher};
 use na::{Matrix4, SVD};
+use test::{self, Bencher};
 
 #[bench]
 fn svd_decompose_4x4(bh: &mut Bencher) {

benches/linalg/symmetric_eigen.rs

@@ -1,5 +1,5 @@
-use test::{self, Bencher};
 use na::{Matrix4, SymmetricEigen};
+use test::{self, Bencher};
 
 #[bench]
 fn symmetric_eigen_decompose_4x4(bh: &mut Bencher) {

examples/dimensional_genericity.rs

@@ -2,15 +2,13 @@ extern crate alga;
 extern crate nalgebra as na;
 
 use alga::linear::FiniteDimInnerSpace;
-use na::{DefaultAllocator, Real, Unit, Vector2, Vector3, VectorN};
 use na::allocator::Allocator;
 use na::dimension::Dim;
+use na::{DefaultAllocator, Real, Unit, Vector2, Vector3, VectorN};
 
 /// Reflects a vector wrt. the hyperplane with normal `plane_normal`.
 fn reflect_wrt_hyperplane_with_algebraic_genericity<V>(plane_normal: &Unit<V>, vector: &V) -> V
-where
-    V: FiniteDimInnerSpace + Copy,
-{
+where V: FiniteDimInnerSpace + Copy {
     let n = plane_normal.as_ref(); // Get the underlying vector of type `V`.
     *vector - *n * (n.dot(vector) * na::convert(2.0))
 }
@@ -31,9 +29,7 @@ where
 
 /// Reflects a 2D vector wrt. the 2D line with normal `plane_normal`.
 fn reflect_wrt_hyperplane2<N>(plane_normal: &Unit<Vector2<N>>, vector: &Vector2<N>) -> Vector2<N>
-where
-    N: Real,
-{
+where N: Real {
     let n = plane_normal.as_ref(); // Get the underlying Vector2
     vector - n * (n.dot(vector) * na::convert(2.0))
 }
@@ -41,9 +37,7 @@ where
 /// Reflects a 3D vector wrt. the 3D plane with normal `plane_normal`.
 /// /!\ This is an exact replicate of `reflect_wrt_hyperplane2, but for 3D.
 fn reflect_wrt_hyperplane3<N>(plane_normal: &Unit<Vector3<N>>, vector: &Vector3<N>) -> Vector3<N>
-where
-    N: Real,
-{
+where N: Real {
     let n = plane_normal.as_ref(); // Get the underlying Vector3
     vector - n * (n.dot(vector) * na::convert(2.0))
 }

examples/homogeneous_coordinates.rs

@@ -2,8 +2,8 @@
 extern crate approx;
 extern crate nalgebra as na;
 
-use std::f32;
 use na::{Isometry2, Point2, Vector2};
+use std::f32;
 
 fn use_dedicated_types() {
     let iso = Isometry2::new(Vector2::new(1.0, 1.0), f32::consts::PI);

examples/identity.rs

@@ -9,9 +9,7 @@ use na::{Id, Isometry3, Point3, Vector3};
  * intermediate value.
  */
 fn complicated_algorithm<T>(v: &Vector3<f32>, t: &T, n: usize) -> Vector3<f32>
-where
-    T: Transformation<Point3<f32>>,
-{
+where T: Transformation<Point3<f32>> {
     let mut result = *v;
 
     // Do lots of operations involving t.

examples/matrix_construction.rs

@@ -48,11 +48,10 @@ fn main() {
         4,
         3,
         [
-        // 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()
+            // 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()
             .cloned(),
     );
 

examples/transform_vector_point.rs

@@ -2,8 +2,8 @@
 extern crate approx;
 extern crate nalgebra as na;
 
-use std::f32;
 use na::{Isometry2, Point2, Vector2};
+use std::f32;
 
 fn main() {
     let t = Isometry2::new(Vector2::new(1.0, 1.0), f32::consts::PI);

nalgebra-glm/src/common.rs

@@ -22,9 +22,7 @@ use traits::{Alloc, Dimension, Number};
 ///
 /// * [`sign`](fn.sign.html)
 pub fn abs<N: Number, R: Dimension, C: Dimension>(x: &TMat<N, R, C>) -> TMat<N, R, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+where DefaultAllocator: Alloc<N, R, C> {
     x.abs()
 }
 
@@ -46,9 +44,7 @@ where
 /// * [`round`](fn.round.html)
 /// * [`trunc`](fn.trunc.html)
 pub fn ceil<N: Real, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|x| x.ceil())
 }
 
@@ -98,9 +94,7 @@ pub fn clamp_scalar<N: Number>(x: N, min_val: N, max_val: N) -> N {
 /// * [`clamp_scalar`](fn.clamp_scalar.html)
 /// * [`clamp_vec`](fn.clamp_vec.html)
 pub fn clamp<N: Number, D: Dimension>(x: &TVec<N, D>, min_val: N, max_val: N) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|x| na::clamp(x, min_val, max_val))
 }
 
@@ -173,9 +167,7 @@ pub fn float_bits_to_int(v: f32) -> i32 {
 /// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
 /// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
 pub fn float_bits_to_int_vec<D: Dimension>(v: &TVec<f32, D>) -> TVec<i32, D>
-where
-    DefaultAllocator: Alloc<f32, D>,
-{
+where DefaultAllocator: Alloc<f32, D> {
     v.map(float_bits_to_int)
 }
 
@@ -210,9 +202,7 @@ pub fn float_bits_to_uint(v: f32) -> u32 {
 /// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
 /// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
 pub fn float_bits_to_uint_vec<D: Dimension>(v: &TVec<f32, D>) -> TVec<u32, D>
-where
-    DefaultAllocator: Alloc<f32, D>,
-{
+where DefaultAllocator: Alloc<f32, D> {
     v.map(float_bits_to_uint)
 }
 
@@ -233,9 +223,7 @@ where
 /// * [`round`](fn.round.html)
 /// * [`trunc`](fn.trunc.html)
 pub fn floor<N: Real, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|x| x.floor())
 }
 
@@ -262,9 +250,7 @@ where
 /// * [`round`](fn.round.html)
 /// * [`trunc`](fn.trunc.html)
 pub fn fract<N: Real, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|x| x.fract())
 }
 
@@ -307,9 +293,7 @@ pub fn int_bits_to_float(v: i32) -> f32 {
 /// * [`uint_bits_to_float`](fn.uint_bits_to_float.html)
 /// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
 pub fn int_bits_to_float_vec<D: Dimension>(v: &TVec<i32, D>) -> TVec<f32, D>
-where
-    DefaultAllocator: Alloc<f32, D>,
-{
+where DefaultAllocator: Alloc<f32, D> {
     v.map(int_bits_to_float)
 }
 
@@ -368,9 +352,7 @@ pub fn mix_scalar<N: Number>(x: N, y: N, a: N) -> N {
 /// * [`mix_scalar`](fn.mix_scalar.html)
 /// * [`mix_vec`](fn.mix_vec.html)
 pub fn mix<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>, a: N) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x * (N::one() - a) + y * a
 }
 
@@ -443,9 +425,7 @@ pub fn lerp_scalar<N: Number>(x: N, y: N, a: N) -> N {
 /// * [`lerp_scalar`](fn.lerp_scalar.html)
 /// * [`lerp_vec`](fn.lerp_vec.html)
 pub fn lerp<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>, a: N) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     mix(x, y, a)
 }
 
@@ -488,9 +468,7 @@ where
 ///
 /// * [`modf`](fn.modf.html)
 pub fn modf_vec<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.zip_map(y, |x, y| x % y)
 }
 
@@ -522,9 +500,7 @@ pub fn modf<N: Number>(x: N, i: N) -> N {
 /// * [`fract`](fn.fract.html)
 /// * [`trunc`](fn.trunc.html)
 pub fn round<N: Real, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|x| x.round())
 }
 
@@ -548,9 +524,7 @@ where
 /// * [`abs`](fn.abs.html)
 ///
 pub fn sign<N: Number, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|x| if x.is_zero() { N::zero() } else { x.signum() })
 }
 
@@ -576,17 +550,13 @@ pub fn step_scalar<N: Number>(edge: N, x: N) -> N {
 
 /// Returns 0.0 if `x[i] < edge`, otherwise it returns 1.0.
 pub fn step<N: Number, D: Dimension>(edge: N, x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|x| step_scalar(edge, x))
 }
 
 /// Returns 0.0 if `x[i] < edge[i]`, otherwise it returns 1.0.
 pub fn step_vec<N: Number, D: Dimension>(edge: &TVec<N, D>, x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     edge.zip_map(x, step_scalar)
 }
 
@@ -607,9 +577,7 @@ where
 /// * [`fract`](fn.fract.html)
 /// * [`round`](fn.round.html)
 pub fn trunc<N: Real, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|x| x.trunc())
 }
 
@@ -644,8 +612,6 @@ pub fn uint_bits_to_float_scalar(v: u32) -> f32 {
 /// * [`int_bits_to_float_vec`](fn.int_bits_to_float_vec.html)
 /// * [`uint_bits_to_float_scalar`](fn.uint_bits_to_float_scalar.html)
 pub fn uint_bits_to_float<D: Dimension>(v: &TVec<u32, D>) -> TVec<f32, D>
-where
-    DefaultAllocator: Alloc<f32, D>,
-{
+where DefaultAllocator: Alloc<f32, D> {
     v.map(uint_bits_to_float_scalar)
 }

nalgebra-glm/src/constructors.rs

@@ -1,3 +1,5 @@
+#![cfg_attr(rustfmt, rustfmt_skip)]
+
 use na::{Scalar, Real, U2, U3, U4};
 use aliases::{TMat, Qua, TVec1, TVec2, TVec3, TVec4, TMat2, TMat2x3, TMat2x4, TMat3, TMat3x2, TMat3x4,
               TMat4, TMat4x2, TMat4x3};
@@ -34,7 +36,8 @@ pub fn vec4<N: Scalar>(x: N, y: N, z: N, w: N) -> TVec4<N> {
 
 
 /// Create a new 2x2 matrix.
-pub fn mat2<N: Scalar>(m11: N, m12: N, m21: N, m22: N) -> TMat2<N> {
+pub fn mat2<N: Scalar>(m11: N, m12: N,
+                       m21: N, m22: N) -> TMat2<N> {
     TMat::<N, U2, U2>::new(
         m11, m12,
         m21, m22,
@@ -42,7 +45,8 @@ pub fn mat2<N: Scalar>(m11: N, m12: N, m21: N, m22: N) -> TMat2<N> {
 }
 
 /// Create a new 2x2 matrix.
-pub fn mat2x2<N: Scalar>(m11: N, m12: N, m21: N, m22: N) -> TMat2<N> {
+pub fn mat2x2<N: Scalar>(m11: N, m12: N,
+                         m21: N, m22: N) -> TMat2<N> {
     TMat::<N, U2, U2>::new(
         m11, m12,
         m21, m22,
@@ -50,7 +54,8 @@ pub fn mat2x2<N: Scalar>(m11: N, m12: N, m21: N, m22: N) -> TMat2<N> {
 }
 
 /// Create a new 2x3 matrix.
-pub fn mat2x3<N: Scalar>(m11: N, m12: N, m13: N, m21: N, m22: N, m23: N) -> TMat2x3<N> {
+pub fn mat2x3<N: Scalar>(m11: N, m12: N, m13: N,
+                         m21: N, m22: N, m23: N) -> TMat2x3<N> {
     TMat::<N, U2, U3>::new(
         m11, m12, m13,
         m21, m22, m23,
@@ -58,7 +63,8 @@ pub fn mat2x3<N: Scalar>(m11: N, m12: N, m13: N, m21: N, m22: N, m23: N) -> TMat
 }
 
 /// Create a new 2x4 matrix.
-pub fn mat2x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N, m21: N, m22: N, m23: N, m24: N) -> TMat2x4<N> {
+pub fn mat2x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N,
+                         m21: N, m22: N, m23: N, m24: N) -> TMat2x4<N> {
     TMat::<N, U2, U4>::new(
         m11, m12, m13, m14,
         m21, m22, m23, m24,
@@ -66,7 +72,9 @@ pub fn mat2x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N, m21: N, m22: N, m23: N,
 }
 
 /// Create a new 3x3 matrix.
-pub fn mat3<N: Scalar>(m11: N, m12: N, m13: N, m21: N, m22: N, m23: N, m31: N, m32: N, m33: N) -> TMat3<N> {
+pub fn mat3<N: Scalar>(m11: N, m12: N, m13: N,
+                       m21: N, m22: N, m23: N,
+                       m31: N, m32: N, m33: N) -> TMat3<N> {
     TMat::<N, U3, U3>::new(
         m11, m12, m13,
         m21, m22, m23,
@@ -75,7 +83,9 @@ pub fn mat3<N: Scalar>(m11: N, m12: N, m13: N, m21: N, m22: N, m23: N, m31: N, m
 }
 
 /// Create a new 3x2 matrix.
-pub fn mat3x2<N: Scalar>(m11: N, m12: N, m21: N, m22: N, m31: N, m32: N) -> TMat3x2<N> {
+pub fn mat3x2<N: Scalar>(m11: N, m12: N,
+                         m21: N, m22: N,
+                         m31: N, m32: N) -> TMat3x2<N> {
     TMat::<N, U3, U2>::new(
         m11, m12,
         m21, m22,
@@ -84,7 +94,9 @@ pub fn mat3x2<N: Scalar>(m11: N, m12: N, m21: N, m22: N, m31: N, m32: N) -> TMat
 }
 
 /// Create a new 3x3 matrix.
-pub fn mat3x3<N: Scalar>(m11: N, m12: N, m13: N, m21: N, m22: N, m23: N, m31: N, m32: N, m33: N) -> TMat3<N> {
+pub fn mat3x3<N: Scalar>(m11: N, m12: N, m13: N,
+                         m21: N, m22: N, m23: N,
+                         m31: N, m32: N, m33: N) -> TMat3<N> {
     TMat::<N, U3, U3>::new(
         m11, m12, m13,
         m31, m32, m33,
@@ -93,7 +105,9 @@ pub fn mat3x3<N: Scalar>(m11: N, m12: N, m13: N, m21: N, m22: N, m23: N, m31: N,
 }
 
 /// Create a new 3x4 matrix.
-pub fn mat3x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N, m21: N, m22: N, m23: N, m24: N, m31: N, m32: N, m33: N, m34: N) -> TMat3x4<N> {
+pub fn mat3x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N,
+                         m21: N, m22: N, m23: N, m24: N,
+                         m31: N, m32: N, m33: N, m34: N) -> TMat3x4<N> {
     TMat::<N, U3, U4>::new(
         m11, m12, m13, m14,
         m21, m22, m23, m24,
@@ -102,7 +116,10 @@ pub fn mat3x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N, m21: N, m22: N, m23: N,
 }
 
 /// Create a new 4x2 matrix.
-pub fn mat4x2<N: Scalar>(m11: N, m12: N, m21: N, m22: N, m31: N, m32: N, m41: N, m42: N) -> TMat4x2<N> {
+pub fn mat4x2<N: Scalar>(m11: N, m12: N,
+                         m21: N, m22: N,
+                         m31: N, m32: N,
+                         m41: N, m42: N) -> TMat4x2<N> {
     TMat::<N, U4, U2>::new(
         m11, m12,
         m21, m22,
@@ -112,7 +129,10 @@ pub fn mat4x2<N: Scalar>(m11: N, m12: N, m21: N, m22: N, m31: N, m32: N, m41: N,
 }
 
 /// Create a new 4x3 matrix.
-pub fn mat4x3<N: Scalar>(m11: N, m12: N, m13: N, m21: N, m22: N, m23: N, m31: N, m32: N, m33: N, m41: N, m42: N, m43: N) -> TMat4x3<N> {
+pub fn mat4x3<N: Scalar>(m11: N, m12: N, m13: N,
+                         m21: N, m22: N, m23: N,
+                         m31: N, m32: N, m33: N,
+                         m41: N, m42: N, m43: N) -> TMat4x3<N> {
     TMat::<N, U4, U3>::new(
         m11, m12, m13,
         m21, m22, m23,
@@ -122,7 +142,10 @@ pub fn mat4x3<N: Scalar>(m11: N, m12: N, m13: N, m21: N, m22: N, m23: N, m31: N,
 }
 
 /// Create a new 4x4 matrix.
-pub fn mat4x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N, m21: N, m22: N, m23: N, m24: N, m31: N, m32: N, m33: N, m34: N, m41: N, m42: N, m43: N, m44: N) -> TMat4<N> {
+pub fn mat4x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N,
+                         m21: N, m22: N, m23: N, m24: N,
+                         m31: N, m32: N, m33: N, m34: N,
+                         m41: N, m42: N, m43: N, m44: N) -> TMat4<N> {
     TMat::<N, U4, U4>::new(
         m11, m12, m13, m14,
         m21, m22, m23, m24,
@@ -132,7 +155,10 @@ pub fn mat4x4<N: Scalar>(m11: N, m12: N, m13: N, m14: N, m21: N, m22: N, m23: N,
 }
 
 /// Create a new 4x4 matrix.
-pub fn mat4<N: Scalar>(m11: N, m12: N, m13: N, m14: N, m21: N, m22: N, m23: N, m24: N, m31: N, m32: N, m33: N, m34: N, m41: N, m42: N, m43: N, m44: N) -> TMat4<N> {
+pub fn mat4<N: Scalar>(m11: N, m12: N, m13: N, m14: N,
+                       m21: N, m22: N, m23: N, m24: N,
+                       m31: N, m32: N, m33: N, m34: N,
+                       m41: N, m42: N, m43: N, m44: N) -> TMat4<N> {
     TMat::<N, U4, U4>::new(
         m11, m12, m13, m14,
         m21, m22, m23, m24,

nalgebra-glm/src/exponential.rs

@@ -8,9 +8,7 @@ use traits::{Alloc, Dimension};
 ///
 /// * [`exp2`](fn.exp2.html)
 pub fn exp<N: Real, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     v.map(|x| x.exp())
 }
 
@@ -20,9 +18,7 @@ where
 ///
 /// * [`exp`](fn.exp.html)
 pub fn exp2<N: Real, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     v.map(|x| x.exp2())
 }
 
@@ -32,9 +28,7 @@ where
 ///
 /// * [`sqrt`](fn.sqrt.html)
 pub fn inversesqrt<N: Real, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     v.map(|x| N::one() / x.sqrt())
 }
 
@@ -44,9 +38,7 @@ where
 ///
 /// * [`log2`](fn.log2.html)
 pub fn log<N: Real, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     v.map(|x| x.ln())
 }
 
@@ -56,17 +48,13 @@ where
 ///
 /// * [`log`](fn.log.html)
 pub fn log2<N: Real, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     v.map(|x| x.log2())
 }
 
 /// Component-wise power.
 pub fn pow<N: Real, D: Dimension>(base: &TVec<N, D>, exponent: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     base.zip_map(exponent, |b, e| b.powf(e))
 }
 
@@ -79,8 +67,6 @@ where
 /// * [`inversesqrt`](fn.inversesqrt.html)
 /// * [`pow`](fn.pow.html)
 pub fn sqrt<N: Real, D: Dimension>(v: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     v.map(|x| x.sqrt())
 }

nalgebra-glm/src/ext/matrix_projection.rs

@@ -45,7 +45,8 @@ pub fn project<N: Real>(
     model: &TMat4<N>,
     proj: &TMat4<N>,
     viewport: TVec4<N>,
-) -> TVec3<N> {
+) -> TVec3<N>
+{
     project_no(obj, model, proj, viewport)
 }
 
@@ -72,7 +73,8 @@ pub fn project_no<N: Real>(
     model: &TMat4<N>,
     proj: &TMat4<N>,
     viewport: TVec4<N>,
-) -> TVec3<N> {
+) -> TVec3<N>
+{
     let proj = project_zo(obj, model, proj, viewport);
     TVec3::new(proj.x, proj.y, proj.z * na::convert(0.5) + na::convert(0.5))
 }
@@ -100,7 +102,8 @@ pub fn project_zo<N: Real>(
     model: &TMat4<N>,
     proj: &TMat4<N>,
     viewport: TVec4<N>,
-) -> TVec3<N> {
+) -> TVec3<N>
+{
     let normalized = proj * model * TVec4::new(obj.x, obj.y, obj.z, N::one());
     let scale = N::one() / normalized.w;
 
@@ -132,7 +135,8 @@ pub fn unproject<N: Real>(
     model: &TMat4<N>,
     proj: &TMat4<N>,
     viewport: TVec4<N>,
-) -> TVec3<N> {
+) -> TVec3<N>
+{
     unproject_no(win, model, proj, viewport)
 }
 
@@ -159,7 +163,8 @@ pub fn unproject_no<N: Real>(
     model: &TMat4<N>,
     proj: &TMat4<N>,
     viewport: TVec4<N>,
-) -> TVec3<N> {
+) -> TVec3<N>
+{
     let _2: N = na::convert(2.0);
     let transform = (proj * model).try_inverse().unwrap_or_else(TMat4::zeros);
     let pt = TVec4::new(
@@ -196,7 +201,8 @@ pub fn unproject_zo<N: Real>(
     model: &TMat4<N>,
     proj: &TMat4<N>,
     viewport: TVec4<N>,
-) -> TVec3<N> {
+) -> TVec3<N>
+{
     let _2: N = na::convert(2.0);
     let transform = (proj * model).try_inverse().unwrap_or_else(TMat4::zeros);
     let pt = TVec4::new(

nalgebra-glm/src/ext/matrix_transform.rs

@@ -5,9 +5,7 @@ use traits::{Alloc, Dimension, Number};
 
 /// The identity matrix.
 pub fn identity<N: Number, D: Dimension>() -> TMat<N, D, D>
-where
-    DefaultAllocator: Alloc<N, D, D>,
-{
+where DefaultAllocator: Alloc<N, D, D> {
     TMat::<N, D, D>::identity()
 }
 

nalgebra-glm/src/ext/vector_common.rs

@@ -17,9 +17,7 @@ use traits::{Alloc, Dimension, Number};
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
 pub fn max<N: Number, D: Dimension>(a: &TVec<N, D>, b: N) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     a.map(|a| na::sup(&a, &b))
 }
 
@@ -37,9 +35,7 @@ where
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
 pub fn max2<N: Number, D: Dimension>(a: &TVec<N, D>, b: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     na::sup(a, b)
 }
 
@@ -57,9 +53,7 @@ where
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
 pub fn max3<N: Number, D: Dimension>(a: &TVec<N, D>, b: &TVec<N, D>, c: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     max2(&max2(a, b), c)
 }
 
@@ -102,9 +96,7 @@ where
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
 pub fn min<N: Number, D: Dimension>(x: &TVec<N, D>, y: N) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|x| na::inf(&x, &y))
 }
 
@@ -122,9 +114,7 @@ where
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
 pub fn min2<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     na::inf(x, y)
 }
 
@@ -142,9 +132,7 @@ where
 /// * [`min2`](fn.min2.html)
 /// * [`min4`](fn.min4.html)
 pub fn min3<N: Number, D: Dimension>(a: &TVec<N, D>, b: &TVec<N, D>, c: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     min2(&min2(a, b), c)
 }
 

nalgebra-glm/src/geometric.rs

@@ -14,17 +14,13 @@ pub fn cross<N: Number, D: Dimension>(x: &TVec3<N>, y: &TVec3<N>) -> TVec3<N> {
 ///
 /// * [`distance2`](fn.distance2.html)
 pub fn distance<N: Real, D: Dimension>(p0: &TVec<N, D>, p1: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     (p1 - p0).norm()
 }
 
 /// The dot product of two vectors.
 pub fn dot<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.dot(y)
 }
 
@@ -54,9 +50,7 @@ where
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude2`](fn.magnitude2.html)
 pub fn length<N: Real, D: Dimension>(x: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.norm()
 }
 
@@ -70,34 +64,26 @@ where
 /// * [`magnitude2`](fn.magnitude2.html)
 /// * [`nalgebra::norm`](../nalgebra/fn.norm.html)
 pub fn magnitude<N: Real, D: Dimension>(x: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.norm()
 }
 
 /// Normalizes a vector.
 pub fn normalize<N: Real, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.normalize()
 }
 
 /// For the incident vector `i` and surface orientation `n`, returns the reflection direction : `result = i - 2.0 * dot(n, i) * n`.
 pub fn reflect_vec<N: Number, D: Dimension>(i: &TVec<N, D>, n: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     let _2 = N::one() + N::one();
     i - n * (n.dot(i) * _2)
 }
 
 /// For the incident vector `i` and surface normal `n`, and the ratio of indices of refraction `eta`, return the refraction vector.
 pub fn refract_vec<N: Real, D: Dimension>(i: &TVec<N, D>, n: &TVec<N, D>, eta: N) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     let ni = n.dot(i);
     let k = N::one() - eta * eta * (N::one() - ni * ni);
 

nalgebra-glm/src/gtc/matrix_access.rs

@@ -10,7 +10,10 @@ use traits::{Alloc, Dimension};
 /// * [`row`](fn.row.html)
 /// * [`set_column`](fn.set_column.html)
 /// * [`set_row`](fn.set_row.html)
-pub fn column<N: Scalar, R: Dimension, C: Dimension>(m: &TMat<N, R, C>, index: usize) -> TVec<N, R>
+pub fn column<N: Scalar, R: Dimension, C: Dimension>(
+    m: &TMat<N, R, C>,
+    index: usize,
+) -> TVec<N, R>
 where
     DefaultAllocator: Alloc<N, R, C>,
 {
@@ -45,9 +48,7 @@ where
 /// * [`set_column`](fn.set_column.html)
 /// * [`set_row`](fn.set_row.html)
 pub fn row<N: Scalar, R: Dimension, C: Dimension>(m: &TMat<N, R, C>, index: usize) -> TVec<N, C>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+where DefaultAllocator: Alloc<N, R, C> {
     m.row(index).into_owned().transpose()
 }
 

nalgebra-glm/src/gtc/matrix_inverse.rs

@@ -5,18 +5,14 @@ use traits::{Alloc, Dimension};
 
 /// Fast matrix inverse for affine matrix.
 pub fn affine_inverse<N: Real, D: Dimension>(m: TMat<N, D, D>) -> TMat<N, D, D>
-where
-    DefaultAllocator: Alloc<N, D, D>,
-{
+where DefaultAllocator: Alloc<N, D, D> {
     // FIXME: this should be optimized.
     m.try_inverse().unwrap_or_else(TMat::<_, D, D>::zeros)
 }
 
 /// Compute the transpose of the inverse of a matrix.
 pub fn inverse_transpose<N: Real, D: Dimension>(m: TMat<N, D, D>) -> TMat<N, D, D>
-where
-    DefaultAllocator: Alloc<N, D, D>,
-{
+where DefaultAllocator: Alloc<N, D, D> {
     m.try_inverse()
         .unwrap_or_else(TMat::<_, D, D>::zeros)
         .transpose()

nalgebra-glm/src/gtc/type_ptr.rs

@@ -384,16 +384,12 @@ pub fn make_vec4<N: Scalar>(ptr: &[N]) -> TVec4<N> {
 
 /// Converts a matrix or vector to a slice arranged in column-major order.
 pub fn value_ptr<N: Scalar, R: Dimension, C: Dimension>(x: &TMat<N, R, C>) -> &[N]
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+where DefaultAllocator: Alloc<N, R, C> {
     x.as_slice()
 }
 
 /// Converts a matrix or vector to a mutable slice arranged in column-major order.
 pub fn value_ptr_mut<N: Scalar, R: Dimension, C: Dimension>(x: &mut TMat<N, R, C>) -> &mut [N]
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+where DefaultAllocator: Alloc<N, R, C> {
     x.as_mut_slice()
 }

nalgebra-glm/src/gtx/component_wise.rs

@@ -22,9 +22,7 @@ use traits::{Alloc, Dimension, Number};
 /// * [`comp_min`](fn.comp_min.html)
 /// * [`comp_mul`](fn.comp_mul.html)
 pub fn comp_add<N: Number, R: Dimension, C: Dimension>(m: &TMat<N, R, C>) -> N
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+where DefaultAllocator: Alloc<N, R, C> {
     m.iter().fold(N::zero(), |x, y| x + *y)
 }
 
@@ -51,9 +49,7 @@ where
 /// * [`max3`](fn.max3.html)
 /// * [`max4`](fn.max4.html)
 pub fn comp_max<N: Number, R: Dimension, C: Dimension>(m: &TMat<N, R, C>) -> N
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+where DefaultAllocator: Alloc<N, R, C> {
     m.iter().fold(N::min_value(), |x, y| na::sup(&x, y))
 }
 
@@ -80,9 +76,7 @@ where
 /// * [`min3`](fn.min3.html)
 /// * [`min4`](fn.min4.html)
 pub fn comp_min<N: Number, R: Dimension, C: Dimension>(m: &TMat<N, R, C>) -> N
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+where DefaultAllocator: Alloc<N, R, C> {
     m.iter().fold(N::max_value(), |x, y| na::inf(&x, y))
 }
 
@@ -105,9 +99,7 @@ where
 /// * [`comp_max`](fn.comp_max.html)
 /// * [`comp_min`](fn.comp_min.html)
 pub fn comp_mul<N: Number, R: Dimension, C: Dimension>(m: &TMat<N, R, C>) -> N
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+where DefaultAllocator: Alloc<N, R, C> {
     m.iter().fold(N::one(), |x, y| x * *y)
 }
 

nalgebra-glm/src/gtx/norm.rs

@@ -9,9 +9,7 @@ use traits::{Alloc, Dimension};
 ///
 /// * [`distance`](fn.distance.html)
 pub fn distance2<N: Real, D: Dimension>(p0: &TVec<N, D>, p1: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     (p1 - p0).norm_squared()
 }
 
@@ -23,9 +21,7 @@ where
 /// * [`l2_distance`](fn.l2_distance.html)
 /// * [`l2_norm`](fn.l2_norm.html)
 pub fn l1_distance<N: Real, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     l1_norm(&(y - x))
 }
 
@@ -40,9 +36,7 @@ where
 /// * [`l2_distance`](fn.l2_distance.html)
 /// * [`l2_norm`](fn.l2_norm.html)
 pub fn l1_norm<N: Real, D: Dimension>(v: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     ::comp_add(&v.abs())
 }
 
@@ -61,9 +55,7 @@ where
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude2`](fn.magnitude2.html)
 pub fn l2_distance<N: Real, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     l2_norm(&(y - x))
 }
 
@@ -84,9 +76,7 @@ where
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude2`](fn.magnitude2.html)
 pub fn l2_norm<N: Real, D: Dimension>(x: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.norm()
 }
 
@@ -102,9 +92,7 @@ where
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`magnitude2`](fn.magnitude2.html)
 pub fn length2<N: Real, D: Dimension>(x: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.norm_squared()
 }
 
@@ -120,9 +108,7 @@ where
 /// * [`magnitude`](fn.magnitude.html)
 /// * [`nalgebra::norm_squared`](../nalgebra/fn.norm_squared.html)
 pub fn magnitude2<N: Real, D: Dimension>(x: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.norm_squared()
 }
 

nalgebra-glm/src/gtx/normalize_dot.rs

@@ -11,9 +11,7 @@ use traits::{Alloc, Dimension};
 ///
 /// * [`normalize_dot`](fn.normalize_dot.html`)
 pub fn fast_normalize_dot<N: Real, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     // XXX: improve those.
     x.normalize().dot(&y.normalize())
 }
@@ -24,9 +22,7 @@ where
 ///
 /// * [`fast_normalize_dot`](fn.fast_normalize_dot.html`)
 pub fn normalize_dot<N: Real, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     // XXX: improve those.
     x.normalize().dot(&y.normalize())
 }

nalgebra-glm/src/gtx/vector_angle.rs

@@ -5,9 +5,7 @@ use traits::{Alloc, Dimension};
 
 /// The angle between two vectors.
 pub fn angle<N: Real, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.angle(y)
 }
 

nalgebra-glm/src/gtx/vector_query.rs

@@ -22,7 +22,11 @@ pub fn are_collinear2d<N: Number>(v0: &TVec2<N>, v1: &TVec2<N>, epsilon: N) -> b
 }
 
 /// Returns `true` if two vectors are orthogonal (up to an epsilon).
-pub fn are_orthogonal<N: Number, D: Dimension>(v0: &TVec<N, D>, v1: &TVec<N, D>, epsilon: N) -> bool
+pub fn are_orthogonal<N: Number, D: Dimension>(
+    v0: &TVec<N, D>,
+    v1: &TVec<N, D>,
+    epsilon: N,
+) -> bool
 where
     DefaultAllocator: Alloc<N, D>,
 {
@@ -36,24 +40,18 @@ where
 
 /// Returns `true` if all the components of `v` are zero (up to an epsilon).
 pub fn is_comp_null<N: Number, D: Dimension>(v: &TVec<N, D>, epsilon: N) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     v.map(|x| abs_diff_eq!(x, N::zero(), epsilon = epsilon))
 }
 
 /// Returns `true` if `v` has a magnitude of 1 (up to an epsilon).
 pub fn is_normalized<N: Real, D: Dimension>(v: &TVec<N, D>, epsilon: N) -> bool
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     abs_diff_eq!(v.norm_squared(), N::one(), epsilon = epsilon * epsilon)
 }
 
 /// Returns `true` if `v` is zero (up to an epsilon).
 pub fn is_null<N: Number, D: Dimension>(v: &TVec<N, D>, epsilon: N) -> bool
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     abs_diff_eq!(*v, TVec::<N, D>::zeros(), epsilon = epsilon)
 }

nalgebra-glm/src/lib.rs

@@ -110,8 +110,6 @@
    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")]
-
 extern crate num_traits as num;
 #[macro_use]
 extern crate approx;
@@ -122,9 +120,8 @@ pub use aliases::*;
 pub use common::{
     abs, ceil, clamp, clamp_scalar, clamp_vec, float_bits_to_int, float_bits_to_int_vec,
     float_bits_to_uint, float_bits_to_uint_vec, floor, fract, int_bits_to_float,
-    int_bits_to_float_vec, lerp, lerp_scalar, lerp_vec, mix, mix_scalar, mix_vec, modf, modf_vec,
-    round, sign, smoothstep, step, step_scalar, step_vec, trunc, uint_bits_to_float,
-    uint_bits_to_float_scalar,
+    int_bits_to_float_vec, mix, modf, modf_vec, round, sign, smoothstep, step, step_scalar,
+    step_vec, trunc, uint_bits_to_float, uint_bits_to_float_scalar,
 };
 pub use constructors::*;
 pub use exponential::{exp, exp2, inversesqrt, log, log2, pow, sqrt};

nalgebra-glm/src/matrix.rs

@@ -5,17 +5,13 @@ use traits::{Alloc, Dimension, Number};
 
 /// The determinant of the matrix `m`.
 pub fn determinant<N: Real, D: Dimension>(m: &TMat<N, D, D>) -> N
-where
-    DefaultAllocator: Alloc<N, D, D>,
-{
+where DefaultAllocator: Alloc<N, D, D> {
     m.determinant()
 }
 
 /// The inverse of the matrix `m`.
 pub fn inverse<N: Real, D: Dimension>(m: &TMat<N, D, D>) -> TMat<N, D, D>
-where
-    DefaultAllocator: Alloc<N, D, D>,
-{
+where DefaultAllocator: Alloc<N, D, D> {
     m.clone()
         .try_inverse()
         .unwrap_or_else(TMat::<N, D, D>::zeros)
@@ -45,8 +41,6 @@ where
 
 /// The transpose of the matrix `m`.
 pub fn transpose<N: Scalar, R: Dimension, C: Dimension>(x: &TMat<N, R, C>) -> TMat<N, C, R>
-where
-    DefaultAllocator: Alloc<N, R, C>,
-{
+where DefaultAllocator: Alloc<N, R, C> {
     x.transpose()
 }

nalgebra-glm/src/traits.rs

@@ -50,8 +50,7 @@ pub trait Alloc<N: Scalar, R: Dimension, C: Dimension = U1>:
 {
 }
 
-impl<N: Scalar, R: Dimension, C: Dimension, T> Alloc<N, R, C> for T where
-    T: Allocator<N, R>
+impl<N: Scalar, R: Dimension, C: Dimension, T> Alloc<N, R, C> for T where T: Allocator<N, R>
         + Allocator<N, C>
         + Allocator<N, U1, R>
         + Allocator<N, U1, C>

nalgebra-glm/src/trigonometric.rs

@@ -5,120 +5,90 @@ use traits::{Alloc, Dimension};
 
 /// Component-wise arc-cosinus.
 pub fn acos<N: Real, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|e| e.acos())
 }
 
 /// Component-wise hyperbolic arc-cosinus.
 pub fn acosh<N: Real, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|e| e.acosh())
 }
 
 /// Component-wise arc-sinus.
 pub fn asin<N: Real, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|e| e.asin())
 }
 
 /// Component-wise hyperbolic arc-sinus.
 pub fn asinh<N: Real, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|e| e.asinh())
 }
 
 /// Component-wise arc-tangent of `y / x`.
 pub fn atan2<N: Real, D: Dimension>(y: &TVec<N, D>, x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     y.zip_map(x, |y, x| y.atan2(x))
 }
 
 /// Component-wise arc-tangent.
 pub fn atan<N: Real, D: Dimension>(y_over_x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     y_over_x.map(|e| e.atan())
 }
 
 /// Component-wise hyperbolic arc-tangent.
 pub fn atanh<N: Real, D: Dimension>(x: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.map(|e| e.atanh())
 }
 
 /// Component-wise cosinus.
 pub fn cos<N: Real, D: Dimension>(angle: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     angle.map(|e| e.cos())
 }
 
 /// Component-wise hyperbolic cosinus.
 pub fn cosh<N: Real, D: Dimension>(angle: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     angle.map(|e| e.cosh())
 }
 
 /// Component-wise conversion from radians to degrees.
 pub fn degrees<N: Real, D: Dimension>(radians: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     radians.map(|e| e * na::convert(180.0) / N::pi())
 }
 
 /// Component-wise conversion fro degrees to radians.
 pub fn radians<N: Real, D: Dimension>(degrees: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     degrees.map(|e| e * N::pi() / na::convert(180.0))
 }
 
 /// Component-wise sinus.
 pub fn sin<N: Real, D: Dimension>(angle: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     angle.map(|e| e.sin())
 }
 
 /// Component-wise hyperbolic sinus.
 pub fn sinh<N: Real, D: Dimension>(angle: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     angle.map(|e| e.sinh())
 }
 
 /// Component-wise tangent.
 pub fn tan<N: Real, D: Dimension>(angle: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     angle.map(|e| e.tan())
 }
 
 /// Component-wise hyperbolic tangent.
 pub fn tanh<N: Real, D: Dimension>(angle: &TVec<N, D>) -> TVec<N, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     angle.map(|e| e.tanh())
 }

nalgebra-glm/src/vector_relational.rs

@@ -21,9 +21,7 @@ use traits::{Alloc, Dimension, Number};
 /// * [`any`](fn.any.html)
 /// * [`not`](fn.not.html)
 pub fn all<D: Dimension>(v: &TVec<bool, D>) -> bool
-where
-    DefaultAllocator: Alloc<bool, D>,
-{
+where DefaultAllocator: Alloc<bool, D> {
     v.iter().all(|x| *x)
 }
 
@@ -48,9 +46,7 @@ where
 /// * [`all`](fn.all.html)
 /// * [`not`](fn.not.html)
 pub fn any<D: Dimension>(v: &TVec<bool, D>) -> bool
-where
-    DefaultAllocator: Alloc<bool, D>,
-{
+where DefaultAllocator: Alloc<bool, D> {
     v.iter().any(|x| *x)
 }
 
@@ -74,9 +70,7 @@ where
 /// * [`not`](fn.not.html)
 /// * [`not_equal`](fn.not_equal.html)
 pub fn equal<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.zip_map(y, |x, y| x == y)
 }
 
@@ -100,9 +94,7 @@ where
 /// * [`not`](fn.not.html)
 /// * [`not_equal`](fn.not_equal.html)
 pub fn greater_than<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.zip_map(y, |x, y| x > y)
 }
 
@@ -125,7 +117,10 @@ where
 /// * [`less_than_equal`](fn.less_than_equal.html)
 /// * [`not`](fn.not.html)
 /// * [`not_equal`](fn.not_equal.html)
-pub fn greater_than_equal<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<bool, D>
+pub fn greater_than_equal<N: Number, D: Dimension>(
+    x: &TVec<N, D>,
+    y: &TVec<N, D>,
+) -> TVec<bool, D>
 where
     DefaultAllocator: Alloc<N, D>,
 {
@@ -152,9 +147,7 @@ where
 /// * [`not`](fn.not.html)
 /// * [`not_equal`](fn.not_equal.html)
 pub fn less_than<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.zip_map(y, |x, y| x < y)
 }
 
@@ -178,9 +171,7 @@ where
 /// * [`not`](fn.not.html)
 /// * [`not_equal`](fn.not_equal.html)
 pub fn less_than_equal<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.zip_map(y, |x, y| x <= y)
 }
 
@@ -205,9 +196,7 @@ where
 /// * [`less_than_equal`](fn.less_than_equal.html)
 /// * [`not_equal`](fn.not_equal.html)
 pub fn not<D: Dimension>(v: &TVec<bool, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<bool, D>,
-{
+where DefaultAllocator: Alloc<bool, D> {
     v.map(|x| !x)
 }
 
@@ -231,8 +220,6 @@ where
 /// * [`less_than_equal`](fn.less_than_equal.html)
 /// * [`not`](fn.not.html)
 pub fn not_equal<N: Number, D: Dimension>(x: &TVec<N, D>, y: &TVec<N, D>) -> TVec<bool, D>
-where
-    DefaultAllocator: Alloc<N, D>,
-{
+where DefaultAllocator: Alloc<N, D> {
     x.zip_map(y, |x, y| x != y)
 }

nalgebra-lapack/benches/linalg/hessenberg.rs

@@ -1,6 +1,6 @@
-use test::{self, Bencher};
 use na::{DMatrix, Matrix4};
 use nl::Hessenberg;
+use test::{self, Bencher};
 
 #[bench]
 fn hessenberg_decompose_100x100(bh: &mut Bencher) {

nalgebra-lapack/benches/linalg/lu.rs

@@ -1,6 +1,6 @@
-use test::{self, Bencher};
 use na::{DMatrix, Matrix4};
 use nl::LU;
+use test::{self, Bencher};
 
 #[bench]
 fn lu_decompose_100x100(bh: &mut Bencher) {

nalgebra-lapack/benches/linalg/mod.rs

@@ -1,3 +1,3 @@
-mod qr;
-mod lu;
 mod hessenberg;
+mod lu;
+mod qr;

nalgebra-lapack/benches/linalg/qr.rs

@@ -1,6 +1,6 @@
-use test::{self, Bencher};
 use na::{DMatrix, Matrix4};
 use nl::QR;
+use test::{self, Bencher};
 
 #[bench]
 fn qr_decompose_100x100(bh: &mut Bencher) {

nalgebra-lapack/src/cholesky.rs

@@ -1,5 +1,5 @@
 #[cfg(feature = "serde-serialize")]
-use serde::{Serialize, Deserialize};
+use serde::{Deserialize, Serialize};
 
 use num::Zero;
 use num_complex::Complex;
@@ -15,26 +15,21 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            serialize = "DefaultAllocator: Allocator<N, D>,
+    serde(bound(
+        serialize = "DefaultAllocator: Allocator<N, D>,
          MatrixN<N, D>: Serialize"
-        )
-    )
+    ))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            deserialize = "DefaultAllocator: Allocator<N, D>,
+    serde(bound(
+        deserialize = "DefaultAllocator: Allocator<N, D>,
          MatrixN<N, D>: Deserialize<'de>"
-        )
-    )
+    ))
 )]
 #[derive(Clone, Debug)]
 pub struct Cholesky<N: Scalar, D: Dim>
-where
-    DefaultAllocator: Allocator<N, D, D>,
+where DefaultAllocator: Allocator<N, D, D>
 {
     l: MatrixN<N, D>,
 }
@@ -43,12 +38,10 @@ impl<N: Scalar, D: Dim> Copy for Cholesky<N, D>
 where
     DefaultAllocator: Allocator<N, D, D>,
     MatrixN<N, D>: Copy,
-{
-}
+{}
 
 impl<N: CholeskyScalar + Zero, D: Dim> Cholesky<N, D>
-where
-    DefaultAllocator: Allocator<N, D, D>,
+where DefaultAllocator: Allocator<N, D, D>
 {
     /// Computes the cholesky decomposition of the given symmetric-definite-positive square
     /// matrix.
@@ -124,9 +117,7 @@ where
     /// Solves in-place the symmetric-definite-positive linear system `self * x = b`, where `x` is
     /// the unknown to be determined.
     pub fn solve_mut<R2: Dim, C2: Dim>(&self, b: &mut MatrixMN<N, R2, C2>) -> bool
-    where
-        DefaultAllocator: Allocator<N, R2, C2>,
-    {
+    where DefaultAllocator: Allocator<N, R2, C2> {
         let dim = self.l.nrows();
 
         assert!(

nalgebra-lapack/src/eigen.rs

@@ -1,5 +1,5 @@
 #[cfg(feature = "serde-serialize")]
-use serde::{Serialize, Deserialize};
+use serde::{Deserialize, Serialize};
 
 use num::Zero;
 use num_complex::Complex;
@@ -18,28 +18,23 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            serialize = "DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
+    serde(bound(
+        serialize = "DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
          VectorN<N, D>: Serialize,
          MatrixN<N, D>: Serialize"
-        )
-    )
+    ))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            deserialize = "DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
+    serde(bound(
+        deserialize = "DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
          VectorN<N, D>: Serialize,
          MatrixN<N, D>: Deserialize<'de>"
-        )
-    )
+    ))
 )]
 #[derive(Clone, Debug)]
 pub struct Eigen<N: Scalar, D: Dim>
-where
-    DefaultAllocator: Allocator<N, D> + Allocator<N, D, D>,
+where DefaultAllocator: Allocator<N, D> + Allocator<N, D, D>
 {
     /// The eigenvalues of the decomposed matrix.
     pub eigenvalues: VectorN<N, D>,
@@ -54,12 +49,10 @@ where
     DefaultAllocator: Allocator<N, D> + Allocator<N, D, D>,
     VectorN<N, D>: Copy,
     MatrixN<N, D>: Copy,
-{
-}
+{}
 
 impl<N: EigenScalar + Real, D: Dim> Eigen<N, D>
-where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>
 {
     /// Computes the eigenvalues and eigenvectors of the square matrix `m`.
     ///
@@ -68,7 +61,8 @@ where
         mut m: MatrixN<N, D>,
         left_eigenvectors: bool,
         eigenvectors: bool,
-    ) -> Option<Eigen<N, D>> {
+    ) -> Option<Eigen<N, D>>
+    {
         assert!(
             m.is_square(),
             "Unable to compute the eigenvalue decomposition of a non-square matrix."
@@ -234,9 +228,7 @@ where
     ///
     /// Panics if the eigenvalue computation does not converge.
     pub fn complex_eigenvalues(mut m: MatrixN<N, D>) -> VectorN<Complex<N>, D>
-    where
-        DefaultAllocator: Allocator<Complex<N>, D>,
-    {
+    where DefaultAllocator: Allocator<Complex<N>, D> {
         assert!(
             m.is_square(),
             "Unable to compute the eigenvalue decomposition of a non-square matrix."

nalgebra-lapack/src/hessenberg.rs

@@ -13,30 +13,25 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            serialize = "DefaultAllocator: Allocator<N, D, D> +
+    serde(bound(
+        serialize = "DefaultAllocator: Allocator<N, D, D> +
                            Allocator<N, DimDiff<D, U1>>,
          MatrixN<N, D>: Serialize,
          VectorN<N, DimDiff<D, U1>>: Serialize"
-        )
-    )
+    ))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            deserialize = "DefaultAllocator: Allocator<N, D, D> +
+    serde(bound(
+        deserialize = "DefaultAllocator: Allocator<N, D, D> +
                            Allocator<N, DimDiff<D, U1>>,
          MatrixN<N, D>: Deserialize<'de>,
          VectorN<N, DimDiff<D, U1>>: Deserialize<'de>"
-        )
-    )
+    ))
 )]
 #[derive(Clone, Debug)]
 pub struct Hessenberg<N: Scalar, D: DimSub<U1>>
-where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
+where DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>
 {
     h: MatrixN<N, D>,
     tau: VectorN<N, DimDiff<D, U1>>,
@@ -47,12 +42,10 @@ where
     DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
     MatrixN<N, D>: Copy,
     VectorN<N, DimDiff<D, U1>>: Copy,
-{
-}
+{}
 
 impl<N: HessenbergScalar + Zero, D: DimSub<U1>> Hessenberg<N, D>
-where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
+where DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>
 {
     /// Computes the hessenberg decomposition of the matrix `m`.
     pub fn new(mut m: MatrixN<N, D>) -> Hessenberg<N, D> {
@@ -104,8 +97,7 @@ where
 }
 
 impl<N: HessenbergReal + Zero, D: DimSub<U1>> Hessenberg<N, D>
-where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>,
+where DefaultAllocator: Allocator<N, D, D> + Allocator<N, DimDiff<D, U1>>
 {
     /// Computes the matrices `(Q, H)` of this decomposition.
     #[inline]

nalgebra-lapack/src/lu.rs

@@ -20,30 +20,25 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            serialize = "DefaultAllocator: Allocator<N, R, C> +
+    serde(bound(
+        serialize = "DefaultAllocator: Allocator<N, R, C> +
                            Allocator<i32, DimMinimum<R, C>>,
          MatrixMN<N, R, C>: Serialize,
          PermutationSequence<DimMinimum<R, C>>: Serialize"
-        )
-    )
+    ))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            deserialize = "DefaultAllocator: Allocator<N, R, C> +
+    serde(bound(
+        deserialize = "DefaultAllocator: Allocator<N, R, C> +
                            Allocator<i32, DimMinimum<R, C>>,
          MatrixMN<N, R, C>: Deserialize<'de>,
          PermutationSequence<DimMinimum<R, C>>: Deserialize<'de>"
-        )
-    )
+    ))
 )]
 #[derive(Clone, Debug)]
 pub struct LU<N: Scalar, R: DimMin<C>, C: Dim>
-where
-    DefaultAllocator: Allocator<i32, DimMinimum<R, C>> + Allocator<N, R, C>,
+where DefaultAllocator: Allocator<i32, DimMinimum<R, C>> + Allocator<N, R, C>
 {
     lu: MatrixMN<N, R, C>,
     p: VectorN<i32, DimMinimum<R, C>>,
@@ -54,8 +49,7 @@ where
     DefaultAllocator: Allocator<N, R, C> + Allocator<i32, DimMinimum<R, C>>,
     MatrixMN<N, R, C>: Copy,
     VectorN<i32, DimMinimum<R, C>>: Copy,
-{
-}
+{}
 
 impl<N: LUScalar, R: Dim, C: Dim> LU<N, R, C>
 where
@@ -139,9 +133,7 @@ where
     /// Applies the permutation matrix to a given matrix or vector in-place.
     #[inline]
     pub fn permute<C2: Dim>(&self, rhs: &mut MatrixMN<N, R, C2>)
-    where
-        DefaultAllocator: Allocator<N, R, C2>,
-    {
+    where DefaultAllocator: Allocator<N, R, C2> {
         let (nrows, ncols) = rhs.shape();
 
         N::xlaswp(
@@ -156,9 +148,7 @@ where
     }
 
     fn generic_solve_mut<R2: Dim, C2: Dim>(&self, trans: u8, b: &mut MatrixMN<N, R2, C2>) -> bool
-    where
-        DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2>,
-    {
+    where DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2> {
         let dim = self.lu.nrows();
 
         assert!(
@@ -246,9 +236,7 @@ where
     ///
     /// Returns `false` if no solution was found (the decomposed matrix is singular).
     pub fn solve_mut<R2: Dim, C2: Dim>(&self, b: &mut MatrixMN<N, R2, C2>) -> bool
-    where
-        DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2>,
-    {
+    where DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2> {
         self.generic_solve_mut(b'N', b)
     }
 
@@ -257,9 +245,7 @@ where
     ///
     /// Returns `false` if no solution was found (the decomposed matrix is singular).
     pub fn solve_transpose_mut<R2: Dim, C2: Dim>(&self, b: &mut MatrixMN<N, R2, C2>) -> bool
-    where
-        DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2>,
-    {
+    where DefaultAllocator: Allocator<N, R2, C2> + Allocator<i32, R2> {
         self.generic_solve_mut(b'T', b)
     }
 

nalgebra-lapack/src/qr.rs

@@ -1,5 +1,5 @@
 #[cfg(feature = "serde-serialize")]
-use serde::{Serialize, Deserialize};
+use serde::{Deserialize, Serialize};
 
 use num::Zero;
 use num_complex::Complex;
@@ -16,30 +16,25 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            serialize = "DefaultAllocator: Allocator<N, R, C> +
+    serde(bound(
+        serialize = "DefaultAllocator: Allocator<N, R, C> +
                            Allocator<N, DimMinimum<R, C>>,
          MatrixMN<N, R, C>: Serialize,
          VectorN<N, DimMinimum<R, C>>: Serialize"
-        )
-    )
+    ))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            deserialize = "DefaultAllocator: Allocator<N, R, C> +
+    serde(bound(
+        deserialize = "DefaultAllocator: Allocator<N, R, C> +
                            Allocator<N, DimMinimum<R, C>>,
          MatrixMN<N, R, C>: Deserialize<'de>,
          VectorN<N, DimMinimum<R, C>>: Deserialize<'de>"
-        )
-    )
+    ))
 )]
 #[derive(Clone, Debug)]
 pub struct QR<N: Scalar, R: DimMin<C>, C: Dim>
-where
-    DefaultAllocator: Allocator<N, R, C> + Allocator<N, DimMinimum<R, C>>,
+where DefaultAllocator: Allocator<N, R, C> + Allocator<N, DimMinimum<R, C>>
 {
     qr: MatrixMN<N, R, C>,
     tau: VectorN<N, DimMinimum<R, C>>,
@@ -50,15 +45,13 @@ where
     DefaultAllocator: Allocator<N, R, C> + Allocator<N, DimMinimum<R, C>>,
     MatrixMN<N, R, C>: Copy,
     VectorN<N, DimMinimum<R, C>>: Copy,
-{
-}
+{}
 
 impl<N: QRScalar + Zero, R: DimMin<C>, C: Dim> QR<N, R, C>
-where
-    DefaultAllocator: Allocator<N, R, C>
+where DefaultAllocator: Allocator<N, R, C>
         + Allocator<N, R, DimMinimum<R, C>>
         + Allocator<N, DimMinimum<R, C>, C>
-        + Allocator<N, DimMinimum<R, C>>,
+        + Allocator<N, DimMinimum<R, C>>
 {
     /// Computes the QR decomposition of the matrix `m`.
     pub fn new(mut m: MatrixMN<N, R, C>) -> QR<N, R, C> {
@@ -105,11 +98,10 @@ where
 }
 
 impl<N: QRReal + Zero, R: DimMin<C>, C: Dim> QR<N, R, C>
-where
-    DefaultAllocator: Allocator<N, R, C>
+where DefaultAllocator: Allocator<N, R, C>
         + Allocator<N, R, DimMinimum<R, C>>
         + Allocator<N, DimMinimum<R, C>, C>
-        + Allocator<N, DimMinimum<R, C>>,
+        + Allocator<N, DimMinimum<R, C>>
 {
     /// Retrieves the matrices `(Q, R)` of this decompositions.
     pub fn unpack(
@@ -131,7 +123,8 @@ where
             return MatrixMN::from_element_generic(nrows, min_nrows_ncols, N::zero());
         }
 
-        let mut q = self.qr
+        let mut q = self
+            .qr
             .generic_slice((0, 0), (nrows, min_nrows_ncols))
             .into_owned();
 

nalgebra-lapack/src/schur.rs

@@ -1,5 +1,5 @@
 #[cfg(feature = "serde-serialize")]
-use serde::{Serialize, Deserialize};
+use serde::{Deserialize, Serialize};
 
 use num::Zero;
 use num_complex::Complex;
@@ -18,28 +18,23 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            serialize = "DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
+    serde(bound(
+        serialize = "DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
          VectorN<N, D>: Serialize,
          MatrixN<N, D>: Serialize"
-        )
-    )
+    ))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            deserialize = "DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
+    serde(bound(
+        deserialize = "DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
          VectorN<N, D>: Serialize,
          MatrixN<N, D>: Deserialize<'de>"
-        )
-    )
+    ))
 )]
 #[derive(Clone, Debug)]
 pub struct RealSchur<N: Scalar, D: Dim>
-where
-    DefaultAllocator: Allocator<N, D> + Allocator<N, D, D>,
+where DefaultAllocator: Allocator<N, D> + Allocator<N, D, D>
 {
     re: VectorN<N, D>,
     im: VectorN<N, D>,
@@ -52,12 +47,10 @@ where
     DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
     MatrixN<N, D>: Copy,
     VectorN<N, D>: Copy,
-{
-}
+{}
 
 impl<N: RealSchurScalar + Real, D: Dim> RealSchur<N, D>
-where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>
 {
     /// Computes the eigenvalues and real Schur form of the matrix `m`.
     ///
@@ -152,9 +145,7 @@ where
 
     /// Computes the complex eigenvalues of the decomposed matrix.
     pub fn complex_eigenvalues(&self) -> VectorN<Complex<N>, D>
-    where
-        DefaultAllocator: Allocator<Complex<N>, D>,
-    {
+    where DefaultAllocator: Allocator<Complex<N>, D> {
         let mut out = unsafe { VectorN::new_uninitialized_generic(self.t.data.shape().0, U1) };
 
         for i in 0..out.len() {

nalgebra-lapack/src/svd.rs

@@ -1,5 +1,5 @@
 #[cfg(feature = "serde-serialize")]
-use serde::{Serialize, Deserialize};
+use serde::{Deserialize, Serialize};
 
 use num::Signed;
 use std::cmp;
@@ -15,34 +15,29 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            serialize = "DefaultAllocator: Allocator<N, DimMinimum<R, C>> +
+    serde(bound(
+        serialize = "DefaultAllocator: Allocator<N, DimMinimum<R, C>> +
                            Allocator<N, R, R> +
                            Allocator<N, C, C>,
          MatrixN<N, R>: Serialize,
          MatrixN<N, C>: Serialize,
          VectorN<N, DimMinimum<R, C>>: Serialize"
-        )
-    )
+    ))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            serialize = "DefaultAllocator: Allocator<N, DimMinimum<R, C>> +
+    serde(bound(
+        serialize = "DefaultAllocator: Allocator<N, DimMinimum<R, C>> +
                            Allocator<N, R, R> +
                            Allocator<N, C, C>,
          MatrixN<N, R>: Deserialize<'de>,
          MatrixN<N, C>: Deserialize<'de>,
          VectorN<N, DimMinimum<R, C>>: Deserialize<'de>"
-        )
-    )
+    ))
 )]
 #[derive(Clone, Debug)]
 pub struct SVD<N: Scalar, R: DimMin<C>, C: Dim>
-where
-    DefaultAllocator: Allocator<N, R, R> + Allocator<N, DimMinimum<R, C>> + Allocator<N, C, C>,
+where DefaultAllocator: Allocator<N, R, R> + Allocator<N, DimMinimum<R, C>> + Allocator<N, C, C>
 {
     /// The left-singular vectors `U` of this SVD.
     pub u: MatrixN<N, R>, // FIXME: should be MatrixMN<N, R, DimMinimum<R, C>>
@@ -58,28 +53,25 @@ where
     MatrixMN<N, R, R>: Copy,
     MatrixMN<N, C, C>: Copy,
     VectorN<N, DimMinimum<R, C>>: Copy,
-{
-}
+{}
 
 /// Trait implemented by floats (`f32`, `f64`) and complex floats (`Complex<f32>`, `Complex<f64>`)
 /// supported by the Singular Value Decompotition.
 pub trait SVDScalar<R: DimMin<C>, C: Dim>: Scalar
-where
-    DefaultAllocator: Allocator<Self, R, R>
+where DefaultAllocator: Allocator<Self, R, R>
         + Allocator<Self, R, C>
         + Allocator<Self, DimMinimum<R, C>>
-        + Allocator<Self, C, C>,
+        + Allocator<Self, C, C>
 {
     /// Computes the SVD decomposition of `m`.
     fn compute(m: MatrixMN<Self, R, C>) -> Option<SVD<Self, R, C>>;
 }
 
 impl<N: SVDScalar<R, C>, R: DimMin<C>, C: Dim> SVD<N, R, C>
-where
-    DefaultAllocator: Allocator<N, R, R>
+where DefaultAllocator: Allocator<N, R, R>
         + Allocator<N, R, C>
         + Allocator<N, DimMinimum<R, C>>
-        + Allocator<N, C, C>,
+        + Allocator<N, C, C>
 {
     /// Computes the Singular Value Decomposition of `matrix`.
     pub fn new(m: MatrixMN<N, R, C>) -> Option<Self> {

nalgebra-lapack/src/symmetric_eigen.rs

@@ -1,5 +1,5 @@
 #[cfg(feature = "serde-serialize")]
-use serde::{Serialize, Deserialize};
+use serde::{Deserialize, Serialize};
 
 use num::Zero;
 use std::ops::MulAssign;
@@ -18,30 +18,25 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            serialize = "DefaultAllocator: Allocator<N, D, D> +
+    serde(bound(
+        serialize = "DefaultAllocator: Allocator<N, D, D> +
                            Allocator<N, D>,
          VectorN<N, D>: Serialize,
          MatrixN<N, D>: Serialize"
-        )
-    )
+    ))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            deserialize = "DefaultAllocator: Allocator<N, D, D> +
+    serde(bound(
+        deserialize = "DefaultAllocator: Allocator<N, D, D> +
                            Allocator<N, D>,
          VectorN<N, D>: Deserialize<'de>,
          MatrixN<N, D>: Deserialize<'de>"
-        )
-    )
+    ))
 )]
 #[derive(Clone, Debug)]
 pub struct SymmetricEigen<N: Scalar, D: Dim>
-where
-    DefaultAllocator: Allocator<N, D> + Allocator<N, D, D>,
+where DefaultAllocator: Allocator<N, D> + Allocator<N, D, D>
 {
     /// The eigenvectors of the decomposed matrix.
     pub eigenvectors: MatrixN<N, D>,
@@ -55,12 +50,10 @@ where
     DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
     MatrixN<N, D>: Copy,
     VectorN<N, D>: Copy,
-{
-}
+{}
 
 impl<N: SymmetricEigenScalar + Real, D: Dim> SymmetricEigen<N, D>
-where
-    DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>
 {
     /// Computes the eigenvalues and eigenvectors of the symmetric matrix `m`.
     ///
@@ -89,7 +82,8 @@ where
     fn do_decompose(
         mut m: MatrixN<N, D>,
         eigenvectors: bool,
-    ) -> Option<(VectorN<N, D>, Option<MatrixN<N, D>>)> {
+    ) -> Option<(VectorN<N, D>, Option<MatrixN<N, D>>)>
+    {
         assert!(
             m.is_square(),
             "Unable to compute the eigenvalue decomposition of a non-square matrix."

nalgebra-lapack/tests/linalg/cholesky.rs

@@ -1,7 +1,7 @@
 use std::cmp;
 
-use nl::Cholesky;
 use na::{DMatrix, DVector, Matrix3, Matrix4, Matrix4x3, Vector4};
+use nl::Cholesky;
 
 quickcheck!{
     fn cholesky(m: DMatrix<f64>) -> bool {

nalgebra-lapack/tests/linalg/lu.rs

@@ -1,7 +1,7 @@
 use std::cmp;
 
-use nl::LU;
 use na::{DMatrix, DVector, Matrix3x4, Matrix4, Matrix4x3, Vector4};
+use nl::LU;
 
 quickcheck!{
     fn lup(m: DMatrix<f64>) -> bool {

nalgebra-lapack/tests/linalg/mod.rs

@@ -1,7 +1,7 @@
-mod real_eigensystem;
-mod symmetric_eigen;
 mod cholesky;
 mod lu;
 mod qr;
-mod svd;
+mod real_eigensystem;
 mod real_schur;
+mod svd;
+mod symmetric_eigen;

nalgebra-lapack/tests/linalg/qr.rs

@@ -1,5 +1,5 @@
-use nl::QR;
 use na::{DMatrix, Matrix4x3};
+use nl::QR;
 
 quickcheck!{
     fn qr(m: DMatrix<f64>) -> bool {

nalgebra-lapack/tests/linalg/real_eigensystem.rs

@@ -1,7 +1,7 @@
 use std::cmp;
 
-use nl::Eigen;
 use na::{DMatrix, Matrix4};
+use nl::Eigen;
 
 quickcheck!{
     fn eigensystem(n: usize) -> bool {

nalgebra-lapack/tests/linalg/real_schur.rs

@@ -1,6 +1,6 @@
-use std::cmp;
-use nl::RealSchur;
 use na::{DMatrix, Matrix4};
+use nl::RealSchur;
+use std::cmp;
 
 quickcheck! {
     fn schur(n: usize) -> bool {

nalgebra-lapack/tests/linalg/svd.rs

@@ -1,5 +1,5 @@
-use nl::SVD;
 use na::{DMatrix, Matrix3x4};
+use nl::SVD;
 
 quickcheck!{
     fn svd(m: DMatrix<f64>) -> bool {

nalgebra-lapack/tests/linalg/symmetric_eigen.rs

@@ -1,7 +1,7 @@
 use std::cmp;
 
-use nl::SymmetricEigen;
 use na::{DMatrix, Matrix4};
+use nl::SymmetricEigen;
 
 quickcheck!{
     fn symmetric_eigen(n: usize) -> bool {

rustfmt.toml

@@ -0,0 +1,3 @@
+unstable_features = true
+indent_style = "Block"
+where_single_line = true

src/base/alias_slice.rs

@@ -1,6 +1,6 @@
-use base::Matrix;
 use base::dimension::{Dynamic, U1, U2, U3, U4, U5, U6};
 use base::matrix_slice::{SliceStorage, SliceStorageMut};
+use base::Matrix;
 
 /*
  *

src/base/allocator.rs

@@ -2,10 +2,10 @@
 
 use std::any::Any;
 
-use base::{DefaultAllocator, Scalar};
 use base::constraint::{SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
 use base::dimension::{Dim, U1};
 use base::storage::ContiguousStorageMut;
+use base::{DefaultAllocator, Scalar};
 
 /// A matrix allocator of a memory buffer that may contain `R::to_usize() * C::to_usize()`
 /// elements of type `N`.
@@ -33,8 +33,9 @@ pub trait Allocator<N: Scalar, R: Dim, C: Dim = U1>: Any + Sized {
 
 /// A matrix reallocator. Changes the size of the memory buffer that initially contains (RFrom ×
 /// CFrom) elements to a smaller or larger size (RTo, CTo).
-pub trait Reallocator<N: Scalar, RFrom: Dim, CFrom: Dim, RTo: Dim, CTo: Dim>
-    : Allocator<N, RFrom, CFrom> + Allocator<N, RTo, CTo> {
+pub trait Reallocator<N: Scalar, RFrom: Dim, CFrom: Dim, RTo: Dim, CTo: Dim>:
+    Allocator<N, RFrom, CFrom> + Allocator<N, RTo, CTo>
+{
     /// Reallocates a buffer of shape `(RTo, CTo)`, possibly reusing a previously allocated buffer
     /// `buf`. Data stored by `buf` are linearly copied to the output:
     ///
@@ -57,8 +58,8 @@ pub type SameShapeC<C1, C2> = <ShapeConstraint as SameNumberOfColumns<C1, C2>>::
 
 // FIXME: Bad name.
 /// Restricts the given number of rows and columns to be respectively the same.
-pub trait SameShapeAllocator<N, R1, C1, R2, C2>
-    : Allocator<N, R1, C1> + Allocator<N, SameShapeR<R1, R2>, SameShapeC<C1, C2>>
+pub trait SameShapeAllocator<N, R1, C1, R2, C2>:
+    Allocator<N, R1, C1> + Allocator<N, SameShapeR<R1, R2>, SameShapeC<C1, C2>>
 where
     R1: Dim,
     R2: Dim,
@@ -78,13 +79,12 @@ where
     N: Scalar,
     DefaultAllocator: Allocator<N, R1, C1> + Allocator<N, SameShapeR<R1, R2>, SameShapeC<C1, C2>>,
     ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
-{
-}
+{}
 
 // XXX: Bad name.
 /// Restricts the given number of rows to be equal.
-pub trait SameShapeVectorAllocator<N, R1, R2>
-    : Allocator<N, R1> + Allocator<N, SameShapeR<R1, R2>> + SameShapeAllocator<N, R1, U1, R2, U1>
+pub trait SameShapeVectorAllocator<N, R1, R2>:
+    Allocator<N, R1> + Allocator<N, SameShapeR<R1, R2>> + SameShapeAllocator<N, R1, U1, R2, U1>
 where
     R1: Dim,
     R2: Dim,
@@ -100,5 +100,4 @@ where
     N: Scalar,
     DefaultAllocator: Allocator<N, R1, U1> + Allocator<N, SameShapeR<R1, R2>>,
     ShapeConstraint: SameNumberOfRows<R1, R2>,
-{
-}
+{}

src/base/blas.rs

@@ -14,7 +14,6 @@ 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> {
-
     /// Computes the index of the vector component with the largest value.
     ///
     /// # Examples:
@@ -162,8 +161,7 @@ impl<N: Scalar + PartialOrd + Signed, R: Dim, C: Dim, S: Storage<N, R, C>> Matri
 }
 
 impl<N, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S>
-where
-    N: Scalar + Zero + ClosedAdd + ClosedMul,
+where N: Scalar + Zero + ClosedAdd + ClosedMul
 {
     /// The dot product between two vectors or matrices (seen as vectors).
     ///
@@ -325,9 +323,7 @@ where
 }
 
 fn array_axpy<N>(y: &mut [N], a: N, x: &[N], beta: N, stride1: usize, stride2: usize, len: usize)
-where
-    N: Scalar + Zero + ClosedAdd + ClosedMul,
-{
+where N: Scalar + Zero + ClosedAdd + ClosedMul {
     for i in 0..len {
         unsafe {
             let y = y.get_unchecked_mut(i * stride1);
@@ -337,9 +333,7 @@ where
 }
 
 fn array_ax<N>(y: &mut [N], a: N, x: &[N], stride1: usize, stride2: usize, len: usize)
-where
-    N: Scalar + Zero + ClosedAdd + ClosedMul,
-{
+where N: Scalar + Zero + ClosedAdd + ClosedMul {
     for i in 0..len {
         unsafe {
             *y.get_unchecked_mut(i * stride1) = a * *x.get_unchecked(i * stride2);
@@ -577,8 +571,7 @@ where
 }
 
 impl<N, R1: Dim, C1: Dim, S: StorageMut<N, R1, C1>> Matrix<N, R1, C1, S>
-where
-    N: Scalar + Zero + ClosedAdd + ClosedMul,
+where N: Scalar + Zero + ClosedAdd + ClosedMul
 {
     /// Computes `self = alpha * x * y.transpose() + beta * self`.
     ///
@@ -685,13 +678,19 @@ where
             // We could use matrixmultiply for large statically-sized matrices but the performance
             // threshold to activate it would be different from SMALL_DIM because our code optimizes
             // better for statically-sized matrices.
-            let is_dynamic = R1::is::<Dynamic>() || C1::is::<Dynamic>() || R2::is::<Dynamic>()
-                || C2::is::<Dynamic>() || R3::is::<Dynamic>()
+            let is_dynamic = R1::is::<Dynamic>()
+                || C1::is::<Dynamic>()
+                || R2::is::<Dynamic>()
+                || C2::is::<Dynamic>()
+                || R3::is::<Dynamic>()
                 || C3::is::<Dynamic>();
             // Threshold determined empirically.
             const SMALL_DIM: usize = 5;
 
-            if is_dynamic && nrows1 > SMALL_DIM && ncols1 > SMALL_DIM && nrows2 > SMALL_DIM
+            if is_dynamic
+                && nrows1 > SMALL_DIM
+                && ncols1 > SMALL_DIM
+                && nrows2 > SMALL_DIM
                 && ncols2 > SMALL_DIM
             {
                 if N::is::<f32>() {
@@ -812,8 +811,7 @@ where
 }
 
 impl<N, R1: Dim, C1: Dim, S: StorageMut<N, R1, C1>> Matrix<N, R1, C1, S>
-where
-    N: Scalar + Zero + ClosedAdd + ClosedMul,
+where N: Scalar + Zero + ClosedAdd + ClosedMul
 {
     /// Computes `self = alpha * x * y.transpose() + beta * self`, where `self` is a **symmetric**
     /// matrix.
@@ -871,8 +869,7 @@ where
 }
 
 impl<N, D1: Dim, S: StorageMut<N, D1, D1>> SquareMatrix<N, D1, S>
-where
-    N: Scalar + Zero + One + ClosedAdd + ClosedMul,
+where N: Scalar + Zero + One + ClosedAdd + ClosedMul
 {
     /// Computes the quadratic form `self = alpha * lhs * mid * lhs.transpose() + beta * self`.
     ///

src/base/cg.rs

@@ -7,15 +7,18 @@
 
 use num::One;
 
-use base::{DefaultAllocator, Matrix3, Matrix4, MatrixN, Scalar, SquareMatrix, Unit, Vector,
-           Vector3, VectorN};
+use base::allocator::Allocator;
 use base::dimension::{DimName, DimNameDiff, DimNameSub, U1};
 use base::storage::{Storage, StorageMut};
-use base::allocator::Allocator;
-use geometry::{Isometry, IsometryMatrix3, Orthographic3, Perspective3, Point, Point3, Rotation2,
-               Rotation3};
+use base::{
+    DefaultAllocator, Matrix3, Matrix4, MatrixN, Scalar, SquareMatrix, Unit, Vector, Vector3,
+    VectorN,
+};
+use geometry::{
+    Isometry, IsometryMatrix3, Orthographic3, Perspective3, Point, Point3, Rotation2, Rotation3,
+};
 
-use alga::general::{Ring, Real};
+use alga::general::{Real, Ring};
 use alga::linear::Transformation;
 
 impl<N, D: DimName> MatrixN<N, D>
@@ -235,9 +238,7 @@ impl<N: Scalar + Ring, D: DimName, S: StorageMut<N, D, D>> SquareMatrix<N, D, S>
     /// Computes in-place the transformation equal to `self` followed by an uniform scaling factor.
     #[inline]
     pub fn append_scaling_mut(&mut self, scaling: N)
-    where
-        D: DimNameSub<U1>,
-    {
+    where D: DimNameSub<U1> {
         let mut to_scale = self.fixed_rows_mut::<DimNameDiff<D, U1>>(0);
         to_scale *= scaling;
     }
@@ -245,9 +246,7 @@ impl<N: Scalar + Ring, D: DimName, S: StorageMut<N, D, D>> SquareMatrix<N, D, S>
     /// Computes in-place the transformation equal to an uniform scaling factor followed by `self`.
     #[inline]
     pub fn prepend_scaling_mut(&mut self, scaling: N)
-    where
-        D: DimNameSub<U1>,
-    {
+    where D: DimNameSub<U1> {
         let mut to_scale = self.fixed_columns_mut::<DimNameDiff<D, U1>>(0);
         to_scale *= scaling;
     }
@@ -302,7 +301,8 @@ impl<N: Scalar + Ring, D: DimName, S: StorageMut<N, D, D>> SquareMatrix<N, D, S>
         SB: Storage<N, DimNameDiff<D, U1>>,
         DefaultAllocator: Allocator<N, DimNameDiff<D, U1>>,
     {
-        let scale = self.fixed_slice::<U1, DimNameDiff<D, U1>>(D::dim() - 1, 0)
+        let scale = self
+            .fixed_slice::<U1, DimNameDiff<D, U1>>(D::dim() - 1, 0)
             .tr_dot(&shift);
         let post_translation =
             self.fixed_slice::<DimNameDiff<D, U1>, DimNameDiff<D, U1>>(0, 0) * shift;
@@ -315,16 +315,16 @@ impl<N: Scalar + Ring, D: DimName, S: StorageMut<N, D, D>> SquareMatrix<N, D, S>
 }
 
 impl<N: Real, D: DimNameSub<U1>> Transformation<Point<N, DimNameDiff<D, U1>>> for MatrixN<N, D>
-where
-    DefaultAllocator: Allocator<N, D, D>
+where DefaultAllocator: Allocator<N, D, D>
         + Allocator<N, DimNameDiff<D, U1>>
-        + Allocator<N, DimNameDiff<D, U1>, DimNameDiff<D, U1>>,
+        + Allocator<N, DimNameDiff<D, U1>, DimNameDiff<D, U1>>
 {
     #[inline]
     fn transform_vector(
         &self,
         v: &VectorN<N, DimNameDiff<D, U1>>,
-    ) -> VectorN<N, DimNameDiff<D, U1>> {
+    ) -> VectorN<N, DimNameDiff<D, U1>>
+    {
         let transform = self.fixed_slice::<DimNameDiff<D, U1>, DimNameDiff<D, U1>>(0, 0);
         let normalizer = self.fixed_slice::<U1, DimNameDiff<D, U1>>(D::dim() - 1, 0);
         let n = normalizer.tr_dot(&v);
@@ -341,9 +341,8 @@ where
         let transform = self.fixed_slice::<DimNameDiff<D, U1>, DimNameDiff<D, U1>>(0, 0);
         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)
-        };
+        let n = normalizer.tr_dot(&pt.coords)
+            + unsafe { *self.get_unchecked(D::dim() - 1, D::dim() - 1) };
 
         if !n.is_zero() {
             return transform * (pt / n) + translation;

src/base/constraint.rs

@@ -8,11 +8,8 @@ pub struct ShapeConstraint;
 /// Constraints `C1` and `R2` to be equivalent.
 pub trait AreMultipliable<R1: Dim, C1: Dim, R2: Dim, C2: Dim>: DimEq<C1, R2> {}
 
-impl<R1: Dim, C1: Dim, R2: Dim, C2: Dim> AreMultipliable<R1, C1, R2, C2> for ShapeConstraint
-where
-    ShapeConstraint: DimEq<C1, R2>,
-{
-}
+impl<R1: Dim, C1: Dim, R2: Dim, C2: Dim> AreMultipliable<R1, C1, R2, C2> for ShapeConstraint where ShapeConstraint: DimEq<C1, R2>
+{}
 
 /// Constraints `D1` and `D2` to be equivalent.
 pub trait DimEq<D1: Dim, D2: Dim> {
@@ -70,8 +67,9 @@ equality_trait_decl!(
 
 /// Constraints D1 and D2 to be equivalent, where they both designate dimensions of algebraic
 /// entities (e.g. square matrices).
-pub trait SameDimension<D1: Dim, D2: Dim>
-    : SameNumberOfRows<D1, D2> + SameNumberOfColumns<D1, D2> {
+pub trait SameDimension<D1: Dim, D2: Dim>:
+    SameNumberOfRows<D1, D2> + SameNumberOfColumns<D1, D2>
+{
     /// This is either equal to `D1` or `D2`, always choosing the one (if any) which is a type-level
     /// constant.
     type Representative: Dim;

src/base/construction.rs

@@ -26,8 +26,7 @@ use base::{DefaultAllocator, Matrix, MatrixMN, MatrixN, Scalar, Unit, Vector, Ve
  *
  */
 impl<N: Scalar, R: Dim, C: Dim> MatrixMN<N, R, C>
-where
-    DefaultAllocator: Allocator<N, R, C>,
+where DefaultAllocator: Allocator<N, R, C>
 {
     /// Creates a new uninitialized matrix. If the matrix has a compile-time dimension, this panics
     /// if `nrows != R::to_usize()` or `ncols != C::to_usize()`.
@@ -55,18 +54,14 @@ where
     /// Creates a matrix with all its elements set to 0.
     #[inline]
     pub fn zeros_generic(nrows: R, ncols: C) -> Self
-    where
-        N: Zero,
-    {
+    where N: Zero {
         Self::from_element_generic(nrows, ncols, N::zero())
     }
 
     /// Creates a matrix with all its elements filled by an iterator.
     #[inline]
     pub fn from_iterator_generic<I>(nrows: R, ncols: C, iter: I) -> Self
-    where
-        I: IntoIterator<Item = N>,
-    {
+    where I: IntoIterator<Item = N> {
         Self::from_data(DefaultAllocator::allocate_from_iterator(nrows, ncols, iter))
     }
 
@@ -105,9 +100,7 @@ where
     /// coordinates.
     #[inline]
     pub fn from_fn_generic<F>(nrows: R, ncols: C, mut f: F) -> Self
-    where
-        F: FnMut(usize, usize) -> N,
-    {
+    where F: FnMut(usize, usize) -> N {
         let mut res = unsafe { Self::new_uninitialized_generic(nrows, ncols) };
 
         for j in 0..ncols.value() {
@@ -125,9 +118,7 @@ where
     /// to the identity matrix. All other entries are set to zero.
     #[inline]
     pub fn identity_generic(nrows: R, ncols: C) -> Self
-    where
-        N: Zero + One,
-    {
+    where N: Zero + One {
         Self::from_diagonal_element_generic(nrows, ncols, N::one())
     }
 
@@ -137,9 +128,7 @@ where
     /// to the identity matrix. All other entries are set to zero.
     #[inline]
     pub fn from_diagonal_element_generic(nrows: R, ncols: C, elt: N) -> Self
-    where
-        N: Zero + One,
-    {
+    where N: Zero + One {
         let mut res = Self::zeros_generic(nrows, ncols);
 
         for i in 0..::min(nrows.value(), ncols.value()) {
@@ -155,9 +144,7 @@ where
     /// Panics if `elts.len()` is larger than the minimum among `nrows` and `ncols`.
     #[inline]
     pub fn from_partial_diagonal_generic(nrows: R, ncols: C, elts: &[N]) -> Self
-    where
-        N: Zero,
-    {
+    where N: Zero {
         let mut res = Self::zeros_generic(nrows, ncols);
         assert!(
             elts.len() <= ::min(nrows.value(), ncols.value()),
@@ -189,9 +176,7 @@ where
     /// ```
     #[inline]
     pub fn from_rows<SB>(rows: &[Matrix<N, U1, C, SB>]) -> Self
-    where
-        SB: Storage<N, U1, C>,
-    {
+    where SB: Storage<N, U1, C> {
         assert!(rows.len() > 0, "At least one row must be given.");
         let nrows = R::try_to_usize().unwrap_or(rows.len());
         let ncols = rows[0].len();
@@ -231,9 +216,7 @@ where
     /// ```
     #[inline]
     pub fn from_columns<SB>(columns: &[Vector<N, R, SB>]) -> Self
-    where
-        SB: Storage<N, R>,
-    {
+    where SB: Storage<N, R> {
         assert!(columns.len() > 0, "At least one column must be given.");
         let ncols = C::try_to_usize().unwrap_or(columns.len());
         let nrows = columns[0].len();
@@ -259,9 +242,7 @@ where
     #[inline]
     #[cfg(feature = "std")]
     pub fn new_random_generic(nrows: R, ncols: C) -> Self
-    where
-        Standard: Distribution<N>,
-    {
+    where Standard: Distribution<N> {
         Self::from_fn_generic(nrows, ncols, |_, _| rand::random())
     }
 
@@ -272,7 +253,8 @@ where
         ncols: C,
         distribution: &mut Distr,
         rng: &mut G,
-    ) -> Self {
+    ) -> Self
+    {
         Self::from_fn_generic(nrows, ncols, |_, _| distribution.sample(rng))
     }
 }
@@ -302,9 +284,7 @@ where
     /// ```
     #[inline]
     pub fn from_diagonal<SB: Storage<N, D>>(diag: &Vector<N, D, SB>) -> Self
-    where
-        N: Zero,
-    {
+    where N: Zero {
         let (dim, _) = diag.data.shape();
         let mut res = Self::zeros_generic(dim, dim);
 
@@ -929,9 +909,7 @@ where
     /// The column vector with a 1 as its first component, and zero elsewhere.
     #[inline]
     pub fn x() -> Self
-    where
-        R::Value: Cmp<typenum::U0, Output = Greater>,
-    {
+    where R::Value: Cmp<typenum::U0, Output = Greater> {
         let mut res = Self::zeros();
         unsafe {
             *res.vget_unchecked_mut(0) = N::one();
@@ -943,9 +921,7 @@ where
     /// The column vector with a 1 as its second component, and zero elsewhere.
     #[inline]
     pub fn y() -> Self
-    where
-        R::Value: Cmp<typenum::U1, Output = Greater>,
-    {
+    where R::Value: Cmp<typenum::U1, Output = Greater> {
         let mut res = Self::zeros();
         unsafe {
             *res.vget_unchecked_mut(1) = N::one();
@@ -957,9 +933,7 @@ where
     /// The column vector with a 1 as its third component, and zero elsewhere.
     #[inline]
     pub fn z() -> Self
-    where
-        R::Value: Cmp<typenum::U2, Output = Greater>,
-    {
+    where R::Value: Cmp<typenum::U2, Output = Greater> {
         let mut res = Self::zeros();
         unsafe {
             *res.vget_unchecked_mut(2) = N::one();
@@ -971,9 +945,7 @@ where
     /// The column vector with a 1 as its fourth component, and zero elsewhere.
     #[inline]
     pub fn w() -> Self
-    where
-        R::Value: Cmp<typenum::U3, Output = Greater>,
-    {
+    where R::Value: Cmp<typenum::U3, Output = Greater> {
         let mut res = Self::zeros();
         unsafe {
             *res.vget_unchecked_mut(3) = N::one();
@@ -985,9 +957,7 @@ where
     /// The column vector with a 1 as its fifth component, and zero elsewhere.
     #[inline]
     pub fn a() -> Self
-    where
-        R::Value: Cmp<typenum::U4, Output = Greater>,
-    {
+    where R::Value: Cmp<typenum::U4, Output = Greater> {
         let mut res = Self::zeros();
         unsafe {
             *res.vget_unchecked_mut(4) = N::one();
@@ -999,9 +969,7 @@ where
     /// The column vector with a 1 as its sixth component, and zero elsewhere.
     #[inline]
     pub fn b() -> Self
-    where
-        R::Value: Cmp<typenum::U5, Output = Greater>,
-    {
+    where R::Value: Cmp<typenum::U5, Output = Greater> {
         let mut res = Self::zeros();
         unsafe {
             *res.vget_unchecked_mut(5) = N::one();
@@ -1013,54 +981,42 @@ where
     /// The unit column vector with a 1 as its first component, and zero elsewhere.
     #[inline]
     pub fn x_axis() -> Unit<Self>
-    where
-        R::Value: Cmp<typenum::U0, Output = Greater>,
-    {
+    where R::Value: Cmp<typenum::U0, Output = Greater> {
         Unit::new_unchecked(Self::x())
     }
 
     /// The unit column vector with a 1 as its second component, and zero elsewhere.
     #[inline]
     pub fn y_axis() -> Unit<Self>
-    where
-        R::Value: Cmp<typenum::U1, Output = Greater>,
-    {
+    where R::Value: Cmp<typenum::U1, Output = Greater> {
         Unit::new_unchecked(Self::y())
     }
 
     /// The unit column vector with a 1 as its third component, and zero elsewhere.
     #[inline]
     pub fn z_axis() -> Unit<Self>
-    where
-        R::Value: Cmp<typenum::U2, Output = Greater>,
-    {
+    where R::Value: Cmp<typenum::U2, Output = Greater> {
         Unit::new_unchecked(Self::z())
     }
 
     /// The unit column vector with a 1 as its fourth component, and zero elsewhere.
     #[inline]
     pub fn w_axis() -> Unit<Self>
-    where
-        R::Value: Cmp<typenum::U3, Output = Greater>,
-    {
+    where R::Value: Cmp<typenum::U3, Output = Greater> {
         Unit::new_unchecked(Self::w())
     }
 
     /// The unit column vector with a 1 as its fifth component, and zero elsewhere.
     #[inline]
     pub fn a_axis() -> Unit<Self>
-    where
-        R::Value: Cmp<typenum::U4, Output = Greater>,
-    {
+    where R::Value: Cmp<typenum::U4, Output = Greater> {
         Unit::new_unchecked(Self::a())
     }
 
     /// The unit column vector with a 1 as its sixth component, and zero elsewhere.
     #[inline]
     pub fn b_axis() -> Unit<Self>
-    where
-        R::Value: Cmp<typenum::U5, Output = Greater>,
-    {
+    where R::Value: Cmp<typenum::U5, Output = Greater> {
         Unit::new_unchecked(Self::b())
     }
 }

src/base/construction_slice.rs

@@ -22,7 +22,8 @@ impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
         ncols: C,
         rstride: RStride,
         cstride: CStride,
-    ) -> Self {
+    ) -> Self
+    {
         let data = SliceStorage::from_raw_parts(
             data.as_ptr().offset(start as isize),
             (nrows, ncols),
@@ -42,7 +43,8 @@ impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
         ncols: C,
         rstride: RStride,
         cstride: CStride,
-    ) -> Self {
+    ) -> Self
+    {
         // NOTE: The assertion implements the following formula, but without subtractions to avoid
         // underflow panics:
         //      len >= (ncols - 1) * cstride + (nrows - 1) * rstride + 1
@@ -73,7 +75,8 @@ impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
         ncols: C,
         rstride: RStride,
         cstride: CStride,
-    ) -> Self {
+    ) -> Self
+    {
         let data = SliceStorageMut::from_raw_parts(
             data.as_mut_ptr().offset(start as isize),
             (nrows, ncols),
@@ -93,7 +96,8 @@ impl<'a, N: Scalar, R: Dim, C: Dim, RStride: Dim, CStride: Dim>
         ncols: C,
         rstride: RStride,
         cstride: CStride,
-    ) -> Self {
+    ) -> Self
+    {
         // NOTE: The assertion implements the following formula, but without subtractions to avoid
         // underflow panics:
         //      len >= (ncols - 1) * cstride + (nrows - 1) * rstride + 1
@@ -120,7 +124,8 @@ impl<'a, N: Scalar, R: Dim, C: Dim> MatrixSliceMN<'a, N, R, C> {
         start: usize,
         nrows: R,
         ncols: C,
-    ) -> Self {
+    ) -> Self
+    {
         Self::from_slice_with_strides_generic_unchecked(data, start, nrows, ncols, U1, nrows)
     }
 
@@ -145,7 +150,8 @@ impl<'a, N: Scalar, R: Dim, C: Dim> MatrixSliceMutMN<'a, N, R, C> {
         start: usize,
         nrows: R,
         ncols: C,
-    ) -> Self {
+    ) -> Self
+    {
         Self::from_slice_with_strides_generic_unchecked(data, start, nrows, ncols, U1, nrows)
     }
 

src/base/coordinates.rs

@@ -7,9 +7,9 @@
 use std::mem;
 use std::ops::{Deref, DerefMut};
 
-use base::{Matrix, Scalar};
 use base::dimension::{U1, U2, U3, U4, U5, U6};
 use base::storage::{ContiguousStorage, ContiguousStorageMut};
+use base::{Matrix, Scalar};
 
 /*
  *

src/base/default_allocator.rs

@@ -54,7 +54,8 @@ where
         nrows: R,
         ncols: C,
         iter: I,
-    ) -> Self::Buffer {
+    ) -> Self::Buffer
+    {
         let mut res = unsafe { Self::allocate_uninitialized(nrows, ncols) };
         let mut count = 0;
 
@@ -93,7 +94,8 @@ impl<N: Scalar, C: Dim> Allocator<N, Dynamic, C> for DefaultAllocator {
         nrows: Dynamic,
         ncols: C,
         iter: I,
-    ) -> Self::Buffer {
+    ) -> Self::Buffer
+    {
         let it = iter.into_iter();
         let res: Vec<N> = it.collect();
         assert!(res.len() == nrows.value() * ncols.value(),
@@ -123,7 +125,8 @@ impl<N: Scalar, R: DimName> Allocator<N, R, Dynamic> for DefaultAllocator {
         nrows: R,
         ncols: Dynamic,
         iter: I,
-    ) -> Self::Buffer {
+    ) -> Self::Buffer
+    {
         let it = iter.into_iter();
         let res: Vec<N> = it.collect();
         assert!(res.len() == nrows.value() * ncols.value(),
@@ -154,7 +157,8 @@ where
         rto: RTo,
         cto: CTo,
         buf: <Self as Allocator<N, RFrom, CFrom>>::Buffer,
-    ) -> MatrixArray<N, RTo, CTo> {
+    ) -> MatrixArray<N, RTo, CTo>
+    {
         let mut res = <Self as Allocator<N, RTo, CTo>>::allocate_uninitialized(rto, cto);
 
         let (rfrom, cfrom) = buf.shape();
@@ -182,7 +186,8 @@ where
         rto: Dynamic,
         cto: CTo,
         buf: MatrixArray<N, RFrom, CFrom>,
-    ) -> MatrixVec<N, Dynamic, CTo> {
+    ) -> MatrixVec<N, Dynamic, CTo>
+    {
         let mut res = <Self as Allocator<N, Dynamic, CTo>>::allocate_uninitialized(rto, cto);
 
         let (rfrom, cfrom) = buf.shape();
@@ -210,7 +215,8 @@ where
         rto: RTo,
         cto: Dynamic,
         buf: MatrixArray<N, RFrom, CFrom>,
-    ) -> MatrixVec<N, RTo, Dynamic> {
+    ) -> MatrixVec<N, RTo, Dynamic>
+    {
         let mut res = <Self as Allocator<N, RTo, Dynamic>>::allocate_uninitialized(rto, cto);
 
         let (rfrom, cfrom) = buf.shape();
@@ -233,7 +239,8 @@ impl<N: Scalar, CFrom: Dim, CTo: Dim> Reallocator<N, Dynamic, CFrom, Dynamic, CT
         rto: Dynamic,
         cto: CTo,
         buf: MatrixVec<N, Dynamic, CFrom>,
-    ) -> MatrixVec<N, Dynamic, CTo> {
+    ) -> MatrixVec<N, Dynamic, CTo>
+    {
         let new_buf = buf.resize(rto.value() * cto.value());
         MatrixVec::new(rto, cto, new_buf)
     }
@@ -248,7 +255,8 @@ impl<N: Scalar, CFrom: Dim, RTo: DimName> Reallocator<N, Dynamic, CFrom, RTo, Dy
         rto: RTo,
         cto: Dynamic,
         buf: MatrixVec<N, Dynamic, CFrom>,
-    ) -> MatrixVec<N, RTo, Dynamic> {
+    ) -> MatrixVec<N, RTo, Dynamic>
+    {
         let new_buf = buf.resize(rto.value() * cto.value());
         MatrixVec::new(rto, cto, new_buf)
     }
@@ -263,7 +271,8 @@ impl<N: Scalar, RFrom: DimName, CTo: Dim> Reallocator<N, RFrom, Dynamic, Dynamic
         rto: Dynamic,
         cto: CTo,
         buf: MatrixVec<N, RFrom, Dynamic>,
-    ) -> MatrixVec<N, Dynamic, CTo> {
+    ) -> MatrixVec<N, Dynamic, CTo>
+    {
         let new_buf = buf.resize(rto.value() * cto.value());
         MatrixVec::new(rto, cto, new_buf)
     }
@@ -278,7 +287,8 @@ impl<N: Scalar, RFrom: DimName, RTo: DimName> Reallocator<N, RFrom, Dynamic, RTo
         rto: RTo,
         cto: Dynamic,
         buf: MatrixVec<N, RFrom, Dynamic>,
-    ) -> MatrixVec<N, RTo, Dynamic> {
+    ) -> MatrixVec<N, RTo, Dynamic>
+    {
         let new_buf = buf.resize(rto.value() * cto.value());
         MatrixVec::new(rto, cto, new_buf)
     }

src/base/dimension.rs

@@ -7,7 +7,7 @@ use std::cmp;
 use std::fmt::Debug;
 use std::ops::{Add, Div, Mul, Sub};
 use typenum::{
-    self, B1, Bit, Diff, Max, Maximum, Min, Minimum, Prod, Quot, Sum, UInt, UTerm, Unsigned,
+    self, Bit, Diff, Max, Maximum, Min, Minimum, Prod, Quot, Sum, UInt, UTerm, Unsigned, B1,
 };
 
 #[cfg(feature = "serde-serialize")]
@@ -30,9 +30,7 @@ impl Dynamic {
 #[cfg(feature = "serde-serialize")]
 impl Serialize for Dynamic {
     fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
-    where
-        S: Serializer,
-    {
+    where S: Serializer {
         self.value.serialize(serializer)
     }
 }
@@ -40,9 +38,7 @@ impl Serialize for Dynamic {
 #[cfg(feature = "serde-serialize")]
 impl<'de> Deserialize<'de> for Dynamic {
     fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
-    where
-        D: Deserializer<'de>,
-    {
+    where D: Deserializer<'de> {
         usize::deserialize(deserializer).map(|x| Dynamic { value: x })
     }
 }

src/base/edition.rs

@@ -16,9 +16,7 @@ impl<N: Scalar + Zero, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// Extracts the upper triangular part of this matrix (including the diagonal).
     #[inline]
     pub fn upper_triangle(&self) -> MatrixMN<N, R, C>
-    where
-        DefaultAllocator: Allocator<N, R, C>,
-    {
+    where DefaultAllocator: Allocator<N, R, C> {
         let mut res = self.clone_owned();
         res.fill_lower_triangle(N::zero(), 1);
 
@@ -28,9 +26,7 @@ impl<N: Scalar + Zero, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// Extracts the upper triangular part of this matrix (including the diagonal).
     #[inline]
     pub fn lower_triangle(&self) -> MatrixMN<N, R, C>
-    where
-        DefaultAllocator: Allocator<N, R, C>,
-    {
+    where DefaultAllocator: Allocator<N, R, C> {
         let mut res = self.clone_owned();
         res.fill_upper_triangle(N::zero(), 1);
 
@@ -50,9 +46,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     /// Fills `self` with the identity matrix.
     #[inline]
     pub fn fill_with_identity(&mut self)
-    where
-        N: Zero + One,
-    {
+    where N: Zero + One {
         self.fill(N::zero());
         self.fill_diagonal(N::one());
     }
@@ -285,7 +279,8 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
             let copied_value_start = i + nremove.value();
 
             unsafe {
-                let ptr_in = m.data
+                let ptr_in = m
+                    .data
                     .ptr()
                     .offset((copied_value_start * nrows.value()) as isize);
                 let ptr_out = m.data.ptr_mut().offset((i * nrows.value()) as isize);
@@ -448,7 +443,8 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 
         if ninsert.value() != 0 && i != ncols.value() {
             let ptr_in = res.data.ptr().offset((i * nrows.value()) as isize);
-            let ptr_out = res.data
+            let ptr_out = res
+                .data
                 .ptr_mut()
                 .offset(((i + ninsert.value()) * nrows.value()) as isize);
 
@@ -549,9 +545,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// rows and/or columns than `self`, then the extra rows or columns are filled with `val`.
     #[cfg(any(feature = "std", feature = "alloc"))]
     pub fn resize(self, new_nrows: usize, new_ncols: usize, val: N) -> DMatrix<N>
-    where
-        DefaultAllocator: Reallocator<N, R, C, Dynamic, Dynamic>,
-    {
+    where DefaultAllocator: Reallocator<N, R, C, Dynamic, Dynamic> {
         self.resize_generic(Dynamic::new(new_nrows), Dynamic::new(new_ncols), val)
     }
 
@@ -560,9 +554,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
     /// rows and/or columns than `self`, then the extra rows or columns are filled with `val`.
     pub fn fixed_resize<R2: DimName, C2: DimName>(self, val: N) -> MatrixMN<N, R2, C2>
-    where
-        DefaultAllocator: Reallocator<N, R, C, R2, C2>,
-    {
+    where DefaultAllocator: Reallocator<N, R, C, R2, C2> {
         self.resize_generic(R2::name(), C2::name(), val)
     }
 
@@ -640,7 +632,8 @@ unsafe fn compress_rows<N: Scalar>(
     ncols: usize,
     i: usize,
     nremove: usize,
-) {
+)
+{
     let new_nrows = nrows - nremove;
 
     if new_nrows == 0 || ncols == 0 {
@@ -679,7 +672,8 @@ unsafe fn extend_rows<N: Scalar>(
     ncols: usize,
     i: usize,
     ninsert: usize,
-) {
+)
+{
     let new_nrows = nrows + ninsert;
 
     if new_nrows == 0 || ncols == 0 {

src/base/helper.rs

@@ -18,9 +18,7 @@ pub fn reject<G: Gen, F: FnMut(&T) -> bool, T: Arbitrary>(g: &mut G, f: F) -> T
 #[doc(hidden)]
 #[inline]
 pub fn reject_rand<G: Rng + ?Sized, F: FnMut(&T) -> bool, T>(g: &mut G, f: F) -> T
-where
-    Standard: Distribution<T>,
-{
+where Standard: Distribution<T> {
     use std::iter;
     iter::repeat(()).map(|_| g.gen()).find(f).unwrap()
 }

src/base/iter.rs

@@ -3,21 +3,20 @@
 use std::marker::PhantomData;
 use std::mem;
 
-use base::Scalar;
 use base::dimension::Dim;
 use base::storage::{Storage, StorageMut};
+use base::Scalar;
 
 macro_rules! iterator {
     (struct $Name:ident for $Storage:ident.$ptr: ident -> $Ptr:ty, $Ref:ty, $SRef: ty) => {
-
         /// An iterator through a dense matrix with arbitrary strides matrix.
         pub struct $Name<'a, N: Scalar, R: Dim, C: Dim, S: 'a + $Storage<N, R, C>> {
-            ptr:       $Ptr,
+            ptr: $Ptr,
             inner_ptr: $Ptr,
             inner_end: $Ptr,
-            size:      usize, // We can't use an end pointer here because a stride might be zero.
-            strides:   (S::RStride, S::CStride),
-            _phantoms: PhantomData<($Ref, R, C, S)>
+            size: usize, // We can't use an end pointer here because a stride might be zero.
+            strides: (S::RStride, S::CStride),
+            _phantoms: PhantomData<($Ref, R, C, S)>,
         }
 
         // FIXME: we need to specialize for the case where the matrix storage is owned (in which
@@ -25,23 +24,25 @@ macro_rules! iterator {
         impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + $Storage<N, R, C>> $Name<'a, N, R, C, S> {
             /// Creates a new iterator for the given matrix storage.
             pub fn new(storage: $SRef) -> $Name<'a, N, R, C, S> {
-                let shape   = storage.shape();
+                let shape = storage.shape();
                 let strides = storage.strides();
                 let inner_offset = shape.0.value() * strides.0.value();
                 let ptr = storage.$ptr();
 
                 $Name {
-                    ptr:       ptr,
+                    ptr: ptr,
                     inner_ptr: ptr,
                     inner_end: unsafe { ptr.offset(inner_offset as isize) },
-                    size:      shape.0.value() * shape.1.value(),
-                    strides:   strides,
-                    _phantoms: PhantomData
+                    size: shape.0.value() * shape.1.value(),
+                    strides: strides,
+                    _phantoms: PhantomData,
                 }
             }
         }
 
-        impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + $Storage<N, R, C>> Iterator for $Name<'a, N, R, C, S> {
+        impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + $Storage<N, R, C>> Iterator
+            for $Name<'a, N, R, C, S>
+        {
             type Item = $Ref;
 
             #[inline]
@@ -82,13 +83,15 @@ macro_rules! iterator {
             }
         }
 
-        impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + $Storage<N, R, C>> ExactSizeIterator for $Name<'a, N, R, C, S> {
+        impl<'a, N: Scalar, R: Dim, C: Dim, S: 'a + $Storage<N, R, C>> ExactSizeIterator
+            for $Name<'a, N, R, C, S>
+        {
             #[inline]
             fn len(&self) -> usize {
                 self.size
             }
         }
-    }
+    };
 }
 
 iterator!(struct MatrixIter for Storage.ptr -> *const N, &'a N, &'a S);

src/base/matrix.rs

@@ -99,9 +99,7 @@ where
     S: Serialize,
 {
     fn serialize<T>(&self, serializer: T) -> Result<T::Ok, T::Error>
-    where
-        T: Serializer,
-    {
+    where T: Serializer {
         self.data.serialize(serializer)
     }
 }
@@ -115,9 +113,7 @@ where
     S: Deserialize<'de>,
 {
     fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
-    where
-        D: Deserializer<'de>,
-    {
+    where D: Deserializer<'de> {
         S::deserialize(deserializer).map(|x| Matrix {
             data: x,
             _phantoms: PhantomData,
@@ -319,9 +315,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// Moves this matrix into one that owns its data.
     #[inline]
     pub fn into_owned(self) -> MatrixMN<N, R, C>
-    where
-        DefaultAllocator: Allocator<N, R, C>,
-    {
+    where DefaultAllocator: Allocator<N, R, C> {
         Matrix::from_data(self.data.into_owned())
     }
 
@@ -355,9 +349,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// Clones this matrix to one that owns its data.
     #[inline]
     pub fn clone_owned(&self) -> MatrixMN<N, R, C>
-    where
-        DefaultAllocator: Allocator<N, R, C>,
-    {
+    where DefaultAllocator: Allocator<N, R, C> {
         Matrix::from_data(self.data.clone_owned())
     }
 
@@ -393,9 +385,7 @@ 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.
     #[inline]
     pub fn map<N2: Scalar, F: FnMut(N) -> N2>(&self, mut f: F) -> MatrixMN<N2, R, C>
-    where
-        DefaultAllocator: Allocator<N2, R, C>,
-    {
+    where DefaultAllocator: Allocator<N2, R, C> {
         let (nrows, ncols) = self.data.shape();
 
         let mut res = unsafe { MatrixMN::new_uninitialized_generic(nrows, ncols) };
@@ -541,9 +531,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// Transposes `self`.
     #[inline]
     pub fn transpose(&self) -> MatrixMN<N, C, R>
-    where
-        DefaultAllocator: Allocator<N, C, R>,
-    {
+    where DefaultAllocator: Allocator<N, C, R> {
         let (nrows, ncols) = self.data.shape();
 
         unsafe {
@@ -666,9 +654,7 @@ 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)
-    where
-        DefaultAllocator: Allocator<N, R, C>,
-    {
+    where DefaultAllocator: Allocator<N, R, C> {
         let (nrows, ncols) = self.shape();
 
         for j in 0..ncols {
@@ -765,9 +751,7 @@ impl<N: Real, R: Dim, C: Dim, S: Storage<Complex<N>, R, C>> Matrix<Complex<N>, R
     /// The conjugate transposition of `self`.
     #[inline]
     pub fn conjugate_transpose(&self) -> MatrixMN<Complex<N>, C, R>
-    where
-        DefaultAllocator: Allocator<Complex<N>, C, R>,
-    {
+    where DefaultAllocator: Allocator<Complex<N>, C, R> {
         let (nrows, ncols) = self.data.shape();
 
         unsafe {
@@ -808,9 +792,7 @@ impl<N: Scalar, D: Dim, S: Storage<N, D, D>> SquareMatrix<N, D, S> {
     /// Creates a square matrix with its diagonal set to `diag` and all other entries set to 0.
     #[inline]
     pub fn diagonal(&self) -> VectorN<N, D>
-    where
-        DefaultAllocator: Allocator<N, D>,
-    {
+    where DefaultAllocator: Allocator<N, D> {
         assert!(
             self.is_square(),
             "Unable to get the diagonal of a non-square matrix."
@@ -831,9 +813,7 @@ impl<N: Scalar, D: Dim, S: Storage<N, D, D>> SquareMatrix<N, D, S> {
     /// Computes a trace of a square matrix, i.e., the sum of its diagonal elements.
     #[inline]
     pub fn trace(&self) -> N
-    where
-        N: Ring,
-    {
+    where N: Ring {
         assert!(
             self.is_square(),
             "Cannot compute the trace of non-square matrix."
@@ -855,9 +835,7 @@ impl<N: Scalar + Zero, D: DimAdd<U1>, S: Storage<N, D>> Vector<N, D, S> {
     /// coordinates.
     #[inline]
     pub fn to_homogeneous(&self) -> VectorN<N, DimSum<D, U1>>
-    where
-        DefaultAllocator: Allocator<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) };
@@ -923,7 +901,8 @@ where
         other: &Self,
         epsilon: Self::Epsilon,
         max_relative: Self::Epsilon,
-    ) -> bool {
+    ) -> bool
+    {
         self.relative_eq(other, epsilon, max_relative)
     }
 }
@@ -1220,8 +1199,7 @@ impl<N: Scalar + Ring, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 }
 
 impl<N: Real, S: Storage<N, U3>> Vector<N, U3, S>
-where
-    DefaultAllocator: Allocator<N, U3>,
+where DefaultAllocator: Allocator<N, U3>
 {
     /// Computes the matrix `M` such that for all vector `v` we have `M * v == self.cross(&v)`.
     #[inline]
@@ -1311,18 +1289,14 @@ impl<N: Real, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     /// Returns a normalized version of this matrix.
     #[inline]
     pub fn normalize(&self) -> MatrixMN<N, R, C>
-    where
-        DefaultAllocator: Allocator<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>,
-    {
+    where DefaultAllocator: Allocator<N, R, C> {
         let n = self.norm();
 
         if n <= min_norm {
@@ -1446,7 +1420,8 @@ where
         other: &Self,
         epsilon: Self::Epsilon,
         max_relative: Self::Epsilon,
-    ) -> bool {
+    ) -> bool
+    {
         self.as_ref()
             .relative_eq(other.as_ref(), epsilon, max_relative)
     }

src/base/matrix_alga.rs

@@ -146,8 +146,7 @@ where
 }
 
 impl<N: Real, R: DimName, C: DimName> NormedSpace for MatrixMN<N, R, C>
-where
-    DefaultAllocator: Allocator<N, R, C>,
+where DefaultAllocator: Allocator<N, R, C>
 {
     #[inline]
     fn norm_squared(&self) -> N {
@@ -181,8 +180,7 @@ where
 }
 
 impl<N: Real, R: DimName, C: DimName> InnerSpace for MatrixMN<N, R, C>
-where
-    DefaultAllocator: Allocator<N, R, C>,
+where DefaultAllocator: Allocator<N, R, C>
 {
     type Real = N;
 
@@ -202,8 +200,7 @@ where
 //   − use `x()` instead of `::canonical_basis_element`
 //   − use `::new(x, y, z)` instead of `::from_slice`
 impl<N: Real, R: DimName, C: DimName> FiniteDimInnerSpace for MatrixMN<N, R, C>
-where
-    DefaultAllocator: Allocator<N, R, C>,
+where DefaultAllocator: Allocator<N, R, C>
 {
     #[inline]
     fn orthonormalize(vs: &mut [MatrixMN<N, R, C>]) -> usize {
@@ -236,9 +233,7 @@ where
 
     #[inline]
     fn orthonormal_subspace_basis<F>(vs: &[Self], mut f: F)
-    where
-        F: FnMut(&Self) -> bool,
-    {
+    where F: FnMut(&Self) -> bool {
         // FIXME: is this necessary?
         assert!(
             vs.len() <= Self::dimension(),

src/base/matrix_array.rs

@@ -107,8 +107,7 @@ where
     R::Value: Mul<C::Value>,
     Prod<R::Value, C::Value>: ArrayLength<N>,
     GenericArray<N, Prod<R::Value, C::Value>>: Copy,
-{
-}
+{}
 
 impl<N, R, C> Clone for MatrixArray<N, R, C>
 where
@@ -133,8 +132,7 @@ where
     C: DimName,
     R::Value: Mul<C::Value>,
     Prod<R::Value, C::Value>: ArrayLength<N>,
-{
-}
+{}
 
 impl<N, R, C> PartialEq for MatrixArray<N, R, C>
 where
@@ -184,17 +182,13 @@ where
 
     #[inline]
     fn into_owned(self) -> Owned<N, R, C>
-    where
-        DefaultAllocator: Allocator<N, R, C>,
-    {
+    where DefaultAllocator: Allocator<N, R, C> {
         self
     }
 
     #[inline]
     fn clone_owned(&self) -> Owned<N, R, C>
-    where
-        DefaultAllocator: Allocator<N, R, C>,
-    {
+    where DefaultAllocator: Allocator<N, R, C> {
         let it = self.iter().cloned();
 
         DefaultAllocator::allocate_from_iterator(self.shape().0, self.shape().1, it)
@@ -234,8 +228,7 @@ where
     R::Value: Mul<C::Value>,
     Prod<R::Value, C::Value>: ArrayLength<N>,
     DefaultAllocator: Allocator<N, R, C, Buffer = Self>,
-{
-}
+{}
 
 unsafe impl<N, R, C> ContiguousStorageMut<N, R, C> for MatrixArray<N, R, C>
 where
@@ -245,8 +238,7 @@ where
     R::Value: Mul<C::Value>,
     Prod<R::Value, C::Value>: ArrayLength<N>,
     DefaultAllocator: Allocator<N, R, C, Buffer = Self>,
-{
-}
+{}
 
 /*
  *
@@ -264,9 +256,7 @@ where
     Prod<R::Value, C::Value>: ArrayLength<N>,
 {
     fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
-    where
-        S: Serializer,
-    {
+    where S: Serializer {
         let mut serializer = serializer.serialize_seq(Some(R::dim() * C::dim()))?;
 
         for e in self.iter() {
@@ -287,9 +277,7 @@ where
     Prod<R::Value, C::Value>: ArrayLength<N>,
 {
     fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
-    where
-        D: Deserializer<'a>,
-    {
+    where D: Deserializer<'a> {
         deserializer.deserialize_seq(MatrixArrayVisitor::new())
     }
 }
@@ -334,9 +322,7 @@ where
 
     #[inline]
     fn visit_seq<V>(self, mut visitor: V) -> Result<MatrixArray<N, R, C>, V::Error>
-    where
-        V: SeqAccess<'a>,
-    {
+    where V: SeqAccess<'a> {
         let mut out: Self::Value = unsafe { mem::uninitialized() };
         let mut curr = 0;
 

src/base/matrix_slice.rs

@@ -206,7 +206,8 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
         start: (usize, usize),
         shape: (usize, usize),
         steps: (usize, usize),
-    ) {
+    )
+    {
         let my_shape = self.shape();
         // NOTE: we don't do any subtraction to avoid underflow for zero-sized matrices.
         //
@@ -803,7 +804,8 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     pub fn rows_range<RowRange: SliceRange<R>>(
         &self,
         rows: RowRange,
-    ) -> MatrixSlice<N, RowRange::Size, C, S::RStride, S::CStride> {
+    ) -> MatrixSlice<N, RowRange::Size, C, S::RStride, S::CStride>
+    {
         self.slice_range(rows, ..)
     }
 
@@ -812,7 +814,8 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
     pub fn columns_range<ColRange: SliceRange<C>>(
         &self,
         cols: ColRange,
-    ) -> MatrixSlice<N, R, ColRange::Size, S::RStride, S::CStride> {
+    ) -> MatrixSlice<N, R, ColRange::Size, S::RStride, S::CStride>
+    {
         self.slice_range(.., cols)
     }
 }
@@ -841,7 +844,8 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     pub fn rows_range_mut<RowRange: SliceRange<R>>(
         &mut self,
         rows: RowRange,
-    ) -> MatrixSliceMut<N, RowRange::Size, C, S::RStride, S::CStride> {
+    ) -> MatrixSliceMut<N, RowRange::Size, C, S::RStride, S::CStride>
+    {
         self.slice_range_mut(rows, ..)
     }
 
@@ -850,7 +854,8 @@ impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
     pub fn columns_range_mut<ColRange: SliceRange<C>>(
         &mut self,
         cols: ColRange,
-    ) -> MatrixSliceMut<N, R, ColRange::Size, S::RStride, S::CStride> {
+    ) -> MatrixSliceMut<N, R, ColRange::Size, S::RStride, S::CStride>
+    {
         self.slice_range_mut(.., cols)
     }
 }

src/base/matrix_vec.rs

@@ -94,8 +94,7 @@ impl<N, R: Dim, C: Dim> Deref for MatrixVec<N, R, C> {
  *
  */
 unsafe impl<N: Scalar, C: Dim> Storage<N, Dynamic, C> for MatrixVec<N, Dynamic, C>
-where
-    DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>,
+where DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>
 {
     type RStride = U1;
     type CStride = Dynamic;
@@ -122,17 +121,13 @@ where
 
     #[inline]
     fn into_owned(self) -> Owned<N, Dynamic, C>
-    where
-        DefaultAllocator: Allocator<N, Dynamic, C>,
-    {
+    where DefaultAllocator: Allocator<N, Dynamic, C> {
         self
     }
 
     #[inline]
     fn clone_owned(&self) -> Owned<N, Dynamic, C>
-    where
-        DefaultAllocator: Allocator<N, Dynamic, C>,
-    {
+    where DefaultAllocator: Allocator<N, Dynamic, C> {
         self.clone()
     }
 
@@ -143,8 +138,7 @@ where
 }
 
 unsafe impl<N: Scalar, R: DimName> Storage<N, R, Dynamic> for MatrixVec<N, R, Dynamic>
-where
-    DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>,
+where DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>
 {
     type RStride = U1;
     type CStride = R;
@@ -171,17 +165,13 @@ where
 
     #[inline]
     fn into_owned(self) -> Owned<N, R, Dynamic>
-    where
-        DefaultAllocator: Allocator<N, R, Dynamic>,
-    {
+    where DefaultAllocator: Allocator<N, R, Dynamic> {
         self
     }
 
     #[inline]
     fn clone_owned(&self) -> Owned<N, R, Dynamic>
-    where
-        DefaultAllocator: Allocator<N, R, Dynamic>,
-    {
+    where DefaultAllocator: Allocator<N, R, Dynamic> {
         self.clone()
     }
 
@@ -197,8 +187,7 @@ where
  *
  */
 unsafe impl<N: Scalar, C: Dim> StorageMut<N, Dynamic, C> for MatrixVec<N, Dynamic, C>
-where
-    DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>,
+where DefaultAllocator: Allocator<N, Dynamic, C, Buffer = Self>
 {
     #[inline]
     fn ptr_mut(&mut self) -> *mut N {
@@ -211,21 +200,14 @@ where
     }
 }
 
-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 MatrixVec<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 MatrixVec<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>
-where
-    DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>,
+where DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>
 {
     #[inline]
     fn ptr_mut(&mut self) -> *mut N {
@@ -253,14 +235,8 @@ 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 MatrixVec<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 MatrixVec<N, R, Dynamic> where DefaultAllocator: Allocator<N, R, Dynamic, Buffer = Self>
+{}

src/base/mod.rs

@@ -12,7 +12,6 @@ pub mod storage;
 
 mod alias;
 mod alias_slice;
-mod swizzle;
 mod cg;
 mod componentwise;
 mod construction;
@@ -27,6 +26,7 @@ mod matrix_slice;
 mod matrix_vec;
 mod properties;
 mod scalar;
+mod swizzle;
 mod unit;
 
 #[doc(hidden)]

src/base/ops.rs

@@ -1,17 +1,19 @@
-use std::iter;
-use std::ops::{Add, AddAssign, Div, DivAssign, Index, IndexMut, Mul, MulAssign, Neg, Sub,
-               SubAssign};
-use std::cmp::PartialOrd;
 use num::{One, Signed, Zero};
+use std::cmp::PartialOrd;
+use std::iter;
+use std::ops::{
+    Add, AddAssign, Div, DivAssign, Index, IndexMut, Mul, MulAssign, Neg, Sub, SubAssign,
+};
 
 use alga::general::{ClosedAdd, ClosedDiv, ClosedMul, ClosedNeg, ClosedSub};
 
-use base::{DefaultAllocator, Matrix, MatrixMN, MatrixN, MatrixSum, Scalar};
-use base::dimension::{Dim, DimMul, DimName, DimProd};
-use base::constraint::{AreMultipliable, DimEq, SameNumberOfColumns, SameNumberOfRows,
-                       ShapeConstraint};
-use base::storage::{ContiguousStorageMut, Storage, StorageMut};
 use base::allocator::{Allocator, SameShapeAllocator, SameShapeC, SameShapeR};
+use base::constraint::{
+    AreMultipliable, DimEq, SameNumberOfColumns, SameNumberOfRows, ShapeConstraint,
+};
+use base::dimension::{Dim, DimMul, DimName, DimProd};
+use base::storage::{ContiguousStorageMut, Storage, StorageMut};
+use base::{DefaultAllocator, Matrix, MatrixMN, MatrixN, MatrixSum, Scalar};
 
 /*
  *
@@ -722,9 +724,7 @@ impl<N: Scalar + ClosedAdd, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C,
     /// Adds a scalar to `self`.
     #[inline]
     pub fn add_scalar(&self, rhs: N) -> MatrixMN<N, R, C>
-    where
-        DefaultAllocator: Allocator<N, R, C>,
-    {
+    where DefaultAllocator: Allocator<N, R, C> {
         let mut res = self.clone_owned();
         res.add_scalar_mut(rhs);
         res
@@ -733,9 +733,7 @@ impl<N: Scalar + ClosedAdd, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C,
     /// Adds a scalar to `self` in-place.
     #[inline]
     pub fn add_scalar_mut(&mut self, rhs: N)
-    where
-        S: StorageMut<N, R, C>,
-    {
+    where S: StorageMut<N, R, C> {
         for e in self.iter_mut() {
             *e += rhs
         }
@@ -783,7 +781,8 @@ impl<N: Scalar + PartialOrd + Signed, R: Dim, C: Dim, S: Storage<N, R, C>> Matri
     #[inline]
     pub fn amin(&self) -> N {
         let mut it = self.iter();
-        let mut min = it.next()
+        let mut min = it
+            .next()
             .expect("amin: empty matrices not supported.")
             .abs();
 

src/base/properties.rs

@@ -100,8 +100,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
 }
 
 impl<N: Real, D: Dim, S: Storage<N, D, D>> SquareMatrix<N, D, S>
-where
-    DefaultAllocator: Allocator<N, D, D>,
+where DefaultAllocator: Allocator<N, D, D>
 {
     /// Checks that this matrix is orthogonal and has a determinant equal to 1.
     #[inline]

src/base/scalar.rs

@@ -1,6 +1,6 @@
+use std::any::Any;
 use std::any::TypeId;
 use std::fmt::Debug;
-use std::any::Any;
 
 /// The basic scalar type for all structures of `nalgebra`.
 ///

src/base/storage.rs

@@ -3,10 +3,10 @@
 use std::fmt::Debug;
 use std::mem;
 
-use base::Scalar;
+use base::allocator::{Allocator, SameShapeC, SameShapeR};
 use base::default_allocator::DefaultAllocator;
 use base::dimension::{Dim, U1};
-use base::allocator::{Allocator, SameShapeC, SameShapeR};
+use base::Scalar;
 
 /*
  * Aliases for allocation results.
@@ -105,13 +105,11 @@ pub unsafe trait Storage<N: Scalar, R: Dim, C: Dim = U1>: Debug + Sized {
 
     /// Builds a matrix data storage that does not contain any reference.
     fn into_owned(self) -> Owned<N, R, C>
-    where
-        DefaultAllocator: Allocator<N, R, C>;
+    where DefaultAllocator: Allocator<N, R, C>;
 
     /// Clones this data storage to one that does not contain any reference.
     fn clone_owned(&self) -> Owned<N, R, C>
-    where
-        DefaultAllocator: Allocator<N, R, C>;
+    where DefaultAllocator: Allocator<N, R, C>;
 }
 
 /// Trait implemented by matrix data storage that can provide a mutable access to its elements.
@@ -177,8 +175,9 @@ pub unsafe trait StorageMut<N: Scalar, R: Dim, C: Dim = U1>: Storage<N, R, C> {
 /// The storage requirement means that for any value of `i` in `[0, nrows * ncols[`, the value
 /// `.get_unchecked_linear` returns one of the matrix component. This trait is unsafe because
 /// failing to comply to this may cause Undefined Behaviors.
-pub unsafe trait ContiguousStorage<N: Scalar, R: Dim, C: Dim = U1>
-    : Storage<N, R, C> {
+pub unsafe trait ContiguousStorage<N: Scalar, R: Dim, C: Dim = U1>:
+    Storage<N, R, C>
+{
 }
 
 /// A mutable matrix storage that is stored contiguously in memory.
@@ -186,6 +185,7 @@ pub unsafe trait ContiguousStorage<N: Scalar, R: Dim, C: Dim = U1>
 /// The storage requirement means that for any value of `i` in `[0, nrows * ncols[`, the value
 /// `.get_unchecked_linear` returns one of the matrix component. This trait is unsafe because
 /// failing to comply to this may cause Undefined Behaviors.
-pub unsafe trait ContiguousStorageMut<N: Scalar, R: Dim, C: Dim = U1>
-    : ContiguousStorage<N, R, C> + StorageMut<N, R, C> {
+pub unsafe trait ContiguousStorageMut<N: Scalar, R: Dim, C: Dim = U1>:
+    ContiguousStorage<N, R, C> + StorageMut<N, R, C>
+{
 }

src/base/swizzle.rs

@@ -1,8 +1,7 @@
-use base::{Scalar, Vector, DimName, Vector2, Vector3};
+use base::{DimName, Scalar, Vector, Vector2, Vector3};
 use storage::Storage;
 use typenum::{self, Cmp, Greater};
 
-
 macro_rules! impl_swizzle {
     ($(where $BaseDim: ident: $name: ident() -> $Result: ident[$($i: expr),*]);*) => {
         $(
@@ -64,4 +63,4 @@ impl_swizzle!(
     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

@@ -25,9 +25,7 @@ pub struct Unit<T> {
 #[cfg(feature = "serde-serialize")]
 impl<T: Serialize> Serialize for Unit<T> {
     fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
-    where
-        S: Serializer,
-    {
+    where S: Serializer {
         self.value.serialize(serializer)
     }
 }
@@ -35,9 +33,7 @@ impl<T: Serialize> Serialize for Unit<T> {
 #[cfg(feature = "serde-serialize")]
 impl<'de, T: Deserialize<'de>> Deserialize<'de> for Unit<T> {
     fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
-    where
-        D: Deserializer<'de>,
-    {
+    where D: Deserializer<'de> {
         T::deserialize(deserializer).map(|x| Unit { value: x })
     }
 }
@@ -143,8 +139,7 @@ impl<T> AsRef<T> for Unit<T> {
  *
  */
 impl<T: NormedSpace> SubsetOf<T> for Unit<T>
-where
-    T::Field: RelativeEq,
+where T::Field: RelativeEq
 {
     #[inline]
     fn to_superset(&self) -> T {

src/debug/random_orthogonal.rs

@@ -13,15 +13,13 @@ use num_complex::Complex;
 /// A random orthogonal matrix.
 #[derive(Clone, Debug)]
 pub struct RandomOrthogonal<N: Real, D: Dim = Dynamic>
-where
-    DefaultAllocator: Allocator<N, D, D>,
+where DefaultAllocator: Allocator<N, D, D>
 {
     m: MatrixN<N, D>,
 }
 
 impl<N: Real, D: Dim> RandomOrthogonal<N, D>
-where
-    DefaultAllocator: Allocator<N, D, D>,
+where DefaultAllocator: Allocator<N, D, D>
 {
     /// Retrieve the generated matrix.
     pub fn unwrap(self) -> MatrixN<N, D> {

src/debug/random_sdp.rs

@@ -13,15 +13,13 @@ use debug::RandomOrthogonal;
 /// A random, well-conditioned, symmetric definite-positive matrix.
 #[derive(Clone, Debug)]
 pub struct RandomSDP<N: Real, D: Dim = Dynamic>
-where
-    DefaultAllocator: Allocator<N, D, D>,
+where DefaultAllocator: Allocator<N, D, D>
 {
     m: MatrixN<N, D>,
 }
 
 impl<N: Real, D: Dim> RandomSDP<N, D>
-where
-    DefaultAllocator: Allocator<N, D, D>,
+where DefaultAllocator: Allocator<N, D, D>
 {
     /// Retrieve the generated matrix.
     pub fn unwrap(self) -> MatrixN<N, D> {

src/geometry/isometry.rs

@@ -6,7 +6,7 @@ use std::io::{Result as IOResult, Write};
 use std::marker::PhantomData;
 
 #[cfg(feature = "serde-serialize")]
-use serde::{Serialize, Deserialize};
+use serde::{Deserialize, Serialize};
 
 #[cfg(feature = "abomonation-serialize")]
 use abomonation::Abomonation;
@@ -26,27 +26,22 @@ use geometry::{Point, Translation};
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            serialize = "R: Serialize,
+    serde(bound(
+        serialize = "R: Serialize,
                      DefaultAllocator: Allocator<N, D>,
                      Owned<N, D>: Serialize"
-        )
-    )
+    ))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(
-            deserialize = "R: Deserialize<'de>,
+    serde(bound(
+        deserialize = "R: Deserialize<'de>,
                        DefaultAllocator: Allocator<N, D>,
                        Owned<N, D>: Deserialize<'de>"
-        )
-    )
+    ))
 )]
 pub struct Isometry<N: Real, D: DimName, R>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     /// The pure rotational part of this isometry.
     pub rotation: R,
@@ -54,7 +49,10 @@ where
     pub translation: Translation<N, D>,
 
     // One dummy private field just to prevent explicit construction.
-    #[cfg_attr(feature = "serde-serialize", serde(skip_serializing, skip_deserializing))]
+    #[cfg_attr(
+        feature = "serde-serialize",
+        serde(skip_serializing, skip_deserializing)
+    )]
     _noconstruct: PhantomData<N>,
 }
 
@@ -98,12 +96,10 @@ impl<N: Real, D: DimName + Copy, R: Rotation<Point<N, D>> + Copy> Copy for Isome
 where
     DefaultAllocator: Allocator<N, D>,
     Owned<N, D>: Copy,
-{
-}
+{}
 
 impl<N: Real, D: DimName, R: Rotation<Point<N, D>> + Clone> Clone for Isometry<N, D, R>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     #[inline]
     fn clone(&self) -> Self {
@@ -112,8 +108,7 @@ where
 }
 
 impl<N: Real, D: DimName, R: Rotation<Point<N, D>>> Isometry<N, D, R>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     /// Creates a new isometry from its rotational and translational parts.
     #[inline]
@@ -177,8 +172,7 @@ where
 // This is OK since all constructors of the isometry enforce the Rotation bound already (and
 // explicit struct construction is prevented by the dummy ZST field).
 impl<N: Real, D: DimName, R> Isometry<N, D, R>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     /// Converts this isometry into its equivalent homogeneous transformation matrix.
     #[inline]
@@ -200,8 +194,7 @@ impl<N: Real, D: DimName, R> Eq for Isometry<N, D, R>
 where
     R: Rotation<Point<N, D>> + Eq,
     DefaultAllocator: Allocator<N, D>,
-{
-}
+{}
 
 impl<N: Real, D: DimName, R> PartialEq for Isometry<N, D, R>
 where
@@ -251,7 +244,8 @@ where
         other: &Self,
         epsilon: Self::Epsilon,
         max_relative: Self::Epsilon,
-    ) -> bool {
+    ) -> bool
+    {
         self.translation
             .relative_eq(&other.translation, epsilon, max_relative)
             && self

src/geometry/isometry_alga.rs

@@ -1,9 +1,12 @@
-use alga::general::{AbstractGroup, AbstractLoop, AbstractMagma, AbstractMonoid,
-                    AbstractQuasigroup, AbstractSemigroup, Id, Identity, Inverse, Multiplicative,
-                    Real};
+use alga::general::{
+    AbstractGroup, AbstractLoop, AbstractMagma, AbstractMonoid, AbstractQuasigroup,
+    AbstractSemigroup, Id, Identity, Inverse, Multiplicative, Real,
+};
 use alga::linear::Isometry as AlgaIsometry;
-use alga::linear::{AffineTransformation, DirectIsometry, ProjectiveTransformation, Rotation,
-                   Similarity, Transformation};
+use alga::linear::{
+    AffineTransformation, DirectIsometry, ProjectiveTransformation, Rotation, Similarity,
+    Transformation,
+};
 
 use base::allocator::Allocator;
 use base::dimension::DimName;

src/geometry/isometry_construction.rs

@@ -20,8 +20,7 @@ use geometry::{
 };
 
 impl<N: Real, D: DimName, R: AlgaRotation<Point<N, D>>> Isometry<N, D, R>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     /// Creates a new identity isometry.
     #[inline]
@@ -39,8 +38,7 @@ where
 }
 
 impl<N: Real, D: DimName, R: AlgaRotation<Point<N, D>>> One for Isometry<N, D, R>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     /// Creates a new identity isometry.
     #[inline]

src/geometry/mod.rs

@@ -4,61 +4,61 @@
 mod op_macros;
 
 mod point;
-mod point_construction;
-mod point_alias;
-mod point_ops;
 mod point_alga;
+mod point_alias;
+mod point_construction;
 mod point_conversion;
 mod point_coordinates;
+mod point_ops;
 
 mod rotation;
-mod rotation_construction;
-mod rotation_ops;
 mod rotation_alga; // FIXME: implement Rotation methods.
-mod rotation_conversion;
 mod rotation_alias;
+mod rotation_construction;
+mod rotation_conversion;
+mod rotation_ops;
 mod rotation_specialization;
 
 mod quaternion;
-mod quaternion_construction;
-mod quaternion_ops;
 mod quaternion_alga;
+mod quaternion_construction;
 mod quaternion_conversion;
 mod quaternion_coordinates;
+mod quaternion_ops;
 
 mod unit_complex;
-mod unit_complex_construction;
-mod unit_complex_ops;
 mod unit_complex_alga;
+mod unit_complex_construction;
 mod unit_complex_conversion;
+mod unit_complex_ops;
 
 mod translation;
-mod translation_construction;
-mod translation_ops;
 mod translation_alga;
-mod translation_conversion;
 mod translation_alias;
+mod translation_construction;
+mod translation_conversion;
+mod translation_ops;
 
 mod isometry;
-mod isometry_construction;
-mod isometry_ops;
 mod isometry_alga;
-mod isometry_conversion;
 mod isometry_alias;
+mod isometry_construction;
+mod isometry_conversion;
+mod isometry_ops;
 
 mod similarity;
-mod similarity_construction;
-mod similarity_ops;
 mod similarity_alga;
-mod similarity_conversion;
 mod similarity_alias;
+mod similarity_construction;
+mod similarity_conversion;
+mod similarity_ops;
 
 mod transform;
-mod transform_construction;
-mod transform_ops;
 mod transform_alga;
-mod transform_conversion;
 mod transform_alias;
+mod transform_construction;
+mod transform_conversion;
+mod transform_ops;
 
 mod reflection;
 

src/geometry/orthographic.rs

@@ -46,9 +46,7 @@ impl<N: Real> PartialEq for Orthographic3<N> {
 #[cfg(feature = "serde-serialize")]
 impl<N: Real + Serialize> Serialize for Orthographic3<N> {
     fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
-    where
-        S: Serializer,
-    {
+    where S: Serializer {
         self.matrix.serialize(serializer)
     }
 }
@@ -56,9 +54,7 @@ impl<N: Real + Serialize> Serialize for Orthographic3<N> {
 #[cfg(feature = "serde-serialize")]
 impl<'a, N: Real + Deserialize<'a>> Deserialize<'a> for Orthographic3<N> {
     fn deserialize<Des>(deserializer: Des) -> Result<Self, Des::Error>
-    where
-        Des: Deserializer<'a>,
-    {
+    where Des: Deserializer<'a> {
         let matrix = Matrix4::<N>::deserialize(deserializer)?;
 
         Ok(Orthographic3::from_matrix_unchecked(matrix))
@@ -238,9 +234,7 @@ impl<N: Real> Orthographic3<N> {
     /// Projects a vector. Faster than matrix multiplication.
     #[inline]
     pub fn project_vector<SB>(&self, p: &Vector<N, U3, SB>) -> Vector3<N>
-    where
-        SB: Storage<N, U3>,
-    {
+    where SB: Storage<N, U3> {
         Vector3::new(
             self.matrix[(0, 0)] * p[0],
             self.matrix[(1, 1)] * p[1],
@@ -325,8 +319,7 @@ impl<N: Real> Orthographic3<N> {
 }
 
 impl<N: Real> Distribution<Orthographic3<N>> for Standard
-where
-    Standard: Distribution<N>,
+where Standard: Distribution<N>
 {
     fn sample<R: Rng + ?Sized>(&self, r: &mut R) -> Orthographic3<N> {
         let left = r.gen();
@@ -342,8 +335,7 @@ where
 
 #[cfg(feature = "arbitrary")]
 impl<N: Real + Arbitrary> Arbitrary for Orthographic3<N>
-where
-    Matrix4<N>: Send,
+where Matrix4<N>: Send
 {
     fn arbitrary<G: Gen>(g: &mut G) -> Self {
         let left = Arbitrary::arbitrary(g);

src/geometry/perspective.rs

@@ -47,9 +47,7 @@ impl<N: Real> PartialEq for Perspective3<N> {
 #[cfg(feature = "serde-serialize")]
 impl<N: Real + Serialize> Serialize for Perspective3<N> {
     fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
-    where
-        S: Serializer,
-    {
+    where S: Serializer {
         self.matrix.serialize(serializer)
     }
 }
@@ -57,9 +55,7 @@ impl<N: Real + Serialize> Serialize for Perspective3<N> {
 #[cfg(feature = "serde-serialize")]
 impl<'a, N: Real + Deserialize<'a>> Deserialize<'a> for Perspective3<N> {
     fn deserialize<Des>(deserializer: Des) -> Result<Self, Des::Error>
-    where
-        Des: Deserializer<'a>,
-    {
+    where Des: Deserializer<'a> {
         let matrix = Matrix4::<N>::deserialize(deserializer)?;
 
         Ok(Perspective3::from_matrix_unchecked(matrix))
@@ -207,9 +203,7 @@ impl<N: Real> Perspective3<N> {
     /// Projects a vector. Faster than matrix multiplication.
     #[inline]
     pub fn project_vector<SB>(&self, p: &Vector<N, U3, SB>) -> Vector3<N>
-    where
-        SB: Storage<N, U3>,
-    {
+    where SB: Storage<N, U3> {
         let inverse_denom = -N::one() / p[2];
         Vector3::new(
             self.matrix[(0, 0)] * p[0] * inverse_denom,
@@ -260,8 +254,7 @@ impl<N: Real> Perspective3<N> {
 }
 
 impl<N: Real> Distribution<Perspective3<N>> for Standard
-where
-    Standard: Distribution<N>,
+where Standard: Distribution<N>
 {
     fn sample<'a, R: Rng + ?Sized>(&self, r: &'a mut R) -> Perspective3<N> {
         let znear = r.gen();

src/geometry/point.rs

@@ -7,7 +7,7 @@ use std::hash;
 use std::io::{Result as IOResult, Write};
 
 #[cfg(feature = "serde-serialize")]
-use serde::{Serialize, Deserialize, Serializer, Deserializer};
+use serde::{Deserialize, Deserializer, Serialize, Serializer};
 
 #[cfg(feature = "abomonation-serialize")]
 use abomonation::Abomonation;
@@ -21,8 +21,7 @@ use base::{DefaultAllocator, Scalar, VectorN};
 #[repr(C)]
 #[derive(Debug)]
 pub struct Point<N: Scalar, D: DimName>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     /// The coordinates of this point, i.e., the shift from the origin.
     pub coords: VectorN<N, D>,
@@ -42,8 +41,7 @@ impl<N: Scalar, D: DimName> Copy for Point<N, D>
 where
     DefaultAllocator: Allocator<N, D>,
     <DefaultAllocator as Allocator<N, D>>::Buffer: Copy,
-{
-}
+{}
 
 impl<N: Scalar, D: DimName> Clone for Point<N, D>
 where
@@ -63,9 +61,7 @@ where
     <DefaultAllocator as Allocator<N, D>>::Buffer: Serialize,
 {
     fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
-    where
-        S: Serializer,
-    {
+    where S: Serializer {
         self.coords.serialize(serializer)
     }
 }
@@ -77,9 +73,7 @@ where
     <DefaultAllocator as Allocator<N, D>>::Buffer: Deserialize<'a>,
 {
     fn deserialize<Des>(deserializer: Des) -> Result<Self, Des::Error>
-    where
-        Des: Deserializer<'a>,
-    {
+    where Des: Deserializer<'a> {
         let coords = VectorN::<N, D>::deserialize(deserializer)?;
 
         Ok(Point::from_coordinates(coords))
@@ -108,8 +102,7 @@ where
 }
 
 impl<N: Scalar, D: DimName> Point<N, D>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     /// Clones this point into one that owns its data.
     #[inline]
@@ -219,7 +212,8 @@ where
         other: &Self,
         epsilon: Self::Epsilon,
         max_relative: Self::Epsilon,
-    ) -> bool {
+    ) -> bool
+    {
         self.coords
             .relative_eq(&other.coords, epsilon, max_relative)
     }
@@ -241,15 +235,10 @@ where
     }
 }
 
-impl<N: Scalar + Eq, D: DimName> Eq for Point<N, D>
-where
-    DefaultAllocator: Allocator<N, D>,
-{
-}
+impl<N: Scalar + Eq, D: DimName> Eq for Point<N, D> where DefaultAllocator: Allocator<N, D> {}
 
 impl<N: Scalar, D: DimName> PartialEq for Point<N, D>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     #[inline]
     fn eq(&self, right: &Self) -> bool {
@@ -258,8 +247,7 @@ where
 }
 
 impl<N: Scalar + PartialOrd, D: DimName> PartialOrd for Point<N, D>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     #[inline]
     fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
@@ -293,8 +281,7 @@ where
  *
  */
 impl<N: Scalar + fmt::Display, D: DimName> fmt::Display for Point<N, D>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
         try!(write!(f, "{{"));

src/geometry/point_alga.rs

@@ -1,9 +1,9 @@
 use alga::general::{Field, JoinSemilattice, Lattice, MeetSemilattice, Real};
 use alga::linear::{AffineSpace, EuclideanSpace};
 
-use base::{DefaultAllocator, Scalar, VectorN};
-use base::dimension::DimName;
 use base::allocator::Allocator;
+use base::dimension::DimName;
+use base::{DefaultAllocator, Scalar, VectorN};
 
 use geometry::Point;
 
@@ -16,8 +16,7 @@ where
 }
 
 impl<N: Real, D: DimName> EuclideanSpace for Point<N, D>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     type Coordinates = VectorN<N, D>;
     type Real = N;

src/geometry/point_construction.rs

@@ -13,8 +13,7 @@ use base::{DefaultAllocator, Scalar, VectorN};
 use geometry::Point;
 
 impl<N: Scalar, D: DimName> Point<N, D>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     /// Creates a new point with uninitialized coordinates.
     #[inline]
@@ -25,9 +24,7 @@ where
     /// Creates a new point with all coordinates equal to zero.
     #[inline]
     pub fn origin() -> Self
-    where
-        N: Zero,
-    {
+    where N: Zero {
         Self::from_coordinates(VectorN::from_element(N::zero()))
     }
 
@@ -63,8 +60,7 @@ where
  *
  */
 impl<N: Scalar + Bounded, D: DimName> Bounded for Point<N, D>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     #[inline]
     fn max_value() -> Self {

src/geometry/point_ops.rs

@@ -19,8 +19,7 @@ use geometry::Point;
  *
  */
 impl<N: Scalar, D: DimName> Index<usize> for Point<N, D>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     type Output = N;
 
@@ -31,8 +30,7 @@ where
 }
 
 impl<N: Scalar, D: DimName> IndexMut<usize> for Point<N, D>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     #[inline]
     fn index_mut(&mut self, i: usize) -> &mut Self::Output {
@@ -46,8 +44,7 @@ where
  *
  */
 impl<N: Scalar + ClosedNeg, D: DimName> Neg for Point<N, D>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     type Output = Point<N, D>;
 
@@ -58,8 +55,7 @@ where
 }
 
 impl<'a, N: Scalar + ClosedNeg, D: DimName> Neg for &'a Point<N, D>
-where
-    DefaultAllocator: Allocator<N, D>,
+where DefaultAllocator: Allocator<N, D>
 {
     type Output = Point<N, D>;
 

src/geometry/quaternion.rs

@@ -8,7 +8,7 @@ use std::io::{Result as IOResult, Write};
 #[cfg(feature = "serde-serialize")]
 use base::storage::Owned;
 #[cfg(feature = "serde-serialize")]
-use serde::{Serialize, Deserialize, Serializer, Deserializer};
+use serde::{Deserialize, Deserializer, Serialize, Serializer};
 
 #[cfg(feature = "abomonation-serialize")]
 use abomonation::Abomonation;
@@ -32,8 +32,7 @@ pub struct Quaternion<N: Real> {
 
 #[cfg(feature = "abomonation-serialize")]
 impl<N: Real> Abomonation for Quaternion<N>
-where
-    Vector4<N>: Abomonation,
+where Vector4<N>: Abomonation
 {
     unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
         self.coords.entomb(writer)
@@ -75,26 +74,20 @@ impl<N: Real> Clone for Quaternion<N> {
 
 #[cfg(feature = "serde-serialize")]
 impl<N: Real> Serialize for Quaternion<N>
-where
-    Owned<N, U4>: Serialize,
+where Owned<N, U4>: Serialize
 {
     fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
-    where
-        S: Serializer,
-    {
+    where S: Serializer {
         self.coords.serialize(serializer)
     }
 }
 
 #[cfg(feature = "serde-serialize")]
 impl<'a, N: Real> Deserialize<'a> for Quaternion<N>
-where
-    Owned<N, U4>: Deserialize<'a>,
+where Owned<N, U4>: Deserialize<'a>
 {
     fn deserialize<Des>(deserializer: Des) -> Result<Self, Des::Error>
-    where
-        Des: Deserializer<'a>,
-    {
+    where Des: Deserializer<'a> {
         let coords = Vector4::<N>::deserialize(deserializer)?;
 
         Ok(Quaternion::from_vector(coords))
@@ -337,7 +330,8 @@ impl<N: Real + RelativeEq<Epsilon = N>> RelativeEq for Quaternion<N> {
         other: &Self,
         epsilon: Self::Epsilon,
         max_relative: Self::Epsilon,
-    ) -> bool {
+    ) -> bool
+    {
         self.as_vector().relative_eq(other.as_vector(), epsilon, max_relative) ||
         // Account for the double-covering of S², i.e. q = -q
        self.as_vector().iter().zip(other.as_vector().iter()).all(|(a, b)| a.relative_eq(&-*b, epsilon, max_relative))
@@ -457,9 +451,11 @@ impl<N: Real> UnitQuaternion<N> {
     /// is not well-defined).
     #[inline]
     pub fn slerp(&self, other: &UnitQuaternion<N>, t: N) -> UnitQuaternion<N> {
-        Unit::new_unchecked(
-            Quaternion::from_vector(Unit::new_unchecked(self.coords).slerp(&Unit::new_unchecked(other.coords), t).unwrap())
-        )
+        Unit::new_unchecked(Quaternion::from_vector(
+            Unit::new_unchecked(self.coords)
+                .slerp(&Unit::new_unchecked(other.coords), t)
+                .unwrap(),
+        ))
     }
 
     /// Computes the spherical linear interpolation between two unit quaternions or returns `None`
@@ -478,8 +474,10 @@ impl<N: Real> UnitQuaternion<N> {
         other: &UnitQuaternion<N>,
         t: N,
         epsilon: N,
-    ) -> Option<UnitQuaternion<N>> {
-        Unit::new_unchecked(self.coords).try_slerp(&Unit::new_unchecked(other.coords), t, epsilon)
+    ) -> Option<UnitQuaternion<N>>
+    {
+        Unit::new_unchecked(self.coords)
+            .try_slerp(&Unit::new_unchecked(other.coords), t, epsilon)
             .map(|q| Unit::new_unchecked(Quaternion::from_vector(q.unwrap())))
     }
 
@@ -659,7 +657,8 @@ impl<N: Real + RelativeEq<Epsilon = N>> RelativeEq for UnitQuaternion<N> {
         other: &Self,
         epsilon: Self::Epsilon,
         max_relative: Self::Epsilon,
-    ) -> bool {
+    ) -> bool
+    {
         self.as_ref()
             .relative_eq(other.as_ref(), epsilon, max_relative)
     }

src/geometry/quaternion_alga.rs

@@ -1,11 +1,15 @@
 use num::Zero;
 
-use alga::general::{AbstractGroup, AbstractGroupAbelian, AbstractLoop, AbstractMagma,
-                    AbstractModule, AbstractMonoid, AbstractQuasigroup, AbstractSemigroup,
-                    Additive, Id, Identity, Inverse, Module, Multiplicative, Real};
-use alga::linear::{AffineTransformation, DirectIsometry, FiniteDimVectorSpace, Isometry,
-                   NormedSpace, OrthogonalTransformation, ProjectiveTransformation, Rotation,
-                   Similarity, Transformation, VectorSpace};
+use alga::general::{
+    AbstractGroup, AbstractGroupAbelian, AbstractLoop, AbstractMagma, AbstractModule,
+    AbstractMonoid, AbstractQuasigroup, AbstractSemigroup, Additive, Id, Identity, Inverse, Module,
+    Multiplicative, Real,
+};
+use alga::linear::{
+    AffineTransformation, DirectIsometry, FiniteDimVectorSpace, Isometry, NormedSpace,
+    OrthogonalTransformation, ProjectiveTransformation, Rotation, Similarity, Transformation,
+    VectorSpace,
+};
 
 use base::{Vector3, Vector4};
 use geometry::{Point3, Quaternion, UnitQuaternion};