Merge pull request #1362 from dimforge/dev-0.32.4

Release v0.32.4

CHANGELOG.md

@@ -4,6 +4,37 @@ documented here.
 
 This project adheres to [Semantic Versioning](https://semver.org/).
 
+## [0.32.4] (19 Feb 2023)
+- Add the `glam-0.25` feature to enable conversion from/to types from `glam` v0.25.
+
+## [0.32.3] (09 July 2023)
+
+### Modified
+- Statically sized matrices are now serialized as tuples to match how serde
+  serialized plain arrays.
+- Don’t require `Scalar` for matrix `PartialEq` and `Eq`.
+
+### Added
+- Allow trailing punctuation in macros `vector!`, `matrix!`, `point!`, etc.
+- Add the methods `Matrix1::as_scalar`, `::as_scalar_mut`, `::to_scalar`, `::into_scalar`.
+- Add `Rotation3::euler_angles_ordered`, a generalized euler angles calculation.
+- Add the `glam-0.24` feature to enable conversion from/to types from `glam` v0.24.
+- Add the `lerp` method to points.
+- Implement `Clone` for `MatrixIter`.
+
+### Fixed
+- Fixed severe catastrophic cancellation issue in variance calculation.
+
+## [0.32.2] (07 March 2023)
+
+### Added
+- Add the `glam-0.23` to enable conversion from/to type from `glam` v0.23. 
+
+## [0.32.1] (14 Jan. 2023)
+
+### Modified
+- Updated `nalgebra-macros` to use the new `Dyn`, avoiding macro-generated deprecation warnings.
+
 ## [0.32.0] (14 Jan. 2023)
 
 ### Modified

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name    = "nalgebra"
-version = "0.32.0"
+version = "0.32.4"
 authors = [ "Sébastien Crozet <developer@crozet.re>" ]
 
 description = "General-purpose linear algebra library with transformations and statically-sized or dynamically-sized matrices."
@@ -47,6 +47,9 @@ convert-glam019 = [ "glam019" ]
 convert-glam020 = [ "glam020" ]
 convert-glam021 = [ "glam021" ]
 convert-glam022 = [ "glam022" ]
+convert-glam023 = [ "glam023" ]
+convert-glam024 = [ "glam024" ]
+convert-glam025 = [ "glam025" ]
 
 # Serialization
 ## To use serde in a #[no-std] environment, enable the
@@ -56,7 +59,7 @@ convert-glam022 = [ "glam022" ]
 serde-serialize-no-std = [ "serde", "num-complex/serde" ]
 serde-serialize        = [ "serde-serialize-no-std", "serde/std" ]
 rkyv-serialize-no-std  = [ "rkyv/size_32" ]
-rkyv-serialize         = [ "rkyv-serialize-no-std", "rkyv/std", "rkyv/validation", "bytecheck" ]
+rkyv-serialize         = [ "rkyv-serialize-no-std", "rkyv/std", "rkyv/validation" ]
 
 # Randomness
 ## To use rand in a #[no-std] environment, enable the
@@ -71,7 +74,7 @@ slow-tests       = []
 rkyv-safe-deser  = [ "rkyv-serialize", "rkyv/validation" ]
 
 [dependencies]
-nalgebra-macros = { version = "0.1", path = "nalgebra-macros", optional = true }
+nalgebra-macros = { version = "0.2.1", path = "nalgebra-macros", optional = true }
 typenum        = "1.12"
 rand-package   = { package = "rand", version = "0.8", optional = true, default-features = false }
 num-traits     = { version = "0.2", default-features = false }
@@ -83,8 +86,7 @@ alga           = { version = "0.9", default-features = false, optional = true }
 rand_distr     = { version = "0.4", default-features = false, optional = true }
 matrixmultiply = { version = "0.3", optional = true }
 serde          = { version = "1.0", default-features = false, features = [ "derive" ], optional = true }
-rkyv           = { version = "0.7", default-features = false, optional = true }
+rkyv           = { version = "0.7.41", default-features = false, optional = true }
-bytecheck      = { version = "~0.6.1", optional = true }
 mint           = { version = "0.5", optional = true }
 quickcheck     = { version = "1", optional = true }
 pest           = { version = "2", optional = true }
@@ -101,6 +103,9 @@ glam019        = { package = "glam", version = "0.19", optional = true }
 glam020        = { package = "glam", version = "0.20", optional = true }
 glam021        = { package = "glam", version = "0.21", optional = true }
 glam022        = { package = "glam", version = "0.22", optional = true }
+glam023        = { package = "glam", version = "0.23", optional = true }
+glam024        = { package = "glam", version = "0.24", optional = true }
+glam025        = { package = "glam", version = "0.25", optional = true }
 cust_core      = { version = "0.1", optional = true }
 rayon          = { version = "1.6", optional = true }
 
@@ -109,6 +114,7 @@ serde_json = "1.0"
 rand_xorshift = "0.3"
 rand_isaac = "0.3"
 criterion = { version = "0.4", features = ["html_reports"] }
+nalgebra = { path = ".", features = ["debug", "compare", "rand", "macros"]}
 
 # For matrix comparison macro
 matrixcompare = "0.3.0"

README.md

@@ -29,22 +29,3 @@
 </p>
 
 -----
-
-## Acknowledgements
-nalgebra is supported by our **platinum** sponsors:
-<p>
-  <a href="https://embark-studios.com">
-    <img src="https://www.embark.dev/img/logo_black.png" width="301px">
-  </a>
-</p>
-
-And our gold sponsors:
-
-<p>
-  <a href="https://fragcolor.com">
-    <img src="https://dimforge.com/img/fragcolor_logo2_color_black.svg" width="300px">
-  </a>
-  <a href="https://resolutiongames.com/">
-    <img src="https://dimforge.com/img/logo_resolution_games.png" width="300px" />
-  </a>
-</p>

nalgebra-glm/src/gtc/epsilon.rs

@@ -7,24 +7,24 @@ use na::DefaultAllocator;
 use crate::traits::{Alloc, Number, Dimension};
 use crate::aliases::TVec;
 
-/// Component-wise approximate equality beween two vectors.
+/// Component-wise approximate equality between two vectors.
 pub fn epsilon_equal<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, epsilon: T) -> TVec<bool, D>
     where DefaultAllocator: Alloc<T, D> {
     x.zip_map(y, |x, y| abs_diff_eq!(x, y, epsilon = epsilon))
 }
 
-/// Component-wise approximate equality beween two scalars.
+/// Component-wise approximate equality between two scalars.
 pub fn epsilon_equal2<T: AbsDiffEq<Epsilon = T>>(x: T, y: T, epsilon: T) -> bool {
     abs_diff_eq!(x, y, epsilon = epsilon)
 }
 
-/// Component-wise approximate non-equality beween two vectors.
+/// Component-wise approximate non-equality between two vectors.
 pub fn epsilon_not_equal<T: Number, const D: usize>(x: &TVec<T, D>, y: &TVec<T, D>, epsilon: T) -> TVec<bool, D>
     where DefaultAllocator: Alloc<T, D> {
     x.zip_map(y, |x, y| abs_diff_ne!(x, y, epsilon = epsilon))
 }
 
-/// Component-wise approximate non-equality beween two scalars.
+/// Component-wise approximate non-equality between two scalars.
 pub fn epsilon_not_equal2<T: AbsDiffEq<Epsilon = T>>(x: T, y: T, epsilon: T) -> bool {
     abs_diff_ne!(x, y, epsilon = epsilon)
 }

nalgebra-glm/src/gtx/quaternion.rs

@@ -80,7 +80,7 @@ pub fn quat_to_mat3<T: RealNumber>(x: &Qua<T>) -> TMat3<T> {
         .into_inner()
 }
 
-/// Converts a quaternion to a rotation matrix in homogenous coordinates.
+/// Converts a quaternion to a rotation matrix in homogeneous coordinates.
 pub fn quat_to_mat4<T: RealNumber>(x: &Qua<T>) -> TMat4<T> {
     UnitQuaternion::new_unchecked(*x).to_homogeneous()
 }

nalgebra-macros/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "nalgebra-macros"
-version = "0.1.0"
+version = "0.2.1"
 authors = [ "Andreas Longva", "Sébastien Crozet <developer@crozet.re>" ]
 edition = "2018"
 description = "Procedural macros for nalgebra"

nalgebra-macros/src/lib.rs

@@ -223,7 +223,7 @@ impl Parse for Vector {
                 elements: Vec::new(),
             })
         } else {
-            let elements = MatrixRowSyntax::parse_separated_nonempty(input)?
+            let elements = MatrixRowSyntax::parse_terminated(input)?
                 .into_iter()
                 .collect();
             Ok(Self { elements })

nalgebra-macros/tests/tests.rs

@@ -94,6 +94,12 @@ fn dmatrix_small_dims_exhaustive() {
                DMatrix::from_row_slice(4, 4,  &[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]));
 }
 
+#[test]
+fn matrix_trailing_semi() {
+    matrix![1, 2;];
+    dmatrix![1, 2;];
+}
+
 // Skip rustfmt because it just makes the test bloated without making it more readable
 #[rustfmt::skip]
 #[test]
@@ -151,6 +157,13 @@ fn dvector_small_dims_exhaustive() {
     assert_eq_and_type!(dvector![1, 2, 3, 4, 5, 6], DVector::from_column_slice(&[1, 2, 3, 4, 5, 6]));
 }
 
+#[test]
+fn vector_trailing_comma() {
+    vector![1, 2,];
+    point![1, 2,];
+    dvector![1, 2,];
+}
+
 #[test]
 fn matrix_trybuild_tests() {
     let t = trybuild::TestCases::new();

nalgebra-sparse/src/cs.rs

@@ -494,7 +494,7 @@ where
     assert_eq!(source_minor_indices.len(), values.len());
     let nnz = values.len();
 
-    // Count the number of occurences of each minor index
+    // Count the number of occurrences of each minor index
     let mut minor_counts = vec![0; minor_dim];
     for minor_idx in source_minor_indices {
         minor_counts[*minor_idx] += 1;

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

@@ -98,7 +98,7 @@ where
 
 /// Faster sparse-sparse matrix multiplication, `C <- beta * C + alpha * op(A) * op(B)`.
 /// This will not return an error even if the patterns don't match.
-/// Should be used for situations where pattern creation immediately preceeds multiplication.
+/// Should be used for situations where pattern creation immediately precedes multiplication.
 ///
 /// Panics if the dimensions of the matrices involved are not compatible with the expression.
 pub fn spmm_csc_prealloc_unchecked<T>(

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

@@ -89,7 +89,7 @@ where
 
 /// Faster sparse-sparse matrix multiplication, `C <- beta * C + alpha * op(A) * op(B)`.
 /// This will not return an error even if the patterns don't match.
-/// Should be used for situations where pattern creation immediately preceeds multiplication.
+/// Should be used for situations where pattern creation immediately precedes multiplication.
 ///
 /// Panics if the dimensions of the matrices involved are not compatible with the expression.
 pub fn spmm_csr_prealloc_unchecked<T>(

src/base/alias.rs

@@ -81,32 +81,32 @@ pub type MatrixXx5<T> = Matrix<T, Dyn, U5, VecStorage<T, Dyn, U5>>;
 #[cfg(any(feature = "std", feature = "alloc"))]
 pub type MatrixXx6<T> = Matrix<T, Dyn, U6, VecStorage<T, Dyn, U6>>;
 
-/// A heap-allocated, row-major, matrix with 1 rows and a dynamic number of columns.
+/// A heap-allocated, column-major, matrix with 1 rows and a dynamic number of columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
 pub type Matrix1xX<T> = Matrix<T, U1, Dyn, VecStorage<T, U1, Dyn>>;
-/// A heap-allocated, row-major, matrix with 2 rows and a dynamic number of columns.
+/// A heap-allocated, column-major, matrix with 2 rows and a dynamic number of columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
 pub type Matrix2xX<T> = Matrix<T, U2, Dyn, VecStorage<T, U2, Dyn>>;
-/// A heap-allocated, row-major, matrix with 3 rows and a dynamic number of columns.
+/// A heap-allocated, column-major, matrix with 3 rows and a dynamic number of columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
 pub type Matrix3xX<T> = Matrix<T, U3, Dyn, VecStorage<T, U3, Dyn>>;
-/// A heap-allocated, row-major, matrix with 4 rows and a dynamic number of columns.
+/// A heap-allocated, column-major, matrix with 4 rows and a dynamic number of columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
 pub type Matrix4xX<T> = Matrix<T, U4, Dyn, VecStorage<T, U4, Dyn>>;
-/// A heap-allocated, row-major, matrix with 5 rows and a dynamic number of columns.
+/// A heap-allocated, column-major, matrix with 5 rows and a dynamic number of columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]
 pub type Matrix5xX<T> = Matrix<T, U5, Dyn, VecStorage<T, U5, Dyn>>;
-/// A heap-allocated, row-major, matrix with 6 rows and a dynamic number of columns.
+/// A heap-allocated, column-major, matrix with 6 rows and a dynamic number of columns.
 ///
 /// **Because this is an alias, not all its methods are listed here. See the [`Matrix`](crate::base::Matrix) type too.**
 #[cfg(any(feature = "std", feature = "alloc"))]

src/base/allocator.rs

@@ -20,9 +20,9 @@ use std::mem::MaybeUninit;
 /// Every allocator must be both static and dynamic. Though not all implementations may share the
 /// same `Buffer` type.
 pub trait Allocator<T, R: Dim, C: Dim = U1>: Any + Sized {
-    /// The type of buffer this allocator can instanciate.
+    /// The type of buffer this allocator can instantiate.
     type Buffer: StorageMut<T, R, C> + IsContiguous + Clone + Debug;
-    /// The type of buffer with uninitialized components this allocator can instanciate.
+    /// The type of buffer with uninitialized components this allocator can instantiate.
     type BufferUninit: RawStorageMut<MaybeUninit<T>, R, C> + IsContiguous;
 
     /// Allocates a buffer with the given number of rows and columns without initializing its content.

src/base/array_storage.rs

@@ -5,12 +5,15 @@ use std::ops::Mul;
 #[cfg(feature = "serde-serialize-no-std")]
 use serde::de::{Error, SeqAccess, Visitor};
 #[cfg(feature = "serde-serialize-no-std")]
-use serde::ser::SerializeSeq;
+use serde::ser::SerializeTuple;
 #[cfg(feature = "serde-serialize-no-std")]
 use serde::{Deserialize, Deserializer, Serialize, Serializer};
 #[cfg(feature = "serde-serialize-no-std")]
 use std::marker::PhantomData;
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
+
 use crate::base::allocator::Allocator;
 use crate::base::default_allocator::DefaultAllocator;
 use crate::base::dimension::{Const, ToTypenum};
@@ -189,7 +192,7 @@ where
     where
         S: Serializer,
     {
-        let mut serializer = serializer.serialize_seq(Some(R * C))?;
+        let mut serializer = serializer.serialize_tuple(R * C)?;
 
         for e in self.as_slice().iter() {
             serializer.serialize_element(e)?;
@@ -208,7 +211,7 @@ where
     where
         D: Deserializer<'a>,
     {
-        deserializer.deserialize_seq(ArrayStorageVisitor::new())
+        deserializer.deserialize_tuple(R * C, ArrayStorageVisitor::new())
     }
 }
 

src/base/dimension.rs

@@ -8,6 +8,8 @@ use std::fmt::Debug;
 use std::ops::{Add, Div, Mul, Sub};
 use typenum::{self, Diff, Max, Maximum, Min, Minimum, Prod, Quot, Sum, Unsigned};
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
 #[cfg(feature = "serde-serialize-no-std")]
 use serde::{Deserialize, Deserializer, Serialize, Serializer};
 

src/base/edition.rs

@@ -1077,7 +1077,7 @@ where
 }
 
 // Move the elements of `data` in such a way that the matrix with
-// the rows `[i, i + nremove[` deleted is represented in a contigous
+// the rows `[i, i + nremove[` deleted is represented in a contiguous
 // way in `data` after this method completes.
 // Every deleted element are manually dropped by this method.
 unsafe fn compress_rows<T: Scalar>(

src/base/iter.rs

@@ -15,9 +15,9 @@ use crate::base::storage::{RawStorage, RawStorageMut};
 use crate::base::{Matrix, MatrixView, MatrixViewMut, Scalar};
 
 macro_rules! iterator {
-    (struct $Name:ident for $Storage:ident.$ptr: ident -> $Ptr:ty, $Ref:ty, $SRef: ty) => {
+    (struct $Name:ident for $Storage:ident.$ptr: ident -> $Ptr:ty, $Ref:ty, $SRef: ty, $($derives:ident),* $(,)?) => {
         /// An iterator through a dense matrix with arbitrary strides matrix.
-        #[derive(Debug)]
+        #[derive($($derives),*)]
         pub struct $Name<'a, T, R: Dim, C: Dim, S: 'a + $Storage<T, R, C>> {
             ptr: $Ptr,
             inner_ptr: $Ptr,
@@ -39,7 +39,7 @@ macro_rules! iterator {
                 let ptr = storage.$ptr();
 
                 // If we have a size of 0, 'ptr' must be
-                // dangling. Howver, 'inner_offset' might
+                // dangling. However, 'inner_offset' might
                 // not be zero if only one dimension is zero, so
                 // we don't want to call 'offset'.
                 // This pointer will never actually get used
@@ -177,8 +177,8 @@ macro_rules! iterator {
     };
 }
 
-iterator!(struct MatrixIter for RawStorage.ptr -> *const T, &'a T, &'a S);
+iterator!(struct MatrixIter for RawStorage.ptr -> *const T, &'a T, &'a S, Clone, Debug);
-iterator!(struct MatrixIterMut for RawStorageMut.ptr_mut -> *mut T, &'a mut T, &'a mut S);
+iterator!(struct MatrixIterMut for RawStorageMut.ptr_mut -> *mut T, &'a mut T, &'a mut S, Debug);
 
 /*
  *

src/base/matrix.rs

@@ -13,6 +13,8 @@ use serde::{Deserialize, Deserializer, Serialize, Serializer};
 
 #[cfg(feature = "rkyv-serialize-no-std")]
 use super::rkyv_wrappers::CustomPhantom;
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
 #[cfg(feature = "rkyv-serialize-no-std")]
 use rkyv::{with::With, Archive, Archived};
 
@@ -1859,14 +1861,14 @@ where
 
 impl<T, R: Dim, C: Dim, S> Eq for Matrix<T, R, C, S>
 where
-    T: Scalar + Eq,
+    T: Eq,
     S: RawStorage<T, R, C>,
 {
 }
 
 impl<T, R, R2, C, C2, S, S2> PartialEq<Matrix<T, R2, C2, S2>> for Matrix<T, R, C, S>
 where
-    T: Scalar + PartialEq,
+    T: PartialEq,
     C: Dim,
     C2: Dim,
     R: Dim,
@@ -2244,3 +2246,102 @@ where
         Unit::new_unchecked(crate::convert_ref(self.as_ref()))
     }
 }
+
+impl<T, S> Matrix<T, U1, U1, S>
+where
+    S: RawStorage<T, U1, U1>,
+{
+    /// Returns a reference to the single element in this matrix.
+    ///
+    /// As opposed to indexing, using this provides type-safety
+    /// when flattening dimensions.
+    ///
+    /// # Example
+    /// ```
+    /// # use nalgebra::Vector3;
+    /// let v = Vector3::new(0., 0., 1.);
+    /// let inner_product: f32 = *(v.transpose() * v).as_scalar();
+    /// ```
+    ///
+    ///```compile_fail
+    /// # use nalgebra::Vector3;
+    /// let v = Vector3::new(0., 0., 1.);
+    /// let inner_product = (v * v.transpose()).item(); // Typo, does not compile.
+    ///```
+    pub fn as_scalar(&self) -> &T {
+        &self[(0, 0)]
+    }
+    /// Get a mutable reference to the single element in this matrix
+    ///
+    /// As opposed to indexing, using this provides type-safety
+    /// when flattening dimensions.
+    ///
+    /// # Example
+    /// ```
+    /// # use nalgebra::Vector3;
+    /// let v = Vector3::new(0., 0., 1.);
+    /// let mut inner_product = (v.transpose() * v);
+    /// *inner_product.as_scalar_mut() = 3.;
+    /// ```
+    ///
+    ///```compile_fail
+    /// # use nalgebra::Vector3;
+    /// let v = Vector3::new(0., 0., 1.);
+    /// let mut inner_product = (v * v.transpose());
+    /// *inner_product.as_scalar_mut() = 3.;
+    ///```
+    pub fn as_scalar_mut(&mut self) -> &mut T
+    where
+        S: RawStorageMut<T, U1>,
+    {
+        &mut self[(0, 0)]
+    }
+    /// Convert this 1x1 matrix by reference into a scalar.
+    ///
+    /// As opposed to indexing, using this provides type-safety
+    /// when flattening dimensions.
+    ///
+    /// # Example
+    /// ```
+    /// # use nalgebra::Vector3;
+    /// let v = Vector3::new(0., 0., 1.);
+    /// let mut inner_product: f32 = (v.transpose() * v).to_scalar();
+    /// ```
+    ///
+    ///```compile_fail
+    /// # use nalgebra::Vector3;
+    /// let v = Vector3::new(0., 0., 1.);
+    /// let mut inner_product: f32 = (v * v.transpose()).to_scalar();
+    ///```
+    pub fn to_scalar(&self) -> T
+    where
+        T: Clone,
+    {
+        self.as_scalar().clone()
+    }
+}
+
+impl<T> super::alias::Matrix1<T> {
+    /// Convert this 1x1 matrix into a scalar.
+    ///
+    /// As opposed to indexing, using this provides type-safety
+    /// when flattening dimensions.
+    ///
+    /// # Example
+    /// ```
+    /// # use nalgebra::{Vector3, Matrix2, U1};
+    /// let v = Vector3::new(0., 0., 1.);
+    /// let inner_product: f32 = (v.transpose() * v).into_scalar();
+    /// assert_eq!(inner_product, 1.);
+    /// ```
+    ///
+    ///```compile_fail
+    /// # use nalgebra::Vector3;
+    /// let v = Vector3::new(0., 0., 1.);
+    /// let mut inner_product: f32 = (v * v.transpose()).into_scalar();
+    ///```
+    pub fn into_scalar(self) -> T {
+        let [[scalar]] = self.data.0;
+        scalar
+    }
+}

src/base/par_iter.rs

@@ -11,7 +11,7 @@ use crate::{
 use rayon::iter::plumbing::Producer;
 use rayon::{iter::plumbing::bridge, prelude::*};
 
-/// A rayon parallel iterator over the colums of a matrix. It is created
+/// A rayon parallel iterator over the columns of a matrix. It is created
 /// using the [`par_column_iter`] method of [`Matrix`].
 ///
 /// *Only available if compiled with the feature `rayon`.*
@@ -89,7 +89,7 @@ pub struct ParColumnIterMut<
 }
 
 #[cfg_attr(doc_cfg, doc(cfg(feature = "rayon")))]
-/// *only availabe if compiled with the feature `rayon`*
+/// *only available if compiled with the feature `rayon`*
 impl<'a, T, R, Cols, S> ParColumnIterMut<'a, T, R, Cols, S>
 where
     R: Dim,
@@ -161,7 +161,7 @@ where
     S: Sync,
 {
     /// Iterate through the columns of the matrix in parallel using rayon.
-    /// This iterates over *immutable* references ot the columns of the matrix,
+    /// This iterates over *immutable* references to the columns of the matrix,
     /// if *mutable* access to the columns is required, use [`par_column_iter_mut`]
     /// instead.
     ///

src/base/statistics.rs

@@ -335,12 +335,12 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
         if self.is_empty() {
             T::zero()
         } else {
-            let val = self.iter().cloned().fold((T::zero(), T::zero()), |a, b| {
+            let n_elements: T = crate::convert(self.len() as f64);
-                (a.0 + b.clone() * b.clone(), a.1 + b)
+            let mean = self.mean();
-            });
+
-            let denom = T::one() / crate::convert::<_, T>(self.len() as f64);
+            self.iter().cloned().fold(T::zero(), |acc, x| {
-            let vd = val.1 * denom.clone();
+                acc + (x.clone() - mean.clone()) * (x.clone() - mean.clone())
-            val.0 * denom - vd.clone() * vd
+            }) / n_elements
         }
     }
 

src/base/uninit.rs

@@ -34,7 +34,7 @@ pub unsafe trait InitStatus<T>: Copy {
 /// A type implementing `InitStatus` indicating that the value is completely initialized.
 pub struct Init;
 #[derive(Copy, Clone, Debug, PartialEq, Eq)]
-/// A type implementing `InitStatus` indicating that the value is completely unitialized.
+/// A type implementing `InitStatus` indicating that the value is completely uninitialized.
 pub struct Uninit;
 
 unsafe impl<T> InitStatus<T> for Init {

src/base/unit.rs

@@ -9,6 +9,9 @@ use crate::base::DefaultAllocator;
 use crate::storage::RawStorage;
 use crate::{Dim, Matrix, OMatrix, RealField, Scalar, SimdComplexField, SimdRealField};
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
+
 /// A wrapper that ensures the underlying algebraic entity has a unit norm.
 ///
 /// **It is likely that the only piece of documentation that you need in this page are:**

src/base/vec_storage.rs

@@ -148,7 +148,7 @@ impl<T, R: Dim, C: Dim> VecStorage<T, R, C> {
         };
 
         // Avoid double-free by forgetting `self` because its data buffer has
-        // been transfered to `new_data`.
+        // been transferred to `new_data`.
         std::mem::forget(self);
         new_data
     }

src/geometry/dual_quaternion.rs

@@ -1,6 +1,9 @@
 // The macros break if the references are taken out, for some reason.
 #![allow(clippy::op_ref)]
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
+
 use crate::{
     Isometry3, Matrix4, Normed, OVector, Point3, Quaternion, Scalar, SimdRealField, Translation3,
     Unit, UnitQuaternion, Vector3, Zero, U8,

src/geometry/isometry.rs

@@ -14,6 +14,9 @@ use crate::base::storage::Owned;
 use crate::base::{Const, DefaultAllocator, OMatrix, SVector, Scalar, Unit};
 use crate::geometry::{AbstractRotation, Point, Translation};
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
+
 /// A direct isometry, i.e., a rotation followed by a translation (aka. a rigid-body motion).
 ///
 /// This is also known as an element of a Special Euclidean (SE) group.

src/geometry/isometry_interpolation.rs

@@ -42,7 +42,7 @@ impl<T: SimdRealField> Isometry3<T> {
     /// Attempts to interpolate between two isometries using a linear interpolation for the translation part,
     /// and a spherical interpolation for the rotation part.
     ///
-    /// Retuns `None` if the angle between both rotations is 180 degrees (in which case the interpolation
+    /// Returns `None` if the angle between both rotations is 180 degrees (in which case the interpolation
     /// is not well-defined).
     ///
     /// # Examples:
@@ -118,7 +118,7 @@ impl<T: SimdRealField> IsometryMatrix3<T> {
     /// Attempts to interpolate between two isometries using a linear interpolation for the translation part,
     /// and a spherical interpolation for the rotation part.
     ///
-    /// Retuns `None` if the angle between both rotations is 180 degrees (in which case the interpolation
+    /// Returns `None` if the angle between both rotations is 180 degrees (in which case the interpolation
     /// is not well-defined).
     ///
     /// # Examples:

src/geometry/orthographic.rs

@@ -17,6 +17,9 @@ use crate::base::{Matrix4, Vector, Vector3};
 
 use crate::geometry::{Point3, Projective3};
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
+
 /// A 3D orthographic projection stored as a homogeneous 4x4 matrix.
 #[repr(C)]
 #[cfg_attr(

src/geometry/perspective.rs

@@ -18,6 +18,9 @@ use crate::base::{Matrix4, Vector, Vector3};
 
 use crate::geometry::{Point3, Projective3};
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
+
 /// A 3D perspective projection stored as a homogeneous 4x4 matrix.
 #[repr(C)]
 #[cfg_attr(

src/geometry/point.rs

@@ -1,9 +1,11 @@
 use approx::{AbsDiffEq, RelativeEq, UlpsEq};
-use num::One;
+use num::{One, Zero};
 use std::cmp::Ordering;
 use std::fmt;
 use std::hash;
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
 #[cfg(feature = "serde-serialize-no-std")]
 use serde::{Deserialize, Deserializer, Serialize, Serializer};
 
@@ -13,6 +15,7 @@ use crate::base::allocator::Allocator;
 use crate::base::dimension::{DimName, DimNameAdd, DimNameSum, U1};
 use crate::base::iter::{MatrixIter, MatrixIterMut};
 use crate::base::{Const, DefaultAllocator, OVector, Scalar};
+use simba::scalar::{ClosedAdd, ClosedMul, ClosedSub};
 use std::mem::MaybeUninit;
 
 /// A point in an euclidean space.
@@ -221,6 +224,31 @@ where
         unsafe { res.assume_init() }
     }
 
+    /// Linear interpolation between two points.
+    ///
+    /// Returns `self * (1.0 - t) + rhs.coords * t`, i.e., the linear blend of the points
+    /// `self` and `rhs` using the scalar value `t`.
+    ///
+    /// The value for a is not restricted to the range `[0, 1]`.
+    ///
+    /// # Examples:
+    ///
+    /// ```
+    /// # use nalgebra::Point3;
+    /// let a = Point3::new(1.0, 2.0, 3.0);
+    /// let b = Point3::new(10.0, 20.0, 30.0);
+    /// assert_eq!(a.lerp(&b, 0.1), Point3::new(1.9, 3.8, 5.7));
+    /// ```
+    #[must_use]
+    pub fn lerp(&self, rhs: &OPoint<T, D>, t: T) -> OPoint<T, D>
+    where
+        T: Scalar + Zero + One + ClosedAdd + ClosedSub + ClosedMul,
+    {
+        OPoint {
+            coords: self.coords.lerp(&rhs.coords, t),
+        }
+    }
+
     /// Creates a new point with the given coordinates.
     #[deprecated(note = "Use Point::from(vector) instead.")]
     #[inline]

src/geometry/quaternion.rs

@@ -19,6 +19,9 @@ use crate::base::{
 
 use crate::geometry::{Point3, Rotation};
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
+
 /// A quaternion. See the type alias `UnitQuaternion = Unit<Quaternion>` for a quaternion
 /// that may be used as a rotation.
 #[repr(C)]
@@ -1577,7 +1580,7 @@ where
     #[inline]
     #[must_use]
     pub fn inverse_transform_point(&self, pt: &Point3<T>) -> Point3<T> {
-        // TODO: would it be useful performancewise not to call inverse explicitly (i-e. implement
+        // TODO: would it be useful performance-wise not to call inverse explicitly (i-e. implement
         // the inverse transformation explicitly here) ?
         self.inverse() * pt
     }

src/geometry/rotation.rs

@@ -17,6 +17,9 @@ use crate::base::dimension::{DimNameAdd, DimNameSum, U1};
 use crate::base::{Const, DefaultAllocator, OMatrix, SMatrix, SVector, Scalar, Unit};
 use crate::geometry::Point;
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
+
 /// A rotation matrix.
 ///
 /// This is also known as an element of a Special Orthogonal (SO) group.

src/geometry/rotation_specialization.rs

@@ -478,9 +478,10 @@ where
         SB: Storage<T, U3>,
         SC: Storage<T, U3>,
     {
+        // Gram–Schmidt process
         let zaxis = dir.normalize();
         let xaxis = up.cross(&zaxis).normalize();
-        let yaxis = zaxis.cross(&xaxis).normalize();
+        let yaxis = zaxis.cross(&xaxis);
 
         Self::from_matrix_unchecked(SMatrix::<T, 3, 3>::new(
             xaxis.x.clone(),
@@ -979,6 +980,176 @@ impl<T: SimdRealField> Rotation3<T> {
             )
         }
     }
+
+    /// Represent this rotation as Euler angles.
+    ///
+    /// Returns the angles produced in the order provided by seq parameter, along with the
+    /// observability flag. The Euler axes passed to seq must form an orthonormal basis. If the
+    /// rotation is gimbal locked, then the observability flag is false.
+    ///
+    /// # Panics
+    ///
+    /// Panics if the Euler axes in `seq` are not orthonormal.
+    ///
+    /// # Example 1:
+    /// ```
+    /// use std::f64::consts::PI;
+    /// use approx::assert_relative_eq;
+    /// use nalgebra::{Matrix3, Rotation3, Unit, Vector3};
+    ///
+    /// // 3-1-2
+    /// let n = [
+    ///     Unit::new_unchecked(Vector3::new(0.0, 0.0, 1.0)),
+    ///     Unit::new_unchecked(Vector3::new(1.0, 0.0, 0.0)),
+    ///     Unit::new_unchecked(Vector3::new(0.0, 1.0, 0.0)),
+    /// ];
+    ///
+    /// let r1 = Rotation3::from_axis_angle(&n[2], 20.0 * PI / 180.0);
+    /// let r2 = Rotation3::from_axis_angle(&n[1], 30.0 * PI / 180.0);
+    /// let r3 = Rotation3::from_axis_angle(&n[0], 45.0 * PI / 180.0);
+    ///
+    /// let d = r3 * r2 * r1;
+    ///
+    /// let (angles, observable) = d.euler_angles_ordered(n, false);
+    /// assert!(observable);
+    /// assert_relative_eq!(angles[0] * 180.0 / PI, 45.0, epsilon = 1e-12);
+    /// assert_relative_eq!(angles[1] * 180.0 / PI, 30.0, epsilon = 1e-12);
+    /// assert_relative_eq!(angles[2] * 180.0 / PI, 20.0, epsilon = 1e-12);
+    /// ```
+    ///
+    /// # Example 2:
+    /// ```
+    /// use std::f64::consts::PI;
+    /// use approx::assert_relative_eq;
+    /// use nalgebra::{Matrix3, Rotation3, Unit, Vector3};
+    ///
+    /// let sqrt_2 = 2.0_f64.sqrt();
+    /// let n = [
+    ///     Unit::new_unchecked(Vector3::new(1.0 / sqrt_2, 1.0 / sqrt_2, 0.0)),
+    ///     Unit::new_unchecked(Vector3::new(1.0 / sqrt_2, -1.0 / sqrt_2, 0.0)),
+    ///     Unit::new_unchecked(Vector3::new(0.0, 0.0, 1.0)),
+    /// ];
+    ///
+    /// let r1 = Rotation3::from_axis_angle(&n[2], 20.0 * PI / 180.0);
+    /// let r2 = Rotation3::from_axis_angle(&n[1], 30.0 * PI / 180.0);
+    /// let r3 = Rotation3::from_axis_angle(&n[0], 45.0 * PI / 180.0);
+    ///
+    /// let d = r3 * r2 * r1;
+    ///
+    /// let (angles, observable) = d.euler_angles_ordered(n, false);
+    /// assert!(observable);
+    /// assert_relative_eq!(angles[0] * 180.0 / PI, 45.0, epsilon = 1e-12);
+    /// assert_relative_eq!(angles[1] * 180.0 / PI, 30.0, epsilon = 1e-12);
+    /// assert_relative_eq!(angles[2] * 180.0 / PI, 20.0, epsilon = 1e-12);
+    /// ```
+    ///
+    /// Algorithm based on:
+    /// Malcolm D. Shuster, F. Landis Markley, “General formula for extraction the Euler
+    /// angles”, Journal of guidance, control, and dynamics, vol. 29.1, pp. 215-221. 2006,
+    /// and modified to be able to produce extrinsic rotations.
+    #[must_use]
+    pub fn euler_angles_ordered(
+        &self,
+        mut seq: [Unit<Vector3<T>>; 3],
+        extrinsic: bool,
+    ) -> ([T; 3], bool)
+    where
+        T: RealField + Copy,
+    {
+        let mut angles = [T::zero(); 3];
+        let eps = T::from_subset(&1e-7);
+        let _2 = T::from_subset(&2.0);
+
+        if extrinsic {
+            seq.reverse();
+        }
+
+        let [n1, n2, n3] = &seq;
+        assert_relative_eq!(n1.dot(n2), T::zero(), epsilon = eps);
+        assert_relative_eq!(n3.dot(n1), T::zero(), epsilon = eps);
+
+        let n1_c_n2 = n1.cross(n2);
+        let s1 = n1_c_n2.dot(n3);
+        let c1 = n1.dot(n3);
+        let lambda = s1.atan2(c1);
+
+        let mut c = Matrix3::zeros();
+        c.column_mut(0).copy_from(n2);
+        c.column_mut(1).copy_from(&n1_c_n2);
+        c.column_mut(2).copy_from(n1);
+        c.transpose_mut();
+
+        let r1l = Matrix3::new(
+            T::one(),
+            T::zero(),
+            T::zero(),
+            T::zero(),
+            c1,
+            s1,
+            T::zero(),
+            -s1,
+            c1,
+        );
+        let o_t = &c * self.matrix() * (c.transpose() * r1l);
+        angles[1] = o_t.m33.acos();
+
+        let safe1 = angles[1].abs() >= eps;
+        let safe2 = (angles[1] - T::pi()).abs() >= eps;
+        let observable = safe1 && safe2;
+        angles[1] += lambda;
+
+        if observable {
+            angles[0] = o_t.m13.atan2(-o_t.m23);
+            angles[2] = o_t.m31.atan2(o_t.m32);
+        } else {
+            // gimbal lock detected
+            if extrinsic {
+                // angle1 is initialized to zero
+                if !safe1 {
+                    angles[2] = (o_t.m12 - o_t.m21).atan2(o_t.m11 + o_t.m22);
+                } else {
+                    angles[2] = -(o_t.m12 + o_t.m21).atan2(o_t.m11 - o_t.m22);
+                };
+            } else {
+                // angle3 is initialized to zero
+                if !safe1 {
+                    angles[0] = (o_t.m12 - o_t.m21).atan2(o_t.m11 + o_t.m22);
+                } else {
+                    angles[0] = (o_t.m12 + o_t.m21).atan2(o_t.m11 - o_t.m22);
+                };
+            };
+        };
+
+        let adjust = if seq[0] == seq[2] {
+            // lambda = 0, so ensure angle2 -> [0, pi]
+            angles[1] < T::zero() || angles[1] > T::pi()
+        } else {
+            // lamda = + or - pi/2, so ensure angle2 -> [-pi/2, pi/2]
+            angles[1] < -T::frac_pi_2() || angles[1] > T::frac_pi_2()
+        };
+
+        // dont adjust gimbal locked rotation
+        if adjust && observable {
+            angles[0] += T::pi();
+            angles[1] = _2 * lambda - angles[1];
+            angles[2] -= T::pi();
+        }
+
+        // ensure all angles are within [-pi, pi]
+        for angle in angles.as_mut_slice().iter_mut() {
+            if *angle < -T::pi() {
+                *angle += T::two_pi();
+            } else if *angle > T::pi() {
+                *angle -= T::two_pi();
+            }
+        }
+
+        if extrinsic {
+            angles.reverse();
+        }
+
+        (angles, observable)
+    }
 }
 
 #[cfg(feature = "rand-no-std")]

src/geometry/scale.rs

@@ -15,6 +15,9 @@ use crate::ClosedMul;
 
 use crate::geometry::Point;
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
+
 /// A scale which supports non-uniform scaling.
 #[repr(C)]
 #[cfg_attr(

src/geometry/similarity.rs

@@ -15,6 +15,9 @@ use crate::base::storage::Owned;
 use crate::base::{Const, DefaultAllocator, OMatrix, SVector, Scalar};
 use crate::geometry::{AbstractRotation, Isometry, Point, Translation};
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
+
 /// A similarity, i.e., an uniform scaling, followed by a rotation, followed by a translation.
 #[repr(C)]
 #[derive(Debug, Copy, Clone)]

src/geometry/transform.rs

@@ -122,7 +122,7 @@ macro_rules! category_mul_impl(
     )*}
 );
 
-// We require stability uppon multiplication.
+// We require stability upon multiplication.
 impl<T: TCategory> TCategoryMul<T> for T {
     type Representative = T;
 }

src/geometry/translation.rs

@@ -15,6 +15,9 @@ use crate::base::{Const, DefaultAllocator, OMatrix, SVector, Scalar};
 
 use crate::geometry::Point;
 
+#[cfg(feature = "rkyv-serialize")]
+use rkyv::bytecheck;
+
 /// A translation.
 #[repr(C)]
 #[cfg_attr(

src/geometry/unit_complex.rs

@@ -347,7 +347,7 @@ where
     #[inline]
     #[must_use]
     pub fn inverse_transform_point(&self, pt: &Point2<T>) -> Point2<T> {
-        // TODO: would it be useful performancewise not to call inverse explicitly (i-e. implement
+        // TODO: would it be useful performance-wise not to call inverse explicitly (i-e. implement
         // the inverse transformation explicitly here) ?
         self.inverse() * pt
     }

src/linalg/convolution.rs

@@ -47,11 +47,11 @@ impl<T: RealField, D1: Dim, S1: Storage<T, D1>> Vector<T, D1, S1> {
             let u_f = cmp::min(i, vec - 1);
 
             if u_i == u_f {
-                conv[i] += self[u_i].clone() * kernel[(i - u_i)].clone();
+                conv[i] += self[u_i].clone() * kernel[i - u_i].clone();
             } else {
                 for u in u_i..(u_f + 1) {
                     if i - u < ker {
-                        conv[i] += self[u].clone() * kernel[(i - u)].clone();
+                        conv[i] += self[u].clone() * kernel[i - u].clone();
                     }
                 }
             }

src/linalg/svd.rs

@@ -724,7 +724,7 @@ where
 
     /// Sort the estimated components of the SVD by its singular values in descending order.
     /// Such an ordering is often implicitly required when the decompositions are used for estimation or fitting purposes.
-    /// Using this function is only required if `new_unordered` or `try_new_unorderd` were used and the specific sorting is required afterward.
+    /// Using this function is only required if `new_unordered` or `try_new_unordered` were used and the specific sorting is required afterward.
     pub fn sort_by_singular_values(&mut self) {
         const VALUE_PROCESSED: usize = usize::MAX;
 

src/sparse/cs_matrix.rs

@@ -498,7 +498,7 @@ where
         }
     }
 
-    // Remove dupliate entries on a sorted CsMatrix.
+    // Remove duplicate entries on a sorted CsMatrix.
     pub(crate) fn dedup(&mut self)
     where
         T: Zero + ClosedAdd,

src/third_party/glam/mod.rs

@@ -16,3 +16,9 @@ mod v020;
 mod v021;
 #[cfg(feature = "glam022")]
 mod v022;
+#[cfg(feature = "glam023")]
+mod v023;
+#[cfg(feature = "glam024")]
+mod v024;
+#[cfg(feature = "glam025")]
+mod v025;

src/third_party/glam/v023/mod.rs

@@ -0,0 +1,18 @@
+#[path = "../common/glam_isometry.rs"]
+mod glam_isometry;
+#[path = "../common/glam_matrix.rs"]
+mod glam_matrix;
+#[path = "../common/glam_point.rs"]
+mod glam_point;
+#[path = "../common/glam_quaternion.rs"]
+mod glam_quaternion;
+#[path = "../common/glam_rotation.rs"]
+mod glam_rotation;
+#[path = "../common/glam_similarity.rs"]
+mod glam_similarity;
+#[path = "../common/glam_translation.rs"]
+mod glam_translation;
+#[path = "../common/glam_unit_complex.rs"]
+mod glam_unit_complex;
+
+pub(self) use glam023 as glam;

src/third_party/glam/v024/mod.rs

@@ -0,0 +1,18 @@
+#[path = "../common/glam_isometry.rs"]
+mod glam_isometry;
+#[path = "../common/glam_matrix.rs"]
+mod glam_matrix;
+#[path = "../common/glam_point.rs"]
+mod glam_point;
+#[path = "../common/glam_quaternion.rs"]
+mod glam_quaternion;
+#[path = "../common/glam_rotation.rs"]
+mod glam_rotation;
+#[path = "../common/glam_similarity.rs"]
+mod glam_similarity;
+#[path = "../common/glam_translation.rs"]
+mod glam_translation;
+#[path = "../common/glam_unit_complex.rs"]
+mod glam_unit_complex;
+
+pub(self) use glam024 as glam;

src/third_party/glam/v025/mod.rs

@@ -0,0 +1,18 @@
+#[path = "../common/glam_isometry.rs"]
+mod glam_isometry;
+#[path = "../common/glam_matrix.rs"]
+mod glam_matrix;
+#[path = "../common/glam_point.rs"]
+mod glam_point;
+#[path = "../common/glam_quaternion.rs"]
+mod glam_quaternion;
+#[path = "../common/glam_rotation.rs"]
+mod glam_rotation;
+#[path = "../common/glam_similarity.rs"]
+mod glam_similarity;
+#[path = "../common/glam_translation.rs"]
+mod glam_translation;
+#[path = "../common/glam_unit_complex.rs"]
+mod glam_unit_complex;
+
+pub(self) use glam025 as glam;

tests/core/mod.rs

@@ -11,6 +11,7 @@ mod reshape;
 #[cfg(feature = "rkyv-serialize-no-std")]
 mod rkyv;
 mod serde;
+mod variance;
 
 #[cfg(feature = "compare")]
 mod matrixcompare;

tests/core/variance.rs

@@ -0,0 +1,18 @@
+use nalgebra::DVector;
+
+#[test]
+fn test_variance_catastrophic_cancellation() {
+    let long_repeating_vector = DVector::repeat(10_000, 100000000.0);
+    assert_eq!(long_repeating_vector.variance(), 0.0);
+
+    let short_vec = DVector::from_vec(vec![1., 2., 3.]);
+    assert_eq!(short_vec.variance(), 2.0 / 3.0);
+
+    let short_vec =
+        DVector::<f64>::from_vec(vec![1.0e8 + 4.0, 1.0e8 + 7.0, 1.0e8 + 13.0, 1.0e8 + 16.0]);
+    assert_eq!(short_vec.variance(), 22.5);
+
+    let short_vec =
+        DVector::<f64>::from_vec(vec![1.0e9 + 4.0, 1.0e9 + 7.0, 1.0e9 + 13.0, 1.0e9 + 16.0]);
+    assert_eq!(short_vec.variance(), 22.5);
+}

tests/linalg/eigen.rs

@@ -123,7 +123,7 @@ fn symmetric_eigen_singular_24x24() {
 //
 //    /*
 //     * NOTE: for the following tests, we use only upper-triangular matrices.
-//     * Thes ensures the schur decomposition will work, and allows use to test the eigenvector
+//     * This ensures the schur decomposition will work, and allows use to test the eigenvector
 //     * computation.
 //     */
 //    fn eigen(n: usize) -> bool {
@@ -134,11 +134,11 @@ fn symmetric_eigen_singular_24x24() {
 //        verify_eigenvectors(m, eig)
 //    }
 //
-//    fn eigen_with_adjascent_duplicate_diagonals(n: usize) -> bool {
+//    fn eigen_with_adjacent_duplicate_diagonals(n: usize) -> bool {
 //        let n = cmp::max(1, cmp::min(n, 10));
 //        let mut m = DMatrix::<f64>::new_random(n, n).upper_triangle();
 //
-//        // Suplicate some adjascent diagonal elements.
+//        // Suplicate some adjacent diagonal elements.
 //        for i in 0 .. n / 2 {
 //            m[(i * 2 + 1, i * 2 + 1)] = m[(i * 2, i * 2)];
 //        }
@@ -147,7 +147,7 @@ fn symmetric_eigen_singular_24x24() {
 //        verify_eigenvectors(m, eig)
 //    }
 //
-//    fn eigen_with_nonadjascent_duplicate_diagonals(n: usize) -> bool {
+//    fn eigen_with_nonadjacent_duplicate_diagonals(n: usize) -> bool {
 //        let n = cmp::max(3, cmp::min(n, 10));
 //        let mut m = DMatrix::<f64>::new_random(n, n).upper_triangle();
 //