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Merge pull request #1165 from geo-ant/feature/parallel-column-iterators

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Parallel Column Iterators with Rayon
This commit is contained in:
Sébastien Crozet 2023-01-14 16:17:44 +01:00 committed by GitHub
commit 731fd0ead1
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7 changed files with 545 additions and 24 deletions
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2
.github/workflows/nalgebra-ci-build.yml vendored
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@ -61,7 +61,7 @@ jobs:
steps:
- uses: actions/checkout@v2
- name: test
run: cargo test --features arbitrary,rand,serde-serialize,sparse,debug,io,compare,libm,proptest-support,slow-tests,rkyv-safe-deser;
run: cargo test --features arbitrary,rand,serde-serialize,sparse,debug,io,compare,libm,proptest-support,slow-tests,rkyv-safe-deser,rayon;
test-nalgebra-glm:
runs-on: ubuntu-latest
steps:

5
Cargo.toml
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@ -34,6 +34,7 @@ libm-force = [ "simba/libm_force" ]
macros = [ "nalgebra-macros" ]
cuda = [ "cust_core", "simba/cuda" ]
# Conversion
convert-mint = [ "mint" ]
convert-bytemuck = [ "bytemuck" ]
@ -101,7 +102,7 @@ glam020 = { package = "glam", version = "0.20", optional = true }
glam021 = { package = "glam", version = "0.21", optional = true }
glam022 = { package = "glam", version = "0.22", optional = true }
cust_core = { version = "0.1", optional = true }
rayon = { version = "1.6", optional = true }
[dev-dependencies]
serde_json = "1.0"
@ -137,3 +138,5 @@ lto = true
[package.metadata.docs.rs]
# Enable all the features when building the docs on docs.rs
all-features = true
# define the configuration attribute `docsrs`
rustdoc-args = ["--cfg", "docsrs"]

123
src/base/iter.rs
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@ -1,5 +1,11 @@
//! Matrix iterators.
// only enables the `doc_cfg` feature when
// the `docsrs` configuration attribute is defined
#![cfg_attr(docsrs, feature(doc_cfg))]
use core::fmt::Debug;
use core::ops::Range;
use std::iter::FusedIterator;
use std::marker::PhantomData;
use std::mem;
@ -288,7 +294,6 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> ExactSizeIte
}
/*
*
* Column iterators.
*
*/
@ -296,12 +301,33 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> ExactSizeIte
/// An iterator through the columns of a matrix.
pub struct ColumnIter<'a, T, R: Dim, C: Dim, S: RawStorage<T, R, C>> {
mat: &'a Matrix<T, R, C, S>,
curr: usize,
range: Range<usize>,
}
impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> ColumnIter<'a, T, R, C, S> {
/// a new column iterator covering all columns of the matrix
pub(crate) fn new(mat: &'a Matrix<T, R, C, S>) -> Self {
ColumnIter { mat, curr: 0 }
ColumnIter {
mat,
range: 0..mat.ncols(),
}
}
pub(crate) fn split_at(self, index: usize) -> (Self, Self) {
// SAFETY: this makes sur the generated ranges are valid.
let split_pos = (self.range.start + index).min(self.range.end);
let left_iter = ColumnIter {
mat: self.mat,
range: self.range.start..split_pos,
};
let right_iter = ColumnIter {
mat: self.mat,
range: split_pos..self.range.end,
};
(left_iter, right_iter)
}
}
@ -310,9 +336,10 @@ impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> Iterator for ColumnIter
#[inline]
fn next(&mut self) -> Option<Self::Item> {
if self.curr < self.mat.ncols() {
let res = self.mat.column(self.curr);
self.curr += 1;
debug_assert!(self.range.start <= self.range.end);
if self.range.start < self.range.end {
let res = self.mat.column(self.range.start);
self.range.start += 1;
Some(res)
} else {
None
@ -321,15 +348,29 @@ impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> Iterator for ColumnIter
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
(
self.mat.ncols() - self.curr,
Some(self.mat.ncols() - self.curr),
)
let hint = self.range.len();
(hint, Some(hint))
}
#[inline]
fn count(self) -> usize {
self.mat.ncols() - self.curr
self.range.len()
}
}
impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> DoubleEndedIterator
for ColumnIter<'a, T, R, C, S>
{
fn next_back(&mut self) -> Option<Self::Item> {
debug_assert!(self.range.start <= self.range.end);
if !self.range.is_empty() {
self.range.end -= 1;
debug_assert!(self.range.end < self.mat.ncols());
debug_assert!(self.range.end >= self.range.start);
Some(self.mat.column(self.range.end))
} else {
None
}
}
}
@ -338,7 +379,7 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> ExactSizeIterat
{
#[inline]
fn len(&self) -> usize {
self.mat.ncols() - self.curr
self.range.end - self.range.start
}
}
@ -346,19 +387,39 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorage<T, R, C>> ExactSizeIterat
#[derive(Debug)]
pub struct ColumnIterMut<'a, T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> {
mat: *mut Matrix<T, R, C, S>,
curr: usize,
range: Range<usize>,
phantom: PhantomData<&'a mut Matrix<T, R, C, S>>,
}
impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> ColumnIterMut<'a, T, R, C, S> {
pub(crate) fn new(mat: &'a mut Matrix<T, R, C, S>) -> Self {
let range = 0..mat.ncols();
ColumnIterMut {
mat,
curr: 0,
phantom: PhantomData,
range,
phantom: Default::default(),
}
}
pub(crate) fn split_at(self, index: usize) -> (Self, Self) {
// SAFETY: this makes sur the generated ranges are valid.
let split_pos = (self.range.start + index).min(self.range.end);
let left_iter = ColumnIterMut {
mat: self.mat,
range: self.range.start..split_pos,
phantom: Default::default(),
};
let right_iter = ColumnIterMut {
mat: self.mat,
range: split_pos..self.range.end,
phantom: Default::default(),
};
(left_iter, right_iter)
}
fn ncols(&self) -> usize {
unsafe { (*self.mat).ncols() }
}
@ -370,10 +431,11 @@ impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> Iterator
type Item = MatrixViewMut<'a, T, R, U1, S::RStride, S::CStride>;
#[inline]
fn next(&mut self) -> Option<Self::Item> {
if self.curr < self.ncols() {
let res = unsafe { (*self.mat).column_mut(self.curr) };
self.curr += 1;
fn next(&'_ mut self) -> Option<Self::Item> {
debug_assert!(self.range.start <= self.range.end);
if self.range.start < self.range.end {
let res = unsafe { (*self.mat).column_mut(self.range.start) };
self.range.start += 1;
Some(res)
} else {
None
@ -382,12 +444,13 @@ impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> Iterator
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
(self.ncols() - self.curr, Some(self.ncols() - self.curr))
let hint = self.range.len();
(hint, Some(hint))
}
#[inline]
fn count(self) -> usize {
self.ncols() - self.curr
self.range.len()
}
}
@ -396,6 +459,22 @@ impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> ExactSizeIte
{
#[inline]
fn len(&self) -> usize {
self.ncols() - self.curr
self.range.len()
}
}
impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> DoubleEndedIterator
for ColumnIterMut<'a, T, R, C, S>
{
fn next_back(&mut self) -> Option<Self::Item> {
debug_assert!(self.range.start <= self.range.end);
if !self.range.is_empty() {
self.range.end -= 1;
debug_assert!(self.range.end < self.ncols());
debug_assert!(self.range.end >= self.range.start);
Some(unsafe { (*self.mat).column_mut(self.range.end) })
} else {
None
}
}
}

1
src/base/matrix.rs
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@ -101,6 +101,7 @@ pub type MatrixCross<T, R1, C1, R2, C2> =
///
/// #### Iteration, map, and fold
/// - [Iteration on components, rows, and columns <span style="float:right;">`iter`, `column_iter`…</span>](#iteration-on-components-rows-and-columns)
/// - [Parallel iterators using rayon <span style="float:right;">`par_column_iter`, `par_column_iter_mut`…</span>](#parallel-iterators-using-rayon)
/// - [Elementwise mapping and folding <span style="float:right;">`map`, `fold`, `zip_map`…</span>](#elementwise-mapping-and-folding)
/// - [Folding or columns and rows <span style="float:right;">`compress_rows`, `compress_columns`…</span>](#folding-on-columns-and-rows)
///

3
src/base/mod.rs
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@ -42,6 +42,9 @@ mod min_max;
/// Mechanisms for working with values that may not be initialized.
pub mod uninit;
#[cfg(feature = "rayon")]
pub mod par_iter;
#[cfg(feature = "rkyv-serialize-no-std")]
mod rkyv_wrappers;

285
src/base/par_iter.rs Normal file
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@ -0,0 +1,285 @@
//! Parallel iterators for matrices compatible with rayon.
// only enables the `doc_cfg` feature when
// the `docsrs` configuration attribute is defined
#![cfg_attr(docsrs, feature(doc_cfg))]
use crate::{
iter::{ColumnIter, ColumnIterMut},
Dim, Matrix, MatrixView, MatrixViewMut, RawStorage, RawStorageMut, Scalar, U1,
};
use rayon::iter::plumbing::Producer;
use rayon::{iter::plumbing::bridge, prelude::*};
/// A rayon parallel iterator over the colums of a matrix. It is created
/// using the [`par_column_iter`] method of [`Matrix`].
///
/// *Only available if compiled with the feature `rayon`.*
/// [`par_column_iter`]: crate::Matrix::par_column_iter
/// [`Matrix`]: crate::Matrix
#[cfg_attr(doc_cfg, doc(cfg(feature = "rayon")))]
pub struct ParColumnIter<'a, T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>> {
mat: &'a Matrix<T, R, Cols, S>,
}
impl<'a, T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>> ParColumnIter<'a, T, R, Cols, S> {
/// Create a new parallel iterator for the given matrix.
fn new(matrix: &'a Matrix<T, R, Cols, S>) -> Self {
Self { mat: matrix }
}
}
#[cfg_attr(doc_cfg, doc(cfg(feature = "rayon")))]
impl<'a, T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>> ParallelIterator
for ParColumnIter<'a, T, R, Cols, S>
where
T: Sync + Send + Scalar,
S: Sync,
{
type Item = MatrixView<'a, T, R, U1, S::RStride, S::CStride>;
fn drive_unindexed<Consumer>(self, consumer: Consumer) -> Consumer::Result
where
Consumer: rayon::iter::plumbing::UnindexedConsumer<Self::Item>,
{
bridge(self, consumer)
}
fn opt_len(&self) -> Option<usize> {
Some(self.mat.ncols())
}
}
#[cfg_attr(doc_cfg, doc(cfg(feature = "rayon")))]
/// *Only available if compiled with the feature `rayon`.*
impl<'a, T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>> IndexedParallelIterator
for ParColumnIter<'a, T, R, Cols, S>
where
T: Send + Sync + Scalar,
S: Sync,
{
fn len(&self) -> usize {
self.mat.ncols()
}
fn drive<C: rayon::iter::plumbing::Consumer<Self::Item>>(self, consumer: C) -> C::Result {
bridge(self, consumer)
}
fn with_producer<CB: rayon::iter::plumbing::ProducerCallback<Self::Item>>(
self,
callback: CB,
) -> CB::Output {
let producer = ColumnProducer(ColumnIter::new(self.mat));
callback.callback(producer)
}
}
#[cfg_attr(doc_cfg, doc(cfg(feature = "rayon")))]
/// A rayon parallel iterator through the mutable columns of a matrix.
/// *Only available if compiled with the feature `rayon`.*
pub struct ParColumnIterMut<
'a,
T,
R: Dim,
Cols: Dim,
S: RawStorage<T, R, Cols> + RawStorageMut<T, R, Cols>,
> {
mat: &'a mut Matrix<T, R, Cols, S>,
}
#[cfg_attr(doc_cfg, doc(cfg(feature = "rayon")))]
/// *only availabe if compiled with the feature `rayon`*
impl<'a, T, R, Cols, S> ParColumnIterMut<'a, T, R, Cols, S>
where
R: Dim,
Cols: Dim,
S: RawStorage<T, R, Cols> + RawStorageMut<T, R, Cols>,
{
/// create a new parallel iterator for the given matrix.
fn new(mat: &'a mut Matrix<T, R, Cols, S>) -> Self {
Self { mat }
}
}
#[cfg_attr(doc_cfg, doc(cfg(feature = "rayon")))]
/// *Only available if compiled with the feature `rayon`*
impl<'a, T, R, Cols, S> ParallelIterator for ParColumnIterMut<'a, T, R, Cols, S>
where
R: Dim,
Cols: Dim,
S: RawStorage<T, R, Cols> + RawStorageMut<T, R, Cols>,
T: Send + Sync + Scalar,
S: Send + Sync,
{
type Item = MatrixViewMut<'a, T, R, U1, S::RStride, S::CStride>;
fn drive_unindexed<C>(self, consumer: C) -> C::Result
where
C: rayon::iter::plumbing::UnindexedConsumer<Self::Item>,
{
bridge(self, consumer)
}
fn opt_len(&self) -> Option<usize> {
Some(self.mat.ncols())
}
}
#[cfg_attr(doc_cfg, doc(cfg(feature = "rayon")))]
/// *Only available if compiled with the feature `rayon`*
impl<'a, T, R, Cols, S> IndexedParallelIterator for ParColumnIterMut<'a, T, R, Cols, S>
where
R: Dim,
Cols: Dim,
S: RawStorage<T, R, Cols> + RawStorageMut<T, R, Cols>,
T: Send + Sync + Scalar,
S: Send + Sync,
{
fn drive<C: rayon::iter::plumbing::Consumer<Self::Item>>(self, consumer: C) -> C::Result {
bridge(self, consumer)
}
fn len(&self) -> usize {
self.mat.ncols()
}
fn with_producer<CB: rayon::iter::plumbing::ProducerCallback<Self::Item>>(
self,
callback: CB,
) -> CB::Output {
let producer = ColumnProducerMut(ColumnIterMut::new(self.mat));
callback.callback(producer)
}
}
#[cfg_attr(doc_cfg, doc(cfg(feature = "rayon")))]
/// # Parallel iterators using `rayon`
/// *Only available if compiled with the feature `rayon`*
impl<T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>> Matrix<T, R, Cols, S>
where
T: Send + Sync + Scalar,
S: Sync,
{
/// Iterate through the columns of the matrix in parallel using rayon.
/// This iterates over *immutable* references ot the columns of the matrix,
/// if *mutable* access to the columns is required, use [`par_column_iter_mut`]
/// instead.
///
/// # Example
/// Using parallel column iterators to calculate the sum of the maximum
/// elements in each column:
/// ```
/// use nalgebra::{dmatrix, DMatrix};
/// use rayon::prelude::*;
///
/// let matrix : DMatrix<f64> = dmatrix![1.0, 0.0, 5.0;
/// 2.0, 4.0, 1.0;
/// 3.0, 2.0, 2.0;
/// ];
/// let sum_of_max :f64 = matrix
/// .par_column_iter()
/// .map(|col| col.max())
/// .sum();
///
/// assert_eq!(sum_of_max,3.0 + 4.0 + 5.0);
///
/// ```
///
/// [`par_column_iter_mut`]: crate::Matrix::par_column_iter_mut
pub fn par_column_iter(&self) -> ParColumnIter<'_, T, R, Cols, S> {
ParColumnIter::new(self)
}
/// Mutably iterate through the columns of this matrix in parallel using rayon.
/// Allows mutable access to the columns in parallel using mutable references.
/// If mutable access to the columns is not required rather use [`par_column_iter`]
/// instead.
///
/// # Example
/// Normalize each column of a matrix with respect to its own maximum value.
///
/// ```
/// use nalgebra::{dmatrix, DMatrix};
/// use rayon::prelude::*;
///
/// let mut matrix : DMatrix<f64> = dmatrix![
/// 2.0, 4.0, 6.0;
/// 1.0, 2.0, 3.0;
/// ];
/// matrix.par_column_iter_mut().for_each(|mut col| col /= col.max());
///
/// assert_eq!(matrix, dmatrix![1.0, 1.0, 1.0; 0.5, 0.5, 0.5]);
/// ```
///
/// [`par_column_iter`]: crate::Matrix::par_column_iter
pub fn par_column_iter_mut(&mut self) -> ParColumnIterMut<'_, T, R, Cols, S>
where
S: RawStorageMut<T, R, Cols>,
{
ParColumnIterMut::new(self)
}
}
/// A private helper newtype that wraps the `ColumnIter` and implements
/// the rayon `Producer` trait. It's just here so we don't have to make the
/// rayon trait part of the public interface of the `ColumnIter`.
struct ColumnProducer<'a, T, R: Dim, C: Dim, S: RawStorage<T, R, C>>(ColumnIter<'a, T, R, C, S>);
#[cfg_attr(doc_cfg, doc(cfg(feature = "rayon")))]
/// *only available if compiled with the feature `rayon`*
impl<'a, T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>> Producer
for ColumnProducer<'a, T, R, Cols, S>
where
T: Send + Sync + Scalar,
S: Sync,
{
type Item = MatrixView<'a, T, R, U1, S::RStride, S::CStride>;
type IntoIter = ColumnIter<'a, T, R, Cols, S>;
#[inline]
fn into_iter(self) -> Self::IntoIter {
self.0
}
#[inline]
fn split_at(self, index: usize) -> (Self, Self) {
// The index is relative to the size of this current iterator.
// It will always start at zero so it serves as an offset.
let (left_iter, right_iter) = self.0.split_at(index);
(Self(left_iter), Self(right_iter))
}
}
/// See `ColumnProducer`. A private wrapper newtype that keeps the Producer
/// implementation private
struct ColumnProducerMut<'a, T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>>(
ColumnIterMut<'a, T, R, C, S>,
);
impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> Producer
for ColumnProducerMut<'a, T, R, C, S>
where
T: Send + Sync + Scalar,
S: Send + Sync,
{
type Item = MatrixViewMut<'a, T, R, U1, S::RStride, S::CStride>;
type IntoIter = ColumnIterMut<'a, T, R, C, S>;
fn into_iter(self) -> Self::IntoIter {
self.0
}
fn split_at(self, index: usize) -> (Self, Self) {
// The index is relative to the size of this current iterator
// it will always start at zero so it serves as an offset.
let (left_iter, right_iter) = self.0.split_at(index);
(Self(left_iter), Self(right_iter))
}
}
/// this implementation is safe because we are enforcing exclusive access
/// to the columns through the active range of the iterator
unsafe impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> Send
for ColumnIterMut<'a, T, R, C, S>
{
}

150
tests/core/matrix.rs
View File

@ -1136,3 +1136,153 @@ fn omatrix_to_string() {
(svec.to_string(), smatr.to_string())
);
}
#[test]
fn column_iteration() {
// dynamic matrix
let dmat = nalgebra::dmatrix![
13,14,15;
23,24,25;
33,34,35;
];
let mut col_iter = dmat.column_iter();
assert_eq!(col_iter.next(), Some(dmat.column(0)));
assert_eq!(col_iter.next(), Some(dmat.column(1)));
assert_eq!(col_iter.next(), Some(dmat.column(2)));
assert_eq!(col_iter.next(), None);
// statically sized matrix
let smat: nalgebra::SMatrix<f64, 2, 2> = nalgebra::matrix![1.0, 2.0; 3.0, 4.0];
let mut col_iter = smat.column_iter();
assert_eq!(col_iter.next(), Some(smat.column(0)));
assert_eq!(col_iter.next(), Some(smat.column(1)));
assert_eq!(col_iter.next(), None);
}
#[test]
fn column_iteration_mut() {
let mut dmat = nalgebra::dmatrix![
13,14,15;
23,24,25;
33,34,35;
];
let mut cloned = dmat.clone();
let mut col_iter = dmat.column_iter_mut();
assert_eq!(col_iter.next(), Some(cloned.column_mut(0)));
assert_eq!(col_iter.next(), Some(cloned.column_mut(1)));
assert_eq!(col_iter.next(), Some(cloned.column_mut(2)));
assert_eq!(col_iter.next(), None);
// statically sized matrix
let mut smat: nalgebra::SMatrix<f64, 2, 2> = nalgebra::matrix![1.0, 2.0; 3.0, 4.0];
let mut cloned = smat.clone();
let mut col_iter = smat.column_iter_mut();
assert_eq!(col_iter.next(), Some(cloned.column_mut(0)));
assert_eq!(col_iter.next(), Some(cloned.column_mut(1)));
assert_eq!(col_iter.next(), None);
}
#[test]
fn column_iteration_double_ended() {
let dmat = nalgebra::dmatrix![
13,14,15,16,17;
23,24,25,26,27;
33,34,35,36,37;
];
let mut col_iter = dmat.column_iter();
assert_eq!(col_iter.next(), Some(dmat.column(0)));
assert_eq!(col_iter.next(), Some(dmat.column(1)));
assert_eq!(col_iter.next_back(), Some(dmat.column(4)));
assert_eq!(col_iter.next_back(), Some(dmat.column(3)));
assert_eq!(col_iter.next(), Some(dmat.column(2)));
assert_eq!(col_iter.next_back(), None);
assert_eq!(col_iter.next(), None);
}
#[test]
fn column_iterator_double_ended_mut() {
let mut dmat = nalgebra::dmatrix![
13,14,15,16,17;
23,24,25,26,27;
33,34,35,36,37;
];
let mut cloned = dmat.clone();
let mut col_iter_mut = dmat.column_iter_mut();
assert_eq!(col_iter_mut.next(), Some(cloned.column_mut(0)));
assert_eq!(col_iter_mut.next(), Some(cloned.column_mut(1)));
assert_eq!(col_iter_mut.next_back(), Some(cloned.column_mut(4)));
assert_eq!(col_iter_mut.next_back(), Some(cloned.column_mut(3)));
assert_eq!(col_iter_mut.next(), Some(cloned.column_mut(2)));
assert_eq!(col_iter_mut.next_back(), None);
assert_eq!(col_iter_mut.next(), None);
}
#[test]
#[cfg(feature = "rayon")]
fn parallel_column_iteration() {
use nalgebra::dmatrix;
use rayon::prelude::*;
let dmat: DMatrix<f64> = dmatrix![
13.,14.;
23.,24.;
33.,34.;
];
let cloned = dmat.clone();
// test that correct columns are iterated over
dmat.par_column_iter().enumerate().for_each(|(idx, col)| {
assert_eq!(col, cloned.column(idx));
});
// test that a more complex expression produces the same
// result as the serial equivalent
let par_result: f64 = dmat.par_column_iter().map(|col| col.norm()).sum();
let ser_result: f64 = dmat.column_iter().map(|col| col.norm()).sum();
assert_eq!(par_result, ser_result);
// repeat this test using mutable iterators
let mut dmat = dmat;
dmat.par_column_iter_mut()
.enumerate()
.for_each(|(idx, col)| {
assert_eq!(col, cloned.column(idx));
});
let par_mut_result: f64 = dmat.par_column_iter_mut().map(|col| col.norm()).sum();
assert_eq!(par_mut_result, ser_result);
}
#[test]
#[cfg(feature = "rayon")]
fn column_iteration_mut_double_ended() {
let dmat = nalgebra::dmatrix![
13,14,15,16,17;
23,24,25,26,27;
33,34,35,36,37;
];
let cloned = dmat.clone();
let mut col_iter = dmat.column_iter();
assert_eq!(col_iter.next(), Some(cloned.column(0)));
assert_eq!(col_iter.next(), Some(cloned.column(1)));
assert_eq!(col_iter.next_back(), Some(cloned.column(4)));
assert_eq!(col_iter.next_back(), Some(cloned.column(3)));
assert_eq!(col_iter.next(), Some(cloned.column(2)));
assert_eq!(col_iter.next_back(), None);
assert_eq!(col_iter.next(), None);
}
#[test]
#[cfg(feature = "rayon")]
fn parallel_column_iteration_mut() {
use rayon::prelude::*;
let mut first = DMatrix::<f32>::zeros(400, 300);
let mut second = DMatrix::<f32>::zeros(400, 300);
first
.column_iter_mut()
.enumerate()
.for_each(|(idx, mut col)| col[idx] = 1.);
second
.par_column_iter_mut()
.enumerate()
.for_each(|(idx, mut col)| col[idx] = 1.);
assert_eq!(first, second);
assert_eq!(second, DMatrix::identity(400, 300));
}