215 lines
6.5 KiB
Rust
215 lines
6.5 KiB
Rust
//! Parallel iterators for matrices compatible with rayon.
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//only enables the `doc_cfg` feature when
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// the `docsrs` configuration attribute is defined
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#![cfg_attr(docsrs, feature(doc_cfg))]
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use crate::{
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iter::{ColumnIter, ColumnIterMut},
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Dim, Matrix, MatrixSlice, MatrixSliceMut, RawStorage, RawStorageMut, Scalar, U1,
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};
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use rayon::{iter::plumbing::bridge, prelude::*};
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/// A rayon parallel iterator over the colums of a matrix. It is created
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/// using the [`par_column_iter`] method of [`Matrix`].
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///
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/// [`par_column_iter`]: crate::Matrix::par_column_iter
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/// [`Matrix`]: crate::Matrix
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#[cfg_attr(doc_cfg, doc(cfg(feature = "par-iter")))]
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pub struct ParColumnIter<'a, T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>> {
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mat: &'a Matrix<T, R, Cols, S>,
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}
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impl<'a, T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>> ParColumnIter<'a, T, R, Cols, S> {
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/// create a new parallel iterator for the given matrix
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fn new(matrix: &'a Matrix<T, R, Cols, S>) -> Self {
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Self { mat: matrix }
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}
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}
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#[cfg_attr(doc_cfg, doc(cfg(feature = "par-iter")))]
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impl<'a, T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>> ParallelIterator
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for ParColumnIter<'a, T, R, Cols, S>
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where
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T: Sync + Send + Scalar,
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S: Sync,
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{
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type Item = MatrixSlice<'a, T, R, U1, S::RStride, S::CStride>;
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fn drive_unindexed<Consumer>(self, consumer: Consumer) -> Consumer::Result
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where
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Consumer: rayon::iter::plumbing::UnindexedConsumer<Self::Item>,
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{
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bridge(self, consumer)
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}
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fn opt_len(&self) -> Option<usize> {
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Some(self.mat.ncols())
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}
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}
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#[cfg_attr(doc_cfg, doc(cfg(feature = "par-iter")))]
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impl<'a, T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>> IndexedParallelIterator
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for ParColumnIter<'a, T, R, Cols, S>
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where
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T: Send + Sync + Scalar,
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S: Sync,
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{
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fn len(&self) -> usize {
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self.mat.ncols()
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}
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fn drive<C: rayon::iter::plumbing::Consumer<Self::Item>>(self, consumer: C) -> C::Result {
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bridge(self, consumer)
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}
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fn with_producer<CB: rayon::iter::plumbing::ProducerCallback<Self::Item>>(
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self,
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callback: CB,
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) -> CB::Output {
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let producer = ColumnIter::new(self.mat);
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callback.callback(producer)
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}
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}
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#[cfg_attr(doc_cfg, doc(cfg(feature = "par-iter")))]
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/// A rayon parallel iterator through the mutable columns of a matrix
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pub struct ParColumnIterMut<
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'a,
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T,
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R: Dim,
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Cols: Dim,
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S: RawStorage<T, R, Cols> + RawStorageMut<T, R, Cols>,
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> {
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mat: &'a mut Matrix<T, R, Cols, S>,
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}
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#[cfg_attr(doc_cfg, doc(cfg(feature = "par-iter")))]
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impl<'a, T, R, Cols, S> ParColumnIterMut<'a, T, R, Cols, S>
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where
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R: Dim,
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Cols: Dim,
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S: RawStorage<T, R, Cols> + RawStorageMut<T, R, Cols>,
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{
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/// create a new parallel iterator for the given matrix
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fn new(mat: &'a mut Matrix<T, R, Cols, S>) -> Self {
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Self { mat }
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}
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}
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#[cfg_attr(doc_cfg, doc(cfg(feature = "par-iter")))]
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impl<'a, T, R, Cols, S> ParallelIterator for ParColumnIterMut<'a, T, R, Cols, S>
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where
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R: Dim,
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Cols: Dim,
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S: RawStorage<T, R, Cols> + RawStorageMut<T, R, Cols>,
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T: Send + Sync + Scalar,
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S: Send + Sync,
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{
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type Item = MatrixSliceMut<'a, T, R, U1, S::RStride, S::CStride>;
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fn drive_unindexed<C>(self, consumer: C) -> C::Result
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where
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C: rayon::iter::plumbing::UnindexedConsumer<Self::Item>,
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{
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bridge(self, consumer)
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}
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fn opt_len(&self) -> Option<usize> {
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Some(self.mat.ncols())
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}
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}
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#[cfg_attr(doc_cfg, doc(cfg(feature = "par-iter")))]
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impl<'a, T, R, Cols, S> IndexedParallelIterator for ParColumnIterMut<'a, T, R, Cols, S>
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where
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R: Dim,
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Cols: Dim,
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S: RawStorage<T, R, Cols> + RawStorageMut<T, R, Cols>,
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T: Send + Sync + Scalar,
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S: Send + Sync,
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{
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fn drive<C: rayon::iter::plumbing::Consumer<Self::Item>>(self, consumer: C) -> C::Result {
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bridge(self, consumer)
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}
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fn len(&self) -> usize {
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self.mat.ncols()
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}
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fn with_producer<CB: rayon::iter::plumbing::ProducerCallback<Self::Item>>(
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self,
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callback: CB,
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) -> CB::Output {
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let producer = ColumnIterMut::new(self.mat);
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callback.callback(producer)
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}
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}
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#[cfg_attr(doc_cfg, doc(cfg(feature = "par-iter")))]
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/// # Parallel iterators using `rayon`
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/// *Only availabe if compiled with the feature `par-iter`*
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impl<T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>>
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Matrix<T, R, Cols, S>
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where
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T: Send + Sync + Scalar,
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S: Sync,
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{
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/// Iterate through the columns of the matrix in parallel using rayon.
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/// This iterates over *immutable* references ot the columns of the matrix,
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/// if *mutable* access to the columns is required, use [`par_column_iter_mut`]
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/// instead.
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///
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/// # Example
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/// Using parallel column iterators to calculate the sum of the maximum
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/// elements in each column:
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/// ```
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/// use nalgebra::{dmatrix,DMatrix};
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/// use rayon::prelude::*;
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///
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/// let matrix : DMatrix<f64> =
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/// nalgebra::dmatrix![1.,0.,5.;
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/// 2.,4.,1.;
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/// 3.,2.,2.;];
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/// let sum_of_max :f64 =
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/// matrix
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/// .par_column_iter()
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/// .map(|col|col.max())
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/// .sum();
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///
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/// assert_eq!(sum_of_max,3.+4.+5.);
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///
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/// ```
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///
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/// [`par_column_iter_mut`]: crate::Matrix::par_column_iter_mut
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pub fn par_column_iter(&self) -> ParColumnIter<'_, T, R, Cols, S> {
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ParColumnIter::new(self)
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}
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/// Mutably iterate through the columns of this matrix in parallel using rayon.
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/// Allows mutable access to the columns in parallel using mutable references.
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/// If mutable access to the columns is not required rather use [`par_column_iter`]
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/// instead.
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///
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/// # Example
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/// Normalize each column of a matrix with respect to its own maximum value.
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///
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/// ```
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/// use nalgebra::{dmatrix,DMatrix};
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/// use rayon::prelude::*;
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///
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/// let mut matrix : DMatrix<f64> =
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/// dmatrix![2.,4.,6.;
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/// 1.,2.,3.];
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/// matrix.par_column_iter_mut().for_each(|mut col| col /= col.max());
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///
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/// assert_eq!(matrix,
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/// dmatrix![1. ,1. , 1.;
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/// 0.5,0.5,0.5]);
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/// ```
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///
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/// [`par_column_iter`]: crate::Matrix::par_column_iter
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pub fn par_column_iter_mut(&mut self) -> ParColumnIterMut<'_, T, R, Cols, S>
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where S: RawStorageMut<T, R, Cols>{
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ParColumnIterMut::new(self)
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}
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}
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