fmt
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61abece7af
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@ -8,8 +8,8 @@ use crate::{
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iter::{ColumnIter, ColumnIterMut},
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iter::{ColumnIter, ColumnIterMut},
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Dim, Matrix, MatrixSlice, MatrixSliceMut, RawStorage, RawStorageMut, Scalar, U1,
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Dim, Matrix, MatrixSlice, MatrixSliceMut, RawStorage, RawStorageMut, Scalar, U1,
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};
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};
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use rayon::{iter::plumbing::bridge, prelude::*};
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use rayon::iter::plumbing::Producer;
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use rayon::iter::plumbing::Producer;
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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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/// 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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/// using the [`par_column_iter`] method of [`Matrix`].
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@ -224,14 +224,15 @@ where
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/// a private helper newtype that wraps the `ColumnIter` and implements
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/// a private helper newtype that wraps the `ColumnIter` and implements
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/// the rayon `Producer` trait. It's just here so we don't have to make the
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/// the rayon `Producer` trait. It's just here so we don't have to make the
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/// rayon trait part of the public interface of the `ColumnIter`
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/// rayon trait part of the public interface of the `ColumnIter`
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struct ColumnProducer<'a,T,R:Dim,C:Dim,S:RawStorage<T,R,C>>(ColumnIter<'a,T,R,C,S>);
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struct ColumnProducer<'a, T, R: Dim, C: Dim, S: RawStorage<T, R, C>>(ColumnIter<'a, T, R, C, S>);
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#[cfg_attr(doc_cfg, doc(cfg(feature = "par-iter")))]
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#[cfg_attr(doc_cfg, doc(cfg(feature = "par-iter")))]
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/// *only available if compiled with the feature `par-iter`*
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/// *only available if compiled with the feature `par-iter`*
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impl<'a, T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>> Producer for ColumnProducer<'a, T, R, Cols, S>
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impl<'a, T, R: Dim, Cols: Dim, S: RawStorage<T, R, Cols>> Producer
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for ColumnProducer<'a, T, R, Cols, S>
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where
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where
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T: Send + Sync + Scalar,
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T: Send + Sync + Scalar,
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S: Sync,
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S: Sync,
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{
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{
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type Item = MatrixSlice<'a, T, R, U1, S::RStride, S::CStride>;
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type Item = MatrixSlice<'a, T, R, U1, S::RStride, S::CStride>;
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type IntoIter = ColumnIter<'a, T, R, Cols, S>;
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type IntoIter = ColumnIter<'a, T, R, Cols, S>;
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@ -260,13 +261,15 @@ S: Sync,
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/// See `ColumnProducer`. A private wrapper newtype that keeps the Producer
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/// See `ColumnProducer`. A private wrapper newtype that keeps the Producer
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/// implementation private
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/// implementation private
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struct ColumnProducerMut<'a, T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>>(ColumnIterMut<'a,T,R,C,S>);
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struct ColumnProducerMut<'a, T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>>(
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ColumnIterMut<'a, T, R, C, S>,
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);
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impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> Producer
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impl<'a, T, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> Producer
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for ColumnProducerMut<'a, T, R, C, S>
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for ColumnProducerMut<'a, T, R, C, S>
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where
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where
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T: Send + Sync + Scalar,
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T: Send + Sync + Scalar,
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S: Send + Sync,
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S: Send + Sync,
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{
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{
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type Item = MatrixSliceMut<'a, T, R, U1, S::RStride, S::CStride>;
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type Item = MatrixSliceMut<'a, T, R, U1, S::RStride, S::CStride>;
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type IntoIter = ColumnIterMut<'a, T, R, C, S>;
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type IntoIter = ColumnIterMut<'a, T, R, C, S>;
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@ -294,10 +297,9 @@ S: Send + Sync,
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}
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}
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}
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}
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/// this implementation is safe because we are enforcing exclusive access
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/// this implementation is safe because we are enforcing exclusive access
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/// to the columns through the active range of the iterator
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/// to the columns through the active range of the iterator
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unsafe impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> Send
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unsafe impl<'a, T: Scalar, R: Dim, C: Dim, S: 'a + RawStorageMut<T, R, C>> Send
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for ColumnIterMut<'a, T, R, C, S>
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for ColumnIterMut<'a, T, R, C, S>
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{
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{
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}
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}
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@ -1240,12 +1240,14 @@ fn parallel_column_iteration() {
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// repeat this test using mutable iterators
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// repeat this test using mutable iterators
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let mut dmat = dmat;
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let mut dmat = dmat;
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dmat.par_column_iter_mut().enumerate().for_each(|(idx, col)| {
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dmat.par_column_iter_mut()
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assert_eq!(col, cloned.column(idx));
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.enumerate()
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});
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.for_each(|(idx, col)| {
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assert_eq!(col, cloned.column(idx));
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});
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let par_mut_result: f64 = dmat.par_column_iter_mut().map(|col| col.norm()).sum();
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let par_mut_result: f64 = dmat.par_column_iter_mut().map(|col| col.norm()).sum();
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assert_eq!(par_mut_result,ser_result);
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assert_eq!(par_mut_result, ser_result);
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}
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}
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#[test]
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#[test]
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