forked from M-Labs/nalgebra
Bring apply permutation function back to serial.rs
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@ -14,7 +14,6 @@ use crate::coo::CooMatrix;
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use crate::cs;
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use crate::csc::CscMatrix;
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use crate::csr::CsrMatrix;
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use crate::utils::apply_permutation;
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/// Converts a dense matrix to [`CooMatrix`].
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pub fn convert_dense_coo<T, R, C, S>(dense: &Matrix<T, R, C, S>) -> CooMatrix<T>
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@ -391,6 +390,15 @@ fn sort_lane<T: Clone>(
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apply_permutation(values_result, values, permutation);
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}
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// TODO: Move this into `utils` or something?
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fn apply_permutation<T: Clone>(out_slice: &mut [T], in_slice: &[T], permutation: &[usize]) {
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assert_eq!(out_slice.len(), in_slice.len());
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assert_eq!(out_slice.len(), permutation.len());
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for (out_element, old_pos) in out_slice.iter_mut().zip(permutation) {
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*out_element = in_slice[*old_pos].clone();
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}
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}
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/// Given *sorted* indices and corresponding scalar values, combines duplicates with the given
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/// associative combiner and calls the provided produce methods with combined indices and values.
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fn combine_duplicates<T: Clone>(
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@ -227,7 +227,8 @@ impl<T> CsrMatrix<T> {
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}
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// permute indices
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let sorted_col_indices: Vec<usize> = Vec::from_iter((p.iter().map(|i| &col_indices[*i])).cloned());
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let sorted_col_indices: Vec<usize> =
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Vec::from_iter((p.iter().map(|i| &col_indices[*i])).cloned());
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// permute values
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let sorted_values: Vec<T> = Vec::from_iter((p.iter().map(|i| &values[*i])).cloned());
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@ -151,7 +151,6 @@ pub mod ops;
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pub mod pattern;
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pub(crate) mod cs;
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pub(crate) mod utils;
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#[cfg(feature = "proptest-support")]
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pub mod proptest;
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@ -1,11 +0,0 @@
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//! Helper functions for sparse matrix computations
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/// permutes entries of in_slice according to permutation slice and puts them to out_slice
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#[inline]
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pub fn apply_permutation<T: Clone>(out_slice: &mut [T], in_slice: &[T], permutation: &[usize]) {
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assert_eq!(out_slice.len(), in_slice.len());
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assert_eq!(out_slice.len(), permutation.len());
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for (out_element, old_pos) in out_slice.iter_mut().zip(permutation) {
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*out_element = in_slice[*old_pos].clone();
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}
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}
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