ndarray-slice 0.1.1

Fast and robust slice-based algorithms (e.g., sorting, selection, search) for non-contiguous (sub)views into n-dimensional arrays.
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ndarray-slice

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Fast and robust slice-based algorithms (e.g., sorting, selection, search) for non-contiguous (sub)views into n-dimensional arrays. Reimplements algorithms in slice for ndarray with arbitrary memory layout (e.g., non-contiguous).

Example

use ndarray_slice::{Slice1Ext, ndarray::arr2};

// 2-dimensional array of 4 rows and 5 columns.
let mut v = arr2(&[[-5, 4, 1, -3,  2],   // row 0, axis 0
                   [ 8, 3, 2,  4,  8],   // row 1, axis 0
                   [38, 9, 3,  0,  3],   // row 2, axis 0
                   [ 4, 9, 0,  8, -1]]); // row 3, axis 0
//                    \     \       \
//                  column 0 \    column 4         axis 1
//                         column 2                axis 1

// Mutable subview into the last column.
let mut column = v.column_mut(4);

// Due to row-major memory layout, columns are non-contiguous and hence cannot be sorted by
// viewing them as mutable slices.
assert_eq!(column.as_slice_mut(), None);

// Instead, sorting is specifically implemented for non-contiguous mutable (sub)views.
column.sort();

assert!(v == arr2(&[[-5, 4, 1, -3, -1],
                    [ 8, 3, 2,  4,  2],
                    [38, 9, 3,  0,  3],
                    [ 4, 9, 0,  8,  8]]));
//                                   \
//                                 column 4 sorted, others untouched

Current Implementation

Complexities where n is the length of the (sub)view.

Algorithm Stable Allocation Recursive Average Worse-Case
Sorting yes yes no O(n) O(n log(n))
Sorting no no yes O(n) O(n log(n))
Selection no no no O(n) O(n log(n))

Roadmap

  • Lower worst-case complexity from O(n log(n)) to O(n) for selection algorithms.
  • Add SliceExt trait for n-dimensional array or (sub)view with methods expecting Axis as their first argument. Comparing methods will always be suffixed with _by or _by_key defining how to compare multi-dimensional elements (e.g., columns) along the provided axis of interest (e.g., rows).

See the release history to keep track of the development.

Features

  • alloc: Enables stable sort. Enabled by std.
  • std: Enables selection of many indices. Enabled by default.

License

Copyright © 2023 Rouven Spreckels rs@qu1x.dev

This project is licensed under either of

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this project by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.