[![Build Status](https://api.travis-ci.org/softdevteam/sparsevec.svg?branch=master)](https://travis-ci.org/softdevteam/sparsevec) [![Latest version](https://img.shields.io/crates/v/sparsevec.svg)](https://crates.io/crates/sparsevec) [![Documentation](https://docs.rs/sparsevec/badge.svg)](https://docs.rs/sparsevec) # Sparse Vector (SparseVec) A SparseVec efficiently encodes a two-dimensional matrix of integers. The input matrix must be encoded as a one-dimensional vector of integers with a row-length. Given an empty value, the SparseVec uses row displacement as described in [1] for the compression and encodes the result further using a PackedVec. [1] Tarjan, Robert Endre, and Andrew Chi-Chih Yao. "Storing a sparse table." Communications of the ACM 22.11 (1979): 606-611. # Usage ```rust extern crate sparsevec; use sparsevec::SparseVec; fn main() { use sparsevec::SparseVec; let v:Vec = vec![1,0,0,0, 0,0,7,8, 9,0,0,3]; let sv = SparseVec::from(&v, 0, 4); assert_eq!(sv.get(0,0).unwrap(), 1); assert_eq!(sv.get(1,2).unwrap(), 7); assert_eq!(sv.get(2,3).unwrap(), 3); } ``` # How it works The following describes the general idea of row displacement for sparse vectors, excluding some additional optimisations from the implementation. Let's take as an example the two-dimensional vector ``` 1 0 0 2 0 0 3 0 0 0 0 4 ``` represented as a one dimensional vector `v = [1,0,0,2,0,0,3,0,0,0,0,4]` with row-length 3. Storing this vector in memory is wasteful as the majority of its elements is 0. We can compress this vector using row displacement, which merges all rows into a vector such that no two non-zero entries are mapped to the same position. For the above example, this would result in the compressed vector `c = [1,2,3,0,4]`: ``` 1 0 0 2 0 0 3 0 0 0 0 4 --------- 1 2 3 0 4 ``` To retrieve values from the compressed vector, we need a displacement vector, which describes how much each row was shifted during the compression. For the above example, the displacement vector would be `d = [0, 1, 2, 2]`. In order to retrieve the value at position (2, 0), we can calculate its compressed position with `pos = d[row] + col`: ``` pos = d[2] + 0 // =2 value = c[pos] // =3 ```