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.

extern crate sparsevec;
use sparsevec::SparseVec;

fn main() {
    use sparsevec::SparseVec;
    let v:Vec<usize> = 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);
}

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