A lightweight rust library for BitVector Rank&Select operations, coupled with a generic Sparse Array implementation. BVRS
Description
This library was written as part of CMSC858D - Algorithms, Data Structures and Inference for High-throughput Genomics Class Homework.
The official version of the library is hosted on github at this repository, while crates.io version is hosted at this page.
Installation
You can download the source code from github and build the project using cargo build
or add it to your project as a dependency from crates.io.
Usage
Below are some ways to instantiate and use given constructs.
BitVector
use bvrs::BitVec;
let size = 16;
let b1 = BitVec::new_with_random(size);
let b2 = BitVec::new_with_zeros(size);
let b3 = BitVec::new_with_vec(vec![0b10010001, 0b10000001]);
let b4 = BitVec::new(size); // uses new with zeros
let b5 = b1 + b2;
let b6 = b1.incr();
let b7 = b1.concat(&b2);
let b8 = b1.extract(0, 7);
let bit = b1.get(2);
Rank Support
use bvrs::BitVec;
use bvrs::RankSupport;
let size = 16;
let b1 = BitVec::new_with_random(size);
let r = RankSupport::new(&b);
let index = 3;
let res = r.rank1(index);
let res_prime = RankSupport::dummy_rank(&b, index);
r.save("example.txt");
let r2 = RankSupport::load("example.txt".to_owned()).unwrap();
Select Support
use bvrs::BitVec;
use bvrs::RankSupport;
use bvrs::SelectSupport;
let b = BitVec::new_with_random(size);
let r = RankSupport::new(&b);
let s = SelectSupport::new(Cow::Borrowed(&r));
let select = s.select1(3);
Sparse Array
use bvrs::SparseArray;
let size = 32;
let mut sa: SparseArray<String> = SparseArray::new(size);
sa.append("alp".to_owned(), 3);
let res = sa.get_at_index(3).unwrap();
assert_eq!(*res, "alp".to_owned());