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// Copyright 2014-2016 Johannes Köster, Taylor Cramer.
// Licensed under the MIT license (http://opensource.org/licenses/MIT)
// This file may not be copied, modified, or distributed
// except according to those terms.
//! The Burrows-Wheeler-Transform and related data structures.
//! The implementation is based on the lecture notes
//! "Algorithmen auf Sequenzen", Kopczynski, Marschall, Martin and Rahmann, 2008 - 2015.
use std::iter::repeat;
use alphabets::Alphabet;
use bytecount;
use data_structures::suffix_array::RawSuffixArray;
use utils::prescan;
pub type BWT = Vec<u8>;
pub type BWTSlice = [u8];
pub type Less = Vec<usize>;
pub type BWTFind = Vec<usize>;
/// Calculate Burrows-Wheeler-Transform of the given text of length n.
/// Complexity: O(n).
///
/// # Arguments
///
/// * `text` - the text ended by sentinel symbol (being lexicographically smallest)
/// * `pos` - the suffix array for the text
///
/// # Example
///
/// ```
/// use bio::data_structures::suffix_array::suffix_array;
/// use bio::data_structures::bwt::bwt;
/// let text = b"GCCTTAACATTATTACGCCTA$";
/// let pos = suffix_array(text);
/// let bwt = bwt(text, &pos);
/// assert_eq!(bwt, b"ATTATTCAGGACCC$CTTTCAA");
/// ```
pub fn bwt(text: &[u8], pos: &RawSuffixArray) -> BWT {
assert_eq!(text.len(), pos.len());
let n = text.len();
let mut bwt: BWT = repeat(0).take(n).collect();
for r in 0..n {
let p = pos[r];
bwt[r] = if p > 0 { text[p - 1] } else { text[n - 1] };
}
bwt
}
/// Calculate the inverse of a BWT of length n, which is the original text.
/// Complexity: O(n).
///
/// This only works if the last sentinel in the original text is unique
/// and lexicographically the smallest.
///
/// # Arguments
///
/// * `bwt` - the BWT
pub fn invert_bwt(bwt: &BWTSlice) -> Vec<u8> {
let alphabet = Alphabet::new(bwt);
let n = bwt.len();
let bwtfind = bwtfind(bwt, &alphabet);
let mut inverse = Vec::with_capacity(n);
let mut r = bwtfind[0];
for _ in 0..n {
r = bwtfind[r];
inverse.push(bwt[r]);
}
inverse
}
/// An occurrence array implementation.
#[derive(Serialize, Deserialize)]
pub struct Occ {
occ: Vec<Vec<usize>>,
k: u32,
}
impl Occ {
/// Calculate occ array with sampling from BWT of length n.
/// Time complexity: O(n).
/// Space complexity: O(n / k * A) with A being the alphabet size.
/// Alphabet size is determined on the fly from the BWT.
/// For large texts, it is therefore advisable to transform
/// the text before calculating the BWT (see alphabets::rank_transform).
///
/// # Arguments
///
/// * `bwt` - the BWT
/// * `k` - the sampling rate: every k-th entry will be stored
pub fn new(bwt: &BWTSlice, k: u32, alphabet: &Alphabet) -> Self {
let n = bwt.len();
let m = alphabet
.max_symbol()
.expect("Expecting non-empty alphabet.") as usize
+ 1;
let mut occ = Vec::with_capacity(n / k as usize);
let mut curr_occ: Vec<usize> = repeat(0).take(m).collect();
for (i, &c) in bwt.iter().enumerate() {
curr_occ[c as usize] += 1;
if i % k as usize == 0 {
occ.push(curr_occ.clone());
}
}
Occ { occ, k }
}
/// Get occurrence count of symbol a in BWT[..r+1].
/// Complexity: O(k).
pub fn get(&self, bwt: &BWTSlice, r: usize, a: u8) -> usize {
// NOTE:
//
// Retrieving byte match counts in this function is critical to the performance of FM Index.
//
// The below manual count code is roughly equivalent to:
// ```
// let count = bwt[(i * self.k) + 1..r + 1].iter().filter(|&&c| c == a).count();
// self.occ[i][a as usize] + count
// ```
//
// But there are a couple of reasons to do this manually:
// 1) As of 2016, versions of rustc/LLVM vectorize this manual loop more reliably
// than the iterator adapter version.
// 2) Manually accumulating the byte match count in a single chunk can allows
// us to use a `u32` for that count, which has faster arithmetic on common arches.
// This does necessitate storing `k` as a u32.
//
// See the conversation in these issues for some of the history here:
//
// https://github.com/rust-bio/rust-bio/pull/74
// https://github.com/rust-bio/rust-bio/pull/76
// self.k is our sampling rate, so find our last sampled checkpoint
let i = r / self.k as usize;
let checkpoint = self.occ[i][a as usize];
// find the portion of the BWT past the checkpoint which we need to count
let start = (i * self.k as usize) + 1;
let end = r + 1;
// count all the matching bytes b/t the closest checkpoint and our desired lookup
let count = bytecount::count(&bwt[start..end], a);
// return the sampled checkpoint for this character + the manual count we just did
checkpoint + (count as usize)
}
}
/// Calculate the less array for a given BWT. Complexity O(n).
pub fn less(bwt: &BWTSlice, alphabet: &Alphabet) -> Less {
let m = alphabet
.max_symbol()
.expect("Expecting non-empty alphabet.") as usize
+ 2;
let mut less: Less = repeat(0).take(m).collect();
for &c in bwt.iter() {
less[c as usize] += 1;
}
// calculate +-prescan
prescan(&mut less[..], 0, |a, b| a + b);
less
}
/// Calculate the bwtfind array needed for inverting the BWT. Complexity O(n).
pub fn bwtfind(bwt: &BWTSlice, alphabet: &Alphabet) -> BWTFind {
let n = bwt.len();
let mut less = less(bwt, alphabet);
let mut bwtfind: BWTFind = repeat(0).take(n).collect();
for (r, &c) in bwt.iter().enumerate() {
bwtfind[less[c as usize]] = r;
less[c as usize] += 1;
}
bwtfind
}
#[cfg(test)]
mod tests {
use super::{bwt, bwtfind, invert_bwt, Occ};
use alphabets::Alphabet;
use data_structures::suffix_array::suffix_array;
#[test]
fn test_bwtfind() {
let text = b"cabca$";
let alphabet = Alphabet::new(b"abc$");
let pos = suffix_array(text);
let bwt = bwt(text, &pos);
let bwtfind = bwtfind(&bwt, &alphabet);
assert_eq!(bwtfind, vec![5, 0, 3, 4, 1, 2]);
}
#[test]
fn test_invert_bwt() {
let text = b"cabca$";
let pos = suffix_array(text);
let bwt = bwt(text, &pos);
let inverse = invert_bwt(&bwt);
assert_eq!(inverse, text);
}
#[test]
fn test_occ() {
let bwt = vec![1u8, 3u8, 3u8, 1u8, 2u8, 0u8];
let alphabet = Alphabet::new(&[0u8, 1u8, 2u8, 3u8]);
let occ = Occ::new(&bwt, 3, &alphabet);
assert_eq!(occ.occ, [[0, 1, 0, 0], [0, 2, 0, 2]]);
assert_eq!(occ.get(&bwt, 4, 2u8), 1);
assert_eq!(occ.get(&bwt, 4, 3u8), 2);
}
}