Crate bitm

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bitm is the Rust library by Piotr Beling for bit and bitmap (bit vector) manipulation.

§Example

use bitm::{BitAccess, BitVec, Rank, ArrayWithRank101111};

let mut b = Box::<[u64]>::with_zeroed_bits(2048);    // b can store 2048 bits
assert_eq!(b.get_bit(100), false);  // b is zeroed so bit at index 100 is not set  
b.set_bit(100);                     // set the bit
assert_eq!(b.get_bit(100), true);   // now it is set
assert_eq!(b.get_bits(99, 5), 0b00010); // 5 bits, beginning from index 99, should be 00010

let (r, ones) = ArrayWithRank101111::build(b);
assert_eq!(ones, 1);        // one bit is set in b
assert_eq!(r.rank(100), 0); // no ones in the first 100 bits of b
assert_eq!(r.rank(101), 1); // 1 one in the first 101 bits of b
assert_eq!(r.rank(999), 1); // 1 one in the first 999 bits of b

§Benchmarks

The performance of some of the structures included in bitm can be tested with the cseq_benchmark crate. Its documentation contains benchmark results.

Structs§

  • AdaptiveCombinedSamplingDensity
    Specifies adaptive sampling of select values by CombinedSampling.
  • BinaryRankSearch
    A select strategy for RankSelect101111 that does not introduce any overhead (on space or construction speed) and is based on a binary search over ranks.
  • BitBIterator
    Iterator over indices of bits set to 1 (if B is true) or 0 (if B is false) in slice of u64.
  • BitIterator
    Iterator over bits in slice of u64. It yields true for bit 1 and false for 0.
  • CombinedSampling
    Fast select strategy for RankSelect101111 with about 0.39% space overhead.
  • ConstCombinedSamplingDensity
    Specifies a constant sampling of select values by CombinedSampling, given as the base 2 logarithm (which can be calculated by optimal_combined_sampling function). The actual sampling is 2 times denser, but every second sample sometimes cannot be recorded accurately.
  • RankSelect101111
    Returns number of bits set (to one) in content whose length does not exceeds 8. Returns number of bits set (to one) in content whose length does not exceeds 8. The structure that holds bit vector content and ranks structure that takes no more than 3.125% extra space. It can return the number of ones (or zeros) in first index bits of the content (see rank and rank0 method) in O(1) time. In addition, it supports select queries utilizing binary search over ranks (see BinaryRankSearch) or (optionally, at the cost of extra space overhead; about 0.39% with default settings) combined sampling (which is usually faster; see CombinedSampling).
  • RankSimple
    The structure that holds array of bits content and ranks structure that takes no more than 6.25% extra space. It can returns the number of ones in first index bits of the content (see rank method) in O(1) time. Only content with less than 232 bit ones is supported. Any type that implements the Deref trait with Target = [u64] can be used as a bit vector.

Traits§

  • BitAccess
    The trait that is implemented for the array of u64 and extends it with methods for accessing and modifying single bits or arbitrary fragments consisted of few (up to 63) bits.
  • BitVec
    The trait that is implemented for Box<[u64]> and extends it with bit-oriented constructors.
  • Rank
    Trait for rank queries on bit vector. Rank query returns the number of ones (or zeros) in requested number of the first bits.
  • Select
    Trait implemented by the types that support select (one) queries, i.e. can (quickly) find the position of the n-th one in the bitmap.
  • Select0
    Trait implemented by the types that support select zero queries, i.e. can (quickly) find the position of the n-th zero in the bitmap.
  • Select0ForRank101111
    Trait implemented by strategies for select zeros operations for ArrayWithRank101111.
  • SelectForRank101111
    Trait implemented by strategies for select (ones) operations for ArrayWithRank101111.

Functions§

  • bits_to_store
    Calculates the minimal number of bits needed to store values from 0 to given max_value.
  • ceiling_div
    Returns ceil of n/d.
  • n_lowest_bits
    Returns the largest how_many-bit number, i.e. 0..01..1 mask with how_many ones. how_many must be in range [0, 63].
  • n_lowest_bits_0_64
    Returns the largest how_many-bit number, i.e. 0..01..1 mask with how_many ones. how_many must be in range [0, 64].
  • n_lowest_bits_1_64
    Returns the largest how_many-bit number, i.e. 0..01..1 mask with how_many ones. how_many must be in range [1, 64].
  • optimal_combined_sampling
    Calculates such a sampling density of select values that provides an approximately constant space overhead (independent of set/unset bits ratio in the vector) of CombinedSampling.
  • select64
    Returns the position of the rank-th (counting from 0) one in the bit representation of n, i.e. the index of the one with the given rank.

Type Aliases§