/// <summary>
/// Creates a new special case of Stable Bloom Filter which is a traditional
/// Bloom filter with m bits and an optimal number of hash functions for the
/// target false-positive rate. Unlike the stable variant, data is not evicted
/// and a cell contains a maximum of 1 hash value.
/// </summary>
/// <param name="m">Number of cells to decrement</param>
/// <param name="fpRate">Desired false-positive rate</param>
/// <returns></returns>
public static StableBloomFilter NewUnstableBloomFilter(uint m, double fpRate)
{
var cells = new Buckets(m, 1);
var k = Utils.OptimalK(fpRate);
return(new StableBloomFilter
{
Hash = Defaults.GetDefaultHashAlgorithm(),
M = m,
k = k,
p = 0,
Max = cells.MaxBucketValue(),
cells = cells,
IndexBuffer = new uint[k]
});
}
/// <summary>
/// Creates a new Stable Bloom Filter with m cells and d bits allocated per cell
/// optimized for the target false-positive rate. Use NewDefaultStableFilter if
/// you don't want to calculate d.
/// </summary>
/// <param name="m">Number of cells to decrement</param>
/// <param name="d">Bits per cell</param>
/// <param name="fpRate">Desired false-positive rate</param>
public StableBloomFilter(uint m, byte d, double fpRate)
{
var k = Utils.OptimalK(fpRate) / 2;
if (k > m)
{
k = m;
}
else if (k <= 0)
{
k = 1;
}
var cells = new Buckets(m, d);
this.Hash = Defaults.GetDefaultHashAlgorithm();
this.M = m;
this.k = k;
this.p = OptimalStableP(m, k, d, fpRate);
this.Max = cells.MaxBucketValue();
this.cells = cells;
this.IndexBuffer = new uint[k];
}