-- Hoogle documentation, generated by Haddock
-- See Hoogle, http://www.haskell.org/hoogle/


-- | Pure and impure Bloom Filter implementations.
--   
--   Pure and impure Bloom Filter implementations.
@package bloomfilter
@version 2.0.1.0


-- | Fast hashing of Haskell values. The hash functions used are Bob
--   Jenkins's public domain functions, which combine high performance with
--   excellent mixing properties. For more details, see
--   <a>http://burtleburtle.net/bob/hash/</a>.
--   
--   In addition to the usual "one input, one output" hash functions, this
--   module provides multi-output hash functions, suitable for use in
--   applications that need multiple hashes, such as Bloom filtering.
module Data.BloomFilter.Hash
class Hashable a where hashIO64 v salt = do { let s1 = fromIntegral (salt `shiftR` 32) .&. maxBound s2 = fromIntegral salt; h1 <- hashIO32 v s1; h2 <- hashIO32 v s2; return $ (fromIntegral h1 `shiftL` 32) .|. fromIntegral h2 }

-- | Compute a 32-bit hash of a value. The salt value perturbs the result.
hashIO32 :: Hashable a => a -> Word32 -> IO Word32

-- | Compute a 64-bit hash of a value. The first salt value perturbs the
--   first element of the result, and the second salt perturbs the second.
hashIO64 :: Hashable a => a -> Word64 -> IO Word64

-- | Compute a 32-bit hash.
hash32 :: Hashable a => a -> Word32
hash64 :: Hashable a => a -> Word64

-- | Compute a salted 32-bit hash.
hashSalt32 :: Hashable a => Word32 -> a -> Word32

-- | Compute a salted 64-bit hash.
hashSalt64 :: Hashable a => Word64 -> a -> Word64

-- | Compute a list of 32-bit hashes. The value to hash may be inspected as
--   many times as there are hashes requested.
hashes :: Hashable a => Int -> a -> [Word32]

-- | Compute a list of 32-bit hashes relatively cheaply. The value to hash
--   is inspected at most twice, regardless of the number of hashes
--   requested.
--   
--   We use a variant of Kirsch and Mitzenmacher's technique from "Less
--   Hashing, Same Performance: Building a Better Bloom Filter",
--   <a>http://www.eecs.harvard.edu/~kirsch/pubs/bbbf/esa06.pdf</a>.
--   
--   Where Kirsch and Mitzenmacher multiply the second hash by a
--   coefficient, we shift right by the coefficient. This offers better
--   performance (as a shift is much cheaper than a multiply), and the low
--   order bits of the final hash stay well mixed.
cheapHashes :: Hashable a => Int -> a -> [Word32]

-- | Compute a 32-bit hash of a <a>Storable</a> instance.
hashOne32 :: Storable a => a -> Word32 -> IO Word32

-- | Compute a 64-bit hash of a <a>Storable</a> instance.
hashOne64 :: Storable a => a -> Word64 -> IO Word64

-- | Compute a 32-bit hash of a list of <a>Storable</a> instances.
hashList32 :: Storable a => [a] -> Word32 -> IO Word32

-- | Compute a 64-bit hash of a list of <a>Storable</a> instances.
hashList64 :: Storable a => [a] -> Word64 -> IO Word64
instance Data.BloomFilter.Hash.Hashable ()
instance Data.BloomFilter.Hash.Hashable GHC.Integer.Type.Integer
instance Data.BloomFilter.Hash.Hashable GHC.Types.Bool
instance Data.BloomFilter.Hash.Hashable GHC.Types.Ordering
instance Data.BloomFilter.Hash.Hashable GHC.Types.Char
instance Data.BloomFilter.Hash.Hashable GHC.Types.Int
instance Data.BloomFilter.Hash.Hashable GHC.Types.Float
instance Data.BloomFilter.Hash.Hashable GHC.Types.Double
instance Data.BloomFilter.Hash.Hashable GHC.Int.Int8
instance Data.BloomFilter.Hash.Hashable GHC.Int.Int16
instance Data.BloomFilter.Hash.Hashable GHC.Int.Int32
instance Data.BloomFilter.Hash.Hashable GHC.Int.Int64
instance Data.BloomFilter.Hash.Hashable GHC.Word.Word8
instance Data.BloomFilter.Hash.Hashable GHC.Word.Word16
instance Data.BloomFilter.Hash.Hashable GHC.Word.Word32
instance Data.BloomFilter.Hash.Hashable GHC.Word.Word64
instance Data.BloomFilter.Hash.Hashable Data.ByteString.Internal.ByteString
instance Data.BloomFilter.Hash.Hashable Data.ByteString.Lazy.Internal.ByteString
instance Data.BloomFilter.Hash.Hashable a => Data.BloomFilter.Hash.Hashable (GHC.Base.Maybe a)
instance (Data.BloomFilter.Hash.Hashable a, Data.BloomFilter.Hash.Hashable b) => Data.BloomFilter.Hash.Hashable (Data.Either.Either a b)
instance (Data.BloomFilter.Hash.Hashable a, Data.BloomFilter.Hash.Hashable b) => Data.BloomFilter.Hash.Hashable (a, b)
instance (Data.BloomFilter.Hash.Hashable a, Data.BloomFilter.Hash.Hashable b, Data.BloomFilter.Hash.Hashable c) => Data.BloomFilter.Hash.Hashable (a, b, c)
instance (Data.BloomFilter.Hash.Hashable a, Data.BloomFilter.Hash.Hashable b, Data.BloomFilter.Hash.Hashable c, Data.BloomFilter.Hash.Hashable d) => Data.BloomFilter.Hash.Hashable (a, b, c, d)
instance (Data.BloomFilter.Hash.Hashable a, Data.BloomFilter.Hash.Hashable b, Data.BloomFilter.Hash.Hashable c, Data.BloomFilter.Hash.Hashable d, Data.BloomFilter.Hash.Hashable e) => Data.BloomFilter.Hash.Hashable (a, b, c, d, e)
instance Foreign.Storable.Storable a => Data.BloomFilter.Hash.Hashable [a]


-- | A fast, space efficient Bloom filter implementation. A Bloom filter is
--   a set-like data structure that provides a probabilistic membership
--   test.
--   
--   <ul>
--   <li>Queries do not give false negatives. When an element is added to a
--   filter, a subsequent membership test will definitely return
--   <a>True</a>.</li>
--   <li>False positives <i>are</i> possible. If an element has not been
--   added to a filter, a membership test <i>may</i> nevertheless indicate
--   that the element is present.</li>
--   </ul>
--   
--   This module provides low-level control. For an easier to use
--   interface, see the <a>Data.BloomFilter.Easy</a> module.
module Data.BloomFilter.Mutable

-- | A hash value is 32 bits wide. This limits the maximum size of a filter
--   to about four billion elements, or 512 megabytes of memory.
type Hash = Word32

-- | A mutable Bloom filter, for use within the <tt>ST</tt> monad.
data MBloom s a

-- | Create a new mutable Bloom filter. For efficiency, the number of bits
--   used may be larger than the number requested. It is always rounded up
--   to the nearest higher power of two, but will be clamped at a maximum
--   of 4 gigabits, since hashes are 32 bits in size.
new :: (a -> [Hash]) -> Int -> ST s (MBloom s a)

-- | Return the size of a mutable Bloom filter, in bits.
length :: MBloom s a -> Int

-- | Query a mutable Bloom filter for membership. If the value is present,
--   return <tt>True</tt>. If the value is not present, there is
--   <i>still</i> some possibility that <tt>True</tt> will be returned.
elem :: a -> MBloom s a -> ST s Bool

-- | Insert a value into a mutable Bloom filter. Afterwards, a membership
--   query for the same value is guaranteed to return <tt>True</tt>.
insert :: MBloom s a -> a -> ST s ()
bitArray :: MBloom s a -> (STUArray s Int Hash)


-- | A fast, space efficient Bloom filter implementation. A Bloom filter is
--   a set-like data structure that provides a probabilistic membership
--   test.
--   
--   <ul>
--   <li>Queries do not give false negatives. When an element is added to a
--   filter, a subsequent membership test will definitely return
--   <a>True</a>.</li>
--   <li>False positives <i>are</i> possible. If an element has not been
--   added to a filter, a membership test <i>may</i> nevertheless indicate
--   that the element is present.</li>
--   </ul>
--   
--   This module provides low-level control. For an easier to use
--   interface, see the <a>Data.BloomFilter.Easy</a> module.
module Data.BloomFilter

-- | A hash value is 32 bits wide. This limits the maximum size of a filter
--   to about four billion elements, or 512 megabytes of memory.
type Hash = Word32

-- | An immutable Bloom filter, suitable for querying from pure code.
data Bloom a

-- | A mutable Bloom filter, for use within the <tt>ST</tt> monad.
data MBloom s a

-- | Create an immutable Bloom filter from a mutable one. The mutable
--   filter may be modified afterwards.
freeze :: MBloom s a -> ST s (Bloom a)

-- | Copy an immutable Bloom filter to create a mutable one. There is no
--   non-copying equivalent.
thaw :: Bloom a -> ST s (MBloom s a)

-- | Create an immutable Bloom filter from a mutable one. The mutable
--   filter <i>must not</i> be modified afterwards, or a runtime crash may
--   occur. For a safer creation interface, use <a>freeze</a> or
--   <a>create</a>.
unsafeFreeze :: MBloom s a -> ST s (Bloom a)

-- | Build an immutable Bloom filter from a seed value. The seeding
--   function populates the filter as follows.
--   
--   <ul>
--   <li>If it returns <a>Nothing</a>, it is finished producing values to
--   insert into the filter.</li>
--   <li>If it returns <tt><a>Just</a> (a,b)</tt>, <tt>a</tt> is added to
--   the filter and <tt>b</tt> is used as a new seed.</li>
--   </ul>
unfold :: forall a b. (a -> [Hash]) -> Int -> (b -> Maybe (a, b)) -> b -> Bloom a

-- | Create an immutable Bloom filter, populating it from a list of values.
--   
--   Here is an example that uses the <tt>cheapHashes</tt> function from
--   the <a>Data.BloomFilter.Hash</a> module to create a hash function that
--   returns three hashes.
--   
--   <pre>
--   import <a>Data.BloomFilter.Hash</a> (cheapHashes)
--   
--   filt = fromList (cheapHashes 3) 1024 ["foo", "bar", "quux"]
--    
--   </pre>
fromList :: (a -> [Hash]) -> Int -> [a] -> Bloom a

-- | Create an empty Bloom filter.
--   
--   This function is subject to fusion with <a>insert</a> and
--   <a>insertList</a>.
empty :: (a -> [Hash]) -> Int -> Bloom a

-- | Create a Bloom filter with a single element.
--   
--   This function is subject to fusion with <a>insert</a> and
--   <a>insertList</a>.
singleton :: (a -> [Hash]) -> Int -> a -> Bloom a

-- | Return the size of an immutable Bloom filter, in bits.
length :: Bloom a -> Int

-- | Query an immutable Bloom filter for membership. If the value is
--   present, return <tt>True</tt>. If the value is not present, there is
--   <i>still</i> some possibility that <tt>True</tt> will be returned.
elem :: a -> Bloom a -> Bool

-- | Query an immutable Bloom filter for non-membership. If the value
--   <i>is</i> present, return <tt>False</tt>. If the value is not present,
--   there is <i>still</i> some possibility that <tt>True</tt> will be
--   returned.
notElem :: a -> Bloom a -> Bool

-- | Create a new Bloom filter from an existing one, with the given member
--   added.
--   
--   This function may be expensive, as it is likely to cause the
--   underlying bit array to be copied.
--   
--   Repeated applications of this function with itself are subject to
--   fusion.
insert :: a -> Bloom a -> Bloom a

-- | Create a new Bloom filter from an existing one, with the given members
--   added.
--   
--   This function may be expensive, as it is likely to cause the
--   underlying bit array to be copied.
--   
--   Repeated applications of this function with itself are subject to
--   fusion.
insertList :: [a] -> Bloom a -> Bloom a
bitArray :: Bloom a -> (UArray Int Hash)
instance GHC.Show.Show (Data.BloomFilter.Bloom a)
instance Control.DeepSeq.NFData (Data.BloomFilter.Bloom a)


-- | An easy-to-use Bloom filter interface.
module Data.BloomFilter.Easy

-- | An immutable Bloom filter, suitable for querying from pure code.
data Bloom a

-- | Create a Bloom filter with the given false positive rate and members.
--   The hash functions used are computed by the <tt>cheapHashes</tt>
--   function from the <a>Hash</a> module.
easyList :: (Hashable a) => Double -> [a] -> Bloom a

-- | Query an immutable Bloom filter for membership. If the value is
--   present, return <tt>True</tt>. If the value is not present, there is
--   <i>still</i> some possibility that <tt>True</tt> will be returned.
elem :: a -> Bloom a -> Bool

-- | Query an immutable Bloom filter for non-membership. If the value
--   <i>is</i> present, return <tt>False</tt>. If the value is not present,
--   there is <i>still</i> some possibility that <tt>True</tt> will be
--   returned.
notElem :: a -> Bloom a -> Bool

-- | Return the size of an immutable Bloom filter, in bits.
length :: Bloom a -> Int

-- | Suggest a good combination of filter size and number of hash functions
--   for a Bloom filter, based on its expected maximum capacity and a
--   desired false positive rate.
--   
--   The false positive rate is the rate at which queries against the
--   filter should return <tt>True</tt> when an element is not actually
--   present. It should be a fraction between 0 and 1, so a 1% false
--   positive rate is represented by 0.01.
safeSuggestSizing :: Int -> Double -> Either String (Int, Int)

-- | Behaves as <a>safeSuggestSizing</a>, but calls <a>error</a> if given
--   invalid or out-of-range inputs.
suggestSizing :: Int -> Double -> (Int, Int)
