filter -base -bytestring

filter :: (Char -> Bool) -> Text -> Text
text Data.Text, text Data.Text.Lazy
O(n) filter, applied to a predicate and a Text, returns a Text containing those characters that satisfy the predicate.
filter :: (Key -> Bool) -> IntSet -> IntSet
containers Data.IntSet
O(n). Filter all elements that satisfy some predicate.
filter :: (a -> Bool) -> IntMap a -> IntMap a
containers Data.IntMap.Strict, containers Data.IntMap.Lazy
O(n). Filter all values that satisfy some predicate. > filter (> "a") (fromList [(5,"a"), (3,"b")]) == singleton 3 "b" > filter (> "x") (fromList [(5,"a"), (3,"b")]) == empty > filter (< "a") (fromList [(5,"a"), (3,"b")]) == empty
filter :: (a -> Bool) -> Map k a -> Map k a
containers Data.Map.Lazy, containers Data.Map.Strict
O(n). Filter all values that satisfy the predicate. > filter (> "a") (fromList [(5,"a"), (3,"b")]) == singleton 3 "b" > filter (> "x") (fromList [(5,"a"), (3,"b")]) == empty > filter (< "a") (fromList [(5,"a"), (3,"b")]) == empty
filter :: (a -> Bool) -> Seq a -> Seq a
containers Data.Sequence
O(n). The filter function takes a predicate p and a sequence xs and returns a sequence of those elements which satisfy the predicate.
filter :: (a -> Bool) -> Set a -> Set a
containers Data.Set
O(n). Filter all elements that satisfy the predicate.
filteredStrategy :: CompressionStrategy
zlib Codec.Compression.Zlib.Internal, zlib Codec.Compression.Zlib.Raw, zlib Codec.Compression.Zlib, zlib Codec.Compression.GZip
Use the filtered compression strategy for data produced by a filter (or predictor). Filtered data consists mostly of small values with a somewhat random distribution. In this case, the compression algorithm is tuned to compress them better. The effect of this strategy is to force more Huffman coding and less string matching; it is somewhat intermediate between defaultCompressionStrategy and huffmanOnlyCompressionStrategy.
filterWithKey :: (Key -> a -> Bool) -> IntMap a -> IntMap a
containers Data.IntMap.Strict, containers Data.IntMap.Lazy
O(n). Filter all keys/values that satisfy some predicate. > filterWithKey (\k _ -> k > 4) (fromList [(5,"a"), (3,"b")]) == singleton 5 "a"
filterWithKey :: (k -> a -> Bool) -> Map k a -> Map k a
containers Data.Map.Lazy, containers Data.Map.Strict
O(n). Filter all keys/values that satisfy the predicate. > filterWithKey (\k _ -> k > 4) (fromList [(5,"a"), (3,"b")]) == singleton 5 "a"
Filtered :: CompressionStrategy
zlib Codec.Compression.Zlib.Internal, zlib Codec.Compression.Zlib.Raw, zlib Codec.Compression.Zlib, zlib Codec.Compression.GZip
Deprecated: Use filteredStrategy. CompressionStrategy constructors will be hidden in version 0.7
package bloomfilter
package
Pure and impure Bloom Filter implementations. Version 1.2.6.10
convolutionFilter1D :: PixelInternalFormat -> GLsizei -> PixelData a -> IO ()
OpenGL Graphics.Rendering.OpenGL.GL.PixelRectangles.Convolution
convolutionFilter2D :: PixelInternalFormat -> Size -> PixelData a -> IO ()
OpenGL Graphics.Rendering.OpenGL.GL.PixelRectangles.Convolution
convolutionFilterBias :: ConvolutionTarget -> StateVar (Color4 GLfloat)
OpenGL Graphics.Rendering.OpenGL.GL.PixelRectangles.Convolution
convolutionFilterScale :: ConvolutionTarget -> StateVar (Color4 GLfloat)
OpenGL Graphics.Rendering.OpenGL.GL.PixelRectangles.Convolution
copyConvolutionFilter1D :: PixelInternalFormat -> Position -> GLsizei -> IO ()
OpenGL Graphics.Rendering.OpenGL.GL.PixelRectangles.Convolution
copyConvolutionFilter2D :: PixelInternalFormat -> Position -> Size -> IO ()
OpenGL Graphics.Rendering.OpenGL.GL.PixelRectangles.Convolution
defaultCookieFilter :: URI -> Cookie -> IO Bool
HTTP Network.Browser
defaultCookieFilter is the initial cookie acceptance filter. It welcomes them all into the store :-)
efilter :: DynGraph gr => (LEdge b -> Bool) -> gr a b -> gr a b
fgl Data.Graph.Inductive.Basic
Filter based on edge property.
elfilter :: DynGraph gr => (b -> Bool) -> gr a b -> gr a b
fgl Data.Graph.Inductive.Basic
Filter based on edge label property.

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