smoothie-0.4.2.9: Smooth curves via several interpolation modes

Data.Spline.Key

Contents

Description

Synopsis

# Key type

data Key a Source #

A Key is a point on the spline with extra information added. It can be, for instance, left and right handles for a Bezier curve, or whatever the interpolation might need.

Hold v is used to express no interpolation and holds its latest value until the next key.

Linear v represents a linear interpolation until the next key.

Cosine v represents a cosine interpolation until the next key.

CubicHermite v represents a cubic hermitian interpolation until the next key.

Bezier l v r represents a cubic Bezier interpolation, where l refers to the input – left – tangent of the key and r is the output – right – tangent of the key.

Constructors

 Hold a Linear a Cosine a CubicHermite a Bezier a a a

Instances

 Source # Methodsfmap :: (a -> b) -> Key a -> Key b #(<\$) :: a -> Key b -> Key a # Eq a => Eq (Key a) Source # Methods(==) :: Key a -> Key a -> Bool #(/=) :: Key a -> Key a -> Bool # Show a => Show (Key a) Source # MethodsshowsPrec :: Int -> Key a -> ShowS #show :: Key a -> String #showList :: [Key a] -> ShowS # ToJSON a => ToJSON (Key a) Source # MethodstoJSON :: Key a -> Value #toEncoding :: Key a -> Encoding #toJSONList :: [Key a] -> Value #toEncodingList :: [Key a] -> Encoding # FromJSON a => FromJSON (Key a) Source # MethodsparseJSON :: Value -> Parser (Key a) #parseJSONList :: Value -> Parser [Key a] #

keyValue :: Key a -> a Source #

Extract the value out of a Key.

# Interpolation

interpolateKeys :: (Additive a, Floating s) => s -> Key (a s) -> Key (a s) -> a s Source #

interpolateKeys t start end interpolates between start and end using s as a normalized sampling value.

Satisfies the following laws:

  interpolateKeys 0 start _ = start
interpolateKeys 1 _ end   = end


normalizeSampling :: Fractional s => (a s -> s) -> s -> Key (a s) -> Key (a s) -> s Source #

Normalize a sampling value by clamping and scaling it between two Keys.

The following laws should be satisfied in order to get a coherent output:

  sampler :: a s -> s

sampler (keyValue k1) s= sampler (keyValue k0)
0 <= normalizeSampling sampler s k0 k1 <= 1