Safe Haskell | None |
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- module Math.Noise.NoiseModule
- module Math.Noise.NoiseGen
- cubic :: Double -> Double -> Double -> Double -> Double -> Double
- linear :: Double -> Double -> Double -> Double
- scurve3 :: Double -> Double
- scurve5 :: Double -> Double
- data NoiseVector = NoiseVector Double Double Double
- genNormalized :: (Double, Double, Double, Double) -> Maybe NoiseVector
- isNormalized :: NoiseVector -> Double
- genUniformDistribution :: Int -> [Double]
- getSuitableUniformDist :: Int -> Maybe [(Double, Double, Double, Double)]
- genVectors :: Int -> Maybe [NoiseVector]
- toList :: [NoiseVector] -> [Double]
- listTable :: [Double] -> UArray Int Double
- staticTable :: Vector Double
- staticTable2 :: UArray Int Double
- constList :: [Double]
- module Math.Noise.Modules.Perlin
Documentation
module Math.Noise.NoiseModule
module Math.Noise.NoiseGen
cubic :: Double -> Double -> Double -> Double -> Double -> DoubleSource
Performs cubic interpolation between two values bound between two other values - The alpha value should range from 0.0 to 1.0. - If the alpha value is 0.0, this function returns the first value. - If the alpha vlaue is 1.0, this function returns the second value.
linear :: Double -> Double -> Double -> DoubleSource
Performs linear interpolation between two values. - The alpha value should range from 0.0 to 1.0. - If the alpha value is 0.0, this function returns the first value. - If the alpha value is 1.0, this function returns the second value.
scurve3 :: Double -> DoubleSource
Maps a value onto a cubic S-curve - the derivative of a cubic S-curve is zero at 0.0 and value at 1.0
genNormalized :: (Double, Double, Double, Double) -> Maybe NoiseVectorSource
Generates a normalized vector based on four numbers on the range of [-1.0, 1.0] - This function uses the Cook (1957) method, and may reject pairs
genUniformDistribution :: Int -> [Double]Source
Generates a uniform distribution of Double values on the range [-1.0, 1.0]
getSuitableUniformDist :: Int -> Maybe [(Double, Double, Double, Double)]Source
Generates a uniform distribution that has at least n*4 values that won't be rejected by the vector generation function
genVectors :: Int -> Maybe [NoiseVector]Source
Generates a list of uniformly distributed normalized vectors
toList :: [NoiseVector] -> [Double]Source
Creates a list of Doubles with 0.0 separating each set of 3 Doubles
staticTable2 :: UArray Int DoubleSource
An immutable table of predefined vectors
module Math.Noise.Modules.Perlin