-- This code was automatically generated by lhs2tex --code, from the file 
-- HSoM/RandomMusic.lhs.  (See HSoM/MakeCode.bat.)

module Euterpea.Examples.RandomMusic where

import Euterpea

import System.Random
import System.Random.Distributions
import qualified Data.MarkovChain as M
sGen :: StdGen
sGen = mkStdGen 42
randInts :: StdGen -> [Int]
randInts g =  let (x,g') = next g
              in x : randInts g'
randFloats :: [Float]
randFloats = randomRs (-1,1) sGen

randIntegers :: [Integer]
randIntegers = randomRs (0,100) sGen

randString :: String
randString = randomRs ('a','z') sGen
randIO :: IO Float
randIO = randomRIO (0,1)
randIO' :: IO ()
randIO' = do  r1 <- randomRIO (0,1) :: IO Float
              r2 <- randomRIO (0,1) :: IO Float
              print (r1 == r2)
toAbsP1    :: Float -> AbsPitch
toAbsP1 x  = round (40*x + 30)
mkNote1  :: AbsPitch -> Music Pitch
mkNote1  = note tn . pitch

mkLine1        :: [AbsPitch] -> Music Pitch
mkLine1 rands  = line (take 32 (map mkNote1 rands))
-- uniform distribution
m1 :: Music Pitch
m1 = mkLine1 (randomRs (30,70) sGen)

-- linear distribution
m2 :: Music Pitch
m2 =  let rs1 = rands linear sGen
      in mkLine1 (map toAbsP1 rs1)

-- exponential distribution
m3      :: Float -> Music Pitch
m3 lam  =  let rs1 = rands (exponential lam) sGen
           in mkLine1 (map toAbsP1 rs1)

-- Gaussian distribution
m4          :: Float -> Float -> Music Pitch
m4 sig mu   =  let rs1 = rands (gaussian sig mu) sGen
               in mkLine1 (map toAbsP1 rs1)
-- Gaussian distribution with mean set to 0
m5      :: Float -> Music Pitch
m5 sig  =  let rs1 = rands (gaussian sig 0) sGen
           in mkLine2 50 (map toAbsP2 rs1)

-- exponential distribution with mean adjusted to 0
m6      :: Float -> Music Pitch
m6 lam  =  let rs1 = rands (exponential lam) sGen
           in mkLine2 50 (map (toAbsP2 . subtract (1/lam)) rs1)

toAbsP2     :: Float -> AbsPitch
toAbsP2 x   = round (5*x)

mkLine2 :: AbsPitch -> [AbsPitch] -> Music Pitch
mkLine2 start rands = 
   line (take 64 (map mkNote1 (scanl (+) start rands)))
m2' = let rs1 = rands linear sGen
      in sum (take 1000 rs1) / 1000 :: Float

m5' sig = let rs1 = rands (gaussian sig 0) sGen
          in sum (take 1000 rs1)

m6' lam = let rs1 = rands (exponential lam) sGen
              rs2 = map (subtract (1/lam)) rs1
          in sum (take 1000 rs2)
-- some sample training sequences
ps0,ps1,ps2 :: [Pitch]
ps0  = [(C,4), (D,4), (E,4)]
ps1  = [(C,4), (D,4), (E,4), (F,4), (G,4), (A,4), (B,4)]
ps2  = [  (C,4), (E,4), (G,4), (E,4), (F,4), (A,4), (G,4), (E,4),
          (C,4), (E,4), (G,4), (E,4), (F,4), (D,4), (C,4)]

-- functions to package up |run| and |runMulti|
mc    ps   n = mkLine3 (M.run n ps 0 (mkStdGen 42))
mcm   pss  n = mkLine3 (concat (M.runMulti  n pss 0 
                                            (mkStdGen 42)))

-- music-making functions
mkNote3     :: Pitch -> Music Pitch
mkNote3     = note tn

mkLine3     :: [Pitch] -> Music Pitch
mkLine3 ps  = line (take 64 (map mkNote3 ps))
-- testing the Markov output directly
lc  ps n    = take 1000 (M.run n ps 0 (mkStdGen 42))
lcl pss n m = take 1000 (M.runMulti n pss 0 (mkStdGen 42) !! m)