hsc3-0.17: Help/UGen/whiteNoise.help.lhs
Sound.SC3.UGen.Help.viewSC3Help "WhiteNoise"
Sound.SC3.UGen.DB.ugenSummary "WhiteNoise"
> import Sound.SC3 {- hsc3 -}
> g_01 = whiteNoise 'α' AR * 0.05
Random filtered noise bursts.
> g_02 =
> let n = whiteNoise 'α' AR
> t = dust 'β' AR (mce [3, 7])
> f = tExpRand 'γ' 20 1800 t
> bw = tExpRand 'δ' 0.001 1 t
> e = decay2 t 0.01 0.2
> in resonz (n * e) f bw
Monadic form of above graph.
> g_03 :: UId m => m UGen
> g_03 = do
> n <- whiteNoiseM AR
> t <- dustM AR (mce [3, 7])
> f <- tExpRandM 20 1800 t
> bw <- tExpRandM 0.001 1 t
> let e = decay2 t 0.01 0.2
> return (resonz (n * e) f bw)
The same graph again, without using do notation.
> g_04 :: UId m => m UGen
> g_04 =
> whiteNoiseM AR >>= \n ->
> dustM AR (mce [3, 7]) >>= \t ->
> tExpRandM 20 1800 t >>= \f ->
> tExpRandM 0.001 1 t >>= \bw ->
> let e = decay2 t 0.01 0.2
> in return (resonz (n * e) f bw)
Drawing
import Sound.SC3.Plot {- hsc3-plot -}
plot_ugen1 0.01 (whiteNoise 'γ' AR)
plot_ugen1 0.05 (lpf (whiteNoise 'γ' AR) 500)
import Sound.SC3.Plot.FFT {- hsc3-plot -}
plot_ugen_fft1 0.1 (whiteNoise 'α' AR)



Speaker balance
> g_05 = let n = whiteNoise 'α' AR * 0.1 in mce2 n n
> g_06 =
> let x = mouseX KR 0.1 2 Linear 0.2
> l = sinOsc KR x 0
> n = whiteNoise 'α' AR
> in pan2 n l 0.1
> g_07 = hpz1 (whiteNoise 'α' AR * 0.01)