/usr/share/SuperCollider/HelpSource/Classes/Pgauss.schelp is in supercollider-common 1:3.8.0~repack-2.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | class:: Pgauss
summary:: random values that follow a Gaussian Distribution
related:: Classes/Ppoisson
categories:: Streams-Patterns-Events>Patterns>Random
description::
This pattern uses the Box-Muller transform to generate a gaussian distribution from uniformly distributed values: code::sqrt(-2 * log(1.0.rand)) * sin(2pi.rand)::
ClassMethods::
method::new
argument::mean
The mean of the distribution.
argument::dev
The spread of values around the mean (standard deviation).
argument::length
Number of values produced.
Examples::
code::
(
var a;
a = Pgauss(0.0, 100, inf);
c = a.asStream.nextN(500);
w = Window.new("Pgauss", Rect(10, 10, 540, 800));
// plot the values
c.plot(bounds: Rect(10, 10, 520, 380), discrete: true, parent: w);
// a histogram of the values
c.histo(500).plot(bounds: Rect(10, 410, 520, 380), parent: w);
)
(
var a, c, w;
a = Pgauss(0.0, 10.0, inf);
c = a.asStream.nextN(500);
w = Window.new("Pgauss", Rect(10, 10, 540, 800));
// plot the values
c.plot(bounds: Rect(10, 10, 520, 380), discrete: true, parent: w);
// a histogram of the values
c.histo(500).plot(bounds: Rect(10, 410, 520, 380), parent: w);
)
// sound example
(
SynthDef(\help_sinegrain,
{ arg out=0, freq=440, sustain=0.05;
var env;
env = EnvGen.kr(Env.perc(0.01, sustain, 0.2), doneAction:2);
Out.ar(out, SinOsc.ar(freq, 0, env))
}).add;
)
(
var a;
a = Pgauss(0.0, 1.0,inf).asStream;
{
loop {
Synth(\help_sinegrain, [\freq, a.next * 600 + 300]);
0.02.wait;
}
}.fork;
)
::
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