Pgauss random values that follow a Gaussian Distribution

superclass: Pattern

Pgauss(mean, standardDeviation, length)

mean The mean of the distribution (defaults to 0.0)

standardDeviation The spread of values around the mean.

length number of values produced (default: inf)

This pattern uses the Box-Müller transform to generate a gaussian distribution from uniformly distributed values:

sqrt(-2 * log(1.0.rand)) * sin(2pi.rand)

// example

(

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))

}).send(s);

)

(

var a;

a = Pgauss(0.0, 1.0,inf).asStream;

{

loop {

Synth(\help_sinegrain, [\freq, a.next * 600 + 300]);

0.02.wait;

}

}.fork;

)