108 lines
2.2 KiB
Text
108 lines
2.2 KiB
Text
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class:: Pprob
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summary:: random values with arbitrary probability distribution
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related:: Classes/Ppoisson
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categories:: Streams-Patterns-Events>Patterns>Random
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description::
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Creates an integral table on instantiation (cpu intensive) which is then used by the streams to generate random values efficiently.
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ClassMethods::
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method::new
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argument::distribution
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desired probability distribution (histogram).
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argument::lo
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lower bound of the resulting values.
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argument::hi
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upper bound of the resulting values.
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argument::length
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number of values to repeat.
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argument::tableSize
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resample table to this size. If the size of the distribution is smaller than 64, it is (linearly) resampled to this minimum size.
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argument::distribution
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set the distribution, the table is recalculated.
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argument::tableSize
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set the resample size, the table is recalculated.
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Examples::
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code::
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// a consistency test
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(
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var a = Pprob([0,0,0,0,1,1,1,1,3,3,6,6,9].scramble);
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var b = a.asStream;
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b.nextN(800).sort.plot("sorted distribution");
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b.nextN(800).sort.plot("sorted distribution, again");
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)
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// comparison: emulate a linrand
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(
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var a, b, x, y;
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a = Pprob([1, 0]);
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x = Pfunc({ 1.0.linrand });
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b = a.asStream;
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y = x.asStream;
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postf("Pprob mean: % linrand mean: % \n", b.nextN(800).mean, y.nextN(800).mean);
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b.nextN(800).sort.plot("this is Pprob");
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y.nextN(800).sort.plot("this is linrand");
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)
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// compare efficiency
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bench { Pprob([0, 1]) } // this is fairly expensive
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bench { 16.do { Pseq([0, 1] ! 32) } }
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x = Pprob([0, 1]).asStream;
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y = Pseq([0, 1], inf).asStream;
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bench { 100.do { x.next } }; // this very efficient
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bench { 100.do { y.next } };
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// sound example
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(
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SynthDef(\help_sinegrain,
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{ arg out=0, freq=440, sustain=0.05;
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var env;
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env = EnvGen.kr(Env.perc(0.01, sustain, 0.2), doneAction: Done.freeSelf);
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Out.ar(out, SinOsc.ar(freq, 0, env))
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}).add;
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)
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(
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var t;
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a = Pprob([0, 0, 1, 0, 1, 1, 0, 0], 60, 80);
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t = a.asStream;
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Routine({
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loop({
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Synth(\help_sinegrain, [\freq, t.next.midicps]);
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0.01.wait;
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})
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}).play;
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)
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a.distribution = [0, 1];
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a.distribution = [1, 0];
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a.distribution = [0, 0, 0, 0, 1, 0];
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a.distribution = [0, 1, 0, 0, 0, 0];
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// higher resolution results in a more accurate distribution:
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a.tableSize = 512;
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a.tableSize = 2048;
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::
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