MarkovSet | SuperCollider 3.13.0 Help

Description

MarkovSet is a Dictionary that contains keys pointing to WeighBags that contain objects and their probabilities. By parsing in a stream the Set "learns" what element can possibly follow another.¹

Part of MathLib, a diverse library of mathematical functions.

Class Methods

.new

Arguments:

args

A list of arrays that each represent one node in the set:

[element, [next_elements], [weigths]]

next_elements	The next node is searched by simple equality. If `nil`, this is a terminator node
weights	The array is normalized. If weigths is `nil`, equal weight is used.

If args is nil, the set is created and may be trained by the other methods.

updateSeeds

If set to true, each element is always added to the seeds

.fill

Arguments:

length	Number of items to read.
stream	A function or stream that returns items to read.

Instance Methods

.put

Insert a node. Any old node is overwritten.

.next

Return a next item for the arg value. If arg is nil, choose from seeds.

.parse

Read length items into the set from the stream.

.asStream

Returns a stream that creates a markov chain.

Examples

creating streams

(
m = MarkovSet([
            [100, [120, 130]],
            [120, [100, 1900]],
            [130, [100]],
            [1900, [1000, 2000, 3000]],
        ]);
)

m.makeSeeds;
x = m.asStream;
32.do { x.next.postln };

// spy out a stream to feed it in
z = Pseq([100, 200, 300, Prand([1.2, 1.4, 1.5])],inf).asStream;
z = Pspy(m, z).asStream;

32.do { x.next.postln };
15.do { z.next } // add some more elements from z
32.do { x.next.postln };

// event streams
(
SynthDef("mark", { arg out, freq, sustain=1, amp=0.1, pan;
    var env, u=1;
    env = EnvGen.kr(Env.perc(0.03, sustain, 5), 1, doneAction:2);
    3.do { var d; d = exprand(0.01, 1); u = SinOsc.ar(d * 300, u, rrand(0.1, 0.4) * d, 1) };
    Out.ar(out, Pan2.ar(SinOsc.ar(u + 1 * freq, 0, amp * env), pan));

}).store;
)

(
a = Pbind(
    \freq, Pshuf([203, 490, 231, 764, 234], inf),
    \dur, Pshuf([0.5, 0.5, 1.0, 0.25, 0.125, 0.5], inf)
);
m = MarkovSet.fill(20, Pevent(a, Event.default).asStream);
)

m.dict.keysValuesDo { |key, val| postf("key: %\t\tvalue: %\n", key, val) }; ""

// compare:
b = Pchain(Pfsm2(m), (instrument: \mark));
c = Pchain(a, (instrument: \mark));

Ppar([b, c]).play;

supermarkov

Authors

Julian Rohrhuber, 2004, 2007.

[1] - See: http://www.taygeta.com/rwalks/rwalks.html

helpfile source: HelpSource/Classes/MarkovSet.schelp
link::MathLib/Classes/MarkovSet::

MarkovSet
Extension

Description

Class Methods

.new

Arguments:

.fill

Arguments:

Instance Methods

.read

.put

.remove

.next

.parse

.asStream

Examples

direct node definition

training by a stream

training bit by bit

creating streams

supermarkov

Authors

MarkovSetExtension

.new

Arguments:

.fill

Arguments:

.read

.put

.remove

.next

.parse

.asStream

MarkovSet
Extension