LotkaVolterra | SuperCollider 3.14.0 Help

Description

UGen implementing 4th order Runge-Kutta approximation of the Lotka and Volterras Predator-Prey model:

Implemented by Till Bovermann inspired by Gary William Flake's Book "The Computational Beauty of Nature". Implementation following on Lance Putnam's chaos UGens and MCLDs ChaosUGens.

http://tai-studio.org

(
Ndef(\lv).addSpec(\freq, [0.1, 24000, \exp]);
Ndef(\lv).addSpec(\h, [0.01, 1, \exp]);
Ndef(\lv).addSpec(\which, [0, 2, \lin]);
Ndef(\lv).addSpec(\a, [0.01, 5, \lin]);
Ndef(\lv).addSpec(\b, [0.01, 5, \lin]);
Ndef(\lv).addSpec(\c, [0.01, 5, \lin]);
Ndef(\lv).addSpec(\d, [0.01, 5, \lin]);

Ndef(\lv, {
    LeakDC.ar(
        LotkaVolterra.ar(SampleRate.ir*0.5, \a.kr(1.5, 0.1), \b.kr(1.5, 0.1), \c.kr(0.5, 0.1), \d.kr(1.5, 0.1), h: \h.kr(0.01), xi: 0.1 + \tr.tr(1)) * 0.2
    ).tanh + 1 * LFPar.ar([100, 150]);
});
)

(
Ndef(\lv, {
    Mix(
        LeakDC.ar(
            LotkaVolterra.ar(SampleRate.ir*0.5,
                a: {LFNoise2.ar(Rand(0.000174, 0.00174)).range(0.49, 0.5)}!3,
                b: \b.kr(1.5, 0.1),
                c: {LFNoise2.ar(Rand(0.000174, 0.00174)).range(2, 4)}!4, // \c.kr(0.5, 0.1),
                a: {LFNoise2.ar(Rand(0.000174, 0.00174)).range(0.4, 0.41)}!4,
                h: \h.kr(0.01).lag2(1) * [0.5, 1, 2, 4],
                xi: 0.1 + \tr.tr(1)) * 0.2
        ) * [5, 3, 3, 1].normalizeSum;
    ).tanh
});

)

Ndef(\lv).set(\tr, 0.1)

Ndef(\lv).set(\a, 3.029850, \b, 4.094132, \c, 1.967217, \d, 2.295942);

Ndef(\lv).scope

Ndef(\lv).edit

helpfile source: /usr/local/share/SuperCollider/Extensions/SC3plugins/ChaosUGens/HelpSource/Classes/LotkaVolterra.schelp
link::Classes/LotkaVolterra::

freq	update frequency, best set to Nyquist frequency. To modulate tonal qualities, use `h`.
a	meta-parameter, useful between 0 and 5; must not be negative.
b	meta-parameter, useful between 0 and 5; must not be negative.
c	meta-parameter, useful between 0 and 5; must not be negative.
d	meta-parameter, useful between 0 and 5; must not be negative.
h	step size for the approximation
xi	initial value for x, resets the UGen when changed
yi	initial value for y, resets the UGen when changed
mul	multiply `withthis`
add	add `that`

LotkaVolterra : MultiOutUGen : UGen : AbstractFunction : Object
Extension

Description

Class Methods

LotkaVolterra.categories

LotkaVolterra.ar(freq: 22050, a: 1.5, b: 1.5, c: 0.5, d: 1.5, h: 0.05, xi: 1, yi: 0.2, mul: 1.0, add: 0.0)

Arguments:

LotkaVolterra.equation

Inherited class methods

Instance Methods

Inherited instance methods

Examples

LotkaVolterra : MultiOutUGen : UGen : AbstractFunction : Object Extension

Description

Class Methods

LotkaVolterra.categories

LotkaVolterra.ar(freq: 22050, a: 1.5, b: 1.5, c: 0.5, d: 1.5, h: 0.05, xi: 1, yi: 0.2, mul: 1.0, add: 0.0)

Arguments:

LotkaVolterra.equation

Inherited class methods

Instance Methods

Inherited instance methods

Examples

LotkaVolterra : MultiOutUGen : UGen : AbstractFunction : Object
Extension