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class:: LFDNoise0
summary:: Dynamic step noise
related:: Classes/LFClipNoise, Classes/LFDClipNoise, Classes/LFDNoise1, Classes/LFDNoise3, Classes/LFNoise0, Classes/LFNoise1, Classes/LFNoise2
categories:: UGens>Generators>Stochastic
Description::
Like link::Classes/LFNoise0::, it generates random values at a rate
given by the code::freq:: argument, with two differences:
list::
## no time quantization
## fast recovery from low freq values footnote::
link::Classes/LFNoise0:: , link::Classes/LFNoise1:: and
link::Classes/LFNoise2:: quantize to the nearest integer division
of the samplerate, and they poll the code::freq::
argument only when scheduled; thus they often seem to hang
when freqs get very low.
::
::
If you don't need very high or very low freqs, or use fixed freqs,
link::Classes/LFNoise0:: is more efficient.
classmethods::
method::ar, kr
argument::freq
Approximate rate at which to generate random values.
argument::mul
Output will be multiplied by this value.
argument::add
This value will be added to the output.
Examples::
code::
// try wiggling mouse quickly;
// LFNoise frequently seems stuck, LFDNoise changes smoothly.
{ LFNoise0.ar(MouseX.kr(0.1, 1000, 1), 0.1) }.play
{ LFDNoise0.ar(MouseX.kr(0.1, 1000, 1), 0.1) }.play
// silent for 2 secs before going up in freq
{ LFNoise0.ar(XLine.kr(0.5, 10000, 3), 0.1) }.scope;
{ LFDNoise0.ar(XLine.kr(0.5, 10000, 3), 0.1) }.scope;
// LFNoise quantizes time steps at high freqs, LFDNoise does not:
{ LFNoise0.ar(XLine.kr(1000, 20000, 10), 0.1) }.scope;
{ LFDNoise0.ar(XLine.kr(1000, 20000, 10), 0.1) }.scope;
{ LFNoise2.ar(1000, 0.25) }.play;
::
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