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;
::