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TITLE:: FluidPCA
summary:: Dimensionality Reduction with Principal Component Analysis
categories:: Dimensionality Reduction, Data Processing
related:: Classes/FluidMDS, Classes/FluidDataSet
DESCRIPTION::
Principal Components Analysis of a link::Classes/FluidDataSet::
https://scikit-learn.org/stable/modules/decomposition.html#principal-component-analysis-pca
CLASSMETHODS::
METHOD:: new
Make a new instance
ARGUMENT:: server
The server on which to run this model
ARGUMENT:: numDimensions
The number of dimensions to reduce to
INSTANCEMETHODS::
PRIVATE:: init
METHOD:: fit
Train this model on a link::Classes/FluidDataSet:: but don't transform the data
ARGUMENT:: dataSet
A link::Classes/FluidDataSet:: to analyse
ARGUMENT:: action
Run when done
METHOD:: transform
Given a trained model, apply the reduction to a source link::Classes/FluidDataSet:: and write to a destination. Can be the same
ARGUMENT:: sourceDataSet
Source data, or the DataSet name
ARGUMENT:: destDataSet
Destination data, or the DataSet name
ARGUMENT:: action
Run when done
METHOD:: fitTransform
link::Classes/FluidPCA#fit:: and link::Classes/FluidPCA#transform:: in a single pass
ARGUMENT:: sourceDataSet
Source data, or the DataSet name
ARGUMENT:: destDataSet
Destination data, or the DataSet name
ARGUMENT:: action
Run when done
METHOD:: transformPoint
Given a trained model, transform the data point in a link::Classes/Buffer:: and write to an output
ARGUMENT:: sourceBuffer
Input data
ARGUMENT:: destBuffer
Output data
ARGUMENT:: action
Run when done
EXAMPLES::
code::
s.boot;
//Preliminaries: we want some audio, a couple of FluidDataSets, some Buffers, a FluidStandardize and a FluidPCA
(
~audiofile = File.realpath(FluidBufPitch.class.filenameSymbol).dirname +/+ "../AudioFiles/Tremblay-ASWINE-ScratchySynth-M.wav";
~raw = FluidDataSet(s,\pca_help_12D);
~standardized = FluidDataSet(s,\pca_help_12Ds);
~reduced = FluidDataSet(s,\pca_help_2D);
~audio = Buffer.read(s,~audiofile);
~mfcc_feature = Buffer.new(s);
~stats = Buffer.alloc(s, 7, 12);
~datapoint = Buffer.alloc(s, 12);
~standardizer = FluidStandardize(s);
~pca = FluidPCA(s,2);
)
// Load audio and run an mfcc analysis, which gives us 13 points (we'll throw the 0th away)
(
~audio = Buffer.read(s,~audiofile);
FluidBufMFCC.process(s,~audio, features: ~mfcc_feature);
)
// Divide the time series in 100, and take the mean of each segment and add this as a point to
// the 'raw' FluidDataSet
(
{
var trig = LocalIn.kr(1, 1);
var buf = LocalBuf(12, 1);
var count = PulseCount.kr(trig) - 1;
var chunkLen = (~mfcc_feature.numFrames / 100).asInteger;
var stats = FluidBufStats.kr(
source: ~mfcc_feature, startFrame: count * chunkLen,
startChan:1, numFrames: chunkLen, stats: ~stats, trig: trig
);
var rd = BufRd.kr(12, ~stats, DC.kr(0), 0, 1);
var bufWr, dsWr;
12.do{|i|
bufWr = BufWr.kr(rd[i], buf, DC.kr(i));
};
dsWr = FluidDataSetWr.kr(\pca_help_12D, buf: buf, trig: Done.kr(stats));
LocalOut.kr( Done.kr(dsWr));
FreeSelf.kr(count - 99);
}.play;
)
// wait for the post window to acknoledge the job is done.
//First standardize our DataSet, so that the MFCC dimensions are on comensurate scales
//Then apply the PCA in-place on the standardized data
//Download the DataSet contents into an array for plotting
(
~reducedarray = Array.new(100);
~standardizer.fitTransform(~raw, ~standardized);
~pca.fitTransform(~standardized, ~reduced, action:{
~reduced.dump{|x| 100.do{|i|
~reducedarray.add(x["data"][i.asString])
}};
});
)
//Visualise the 2D projection of our original 12D data
(
d = ~reducedarray.flatten(1).unlace.deepCollect(1, { |x| x.normalize});
w = Window("scatter", Rect(128, 64, 200, 200));
w.drawFunc = {
Pen.use {
d[0].size.do{|i|
var x = (d[0][i]*200);
var y = (d[1][i]*200);
var r = Rect(x,y,5,5);
Pen.fillColor = Color.blue;
Pen.fillOval(r);
}
}
};
w.refresh;
w.front;
)
::
subsection:: Server Side Queries
Let's map our learned PCA dimensions to the controls of a processor
code::
(
~inputPoint = Buffer.alloc(s,12);
~predictPoint = Buffer.alloc(s,2);
~pitchingBus = Bus.control;
~catchingBus = Bus.control;
)
(
~pca.inBus_(~pitchingBus).outBus_(~catchingBus).inBuffer_(~inputPoint).outBuffer_(~predictPoint);
{
var mapped;
var audio = BufRd.ar(1,~audio,LFSaw.ar(BufDur.ir(~audio).reciprocal).range(0, BufFrames.ir(~audio)));
var mfcc = FluidMFCC.kr(audio)[1..12];
var smoothed = LagUD.kr(mfcc,1*ControlDur.ir,500*ControlDur.ir);
var trig = Impulse.kr(ControlRate.ir / 2);
smoothed.collect{|coeff,i| BufWr.kr([coeff],~inputPoint,i)};
Out.kr(~pitchingBus,[trig]);
mapped = Latch.kr(BufRd.kr(2,~predictPoint).linlin(-3,3,0,3),In.kr(~catchingBus));
CombC.ar(audio,3,mapped[0],mapped[1]*3)
}.play(~pca.synth,addAction:\addBefore);
)
::