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s.reboot
~urn = { |n=31416, min=0,max=31415| (min..max).scramble.keep(n) };
// creates 200 indices, then values of the output of a fundion with a predictable shape of a sinewave
n = 200
~idx = ~urn.value(n)
~data = n.collect{|i|sin(~idx[i]/5000)}
// creates the dataset with these associated indices and values
(
~simpleInput = FluidDataSet(s,\simpleInput,1);
~simpleOutput = FluidDataSet(s,\simpleOutput,1);
b = Buffer.alloc(s,1,1);
~mappingviz = Buffer.alloc(s,512);
)
(
Routine{
n.do{|i|
b.set(0,~idx[i]);
s.sync;
~simpleInput.addPoint(i.asString,b,{("Added Input" + i).postln});
b.set(0,~data[i]);
s.sync;
~simpleOutput.addPoint(i.asString,b,{("Added Output" + i).postln});
~mappingviz.set((~idx[i]/61).asInt,~data[i])
}
}.play
)
//look at the seeing material
~mappingviz.plot(minval:-1,maxval:1)
//create a buffer to query
~mappingresult = Buffer.alloc(s,512);
//make the process then fit the data
~knn = FluidKNN(s)
~knn.fit(~simpleInput,action:{"fitting done".postln})
// query 512 points along the line (slow because of all that sync'ing)
(
k = 1; // change to see how many points the system uses to regress
Routine{
512.do{|i|
b.set(0,i*61);
s.sync;
~knn.regressPoint(b,~simpleOutput,k,action:{|d|~mappingresult.set(i,d);});
s.sync;
i.postln;
}
}.play
)
// look at the interpolated values
~mappingresult.plot
// clears both datasets
(
~simpleInput.clear;
~simpleOutput.clear;
)